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There is no shortage of articles and books exploring women’s underrepresentation in science. Everyone is interested--academics, politicians, parents, high school girls (and boys), women in search of college majors, administrators working to accommodate women’s educational interests; the list goes on. But one thing often missing is an evidence-based examination of the problem, uninfluenced by personal opinions, accounts of “lived experiences,” anecdotes, and the always-encroaching inputs of popular culture. This is why this special issue of Frontiers in Psychology can make a difference. In it, a diverse group of authors and researchers with even more diverse viewpoints find themselves united by their empirical, objective approaches to understanding women’s underrepresentation in science today. The questions considered within this special issue span academic disciplines, methods, levels of analysis, and nature of analysis; what these article share is their scholarly, evidence-based approach to understanding a key issue of our time.

stereotypes --- women in science --- Bias --- leaky pipeline --- sex differences

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This book presents a selection of papers representing current research on using field programmable gate arrays (FPGAs) for realising image processing algorithms. These papers are reprints of papers selected for a Special Issue of the Journal of Imaging on image processing using FPGAs. A diverse range of topics is covered, including parallel soft processors, memory management, image filters, segmentation, clustering, image analysis, and image compression. Applications include traffic sign recognition for autonomous driving, cell detection for histopathology, and video compression. Collectively, they represent the current state-of-the-art on image processing using FPGAs.

nuclei detection --- System-on-Chip --- FPGA --- K-Means --- hardware acceleration --- image analysis --- perceptual coding --- line buffer --- heterogeneous computing --- window filters --- processor architectures --- hardware accelerators --- stream processing --- embedded systems --- image processing pipeline --- image processing --- generalized Laplacian of Gaussian filter --- background estimation --- real-time systems --- FPGA implementation --- hardware architecture --- compression --- image borders --- memory --- zig-zag scan --- histopathology --- just-noticeable difference (JND) --- memory management --- downsampling --- image segmentation --- feature extraction --- design --- mean Shift clustering --- high-throughput --- segmentation --- streaming architecture --- power --- D-SWIM --- hardware/software co-design --- high-level synthesis --- contrast masking --- texture detection --- pipeline --- field programmable gate array (FPGA) --- JPEG-LS --- low-latency --- connected components analysis --- luminance masking --- field programmable gate arrays (FPGA)

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This open access book as one of the fastest-growing areas of research in machine learning, metalearning studies principled methods to obtain efficient models and solutions by adapting machine learning and data mining processes. This adaptation usually exploits information from past experience on other tasks and the adaptive processes can involve machine learning approaches. As a related area to metalearning and a hot topic currently, automated machine learning (AutoML) is concerned with automating the machine learning processes. Metalearning and AutoML can help AI learn to control the application of different learning methods and acquire new solutions faster without unnecessary interventions from the user. This book offers a comprehensive and thorough introduction to almost all aspects of metalearning and AutoML, covering the basic concepts and architecture, evaluation, datasets, hyperparameter optimization, ensembles and workflows, and also how this knowledge can be used to select, combine, compose, adapt and configure both algorithms and models to yield faster and better solutions to data mining and data science problems. It can thus help developers to develop systems that can improve themselves through experience. This book is a substantial update of the first edition published in 2009. It includes 18 chapters, more than twice as much as the previous version. This enabled the authors to cover the most relevant topics in more depth and incorporate the overview of recent research in the respective area. The book will be of interest to researchers and graduate students in the areas of machine learning, data mining, data science and artificial intelligence. ; Metalearning is the study of principled methods that exploit metaknowledge to obtain efficient models and solutions by adapting machine learning and data mining processes. While the variety of machine learning and data mining techniques now available can, in principle, provide good model solutions, a methodology is still needed to guide the search for the most appropriate model in an efficient way. Metalearning provides one such methodology that allows systems to become more effective through experience. This book discusses several approaches to obtaining knowledge concerning the performance of machine learning and data mining algorithms. It shows how this knowledge can be reused to select, combine, compose and adapt both algorithms and models to yield faster, more effective solutions to data mining problems. It can thus help developers improve their algorithms and also develop learning systems that can improve themselves. The book will be of interest to researchers and graduate students in the areas of machine learning, data mining and artificial intelligence.

Artificial intelligence --- Data mining --- Machine learning --- Metalearning --- Automating Machine Learning (AutoML) --- Machine Learning --- Artificial Intelligence --- algorithm selection --- algorithm recommendation --- algorithm configuration --- hyperparameter optimization --- automating the workflow/pipeline design --- metalearning in ensemble construction --- metalearning in deep neural networks --- transfer learning --- algorithm recommendation for data streams --- automating data science --- Open Access

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With rapid developments being made in the exploration of marine resources, coastal geohazard and offshore geotechnics have attracted a great deal of attention from coastal geotechnical engineers, with significant progress being made in recent years. Due to the complicated nature of marine environmnets, there are numerous natural marine geohazard preset throughout the world’s marine areas, e.g., the South China Sea. In addition, damage to offshore infrastructure (e.g., monopiles, bridge piers, etc.) and their supporting installations (pipelines, power transmission cables, etc.) has occurred in the last decades. A better understanding of the fundamental mechanisms and soil behavior of the seabed in marine environments will help engineers in the design and planning processes of coastal geotechnical engineering projects. The purpose of this book is to present the recent advances made in the field of coastal geohazards and offshore geotechnics. The book will provide researchers with information reagrding the recent developments in the field, and possible future developments. The book is composed of eighteen papers, covering three main themes: (1) the mechanisms of fluid–seabed interactions and the instability associated with seabeds when they are under dynamic loading (papers 1–5); (2) evaluation of the stability of marine infrastructure, including pipelines (papers 6–8), piled foundation and bridge piers (papers 9–12), submarine tunnels (paper 13), and other supported foundations (paper 14); and (3) coastal geohazards, including submarine landslides and slope stability (papers 15–16) and other geohazard issues (papers 17–18). The editors hope that this book will functoin as a guide for researchers, scientists, and scholars, as well as practitioners of coastal and offshore engineering.

wave motion --- offshore deposits --- seabed response --- FEM --- pore pressure --- wave-current-seabed interaction --- RANS equations --- k-ε model --- current velocity --- seabed liquefaction --- liquefaction --- lateral displacement --- response surface method (RSM) --- artificial neural network (ANN) --- wave action --- silty sand --- seepage flow --- soil erosion --- pore-pressure accumulation --- three-phase soil model --- immersed tunnel --- trench --- numerical study --- porous seabed --- pumping well test --- groundwater fluctuation --- stratum deformation --- micro-confined aquifer --- wave–current–seabed interaction --- Reynolds-Averaged Navier-Stokesequations --- buried pipeline --- k-ε turbulence model --- oscillatory liquefaction --- wave-soil-pipeline interactions --- meshfree model --- local radial basis functions collocation method --- hydrate-bearing sediments --- damage statistical constitutive model --- multi-field coupling --- wellbore stability --- bridge scour --- identification --- ambient vibration --- field application --- natural frequency --- mode shape --- superstructure --- cable-stayed bridge --- Principal stress rotation --- dynamic loading --- wave (current)-induced soil response --- open-ended pile --- soil plug --- offshore wind turbines --- lateral cyclic loading --- model test --- discrete element simulation --- rock-socketed piles --- monopiles --- impedances --- dynamic responses --- buoyancy --- bottom-supported foundation --- field test --- numerical analysis --- giant submarine landslides --- shelf break --- South China Sea --- Himalayan orogeny --- repeated submarine landslides --- coastal-embankment slope --- stability --- unsaturated soil --- multilayered --- matric suction --- random searching algorithm --- rainfall infiltration --- scour --- soft clay --- monopile --- stress history --- hypoplastic model --- submarine pipeline --- dense seabed foundation --- seismic dynamics --- resonance of submarine pipeline --- FSSI-CAS 2D --- n/a

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Carceral logics permeate our thinking about humans and nonhumans. We imagine that greater punishment will reduce crime and make society safer. We hope that more convictions and policing for animal crimes will keep animals safe and elevate their social status. The dominant approach to human-animal relations is governed by an unjust imbalance of power that subordinates or ignores the interest nonhumans have in freedom. In this volume Lori Gruen and Justin Marceau invite experts to provide insights into the complicated intersection of issues that arise in thinking about animal law, violence, mass incarceration, and social change. Advocates for enhancing the legal status of animals could learn a great deal from the history and successes (and failures) of other social movements. Likewise, social change lawyers, as well as animal advocates, might learn lessons from each other about the interconnections of oppression as they work to achieve liberation for all. This title is also available as Open Access on Cambridge Core.

Animal welfare --- Imprisonment --- Law and legislation --- Philosophy. --- Corrections --- Detention of persons --- Punishment --- Prison-industrial complex --- Prisons --- School-to-prison pipeline --- Confinement --- Incarceration --- Animals --- Abuse of animals --- Animal cruelty --- Animals, Cruelty to --- Animals, Protection of --- Animals, Treatment of --- Cruelty to animals --- Humane treatment of animals --- Kindness to animals --- Mistreatment of animals --- Neglect of animals --- Prevention of cruelty to animals --- Protection of animals --- Treatment of animals --- Welfare, Animal --- Social aspects --- Abuse of --- animal cruelty --- mass incarceration --- solitary confinement --- prisoner rights --- punishment --- animal abuse --- civil rights