Understanding the impacts of human activities on the plateau’s living environment is essential for advancing modernization pathways that promote harmony between humanity and nature.However,studies on the dynamic inte...Understanding the impacts of human activities on the plateau’s living environment is essential for advancing modernization pathways that promote harmony between humanity and nature.However,studies on the dynamic interactions between human activities and the living environment on the Qinghai-Xizang Plateau(QXP)remain limited,with a paucity of quantitative relationship analyses.This study established an assessment framework to evaluate human influences on the living environment in QXP,using data on typical human activities,ecological conditions,and human settlements.Within this framework,the spatial analysis methods and the coupling coordination model were used to examine the spatio-temporal characteristics and relationship of human activities and living environment on the QXP from 2000 to 2020.The geographical detector model was then applied to identify the key factors influencing the plateau’s human living environment.Subsequently,the four-quadrant analysis model was adopted to assess human influences on the living environment.The results indicate that the human activity intensity(HAI)on the QXP remained relatively low yet increased by 15.41%from 2000 to 2020.Spatially,the human living environment quality(LEQ)improved from northwest to southeast,with 61.14%of the areas remaining stable and 18.47%experiencing slight improvement.The analysis of coupling coordination revealed a continuous improvement between the HAI and LEQ,with the areas of high and relatively high coordinated types increasing by more than 9%.Precipitation and urban-rural construction were identified as the primary factors influencing changes in the LEQ.The interaction between the HAI and LEQ was strengthening,with 40.44%classified as coordinated development type and 38.35%as development-environment conflict type.These findings provide valuable insights for enhancing the resilience of human settlements and promoting green development across the plateau.展开更多
Prevention of biological invasion requires understanding how alien species invade native communities.Although studies have identified mechanisms that underlie plant invasion in some habitats,limited attention has focu...Prevention of biological invasion requires understanding how alien species invade native communities.Although studies have identified mechanisms that underlie plant invasion in some habitats,limited attention has focused on invasion patterns along elevational gradients.In this study,we asked which factors drive the global and regional distribution of the invasive plant Galinsoga quadriradiata along elevational gradients.To answer this question,we examined whether human activities(i.e.,roads)promote G.quadriradiata invasion,how seed dispersal-related traits of G.quadriradiata change along elevation gradients,and whether G.quadriradiata has adapted to high-elevation environments through phenotypic plasticity or genetic variation.On the global scale,we found that human activities and road density positively contribute to the G.quadriradiata expansion in mountainous areas.Field surveys in China revealed significant elevational differences in the seed dispersal traits of G.quadriradiata,with higher-elevation populations exhibiting lower dispersal ability and generally lower genetic diversity.Under common conditions,high-elevation populations showed higher leaf mass ratio but lower root mass ratio and reproductive allocation.This suggests that high-elevation environments create a barrier to dispersal for G.quadriradiata,and that G.quadriradiata has adapted phenotypically to these conditions.Our study indicates that the elevational invasion pattern of G.quadriradiata is shaped by multiple factors,particularly human activities and phenotypic adaptability.In addition,our finding that G.quadriradiata invasion at high elevations is not constrained by low genetic diversity indicates that monitoring and management of G.quadriradiata in mountainous areas should be strengthened.展开更多
Human activities have significantly impacted the land surface temperature(LST),endangering human health;however,the relationship between these two factors has not been adequately quantified.This study comprehensively ...Human activities have significantly impacted the land surface temperature(LST),endangering human health;however,the relationship between these two factors has not been adequately quantified.This study comprehensively constructs a Human Activity Intensity(HAI)index and employs the Maximal Information Coefficient,four-quadrant model,and XGBoostSHAP model to investigate the spatiotemporal relationship and influencing factors of HAI-LST in the Yellow River Basin(YRB)from 2000 to 2020.The results indicated that from 2000 to 2020,as HAI and LST increased,the static HAI-LST relationship in the YRB showed a positive correlation that continued to strengthen.This dynamic relationship exhibited conflicting development,with the proportion of coordinated to conflicting regions shifting from 1:4 to 1:2,indicating a reduction in conflict intensity.Notably,only the degree of conflict in the source area decreased significantly,whereas it intensified in the upper and lower reaches.The key factors influencing the HAI-LST relationship include fractional vegetation cover,slope,precipitation,and evapotranspiration,along with region-specific factors such as PM_(2.5),biodiversity,and elevation.Based on these findings,region-specific ecological management strategies have been proposed to mitigate conflict-prone areas and alleviate thermal stress,thereby providing important guidance for promoting harmonious development between humans and nature.展开更多
To address the deficiencies in comprehensive surface contamination prevention strategies within China's nitrate-affected regions,this research innovatively proposes the DITAPH model-a systematic framework integrat...To address the deficiencies in comprehensive surface contamination prevention strategies within China's nitrate-affected regions,this research innovatively proposes the DITAPH model-a systematic framework integrating groundwater nitrate vulnerability assessment and Nitrate Vulnerable Zones(NVZs)delineation through optimization of hydrogeological parameters.Based on detailed hydrogeological and hydrochemical investigations,the DITAPH model was applied in the plain areas of Quanzhou to evaluate its applicability.The model selected hydrogeological parameters(depth of groundwater,lithology of the vadose zone,topographic slope,aquifer water yield property),one climatic parameter(precipitation),and two anthropogenic parameters(land use type and population density)as assessment indicators.The results of the groundwater nitrate vulnerability assessment showed that the low,relatively low,relatively high,and high groundwater nitrate vulnerability zones in the study area accounted for 5.96%,35.44%,53.74%and 4.86%of the total area,respectively.Groundwater nitrate vulnerability was most strongly influenced by human activities,followed by groundwater depth and topographic slope.The high vulnerability zone is mainly affected by domestic and industrial wastewater,whereas the relatively high groundwater nitrate vulnerability zone is primarily influenced by agricultural activities.Validation of the DITAPH model revealed a significant positive correlation between the DITAPH index(DI)and nitrate concentration(ρ(NO3−)).The results of the NVZs delineated by the DITAPH model are reliable and can serve as a tool for water resource management planning,guiding the development of targeted measures in the NVZs to prevent groundwater contamination.展开更多
Carbon fluxes are essential indicators assessing vegetation carbon cycle functions.However,the extent and mechanisms by which climate change and human activities influence the spatiotemporal dynamics of carbon fluxes ...Carbon fluxes are essential indicators assessing vegetation carbon cycle functions.However,the extent and mechanisms by which climate change and human activities influence the spatiotemporal dynamics of carbon fluxes in arid oasis and non-oasis area remains unclear.Here,we assessed and predicted the future effects of climate change and human activities on carbon fluxes in the Hexi Corridor.The results showed that the annual average gross primary productivity(GPP),net ecosystem productivity(NEP),and ecosystem respiration(Reco)in the Hexi Corridor oasis increased by 263.91 g C·m^(-2)·yr^(-1),118.45 g C·m^(-2)·yr^(-1)and 122.46 g C·m^(-2)·yr^(-1),respectively,due to the expansion of the oasis area by 3424.84 km^(2) caused by human activities from 2000 to 2022.Both oasis and non-oasis arid ecosystems in the Hexi Corridor acted as carbon sinks.Compared to the non-oasis area,the carbon fluxes contributions of oasis area increased,ranging from 10.21%to 13.99%for GPP,8.50%to11.68%for NEP,and 13.34%to 17.13%for Reco.The contribution of the carbon flux from the oasis expansion area to the total carbon flux change in the Hexi Corridor was 30.96%(7.09 Tg C yr^(-1))for GPP,29.57%(3.39 Tg C yr^(-1))for NEP and 32.40%(3.58 Tg C yr^(-1))for Reco.The changes in carbon fluxes in the oasis area were mainly attributed to human activities(oasis expansion)and temperature,whereas non-oasis area was mainly due to climate factors.Moreover,the future increasing trends were observed for GPP(64.99%),NEP(66.29%)and Reco(82.08%)in the Hexi Corridor.This study provides new insights into the regulatory mechanisms of carbon cycle in the arid oasis and non-oasis area.展开更多
Based on regional paleoclimate sequences,records of human activities,paleoclimate simulations,and detailed environmental historical records,we discuss the impacts of Holocene climate change and human activities on the...Based on regional paleoclimate sequences,records of human activities,paleoclimate simulations,and detailed environmental historical records,we discuss the impacts of Holocene climate change and human activities on the evolution of the Shule River in the western Qilian Mountains,China.The results indicate that during the early to mid-Holocene,the river evolution of the Shule River alluvial fan was closely related to regional climate fluctuations.In the late Holocene,flood agriculture began to emerge along the Shule River.During the historical period,population growth and the expansion of arable land led to increased river water usage,resulting in decreased access to the expected distribution of water resources in other regions,which in turn has caused imbalances in the regional hydrological ecosystem.展开更多
Central Asia(CA)faces escalating threats from increasing temperature,glacier retreat,biodiversity loss,unsustainable water use,terminal lake shrinkage,and soil salinization,all of which challenge the balance between e...Central Asia(CA)faces escalating threats from increasing temperature,glacier retreat,biodiversity loss,unsustainable water use,terminal lake shrinkage,and soil salinization,all of which challenge the balance between ecological integrity and socio-economic development essential for achieving Sustainable Development Goals.However,a comprehensive understanding of priority areas from a multi-dimensional perspective is lacking,hindering effective conservation and development strategies.To address this,we developed a comprehensive assessment framework with a tailored indicator system,enabling a spatial evaluation of CA’s priority areas by integrating biodiversity,ecosystem services(ESs),and human activities.Combining zonation and geographical detectors,this approach facilitates spatial prioritization and examines ecological and socio-economic heterogeneity.Our findings reveal a heterogeneous distribution of priority areas across CA,with significant concentrations in eastern mountainous regions,river valleys,and oasis agricultural lands.We identified 184 key districts crucial for ecological and societal sustainability.Attribution analysis shows that natural factors like soil types,precipitation,and evapotranspiration significantly shape these areas,influencing human activities and the distribution of biodiversity and ESs.Multi-dimensional analysis indicates existing protected areas cover only 15%of the top 30%priority areas,revealing substantial conservation gaps.Additionally,a 38%overlap between ESs and human activities,along with 63.25%congruence in integrated areas,underscores significant human impacts on ecological systems and their dependency on ESs.Given CA’s limited resources,it is crucial to implement measures that strengthen conservation efforts,align ecological preservation with socio-economic demands,and enhance resource efficiency through sustainable integrated land and water resource management.展开更多
The Songhua River Basin(SRB),ranking third largest in China in terms of both runoff volume and basin area,has experi-enced frequent disasters and drastic changes in runoff since the early 20th century.Many studies hav...The Songhua River Basin(SRB),ranking third largest in China in terms of both runoff volume and basin area,has experi-enced frequent disasters and drastic changes in runoff since the early 20th century.Many studies have analyzed the causes of runoff re-duction;however,the spatiotemporal differences in runoff contributions and their underlying mechanisms remain poorly understood,which are crucial for regional water resources management and effective utilization.This study used the Mann-Kendall rank correlation trend test,continuous wavelet analysis,cumulative anomaly,and the slope change ratio of cumulative quantities(SCRCQ)method to explore the runoff changes characteristics and spatiotemporal differences of the contributions of climate change and human activities to runoff changes across three sub-basins of the SRB.The results show that:1)runoff from 1955 to 2022 in all the three sub-basins exhibit a statistically significant decreasing trend at 0.05 significant level.2)Four abrupt change points in runoff were detected in Nenjiang River Basin(NRB)and the mainstream of the SRB(MSRB),whereas only two change points in the Second Songhua River(SSRB).3)Runoff and precipitation series of the NRB and MSRB exhibit similar multi-timescale cycle characteristics with the most dominated cycles of 45-58 yr.In contrast,it is 12-18 yr for SSRB.4)Anthropogenic activities are the primary factor leading to in the reduction of runoff in NRB(74.33%-91.67%)and MSRB(50.11%-102.12%),whereas it is only 5.38%-33.12%in SSRB.This is attributed to the uneven distribution of regional climate and human activities in the entire SRB.5)With the growing demand for water diversion for agri-cultural irrigation,anthropogenic activities in the NRB and MSRB have increased.However,the opposite is found in SSR,where the in-creased influence of precipitation on runoff and water conservation policies are identified.展开更多
Human Activity Recognition(HAR)is a novel area for computer vision.It has a great impact on healthcare,smart environments,and surveillance while is able to automatically detect human behavior.It plays a vital role in ...Human Activity Recognition(HAR)is a novel area for computer vision.It has a great impact on healthcare,smart environments,and surveillance while is able to automatically detect human behavior.It plays a vital role in many applications,such as smart home,healthcare,human computer interaction,sports analysis,and especially,intelligent surveillance.In this paper,we propose a robust and efficient HAR system by leveraging deep learning paradigms,including pre-trained models,CNN architectures,and their average-weighted fusion.However,due to the diversity of human actions and various environmental influences,as well as a lack of data and resources,achieving high recognition accuracy remain elusive.In this work,a weighted average ensemble technique is employed to fuse three deep learning models:EfficientNet,ResNet50,and a custom CNN.The results of this study indicate that using a weighted average ensemble strategy for developing more effective HAR models may be a promising idea for detection and classification of human activities.Experiments by using the benchmark dataset proved that the proposed weighted ensemble approach outperformed existing approaches in terms of accuracy and other key performance measures.The combined average-weighted ensemble of pre-trained and CNN models obtained an accuracy of 98%,compared to 97%,96%,and 95%for the customized CNN,EfficientNet,and ResNet50 models,respectively.展开更多
Understanding the complex interactions between human activities and ecosystem functions is a prerequisite for achieving sustainable development.Since the implementation of the“Grain for Green”Project in 1999,ecosyst...Understanding the complex interactions between human activities and ecosystem functions is a prerequisite for achieving sustainable development.Since the implementation of the“Grain for Green”Project in 1999,ecosystem functions in China’s Loess Plateau have significantly improved.However,intensified human activities have also exacerbated the pressures on the region’s fragile ecological environment.This study investigates the spatiotemporal variations in the human activity intensity index(HAI)and net ecosystem benefits(NEB)from 2000 to 2020,using expert-based assessments and an enhanced cost-benefit evaluation framework.Results indicate that HAI increased by 16.7% and 16.6% at the grid and county levels,respectively.NEB exhibited pronounced spatial heterogeneity,with a total increase of USD 36.2 trillion at the grid scale.At the county level,the average NEB rose by 75%.The degree of trade-off was higher at the grid scale than at the county scale,while the synergistic areas initially expanded and then declined at both scales.Key areas for improvement and regions of lagging development were identified as priority zones for ecological management and spatial planning at both spatial resolutions.This study offers scientific insights and practical guidance for harmonizing ecological conservation with high-quality development in ecologically vulnerable regions.展开更多
Human activity recognition(HAR)is a method to predict human activities from sensor signals using machine learning(ML)techniques.HAR systems have several applications in various domains,including medicine,surveillance,...Human activity recognition(HAR)is a method to predict human activities from sensor signals using machine learning(ML)techniques.HAR systems have several applications in various domains,including medicine,surveillance,behavioral monitoring,and posture analysis.Extraction of suitable information from sensor data is an important part of the HAR process to recognize activities accurately.Several research studies on HAR have utilizedMel frequency cepstral coefficients(MFCCs)because of their effectiveness in capturing the periodic pattern of sensor signals.However,existing MFCC-based approaches often fail to capture sufficient temporal variability,which limits their ability to distinguish between complex or imbalanced activity classes robustly.To address this gap,this study proposes a feature fusion strategy that merges time-based and MFCC features(MFCCT)to enhance activity representation.The merged features were fed to a convolutional neural network(CNN)integrated with long shortterm memory(LSTM)—DeepConvLSTM to construct the HAR model.The MFCCT features with DeepConvLSTM achieved better performance as compared to MFCCs and time-based features on PAMAP2,UCI-HAR,and WISDM by obtaining an accuracy of 97%,98%,and 97%,respectively.In addition,DeepConvLSTM outperformed the deep learning(DL)algorithms that have recently been employed in HAR.These results confirm that the proposed hybrid features are not only practical but also generalizable,making them applicable across diverse HAR datasets for accurate activity classification.展开更多
With the growing advancement of wireless communication technologies,WiFi-based human sensing has gained increasing attention as a non-intrusive and device-free solution.Among the available signal types,Channel State I...With the growing advancement of wireless communication technologies,WiFi-based human sensing has gained increasing attention as a non-intrusive and device-free solution.Among the available signal types,Channel State Information(CSI)offers fine-grained temporal,frequency,and spatial insights into multipath propagation,making it a crucial data source for human-centric sensing.Recently,the integration of deep learning has significantly improved the robustness and automation of feature extraction from CSI in complex environments.This paper provides a comprehensive review of deep learning-enhanced human sensing based on CSI.We first outline mainstream CSI acquisition tools and their hardware specifications,then provide a detailed discussion of preprocessing methods such as denoising,time–frequency transformation,data segmentation,and augmentation.Subsequently,we categorize deep learning approaches according to sensing tasks—namely detection,localization,and recognition—and highlight representative models across application scenarios.Finally,we examine key challenges including domain generalization,multi-user interference,and limited data availability,and we propose future research directions involving lightweight model deployment,multimodal data fusion,and semantic-level sensing.展开更多
The concept of Human Activity Recognition(HAR)is integral to applications based on Internet of Things(IoT)-enabled devices,particularly in healthcare,fitness tracking,and smart environments.The streams of data from we...The concept of Human Activity Recognition(HAR)is integral to applications based on Internet of Things(IoT)-enabled devices,particularly in healthcare,fitness tracking,and smart environments.The streams of data from wearable sensors are rich in information,yet their high dimensionality and variability pose a significant challenge to proper classification.To address this problem,this paper proposes hybrid architectures that integrate traditional machine learning models with a deep neural network(DNN)to deliver improved performance and enhanced capabilities for HAR tasks.Multi-sensor HAR data were used to systematically test several hybrid models,including:RF+DNN(Random Forest+Deep Neural Network),XGB+DNN(XGBoost+DNN),GB+DNN(Gradient Boosting+DNN),KNN+DNN(K-Nearest Neighbors+DNN),and DT+DNN(Decision Tree+DNN).The RF+DNN model was the most accurate,achieving a 97.03%score with excellent precision,recall,and F1-score.These findings demonstrate that hybrid machine learning and deep learning systems have a promising future in IoT-based HAR applications.The model provides a novel solution for developing smart and trustworthy monitoring systems that support real-time analytics,patient surveillance,and other IoT applications.展开更多
new heterocyclic dipeptide with a highly functionalized 1,2-oxazadecaline core,named trichodermamide H(1),and three known analogues,along with three known polyketides,were isolated from the fermentation extract of the...new heterocyclic dipeptide with a highly functionalized 1,2-oxazadecaline core,named trichodermamide H(1),and three known analogues,along with three known polyketides,were isolated from the fermentation extract of the mangrovederived fungus Penicillium janthinellum XLN32122.The structure of 1 was elucidated on the basis of extensive 1D and 2D NMR spectra data analysis,HR-ESI-MS,electronic circular dichroism(ECD)calculations.Trichodermamide B(3)exhibited better inhibitory effect on nitric oxide(NO)production in lipopolysaccharide(LPS)induced RAW 264.7 cells with an IC_(50)value of(13.13±0.005)μmol/L than that of the positive control dexamethasone[IC_(50)=(136.84±1.33)μmol/L].Compound 3 exhibited antibacterial activity against methicillin-resistant Staphylococcus aureus(MRSA)with an IC_(50)value of 12.5μg/mL,while the positive control vancomycin showed an IC_(50)value of 1.563μg/mL.展开更多
Activation of neutrophil membrane receptors initiates intracellular signal transduction cascades that orchestrate the cell's effector functions,including phagocytosis,production of reactive oxygen and halogen spec...Activation of neutrophil membrane receptors initiates intracellular signal transduction cascades that orchestrate the cell's effector functions,including phagocytosis,production of reactive oxygen and halogen species,degranulation,and NETosis(formation of neutrophil extracellular traps[NETs]).NETs,which contain antimicrobial compounds such as myeloperoxidase(MPO),represent a strategy to combat infection.However,excessive production of NETs promotes thrombosis,diabetes mellitus,and other diseases.Therefore,investigations into the mechanisms of NETosis and the identification of modulators of this process are critical for developing strategies to address NETosis-related disorders.Here,we identified a novel NETosis inducer,human serum albumin(HSA)modified by the MPO product hypochlorous acid(HSAHOCl),whose accumulation in vivo was correlated with inflammatory processes.Using human blood neutrophils,we investigated HSAHOCl-induced NETosis and detected NET formation by flow cytometry.The results showed that the mechanism of HSAHOClinduced NETosis involved MPO,NADPH oxidase,and phosphatidylinositol 3-kinases(PI3Ks),and that HSAHOCl activated a reactive oxygen species-dependent suicidal type of NETosis.Moreover,HSAHOCl-induced NETosis was inhibited by an anti-HSAHOCl monoclonal antibody.Thus,our findings may facilitate the development of strategies to modulate NETosis in inflammation associated with elevated MPO activity.展开更多
Background:Cardiorespiratory fitness(CRF)is a powerful predictor of mortality and chronic disease risk,yet global patterns and determinants of CRF remain poorly defined,particularly in females and underrepresented pop...Background:Cardiorespiratory fitness(CRF)is a powerful predictor of mortality and chronic disease risk,yet global patterns and determinants of CRF remain poorly defined,particularly in females and underrepresented populations.We conducted a systematic review and quantitative synthesis of directly measured peak oxygen uptake(VO_(2peak))internationally and examined its association with human development and gender ine quality.Methods:Studies were eligible if VO_(2peak)was assessed via direct gas analysis during maximal exercise testing,and if the countries had scores for the Human Development Index(HDI)and Gender Inequality Index(GII).Studies were identified through MEDLINE/PubMed,Embase,CINAHL,and Web of Science.Risks of bias were assessed by an adaptation of the Newcastle-Ottawa Scale.Multivariable linear regression models examined associations between VO_(2peak),age,sex,exercise modality,HDI,GII,and study year.Results:Data included 95 studies from 24 countries with HDI and GII scores,comprising 119,435 adults(42%females)with VO_(2peak)assessed via direct gas analysis during maximal exercise testing.The risk of bias was low.VO_(2peak)was positively associated with HDI(β=14.1)and negatively associated with GII(β=-3.6).Slightly stronger associations were observed in females than males(HDI:β=18.9 vs.β=13.9,GII:β=-4.6vs.β=-3.6).Young females in middle-HDI countries had higher VO_(2peak)than those in low-HDI countries(31.2mL/kg/min vs.28.5 mL/kg/min),with limited additional gams in high-HDI contexts.VO_(2peak)decreased with higher gender inequality,with the largest disparities observed in young females between high-and low-GII countries(26.3 mL/kg/min vs.32.8 mL/kg/min).Conclusion:Global variation in CRF is tied to national levels of human development and gender equality.These findings support prioritizing structural and policy-level interventions that address social and gender disparities in physical activity access and health promotion.Studies from countries with lower HDI and information on ethnicity and socioeconomic status will bridge crucial gaps in understanding factors involved in global CRF levels.展开更多
Food Science and Human Wellness (FSHW ISSN:2213-4530, CN 10-1750/TS) publishes original research papers demonstrating the latest advancement of multidisciplinary subjects related to food science and human health.Topic...Food Science and Human Wellness (FSHW ISSN:2213-4530, CN 10-1750/TS) publishes original research papers demonstrating the latest advancement of multidisciplinary subjects related to food science and human health.Topics may include but not limited to: nutriology, biochemistry, microbiology, immunology and toxicology.展开更多
Food Science and Human Wellness(FSHW ISSN:2213-4530,CN 10-1750/TS)publishes original research papers demonstrating the latest advancement of multidisci plinary subjects related to food science and human health Topics ...Food Science and Human Wellness(FSHW ISSN:2213-4530,CN 10-1750/TS)publishes original research papers demonstrating the latest advancement of multidisci plinary subjects related to food science and human health Topics may include but not limited to:nutriology,bio.chemistry,microbiology,immunology and toxicology.展开更多
Lip synchronization serves as a core technology for enabling natural interactions in digital virtual humans.However,it faces challenges such as insufficient dynamic correspondence between speech and lip movements and ...Lip synchronization serves as a core technology for enabling natural interactions in digital virtual humans.However,it faces challenges such as insufficient dynamic correspondence between speech and lip movements and inadequate modeling of image details.To address these limitations,a comprehensively optimized lip synchronization framework extending the Wav2Lip architecture was proposed in this study.Firstly,based on the Wav2Lip model,a facial region extraction strategy using facial keypoints was designed,which effectively enhances the robustness of facial alignment during lip synchronization for digital virtual humans.Then,a cross-modal attention fusion module between visual and speech features was introduced to improve cross-modal information fusion,and a dynamic receptive field convolution module was developed in the generation branch to enhance the modeling performance of the lip region.Finally,experiments were conducted on the VFHQ dataset.The proposed method was compared with Wav2Lip,VideoRetalking,and DI-Net models,and its performance was evaluated using three metrics:LSE-C,CSIM,and FID.Experimental results showed that the proposed method achieves significant improvements in synchronization accuracy and image fidelity,providing an efficient and feasible solution for lip-synthesis tasks of digital virtual humans.展开更多
Two Co(Ⅱ)and Ni(Ⅱ)complexes were synthesized by synergistic coordination of 3,3-diphenylpropionic acid(HDPA)and 2,2′-bipyridylamine(PAm).The structures of complexes[Co(DPA)_(2)(PAm)]·2H_(2)O(1)and[Ni(DPA)_(2)(...Two Co(Ⅱ)and Ni(Ⅱ)complexes were synthesized by synergistic coordination of 3,3-diphenylpropionic acid(HDPA)and 2,2′-bipyridylamine(PAm).The structures of complexes[Co(DPA)_(2)(PAm)]·2H_(2)O(1)and[Ni(DPA)_(2)(PAm)]·2H_(2)O(2)were determined by single-crystal X-ray diffraction,IR spectroscopy,and powder X-ray diffraction.Hirshfeld surface analysis provided quantitative insights into the intermolecular interactions within the complexes,while molecular docking studies elucidated their binding modes and affinities toward urease.Furthermore,the biological activities of both complexes were systematically evaluated through a range of assays,including DNA binding,urease inhibition,antibacterial activity,and in vitro cytotoxicity against cancer cells.Both complexes exhibited binding affinity for DNA and displayed notable urease inhibitory activity.Under in vitro conditions,both complexes showed appreciable cytotoxicity toward HepG2 cells with efficacy comparable to clinically used platinumbased anticancer agents.CCDC:2479943,1;2479944,2.展开更多
基金The Second Tibetan Plateau Scientific Expedition and Research Program,No.2019QZKK0608。
文摘Understanding the impacts of human activities on the plateau’s living environment is essential for advancing modernization pathways that promote harmony between humanity and nature.However,studies on the dynamic interactions between human activities and the living environment on the Qinghai-Xizang Plateau(QXP)remain limited,with a paucity of quantitative relationship analyses.This study established an assessment framework to evaluate human influences on the living environment in QXP,using data on typical human activities,ecological conditions,and human settlements.Within this framework,the spatial analysis methods and the coupling coordination model were used to examine the spatio-temporal characteristics and relationship of human activities and living environment on the QXP from 2000 to 2020.The geographical detector model was then applied to identify the key factors influencing the plateau’s human living environment.Subsequently,the four-quadrant analysis model was adopted to assess human influences on the living environment.The results indicate that the human activity intensity(HAI)on the QXP remained relatively low yet increased by 15.41%from 2000 to 2020.Spatially,the human living environment quality(LEQ)improved from northwest to southeast,with 61.14%of the areas remaining stable and 18.47%experiencing slight improvement.The analysis of coupling coordination revealed a continuous improvement between the HAI and LEQ,with the areas of high and relatively high coordinated types increasing by more than 9%.Precipitation and urban-rural construction were identified as the primary factors influencing changes in the LEQ.The interaction between the HAI and LEQ was strengthening,with 40.44%classified as coordinated development type and 38.35%as development-environment conflict type.These findings provide valuable insights for enhancing the resilience of human settlements and promoting green development across the plateau.
基金supported by the National Natural Science Foundation of China(32271584 and 31600445)the Natural Science Basic Research Plan in Shaanxi Province of China(2020JM-286)+2 种基金the Fundamental Research Funds for the Central Universities(GK202103072,GK202103073)the National College Students'Innovative Entrepreneurial Training Plan Program(202310718085)Special Research Project in Philosophy and Social Sciences of Shaanxi Province(2022HZ1795).
文摘Prevention of biological invasion requires understanding how alien species invade native communities.Although studies have identified mechanisms that underlie plant invasion in some habitats,limited attention has focused on invasion patterns along elevational gradients.In this study,we asked which factors drive the global and regional distribution of the invasive plant Galinsoga quadriradiata along elevational gradients.To answer this question,we examined whether human activities(i.e.,roads)promote G.quadriradiata invasion,how seed dispersal-related traits of G.quadriradiata change along elevation gradients,and whether G.quadriradiata has adapted to high-elevation environments through phenotypic plasticity or genetic variation.On the global scale,we found that human activities and road density positively contribute to the G.quadriradiata expansion in mountainous areas.Field surveys in China revealed significant elevational differences in the seed dispersal traits of G.quadriradiata,with higher-elevation populations exhibiting lower dispersal ability and generally lower genetic diversity.Under common conditions,high-elevation populations showed higher leaf mass ratio but lower root mass ratio and reproductive allocation.This suggests that high-elevation environments create a barrier to dispersal for G.quadriradiata,and that G.quadriradiata has adapted phenotypically to these conditions.Our study indicates that the elevational invasion pattern of G.quadriradiata is shaped by multiple factors,particularly human activities and phenotypic adaptability.In addition,our finding that G.quadriradiata invasion at high elevations is not constrained by low genetic diversity indicates that monitoring and management of G.quadriradiata in mountainous areas should be strengthened.
基金Shanxi Province Graduate Research Practice Innovation Project,No.2023KY465Project on the Reform of Graduate Education and Teaching in Shanxi Province,No.2021YJJG146+1 种基金Research Project of Shanxi Provincial Cultural Relics Bureau,No.22-8-14-1400-119National Key R&D Program of China,No.2021YFB3901300。
文摘Human activities have significantly impacted the land surface temperature(LST),endangering human health;however,the relationship between these two factors has not been adequately quantified.This study comprehensively constructs a Human Activity Intensity(HAI)index and employs the Maximal Information Coefficient,four-quadrant model,and XGBoostSHAP model to investigate the spatiotemporal relationship and influencing factors of HAI-LST in the Yellow River Basin(YRB)from 2000 to 2020.The results indicated that from 2000 to 2020,as HAI and LST increased,the static HAI-LST relationship in the YRB showed a positive correlation that continued to strengthen.This dynamic relationship exhibited conflicting development,with the proportion of coordinated to conflicting regions shifting from 1:4 to 1:2,indicating a reduction in conflict intensity.Notably,only the degree of conflict in the source area decreased significantly,whereas it intensified in the upper and lower reaches.The key factors influencing the HAI-LST relationship include fractional vegetation cover,slope,precipitation,and evapotranspiration,along with region-specific factors such as PM_(2.5),biodiversity,and elevation.Based on these findings,region-specific ecological management strategies have been proposed to mitigate conflict-prone areas and alleviate thermal stress,thereby providing important guidance for promoting harmonious development between humans and nature.
基金supported by the National Key Research and Development Program of China(No.2022YFF1301301)the Natural Science Foundation of Xiamen Municipality(No.3502Z202472047)the Geological Survey Program of China Geological Survey(DD20190303).
文摘To address the deficiencies in comprehensive surface contamination prevention strategies within China's nitrate-affected regions,this research innovatively proposes the DITAPH model-a systematic framework integrating groundwater nitrate vulnerability assessment and Nitrate Vulnerable Zones(NVZs)delineation through optimization of hydrogeological parameters.Based on detailed hydrogeological and hydrochemical investigations,the DITAPH model was applied in the plain areas of Quanzhou to evaluate its applicability.The model selected hydrogeological parameters(depth of groundwater,lithology of the vadose zone,topographic slope,aquifer water yield property),one climatic parameter(precipitation),and two anthropogenic parameters(land use type and population density)as assessment indicators.The results of the groundwater nitrate vulnerability assessment showed that the low,relatively low,relatively high,and high groundwater nitrate vulnerability zones in the study area accounted for 5.96%,35.44%,53.74%and 4.86%of the total area,respectively.Groundwater nitrate vulnerability was most strongly influenced by human activities,followed by groundwater depth and topographic slope.The high vulnerability zone is mainly affected by domestic and industrial wastewater,whereas the relatively high groundwater nitrate vulnerability zone is primarily influenced by agricultural activities.Validation of the DITAPH model revealed a significant positive correlation between the DITAPH index(DI)and nitrate concentration(ρ(NO3−)).The results of the NVZs delineated by the DITAPH model are reliable and can serve as a tool for water resource management planning,guiding the development of targeted measures in the NVZs to prevent groundwater contamination.
基金The Foundation for Distinguished Young Scholars of Gansu Province,No.22JR5RA046Key Research Program of Gansu Province,No.23ZDKA0004+2 种基金The Joint Funds of the National Natural Science Foundation of China,No.U22A202690Interdisciplinary Youth Team Project from the Key Laboratory of Cryospheric Science and Frozen Soil Engineering,No.CSFSE-ZQ-2408The Youth Innovation Promotion Association CAS to X.W.,No.2020422。
文摘Carbon fluxes are essential indicators assessing vegetation carbon cycle functions.However,the extent and mechanisms by which climate change and human activities influence the spatiotemporal dynamics of carbon fluxes in arid oasis and non-oasis area remains unclear.Here,we assessed and predicted the future effects of climate change and human activities on carbon fluxes in the Hexi Corridor.The results showed that the annual average gross primary productivity(GPP),net ecosystem productivity(NEP),and ecosystem respiration(Reco)in the Hexi Corridor oasis increased by 263.91 g C·m^(-2)·yr^(-1),118.45 g C·m^(-2)·yr^(-1)and 122.46 g C·m^(-2)·yr^(-1),respectively,due to the expansion of the oasis area by 3424.84 km^(2) caused by human activities from 2000 to 2022.Both oasis and non-oasis arid ecosystems in the Hexi Corridor acted as carbon sinks.Compared to the non-oasis area,the carbon fluxes contributions of oasis area increased,ranging from 10.21%to 13.99%for GPP,8.50%to11.68%for NEP,and 13.34%to 17.13%for Reco.The contribution of the carbon flux from the oasis expansion area to the total carbon flux change in the Hexi Corridor was 30.96%(7.09 Tg C yr^(-1))for GPP,29.57%(3.39 Tg C yr^(-1))for NEP and 32.40%(3.58 Tg C yr^(-1))for Reco.The changes in carbon fluxes in the oasis area were mainly attributed to human activities(oasis expansion)and temperature,whereas non-oasis area was mainly due to climate factors.Moreover,the future increasing trends were observed for GPP(64.99%),NEP(66.29%)and Reco(82.08%)in the Hexi Corridor.This study provides new insights into the regulatory mechanisms of carbon cycle in the arid oasis and non-oasis area.
基金The National Natural Science Foundation of China(Grant 42371159)。
文摘Based on regional paleoclimate sequences,records of human activities,paleoclimate simulations,and detailed environmental historical records,we discuss the impacts of Holocene climate change and human activities on the evolution of the Shule River in the western Qilian Mountains,China.The results indicate that during the early to mid-Holocene,the river evolution of the Shule River alluvial fan was closely related to regional climate fluctuations.In the late Holocene,flood agriculture began to emerge along the Shule River.During the historical period,population growth and the expansion of arable land led to increased river water usage,resulting in decreased access to the expected distribution of water resources in other regions,which in turn has caused imbalances in the regional hydrological ecosystem.
基金funded by the Joint CAS-MPG Research Project(HZXM20225001MI)this research was also supported partly by the key program of National Natural Science Foundation of China(42230708)the Tianshan Talent Project of Xinjiang Uygur Autonomous Region,China(2022TSYCLJ0056).
文摘Central Asia(CA)faces escalating threats from increasing temperature,glacier retreat,biodiversity loss,unsustainable water use,terminal lake shrinkage,and soil salinization,all of which challenge the balance between ecological integrity and socio-economic development essential for achieving Sustainable Development Goals.However,a comprehensive understanding of priority areas from a multi-dimensional perspective is lacking,hindering effective conservation and development strategies.To address this,we developed a comprehensive assessment framework with a tailored indicator system,enabling a spatial evaluation of CA’s priority areas by integrating biodiversity,ecosystem services(ESs),and human activities.Combining zonation and geographical detectors,this approach facilitates spatial prioritization and examines ecological and socio-economic heterogeneity.Our findings reveal a heterogeneous distribution of priority areas across CA,with significant concentrations in eastern mountainous regions,river valleys,and oasis agricultural lands.We identified 184 key districts crucial for ecological and societal sustainability.Attribution analysis shows that natural factors like soil types,precipitation,and evapotranspiration significantly shape these areas,influencing human activities and the distribution of biodiversity and ESs.Multi-dimensional analysis indicates existing protected areas cover only 15%of the top 30%priority areas,revealing substantial conservation gaps.Additionally,a 38%overlap between ESs and human activities,along with 63.25%congruence in integrated areas,underscores significant human impacts on ecological systems and their dependency on ESs.Given CA’s limited resources,it is crucial to implement measures that strengthen conservation efforts,align ecological preservation with socio-economic demands,and enhance resource efficiency through sustainable integrated land and water resource management.
基金Under the auspices of National Natural Science Foundation of China(No.42271125)Jilin Province Foreign Expert Project(No.L202322)Doctoral Research Initiation Project of Jilin Normal University(No.0420237)。
文摘The Songhua River Basin(SRB),ranking third largest in China in terms of both runoff volume and basin area,has experi-enced frequent disasters and drastic changes in runoff since the early 20th century.Many studies have analyzed the causes of runoff re-duction;however,the spatiotemporal differences in runoff contributions and their underlying mechanisms remain poorly understood,which are crucial for regional water resources management and effective utilization.This study used the Mann-Kendall rank correlation trend test,continuous wavelet analysis,cumulative anomaly,and the slope change ratio of cumulative quantities(SCRCQ)method to explore the runoff changes characteristics and spatiotemporal differences of the contributions of climate change and human activities to runoff changes across three sub-basins of the SRB.The results show that:1)runoff from 1955 to 2022 in all the three sub-basins exhibit a statistically significant decreasing trend at 0.05 significant level.2)Four abrupt change points in runoff were detected in Nenjiang River Basin(NRB)and the mainstream of the SRB(MSRB),whereas only two change points in the Second Songhua River(SSRB).3)Runoff and precipitation series of the NRB and MSRB exhibit similar multi-timescale cycle characteristics with the most dominated cycles of 45-58 yr.In contrast,it is 12-18 yr for SSRB.4)Anthropogenic activities are the primary factor leading to in the reduction of runoff in NRB(74.33%-91.67%)and MSRB(50.11%-102.12%),whereas it is only 5.38%-33.12%in SSRB.This is attributed to the uneven distribution of regional climate and human activities in the entire SRB.5)With the growing demand for water diversion for agri-cultural irrigation,anthropogenic activities in the NRB and MSRB have increased.However,the opposite is found in SSR,where the in-creased influence of precipitation on runoff and water conservation policies are identified.
基金supported by Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2026R765),Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘Human Activity Recognition(HAR)is a novel area for computer vision.It has a great impact on healthcare,smart environments,and surveillance while is able to automatically detect human behavior.It plays a vital role in many applications,such as smart home,healthcare,human computer interaction,sports analysis,and especially,intelligent surveillance.In this paper,we propose a robust and efficient HAR system by leveraging deep learning paradigms,including pre-trained models,CNN architectures,and their average-weighted fusion.However,due to the diversity of human actions and various environmental influences,as well as a lack of data and resources,achieving high recognition accuracy remain elusive.In this work,a weighted average ensemble technique is employed to fuse three deep learning models:EfficientNet,ResNet50,and a custom CNN.The results of this study indicate that using a weighted average ensemble strategy for developing more effective HAR models may be a promising idea for detection and classification of human activities.Experiments by using the benchmark dataset proved that the proposed weighted ensemble approach outperformed existing approaches in terms of accuracy and other key performance measures.The combined average-weighted ensemble of pre-trained and CNN models obtained an accuracy of 98%,compared to 97%,96%,and 95%for the customized CNN,EfficientNet,and ResNet50 models,respectively.
基金National Natural Science Foundation of China(Grant No.U2243225)the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDB40000000)+2 种基金the Natural Science Basic Research Program of Shaanxi(Grant No.Z2024-ZYFS-0065)the Funding of Top Young talents of Ten Thousand talents Plan in China(2021)the Fundamental Research Funds for the Central Universities(Grants No.2452023071 and 2023HHZX002).
文摘Understanding the complex interactions between human activities and ecosystem functions is a prerequisite for achieving sustainable development.Since the implementation of the“Grain for Green”Project in 1999,ecosystem functions in China’s Loess Plateau have significantly improved.However,intensified human activities have also exacerbated the pressures on the region’s fragile ecological environment.This study investigates the spatiotemporal variations in the human activity intensity index(HAI)and net ecosystem benefits(NEB)from 2000 to 2020,using expert-based assessments and an enhanced cost-benefit evaluation framework.Results indicate that HAI increased by 16.7% and 16.6% at the grid and county levels,respectively.NEB exhibited pronounced spatial heterogeneity,with a total increase of USD 36.2 trillion at the grid scale.At the county level,the average NEB rose by 75%.The degree of trade-off was higher at the grid scale than at the county scale,while the synergistic areas initially expanded and then declined at both scales.Key areas for improvement and regions of lagging development were identified as priority zones for ecological management and spatial planning at both spatial resolutions.This study offers scientific insights and practical guidance for harmonizing ecological conservation with high-quality development in ecologically vulnerable regions.
基金supported by Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia through the Researchers Supporting Project PNURSP2025R333.
文摘Human activity recognition(HAR)is a method to predict human activities from sensor signals using machine learning(ML)techniques.HAR systems have several applications in various domains,including medicine,surveillance,behavioral monitoring,and posture analysis.Extraction of suitable information from sensor data is an important part of the HAR process to recognize activities accurately.Several research studies on HAR have utilizedMel frequency cepstral coefficients(MFCCs)because of their effectiveness in capturing the periodic pattern of sensor signals.However,existing MFCC-based approaches often fail to capture sufficient temporal variability,which limits their ability to distinguish between complex or imbalanced activity classes robustly.To address this gap,this study proposes a feature fusion strategy that merges time-based and MFCC features(MFCCT)to enhance activity representation.The merged features were fed to a convolutional neural network(CNN)integrated with long shortterm memory(LSTM)—DeepConvLSTM to construct the HAR model.The MFCCT features with DeepConvLSTM achieved better performance as compared to MFCCs and time-based features on PAMAP2,UCI-HAR,and WISDM by obtaining an accuracy of 97%,98%,and 97%,respectively.In addition,DeepConvLSTM outperformed the deep learning(DL)algorithms that have recently been employed in HAR.These results confirm that the proposed hybrid features are not only practical but also generalizable,making them applicable across diverse HAR datasets for accurate activity classification.
基金supported by National Natural Science Foundation of China(NSFC)under grant U23A20310.
文摘With the growing advancement of wireless communication technologies,WiFi-based human sensing has gained increasing attention as a non-intrusive and device-free solution.Among the available signal types,Channel State Information(CSI)offers fine-grained temporal,frequency,and spatial insights into multipath propagation,making it a crucial data source for human-centric sensing.Recently,the integration of deep learning has significantly improved the robustness and automation of feature extraction from CSI in complex environments.This paper provides a comprehensive review of deep learning-enhanced human sensing based on CSI.We first outline mainstream CSI acquisition tools and their hardware specifications,then provide a detailed discussion of preprocessing methods such as denoising,time–frequency transformation,data segmentation,and augmentation.Subsequently,we categorize deep learning approaches according to sensing tasks—namely detection,localization,and recognition—and highlight representative models across application scenarios.Finally,we examine key challenges including domain generalization,multi-user interference,and limited data availability,and we propose future research directions involving lightweight model deployment,multimodal data fusion,and semantic-level sensing.
基金supported by Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2026R909)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘The concept of Human Activity Recognition(HAR)is integral to applications based on Internet of Things(IoT)-enabled devices,particularly in healthcare,fitness tracking,and smart environments.The streams of data from wearable sensors are rich in information,yet their high dimensionality and variability pose a significant challenge to proper classification.To address this problem,this paper proposes hybrid architectures that integrate traditional machine learning models with a deep neural network(DNN)to deliver improved performance and enhanced capabilities for HAR tasks.Multi-sensor HAR data were used to systematically test several hybrid models,including:RF+DNN(Random Forest+Deep Neural Network),XGB+DNN(XGBoost+DNN),GB+DNN(Gradient Boosting+DNN),KNN+DNN(K-Nearest Neighbors+DNN),and DT+DNN(Decision Tree+DNN).The RF+DNN model was the most accurate,achieving a 97.03%score with excellent precision,recall,and F1-score.These findings demonstrate that hybrid machine learning and deep learning systems have a promising future in IoT-based HAR applications.The model provides a novel solution for developing smart and trustworthy monitoring systems that support real-time analytics,patient surveillance,and other IoT applications.
基金Project supported by the National Natural Science Foundation of China(No.32160108)the Science and Technology Special Fund of Hainan Province(No.ZDYF2024SHFZ116)+2 种基金the Specific Research Fund of the Innovation Center for Academicians of Hainan Province(No.YSPTZX202309)the Scientific Research Project of Hainan Higher Education Institutions(No.Hnky2022ZD-6)the Hainan Normal University National College Student Innovation Training Program(No.202411658006)。
文摘new heterocyclic dipeptide with a highly functionalized 1,2-oxazadecaline core,named trichodermamide H(1),and three known analogues,along with three known polyketides,were isolated from the fermentation extract of the mangrovederived fungus Penicillium janthinellum XLN32122.The structure of 1 was elucidated on the basis of extensive 1D and 2D NMR spectra data analysis,HR-ESI-MS,electronic circular dichroism(ECD)calculations.Trichodermamide B(3)exhibited better inhibitory effect on nitric oxide(NO)production in lipopolysaccharide(LPS)induced RAW 264.7 cells with an IC_(50)value of(13.13±0.005)μmol/L than that of the positive control dexamethasone[IC_(50)=(136.84±1.33)μmol/L].Compound 3 exhibited antibacterial activity against methicillin-resistant Staphylococcus aureus(MRSA)with an IC_(50)value of 12.5μg/mL,while the positive control vancomycin showed an IC_(50)value of 1.563μg/mL.
文摘Activation of neutrophil membrane receptors initiates intracellular signal transduction cascades that orchestrate the cell's effector functions,including phagocytosis,production of reactive oxygen and halogen species,degranulation,and NETosis(formation of neutrophil extracellular traps[NETs]).NETs,which contain antimicrobial compounds such as myeloperoxidase(MPO),represent a strategy to combat infection.However,excessive production of NETs promotes thrombosis,diabetes mellitus,and other diseases.Therefore,investigations into the mechanisms of NETosis and the identification of modulators of this process are critical for developing strategies to address NETosis-related disorders.Here,we identified a novel NETosis inducer,human serum albumin(HSA)modified by the MPO product hypochlorous acid(HSAHOCl),whose accumulation in vivo was correlated with inflammatory processes.Using human blood neutrophils,we investigated HSAHOCl-induced NETosis and detected NET formation by flow cytometry.The results showed that the mechanism of HSAHOClinduced NETosis involved MPO,NADPH oxidase,and phosphatidylinositol 3-kinases(PI3Ks),and that HSAHOCl activated a reactive oxygen species-dependent suicidal type of NETosis.Moreover,HSAHOCl-induced NETosis was inhibited by an anti-HSAHOCl monoclonal antibody.Thus,our findings may facilitate the development of strategies to modulate NETosis in inflammation associated with elevated MPO activity.
基金NJP holds a Future Leader Award from the Novo Nordisk Foundation and European Foundation for the Study of Diabetes(NNF/EFSD NNF21SA0072747)a grant from the Diabetes Wellness Network Sverige(PG21-6524)+5 种基金supported by the Swedish Research Council(2015-00165)the European Research Council(ERC-2023-Ad G 101142093)a Wallenberg Scholars Award from the Knut and Alice Wallenberg Foundation(KAW 2023.0312)the Swedish Research Council for Sport Science(P2023-0093)The Novo Nordisk Foundation Center for Basic Metabolic Research is an independent research center at the Faculty of Health and Medical Sciences,University of Copenhagen,Denmark partially funded by an unrestricted donation from the Novo Nordisk Foundation(NNF18CC0034900,NNF23SA0084103)supported by a postdoctoral fellowship from the Strategic Research Program in Diabetes at Karolinska Institutet。
文摘Background:Cardiorespiratory fitness(CRF)is a powerful predictor of mortality and chronic disease risk,yet global patterns and determinants of CRF remain poorly defined,particularly in females and underrepresented populations.We conducted a systematic review and quantitative synthesis of directly measured peak oxygen uptake(VO_(2peak))internationally and examined its association with human development and gender ine quality.Methods:Studies were eligible if VO_(2peak)was assessed via direct gas analysis during maximal exercise testing,and if the countries had scores for the Human Development Index(HDI)and Gender Inequality Index(GII).Studies were identified through MEDLINE/PubMed,Embase,CINAHL,and Web of Science.Risks of bias were assessed by an adaptation of the Newcastle-Ottawa Scale.Multivariable linear regression models examined associations between VO_(2peak),age,sex,exercise modality,HDI,GII,and study year.Results:Data included 95 studies from 24 countries with HDI and GII scores,comprising 119,435 adults(42%females)with VO_(2peak)assessed via direct gas analysis during maximal exercise testing.The risk of bias was low.VO_(2peak)was positively associated with HDI(β=14.1)and negatively associated with GII(β=-3.6).Slightly stronger associations were observed in females than males(HDI:β=18.9 vs.β=13.9,GII:β=-4.6vs.β=-3.6).Young females in middle-HDI countries had higher VO_(2peak)than those in low-HDI countries(31.2mL/kg/min vs.28.5 mL/kg/min),with limited additional gams in high-HDI contexts.VO_(2peak)decreased with higher gender inequality,with the largest disparities observed in young females between high-and low-GII countries(26.3 mL/kg/min vs.32.8 mL/kg/min).Conclusion:Global variation in CRF is tied to national levels of human development and gender equality.These findings support prioritizing structural and policy-level interventions that address social and gender disparities in physical activity access and health promotion.Studies from countries with lower HDI and information on ethnicity and socioeconomic status will bridge crucial gaps in understanding factors involved in global CRF levels.
文摘Food Science and Human Wellness (FSHW ISSN:2213-4530, CN 10-1750/TS) publishes original research papers demonstrating the latest advancement of multidisciplinary subjects related to food science and human health.Topics may include but not limited to: nutriology, biochemistry, microbiology, immunology and toxicology.
文摘Food Science and Human Wellness(FSHW ISSN:2213-4530,CN 10-1750/TS)publishes original research papers demonstrating the latest advancement of multidisci plinary subjects related to food science and human health Topics may include but not limited to:nutriology,bio.chemistry,microbiology,immunology and toxicology.
文摘Lip synchronization serves as a core technology for enabling natural interactions in digital virtual humans.However,it faces challenges such as insufficient dynamic correspondence between speech and lip movements and inadequate modeling of image details.To address these limitations,a comprehensively optimized lip synchronization framework extending the Wav2Lip architecture was proposed in this study.Firstly,based on the Wav2Lip model,a facial region extraction strategy using facial keypoints was designed,which effectively enhances the robustness of facial alignment during lip synchronization for digital virtual humans.Then,a cross-modal attention fusion module between visual and speech features was introduced to improve cross-modal information fusion,and a dynamic receptive field convolution module was developed in the generation branch to enhance the modeling performance of the lip region.Finally,experiments were conducted on the VFHQ dataset.The proposed method was compared with Wav2Lip,VideoRetalking,and DI-Net models,and its performance was evaluated using three metrics:LSE-C,CSIM,and FID.Experimental results showed that the proposed method achieves significant improvements in synchronization accuracy and image fidelity,providing an efficient and feasible solution for lip-synthesis tasks of digital virtual humans.
文摘Two Co(Ⅱ)and Ni(Ⅱ)complexes were synthesized by synergistic coordination of 3,3-diphenylpropionic acid(HDPA)and 2,2′-bipyridylamine(PAm).The structures of complexes[Co(DPA)_(2)(PAm)]·2H_(2)O(1)and[Ni(DPA)_(2)(PAm)]·2H_(2)O(2)were determined by single-crystal X-ray diffraction,IR spectroscopy,and powder X-ray diffraction.Hirshfeld surface analysis provided quantitative insights into the intermolecular interactions within the complexes,while molecular docking studies elucidated their binding modes and affinities toward urease.Furthermore,the biological activities of both complexes were systematically evaluated through a range of assays,including DNA binding,urease inhibition,antibacterial activity,and in vitro cytotoxicity against cancer cells.Both complexes exhibited binding affinity for DNA and displayed notable urease inhibitory activity.Under in vitro conditions,both complexes showed appreciable cytotoxicity toward HepG2 cells with efficacy comparable to clinically used platinumbased anticancer agents.CCDC:2479943,1;2479944,2.
