Quantitative real-time PCR(qPCR)is widely used for gene expression analysis,but its accuracy critically depends on stable internal reference genes for normalization.In marine invertebrates,especially non-model taxa su...Quantitative real-time PCR(qPCR)is widely used for gene expression analysis,but its accuracy critically depends on stable internal reference genes for normalization.In marine invertebrates,especially non-model taxa such as cephalopods,systematic evaluation of reference genes is limited,leading to potential bias.The cuttlefish Sepiella japonica is ecologically and economically important in China,yet previous molecular studies have often relied on single unvalidated reference genes,which may compromise data reliability.This study aimed to systematically evaluate the stability of five commonly used reference genes(18S,ef-1α,ef-1γ,gapdh,andβ-actin)across multiple tissues and sexes of S.japonica,and to identify the most suitable reference genes and optimal number for qPCR normalization.Fifteen to sixteen tissue types were collected from ten healthy adults(five males and five females).Total RNA was extracted,reverse-transcribed,and analyzed by qPCR.Gene stability was assessed using four algorithms(geNorm,NormFinder,BestKeeper,andΔCt)integrated with RefFinder,and the optimal gene number was determined using geNorm pairwise variation(V_(n/n+1)<0.15).Four transcriptome-derived genes(creld2,cd109,acy1,and miox)were used for validation.The C_(t)values of the five genes ranged from 15.47 to 20.83.β-actin and gapdh showed pronounced variability in expression stability among tissues and sexes,indicating their limited suitability for normalization.18S exhibited the highest expression(mean C_(t):15.47-16.29)and lowest variability but displayed sex-biased expression,whereas ef-1αand ef-1γremained consistently stable across most tissues in both sexes,with ef-1αbeing the most robust and showing no sex-related bias.Although specific rankings varied among tissues and sexes,the comprehensive results indicated that ef-1αand ef-1γpossessed the highest overall stability,followed by 18S,whileβ-actin and gapdh were the least stable.The final comprehensive rankings were ef-1γ>ef-1α>18S>gapdh>β-actin(male)and ef-1α>ef-1γ>18S>gapdh>β-actin(female).geNorm analysis(V2/3<0.15)indicated that two genes,mainly ef-1αand ef-1γ,were generally sufficient for reliable normalization in most tissues.Validation confirmed that normalization using the stable ef-1αand ef-1γaccurately reflected the expression differences among tissues,whereasβ-actin and gapdh can bias or confound statistical analyses.ef-1αand ef-1γare identified as the most reliable reference gene combination for qPCR analysis in S.japonica,while 18S can serve as an auxiliary gene for within-sex comparisons.The use ofβ-actin or gapdh alone is not recommended.This study establishes a systematic framework for selecting reliable reference genes in S.japonica,thereby facilitating robust qPCR normalization and providing a foundation for future gene expression research in S.japonica and other cephalopods.展开更多
WE observe that the response speed of a linear timeinvariant system to a step reference input depends not only on the system parameters but also on the magnitude of the step input.Based on this observation,we demonstr...WE observe that the response speed of a linear timeinvariant system to a step reference input depends not only on the system parameters but also on the magnitude of the step input.Based on this observation,we demonstrate a method to schedule the magnitude of the reference input to achieve a faster response.展开更多
Traffic flow prediction constitutes a fundamental component of Intelligent Transportation Systems(ITS),playing a pivotal role in mitigating congestion,enhancing route optimization,and improving the utilization efficie...Traffic flow prediction constitutes a fundamental component of Intelligent Transportation Systems(ITS),playing a pivotal role in mitigating congestion,enhancing route optimization,and improving the utilization efficiency of roadway infrastructure.However,existingmethods struggle in complex traffic scenarios due to static spatio-temporal embedding,restricted multi-scale temporal modeling,and weak representation of local spatial interactions.This study proposes Bi-STAT+,an enhanced bidirectional spatio-temporal attention framework to address existing limitations through three principal contributions:(1)an adaptive spatio-temporal embedding module that dynamically adjusts embeddings to capture complex traffic variations;(2)frequency-domain analysis in the temporal dimension for simultaneous high-frequency details and low-frequency trend extraction;and(3)an agent attention mechanism in the spatial dimension that enhances local feature extraction through dynamic weight allocation.Extensive experiments were performed on four distinct datasets,including two publicly benchmark datasets(PEMS04 and PEMS08)and two private datasets collected from Baotou and Chengdu,China.The results demonstrate that Bi-STAT+consistently outperforms existing methods in terms of MAE,RMSE,and MAPE,while maintaining strong robustness against missing data and noise.Furthermore,the results highlight that prediction accuracy improves significantly with higher sampling rates,providing crucial insights for optimizing real-world deployment scenarios.展开更多
The pseudo-two-dimensional(P2D)model plays an important role in exploring physicochemical mechanisms,predicting the state of health,and improving the fast charge capability for Li-ion batteries(LIBs).However,the fast ...The pseudo-two-dimensional(P2D)model plays an important role in exploring physicochemical mechanisms,predicting the state of health,and improving the fast charge capability for Li-ion batteries(LIBs).However,the fast charge leads to the lithium concentration gradient in the solid and electrolyte phases and the non-uniform electrochemical reaction at the solid/electrolyte interface.In order to decouple charge transfer reactions in LIBs under dynamic conditions,understanding the spatio-temporal resolution of the P2D model is urgently required.Till now,the study of this aspect is still insufficient.This work studies the spatio-temporal resolution for dynamic/static electrochemical impedance spectroscopy(DEIS/SEIS)on multiple scales.In detail,DEIS and SEIS with spatio-temporal resolutions are used to decouple charge transfer reactions in LIBs based on the numerical solution of the P2D model in the frequency domain.The calculated results indicate that decoupling solid diffusion requires a high spatial resolution along the r-direction in particles,decoupling electrolyte diffusion and interfacial transfer reaction requires a high spatial resolution along the x-direction,and decoupling charge transfer reactions in LIBs at an extremely low state of charge(SOC)requires an extremely high temporal resolution along the t-direction.Finally,the optimal range of spatio-temporal resolutions for DEIS/SEIS is derived,and the method to decouple charge transfer reactions with spatio-temporal resolutions is developed.展开更多
This study proposes a novel forecasting framework that simultaneously captures the strong periodicity and irregular meteorological fluctuations inherent in solar radiation time series.Existing approaches typically def...This study proposes a novel forecasting framework that simultaneously captures the strong periodicity and irregular meteorological fluctuations inherent in solar radiation time series.Existing approaches typically define inter-regional correlations using either simple correlation coefficients or distance-based measures when applying spatio-temporal graph neural networks(STGNNs).However,such definitions are prone to generating spurious correlations due to the dominance of periodic structures.To address this limitation,we adopt the Elastic-Band Transform(EBT)to decompose solar radiation into periodic and amplitude-modulated components,which are then modeled independently with separate graph neural networks.The periodic component,characterized by strong nationwide correlations,is learned with a relatively simple architecture,whereas the amplitude-modulated component is modeled with more complex STGNNs that capture climatological similarities between regions.The predictions from the two components are subsequently recombined to yield final forecasts that integrate both periodic patterns and aperiodic variability.The proposed framework is validated with multiple STGNN architectures,and experimental results demonstrate improved predictive accuracy and interpretability compared to conventional methods.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
Bamboo was one of the first plants to be cultivated in China and is widely used in industry and daily life.The study of gene function has become an important part of bamboo breeding,whereas quantitative real-time PCR(...Bamboo was one of the first plants to be cultivated in China and is widely used in industry and daily life.The study of gene function has become an important part of bamboo breeding,whereas quantitative real-time PCR(qRT-PCR)is a powerful tool for gene expression analysis.The accuracy of qRT-PCR results largely depends on suitable reference genes.In this study,a transcriptome-wide identification of reference genes was conducted based on 447 transcriptome datasets,comprising 200 tissue samples,107 treated samples,and 140 samples from various moso bamboo(Phyllostachys edulis)forms.A total of 3444,1013,and 3962 stably expressed genes were identified from these three groups,respectively.Functional enrichment analysis revealed significant enrichment of these genes in pathways,including the spliceosome,proteasome,and oxidative phosphorylation.Eight candidate genes(ADPRE,GAPDH,TRX,TUBA,NRP,MBF,UNK,and CAM1),were selected for qRT-PCR validation using 112 samples.To assess their stability,five statistical methods(geNorm,NormFinder,BestKeeper,Delta-Ct,and RefFinder)were employed.The most suitable reference genes were ADPRE and GAPDH for different tissues,GAPDH and CAM1 for different treatments,and GAPDH and TRX for various moso bamboo forms.Overall,ADPRE and GAPDH were the most stable reference genes across all conditions,while TUBA and TRX were the least stable reference genes.In addition,a significant negative correlation was found between the Ct values of RT-qPCR and the log2TPM values from the transcriptome data(Ct=-1.534x+37.221),providing a potential method for estimating gene expression levels.The identified reference genes,particularly ADPRE and GAPDH,provide a robust set of references for gene expression studies in moso bamboo.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
This paper introduces a high-precision bandgap reference(BGR)designed for battery management systems(BMS),fea-turing an ultra-low temperature coefficient(TC)and line sensitivity(LS).The BGR employs a current-mode sche...This paper introduces a high-precision bandgap reference(BGR)designed for battery management systems(BMS),fea-turing an ultra-low temperature coefficient(TC)and line sensitivity(LS).The BGR employs a current-mode scheme with chopped op-amps and internal clock generators to eliminate op-amp offset.A low dropout regulator(LDO)and a pre-regula-tor enhance output driving and LS,respectively.Curvature compensation enhances the TC by addressing higher-order nonlinear-ity.These approaches,effective near room temperature,employs trimming at both 20 and 60°C.When combined with fixed cur-vature correction currents,it achieves an ultra-low TC for each chip.Implemented in a CMOS 180 nm process,the BGR occu-pies 0.548 mm²and operates at 2.5 V with 84μA current draw from a 5 V supply.An average TC of 2.69 ppm/℃ with two-point trimming and 0.81 ppm/℃ with multi-point trimming are achieved over the temperature range of-40 to 125℃.It accommo-dates a load current of 1 mA and an LS of 42 ppm/V,making it suitable for precise BMS applications.展开更多
Introduction: Childbirth on a scarred uterus is a major issue for health centers, especially peripheral, due to the major obstetric risks it presents. The objectives were to evaluate the frequency, route of delivery a...Introduction: Childbirth on a scarred uterus is a major issue for health centers, especially peripheral, due to the major obstetric risks it presents. The objectives were to evaluate the frequency, route of delivery and maternal-fetal prognosis of this type of delivery at csref of Kolondiéba. Materials and Methods: This was a retrospective cross-sectional study for one year (1 January 2023-31 December 2023). All patients admitted to the maternity ward of the center with at least one uterine scar and treated in the center were included. We extracted data from partograms, OR records, birth records and obstetric records. Input was done on Excel 2010 and analysis on SPSS.23. Results: The frequency of scarring uterus was 16.8% (217/1285 births). The average age was 27. Pauciparous were most represented (59%). Patients were received from community health centers (44.7%). Prenatal consultation sessions (1 - 3 sessions) were performed at (64.9%). Uterine scars were obstetric in (99%). The cesarean section was performed immediately in (59.4%), it was prophylactic in 17%. The uterine test was attempted in (25.34%) with (69%) success. We recorded 3.6% uterine ruptures, 8.7% postoperative complications, 5.5% stillbirths and one maternal death (0.46%). Conclusion: Births on a scarred uterus are frequent and associated with a high rate of complications.展开更多
Computed tomography is an indispensable X-ray imaging modality used to diagnose numerous pathologies, but it can also involve the delivery of high ionizing radiation doses harmful to the health of patients. This study...Computed tomography is an indispensable X-ray imaging modality used to diagnose numerous pathologies, but it can also involve the delivery of high ionizing radiation doses harmful to the health of patients. This study aims to survey the level of radiation doses delivered to child patients during head exams in CT imaging to set up the Dosimetric Reference Levels (DRLs), a routine dose optimization tool, based on data acquired at the University Hospital of Angré (UHA), the University Hospital of Treichville (UHT) and the Polyclinic Hospital Farah (Farah) for optimizing procedures in Ivorian hospitals. Prospectively performed on 334 CT images of 186 child patients, this study was carried out on CT systems such as Hitachi Scenaria, Sinovision Insitum, and Philips Incisive used respectively at UHA, UHT and Farah. Children’s scan data were classified into four age bands: vol or dose-length product as DLP) value, whatever the hospital, increases with respect to the age of child patients. Based on the 75th percentile of the whole dose distributions, the DRLs of the CTDIvol is 54.37 mGy whatever the age groups and those of the DLP with respect to age bands are 1224.55 mGy∙cm, 1414.06 mGy∙cm, 1632.24 mGy.cm and 1544.57 mGy∙cm, respectively. The averaged values of CTDIvol and DLP smaller than the corresponding DRLs values suggest that practices in our three facilities are optimized. However, comparing our results with those from different international studies, we see that the CTDIvol and DLP values obtained in the present work are higher. These results suggest additional surveys to ensure our DRLs values and efforts from radiologists, imaging technicians and medical physicists to strengthen clinical procedures for the radiation protection of children undergoing CT scans in Côte d’Ivoire.展开更多
The purpose of this research was to evaluate radiological safety in pediatric radiology in hospitals in the Kongo Central province of the DRC. To this end, we surveyed a convenience sample of 50 health professionals, ...The purpose of this research was to evaluate radiological safety in pediatric radiology in hospitals in the Kongo Central province of the DRC. To this end, we surveyed a convenience sample of 50 health professionals, including 10 radiologists working in the hospitals covered by the survey, to assess the practice of pediatric radiology and the degree of compliance with radiation protection principles for the safety of children and the environment. We collected radiophysical parameters to calculate entrance doses in pediatric radiology in radiology departments to determine the dosimetric level by comparison with the diagnostic reference levels of the International Commission on Radiological Protection (ICRP). All in all, we found that in Kongo Central in the DRC, many health personnel surveyed reported that more than 30% of requested radiological examinations are not justified. Also, after comparing the entrance doses produced in the surveyed departments with those of the International Commission on Radiological Protection (ICRP), a statistically significant difference was found in pediatric radiology between the average doses in five out of six surveyed departments and those of the ICRP. Therefore, almost all of the surveyed departments were found to be highly irradiating in children, while excessive X-ray irradiation in children can have significant effects due to their increased sensitivity to radiation. Among the risks are: increased cancer risks, damage to developing cells, potential genetic effects, and neurological effects. This is why support for implementing radiation protection principles is a necessity to promote the safety of patients and the environment against the harmful effects of X-rays in conventional radiology.展开更多
BACKGROUND Pepsinogen(PG)and the PG I/II ratio(PGR)are critical indicators for diagnosing Helicobacter pylori infection and chronic atrophic gastritis,and assessing gastric cancer risk.Existing reference intervals(RIs...BACKGROUND Pepsinogen(PG)and the PG I/II ratio(PGR)are critical indicators for diagnosing Helicobacter pylori infection and chronic atrophic gastritis,and assessing gastric cancer risk.Existing reference intervals(RIs)often overlook age,sex,and demographic variations.Partitioned RIs,while considering these factors,fail to capture the gradual age-related physiological changes.Next-generation RIs offer a solution to this limitation.AIM To investigate age-and sex-specific dynamics of PG and establish next-generation RIs for adults and the elderly in northern China.METHODS After screening,708 healthy individuals were included in this observational study.Serum PG was measured using chemiluminescence immunoassay.Age-and sex-related effects on PG were analyzed with a two-way analysis of variance.RI partitioning was determined by the standard deviation ratio(SDR).Traditional RIs were established using a non-parametric approach.Generalized Additive Models for Location,Scale,and Shape(GAMLSS)modeled age-related trends and continuous reference percentiles for PG I and PG II.Reference limit flagging rates for both RI types were compared.RESULTS PG I and PG II levels were influenced by age(P<0.001)and sex(P<0.001),while PGR remained stable.Age-specific RIs were required for PG I(SDR=0.366)and PG II(SDR=0.424).Partitioned RIs were established for PG I and PG II,with a single RI for PGR.GAMLSS modeling revealed distinct age-dependent trajectories:PG I increased from a median of 39.75μg/L at age 20 years to 49.75μg/L at age 60 years,a 25.16%increase,after which it plateaued through age 80 years.In contrast,PG II showed a continuous rise throughout the age range,with the median value increasing from 5.07μg/L at age 20 years to 8.36μg/L at age 80 years,corresponding to a 64.89%increase.Continuous reference percentiles intuitively reflected these trends and were detailed in this study.Next-generation RIs demonstrated superior accuracy compared to partitioned RIs when applied to specific age subgroups.CONCLUSION This study elucidates the age-and sex-specific dynamics of PG and,to our knowledge,is the first to establish next-generation RIs for PG,supporting more individualized interpretation in laboratory medicine.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
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
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
Sandfly fever is a viral infectious disease transmitted by sand flies that is widely prevalent in tropical and subtropical regions.Previous studies on its infection mechanism,immune response and diagnosis and treatmen...Sandfly fever is a viral infectious disease transmitted by sand flies that is widely prevalent in tropical and subtropical regions.Previous studies on its infection mechanism,immune response and diagnosis and treatment methods were lack of systematic.This study applied spatio-temporal omics technology to comprehensively explain the dynamic changes of immunity in the incubation period,exacerbation period,peak period and recovery period of Sandfl y fever,and integrated with diff erent coping strategies.To provide new research ideas for its overall research.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
文摘Quantitative real-time PCR(qPCR)is widely used for gene expression analysis,but its accuracy critically depends on stable internal reference genes for normalization.In marine invertebrates,especially non-model taxa such as cephalopods,systematic evaluation of reference genes is limited,leading to potential bias.The cuttlefish Sepiella japonica is ecologically and economically important in China,yet previous molecular studies have often relied on single unvalidated reference genes,which may compromise data reliability.This study aimed to systematically evaluate the stability of five commonly used reference genes(18S,ef-1α,ef-1γ,gapdh,andβ-actin)across multiple tissues and sexes of S.japonica,and to identify the most suitable reference genes and optimal number for qPCR normalization.Fifteen to sixteen tissue types were collected from ten healthy adults(five males and five females).Total RNA was extracted,reverse-transcribed,and analyzed by qPCR.Gene stability was assessed using four algorithms(geNorm,NormFinder,BestKeeper,andΔCt)integrated with RefFinder,and the optimal gene number was determined using geNorm pairwise variation(V_(n/n+1)<0.15).Four transcriptome-derived genes(creld2,cd109,acy1,and miox)were used for validation.The C_(t)values of the five genes ranged from 15.47 to 20.83.β-actin and gapdh showed pronounced variability in expression stability among tissues and sexes,indicating their limited suitability for normalization.18S exhibited the highest expression(mean C_(t):15.47-16.29)and lowest variability but displayed sex-biased expression,whereas ef-1αand ef-1γremained consistently stable across most tissues in both sexes,with ef-1αbeing the most robust and showing no sex-related bias.Although specific rankings varied among tissues and sexes,the comprehensive results indicated that ef-1αand ef-1γpossessed the highest overall stability,followed by 18S,whileβ-actin and gapdh were the least stable.The final comprehensive rankings were ef-1γ>ef-1α>18S>gapdh>β-actin(male)and ef-1α>ef-1γ>18S>gapdh>β-actin(female).geNorm analysis(V2/3<0.15)indicated that two genes,mainly ef-1αand ef-1γ,were generally sufficient for reliable normalization in most tissues.Validation confirmed that normalization using the stable ef-1αand ef-1γaccurately reflected the expression differences among tissues,whereasβ-actin and gapdh can bias or confound statistical analyses.ef-1αand ef-1γare identified as the most reliable reference gene combination for qPCR analysis in S.japonica,while 18S can serve as an auxiliary gene for within-sex comparisons.The use ofβ-actin or gapdh alone is not recommended.This study establishes a systematic framework for selecting reliable reference genes in S.japonica,thereby facilitating robust qPCR normalization and providing a foundation for future gene expression research in S.japonica and other cephalopods.
文摘WE observe that the response speed of a linear timeinvariant system to a step reference input depends not only on the system parameters but also on the magnitude of the step input.Based on this observation,we demonstrate a method to schedule the magnitude of the reference input to achieve a faster response.
基金partly supported by the Youth Foundation of the Inner Mongolia Natural Science Foundation[grant number 2024QN06017 and 2025MS06022]the Basic Scientific Research Business Fee Project for Universities in Inner Mongolia[grant numbers 2023XKJX019 and 2023XKJX024]the Central Guidance on Local Science and Technology Development Fund through[grant number 2024ZY0084].
文摘Traffic flow prediction constitutes a fundamental component of Intelligent Transportation Systems(ITS),playing a pivotal role in mitigating congestion,enhancing route optimization,and improving the utilization efficiency of roadway infrastructure.However,existingmethods struggle in complex traffic scenarios due to static spatio-temporal embedding,restricted multi-scale temporal modeling,and weak representation of local spatial interactions.This study proposes Bi-STAT+,an enhanced bidirectional spatio-temporal attention framework to address existing limitations through three principal contributions:(1)an adaptive spatio-temporal embedding module that dynamically adjusts embeddings to capture complex traffic variations;(2)frequency-domain analysis in the temporal dimension for simultaneous high-frequency details and low-frequency trend extraction;and(3)an agent attention mechanism in the spatial dimension that enhances local feature extraction through dynamic weight allocation.Extensive experiments were performed on four distinct datasets,including two publicly benchmark datasets(PEMS04 and PEMS08)and two private datasets collected from Baotou and Chengdu,China.The results demonstrate that Bi-STAT+consistently outperforms existing methods in terms of MAE,RMSE,and MAPE,while maintaining strong robustness against missing data and noise.Furthermore,the results highlight that prediction accuracy improves significantly with higher sampling rates,providing crucial insights for optimizing real-world deployment scenarios.
基金supported by the National Natural Science Foundation of China(Nos.22479092 and 22078190)。
文摘The pseudo-two-dimensional(P2D)model plays an important role in exploring physicochemical mechanisms,predicting the state of health,and improving the fast charge capability for Li-ion batteries(LIBs).However,the fast charge leads to the lithium concentration gradient in the solid and electrolyte phases and the non-uniform electrochemical reaction at the solid/electrolyte interface.In order to decouple charge transfer reactions in LIBs under dynamic conditions,understanding the spatio-temporal resolution of the P2D model is urgently required.Till now,the study of this aspect is still insufficient.This work studies the spatio-temporal resolution for dynamic/static electrochemical impedance spectroscopy(DEIS/SEIS)on multiple scales.In detail,DEIS and SEIS with spatio-temporal resolutions are used to decouple charge transfer reactions in LIBs based on the numerical solution of the P2D model in the frequency domain.The calculated results indicate that decoupling solid diffusion requires a high spatial resolution along the r-direction in particles,decoupling electrolyte diffusion and interfacial transfer reaction requires a high spatial resolution along the x-direction,and decoupling charge transfer reactions in LIBs at an extremely low state of charge(SOC)requires an extremely high temporal resolution along the t-direction.Finally,the optimal range of spatio-temporal resolutions for DEIS/SEIS is derived,and the method to decouple charge transfer reactions with spatio-temporal resolutions is developed.
基金supported by Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(RS-2023-00249743).
文摘This study proposes a novel forecasting framework that simultaneously captures the strong periodicity and irregular meteorological fluctuations inherent in solar radiation time series.Existing approaches typically define inter-regional correlations using either simple correlation coefficients or distance-based measures when applying spatio-temporal graph neural networks(STGNNs).However,such definitions are prone to generating spurious correlations due to the dominance of periodic structures.To address this limitation,we adopt the Elastic-Band Transform(EBT)to decompose solar radiation into periodic and amplitude-modulated components,which are then modeled independently with separate graph neural networks.The periodic component,characterized by strong nationwide correlations,is learned with a relatively simple architecture,whereas the amplitude-modulated component is modeled with more complex STGNNs that capture climatological similarities between regions.The predictions from the two components are subsequently recombined to yield final forecasts that integrate both periodic patterns and aperiodic variability.The proposed framework is validated with multiple STGNN architectures,and experimental results demonstrate improved predictive accuracy and interpretability compared to conventional methods.
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.
基金supported by the National Key Research and Development Program of China(Grant No.2021YFD2200502)the National Natural Science Foundation of China(Grant No.31971736).
文摘Bamboo was one of the first plants to be cultivated in China and is widely used in industry and daily life.The study of gene function has become an important part of bamboo breeding,whereas quantitative real-time PCR(qRT-PCR)is a powerful tool for gene expression analysis.The accuracy of qRT-PCR results largely depends on suitable reference genes.In this study,a transcriptome-wide identification of reference genes was conducted based on 447 transcriptome datasets,comprising 200 tissue samples,107 treated samples,and 140 samples from various moso bamboo(Phyllostachys edulis)forms.A total of 3444,1013,and 3962 stably expressed genes were identified from these three groups,respectively.Functional enrichment analysis revealed significant enrichment of these genes in pathways,including the spliceosome,proteasome,and oxidative phosphorylation.Eight candidate genes(ADPRE,GAPDH,TRX,TUBA,NRP,MBF,UNK,and CAM1),were selected for qRT-PCR validation using 112 samples.To assess their stability,five statistical methods(geNorm,NormFinder,BestKeeper,Delta-Ct,and RefFinder)were employed.The most suitable reference genes were ADPRE and GAPDH for different tissues,GAPDH and CAM1 for different treatments,and GAPDH and TRX for various moso bamboo forms.Overall,ADPRE and GAPDH were the most stable reference genes across all conditions,while TUBA and TRX were the least stable reference genes.In addition,a significant negative correlation was found between the Ct values of RT-qPCR and the log2TPM values from the transcriptome data(Ct=-1.534x+37.221),providing a potential method for estimating gene expression levels.The identified reference genes,particularly ADPRE and GAPDH,provide a robust set of references for gene expression studies in moso bamboo.
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 National Natural Science Foundation of China(NSFC)under grant No.62204235。
文摘This paper introduces a high-precision bandgap reference(BGR)designed for battery management systems(BMS),fea-turing an ultra-low temperature coefficient(TC)and line sensitivity(LS).The BGR employs a current-mode scheme with chopped op-amps and internal clock generators to eliminate op-amp offset.A low dropout regulator(LDO)and a pre-regula-tor enhance output driving and LS,respectively.Curvature compensation enhances the TC by addressing higher-order nonlinear-ity.These approaches,effective near room temperature,employs trimming at both 20 and 60°C.When combined with fixed cur-vature correction currents,it achieves an ultra-low TC for each chip.Implemented in a CMOS 180 nm process,the BGR occu-pies 0.548 mm²and operates at 2.5 V with 84μA current draw from a 5 V supply.An average TC of 2.69 ppm/℃ with two-point trimming and 0.81 ppm/℃ with multi-point trimming are achieved over the temperature range of-40 to 125℃.It accommo-dates a load current of 1 mA and an LS of 42 ppm/V,making it suitable for precise BMS applications.
文摘Introduction: Childbirth on a scarred uterus is a major issue for health centers, especially peripheral, due to the major obstetric risks it presents. The objectives were to evaluate the frequency, route of delivery and maternal-fetal prognosis of this type of delivery at csref of Kolondiéba. Materials and Methods: This was a retrospective cross-sectional study for one year (1 January 2023-31 December 2023). All patients admitted to the maternity ward of the center with at least one uterine scar and treated in the center were included. We extracted data from partograms, OR records, birth records and obstetric records. Input was done on Excel 2010 and analysis on SPSS.23. Results: The frequency of scarring uterus was 16.8% (217/1285 births). The average age was 27. Pauciparous were most represented (59%). Patients were received from community health centers (44.7%). Prenatal consultation sessions (1 - 3 sessions) were performed at (64.9%). Uterine scars were obstetric in (99%). The cesarean section was performed immediately in (59.4%), it was prophylactic in 17%. The uterine test was attempted in (25.34%) with (69%) success. We recorded 3.6% uterine ruptures, 8.7% postoperative complications, 5.5% stillbirths and one maternal death (0.46%). Conclusion: Births on a scarred uterus are frequent and associated with a high rate of complications.
文摘Computed tomography is an indispensable X-ray imaging modality used to diagnose numerous pathologies, but it can also involve the delivery of high ionizing radiation doses harmful to the health of patients. This study aims to survey the level of radiation doses delivered to child patients during head exams in CT imaging to set up the Dosimetric Reference Levels (DRLs), a routine dose optimization tool, based on data acquired at the University Hospital of Angré (UHA), the University Hospital of Treichville (UHT) and the Polyclinic Hospital Farah (Farah) for optimizing procedures in Ivorian hospitals. Prospectively performed on 334 CT images of 186 child patients, this study was carried out on CT systems such as Hitachi Scenaria, Sinovision Insitum, and Philips Incisive used respectively at UHA, UHT and Farah. Children’s scan data were classified into four age bands: vol or dose-length product as DLP) value, whatever the hospital, increases with respect to the age of child patients. Based on the 75th percentile of the whole dose distributions, the DRLs of the CTDIvol is 54.37 mGy whatever the age groups and those of the DLP with respect to age bands are 1224.55 mGy∙cm, 1414.06 mGy∙cm, 1632.24 mGy.cm and 1544.57 mGy∙cm, respectively. The averaged values of CTDIvol and DLP smaller than the corresponding DRLs values suggest that practices in our three facilities are optimized. However, comparing our results with those from different international studies, we see that the CTDIvol and DLP values obtained in the present work are higher. These results suggest additional surveys to ensure our DRLs values and efforts from radiologists, imaging technicians and medical physicists to strengthen clinical procedures for the radiation protection of children undergoing CT scans in Côte d’Ivoire.
文摘The purpose of this research was to evaluate radiological safety in pediatric radiology in hospitals in the Kongo Central province of the DRC. To this end, we surveyed a convenience sample of 50 health professionals, including 10 radiologists working in the hospitals covered by the survey, to assess the practice of pediatric radiology and the degree of compliance with radiation protection principles for the safety of children and the environment. We collected radiophysical parameters to calculate entrance doses in pediatric radiology in radiology departments to determine the dosimetric level by comparison with the diagnostic reference levels of the International Commission on Radiological Protection (ICRP). All in all, we found that in Kongo Central in the DRC, many health personnel surveyed reported that more than 30% of requested radiological examinations are not justified. Also, after comparing the entrance doses produced in the surveyed departments with those of the International Commission on Radiological Protection (ICRP), a statistically significant difference was found in pediatric radiology between the average doses in five out of six surveyed departments and those of the ICRP. Therefore, almost all of the surveyed departments were found to be highly irradiating in children, while excessive X-ray irradiation in children can have significant effects due to their increased sensitivity to radiation. Among the risks are: increased cancer risks, damage to developing cells, potential genetic effects, and neurological effects. This is why support for implementing radiation protection principles is a necessity to promote the safety of patients and the environment against the harmful effects of X-rays in conventional radiology.
文摘BACKGROUND Pepsinogen(PG)and the PG I/II ratio(PGR)are critical indicators for diagnosing Helicobacter pylori infection and chronic atrophic gastritis,and assessing gastric cancer risk.Existing reference intervals(RIs)often overlook age,sex,and demographic variations.Partitioned RIs,while considering these factors,fail to capture the gradual age-related physiological changes.Next-generation RIs offer a solution to this limitation.AIM To investigate age-and sex-specific dynamics of PG and establish next-generation RIs for adults and the elderly in northern China.METHODS After screening,708 healthy individuals were included in this observational study.Serum PG was measured using chemiluminescence immunoassay.Age-and sex-related effects on PG were analyzed with a two-way analysis of variance.RI partitioning was determined by the standard deviation ratio(SDR).Traditional RIs were established using a non-parametric approach.Generalized Additive Models for Location,Scale,and Shape(GAMLSS)modeled age-related trends and continuous reference percentiles for PG I and PG II.Reference limit flagging rates for both RI types were compared.RESULTS PG I and PG II levels were influenced by age(P<0.001)and sex(P<0.001),while PGR remained stable.Age-specific RIs were required for PG I(SDR=0.366)and PG II(SDR=0.424).Partitioned RIs were established for PG I and PG II,with a single RI for PGR.GAMLSS modeling revealed distinct age-dependent trajectories:PG I increased from a median of 39.75μg/L at age 20 years to 49.75μg/L at age 60 years,a 25.16%increase,after which it plateaued through age 80 years.In contrast,PG II showed a continuous rise throughout the age range,with the median value increasing from 5.07μg/L at age 20 years to 8.36μg/L at age 80 years,corresponding to a 64.89%increase.Continuous reference percentiles intuitively reflected these trends and were detailed in this study.Next-generation RIs demonstrated superior accuracy compared to partitioned RIs when applied to specific age subgroups.CONCLUSION This study elucidates the age-and sex-specific dynamics of PG and,to our knowledge,is the first to establish next-generation RIs for PG,supporting more individualized interpretation in laboratory medicine.
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 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College Students Innovation and Entrepreneurship Training Program(X202511049398)College Students Innovation and Entrepreneurship Training Program(X202511049201)+1 种基金College Students Innovation and Entrepreneurship Training Program(X202511258005S)University-Level Research Funding Program of Hainan Science and Technology Vocational University(HKKY2024-87)。
文摘Sandfly fever is a viral infectious disease transmitted by sand flies that is widely prevalent in tropical and subtropical regions.Previous studies on its infection mechanism,immune response and diagnosis and treatment methods were lack of systematic.This study applied spatio-temporal omics technology to comprehensively explain the dynamic changes of immunity in the incubation period,exacerbation period,peak period and recovery period of Sandfl y fever,and integrated with diff erent coping strategies.To provide new research ideas for its overall research.
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.
