694 research outputs found

    Co-Evolution of Pose and Mesh for 3D Human Body Estimation from Video

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    Despite significant progress in single image-based 3D human mesh recovery, accurately and smoothly recovering 3D human motion from a video remains challenging. Existing video-based methods generally recover human mesh by estimating the complex pose and shape parameters from coupled image features, whose high complexity and low representation ability often result in inconsistent pose motion and limited shape patterns. To alleviate this issue, we introduce 3D pose as the intermediary and propose a Pose and Mesh Co-Evolution network (PMCE) that decouples this task into two parts: 1) video-based 3D human pose estimation and 2) mesh vertices regression from the estimated 3D pose and temporal image feature. Specifically, we propose a two-stream encoder that estimates mid-frame 3D pose and extracts a temporal image feature from the input image sequence. In addition, we design a co-evolution decoder that performs pose and mesh interactions with the image-guided Adaptive Layer Normalization (AdaLN) to make pose and mesh fit the human body shape. Extensive experiments demonstrate that the proposed PMCE outperforms previous state-of-the-art methods in terms of both per-frame accuracy and temporal consistency on three benchmark datasets: 3DPW, Human3.6M, and MPI-INF-3DHP. Our code is available at https://github.com/kasvii/PMCE.Comment: Accepted by ICCV 2023. Project page: https://kasvii.github.io/PMC

    GATOR: Graph-Aware Transformer with Motion-Disentangled Regression for Human Mesh Recovery from a 2D Pose

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    3D human mesh recovery from a 2D pose plays an important role in various applications. However, it is hard for existing methods to simultaneously capture the multiple relations during the evolution from skeleton to mesh, including joint-joint, joint-vertex and vertex-vertex relations, which often leads to implausible results. To address this issue, we propose a novel solution, called GATOR, that contains an encoder of Graph-Aware Transformer (GAT) and a decoder with Motion-Disentangled Regression (MDR) to explore these multiple relations. Specifically, GAT combines a GCN and a graph-aware self-attention in parallel to capture physical and hidden joint-joint relations. Furthermore, MDR models joint-vertex and vertex-vertex interactions to explore joint and vertex relations. Based on the clustering characteristics of vertex offset fields, MDR regresses the vertices by composing the predicted base motions. Extensive experiments show that GATOR achieves state-of-the-art performance on two challenging benchmarks.Comment: Accepted by ICASSP 202

    The developmental regulator Pax6 is essential for maintenance of islet cell function in the adult mouse pancreas

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    The transcription factor Pax6 is a developmental regulator with a crucial role in development of the eye, brain, and olfactory system. Pax6 is also required for correct development of the endocrine pancreas and specification of hormone producing endocrine cell types. Glucagon-producing cells are almost completely lost in Pax6-null embryos, and insulin-expressing beta and somatostatin-expressing delta cells are reduced. While the developmental role of Pax6 is well-established, investigation of a further role for Pax6 in the maintenance of adult pancreatic function is normally precluded due to neonatal lethality of Pax6-null mice. Here a tamoxifen-inducible ubiquitous Cre transgene was used to inactivate Pax6 at 6 months of age in a conditional mouse model to assess the effect of losing Pax6 function in adulthood. The effect on glucose homeostasis and the expression of key islet cell markers was measured. Homozygous Pax6 deletion mice, but not controls, presented with all the symptoms of classical diabetes leading to severe weight loss requiring termination of the experiment five weeks after first tamoxifen administration. Immunohistochemical analysis of the pancreata revealed almost complete loss of Pax6 and much reduced expression of insulin, glucagon, and somatostatin. Several other markers of islet cell function were also affected. Notably, strong upregulation in the number of ghrelin-expressing endocrine cells was observed. These findings demonstrate that Pax6 is essential for adult maintenance of glucose homeostasis and function of the endocrine pancreas

    Almost Automorphic Solutions to Abstract Fractional Differential Equations

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    A new and general existence and uniqueness theorem of almost automorphic solutions is obtained for the semilinear fractional differential equation Dtαu(t)=Au(t)+Dtα−1f(t,u(t))  (1<α<2), in complex Banach spaces, with Stepanov-like almost automorphic coefficients. Moreover, an application to a fractional relaxation-oscillation equation is given

    SeaEval for Multilingual Foundation Models: From Cross-Lingual Alignment to Cultural Reasoning

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    We present SeaEval, a benchmark for multilingual foundation models. In addition to characterizing how these models understand and reason with natural language, we also investigate how well they comprehend cultural practices, nuances, and values. Alongside standard accuracy metrics, we investigate the brittleness of foundation models in the dimensions of semantics and multilinguality. Our analyses span both open-sourced and closed models, leading to empirical results across classic NLP tasks, reasoning, and cultural comprehension. Key findings indicate (1) Most models exhibit varied behavior when given paraphrased instructions. (2) Many models still suffer from exposure bias (e.g., positional bias, majority label bias). (3) For questions rooted in factual, scientific, and commonsense knowledge, consistent responses are expected across multilingual queries that are semantically equivalent. Yet, most models surprisingly demonstrate inconsistent performance on these queries. (4) Multilingually-trained models have not attained "balanced multilingual" capabilities. Our endeavors underscore the need for more generalizable semantic representations and enhanced multilingual contextualization. SeaEval can serve as a launchpad for more thorough investigations and evaluations for multilingual and multicultural scenarios.Comment: 15 pages, 7 figure

    Integration of genome-wide association studies with biological knowledge identifies six novel genes related to kidney function

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    In conducting genome-wide association studies (GWAS), analytical approaches leveraging biological information may further understanding of the pathophysiology of clinical traits. To discover novel associations with estimated glomerular filtration rate (eGFR), a measure of kidney function, we developed a strategy for integrating prior biological knowledge into the existing GWAS data for eGFR from the CKDGen Consortium. Our strategy focuses on single nucleotide polymorphism (SNPs) in genes that are connected by functional evidence, determined by literature mining and gene ontology (GO) hierarchies, to genes near previously validated eGFR associations. It then requires association thresholds consistent with multiple testing, and finally evaluates novel candidates by independent replication. Among the samples of European ancestry, we identified a genome-wide significant SNP in FBXL20 (P = 5.6 × 10−9) in meta-analysis of all available data, and additional SNPs at the INHBC, LRP2, PLEKHA1, SLC3A2 and SLC7A6 genes meeting multiple-testing corrected significance for replication and overall P-values of 4.5 × 10−4-2.2 × 10−7. Neither the novel PLEKHA1 nor FBXL20 associations, both further supported by association with eGFR among African Americans and with transcript abundance, would have been implicated by eGFR candidate gene approaches. LRP2, encoding the megalin receptor, was identified through connection with the previously known eGFR gene DAB2 and extends understanding of the megalin system in kidney function. These findings highlight integration of existing genome-wide association data with independent biological knowledge to uncover novel candidate eGFR associations, including candidates lacking known connections to kidney-specific pathways. The strategy may also be applicable to other clinical phenotypes, although more testing will be needed to assess its potential for discovery in genera

    Genome-wide association and functional follow-up reveals new loci for kidney function

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    Chronic kidney disease (CKD) is an important public health problem with a genetic component. We performed genome-wide association studies in up to 130,600 European ancestry participants overall, and stratified for key CKD risk factors. We uncovered 6 new loci in association with estimated glomerular filtration rate (eGFR), the primary clinical measure of CKD, in or near MPPED2, DDX1, SLC47A1, CDK12, CASP9, and INO80. Morpholino knockdown of mpped2 and casp9 in zebrafish embryos revealed podocyte and tubular abnormalities with altered dextran clearance, suggesting a role for these genes in renal function. By providing new insights into genes that regulate renal function, these results could further our understanding of the pathogenesis of CKD

    New genetic loci link adipose and insulin biology to body fat distribution.

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    Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

    Genome wide analysis of DNA copy number neutral loss of heterozygosity (CNNLOH) and its relation to gene expression in esophageal squamous cell carcinoma

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    Abstract Background Genomic instability plays an important role in human cancers. We previously characterized genomic instability in esophageal squamous cell carcinomas (ESCC) in terms of loss of heterozygosity (LOH) and copy number (CN) changes in tumors using the Affymetrix GeneChip Human Mapping 500K array in 30 cases from a high-risk region of China. In the current study we focused on copy number neutral (CN = 2) LOH (CNNLOH) and its relation to gene expression in ESCC. Results Overall we found that 70% of all LOH observed was CNNLOH. Ninety percent of ESCCs showed CNNLOH (median frequency in cases = 60%) and this was the most common type of LOH in two-thirds of cases. CNNLOH occurred on all 39 autosomal chromosome arms, with highest frequencies on 19p (100%), 5p (96%), 2p (95%), and 20q (95%). In contrast, LOH with CN loss represented 19% of all LOH, occurred in just half of ESCCs (median frequency in cases = 0%), and was most frequent on 3p (56%), 5q (47%), and 21q (41%). LOH with CN gain was 11% of all LOH, occurred in 93% of ESCCs (median frequency in cases = 13%), and was most common on 20p (82%), 8q (74%), and 3q (42%). To examine the effect of genomic instability on gene expression, we evaluated RNA profiles from 17 pairs of matched normal and tumor samples (a subset of the 30 ESCCs) using Affymetrix U133A 2.0 arrays. In CN neutral regions, expression of 168 genes (containing 1976 SNPs) differed significantly in tumors with LOH versus tumors without LOH, including 101 genes that were up-regulated and 67 that were down-regulated. Conclusion Our results indicate that CNNLOH has a profound impact on gene expression in ESCC, which in turn may affect tumor development. </jats:sec
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