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Author Fischer, S.; Ehrig, R.; Schaefer, S.; Tronci, E.; Mancini, T.; Egli, M.; Ille, F.; Krueger, T.H.C.; Leeners, B.; Roeblitz, S. pdf  url
doi  openurl
  Title Mathematical Modeling and Simulation Provides Evidence for New Strategies of Ovarian Stimulation Type Journal Article
  Year 2021 Publication Frontiers in Endocrinology Abbreviated Journal  
  Volume 12 Issue Pages 117  
  Keywords (up)  
  Abstract New approaches to ovarian stimulation protocols, such as luteal start, random start or double stimulation, allow for flexibility in ovarian stimulation at different phases of the menstrual cycle. It has been proposed that the success of these methods is based on the continuous growth of multiple cohorts (“waves”) of follicles throughout the menstrual cycle which leads to the availability of ovarian follicles for ovarian controlled stimulation at several time points. Though several preliminary studies have been published, their scientific evidence has not been considered as being strong enough to integrate these results into routine clinical practice. This work aims at adding further scientific evidence about the efficiency of variable-start protocols and underpinning the theory of follicular waves by using mathematical modeling and numerical simulations. For this purpose, we have modified and coupled two previously published models, one describing the time course of hormones and one describing competitive follicular growth in a normal menstrual cycle. The coupled model is used to test ovarian stimulation protocols in silico. Simulation results show the occurrence of follicles in a wave-like manner during a normal menstrual cycle and qualitatively predict the outcome of ovarian stimulation initiated at different time points of the menstrual cycle.  
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  ISSN 1664-2392 ISBN Medium  
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  Notes Approved no  
  Call Number MCLab @ davi @ ref10.3389/fendo.2021.613048 Serial 189  
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Author Chen, Q.M.; Finzi, A.; Mancini, T.; Melatti, I.; Tronci, E. pdf  doi
openurl 
  Title MILP, Pseudo-Boolean, and OMT Solvers for Optimal Fault-Tolerant Placements of Relay Nodes in Mission Critical Wireless Networks Type Journal Article
  Year 2020 Publication Abbreviated Journal Fundamenta Informaticae  
  Volume 174 Issue Pages 229-258  
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  Abstract In critical infrastructures like airports, much care has to be devoted in protecting radio communication networks from external electromagnetic interference. Protection of such mission-critical radio communication networks is usually tackled by exploiting radiogoniometers: at least three suitably deployed radiogoniometers, and a gateway gathering information from them, permit to monitor and localise sources of electromagnetic emissions that are not supposed to be present in the monitored area. Typically, radiogoniometers are connected to the gateway through relay nodes . As a result, some degree of fault-tolerance for the network of relay nodes is essential in order to offer a reliable monitoring. On the other hand, deployment of relay nodes is typically quite expensive. As a result, we have two conflicting requirements: minimise costs while guaranteeing a given fault-tolerance. In this paper, we address the problem of computing a deployment for relay nodes that minimises the overall cost while at the same time guaranteeing proper working of the network even when some of the relay nodes (up to a given maximum number) become faulty (fault-tolerance ). We show that, by means of a computation-intensive pre-processing on a HPC infrastructure, the above optimisation problem can be encoded as a 0/1 Linear Program, becoming suitable to be approached with standard Artificial Intelligence reasoners like MILP, PB-SAT, and SMT/OMT solvers. Our problem formulation enables us to present experimental results comparing the performance of these three solving technologies on a real case study of a relay node network deployment in areas of the Leonardo da Vinci Airport in Rome, Italy.  
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  Publisher IOS Press Place of Publication Editor  
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  Series Volume Series Issue Edition  
  ISSN 1875-8681 ISBN Medium  
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  Notes Approved no  
  Call Number MCLab @ davi @ Serial 188  
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Author Pappagallo, A.; Massini, A.; Tronci, E. pdf  doi
openurl 
  Title Monte Carlo Based Statistical Model Checking of Cyber-Physical Systems: A Review Type Journal Article
  Year 2020 Publication Information Abbreviated Journal  
  Volume 11 Issue 558 Pages  
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  Notes Approved no  
  Call Number MCLab @ davi @ Serial 181  
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Author Tortora, L.; Meynen, G.; Bijlsma, J.; Tronci, E.; Ferracuti, S. pdf  url
doi  openurl
  Title Neuroprediction and A.I. in Forensic Psychiatry and Criminal Justice: A Neurolaw Perspective Type Journal Article
  Year 2020 Publication Frontiers in Psychology Abbreviated Journal  
  Volume 11 Issue Pages 220  
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  Abstract Advances in the use of neuroimaging in combination with A.I., and specifically the use of machine learning techniques, have led to the development of brain-reading technologies which, in the nearby future, could have many applications, such as lie detection, neuromarketing or brain-computer interfaces. Some of these could, in principle, also be used in forensic psychiatry. The application of these methods in forensic psychiatry could, for instance, be helpful to increase the accuracy of risk assessment and to identify possible interventions. This technique could be referred to as ‘A.I. neuroprediction,Â’ and involves identifying potential neurocognitive markers for the prediction of recidivism. However, the future implications of this technique and the role of neuroscience and A.I. in violence risk assessment remain to be established. In this paper, we review and analyze the literature concerning the use of brain-reading A.I. for neuroprediction of violence and rearrest to identify possibilities and challenges in the future use of these techniques in the fields of forensic psychiatry and criminal justice, considering legal implications and ethical issues. The analysis suggests that additional research is required on A.I. neuroprediction techniques, and there is still a great need to understand how they can be implemented in risk assessment in the field of forensic psychiatry. Besides the alluring potential of A.I. neuroprediction, we argue that its use in criminal justice and forensic psychiatry should be subjected to thorough harms/benefits analyses not only when these technologies will be fully available, but also while they are being researched and developed.  
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  ISSN 1664-1078 ISBN Medium  
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  Call Number MCLab @ davi @ Neuroprediction-2020 Serial 180  
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Author Mancini, T.; Mari, F.; Massini, A.; Melatti, I.; Salvo, I.; Sinisi, S.; Tronci, E.; Ehrig, R.; Röblitz, S.; Leeners, B. pdf  doi
openurl 
  Title Computing Personalised Treatments through In Silico Clinical Trials. A Case Study on Downregulation in Assisted Reproduction Type Conference Article
  Year 2018 Publication 25th RCRA International Workshop on “Experimental Evaluation of Algorithms for Solving Problems with Combinatorial Explosion” (RCRA 2018) Abbreviated Journal  
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  Notes Approved no  
  Call Number MCLab @ davi @ Serial 175  
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Author Mancini, T.; Tronci, E.; Scialanca, A.; Lanciotti, F.; Finzi, A.; Guarneri, R.; Di Pompeo, S. pdf  doi
openurl 
  Title Optimal Fault-Tolerant Placement of Relay Nodes in a Mission Critical Wireless Network Type Conference Article
  Year 2018 Publication 25th RCRA International Workshop on “Experimental Evaluation of Algorithms for Solving Problems with Combinatorial Explosion” (RCRA 2018) Abbreviated Journal  
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  Notes Approved no  
  Call Number MCLab @ davi @ Serial 174  
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Author Driouich, Y.; Parente, M.; Tronci, E. pdf  doi
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  Title Model Checking Cyber-Physical Energy Systems Type Conference Article
  Year 2018 Publication Proceedings of 2017 International Renewable and Sustainable Energy Conference, IRSEC 2017 Abbreviated Journal  
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  Publisher Institute of Electrical and Electronics Engineers Inc. Place of Publication Editor  
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  Notes Approved no  
  Call Number MCLab @ davi @ Driouich2018 Serial 177  
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Author Mancini, T.; Mari, F.; Melatti, I.; Salvo, I.; Tronci, E.; Gruber, J.; Hayes, B.; Prodanovic, M.; Elmegaard, L. pdf  doi
openurl 
  Title Parallel Statistical Model Checking for Safety Verification in Smart Grids Type Conference Article
  Year 2018 Publication 2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm) Abbreviated Journal  
  Volume Issue Pages 1-6  
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  Notes Approved no  
  Call Number MCLab @ davi @ mancini-etal:2018:smartgridcomm Serial 170  
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Author Driouich, Y.; Parente, M.; Tronci, E. pdf  doi
openurl 
  Title A methodology for a complete simulation of Cyber-Physical Energy Systems Type Conference Article
  Year 2018 Publication EESMS 2018 – Environmental, Energy, and Structural Monitoring Systems, Proceedings Abbreviated Journal  
  Volume Issue Pages 1-5  
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  Call Number MCLab @ davi @ Driouich20181 Serial 169  
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Author Sinisi, S.; Alimguzhin, V.; Mancini, T.; Tronci, E.; Mari, F.; Leeners, B. pdf  doi
openurl 
  Title Optimal Personalised Treatment Computation through In Silico Clinical Trials on Patient Digital Twins Type Journal Article
  Year 2020 Publication Abbreviated Journal Fundamenta Informaticae  
  Volume 174 Issue Pages 283-310  
  Keywords (up) Artificial Intelligence; Virtual Physiological Human; In Silico Clinical Trials; Simulation; Personalised Medicine; In Silico Treatment Optimisation  
  Abstract In Silico Clinical Trials (ISCT), i.e. clinical experimental campaigns carried out by means of computer simulations, hold the promise to decrease time and cost for the safety and efficacy assessment of pharmacological treatments, reduce the need for animal and human testing, and enable precision medicine. In this paper we present methods and an algorithm that, by means of extensive computer simulation-based experimental campaigns (ISCT) guided by intelligent search, optimise a pharmacological treatment for an individual patient (precision medicine ). We show the effectiveness of our approach on a case study involving a real pharmacological treatment, namely the downregulation phase of a complex clinical protocol for assisted reproduction in humans.  
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  Publisher IOS Press Place of Publication Editor  
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  Series Volume Series Issue Edition  
  ISSN 1875-8681 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number MCLab @ davi @ Serial 187  
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