ViP3D: End-to-end Visual Trajectory Prediction via 3D Agent Queries

Existing autonomous driving pipelines separate the perception module from the prediction module. The two modules communicate via hand-picked features such as agent boxes and trajectories as interfaces. Due to this separation, the prediction module only receives partial information from the perception module. Even worse, errors from the perception modules can propagate and accumulate, adversely affecting the prediction results. In this work, we propose ViP3D, a visual trajectory prediction pipeline that leverages the rich information from raw videos to predict future trajectories of agents in a scene. ViP3D employs sparse agent queries throughout the pipeline, making it fully differentiable and interpretable. Furthermore, we propose an evaluation metric for this novel end-to-end visual trajectory prediction task. Extensive experimental results on the nuScenes dataset show the strong performance of ViP3D over traditional pipelines and previous end-to-end models.Comment: Project page is at https://tsinghua-mars-lab.github.io/ViP3

Paxbp1 is indispensable for the survival of CD4 and CD8 double-positive thymocytes

The lifespan of double-positive (DP) thymocytes is critical for intrathymic development and shaping the peripheral T cell repertoire. However, the molecular mechanisms that control DP thymocyte survival remain poorly understood. Paxbp1 is a conserved nuclear protein that has been reported to play important roles in cell growth and development. Its high expression in T cells suggests a possible role in T cell development. Here, we observed that deletion of Paxbp1 resulted in thymic atrophy in mice lacking Paxbp1 in the early stages of T cell development. Conditional loss of Paxbp1 resulted in fewer CD4+CD8+ DP T cells, CD4 and CD8 single positive (SP) T cells in the thymus, and fewer T cells in the periphery. Meanwhile, Paxbp1 deficiency had limited effects on the CD4-CD8- double negative (DN) or immature single-positive (ISP) cell populations. Instead, we observed a significant increase in the susceptibility of Paxbp1-deficient DP thymocytes to apoptosis. Consistent with this, RNA-Seq analysis revealed a significant enrichment of the apoptotic pathway within differentially expressed genes in Paxbp1-deficient DP cells compared to control DP cells. Together, our results suggest a new function for Paxbp1, which is an important mediator of DP thymocyte survival and critical for proper thymic development

A statistical method for region-based meta-analysis of genome-wide association studies in genetically diverse populations

Genome-wide association studies (GWAS) have become the preferred experimental design in exploring the genetic etiology of complex human traits and diseases. Standard SNP-based meta-analytic approaches have been utilized to integrate the results from multiple experiments. This fundamentally assumes that the patterns of linkage disequilibrium (LD) between the underlying causal variants and the directly genotyped SNPs are similar across the populations for the same SNPs to emerge with surrogate evidence of disease association. We introduce a novel strategy for assessing regional evidence of phenotypic association that explicitly incorporates the extent of LD in the region. This provides a natural framework for combining evidence from multi-ethnic studies of both dichotomous and quantitative traits that (i) accommodates different patterns of LD, (ii) integrates different genotyping platforms and (iii) allows for the presence of allelic heterogeneity between the populations. Our method can also be generalized to perform gene-based or pathway-based analyses. Applying this method on real GWAS data in type 2 diabetes (T2D) boosted the association evidence in regions well-established for T2D etiology in three diverse South-East Asian populations, as well as identified two novel gene regions and a biologically convincing pathway that are subsequently validated with data from the Wellcome Trust Case Control Consortium

Evaluating the contribution of rare variants to type 2 diabetes and related traits using pedigrees

Significance Contributions of rare variants to common and complex traits such as type 2 diabetes (T2D) are difficult to measure. This paper describes our results from deep whole-genome analysis of large Mexican-American pedigrees to understand the role of rare-sequence variations in T2D and related traits through enriched allele counts in pedigrees. Our study design was well-powered to detect association of rare variants if rare variants with large effects collectively accounted for large portions of risk variability, but our results did not identify such variants in this sample. We further quantified the contributions of common and rare variants in gene expression profiles and concluded that rare expression quantitative trait loci explain a substantive, but minor, portion of expression heritability.</jats:p

A new strategy for enhancing imputation quality of rare variants from next-generation sequencing data via combining SNP and exome chip data

Background: Rare variants have gathered increasing attention as a possible alternative source of missing heritability. Since next generation sequencing technology is not yet cost-effective for large-scale genomic studies, a widely used alternative approach is imputation. However, the imputation approach may be limited by the low accuracy of the imputed rare variants. To improve imputation accuracy of rare variants, various approaches have been suggested, including increasing the sample size of the reference panel, using sequencing data from study-specific samples (i.e., specific populations), and using local reference panels by genotyping or sequencing a subset of study samples. While these approaches mainly utilize reference panels, imputation accuracy of rare variants can also be increased by using exome chips containing rare variants. The exome chip contains 250 K rare variants selected from the discovered variants of about 12,000 sequenced samples. If exome chip data are available for previously genotyped samples, the combined approach using a genotype panel of merged data, including exome chips and SNP chips, should increase the imputation accuracy of rare variants. Results: In this study, we describe a combined imputation which uses both exome chip and SNP chip data simultaneously as a genotype panel. The effectiveness and performance of the combined approach was demonstrated using a reference panel of 848 samples constructed using exome sequencing data from the T2D-GENES consortium and 5,349 sample genotype panels consisting of an exome chip and SNP chip. As a result, the combined approach increased imputation quality up to 11 %, and genomic coverage for rare variants up to 117.7 % (MAF < 1 %), compared to imputation using the SNP chip alone. Also, we investigated the systematic effect of reference panels on imputation quality using five reference panels and three genotype panels. The best performing approach was the combination of the study specific reference panel and the genotype panel of combined data. Conclusions: Our study demonstrates that combined datasets, including SNP chips and exome chips, enhances both the imputation quality and genomic coverage of rare variants

Generating True Random Numbers Using On-chip Complementary Polarizer Spin-Transfer Torque Magnetic Tunnel Junctions

10.1109/DRC.2014.687231872nd Annual Device Research Conference (DRC)103-

Analysis of super cut-off transistors for ultralow power digital logic circuits

10.1109/LPE.2006.4271798International Symposium on Low Power Electronics and Design2-

Domain Wall Motion-based Low Power Hybrid Spin-CMOS 5-bit Flash Analog Data Converter

10.1109/ISQED.2015.708549616th International Symposium on Quality Electronic Design (ISQED)2015-April604-60