Sex and design in our evolutionary cousins: The perception of beauty in nature

Desde un enfoque evolutivo de la belleza, en este texto analizamos la expresión y la percepción de la belleza sexual en el reino animal. Los cerebros de los animales perciben la belleza y detectan las características del entorno que resultan más relevantes para su supervivencia. A lo largo de la evolución, los animales con reproducción sexual han explotado este proceso de detección para maximizar su atractivo para el sexo opuesto. Habitualmente, esto ha conllevado la aparición de comportamientos y rasgos de cortejo extremos. Estos son rasgos de belleza sexual. Combinando principios neurocientíficos y neuroestéticos modernos con otros provenientes de la biología evolutiva, tratamos de entender las bases biológicas y la evolución de la belleza en todos los animales, incluidos nosotros mismos.; Des d’un enfocament evolutiu de la bellesa, en aquest text analitzem l’expressió i la percepció de labellesa sexual en el regne animal. Els cervells dels animals perceben la bellesa i detecten les característiquesde l’entorn que resulten més rellevants per a la seua supervivència. Al llarg de l’evolució,els animals amb reproducció sexual han explotat aquest procés de detecció per a maximitzar el seuatractiu per a l’altre sexe. Habitualment, això ha comportat l’aparició de comportaments i trets defesteig extrems. Aquests són trets de bellesa sexual. Combinant principis neurocientífics i neuroestèticsmoderns amb altres provinents de la biologia evolutiva, tractem d’entendre les bases biològiquesi l’evolució de la bellesa en tots els animals, inclosos nosaltres mateixos.; Taking an evolutionary approach to the question of beauty, we discuss the expression and perception of sexual beauty across the animal kingdom. Animals experience beauty in their brains, and animal brains are tuned to features of the environment most relevant to their survival. Over evolutionary time, sexually reproducing animals have exploited that tuning to maximize their attractiveness to the opposite sex, often leading to extreme courtship traits and behaviors. These are the traits of sexual beauty. Combining modern principles of neuroscience and neuroaesthetics with established principles of evolutionary biology, we aim to understand the biological basis and evolution of beauty in all animals, including ourselves

MILEPOST GCC: machine learning based research compiler

International audienceTuning hardwired compiler optimizations for rapidly evolving hardware makes porting an optimizing compiler for each new platform extremely challenging. Our radical approach is to develop a modular, extensible, self-optimizing compiler that automatically learns the best optimization heuristics based on the behavior of the platform. In this paper we describe MILEPOST GCC, a machine-learning-based compiler that automatically adjusts its optimization heuristics to improve the execution time, code size, or compilation time of specific programs on different architectures. Our preliminary experimental results show that it is possible to considerably reduce execution time of the MiBench benchmark suite on a range of platforms entirely automatically

Using decision analysis to support proactive management of emerging infectious wildlife diseases

Despite calls for improved responses to emerging infectious diseases in wildlife, management is seldom considered until a disease has been detected in affected populations. Reactive approaches may limit the potential for control and increase total response costs. An alternative, proactive management framework can identify immediate actions that reduce future impacts even before a disease is detected, and plan subsequent actions that are conditional on disease emergence. We identify four main obstacles to developing proactive management strategies for the newly discovered salamander pathogen Batrachochytrium salamandrivorans (Bsal). Given that uncertainty is a hallmark of wildlife disease management and that associated decisions are often complicated by multiple competing objectives, we advocate using decision analysis to create and evaluate trade-offs between proactive (pre-emergence) and reactive (post-emergence) management options. Policy makers and natural resource agency personnel can apply principles from decision analysis to improve strategies for countering emerging infectious diseases

Sexual selection and speciation : a meta-analysis of comparative studies

Funding: T.J. is funded by the CNRS, M.G.R. by NERC (UK), T.C.M. by US NSF 2026334, and J.T. by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (Grant Agreement No. 101078021)Understanding the drivers of biodiversity is a central goal in evolutionary biology. In particular, sexual selection has long been proposed as a potential catalyst of speciation, but empirical evidence remains inconclusive. Here, we present a comprehensive meta-analysis synthesizing 145 effect sizes from 50 comparative studies testing the relationship between proxies of sexual selection and species diversity across the animal kingdom. Our results reveal a modest but consistent positive association (global effect size: r = 0.201; 95% confidence interval: 0.035–0.366), supporting the hypothesis that sexual selection contributes to speciation. However, the global effect size corresponds to an R2 of only 0.04, suggesting that sexual selection is not a dominant driver of speciation. We also uncover substantial heterogeneity among effect sizes, largely attributable to between-study variation and taxonomic affinities of effect sizes. Studies that fail to account for phylogenetic non-independence tend to report stronger effects. In contrast, other tested methodological and biological moderators, such as the proxies used to estimate the strength of sexual selection or proxies of speciation, do not explain the observed heterogeneity in effect sizes. Sensitivity analyses confirm the robustness of our results, and we find no signatures of publication bias. We highlight the need for broader taxonomic coverage and a greater focus on understudied mechanisms, such as post-copulatory sexual selection, to refine our understanding of the role of sexual selection in shaping species diversity.Peer reviewe

Discovery of Genetic Variation on Chromosome 5q22 Associated with Mortality in Heart Failure

Failure of the human heart to maintain sufficient output of blood for the demands of the body, heart failure, is a common condition with high mortality even with modern therapeutic alternatives. To identify molecular determinant

Adókedvezmények és a jövedelemváltozásokra adható válaszok

Az adórendszer az állampolgároknak az állam számára folyósított befizetéseit foglalja magában. A szociális biztonsági rendszer ugyanakkor az állampolgároknak fizetett állami juttatások összefoglalása. Mindegyik más szerepet tölt be a jövedelem-újraelosztásban. Bár már többször javasolták, hogy egyetlen juttatási rendszerben egységesítsék ezeket, az Egyesült Királyságban az adók és a juttatások – legalábbis napjainkig – általában megőrizték sajátos jellegüket, különböző szerepüket, külön adminisztrációjukat és eltérő jövedelemfelmérési módszereiket

Memorandum on Reopening the Dodd-Frank Act Section 956 Incentive Compensation Rule

Professor Michael Herz, along with four other administrative law professors, sent a letter to six agencies about legal options regarding a long-delayed rule aimed at executive compensation

Communication-Efficient Federated Learning via Robust Distributed Mean Estimation

Distributed Mean Estimation (DME) is a central building block in federated learning, where clients send local gradients to a parameter server for averaging and updating the model. Due to communication constraints, clients often use lossy compression techniques to compress the gradients, resulting in estimation inaccuracies. DME is more challenging when clients have diverse network conditions, such as constrained communication budgets and packet losses. In such settings, DME techniques often incur a significant increase in the estimation error leading to degraded learning performance. In this work, we propose a robust DME technique named EDEN that naturally handles heterogeneous communication budgets and packet losses. We derive appealing theoretical guarantees for EDEN and evaluate it empirically. Our results demonstrate that EDEN consistently improves over state-of-the-art DME techniques