First-Order Logic with Connectivity Operators

First-order logic (FO) can express many algorithmic problems on graphs, such as the independent set and dominating set problem, parameterized by solution size. On the other hand, FO cannot express the very simple algorithmic question of whether two vertices are connected. We enrich FO with connectivity predicates that are tailored to express algorithmic graph properties that are commonly studied in parameterized algorithmics. By adding the atomic predicates $conn_k (x, y, z_1 ,\ldots, z_k)$ that hold true in a graph if there exists a path between (the valuations of) $x$ and $y$ after (the valuations of) $z_1,\ldots,z_k$ have been deleted, we obtain separator logic $FO + conn$. We show that separator logic can express many interesting problems such as the feedback vertex set problem and elimination distance problems to first-order definable classes. We then study the limitations of separator logic and prove that it cannot express planarity, and, in particular, not the disjoint paths problem. We obtain the stronger disjoint-paths logic $FO + DP$ by adding the atomic predicates $disjoint-paths_k [(x_1, y_1 ),\ldots , (x_k , y_k )]$ that evaluate to true if there are internally vertex disjoint paths between (the valuations of) $x_i$ and $y_i$ for all $1 \le i \le k$. Disjoint-paths logic can express the disjoint paths problem, the problem of (topological) minor containment, the problem of hitting (topological) minors, and many more. Finally, we compare the expressive power of the new logics with that of transitive closure logics and monadic second-order logic.Comment: 18 pages, 3 figure

Measuring mortality heterogeneity with multi-state models and interval-censored data

In this paper, our aim is to measure mortality rates which are specific to individual observable factors when these can change during life. The study is based on longitudinal data recording marital status and socio-professional features at census times, therefore the observation scheme is interval-censored since individual characteristics are only observed at isolated dates and transition times remain unknown. To this aim, we develop a parametric maximum likelihood estimation procedure for multi-state models that takes into account both interval-censoring and reversible transitions. This method, inspired by recent advances in the statistical literature, allows us to capture characteristic-specific mortality rates, in particular to recover the mortality compensation law at high ages, but also to capture the age pattern of characteristics changes. The dynamics of several population compositions is addressed, and allows us to give explanations on the pattern of aggregate mortality, as well as on the impact on typical life insurance products. Particular attention is devoted to characteristics changes and parameter uncertainty that are both crucial to take into account

Vagueness in implicature:The case of modified adjectives

We show that the interpretation of sentences like John is not very Adj depends on whether Adj is vague. We argue that this follows from a constraint on the interaction between vagueness and conversational implicature, a domain that has not been studied extensively. The constraint states that implicatures are not drawn if they lead to “borderline contradictions” (see Ripley 2011; Alxatib & Pelletier 2011; a.o.), a natural extension of the idea that implicatures should not contradict assertions (Hackl 2006; Fox 2007; a.o.). Experiment 1 establishes that not very Adj gives rise to the implicature Adj for the non-vague absolute adjective late, but not for the vague relative adjective tall (in the terminology of Kennedy & McNally 2005a). Experiment 2 generalizes this result to three relative adjectives in the positive form (tall, hot, fast), against those same adjectives in their (non-vague) comparative forms (taller/hotter/faster than the average X). We also constructed quantitative meaning representations for complex predicates of the form Adj ∧¬very Adj, using fuzzy logic to model the contribution of Boolean connectives and our experimental data to represent the meanings of adjectives. The results of these analyses suggest that strengthening not very Adj with Adj leads to a more contradictory interpretation when Adj is vague than when it is not, as expected on our theory. While our results apply directly to only a specific set of lexical items, we hypothesize that they reflect a more general pattern among gradable predicates. This motivates more systematic investigation into the role that vagueness can play in the derivation of conversational implicatures

Bulletin des bibliothèques de France dans l’histoire des bibliothèques (Le)

Ce mémoire retrace l’évolution des bibliothèques françaises depuis 1980 telle que la restitue le BBF. L’historique de la revue rend compte de ses modifications structurelles et matérielles successives tandis que l’analyse de différents thèmes abordés par le BBF renseigne sur l’évolution de la réflexion des professionnels des bibliothèques

CSN5 binds to misfolded CFTR and promotes its degradation

AbstractCystic fibrosis is mainly caused by mutations that interfere with the biosynthetic folding of the cystic fibrosis transmembrane conductance regulator (CFTR) protein. The aim of this study was to find cellular proteins interacting with CFTR and regulating its processing. We have used a genetic screen in yeast to identify such proteins and identified CSN5 that interacted with the third cytoplasmic loop of CFTR. CSN5 is the 5th component of the COP9 signalosome, a complex of eight subunits that shares significant homologies to the lid subcomplex of the 26S proteasome and controls the stability of many proteins. The present study shows that CSN5 associates with the core-glycosylated form of CFTR and suggests that this association targets misfolded CFTR to the degradative pathway. Identifying CSN5 as a new component of the degradative pathway is an important step towards the goal of unraveling the sorting between misfolded and correctly folded CFTR proteins

COMPARAÇÃO DE TRATAMENTOS MEDICAMENTOSOS EM PACIENTES INTERNADOS COM COVID19

This systematic review aims to compare the drugs used for the treatment of COVID-19 in diagnosed and hospitalized patients. The search in the databases generated 97 references, which after the selection and eligibility process, 4 systematic reviews (SR) were selected and used in this narrative synthesis where their data were extracted. The AMSTAR 2 tool was used in the evaluation of methodological quality. The options were grouped according to the adopted interventions: Tocilizumab, Vitamin D, and Atorvastatin. It is concluded that the study has limitations in its methodology, and the results should be analyzed with caution. The presented options need to describe the standard treatment used. Tocilizumab appears to be the best choice in concurrent use with standard treatment.Esta revisão sistemática tem por objetivo comparar os medicamentos utilizados para tratamento da covid19 em pacientes diagnosticados com a doença e internados. A busca nas bases e dados gerou 97 referências, que após o processo de seleção e elegibilidade, foram selecionadas 4 revisões sistemáticas (RS) utilizadas nesta síntese narrativa onde seus dados foram extraídos. A ferramenta AMSTAR 2 foi utilizada na avaliação da qualidade metodológica. As opções foram agrupadas de acordo com as intervenções adotadas: Tociluzumabe, vitamina D e Atorvastatina. Conclui-se que o estudo possui limitações em sua metodologia, devendo os resultados serem analisados com prudência. As opções apresentadas necessitam descrever o tratamento padrão utilizado. O tociluzumabe se mostra a melhor escolha em uso concomitante com o tratamento padrão

Statistical Workflow for Feature Selection in Human Metabolomics Data.

High-throughput metabolomics investigations, when conducted in large human cohorts, represent a potentially powerful tool for elucidating the biochemical diversity underlying human health and disease. Large-scale metabolomics data sources, generated using either targeted or nontargeted platforms, are becoming more common. Appropriate statistical analysis of these complex high-dimensional data will be critical for extracting meaningful results from such large-scale human metabolomics studies. Therefore, we consider the statistical analytical approaches that have been employed in prior human metabolomics studies. Based on the lessons learned and collective experience to date in the field, we offer a step-by-step framework for pursuing statistical analyses of cohort-based human metabolomics data, with a focus on feature selection. We discuss the range of options and approaches that may be employed at each stage of data management, analysis, and interpretation and offer guidance on the analytical decisions that need to be considered over the course of implementing a data analysis workflow. Certain pervasive analytical challenges facing the field warrant ongoing focused research. Addressing these challenges, particularly those related to analyzing human metabolomics data, will allow for more standardization of as well as advances in how research in the field is practiced. In turn, such major analytical advances will lead to substantial improvements in the overall contributions of human metabolomics investigations