d3.4 knowledge sharing and best practice final …conan.diei.unipg.it/lab/circle/d3_4.pdfd3.4 –...

HORIZON 2020

D3.4 Knowledge Sharing and Best Practice Final Report

Edited by Gianluca Reali and Mauro Femminella. Contributions received from all the

CIRCLE beneficiaries.

Document Number D3.4

Document Title Knowledge Sharing and Best Practice Final Report

Version 2.0

Status Final

Work Package WP3

Deliverable Type Report

Responsible Partner CNIT

Dissemination level PU

D3.4 – Knowledge Sharing and Best Practice Final Report

H2020-CIRCLE-665564 Version 2.0 of 112

Change History

Version Date Status Author (Unit) Description

0.1 15/MAY/2016 Working Gianluca Reali (CNIT),

Mauro Femminella (CNIT)

Create working version of

deliverable

1.0 29/MAY/2017 Working Gianluca Reali (CNIT),


Create working version of

deliverable

2.0 31/MAY/2017 Final Gianluca Reali (CNIT),


Finalization of the deliverable



Table of Contents

1. Introduction .................................................................................... 4

2. Knowledge sharing events ................................................................... 8

2.1. Knowledge Sharing Events for Research Personnel ........................................................ 8

2.1.1. Students .................................................................................................... 8

2.1.2. University researchers .................................................................................. 12

2.1.3. Industry researchers ..................................................................................... 16

2.2. Dissemination activities for the general public ........................................................... 17

3. Staff exchange in CIRCLE .................................................................. 18

4. Joint research activities ................................................................... 24

4.1. Joint project-level collaboration ............................................................................ 24

4.2. Individual research clusters .................................................................................. 25

4.3. Publications ..................................................................................................... 29

4.3.1. Papers published/accepted for publication ......................................................... 30

4.3.2. Papers in preparation/submitted ..................................................................... 31

5. CIRCLE MolCom Toolbox ................................................................... 32

5.1. CIRCLE MolCom Toolbox implementation .................................................................. 33

5.2. MolCom Markup Language (MolcomML) ..................................................................... 36

5.2.1. Example of usage of MolComML with two simulators ............................................. 49

5.2.2. Example of MolComMl usage for simulating blood vessels ........................................ 51

6. Performance assessment of the knowledge sharing initiatives. ................... 51

Appendix 1: Staff Exchange Reports ............................................................ 54

Source institution: WIT ................................................................................................. 54

Source institution: UPC ................................................................................................. 57

Source institution: UCAM ............................................................................................... 63

Source institution: KU .................................................................................................. 70

Source institution: IMINDS ............................................................................................. 75

Source institution: UNIPG .............................................................................................. 77

Source institution: TUT ................................................................................................. 79

Source institution: CNIT ................................................................................................ 81

List of acronyms and abbreviations ............................................................. 87

Appendix 2: MolComML for puctiform simulation ............................................ 88

Appendix 3: MolComML for blood simulation ................................................. 97

References .......................................................................................... 112



1. Introduction This deliverable of the CIRCLE WP3 “KNOWLEDGE SHARING AND EXCHANGE” reports on the final

results of the CIRCLE project about Knowledge Sharing and Best Practice roadmap and the

associated activities. This deliverable logically follows the Deliverables D3.1 and D3.3. The

knowledge sharing activities and the related plans, illustrated in D3.1 and D3.3, have been

revised and integrated by including the activities carried out in the second year of the project.

Hence, this document includes all the CIRCLE activities related to knowledge and best practice

sharing.

The general objective of the knowledge sharing initiatives is to promote collaboration between

organizations on methodologies and research tools for investigating the issues related to

molecular communications and to stimulate their growth.

Knowledge sharing has happened both within the CIRCLE consortium and between CIRCLE

organizations and external organizations who considered CIRCLE a valuable project in molecular

communications (MolCom).

The most important MolCom feature is its heterogeneity, as shown in Figure 1. The set of

involved areas constitutes the body of the MolCom knowledge; each of them can contribute to

the MolCom research and receive contributions from it and from the other bridged areas. The

overall effects of the CIRCLE collaboration activities is sharing of research methods (different

analytical models, simulators, lab experiments) and construction of a common and

interdisciplinary research framework, as demonstrated by the wide participation to the CIRCLE

workshops described in this document.



MOLECULARBIOLOGY

SYNTH

ETIC AN

D

SYSTEM B

IOLO

GY

CHEMISTRY

NA

NO

TECHN

OLO

GY

MOLECULARCOMMUNICATIONS

Computer Science, Telecommunictions, Networking, Nano Electronics, Big Data,Signal/Image Processing.

New materialsNano energy harvesting

Molecular nanotechnologyNano/bio sensing

Synthetic chemistryBiochemistry

Personalized diagnosisDrug deliveryCTC DetectionImmune response

Information storage in DNACell transformationVirtual Physiological Human Synthetic molecular motors

Body-on-chip emulaors

Cell reception capabilitiesPathways and trafficking properties

Figure 1. Research areas related to MolCom.

In order to contextualize the CIRCLE knowledge sharing initiatives in this challenging

environment, it is convenient to associate them with the CIRCLE objectives:

O1 Harmonize heterogeneous islands of research in Molecular Communications across

Europe by providing a structured research agenda through the collaborative specification

and continual refinement of a research roadmap that will be developed within CIRCLE

project.

O2 Stimulate guided learning for young researchers entering the area of Molecular

Communications, through improving efficiency of knowledge acquisition in key

disciplines.

O3 Build a structured community across Europe of research leaders and collaborators

working in the area of Molecular Communications.

O4 Accelerate the exchange of knowledge and best practice between researchers with

Europe and internationally focusing on Molecular Communications.

O5 Facilitate a staff exchange program between partners within CIRCLE specifically

focusing on young researchers.



O6 Reduce the barriers for entry into the area of Molecular Communications for high tech

SMEs through the collaborative specification and continual refinement of an industry

engagement roadmap (mainly addressed by WP4).

These objectives have been mapped in the structure of the WP3, the tasks of which are:

Task 3.1 Collect and exchange knowledge between research groups (O1, O2, O3) Task 3.2 Collect and exchange simulation/modeling tools used in Molecular

communications (O4) Task 3.3 Collect and exchange approaches and experimental methodologies (O4) Task 3.4 Collect and exchange knowledge / best practice at Member State and EU level

(O3, O5, O6)

In what follows, any reference of the CIRCLE objectives in the knowledge sharing activities will

be indicated by the relevant index.

The knowledge and best practice sharing initiatives in CIRCLE have been organized according to

the scheme shown in Figure 2. The figure shows also relations between individual activities and

their association with the CIRCLE objectives and the WP3 Tasks.

Knowledge SharingInitiatives in CIRCLE

Knowledge SharingEvents O2, O3, O6

Staff ExchangeO1, O4, O5

Joint ResearchO1, O3, O4

ResearchPersonnel

GeneralPublic

Project Level

IndividualClusters

ResearchMethods

CIRCLE Toolbox

Task 3.1 Collect and exchange knowledge between research groups (O1, O2, O3)Task 3.2 Collect and exchange simulation/modeling tools used in Molecular communications (O4)Task 3.3 Collect and exchange approaches and experimental methodologies (O4)Task 3.4 Collect and exchange knowledge / best practice at Member State and EU level (O3, O5, O6)

Figure 2. Knowledge sharing in CIRCLE.



Knowledge sharing in CIRCLE has been organized in three main strands of activities. They

consists of the organization of events (O2, O3, O6), the staff exchange process (O1, O4, O5),

and joint research activities (O1, O3, O4).

In turn, some events are dedicated to research personnel, intended as PhD Students (O2),

Academics, (O3) and Company Researchers (O6). Other events have been organized for

disseminating general information on molecular communications to a generic audience. For

what concerns the staff exchanges (O1), they aimed to sharing mutual expertise and research

methodologies (O1, O4, O5) and also aimed to implementing research tools (O4, O5), such as

the MolCom Murkup Language in the CIRCLE simulation Toolbox. The latter had a central role in

mutual collaboration of the CIRCLE beneficiaries. In terms of joint research, CIRCLE has

stimulated the birth of novel research clusters that, for some key activities, involved all the

CIRCLE beneficiaries. Some of these clusters involved partners who formally were not part of the

project, but thanks to the knowledge sharing activities in CIRCLE they have established sound

collaborations with the CIRCLE participants (O1, O3, O4).

As expected, these initiatives are interrelated. Logical and practical relations between

initiatives are shown by dashed arrows. For example, the organization of a workshop including

tutorials, presentation of research results, and targeted meetings for solving implementation

issues and organising publication activities can contribute to many categories, shown in Figure 2.

The organization of this deliverable follows the scheme depicted in Figure 2. In Section 2, we

describe the knowledge sharing events. The Section 3 is entirely dedicated to the staff exchange

executed during the project lifetime. The joint research initiatives are illustrated in Section 4.

Besides the mere description of the knowledge sharing activities, and although research

activities fall beyond the scope of the project, we think that it is useful to describe also a technical

activity that was of particular importance in establishing collaborations in the project. This activity is

shown in Section 5. It consists of the CIRCLE MolCom Toolbox, which had a central role in the

knowledge sharing process. It is the simulation framework that has been developed through the

contribution of the CIRCLE participants. A performance assessment of the CIRCLE knowledge

sharing activities is reported in Section 6. Conclusions are reported in Section 7. Finally, the

Appendixes contain the reports of the staff exchanges of CIRCLE and some XML code related to

the activity described in Section 5.



2. Knowledge sharing events This section describes the knowledge sharing events that have been organized in CIRCLE. This

section is organized according to the nature of the event and the target audience.

2.1. Knowledge Sharing Events for Research Personnel

This subsection describes the events organized for people involved in the MolCom research

activities, detailed for Ph.D. students, university researchers, and company researchers.

2.1.1. Students The following events have been organised in order to stimulate young researchers to approach

the MolCom research area.

- The 1st CIRCLE Workshop on Molecular Communications, organized by UCAM, held in

Cambridge on 11th – 12th April 20161 included the session “Young Researchers in

Molecular Communications”, hosted by Prof. Chun Tung Chou, who is a member of the

Expert Working Group of CIRCLE. This session included the talk "Paradigms and interfaces

of molecular communications", by prof. Chou, "Education and Training Opportunities in

Molecular Communications", by Prof. Reali, and "The state of the art in Molecular

Communications: art or science? Squaring the Circle", by prof. Alarcon, followed by an

open discussion on these topics. Special emphasis has been given to the initiatives for

supporting young researchers, including both general wisdom indications for undertaking

research activities and specific suggestions about molecular communications. The latter

has also included a detailed description of paradigms and interfaces of molecular

communication. In addition, the MolCom Started Kit has been presented, together with a

list of possible academic programs dealing with molecular communications. Finally, a

survey of the state of the art, with a critical perspective, has concluded the session

devoted to young researchers.

- The 2nd CIRCLE Workshop on Molecular Communications2, organized by WIT, held in Dublin

on 9th – 11th May of 20173 included a panel on “Young Researchers in Molecular

1 http://fet-circle.eu/index.php/1st-circle-workshop-on-molecular-communications/ 2 https://www.youtube.com/channel/UC9JHUr3EuBtwHHHAbokInlQ



Communications”4 . This panel was chaired by Dr. Sasitharan Balasubramaniam. The

other members of the panel were: Prof. Ozgur AKan, Prof. Ilanko Balasingham, Dr. Goksel

Misirli, and Dr. Michael Barros.

The panel has thoroughly analyzed all the main aspects related to the involvement of

young researchers in the MolCom research. They included cross-disciplinary aspects,

motivations for young researchers, the available academic programs, the expected

importance for industries of MolCom PhDs, the EU funded programs, the feedback from a

young researcher already involved in a MolCom PhD program (Dr. Barros). In particular,

the most important barriers for young researchers were identified into the missing of

standard academic programs (both masters and PhD) for specialising in the MolCom field,

and the consequent absence of academic positions dedicated to this new sector.

However, the stimulating discussion, which involved also young researchers from the

audience, highlighted the great potentials for MolCom research and application in the

near future, and sketched a very encouraging situation for young researchers.

- Talks in PhD schools/international forums:

Special session, sponsored by CIRCLE, in the Doctoral School "Multiscale

Bioengineering: from Molecules to organs (µMBioEng)"5. This school will be held in

Perugia on June 6-10, 2016. The special Session has been organized by CNIT and

has included lecturers from CNIT, UNIPG, and UCAM.

Talk 1: Education and training opportunities in Molecular Communications,

Gianluca Reali (CNIT): this talk has illustrated the novel opportunities in

education for young researchers willing to face the challenges of molecular

communications. During the session, the MolCom Starter Kit has been sketched,

as well as the various opportunities in terms of PhD programs and Master schools

oriented to molecular communications or including well distinguishable contents

of them.

3 http://fet-circle.eu/index.php/2nd-workshop-on-molecular-communications/ 4 https://www.youtube.com/watch?v=L5aLs-rLuNY 5 http://mmbioeng2016.jimdo.com/



Talk 2: Applications Opportunities of Molecular Communications, Pietro Liò

(UCAM). This talk has illustrated the novel applications that could leverage the

molecular communications paradigm as enabling technology.

Talk 3: Cellular Interaction Mechanisms, Antonio Macchiarulo (UNIPG). This talk

has explored the research opportunity for molecular communications in

chemistry and drug discovery, which is one of the most important research fields

in pharmacology.

Talk 4: Models of Molecular Communications Systems, Mauro Femminella (CNIT).

This talk has illustrated various models for molecular communication systems,

focusing on the receiver models. Some models, characterized by different

complexity and achievable performance have been presented and analysed,

together with an applicability analysis tailored to the considered application

scenario.

Training session: Simulation of Molecular Communication Systems, executed in

the Software Engineering Lab, by Luca Felicetti and Mauro Femminella (CNIT).

During this session, the students have used the open source simulator BiNS2 to

test the reliability of a receiver models illustrated during the previous talk.

Pietro Liò: “Inflammatory events and cancer: a statistical Bioinformatics

perspectives” and “Combining Bioinformatics and cancer survival analysis”,

Cancer development and complexity, May 2016.

Pietro Liò: invited speaker in the session "Computational Intelligence Applications

in Health and Smart Cities", 2nd International Forum on Research and

Technologies for Society and Industry Technologies for smarter societies, Bologna,

September 2016.

2.1.1.1. Catalogue of Courses

A Catalogue of the skills and the available academic programs for Molecular Communications

have been prepared and presented and the 1st CIRCLE Workshop on Molecular Communications in

Cambridge. This report includes PhD programs, academic courses, and targeted academic

initiatives:

University of Tampere, Finland, ELT-53406, Special course on networking,

http://www.cs.tut.fi/kurssit/ELT-53406/



Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany, Seminar Special Topics in

Communication, http://www.idc.lnt.de/en/lehre/winter-term-201516/seminar-special-

topics-in-communication/

Ss Cyril and Methodius University (SsCMU), Skopje, Macedonia, master study program in

Micro and Nano Technologies, http://en.feit.ukim.edu.mk/news/new-master-study-

program-in-micro-and-nano-technologies-a-t-feeit-ss-c-yril-and-methodius-university-ssc-

mu

Boğaziçi University, Turkey, CmpE 49I Sp.Tp. Nanonetworking & Molecular

Communications, https://www.cmpe.boun.edu.tr/courses/cmpe49i/2015/fall

Integrated Research Training Group "Erlangen School of Molecular Communication",

Germany, http://www.sfb796-gk.forschung.uni-erlangen.de/

Osaka University, Japan, OU-Nanoprogram, http://www.sigma.es.osaka-

u.ac.jp/pub/nanokiko/html/english/index.html

The discussion following the presentation of the report has allowed to further integrate and

improve the catalogue. UPC has undertaken an initiative aiming to identify the key elements of

research on Molecular Communications. Although this activity is essentially targeted to WP4, it

has provided also a contribution to the ongoing WP3 activities focuses on young researchers. It

consists of collecting and processing information from the main research publishers regarding

papers related to Molecular Communications. These data have been processed through algorithm

and techniques typical of Data Science. Results have allowed identifying suitable taxonomy,

which is very important since MolCom is an open field, which encompasses some other scientific

disciplines. In addition, it was shown how it can take advantage of achievements in different

areas and how it can contribute to future science and technology. Hence, it emerged a

considerable social impact due to the wide range of possible applications.

In addition, during the workshop and in the subsequent PhD school in Perugia, where CIRCLE

hosted a dedicated session on Molecular Communication Systems, the MolCom Starter Kit has

been presented.

2.1.1.2. CIRCLE School

The CIRCLE Spring Scholl on Molecular Communications was organized in conjunction with the 2nd CIRCLE

Workshop on Molecular Communications, Dublin on 9th – 11th May of 2017. This schools included

three tutorials:



Tutorial 1 – Prof. Gianluca Reali, CNIT, Italy: “The CIRCLE Simulation Toolkit and the MolCom Markup

Language”6.

This tutorial, focused on the simulation of MolCom Systems. The initial part of the tutorial focused on the

MolComML, a markup language for MolCom, developed through an extensive collaboration in CIRCLE (see

Section 5). The second part of the tutorial focused on the integration of MolComML in a specific Molcom

Simulator, BiNS2 [2]. In the final part of the tutorial two live simulations have been instantiated and

commented. The first simulation was relevant to a point-to-point diffusive communication system, the

second one consisted in the propagation of particles in a blood vessel.

Tutorial 2 - Dr. Mirela Alistar, Technical University of Denmark: “Design Automation for Digital

Microfluidics”7.

This tutorial consisted in the theoretical description and the practical implementation of a microfluidic

system. Step by step, the audience have been closely involved in the definition and execution of a

microfluidic experiment. The experiment, consisting in the guided motion of droplets over a microfluidic

circuit by means of voltage signals was successful and stimulated an open discussion. Also, the presenter

used one of the implemented circuits to move droplets containing her own DNA molecules, thus showing

as microfluidics can be an enabler for biomedical or environmental molecular communications

applications.

Tutorial 3 - Dr. Filippo Castiglione, National Research Council of Italy: “Simulating Biological Networks”8.

This tutorial showed how to implement computing models for analysing biological networks. The proposed

models were much more functional than those presented in the tutorial 1 by Prof. G. Reali, and the two

tutorials complemented each other at different scales, both spatial and temporal. The tutorial also

highlighted possible applications and roles of the models described, such as the improvement of

understanding of impaired metabolism, immunosenescence in humans, and regulatory networks.

2.1.2. University researchers The knowledge sharing events for university researchers had the scope of building a sound and

harmonised MolCom research community. Some involved people have organizational and

scientific roles in research journals, international conferences, and organization of PhD schools

having molecular communications in their principal research areas. A list of these events

follows.

6 https://www.youtube.com/watch?v=s7VkBOWjMFE 7 https://www.youtube.com/watch?v=CldwqbHS450 8 https://www.youtube.com/watch?v=mJZeld7wIO8



- CIRCLE was publicly launched at the ACM Nanocom event in Boston, Sept 2015, to some

100+ registered attendees.

- Project meetings: Besides the organizational purposes of the project meetings, illustrated

in the framework of WP1, these meetings always had the purpose of discussing and

harmonising the research activities on the CIRCLE beneficiaries. These meetings were

organized in Barcelona (the kick-off meeting), hosted by UPC (July 2015); in Perugia,

hosted by CNIT in January 2016; in New York, in conjunction with the ACM Nanocom

Conference, September 2016; in Dublin, after the 2nd CIRCLE Workshop on Molecular

Communications, May 2017. During these meetings, specific knowledge sharing

initiatives, publication, and follow-up activities have been proposed, discussed, and

agreed by the participants. For example, the participants have agreed the need of

developing the CIRCLE MolCom Toolkit and contributing to the IEEE TCSIM Newsletter.

Most of these initiatives, which represent measurable indicators for the progress of the

project, has been illustrated in the deliverable D3.1 and D3.3.

- Other meetings:

On March 31st 2017, a meeting was held in Perugia for discussing the usage of the

Big Data management tools for simulating MolCom systems and the preparation of

a paper to be submitted to ACM Nanocom 2017. This meeting was attended by

Gianluca Reali (CNIT), Pietro Liò (UCAM), Luca Felicetti (CNIT), and Todor Ivanov

(Goethe University of Frankfurt), not involved in CIRCLE.

On May 23rd 2017, a meeting was held in Perugia for exploring the possibility of

exploiting MolCom and microfluidics for supporting research on ciliated. This

meeting was attended by Gianluca Reali (CNIT), Pietro Liò (UCAM), Luca Felicetti

(CNIT), and Sandra Pucciarelli (University of Camerino), not involved in CIRCLE.

- Talks in seminars and workshops

Prof. Ozgur Akan: "Fundamentals of Molecular Communications in Nanonetworks"),

Polytechnic University of Milan, Milan-Italy, 23-29 January 2016.

Prof.Ozgur Akan: "Communication Theoretical Understanding of Nervous

Nanonetworks", University of Naples Federico II, Naples, Italy, October 2015.



Prof.Ozgur Akan: “Fundamentals of Molecular Information and Communication

Science”, Workshop on Bio-Nano Things for Human Health, Oslo University

Hospital/Rikshospitalet, Oslo, Norway, March 2016.

Prof.Ozgur Akan: "Fundamentals of Molecular Communications in Nanonetworks",

Sapienza University of Rome, Rome, Italy, 23 – 29 January 2016

Pietro Liò, “Multidimensional methods to integrate biological data”, Dagstuhl

workshop, June 2016.

- Talks in seminars and workshops (scheduled)

Pietro Liò, “Design of Microfluidic Biochips: Connecting Algorithms and

Foundations of Chip Design to Biochemistry and the Life Sciences”, Dagstuhl

workshop, August 2016.

P. Liò, “Next Generation Sequencing – Algorithms, and Software For Biomedical

Applications”, Dagstuhl workshop, August-September 2016.

- Courses: “Nanoscale and Molecular Communications”, Prof Ozgur Akan, (KU-ELEC 550

Selected Topics in Electrical and Electronics Engineering), Spring 2016, Koc University.

- The CIRCLE personnel had a central role in the organization of the ACM Nanocom 2015 9,

201610, and 201711, a conference focused on research activities on nanoscale

communications, including molecular and terahertz communications. This conference was

held in Boston, USA, in September, 2015, In New York in Semptember 2016, and will be

held in Washington DC in September 2017. In addition, CIRCLE sponsored the conference

in 2015 and 2016. Many researchers in CIRCLE were included in the conference

committees, as follows:

Steering committee: Sasitharan Balasubramaniam (2015,2016, 2017), Ozgur Baris

Akan, (2015,2016, 2017), and Albert Cabellos (2015);

Conference co-chair: Sasitharan Balasubramaniam (2015), Yevgeni Koucheryavy

(2016), and Alan Davy (2017);

9 https://nanocom.acm.org/nanocom2015/index.html 10 https://nanocom.acm.org/nanocom2016/ 11 https://nanocom.acm.org/



TPC co-chair: Gianluca Reali (2017);

Tutorial co-chair: Mauro Femminella (2016); he organized a tutorial on molecular

communications entitled "Enlisting Synthetic Biology and Electrochemistry for

Molecular Communication", to be presented by prof. W.E. Bentley and G.P. Payne,

both of University of Maryland

Sponsorship co-chair: Alan Davy (2016)

Publication co-chair Albert Cabellos (2015)

The following CIRCLE participants have been members of the TPCs: Ozgur Akan,

Eduard Alarcon, Josep Solé-Pareta, Mauro Femminella, Gianluca Reali, Luca

Felicetti, Brendan Jennings, Pietro Liò, Yevgeni Koucheryavy.

- Coordination of a Special Issue of the research journal Elsevier Nano Communication

Networks. Alan Davy (WIT) and Gianluca Reali (CNIT) have organized the special issue

Special Issue on “Molecular Communications in Action: A Tutorial on Implementation,

Applications, Implications”12. This special issue provides tutorial contributions for

entering Molecular Communications by documenting the lessons learned from testbeds,

field-trials, and real deployments. In addition, it provides cutting-edge results that allow

newly entered researchers to be aware of the current status of the research.

The Special Issue includes five articles, co-authored also by researchers in CIRCLE,

organized in the following categories: Applications (A), Simulations (S), and Technologies

(T):

Adam Noel, Karen C. Cheung, Robert Schober, Dimitrios Makrakis, and Abdelhakim

Hafid, “Simulating with AcCoRD: Actor- �Based Communication via Reaction Diffusion''

(S). It introduces the AcCoRD simulator. It makes use of a combination of microscopic

and mesoscopic simulation models to represent molecule behavior. Readers are both

introduced to the reaction-diffusion theory and trained through the use utilities of the

simulator, which visualize the simulation environment designed to plot the time-

varying behavior or the observed phenomena.

12 https://www.journals.elsevier.com/nano-communication-networks/call-for-papers/special-issue-on-molecular-communications-in-action-a-tutori



Yi Liu, Eunkyoung Kim, Jinyang Li, Mijeong Kang, William E. Bentley, and Gregory F.

Payne “Electrochemistry for Bio-device Molecular Communication: The Potential to

Characterize, Analyze and Actuate Biological Systems'' (T). It shows that reduction

oxidation (redox) reactions may be used to provide a communication link for bio-

device communication.

Youssef Chahibi “Molecular Communication for Drug Delivery Systems: A Survey'' (A,S).

It presents the current status, challenges and research opportunities relevant to the

use of Molecular Communications for implementing targeted Drug Delivery Systems.

Michael Barros “Ca2C-signaling-based molecular communication systems: design and

future research directions'' (S,T). It surveys nanonetworks inside cellular tissues based

on calcium ions.

Shirin Salehi, Naghmeh S. Moayedian, Simon Assaf, Raul G. Cid-Fuentes, Josep Sole-

Pareta, and Eduard Alarcon “Releasing Rate Optimization in a Single and Multiple

Transmitter Local Drug Delivery System with Limited Resources'' (A,S), considers a

communications system, with multiple transmitters for targeted drug delivery.

- Organization of Special Sessions in International Conferences. Pietro Liò (UCAM) and

Gianluca Reali (CNIT) organized a special session on “Molecular Communications” at the

14th International Conference on Computational Intelligence methods for Bioinformatics

and Biostatistics, Cagliari, September 201713.

2.1.3. Industry researchers The program of the 1st CIRCLE Workshop on Molecular Communications, organized by UCAM,

Cambridge 11–12 April 2016, included the session “Stimulating Industry Engagement in

Molecular Communications”, chaired by Prof. Yifan Chen. This session included the following

presentations:

Yifan Chen “IEEE Std 1906.1TM on Nanoscale and Molecular Communications”

Dario Mazzella “Uptake of FET Projects – FET2RIN.com”

Andrew Young “ COMSOL – Multiphysics suite for Industry”

13 - http://co2.unica.it/cibb2017/



This session showed three important perspectives related to the MolCom penetration in

industries, namely the standardization process, the public EU funding, and the direct

involvement in the company products. The relevant discussion was fruitful and stimulating since

the attendees had the possibility to share their ideas on these subjects and allowed identifying

the issues for the industry exploitation of MolCom, which essentially originate from its

interdisciplinary and visionary nature.

The program of the 2nd CIRCLE Workshop on Molecular Communications, organized by WIT,

Dublin 9–11 May 2017, included the panel “Stimulating Industry Engagement in Molecular

Communications”14. The panel was chaired by Dr. Pietro Liò (Cambridge University): the other

panel members were Dr. Mirela Alistar (Hasso Plattner Institute), Sheryas Shah (Nokia Bell Labs,

US), Prof. Filippo Castiglione (National Research Council of Italy), Emre Ozer (ARM, UK).

In comparison to the 1st CIRCLE workshop, this panel showed a significantly more mature

awareness and attitudes of companies towards MolCom. The panellists, which were from well

established enterprises, attended all the workshop and not only demonstrated high interest for

MolCom, but also gave the view of their company and discussed it with the attendees in an open

and fruitful manner. They also made them available for organizing future events in collaboration

with the CIRCLE beneficiaries.

2.2. Dissemination activities for the general public This type of knowledge sharing activities can be better contextualised in WP5. Nevertheless, for

the readers’ convenience we list the most significant events.

- In the framework of the European Night of Researchers, on September 30th 2016, Luca

Felicetti (CNIT) and Marco Malvestiti (University of Perugia) gave the talk “Molecular

Communications”, within the so-called Storytellers Night Show event (See

http://www.perugiatoday.it/eventi/2-ottobre-sharper-notte-europea-ricercatori.html -

in Italian, visited on May 25th, 2017).

- On February 9th, 2017, Gianluca Reali (CNIT) and Marco Malvestiti (University of Perugia)

presented the CIRCLE project in a television program. This program was transmitted by

the broadcaster TEF Channel of the central Italy. The registration of the program (in

Italian) can be accessed at the following link:

14 https://www.youtube.com/watch?v=NCM709oRbvw



http://www.tefchannel.it/media/speciale-universita-9-febbraio-2017-000

• The CIRCLE Coordinator, Alan Davy, and the CIRCLE project appeared different times in

the Irish press, 2015.

• On September 25, 2015, Luca Felicetti (CNIT) presented the CIRCLE project at the event

Appy Days, Todi, Italy 15.

3. Staff exchange in CIRCLE Staff Exchange was a key activity for knowledge sharing in CIRCLE. The “Staff exchange

reporting process and register” document has been prepared and made available to the CIRCLE

participants in the initial phase of the project in order to put the process in motion.

The exchange of researchers has happened both between CIRCLE beneficiaries and between a

beneficiary in CIRCLE and other prestigious institutions that have established research

collaboration with CIRCLE since the project has started. This collaboration between CIRCLE and

other external institutions, and the relevant fruitful exchange of knowledge and best practices,

is a further important result the project.

The following Table 1 reports a summary of the exchanges carried out during the project

lifetime. The columns and rows of Table 1 report the source and hosting organizations,

respectively, of the staff exchange. As mentioned above, both of them can be either a CIRCLE

beneficiary or an external organization. Each staff exchange has been reported by using a

specific form, referred to as Staff Exchange Report Form. All reports are in Appendix. They

include the collaborating organizations, topics of the research collaboration, the period of the

exchange, the name of the involved people, the expected benefits for CIRCLE, and an evaluation

of the initiative.

A synthetic view of single staff exchanges, including just exchange ID, researcher name, source

institution, and hosting institution, is reported in Table 2.

From the content of the table it is evident that most of the CIRCLE partners have a single

outgoing researcher (i.e. visiting another organization), whereas most of the CIRCLE

beneficiaries host 2 incoming researchers or more. A picture of these data is shown in Figure 3.

It shows that all beneficiaries have contributed to CIRCLE outgoing mobility, and most of them

15 http://www.appydays.it/speakers/luca-felicetti/



with a single researchers (only CNIT and KU report two outgoing staff exchanges). However,

most of them have hosted more than one external researchers, with a mean number of staff

exchanges, both outgoing and incoming, of about 3 (the exact value is 2.875). This is a good

result, considering that the first year of the project, as mentioned in the Deliverable D3.3, has

essentially been used to set up the infrastructure and establish sound research collaborations.

This means that, during the second year of the project, on average, one researcher of each

CIRCLE beneficiary visited another institution and each beneficiary hosted two external

researchers.

Total incoming people

WIT UPC CAM KU IMINDS UNIPG TUT CNITOutside CIRCLE

15

WIT 1 1 1 3UPC 1 1 2CAM 1 1 2 4KU 1 1IMINDS 0UNIPG 0TUT 1 1CNIT 1 1 2Outside CIRCLE

1 1 2

Total outgoing people

15 1 1 1 2 1 1 1 2 5

Source Organization

Hos

ting

org

aniz

atio

n

Table 1. CIRCLE staff exchange summary.

Staff Exchange

ID

Researcher Source Institution Host Institution

1 Michael Taynnan Barros WIT TUT

2 Raphael Tavares de Alencar Federal University of Campina Grande (Brazil, extra CIRCLE)

WIT

3 Simon Sassine Assaf UPC CNIT

4 Shirin Salehi Isfahan University of Technology (Iran, extra CIRCLE)

UPC

5 Pietro Liò UCAM CNIT

6 He Peng University of Electronic Technology and Science of China (China, extra

CIRCLE)

UCAM



7 Eugenio Del Prete University of Basilicata (Italy, extra CIRCLE)

UCAM

8 Ozgur B. Akan KU UCAM

9 Ozgur B. Akan KU Georgia Institute of Technology (US, extra CIRCLE)

10 Ahmet Ozan Bicen Georgia Institute of Technology (US, extra CIRCLE)

KU

11 Pieter Stroobant IMINDS UPC

12 Marco Malvestiti UNIPG VUmc Cancer Center Amsterdam (Netherland, extra CIRCLE)

13 Stefanus Arinno Wirdatmadja

TUT WIT

14 Luca Felicetti CNIT UCAM

15 Luca Felicetti CNIT WIT

Table 2. List of staff exchanges.

0

1

2

3

4

5

6

WIT UPC CAM KU IMINDS UNIPG TUT CNIT

# of exchanges

Host Source

Figure 3. Role of CIRCLE beneficiaries in the staff exchange process.



This difference between the number of incoming and outgoing researchers was expected and it

is appreciable, since it demonstrated that CIRCLE has gained a good reputation in the MolCom

research community, and has attracted a significant number of external researchers. This

incoming flow of researchers has extended and improved the knowledge sharing process, the

scope of which has been well beyond the CIRCLE borders, as clearly shown in Figure 4. In this

figure, it can be observed that the collaborating institutions external to the CIRCLE project are,

by far, the most significant source of incoming visiting researchers, contributing with 1/3 to the

whole process. This witnesses the effectiveness of the CIRCLE project, and in particular of its

knowledge sharing strategy. Instead, and this was also expected, research institutions outside

CIRCLE had a less significant role in hosting visiting researchers from them CIRCLE beneficiaries,

as shown in Figure 5. This figure shows that in only two cases external institutions have hosted

CIRCLE researchers. In the first case, a researcher from UNIPG (a biomedical partner in CIRCLE)

has visited a prestigious biomedical institution in Europe (VUmc Cancer Center Amsterdam), in

order to explore potential applications of molecular communication in cancer diagnosis/therapy.

This is actually the desired type of knowledge sharing initiatives pursued by the project, since it

aimed to apply the knowledge received by participating to the project in a very important field,

with potential significant outcomes on biomedical research. The other case is completely

different, and consists of a bilateral exchange between KU and Georgia Tech, a very prestigious

university in the United States of America. In this case, Georgia Tech is leading a pioneering NSF

project on molecular communications named MONACO. The aim of this bilateral exchange was to

share knowledge in both institutions, thus creating a bridge between EU and US research

MolCom.

Instead, the other cases of exchanges from external institutions essentially consist of young

researchers coming from extra-EU willing to specialize in the novel MolCom area. In this regard,

a further analysis is presented in Figure 6. It shows the percentage of staff exchanges carried out

between CIRLCE partners (54%) with respect to the ones carried out with an external partner. It

is very interesting that 33% of the external institutions were extra EU. This demonstrates the

international profile of the knowledge sharing process of CIRCLE.



WIT20%

UPC13%

CAM27%

KU7%

IMINDS0%

UNIPG0%

TUT7%

CNIT13%

Outside CIRCLE

13%

Hosting institution

Figure 4. Outgoing mobility outlook.

WIT6% UPC

7%CAM7%

KU13%

IMINDS7%UNIPG

7%TUT7%

CNIT13%

Outside CIRCLE

33%

Source Institution

Figure 5. Hosting visiting researchers outlook.



Between CIRCLE partners

54% EU13%

Ouside EU33%Involving non

CIRCLE partners46%

8 exchanges

5 exchanges

2 exchanges

7 exchanges

Figure 6. Staff exchanges within CIRCLE and with external institutions.

Finally, the geographical distribution of extra-EU organizations involved in staff exchanges is

plotted in Figure 7. It emerges that exchanges with Asia (China and Iran) and North America (US)

represent 40% each of the exchanges, with one example also for South America (Brazil).

Asia40%

South America

20%

North America

40%

2 exchanges 2 exchanges

1 exchange

Figure 7. Hosting visiting researchers outlook.



A further level of analysis consists of mapping the staff exchange process with the joint research

activity carried out by research clusters, which are illustrated in Section 4.2. Thus, this analysis

is presented at the end of that section, after the description of the research activities in

research clusters. This mapping demonstrates that the staff exchange process was a key element

to reinforce joint research between institutions.

4. Joint research activities A considerable number of research and collaboration activities have been undertaken during the

CIRCLE project. We classify these activities in two categories. The first one includes the

activities that have been contributed by all CIRCLE participants. The second one includes the

activities that have been contributed by some CIRCLE participants and received also

collaboration from external groups.

4.1. Joint project-level collaboration Joint research and relevant knowledge sharing in CIRCLE is promoted also through the

establishment of the CIRCLE Forum, accessible in the CIRCLE portal under the Forum tab, or by

means a direct link16. The CIRCLE code repository is an additional tool supporting knowledge

sharing and collaborative research. These infrastructures have been implemented in the

framework of WP2, but its main usage is relevant to WP3.

In addition, the CIRCLE project publishes a CIRCLE Newsletter. The subscription to this

newsletter can be done via the project web site. The strategic plan of the project consists of

improving the amount of novel contents published in the CIRCLE web site, and in particular on

the home page, in order to attract visitors.

All CIRCLE participants contributed to the Review of Molecular Communications Simulators, with

integration of the existing simulators, developed by the CIRCLE participants, within a

comprehensive CIRCLE MolCom Toolbox. The integration leverages the input/output

capabilities of the MolComML language. Since this activity is a central point of the CIRCLE

project, and mainly of the WP3, an extensive description is reported in section 5.1. A survey on

16 http://conan.diei.unipg.it/lab/index.php/forum-circle



currently available MolCom simulators has been published in the IEEE TCSIM (Technical

Committee on Simulation) Newsletter, described in the following Section 4.3.

4.2. Individual research clusters In what follows we report a list of the collaboration and knowledge sharing activities in CIRCLE

in addition to the above mentioned CIRCLE Toolbox.

- Blood (UCAM, CNIT, UNIPG): Knowledge sharing activities on MolCom systems in blood

vessels. A survey of medical applications of Molecular Communications has been

published in the Elsevier Nano Communication Networks journal (see the publications

section). In addition, a further knowledge sharing activity is pursued by this cluster,

based on staff exchange, focused on Molecular Communications techniques devoted to

the early detection of circulating tumour cells (CTC) in blood vessels. UNIPG provided

values of the key parameters (e.g. vessels and cells size, bloodstream velocity, receptor

expressed on the surface of endothelial cells) by analysing the state of the art literature.

UCAM provided models about the generation and the survival of CTCs. Finally, CNIT

integrated models and simulations.

- MolComML (UCAM, UPC, CNIT, WIT): Development of a mark-up language for Molecular

Communications Systems (Molecular Communications Markup Language, MolComML). This

markup language had a central role in the CIRCLE activities since it was defined to

univocally specify simulation configuration (simulation parameters, topology, output

format), also using different simulators. This would help to make in silico analysis

comparable. A co-authored paper has been accepted and presented to the conference

ACM Nanocom 2016. Given the strategic importance of MolComML for CIRCLE and in

particular for the implementation of the CIRCLE MolCom Toolbox, an extensive

description of this activity is reported in section 5.2.

- Neuronal (WIT, TUT, KU): Collaboration and knowledge sharing activity in the framework

of neural dust motes to stimulate neuronal circuits molecular communications within the

cortex. The context consists of investigating the development of neural dust motes that

can be used to stimulate neuronal circuits molecular communications within the cortex.

The aim here is to provide new, long-term solutions that will allow these devices to be

embedded permanently within the cortex, and stimulate the neurons at single cell level.

The mechanism of stimulation is through the process known as optogenetics, where light

is used to stimulate the neurons that are genetically engineered. The key challenges of



this activity is the development of such a small scale device that can interface and

stimulate the neuron, and mechanism of powering the devices as well. The shared

expertise of each of the organization is as follows: TUT - neural dust modelling, in

particular light behaviour within the tissue; WIT - calcium signalling molecular

communication within the neurons; Koc University - electro-chemical signalling between

neurons. The collaboration includes a prestigious external organization, the University at

Buffalo, State University of New York, coordinated by Prof. Josep Miquel Jornet, who has

a sound expertise in the research on electromagnetic wireless nano sensor networks.

- Bacteria (KU, WIT, and UCAM): Knowledge sharing activities relevant to testing molecular

+ electromagnetic communications between bacteria. KU, in collaboration with WIT and

UCAM, is working on an initiative external to the CIRCLE project that consists of initiating

a wet-lab experiment with the objective of realizing molecular + EM communication

between bacterial populations located in different university campuses. The experiments

are expected to evolve towards a multi-purpose testbed, which will be used to test

synthetic biology based interfacing and transceiving capabilities of engineered bacteria.

This will be a first major step towards realizing synthetic bacteria based bio-transceivers

for molecular communication applications. Sharing of knowledge and best practices is in

the scope of CIRCLE

- Nano_SDN (UPC, IMINDS): Software defined networking applied to nanonetworks. The

algorithmic and routing knowledge of IMINDS together with the low layer expertise in

nanonetworks gave rise to new ideas and concrete proposals to explore, in particular in

the context of opportunistic routing with potential in vivo applications. The exchange

aimed at performing research involving ideas from the fields of opportunistic &

approximate routing to propose a routing algorithm that works in a range of applications

that involve very large networks with devices that are limited in their computing and

communication capabilities. These applications include applications of software defined

networking to nanonetworks, involving metamaterials.

Given those research clusters, we have elaborated on them and extracted insights. For this

purpose, we have used a weighted graph visualization approach in Figure 8. In the graph, nodes

are associated with research clusters, whereas edges represent the common institutions

participating in two clusters. The size of nodes is proportional to the number of participating

institutions, whereas the thickness of edges is proportional to the number of CIRCLE institutions



participating to nodes connected by the considered edge. In order to make things clearer, we

have reported these common institutions as labels of graph edges.

It is evident that, beyond a global participation in the CIRCLE MolCom Toolbox, which is a global

project target, there are a number of interconnected, smaller research clusters. The

participation of CIRCLE beneficiaries to those clusters is quite balanced.

Cluster WIT UPC UCAM KU IMINDS UNIPG TUT CNIT

Blood X X X

MolComML X X X X

Neuronal X X X

Bacteria X X X

Nano_SDN X X

CIRCLE Toolbox X X X X X X X X

Table 3. Research clusters in CIRCLE.

Figure 8. Research clusters outlook and relevant connections.



Finally, we present the mapping between the research clusters and the staff exchanges.

Whereas the detailed activities carried out during the researchers exchanges are reported in

Appendix 1, in Table 4 shows the research cluster to which each staff exchange (identified by

the staff exchange ID, defined in Table 2 and used also in Appendix 1) contributed.

Staff

exchange

ID

Research clusters

Blood MolComML Neuronal Bacteria Nano_SDN CIRCLE

Toolbox

1 X

2 X

3 X X

4 X

5 X X X

6 X

7 X

8 X

9 X

10 X X

11 X

12 X

13 X

14 X X X

15 X X

Table 4. Mapping of staff exchanges into research clusters.



Since multiple activities can be in place between different institutions concurrently, in some

cases the staff exchange of a single researcher contributed to the advancement of multiple

research clusters. For instance, it happened in exchange 5 (Pietro Liò, UCAM, visiting multiple

times CNIT) and exchange 14 (Luca Felicetti, CNIT, visiting UCAM). Another example is the visit

of Simon Assaf (UPC) to CNIT. During this staff exchange, the joint research on MolComML was

practically executed (see 5.2. for additional details), but the also the activity on CIRCLE MolCom

Toolbox significantly benefited from the achievements, consisting of the implementation of a

simulator combining two existing simulators (N3SIM and BiNS2), which interact through the

MolComML.

4.3. Publications Collaboration activities on Molecular Communications, carried out either in clusters or

individually, are accompanied by publication activities. Some papers have already been

accepted and published. Other papers are submitted for publication in the upcoming months.

For what concerns the publication activities involving the CIRCLE consortium as a whole, two

initiatives were undertaken, mentioned also above in Section 2.1.2. for their knowledge sharing

contribution between academic researchers.

- A CIRCLE contribution have been published in the IEEE Technical Committee on

Simulation newsletter (TCSIM Issue 22- July 19 2016,)17. This contribution illustrates the

current status of the simulation technologies in Molecular Communications and the plans

for a comprehensive CIRCLE Molcom ToolBox. In addition, a paper will be submitted to a

research journal illustrating the technical novelties of the CIRCLE MolCom ToolBox. The

WP3 leader Prof. Gianluca Reali has joined the Editorial Board of IEEE TCSIM as Vice-

Editor. He will chair a stable Section of the Newsletter dedicated to Molecular

Communication systems in the forthcoming TCSIM issues. Contributions can be short

papers, but also interviews to distinguished researchers, call for papers, etc.

- Special Issue in the Elsevier Nano Communication Networks journal, consisting of MolCom

tutorials, organized, edited and contributed by different CIRCLE participants (see Section

2.1.2. , published in May 2017. Given the prestige of this publication venue, it is

expected to boost the interest in MolCom, especially in young researchers, which could

smoothly enter this challenging area. This would be a significant contribution, aimed to

17 https://www.computer.org/web/tcsim/newsletter;jsessionid=8f6eb869e113cb1bafbcf1cdceef



young researchers, to provide a systematic organization of all the available teaching and

research material, dispersed in a number of journals, conference proceedings, and books.

For what concerns the individual publication activities, we have to distinguish between paper

published or accepted for publication, and papers in preparation. Papers belonging to these two

categories are listed in the two following sub-sections.

4.3.1. Papers published/accepted for publication

Luca Felicetti, Mauro Femminella, and Gianluca Reali. 2015. Smart antennas for

diffusion-based molecular communications. In Proceedings of the Second Annual

International Conference on Nanoscale Computing and Communication (NANOCOM' 15),

Boston, September 2015.

M. Femminella, G. Reali and A. V. Vasilakos, "A Molecular Communications Model for Drug

Delivery," in IEEE Transactions on NanoBioscience, vol. 14, no. 8, pp. 935-945, Dec. 2015.

doi: 10.1109/TNB.2015.2489565

L. Felicetti, M. Femminella, G. Reali, P. Liò, Applications of molecular communications to

medicine: A survey, Nano Communication Networks, Volume 7, March 2016, Pages 27-45,

ISSN 1878-7789, doi: 10.1016/j.nancom.2015.08.004.

L. Felicetti, M. Femminella, G. Reali. A simple and scalable receiver model in molecular

communication systems. Proceedings of the 3rd ACM International Conference on

Nanoscale Computing and Communication (ACM NanoCom 2016), New York, September

2016.

E. Alarcon, R. G. Cid-Fuentes, A. Davy, L. Felicetti, M. Femminella, P. Liò, G. Reali, J.S.

Pareta. MolComML: The Molecular Communication Markup Language. Proceedings of the

3rd ACM International Conference on Nanoscale Computing and Communication (ACM

NanoCom 2016), New York, September 2016.

G. Reali, M. Femminella, L. Felicetti, A. Davy, Michael Barros, R. G. Cid-Fuentes, A.

Cabellos-Aparicio, J.S. Pareta, E. Alarcon, P. Liò, P. Gresele, M. Malvestiti, W. Tavernier,

Y. Koucheryavy, V. Petrov, S. Balasubramaniam, Ozgur B. Akan. Simulation tools for

molecular communications. IEEE TCSIM (IEEE Computer Society Technical Committee on

Simulation) Newsletter.

S. S. Assaf, S. Salehi, R. G. Cid-Fuentes, J. Solé-Pareta and E. Alarcón. Characterizing the

Physical Influence of Neighboring Absorbing Receivers in Molecular Communication.



Proceedings of the 3rd ACM International Conference on Nanoscale Computing and

Communication (ACM NanoCom 2016), New York, September 2016.

O. B. Akan, H. Ramezani, T. Khan, N. A. Abbasi, M. Kuscu. Fundamentals of Molecular

Information and Communication Science. Accepted for publication in the Proceedings of

IEEE.

M. Kuscu, O. B. Akan. Modeling and Analysis of SiNW FET-Based Molecular Communication

Receiver. Accepted for publication in IEEE Transactions on Communications.

S. Salehi, S. S. Assaf, R. G. Cid-Fuentes, J. Solé-Pareta, E. Alarcón and N. S. Moayedian.

Optimal Deployment of Multiple Transmitter Drug Delivery System: A Spatial Sampling

Theorem Approach. Proceedings of the 3rd ACM International Conference on Nanoscale

Computing and Communication (ACM NanoCom 2016), New York, September 2016.

S. Salehi, S. S. Assaf, R. G. Cid-Fuentes, J. Solé-Pareta, E. Alarcón and N. S. Moayedian.

Designing a Local Drug Delivery System Considering Multiple Transmitter Deployments. In

preparation. Proceedings of the 3rd ACM International Conference on Nanoscale

Computing and Communication (ACM NanoCom 2016), New York, September 2016.

L. Felicetti, M. Femminella, G. Reali, "Congestion Control for Biological Nanoscale Cyber-

Physical Systems", Bodynets 2016, Torino, Italy, DOI: 10.4108/eai.24-4-2017.152544.

L. Felicetti, M. Femminella, G. Reali, "Congestion Control in Molecular Cyber-Physical

Systems", IEEE Access, DOI: 10.1109/ACCESS.2017.2707597.

4.3.2. Papers in preparation/submitted

G. Reali, M. Femminella, L. Felicetti, A. Davy, Michael Barros, R. G. Cid-Fuentes, A.

Cabellos-Aparicio, J.S. Pareta, E. Alarcon, P. Liò, P. Gresele, M. Malvestiti, W. Tavernier,

Y. Koucheryavy, V. Petrov, S. Balasubramaniam, Ozgur B. Akan. A survey of simulation

tools for molecular communications. In preparation.

E. Alarcon, R. G. Cid-Fuentes, A. Davy, L. Felicetti, M. Femminella, P. Liò, G. Reali, J.S.

Pareta. MolComML: The Molecular Communication Markup Language. Journal paper

extension, in preparation.



T. Khan, B. A. Bilgin, O. B. Akan. Three-Dimensional Diffusion-based Model of a Synaptic

Channel with Pre-synaptic Re-uptake. Submitted for publication in IEEE Transactions on

Communications.

B. A. Bilgin, O. B. Akan. A Deterministic Approach for Modelling Stochastic Synaptic

Communication. Submitted for publication in IEEE Transactions on Nanobioscience.

N. A. Abbasi, O. B. Akan. Nervous system based molecular communication link using

Earthworms. Submitted for publication in Nature Communications.

H. Ramezani, O. B. Akan. Modeling Spike Amplitude Variation in the Axonal Transmission.

Submitted for publication in IEEE Transactions on Communications.

D. Malak, H. Ramezani, O. B. Akan. Adaptive Weight Update in Cortical Neurons and

Estimation of Channel Weights in Synaptic Interference Channel. Submitted for

publication in IEEE Transactions on Nanobioscience.

5. CIRCLE MolCom Toolbox As an example of intense collaboration of the CIRCLE beneficiaries, and the fruitful collaboration

also through staff exchange detailed in Section 3. , we illustrate the development of the CIRCLE

MolCom Toolbox, which is a pivotal activity in CIRCLE. The beneficiaries that have mostly

contributed to this toolbox are UPC, CNIT, UCAM, and WIT. Nevertheless, all the CIRCLE

beneficiaries in CIRCLE have given a contribution for the design, implementation,

experimentation, assessment, and dissemination of this toolbox. In particular, the different

contributions to this activity are sketched in Figure 9. Most of partners have contributed by

means of simulation platforms, and namely UPC (N3Sim), CNIT (BiNS2), TUT (NCSim), KU

(NanoNS), and WIT (CalComSim). In addition, IMINDS contributed by providing knowledge about

computationally efficient algorithms, with the target of lowering the computational requirement

of MolCom Simulations. Finally, UNIPG contributed by providing realistic data by conducting a

deep literature analysis, whereas UCAM contributed with a number of mathematical models in

different simulators.

This activity tackles the need of harmonizing the various MolCom simulation tools in a single

toolbox, able to provide users with a unified interface to interact with the simulator. This

activity is strategic for the future of molecular communication research, since it is relevant to

Task 3.2, with the aim of fulfilling the objective O4. This activity has generated, in turn, two

distinct although strongly related activities: the design of an integrated MolCom toolbox, and



the definition of a MolCom Markup Language (MolComML). Whilst the first activity clearly

addresses the need of providing a unified simulation platform, the second has a slight different

scope. In fact, the MolCom Toolbox, as illustrated in the next subsection, may need to exchange

simulation and configuration data between the integrated simulators during a single simulation

session. This requires a standardized way to encode data, and especially simulation

configuration, in order to provide configuration information that do not strictly depend on the

source/destination simulator, but are standardized. This relieves each researcher with unneeded

knowledge of the internal simulation structure. Finally, the scope of MolComML, in principle, is

not tied to simulations only. In fact, it could be used to describe, in a standardized and unique

way, also web lab experiments, to ease their reproducibility in different laboratory. Clearly, this

would require also the design and implementation of a software tool able to visualize, in an easy

to use way, the information encoded in the XML format.

CIRCLE Toolbox

Simulation platform providers1. CNIT (BiNS2)2. UPC (N3Sim)3. WIT (CalComSim)4. KU (NanoNS)5. TUT (NCSim)

Computationally efficient algorithms(IMINDS)

Modelsand data providers

(UNIPG & UCAM)

Figure 9. Contribution to the CIRCLE MolCom Toolbox.

To sum up, the main goals of this activity include the integration of at least two simulators into

the CIRCLE MolCom Toolbox. In this way, we could show a practical case study where the

toolbox works, and the complete definition and implementation of the MolComML. This required

the design and implementation of the input models in existing simulators to read these

standardized simulation configuration data. Both these targets have been achieved, as shown in

the following two sub-sections.

5.1. CIRCLE MolCom Toolbox implementation The CIRCLE MolCom toolbox has a modular software architecture, based on three main modules

sketched in Figure 10. These modules are the I/O module, the orchestration module and the



execution module. The latter is a container including the functions and algorithms which are

already available within the relevant packages.

Note that the CIRCLE MolCom toolbox is not aimed at introducing a new simulator, or a different

simulation strategy. On the contrary, it leverages the existing simulators, by taking advantage

from all their peculiarities, and achieving ambitious results by their integration.

Figure 10. CIRCLE MolCom Toolbox.

In order to show a practical example, UPC and CNIT have integrated their respective simulators

(N3Sim and BiNS2) in order to simulate the communication via diffusion of neurotransmitters

(form the axon terminal to the dendrite, see Figure 11. ). This communications happens by

means of messenger molecules with a radius equal to 0.2 nm, which diffuse in the chemical

synaptic cleft to exchange information between the neurotransmitter of the axon and the

receiver (dendrites) with 20 receptors. The synaptic cleft is the distance between the

transmitter and the receiver and it is equal to 20 nm. The radius of the transmitter is 0.1 nm,

whereas the radius of the receivers is 4 nm, with twenty receptors each one with radius of 1 nm.

The simulation time step is 0.1 ns.



Figure 11. Communications via diffusion in a synaptic cleft.

The goal is to simulate this scenario with N3Sim, since it is a simple but very agile simulator,

which can speed up simulations by neglecting collisions between molecules. Although also BiNS2

implements this function, the benefit that can be obtained by disabling the checks among

molecules are not so significant. However, the N3Sim simulator is able to simulate just absorbing

receivers, without implementing the functions associated with individual receptors. Instead, this

is a key function of BiNS2. Thus, the idea is to simulate the overall scenario with receptors as

very small absorbing receivers. The missing step is the capability of placing these receptors on

specific positions over the surface of the receiver, which can be easily done by using BiNS2. In

synthesis, the goal of the integration of of the two simulators is to produce a single and fast

simulation, is shown in Figure 12. The simulation settings are specified by MolComML, as a

common simulation description language. Then, the simulation is started in BiNS2, which easily

places nodes with relevant transmission channels and receptors. This simulation ends by

producing a simulation status report, encoded again by MolComML. This is sent to the N3SIM

simulator, which runs the simulation by implementing the release of molecules by multiple

nodes (neurotransmitter transporters) and the reception by multiple adsorbing receivers

(receptors on the dendrite), thus implementing a sort of multiple input multiple output (MIMO)

simulation.

Although this simulation is quite simple, it implements the three modules of the CIRCLE MolCom

Toolbox:

1. The I/O module, implemented by means of MolComML files.

2. The orchestration module, implemented by means of a bash script, which triggers the

start/stop of different simulators, when the MolComML intermediate output file is

generated. It could also launch multiple instances of the same simulation, in order to

extract data which are statistically significant.



Figure 12. Simulation of neuronal communications through the CIRCLE MolCom Toolbox.

3. The execution modules are the .jar files of the two simulators, which are both

implemented in Java. In this case, the "containers" are the two Java Virtual Machines

running the two simulators.

5.2. MolCom Markup Language (MolcomML) The existing simulation tools of molecular communication systems, some of which have been

mentioned in the previous section, utilize different languages, configuration and output files,

and other particular features that make cross-validation and reproducibility or results often

unfeasible, especially for complex communication architectures. In order to facilitate

collaboration and knowledge sharing we have pursued the development of a harmonization tool,

the so called MolCom Markup Language (MolComML).

In this section, we provide some details about the initial design MolComML. It is an XML-based

language that promises to reunite both numerical analysis and experimental synthesis by

ensuring a flexible markup language [4]. This will allow cross-validation of experiments with the

theoretical results, as well as to reduce significant researcher time in interfacing different

software tools. As sketched in Figure 14. , the target of this activity can be compared with that



of XML-based languages, which allow specifying network configuration in a unified way, such as

NETCONF [6], or OF-CONF [5] for Software Defined Networking devices.

The MolCom Toolbox may need to exchange simulation and configuration data between the

integrated simulators during a single simulation session. This requires a standardized way to

encode data, and especially simulation configuration, in order to provide configuration

information that do not strictly depend on the source/destination simulator, but are

standardized. This relieves each researcher with unneeded knowledge of the internal simulation

structure. In addition, the MolComML, similarly to other markup languages, such as SBML, SBOL,

and CellML, has a broader scope, since it allows exchanging also simulation models in a compact

yet effective way. Finally, the scope of MolComML, in principle, is not tied to simulations only.

In fact, it could be used also to describe, in a standardized way, wet lab experiments, to ease

their reproducibility in different laboratories. All these concepts are sketched in Figure 13.

Sim#1

Sim#2

Sim#3

Lab

out

in

in

Figure 13. Potential usage of the MolComML.

We present the initial design concepts of MolComML, including the main objectives, elements

and functionality of the proposed language.

The definition of the MolComML is guided through a simple example, which aids the overall

understanding of the language. First, we overview existing specification languages for other

disciplines, as well as the IEEE 1906.1 standard.



� The model defined by the IEEE 1906.1 Working Group stands as the first nanoscale and

molecular communication standard and constitutes a recommended practice for the

definition of a general framework for the nanoscale communications. The proposed

markup language extends the definitions given by the IEEE 1906.1, allowing an easy

description of the molecular communication networks. This standard proposes an

architecture based on the following blocks: NetDevice, Communication Interface,

Medium, Motion, Field, Specificity, and Perturbation.

� As for mark-up languages used in biology, one of the most important related language is

SBML [8], that is nowadays the standard for representing computational models in system

biology. Specifically, it allows communication and storing of computational models of

biological processes. Its success is due to the possibility to represent different classes of

biological phenomena, such as cell signalling pathways, regulatory networks, and many

others. The main purposes of SBML are essentially model sharing on different software

environments and allow these models to survive beyond the lifetime of the software

packages used to create them. Given the strategic importance of these features, we have

decided to introduce them also in MolComML, thus allowing also an easy integration of

the SBML models.

� Another specification language used for the description of molecular biology is SBOL [9].

It was introduced for specifying and exchanging biological design information in synthetic

biology. It can describe biological processes in deeper details than SBML. For example, it

allow representing amino acid or nucleotide sequences. In particular, it supports the

explicit and unambiguous description of biological designs through a rigorous definition of

rules on how to use the provided data models with a special focus on the design details.

Hence, the SBOL standard is fully qualified to represent structural components of a

biological design, such as DNA and RNA, proteins, small molecules, including also

behavioural aspects.

� The CellML language is an open standard based on the XML markup language [10]. The

purpose of CellML is to store and exchange computer-based mathematical models. CellML

allows scientists to share models even when they use different model-building software.

It also enables them to reuse components from one model to another one, thus

accelerating model building. Although CellML was originally aimed to the description of

biological models, it has a broader application. CellML includes information about model

structure, mathematics and metadata by leveraging existing languages, including MathML



and RDF. The CellML project is closely affiliated with another XML-based language

project currently underway at the University of Auckland, FieldML. Combined, these

languages provide a complete vocabulary for describing biological information at a range

of resolutions from the subcellular to organism level.

� NeuroML is an XML-based model description language, which provides a powerful common

data format for defining and exchanging models of neurons and neuronal networks [11].

The structure and behaviour of ion channel, synapse, cell, and network model

descriptions are based on underlying definitions provided in LEMS, a domain-independent

language for expressing hierarchical mathematical models of physical entities. It includes

two Application Programming Interfaces (APIs) written in Python to simplify the process

of developing and modifying models expressed in NeuroML and LEMS.

The basic structure of the MolComML consists of several main blocks, reflecting the main

components of a general molecular communication system. Each block is composed of a set of

required parameters and a set of custom parameters that are defined according to the molecular

communication purposes. The complete UML structure of the MolComML is shown in Figure 15.

This figure highlights two main sections in the UML structure. The first one is used to specify the

functional elements in the language (blue shaded). The other is used to specify attributes and

mathematical formulas (red shaded).

A possible application scenario is illustrated in Figure 16. Part of the XML code relevant to the

depicted scenario is reported in Figure 17.

In order to be able to use a MolComML file, each compliant simulator needs a parser module,

able to extract the information from MolComML and translate it into its specific configuration

file. A further step is to design an input module, able to read directly the information contained

in the MolComML file. We have almost finalized its implementation in BiNS2 [2] as a proof-of-

concept.



Figure 14. Top-bottom comparison between a computer network and a Biological System



Figure 15. UML diagram of the MolComML.

Attr

ibut

es a

nd

Mat

hem

atic

al fo

rmul

asM

olC

omM

Lele

men

ts



Channel

Network Topology

Figure 16. Graphical description of the MolComML file used to illustrate the framework in [7].

List of objectives

The main objectives of the MolComML format are listed in what follows:

� Representation of different classes of molecular communication scenarios, at all levels of

abstraction.

� Enable the use of multiple software tools without having to rewrite models to conform to

different file formats.

� Guarantee the survival of models beyond the lifetime of the software used to create

them.

� Usage of a single language both to analyze the considered scenarios through software

tools, as well as to synthesize actual experiments. This ensures repeatability and cross-

validation.



� Enable models to be shared and published in a form that any researcher can use even by

making use of different software environments.

� Enable future expandability of the markup language. Due to the rapid knowledge growth

in this field, this language needs to be constantly updated. MolComML will be versioned

to structure the integration of novel definitions and models.

Elements and Functionality

Network Elements

Network elements are regarded as the building blocks by users. They are created and

interconnected to define the simulation or experimental set-up. Each element may be defined

by different levels of abstraction. For instance, it can be an entirely conceptual entity, it can

have some real physical interpretation, or both. Each network element has a set of standard

attributes that could be extended by the introduction of custom ones.

The most important attributes describe the shape and size of the element, its mass and time to

live properties, the accepted and transmitted signals and, finally, the motion rules, if such

element is equipped by autonomous propulsion system.

The main network elements are as follows:

� Transmitter: These elements are in charge of encoding information in the form of a

molecular communication. They need to include all the relevant parameters. Among

others, rate of creation of molecules, rate of emission, and the molecule release

mechanism.

� Receiver: These elements are in charge of decoding the information by detecting the

induced fluctuations in the molecular channel. They need to consider multiple

configurations and types of receivers, such as absorbing receiver and receiver with

absorbing receptors.

� Signal: The transmitted signal carries the information towards the receiver. This can be

based on DNA, proteins, ions, and others.

Derivations of these elements, as well as other elements (active or passive) in the

communication channel that may affect the communication process can also be part of this list.

An example, relevant to [7] (see Figure 16. ) is illustrated in Figure 17.



Figure 17. Network elements in the MolComML Configuration file of the framework presented in [7] and Figure 16.

Communication Interface

Network Elements can be connected with other elements by using the Communication Interface

element, that describes the external interfaces of each network element. Such interfaces have

several properties that describe also the type of transmitted and received signals, their affinity

and the direction of communication. Again, a subset of custom parameters can be defined in

order to describe more in details the properties of each interface, as described in what follows.


Figure 18. Communications interface in the MolComML Configuration file of the framework presented in [7] and Figure 16.

Properties and parameters

It is often allowed the definition of a list of custom attributes. This approach allows a high

customization capabilities, extending the predefined attributes or introducing completely new

ones. This approach allows specifying both properties and attributes of each element described

in the MolComML configuration file.



Compartment Elements

The compartments are intended as a kind of well-stirred container of a particular type and finite

size where species (e.g. chemical substances) may be located. A model may contain multiple

compartments even of the same compartment type, and they can also be located inside each

another, hierarchically. Connections between different compartments are handled by Gates,

that define the rules for crossing. Note that each species (i.e. Network Element) in a model must

be located within a compartment.


Figure 19. Compartment in the MolComML Configuration file of the framework presented in [7] and Figure 16.

Gates

It is possible to define a list of Interconnection gates between a couple of adjacent

compartments. Each gate is identified by a unique name, a position, size, shape and orientation,

in order to create a sort of passing hole on the surface of both compartments.

Interaction Rules

A set of rules need to be defined. They restrict or specify the operation of the network elements

and their connections. The collision behaviour is a typical example: upon impact, molecules can

join, merge, or absorb each other, or they can bounce away from each other.

Each rule could either be a global rule valid everywhere or be more specific, describing only a

part of the communication environment, or be valid only for a subset of network elements. In

general, rules are described by mathematical expressions imported from an external model (e.g.

MathML). It is also possible to initialize constants and variables of the imported equations.




Interaction Rules

Figure 20. Interaction rules in the MolComML Configuration file of the framework presented in [7] and Figure 16.

Communication Channels

The transmitted signals are transferred to receivers through communication channels. There

exist several channel types. Junction-based, diffusion, and diffusion-with-drift are examples of

existing channel types. A channel element has to be defined and connected to each

compartment placed in the communication environment. This ensures the description, with a

high degree of accuracy, of the local environmental conditions, by means of specific

mathematical rules defined in one or more external MathML files. It is also possible to initialize a

set of the parameters used in the imported equations. Each channel definition could be shared

between two or more Compartments. The association channel-compartment is defined in the

compartment section.


Channel

Figure 21. Communication channel in the MolComML Configuration file of the framework presented in [7] and Figure 16.

Network Topology

Each Network Element defines only the main properties of such element. The Network Topology

section is used to place the required elements in the proper Compartment. The Topology of the



molecular communication network is described by defining the position and orientation of each

element and also the communication protocol at the basis of the end-to-end communication.

The initialization of any node parameters are declared here.


Network Topology

Figure 22. Network topology in the MolComML Configuration file of the framework presented in [7] and Figure 16.

Protocol Stack

In this section we define the protocol stack that could be used for the communication needs. It

is possible to define any number of protocol stacks and each one could have a custom structure

composed of different depth and identification name. Each layer could map the well known

protocol stacks of the traditional telecommunication field or define completely new layers.

The layers are defined by a set of rules and each one is composed of two signals, the first is for

the forward communication and the second is for the backward communication. For each signal,

the type of carrier that will be transmitted and the modulation type are defined. It is also

allowed the definition of a set of custom parameters in the standard XML format in order to

initialize all the required parameters for that layer. By considering the scenario in Figure 16. , it

is necessary, for the link layer, to specify the format of the transmitted messages, along with

the algorithms that manage the communication, such as the synchronization and the rate control

algorithms for each signal type defined above.




Figure 23. Protocol stack in the MolComML Configuration file of the framework presented in [7] and Figure 16.

Event Scheduler

The Event Scheduler tag allows the definition of both the initial state for each Network Element

and specific events that cause a state transition on a target node, upon the occurrence of an

event or at scheduled times.

Unit Definition

Each numerical attribute defined in the MolComML files is associated with a unit of measure

declared in a specific section. It is possible to define the most common units, and their

multiples, in the International System. The definition of custom units is based on the

combination of the previous ones, by setting their values, scales and exponents. The name

selected for each custom unit can be used in the other sections of the file, i.e. for the definition

of the numerical value of the considered attribute.



External Sources

MolCom systems is expected to interact with elements modelled in the neighbouring disciplines.

In order to allow interoperability, it is necessary to translate the configuration parameters and

results from the other languages, such as SBML or SBOL, providing a flexible adaptation layer

that will help integrating and extending the usability of MolComML. For this reason, in the

MolComML files it is possible to define the elements to be imported from each external source.

For each one, the list of imported elements is defined by specifying the coupling between the

original name in the external source with the name used in the MolComML file. For each pairing,

also the importing rule is specified; it could be either a comprehensive or a partial import. For

the latter case, it is necessary to define each parameter that has to been imported, by

specifying its identification name on the external source.

Output

The output data format is fixed for all simulations and numerical results. The defined output

scheme allows it to specify which elements have to be exported. In more detail, it is possible to

define the list of Network Elements, of the Compartments and of their attributes, by specifying

also the time interval for their monitoring. The definition of the monitored attributes is

completely custom, so you can define a rule for each attribute of interest.

If the software performs additional post-processing steps applied on the raw numerical results of

simulation steps, these have to be described in detail. This includes the identification of data to

process, the order in which changes were applied, and also the nature of changes.

A possible format of the output could be, once again, the MolComML format, so as to use the

output of a simulator to feed another simulation run with a different program, which can parse

the MolComML format.

5.2.1. Example of usage of MolComML with two simulators This section illustrates the simulation scenario used to validate the MolComML concepts. In

particular, we have implemented two parser modules of the MolComML files in two specific

simulators: N3Sim and BiNS2. Both simulators support molecule propagation due to pure

diffusion in a 3D space, and both of them can implement the absorbing receiver model. Thus,

these simulators are good candidate to assess our implementation of the MolComML. In more

detail, our goal is is to verify that we obtain the same results by loading the same MolComML

input file into the two simulation platforms.



We have defined a simulation with the following main parameters:

single burst of molecules: 500 or 1000 molecules

time step: dt = 50us;

RX-TX distance: 5 m

RX node Radius: 5 m

TX node Radius: 50nm

Carrier Radius: 1.75nm

The complete simulation configuration is shown in the MolComML file reported in Appendix 2.

We have run the test with two different burst sizes: 500 and 1000 molecules, in order to verify

possible dysfunction with system size. The results are shown in Figure 24. The yellow solid curve

represents the theoretical model, used to validate the results of both simulator, for a burst size

of 1000 molecules. The solid blue curve represents the theoretical model for a burst size of 500

molecules. The BiNS2 results are represented by the green solid curves, whereas the N3Sim ones

by the dashed red curves.

Theoretical curve, burst 1000 molecules

Theoretical curve, burst 500 molecules

BiNS2 N3SIM

Figure 24. Simulation results obtained with N3Sim and BiNS2 with the same MolComML input file.



The agreement between simulation curves and theoretical ones is excellent. Thus, MolComML is

a way to configure the same simulation across heterogeneous platforms, which is exactly the

desired minimal result.

5.2.2. Example of MolComMl usage for simulating blood vessels In this section, we show how to generate, by means of the MolComML, a simulation of a system

more complex than the one in Section 5.2.1. We consider a section of a blood vessel, in which

white blood cells, red blood cells, and platelets move as a consequence of collisions and the

Hagen–Poiseuille law. The relevant MolComML configuration file is reported in Appendix 3 of this

deliverable. In addition to these cells, we have considered also the presence of circulating

tumour cells (CTC). We assume to analyse a vessel portion far from the tumour location; thus

the probability of having more than one CTC at time in the same short vessel section is

negligible. We simulate the presence of a CTC at the vessel entrance, and locate the receiver at

different distances from the vessel axis. We assume that the receiver can detect the presence of

the CTC by using its surface receptors which are affine to the ligands present on the CTC

surface. In addition, it does not affect the movement of the CTC (hypothesis of transparent

receiver). This study, carried out in the framework of the Blood research cluster, aims at

identifying potential optimal positions of a CTC sensors within a blood vessel.

Extensive simulations have shown that CTC close to the vessel tend to remain close to the

endothelium, whereas CTC close to the vessel axis tend to maintain that position. Instead, CTCs

that are in an intermediate region between the vessel axis and the vessels wall18 tend to

randomly move toward one of the two extremes, mainly depending on the collisions with other

blood cells. Thus, CTC sensors should be placed on the endothelium, or close to the vessel walls,

to maximize the probability to intercept CTCs in the blood.

6. Performance assessment of the knowledge sharing initiatives.

This section includes the final evaluation of the WP3 project activities (knowledge sharing), on

the basis of the criteria introduced in the deliverable D3.1. This assessment consists of the joint

verification of the milestones and other performance metrics. For what concerns the project

milestones, MS3 and MS5 are formally in charge to WP3, and have been accomplished within the

18 For instance at the exit of a curvature of the vessel.



first year of the project. In addition, even the other project milestones, which are necessary for

a correct execution of the WP3 activities, were successfully accomplished. Thus, the necessary

conditions identified in D3.1 are met. For what concerns the other performance metrics, which

are relevant to the objectives of the project, that are reported in what follows for the readers’

convenience, along with their assessment.

O1: Submission of papers on molecular communications contributed by all the CIRCLE

participants. At least a research paper, demonstrating the contribution of different

research groups in CIRCLE, must be submitted by the end of the first year of the project.

It is expected, for very positive assessment, multiple papers to be published. Largely

Accomplished. See section 4.3.1.

O2: At least a tutorial paper must be published. This tutorial paper should include the

expertise of different disciplines and demonstrate the suitable integration of the

biomedical expertise and the ICT expertise. Largely accomplished. In Section 2.1.2. we

have illustrated that a Special Issue in the Elsevier Nano Communication Networks

journal, consisting of MolCom tutorials, organized and written by the CIRCLE participants,

have published.

O3: The definitive performance assessment relevant to this objective can be done well

beyond the end of the project. However, the results obtained by the staff exchange

process and the establishment of a sound research collaborations of the CIRCLE

participants, both in EU And Extra EU, are very promising and have surely determined the

presence of a well known EU MolCom research community. The success of the knowledge

sharing event dedicated to research personnel is a further indication of this result.

Accomplished.

O4: Performance assessment of knowledge sharing relevant to this objective consists of

fulfilling the following four requirements:

O4.1: Presence of at least one follow-on initiative oriented to support research in

molecular communications. Accomplished. See D5.2 Section 2.1.

O4.2: Presence of a research initiative compliant with the existing standardization

activities. Accomplished. MolComML is compliant with IEEE 1906.1. See Section 6.2.

04.3: Accomplishment of a comprehensive analysis on the current opportunities for

undertaking studies at master and PhD levels in molecular communications.



Accomplished. See Section 2.1.1.

O4.4: CIRCLE sponsorship to a specialized conference on molecular communication and

contribution to a school See Section 2.1.1. CIRCLE also sponsored the ACM Nanocom

conference in 2015 and 2016 . Accomplished.

O5: The Staff Exchange process has been successfully executed. The relevant analysis is

illustrated in Section 3. Accomplished.

O6: The definitive performance assessment relevant to this objective can be done well

beyond the end of the project. Nevertheless, the CIRCLE initiatives aiming at industry

engagement (see Section 2.1.3. ) gave good results in terms of participation and paved

the way for future collaborations. Accomplished.



Appendix 1: Staff Exchange Reports In this appendix, we report all the staff exchange reports, grouped by the institution to which the

researcher belongs. In case of researchers coming from institutions that are not CIRCLE beneficiaries, the

report will be included in the section relevant to the hosting institution (CIRCLE beneficiary).

Source institution: WIT

1. CIRCLE Staff Exchange Report Form for Michael Taynnan Barros Name of the researcher taking part in the CIRCLE exchange initiative: Michael Taynnan Barros

Affiliation (CIRCLE partner): Waterford Institute of Technology, Ireland Name of the visited institution (CIRCLE partner): Tampere University of Technology, Finland - Objectives the CIRCLE staff exchange initiative: Abstract of the activities promoted by the Staff Exchange.

The researcher had the following objectives in visiting the NanoCommunication Center, in the Tampere University of Technology, Finland:

Develop a communication system model for cortical microcircuits. Obtain training about wireless optogenetics nanonetworks, its challenges and research directions. Integrate this communication system model with the wireless optogenetics nanonetwork study (currently

performed in the NCC/TUT), and investigate how knowledge from the cortical microcircuit communication can benefit the design of wireless optogenetics nanonetwork systems.

Two papers were submitted as an outcome of the exchange program:

1. M. T. Barros. Information Theoretical Analysis of the Cortical Microcircuit Communication Channel. Submitted to ACM NANOCOM. 2017.

2. S. Balasubramaniam, S. Wirdatmadja, M. T. Barros, Y. Koucheryavy, M. Stachowiak and J. Jornet. Wireless Communications for Optogenetics: Present Technology and Future Challenges. Submitted to IEEE Communications Magazine. 2017.

- Details about the exchange



Start date: 01-03-2017 End date: 01-04-2017 Evaluation of the CIRCLE staff exchange initiative: - Were these objectives met? X ‘Yes’ □ more than 70% of the objectives were met. □ less than 70% of the objectives were met □ ‘No’ - Rate the general satisfaction of the staff exchange initiative X 100% □ 75% □ 50% □ 25% □ none

- What were the most important benefits of the exchange? Please outline the most important areas that could have been improved and allowed you to get more out of the exchange. The exchange program has allowed me enlarge my research topics by being introduced to wireless optogenetics nanonetworks. I obtained a fast knowledge of the area that was only possible through this exchange program due the given time period, otherwise, the same knowledge would have taken a longer time. This was essential for the enhancement of my professional skills, by enlarging my networking within Europe and by opening new research expertise and possibilities. The exchange program can be improved with longer periods, in which both the researcher and the visited institution can be benefited even more. - Logistic aspects Were there any problems with travel and accommodation arrangements and if so what could be done to improve them in the future? The travel and accommodation arrangements were high standards and allowed me to fell very comfortable during my visit.

- Any other comments about the exchange: This exchange program is essential for a novel knowledge area such as molecular communications, and there needs to be more actions like this in the near future. Please note that information in this form will be shared with other CIRCLE partners and be processed for producing results to be published in the CIRCLE deliverables and documents.



2. CIRCLE Staff Exchange Report Form for Raphael Tavares de Alencar

Name of the researcher taking part in the CIRCLE exchange initiative: Raphael Tavares de Alencar

Affiliation (non CIRCLE partner): Federal University of Campina Grande, Brazil Name of the visited institution (CIRCLE partner): Waterford Institute of Technology, Ireland - Objectives the CIRCLE staff exchange initiative: Abstract of the activities promoted by the Staff Exchange.

The following objectives were proposed during the visit. Training on molecular communication and bacteria communication nanonetworks Develop a encoding method to encode videos in populations of bacteria and a

reliability technique based on their communication

- Details about the exchange Start date: 24-09-2016 End date: 07-11-2016 Evaluation of the CIRCLE staff exchange initiative: - Were these objectives met? x ‘Yes’ □ more than 70% of the objectives were met. □ less than 70% of the objectives were met □ ‘No’ - Rate the general satisfaction of the staff exchange initiative x 100%



□ 75% □ 50% □ 25% □ none

- What were the most important benefits of the exchange? Please outline the most important areas that could have been improved and allowed you to get more out of the exchange. The exchange program has allowed me enlarge my research topics by being introduced to bacteria communication, DNA computing and genetic enconding techniques. Before this exchange program, I had no previous experience with the area of molecular communications and I obtained a fast knowledge of the area that was within time period. This was essential for the continuity of my PhD research by enhancement of my research skills, whilst improving my networking within Europe. The exchange program can be improved with longer periods, in which both the researcher and the visited institution can be benefited even more. - Logistic aspects Were there any problems with travel and accommodation arrangements and if so what could be done to improve them in the future? The travel and accommodation arrangements were perfect.

- Any other comments about the exchange: None. Please note that information in this form will be shared with other CIRCLE partners and be processed for producing results to be published in the CIRCLE deliverables and documents.

Date: 24/05/2017

Source institution: UPC

3. CIRCLE Staff Exchange Report Form for Simon Sassine Assaf Name of the researcher taking part in the CIRCLE exchange initiative: Simon Sassine Assaf. Affiliation (CIRCLE partner):



Universitat Politècnica de Catalunya (UPC). Name of the visited institution (CIRCLE partner): CNIT. - Objectives the CIRCLE staff exchange initiative:

First, N3Sim is a complete simulation framework for diffusion-based molecular communication which allows the evaluation of the communication performance of molecular networks with several transmitters and receivers in an infinite space with a given concentration of molecules. Second, BiNS2 is a java package designed to simulate nano-scale biological communication. One of the difference between the two simulators is that BiNS2 allows modeling a receiver node with a finite number of receptors however, N3Sim allows to implement an absorbing receiver node without receptors. Particularly, in BiNS2 when a molecules hit one of the receptors on the receiver surface, if it is not busy in another bond, the receptor absorb the molecules. However, in N3Sim when a molecule hit the surface of the receiver, the molecule will be absorbed. Indeed, the objective is to exchange information from BiNS2 to N3Sim while using the MolComML file. Hence, first we develop an intermediate parser able to translate the MolComML data into the configuration file of BiNS2. Second, we update the MolComML data of the receptors position (x, y, and z) by using BiNS2. Third, we develop an intermediate parser able to translate the updated MolComML data into the configuration file of N3Sim. Finally, we demonstrate that the same MolComML data file will generate comparable simulation results. The methodology and the comparable results are shown below where we evaluate the performance of the communication via diffusion system by using neurotransmitters as the messenger molecules with a radius equal to 0.2 nm which diffuse in the chemical synaptic cleft to exchange information between the transmitter and the receiver with 20 receptors. The synaptic cleft is the distance between the transmitter and the receiver and it is equal to 20 nm. The radius of the transmitter is 0.1 nm however, the radius of the receivers is 4 nm with twenty receptors each one with radius of 1 nm. Note that the time step is 0.1 ns.



- Details about the exchange Start date: 15/05/2017 End date: 22/05/2017 Evaluation of the CIRCLE staff exchange initiative: - Were these objectives met? x ‘Yes’ □ more than 70% of the objectives were met.



□ less than 70% of the objectives were met □ ‘No’ - Rate the general satisfaction of the staff exchange initiative x 100% □ 75% □ 50% □ 25% □ none - What were the most important benefits of the exchange? Developing an intermediate parser able to translate the MolComML specifications into the original configuration files of each simulation tool, will allow a fast integration of MolComML specification rules without any changes on the simulator source code. In addition, allowing to exchange the specific capabilities of each simulator by using the MolComML file. - Logistic aspects

There weren’t any problems with the travel and the accommodation arrangement.

- Any other comments about the exchange: No. Date: 24/05/2017

4. CIRCLE Staff Exchange Report Form for Shirin Salehi Name of the researcher taking part in the CIRCLE exchange initiative: Shirin Salehi

Affiliation (non CIRCLE partner): Isfahan University of Technology (IUT) Name of the visited institution (CIRCLE partner):



Universitat Politècnica de Catalunya (UPC) - Objectives the CIRCLE staff exchange initiative: Abstract of the activities promoted by the Staff Exchange.

1. Involvement in the area of molecular communication with applications in drug delivery including nanomachine deployment, rate control, improving the time duration between consecutive administrations, etc. The result of this work has been published in Nano Communication Network journal (Elsevier) entitled “Releasing Rate Optimization in a Single and Multiple Transmitter Local Drug Delivery System with Limited Resources”. Drug delivery is one of the most important applications of molecular communication. Drug transmitters have limited resources in terms of energy and reservoir and these limitations should be taken into consideration when designing a drug delivery system. Drug molecules may also be expensive and releasing a large amount of them can have harmful effects on the healthy parts of the body. We have considered a multiple transmitter local drug delivery system in which the nearest transmitters to a randomly located tumor are activated to release drug molecules and guarantee the Least Effective Concentration (LEC) in every part of the tumor. We proposed two different scenarios: a single transmitter drug delivery system for which the optimal rate of the transmitting nanomachine and the optimal density of deployed nanomachines are derived through formulations and simulations. Poisson distributed as well as regular square and hexagon grid deployments are investigated. We then extended it to a multiple transmitter drug delivery system for which the optimal allocated rate to each releasing transmitter is derived in order to minimize the total rate of release and maintain LEC in every part of the tumor. It is shown that activating multiple transmitters leads to a reduction in the total optimal release rate of drug molecules as well as improving the time duration between consecutive administrations. 2. Getting familiar with N3Sim, which is a well-known simulation framework for diffusion-based molecular communication developed in UPC and using MATLAB as an interface to specify the values of simulation parameters to exploit the automated simulation capability of N3Sim. We used MATLAB as well for integrating, processing and representing the results. 3. Involvement in data-driven analysis of molecular communication literature. The results of this work can provide a roadmap for future research, young researchers and also industry engagement. - Details about the exchange Start date: 23/02/2016 End date: 14/12/2016 Evaluation of the CIRCLE staff exchange initiative: - Were these objectives met? ■ ‘Yes’ □ more than 70% of the objectives were met. □ less than 70% of the objectives were met □ ‘No’



- Rate the general satisfaction of the staff exchange initiative ■ 100% □ 75% □ 50% □ 25% □ none

- What were the most important benefits of the exchange? Please outline the most important areas that could have been improved and allowed you to get more out of the exchange.

Taking part in 3rd International Conference on Nanoscale Computing and Communication presenting two short papers entitled “Optimal Deployment of Multiple Transmitter Drug Delivery System: A Spatial Sampling Theorem Approach” and “Characterizing the Physical Influence of Neighbouring Absorbing Receivers in Molecular Communication”

Taking part in 2nd Workshop on Molecular Communications

Participation in the above mentioned international societies helped me to: • Learn about emerging research, trends and techniques in this field • Network with other scientists to form connections that will enhance our research efforts • Develop skills to become more competitive in my field - Logistic aspects Were there any problems with travel and accommodation arrangements and if so what could be done to improve them in the future?

There was no problem in terms of travel and accommodation arrangement.

- Any other comments about the exchange: No. Please note that information in this form will be shared with other CIRCLE partners and be processed for producing results to be published in the CIRCLE deliverables and documents.

Date: 25/5/2017 Sign: Shirin Salehi



Source institution: UCAM

5. CIRCLE Staff Exchange Report Form for Pietro Liò

Name of the researcher taking part in the CIRCLE exchange initiative: Pietro Liò

Affiliation (CIRCLE partner): UCAM Name of the visited institution (CIRCLE partner): CNIT - Objectives the CIRCLE staff exchange initiative:

Knowledge sharing activities on molecular communication systems in blood vessels. The scope of the meetings was to understand the biological phenomena (i.e. molecular communications) related to the Circulating Tumor Cells inside blood vessels. The biological parameters involved in these phenomena have been identified and on the basis of such parameters several nanoscale communication scenarios have been proposed and analyzed. - Details about the exchange Regular short meetings has been held in Perugia at CNIT Research Unit c/o Department of Engineering, University of Perugia. Here is the details: Start date: 13/05/2016 End date: 14/05/2016 Start date: 10/06/2016 End date: 11/06/2016 Start date: 17/02/2017 End date: 18/02/2017 Start date: 20/02/2017



End date: 20/02/2017 Start date: 27/02/2017 End date: 27/02/2017 Start date: 24/03/2017 End date: 25/03/2017 Start date: 20/04/2017 End date: 21/04/2017 Start date: 23/05/2017 End date: 23/05/2017 The knowledge sharing activity pursued by the three CIRCLE partners, based on staff exchange, is focused on Molecular Communications techniques devoted to the early detection of circulating tumor cells (CTC) in blood vessels. P. Liò provided models about the generation and the survival of CTCs, as well as their concentration. This allowed CNIT personnel to integrate these models into simulations. In particular, the MolComML language has been used to specify a meaningful simulation scenario, aimed to optimize the position of a CTC sensor within blood vessels. Extensive simulations have been carried out, using realistic values for CTC densities and survival probabilities far from tumor sites. Obtained results show that CTCs tend to remain/move towards the center of the cells or close to the endothelium. Evaluation of the CIRCLE staff exchange initiative: - Were these objectives met? X ‘Yes’ □ more than 70% of the objectives were met. □ less than 70% of the objectives were met □ ‘No’ - Rate the general satisfaction of the staff exchange initiative X 100% □ 75% □ 50% □ 25% □ none - What were the most important benefits of the exchange? The exchange allowed a deep understanding of the biological phenomena related to the CTC in blood vessels and the simulation results have shown how the CTC are distributed



inside blood vessels. The collected results provide meaningful information about the propagation phenomena of such cells, giving the opportunity to develop further detection and destruction techniques of tumor cells in the body. These results will be included in a journal publication, currently in preparation. Moreover, a survey of medical applications of Molecular Communications has been published in the Elsevier Nano Communication Networks journal (see the publications section). - Logistic aspects The direct and fast route from Stansted Airport to Perugia Airport (Aeroporto Internazionale dell'Umbria) has allowed regular short meetings over the time between the staff of UCAM and CNIT. - Any other comments about the exchange: Date: 24/05/2017 Sign:

6. CIRCLE Staff Exchange Report Form for He Peng

Name of the researcher taking part in the CIRCLE exchange initiative: Peng He ………….………………..

Affiliation (non CIRCLE partner): University of Electronic Technology and Science of China …………………………… Name of the visited institution (CIRCLE partner): University of Cambridge …………………………… - Objectives the CIRCLE staff exchange initiative:



Abstract of the activities promoted by the Staff Exchange.

The general objective is to promote staff exchanges between partners to coordinate their activities. By this way, researchers are able to share their works and discuss possibility of cooperative work in the field of molecular communication. - Details about the exchange During the exchange, the research of molecular communication is proceeded in Computer Lab. One major topic is the switching application of calcium signaling in living cells. Two different cases are considered, which are noise-free and noise case. Switching behavior of both cases are discussed and presented by numerical results. Also, we are considering to use BiNS2 simulator to model the switching process, that are proposed by Luca Felicetti. In addition, machine learning technology is studied during my exchange. I am considering to use machine learning method to solve some molecular communication problems. I study some basic material of machine learning including deep learning, tensorflow, etc. I join the practice cource of tensorflow, and take part in the technical program of machine learning which is organized by Cambridge Microsoft Research. One possible problem is the stochastic switch of calcium signaling, the switching problem could be changed into a decision-make problem and the result could be optimized via training process of machine learning. Another possible problem is receiver design of molecular communication problem, in which threshold of decoding could be optimized according to variation of channel condition through training process. Start date: 15 Dec 2016 End date: 14 Dec 2017 Evaluation of the CIRCLE staff exchange initiative: - Were these objectives met?

‘Yes’ □ more than 70% of the objectives were met. □ less than 70% of the objectives were met □ ‘No’ - Rate the general satisfaction of the staff exchange initiative

100% □ 75% □ 50% □ 25% □ none



- What were the most important benefits of the exchange? Please outline the most important areas that could have been improved and allowed you to get more out of the exchange. The exchange is helpful to broad our sight and bring more idea of work. The exchange also promotes the integration of subjects in research including molecular biology, engineering of communication, computer science, etc. The exchange lays a firm foundation of cooperation in area of molecular communication. - Logistic aspects Were there any problems with travel and accommodation arrangements and if so what could be done to improve them in the future?

The accommodation arrangements are good, I have no further comments. - Any other comments about the exchange: No more comments. Expect more similar exchange in the future. Please note that information in this form will be shared with other CIRCLE partners and be processed for producing results to be published in the CIRCLE deliverables and documents.

Date: 24 May 2017 Sign:

7. CIRCLE Staff Exchange Report Form for Eugenio Del Prete

Name of the researcher taking part in the CIRCLE exchange initiative: Eugenio Del Prete

Affiliation (non CIRCLE partner): Department of Sciences, University of Basilicata (Italy) - No CIRCLE partner Name of the visited institution (CIRCLE partner): Computer Laboratory, University of Cambridge (United Kingdom) - Objectives the CIRCLE staff exchange initiative:



The meeting was held to improve the research activities in molecular communication and to strengthened the relationships among different researchers in such project. The involved entities were:

a) Pietro Liò (Computer Laboratory, Univerisity of Cambridge, UK), b) Eugenio Del Prete (Department of Sciences, University of Basilicata, Italy); c) Peng He (University of Electronic Science and Technology of China, China).

The aims of the meeting were: 1) the analysis of molecular communication among cells by means of calcium ions; 2) the feasibility study of a tool for analysing the cell behaviour in the metabolism

context, using the exsisting BiNS simulator; 3) miscellaneous.

- Details about the exchange Start date: 24/04/2017 End date: 28/04/2017 Place: Computer Laboratory, University of Cambridge In the first part of the meeting, the discussion was about the inter-cellular calcium comunication system and the model chosen by P. He in order to simulate the system. The explanation was directed to understand if it was possible to use the data inside the BiNS simulator created by L. Felicetti and his team; furthermore, physical details about the simulator were discussed, highlighting all its pros. The second part of meeting was held in order to verify the functioning of the METRADE toolbox (available for Matlab), debugging some code chunks and noting the possibility to rewrite the parts related to the parallel calculation. This control was made in order to understand if there can be a link among metabolism, inflammation and molecular communication. Moreover, it was discussed about the benefit in using R environment in place of Matlab, since biologists seem to be more comfortable with high-level programming language, and the reporting is simpler by using some typical libraries. Evaluation of the CIRCLE staff exchange initiative: - Were these objectives met? X ‘Yes’ □ more than 70% of the objectives were met. □ less than 70% of the objectives were met □ ‘No’ - Rate the general satisfaction of the staff exchange initiative X 100% □ 75% □ 50%



□ 25% □ none - What were the most important benefits of the exchange? The collaboration among different institutions and research fields are essential for the development of common strategy in molecular communication, not only in terms of knowledge, but even for practical applications. The exchange furnished some details about the state-of-art on cells communication, especially on changing the point of view about the scale level, from extra-cellular to inter/intra-cellular. Thus, physics rules could be linked to BiNS simulator (developed by the staff in which L. Felicetti is involved). At least, the possibility of interconnection with the bioinformatics was viewed, by means of tools that are already available, such as METRADE in Matlab environment, in order to build a bridge among cellular metabolism and inflammation. Future work could take this direction and, for this purpose, other meetings should be suggested. Nevertheless, it is not to underestimate the importance of visiting different research laboratories, gaining novel work approach, which takes place only from successfuldiscussions. - Logistic aspects No problem with the logistic aspects. Positive details:

the travel from the Stansted Airport in London to the Railway Station in Cambridge is simple and fast by train (around 35-40 min.);

many different kinds of accommodation are available and the travels through the city are comfortable by bus or bicycle;

Computer Laboratory rooms and furniture are very suitable for a meeting. Furthermore, a cafe and a cafeteria can be used for the meals.

- Any other comments about the exchange: The exchange was very interesting and fruitful, thanks to L. Felicetti’s explanation about his work and simulator functioning, and to P. He’s explanation about his idea and cell communication model. Information technology, programming and bioinformatics can cooperate,in order to improve the molecular communication field of research. Date: 24/05/2017 Sign:



Source institution: KU

8. CIRCLE Staff Exchange Report Form for Ozgur B. Akan

Name of the researcher taking part in the CIRCLE exchange initiative: Prof. Ozgur B. Akan

Affiliation (CIRCLE partner): KU Name of the visited institution (CIRCLE partner): UCAM - Objectives the CIRCLE staff exchange initiative:

The staff exchange has been initiated to investigate robust detection methods for molecular communications inspired from bacterial signalling in collaboration with Dr. Pietro Lio from UCAM. The researchers have analysed the performance of these detection methods for different modulation techniques and under several interference and noise conditions.

- Details about the exchange Start date: 06.02.2017 End date: 10.02.2017 Evaluation of the CIRCLE staff exchange initiative: - Were these objectives met? □ ‘Yes’ more than 70% of the objectives were met. □ less than 70% of the objectives were met □ ‘No’ - Rate the general satisfaction of the staff exchange initiative 100% □ 75% □ 50% □ 25%



□ none

- What were the most important benefits of the exchange? The exchange has fostered the strategic collaboration towards conducting detection experiments using engineered bacteria for realizing synthetic bacteria based bio-transceivers of molecular communications. - Logistic aspects There was no problem with travel and accommodation arrangements.

- Any other comments about the exchange: The travel and accommodation expenses incurred during the staff exchange have been covered by other financial sources. Date: 24.05.2017 Sign:

Prof. Ozgur B. Akan Director of Next-generation and Wireless Communications Laboratory Department of Electrical and Electronics Engineering Koç University, Istanbul, Turkey 34450 Phone: +90-212-338 1794 E-mail: [email protected] http://elec.ku.edu.tr/~akan

9. CIRCLE Staff Exchange Report Form for Ozgur B. Akan

Name of the researcher taking part in the CIRCLE exchange initiative: Prof. Ozgur B. Akan



Affiliation (CIRCLE partner): KU Name of the visited institution: Georgia Institute of Technology (GATECH) - Objectives the CIRCLE staff exchange initiative:

The staff exchange has been initiated for a series of research meetings with NSF MoNaCo Project collaborators at Georgia Institute of Technology (GATECH), Prof. Ian F. Akyildiz from BWN Lab, Prof. Craig R. Forest from Precision Biosystems Laboratory, and Prof. Faramarz Fekri from Sensing, Processing, and Communication (SPC) Research Lab at GATECH. - Details about the exchange Start date: 30.04.2017 End date: 04.05.2017 Evaluation of the CIRCLE staff exchange initiative: - Were these objectives met? ‘Yes’ □ more than 70% of the objectives were met. □ less than 70% of the objectives were met □ ‘No’ - Rate the general satisfaction of the staff exchange initiative 100% □ 75% □ 50% □ 25% □ none

- What were the most important benefits of the exchange? As part of this staff exchange initiative, Ozgur B. Akan gave a series of seminars at GATECH on the latest research activities of his group in the field of molecular communications and on the research results obtained towards the development of molecular communication simulator within the CIRCLE Project. He also held several discussion meetings with the MoNaCo Project



collaborators on potential collaboration opportunities for extending the impact of outcomes of the CIRCLE Project. - Logistic aspects There was no problem with travel and accommodation arrangements.

- Any other comments about the exchange: The travel and accommodation expenses incurred during the staff exchange have been covered by other financial sources. Date: 24.05.2017 Sign:


10. CIRCLE Staff Exchange Report Form for Ahmet Ozan Bicen

Name of the researcher taking part in the CIRCLE exchange initiative: Ahmet Ozan Bicen

Affiliation (non CIRCLE partner): Georgia Institute of Technology (GATECH) Name of the visited institution (CIRCLE partner):



KU - Objectives the CIRCLE staff exchange initiative:

The staff exchange has been initiated for information exchange and collaboration in the modeling, analysis and simulation of microfluidic molecular communication systems as part of the research efforts to implement artificial synapses. - Details about the exchange Start date: 10.03.2017 End date: 30.03.2017 Evaluation of the CIRCLE staff exchange initiative: - Were these objectives met? ‘Yes’ □ more than 70% of the objectives were met. □ less than 70% of the objectives were met □ ‘No’ - Rate the general satisfaction of the staff exchange initiative 100% □ 75% □ 50% □ 25% □ none

- What were the most important benefits of the exchange? This staff exchange has laid the groundwork for several collaborations in multiple research directions, e.g., development of simulation tools for microfluidic MC channels, fabrication of microfluidic MC systems, and implementation and tests of artificial synapses towards organ-on-a-chip devices. - Logistic aspects There was no problem with travel and accommodation arrangements.

- Any other comments about the exchange: The travel and accommodation expenses incurred during the staff exchange have been covered by other financial sources.



Date: 24.05.2017 Sign:


Source institution: IMINDS

11. CIRCLE Staff Exchange Report Form for Pieter Stroobant

Name of the researcher taking part in the CIRCLE exchange initiative:

Pieter Stroobant

Affiliation (CIRCLE partner):

IMINDS

Name of the visited institution (CIRCLE partner):

UPC/N3CAT

- Objectives the CIRCLE staff exchange initiative:

Abstract of the activities promoted by the Staff Exchange.

The exchange aims at performing research involving ideas from the fields of opportunistic & approximate routing to propose a routing algorithm that works in a range of applications



that involve very large networks with devices that are limited in their computing and communication capabilities. These applications include SDNs, nanonetworks, ... Ideas on routing protocols and application areas are exchanged and combined with the expertise of the UPC partner in the domains of nanonetworking, software defined metamaterials, … - Details about the exchange Start date: April 6, 2017 End date: May 8, 2017

Evaluation of the CIRCLE staff exchange initiative:

- Were these objectives met? X ‘Yes’ □ more than 70% of the objectives were met. □ less than 70% of the objectives were met □ ‘No’ - Rate the general satisfaction of the staff exchange initiative X 100% □ 75% □ 50% □ 25% □ none - What were the most important benefits of the exchange? The complementarity of the expertise of both groups resulted in an adequate exchange climate leading to fruitful weekly meetings and valuable insights. The algorithmic and routing knowledge of IMINDS together with the low layer expertise in nanonetworks gave rise to new ideas and concrete proposals to explore, in particular in the context of opportunistic routing with potential in vivo applications. The ability of UPC to provide a wide range of background information, based on previous research, resulted into a very rapid entry of the young PhD researcher of IMINDS to delve into routin research in the domain of molecular communications and metamaterials. The regular meetings helped in resolving a range of background questions, as well as refining the routing research questions at molcom level. - Logistic aspects Accomodation was excellent in terms of comfort, cost and travel time between the campus and the accommodation. Commuting was easy and fairly priced.



- Any other comments about the exchange: Date: May 23, 2017 Sign:

Source institution: UNIPG

12. CIRCLE Staff Exchange Report Form for Marco Malvestiti

Name of the researcher taking part in the CIRCLE exchange initiative: Marco Malvestiti

Affiliation (CIRCLE partner): UNIPG Name of the visited institution (non CIRCLE partner): Laboratory of the Neuro-oncology Research Group at the VUmc Cancer Center Amsterdam directed by Dr Thomas WurdingerVUmc Cancer Center Amsterdam - Objectives the CIRCLE staff exchange initiative: Abstract of the activities promoted by the Staff Exchange.

The staff exchange’s goals were:

Create a collaboration involving a new medical center Involving a medical center focused on cancer research Starting research joint activities

The Neuro-oncology Research Group at the VUmc Cancer Center Amsterdam and in particular his leader Thomas Wurdinger are interested in molecular communication between blood cells and cancer cells, e.g. in exchange of genetic communication via RNA between thrombocytes and glioblastoma multiforme (and other cancer types). The activities issued during the staff exchange period are:

The involvement of Thomas Wurdinger in the writing of a chapter named “Platelet-Cancer signature” in a review entitled “Platelet: Cancer and Metastasis” submitted



in scientific journal “Cancer and Metastasis Reviews” (submitted). The UNIPG group wrote a different chapter entitled “Platelet Pharmacology”. In both chapters there are an extended description of the molecular communication regarding platelets and cancer cells.

The invitation of Thomas Wurdinger to hold a seminar in Department of Medicine at University of Perugia (Italy) regarding Platelet-Cancer molecular communication (Perugia, 27 OCT 2017)

The writing of a grant for joint research focusing on the explanation of mechanism of molecular communication between platelets and glioblastoma multiforme, in particular to investigate the possibility of use that molecular communication for therapeutic purpose.

- Details about the exchange Start date: 24 Apr 2017 End date: 30 June 2017

Evaluation of the CIRCLE staff exchange initiative: - Were these objectives met? ‘Yes’ □ more than 70% of the objectives were met. □ less than 70% of the objectives were met □ ‘No’ - Rate the general satisfaction of the staff exchange initiative 100% □ 75% □ 50% □ 25% □ none - What were the most important benefits of the exchange? Expand network of European group working on molecular communication. Mostly this staff exchange is useful to involve new bio-medicine research group joining CIRCLE due to a lack a research group with bio-medical background. Furthermore the involved group is focused on research in cancer area where the CIRCLE partner are missing. - Logistic aspects

- Any other comments about the exchange:



Please note that information in this form will be shared with other CIRCLE partners and be processed for producing results to be published in the CIRCLE deliverables and documents.

Date: 29 May 2017

Sign:

Source institution: TUT

13. CIRCLE Staff Exchange Report Form for Stefanus Arinno Wirdatmadja

Name of the researcher taking part in the CIRCLE exchange initiative: Stefanus Arinno Wirdatmadja

Affiliation (CIRCLE partner): Tampere University of Technology (TUT) Name of the visited institution (CIRCLE partner): Waterford Institute of Technology (WIT) - Objectives the CIRCLE staff exchange initiative:

The collaboration with Dr. Michael Barros on brain neural circuit topic. The activities include brainstorming of the measurement metrics for the brain machine interface, discussion on possible improvement of energy efficiency for the micro size brain interface device, and charging protocols that can be implemented to support the energy efficiency. These activities will lead to the collaboration in publishing one paper related to the brain machine interface topic.Moreover, the presentation of the research will be held to promote the topic, particularly for WIT researchers and students. - Details about the exchange Start date: May 15, 2017 End date: May 31, 2017



Evaluation of the CIRCLE staff exchange initiative: - Were these objectives met? ‘Yes’ □ more than 70% of the objectives were met. □ less than 70% of the objectives were met □ ‘No’ - Rate the general satisfaction of the staff exchange initiative 100% □ 75% □ 50% □ 25% □ none - What were the most important benefits of the exchange? This exchange activity broadening my knowledge on my topic on interest (brain machine interface). The collaboration does not only cover the major aspects of the research topic, but also the fundamental theoretical approach. In this way, the generated paper on this topic is enriched with deeper analysis and approach than the previous one. The close collaboration definitely brings more productive and effective results on my research. - Logistic aspects

Before arriving here, housing arrangement has been done by the help of Dr. Michael Barros and the invitation letter was sent by Dr. Sasitharan Balasubramaniam. Arriving in Waterford, Dr. Michael Barros gave thorough explanation about transportation and the city. I live in WIT student accommodation. Overall, there is no problem in logistic aspects.

- Any other comments about the exchange: This exchange activity brings positive vibes on my research. The collaborator is supportive and cooperative. In my opinion, that is one of the most important aspect in the exchange. Similar research interest in brain neural circuit makes the collaboration and discussion more constructive. In the future, it might be good to have collaboration with the neuroscience researchers. Please note that information in this form will be shared with other CIRCLE partners and be processed for producing results to be published in the CIRCLE deliverables and documents.



Date: May 24, 2017 Sign: Stefanus Arinno Wirdatmadja

Source institution: CNIT

14. CIRCLE Staff Exchange Report Form for Luca Felicetti

Name of the researcher taking part in the CIRCLE exchange initiative: …Luca Felicetti…………..

Affiliation (CIRCLE partner): …CNIT…………………… Name of the visited institution (CIRCLE partner): …University of Cambridge, UK (UCAM) - Objectives the CIRCLE staff exchange initiative:

The planned meeting aims to coordinate the research activities in the molecular communication field involving the experts:

prof. Pietro Liò (University of Cambridge, UK) Peng He (Phd student of University of Electronic Science and Technology of China) Eugenio del Prete (University of Basilicata, IT)

Both Peng He and Eugenio del Prete are PhD visiting students at the University of Cambridge, UK. The main scopes of these meetings are:



The analysis of calcium based molecular communication techniques applied to switching devices.

Configuration of the analytic tool for the analysis of cell metabolism in order to implement inner cell behavior in the BiNS2 simulation framework

- Details about the exchange Start date: 24/04/2017 End date: 28/04/2017 During the staff exchange period has been discussed about the intercellular calcium communication system and the model chosen by Peng He in order to simulate this system. It has been also analyzed the feasibility of an integration of the stochastic switching by means calcium ions in the BiNS2 simulator, in order to analyze more complex scenarios and to develop more sophisticated communication techniques. The second part of the period was spent to verify the functioning of the METRADE toolbox (available for Matlab). This toolbox had required the debugging of some code chunks and it has been considered the possibility to rewrite the parts related to the parallel calculation. This analysis has been made in order to understand if there can be a link among metabolism, inflammation and molecular communication. The final scope is the integration of the metabolism model into the BiNS2 simulator, in order to describe in details the inner state and the specific behavior of the biological elements that may interact with the nanomachines and the other elements of the simulation scenario. Evaluation of the CIRCLE staff exchange initiative: - Were these objectives met? □ ‘Yes’ □ more than 70% of the objectives were met. □ less than 70% of the objectives were met □ ‘No’ - Rate the general satisfaction of the staff exchange initiative □ 100% □ 75% □ 50% □ 25% □ none - What were the most important benefits of the exchange? (Please outline the most important areas that could have been improved and allowed you to get more out of the exchange.)



The staff exchange has given the opportunity to share knowledge between CIRCLE's personnel and to realize a fruitful collaboration for the extension of the features of the BiNS2 simulation framework. More in details, these meetings have allowed us to evaluate opportunities and challenges to analyze the environment inside the cells, moving the focus on smaller scales. The main improvements for the BiNS2 simulator are the extension of the available simulation scenarios, by means the implementation of the intercellular calcium communication system for the simulation of the stochastic switching. This scenario involves the inner volume of each cell involved in the propagation of calcium waves. This is a new communication scenario that has never been simulated by the BiNS2 simulator (the previous communication scenarios analyzed the extracellular environment only). The second main improvement is the implementation of the cell behavior by means of the cellular metabolism algorithms. This second scope requires an ongoing collaboration by means of the analysis and configuration of the METRADE toolbox until the setup of this tool could be considered done. This collaboration with the bioinformatics staff will improve the simulation capabilities, by a biological point of view, of the BiNS2 simulator in order to reproduce with an higher degree of details the complex biological communication scenarios considering the cell reaction to specific stimulus. - Logistic aspects (Were there any problems with travel and accommodation arrangements and if so what could be done to improve them in the future?)

Nothing to report. - Any other comments about the exchange: Please note that information in this form will be shared with other CIRCLE partners and be processed for producing results to be published in the CIRCLE deliverables and documents.

Date: 23/5/2017 Sign:

15. CIRCLE Staff Exchange Report Form for Luca Felicetti

Name of the researcher taking part in the CIRCLE exchange initiative:



…Luca Felicetti…………..

Affiliation (CIRCLE partner): …CNIT…………………… Name of the visited institution (CIRCLE partner): …Waterford Institute of Technology………………………… - Objectives the CIRCLE staff exchange initiative:

The planned meetings have allowed to review, finalize and plan future extensions of the MolCom Markup Language. Other participants to the meetings:

Alan Davy (TSSG, IE) Michael Taynnan Barros (TSSG, IE) Goksel Misirli (Newcastle University, UK. Keele University, UK)

- Details about the exchange Start date: 09/05/2017 End date: 12/05/2017 During the meetings have been reviewed the current version of the MolComML. The structure of the markup language has been finalized and the main building block has been defined in details. The current version is suitable to describe a lot of molecular communication scenarios, both on simulators and on laboratory experiments. Some work has been done also to debug some code chunks. These meetings have produced the final version (v.2.0) of the MolComML that has been used to describe two simulation scenarios, identified during the meeting:

1. a diffusion based communication system, composed by a single transmitter and a single receiver

2. a diffusion with drift communication system, focused inside a short section of a blood vessel, composed by a single transmitter and multiple receivers

Evaluation of the CIRCLE staff exchange initiative: - Were these objectives met? □ ‘Yes’ □ more than 70% of the objectives were met.



□ less than 70% of the objectives were met □ ‘No’ - Rate the general satisfaction of the staff exchange initiative □ 100% □ 75% □ 50% □ 25% □ none - What were the most important benefits of the exchange? (Please outline the most important areas that could have been improved and allowed you to get more out of the exchange.) The meetings have given the opportunity to finalize the MolComML and to take benefits from the expertise of each participants in order to plan future extensions of the MolComML. The communication scenarios identified here have been described by the MolComML files in order to set up relevant simulations on both BiNS2 and N3SIM simulation frameworks. It has also been defined a brief roadmap for the future extension of the MolComML, composed by the following points:

definition of an ontology in order to standardize the meaning of each MolComML elements, defining in details: name, description and relationships to other terms.

creation of a reference website for MolComML creation of API library for MolComML create a community email list Planning regular meetings

- Logistic aspects (Were there any problems with travel and accommodation arrangements and if so what could be done to improve them in the future?)

For logistical reasons, the meetings have been relocated and held in Dublin, because each participant has attended to the 2nd Workshop on Molecular Communications that was held in Dublin on the same days. - Any other comments about the exchange: Please note that information in this form will be shared with other CIRCLE partners and be processed for producing results to be published in the CIRCLE deliverables and documents.

Date: 23/5/2017 Sign:



List of acronyms and abbreviations

API Application Program Interface

CTC Circulating Tumor Cell

IEEE Institute of Electrical and Electronic Engineers

MolCom Molecular Communications

MolComML MolCom Markup Language

SBML Systems Biology Markup Language

SBOL Synthetic Biology Open Language

TCSIM Technical Commettee on Simulation

Circle Participants

WIT Waterford Institute of Technology

UNIPG Università degli Studi di Perugia

UPC Universitat Politècnica de Catalunya

UMC University Medical Center

KU Koc University

TUT Tampere University of Technology

UCAM The Chancellor, Masters and Scholars of the University of Cambridge

iMINDS iMINDS

CNIT Consorzio Nazionale Interuniversitario per le Telecomunicazioni

Appendix 2: MolComML for puctiform simulation

<?xml version="1.0" encoding="UTF-8"?>

<molcomml version="1.2.1">

<model name="Free Diffusion" description="Punctiform Emission of a single

burst of molecules">

<listOfConfigurationParameter>

<param id="CP01" type="value" name="timestep" value="50" unit="us"

refUnit="U04" description="discrete timestep" />

<param id="CP02" type="value" name="k_B" value="1.3806488E-23" unit="J/K"

refUnit="UD02" description="Boltzmann constant" />

<param id="CP03" type="value" name="T" value="310" unit="K" refUnit="U10"

description="temperature of the simulated environment" />

<param id="CP04" type="value" name="eta" value="0.0011" unit="kg/ms"

refUnit="UD01" description="viscosity of the simulated environment" />

<param id="CP05" type="value" name="ed" value="0.9" unit="" refUnit=""

description="restitution coefficient" />

</listOfConfigurationParameter>

<listOfUnit>

<unit id="U01" name="m" scale="0" />

<unit id="U02" name="g" scale="0" />

<unit id="U03" name="s" scale="0" />

<unit id="U04" name="um" scale="-6" />

<unit id="U05" name="nm" scale="-9" />

<unit id="U06" name="ng" scale="-9" />

<unit id="U07" name="pg" scale="-12" />

<unit id="U08" name="zg" scale="-21" />

<unit id="U09" name="kg" scale="3" />

<unit id="U10" name="K" scale="0" />

<unit id="U11" name="J" scale="0" />

<unit id="U12" name="mmHg" scale="0" />

<unit id="U13" name="int" scale="0" />

<unit id="U14" name="ns" scale="-9" />

<unit id="U15" name="cell" scale="0" />

<unit id="U16" name="mm" scale="-3" />

<unit id="U17" name="rad" scale="0" />

</listOfUnit>

<listOfUnitDefinition>



<unitDefinition id="UD01" name="kg/ms"> 

<subUnit refUnit="U02" name="g" value="1" scale="3" exponent="1" />

<subUnit refUnit="U01" name="m" value="1" scale="0" exponent="-1" />

<subUnit refUnit="U03" name="s" value="1" scale="0" exponent="-1" />

</unitDefinition>

<unitDefinition id="UD02" name="J/K"> 

<subUnit refUnit="U11" name="J" value="1" scale="0" exponent="1" />

<subUnit refUnit="U10" name="K" value="1" scale="0" exponent="-1" />

</unitDefinition>

<unitDefinition id="UD03" name="hour">

<subUnit refUnit="U03" name="s" value="3.6" scale="3" exponent="1"/>

</unitDefinition>

<unitDefinition id="UD04" name="cell/mm3">

<subUnit refUnit="U15" name="cell" value="1" scale="0" exponent="1"/>

<subUnit refUnit="U16" name="mm" value="1" scale="-3" exponent="-1"/>

</unitDefinition>

<unitDefinition id="UD05" name="m/s">

<subUnit refUnit="U03" name="s" value="1" scale="0" exponent="-1"/>

<subUnit refUnit="U01" name="m" value="1" scale="0" exponent="1"/>

</unitDefinition>

</listOfUnitDefinition>

<listOfNetworkElement>



<networkElement id="NE01" name="TX_node" type="transmitter">

<shape id="SH001" type="sphere" /> 

<motion refID="" name="none" />

<child id="NE01-1" childOf="NE01" name="TX_Punctiform" >

<size refShape="SH001" name="radius" refUnit="U05" unit="nm" value="50"

/>

<mass value="0.6" refUnit="U05" unit="ng" />

<timeToLive value="10" refUnit="UD03" unit="hour" />

<interface refID="CI01-01" type="TX_FullSurface" value="1" />

</child>

</networkElement>

<networkElement id="NE02" name="RX_Node" type="receiver">

<shape id="SH001" type="sphere" />


<child id="NE02-1" childOf="NE02" name="RX" >

<size refShape="SH001" name="radius" refUnit="U05" unit="nm"

value="5000" />

<mass value="0.6" refUnit="U05" unit="ng" />


<interface refID="CI01-02" type="RX_FullSurface" value="1" />

</child>

</networkElement>

<networkElement id="NE03" name="generic carrier" type="signal">


<motion refID="" type="none" />

<child id="NE03-1" childOf="NE03" name="carrier" >


value="1.75" />

<mass value="9.8E-10" refUnit="U08" unit="pg" />


</child>

</networkElement>

</listOfNetworkElement>

<listOfCommunicationInterface>

<CommunicationInterface id="CI01" name="Absorbing surface" type="virtual">

<child id="CI01-01" childOf="CI01" name="TX_FullSurface" >

<outbound enabled="yes">

<signal refID="NE03-1" type="generic carrier" time="0" unit="us"

refUnit="U04" affinity="0" internalizeSignal="no"/>

</outbound>

<inbound enabled="no">

</inbound>

<child id="CI01-02" childOf="CI01" name="RX_FullSurface" >

<inbound enabled="yes" >

<signal refID="NE03-1" type="generic carrier" time="0" unit="s"

refUnit="U03" affinity="1" internalizeSignal="yes" /> 

</inbound>

<outbound enabled="no">

</outbound>

</child>

</CommunicationInterface>

</listOfCommunicationInterface>

<listOfExternalML>

</listOfExternalML>

<listOfProtocolStack>

<protocolStack id="PS01" name="Emission of a Single Burst of carriers"

type="SingleBurst" maxLevel="2">

<layer level="1" name="Physical">

<rule id="PR1-01" type="on_off_keying_modulation" >

<mathRule id="MR020" name="impulse" path="./mathEquations/impulse2.xml" >

<param type="value" direction="out" name="A" description="released

carrier" value="" unit="" refUnit="" />

<param type="ref" direction="in" name="burst1" description="burst of

carrier for symbol 1" value="MOL001.name[burst].value"

unit="MOL001.name[burst].unit" refUnit="MOL001.name[burst].refUnit" />

<param type="ref" direction="in" name="d1" description="duration of

symbol 1" value="MOL001.name[duration].value" unit="MOL001.name[duration].unit"

refUnit="MOL001.name[duration].refUnit" />

<param type="ref" direction="in" name="burst2" description="burst of

carrier for symbol 2" value="MOL002.name[burst].value"

unit="MOL002.name[burst].unit" refUnit="MOL002.name[burst].refUnit" />

<param type="ref" direction="in" name="d2" description="duration of

symbol 2" value="MOL002.name[duration].value" unit="MOL002.name[duration].unit"

refUnit="MOL002.name[duration].refUnit" />

</mathRule>



<param type="array" direction="in" name="Vi" description="velocity vector

before collision" value="" unit="" refUnit="" />

</mathRule>

<element type="NetworkElement" refID="NE01" name="transmitter" role="target"

/>

<element type="NetworkElement" refID="NE02" name="passive" role="player"

targetID="NE01" />

<element type="NetworkElement" refID="NE03" name="signal" role="player"

targetID="NE01" />

</specificRule>

</listOfInteractionRule>

<listOfChannel>

<channel id="CH001" name="free diffusion" type="Diffusion">

<mathRule id="MR010" name="brownian_diffusion"

path="./mathEquations/brownian.xml" >

<param type="value" direction="out" name="sigma" description="standard

deviation" value="" unit="nm" refUnit="U05" />

<param type="ref" direction="in" name="k" description="Boltzmann constant"

value="CP02.value" unit="CP02.unit" refUnit="CP02.refUnit" />

<param type="ref" direction="in" name="T" description="temperature of the

simulated environment" value="CP03.value" unit="CP03.unit"

refUnit="CP03.refUnit" />

<param type="ref" direction="in" name="r" description="element radius"

value="{NE02, NE03}.size.name[radius].value" unit="{NE02,


/>

<param type="ref" direction="in" name="eta" description="viscosity"


<param type="ref" direction="in" name="t" description="dicrete timestep"


<param type="value" direction="in" name="pi" description="Pi Greek"

value="3.141592653589793" unit="" refUnit="" />

</mathRule>

</channel>

</listOfChannel>

<MotionRule>

</MotionRule>

<networkTopology>

<disposedCompartment id="DC001" refID="C001" name="unbounded domain"

rule="single">

<position refShape="SH002" name="coords" value="array(x=0; y=0; z=0)"

unit="" refUnit=""/>

<disposedElement id="DE001" refID="NE01-1" name="transmitter" rule="single"

>


unit="um" refUnit="U04" />

<initialization refID="IS01" />



</disposedElement>

<disposedElement id="DE002" refID="NE02-1" name="receiver" rule="single">




</disposedElement>

</disposedCompartment>

</networkTopology>

<listOfState>

<state id="IS01" name="transmission" nextState="IS03">

<action name="releaseCarrier" time="0" unit="us" refUnit="U04"

stateChange="yes"/>

<protocol refID="PS01" name="Single_Burst" />

</state>

<state id="IS02" name="reception" nextState="IS02">

<action name="receiveCarrier" time="5" unit="s" refUnit="U03"

stateChange="no"/>

</state>

<state id="IS03" name="idle" nextState="IS01">

<action name="idle" time="1" unit="s" refUnit="U03" stateChange="yes"/>

</state>

</listOfState>

<listOfOutput>

<outputFormat id="output001" type="TXT">

<path name="filename" url="./outputData/Assimilations.txt" />

<row id="row001" name="">

<column id="col001" name="time"/>

<column id="col002" name="element"/>

<column id="col003" name="assimilation"/>

</row>

<outputRule id="out001" refOutput="output001" event="E002" >

<listOfOutputObjects>

<outputObj element="receiverNode" type="NetworkElement" refID="NE02"

colID="col002" >

<outputParam type="ref" name="t" description="current time"

outputType="long" value="#" unit="s" refUnit="U03" colID="col001" />

<outputParam type="ref" name="assimilation" description="total

assimilations" outputType="long" value="#" unit="" refUnit="" colID="col003"/>

</outputObj>

</listOfOutputObjects>

</outputRule>

</outputFormat>

<path name="filename" url="./outputData/transmission.txt" />




<column id="col0012" name="event"/>

<column id="col0013" name="value"/>

</row>

<outputRule id="out002" refOutput="output002" event="E003">


<outputObj element="transmitterNode" type="NetworkElement" refID="NE01"

colID="col0011">


outputType="long" value="#" unit="s" refUnit="U03" colID="col010" />

<outputParam type="string" name="eventName" description="transmission

event" outputType="string" value="transmission" unit="" refUnit=""

colID="col0012"/>

<outputParam type="ref" name="releasedCarrier" description="released

carriers" outputType="long" value="#" unit="" refUnit="" colID="col0013" />

</outputObj>


</outputRule>

</outputFormat>

</listOfOutput>

<listOfEvent>

<observedAttribute>



<attribute name="t" description="current time" unit="s" refUnit="U03" />

<attribute name="t_tx" description="emission event" unit="s" refUnit="U03"

/>

</observedAttribute>

<event id="E001" name="shutdown" description="stop simulation">

<condition if="t>300">

<![CDATA[ event handling if condition is true

shutdown();

]]>

<else>

<![CDATA[ event handling if condition is false

nextSimulationStep();

]]>

</else>

</condition>

</event>

Appendix 3: MolComML for blood simulation

<?xml version="1.0" encoding="UTF-8"?>

<molcomml version="1.2.1">

<model name="CTC Detection in Blood Vessels" description="free text">

<listOfConfigurationParameter>

<param id="CP01" type="value" name="timestep" value="100" unit="us"

refUnit="U04" description="discrete timestep" />

<param id="CP02" type="value" name="k_B" value="1.3806488E-23" unit="J/K"

refUnit="UD02" description="Boltzmann constant" />

<param id="CP03" type="value" name="T" value="310" unit="K" refUnit="U10"

description="temperature of the simulated environment" />

<param id="CP04" type="value" name="eta" value="0.0013" unit="kg/ms"

refUnit="UD01" description="viscosity of the simulated environment" />

<param id="CP05" type="value" name="ed" value="0.9" unit="" refUnit=""

description="restitution coefficient" />

</listOfConfigurationParameter>

<listOfUnit>

<unit id="U01" name="m" scale="0" />

<unit id="U02" name="g" scale="0" />

<unit id="U03" name="s" scale="0" />

<unit id="U04" name="um" scale="-6" />

<unit id="U05" name="nm" scale="-9" />

<unit id="U06" name="ng" scale="-9" />

<unit id="U07" name="pg" scale="-12" />

<unit id="U08" name="zg" scale="-21" />

<unit id="U09" name="kg" scale="3" />

<unit id="U10" name="K" scale="0" />

<unit id="U11" name="J" scale="0" />

<unit id="U12" name="mmHg" scale="0" />

<unit id="U13" name="int" scale="0" />

<unit id="U14" name="ns" scale="-9" />

<unit id="U15" name="cell" scale="0" />

<unit id="U16" name="mm" scale="-3" />

<unit id="U17" name="rad" scale="0" />

</listOfUnit>

<listOfUnitDefinition>



<unitDefinition id="UD01" name="kg/ms"> 

<subUnit refUnit="U02" name="g" value="1" scale="3" exponent="1" />

<subUnit refUnit="U01" name="m" value="1" scale="0" exponent="-1" />

<subUnit refUnit="U03" name="s" value="1" scale="0" exponent="-1" />

</unitDefinition>

<unitDefinition id="UD02" name="J/K"> 

<subUnit refUnit="U11" name="J" value="1" scale="0" exponent="1" />

<subUnit refUnit="U10" name="K" value="1" scale="0" exponent="-1" />

</unitDefinition>

<unitDefinition id="UD03" name="hour">

<subUnit refUnit="U03" name="s" value="3.6" scale="3" exponent="1"/>

</unitDefinition>

<unitDefinition id="UD04" name="cell/mm3">

<subUnit refUnit="U15" name="cell" value="1" scale="0" exponent="1"/>

<subUnit refUnit="U16" name="mm" value="1" scale="-3" exponent="-1"/>

</unitDefinition>

<unitDefinition id="UD05" name="m/s">

<subUnit refUnit="U03" name="s" value="1" scale="0" exponent="-1"/>

<subUnit refUnit="U01" name="m" value="1" scale="0" exponent="1"/>

</unitDefinition>

</listOfUnitDefinition>

<listOfNetworkElement>



<networkElement id="NE01" name="generic_node" type="passive">

<shape id="SH001" type="sphere" /> 


<child id="NE01-1" childOf="NE01" name="PLA" >


value="1000" />

<mass value="4.7" refUnit="U07" unit="pg" />


<interface/>

</child>

<child id="NE01-2" childOf="NE01" name="WBC" >


value="3800" />



<interface/>

</child>

<child id="NE01-3" childOf="NE01" name="RBC" >


value="2900" />



<interface/>

</child>

</networkElement>

<networkElement id="NE02" name="RX_node" type="receiver">



<child id="NE02-1" childOf="NE02" name="CTC_Counter" >


value="5000" />

<mass value="0" refUnit="U07" unit="pg" />




<interface refID="CI01-01" type="CTC_RX_Virtual" value="1" />

</child>

</networkElement>

<networkElement id="NE03" name="generic_signal" type="signal">


<motion refID="" type="none" />

<child id="NE03-1" childOf="NE03" name="CTC" >


value="5000" />

<mass value="112" refUnit="U08" unit="pg" />


</child>

</networkElement>

</listOfNetworkElement>

<listOfCommunicationInterface>

<CommunicationInterface id="CI01" name="Absorbing surface" type="virtual">

<child id="CI01-01" childOf="CI01" name="CTC_RX_Virtual" >

<inbound enabled="yes">

<signal refID="NE03-1" type="CTC_cell_signal" time="0" unit="s"

refUnit="U03" affinity="1" internalizeSignal="no"/>

</inbound>

<outbound enabled="no">

</outbound>

</child>

</CommunicationInterface>

</listOfCommunicationInterface>

<listOfExternalML>

</listOfExternalML>

<listOfProtocolStack>

</listOfProtocolStack>

<listOfCompartment>

<Compartment id="C003" name="tube" >

<shape id="SH003" type="cylinder" >

<size name="length" value="3000" unit="um" refUnit="U04" />

<size name="radius" value="30" unit="um" refUnit="U04" />

</shape>

<channel name="diffusion_drift" refID="CH002" />

<gate name="gate1" refID="G001"/>

</Compartment>

</listOfCompartment>

<listOfGate>

<gate id="G001" name="gate1">

<shape id="SH004" type="circle" />

<size refShape="SH004" name="radius" value="30" unit="um" refUnit="U04"

/>


unit="um" refUnit="U04"/>

<orientation refShape="SH004" name="normal" value="array(vx=0; vy=1; vz=0)"

/>

<compartment1 name="tube" refID="C003-1"/>

<compartment2 name="root" refID=""/>

</gate>

</listOfGate>

<listOfInteractionRule>

<globalRule id="IR001" name="generalCollisionRule" type="global">


path="./mathEquations/resolveCollision.xml" > 

<param type="value" direction="in" name="ed" description="restitution

coefficient" value="CP05.value" unit="CP05.unit" refUnit="CP05.refUnit" /> 

<param type="array" direction="out" name="ca" description="center of the

evaluated element" value="" unit="" refUnit="" />

<param type="array" direction="out" name="Va" description="velocity vector

of the evaluated element" value="" unit="" refUnit="" />

<param type="array" direction="internal" name="Vap" description="parallel


refUnit="" />

<param type="array" direction="internal" name="Van" description="normal


refUnit="" />

<param type="array" direction="internal" name="Vbp" description="parallel


refUnit="" />

<param type="array" direction="internal" name="Vbn" description="normal


refUnit="" />

<param type="value" direction="in" name="ma" description="mass of the

evaluated element" value="{NE01, NE03}.mass.value" unit="{NE01, NE03}.mass.unit"

refUnit="{NE01, NE03}.mass.refUnit" />

<param type="value" direction="in" name="mb" description="mass of the

collinding element" value="{NE01, NE03}.mass.value" unit="{NE01,

NE03}.mass.unit" refUnit="{NE01, NE03}.mass.refUnit" />

<param type="value" direction="in" name="ra" description="radius of the

evaluated element" value="{NE01, NE03}.size.name[radius].value" unit="{NE01,


/>

<param type="value" direction="in" name="rb" description="radius of the

collinding element" value="{NE01, NE03}.size.name[radius].value" unit="{NE01,


/>

<param type="value" direction="internal" name="d" description="distance

between the two elements" value="" unit="nm" refUnit="U05" />

<param type="value" direction="internal" name="dt" description="overlapping

time" value="" unit="ns" refUnit="U14" />

</mathRule>

<element type="NetworkElement" refID="*" name="" role="both" targetID="*"

/>

</globalRule>

<specificRule id="IR002" name="collisionRuleBox" type="collision">


path="./mathEquations/resolveCollisionCylinder.xml" >

<param type="array" direction="out" name="Vnf" description="velocity

vector after collision" value="" unit="" refUnit="" />

<param type="array" direction="internal" name="d" description="velocity

component over longitudinal axis" value="" unit="" refUnit="" />

<param type="array" direction="internal" name="n" description="velocity

component over the axis joint to the center of the node" value="" unit=""

refUnit="" />

<param type="array" direction="internal" name="o" description="velocity

component over the axis normal to n" value="" unit="" refUnit="" />

<param type="ref" direction="in" name="r" description="Colliding

NetworkElement radius" value="{NE01, NE03}.size.name[radius].value" unit="{NE01,


/>

<param type="value" direction="in" name="ed" value="0.6" unit="" refUnit=""

/> 

<param type="value" direction="internal" name="dn" description="projection

of the velocity vector on the axis n" value="" unit="" refUnit="" />

<param type="value" direction="internal" name="dp" description="projection

of the velocity vector on the longitudinal axis d" value="" unit="" refUnit=""

/>

<param type="ref" direction="in" name="l" description="Cylinder Length"

value="C003.size.name[length].value" unit="C003.size.name[length].unit"

refUnit="C003.size.name[length].refUnit" />

<param type="ref" direction="in" name="R" description="Cylinder radius"

value="C003.size.name[radius].value" unit="C003.size.name[radius].unit"

refUnit="C003.size.name[radius].refUnit" />

</mathRule>

<element type="Compartment" refID="C003" name="tube" role="target" />


targetID="C003" />

targetID="C003" />

</specificRule>

<specificRule id="IR003" name="transparentCollision" type="collision">

<mathRule id="MR004" name="transparentCollision"

path="./mathEquations/transparent.xml" >

<param type="array" direction="out" name="Vf" description="velocity vector

after collision" value="" unit="" refUnit="" />

<param type="array" direction="in" name="Vi" description="velocity vector

before collision" value="" unit="" refUnit="" />

</mathRule>

<element type="NetworkElement" refID="NE02" name="receiver" role="target" />


targetID="NE02" />


targetID="NE02" />

</specificRule>

<specificRule id="IR004" name="removeElement" type="collision"

description="remove colliding element from the simulation environment">

<mathRule />

<element type="Compartment" refID="C003" name="tube" role="target"> 

<subElement type="Gate" refID="G001" name="bottomSide" />

</element>


targetID="C003.G001" />


targetID="C003.G001" />

</specificRule>

</listOfInteractionRule>

<listOfChannel>

<channel id="CH002" name="diffusion_drift" type="DiffusionDrift">

<mathRule id="MR010" name="velocity of the flow"

path="./mathEquations/flow_velocity.xml" >

<param type="value" direction="out" name="v" description="velocity of the

blood flow as a function of the " value="" unit="" refUnit="" />

<param type="value" direction="in" name="vm" description="mean velocity of

the blood flow" value="0.005" unit="m/s" refUnit="UD05" />

<param type="ref" direction="in" name="R" description="Cylinder radius"



<param type="internal" direction="in" name="r" description="distance from

the longitudinal axis" value="" unit="" refUnit="" />

<param type="ref" direction="in" name="l" description="Cylinder Length"

value="C003.size.name[length].value" unit="C003.size.name[length].unit"

refUnit="C003.size.name[length].refUnit" />



<param type="ref" direction="in" name="eta" description="blood viscosity"


</mathRule>

<mathRule id="MR011" name="brownian_diffusion"

path="./mathEquations/brownian.xml" >

<param type="value" direction="out" name="sigma" description="standard

deviation" value="" unit="nm" refUnit="U05" />

<param type="ref" direction="in" name="k" description="Boltzmann constant"


<param type="ref" direction="in" name="T" description="temperature of the

simulated environment" value="CP03.value" unit="CP03.unit"

refUnit="CP03.refUnit" />

<param type="ref" direction="in" name="r" description="element radius"

value="{NE01, NE03}.size.name[radius].value" unit="{NE01,


/>

<param type="ref" direction="in" name="eta" description="viscosity"


<param type="ref" direction="in" name="t" description="dicrete timestep"


<param type="value" direction="in" name="pi" description="Pi Greek"

value="3.141592653589793" unit="" refUnit="" />

</mathRule>

</channel>

</listOfChannel>

<MotionRule>

</MotionRule>

<networkTopology>

<disposedCompartment id="DC001" refID="C003" name="tube" rule="single">


unit="um" refUnit="U04"/>

<orientation refShape="SH001" name="length" value="array(vx=0; vy=1; vz=0)"

/>

<disposedElement id="DE001" refID="NE01-1" name="PLA" rule="multiple" >

<position refShape="SH001" name="concentration" >

<mathRule id="MR020" name="ro" path="./mathEquations/ro.xml" >

<param type="ref" direction="in" name="r" description="WBC radius"

value="NE01-1.size.name[radius].value" unit="NE01-1.size.name[radius].unit"

refUnit="NE01-1.size.name[radius].refUnit" />

<param type="ref" direction="in" name="R" description="Vessel radius"



<param type="value" direction="out" name="ro" description="ro" value=""

unit="nm" refUnit="U05" />

<param type="internal" direction="in" name="rand" description="random

number [0; 1]" value="" unit="" refUnit="" />



</mathRule>

<mathRule id="MR021" name="theta_angle" path="./mathEquations/theta.xml"

>

<param type="value" direction="out" name="theta" description="theta

angle" value="" unit="rad" refUnit="U17" />



</mathRule>

<mathRule id="MR022" name="coord_x" path="./mathEquations/uniform_x.xml"

>

<param type="value" direction="out" name="x" description="x coordinate"

value="" unit="nm" refUnit="U05" />

<param type="ref" direction="in" name="theta" description="theta angle"

value="MR021.name[theta].value" unit="MR021.name[theta].unit"

refUnit="MR021.name[theta].refUnit" />

<param type="ref" direction="in" name="ro" description="ro"

value="MR020.name[ro].value" unit="MR020.name[ro].unit"

refUnit="MR020.name[ro].refUnit" />

</mathRule>

<mathRule id="MR023" name="coord_z" path="./mathEquations/uniform_z.xml"

>

<param type="value" direction="out" name="z" description="z coordinate"








</mathRule>

<mathRule id="MR024" name="coord_y" path="./mathEquations/uniform_y.xml"

>

<param type="value" direction="out" name="y" description="y

coordinate" value="" unit="nm" refUnit="U05" />

<param type="value" direction="in" name="depth"

description="longitudinal length for initialization" value="88.5" unit="um"

refUnit="U04" />



</mathRule>

<mathRule id="MR025" name="PLA_count"

path="./mathEquations/getCreationElementsCount.xml" >

<param type="value" direction="out" name="N" description="Platelet

count" value="" unit="" refUnit="" />

<param type="value" direction="in" name="C" description="Platelet

concentration" value="250000" unit="cell/mm3" refUnit="UD04" />

<param type="value" direction="in" name="depth"

description="longitudinal length of vessel section" value="88.5" unit="um"

refUnit="U04" />

<param type="ref" direction="in" name="R" description="Vessel

radius" value="C003.size.name[radius].value" unit="C003.size.name[radius].unit"




</mathRule>

</position>


</disposedElement>

<disposedElement id="DE002" refID="NE01-2" name="WBC" rule="multiple">


<mathRule id="MR030" name="ro" path="./mathEquations/ro.xml" >

<param type="ref" direction="in" name="r" description="WBC radius"






<param type="value" direction="out" name="ro" description="ro" value=""

unit="nm" refUnit="U05" />



</mathRule>


>





</mathRule>


>









</mathRule>


>









</mathRule>


>

<param type="value" direction="out" name="y" description="y coordinate"










</mathRule>


>









</mathRule>


>

<param type="value" direction="out" name="y" description="y coordinate"



length of vessel section" value="88.5" unit="um" refUnit="U04" />



</mathRule>

<mathRule id="MR045" name="RBC_count"


<param type="value" direction="out" name="N" description="RBC count"

value="" unit="" refUnit="" />

<param type="value" direction="in" name="C" description="RBC



length of vessel section" value="88.5" unit="um" refUnit="U04" />




</mathRule>

</position>


</disposedElement>

<disposedElement id="DE004" refID="NE03-1" name="CTC" rule="single">

<position refShape="SH001" name="center" >

<param type="array" name="coords" value="array(x=0; y=-1400; z=0)"


<param type="value" name="level" value="1" unit="" refUnit="" />

<param type="value" name="angle" value="1.5707" unit="rad" refUnit="U17"

/>

</position>




</disposedElement>

<disposedElement id="DE005" refID="NE02-1" name="CTC_Counter" rule="single">

<position refShape="SH001" name="center" >

<param type="array" name="coords" value="array(x=0; y=0; z=0)" unit="um"

refUnit="U04" />

<param type="value" name="level" value="1" unit="" refUnit="" />

<param type="value" name="angle" value="1.5707" unit="rad" refUnit="U17"

/>

<param type="value" name="CTCdistance" value="2" unit="mm" refUnit="U16"

/>

</position>


</disposedElement>

</disposedCompartment>

</networkTopology>

<listOfState>

<state id="IS01" name="idle" nextState="IS01">

<action name="idle" time="0" unit="s" refUnit="U03" stateChange="no" />

</state>

<state id="IS02" name="creationState" nextState="IS01">

<action name="creation" time="0.1" unit="s" refUnit="U03"

stateChange="yes"/>

</state>

<state id="IS03" name="reception" nextState="IS01">

<action name="countCTC" time="0" unit="s" refUnit="U03" stateChange="no"/>

</state>

</listOfState>

<listOfOutput>


<path name="filename" url="./outputData/CTC_tracking.txt" />




<column id="col003" name="position"/>

</row>



<outputObj element="CTC_cell_signal" type="NetworkElement" refID="NE03-1"

colID="col002" >


outputType="long" value="#" colID="col001"/>

<outputParam type="ref" name="coords" description="object position"

outputType="float[3]" value="#" colID="col003"/>

</outputObj>


</outputRule>

</outputFormat>


<path name="filename" url="./outputData/CTC_detected.txt" />




<column id="col0012" name="event"/>

<column id="col0013" name="value"/>

</row>



<outputObj element="CTC_Counter" type="NetworkElement" refID="NE02-1"

colID="col0011">


outputType="long" value="#" colID="col0010"/>

<outputParam type="ref" name="eventName" description="observed event"

outputType="string" value="CTC_detected" colID="col0012"/>

<outputParam type="ref" name="detectionValue" description="assimilated

carriers" outputType="long" value="#" colID="col0013" />

</outputObj>


</outputRule>

</outputFormat>

</listOfOutput>

<listOfEvent>

<observedAttribute>



<attribute name="t" description="current time" unit="s" refUnit="U03" />

<attribute name="tr" description="next regeneration time" unit="s"

refUnit="U03" />

</observedAttribute>

<event id="E001" name="populate" description="refill the blood vessel with

new cells">

<mathRule id="MR080" name="calc next generation time"

path="./mathEquations/generation_time.xml" >

<param type="value" direction="out" name="tr" description="next generation

time" value="" unit="s" refUnit="U03" />

<param type="value" direction="in" name="l" escription="vessel_section"

value="88.5" unit="um" refUnit="U04" />

<param type="ref" direction="in" name="vm" description="mean velocity"

value="MR010.name[vmean].value" unit="MR010.name[vmean].unit"

refUnit="MR010.name[vmean].refUnit" />

</mathRule>

<if condition="t>=tr">

<![CDATA[



refillVessel(vessel_section);

/*

generation of new blood cells on a short section according to cell

concentration values (PLA, WBC, RBC),

as reported on rules: DE001, DE002, DE003

This section is centered on the top longitudinal coordinate of the cylinder

*/

]]>

<else>

<![CDATA[

// Do nothing

]]>

</else>

</if>

</event>

<event id="E002" name="shutdown" description="stop simulation">

<if condition="t>3600">


shutdown();

]]>

<else>



]]>

</else>

</if>

</event>

<event id="E003" name="output results" description="store simulation

results">

<condition if="t%0.001==0">




]]>

<else>





]]>

</else>

</condition>

</event>

</listOfEvent>

</model>

</molcomml>



References

[1] L. Felicetti, M. Femminella, G. Reali, P. Liò, " Applications of molecular communications to medicine: A survey", Nano Communcation Networks, 2015, DOI: 10.1016/j.nancom.2015.08.004.

[2] L. Felicetti, M. Femminella, G. Reali, "A simulation tool for nanoscale biological networks", Nano Communcation Networks, 2012, 3(1), pp. 2-18.

[3] M. T. Barros, S. Balasubramaniam, B. Jennings, “ Comparative End-to-end Analysis of Ca2+ Signaling-based Molecular Communication in Biological Tissues,” IEEE Transactions on Communications, 2015.

[4] F. Achard, G. Vaysseix, and E. Barillot. XML, bioinformatics and data integration. Bioinformatics, 17(2):115{125, Feb 2001.

[5] OF-CONFIG 1.2, OpenFlow Management and Configuration Protocol. TS-016. [6] R. Enns, M. Bjorklund, J. Schoenwaelder, and A. Bierman. Network Conguration Protocol

(NETCONF). RFC 6241 (Proposed Standard), June 2011. [7] L. Felicetti, M. Femminella, G. Reali, T. Nakano, and A. V. Vasilakos. Tcp-like molecular

communications. IEEE Journal on Selected Areas in Communications, 32(12):2354{2367, Dec 2014.

[8] M. Hucka et al. The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models. Bioinformatics, 19(4):524{531, Mar 2003.

[9] M. Galdzicki et al. The Synthetic Biology Open Language (SBOL) provides a community standard for communicating designs in synthetic biology. Nat. Biotechnol., 32(6):545{550, Jun 2014.

[10] A. Cuellar et al. The CellML 1.1 Specication. J Integr Bioinform, 12(2):259, 2015. [11] M. Vella et al. libNeuroML and PyLEMS: using Python to combine procedural and

declarative modeling approaches in computational neuroscience. Front Neuroinform, 8:38, 2014.

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