SNEkhorn: Dimension Reduction with Symmetric Entropic Affinities

Many approaches in machine learning rely on a weighted graph to encode the similarities between samples in a dataset. Entropic affinities (EAs), which are notably used in the popular Dimensionality Reduction (DR) algorithm t-SNE, are particular instances of such graphs. To ensure robustness to heterogeneous sampling densities, EAs assign a kernel bandwidth parameter to every sample in such a way that the entropy of each row in the affinity matrix is kept constant at a specific value, whose exponential is known as perplexity. EAs are inherently asymmetric and row-wise stochastic, but they are used in DR approaches after undergoing heuristic symmetrization methods that violate both the row-wise constant entropy and stochasticity properties. In this work, we uncover a novel characterization of EA as an optimal transport problem, allowing a natural symmetrization that can be computed efficiently using dual ascent. The corresponding novel affinity matrix derives advantages from symmetric doubly stochastic normalization in terms of clustering performance, while also effectively controlling the entropy of each row thus making it particularly robust to varying noise levels. Following, we present a new DR algorithm, SNEkhorn, that leverages this new affinity matrix. We show its clear superiority to state-of-the-art approaches with several indicators on both synthetic and real-world datasets

Surface blistering and flaking of sintered uranium dioxide samples under high dose gas implantation and annealing

International audienceHigh helium contents will be generated within minor actinide doped uranium dioxide blankets which could be used in fourth generation reactors. In this framework, it is essential to improve our understanding of the type of damage which a pellet could incur as a result of extensive helium build-up. This paper is an attempt at tackling this issue. Sintered uranium dioxide disks have been implanted with helium ions then annealed at various temperatures. Above a concentration of 0.4 at.% and above 1000°C, optical images of the sample surface revealed swollen grains and extensive areas which have exfoliated. Nuclear reaction microanalyses and atomic force microscopy observations were performed to demonstrate that helium has substantially precipitated within the swollen grains. Massive precipitation of the gas leads under these conditions to sample surface blistering which appears to precede flaking. Deuterium ion irradiations have also been performed at ambient and a direct flaking of the sample surface was observed, but for this phenomenon to be observed required much higher doses than in the He study, indicating that temperature could be an essential ingredient for gas to migrate and cause extensive precipitation. Such phenomena could possibly lead to degradation of the fuel

The future of wildlife conservation funding: What options do U.S. college students support?

Insufficient funding is a major impediment to conservation efforts around the world. In the United States, a decline in hunting participation threatens sustainability of the “user-pay, public benefit” model that has supported wildlife conservation for nearly 100 years, forcing wildlife management agencies to contemplate alternative funding strategies. We investigated support for potential funding options among diverse college students, a rapidly expanding and politically active voting bloc with a potentially powerful influence on the future of conservation. From 2018 to 2020, we surveyed 17,203 undergraduate students at public universities across 22 states. Students preferred innovative approaches to conservation funding, with 72% supporting funding derived from industry sources (e.g., natural resource extraction companies), 63% supporting state sources (e.g., general sales tax), and 43% supporting conventional user-based sources such as license fees and excise taxes associated with outdoor recreation activities (e.g., hunting). Findings emphasize the need to broaden the base of support for conservation funding and highlight the importance of considering the preferences and perspectives of young adults and other diverse beneficiaries of wildlife conservation

Escuela de principes y cavalleros : primera [-segunda] parte ...

V. I : Escuela de principes y cavalleros: primera parte, que contiene la geografia, y la retorica / compuesta por el Señor de la Mota Levayer ... ; sacada en toscano por el abad Scipion Alerano ... ; y nuevamente traducida en lengua española ... por el P. Fr. Alonso Manrique ... -- Barcelona : en la imprenta de Carlos Sapéra, y Jayme Ossét ... : a costa de los dichos y Compañía, 1752 . -- [22], 242, [13] p., [1] p. en bl. -- Sign. : [ ]1, [parágrafo]6, [2parágrafo]4, A-Q8 ----------- V. II : Escuela de principes y cavalleros : segunda parte, que contiene la moral, economica, politica, logica, y fisica / compuesta por el Señor de la Mota Levayer ... ; sacada en toscano por el abad Scipion Alerano ... ; y nuevamente traducida en lengua española ... por el P. Fr. Alonso Manrique ... -- Barcelona : en la imprenta de Carlos Sapéra, y Jayme Ossét ... : a costa de los dichos y Compañía, [s.a.] . -- 334 [i.e. 344] p. -- Sign. : A-X8, Y4 . -- Error de pag. en última pág.Copia digital. Madrid : Ministerio de Educación, Cultura y Deporte. Subdirección General de Coordinación Bibliotecaria, 2016Antep. en t. 1Cada tomo con port. propi

Mapping Drug Physico-Chemical Features to Pathway Activity Reveals Molecular Networks Linked to Toxicity Outcome

The identification of predictive biomarkers is at the core of modern toxicology. So far, a number of approaches have been proposed. These rely on statistical inference of toxicity response from either compound features (i.e., QSAR), in vitro cell based assays or molecular profiling of target tissues (i.e., expression profiling). Although these approaches have already shown the potential of predictive toxicology, we still do not have a systematic approach to model the interaction between chemical features, molecular networks and toxicity outcome. Here, we describe a computational strategy designed to address this important need. Its application to a model of renal tubular degeneration has revealed a link between physico-chemical features and signalling components controlling cell communication pathways, which in turn are differentially modulated in response to toxic chemicals. Overall, our findings are consistent with the existence of a general toxicity mechanism operating in synergy with more specific single-target based mode of actions (MOAs) and provide a general framework for the development of an integrative approach to predictive toxicology