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Purposes How to perform bias-correction for precipitation data based on terrain information has been an important problem in meteorological big data research. However, the existing precipitation terrain-based bias-correction methods mostly suffer from two limitations. First, most of them are designed based on statistical models or conventional machine learning models, thus fails to go beyond to the deep learning models with more powerful feature learning ability. Second, they also lack the ability to incorporate the spatiotemporal correlation information in meteorological data for enhancing the bias-correction quality. Methods To address these limitations, in this paper, a terrain-based bias-correction method for precipitation data based on deep learning and spatiotemporal correlation modeling is presented. First, the precipitation data and multi-source terrain information with alignment and encoding based on the longitude and latitude are preprocessed, and thus the corresponding data matrices are constructed. Then the precipitation and terrain data in the spatial and temporal neighborhood of each grid are adopted to achieve the multi-source spatiotemporal information modeling, and a down-sampling strategy is used to alleviate the imbalance between the precipitation grids and the non-precipitation grids. Finally, the deep neural network is constructed for regression and bias-correction. The experiments are conducted on the real meteorological data from over 4 000 meteorological observation stations and over 150 thousand meteorological grids in Guangdong Province. Findings Experimental results have verified the significance influence of the spatiotemporal modeling strategy over precipitation bias correction quality and performance advantage of the proposed method over the baseline methods.

In this study, poly 4-vinylpyridine-modified multilayered mesoporous silica (FS-VP) was synthesized by radiation grafting, and the effects of the synthesis conditions on the grafting ratio were investigated. The results of Fourier transform infrared (FTIR) spectroscopy, X-ray photoelectron spectroscopy (XPS), and thermogravimetric analysis (TGA) indicated that the grafting ratio of FS-VP reached the maximum value of 27.8% under the following conditions: 4-vinylpyridine (4-VP) monomer concentration, 50%; radiation dose rate, 3 kGy/h; and absorbed dose, 72 kGy. In addition, quaternized FS-VP (FS-VPQ) was prepared, and its adsorption performance for Re(VII) was also studied. The adsorption capacities were the maximum at pH 2 and 3. The adsorption isotherm of FS-VPQ for Re(VII) conformed to the Langmuir model. The saturated adsorption capacity reached 68.0 mg/g at pH 3. The high adsorption capacity was attributed to the high specific surface area of the multilayered pore structure and the two inherent positive charges of the adsorbent after quaternization. Moreover, due to the high mass transfer rate resulting from the multilayered pore structure, FS-VPQ reached adsorption equilibrium within 3 min. The findings of this study provide theoretical guidance for Re separation and enrichment technology, and also can serve as reference for the separation of Tc from radioactive waste liquids.

Aging‐associated renal dysfunction promotes the pathogenesis of chronic kidney disease. Mitochondrial dysfunction in renal tubular epithelial cells is a hallmark of senescence and leads to accelerated progression of renal disorders. Dysregulated calcium profiles in mitochondria contribute to aging‐associated disorders, but the detailed mechanism of this process is not clear. In this study, modulation of the sirtuin 1/angiotensin II type 1 receptor (Sirt1/AT1R) pathway partially attenuated renal glomerular sclerosis, tubular atrophy, and interstitial fibrosis in D‐galactose (D‐gal)‐induced accelerated aging mice. Moreover, modulation of the Sirt1/AT1R pathway improved mitochondrial dysfunction induced by D‐gal treatment. Transient receptor potential channel, subtype C, member 3 (TRPC3) upregulation mediated dysregulated cellular and mitochondrial calcium homeostasis during aging. Furthermore, knockdown or knockout (KO) of Trpc3 in mice ameliorated D‐gal‐induced mitochondrial reactive oxygen species production, membrane potential deterioration, and energy metabolism disorder. Mechanistically, activation of the AT1R/PKA pathway promoted CREB phosphorylation and nucleation of CRE2 binding to the Trpc3 promoter (−1659 to −1648 bp) to enhance transcription. Trpc3 KO significantly improved the renal disorder and cell senescence in D‐gal‐induced mice. Taken together, these results indicate that TRPC3 upregulation mediates age‐related renal disorder and is associated with mitochondrial calcium overload and dysfunction. TRPC3 is a promising therapeutic target for aging‐associated renal disorders. [ABSTRACT FROM AUTHOR]

Soybean frogeye leaf spot (FLS) disease is a global disease affecting soybean yield, especially in the soybean growing area of Heilongjiang Province. In order to realize genomic selection breeding for FLS resistance of soybean, least absolute shrinkage and selection operator (LASSO) regression and stepwise regression were combined, and a genomic selection model was established for 40 002 SNP markers covering soybean genome and relative lesion area of soybean FLS. As a result, 68 molecular markers controlling soybean FLS were detected accurately, and the phenotypic contribution rate of these markers reached 82.45%. In this study, a model was established, which could be used directly to evaluate the resistance of soybean FLS and to select excellent offspring. This research method could also provide ideas and methods for other plants to breeding in disease resistance. [ABSTRACT FROM AUTHOR]