Functional and metabolic dichotomy of murine γδ T cell subsets in cancer immunity

© 2020 The Authors. European Journal of Immunology published by Wiley-VCH GmbH. This is an open access article under the terms of the Creative Commons Attribution License.γδ T cells can display a plethora of immune functions, but recent studies have highlighted their importance, in multiple disease models, as sources of the pro-inflammatory cytokines, IL-17A (IL-17), and IFN-γ. These are produced by distinct murine effector γδ T cell subsets that diverge during thymic γδ T cell development. Among the multiple roles these subsets play in peripheral tissues, a striking dichotomy has emerged at tumor sites: whereas IFN-γ+ γδ T cells inhibit tumor cell growth, IL-17+ γδ T cells promote tumor progression and metastasis formation. In this review, we discuss the main lines of evidence, mostly from preclinical studies in mouse models, for this functional dichotomy in cancer immunity. We further highlight very recent advances in our understanding how metabolic sources and pathways can impact on the balance between IFN-γ+ and IL-17+ γδ T cells in the tumor microenvironment, which opens a new exciting avenue to explore toward the application of γδ T cells in cancer immunotherapy.Our work is supported by “la Caixa” Foundation’s Health Research Program, project HR18-00069; PAC-PRECISE LISBOA-01-0145-FEDER-016394, co-funded by FEDER (POR Lisboa 2020) and Fundação para a Ciência e a Tecnologia (Portugal); and N.L. received an EMBO long term fellowship (ALTF 752–2018).info:eu-repo/semantics/publishedVersio

Efficiently Estimating Survival Signature and Two-Terminal Reliability of Heterogeneous Networks through Multi-Objective Optimization

The two-terminal reliability problem is a classical reliability problem with applications in wired and wireless communication networks, electronic circuit design, computer networks, and electrical power distribution, among other systems. However, the two-terminal reliability problem is among the hardest combinatorial problems and is intractable for large, complex networks. Several exact methods to solve the two-terminal reliability problem have been proposed since the 1960s, but they have exponential time complexity in general. Hence, practical studies involving large network-type systems resort to approximation methods to estimate the system\u27s reliability. One attractive approach for quantifying the reliability of complex systems is to use signatures, but even signature-based approaches in computing exact network reliability may become computationally prohibitive as the number of components grows, and simulation-based approximations, such as Monte Carlo algorithms, are generally required. Nonetheless, the computation of the network\u27s signature poses a majorchallenge in terms of computational time, especially when considering large, heterogeneous networks. Motivated by this, we propose a MC-survival signature based method to estimate two-terminal reliability for heterogeneous networks through multi-objective optimization. We formulate the problem of estimating the multi-dimensional survival signature of a network with heterogeneous components as a repeated multi-objective maximum capacity path problem and we present a fast and memory-efficient, Dijkstra-like algorithm to solve it. To the best of our knowledge, this is the first work to point out the relationship between the multi-dimensional survival signature computation and a multi-objective optimization problem. We empirically validate our method and perform computational experiments to compare its performance against two other approaches. The results of the experiments shows that our method is much faster than the other two approaches and can be used with a larger number of replications so to improve the accuracy of the reliability estimation

Compostos satíricos em português: bases unidas em favor da criticidade

No presente trabalho, pretendemos demonstrar que, não raro, novas formações compostas surgem em contextos políticos por motivações estilísticas, fundamentalmente para expressar ironia, humor e crítica

Performing edge detection by difference of Gaussians using q-Gaussian kernels

In image processing, edge detection is a valuable tool to perform the extraction of features from an image. This detection reduces the amount of information to be processed, since the redundant information (considered less relevant) can be unconsidered. The technique of edge detection consists of determining the points of a digital image whose intensity changes sharply. This changes are due to the discontinuities of the orientation on a surface for example. A well known method of edge detection is the Difference of Gaussians (DoG). The method consists of subtracting two Gaussians, where a kernel has a standard deviation smaller than the previous one. The convolution between the subtraction of kernels and the input image results in the edge detection of this image. This paper introduces a method of extracting edges using DoG with kernels based on the q-Gaussian probability distribution, derived from the q-statistic proposed by Constantino Tsallis. To demonstrate the method's potential, we compare the introduced method with the traditional DoG using Gaussians kernels. The results showed that the proposed method can extract edges with more accurate details.Comment: 5 pages, 5 figures, IC-MSQUARE 201

Sistema de controle do trio automotivo por meio de SMS

A partir de 1990, o uso da tecnologia GSM nas redes de celulares alcançou um grande sucesso, difundindo-se de forma e tornando-se realmente um sistema de comunicação global. Com a utilização dessa tecnologia o presente trabalho busca o controle e monitoramento remoto do alarme automotivo e de todas as funções por ele gerenciadas, como a abertura e fechamento dos vidros, travamento e destravamento de portas e notificação da quebra do bloqueio eletrônico criado pelo alarme automotivo. Assim, o projeto apresenta um sistema capaz de monitorar e controlar as funções da central de alarme e fazer comunicação com o celular por meio de SMS. Para isso, incluiu-se no sistema um Shield GSM com o módulo SIM900. Tudo isso foi feito por meio de um microcontrolador Atmega328 inserido em um Arduino Un

Qualidade de software no desenvolvimento utilizando metodologias ágeis

Observando a engenharia de software sobre o prisma histórico, percebemos como o desenvolvimento de software evoluiu ao longo dos anos. O uso adequado da metodologia de desenvolvimento com as corretas configurações sempre foi o desafio. Além disso, sempre foi necessário a observação prática sobre o que funciona e o que não funciona, e sobre quais fatores afetam as diferentes variáveis do desenvolvimento de software. A mudança mais notável nos últimos 15 anos foi a introdução do paradigma ágil. Como em qualquer área é necessário o entendimento de seus componentes e relacionamentos, como um estudo empírico que evidencie o funcionamento do método em situações reais. Esse trabalho tem como objetivo investigar o tema qualidade de software sobre o contexto do desenvolvimento ágil, ou seja, estudar quais métricas e ferramentas de controle e garantia de qualidade são empregadas nesse contexto. Para tanto, realizou-se um estudo empírico, tipo survey, sobre as atividades de controle e garantia de qualidade utilizadas no processo de desenvolvimento. Assim sendo, foi possível observar que a qualidade de software é tema importante durante todo o ciclo de desenvolvimento ágil por meio de atividades essenciais de garantia de qualidade, como revisão e refatoração. O ambiente ágil é motivador e fortalece o engajamento das equipes de desenvolvimento, fatores que influenciam diretamente na qualidade final dos produtos

Bifurcations of the Riccati quadratic polynomial differential systems

In this paper, we characterize the global phase portrait of the Riccati quadratic polynomial differential system ẋ = α2(x), ẏ = ky2 + β1(x)y + γ2(x), with (x,y)∈R2, γ2(x) nonzero (otherwise the system is a Bernoulli differential system), k ≠ 0 (otherwise the system is a Liénard differential system), β1(x) a polynomial of degree at most 1, α2(x) and γ2(x) polynomials of degree at most 2, and the maximum of the degrees of α2(x) and ky2 + β1(x)y + γ2(x) is 2. We give the complete description of the phase portraits in the Poincaré disk (i.e. in the compactification of R2 adding the circle S1 of the infinity) modulo topological equivalence

Argumentation models and their use in corpus annotation: practice, prospects, and challenges

The study of argumentation is transversal to several research domains, from philosophy to linguistics, from the law to computer science and artificial intelligence. In discourse analysis, several distinct models have been proposed to harness argumentation, each with a different focus or aim. To analyze the use of argumentation in natural language, several corpora annotation efforts have been carried out, with a more or less explicit grounding on one of such theoretical argumentation models. In fact, given the recent growing interest in argument mining applications, argument-annotated corpora are crucial to train machine learning models in a supervised way. However, the proliferation of such corpora has led to a wide disparity in the granularity of the argument annotations employed. In this paper, we review the most relevant theoretical argumentation models, after which we survey argument annotation projects closely following those theoretical models. We also highlight the main simplifications that are often introduced in practice. Furthermore, we glimpse other annotation efforts that are not so theoretically grounded but instead follow a shallower approach. It turns out that most argument annotation projects make their own assumptions and simplifications, both in terms of the textual genre they focus on and in terms of adapting the adopted theoretical argumentation model for their own agenda. Issues of compatibility among argument-annotated corpora are discussed by looking at the problem from a syntactical, semantic, and practical perspective. Finally, we discuss current and prospective applications of models that take advantage of argument-annotated corpora

Machine learning methods for quality prediction in thermoplastics injection molding

© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksNowadays, competitiveness is a reality in all industrial fields and the plastic injection industry is not an exception. Due to the complex intrinsic changes that the parameters undergo during the injection process, it is essential to monitor the parameters that influence the quality of the final part to guarantee a superior quality of service provided to customers. Quality requirements impose the development of intelligent systems capable to detect defects in the produced parts. This article presents a first step towards building an intelligent system for classifying the quality of produced parts. The basic approach of this work is machine learning methods (Artificial Neural Networks and Support Vector Machines) and techniques that combine the two previous approaches (ensemble method). These are trained as classifiers to detect conformity or even defect types in parts. The data analyzed were collected at a plastic injection company in Portugal. The results show that these techniques are capable of incorporating the non-linear relationships between the process variables, which allows for a good accuracy ( ˜ 99%) in the identification of defects. Although these techniques present good accuracy, we show that taking into account the history of the last cycles and the use of combined techniques improves even further the performance. The approach presented in this article has a number of potential advantages for online predicting of parts quality in injection molding processes.This work was partially supported by the Spanish State Research Agency through the project CHLOE-GRAPH (PID2020-118649RB-l00) and by FCT—Portuguese Foundation for Science and Technology under project grant UIDB/00308/2020.Postprint (author's final draft