High performance implementation of 3D FEM for nonlocal Poisson problem with different ball approximation strategies

Nonlocality brings many challenges to the implementation of finite element methods (FEM) for nonlocal problems, such as large number of queries and invoke operations on the meshes. Besides, the interactions are usually limited to Euclidean balls, so direct numerical integrals often introduce numerical errors. The issues of interactions between the ball and finite elements have to be carefully dealt with, such as using ball approximation strategies. In this paper, an efficient representation and construction methods for approximate balls are presented based on combinatorial map, and an efficient parallel algorithm is also designed for assembly of nonlocal linear systems. Specifically, a new ball approximation method based on Monte Carlo integrals, i.e., the fullcaps method, is also proposed to compute numerical integrals over the intersection region of an element with the ball

Doubly Flexible Estimation under Label Shift

In studies ranging from clinical medicine to policy research, complete data are usually available from a population $\mathscr{P}$, but the quantity of interest is often sought for a related but different population $\mathscr{Q}$ which only has partial data. In this paper, we consider the setting that both outcome $Y$ and covariate ${\bf X}$ are available from $\mathscr{P}$ whereas only ${\bf X}$ is available from $\mathscr{Q}$, under the so-called label shift assumption, i.e., the conditional distribution of ${\bf X}$ given $Y$ remains the same across the two populations. To estimate the parameter of interest in $\mathscr{Q}$ via leveraging the information from $\mathscr{P}$, the following three ingredients are essential: (a) the common conditional distribution of ${\bf X}$ given $Y$, (b) the regression model of $Y$ given ${\bf X}$ in $\mathscr{P}$, and (c) the density ratio of $Y$ between the two populations. We propose an estimation procedure that only needs standard nonparametric technique to approximate the conditional expectations with respect to (a), while by no means needs an estimate or model for (b) or (c); i.e., doubly flexible to the possible model misspecifications of both (b) and (c). This is conceptually different from the well-known doubly robust estimation in that, double robustness allows at most one model to be misspecified whereas our proposal can allow both (b) and (c) to be misspecified. This is of particular interest in our setting because estimating (c) is difficult, if not impossible, by virtue of the absence of the $Y$-data in $\mathscr{Q}$. Furthermore, even though the estimation of (b) is sometimes off-the-shelf, it can face curse of dimensionality or computational challenges. We develop the large sample theory for the proposed estimator, and examine its finite-sample performance through simulation studies as well as an application to the MIMIC-III database

Semantic Enhanced Knowledge Graph for Large-Scale Zero-Shot Learning

Zero-Shot Learning has been a highlighted research topic in both vision and language areas. Recently, most existing methods adopt structured knowledge information to model explicit correlations among categories and use deep graph convolutional network to propagate information between different categories. However, it is difficult to add new categories to existing structured knowledge graph, and deep graph convolutional network suffers from over-smoothing problem. In this paper, we provide a new semantic enhanced knowledge graph that contains both expert knowledge and categories semantic correlation. Our semantic enhanced knowledge graph can further enhance the correlations among categories and make it easy to absorb new categories. To propagate information on the knowledge graph, we propose a novel Residual Graph Convolutional Network (ResGCN), which can effectively alleviate the problem of over-smoothing. Experiments conducted on the widely used large-scale ImageNet-21K dataset and AWA2 dataset show the effectiveness of our method, and establish a new state-of-the-art on zero-shot learning. Moreover, our results on the large-scale ImageNet-21K with various feature extraction networks show that our method has better generalization and robustness

Développement de catalyseurs cathodiques nanométriques sélectifs à l'environnement organique pour leur utilisation dans une pile microfluidique

Les piles à combustible sans membrane polymérique comme les piles à combustible microfluidique ont des perspectives très intéressantes pour des applications énergétiques à basse puissance. L'étude menée consistait donc à poursuivre le développement de catalyseurs cathodiques nanométriques pouvant être utilisés en tant que cathode dans une pile à combustible microfluidique directe. Au cours de ce travail de thèse, une modification du comportement catalytique du platine a été réalisée grâce à un effet de support, d'alliage avec un métal de transition 3d (titane), ou bien encore par coordination de la surface de nanoparticules de platine avec un élément chalcogène (sélénium). Les effets induits par ces modifications sur les propriétés électroniques du matériau catalytique, et leurs implications sur son activité catalytique ont été étudiés au même titre que sa stabilité et sa tolérance vis-à-vis de petites molécules organiques. Les études ont été menées dans le but de présenter un nouveau paradigme des relations structure-activité, structure-stabilité et structure-tolérance gouvernant le comportement catalytique d'une surface de platine. Les expériences ont par voie de conséquence été conduites de façon à pouvoir séparer les effets catalytiques induits par le support, de ceux induits par un effet d'alliage ou bien encore par coordination des atomes de surface avec un élément chalcogène. En conclusion, ces études ont démontrés l'effet de l'interaction du métal avec le support (oxyde ou matériau carboné présentant divers degrés de graphitisation) sur l'activité et la stabilité des catalyseurs. Un autre point important, qui a été développé dans ce travail de thèse, est la modifFuel cells without polymeric membrane such as the microfluidic fuel cells (MFFC) possess very interesting perspectives for low-power energy applications. The study aimed at pursuing the development of nanometric cathodic catalysts and to study their activity, stability and tolerance in a microfluidic system. In the present thesis, the activity, stability and tolerance of Pt-based nanoparticle electrocatalysts were investigated. The effect of the support materials and the influence of surface modification by a second element including 3d transition metal (titanium) and chalcogenide (selenium) were studied. The separation and reduction of the complexity of the interaction between nanoparticles-support and nanoparticles modification by a second element enables to achieve a clear relationship of the structure-activity-stability-tolerance of the supported fuel-cell electrocatalysts. The present experimental results from the effects of the support materials and of the modification of Pt by a second element led to improve activity, stability and tolerance. The developed approach and acquired knowledge about surface property correlation can be further generalized and used in the design of advanced selective electrocatalysts. Furthermore, the synthesized electrocatalysts were used as cathode in an organic microfluidic fuel cell.POITIERS-SCD-Bib. électronique (861949901) / SudocSudocFranceF

The impact of income level on skeletal muscle health in rural Chinese older residents: a study of mediating effects based on dietary knowledge

China’s rural residents have basically solved the problem of subsistence, but due to aging, the prevalence of sarcopenia (abbreviated as sarcopenia) has been increasing year by year, especially the skeletal muscle health of the rural older residents has not been sufficiently paid attention to, so analyses of the impact of income level on the skeletal muscle health of the older people in rural areas of China are of great practical significance. Based on the annual data of the China Health and Nutrition Survey (CHNS) in 2006, 2009, and 2011, we introduced the mediator variable of dietary knowledge and used the Probit model regression, mediation effect model, and instrumental variable regression to assess the skeletal muscle health status of the rural older people in China and explore the mechanism of the influence of the income level on the skeletal muscle health of the rural older residents in China. The primary objectives of this study were to evaluate the impact of income level on the skeletal muscle health status of older adults living in rural areas of China and to investigate the underlying mechanisms. By analyzing the findings of this study, our aim is to establish a correlation between the economic status and skeletal muscle health of older adults in rural communities, as well as elucidate the influence of income level and dietary knowledge on their skeletal muscle health. Through the attainment of these objectives, we hope to provide valuable insights and recommendations for enhancing skeletal muscle health among the rural older population in China. Based on our research findings, it can be inferred that there was a significant association between the financial status of rural older adults and their skeletal muscle health. Additionally, the prevalence of sarcopenia was lower among individuals with higher income levels, and there was a negative correlation between the prevalence of sarcopenia and the level of dietary knowledge among rural older individuals. The knowledge of dietary knowledge level of rural older people plays a mediating role in the income level and the prevalence of sarcopenia. Moreover, with the change in income level and the increase in age, the change in skeletal muscle health status showed obvious heterogeneity, in which the effect on the relatively younger (65–70 years old) samples was greater. Therefore, sustained income growth remains an effective way to improve the skeletal muscle health of older rural residents. At the same time, improving dietary knowledge and dietary quality among the older people is important in preventing a decline in muscle strength and physical function and in preventing the onset of sarcopenia

Exploiting Cationic Vacancies for Increased Energy Densities in Dual-Ion Batteries

© 2019 Elsevier B.V. Dual-ion Li–Mg batteries offer a potential route to cells that combine desirable properties of both single-ion species. To maximize the energy density of a dual-ion battery, we propose a strategy for achieving simultaneous intercalation of both ionic species, by chemically modifying the intercalation host material to produce a second, complementary, class of insertion sites. We show that donor-doping of anatase TiO2 to form large numbers of cationic vacancies allows the complementary insertion of Li+ and Mg2+ in a dual-ion cell with a net increase in cell energy density, due to a combination of an increased reversible capacity, an increased operating voltage, and a reduced polarization. By tuning the lithium concentration in the electrolyte, we achieve full utilization of the Ti4+/Ti3+ redox couple with excellent cyclability and rate capability. We conclude that native interstitial sites preferentially accommodate Li+ ions, while Mg2+ ions occupy single-vacancy sites. We also predict a narrow range of electrochemical conditions where adjacent vacancy pairs preferentially accommodate one ion of each species, i.e., a [LiTi ​+ ​MgTi] configuration. These results demonstrate the implementation of additional host sites such as cationic sites as an effective approach to increase the energy density in dual-ion batteries

The treatment of tuberculosis in the upper thoracic spine using the small incision technique through the third rib

BackgroundThe complex anatomical structure of the upper thoracic spine makes it challenging to achieve surgical exposure, resulting in significant surgical risks and difficulties. Posterior surgery alone fails to adequately address and reconstruct upper thoracic lesions due to limited exposure. While the anterior approach offers advantages in fully exposing the anterior thoracic lesions, the surgical procedure itself is highly intricate. Although there exist various anterior approaches for the upper thoracic spine, the incidence of upper thoracic spine lesions is relatively low. Consequently, there are limited reports on the treatment and reconstruction of upper thoracic spine lesions using the third rib small incision approach in the context of upper thoracic tuberculosis.MethodsWe collected data from four patients with upper thoracic tuberculosis who were admitted to our department between July 2017 and November 2022. The treatment for upper thoracic tuberculosis involved utilizing the third rib small incision approach, which included two cases of thoracic 3–4 vertebral tuberculosis, one case of thoracic 4 vertebral tuberculosis, and one case of thoracic 5 vertebral tuberculosis. Among the patients, three were positioned in the left lateral position, while one was positioned in the right lateral position. Prior to admission, all four patients received a two-week course of oral medication, consisting of isoniazid, rifampicin, pyrazinamide, and ethambutol. After the surgical procedure, they continued receiving anti-tuberculosis treatment for a duration of 12 months.ResultsThe average duration of the surgical procedure was 150 min, with an average blood loss of 500 ml. One patient exhibited symptoms of brachial plexus injury, which gradually improved after careful observation. All patients experienced primary wound healing, and no complications such as pulmonary infection, respiratory failure, or other adverse events were observed. Additionally, one patient showed elevated transaminase levels, leading to a modification in the anti-tuberculosis drug regimen from quadruple therapy to triple therapy.ConclusionThe treatment of upper thoracic tuberculosis through the third rib small incision technique is a very good surgical approach, which has the advantages of safety and effectiveness