Bisimulation and simulation algorithms on probabilistic transition systems by abstract interpretation

We show how bisimulation equivalence and simulation preorder on probabilistic LTSs (PLTSs), namely the main behavioural relations on probabilistic nondeterministic processes, can be characterized by abstract interpretation. Both bisimulation and simulation can be obtained as completions of partitions and preorders, viewed as abstract domains, w.r.t. a pair of concrete functions that encode a PLTS. This approach provides a general framework for designing algorithms that compute bisimulation and simulation on PLTSs. Notably, (i)?we show that the standard bisimulation algorithm by Baier et al. (2000) can be viewed as an instance of such a framework and (ii)?we design a new efficient simulation algorithm that improves the state of the art.     

Cytogenomics Unveil Possible Transposable Elements Driving Rearrangements in Chromosomes 2 and 4 of Solea senegalensis

Cytogenomics, the integration of cytogenetic and genomic data, has been used here to reconstruct the evolution of chromosomes 2 and 4 of Solea senegalensis. S. senegalensis is a flat fish with a karyotype comprising 2n = 42 chromosomes: 6 metacentric + 4 submetacentric + 8 subtelocentric + 24 telocentric. The Fluorescence in situ Hybridization with Bacterial Artificial Chromosomes (FISH-BAC) technique was applied to locate BACs in these chromosomes (11 and 10 BACs in chromosomes 2 and 4, respectively) and to generate integrated maps. Synteny analysis, taking eight reference fish species (Cynoglossus semilaevis, Scophthalmus maximus, Sparus aurata, Gasterosteus aculeatus, Xiphophorus maculatus, Oryzias latipes, Danio rerio, and Lepisosteus oculatus) for comparison, showed that the BACs of these two chromosomes of S. senegalensis were mainly distributed in two principal chromosomes in the reference species. Transposable Elements (TE) analysis showed significant differences between the two chromosomes, in terms of number of loci per Mb and coverage, and the class of TE (I or II) present. Analysis of TE divergence in chromosomes 2 and 4 compared to their syntenic regions in four reference fish species (C. semilaevis, S. maximus, O. latipes, and D. rerio) revealed differences in their age of activity compared with those species but less notable differences between the two chromosomes. Differences were also observed in peaks of divergence and coverage of TE families for all reference species even in those close to S. senegalensis, like S. maximus and C. semilaevis. Considered together, chromosomes 2 and 4 have evolved by Robertsonian fusions, pericentric inversions, and other chromosomal rearrangements mediated by TEs.     

A2A Receptor Dysregulation in Dystonia DYT1 Knock-Out Mice

We aimed to investigate A2A receptors in the basal ganglia of a DYT1 mouse model of dystonia. A2A was studied in control Tor1a+/+ and Tor1a+/− knock-out mice. A2A expression was assessed by anti-A2A antibody immunofluorescence and Western blotting. The co-localization of A2A was studied in striatal cholinergic interneurons identified by anti-choline-acetyltransferase (ChAT) antibody. A2A mRNA and cyclic adenosine monophosphate (cAMP) contents were also assessed. In Tor1a+/+, Western blotting detected an A2A 45 kDa band, which was stronger in the striatum and the globus pallidus than in the entopeduncular nucleus. Moreover, in Tor1a+/+, immunofluorescence showed A2A roundish aggregates, 0.3–0.4 μm in diameter, denser in the neuropil of the striatum and the globus pallidus than in the entopeduncular nucleus. In Tor1a+/−, A2A Western blotting expression and immunofluorescence aggregates appeared either increased in the striatum and the globus pallidus, or reduced in the entopeduncular nucleus. Moreover, in Tor1a+/−, A2A aggregates appeared increased in number on ChAT positive interneurons compared to Tor1a+/+. Finally, in Tor1a+/−, an increased content of cAMP signal was detected in the striatum, while significant levels of A2A mRNA were neo-expressed in the globus pallidus. In Tor1a+/−, opposite changes of A2A receptors’ expression in the striatal-pallidal complex and the entopeduncular nucleus suggest that the pathophysiology of dystonia is critically dependent on a composite functional imbalance of the indirect over the direct pathway in basal ganglia.     

Skeletal Muscle Proteomic Profile Revealed Gender-Related Metabolic Responses in a Diet-Induced Obesity Animal Model

Obesity is a chronic, complex pathology associated with a risk of developing secondary pathologies, including cardiovascular diseases, cancer, type 2 diabetes (T2DM) and musculoskeletal disorders. Since skeletal muscle accounts for more than 70% of total glucose disposal, metabolic alterations are strictly associated with the onset of insulin resistance and T2DM. The present study relies on the proteomic analysis of gastrocnemius muscle from 15 male and 15 female C56BL/J mice fed for 14 weeks with standard, 45% or 60% high-fat diets (HFD) adopting a label-free LC–MS/MS approach followed by bioinformatic pathway analysis. Results indicate changes in males due to HFD, with increased muscular stiffness (Col1a1, Col1a2, Actb), fiber-type switch from slow/oxidative to fast/glycolytic (decreased Myh7, Myl2, Myl3 and increased Myh2, Mylpf, Mybpc2, Myl1), increased oxidative stress and mitochondrial dysfunction (decreased respiratory chain complex I and V and increased complex III subunits). At variance, females show few alterations and activation of compensatory mechanisms to counteract the increase of fatty acids. Bioinformatics analysis allows identifying upstream molecules involved in regulating pathways identified at variance in our analysis (Ppargc1a, Pparg, Cpt1b, Clpp, Tp53, Kdm5a, Hif1a). These findings underline the presence of a gender-specific response to be considered when approaching obesity and related comorbidities.     

The Quorum Sensing Auto-Inducer 2 (AI-2) Stimulates Nitrogen Fixation and Favors Ethanol Production over Biomass Accumulation in Zymomonas mobilis

Autoinducer 2 (or AI-2) is one of the molecules used by bacteria to trigger the Quorum Sensing (QS) response, which activates expression of genes involved in a series of alternative mechanisms, when cells reach high population densities (including bioluminescence, motility, biofilm formation, stress resistance, and production of public goods, or pathogenicity factors, among others). Contrary to most autoinducers, AI-2 can induce QS responses in both Gram-negative and Gram-positive bacteria, and has been suggested to constitute a trans-specific system of bacterial communication, capable of affecting even bacteria that cannot produce this autoinducer. In this work, we demonstrate that the ethanologenic Gram-negative bacterium Zymomonas mobilis (a non-AI-2 producer) responds to exogenous AI-2 by modulating expression of genes involved in mechanisms typically associated with QS in other bacteria, such as motility, DNA repair, and nitrogen fixation. Interestingly, the metabolism of AI-2-induced Z. mobilis cells seems to favor ethanol production over biomass accumulation, probably as an adaptation to the high-energy demand of N₂ fixation. This opens the possibility of employing AI-2 during the industrial production of second-generation ethanol, as a way to boost N₂ fixation by these bacteria, which could reduce costs associated with the use of nitrogen-based fertilizers, without compromising ethanol production in industrial plants.     

Neuro-fuzzy knowledge processing in intelligent learning environments for improved student diagnosis

In this paper, a neural network implementation for a fuzzy logic-based model of the diagnostic process is proposed as a means to achieve accurate student diagnosis and updates of the student model in Intelligent Learning Environments. The neuro-fuzzy synergy allows the diagnostic model to some extent “imitate” teachers in diagnosing students' characteristics, and equips the intelligent learning environment with reasoning capabilities that can be further used to drive pedagogical decisions depending on the student learning style. The neuro-fuzzy implementation helps to encode both structured and non-structured teachers' knowledge: when teachers' reasoning is available and well defined, it can be encoded in the form of fuzzy rules; when teachers' reasoning is not well defined but is available through practical examples illustrating their experience, then the networks can be trained to represent this experience. The proposed approach has been tested in diagnosing aspects of student's learning style in a discovery-learning environment that aims to help students to construct the concepts of vectors in physics and mathematics. The diagnosis outcomes of the model have been compared against the recommendations of a group of five experienced teachers, and the results produced by two alternative soft computing methods. The results of our pilot study show that the neuro-fuzzy model successfully manages the inherent uncertainty of the diagnostic process; especially for marginal cases, i.e. where it is very difficult, even for human tutors, to diagnose and accurately evaluate students by directly synthesizing subjective and, some times, conflicting judgments.     

Interpretation des Sourcings der Informationsverarbeitung: Hintergründe und Grenzen ökonomischer Einflussgrößen

This article aims to develop a more profound understanding of the heterogeneous behaviour in the field of Information Systems (IS) Outsourcing in German organizations. Based on multiple case studies in the German Manufacturing Industry, it demonstrates that resource deficits serve as an overriding contingency for the outsourcing decision. However, specific knowledge on internal business processes may lead to production cost advantages for the firm and, thus, inhibits the outsourcing of IS functions. Furthermore, cultural variables like distrust and sociability serve as additional contingencies for explaining heterogeneous outsourcing patterns.     

Selection and Evaluation of Test Data Based on Genetic Programming

In the literature, we find several criteria that consider different aspects of the program to guide the testing, a fundamental activity for software quality assurance. They address two important questions: how to select test cases to reveal as many fault as possible and how to evaluate a test set T and end the test. Fault-based criteria, such as mutation testing, use mutation operators to generate alternatives for the program P being tested. The goal is to derive test cases capable of producing different behaviors in P and its alternatives. However, this approach usually does not allow the test of interaction between faults since the alternative differs from P by a simple modification. This work explores the use of Genetic Programming (GP), a field of Evolutionary Computation, to derive alternatives for testing P and introduces two GP-based procedures for selection and evaluation of test data. The procedures are related to the above questions, usually addressed by most testing criteria and tools. A tool, named GPTesT, is described and results from an experiment using this tool are also presented. The results show the applicability of our approach and allow comparison with mutation testing.     

Reducibility: A ubiquitous method in lambda calculus with intersection types

A general reducibility method is developed for proving reduction properties of lambda terms typeable in intersection type systems with and without the universal type Ω. Sufficient conditions for its application are derived. This method leads to uniform proofs of confluence, standardization, and weak head normalization of terms typeable in the system with the type Ω. The method extends Tait's reducibility method for the proof of strong normalization of the simply typed lambda calculus, Krivine's extension of the same method for the strong normalization of intersection type system without Ω, and Statman-Mitchell's logical relation method for the proof of confluence of βη-reduction on the simply typed lambda terms. As a consequence, the confluence and the standardization of all (untyped) lambda terms is obtained.     

Arginase 2 and Polyamines in Human Pancreatic Beta Cells: Possible Role in the Pathogenesis of Type 2 Diabetes

Arginase 2 (ARG2) is a manganese metalloenzyme involved in several tissue specific processes, from physiology to pathophysiology. It is variably expressed in extra-hepatic tissues and is located in the mitochondria. In human pancreatic beta cells, ARG2 is downregulated in type 2 diabetes. The enzyme regulates the synthesis of polyamines, that are involved in pancreas development and regulation of beta cell function. Here, we discuss several features of ARG2 and polyamines, which can be relevant to the pathophysiology of type 2 diabetes.