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Author Cesta, Amedeo; Fratini, Simone; Orlandini, Andrea; Finzi, Alberto; Tronci, Enrico pdf  doi
openurl 
  Title Flexible Plan Verification: Feasibility Results Type Journal Article
  Year 2011 Publication (down) Fundamenta Informaticae Abbreviated Journal  
  Volume 107 Issue 2 Pages 111-137  
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  Notes Approved yes  
  Call Number Sapienza @ mari @ fi11 Serial 15  
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Author Mancini, T. pdf  doi
openurl 
  Title Now or Never: Negotiating Efficiently with Unknown or Untrusted Counterparts Type Journal Article
  Year 2016 Publication (down) Fundamenta Informaticae Abbreviated Journal  
  Volume 149 Issue 1-2 Pages 61-100  
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  Notes Approved no  
  Call Number MCLab @ davi @ DBLP:journals/fuin/Mancini16 Serial 161  
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Author Mancini, T.; Mari, F.; Massini, A.; Melatti, I.; Tronci, E. pdf  doi
openurl 
  Title SyLVaaS: System Level Formal Verification as a Service Type Journal Article
  Year 2016 Publication (down) Fundamenta Informaticae Abbreviated Journal  
  Volume 149 Issue 1-2 Pages 101-132  
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  Notes Approved no  
  Call Number MCLab @ davi @ DBLP:journals/fuin/ManciniMMMT16 Serial 160  
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Author Leeners, B.; Krueger, T.H.C.; Geraedts, K.; Tronci, E.; Mancini, T.; Egli, M.; Roeblitz, S.; Saleh, L.; Spanaus, K.; Schippert, C.; Zhang, Y.; Ille, F. pdf  url
doi  openurl
  Title Associations Between Natural Physiological and Supraphysiological Estradiol Levels and Stress Perception Type Journal Article
  Year 2019 Publication (down) Frontiers in Psychology Abbreviated Journal  
  Volume 10 Issue Pages 1296  
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  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.  
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  ISSN 1664-1078 ISBN Medium  
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  Notes Approved no  
  Call Number MCLab @ davi @ ref10.3389/fpsyg.2019.01296 Serial 178  
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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 (down) 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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  Notes Approved no  
  Call Number MCLab @ davi @ Neuroprediction-2020 Serial 180  
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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 (down) Frontiers in Endocrinology Abbreviated Journal  
  Volume 12 Issue Pages 117  
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  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 Leeners, B.; Kruger, T.H.C.; Geraedts, K.; Tronci, E.; Mancini, T.; Ille, F.; Egli, M.; Röblitz, S.; Saleh, L.; Spanaus, K.; Schippert, C.; Zhang, Y.; Hengartner, M.P. pdf  url
doi  openurl
  Title Lack of Associations between Female Hormone Levels and Visuospatial Working Memory, Divided Attention and Cognitive Bias across Two Consecutive Menstrual Cycles Type Journal Article
  Year 2017 Publication (down) Frontiers in Behavioral Neuroscience Abbreviated Journal  
  Volume 11 Issue Pages 120  
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  Abstract Background: Interpretation of observational studies on associations between prefrontal cognitive functioning and hormone levels across the female menstrual cycle is complicated due to small sample sizes and poor replicability. Methods: This observational multisite study comprised data of n=88 menstruating women from Hannover, Germany, and Zurich, Switzerland, assessed during a first cycle and n=68 re-assessed during a second cycle to rule out practice effects and false-positive chance findings. We assessed visuospatial working memory, attention, cognitive bias and hormone levels at four consecutive time-points across both cycles. In addition to inter-individual differences we examined intra-individual change over time (i.e., within-subject effects). Results: Oestrogen, progesterone and testosterone did not relate to inter-individual differences in cognitive functioning. There was a significant negative association between intra-individual change in progesterone and change in working memory from pre-ovulatory to mid-luteal phase during the first cycle, but that association did not replicate in the second cycle. Intra-individual change in testosterone related negatively to change in cognitive bias from menstrual to pre-ovulatory as well as from pre-ovulatory to mid-luteal phase in the first cycle, but these associations did not replicate in the second cycle. Conclusions: There is no consistent association between women's hormone levels, in particular oestrogen and progesterone, and attention, working memory and cognitive bias. That is, anecdotal findings observed during the first cycle did not replicate in the second cycle, suggesting that these are false-positives attributable to random variation and systematic biases such as practice effects. Due to methodological limitations, positive findings in the published literature must be interpreted with reservation.  
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  ISSN 1662-5153 ISBN Medium  
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  Notes Approved no  
  Call Number Sapienza @ mari @ ref10.3389/fnbeh.2017.00120 Serial 167  
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Author Mancini, T.; Mari, F.; Melatti, I.; Salvo, I.; Tronci, E. pdf  url
doi  openurl
  Title An Efficient Algorithm for Network Vulnerability Analysis Under Malicious Attacks Type Conference Article
  Year 2018 Publication (down) Foundations of Intelligent Systems – 24th International Symposium, ISMIS 2018, Limassol, Cyprus, October 29-31, 2018, Proceedings Abbreviated Journal  
  Volume Issue Pages 302-312  
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  Notes Best Paper Approved no  
  Call Number MCLab @ davi @ DBLP:conf/ismis/ManciniMMST18 Serial 176  
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Author Della Penna, Giuseppe; Intrigila, Benedetto; Melatti, Igor; Tronci, Enrico; Venturini Zilli, Marisa pdf  doi
openurl 
  Title Bounded Probabilistic Model Checking with the Mur$\varphi$ Verifier Type Conference Article
  Year 2004 Publication (down) Formal Methods in Computer-Aided Design, 5th International Conference, FMCAD 2004, Austin, Texas, USA, November 15-17, 2004, Proceedings Abbreviated Journal  
  Volume Issue Pages 214-229  
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  Abstract In this paper we present an explicit verification algorithm for Probabilistic Systems defining discrete time/finite state Markov Chains. We restrict ourselves to verification of Bounded PCTL formulas (BPCTL), that is, PCTL formulas in which all Until operators are bounded, possibly with different bounds. This means that we consider only paths (system runs) of bounded length. Given a Markov Chain $\cal M$ and a BPCTL formula Φ, our algorithm checks if Φ is satisfied in $\cal M$. This allows to verify important properties, such as reliability in Discrete Time Hybrid Systems. We present an implementation of our algorithm within a suitable extension of the Mur$\varphi$ verifier. We call FHP-Mur$\varphi$ (Finite Horizon Probabilistic Mur$\varphi$) such extension of the Mur$\varphi$ verifier. We give experimental results comparing FHP-Mur$\varphi$ with (a finite horizon subset of) PRISM, a state-of-the-art symbolic model checker for Markov Chains. Our experimental results show that FHP-Mur$\varphi$ can effectively handle verification of BPCTL formulas for systems that are out of reach for PRISM, namely those involving arithmetic operations on the state variables (e.g. hybrid systems).  
  Address  
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  Publisher Springer Place of Publication Editor Hu, A.J.; Martin, A.K.  
  Language Summary Language Original Title  
  Series Editor Series Title Lecture Notes in Computer Science Abbreviated Series Title  
  Series Volume 3312 Series Issue Edition  
  ISSN 3-540-23738-0 ISBN Medium  
  Area Expedition Conference  
  Notes Approved yes  
  Call Number Sapienza @ mari @ Dimtz04 Serial 87  
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Author Tronci, E.; Mancini, T.; Salvo, I.; Mari, F.; Melatti, I.; Massini, A.; Sinisi, S.; Davì, F.; Dierkes, T.; Ehrig, R.; Röblitz, S.; Leeners, B.; Krüger, T.; Egli, M.; Ille, F. pdf  doi
openurl 
  Title Patient-Specific Models from Inter-Patient Biological Models and Clinical Records Type Conference Article
  Year 2014 Publication (down) Formal Methods in Computer-Aided Design (FMCAD) Abbreviated Journal  
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  Notes Approved no  
  Call Number Sapienza @ mari @ Serial 120  
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