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The frequency of extreme weather events has increased worldwide, leading to more intense natural disasters, which pose significant threats to human life and property safety. The main form of disaster occurrence is multi-hazard coupling and multi-hazard chaining. This paper constructs a road natural disaster risk assessment model using a fuzzy comprehensive evaluation method and neural network to quantitatively analyze road disasters with multiple hazards, and provides valuable insights for the predication of road natural disaster risk. Here, ten factors, including temperature, relative humidity, precipitation, elevation, slope, slope orientation, vegetation cover, geologic lithology, historical impact factors, and road density, were selected as input variables, and risk grade was selected as the output value (the evaluation results). The remaining hidden layers use the fully connected neural network. This model was first trained using historical data (from 2011 to 2021) obtained from road networks and natural disasters in Guangxi, China. Then, taking Lingchuan County as an example, the model was used to predict the risk of natural disasters on its roads, and, finally, the prediction accuracy of the model was determined by comparing the results with actual disaster situations. This study can provide theoretical support and technical operations for the development of subsequent early warning systems. [ABSTRACT FROM AUTHOR]

The Ningxiang pig, a distinguished local breed in China, is recognized for its good meat quality traits. This study examines the proteomics of Ningxiang pigs at three developmental stages and delves into the upstream transcriptomics of these proteomics. Such an analysis facilitates a deeper understanding of the molecular interplay between proteins and transcriptomes in the Ningxiang pig muscle, influencing muscle growth and development. In this research, we analyzed the muscles of Ningxiang pigs at three developmental stages: 30 days in weaned piglets, 90 days in nursery pigs, and 210 days in late fattening pigs. There a total of 16 differentially co-expressed miRNAs (ssc-miRNA-1, ssc-miRNA-378, ssc-miRNA-143, ssc-miRNA-30e, etc.), 74 differentially co-expressed mRNA ( PLIN3 , CPT2 , IGF2 and HSP90AB1 , etc.) have been identified in the three stages. 572 differentially abundant proteins (DAPs) ( APOC3 , NDUFA2 , HSPD1 , ATP5E , PDHA1 , etc.) were readily identified by comparing different time periods. According to the KEGG enrich pathway results that DAPs most enriched in growth and development pathways, immune mechanism pathways and maintaining functions of physical. Through short time-series expression miner (STEM) association analysis, a total of 571 negative miRNA-mRNA interaction pairs and 2 negative miRNA-mRNA-protein (Chr05_11955-Pig.17268.1- ATP5F1B , ssc-miR-194a-3p-Pig.15802.1- ACY1 ) interaction pairs were found. Our study provides a theoretical basis on molecular mechanism for the study of IMF deposition, muscle growth and immunity in Ningxiang pig breed., Competing Interests: Author SZ employed by Yunnan Southwest Agriculture and Animal Husbandry Group Co., Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Chen, Xiao, Yang, Liufu, Gong, Li, Zhang, Tang, Li and Ma.)