DSGN++: Exploiting Visual-Spatial Relation for Stereo-based 3D Detectors

Camera-based 3D object detectors are welcome due to their wider deployment and lower price than LiDAR sensors. We revisit the prior stereo modeling DSGN about the stereo volume constructions for representing both 3D geometry and semantics. We polish the stereo modeling and propose our approach, DSGN++, aiming for improving information flow throughout the 2D-to-3D pipeline in the following three main aspects. First, to effectively lift the 2D information to stereo volume, we propose depth-wise plane sweeping (DPS) that allows denser connections and extracts depth-guided features. Second, for better grasping differently spaced features, we present a novel stereo volume -- Dual-view Stereo Volume (DSV) that integrates front-view and top-view features and reconstructs sub-voxel depth in the camera frustum. Third, as the foreground region becomes less dominant in 3D space, we firstly propose a multi-modal data editing strategy -- Stereo-LiDAR Copy-Paste, which ensures cross-modal alignment and improves data efficiency. Without bells and whistles, extensive experiments in various modality setups on the popular KITTI benchmark show that our method consistently outperforms other camera-based 3D detectors for all categories. Code will be released at https://github.com/chenyilun95/DSGN2

CLEVA: Chinese Language Models EVAluation Platform

With the continuous emergence of Chinese Large Language Models (LLMs), how to evaluate a model's capabilities has become an increasingly significant issue. The absence of a comprehensive Chinese benchmark that thoroughly assesses a model's performance, the unstandardized and incomparable prompting procedure, and the prevalent risk of contamination pose major challenges in the current evaluation of Chinese LLMs. We present CLEVA, a user-friendly platform crafted to holistically evaluate Chinese LLMs. Our platform employs a standardized workflow to assess LLMs' performance across various dimensions, regularly updating a competitive leaderboard. To alleviate contamination, CLEVA curates a significant proportion of new data and develops a sampling strategy that guarantees a unique subset for each leaderboard round. Empowered by an easy-to-use interface that requires just a few mouse clicks and a model API, users can conduct a thorough evaluation with minimal coding. Large-scale experiments featuring 23 Chinese LLMs have validated CLEVA's efficacy.Comment: EMNLP 2023 System Demonstrations camera-read

Causal association between self-reported fatigue and coronary artery disease: a bidirectional two-sample Mendelian randomization analysis

BackgroundObservational studies have reported the association between fatigue and coronary artery disease (CAD), but the causal association between fatigue and CAD is unclear.MethodWe conducted a bidirectional Mendelian randomization (MR) study using publicly available genome-wide association studies (GWAS) data. The inverse-variance weighted (IVW) method was used as the primary analysis. We performed three complementary methods, including weighted median, MR-Egger regression, and MR pleiotropy residual sum and outlier (MR-PRESSO) to evaluate the sensitivity and horizontal pleiotropy of the results.ResultSelf-reported fatigue had a causal effect on coronary artery atherosclerosis (CAA) (OR 1.047, 95%CI 1.033–1.062), myocardial infarction (MI) (OR 1.027 95%CI 1.014–1.039) and coronary heart disease (CHD) (OR 1.037, 95%CI 1.021–1.053). We did not find a significant reverse causality between self-reported fatigue and CAD. Given the heterogeneity revealed by MR-Egger regression, we employed the IVW random effect model. For the examination of fatigue on CHD and the reverse analysis of CAA, and MI on fatigue, the MR-PRESSO test found horizontal pleiotropy. No significant outliers were found.ConclusionThe MR analysis reveals a causal relationship between self-reported fatigue and CAD. The results should be interpreted with caution due to horizontal pleiotropy

Transient ischemic attack and coronary artery disease: a two-sample Mendelian randomization analysis

BackgroundAlthough observational studies have shown that patients who experienced transient ischemic attacks (TIAs) had a higher risk of coronary artery disease (CAD), the causal relationship is ambiguous.MethodsWe conducted a two-sample Mendelian randomization (MR) study to analyze the causal relationship between TIA and CAD using data from the FinnGen genome-wide association study. Analysis was performed using the inverse-variance weighted (IVW) method. The robustness of the results was evaluated using MR-Egger regression, the weighted median, MR pleiotropy residual sum, and outlier (MR-PRESSO) and multivariable MR analysis.ResultsResults from IVW random-effect model showed that TIA was associated with an increased risk of coronary artery atherosclerosis (OR 1.17, 95% CI 1.06–1.28, P = 0.002), ischemic heart disease (OR 1.15, 95% CI 1.04–1.27, P = 0.007), and myocardial infarction (OR1.15, 95% CI 1.02–1.29, P = 0.025). In addition, heterogeneity and horizontal pleiotropy were observed in the ischemic heart disease results, while the sensitivity analysis revealed no evidence of horizontal pleiotropy in other outcomes.ConclusionsThis MR study demonstrated a potential causal relationship between TIA and CAD. Further research should be conducted to investigate the mechanism underlying the association

Metagenomic surveillance and comparative genomic analysis of Chlamydia psittaci in patients with pneumonia

Chlamydia psittaci, a strictly intracellular bacterium, is an underestimated etiologic agent leading to infections in a broad range of animals and mild illness or pneumonia in humans. In this study, the metagenomes of bronchoalveolar lavage fluids from the patients with pneumonia were sequenced and highly abundant C. psittaci was found. The target-enriched metagenomic reads were recruited to reconstruct draft genomes with more than 99% completeness. Two C. psittaci strains from novel sequence types were detected and these were closely related to the animal-borne isolates derived from the lineages of ST43 and ST28, indicating the zoonotic transmissions of C. psittaci would benefit its prevalence worldwide. Comparative genomic analysis combined with public isolate genomes revealed that the pan-genome of C. psittaci possessed a more stable gene repertoire than those of other extracellular bacteria, with ~90% of the genes per genome being conserved core genes. Furthermore, the evidence for significantly positive selection was identified in 20 virulence-associated gene products, particularly bacterial membrane-embedded proteins and type three secretion machines, which may play important roles in the pathogen-host interactions. This survey uncovered novel strains of C. psittaci causing pneumonia and the evolutionary analysis characterized prominent gene candidates involved in bacterial adaptation to immune pressures. The metagenomic approach is of significance to the surveillance of difficult-to-culture intracellular pathogens and the research into molecular epidemiology and evolutionary biology of C. psittaci

Master Transcription Factor Reprogramming Unleashes Selective Translation Promoting Castration Resistance and Immune Evasion in Lethal Prostate Cancer

Signaling rewiring allows tumors to survive therapy. Here we show that the decrease of the master regulator microphthalmia transcription factor (MITF) in lethal prostate cancer unleashes eukaryotic initiation factor 3B (eIF3B)-dependent translation reprogramming of key mRNAs conferring resistance to androgen deprivation therapy (ADT) and promoting immune evasion. Mechanistically, MITF represses through direct promoter binding eIF3B, which in turn regulates the translation of specific mRNAs. Genome-wide eIF3B enhanced cross-linking immunoprecipitation sequencing (eCLIP-seq) showed specialized binding to a UC-rich motif present in subsets of 5\u27 untranslated regions. Indeed, translation of the androgen receptor and major histocompatibility complex I (MHC-I) through this motif is sensitive to eIF3B amount. Notably, pharmacologic targeting of eIF3B-dependent translation in preclinical models sensitizes prostate cancer to ADT and anti-PD-1 therapy. These findings uncover a hidden connection between transcriptional and translational rewiring promoting therapy-refractory lethal prostate cancer and provide a druggable mechanism that may transcend into effective combined therapeutic strategies. SIGNIFICANCE: Our study shows that specialized eIF3B-dependent translation of specific mRNAs released upon downregulation of the master transcription factor MITF confers castration resistance and immune evasion in lethal prostate cancer. Pharmacologic targeting of this mechanism delays castration resistance and increases immune-checkpoint efficacy. This article is featured in Selected Articles from This Issue, p. 2489

Factors Affecting the Structural Behavior of FRP Wrapped Concrete Columns and Applications in Design

In this paper, the FRP wrapped concrete column is investigated. . According to the research results of Shan et al. (2020) [2], Li et al. (2006) [3], and Deb et al. (2010) [4], this paper analyzes the variables that need to be controlled in the design of columns from these three perspectives: the shape of the cross-section, fiber orientation and bonding between the concrete column and FRP confinement. Impact tests and compressive tests are performed on different specimen. The setting of different samples follows the principle of controlling variables. The results indicate that FRP-wrapped columns with a circular cross-section are better than that with square or rectangular columns and basalt FRP is the optimal FRP material for strengthening the concrete column under the impact. Fiber orientation and types of bonding layers have a great impact on the mechanical properties of FRP wrapped concrete columns

The influence of methods of selecting concepts of an expository text on different reading representations' predictive ability

In this study, we compared two experimental methods of selecting terms in expository text to generate reading representations and tested how well these reading representations predicted reading comprehension. The two experimental methods were the traditional method of using all terms (all keywords) to create participants' representation networks, and the terms categorization (TC) method of using only important terms (core and branch words). Representation networks were assessed using participants' adjacency scores, ratings of relatedness in pairs of terms, and using summary (summary writing) by all turms. An in-subject design was performed in experiments 1 and 2, and an inter-subject design was performed in experiment 3 to test the hypothesis. With the same sample in exp1 and epx2, a different sample in each exp3. Experiment 1 showed that when using only the traditional way of selecting terms, adjacency was better than relatedness in predicting reading comprehension. Reading representations generated based on the summary method could not predict participants' reading comprehension ability, so this method was excluded from subsequent studies. Experiment 2 showed that the terms selected in Experiment 1 were stronger predictors of reading comprehension when the word pairs included a core term (central to understanding of full text) or a branch term (key to understanding paragraph), relative to a detail term (not affect the understanding full text). Experiment 3 found that whereas the two methods were equally effective in generating representations measured by adjacency, TC was superior in generating representations measured by relatedness. These conclusions have important implications for future research and application

Index investment strategy

This study aims to formulate a portfolio model that replicates the returns of the Standard and Poor's 500 Index by minimising tracking error. Stock selection is based on stratified sampling and correlation between the stock and the index's returns. Effects of short selling constraint, rebalancing, and transaction costs are investigated