10,767 research outputs found

    FairGen: Towards Fair Graph Generation

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    There have been tremendous efforts over the past decades dedicated to the generation of realistic graphs in a variety of domains, ranging from social networks to computer networks, from gene regulatory networks to online transaction networks. Despite the remarkable success, the vast majority of these works are unsupervised in nature and are typically trained to minimize the expected graph reconstruction loss, which would result in the representation disparity issue in the generated graphs, i.e., the protected groups (often minorities) contribute less to the objective and thus suffer from systematically higher errors. In this paper, we aim to tailor graph generation to downstream mining tasks by leveraging label information and user-preferred parity constraint. In particular, we start from the investigation of representation disparity in the context of graph generative models. To mitigate the disparity, we propose a fairness-aware graph generative model named FairGen. Our model jointly trains a label-informed graph generation module and a fair representation learning module by progressively learning the behaviors of the protected and unprotected groups, from the `easy' concepts to the `hard' ones. In addition, we propose a generic context sampling strategy for graph generative models, which is proven to be capable of fairly capturing the contextual information of each group with a high probability. Experimental results on seven real-world data sets, including web-based graphs, demonstrate that FairGen (1) obtains performance on par with state-of-the-art graph generative models across six network properties, (2) mitigates the representation disparity issues in the generated graphs, and (3) substantially boosts the model performance by up to 17% in downstream tasks via data augmentation

    Neural Architecture Search: Insights from 1000 Papers

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    In the past decade, advances in deep learning have resulted in breakthroughs in a variety of areas, including computer vision, natural language understanding, speech recognition, and reinforcement learning. Specialized, high-performing neural architectures are crucial to the success of deep learning in these areas. Neural architecture search (NAS), the process of automating the design of neural architectures for a given task, is an inevitable next step in automating machine learning and has already outpaced the best human-designed architectures on many tasks. In the past few years, research in NAS has been progressing rapidly, with over 1000 papers released since 2020 (Deng and Lindauer, 2021). In this survey, we provide an organized and comprehensive guide to neural architecture search. We give a taxonomy of search spaces, algorithms, and speedup techniques, and we discuss resources such as benchmarks, best practices, other surveys, and open-source libraries

    Deep Transfer Learning Applications in Intrusion Detection Systems: A Comprehensive Review

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    Globally, the external Internet is increasingly being connected to the contemporary industrial control system. As a result, there is an immediate need to protect the network from several threats. The key infrastructure of industrial activity may be protected from harm by using an intrusion detection system (IDS), a preventive measure mechanism, to recognize new kinds of dangerous threats and hostile activities. The most recent artificial intelligence (AI) techniques used to create IDS in many kinds of industrial control networks are examined in this study, with a particular emphasis on IDS-based deep transfer learning (DTL). This latter can be seen as a type of information fusion that merge, and/or adapt knowledge from multiple domains to enhance the performance of the target task, particularly when the labeled data in the target domain is scarce. Publications issued after 2015 were taken into account. These selected publications were divided into three categories: DTL-only and IDS-only are involved in the introduction and background, and DTL-based IDS papers are involved in the core papers of this review. Researchers will be able to have a better grasp of the current state of DTL approaches used in IDS in many different types of networks by reading this review paper. Other useful information, such as the datasets used, the sort of DTL employed, the pre-trained network, IDS techniques, the evaluation metrics including accuracy/F-score and false alarm rate (FAR), and the improvement gained, were also covered. The algorithms, and methods used in several studies, or illustrate deeply and clearly the principle in any DTL-based IDS subcategory are presented to the reader

    Estudo da remodelagem reversa miocárdica através da análise proteómica do miocárdio e do líquido pericárdico

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    Valve replacement remains as the standard therapeutic option for aortic stenosis patients, aiming at abolishing pressure overload and triggering myocardial reverse remodeling. However, despite the instant hemodynamic benefit, not all patients show complete regression of myocardial hypertrophy, being at higher risk for adverse outcomes, such as heart failure. The current comprehension of the biological mechanisms underlying an incomplete reverse remodeling is far from complete. Furthermore, definitive prognostic tools and ancillary therapies to improve the outcome of the patients undergoing valve replacement are missing. To help abridge these gaps, a combined myocardial (phospho)proteomics and pericardial fluid proteomics approach was followed, taking advantage of human biopsies and pericardial fluid collected during surgery and whose origin anticipated a wealth of molecular information contained therein. From over 1800 and 750 proteins identified, respectively, in the myocardium and in the pericardial fluid of aortic stenosis patients, a total of 90 dysregulated proteins were detected. Gene annotation and pathway enrichment analyses, together with discriminant analysis, are compatible with a scenario of increased pro-hypertrophic gene expression and protein synthesis, defective ubiquitinproteasome system activity, proclivity to cell death (potentially fed by complement activity and other extrinsic factors, such as death receptor activators), acute-phase response, immune system activation and fibrosis. Specific validation of some targets through immunoblot techniques and correlation with clinical data pointed to complement C3 β chain, Muscle Ring Finger protein 1 (MuRF1) and the dual-specificity Tyr-phosphorylation regulated kinase 1A (DYRK1A) as potential markers of an incomplete response. In addition, kinase prediction from phosphoproteome data suggests that the modulation of casein kinase 2, the family of IκB kinases, glycogen synthase kinase 3 and DYRK1A may help improve the outcome of patients undergoing valve replacement. Particularly, functional studies with DYRK1A+/- cardiomyocytes show that this kinase may be an important target to treat cardiac dysfunction, provided that mutant cells presented a different response to stretch and reduced ability to develop force (active tension). This study opens many avenues in post-aortic valve replacement reverse remodeling research. In the future, gain-of-function and/or loss-of-function studies with isolated cardiomyocytes or with animal models of aortic bandingdebanding will help disclose the efficacy of targeting the surrogate therapeutic targets. Besides, clinical studies in larger cohorts will bring definitive proof of complement C3, MuRF1 and DYRK1A prognostic value.A substituição da válvula aórtica continua a ser a opção terapêutica de referência para doentes com estenose aórtica e visa a eliminação da sobrecarga de pressão, desencadeando a remodelagem reversa miocárdica. Contudo, apesar do benefício hemodinâmico imediato, nem todos os pacientes apresentam regressão completa da hipertrofia do miocárdio, ficando com maior risco de eventos adversos, como a insuficiência cardíaca. Atualmente, os mecanismos biológicos subjacentes a uma remodelagem reversa incompleta ainda não são claros. Além disso, não dispomos de ferramentas de prognóstico definitivos nem de terapias auxiliares para melhorar a condição dos pacientes indicados para substituição da válvula. Para ajudar a resolver estas lacunas, uma abordagem combinada de (fosfo)proteómica e proteómica para a caracterização, respetivamente, do miocárdio e do líquido pericárdico foi seguida, tomando partido de biópsias e líquidos pericárdicos recolhidos em ambiente cirúrgico. Das mais de 1800 e 750 proteínas identificadas, respetivamente, no miocárdio e no líquido pericárdico dos pacientes com estenose aórtica, um total de 90 proteínas desreguladas foram detetadas. As análises de anotação de genes, de enriquecimento de vias celulares e discriminativa corroboram um cenário de aumento da expressão de genes pro-hipertróficos e de síntese proteica, um sistema ubiquitina-proteassoma ineficiente, uma tendência para morte celular (potencialmente acelerada pela atividade do complemento e por outros fatores extrínsecos que ativam death receptors), com ativação da resposta de fase aguda e do sistema imune, assim como da fibrose. A validação de alguns alvos específicos através de immunoblot e correlação com dados clínicos apontou para a cadeia β do complemento C3, a Muscle Ring Finger protein 1 (MuRF1) e a dual-specificity Tyr-phosphoylation regulated kinase 1A (DYRK1A) como potenciais marcadores de uma resposta incompleta. Por outro lado, a predição de cinases a partir do fosfoproteoma, sugere que a modulação da caseína cinase 2, a família de cinases do IκB, a glicogénio sintase cinase 3 e da DYRK1A pode ajudar a melhorar a condição dos pacientes indicados para intervenção. Em particular, a avaliação funcional de cardiomiócitos DYRK1A+/- mostraram que esta cinase pode ser um alvo importante para tratar a disfunção cardíaca, uma vez que os miócitos mutantes responderam de forma diferente ao estiramento e mostraram uma menor capacidade para desenvolver força (tensão ativa). Este estudo levanta várias hipóteses na investigação da remodelagem reversa. No futuro, estudos de ganho e/ou perda de função realizados em cardiomiócitos isolados ou em modelos animais de banding-debanding da aorta ajudarão a testar a eficácia de modular os potenciais alvos terapêuticos encontrados. Além disso, estudos clínicos em coortes de maior dimensão trarão conclusões definitivas quanto ao valor de prognóstico do complemento C3, MuRF1 e DYRK1A.Programa Doutoral em Biomedicin

    Targeting Fusion Proteins of HIV-1 and SARS-CoV-2

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    Viruses are disease-causing pathogenic agents that require host cells to replicate. Fusion of host and viral membranes is critical for the lifecycle of enveloped viruses. Studying viral fusion proteins can allow us to better understand how they shape immune responses and inform the design of therapeutics such as drugs, monoclonal antibodies, and vaccines. This thesis discusses two approaches to targeting two fusion proteins: Env from HIV-1 and S from SARS-CoV-2. The first chapter of this thesis is an introduction to viruses with a specific focus on HIV-1 CD4 mimetic drugs and antibodies against SARS-CoV-2. It discusses the architecture of these viruses and fusion proteins and how small molecules, peptides, and antibodies can target these proteins successfully to treat and prevent disease. In addition, a brief overview is included of the techniques involved in structural biology and how it has informed the study of viruses. For the interested reader, chapter 2 contains a review article that serves as a more in-depth introduction for both viruses as well as how the use of structural biology has informed the study of viral surface proteins and neutralizing antibody responses to them. The subsequent chapters provide a body of work divided into two parts. The first part in chapter 3 involves a study on conformational changes induced in the HIV-1 Env protein by CD4-mimemtic drugs using single particle cryo-EM. The second part encompassing chapters 4 and 5 includes two studies on antibodies isolated from convalescent COVID-19 donors. The former involves classification of antibody responses to the SARS-CoV-2 S receptor-binding domain (RBD). The latter discusses an anti-RBD antibody class that binds to a conserved epitope on the RBD and shows cross-binding and cross-neutralization to other coronaviruses in the sarbecovirus subgenus.</p

    DIN Spec 91345 RAMI 4.0 compliant data pipelining: An approach to support data understanding and data acquisition in smart manufacturing environments

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    Today, data scientists in the manufacturing domain are confronted with a set of challenges associated to data acquisition as well as data processing including the extraction of valuable in-formation to support both, the work of the manufacturing equipment as well as the manufacturing processes behind it. One essential aspect related to data acquisition is the pipelining, including various commu-nication standards, protocols and technologies to save and transfer heterogenous data. These circumstances make it hard to understand, find, access and extract data from the sources depend-ing on use cases and applications. In order to support this data pipelining process, this thesis proposes the use of the semantic model. The selected semantic model should be able to describe smart manufacturing assets them-selves as well as to access their data along their life-cycle. As a matter of fact, there are many research contributions in smart manufacturing, which already came out with reference architectures or standards for semantic-based meta data descrip-tion or asset classification. This research builds upon these outcomes and introduces a novel se-mantic model-based data pipelining approach using as a basis the Reference Architecture Model for Industry 4.0 (RAMI 4.0).Hoje em dia, os cientistas de dados no domínio da manufatura são confrontados com várias normas, protocolos e tecnologias de comunicação para gravar, processar e transferir vários tipos de dados. Estas circunstâncias tornam difícil compreender, encontrar, aceder e extrair dados necessários para aplicações dependentes de casos de utilização, desde os equipamentos aos respectivos processos de manufatura. Um aspecto essencial poderia ser um processo de canalisação de dados incluindo vários normas de comunicação, protocolos e tecnologias para gravar e transferir dados. Uma solução para suporte deste processo, proposto por esta tese, é a aplicação de um modelo semântico que descreva os próprios recursos de manufactura inteligente e o acesso aos seus dados ao longo do seu ciclo de vida. Muitas das contribuições de investigação em manufatura inteligente já produziram arquitecturas de referência como a RAMI 4.0 ou normas para a descrição semântica de meta dados ou classificação de recursos. Esta investigação baseia-se nestas fontes externas e introduz um novo modelo semântico baseado no Modelo de Arquitectura de Referência para Indústria 4.0 (RAMI 4.0), em conformidade com a abordagem de canalisação de dados no domínio da produção inteligente como caso exemplar de utilização para permitir uma fácil exploração, compreensão, descoberta, selecção e extracção de dados

    Desarrollo de una herramienta integral de gestión de gases de efecto invernadero para la toma de decisión contra el cambio climático a nivel regional y local en la Comunitat Valenciana

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    Tesis por compendio[ES] Actualmente, los responsables de tomar decisiones contra el cambio climático carecen de herramientas para desarrollar inventarios de emisiones de gases de efecto invernadero (GEI) con suficiente rigor científico-técnico y precisión para priorizar e invertir los recursos disponibles de manera eficiente en las medidas necesarias para luchar contra el cambio climático. Por ello, en esta tesis se expone el desarrollo de un sistema de información territorial y sectorial (SITE) para monitorear las emisiones de GEI que sirva como herramienta de gobernanza climática local y regional. SITE combina las ventajas de los enfoques metodológicos descendente o top-down (de arriba hacia abajo) y ascendente o bottom-up (de abajo hacia arriba), para lograr un enfoque híbrido innovador para contabilizar y gestionar de manera eficiente las emisiones de GEI. Por tanto, en esta tesis se definen los diferentes desarrollos metodológicos, tanto generales como específicos de sectores clave del Panel Intergubernamental de Cambio Climático (IPPC) (edificación, transporte, sector forestal, etc.), un desarrollo informático para la parte de SITE que se ejecuta del lado del servidor, que de ahora en adelante denominaremos back-end del sistema, y siete implementaciones como casos de estudio representativos, a diferentes escalas y aplicados sobre diferentes sectores. Estas implementaciones a diferentes escalas y sectores demuestran el potencial del sistema como herramienta de apoyo en la toma de decisión contra el cambio climático a nivel regional y local. Las diferentes implementaciones en casos piloto representativos, tanto a nivel regional en la Comunitat Valenciana como a nivel local en municipios grandes (València) y medianos (Quart de Poblet y Llíria) muestran el potencial de adaptación territorial y sectorial que tiene la herramienta. Las metodologías desarrolladas para los sectores específicos de tráfico rodado, edificación o sector forestal, ofrecen cuantificaciones con una resolución espacial con gran capacidad de optimizar las políticas locales y regionales. Por tanto, la herramienta cuenta con un gran potencial de escalabilidad y gran capacidad de mejora continua mediante la inclusión de nuevos enfoques metodológicos, adaptación de las metodologías a la disponibilidad de datos, metodologías concretas para sectores clave y actualización a las mejores metodologías disponibles derivadas de actividades de investigación de la comunidad científica.[CA] Actualment, els responsables de prendre decisions contra el canvi climàtic no tenen eines per aconseguir inventaris d'emissions de gasos d'efecte hivernacle (GEH) amb prou cientificotècnic rigor, precisió i integritat per invertir els recursos disponibles de manera eficient en les mesures necessàries contra el canvi climàtic. Per això, en aquesta tesis se exposa el desenvolupa un sistema d'informació territorial i sectorial (SITE) per monitoritzar les emissions de GEH com a eina de governança climàtica local i regional. Aquest sistema combina els avantatges dels enfocaments metodològics descendent o top-down (de dalt a baix) i ascendent o bottom-up (de baix a dalt), per aconseguir un enfocament híbrid innovador per comptabilitzar i gestionar de manera eficient les emissions de GEH. Per tant, en aquesta tesi doctoral es descriuen els diferents desenvolupaments metodològics, tant generals com específics de sectors clau del Panel Intergovernamental contra el Canvi Climàtic (edificació, transport, forestal, etc.), un desenvolupament informàtic per al back-end del sistema i set implementacions com a casos d'estudi representatius, a diferents escales, amb els diferents enfocaments metodològics i aplicats sobre diferents sectors. Això queda descrit en sis capítols. Aquestes implementacions a diferents escales i sectors demostren el potencial del sistema com a eina de suport en la presa de decisió contra el canvi climàtic a nivell regional i local. Les diferents implementacions en casos pilot representatius, tant a nivell regional a la Comunitat Valenciana com a nivell local en municipis grans (València) i mitjans (Quart de Poblet i Llíria,) mostren el potencial d'adaptació territorial i sectorial que té l'eina. Les metodologies desenvolupades per als sectors específics de trànsit rodat, edificació i forestal, ofereixen quantificacions amb una resolució espacial amb gran capacitat d'optimitzar les polítiques locals i regionals. Per tant, l'eina compta amb un gran potencial d'escalabilitat i gran capacitat de millora contínua mitjançant la inclusió de nous enfocaments metodològics, adaptació de les metodologies a la disponibilitat de dades, metodologies concretes per a sectors clau, i actualització a les millors metodologies disponibles derivades de activitats de investigació de la comunitat científica.[EN] Currently, regional and local decision-makers lack of tools to achieve greenhouse gases (GHG) emissions inventories with enough rigor, accuracy and completeness in order to prioritize available resources efficiently against climate change. Thus, in this thesis the development of a territorial and sectoral information system (SITE) to monitor GHG emissions as a local and regional climate governance tool is exposed. This system combines the advantages of both, top-down and bottom-up approaches, to achieve an innovative hybrid approach to account and manage efficiently GHG emissions. Furthermore, this thesis defines the methodologies developed, a computer proposal for the back-end of the system and seven implementations as representative case studies at different scales (local and regional level), with the different methodological approaches and applied to different sectors. Thus, these implementations demonstrate the potential of the system as decision-making tool against climate change at the regional and local level as climate governance tool. The different implementations in representative pilot cases, both at the regional level in the Valencian Community and at the local level in large (Valencia) and medium-sized municipalities (Quart de Poblet and Llíria) demonstrate the potential for territorial and sectoral adaptation of the system developed. The methodologies developed for the specific sectors of road transport, building and forestry, offer quantifications with a spatial resolution with a great capacity to optimize local and regional policies. Therefore, the tool has a great potential for scalability and a great capacity for continuous improvement through the inclusion of new methodological approaches, adapting the methodologies to the availability of data, specific methodologies for key sectors, and updating to the best methodologies available in the scientific community.Lorenzo Sáez, E. (2022). Desarrollo de una herramienta integral de gestión de gases de efecto invernadero para la toma de decisión contra el cambio climático a nivel regional y local en la Comunitat Valenciana [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/181662TESISCompendi
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