rivista” FUZZY POSSIBILITIES AS UPPER PREVISIONS

In this paper we analyze, mainly in a finitary setting, the consistency properties of fuzzy possibilities, interpreting them as instances of upper previsions and applying the basic notions of avoiding sure loss and coherence from the theory of imprecise probabilities. It ensues that fuzzy possibilities always avoid sure loss, but satisfy the stronger coherence condition only in a special case. Their natural extension, i.e. their least–committal correction to a coherent upper prevision, is determined. The same analysis is then performed when min is replaced by a T–norm (or seminorm) in the definition of fuzzy possibility, showing that the consistency properties and also the natural extension remain the same. Some “closure ” properties are also discussed, which are guaranteed to hold if the T–norm is continuous, and are satisfied by (ordinary) possibilities too

Scoring predictive models using a reduced representation of proteins: model and energy definition

BACKGROUND: Reduced representations of proteins have been playing a keyrole in the study of protein folding. Many such models are available, with different representation detail. Although the usefulness of many such models for structural bioinformatics applications has been demonstrated in recent years, there are few intermediate resolution models endowed with an energy model capable, for instance, of detecting native or native-like structures among decoy sets. The aim of the present work is to provide a discrete empirical potential for a reduced protein model termed here PC2CA, because it employs a PseudoCovalent structure with only 2 Centers of interactions per Amino acid, suitable for protein model quality assessment. RESULTS: All protein structures in the set top500H have been converted in reduced form. The distribution of pseudobonds, pseudoangle, pseudodihedrals and distances between centers of interactions have been converted into potentials of mean force. A suitable reference distribution has been defined for non-bonded interactions which takes into account excluded volume effects and protein finite size. The correlation between adjacent main chain pseudodihedrals has been converted in an additional energetic term which is able to account for cooperative effects in secondary structure elements. Local energy surface exploration is performed in order to increase the robustness of the energy function. CONCLUSION: The model and the energy definition proposed have been tested on all the multiple decoys' sets in the Decoys'R'us database. The energetic model is able to recognize, for almost all sets, native-like structures (RMSD less than 2.0 Å). These results and those obtained in the blind CASP7 quality assessment experiment suggest that the model compares well with scoring potentials with finer granularity and could be useful for fast exploration of conformational space. Parameters are available at the url:

Understanding the potentiality of accelerator based-boron neutron capture therapy for osteosarcoma: Dosimetry assessment based on the reported clinical experience

Background: Osteosarcoma is the most frequent primary malignant bone tumour, and its incidence is higher in children and adolescents, for whom it represents more than 10% of solid cancers. Despite the introduction of adjuvant and neo-adjuvant chemotherapy that markedly increased the success rate in the treatment, aggressive surgery is still needed and a considerable percentage of patients do not survive due to recurrences or early metastases. Boron Neutron Capture Therapy (BNCT), an experimental radiotherapy, was investigated as a treatment that could allow a less aggressive surgery by killing infiltrated tumour cells in the surrounding healthy tissues. BNCT requires an intense neutron beam to ensure irradiation times of the order of 1h. In Italy, a Radio Frequency Quadrupole (RFQ) proton accelerator has been designed and constructed for BNCT, and a suitable neutron spectrum was tailored by means of Monte Carlo calculations. This paper explores the feasibility of BNCT to treat osteosarcoma using this neutron source based on accelerator. Methods: The therapeutic efficacy of BNCT was analysed evaluating the dose distribution obtained in a clinical case of femur osteosarcoma. Mixed field dosimetry was assessed with two different formalisms whose parameters were specifically derived from radiobiological experiments involving in vitro UMR-106 osteosarcoma cell survival assays and boron concentration assessments in an animal model of osteosarcoma. A clinical case of skull osteosarcoma treated with BNCT in Japan was re-evaluated from the point of view of dose calculation and used as a reference for comparison. Results: The results in the case of femur osteosarcoma show that the RFQ beam would ensure a suitable tumour dose painting in a total irradiation time of less than an hour. Comparing the dosimetry between the analysed case and the treated patient in Japan it turns out that doses obtained in the femur tumour are at least as good as the ones delivered in the skull osteosarcoma. The same is concluded when the comparison is carried out taking into account osteosarcoma irradiations with photon radiation therapy. Conclusions: The possibility to apply BNCT to osteosarcoma would allow a multimodal treatment consisting in neo-adjuvant chemotherapy, high-LET selective radiation treatment and a more conservative surgery.Fil: Bortolussi, Silva. University of Pavia; ItaliaFil: Postuma, Ian. University of Pavia; ItaliaFil: Protti, Nicoletta. University of Pavia; ItaliaFil: Provenzano, Lucas. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Comisión Nacional de Energía Atómica; ArgentinaFil: Ferrari, Cinzia. University of Pavia; ItaliaFil: Cansolino, Laura. University of Pavia; ItaliaFil: Dionigi, Paolo. University of Pavia; ItaliaFil: Galasso, Olimpio. University of Catanzaro; ItaliaFil: Gasparini, Giorgio. University of Catanzaro; ItaliaFil: Altieri, Saverio. University of Pavia; ItaliaFil: Miyatake, Shin Ichi. Osaka Medical College; JapónFil: González, Sara Josefina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Comisión Nacional de Energía Atómica; Argentin

Statistical Model Checking for Stochastic Hybrid Systems

This paper presents novel extensions and applications of the UPPAAL-SMC model checker. The extensions allow for statistical model checking of stochastic hybrid systems. We show how our race-based stochastic semantics extends to networks of hybrid systems, and indicate the integration technique applied for implementing this semantics in the UPPAAL-SMC simulation engine. We report on two applications of the resulting tool-set coming from systems biology and energy aware buildings.Comment: In Proceedings HSB 2012, arXiv:1208.315

A Process Calculus for Molecular Interaction Maps

We present the MIM calculus, a modeling formalism with a strong biological basis, which provides biologically-meaningful operators for representing the interaction capabilities of molecular species. The operators of the calculus are inspired by the reaction symbols used in Molecular Interaction Maps (MIMs), a diagrammatic notation used by biologists. Models of the calculus can be easily derived from MIM diagrams, for which an unambiguous and executable interpretation is thus obtained. We give a formal definition of the syntax and semantics of the MIM calculus, and we study properties of the formalism. A case study is also presented to show the use of the calculus for modeling biomolecular networks.Comment: 15 pages; 8 figures; To be published on EPTCS, proceedings of MeCBIC 200

Systematic versus on-demand early palliative care: results from a multicentre, randomised clinical trial

Background Early palliative care (EPC) in oncology has been shown to have a positive impact on clinical outcome, quality-of-care outcomes, and costs. However, the optimal way for activating EPC has yet to be defined. Methods This prospective, multicentre, randomised study was conducted on 207 outpatients with metastatic or locally advanced inoperable pancreatic cancer. Patients were randomised to receive ‘standard cancer care plus on-demand EPC’ (n = 100) or ‘standard cancer care plus systematic EPC’ (n = 107). Primary outcome was change in quality of life (QoL) evaluated through the Functional Assessment of Cancer Therapy – Hepatobiliary questionnaire between baseline (T0) and after 12 weeks (T1), in particular the integration of physical, functional, and Hepatic Cancer Subscale (HCS) combined in the Trial Outcome Index (TOI). Patient mood, survival, relatives' satisfaction with care, and indicators of aggressiveness of care were also evaluated. Findings The mean changes in TOI score and HCS score between T0 and T1 were −4.47 and −0.63, with a difference between groups of 3.83 (95% confidence interval [CI] 0.10–7.57) (p = 0.041), and −2.23 and 0.28 (difference between groups of 2.51, 95% CI 0.40–4.61, p = 0.013), in favour of interventional group. QoL scores at T1 of TOI scale and HCS were 84.4 versus 78.1 (p = 0.022) and 52.0 versus 48.2 (p = 0.008), respectively, for interventional and standard arm. Until February 2016, 143 (76.9%) of the 186 evaluable patients had died. There was no difference in overall survival between treatment arms. Interpretations Systematic EPC in advanced pancreatic cancer patients significantly improved QoL with respect to on-demand EPC

Fuzzy Possibilities as Upper Previsions

In this paper we analyze, mainly in a nitary setting, the consistency properties of fuzzy possibilities, interpreting them as instances of upper previsions and applying the basic notions of avoiding sure loss and coherence from the theory of imprecise probabilities. It ensues that fuzzy possibilities always avoid sure loss, but satisfy the stronger coherence condition only in a special case. Their natural extension, i.e. their least committal correction to a coherent upper prevision, is determined. The same analysis is then performed when min is replaced by a T norm (or seminorm) in the de nition of fuzzy possibility, showing that the consistency properties and also the natural extension remain the same. Some closure properties are also discussed, which are guaranteed to hold if the T norm is continuous, and are satis ed by (ordinary) possibilities too

Fake news e polarizzazione: come cambia l'informazione ai tempi di internet

La conferenza si svolge nell'ambito di Trieste Next 2019-Big data e Deep Science: si pensa che Internet possa garantire a tutti un accesso libero ed esaustivo all’informazione. Tuttavia, in un sistema informativo iperconnesso quale quello digitale, le informazioni sono tante, a volte difficilmente verificabili, ma la nostra attenzione è limitata, e alcuni meccanismi cognitivi tendono a prendere il sopravvento, rendendo il dibattito fortemente polarizzato. Ma come funzionano questi meccanismi? Quali strategie possono essere messe in campo per attenuare la polarizzazione? E come possiamo difenderci ed essere dei cittadini digitali consapevoli

Stochastic Variational Smoothed Model Checking

Model-checking for parametric stochastic models can be expressed as checking the satisfaction probability of a certain property as a function of the parameters of the model. Smoothed model checking (smMC) leverages Gaussian Processes (GP) to infer the satisfaction function over the entire parameter space from a limited set of observations obtained via simulation. This approach provides accurate reconstructions with statistically sound quantification of the uncertainty. However, it inherits the scalability issues of GP. In this paper, we exploit recent advances in probabilistic machine learning to push this limitation forward, making Bayesian inference of smMC scalable to larger datasets, enabling its application to larger models in terms of the dimension of the parameter set. We propose Stochastic Variational Smoothed Model Checking (SV-smMC), a solution that exploits stochastic variational inference (SVI) to approximate the posterior distribution of the smMC problem. The strength and flexibility of SVI make SV-smMC applicable to two alternative probabilistic models: Gaussian Processes (GP) and Bayesian Neural Networks (BNN). Moreover, SVI makes inference easily parallelizable and it enables GPU acceleration. In this paper, we compare the performances of smMC against those of SV-smMC by looking at the scalability, the computational efficiency and at the accuracy of the reconstructed satisfaction function