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In China, rural settlements have undergone significant changes in response to dramatic socioeconomic shifts. However, there has not been any report on rural settlements in the Lijiang River Basin. In this study, ArcGIS 10.2 (including hot spot analysis and kernel density estimation) and Fragstats 4.2 (such as the landscape pattern index) software were used to analyze the spatial pattern and causes of rural settlements in the Lijiang River Basin. The Lijiang River Basin is mainly dominated by micro- and small-sized rural settlements with small areas. Moreover, the results of a hot spot analysis showed that micro- and small-sized rural settlements were mainly located in the upper reaches, and medium- and large-sized rural settlements were mainly located in the middle and lower reaches. The kernel density estimation results showed that the distribution characteristics of the rural settlements in the upper, middle, and lower reaches were significantly different. The spatial forms of rural settlements were affected by physiographic factors such as elevation and slope, karst landforms, and river trunk channels as well as the national policy system, tourism economic development, town distribution, historical heritage, and minority culture. This study is the first to systematically elaborate on the rural settlement pattern and its internal logic from the perspective of the Lijiang River Basin, providing a basis for the optimization and construction of the rural settlement pattern.

Time-of-use price is an important means of demand side management, how to accurately divide peak and valley periods is an important problem to be solved. In this paper, an improved fuzzy c-means (FCM) clustering algorithm is proposed to solve the problem that traditional FCM clustering algorithm is sensitive to the initial clustering center and easy to fall into local optimal. This algorithm combines an improved particle swarm optimization (PSO) based on support vector machine regression (SVR) with FCM algorithm, makes full use of the strong global search ability of PSO, replaces FCM to find the clustering center at the beginning of iteration, makes it out of the local optimal, realizes fuzzy clustering, and thus classifies more accurate peak and valley periods. Finally, the improved algorithm is applied to an example of an industrial park, and a distributed energy storage system is set up. The effectiveness of the proposed method is verified by simulation.

Objective: Stroke is a leading cause of mortality and morbidity globally. This study aimed to analyze the burden and 30-year trends of ischemic stroke, intracerebral hemorrhage (ICH), and subarachnoid hemorrhage (SAH) in China.Methods: Data that include incidence and mortality of stroke in China from January 1, 1990 to December 31, 2019 were derived from the Global Burden of Disease (GBD) study 2019. The absolute numbers of incident cases and deaths over the time, and age-standardized rates per 100,000, such as age-standardized incidence rate (ASIR) and age-standardized mortality rate (ASMR), were analyzed.Results: In 2019, there were 3.9 (95% uncertainty intervals (UI) 3.4–4.5) million incident cases and 2.1 (3.4–4.5) million deaths related to stroke in China. The ASIR and ASMR of stroke in China was 200 (176–230) and 127 (110–144). From 1990 to 2019, the ASIR of ischemic stroke had increased by 35.0% (29.0–40.0) while the ASIR of ICH and SAH had decreased by −53.0% (−56.0 to −50.0) and by −39.0% (−44.0 to −35.0), respectively. The ASMR of ischemic stroke had increased by 3.0% (−26.0 to 16.0) while the ASMR of ICH and SAH had decreased by −48.0% (−59.0 to −38.0) and by −84.0% (−89.0 to −69.0), respectively.Conclusion: Although the incidence and mortality rates of stroke in China were decreased from 1990 to 2019, the number of incident cases and deaths nearly doubled. A sharp increase in the incidence rate of ischemic stroke was observed. A higher incidence rate of ischemic stroke in the women was also observed.

A strain WZ-01 that can improve the flavor of carrot juice was isolated from naturally fermented orange and identified as Lactobacillus plantarum by 16S rRNA sequence analysis. After inoculation into carrot juice, L. plantarum WZ-01 could proliferate rapidly, and the bacterial population increased from 5.5 × 104 to 5.3 × 108 CFU mL−1 in 48 h. Organic acids were produced, resulting in a decrease in the pH value. Fermentation simultaneously enhanced the antioxidant activity of carrot juice and slightly changed the color and carotenoids content of the carrot juice. Solid-phase microextraction-gas chromatography–mass spectrometry analysis showed that β-pinene and β-phellandrene disappeared, and the relative contents of α-pinene, sabinene and β-myrcene decreased, while some aldehydes and ketones were formed by fermentation. Fermentation by strain WZ-01 could significantly weaken the terpene flavor of carrot juice and improve its sensory qualities.

Okra (Abelmoschus esculentus), famous for its desired nutritional and medicinal values, could accumulate approximately 20% (w/w) seed oil dominated with unsaturated fatty acids (UFAs). However, the mechanism of oil biosynthesis and metabolic regulation in its seeds remains poorly understood. Here, storage oil profiles and transcriptome of okra seeds at different developmental stages were analyzed. Seed oil accumulated at a high rate during 21 to 28 days after flowering (DAF). Total of 136.6 million clean reads were obtained and 109,171 unigenes were assembled from the seed transcriptome. Differentially expressed genes among three developing stages of seeds were functionally annotated into the storage lipid metabolism pathway. Comparative analysis was performed for structural genes and transcription factor genes that participate in fatty acid biosynthesis, triacylglycerol assembly, oil body formation, and triacylglycerol degradation. A complex regulating network was built accordingly. Additionally, expressions of 12 key functional genes responsible for okra oil accumulation were examined by quantitative real-time PCR (qRT-PCR), demonstrating that RNA-sequencing data were reliable. This study will facilitate further investigation of molecular mechanism responsible for unsaturated fatty acid biosynthesis and oil accumulation in plant seed, providing valued reference for creating new okra varieties with better lipid composition and high oil yield.

Overexpression of the global regulator LaeA in a marine-derived fungal strain of Penicillium dipodomyis YJ-11 induced obvious morphological changes and metabolic variations. Further chemical investigation of the mutant strain afforded a series of sorbicillinoids including two new ones named 10,11-dihydrobislongiquinolide (1) and 10,11,16,17-tetrahydrobislongiquinolide (2), as well as four known analogues, bislongiquinolide (3), 16,17-dihydrobislongiquinolide (4), sohirnone A (5), and 2&prime, 3&prime, dihydrosorbicillin (6). The results support that the global regulator LaeA is a useful tool in activating silent gene clusters in Penicillium strains to obtain previously undiscovered compounds.

Okra (Abelmoschus esculentus) is a well-known nutritional and health-benefit vegetable crop worldwide. Quantitative real-time PCR (qPCR) is an effective approach to characterize gene functions, and for such analysis, it is crucial to select the optimal reference genes. However, no systematic evaluation of reference genes was performed in okra. Here, to characterize expression profiles of genes involved in lipid biosynthesis and oil accumulation in okra, nine okra genes including ACT4, EF1a, MZA, PP2A, FBX, RAN, UBQ7, TUBα, and UBC selected from transcriptome sequencing data were examined with respect to their suitability as reliable reference genes. The expression stability of the nine candidates was assessed by four statistical algorithms (geNorm, NormFinder, BestKeeper and RankAggreg). Notably, MZA and PP2A were identified as the stable reference genes for different developmental seeds while EF1a was the optimal reference gene for different okra tissues. RAN was the highest-ranked reference gene for seed samples of different okra genotypes. Conversely, TUBα was not suitable reference gene in all the experimental conditions. The expression profiles of six lipid biosynthesis-related genes (AeFAD2, AeSAD, AeDGAT1, AeDGAT2, AePDAT1 and AePDAT2) were investigated by qPCR to evaluate the effectiveness and reliability of the reference genes identified. When MZA, PP2A and EF1a, the most suitable reference genes, were employed to normalize the expression data of these six genes in okra, the expression patterns of the six genes were consistent with the results of transcriptome. The present findings provide valuable data for further research on molecular mechanism of lipid biosynthesis and also the basis to select the reliable reference genes for gene expression and functional genomics studies in okra.

In large-space building, the distribution of vertical temperature has obvious difference. According to this feature, the energy consumption in air-conditioning would be greatly reduced if the designs of airflow are preferable in these buildings. The low sidewall air supply system is widely installed in the large-space buildings since it can directly sent the handled air to the personnel activity area, thereby has lower energy consumption than other systems. In this paper, a Gebhart-Block synchronous solving model is built to solve the vertical temperature distribution of an actual large-space building with low sidewall air supply system. The simulative physical model is divided into eight blocks in the vertical direction. According to the mechanism of heat transfer, unsteady-state heat balance equation is established for indoor air and wall in each block. The unsteady and synchronous solving model is established with integrating these balance equations. Furthermore, to predict the temperature distribution of indoor air and inner wall surface, the theoretical values of this model are calculated with programming by Visual Basic.

In order to detect the crack width of the concrete surface, we propose an algorithm of local rotation of images. Firstly, we calculate the normal direction of the given point in the crack to get the rotation angel. Secondly, we take a sub-image centering in the point, and rotate the sub-image around the point to make the crack in the sub-image changing to be vertical. Finally, the crack width is defined by the number of pixels on the line where the point is. By this algorithm, we can calculate the width of every cross-section on the entire crack, and the automation of the crack width detection will be come true. Based on this, we can also derive the crack length through the number of pixels on the crack (area) and the crack width. Theoretical analysis and numerical experiments show that this algorithm has high precision and good stability.