LEEC: A Legal Element Extraction Dataset with an Extensive Domain-Specific Label System

As a pivotal task in natural language processing, element extraction has gained significance in the legal domain. Extracting legal elements from judicial documents helps enhance interpretative and analytical capacities of legal cases, and thereby facilitating a wide array of downstream applications in various domains of law. Yet existing element extraction datasets are limited by their restricted access to legal knowledge and insufficient coverage of labels. To address this shortfall, we introduce a more comprehensive, large-scale criminal element extraction dataset, comprising 15,831 judicial documents and 159 labels. This dataset was constructed through two main steps: first, designing the label system by our team of legal experts based on prior legal research which identified critical factors driving and processes generating sentencing outcomes in criminal cases; second, employing the legal knowledge to annotate judicial documents according to the label system and annotation guideline. The Legal Element ExtraCtion dataset (LEEC) represents the most extensive and domain-specific legal element extraction dataset for the Chinese legal system. Leveraging the annotated data, we employed various SOTA models that validates the applicability of LEEC for Document Event Extraction (DEE) task. The LEEC dataset is available on https://github.com/THUlawtech/LEEC

Demographics, behaviours, and preferences of birdwatchers and their implications for avitourism and avian conservation: A case study of birding in Nonggang, Southern China

Birding, a sustainable ecotourism, capitalizes on the community's rich bird resources to attract an increasing number of birdwatchers. However, the influence of the preferences and behaviour of birdwatchers during birding is unclear. Here, we explore the demographics, behaviours, and preferences of birdwatchers using a case study of birding in Nonggang, southern China. The data was collected from a survey of 201 birdwatchers between April 2017 and April 2018. Results demonstrated that respondents were mainly male, middle-aged, middle-to-high income, and higher-educated. When birding, 96.0% of respondents would photograph birds, and 45.3% prefer photography at fixed-points (i.e., bird-pond photography). Respondents' primary photographic subjects were more likely to be birds with narrower distribution ranges, lower encounter rates, or more feather colors. The majority of the respondents had a strong sense of protection, although the level of awareness against injuring birds was average. Our findings suggest that bird-pond photography has become the dominant form of birding. Solving the relationship between bird photographers' preferences and the conservation of unique species requires an understanding of the rare species and the value of wildlife viewing recreation by humans

Effects of follicle-stimulating hormone beta subunit and nuclear receptor coactivator 1 gene polymorphisms and expressions on pink-eyed white mink reproductive traits

The present study was designed to investigate comparative expressions of follicle-stimulating hormone beta subunit (FSHβ) and nuclear receptor coactivator 1 (NCOA1) genes by real-time polymerase chain reaction, using polymerase chain reaction single-strand conformation polymorphism methods to investigate the effects of gene polymorphisms on reproductive traits, including total number of kits born (TNB) and number of born alive (NBA) in pink-eyed white mink. Four single-nucleotide polymorphisms were identified in the FSHβ and NCOA1 genes. The g.1228G>A polymorphism of FSHβ was associated with NBA and TNB (P C polymorphism of NCOA1 was associated with NBA and TNB (P C polymorphism of FSHβ and the g.151536T>C polymorphism of NCOA1 could be molecular markers for reproductive traits, and expressions of FSHβ and NCOA1 might be involved in the regulation of embryo attachment mechanisms in pink-eyed white mink breeding.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Analyses of artificial morel soil bacterial community structure and mineral element contents in ascocarp and the cultivated soil

This study explored the differences among different artificial morel cultivations and the influential factors, including soil bacterial community structure, yield, and mineral element contents of ascocarp and the cultivated soil. High-throughput sequencing results revealed that the dominant bacterial phyla in all the samples, including Proteobacteria, Acidobacteria, Chloroflexi, Bacteroides and Gemmatimonadetes, were found not only in morel soils (experimental group) but also in wheat soil (control group), while the highest richness and diversity in the soil bacteria were observed during the primordial differentiation stage. M6 group exhibited the highest yield (271.8g/m2) and had an unexpectedly high proportion of Pseudomonas (25.30%) during the primordial differentiation stage, which was 1.77ď˝ 194.62 times more than the proportion of Pseudomonas in other samples. Pseudomonas may influence the growth of morel. Mineral element contents of the varied soil groups and ascocarp were determined using electro thermal digestion and inductively coupled plasma mass spectrometry. The results revealed that morel had high enrichment effects on Phosphorus (P, Bioconcentration factor = 16.83), Potassium (K, 2.18), Boron (B, 1.47), Zinc (Zn, 1.36), Copper (Cu, 1.15) and Selenium (Se, 2.27). P levels were the highest followed by Se and K, and the mineral element contents in ascocarp were positively correlated with the soil element contents.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

The Genetic Diversity of Mink (<i>Neovison vison</i>) Populations in China

The American mink (Neovison vison) is a semiaquatic species of Mustelid native to North America that is now widespread in China. However, the knowledge of genetic diversity of mink in China is still limited. In this study, we investigated the genetic diversity and identified significant single nucleotide polymorphisms (SNPs) in mink populations of five different color types in three different mink farms in China. Using double-digest restriction site-associated DNA sequencing, we identified a total of 1.3 million SNPs. After filtering the SNPs, phylogenetic tree, Fst, principal component, and population structure analyses were performed. The results demonstrated that red mink and black mink grouped, with separate clustering of all other color types. The population divergence index (Fst) study confirmed that different mink populations were distinct (K = 4). Two populations with different coat colors were subjected to the selection signature analysis, and 2300 genes were found to have a clear selection signature. The genes with a selection signature were subjected to Gene Ontology (GO) categorization and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, the results revealed that the genes with a selection signature were enriched in the melanogenesis pathway. These study’s findings have set the stage for improved breeding and conservation of genetic resources in real-world practical mink farming

EPDet: Enhancing point clouds features with effective representation for 3D object detection

Effective 3D object detection relies on strong feature representation. Both global features and representative characteristics of the objects are vital for detection. However, traditional convolution’s perception range limits large receptive fields, and current object feature representation has room for enhancement. Addressing these concerns, we introduce a 3D outdoor object detector to enhance the point clouds feature, referred to as EPDet. Specifically, for global features, we propose a BEV-Offset Transformer in the BEV (Bird’s Eye View) domain. This adaptable module enhances semantic connections among objects, suiting various 3D detection methods. In addition, to refine point cloud features, we employ Focal Conv as our 3D ( 3-dimensional) backbone, exploring multi-modal fusion effects. In the 2D (2-dimensional) backbone, our Pyramid-like Conv captures detailed contextual features. EPDet performs well in the dense object scene owing to scene-wide global features captured by BEV Offset Transformer. In the multi-class tests, EPDet excels in detecting smaller objects due to more refined features represented by Focal Conv and Pyramid-like Conv. In experiments, as a plug-and-play module, we validate the BEV Offset Transformer’s effectiveness across single-stage (SECOND), two-stage (Voxel-RCNN), and multi-stage (CasA) algorithms. Robustness is tested on KITTI, NuScenes, and ONCE datasets. The proposed EPDet, in the KITTI subset, EPDet (CasA-based) achieves an impressive 85.56% accuracy in the car category. EPDet (Voxel-RCNN-based) surpassed baseline 1.65% mAP (mean Average Precision) (moderate subsets) in multi-class detection. The precision of EPDet is on par with the SotA (State of the Art) 3D outdoor object detectors based on point clouds

MicroRNA-92a as a potential biomarker in diagnosis of colorectal cancer: a systematic review and meta-analysis.

INTRODUCTION: Previous studies demonstrated that MicroRNA-92a (miR-92a) was significantly differential expressed between colorectal cancer (CRC) patients and control cohorts, which provide timely relevant evidence for miR-92a as a novel promising biomarker in the colorectal cancer patients. This meta-analysis aimed to evaluate potential diagnostic value of plasma miR-92a. METHODS: Relevant literatures were collected in PubMed, Embase, Chinese Biomedical Literature Database (CBM), Chinese National Knowledge Infrastructure (CNKI) and Technology of Chongqing (VIP), and Wan Fang Data. Sensitivity, specificity and diagnostic odds ratio (DOR) for miR-92a in the diagnosis of CRC were pooled using random effects models. Summary receiver operating characteristic (SROC) curve analysis and the area under the curve (AUC) were used to estimate the overall test performance. RESULTS: This Meta-analysis included six studies with a total of 521 CRC patients and 379 healthy controls. For miR-92a, the pooled sensitivity, specificity and DOR to predict CRC patients were 76% (95% confidence interval [CI]: 72%-79%), 64% (95% confidence interval [CI]: 59%-69%) and 8.05 (95% CI: 3.50-18.56), respectively. In addition, the AUC of miR-92a in diagnosis CRC is 0.7720. CONCLUSIONS: MicroRNA-92a might be a novel potential biomarker in the diagnosis of colorectal cancer, and more studies are needed to highlight the theoretical strengths