|
M. P. Hengartner, T. H. C. Kruger, K. Geraedts, E. Tronci, T. Mancini, F. Ille, M. Egli, S. Röblitz, R. Ehrig, L. Saleh et al. "Negative affect is unrelated to fluctuations in hormone levels across the menstrual cycle: Evidence from a multisite observational study across two successive cycles." Journal of Psychosomatic Research 99 (2017): 21–27. DOI: 10.1016/j.jpsychores.2017.05.018.
|
|
|
T. Mancini, A. Massini, and E. Tronci. "Parallelization of Cycle-Based Logic Simulation." Parallel Processing Letters 27, no. 02 (2017). DOI: 10.1142/S0129626417500037.
|
|
|
F. Maggioli, T. Mancini, and E. Tronci. "SBML2Modelica: Integrating biochemical models within open-standard simulation ecosystems." Bioinformatics 36, no. 7 (2019): 2165–2172. ISSN: 1367-4803. DOI: 10.1093/bioinformatics/btz860.
Abstract: SBML is the most widespread language for the definition of biochemical models. Although dozens of SBML simulators are available, there is a general lack of support to the integration of SBML models within open-standard general-purpose simulation ecosystems. This hinders co-simulation and integration of SBML models within larger model networks, in order to, e.g., enable in-silico clinical trials of drugs, pharmacological protocols, or engineering artefacts such as biomedical devices against Virtual Physiological Human models.Modelica is one of the most popular existing open-standard general-purpose simulation languages, supported by many simulators. Modelica models are especially suited for the definition of complex networks of heterogeneous models from virtually all application domains. Models written in Modelica (and in 100+ other languages) can be readily exported into black-box Functional Mock-Up Units (FMUs), and seamlessly co-simulated and integrated into larger model networks within open-standard language-independent simulation ecosystems.In order to enable SBML model integration within heterogeneous model networks, we present SBML2Modelica, a software system translating SBML models into well-structured, user-intelligible, easily modifiable Modelica models. SBML2Modelica is SBML Level 3 Version 2 -compliant and succeeds on 96.47% of the SBML Test Suite Core (with a few rare, intricate, and easily avoidable combinations of constructs unsupported and cleanly signalled to the user). Our experimental campaign on 613 models from the BioModels database (with up to 5438 variables) shows that the major open-source (general-purpose) Modelica and FMU simulators achieve performance comparable to state-of-the-art specialised SBML simulators.SBML2Modelica is written in Java and is freely available for non-commercial use at https://bitbucket.org/mclab/sbml2modelica
|
|
|
R. Ehrig, T. Dierkes, S. Schaefer, S. Roeblitz, E. Tronci, T. Mancini, I. Salvo, V. Alimguzhin, F. Mari, I. Melatti et al. "An integrative approach for model driven computation of treatments in reproductive medicine." In Proceedings of the 15th International Symposium on Mathematical and Computational Biology (BIOMAT 2015), Rorkee, India., 2015. DOI: 10.1142/9789813141919_0005.
|
|
|
B. P. Hayes, I. Melatti, T. Mancini, M. Prodanovic, and E. Tronci. "Residential Demand Management using Individualised Demand Aware Price Policies." IEEE Transactions On Smart Grid 8, no. 3 (2017): 1284–1294. DOI: 10.1109/TSG.2016.2596790.
|
|
|
T. Mancini. "Now or Never: Negotiating Efficiently with Unknown or Untrusted Counterparts." Fundamenta Informaticae 149, no. 1-2 (2016): 61–100. DOI: 10.3233/FI-2016-1443.
|
|
|
T. Mancini, F. Mari, A. Massini, I. Melatti, and E. Tronci. "SyLVaaS: System Level Formal Verification as a Service." Fundamenta Informaticae 149, no. 1-2 (2016): 101–132. DOI: 10.3233/FI-2016-1444.
|
|
|
B. Leeners, T. H. C. Krueger, K. Geraedts, E. Tronci, T. Mancini, M. Egli, S. Roeblitz, L. Saleh, K. Spanaus, C. Schippert et al. "Associations Between Natural Physiological and Supraphysiological Estradiol Levels and Stress Perception." Frontiers in Psychology 10 (2019): 1296. ISSN: 1664-1078. DOI: 10.3389/fpsyg.2019.01296.
Abstract: Stress is a risk factor for impaired general, mental and reproductive health. The role of physiological and supraphysiological estradiol concentrations in stress perception and stress processing is less well understood. We therefore, conducted a prospective observational study to investigate the association between estradiol, stress perception and stress-related cognitive performance within serial measurements either during the natural menstrual cycle or during fertility treatment, where estradiol levels are strongly above the physiological level of a natural cycle and consequently, represent a good model to study dose-dependent effects of estradiol. Data from 44 women receiving in vitro fertilization at the Department of Reproductive Endocrinology in Zurich, Switzerland was compared to data from 88 women with measurements during their natural menstrual cycle. The german version of the Perceived Stress Questionnaire (PSQ) and the Cognitive Bias Test (CBT), in which cognitive performance is tested under time stress were used to evaluate subjective and functional aspects of stress. Estradiol levels were investigated at four different time points during the menstrual cycle and at two different time points during a fertility treatment. Cycle phase were associated with PSQ worry and cognitive bias in normally cycling women, but different phases of fertility treatment were not associated with subjectively perceived stress and stress-related cognitive bias. PSQ lack of joy and PSQ demands related to CBT in women receiving fertility treatment but not in women with a normal menstrual cycle. Only strong changes of the estradiol level during fertility treatment were weakly associated with CBT, but not with subjectively experienced stress. Our research emphasises the multidimensional character of stress and the necessity to adjust stress research to the complex nature of stress perception and processing. Infertility is associated with an increased psychological burden in patients. However, not all phases of the process to overcome infertility do significantly increase patient stress levels. Also, research on the psychological burden of infertility should consider that stress may vary during the different phases of fertility treatment.
|
|
|
Y. Driouich, M. Parente, and E. Tronci. "Modeling cyber-physical systems for automatic verification." In 14th International Conference on Synthesis, Modeling, Analysis and Simulation Methods and Applications to Circuit Design (SMACD 2017), 1–4., 2017. DOI: 10.1109/SMACD.2017.7981621.
Keywords: cyber-physical systems;formal verification;maximum power point trackers;power engineering computing;Modelica;automatic verification;complex power electronics systems;cyber-physical systems modeling;distributed maximum power point tracking system;open standard modeling language;Computational modeling;Control systems;Integrated circuit modeling;Mathematical model;Maximum power point trackers;Object oriented modeling;Radiation effects;Automatic Formal Verification;Cyber-Physical Systems;DMPPT;Modeling;Photovoltaic systems;Simulation;System Analysis and Design
|
|
|
Y. Driouich, M. Parente, and E. Tronci. "A methodology for a complete simulation of Cyber-Physical Energy Systems." In EESMS 2018 – Environmental, Energy, and Structural Monitoring Systems, Proceedings, 1–5., 2018. DOI: 10.1109/EESMS.2018.8405826.
|
|