Software for Exact Integration of Polynomials over Polyhedra

We are interested in the fast computation of the exact value of integrals of polynomial functions over convex polyhedra. We present speed ups and extensions of the algorithms presented in previous work. We present the new software implementation and provide benchmark computations. The computation of integrals of polynomials over polyhedral regions has many applications; here we demonstrate our algorithmic tools solving a challenge from combinatorial voting theory.Comment: Major updat

3D Model-based Zero-Shot Pose Estimation Pipeline

Most existing learning-based pose estimation methods are typically developed for non-zero-shot scenarios, where they can only estimate the poses of objects present in the training dataset. This setting restricts their applicability to unseen objects in the training phase. In this paper, we introduce a fully zero-shot pose estimation pipeline that leverages the 3D models of objects as clues. Specifically, we design a two-step pipeline consisting of 3D model-based zero-shot instance segmentation and a zero-shot pose estimator. For the first step, there is a novel way to perform zero-shot instance segmentation based on the 3D models instead of text descriptions, which can handle complex properties of unseen objects. For the second step, we utilize a hierarchical geometric structure matching mechanism to perform zero-shot pose estimation which is 10 times faster than the current render-based method. Extensive experimental results on the seven core datasets on the BOP challenge show that the proposed method outperforms the zero-shot state-of-the-art method with higher speed and lower computation cost

Knowledge mapping and research hotspots of immunotherapy in renal cell carcinoma: A text-mining study from 2002 to 2021

BackgroundRenal cell carcinoma (RCC) is one of the most lethal urological malignancies, and because early-stage RCC is asymptomatic, many patients present metastatic diseases at first diagnosis. With the development of immunotherapy, the treatment of RCC has entered a new stage and has made a series of progress. This study mainly outlines the knowledge map and detects the potential research hotspots by using bibliometric analysis.MethodsPublications concerning RCC immunotherapy from 2002 to 2021 in the Web of Science Core Collection were collected. Visualization and statistical analysis were mainly performed by freeware tools VOSviewer, CiteSpace, R software, and Microsoft Office Excel 2019.ResultsA total of 3,432 papers were collected in this study, and the annual number of papers and citations showed a steady growth trend. The United States is the leading country with the most high-quality publications and is also the country with the most international cooperation. The University of Texas MD Anderson Cancer Center is the most productive organization. The Journal of Clinical Oncology is the highest co-cited journal, and Brian I. Rini is both the most prolific author and the author with the largest centrality. The current research hotspots may be focused on “immune checkpoint inhibitors (ICIs),” “PD-1,” and “mammalian target of rapamycin.”ConclusionImmunotherapy has a bright future in the field of RCC treatment, among which ICIs are one of the most important research hotspots. The main future research directions of ICI-based immunotherapy may focus on combination therapy, ICI monotherapy, and the development of new predictive biomarkers

A New Race (X12) of Soybean Cyst Nematode in China

The soybean cyst nematode (SCN), Heterodera glycines, is a serious economic threat to soybean-producing regions worldwide. A new SCN population (called race X12) was detected in Shanxi province, China. Race X12 could reproduce on all the indicator lines of both race and Heterodera glycines (HG) type tests. The average number of females on Lee68 (susceptible control) was 171.40 with the lowest Female Index (FI) 61.31 on PI88788 and the highest FI 117.32 on Pickett in the race test. The average number of females on Lee68 was 323.17 with the lowest FI 44.18 on PI88788 and the highest FI 97.83 on PI548316 in the HG type test. ZDD2315 and ZDD24656 are elite resistant germplasms in China. ZDD2315 is highly resistant to race 4, the strongest infection race in the 16 races with FI 1.51 while being highly sensitive to race X12 with FI 64.32. ZDD24656, a variety derived from PI437654 and ZDD2315, is highly resistant to race 1 and race 2. ZDD24656 is highly sensitive to race X12 with FI 99.12. Morphological and molecular studies of J2 and cysts confirmed the population as the SCN H. glycines. This is a new SCN race with stronger virulence than that of race 4 and is a potential threat to soybean production in China

Geo6D: Geometric Constraints Learning for 6D Pose Estimation

Numerous 6D pose estimation methods have been proposed that employ end-to-end regression to directly estimate the target pose parameters. Since the visible features of objects are implicitly influenced by their poses, the network allows inferring the pose by analyzing the differences in features in the visible region. However, due to the unpredictable and unrestricted range of pose variations, the implicitly learned visible feature-pose constraints are insufficiently covered by the training samples, making the network vulnerable to unseen object poses. To tackle these challenges, we proposed a novel geometric constraints learning approach called Geo6D for direct regression 6D pose estimation methods. It introduces a pose transformation formula expressed in relative offset representation, which is leveraged as geometric constraints to reconstruct the input and output targets of the network. These reconstructed data enable the network to estimate the pose based on explicit geometric constraints and relative offset representation mitigates the issue of the pose distribution gap. Extensive experimental results show that when equipped with Geo6D, the direct 6D methods achieve state-of-the-art performance on multiple datasets and demonstrate significant effectiveness, even with only 10% amount of data

Associations between urinary paraben levels and obesity of 10-year-old children

BackgroundParabens, a widely used class of preservatives, are suspected to be potential obesogens as emerging endocrine disrupting chemicals with reproductive and developmental toxicity. ObjectiveTo analyze five urinary parabens (PBs) and estimate the associations of exposure to PBs with adiposity measures in 10-year-old school-age children. MethodsA total of 471 school-age children aged 10 years from the Sheyang Mini Birth Cohort were enrolled in this study. A questionnaire survey was conducted to collect socio-demographic information, physical activity, and dietary intake. Weight, height, and waist circumference of children were measured, and age- and sex-adjusted body mass index (BMI-Z score) was calculated. Spot urine samples were collected during the follow-up visits. Urinary concentrations of five PBs including methyl-paraben (MeP), ethyl-paraben (EtP), propyl-paraben (PrP), butyl-paraben (BuP), and benzyl-paraben (BzP) were detected by gas chromatography-tandem mass spectrometry (GC-MS/MS). Generalized linear models (GLMs) and Bayesian kernel machine regression (BKMR) models were applied to estimate associations of individual/overall urinary PBs concentrations with BMI Z-score and waist circumference. ResultsThe positive rates of selected five urinary PBs were in the range from 78.98% to 98.94%. The urinary PBs concentrations (geometric mean) were in the range of 0.31-5.43 μg·L−1. The children's BMI Z-score and waist circumference (mean ± standard deviation) were (0.56±1.40) and (67.62±10.07) cm respectively. The GLMs results showed that the urinary BzP concentration was negatively associated with waist circumference (b=−0.08, 95%CI: −0.14, −0.02; P=0.01). In sex-stratified analysis, the urinary concentration of BzP was negatively associated with BMI-Z score (b=−0.59, 95%CI: −0.88, −0.30; P<0.001) and waist circumference (b=−0.80, 95%CI: −1.23, −0.37; P<0.001) in boys, but not in girls. The BKMR results also found significant negative correlations of urinary BzP concentrations with BMI-Z score and waist circumference, which were consistent with the GLM results. ConclusionThe selected 10-year-old children are extensively exposed to PBs in the study area. Furthermore, childhood PBs exposure may have potential impacts on childhood adiposity measures with sex-specific effects

Expression map of a complete set of gustatory receptor genes in chemosensory organs of \u3cem\u3eBombyx mori\u3c/em\u3e

Most lepidopteran species are herbivores, and interaction with host plants affects their gene expression and behavior as well as their genome evolution. Gustatory receptors (Grs) are expected to mediate host plant selection, feeding, oviposition and courtship behavior. However, due to their high diversity, sequence divergence and extremely low level of expression it has been difficult to identify precisely a complete set of Grs in Lepidoptera. By manual annotation and BAC sequencing, we improved annotation of 43 gene sequences compared with previously reported Grs in the most studied lepidopteran model, the silkworm, Bombyx mori, and identified 7 new tandem copies of BmGr30 on chromosome 7, bringing the total number of BmGrs to 76. Among these, we mapped 68 genes to chromosomes in a newly constructed chromosome distribution map and 8 genes to scaffolds; we also found new evidence for large clusters of BmGrs, especially from the bitter receptor family. RNA-seq analysis of diverse BmGr expression patterns in chemosensory organs of larvae and adults enabled us to draw a precise organ specific map of BmGr expression. Interestingly, most of the clustered genes were expressed in the same tissues and more than half of the genes were expressed in larval maxillae, larval thoracic legs and adult legs. For example, BmGr63 showed high expression levels in all organs in both larval and adult stages. By contrast, some genes showed expression limited to specific developmental stages or organs and tissues. BmGr19 was highly expressed in larval chemosensory organs (especially antennae and thoracic legs), the single exon genes BmGr53 and BmGr67, were expressed exclusively in larval tissues, the BmGr27–BmGr31 gene cluster on chr7 displayed a high expression level limited to adult legs and the candidate CO2 receptor BmGr2 was highly expressed in adult antennae, where few other Grs were expressed. Transcriptional analysis of the Grs in B. mori provides a valuable new reference for finding genes involved in plant-insect interactions in Lepidoptera and establishing correlations between these genes and vital insect behaviors like host plant selection and courtship for mating