As an important river in the western part of Jilin Province,the lower reach of the Nenjiang River is an important wetland water source conservation area in Jilin Province.Within the watershed,it governs the Momoge Wet...As an important river in the western part of Jilin Province,the lower reach of the Nenjiang River is an important wetland water source conservation area in Jilin Province.Within the watershed,it governs the Momoge Wetland,the Xianghai Wetland,and the Danjiang Wetland in Jilin Province.The main problem in the lower reaches of the Nenjiang River is the uneven distribution of water resources in time and space,and the intensification of land salinization.Zhenlai County and Da an City in the Nenjiang River Basin have sufficient surface water resources,with surface water as the drinking water source.Baicheng City and Tongyu County have scarce surface water resources,and both use groundwater as their domestic water source.The main polluted section in the basin is the Xianghai Reservoir,and the annual water quality evaluation is Class V.However,the water quality of the Tao er River,the main stream of the Nenjiang River,is significantly better than that of the Xianghai Reservoir.In order to better study the water environmental pollution situation in the Nenjiang River basin,monitoring data from five sections of non seasonal rivers in the basin from 2012 to 2021 were selected for studying water quality.This in-depth exploration of the water pollution status and river water quality change trends in the Nenjiang River basin is of great significance for future rural development,agricultural pattern transformation,and the promotion of water ecological civilization construction.展开更多
In the Industrial Internet of Things(IIoT),sensors generate time series data to reflect the working state.When the systems are attacked,timely identification of outliers in time series is critical to ensure security.A...In the Industrial Internet of Things(IIoT),sensors generate time series data to reflect the working state.When the systems are attacked,timely identification of outliers in time series is critical to ensure security.Although many anomaly detection methods have been proposed,the temporal correlation of the time series over the same sensor and the state(spatial)correlation between different sensors are rarely considered simultaneously in these methods.Owing to the superior capability of Transformer in learning time series features.This paper proposes a time series anomaly detection method based on a spatial-temporal network and an improved Transformer.Additionally,the methods based on graph neural networks typically include a graph structure learning module and an anomaly detection module,which are interdependent.However,in the initial phase of training,since neither of the modules has reached an optimal state,their performance may influence each other.This scenario makes the end-to-end training approach hard to effectively direct the learning trajectory of each module.This interdependence between the modules,coupled with the initial instability,may cause the model to find it hard to find the optimal solution during the training process,resulting in unsatisfactory results.We introduce an adaptive graph structure learning method to obtain the optimal model parameters and graph structure.Experiments on two publicly available datasets demonstrate that the proposed method attains higher anomaly detection results than other methods.展开更多
Southerly moisture surges over the central South China Sea(SCS)are characterized by the strengthening of lowlevel southerlies that transport moisture northward from the Pacific or Indian Oceans to South China.These su...Southerly moisture surges over the central South China Sea(SCS)are characterized by the strengthening of lowlevel southerlies that transport moisture northward from the Pacific or Indian Oceans to South China.These surge events typically occur for days in the early-summer season(from April to June)and can lead to heavy rains in South China.This study categorizes surge events into three types of flow patterns and examines their multiscale variations and impacts on rainfall.The first type occurs mainly in April,with the southeasterlies enhanced by a deepening trough in South China and the western Pacific subtropical high established over the SCS.The second type of surge events mostly appears in June,featuring the prevailing southwesterlies of summer monsoon from the Indian Ocean during the active phases of intraseasonal oscillations.Most surge events exhibit semi-diurnal variations with morning and afternoon peaks of northward moisture fluxes.Specifically,the first type features a dominant afternoon peak,while the second type shows a dominant early-morning peak,which is induced by thermal contrast between the Indochina Peninsula and the SCS.In general,the surge events enhance moisture convergence and increase rainfall downstream in South China,but they show some regional differences.The second type strengthens moisture convergence and rainfall in coastal regions with a morning peak.In contrast,the first type enhances inland rainfall with a morning peak,while moisture divergence dominates coastal regions.The third type of surge events denotes transitional conditions between the first two types,in terms of atmospheric circulations,diurnal cycles,and rainfall patterns.These results highlight a diversity of regional moisture surges and related rainfall ranging from diurnal to sub-seasonal scales.展开更多
Subtropical evergreen broad-leaved trees are usually vulnerable to freezing stress,while hexaploid wild Camellia oleifera shows strong freezing tolerance.As a valuable genetic resource of woody oil crop C.oleifera,wil...Subtropical evergreen broad-leaved trees are usually vulnerable to freezing stress,while hexaploid wild Camellia oleifera shows strong freezing tolerance.As a valuable genetic resource of woody oil crop C.oleifera,wild C.oleifera can serve as a case for studying the molecular bases of adaptive evolution to freezing stress.Here,47 wild C.oleifera from 11 natural distribution sites in China and 4 relative species of C.oleifera were selected for genome sequencing.“Min Temperature of Coldest Month”(BIO6)had the highest comprehensive contribution to wild C.oleifera distribution.The population genetic structure of wild C.oleifera could be divided into two groups:in cold winter(BIO6≤0℃)and warm winter(BIO6>0℃)areas.Wild C.oleifera in cold winter areas might have experienced stronger selection pressures and population bottlenecks with lower N_(e) than those in warm winter areas.155 singlenucleotide polymorphisms(SNPs)were significantly correlated with the key bioclimatic variables(106 SNPs significantly correlated with BIO6).Twenty key SNPs and 15 key copy number variation regions(CNVRs)were found with genotype differentiation>50%between the two groups of wild C.oleifera.Key SNPs in cis-regulatory elements might affect the expression of key genes associated with freezing tolerance,and they were also found within a CNVR suggesting interactions between them.Some key CNVRs in the exon regions were closely related to the differentially expressed genes under freezing stress.The findings suggest that rich SNPs and CNVRs in polyploid trees may contribute to the adaptive evolution to freezing stress.展开更多
Analysis of spatial-temporal variations of desert vegetation under the background of climate changes can provide references for ecological restoration in arid and semi-arid areas. In this study, we used the Global Inv...Analysis of spatial-temporal variations of desert vegetation under the background of climate changes can provide references for ecological restoration in arid and semi-arid areas. In this study, we used the Global Inventory Modeling and Mapping Studies （GIMMS） NDVI data from 1982 to 2006 and Moderate Resolution Imaging Spectroradiometer （MODIS） NDVI data from 2000 to 2013 to reveal the dynamics of desert vegetation in Hexi region of Northwest China over the past three decades. We also used the annual temperature and precipitation data acquired from the Chinese meteorological stations to analyze the response of desert vegetation to climatic variations. The average value of NDVImax （the maximum NDVI during the growing season） for desert vegetation in Hexi region increased at the rate of 0.65x10-3/a （P〈0.05） from 1982 to 2013, and the significant increases of NDVImax mainly appeared in the typical desert vegetation areas. Vegetation was significantly improved in the lower reaches of Shule and Shiyang river basins, and the weighted mean center of desert vegetation mainly shifted toward the lower reaches of the two basins. Almost 95.32% of the total desert vegetation area showed positive correlation between NDVImax and annual precipitation, indicating that precipitation is the key factor for desert vegetation growth in the entire study area. Moreover, the areas with non-significant positive correlation between NDVImax and annual precipitation mainly located in the lower reaches of Shiyang and Shule river basins, this may be due to human activities. Only 7.64% of the desert vegetation showed significant positive correlation between NDVImax and annual precipitation in the Shule River Basin （an extremely arid area）, indicating that precipitation is not the most important factor for vegetation growth in this basin, and further studies are needed to investigate the mechanism for this phenomenon.展开更多
The prediction for Multivariate Time Series(MTS)explores the interrelationships among variables at historical moments,extracts their relevant characteristics,and is widely used in finance,weather,complex industries an...The prediction for Multivariate Time Series(MTS)explores the interrelationships among variables at historical moments,extracts their relevant characteristics,and is widely used in finance,weather,complex industries and other fields.Furthermore,it is important to construct a digital twin system.However,existing methods do not take full advantage of the potential properties of variables,which results in poor predicted accuracy.In this paper,we propose the Adaptive Fused Spatial-Temporal Graph Convolutional Network(AFSTGCN).First,to address the problem of the unknown spatial-temporal structure,we construct the Adaptive Fused Spatial-Temporal Graph(AFSTG)layer.Specifically,we fuse the spatial-temporal graph based on the interrelationship of spatial graphs.Simultaneously,we construct the adaptive adjacency matrix of the spatial-temporal graph using node embedding methods.Subsequently,to overcome the insufficient extraction of disordered correlation features,we construct the Adaptive Fused Spatial-Temporal Graph Convolutional(AFSTGC)module.The module forces the reordering of disordered temporal,spatial and spatial-temporal dependencies into rule-like data.AFSTGCN dynamically and synchronously acquires potential temporal,spatial and spatial-temporal correlations,thereby fully extracting rich hierarchical feature information to enhance the predicted accuracy.Experiments on different types of MTS datasets demonstrate that the model achieves state-of-the-art single-step and multi-step performance compared with eight other deep learning models.展开更多
Forest soil carbon is a major carbon pool of terrestrial ecosystems,and accurate estimation of soil organic carbon(SOC)stocks in forest ecosystems is rather challenging.This study compared the prediction performance o...Forest soil carbon is a major carbon pool of terrestrial ecosystems,and accurate estimation of soil organic carbon(SOC)stocks in forest ecosystems is rather challenging.This study compared the prediction performance of three empirical model approaches namely,regression kriging(RK),multiple stepwise regression(MSR),random forest(RF),and boosted regression trees(BRT)to predict SOC stocks in Northeast China for 1990 and 2015.Furthermore,the spatial variation of SOC stocks and the main controlling environmental factors during the past 25 years were identified.A total of 82(in 1990)and 157(in 2015)topsoil(0–20 cm)samples with 12 environmental factors(soil property,climate,topography and biology)were selected for model construction.Randomly selected80%of the soil sample data were used to train the models and the other 20%data for model verification using mean absolute error,root mean square error,coefficient of determination and Lin's consistency correlation coefficient indices.We found BRT model as the best prediction model and it could explain 67%and 60%spatial variation of SOC stocks,in 1990,and 2015,respectively.Predicted maps of all models in both periods showed similar spatial distribution characteristics,with the lower SOC in northeast and higher SOC in southwest.Mean annual temperature and elevation were the key environmental factors influencing the spatial variation of SOC stock in both periods.SOC stocks were mainly stored under Cambosols,Gleyosols and Isohumosols,accounting for 95.6%(1990)and 95.9%(2015).Overall,SOC stocks increased by 471 Tg C during the past 25 years.Our study found that the BRT model employing common environmental factors was the most robust method for forest topsoil SOC stocks inventories.The spatial resolution of BRT model enabled us to pinpoint in which areas of Northeast China that new forest tree planting would be most effective for enhancing forest C stocks.Overall,our approach is likely to be useful in forestry management and ecological restoration at and beyond the regional scale.展开更多
Empirical Orthogonal Function (EOF) was performed to investigate spatial variation in January precipitation over Pakistan using ground observed mean monthly precipitation data from 1950-2000 with a combination of grid...Empirical Orthogonal Function (EOF) was performed to investigate spatial variation in January precipitation over Pakistan using ground observed mean monthly precipitation data from 1950-2000 with a combination of gridded reanalysis data of sea level pressure (SLP) and 500 hPa geopotential height. The leading EOF mode captures 37.51% of the total variance and the spatial-temporal variability of January precipitation was consistent in the study area. The temporal changes explicate non-periodic interannual variability and some tacit interdecadal variation. The anomalous condition is more prominent along the western bordering mountains and northern high mountainous region than any other region of Pakistan. Based on results the study reveals spatial-temporal variation in January precipitation and possible links with global teleconnections located both in the proximity as well as in the remote areas from the study locus.展开更多
By making use of Empirical Orthogonal Function (EOF) analysis the spatial and temporal variability was investigated in January over the period of 1950 to 2000 in Pakistan. The analysis is based on the combination of g...By making use of Empirical Orthogonal Function (EOF) analysis the spatial and temporal variability was investigated in January over the period of 1950 to 2000 in Pakistan. The analysis is based on the combination of ground observed mean monthly temperature data and National Centre for Environmental Prediction (NCEP) reanalysis data of sea level pressure (SLP) and 500-hPa fields. The results reasonably reveal that the variation in January temperature have links with global teleconnections at SLP and 500-hPa pressure heights. The analysis shows variability at interannual to interdecadal time scale. The interannual variation is more prominent than the interdecadal signal of temperature anomaly. The simulated coefficient patterns show reasonable variation with regional detail from south (north) to north (south) in the study area. The study could be useful as baseline information for climate change studies in Pakistan.展开更多
Grid method is employed for sampling covering soil at the test field,whic h is reclamation area filled by coal mining wastes for cropland in th e Fushun coal mine,Liaoning Province,the Northeast China.The soil samp le...Grid method is employed for sampling covering soil at the test field,whic h is reclamation area filled by coal mining wastes for cropland in th e Fushun coal mine,Liaoning Province,the Northeast China.The soil samp les are taken at different locations,inclu ding three kinds of covering soil,th ree different depths of soil layers a nd four different covering ages of covering soil.The s patial-temporal variation of heavy metal element content in reclamatio n soil is stud-ied.The results indicate that the co ntent of heavy metal elements is decreasing year after year;the determin ant reason why the content of heavy metal elemen ts at 60cm depth layer is higher than t hat at 30cm depth layer and surface is fertiliz-er and manure application;the metal elements mainly come from external environment;there is no metal pollut ion coming from mother material(coal mining wastes)in plough layer of covering soil.展开更多
Using the daily precipitation data of 118 meteorological stations in Northwest China from January 1, 1961 to December 31,2010, we analyzed extreme precipitation events from prime precipitation data by applying R-langu...Using the daily precipitation data of 118 meteorological stations in Northwest China from January 1, 1961 to December 31,2010, we analyzed extreme precipitation events from prime precipitation data by applying R-language Climate Index （RClimDex）. The spatial-temporal change characteristics in the past 50 years have been examined using the method of trend analysis, Mann-Kendall and the spatial analysis module of Arcgis9.2. The results show that the spatial distribution of the indices for extreme precipitation in Northwest China is greatly influenced by geographic location, atmospheric circulation and topography, and the spatial difference of extreme precipitation events is very evident, while the indices reduce from the southeast to the northwest except Consecutive Dry Days （CDD）. In Xinjiang region, high values appear in Tianshan Mountains and decrease towards the south and north respectively. In the past 50 years, the temporal variation tendency of the indices for extreme precipitation in Northwest China has a great spatial distinction. It shows that the variation tendency is opposite between the east （decrease） and the west （increase）, and CDD has a decreasing tendency while other indices increase. For each region, it is found that the indices for extreme precipitation in Xinjiang and Qinghai Province shows an increasing trend, and it is remarkable in Tianshan Mountains, the north of Xinjiang and the northeast of Qinghai Province. The temporal variation tendency of the indices for extreme precipitation in Ningxia, Shaanxi and Gansu has a large spatial distinction. The stations which have an increasing tend are mainly found in the north of Ningxia, south of Shaanxi and Hexi Corridor of Gansu. However, the south of Ningxia, north of Shaanxi and Longnan of Gansu Province mainly present a decreasing trend. The temporal variation tendency of the indices for extreme precipitation in Inner Mongolia is not obvious. Overall, the east part of Northwest China has a dry tendency, while the west part has an opposite trend.展开更多
Background During approximately 10,000 years of domestication and selection,a large number of structural variations(SVs)have emerged in the genome of pig breeds,profoundly influencing their phenotypes and the ability ...Background During approximately 10,000 years of domestication and selection,a large number of structural variations(SVs)have emerged in the genome of pig breeds,profoundly influencing their phenotypes and the ability to adapt to the local environment.SVs(≥50 bp)are widely distributed in the genome,mainly in the form of insertion(INS),mobile element insertion(MEI),deletion(DEL),duplication(DUP),inversion(INV),and translocation(TRA).While studies have investigated the SVs in pig genomes,genome-wide association studies(GWAS)-based on SVs have been rarely conducted.Results Here,we obtained a high-quality SV map containing 123,151 SVs from 15 Large White and 15 Min pigs through integrating the power of several SV tools,with 53.95%of the SVs being reported for the first time.These high-quality SVs were used to recover the population genetic structure,confirming the accuracy of genotyping.Potential functional SV loci were then identified based on positional effects and breed stratification.Finally,GWAS were performed for 36 traits by genotyping the screened potential causal loci in the F2 population according to their corresponding genomic positions.We identified a large number of loci involved in 8 carcass traits and 6 skeletal traits on chromosome 7,with FKBP5 containing the most significant SV locus for almost all traits.In addition,we found several significant loci in intramuscular fat,abdominal circumference,heart weight,and liver weight,etc.Conclusions We constructed a high-quality SV map using high-coverage sequencing data and then analyzed them by performing GWAS for 25 carcass traits,7 skeletal traits,and 4 meat quality traits to determine that SVs may affect body size between European and Chinese pig breeds.展开更多
Background Domestic goose breeds are descended from either the Swan goose(Anser cygnoides)or the Greylag goose(Anser anser),exhibiting variations in body size,reproductive performance,egg production,feather color,and ...Background Domestic goose breeds are descended from either the Swan goose(Anser cygnoides)or the Greylag goose(Anser anser),exhibiting variations in body size,reproductive performance,egg production,feather color,and other phenotypic traits.Constructing a pan-genome facilitates a thorough identification of genetic variations,thereby deepening our comprehension of the molecular mechanisms underlying genetic diversity and phenotypic variability.Results To comprehensively facilitate population genomic and pan-genomic analyses in geese,we embarked on the task of 659 geese whole genome resequencing data and compiling a database of 155 RNA-seq samples.By constructing the pan-genome for geese,we generated non-reference contigs totaling 612 Mb,unveiling a collection of 2,813 novel genes and pinpointing 15,567 core genes,1,324 softcore genes,2,734 shell genes,and 878 cloud genes in goose genomes.Furthermore,we detected an 81.97 Mb genomic region showing signs of genome selection,encompassing the TGFBR2 gene correlated with variations in body weight among geese.Genome-wide association studies utilizing single nucleotide polymorphisms(SNPs)and presence-absence variation revealed significant genomic associations with various goose meat quality,reproductive,and body composition traits.For instance,a gene encoding the SVEP1 protein was linked to carcass oblique length,and a distinct gene-CDS haplotype of the SVEP1 gene exhibited an association with carcass oblique length.Notably,the pan-genome analysis revealed enrichment of variable genes in the“hair follicle maturation”Gene Ontology term,potentially linked to the selection of feather-related traits in geese.A gene presence-absence variation analysis suggested a reduced frequency of genes associated with“regulation of heart contraction”in domesticated geese compared to their wild counterparts.Our study provided novel insights into gene expression features and functions by integrating gene expression patterns across multiple organs and tissues in geese and analyzing population variation.Conclusion This accomplishment originates from the discernment of a multitude of selection signals and candidate genes associated with a wide array of traits,thereby markedly enhancing our understanding of the processes underlying domestication and breeding in geese.Moreover,assembling the pan-genome for geese has yielded a comprehensive apprehension of the goose genome,establishing it as an indispensable asset poised to offer innovative viewpoints and make substantial contributions to future geese breeding initiatives.展开更多
To better understand the spatial-temporal variation in phytoplankton community structure and its controlling factors in Jiaozhou Bay, Qingdao, North China, four seasonal sampling were carried out in 2017. The phytopla...To better understand the spatial-temporal variation in phytoplankton community structure and its controlling factors in Jiaozhou Bay, Qingdao, North China, four seasonal sampling were carried out in 2017. The phytoplankton community structure and various environmental parameters were examined. The phytoplankton community in the bay was composed of mainly diatoms and dinofl agellates, and several other species of Chrysophyta were also observed. Diatoms were the most dominant phytoplankton group throughout the year, except in spring and winter, when Noctiluca scintillans was co-dominant. High Si/N ratios in summer and fall refl ect the high dominance of diatoms in the two seasons. Temporally, the phytoplankton cell abundance peaked in summer, due mainly to the high temperatures and nutrient concentrations in summer. Spatially, the phytoplankton cell abundance was higher in the northern part of the bay than in the other parts of the bay in four seasons. The diatom cell abundances show signifi cant positive correlations with the nutrient concentrations, while the dinofl agellate cell abundances show no correlation or a negative correlation with the nutrient concentrations but a signifi cant positive correlation with the stratifi cation index. This discrepancy was mainly due to the diff erent survival strategies between diatoms and dinofl agellates. The Shannon-Wiener diversity index ( H′) values in the bay ranged from 0.08 to 4.18, which fell in the range reported in historical studies. The distribution pattern of H′ values was quite diff erent from that of chlorophyll a , indicating that the phytoplankton community structure might have high biomass with a low diversity index. Compared with historical studies, we believe that the dominant phytoplankton species have been changed in recent years due mainly to the changing environment in the Jiaozhou Bay in recent 30 years.展开更多
To address the mooring issues of floating photovoltaic systems in areas with large tidal variations,three mooring schemes were designed and compared in this paper:anchor chain,anchor chain with added weights,and ancho...To address the mooring issues of floating photovoltaic systems in areas with large tidal variations,three mooring schemes were designed and compared in this paper:anchor chain,anchor chain with added weights,and anchor chain with Superflex.The model was established via the numerical simulation tool Orcaflex,which considers the combined effects of wind,waves,and currents.A time-domain coupled dynamic analysis was conducted on the performance of the three mooring schemes under various tidal conditions to determine the mooring cable tension and platform motion response.Furthermore,the mooring system with an anchor chain and Superflex was optimized,with a focus on analyzing the effects of the Superflex length,the diameter of the anchor chains,and the mooring radius.The mooring system with the anchor chain and Superflex exhibits more controllable and stable mooring performance in areas with large tidal variations,so that it more effectively maintains the required mooring tension level.These findings not only provide a reference for the feasibility and optimization design of photovoltaic systems in areas with large tidal variations but also offer valuable experience for the sustainable application of clean energy under specific environmental conditions.展开更多
Based on meteorological data collected over nearly 60 years(1960-2017)from four national meteorological stations along the margins of the Badain Jaran Desert,this study analyzed the spatiotemporal variations in evapor...Based on meteorological data collected over nearly 60 years(1960-2017)from four national meteorological stations along the margins of the Badain Jaran Desert,this study analyzed the spatiotemporal variations in evaporation from water surfaces and identified the dominant controlling factors.Methods used included linear trend analysis,linear tendency estimation,the departure method,the rank correlation coefficient-based method,and Multiple Linear Regression(MLR).Results indicate notable spatiotemporal differences in evaporation distribution and evolution.Spatially,average annual evaporation exhibited a pronounced altitude effect,decreasing at a rate of about 8.23 mm/m from east to west with increasing altitude.Temporally,annual evaporation showed significant upward trends after 1996 at the northeastern(Guaizi Lake)and western(Dingxin)margins,with rates of 132 mm/10a and 105 mm/10a,respectively.Conversely,along the northwestern(Ejina Banner)and southern(Alxa Right Banner)margins of the desert,an evaporation paradox was observed,with annual evaporation trending downward at rates of 162 mm/10a and 187 mm/10a,respectively,especially after 1987.The dominant factors controlling evaporation varied spatially:Average annual temperature and relative humidity influended the western margin(Dingxin),average annual temperature was the key factor for the northeastern margin(Guaizi Lake),and average wind speed was crucial for the northern(Ejina Banner)and southern(Alxa Right Banner)margins.展开更多
Structural variations(SVs),a newly discovered genetic variation,have gained increasing recognition for their importance,yet much about them remains unknown.With the completion of whole-genome sequencing projects in oi...Structural variations(SVs),a newly discovered genetic variation,have gained increasing recognition for their importance,yet much about them remains unknown.With the completion of whole-genome sequencing projects in oil crops,more SVs have been identified,revealing their types,genomic distribution,and characteristics.These findings have demonstrated the crucial roles of SVs in regulating gene expression,driving trait innovation,facilitating domestication,making this an opportune time for a systematic review.We summarized the progress of SV-related studies in oil crops,focusing on the types of SVs and their mechanisms of occurrence,the strategies and methods for SV detection,and the SVs identified in oil crops such as rapeseed,soybean,peanut,and sesame.The various types of SVs,such as presence-absence variations(PAVs),copy number variations(CNVs),and homeologous exchanges(HEs),have been shown.Along with their genomic characterization,their roles in crop domestication and breeding,and regulatory impact on gene expression and agronomic traits have also been demonstrated.This review will provide an overview of the SV research process in oil crops,enabling researchers to quickly understand key information and apply this knowledge in future studies and crop breeding.展开更多
To clarify the connotations and extensions of urban resilience,this study focuses on the Chengdu-Chongqing Economic Circle with 16 cities as research subjects.A comprehensive evaluation index system was constructed to...To clarify the connotations and extensions of urban resilience,this study focuses on the Chengdu-Chongqing Economic Circle with 16 cities as research subjects.A comprehensive evaluation index system was constructed to measure the resilience of each city from 2003 to 2020.The spatial-temporal evolution characteristics were analyzed using Kernel density estimation,standard deviation ellipse,and spatial Markov chain analysis,and the spatial Tobit model was introduced to discover the influencing factors.The results indicate the following:①Urban resilience in the Chengdu-Chongqing Economic Circle displays an upward trend,with the center of gravity moving to the southwest,and the polarization phenomenon intensifying.②The urban resilience level in a region has certain spatial and geographical dependence,while the probability of urban resilience transfer differs in adjacent cities with different resilience levels.③Urban centrality,economic scale,openness level,and financial development promote urban resilience,whereas government scale significantly inhibits it.Finally,this paper proposes countermeasures and suggestions to improve the urban resilience of the Chengdu-Chongqing Economic Circle.展开更多
The vertebral arteries (VAs) are a system of two blood vessels through which blood is transported to the posterior cerebral fossa. VAs may emerge at different sides from the aortic ostium. The aim of our study was to ...The vertebral arteries (VAs) are a system of two blood vessels through which blood is transported to the posterior cerebral fossa. VAs may emerge at different sides from the aortic ostium. The aim of our study was to establish a reference of radio-anatomical variations of the VAs in black African human from Côte d’Ivoire experience. Materials and Methods: Forty patients underwent Computed Angio-Tomography (CAT) of the supra-aortic vessels (SAoVs). Included in our study were patients who underwent CAT of the SAoV from January 2019 to December 2021, those excluded in our study as Caucasians and other leucoderma humans. This exclusion allowed for highlighting only black humans VAs variations. The variations of both origins and foraminal entrance of VA were assessed. We carried out a model of univariate regression for assessing the occurrence of VA variations related to demographic included mainly age, gender and clinical features. Results: The average age was 48 ± 12 years with 0.66 of sex ratio. The most frequent indication for carrying out CAT was brain ischemic stroke assessment (25%). The atypical origin of the VAs out of subclavian arteries (SCA) was 25%. Origin from the aortic arch (AoA) was 17.5%. Six (15%) were unilateral while one (2.5%) was bilateral variation from a common trunk as pattern. Bilateral sixth cervical foramina inlet was 85%. Female sex and ischemic stroke assessment had a statistically significant correlation. Conclusion: VAs variations studies in black African human are lacking in the literature. Our findings depicted a considerable amount of VAs variations opening the field for further observational studies in black African human.展开更多
Dynamic control is essential to guarantee the stable performance of continuous chromatography.AutoMAb dynamic control strategy has been developed to ensure a consistent protein load in twincolumn CaptureSMB continuous...Dynamic control is essential to guarantee the stable performance of continuous chromatography.AutoMAb dynamic control strategy has been developed to ensure a consistent protein load in twincolumn CaptureSMB continuous capture by integrating the UV signal of breakthrough.In this study,the process risk of CaptureSMB continuous capture under AutoMAb control towards the feedstock variations was assessed by a mechanistic model developed by us.The effects of target protein and impurities under the variation range of±10 mAU·min^(-1) on load amount,protein loss,process productivity,and resin capacity utilization were investigated.The results showed that the CaptureSMB process could be successfully controlled by AutoMAb towards increased or slightly decreased concentration of feedstock.However,the load process would be out of control with drastically decreased target protein or impurities,and the decreased impurities would lead to protein loss.It was found that AutoMAb control would cause 44.7%non-operational areas and 18.3%protein loss areas in the variation range of±10 mAU·min^(-1).To improve the stability of the CaptureSMB process,a modified AutoMAb control that would stop the load procedure when the absolute value of the integral area reached the preset value,was proposed to reduce the risk of protein loss and the non-operational area.展开更多
文摘As an important river in the western part of Jilin Province,the lower reach of the Nenjiang River is an important wetland water source conservation area in Jilin Province.Within the watershed,it governs the Momoge Wetland,the Xianghai Wetland,and the Danjiang Wetland in Jilin Province.The main problem in the lower reaches of the Nenjiang River is the uneven distribution of water resources in time and space,and the intensification of land salinization.Zhenlai County and Da an City in the Nenjiang River Basin have sufficient surface water resources,with surface water as the drinking water source.Baicheng City and Tongyu County have scarce surface water resources,and both use groundwater as their domestic water source.The main polluted section in the basin is the Xianghai Reservoir,and the annual water quality evaluation is Class V.However,the water quality of the Tao er River,the main stream of the Nenjiang River,is significantly better than that of the Xianghai Reservoir.In order to better study the water environmental pollution situation in the Nenjiang River basin,monitoring data from five sections of non seasonal rivers in the basin from 2012 to 2021 were selected for studying water quality.This in-depth exploration of the water pollution status and river water quality change trends in the Nenjiang River basin is of great significance for future rural development,agricultural pattern transformation,and the promotion of water ecological civilization construction.
基金This work is partly supported by the National Key Research and Development Program of China(Grant No.2020YFB1805403)the National Natural Science Foundation of China(Grant No.62032002)the 111 Project(Grant No.B21049).
文摘In the Industrial Internet of Things(IIoT),sensors generate time series data to reflect the working state.When the systems are attacked,timely identification of outliers in time series is critical to ensure security.Although many anomaly detection methods have been proposed,the temporal correlation of the time series over the same sensor and the state(spatial)correlation between different sensors are rarely considered simultaneously in these methods.Owing to the superior capability of Transformer in learning time series features.This paper proposes a time series anomaly detection method based on a spatial-temporal network and an improved Transformer.Additionally,the methods based on graph neural networks typically include a graph structure learning module and an anomaly detection module,which are interdependent.However,in the initial phase of training,since neither of the modules has reached an optimal state,their performance may influence each other.This scenario makes the end-to-end training approach hard to effectively direct the learning trajectory of each module.This interdependence between the modules,coupled with the initial instability,may cause the model to find it hard to find the optimal solution during the training process,resulting in unsatisfactory results.We introduce an adaptive graph structure learning method to obtain the optimal model parameters and graph structure.Experiments on two publicly available datasets demonstrate that the proposed method attains higher anomaly detection results than other methods.
基金Guangdong Major Project of Basic and Applied Basic Research(2020B0301030004)National Natural Science Foundation of China(42475003)Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)(SML2023SP209)。
文摘Southerly moisture surges over the central South China Sea(SCS)are characterized by the strengthening of lowlevel southerlies that transport moisture northward from the Pacific or Indian Oceans to South China.These surge events typically occur for days in the early-summer season(from April to June)and can lead to heavy rains in South China.This study categorizes surge events into three types of flow patterns and examines their multiscale variations and impacts on rainfall.The first type occurs mainly in April,with the southeasterlies enhanced by a deepening trough in South China and the western Pacific subtropical high established over the SCS.The second type of surge events mostly appears in June,featuring the prevailing southwesterlies of summer monsoon from the Indian Ocean during the active phases of intraseasonal oscillations.Most surge events exhibit semi-diurnal variations with morning and afternoon peaks of northward moisture fluxes.Specifically,the first type features a dominant afternoon peak,while the second type shows a dominant early-morning peak,which is induced by thermal contrast between the Indochina Peninsula and the SCS.In general,the surge events enhance moisture convergence and increase rainfall downstream in South China,but they show some regional differences.The second type strengthens moisture convergence and rainfall in coastal regions with a morning peak.In contrast,the first type enhances inland rainfall with a morning peak,while moisture divergence dominates coastal regions.The third type of surge events denotes transitional conditions between the first two types,in terms of atmospheric circulations,diurnal cycles,and rainfall patterns.These results highlight a diversity of regional moisture surges and related rainfall ranging from diurnal to sub-seasonal scales.
基金funded by the National Natural Science Foundation of China(grant no.32270238 and 31870311).
文摘Subtropical evergreen broad-leaved trees are usually vulnerable to freezing stress,while hexaploid wild Camellia oleifera shows strong freezing tolerance.As a valuable genetic resource of woody oil crop C.oleifera,wild C.oleifera can serve as a case for studying the molecular bases of adaptive evolution to freezing stress.Here,47 wild C.oleifera from 11 natural distribution sites in China and 4 relative species of C.oleifera were selected for genome sequencing.“Min Temperature of Coldest Month”(BIO6)had the highest comprehensive contribution to wild C.oleifera distribution.The population genetic structure of wild C.oleifera could be divided into two groups:in cold winter(BIO6≤0℃)and warm winter(BIO6>0℃)areas.Wild C.oleifera in cold winter areas might have experienced stronger selection pressures and population bottlenecks with lower N_(e) than those in warm winter areas.155 singlenucleotide polymorphisms(SNPs)were significantly correlated with the key bioclimatic variables(106 SNPs significantly correlated with BIO6).Twenty key SNPs and 15 key copy number variation regions(CNVRs)were found with genotype differentiation>50%between the two groups of wild C.oleifera.Key SNPs in cis-regulatory elements might affect the expression of key genes associated with freezing tolerance,and they were also found within a CNVR suggesting interactions between them.Some key CNVRs in the exon regions were closely related to the differentially expressed genes under freezing stress.The findings suggest that rich SNPs and CNVRs in polyploid trees may contribute to the adaptive evolution to freezing stress.
基金supported by the Opening Foundation of the State Key Laboratory Breeding Base of Desertification and Aeolian Sand Disaster Combating,Gansu Desert Control Research Institute (GSDC201503)the National Natural Science Foundation of China (41271024,31260129,31360204)+1 种基金the Program for Innovative Research Group of Gansu Province,China (1506RJIA155)Lanzhou University for providing Arc GIS technical support in the data processing
文摘Analysis of spatial-temporal variations of desert vegetation under the background of climate changes can provide references for ecological restoration in arid and semi-arid areas. In this study, we used the Global Inventory Modeling and Mapping Studies （GIMMS） NDVI data from 1982 to 2006 and Moderate Resolution Imaging Spectroradiometer （MODIS） NDVI data from 2000 to 2013 to reveal the dynamics of desert vegetation in Hexi region of Northwest China over the past three decades. We also used the annual temperature and precipitation data acquired from the Chinese meteorological stations to analyze the response of desert vegetation to climatic variations. The average value of NDVImax （the maximum NDVI during the growing season） for desert vegetation in Hexi region increased at the rate of 0.65x10-3/a （P〈0.05） from 1982 to 2013, and the significant increases of NDVImax mainly appeared in the typical desert vegetation areas. Vegetation was significantly improved in the lower reaches of Shule and Shiyang river basins, and the weighted mean center of desert vegetation mainly shifted toward the lower reaches of the two basins. Almost 95.32% of the total desert vegetation area showed positive correlation between NDVImax and annual precipitation, indicating that precipitation is the key factor for desert vegetation growth in the entire study area. Moreover, the areas with non-significant positive correlation between NDVImax and annual precipitation mainly located in the lower reaches of Shiyang and Shule river basins, this may be due to human activities. Only 7.64% of the desert vegetation showed significant positive correlation between NDVImax and annual precipitation in the Shule River Basin （an extremely arid area）, indicating that precipitation is not the most important factor for vegetation growth in this basin, and further studies are needed to investigate the mechanism for this phenomenon.
基金supported by the China Scholarship Council and the CERNET Innovation Project under grant No.20170111.
文摘The prediction for Multivariate Time Series(MTS)explores the interrelationships among variables at historical moments,extracts their relevant characteristics,and is widely used in finance,weather,complex industries and other fields.Furthermore,it is important to construct a digital twin system.However,existing methods do not take full advantage of the potential properties of variables,which results in poor predicted accuracy.In this paper,we propose the Adaptive Fused Spatial-Temporal Graph Convolutional Network(AFSTGCN).First,to address the problem of the unknown spatial-temporal structure,we construct the Adaptive Fused Spatial-Temporal Graph(AFSTG)layer.Specifically,we fuse the spatial-temporal graph based on the interrelationship of spatial graphs.Simultaneously,we construct the adaptive adjacency matrix of the spatial-temporal graph using node embedding methods.Subsequently,to overcome the insufficient extraction of disordered correlation features,we construct the Adaptive Fused Spatial-Temporal Graph Convolutional(AFSTGC)module.The module forces the reordering of disordered temporal,spatial and spatial-temporal dependencies into rule-like data.AFSTGCN dynamically and synchronously acquires potential temporal,spatial and spatial-temporal correlations,thereby fully extracting rich hierarchical feature information to enhance the predicted accuracy.Experiments on different types of MTS datasets demonstrate that the model achieves state-of-the-art single-step and multi-step performance compared with eight other deep learning models.
基金funded by the National Key R&D Program of China(Grant No.2021YFD1500200)National Natural Science Foundation of China(Grant No.42077149)+4 种基金China Postdoctoral Science Foundation(Grant No.2019M660782)National Science and Technology Basic Resources Survey Program of China(Grant No.2019FY101300)Doctoral research start-up fund project of Liaoning Provincial Department of Science and Technology(Grant No.2021-BS-136)China Scholarship Council(201908210132)Young Scientific and Technological Talents Project of Liaoning Province(Grant Nos.LSNQN201910 and LSNQN201914)。
文摘Forest soil carbon is a major carbon pool of terrestrial ecosystems,and accurate estimation of soil organic carbon(SOC)stocks in forest ecosystems is rather challenging.This study compared the prediction performance of three empirical model approaches namely,regression kriging(RK),multiple stepwise regression(MSR),random forest(RF),and boosted regression trees(BRT)to predict SOC stocks in Northeast China for 1990 and 2015.Furthermore,the spatial variation of SOC stocks and the main controlling environmental factors during the past 25 years were identified.A total of 82(in 1990)and 157(in 2015)topsoil(0–20 cm)samples with 12 environmental factors(soil property,climate,topography and biology)were selected for model construction.Randomly selected80%of the soil sample data were used to train the models and the other 20%data for model verification using mean absolute error,root mean square error,coefficient of determination and Lin's consistency correlation coefficient indices.We found BRT model as the best prediction model and it could explain 67%and 60%spatial variation of SOC stocks,in 1990,and 2015,respectively.Predicted maps of all models in both periods showed similar spatial distribution characteristics,with the lower SOC in northeast and higher SOC in southwest.Mean annual temperature and elevation were the key environmental factors influencing the spatial variation of SOC stock in both periods.SOC stocks were mainly stored under Cambosols,Gleyosols and Isohumosols,accounting for 95.6%(1990)and 95.9%(2015).Overall,SOC stocks increased by 471 Tg C during the past 25 years.Our study found that the BRT model employing common environmental factors was the most robust method for forest topsoil SOC stocks inventories.The spatial resolution of BRT model enabled us to pinpoint in which areas of Northeast China that new forest tree planting would be most effective for enhancing forest C stocks.Overall,our approach is likely to be useful in forestry management and ecological restoration at and beyond the regional scale.
文摘Empirical Orthogonal Function (EOF) was performed to investigate spatial variation in January precipitation over Pakistan using ground observed mean monthly precipitation data from 1950-2000 with a combination of gridded reanalysis data of sea level pressure (SLP) and 500 hPa geopotential height. The leading EOF mode captures 37.51% of the total variance and the spatial-temporal variability of January precipitation was consistent in the study area. The temporal changes explicate non-periodic interannual variability and some tacit interdecadal variation. The anomalous condition is more prominent along the western bordering mountains and northern high mountainous region than any other region of Pakistan. Based on results the study reveals spatial-temporal variation in January precipitation and possible links with global teleconnections located both in the proximity as well as in the remote areas from the study locus.
文摘By making use of Empirical Orthogonal Function (EOF) analysis the spatial and temporal variability was investigated in January over the period of 1950 to 2000 in Pakistan. The analysis is based on the combination of ground observed mean monthly temperature data and National Centre for Environmental Prediction (NCEP) reanalysis data of sea level pressure (SLP) and 500-hPa fields. The results reasonably reveal that the variation in January temperature have links with global teleconnections at SLP and 500-hPa pressure heights. The analysis shows variability at interannual to interdecadal time scale. The interannual variation is more prominent than the interdecadal signal of temperature anomaly. The simulated coefficient patterns show reasonable variation with regional detail from south (north) to north (south) in the study area. The study could be useful as baseline information for climate change studies in Pakistan.
文摘Grid method is employed for sampling covering soil at the test field,whic h is reclamation area filled by coal mining wastes for cropland in th e Fushun coal mine,Liaoning Province,the Northeast China.The soil samp les are taken at different locations,inclu ding three kinds of covering soil,th ree different depths of soil layers a nd four different covering ages of covering soil.The s patial-temporal variation of heavy metal element content in reclamatio n soil is stud-ied.The results indicate that the co ntent of heavy metal elements is decreasing year after year;the determin ant reason why the content of heavy metal elemen ts at 60cm depth layer is higher than t hat at 30cm depth layer and surface is fertiliz-er and manure application;the metal elements mainly come from external environment;there is no metal pollut ion coming from mother material(coal mining wastes)in plough layer of covering soil.
基金Supported by the Natural Science Foundation of Shandong Province,China(ZR2010DM011)
文摘Using the daily precipitation data of 118 meteorological stations in Northwest China from January 1, 1961 to December 31,2010, we analyzed extreme precipitation events from prime precipitation data by applying R-language Climate Index （RClimDex）. The spatial-temporal change characteristics in the past 50 years have been examined using the method of trend analysis, Mann-Kendall and the spatial analysis module of Arcgis9.2. The results show that the spatial distribution of the indices for extreme precipitation in Northwest China is greatly influenced by geographic location, atmospheric circulation and topography, and the spatial difference of extreme precipitation events is very evident, while the indices reduce from the southeast to the northwest except Consecutive Dry Days （CDD）. In Xinjiang region, high values appear in Tianshan Mountains and decrease towards the south and north respectively. In the past 50 years, the temporal variation tendency of the indices for extreme precipitation in Northwest China has a great spatial distinction. It shows that the variation tendency is opposite between the east （decrease） and the west （increase）, and CDD has a decreasing tendency while other indices increase. For each region, it is found that the indices for extreme precipitation in Xinjiang and Qinghai Province shows an increasing trend, and it is remarkable in Tianshan Mountains, the north of Xinjiang and the northeast of Qinghai Province. The temporal variation tendency of the indices for extreme precipitation in Ningxia, Shaanxi and Gansu has a large spatial distinction. The stations which have an increasing tend are mainly found in the north of Ningxia, south of Shaanxi and Hexi Corridor of Gansu. However, the south of Ningxia, north of Shaanxi and Longnan of Gansu Province mainly present a decreasing trend. The temporal variation tendency of the indices for extreme precipitation in Inner Mongolia is not obvious. Overall, the east part of Northwest China has a dry tendency, while the west part has an opposite trend.
基金supported by the National Key R&D Program of China(2021YFD1301101)National Swine Industry Technology System(CARS-35)Agricultural Science and Technology Innovation Program(ASTIP-IAS02)。
文摘Background During approximately 10,000 years of domestication and selection,a large number of structural variations(SVs)have emerged in the genome of pig breeds,profoundly influencing their phenotypes and the ability to adapt to the local environment.SVs(≥50 bp)are widely distributed in the genome,mainly in the form of insertion(INS),mobile element insertion(MEI),deletion(DEL),duplication(DUP),inversion(INV),and translocation(TRA).While studies have investigated the SVs in pig genomes,genome-wide association studies(GWAS)-based on SVs have been rarely conducted.Results Here,we obtained a high-quality SV map containing 123,151 SVs from 15 Large White and 15 Min pigs through integrating the power of several SV tools,with 53.95%of the SVs being reported for the first time.These high-quality SVs were used to recover the population genetic structure,confirming the accuracy of genotyping.Potential functional SV loci were then identified based on positional effects and breed stratification.Finally,GWAS were performed for 36 traits by genotyping the screened potential causal loci in the F2 population according to their corresponding genomic positions.We identified a large number of loci involved in 8 carcass traits and 6 skeletal traits on chromosome 7,with FKBP5 containing the most significant SV locus for almost all traits.In addition,we found several significant loci in intramuscular fat,abdominal circumference,heart weight,and liver weight,etc.Conclusions We constructed a high-quality SV map using high-coverage sequencing data and then analyzed them by performing GWAS for 25 carcass traits,7 skeletal traits,and 4 meat quality traits to determine that SVs may affect body size between European and Chinese pig breeds.
基金funding from several sources,including the Chongqing Scientific Research Institution Performance Incentive Project(grant number cstc2022jxjl80007)the Earmarked Fund for China Agriculture Research System(grant number CARS-42-51)+5 种基金the Chongqing Scientific Research Institution Performance Incentive Project(grant number 22527 J)the Key R&D Project in Agriculture and Animal Husbandry of Rongchang(grant number No.22534C-22)Natural Science Foundation of Chongqing Project,grant number CSTB2022NSCQ-MSX0434Natural Science Foundation of Sichuan Project,grant number 2022NSFSC0605Natural Science Foundation of Sichuan Project,grant number 2021YFS0379the Chongqing Technology Innovation and Application Development Project(grant number No.cstc2021ycjh-bgzxm0248)。
文摘Background Domestic goose breeds are descended from either the Swan goose(Anser cygnoides)or the Greylag goose(Anser anser),exhibiting variations in body size,reproductive performance,egg production,feather color,and other phenotypic traits.Constructing a pan-genome facilitates a thorough identification of genetic variations,thereby deepening our comprehension of the molecular mechanisms underlying genetic diversity and phenotypic variability.Results To comprehensively facilitate population genomic and pan-genomic analyses in geese,we embarked on the task of 659 geese whole genome resequencing data and compiling a database of 155 RNA-seq samples.By constructing the pan-genome for geese,we generated non-reference contigs totaling 612 Mb,unveiling a collection of 2,813 novel genes and pinpointing 15,567 core genes,1,324 softcore genes,2,734 shell genes,and 878 cloud genes in goose genomes.Furthermore,we detected an 81.97 Mb genomic region showing signs of genome selection,encompassing the TGFBR2 gene correlated with variations in body weight among geese.Genome-wide association studies utilizing single nucleotide polymorphisms(SNPs)and presence-absence variation revealed significant genomic associations with various goose meat quality,reproductive,and body composition traits.For instance,a gene encoding the SVEP1 protein was linked to carcass oblique length,and a distinct gene-CDS haplotype of the SVEP1 gene exhibited an association with carcass oblique length.Notably,the pan-genome analysis revealed enrichment of variable genes in the“hair follicle maturation”Gene Ontology term,potentially linked to the selection of feather-related traits in geese.A gene presence-absence variation analysis suggested a reduced frequency of genes associated with“regulation of heart contraction”in domesticated geese compared to their wild counterparts.Our study provided novel insights into gene expression features and functions by integrating gene expression patterns across multiple organs and tissues in geese and analyzing population variation.Conclusion This accomplishment originates from the discernment of a multitude of selection signals and candidate genes associated with a wide array of traits,thereby markedly enhancing our understanding of the processes underlying domestication and breeding in geese.Moreover,assembling the pan-genome for geese has yielded a comprehensive apprehension of the goose genome,establishing it as an indispensable asset poised to offer innovative viewpoints and make substantial contributions to future geese breeding initiatives.
基金Supported by the National Natural Science Foundation of China(Nos.31700425,91751202)the Innovation Plan of Science and Technology for Aoshan(No.2016ASKJ02)the Health Assessment and Decision Support System for Coastal Ecosystem(No.XDA19060204)
文摘To better understand the spatial-temporal variation in phytoplankton community structure and its controlling factors in Jiaozhou Bay, Qingdao, North China, four seasonal sampling were carried out in 2017. The phytoplankton community structure and various environmental parameters were examined. The phytoplankton community in the bay was composed of mainly diatoms and dinofl agellates, and several other species of Chrysophyta were also observed. Diatoms were the most dominant phytoplankton group throughout the year, except in spring and winter, when Noctiluca scintillans was co-dominant. High Si/N ratios in summer and fall refl ect the high dominance of diatoms in the two seasons. Temporally, the phytoplankton cell abundance peaked in summer, due mainly to the high temperatures and nutrient concentrations in summer. Spatially, the phytoplankton cell abundance was higher in the northern part of the bay than in the other parts of the bay in four seasons. The diatom cell abundances show signifi cant positive correlations with the nutrient concentrations, while the dinofl agellate cell abundances show no correlation or a negative correlation with the nutrient concentrations but a signifi cant positive correlation with the stratifi cation index. This discrepancy was mainly due to the diff erent survival strategies between diatoms and dinofl agellates. The Shannon-Wiener diversity index ( H′) values in the bay ranged from 0.08 to 4.18, which fell in the range reported in historical studies. The distribution pattern of H′ values was quite diff erent from that of chlorophyll a , indicating that the phytoplankton community structure might have high biomass with a low diversity index. Compared with historical studies, we believe that the dominant phytoplankton species have been changed in recent years due mainly to the changing environment in the Jiaozhou Bay in recent 30 years.
基金financially supported by the National Key R&D Program of China(Grant No.2022YFB4200700).
文摘To address the mooring issues of floating photovoltaic systems in areas with large tidal variations,three mooring schemes were designed and compared in this paper:anchor chain,anchor chain with added weights,and anchor chain with Superflex.The model was established via the numerical simulation tool Orcaflex,which considers the combined effects of wind,waves,and currents.A time-domain coupled dynamic analysis was conducted on the performance of the three mooring schemes under various tidal conditions to determine the mooring cable tension and platform motion response.Furthermore,the mooring system with an anchor chain and Superflex was optimized,with a focus on analyzing the effects of the Superflex length,the diameter of the anchor chains,and the mooring radius.The mooring system with the anchor chain and Superflex exhibits more controllable and stable mooring performance in areas with large tidal variations,so that it more effectively maintains the required mooring tension level.These findings not only provide a reference for the feasibility and optimization design of photovoltaic systems in areas with large tidal variations but also offer valuable experience for the sustainable application of clean energy under specific environmental conditions.
基金supported by the Natural Science Foundation of Hebei Province(D202450411)the Basic Research Programme of Chinese Academy of Geological Sciences(CAGS)(YK202302).
文摘Based on meteorological data collected over nearly 60 years(1960-2017)from four national meteorological stations along the margins of the Badain Jaran Desert,this study analyzed the spatiotemporal variations in evaporation from water surfaces and identified the dominant controlling factors.Methods used included linear trend analysis,linear tendency estimation,the departure method,the rank correlation coefficient-based method,and Multiple Linear Regression(MLR).Results indicate notable spatiotemporal differences in evaporation distribution and evolution.Spatially,average annual evaporation exhibited a pronounced altitude effect,decreasing at a rate of about 8.23 mm/m from east to west with increasing altitude.Temporally,annual evaporation showed significant upward trends after 1996 at the northeastern(Guaizi Lake)and western(Dingxin)margins,with rates of 132 mm/10a and 105 mm/10a,respectively.Conversely,along the northwestern(Ejina Banner)and southern(Alxa Right Banner)margins of the desert,an evaporation paradox was observed,with annual evaporation trending downward at rates of 162 mm/10a and 187 mm/10a,respectively,especially after 1987.The dominant factors controlling evaporation varied spatially:Average annual temperature and relative humidity influended the western margin(Dingxin),average annual temperature was the key factor for the northeastern margin(Guaizi Lake),and average wind speed was crucial for the northern(Ejina Banner)and southern(Alxa Right Banner)margins.
基金funded by the National Natural Science Foundation of China(32370693 and U20A2034)Innovation Program of Chinese Academy of Agricultural Sciences(CAAS-CSIAF-202402)+1 种基金the Young Top-notch Talent Cultivation Program of Hubei Province for Dr.Chaobo Tong,the National Key Research and Development Program of China(2021YFD1600500)Central Public-interest Scientific Institution Basal Research Fund(2021-2060302-061-027,2021-2060302-061-029).
文摘Structural variations(SVs),a newly discovered genetic variation,have gained increasing recognition for their importance,yet much about them remains unknown.With the completion of whole-genome sequencing projects in oil crops,more SVs have been identified,revealing their types,genomic distribution,and characteristics.These findings have demonstrated the crucial roles of SVs in regulating gene expression,driving trait innovation,facilitating domestication,making this an opportune time for a systematic review.We summarized the progress of SV-related studies in oil crops,focusing on the types of SVs and their mechanisms of occurrence,the strategies and methods for SV detection,and the SVs identified in oil crops such as rapeseed,soybean,peanut,and sesame.The various types of SVs,such as presence-absence variations(PAVs),copy number variations(CNVs),and homeologous exchanges(HEs),have been shown.Along with their genomic characterization,their roles in crop domestication and breeding,and regulatory impact on gene expression and agronomic traits have also been demonstrated.This review will provide an overview of the SV research process in oil crops,enabling researchers to quickly understand key information and apply this knowledge in future studies and crop breeding.
基金supported by the Graduate Research and Innovation Project of Chongqing Normal University[Grant No.YKC23035],comprehensive evaluation,and driving factors of urban resilience in the Chengdu-Chongqing Economic Circle.
文摘To clarify the connotations and extensions of urban resilience,this study focuses on the Chengdu-Chongqing Economic Circle with 16 cities as research subjects.A comprehensive evaluation index system was constructed to measure the resilience of each city from 2003 to 2020.The spatial-temporal evolution characteristics were analyzed using Kernel density estimation,standard deviation ellipse,and spatial Markov chain analysis,and the spatial Tobit model was introduced to discover the influencing factors.The results indicate the following:①Urban resilience in the Chengdu-Chongqing Economic Circle displays an upward trend,with the center of gravity moving to the southwest,and the polarization phenomenon intensifying.②The urban resilience level in a region has certain spatial and geographical dependence,while the probability of urban resilience transfer differs in adjacent cities with different resilience levels.③Urban centrality,economic scale,openness level,and financial development promote urban resilience,whereas government scale significantly inhibits it.Finally,this paper proposes countermeasures and suggestions to improve the urban resilience of the Chengdu-Chongqing Economic Circle.
文摘The vertebral arteries (VAs) are a system of two blood vessels through which blood is transported to the posterior cerebral fossa. VAs may emerge at different sides from the aortic ostium. The aim of our study was to establish a reference of radio-anatomical variations of the VAs in black African human from Côte d’Ivoire experience. Materials and Methods: Forty patients underwent Computed Angio-Tomography (CAT) of the supra-aortic vessels (SAoVs). Included in our study were patients who underwent CAT of the SAoV from January 2019 to December 2021, those excluded in our study as Caucasians and other leucoderma humans. This exclusion allowed for highlighting only black humans VAs variations. The variations of both origins and foraminal entrance of VA were assessed. We carried out a model of univariate regression for assessing the occurrence of VA variations related to demographic included mainly age, gender and clinical features. Results: The average age was 48 ± 12 years with 0.66 of sex ratio. The most frequent indication for carrying out CAT was brain ischemic stroke assessment (25%). The atypical origin of the VAs out of subclavian arteries (SCA) was 25%. Origin from the aortic arch (AoA) was 17.5%. Six (15%) were unilateral while one (2.5%) was bilateral variation from a common trunk as pattern. Bilateral sixth cervical foramina inlet was 85%. Female sex and ischemic stroke assessment had a statistically significant correlation. Conclusion: VAs variations studies in black African human are lacking in the literature. Our findings depicted a considerable amount of VAs variations opening the field for further observational studies in black African human.
基金supported by the Zhejiang Key Science and Technology Project(2023C03116)National Natural Science Foundation of China(22078286)National Key Research and Development Program of China(2021YFE0113300).
文摘Dynamic control is essential to guarantee the stable performance of continuous chromatography.AutoMAb dynamic control strategy has been developed to ensure a consistent protein load in twincolumn CaptureSMB continuous capture by integrating the UV signal of breakthrough.In this study,the process risk of CaptureSMB continuous capture under AutoMAb control towards the feedstock variations was assessed by a mechanistic model developed by us.The effects of target protein and impurities under the variation range of±10 mAU·min^(-1) on load amount,protein loss,process productivity,and resin capacity utilization were investigated.The results showed that the CaptureSMB process could be successfully controlled by AutoMAb towards increased or slightly decreased concentration of feedstock.However,the load process would be out of control with drastically decreased target protein or impurities,and the decreased impurities would lead to protein loss.It was found that AutoMAb control would cause 44.7%non-operational areas and 18.3%protein loss areas in the variation range of±10 mAU·min^(-1).To improve the stability of the CaptureSMB process,a modified AutoMAb control that would stop the load procedure when the absolute value of the integral area reached the preset value,was proposed to reduce the risk of protein loss and the non-operational area.
