GLT-T: Global-Local Transformer Voting for 3D Single Object Tracking in Point Clouds

Current 3D single object tracking methods are typically based on VoteNet, a 3D region proposal network. Despite the success, using a single seed point feature as the cue for offset learning in VoteNet prevents high-quality 3D proposals from being generated. Moreover, seed points with different importance are treated equally in the voting process, aggravating this defect. To address these issues, we propose a novel global-local transformer voting scheme to provide more informative cues and guide the model pay more attention on potential seed points, promoting the generation of high-quality 3D proposals. Technically, a global-local transformer (GLT) module is employed to integrate object- and patch-aware prior into seed point features to effectively form strong feature representation for geometric positions of the seed points, thus providing more robust and accurate cues for offset learning. Subsequently, a simple yet effective training strategy is designed to train the GLT module. We develop an importance prediction branch to learn the potential importance of the seed points and treat the output weights vector as a training constraint term. By incorporating the above components together, we exhibit a superior tracking method GLT-T. Extensive experiments on challenging KITTI and NuScenes benchmarks demonstrate that GLT-T achieves state-of-the-art performance in the 3D single object tracking task. Besides, further ablation studies show the advantages of the proposed global-local transformer voting scheme over the original VoteNet. Code and models will be available at https://github.com/haooozi/GLT-T.Comment: Accepted to AAAI 2023. The source code and models will be available at https://github.com/haooozi/GLT-

Sensitivity analysis in non-inferiority trials with residual inconstancy after covariate adjustment

A major issue in non-inferiority trials is the controversial assumption of constancy, namely that the active control has the same effect relative to placebo as in previous studies comparing the active control with placebo. The constancy assumption is often in doubt, which has motivated various methods that ‘discount’ the control effect estimate from historical data as well as methods that adjust for imbalances in observed covariates. We develop a new approach to deal with residual inconstancy, i.e. possible violations of the constancy assumption due to imbalances in unmeasured covariates after adjusting for the measured covariates. We characterize the extent of residual inconstancy under a generalized linear model framework and use the results to obtain fully adjusted estimates of the control effect in the current study based on plausible assumptions about an unmeasured covariate. Because such assumptions may be difficult to justify, we propose a sensitivity analysis approach that covers a range of situations. This approach is developed for indirect comparison with placebo and effect retention, and implemented through additive and multiplicative adjustments.The approach proposed is applied to two examples concerning benign prostate hyperplasia and human immunodeficiency virus infection, and evaluated in simulation studies.Keywords: Active control, Effect retention, Putative placebo, Discounting, Conditional effect, Constanc

Dimension Analysis-Based Model for Prediction of Shale Compressive Strength

The compressive strength of shale is a comprehensive index for evaluating the shale strength, which is linked to shale well borehole stability. Based on correlation analysis between factors (confining stress, height/diameter ratio, bedding angle, and porosity) and shale compressive strength (Longmaxi Shale in Sichuan Basin, China), we develop a dimension analysis-based model for prediction of shale compressive strength. A nonlinear-regression model is used for comparison. A multitraining method is used to achieve reliability of model prediction. The results show that, compared to a multi-nonlinear-regression model (average prediction error = 19.5%), the average prediction error of the dimension analysis-based model is 19.2%. More importantly, our dimension analysis-based model needs to determine only one parameter, whereas the multi-nonlinear-regression model needs to determine five. In addition, sensitivity analysis shows that height/diameter ratio has greater sensitivity to compressive strength than other factors

Lumbar Spinal Cord Activity and Blood Biochemical Changes in Individuals With Diabetic Peripheral Neuropathy During Electrical Stimulation

It is difficult to perform an in vivo evaluation of the nerve conduction mechanism in a patient with diabetic peripheral neuropathy (DPN). We aim to explore possible activation differences to enable a further understanding of the nerve conduction mechanisms of diabetic neuropathy and to present a novel clinical method to evaluate nerve injury and recovery. DPN patients (n = 20) and healthy volunteers (n = 20) were included in this study to detect the functional activation of the lumbar spinal cord via electric stimulation. Spinal fMRI data sets were acquired via a single-shot fast spin echo (SSFSE) sequence. A task-related fMRI was performed via low-frequency electrical stimulation. After post-processing, the active voxels and the percentage of signal changes were calculated for the DPN evaluation and the correlations between the blood biochemical indexes, such as glucose, total cholesterol, and hemoglobin A1c were explored. Activation in the DPN patients was primarily observed in the T12 (10/13) vertebral level. The percentage of signal changes in DPN patients was higher than that in the control group (Z = −2.757, P < 0.05). Positive correlation between the percentage of signal changes and the total cholesterol/glucose in the DNP group was found (P < 0.05). Lumbar spinal cord fMRI, based on the SEEP effect, was determined to be feasible. The repetitive activation distribution was primarily located at the T12 vertebral level. Lumbar spinal cord fMRI might be used as a potential tool to assess and reveal the nerve conduction mechanisms in DPN

Establishment of Three Rapid Visual Detection Methods for Burkholderia gladioli pv. cocovenenans Based on Body Temperature Amplification

Three rapid visual methods, namely chromogenic, fluorescence and test strip, for the rapid detection of Burkholderia gladioli pv. cocovenenans in foods were established based on enzymatic recombinase amplification (ERA). Primers and probes were designed and screened based on the bonM gene of B. gladioli pv. cocovenenans. Then the specificity and sensitivity of the three methods were evaluated, as well as their applicability and accuracy in the detection of commercial food samples. The results showed that three strains of B. gladioli pv. cocovenenans, but not other common foodborne pathogens and other B. gladioli strains, were amplified by the three methods, indicating their good specificity. The detection limits of these methods were all 10-2 ng/μL, and their sensitivity was good. Out of 15 commercial samples, two tested positive by each of these methods with a detection rate of 13.3%. This result was consistent with that of the national standard method, indicating that our methods had good applicability and accuracy. All three methods give results that can be observed by the naked eye after amplification at 37 ℃ for 15 min, which provide a new and simple strategy for the rapid, visual and on-site screening of B. gladioli pv. cocovenenans in foods

Gut Symbionts alleviate Mash Through a Secondary Bile acid Biosynthetic Pathway

The gut microbiota has been found to play an important role in the progression of metabolic dysfunction-associated steatohepatitis (MASH), but the mechanisms have not been established. Here, by developing a click-chemistry-based enrichment strategy, we identified several microbial-derived bile acids, including the previously uncharacterized 3-succinylated cholic acid (3-sucCA), which is negatively correlated with liver damage in patients with liver-tissue-biopsy-proven metabolic dysfunction-associated fatty liver disease (MAFLD). By screening human bacterial isolates, we identified Bacteroides uniformis strains as effective producers of 3-sucCA both in vitro and in vivo. By activity-based protein purification and identification, we identified an enzyme annotated as β-lactamase in B. uniformis responsible for 3-sucCA biosynthesis. Furthermore, we found that 3-sucCA is a lumen-restricted metabolite and alleviates MASH by promoting the growth of Akkermansia muciniphila. together, our data offer new insights into the gut microbiota-liver axis that may be leveraged to augment the management of MASH

Defining Key Genes Regulating Morphogenesis of Apocrine Sweat Gland in Sheepskin

The apocrine sweat gland is a unique skin appendage in humans compared to mouse and chicken models. The absence of apocrine sweat glands in chicken and murine skin largely restrains further understanding of the complexity of human skin biology and skin diseases, like hircismus. Sheep may serve as an additional system for skin appendage investigation owing to the distributions and histological similarities between the apocrine sweat glands of sheep trunk skin and human armpit skin. To understand the molecular mechanisms underlying morphogenesis of apocrine sweat glands in sheepskin, transcriptome analyses were conducted to reveal 1631 differentially expressed genes that were mainly enriched in three functional groups (cellular component, molecular function and biological process), particularly in gland, epithelial, hair follicle and skin development. There were 7 Gene Ontology (GO) terms enriched in epithelial cell migration and morphogenesis of branching epithelium that were potentially correlated with the wool follicle peg elongation. An additional 5 GO terms were enriched in gland morphogenesis (20 genes), gland development (42 genes), salivary gland morphogenesis and development (8 genes), branching involved in salivary gland morphogenesis (6 genes) and mammary gland epithelial cell differentiation (4 genes). The enriched gland-related genes and two Kyoto Encyclopedia of Genes and Genomes pathway genes (WNT and TGF-β) were potentially involved in the induction of apocrine sweat glands. Genes named BMPR1A, BMP7, SMAD4, TGFB3, WIF1, and WNT10B were selected to validate transcript expression by qRT-PCR. Immunohistochemistry was performed to localize markers for hair follicle (SOX2), skin fibroblast (PDGFRB), stem cells (SOX9) and BMP signaling (SMAD5) in sheepskin. SOX2 and PDGFRB were absent in apocrine sweat glands. SOX9 and SMAD5 were both observed in precursor cells of apocrine sweat glands and later in gland ducts. These results combined with the upregulation of BMP signaling genes indicate that apocrine sweat glands were originated from outer root sheath of primary wool follicle and positively regulated by BMP signaling. This report established the primary network regulating early development of apocrine sweat glands in sheepskin and will facilitate the further understanding of histology and pathology of apocrine sweat glands in human and companion animal skin