Wildlife crimes that involve smuggling threaten national security and biodiversity, cause regional conflicts, and hinder economic development, especially in developing countries with abundant wildlife resources. Over the past few decades, significant headway has been made in combating wildlife smuggling and the related illegal domestic trade in China. Previous studies on the wildlife smuggling trade were based mainly on customs punishment and confiscation data. From the China Judgments Online website, we retrieved cases related to cross-border wildlife and wildlife products smuggling from 2014 to 2020. In total, 510 available cases and 927 records for more than 110 species were registered. We studied each judgment and ruling file thoroughly to extract information on cases, defendants, species, sentences, and origins and destinations of wildlife and wildlife products. Furthermore, the frequency of origin-destination place occurrences and spatial patterns of cross-border wildlife crime in China were shown in this data paper. The main purpose of our data set is to make these wildlife and wildlife products trade data accessible for researchers to develop conservation studies. We expect that this data set will be valuable for network analysis of regional or global wildlife trafficking, which has attracted global attention. There are no copyright restrictions on the data; we ask that researchers please cite this paper and the associated data set when using the data in publications.
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http://dx.doi.org/10.1002/ecy.4046 | DOI Listing |
PLoS Genet
January 2025
Department of Human Genetics, The University of Chicago, Chicago, Illinois, United States of America.
Understanding the genetic regulatory mechanisms of gene expression is an ongoing challenge. Genetic variants that are associated with expression levels are readily identified when they are proximal to the gene (i.e.
View Article and Find Full Text PDFPLoS One
January 2025
Department of Civil and Environmental Engineering, Nazarbayev University, Nur-Sultan, Kazakhstan.
Rainfall-induced landslides are a frequent geohazard for tropical regions with prevalent residual soils and year-round rainy seasons. The water infiltration into unsaturated soil can be analyzed using the soil-water characteristic curve (SWCC) and permeability function which can be used to monitor and predict incoming landslides, showing the necessity of selecting the appropriate model parameter while fitting the SWCC model. This paper presents a set of data from six different sections of the studied slope at varying depths that are used to test the performance of three SWCC models, the van Genuchten-Mualem (vG-M), Fredlund-Xing (F-X) and Gardner (G).
View Article and Find Full Text PDFAnal Bioanal Chem
January 2025
Institute of Chemistry, Analytical Chemistry, University of Graz, Graz, Austria.
This work provides a statistical analysis of four different approaches suggested in the literature for the estimation of an unknown concentration based on data collected using the standard addition method. These approaches are the conventional extrapolation approach, the interpolation approach, inverse regression, and the normalization approach. These methods are compared under the assumption that the measurement errors are normally distributed and homoscedastic.
View Article and Find Full Text PDFMicrobiol Spectr
January 2025
Department of Biology, Appalachian State University, Boone, North Carolina, USA.
Unlabelled: Testing for the causative agent of coronavirus disease 2019 (COVID-19), severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been crucial in tracking disease spread and informing public health decisions. Wastewater-based epidemiology has helped to alleviate some of the strain of testing through broader, population-level surveillance, and has been applied widely on college campuses. However, questions remain about the impact of various sampling methods, target types, environmental factors, and infrastructure variables on SARS-CoV-2 detection.
View Article and Find Full Text PDFAntimicrob Agents Chemother
January 2025
InsightRX, San Francisco, California, USA.
Tobramycin dosing in patients with cystic fibrosis (CF) is challenged by its high pharmacokinetic (PK) variability and narrow therapeutic window. Doses are typically individualized using two-sample log-linear regression (LLR) to quantify the area under the concentration-time curve (AUC). Bayesian model-informed precision dosing (MIPD) may allow dose individualization with fewer samples; however, the relative performance of these methods is unknown.
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