Totally positive refinable functions with general dilation M

We construct a new class of approximating functions that are M-refinable and provide shape preserving approximations. The refinable functions in the class are smooth, compactly supported, centrally symmetric and totally positive. Moreover, their refinable masks are associated with convergent subdivision schemes. The presence of one or more shape parameters gives a great flexibility in the applications. Some examples for dilation M=4and M=5are also given

Abstract Interpretation for Probabilistic Termination of Biological Systems

In a previous paper the authors applied the Abstract Interpretation approach for approximating the probabilistic semantics of biological systems, modeled specifically using the Chemical Ground Form calculus. The methodology is based on the idea of representing a set of experiments, which differ only for the initial concentrations, by abstracting the multiplicity of reagents present in a solution, using intervals. In this paper, we refine the approach in order to address probabilistic termination properties. More in details, we introduce a refinement of the abstract LTS semantics and we abstract the probabilistic semantics using a variant of Interval Markov Chains. The abstract probabilistic model safely approximates a set of concrete experiments and reports conservative lower and upper bounds for probabilistic termination

An Analysis for Proving Probabilistic Termination of Biological Systems

In this paper we apply the abstract interpretation approach for approximating the behavior of biological systems, modeled specifically using the Chemical Ground Form calculus, a simple stochastic calculus rich enough to model the dynamics of biochemical reactions. The analysis is based on the idea of representing a set of experiments, which differ only for the initial concentrations, by abstracting the multiplicity of reagents present in a solution, using intervals. For abstracting the probabilistic semantics, modeled as a Discrete-Time Markov Chain, we use a variant of Interval Markov Chains, where probabilistic and non-deterministic steps are combined together. The abstract probabilistic semantics is systematically derived from an abstract Labeled Transition System. The abstract probabilistic model safely approximates the set of concrete experiments and reports conservative lower and upper bounds for probabilistic termination

Causal static analysis for Brane Calculi

We present here a static analysis, based on Abstract Interpretation, obtained by defining an abstract version of the causal semantics for the Mate/Bud/Drip (MBD) version of Brane Calculi, proposed by Busi. Our analysis statically approximates the dynamic behaviour of MBD systems. More precisely, the analysis is able to describe the essential behaviour of the represented membranes, in terms of their possible interactions. Furthermore, our analysis is able to statically capture the possible causal dependencies among interactions, whose determination can be exploited to better understand the modelled biological phenomena. Finally, we apply our analysis to an abstract specification of the receptor-mediated endocytosis mechanism

Vaccine Hesitancy: Lessons Learned and Perspectives for a Post-Pandemic Tomorrow

Infectious diseases have always posed a significant threat to mankind, resulting in high mortality and morbidity throughout history [1]. Currently, the burden of communicable diseases still remains very high in all age groups worldwide [2]. Moreover, the current COVID-19 pandemic has once again underlined the tremendous impact of transmittable diseases in terms of public health [1]. From this point of view, vaccines have always represented a fundamental public health tool. Indeed, mass immunization campaigns save millions of lives each year [3]. Furthermore, COVID-19 vaccines are enabling us to overcome the ongoing pandemic. Therefore, it is of utmost importance to promote vaccine uptake and to identify and address barriers for achieving adequate vaccination coverage. Among the obstacles to reaching adequate vaccination coverage, vaccine hesitancy (VH) is rightfully included. VH is defined by SAGE working group as “the delay in acceptance or refusal of vaccination despite the availability of vaccination services”[4] and was included by the World Health Organization (WHO) amongst the major health concerns in 2019 [5]. Going into detail, VH appears to be complex and context specific, varying across time, place and types of vaccines [4]. All these factors have been studied with respect to VH in recent decades and have played a big role during the COVID-19 pandemic and will certainly continue to do so in the post-pandemic future

Ausiliarie, spie, amanti. Donne tra guerra totale, guerra civile e giustizia di transizione in Italia. 1943-1953

La ricerca si è proposta di indagare le esperienze delle donne che durante la guerra aderirono al fascismo repubblicano o si schierarono a favore dell’occupante nazista, attraverso l’analisi dei fascicoli dei processi celebrati presso le Corti d’assise straordinarie per il reato di collaborazionismo, conservati presso le corti di Firenze, Genova e Torino. L’esame delle carte ha contribuito a delineare da un lato una morfologia del “collaborazionismo” femminile, permettendo di andare oltre il Saf, non rappresentativo dell'universo femminile fascista repubblicano, di decostruire lo stereotipo della casta e giovane ausiliaria e di evidenziare le differenti e complesse esperienze delle donne in guerra "dalla parte del nemico". D’altra parte lo studio delle carte ha consentito di delineare il periodo post-bellico e le vicende di violenza e giustizia che seguirono la fine della guerra. Sono state dunque analizzate, attraverso uno sguardo di genere, le strategie punitive giudiziarie ed extra-giudiziarie. All'analisi della pratica diffusa della rapatura delle donne, punizione sessuata riservata alle nemiche politiche, è seguito un esame delle retoriche giudiziarie attraverso le quali i protagonisti, maschi, dei processi rappresentarono le "collaborazioniste"

Case report: Infection with Dicrocoelium dendriticum in a Japanese Chin dog

Dicrocoelium dendriticum is a trematode colonising the bile ducts of herbivores. Coproscopic findings in dogs are usually considered gastrointestinal passages of eggs after ingestion of unheated liver tissue or infected ruminant faeces. Here, a Japanese Chin presented with diarrhoea and weight loss. Eggs comparable to D. dendriticum were detected in faeces and infection was confirmed via PCR and by ruling out differential diagnoses. Egg excretion continued for a period of 10 months. Praziquantel (50 mg/kg body weight [BW]) was administered orally for four consecutive days. Egg excretion 10 days after treatment entailed further treatments with 100 mg/kg BW, again for four days. Faecal samples were negative ten days and four weeks afterwards, diarrhoea resolved, and the dog gained weight. In cases of repeated coproscopic positivity for D. dendriticum, an infection with dogs acting as definitive hosts should be considered. Treatment with praziquantel at a higher dosage may be required

Generalized contexts for reaction systems: definition and study of dynamic causalities

Reaction systems are a qualitative formalism for the modelling of systems of biochemical reactions. In their original formulation, a reaction system executes in an environment (or context) that can supply it with new objects at each evolution step. The context drives the behaviour of a reaction system: it can provide different inputs to the system that can lead to different behaviours. In order to more faithfully deal with open systems, in this paper we propose a more powerful notion of context having not only the capability to provide objects, but also to absorb (or remove) objects at each evolution step. For such reaction systems with generalized context we investigate properties of dynamic causality by revising the previously proposed concept of formula based predictor. A formula based predictor is a Boolean formula characterising all contexts that lead to the production of a certain object after a given number of steps. In this paper, we revise the theory of formula based predictors in order to deal with reaction systems executed in a context of the new kind. As applications, we show an example of interaction between biochemical pathways and a reaction system modelling cell metabolism and respiration

Investigating dynamic causalities in reaction systems

Reaction systems are a qualitative formalism for modeling systems of biochemical reactions characterized by the non-permanency of the elements: molecules disappear if not produced by any enabled reaction. Moreover, reaction systems execute in an environment that provides new molecules at each step. Brijder, Ehrenfeucht and Rozenberg investigated dynamic causalities in reaction systems by introducing the idea of predictors. A predictor of a molecule s, for a given n, is the set of molecules to be observed in the environment in order to determine whether s is produced or not by the system at step n. In this paper, we continue the investigation on dynamic causalities by defining an abstract interpretation framework containing three different notions of predictor: Formula based predictors, that is a propositional logic formula that precisely characterizes environments that lead to the production of s after n steps; Multi-step based predictors, that consist of n sets of molecules to be observed in the environment, one for each step; and Set based predictors, that are those proposed by Brijder, Ehrenfeucht and Rozenberg, and consist of a unique set of molecules to be observed in all steps. For each kind of predictor we define an effective operator that allows predictors to be computed for any molecule s and number of steps n. The abstract interpretation framework allows us to compare the three notions of predictor in terms of precision, to relate the three defined operators and to compute minimal predictors. We also discuss a generalization of this approach that allows predictors to be defined independently of the value of n, and a tabling approach for the practical use of predictors on reaction systems models. As an application, we use predictors, generalization and tabling to give theoretical grounds to previously obtained results on a model of gene regulation

Commentary - Much ado about something else. Donald Trump, the US stock market, and the public interest ethics of social media communication

Trump’s use of social media during both his presidential campaign and term questions the principle that institutional responsibility in the digital realm implies treating the infosphere as a commons. We discuss the implications for the functioning of the stock market and the emerging public interest ethical issues related to the breakdown of this principle