The primary purpose of this research is to understand those elements that define heavy metals contamination and to propose a novel assessment method based on principal component analysis (PCA) in the Yangping River region of Lingbao City, China. This paper makes detailed calculations regarding such factors the single-factor assessment (Pi) and Nemerow's multi-factor index (PN) of heavy metals found in the surface water of the Yangping River. The maximum values of Pi (Cd) and Pi (Pb) were determined to be 892.000 and 113.800 respectively. The maximum value of PN was calculated to be 639.836. The results of Pearson's correlation analysis, hierarchical cluster analysis, and PCA indicated heavy metal groupings as follows: Cu, Pb, Zn and As, Hg, Cd. The PCA-based pollution index (Pαn) of samplings was subsequently calculated. The relative coefficient square was valued at 0.996 between Pαn and PN, which indicated that Pαn is able to serve as a new heavy metal pollution index; not only this index able to eliminate the influence of the maximum value of Pi, but further, this index contains the principal component elements needed to evaluate heavy metal pollution levels.

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Dehong humped cattle are precious livestock resources of Yunnan Province, China; they have typical zebu traits. Here, we investigated their genetic characteristics using whole-genome resequencing data of Dehong humped animals (n = 18). When comparing our data with the publicly-available data, we found that Dehong humped cattle have high nucleotide diversity. Based on clustering models in a population structure analysis, Dehong humped cattle had a mutual genome ancestor with Chinese and Indian indicine cattle. While using the RFMix method, it is speculated that the body sizes of Dehong humped cattle were influenced by the Chinese indicine segments and that the immune systems of Dehong humped cattle were affected by additional ancestral segments (Indian indicine). Furthermore, we explored the position selection regions harboring genes in the Dehong humped cattle, which were related to heat tolerance (FILIP1L, ABHD6) and immune responses (GZMM, PRKCZ, STOML2, LRBA, PIK3CD). Notably, missense mutations were detected in the candidate gene ABHD6 (c.870C>A p.Asp290Glu; c.987C>A p.Ser329Arg). The missense mutations may have implications for Dehong humped cattle adaptation to hot environments. This study provides valuable genomic resource data at the genome-wide level and paves the way for future genetic breeding work in the Dehong humped cattle.

In order to improve the utilization rate of coal gangue as aggregate in concrete, based on the orthogonal experimental design method, the L16 (45) orthogonal table was used to initially prepare the mix ratio, and the concrete compressive specimens were poured, and their compressive strength was tested after standard curing for 7 days. The significance of the three factors of coal gangue ratio, coal gangue-sand ratio and water-binder ratio on strength was preliminarily understood. Then adjust the factor levels, use the L9 (34) orthogonal table to arrange the factor levels, formulate the mix ratio, test its strength after curing under the same conditions, and finally analyze that the optimal mix ratio of high-volume coal gangue concrete is 90% of coal gangue. Coal gangue sand accounts for 60% of the total sand, the water-binder ratio is 0.4, the sand rate is 35%, and the amount of cement per cubic meter is 350 kg. This mix ratio can use a large amount of coal gangue as a concrete cushion or sub-base in road engineering.

The probability of surface collapse, landslide, collapse and debris flow is very high in hilly and mountainous areas of Mianchi County of western Henan province. The article obtained geological hazard district of Mianchi County though the analytic hierarchy process(AHP) to carry on the geological hazard risk assessment in the study area. Eight disaster-inducing factors were selected the density of disasters, slope gradient, slope height, slope shape, rock-soil body types, vegetation index, rainfall index, and engineering activity intensity based on the GIS platform and combined with the field investigation result of geological disaster points.