Confocal laser scanning microscopy was used to observe the spatio-temporal expression of the pathway-specific gene redD during S. coelicolor cell cultivation. The corresponding mutant S. coelicolor lyqRY1522 carrying ...Confocal laser scanning microscopy was used to observe the spatio-temporal expression of the pathway-specific gene redD during S. coelicolor cell cultivation. The corresponding mutant S. coelicolor lyqRY1522 carrying redD::eyfp in the chro- mosome was constructed. The temporal expression results of the fusion protein during submerged cultivation demonstrated that expression of redD began in the transition phase, continuing through the exponential growth phase to the stationary phase, and reached maximum in the stationary phase. On the other hand, redD was expressed only in substrate mycelia during solid-state culture, while aerial mycelia remained essentially non-fluorescent throughout culture. Results demonstrated that the expression pattern of redD coincides with that of the biosynthesis of the antibiotics during culture, revealing a direct correlation between the spatio-temporal distribution of regulatory gene expression and second metabolism.展开更多
Due to water conflicts and allocation in the Lancang-Mekong River Basin(LMRB),the spatio-temporal differentiation of total water resources and the natural-human influence need to be clarified.This work investigated LM...Due to water conflicts and allocation in the Lancang-Mekong River Basin(LMRB),the spatio-temporal differentiation of total water resources and the natural-human influence need to be clarified.This work investigated LMRB's terrestrial water storage anomaly(TWSA)and its spatio-temporal dynamics during 2002–2020.Considering the effects of natural factors and human activities,the respective contributions of climate variability and human activities to terrestrial water storage change(TWSC)were separated.Results showed that:(1)LMRB's TWSA decreased by 0.3158 cm/a.(2)TWSA showed a gradual increase in distribution from southwest of MRB to middle LMRB and from northeast of LRB to middle LMRB.TWSA positively changed in Myanmar while slightly changed in Laos and China.It negatively changed in Vietnam,Thailand and Cambodia.(3)TWSA components decreased in a descending order of soil moisture,groundwater and precipitation.(4)Natural factors had a substantial and spatial differentiated influence on TWSA over the LMRB.(5)Climate variability contributed 79%of TWSC in the LMRB while human activities contributed 21%with an increasing impact after 2008.The TWSC of upstream basin countries was found to be controlled by climate variability while Vietnam and Cambodia's TWSC has been controlled by human activities since 2012.展开更多
The ability to accurately predict urban traffic flows is crucial for optimising city operations.Consequently,various methods for forecasting urban traffic have been developed,focusing on analysing historical data to u...The ability to accurately predict urban traffic flows is crucial for optimising city operations.Consequently,various methods for forecasting urban traffic have been developed,focusing on analysing historical data to understand complex mobility patterns.Deep learning techniques,such as graph neural networks(GNNs),are popular for their ability to capture spatio-temporal dependencies.However,these models often become overly complex due to the large number of hyper-parameters involved.In this study,we introduce Dynamic Multi-Graph Spatial-Temporal Graph Neural Ordinary Differential Equation Networks(DMST-GNODE),a framework based on ordinary differential equations(ODEs)that autonomously discovers effective spatial-temporal graph neural network(STGNN)architectures for traffic prediction tasks.The comparative analysis of DMST-GNODE and baseline models indicates that DMST-GNODE model demonstrates superior performance across multiple datasets,consistently achieving the lowest Root Mean Square Error(RMSE)and Mean Absolute Error(MAE)values,alongside the highest accuracy.On the BKK(Bangkok)dataset,it outperformed other models with an RMSE of 3.3165 and an accuracy of 0.9367 for a 20-min interval,maintaining this trend across 40 and 60 min.Similarly,on the PeMS08 dataset,DMST-GNODE achieved the best performance with an RMSE of 19.4863 and an accuracy of 0.9377 at 20 min,demonstrating its effectiveness over longer periods.The Los_Loop dataset results further emphasise this model’s advantage,with an RMSE of 3.3422 and an accuracy of 0.7643 at 20 min,consistently maintaining superiority across all time intervals.These numerical highlights indicate that DMST-GNODE not only outperforms baseline models but also achieves higher accuracy and lower errors across different time intervals and datasets.展开更多
Rice is a poor source of folate,an essential micronutrient for the body.Biofortification offers an effective way to enhance the folate content of rice and alleviate folate deficiencies in humans.In this study,we confi...Rice is a poor source of folate,an essential micronutrient for the body.Biofortification offers an effective way to enhance the folate content of rice and alleviate folate deficiencies in humans.In this study,we confirmed that OsADCS and OsGTPCHI,encoding the initial enzymes necessary for folate synthesis,positively regulate folate accumulation in knockout mutants of both japonica and indica rice backgrounds.The folate content in the low-folate japonica variety was slightly increased by the expression of the indica alleles driven by the endosperm-specific promoter.We further obtained co-expression lines by stacking OsADCS and OsGTPCHI genes;the folate accumulation in brown rice and polished rice reached 5.65μg/g and 2.95μg/g,respectively,representing 37.9-fold and 26.5-fold increases compared with the wild type.Transcriptomic analysis of rice grains from six transgenic lines showed that folate changes affected biological pathways involved in the synthesis and metabolism of rice seed storage substances,while the expression of other folate synthesis genes was weakly regulated.In addition,we identified Aus rice as a high-folate germplasm carrying superior haplotypes of OsADCS and OsGTPCHI through natural variation.This study provides an alternative and effective complementary strategy for rice biofortification,promoting the rational combination of metabolic engineering and conventional breeding to breed high-folate varieties.展开更多
Objective INF2 is a member of the formins family.Abnormal expression and regulation of INF2 have been associated with the progression of various tumors,but the expression and role of INF2 in hepatocellular carcinoma(H...Objective INF2 is a member of the formins family.Abnormal expression and regulation of INF2 have been associated with the progression of various tumors,but the expression and role of INF2 in hepatocellular carcinoma(HCC)remain unclear.HCC is a highly lethal malignant tumor.Given the limitations of traditional treatments,this study explored the expression level,clinical value and potential mechanism of INF2 in HCC in order to seek new therapeutic targets.Methods In this study,we used public databases to analyze the expression of INF2 in pan-cancer and HCC,as well as the impact of INF2 expression levels on HCC prognosis.Quantitative real time polymerase chain reaction(RT-qPCR),Western blot,and immunohistochemistry were used to detect the expression level of INF2 in liver cancer cells and human HCC tissues.The correlation between INF2 expression and clinical pathological features was analyzed using public databases and clinical data of human HCC samples.Subsequently,the effects of INF2 expression on the biological function and Drp1 phosphorylation of liver cancer cells were elucidated through in vitro and in vivo experiments.Finally,the predictive value and potential mechanism of INF2 in HCC were further analyzed through database and immunohistochemical experiments.Results INF2 is aberrantly high expression in HCC samples and the high expression of INF2 is correlated with overall survival,liver cirrhosis and pathological differentiation of HCC patients.The expression level of INF2 has certain diagnostic value in predicting the prognosis and pathological differentiation of HCC.In vivo and in vitro HCC models,upregulated expression of INF2 triggers the proliferation and migration of the HCC cell,while knockdown of INF2 could counteract this effect.INF2 in liver cancer cells may affect mitochondrial division by inducing Drp1 phosphorylation and mediate immune escape by up-regulating PD-L1 expression,thus promoting tumor progression.Conclusion INF2 is highly expressed in HCC and is associated with poor prognosis.High expression of INF2 may promote HCC progression by inducing Drp1 phosphorylation and up-regulation of PD-L1 expression,and targeting INF2 may be beneficial for HCC patients with high expression of INF2.展开更多
The xylitol dehydrogenase(XDH)is a crucial enzyme involved in the xylose utilization in pentose⁃catabolizing yeasts and fungi.In addition to producing xylulose,XDH can also be employed to develop a biosensor for monit...The xylitol dehydrogenase(XDH)is a crucial enzyme involved in the xylose utilization in pentose⁃catabolizing yeasts and fungi.In addition to producing xylulose,XDH can also be employed to develop a biosensor for monitoring xylitol concentration.In this study,the gene encoding the thermophilic fungus Talaromyces emersonii XDH(TeXDH)was heterologously expressed in Escherichia coli BL21(DE3)at 16℃in the soluble form.Recombinant TeXDH with high purity was purified by using a Ni⁃NTA affinity column.Size⁃exclusion chromatography and SDS⁃PAGE analysis demonstrated that the puri⁃fied recombinant TeXDH exists as a native trimer with a molecular mass of approximately 116 kD,and is composed of three identical subunits,each with a molecular weight of around 39 kD.The TeXDH strictly preferred NAD^(+)as a coenzyme to NADP^(+).The optimal temperature and pH of the TeXDH were 40℃and 10.0,respectively.After EDTA treatment,the enzyme activity of TeXDH decreased to 43.26%of the initial enzyme activity,while the divalent metal ions Mg^(2+)or Ca^(2+)could recover the enzyme activity of TeXDH,reaching 103.32%and 110.69%of the initial enzyme activity,respectively,making them the optimal divalent metal ion cofactors for TeXDH enzyme.However,the divalent metal ions of Mn^(2+),Ni^(2+),Cu^(2+),Zn^(2+),Co^(2+),and Cd^(2+)significantly inhibited the activity of TeXDH.ICP⁃MS and molecular doc⁃king studies revealed that 1 mol/L of TeXDH bound 2 mol/L Zn^(2+)ions and 1 mol/L Mg^(2+)ion.Further⁃more,TeXDH exhibited a high specificity for xylitol,laying the foundation for the development of future xylitol biosensors.展开更多
Objective To investigate the spatiotemporal patterns and socioeconomic factors influencing the incidence of tuberculosis(TB)in the Guangdong Province between 2010 and 2019.Method Spatial and temporal variations in TB ...Objective To investigate the spatiotemporal patterns and socioeconomic factors influencing the incidence of tuberculosis(TB)in the Guangdong Province between 2010 and 2019.Method Spatial and temporal variations in TB incidence were mapped using heat maps and hierarchical clustering.Socioenvironmental influencing factors were evaluated using a Bayesian spatiotemporal conditional autoregressive(ST-CAR)model.Results Annual incidence of TB in Guangdong decreased from 91.85/100,000 in 2010 to 53.06/100,000in 2019.Spatial hotspots were found in northeastern Guangdong,particularly in Heyuan,Shanwei,and Shantou,while Shenzhen,Dongguan,and Foshan had the lowest rates in the Pearl River Delta.The STCAR model showed that the TB risk was lower with higher per capita Gross Domestic Product(GDP)[Relative Risk(RR),0.91;95%Confidence Interval(CI):0.86–0.98],more the ratio of licensed physicians and physician(RR,0.94;95%CI:0.90-0.98),and higher per capita public expenditure(RR,0.94;95%CI:0.90–0.97),with a marginal effect of population density(RR,0.86;95%CI:0.86–1.00).Conclusion The incidence of TB in Guangdong varies spatially and temporally.Areas with poor economic conditions and insufficient healthcare resources are at an increased risk of TB infection.Strategies focusing on equitable health resource distribution and economic development are the key to TB control.展开更多
DNA microarray technology is an extremely effective technique for studying gene expression patterns in cells, and the main challenge currently faced by this technology is how to analyze the large amount of gene expres...DNA microarray technology is an extremely effective technique for studying gene expression patterns in cells, and the main challenge currently faced by this technology is how to analyze the large amount of gene expression data generated. To address this, this paper employs a mixed-effects model to analyze gene expression data. In terms of data selection, 1176 genes from the white mouse gene expression dataset under two experimental conditions were chosen, setting up two conditions: pneumococcal infection and no infection, and constructing a mixed-effects model. After preprocessing the gene chip information, the data were imported into the model, preliminary results were calculated, and permutation tests were performed to biologically validate the preliminary results using GSEA. The final dataset consists of 20 groups of gene expression data from pneumococcal infection, which categorizes functionally related genes based on the similarity of their expression profiles, facilitating the study of genes with unknown functions.展开更多
This study examines the effects of rapid land use changes in India,with a specific focus on Sonipat District in Haryana—a region undergoing significant urban expansion.Over the past two decades,rural landscapes in So...This study examines the effects of rapid land use changes in India,with a specific focus on Sonipat District in Haryana—a region undergoing significant urban expansion.Over the past two decades,rural landscapes in Sonipat have undergone notable transformation,as open spaces and agricultural lands are increasingly converted into residential colonies,commercial hubs,and industrial zones.While such changes reflect economic development and urban growth,they also raise critical concerns about sustainability,especially in terms of food security,groundwater depletion,and environmental degradation.The study examines land use changes between 2000 and 2024 using remote sensing techniques and spatial analysis.It further incorporates secondary data and insights from community-level interactions to assess the socio-economic and ecological impacts of this transformation.The findings indicate rising land fragmentation,loss of agricultural livelihoods,pressure on civic infrastructure,and increasing pollution—factors that threaten long-term regional sustainability.The study underscores the urgent need to reconcile urban development with environmental and social sustainability.By offering a detailed case study of Sonipat,this research contributes to the broader discourse on India’s urbanisation pathways.It aims to provide policymakers,planners,and researchers with evidence-based recommendations to manage land transitions more responsibly,promoting urban growth models that ensure ecological integrity,equitable development,and long-term resilience.展开更多
Neuronal activity,synaptic transmission,and molecular changes in the basolateral amygdala play critical roles in fear memory.Cylindromatosis(CYLD)is a deubiquitinase that negatively regulates the nuclear factor kappa-...Neuronal activity,synaptic transmission,and molecular changes in the basolateral amygdala play critical roles in fear memory.Cylindromatosis(CYLD)is a deubiquitinase that negatively regulates the nuclear factor kappa-B pathway.CYLD is well studied in non-neuronal cells,yet underinvestigated in the brain,where it is highly expressed.Emerging studies have shown involvement of CYLD in the remodeling of glutamatergic synapses,neuroinflammation,fear memory,and anxiety-and autism-like behaviors.However,the precise role of CYLD in glutamatergic neurons is largely unknown.Here,we first proposed involvement of CYLD in cued fear expression.We next constructed transgenic model mice with specific deletion of Cyld from glutamatergic neurons.Our results show that glutamatergic CYLD deficiency exaggerated the expression of cued fear in only male mice.Further,loss of CYLD in glutamatergic neurons resulted in enhanced neuronal activation,impaired excitatory synaptic transmission,and altered levels of glutamate receptors accompanied by over-activation of microglia in the basolateral amygdala of male mice.Altogether,our study suggests a critical role of glutamatergic CYLD in maintaining normal neuronal,synaptic,and microglial activation.This may contribute,at least in part,to cued fear expression.展开更多
As Deepfake technology continues to evolve,the distinction between real and fake content becomes increasingly blurred.Most existing Deepfake video detectionmethods rely on single-frame facial image features,which limi...As Deepfake technology continues to evolve,the distinction between real and fake content becomes increasingly blurred.Most existing Deepfake video detectionmethods rely on single-frame facial image features,which limits their ability to capture temporal differences between frames.Current methods also exhibit limited generalization capabilities,struggling to detect content generated by unknown forgery algorithms.Moreover,the diversity and complexity of forgery techniques introduced by Artificial Intelligence Generated Content(AIGC)present significant challenges for traditional detection frameworks,whichmust balance high detection accuracy with robust performance.To address these challenges,we propose a novel Deepfake detection framework that combines a two-stream convolutional network with a Vision Transformer(ViT)module to enhance spatio-temporal feature representation.The ViT model extracts spatial features from the forged video,while the 3D convolutional network captures temporal features.The 3D convolution enables cross-frame feature extraction,allowing the model to detect subtle facial changes between frames.The confidence scores from both the ViT and 3D convolution submodels are fused at the decision layer,enabling themodel to effectively handle unknown forgery techniques.Focusing on Deepfake videos and GAN-generated images,the proposed approach is evaluated on two widely used public face forgery datasets.Compared to existing state-of-theartmethods,it achieves higher detection accuracy and better generalization performance,offering a robust solution for deepfake detection in real-world scenarios.展开更多
Agriculture holds a pivotal position in the economic fabric of every nation,yet concerns about agricultural carbon emission intensity(ACI)have become a major hurdle to achieving global economic sustainability.Focusing...Agriculture holds a pivotal position in the economic fabric of every nation,yet concerns about agricultural carbon emission intensity(ACI)have become a major hurdle to achieving global economic sustainability.Focusing on 31 provincial-level regions in China,this study uses the Exploratory Spatio-temporal Data Analysis(ESTDA)and Panel Quantile Regression(PQR)model to analyze the spatio-temporal interaction characteristics and influencing factors of ACI in China from 2004 to 2023.The findings are as follows:(1)ACI showed an overall downward trend,and the spatial distribution pattern was characterized by“high in the western region and low along the southeastern coast”.Although the overall disparity tended to converge,some high-carbon-intensity regions exhibited extreme trends.ACI displayed clear spatial directionality,with the spatial center shifting steadily toward the northeast.(2)Regions in the northwest,northeast,and central-south parts exhibited strong local spatial structural dynamics,and the local spatial dependence of ACI in each region showed a nonlinear trend.Generally speaking,the spatial association pattern demonstrated a certain degree of inertia in spatial transfer,reflecting strong path dependence or spatial lock-in characteristics.(3)Optimization of industrial structure and improvement in agricultural mechanization will increase ACI,while economic development can effectively reduce it.The impact of urbanization on ACI exhibits a nonlinear pattern.The coordinated development of economic growth and urbanization significantly reduces ACI,with a stronger emission reduction observed in regions with low ACI.The optimization of industrial structure,when combined with urbanization and environmental regulation,contributes to significant emission reductions particularly in high-ACI areas.Similarly,the synergy between agricultural mechanization and urbanization effectively lowers emissions in low-ACI regions,though this effect diminishes in areas with higher ACI.展开更多
Sloping farmland,particularly in mountainous and hilly areas,constitutes a significant component of regional farmland resources.An investigation into the spatio-temporal pattern of sloping farmland and its influencing...Sloping farmland,particularly in mountainous and hilly areas,constitutes a significant component of regional farmland resources.An investigation into the spatio-temporal pattern of sloping farmland and its influencing factors in China is imperative for the efficient utilization of farmland and the optimization of land space.We used land use transfer matrix,geographically weighted regression model and geographical detector to conduct this study.Results showed that sloping farmland in China firstly decreased and then increased from 2000 to 2020.The proportion of sloping farmland decreased radially outward from Sichuan basin to the surrounding areas.Change rates of sloping farmland with different slopes varied and the slope with 6°-15°underwent the fastest changes.The influencing factors of farmland at various slope degrees were different.For sloping farmland below 15°,land use intensity and elevation had the greatest contribution.For sloping farmland between 15°and 25°,elevation,land use intensity,and population density were the main influencing factors.Sloping farmland above 25°was mostly affected by natural factors.This study can provide scientific basis for rational development and protection of sloping farmland.展开更多
Current spatio-temporal action detection methods lack sufficient capabilities in extracting and comprehending spatio-temporal information. This paper introduces an end-to-end Adaptive Cross-Scale Fusion Encoder-Decode...Current spatio-temporal action detection methods lack sufficient capabilities in extracting and comprehending spatio-temporal information. This paper introduces an end-to-end Adaptive Cross-Scale Fusion Encoder-Decoder (ACSF-ED) network to predict the action and locate the object efficiently. In the Adaptive Cross-Scale Fusion Spatio-Temporal Encoder (ACSF ST-Encoder), the Asymptotic Cross-scale Feature-fusion Module (ACCFM) is designed to address the issue of information degradation caused by the propagation of high-level semantic information, thereby extracting high-quality multi-scale features to provide superior features for subsequent spatio-temporal information modeling. Within the Shared-Head Decoder structure, a shared classification and regression detection head is constructed. A multi-constraint loss function composed of one-to-one, one-to-many, and contrastive denoising losses is designed to address the problem of insufficient constraint force in predicting results with traditional methods. This loss function enhances the accuracy of model classification predictions and improves the proximity of regression position predictions to ground truth objects. The proposed method model is evaluated on the popular dataset UCF101-24 and JHMDB-21. Experimental results demonstrate that the proposed method achieves an accuracy of 81.52% on the Frame-mAP metric, surpassing current existing methods.展开更多
Electrocardiogram (ECG) analysis is critical for detecting arrhythmias, but traditional methods struggle with large-scale Electrocardiogram data and rare arrhythmia events in imbalanced datasets. These methods fail to...Electrocardiogram (ECG) analysis is critical for detecting arrhythmias, but traditional methods struggle with large-scale Electrocardiogram data and rare arrhythmia events in imbalanced datasets. These methods fail to perform multi-perspective learning of temporal signals and Electrocardiogram images, nor can they fully extract the latent information within the data, falling short of the accuracy required by clinicians. Therefore, this paper proposes an innovative hybrid multimodal spatiotemporal neural network to address these challenges. The model employs a multimodal data augmentation framework integrating visual and signal-based features to enhance the classification performance of rare arrhythmias in imbalanced datasets. Additionally, the spatiotemporal fusion module incorporates a spatiotemporal graph convolutional network to jointly model temporal and spatial features, uncovering complex dependencies within the Electrocardiogram data and improving the model’s ability to represent complex patterns. In experiments conducted on the MIT-BIH arrhythmia dataset, the model achieved 99.95% accuracy, 99.80% recall, and a 99.78% F1 score. The model was further validated for generalization using the clinical INCART arrhythmia dataset, and the results demonstrated its effectiveness in terms of both generalization and robustness.展开更多
Exploring the spatial evolution patterns of land use in creative urban tourism complexes provides theoretical and decision-making support to foster creative tourism projects.This study focuses on the Hangzhou Leisure ...Exploring the spatial evolution patterns of land use in creative urban tourism complexes provides theoretical and decision-making support to foster creative tourism projects.This study focuses on the Hangzhou Leisure Expo Garden as a case study,utilizing a land use change index model to analyze the spatial evolution characteristics and dynamic processes of creative urban tourism complexes,as well as to explore their spatial differentiation mechanisms.The analysis indicates that Hangzhou Leisure Expo Garden,initially a derelict industrial area dominated by production and residential land use,has evolved into a creative urban tourism complex with tourism comprehensive service land at its core,going through the pattern evolution processes of“constrained sprawl,”“intensive expansion,”and“random integration.”From the perspective of tourism human-land relationships,the formation of land use evolution patterns in creative urban tourism complexes results from various stakeholders(government,tourism enterprises,residents,tourists,etc.),as humanistic factors,continuously adapting to specific urban spaces,which are considered as geographical elements and have locational advantages and are oriented towards economic and social values.Based on the acquisition of stakeholder interests,the transformation of resource-disadvantaged areas into tourism advantage areas is facilitated,thereby achieving the re-creation of tourism creative space and promoting intensive spatial growth.展开更多
False Data Injection Attacks(FDIAs)pose a critical security threat to modern power grids,corrupting state estimation and enabling malicious control actions that can lead to severe consequences,including cascading fail...False Data Injection Attacks(FDIAs)pose a critical security threat to modern power grids,corrupting state estimation and enabling malicious control actions that can lead to severe consequences,including cascading failures,large-scale blackouts,and significant economic losses.While detecting attacks is important,accurately localizing compromised nodes or measurements is even more critical,as it enables timely mitigation,targeted response,and enhanced system resilience beyond what detection alone can offer.Existing research typically models topological features using fixed structures,which can introduce irrelevant information and affect the effectiveness of feature extraction.To address this limitation,this paper proposes an FDIA localization model with adaptive neighborhood selection,which dynamically captures spatial dependencies of the power grid by adjusting node relationships based on data-driven similarities.The improved Transformer is employed to pre-fuse global spatial features of the graph,enriching the feature representation.To improve spatio-temporal correlation extraction for FDIA localization,the proposed model employs dilated causal convolution with a gating mechanism combined with graph convolution to capture and fuse long-range temporal features and adaptive topological features.This fully exploits the temporal dynamics and spatial dependencies inherent in the power grid.Finally,multi-source information is integrated to generate highly robust node embeddings,enhancing FDIA detection and localization.Experiments are conducted on IEEE 14,57,and 118-bus systems,and the results demonstrate that the proposed model substantially improves the accuracy of FDIA localization.Additional experiments are conducted to verify the effectiveness and robustness of the proposed model.展开更多
Strong sensitivity of satellite microwave remote sensing to the change of surface dielectric properties,as well as the insensitivity to air pollution and solar illumination effects,makes it very suitable for monitorin...Strong sensitivity of satellite microwave remote sensing to the change of surface dielectric properties,as well as the insensitivity to air pollution and solar illumination effects,makes it very suitable for monitoring freeze-thaw conditions.The freeze-thaw cycle changes in the Qinghai-Xizang Plateau have an important impact on the ecological environment and infrastructure.Based on the Scanning Multi-channel Microwave Radiometer(SMMR)and other sensors of microwave satellite,the freeze-thaw cycle data of permafrost in the Qinghai-Xizang Plateau in the past 40 years from 1981 to 2020 was obtained.The changes of soil freeze-thaw conditions in different seasons of 2020 and in the same season of 1990,2000,2010 and 2020 were compared,and the annual variation trend of soil freeze-thaw area in the four years was analyzed.Further,the linear regression analysis was carried out on the duration of soil freezing/thawing/transition and the interannual variation trend under different area conditions from 1981 to 2020.The results show that the freeze-thaw changes in different years are similar.In winter,it is mainly frozen for about 110 days.Spring and autumn are transitional periods,lasting for 170 days.In summer,it is mainly thawed for about 80 days.From 1981 to 2020,the freezing period and the average freezing area of the Qinghai-Xizang Plateau decreased at a rate of 0.22 days and 1986 km^(2) per year,respectively,while the thawing period and the average thawing area increased at a rate of 0.07 days and 3187 km^(2) per year,respectively.The research results provide important theoretical support for the ecological environment and permafrost protection of the Qinghai-Xizang Plateau.展开更多
Mandarin fish(Siniperca scherzeri) has high market prices and significant market potential in China because of its highquality meat and high nutritional value. However, due to the limited scale of aquaculture, meeting...Mandarin fish(Siniperca scherzeri) has high market prices and significant market potential in China because of its highquality meat and high nutritional value. However, due to the limited scale of aquaculture, meeting the market demand is difficult, making the effective development of the aquaculture potential of mandarin fish an important challenge for the industry. In this study, a 30-d breeding experiment was conducted on mandarin fish larvae under three photoperiod conditions: G1 8 h light:16 h dark(8L:16D), G2 12 h light:12 h dark(12L:12D), and G3 16 h light:8 h dark(16L:8D). The results showed that the G2 group exhibited the best growth performance and development status, with final body weights, weight gain rates, and specific growth rates all higher than those of the other two groups(P < 0.05). Observations of sections from each group revealed that the intestinal villi length and muscle thickness of the G2 group were significantly greater than those of the other two groups(P < 0.05). The G2 group inhibited the transcriptional activation of key circadian rhythm genes, including nr1d2a, nr1d1 and per1, while upregulating the expression of BMAL1 in S. scherzeri.The activation of both the insulin signalling pathway and the Fox O signalling pathway enhanced the efficient secretion of insulin, which subsequently played a critical role in regulating fatty acid metabolism. This active fatty acid metabolism provided an optimal energy supply, ensuring that other nutrients were fully utilized during the growth and development process while minimizing unnecessary nutrient loss. Consequently, this mechanism effectively promoted the overall growth and development of S. scherzeri. This study was the first to elucidate the transcriptomic expression patterns of S. scherzeri under varying photoperiod conditions. In response to the cyclic alternation of day and night, S. scherzeri regulated their metabolic levels and the transcriptional activation of downstream target genes via insulin signalling.展开更多
Rural industrial development and ecological civilization transformation are crucial to China's comprehensive advancement of rural revitalization. However, many regions still face the issue of a conflict between ec...Rural industrial development and ecological civilization transformation are crucial to China's comprehensive advancement of rural revitalization. However, many regions still face the issue of a conflict between economic development and ecological protection. Symbiosis theory provides a new perspective for understanding the interactive relationship of rural industry and ecology(RIE). Jiangxi Province, one of China's first national pilot zones for ecological conservation, exemplifies rural areas' typical challenges in balancing industrial development and ecological protection, and has been selected as the study area. By integrating the characteristics of RIE with symbiosis theory, a comprehensive RIE assessment framework was constructed. The comprehensive model, spatial autocorrelation method, and symbiosis theory model were employed to address the spatio-temporal evolution characteristics of RIE, reveal the symbiotic relationship(SR) and the symbiosis types of RIE, and explore the path of symbiotic development between RIE. Results indicated that:(1) Since 2015, RIE has shown an upward trend, with regional differences in ecological development levels gradually shrinking. Significant spatial correlation and agglomeration characteristics exist, but a coordinated regional development pattern has not yet emerged.(2) Overall, the symbiosis degree(SD) between RIE showed a positive trend with narrowing gaps, the symbiosis coefficient(SC) of industry to ecology converged to 0.5 under a positive asymmetric mutualism(PAM) mode, suggesting that their relationship tended to be coordinated. Specifically, rural ecology grew increasingly influential on industry in most counties.(3) Rural areas were classified into different types led by industry-dominated PAM, and various optimization paths were proposed. Future efforts should promote the equalization of the interaction forces between RIE according to local conditions.展开更多
基金Project (No. 2004-527) supported by the Scientific Research Foun-dation for the Returned Overseas Chinese Scholars, State EducationMinistry, China
文摘Confocal laser scanning microscopy was used to observe the spatio-temporal expression of the pathway-specific gene redD during S. coelicolor cell cultivation. The corresponding mutant S. coelicolor lyqRY1522 carrying redD::eyfp in the chro- mosome was constructed. The temporal expression results of the fusion protein during submerged cultivation demonstrated that expression of redD began in the transition phase, continuing through the exponential growth phase to the stationary phase, and reached maximum in the stationary phase. On the other hand, redD was expressed only in substrate mycelia during solid-state culture, while aerial mycelia remained essentially non-fluorescent throughout culture. Results demonstrated that the expression pattern of redD coincides with that of the biosynthesis of the antibiotics during culture, revealing a direct correlation between the spatio-temporal distribution of regulatory gene expression and second metabolism.
基金National Natural Science Foundation of China,No.42161006Yunnan Fundamental Research Projects No.202201AT070094,No.202301BF070001-004+1 种基金Special Project for High-level Talents of Yunnan Province for Young Top Talents,No.C6213001159European Research Council(ERC)Starting-Grant STORIES,No.101040939。
文摘Due to water conflicts and allocation in the Lancang-Mekong River Basin(LMRB),the spatio-temporal differentiation of total water resources and the natural-human influence need to be clarified.This work investigated LMRB's terrestrial water storage anomaly(TWSA)and its spatio-temporal dynamics during 2002–2020.Considering the effects of natural factors and human activities,the respective contributions of climate variability and human activities to terrestrial water storage change(TWSC)were separated.Results showed that:(1)LMRB's TWSA decreased by 0.3158 cm/a.(2)TWSA showed a gradual increase in distribution from southwest of MRB to middle LMRB and from northeast of LRB to middle LMRB.TWSA positively changed in Myanmar while slightly changed in Laos and China.It negatively changed in Vietnam,Thailand and Cambodia.(3)TWSA components decreased in a descending order of soil moisture,groundwater and precipitation.(4)Natural factors had a substantial and spatial differentiated influence on TWSA over the LMRB.(5)Climate variability contributed 79%of TWSC in the LMRB while human activities contributed 21%with an increasing impact after 2008.The TWSC of upstream basin countries was found to be controlled by climate variability while Vietnam and Cambodia's TWSC has been controlled by human activities since 2012.
文摘The ability to accurately predict urban traffic flows is crucial for optimising city operations.Consequently,various methods for forecasting urban traffic have been developed,focusing on analysing historical data to understand complex mobility patterns.Deep learning techniques,such as graph neural networks(GNNs),are popular for their ability to capture spatio-temporal dependencies.However,these models often become overly complex due to the large number of hyper-parameters involved.In this study,we introduce Dynamic Multi-Graph Spatial-Temporal Graph Neural Ordinary Differential Equation Networks(DMST-GNODE),a framework based on ordinary differential equations(ODEs)that autonomously discovers effective spatial-temporal graph neural network(STGNN)architectures for traffic prediction tasks.The comparative analysis of DMST-GNODE and baseline models indicates that DMST-GNODE model demonstrates superior performance across multiple datasets,consistently achieving the lowest Root Mean Square Error(RMSE)and Mean Absolute Error(MAE)values,alongside the highest accuracy.On the BKK(Bangkok)dataset,it outperformed other models with an RMSE of 3.3165 and an accuracy of 0.9367 for a 20-min interval,maintaining this trend across 40 and 60 min.Similarly,on the PeMS08 dataset,DMST-GNODE achieved the best performance with an RMSE of 19.4863 and an accuracy of 0.9377 at 20 min,demonstrating its effectiveness over longer periods.The Los_Loop dataset results further emphasise this model’s advantage,with an RMSE of 3.3422 and an accuracy of 0.7643 at 20 min,consistently maintaining superiority across all time intervals.These numerical highlights indicate that DMST-GNODE not only outperforms baseline models but also achieves higher accuracy and lower errors across different time intervals and datasets.
基金supported by the Central Public-Interest Scientific Institution Basal Research Fund,China(Grant No.CPSIBRF-CNRRI-202403)。
文摘Rice is a poor source of folate,an essential micronutrient for the body.Biofortification offers an effective way to enhance the folate content of rice and alleviate folate deficiencies in humans.In this study,we confirmed that OsADCS and OsGTPCHI,encoding the initial enzymes necessary for folate synthesis,positively regulate folate accumulation in knockout mutants of both japonica and indica rice backgrounds.The folate content in the low-folate japonica variety was slightly increased by the expression of the indica alleles driven by the endosperm-specific promoter.We further obtained co-expression lines by stacking OsADCS and OsGTPCHI genes;the folate accumulation in brown rice and polished rice reached 5.65μg/g and 2.95μg/g,respectively,representing 37.9-fold and 26.5-fold increases compared with the wild type.Transcriptomic analysis of rice grains from six transgenic lines showed that folate changes affected biological pathways involved in the synthesis and metabolism of rice seed storage substances,while the expression of other folate synthesis genes was weakly regulated.In addition,we identified Aus rice as a high-folate germplasm carrying superior haplotypes of OsADCS and OsGTPCHI through natural variation.This study provides an alternative and effective complementary strategy for rice biofortification,promoting the rational combination of metabolic engineering and conventional breeding to breed high-folate varieties.
文摘Objective INF2 is a member of the formins family.Abnormal expression and regulation of INF2 have been associated with the progression of various tumors,but the expression and role of INF2 in hepatocellular carcinoma(HCC)remain unclear.HCC is a highly lethal malignant tumor.Given the limitations of traditional treatments,this study explored the expression level,clinical value and potential mechanism of INF2 in HCC in order to seek new therapeutic targets.Methods In this study,we used public databases to analyze the expression of INF2 in pan-cancer and HCC,as well as the impact of INF2 expression levels on HCC prognosis.Quantitative real time polymerase chain reaction(RT-qPCR),Western blot,and immunohistochemistry were used to detect the expression level of INF2 in liver cancer cells and human HCC tissues.The correlation between INF2 expression and clinical pathological features was analyzed using public databases and clinical data of human HCC samples.Subsequently,the effects of INF2 expression on the biological function and Drp1 phosphorylation of liver cancer cells were elucidated through in vitro and in vivo experiments.Finally,the predictive value and potential mechanism of INF2 in HCC were further analyzed through database and immunohistochemical experiments.Results INF2 is aberrantly high expression in HCC samples and the high expression of INF2 is correlated with overall survival,liver cirrhosis and pathological differentiation of HCC patients.The expression level of INF2 has certain diagnostic value in predicting the prognosis and pathological differentiation of HCC.In vivo and in vitro HCC models,upregulated expression of INF2 triggers the proliferation and migration of the HCC cell,while knockdown of INF2 could counteract this effect.INF2 in liver cancer cells may affect mitochondrial division by inducing Drp1 phosphorylation and mediate immune escape by up-regulating PD-L1 expression,thus promoting tumor progression.Conclusion INF2 is highly expressed in HCC and is associated with poor prognosis.High expression of INF2 may promote HCC progression by inducing Drp1 phosphorylation and up-regulation of PD-L1 expression,and targeting INF2 may be beneficial for HCC patients with high expression of INF2.
基金湖南省教育厅基金优秀青年项目(No.22B0482)湖南科技大学博士启动基金(No.E51992 and E51993)资助。
文摘The xylitol dehydrogenase(XDH)is a crucial enzyme involved in the xylose utilization in pentose⁃catabolizing yeasts and fungi.In addition to producing xylulose,XDH can also be employed to develop a biosensor for monitoring xylitol concentration.In this study,the gene encoding the thermophilic fungus Talaromyces emersonii XDH(TeXDH)was heterologously expressed in Escherichia coli BL21(DE3)at 16℃in the soluble form.Recombinant TeXDH with high purity was purified by using a Ni⁃NTA affinity column.Size⁃exclusion chromatography and SDS⁃PAGE analysis demonstrated that the puri⁃fied recombinant TeXDH exists as a native trimer with a molecular mass of approximately 116 kD,and is composed of three identical subunits,each with a molecular weight of around 39 kD.The TeXDH strictly preferred NAD^(+)as a coenzyme to NADP^(+).The optimal temperature and pH of the TeXDH were 40℃and 10.0,respectively.After EDTA treatment,the enzyme activity of TeXDH decreased to 43.26%of the initial enzyme activity,while the divalent metal ions Mg^(2+)or Ca^(2+)could recover the enzyme activity of TeXDH,reaching 103.32%and 110.69%of the initial enzyme activity,respectively,making them the optimal divalent metal ion cofactors for TeXDH enzyme.However,the divalent metal ions of Mn^(2+),Ni^(2+),Cu^(2+),Zn^(2+),Co^(2+),and Cd^(2+)significantly inhibited the activity of TeXDH.ICP⁃MS and molecular doc⁃king studies revealed that 1 mol/L of TeXDH bound 2 mol/L Zn^(2+)ions and 1 mol/L Mg^(2+)ion.Further⁃more,TeXDH exhibited a high specificity for xylitol,laying the foundation for the development of future xylitol biosensors.
基金supported by the Guangdong Provincial Clinical Research Center for Tuberculosis(No.2020B1111170014)。
文摘Objective To investigate the spatiotemporal patterns and socioeconomic factors influencing the incidence of tuberculosis(TB)in the Guangdong Province between 2010 and 2019.Method Spatial and temporal variations in TB incidence were mapped using heat maps and hierarchical clustering.Socioenvironmental influencing factors were evaluated using a Bayesian spatiotemporal conditional autoregressive(ST-CAR)model.Results Annual incidence of TB in Guangdong decreased from 91.85/100,000 in 2010 to 53.06/100,000in 2019.Spatial hotspots were found in northeastern Guangdong,particularly in Heyuan,Shanwei,and Shantou,while Shenzhen,Dongguan,and Foshan had the lowest rates in the Pearl River Delta.The STCAR model showed that the TB risk was lower with higher per capita Gross Domestic Product(GDP)[Relative Risk(RR),0.91;95%Confidence Interval(CI):0.86–0.98],more the ratio of licensed physicians and physician(RR,0.94;95%CI:0.90-0.98),and higher per capita public expenditure(RR,0.94;95%CI:0.90–0.97),with a marginal effect of population density(RR,0.86;95%CI:0.86–1.00).Conclusion The incidence of TB in Guangdong varies spatially and temporally.Areas with poor economic conditions and insufficient healthcare resources are at an increased risk of TB infection.Strategies focusing on equitable health resource distribution and economic development are the key to TB control.
文摘DNA microarray technology is an extremely effective technique for studying gene expression patterns in cells, and the main challenge currently faced by this technology is how to analyze the large amount of gene expression data generated. To address this, this paper employs a mixed-effects model to analyze gene expression data. In terms of data selection, 1176 genes from the white mouse gene expression dataset under two experimental conditions were chosen, setting up two conditions: pneumococcal infection and no infection, and constructing a mixed-effects model. After preprocessing the gene chip information, the data were imported into the model, preliminary results were calculated, and permutation tests were performed to biologically validate the preliminary results using GSEA. The final dataset consists of 20 groups of gene expression data from pneumococcal infection, which categorizes functionally related genes based on the similarity of their expression profiles, facilitating the study of genes with unknown functions.
文摘This study examines the effects of rapid land use changes in India,with a specific focus on Sonipat District in Haryana—a region undergoing significant urban expansion.Over the past two decades,rural landscapes in Sonipat have undergone notable transformation,as open spaces and agricultural lands are increasingly converted into residential colonies,commercial hubs,and industrial zones.While such changes reflect economic development and urban growth,they also raise critical concerns about sustainability,especially in terms of food security,groundwater depletion,and environmental degradation.The study examines land use changes between 2000 and 2024 using remote sensing techniques and spatial analysis.It further incorporates secondary data and insights from community-level interactions to assess the socio-economic and ecological impacts of this transformation.The findings indicate rising land fragmentation,loss of agricultural livelihoods,pressure on civic infrastructure,and increasing pollution—factors that threaten long-term regional sustainability.The study underscores the urgent need to reconcile urban development with environmental and social sustainability.By offering a detailed case study of Sonipat,this research contributes to the broader discourse on India’s urbanisation pathways.It aims to provide policymakers,planners,and researchers with evidence-based recommendations to manage land transitions more responsibly,promoting urban growth models that ensure ecological integrity,equitable development,and long-term resilience.
基金supported by the National Natural Science Foundation of China,Nos.32371065(to CL)and 32170950(to LY)the Natural Science Foundation of the Guangdong Province,No.2023A1515010899(to CL)the Science and Technology Projects in Guangzhou,Nos.2023A4J0578 and 2024A03J0180(to CW)。
文摘Neuronal activity,synaptic transmission,and molecular changes in the basolateral amygdala play critical roles in fear memory.Cylindromatosis(CYLD)is a deubiquitinase that negatively regulates the nuclear factor kappa-B pathway.CYLD is well studied in non-neuronal cells,yet underinvestigated in the brain,where it is highly expressed.Emerging studies have shown involvement of CYLD in the remodeling of glutamatergic synapses,neuroinflammation,fear memory,and anxiety-and autism-like behaviors.However,the precise role of CYLD in glutamatergic neurons is largely unknown.Here,we first proposed involvement of CYLD in cued fear expression.We next constructed transgenic model mice with specific deletion of Cyld from glutamatergic neurons.Our results show that glutamatergic CYLD deficiency exaggerated the expression of cued fear in only male mice.Further,loss of CYLD in glutamatergic neurons resulted in enhanced neuronal activation,impaired excitatory synaptic transmission,and altered levels of glutamate receptors accompanied by over-activation of microglia in the basolateral amygdala of male mice.Altogether,our study suggests a critical role of glutamatergic CYLD in maintaining normal neuronal,synaptic,and microglial activation.This may contribute,at least in part,to cued fear expression.
基金supported by National Natural Science Foundation of China(Nos.62477026,62177029,61807020)Humanities and Social Sciences Research Program of the Ministry of Education of China(No.23YJAZH047)the Startup Foundation for Introducing Talent of Nanjing University of Posts and Communications under Grant NY222034.
文摘As Deepfake technology continues to evolve,the distinction between real and fake content becomes increasingly blurred.Most existing Deepfake video detectionmethods rely on single-frame facial image features,which limits their ability to capture temporal differences between frames.Current methods also exhibit limited generalization capabilities,struggling to detect content generated by unknown forgery algorithms.Moreover,the diversity and complexity of forgery techniques introduced by Artificial Intelligence Generated Content(AIGC)present significant challenges for traditional detection frameworks,whichmust balance high detection accuracy with robust performance.To address these challenges,we propose a novel Deepfake detection framework that combines a two-stream convolutional network with a Vision Transformer(ViT)module to enhance spatio-temporal feature representation.The ViT model extracts spatial features from the forged video,while the 3D convolutional network captures temporal features.The 3D convolution enables cross-frame feature extraction,allowing the model to detect subtle facial changes between frames.The confidence scores from both the ViT and 3D convolution submodels are fused at the decision layer,enabling themodel to effectively handle unknown forgery techniques.Focusing on Deepfake videos and GAN-generated images,the proposed approach is evaluated on two widely used public face forgery datasets.Compared to existing state-of-theartmethods,it achieves higher detection accuracy and better generalization performance,offering a robust solution for deepfake detection in real-world scenarios.
基金National Natural Science Foundation of China,No.42230106,No.42171250State Key Laboratory of Earth Surface Processes and Resource Ecology,No.2022-ZD-04。
文摘Agriculture holds a pivotal position in the economic fabric of every nation,yet concerns about agricultural carbon emission intensity(ACI)have become a major hurdle to achieving global economic sustainability.Focusing on 31 provincial-level regions in China,this study uses the Exploratory Spatio-temporal Data Analysis(ESTDA)and Panel Quantile Regression(PQR)model to analyze the spatio-temporal interaction characteristics and influencing factors of ACI in China from 2004 to 2023.The findings are as follows:(1)ACI showed an overall downward trend,and the spatial distribution pattern was characterized by“high in the western region and low along the southeastern coast”.Although the overall disparity tended to converge,some high-carbon-intensity regions exhibited extreme trends.ACI displayed clear spatial directionality,with the spatial center shifting steadily toward the northeast.(2)Regions in the northwest,northeast,and central-south parts exhibited strong local spatial structural dynamics,and the local spatial dependence of ACI in each region showed a nonlinear trend.Generally speaking,the spatial association pattern demonstrated a certain degree of inertia in spatial transfer,reflecting strong path dependence or spatial lock-in characteristics.(3)Optimization of industrial structure and improvement in agricultural mechanization will increase ACI,while economic development can effectively reduce it.The impact of urbanization on ACI exhibits a nonlinear pattern.The coordinated development of economic growth and urbanization significantly reduces ACI,with a stronger emission reduction observed in regions with low ACI.The optimization of industrial structure,when combined with urbanization and environmental regulation,contributes to significant emission reductions particularly in high-ACI areas.Similarly,the synergy between agricultural mechanization and urbanization effectively lowers emissions in low-ACI regions,though this effect diminishes in areas with higher ACI.
基金supported by the Key Laboratory of Natural Resources Monitoring and Supervision in Southern Hilly Region,Ministry of Natural Resources(NRMSSHR2023Y02)Yunnan Key Laboratory of Plateau Geographic Processes and Environmental Changes,Faculty of Geography,Yunnan Normal University(PGPEC2304)China Scholarship Council。
文摘Sloping farmland,particularly in mountainous and hilly areas,constitutes a significant component of regional farmland resources.An investigation into the spatio-temporal pattern of sloping farmland and its influencing factors in China is imperative for the efficient utilization of farmland and the optimization of land space.We used land use transfer matrix,geographically weighted regression model and geographical detector to conduct this study.Results showed that sloping farmland in China firstly decreased and then increased from 2000 to 2020.The proportion of sloping farmland decreased radially outward from Sichuan basin to the surrounding areas.Change rates of sloping farmland with different slopes varied and the slope with 6°-15°underwent the fastest changes.The influencing factors of farmland at various slope degrees were different.For sloping farmland below 15°,land use intensity and elevation had the greatest contribution.For sloping farmland between 15°and 25°,elevation,land use intensity,and population density were the main influencing factors.Sloping farmland above 25°was mostly affected by natural factors.This study can provide scientific basis for rational development and protection of sloping farmland.
基金support for this work was supported by Key Lab of Intelligent and Green Flexographic Printing under Grant ZBKT202301.
文摘Current spatio-temporal action detection methods lack sufficient capabilities in extracting and comprehending spatio-temporal information. This paper introduces an end-to-end Adaptive Cross-Scale Fusion Encoder-Decoder (ACSF-ED) network to predict the action and locate the object efficiently. In the Adaptive Cross-Scale Fusion Spatio-Temporal Encoder (ACSF ST-Encoder), the Asymptotic Cross-scale Feature-fusion Module (ACCFM) is designed to address the issue of information degradation caused by the propagation of high-level semantic information, thereby extracting high-quality multi-scale features to provide superior features for subsequent spatio-temporal information modeling. Within the Shared-Head Decoder structure, a shared classification and regression detection head is constructed. A multi-constraint loss function composed of one-to-one, one-to-many, and contrastive denoising losses is designed to address the problem of insufficient constraint force in predicting results with traditional methods. This loss function enhances the accuracy of model classification predictions and improves the proximity of regression position predictions to ground truth objects. The proposed method model is evaluated on the popular dataset UCF101-24 and JHMDB-21. Experimental results demonstrate that the proposed method achieves an accuracy of 81.52% on the Frame-mAP metric, surpassing current existing methods.
基金supported by The Henan Province Science and Technology Research Project(242102211046)the Key Scientific Research Project of Higher Education Institutions in Henan Province(25A520039)+1 种基金theNatural Science Foundation project of Zhongyuan Institute of Technology(K2025YB011)the Zhongyuan University of Technology Graduate Education and Teaching Reform Research Project(JG202424).
文摘Electrocardiogram (ECG) analysis is critical for detecting arrhythmias, but traditional methods struggle with large-scale Electrocardiogram data and rare arrhythmia events in imbalanced datasets. These methods fail to perform multi-perspective learning of temporal signals and Electrocardiogram images, nor can they fully extract the latent information within the data, falling short of the accuracy required by clinicians. Therefore, this paper proposes an innovative hybrid multimodal spatiotemporal neural network to address these challenges. The model employs a multimodal data augmentation framework integrating visual and signal-based features to enhance the classification performance of rare arrhythmias in imbalanced datasets. Additionally, the spatiotemporal fusion module incorporates a spatiotemporal graph convolutional network to jointly model temporal and spatial features, uncovering complex dependencies within the Electrocardiogram data and improving the model’s ability to represent complex patterns. In experiments conducted on the MIT-BIH arrhythmia dataset, the model achieved 99.95% accuracy, 99.80% recall, and a 99.78% F1 score. The model was further validated for generalization using the clinical INCART arrhythmia dataset, and the results demonstrated its effectiveness in terms of both generalization and robustness.
文摘Exploring the spatial evolution patterns of land use in creative urban tourism complexes provides theoretical and decision-making support to foster creative tourism projects.This study focuses on the Hangzhou Leisure Expo Garden as a case study,utilizing a land use change index model to analyze the spatial evolution characteristics and dynamic processes of creative urban tourism complexes,as well as to explore their spatial differentiation mechanisms.The analysis indicates that Hangzhou Leisure Expo Garden,initially a derelict industrial area dominated by production and residential land use,has evolved into a creative urban tourism complex with tourism comprehensive service land at its core,going through the pattern evolution processes of“constrained sprawl,”“intensive expansion,”and“random integration.”From the perspective of tourism human-land relationships,the formation of land use evolution patterns in creative urban tourism complexes results from various stakeholders(government,tourism enterprises,residents,tourists,etc.),as humanistic factors,continuously adapting to specific urban spaces,which are considered as geographical elements and have locational advantages and are oriented towards economic and social values.Based on the acquisition of stakeholder interests,the transformation of resource-disadvantaged areas into tourism advantage areas is facilitated,thereby achieving the re-creation of tourism creative space and promoting intensive spatial growth.
基金supported by National Key Research and Development Plan of China(No.2022YFB3103304).
文摘False Data Injection Attacks(FDIAs)pose a critical security threat to modern power grids,corrupting state estimation and enabling malicious control actions that can lead to severe consequences,including cascading failures,large-scale blackouts,and significant economic losses.While detecting attacks is important,accurately localizing compromised nodes or measurements is even more critical,as it enables timely mitigation,targeted response,and enhanced system resilience beyond what detection alone can offer.Existing research typically models topological features using fixed structures,which can introduce irrelevant information and affect the effectiveness of feature extraction.To address this limitation,this paper proposes an FDIA localization model with adaptive neighborhood selection,which dynamically captures spatial dependencies of the power grid by adjusting node relationships based on data-driven similarities.The improved Transformer is employed to pre-fuse global spatial features of the graph,enriching the feature representation.To improve spatio-temporal correlation extraction for FDIA localization,the proposed model employs dilated causal convolution with a gating mechanism combined with graph convolution to capture and fuse long-range temporal features and adaptive topological features.This fully exploits the temporal dynamics and spatial dependencies inherent in the power grid.Finally,multi-source information is integrated to generate highly robust node embeddings,enhancing FDIA detection and localization.Experiments are conducted on IEEE 14,57,and 118-bus systems,and the results demonstrate that the proposed model substantially improves the accuracy of FDIA localization.Additional experiments are conducted to verify the effectiveness and robustness of the proposed model.
基金National Natural Science foundation of China(No.42271432)Foundation of Shanxi Vocational University of Engineering Science and Technology(No.KJ 202426).
文摘Strong sensitivity of satellite microwave remote sensing to the change of surface dielectric properties,as well as the insensitivity to air pollution and solar illumination effects,makes it very suitable for monitoring freeze-thaw conditions.The freeze-thaw cycle changes in the Qinghai-Xizang Plateau have an important impact on the ecological environment and infrastructure.Based on the Scanning Multi-channel Microwave Radiometer(SMMR)and other sensors of microwave satellite,the freeze-thaw cycle data of permafrost in the Qinghai-Xizang Plateau in the past 40 years from 1981 to 2020 was obtained.The changes of soil freeze-thaw conditions in different seasons of 2020 and in the same season of 1990,2000,2010 and 2020 were compared,and the annual variation trend of soil freeze-thaw area in the four years was analyzed.Further,the linear regression analysis was carried out on the duration of soil freezing/thawing/transition and the interannual variation trend under different area conditions from 1981 to 2020.The results show that the freeze-thaw changes in different years are similar.In winter,it is mainly frozen for about 110 days.Spring and autumn are transitional periods,lasting for 170 days.In summer,it is mainly thawed for about 80 days.From 1981 to 2020,the freezing period and the average freezing area of the Qinghai-Xizang Plateau decreased at a rate of 0.22 days and 1986 km^(2) per year,respectively,while the thawing period and the average thawing area increased at a rate of 0.07 days and 3187 km^(2) per year,respectively.The research results provide important theoretical support for the ecological environment and permafrost protection of the Qinghai-Xizang Plateau.
基金The Science and Technology Plan of Dalian under contract Nos 2023RO058 and 2022RQ060the Liaoning Province Natural Science Planning Fund Project under contract No. 2022-BS-273+1 种基金the Liaoning Provincial Department of Education Basic Research Project under contract No. LJKQZ20222357the Discipline Construction Funding for Marine Science Subject of Dalian Ocean University。
文摘Mandarin fish(Siniperca scherzeri) has high market prices and significant market potential in China because of its highquality meat and high nutritional value. However, due to the limited scale of aquaculture, meeting the market demand is difficult, making the effective development of the aquaculture potential of mandarin fish an important challenge for the industry. In this study, a 30-d breeding experiment was conducted on mandarin fish larvae under three photoperiod conditions: G1 8 h light:16 h dark(8L:16D), G2 12 h light:12 h dark(12L:12D), and G3 16 h light:8 h dark(16L:8D). The results showed that the G2 group exhibited the best growth performance and development status, with final body weights, weight gain rates, and specific growth rates all higher than those of the other two groups(P < 0.05). Observations of sections from each group revealed that the intestinal villi length and muscle thickness of the G2 group were significantly greater than those of the other two groups(P < 0.05). The G2 group inhibited the transcriptional activation of key circadian rhythm genes, including nr1d2a, nr1d1 and per1, while upregulating the expression of BMAL1 in S. scherzeri.The activation of both the insulin signalling pathway and the Fox O signalling pathway enhanced the efficient secretion of insulin, which subsequently played a critical role in regulating fatty acid metabolism. This active fatty acid metabolism provided an optimal energy supply, ensuring that other nutrients were fully utilized during the growth and development process while minimizing unnecessary nutrient loss. Consequently, this mechanism effectively promoted the overall growth and development of S. scherzeri. This study was the first to elucidate the transcriptomic expression patterns of S. scherzeri under varying photoperiod conditions. In response to the cyclic alternation of day and night, S. scherzeri regulated their metabolic levels and the transcriptional activation of downstream target genes via insulin signalling.
基金supported by the National Natural Science Foundation of China (No.42361050,42201232)Humanities and Social Sciences Research Project of Jiangxi Colleges and Universities (No.JC24211)+1 种基金Science and Technology Research Project of Jiangxi Provincial Department of Education (No.GJJ2200553)Jiangxi provincial Social Science Foundation of China (No.23JL11)。
文摘Rural industrial development and ecological civilization transformation are crucial to China's comprehensive advancement of rural revitalization. However, many regions still face the issue of a conflict between economic development and ecological protection. Symbiosis theory provides a new perspective for understanding the interactive relationship of rural industry and ecology(RIE). Jiangxi Province, one of China's first national pilot zones for ecological conservation, exemplifies rural areas' typical challenges in balancing industrial development and ecological protection, and has been selected as the study area. By integrating the characteristics of RIE with symbiosis theory, a comprehensive RIE assessment framework was constructed. The comprehensive model, spatial autocorrelation method, and symbiosis theory model were employed to address the spatio-temporal evolution characteristics of RIE, reveal the symbiotic relationship(SR) and the symbiosis types of RIE, and explore the path of symbiotic development between RIE. Results indicated that:(1) Since 2015, RIE has shown an upward trend, with regional differences in ecological development levels gradually shrinking. Significant spatial correlation and agglomeration characteristics exist, but a coordinated regional development pattern has not yet emerged.(2) Overall, the symbiosis degree(SD) between RIE showed a positive trend with narrowing gaps, the symbiosis coefficient(SC) of industry to ecology converged to 0.5 under a positive asymmetric mutualism(PAM) mode, suggesting that their relationship tended to be coordinated. Specifically, rural ecology grew increasingly influential on industry in most counties.(3) Rural areas were classified into different types led by industry-dominated PAM, and various optimization paths were proposed. Future efforts should promote the equalization of the interaction forces between RIE according to local conditions.
