In the Kigongo area of Mwanza Region,northwest Tanzania,fishmonger Neema Aisha remembers how the morning’s fresh catch would sour while she queued for the ferry,putting her business at risk.
Blockchain offers a promising solution to the security challenges faced by the Internet of Vehicles(IoV).However,due to the dynamic connectivity of IoV,blockchain based on a single-chain structure or Directed Acyclic ...Blockchain offers a promising solution to the security challenges faced by the Internet of Vehicles(IoV).However,due to the dynamic connectivity of IoV,blockchain based on a single-chain structure or Directed Acyclic Graph(DAG)structure often suffer from performance limitations.The DAG lattice structure is a novel blockchain model in which each node maintains its own account chain,and only the node itself is allowed to update it.This feature makes the DAG lattice structure particularly suitable for addressing the challenges in dynamically connected IoV environment.In this paper,we propose a blockchain architecture based on the DAG lattice structure,specifically designed for dynamically connected IoV.In the proposed system,nodes must obtain authorization from a trusted authority before joining,forming a permissioned blockchain.Each node is assigned an individual account chain,allowing vehicles with limited storage capacity to participate in the blockchain by storing transactions only from nearby vehicles’account chains.Every transmitted message is treated as a transaction and added to the blockchain,enablingmore efficient data transmission in a dynamic network environment.Areputation-based incentivemechanism is introduced to encourage nodes to behave normally.Experimental results demonstrate that the proposed architecture achieves better performance compared with traditional single-chain and DAG-based approaches in terms of average transmission delay and storage cost.展开更多
BACKGROUND Suicide constitutes the second leading cause of death among adolescents globally and represents a critical public health concern.The neural mechanisms underlying suicidal behavior in adolescents with major ...BACKGROUND Suicide constitutes the second leading cause of death among adolescents globally and represents a critical public health concern.The neural mechanisms underlying suicidal behavior in adolescents with major depressive disorder(MDD)remain poorly understood.Aberrant resting-state functional connectivity(rsFC)in the amygdala,a key region implicated in emotional regulation and threat detection,is strongly implicated in depression and suicidal behavior.AIM To investigate rsFC alterations between amygdala subregions and whole-brain networks in adolescent patients with depression and suicide attempts.METHODS Resting-state functional magnetic resonance imaging data were acquired from 32 adolescents with MDD and suicide attempts(sMDD)group,33 adolescents with MDD but without suicide attempts(nsMDD)group,and 34 demographically matched healthy control(HC)group,with the lateral and medial amygdala(MeA)defined as regions of interest.The rsFC patterns of amygdala subregions were compared across the three groups,and associations between aberrant rsFC values and clinical symptom severity scores were examined.RESULTS Compared with the nsMDD group,the sMDD group exhibited reduced rsFC between the right lateral amygdala(LA)and the right inferior occipital gyrus as well as the left middle occipital gyrus.Compared with the HC group,the abnormal brain regions of rsFC in the sMDD group and nsMDD group involve the parahippocampal gyrus(PHG)and fusiform gyrus.In the sMDD group,right MeA and right temporal pole:Superior temporal gyrus rsFC value negatively correlated with the Rosenberg Self-Esteem Scale scores(r=-0.409,P=0.025),while left LA and right PHG rsFC value positively correlated with the Adolescent Self-Rating Life Events Checklist interpersonal relationship scores(r=0.372,P=0.043).CONCLUSION Aberrant rsFC changes between amygdala subregions and these brain regions provide novel insights into the underlying neural mechanisms of suicide attempts in adolescents with MDD.展开更多
The development of brain-computer interfaces(BCI)based on motor imagery(MI)has greatly improved patients’quality of life with movement disorders.The classification of upper limb MI has been widely studied and applied...The development of brain-computer interfaces(BCI)based on motor imagery(MI)has greatly improved patients’quality of life with movement disorders.The classification of upper limb MI has been widely studied and applied in many fields,including rehabilitation.However,the physiological representations of left and right lower limb movements are too close and activated deep in the cerebral cortex,making it difficult to distinguish their features.Therefore,classifying lower limbs motor imagery is more challenging.In this study,we propose a feature extraction method based on functional connectivity,which utilizes phase-locked values to construct a functional connectivity matrix as the features of the left and right legs,which can effectively avoid the problem of physiological representations of the left and right lower limbs being too close to each other during movement.In addition,considering the topology and the temporal characteristics of the electroencephalogram(EEG),we designed a temporal-spatial convolutional network(TSGCN)to capture the spatiotemporal information for classification.Experimental results show that the accuracy of the proposed method is higher than that of existing methods,achieving an average classification accuracy of 73.58%on the internal dataset.Finally,this study explains the network mechanism of left and right foot MI from the perspective of graph theoretic features and demonstrates the feasibility of decoding lower limb MI.展开更多
Floodplain wetlands are invaluable ecosystems providing numerous ecological benefits,yet they face a global crisis necessitating sustainable preservation efforts.This study examines the depletion of floodplain wetland...Floodplain wetlands are invaluable ecosystems providing numerous ecological benefits,yet they face a global crisis necessitating sustainable preservation efforts.This study examines the depletion of floodplain wetlands within the Hastinapur Wildlife Sanctuary(HWLS)in Uttar Pradesh.Encroachment activities such as grazing,agriculture,and human settlements have fragmented and degraded critical wetland ecosystems.Additionally,irrigation projects,dam construction,and water diversion have disrupted natural water flow and availability.To assess wetland inundation in 2023,five classification techniques were employed:Random Forest(RF),Support Vector Machine(SVM),artificial neural network(ANN),Spectral Information Divergence(SID),and Maximum Likelihood Classifier(MLC).SVM emerged as the most precise method,as determined by kappa coefficient and index-based validation.Consequently,the SVM classifier was used to model wetland inundation areas from 1983 to 2023 and analyze spatiotemporal changes and fragmentation patterns.The findings revealed that the SVM clas-sifier accurately mapped 2023 wetland areas.The modeled time-series data demonstrated a 62.55%and 38.12%reduction in inundated wetland areas over the past 40 years in the pre-and post-monsoon periods,respectively.Fragmentation analysis indicated an 86.27%decrease in large core wetland areas in the pre-monsoon period,signifying severe habitat degradation.This rapid decline in wetlands within protected areas raises concerns about their ecological impacts.By linking wetland loss to global sustainability objectives,this study underscores the global urgency for strengthened wetland protection measures and highlights the need for integrating wetland conservation into broader sustainable development goals.Effective policies and adaptive management strategies are crucial for preserving these ecosystems and their vital services,which are essential for biodiversity,climate regulation,and human well-being.展开更多
This study aims to explore the impact of fatigue induced by different limb exercises on cerebral cortical oxygenation levels and functional connectivity strength using functional near-infrared spectroscopy(fNIRS).Fati...This study aims to explore the impact of fatigue induced by different limb exercises on cerebral cortical oxygenation levels and functional connectivity strength using functional near-infrared spectroscopy(fNIRS).Fatigue was induced using an upper limb ergometer or a lower limb ergometer,with the load increasing gradually each minute.fNIRS covering the prefrontal cortex and motor cortex were used to collect data during the resting state,both before and after fatigue induction.A two-way ANOVA was conducted to examine differences in oxyhemoglobin(HbO_(2))and functional connectivity before and after fatigue induction in both groups,with the significance level set at 0.05.Exercise-induced fatigue in both the upper and lower limbs leads to a significant decrease in cerebral cortical oxygenation levels.Upper limb fatigue leads to a significant reduction in functional connectivity,there were significant decreases in connectivity within the motor cortex,between the motor cortex and frontal regions,and between the right ventrolateral prefrontal cortex and other frontal regions.Conversely,no significant changes were observed before and after lower limb fatigue.Future studies should focus on examining the extent to which how changes in the cerebral cortex,induced by exercise fatigue,are linked to exercise-and/or performance-related outcomes.展开更多
The advent of sixth-generation(6G)networks introduces unprecedented challenges in achieving seamless connectivity,ultra-low latency,and efficient resource management in highly dynamic environments.Although fifth-gener...The advent of sixth-generation(6G)networks introduces unprecedented challenges in achieving seamless connectivity,ultra-low latency,and efficient resource management in highly dynamic environments.Although fifth-generation(5G)networks transformed mobile broadband and machine-type communications at massive scales,their properties of scaling,interference management,and latency remain a limitation in dense high mobility settings.To overcome these limitations,artificial intelligence(AI)and unmanned aerial vehicles(UAVs)have emerged as potential solutions to develop versatile,dynamic,and energy-efficient communication systems.The study proposes an AI-based UAV architecture that utilizes cooperative reinforcement learning(CoRL)to manage an autonomous network.The UAVs collaborate by sharing local observations and real-time state exchanges to optimize user connectivity,movement directions,allocate power,and resource distribution.Unlike conventional centralized or autonomous methods,CoRL involves joint state sharing and conflict-sensitive reward shaping,which ensures fair coverage,less interference,and enhanced adaptability in a dynamic urban environment.Simulations conducted in smart city scenarios with 10 UAVs and 50 ground users demonstrate that the proposed CoRL-based UAV system increases user coverage by up to 10%,achieves convergence 40%faster,and reduces latency and energy consumption by 30%compared with centralized and decentralized baselines.Furthermore,the distributed nature of the algorithm ensures scalability and flexibility,making it well-suited for future large-scale 6G deployments.The results highlighted that AI-enabled UAV systems enhance connectivity,support ultra-reliable low-latency communications(URLLC),and improve 6G network efficiency.Future work will extend the framework with adaptive modulation,beamforming-aware positioning,and real-world testbed deployment.展开更多
Against a backdrop of rising global trade protectionism and accelerated restructuring of international industrial and supply chains,regional institutional cooperation is becoming a key force in stabilizing cross-borde...Against a backdrop of rising global trade protectionism and accelerated restructuring of international industrial and supply chains,regional institutional cooperation is becoming a key force in stabilizing cross-border trade and investment.The ASEAN region enjoys strong economic growth momentum with a distinct demographic advantage while China boasts a complete industrial system and manufacturing capacity.展开更多
Spartina alterniflora invasions seriously threaten the structure and functions of coastal wetlands in China.In this study,the Suaeda salsa community in the Yellow River Estuary wetland was monitored using long-term La...Spartina alterniflora invasions seriously threaten the structure and functions of coastal wetlands in China.In this study,the Suaeda salsa community in the Yellow River Estuary wetland was monitored using long-term Landsat satellite images acquired from 1997 to 2020 to quantify the impact of changes in hydrological connectivity induced by S.alterniflora on neighboring vegetation com-munities.The results showed that S.alterniflora rapidly expanded in the estuary area at a rate of 4.91 km^(2)/yr from 2010 to 2020.At the same time,the hydrological connectivity of the area and the distribution of S.salsa changed significantly.Small tidal creeks dominated the S.alterniflora landscape.The number of tidal creeks increased significantly,but their average length decreased and they tended to develop in a horizontal tree-like pattern.Affected by the changes in hydrological connectivity due to the S.alterniflora invasion,the area of S.salsa decreased by 41.1%,and the degree of landscape fragmentation increased from 1997 to 2020.Variations in the Largest Patch Index(LPI)indicated that the S.alterniflora landscape had become the dominant landscape type in the Yellow River Estuary.The res-ults of standard deviation ellipse(SDE)and Pearson’s correlation analyses indicated that a well-developed hydrological connectivity could promote the maintenance of the S.salsa landscape.The degradation of most S.salsa communities is caused by the influence of S.alterniflora on the morphological characteristics of the hydrological connectivity of tidal creek systems.展开更多
During oilfield development,a comprehensive model for assessing inter-well connectivity and connected volume within reservoirs is crucial.Traditional capacitance(TC)models,widely used in inter-well data analysis,face ...During oilfield development,a comprehensive model for assessing inter-well connectivity and connected volume within reservoirs is crucial.Traditional capacitance(TC)models,widely used in inter-well data analysis,face challenges when dealing with rapidly changing reservoir conditions over time.Additionally,TC models struggle with complex,random noise primarily caused by measurement errors in production and injection rates.To address these challenges,this study introduces a dynamic capacitance(SV-DC)model based on state variables.By integrating the extended Kalman filter(EKF)algorithm,the SV-DC model provides more flexible predictions of inter-well connectivity and time-lag efficiency compared to the TC model.The robustness of the SV-DC model is verified by comparing relative errors between preset and calculated values through Monte Carlo simulations.Sensitivity analysis was performed to compare the model performance with the benchmark,using the Qinhuangdao Oilfield as a case study.The results show that the SV-DC model accurately predicts water breakthrough times.Increases in the liquid production index and water cut in two typical wells indicate the development time of ineffective circulation channels,further confirming the accuracy and reliability of the model.The SV-DC model offers significant advantages in addressing complex,dynamic oilfield production scenarios and serves as a valuable tool for the efficient and precise planning and management of future oilfield developments.展开更多
Infrastructure and energy are two important areas for African countries to achieve sustainable development,as well as are among the priorities in the African Union’s Agenda 2063,the continent’s ambitious development...Infrastructure and energy are two important areas for African countries to achieve sustainable development,as well as are among the priorities in the African Union’s Agenda 2063,the continent’s ambitious development blueprint.In February,Lerato Mataboge was elected as the African Union Commissioner for Infrastructure and Energy.She is a global policy and trade and investment facilitation expert and was the deputy director general in the South African Department of Trade,Industry and Competition when she was elected.展开更多
Background The heterogeneity of depression limits the treatment outcomes of intermittent theta burst stimulation(iTBS)and hinders the identification of predictive factors.This study investigated functional network con...Background The heterogeneity of depression limits the treatment outcomes of intermittent theta burst stimulation(iTBS)and hinders the identification of predictive factors.This study investigated functional network connectivity and predictors of iTBS treatment outcomes in adolescents and young adults with depression.Aim This study aimed to identify default mode network(DMN)-based connectivity patterns associated with varying iTBS treatment outcomes in depression.Methods Data from a randomised controlled trial of iTBS in depression(n=82)were analysed using a data-driven approach to classify homogeneous subgroups based on the DMN.Connectivity subgroups were compared on depressive symptoms and cognitive function at pretreatment and post-treatment.Furthermore,the predictive significance of baseline inflammatory cytokines on post-treatment outcomes was evaluated.Results Two distinct subgroups were identified.Subgroup 1 exhibited high heterogeneity and greater centrality in the posterior cingulate cortex and retrosplenial cortex,while subgroup 2 showed more homogeneous connectivity patterns and greater centrality in the temporoparietal junction and posterior inferior parietal lobule.No main effect for subgroup,treatment or subgroup×treatment interaction was revealed in the improvement of depressive symptoms.A significant subgroup×treatment interaction related to symbol coding improvement was detected(F=5.22,p=0.026).Within subgroup 1,the active group showed significantly greater improvement in symbol coding compared with the sham group(t=2.30,p=0.028),while baseline levels of interleukin-6 and C-reactive protein emerged as significant indicators for predicting improvements in symbolic coding(R2=0.35,RMSE(root-mean-square error)=5.72,p=0.013).Subgroup 2 showed no significant findings in terms of cognitive improvement or inflammatory cytokines predictions.展开更多
With the discovery of ultra-deepwater and ultra-shallow large natural gas reservoirs in the South China Sea,unconsolidated sandstone reservoirs have once again become a focal point of research.In response to the uncle...With the discovery of ultra-deepwater and ultra-shallow large natural gas reservoirs in the South China Sea,unconsolidated sandstone reservoirs have once again become a focal point of research.In response to the unclear controlling factors and the need for connectivity evaluation of unconsolidated sandstone reservoirs in the Ledong formation of the Lingshui A area in the Qiongdongnan Basin,this study employs a range of experimental techniques,namely,cast thin sections,scanning electron microscopy,Xray diffraction mineral analysis,laser granulometry,and nuclear magnetic resonance(NMR),to investigate the microstructural characteristics of these reservoirs.The primary objective is to elucidate the controlling mechanisms behind pore-throat variability and to identify how sedimentary factors,mineral composition,and gas hydrate occurrence modes collectively influence pore-throat structural characteristics.Guided by fractal theory,a multidimensional analysis of pore-throat modal characteristics is conducted using a combination of image analysis,mercury intrusion capillary pressure,and NMR techniques.Furthermore,connectivity evaluation factors(CEFs)are constructed based on reservoir parameters to quantitatively assess reservoir connectivity and to establish connectivity evaluation standards.Results indicate that sedimentary factors are the principal determinants of pore-throat differences in the study area.Coarse grains,low clay content,and enhanced reservoir porosity contribute to improved permeability.At the microscopic level,variations in mineral composition also play a critical role.Higher quartz content and reduced clay mineral content,particularly illite and chlorite,are associated with excellent reservoir properties.By contrast,diagenesis exhibits a limited effect on reservoir quality.The gas hydrate occurrence state is characterized as a pore suspension type,exhibiting a relatively uniform pore-throat distribution.This load-bearing hydrate type may enhance pore-throat heterogeneity.Pore-throat modes are classified into three types:bimodal,multimodalⅠ,and multimodalⅡ.The bimodal hydrate occurrence state is dominated by the pore suspension type and characterized by low sorting coefficients,reduced fractal dimensions,increased uniform pore-throat structures,and improved reservoir connectivity.Five key reservoir parameters are selected,forming the basis of the CEFs,which comprehensively characterize reservoir connectivity.Ultimately,a connectivity evaluation standard and a microscopic connectivity model for typical unconsolidated sandstones in the South China Sea are established,providing critical guidance for future reservoir development strategies.展开更多
Indonesia is facing severe congestion and high accident rates as motor vehicle growth continues to outpace road capacity,underscoring the urgent need for alternative mass transportation.A promising solution is the rea...Indonesia is facing severe congestion and high accident rates as motor vehicle growth continues to outpace road capacity,underscoring the urgent need for alternative mass transportation.A promising solution is the reactivation of the Surabaya–Madura railway,an abandoned infrastructure with significant potential to enhance regional connectivity and urban mobility.However,academic studies on railway reactivation remain limited,particularly in the Madura context where dependence on road-based transport persists.This research gap highlights the importance of examining reactivation not only as a transportation alternative but also as a catalyst for regional development.This study adopts a qualitative approach through descriptive surveys to evaluate infrastructure conditions,identify feasible routes,and analyze broader spatial implications.Findings reveal that railway reactivation could strengthen multimodal integration,reduce congestion,and support sustainable growth.This study provides the first empirical evidence of the strategic value of the Surabaya–Madura railway within Indonesia’s transport and regional development discourse.展开更多
Background:Previous studies have demonstrated the underlying neurophysiologic mechanism during general anesthesia in adults.However,the mechanism of propofol-induced moderate-deep sedation(PMDS)in modulating pediatric...Background:Previous studies have demonstrated the underlying neurophysiologic mechanism during general anesthesia in adults.However,the mechanism of propofol-induced moderate-deep sedation(PMDS)in modulating pediatric neural activity remains unknown,which therefore was investigated in the present study based on functional magnetic resonance imaging(fMRI).Methods:A total of 41 children(5.10�1.14 years,male/female 21/20)with fMRI were employed to construct the functional connectivity network(FCN).The network communication,graph-theoretic properties,and network hub identification were statistically analyzed(t test and Bonferroni correction)between sedation(21 children)and awake(20 children)groups.All involved analyses were established on the whole-brain FCN and seven sub-networks,which included the default mode network(DMN),dorsal attentional network(DAN),salience network(SAN),auditory network(AUD),visual network(VIS),subcortical network(SUB),and other networks(Other).Results:Under PMDS,significant decreases in network communication were observed between SUB-VIS,SUB-DAN,and VIS-DAN,and between brain regions from the temporal lobe,limbic system,and subcortical tissues.However,no significant decrease in thalamus-related communication was observed.Most graph-theoretic properties were significantly decreased in the sedation group,and all graphical features of the DMN showed significant group differences.The superior parietal cortex with different neurological functions was identified as a network hub that was not greatly affected.Conclusions:Although the children had a depressed level of neural activity under PMDS,the crucial thalamus-related communication was maintained,and the network hub superior parietal cortex stayed active,which highlighted clinical prac-tices that the human body under PMDS is still perceptible to external stimuli and can be awakened by sound or touch.展开更多
In this study,we systematically tested the hypothesis that during the critical developmental period of adolescence,on a macro scale,the concentrations of major excitatory and inhibitory neurotransmitters(glutamate/glu...In this study,we systematically tested the hypothesis that during the critical developmental period of adolescence,on a macro scale,the concentrations of major excitatory and inhibitory neurotransmitters(glutamate/glutamine andγ‑aminobutyric acid[GABA])in the dorsal and ventral lateral prefrontal cortex are associated with the brain’s functional connectivity and an individual’s psychopathology.Neurotransmitters were measured via magnetic resonance spectroscopy while functional connectivity was measured with resting-state fMRI(n=121).Seed-based and network-based analyses revealed associations of neurotransmitter concentrations and functional connectivities between regions/networks that are connected to prefrontal cortices via structural connections that are thought to be under dynamic development during adolescence.These regions tend to be boundary areas between functional networks.Furthermore,several connectivities were found to be associated with individual’s levels of internalizing psychopathology.These findings provide insights into specific neurochemical mechanisms underlying the brain’s macroscale functional organization,its development during adolescence,and its potential associations with symptoms associated with internalizing psychopathology.展开更多
The ability to localize sound sources rapidly allows human beings to efficiently understand the surrounding environment.Previous studies have suggested that there is an auditory“where”pathway in the cortex for proce...The ability to localize sound sources rapidly allows human beings to efficiently understand the surrounding environment.Previous studies have suggested that there is an auditory“where”pathway in the cortex for processing sound locations.The neural activation in regions along this pathway encodes sound locations by opponent hemifield coding,in which each unilateral region is activated by sounds coming from the contralateral hemifield.However,it is still unclear how these regions interact with each other to form a unified representation of the auditory space.In the present study,we investigated whether functional connectivity in the auditory“where”pathway encoded sound locations during passive listening.Participants underwent functional magnetic resonance imaging while passively listening to sounds from five distinct horizontal locations(−90°,−45°,0°,45°,90°).We were able to decode sound locations from the functional connectivity patterns of the“where”pathway.Furthermore,we found that such neural representation of sound locations was primarily based on the coding of sound lateralization angles to the frontal midline.In addition,whole-brain analysis indicated that functional connectivity between occipital regions and the primary auditory cortex also encoded sound locations by lateralization angles.Overall,our results reveal a lateralization-angle-based representation of sound locations encoded by functional connectivity patterns,which could add on the activation-based opponent hemifield coding to provide a more precise representation of the auditory space.展开更多
文摘In the Kigongo area of Mwanza Region,northwest Tanzania,fishmonger Neema Aisha remembers how the morning’s fresh catch would sour while she queued for the ferry,putting her business at risk.
基金funded in part by the Supported by Natural Science Foundation of Inner Mongolia Autonomous Region of China under Grants 2024QN06022 and 2023QN06008in part by the First-Class Discipline Research Special Project under Grant YLXKZX-NGD-015in part by the Inner Mongolia University of Technology Scientific Research Start-Up Project under Grant BS2024067.
文摘Blockchain offers a promising solution to the security challenges faced by the Internet of Vehicles(IoV).However,due to the dynamic connectivity of IoV,blockchain based on a single-chain structure or Directed Acyclic Graph(DAG)structure often suffer from performance limitations.The DAG lattice structure is a novel blockchain model in which each node maintains its own account chain,and only the node itself is allowed to update it.This feature makes the DAG lattice structure particularly suitable for addressing the challenges in dynamically connected IoV environment.In this paper,we propose a blockchain architecture based on the DAG lattice structure,specifically designed for dynamically connected IoV.In the proposed system,nodes must obtain authorization from a trusted authority before joining,forming a permissioned blockchain.Each node is assigned an individual account chain,allowing vehicles with limited storage capacity to participate in the blockchain by storing transactions only from nearby vehicles’account chains.Every transmitted message is treated as a transaction and added to the blockchain,enablingmore efficient data transmission in a dynamic network environment.Areputation-based incentivemechanism is introduced to encourage nodes to behave normally.Experimental results demonstrate that the proposed architecture achieves better performance compared with traditional single-chain and DAG-based approaches in terms of average transmission delay and storage cost.
基金Supported by Suzhou Clinical Medical Center for Mood Disorders,No.Szlcyxzx202109Suzhou Key Laboratory,No.SZS2024016Multicenter Clinical Research on Major Diseases in Suzhou,No.DZXYJ202413.
文摘BACKGROUND Suicide constitutes the second leading cause of death among adolescents globally and represents a critical public health concern.The neural mechanisms underlying suicidal behavior in adolescents with major depressive disorder(MDD)remain poorly understood.Aberrant resting-state functional connectivity(rsFC)in the amygdala,a key region implicated in emotional regulation and threat detection,is strongly implicated in depression and suicidal behavior.AIM To investigate rsFC alterations between amygdala subregions and whole-brain networks in adolescent patients with depression and suicide attempts.METHODS Resting-state functional magnetic resonance imaging data were acquired from 32 adolescents with MDD and suicide attempts(sMDD)group,33 adolescents with MDD but without suicide attempts(nsMDD)group,and 34 demographically matched healthy control(HC)group,with the lateral and medial amygdala(MeA)defined as regions of interest.The rsFC patterns of amygdala subregions were compared across the three groups,and associations between aberrant rsFC values and clinical symptom severity scores were examined.RESULTS Compared with the nsMDD group,the sMDD group exhibited reduced rsFC between the right lateral amygdala(LA)and the right inferior occipital gyrus as well as the left middle occipital gyrus.Compared with the HC group,the abnormal brain regions of rsFC in the sMDD group and nsMDD group involve the parahippocampal gyrus(PHG)and fusiform gyrus.In the sMDD group,right MeA and right temporal pole:Superior temporal gyrus rsFC value negatively correlated with the Rosenberg Self-Esteem Scale scores(r=-0.409,P=0.025),while left LA and right PHG rsFC value positively correlated with the Adolescent Self-Rating Life Events Checklist interpersonal relationship scores(r=0.372,P=0.043).CONCLUSION Aberrant rsFC changes between amygdala subregions and these brain regions provide novel insights into the underlying neural mechanisms of suicide attempts in adolescents with MDD.
基金supported in part by the National Natural Science Foundation of China under Grant 62172368the Natural Science Foundation of Zhejiang Province under Grant LR22F020003.
文摘The development of brain-computer interfaces(BCI)based on motor imagery(MI)has greatly improved patients’quality of life with movement disorders.The classification of upper limb MI has been widely studied and applied in many fields,including rehabilitation.However,the physiological representations of left and right lower limb movements are too close and activated deep in the cerebral cortex,making it difficult to distinguish their features.Therefore,classifying lower limbs motor imagery is more challenging.In this study,we propose a feature extraction method based on functional connectivity,which utilizes phase-locked values to construct a functional connectivity matrix as the features of the left and right legs,which can effectively avoid the problem of physiological representations of the left and right lower limbs being too close to each other during movement.In addition,considering the topology and the temporal characteristics of the electroencephalogram(EEG),we designed a temporal-spatial convolutional network(TSGCN)to capture the spatiotemporal information for classification.Experimental results show that the accuracy of the proposed method is higher than that of existing methods,achieving an average classification accuracy of 73.58%on the internal dataset.Finally,this study explains the network mechanism of left and right foot MI from the perspective of graph theoretic features and demonstrates the feasibility of decoding lower limb MI.
基金support through the“Trans-Disciplinary Research”Grant(No.R/Dev/IoE/TDRProjects/2023-24/61658),which played a crucial role in enabling this research endeavor.
文摘Floodplain wetlands are invaluable ecosystems providing numerous ecological benefits,yet they face a global crisis necessitating sustainable preservation efforts.This study examines the depletion of floodplain wetlands within the Hastinapur Wildlife Sanctuary(HWLS)in Uttar Pradesh.Encroachment activities such as grazing,agriculture,and human settlements have fragmented and degraded critical wetland ecosystems.Additionally,irrigation projects,dam construction,and water diversion have disrupted natural water flow and availability.To assess wetland inundation in 2023,five classification techniques were employed:Random Forest(RF),Support Vector Machine(SVM),artificial neural network(ANN),Spectral Information Divergence(SID),and Maximum Likelihood Classifier(MLC).SVM emerged as the most precise method,as determined by kappa coefficient and index-based validation.Consequently,the SVM classifier was used to model wetland inundation areas from 1983 to 2023 and analyze spatiotemporal changes and fragmentation patterns.The findings revealed that the SVM clas-sifier accurately mapped 2023 wetland areas.The modeled time-series data demonstrated a 62.55%and 38.12%reduction in inundated wetland areas over the past 40 years in the pre-and post-monsoon periods,respectively.Fragmentation analysis indicated an 86.27%decrease in large core wetland areas in the pre-monsoon period,signifying severe habitat degradation.This rapid decline in wetlands within protected areas raises concerns about their ecological impacts.By linking wetland loss to global sustainability objectives,this study underscores the global urgency for strengthened wetland protection measures and highlights the need for integrating wetland conservation into broader sustainable development goals.Effective policies and adaptive management strategies are crucial for preserving these ecosystems and their vital services,which are essential for biodiversity,climate regulation,and human well-being.
基金supported by National Natural Science Foundation of China[NO.11932013].
文摘This study aims to explore the impact of fatigue induced by different limb exercises on cerebral cortical oxygenation levels and functional connectivity strength using functional near-infrared spectroscopy(fNIRS).Fatigue was induced using an upper limb ergometer or a lower limb ergometer,with the load increasing gradually each minute.fNIRS covering the prefrontal cortex and motor cortex were used to collect data during the resting state,both before and after fatigue induction.A two-way ANOVA was conducted to examine differences in oxyhemoglobin(HbO_(2))and functional connectivity before and after fatigue induction in both groups,with the significance level set at 0.05.Exercise-induced fatigue in both the upper and lower limbs leads to a significant decrease in cerebral cortical oxygenation levels.Upper limb fatigue leads to a significant reduction in functional connectivity,there were significant decreases in connectivity within the motor cortex,between the motor cortex and frontal regions,and between the right ventrolateral prefrontal cortex and other frontal regions.Conversely,no significant changes were observed before and after lower limb fatigue.Future studies should focus on examining the extent to which how changes in the cerebral cortex,induced by exercise fatigue,are linked to exercise-and/or performance-related outcomes.
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(RS-2025-00559546)supported by the IITP(Institute of Information&Coummunications Technology Planning&Evaluation)-ITRC(Information Technology Research Center)grant funded by the Korea government(Ministry of Science and ICT)(IITP-2025-RS-2023-00259004).
文摘The advent of sixth-generation(6G)networks introduces unprecedented challenges in achieving seamless connectivity,ultra-low latency,and efficient resource management in highly dynamic environments.Although fifth-generation(5G)networks transformed mobile broadband and machine-type communications at massive scales,their properties of scaling,interference management,and latency remain a limitation in dense high mobility settings.To overcome these limitations,artificial intelligence(AI)and unmanned aerial vehicles(UAVs)have emerged as potential solutions to develop versatile,dynamic,and energy-efficient communication systems.The study proposes an AI-based UAV architecture that utilizes cooperative reinforcement learning(CoRL)to manage an autonomous network.The UAVs collaborate by sharing local observations and real-time state exchanges to optimize user connectivity,movement directions,allocate power,and resource distribution.Unlike conventional centralized or autonomous methods,CoRL involves joint state sharing and conflict-sensitive reward shaping,which ensures fair coverage,less interference,and enhanced adaptability in a dynamic urban environment.Simulations conducted in smart city scenarios with 10 UAVs and 50 ground users demonstrate that the proposed CoRL-based UAV system increases user coverage by up to 10%,achieves convergence 40%faster,and reduces latency and energy consumption by 30%compared with centralized and decentralized baselines.Furthermore,the distributed nature of the algorithm ensures scalability and flexibility,making it well-suited for future large-scale 6G deployments.The results highlighted that AI-enabled UAV systems enhance connectivity,support ultra-reliable low-latency communications(URLLC),and improve 6G network efficiency.Future work will extend the framework with adaptive modulation,beamforming-aware positioning,and real-world testbed deployment.
文摘Against a backdrop of rising global trade protectionism and accelerated restructuring of international industrial and supply chains,regional institutional cooperation is becoming a key force in stabilizing cross-border trade and investment.The ASEAN region enjoys strong economic growth momentum with a distinct demographic advantage while China boasts a complete industrial system and manufacturing capacity.
基金Under the auspices of Key Program of the National Natural Science Foundation of China(No.U2006215,U1806218)the National Key R&D Program of China(No.2017YFC0505902)。
文摘Spartina alterniflora invasions seriously threaten the structure and functions of coastal wetlands in China.In this study,the Suaeda salsa community in the Yellow River Estuary wetland was monitored using long-term Landsat satellite images acquired from 1997 to 2020 to quantify the impact of changes in hydrological connectivity induced by S.alterniflora on neighboring vegetation com-munities.The results showed that S.alterniflora rapidly expanded in the estuary area at a rate of 4.91 km^(2)/yr from 2010 to 2020.At the same time,the hydrological connectivity of the area and the distribution of S.salsa changed significantly.Small tidal creeks dominated the S.alterniflora landscape.The number of tidal creeks increased significantly,but their average length decreased and they tended to develop in a horizontal tree-like pattern.Affected by the changes in hydrological connectivity due to the S.alterniflora invasion,the area of S.salsa decreased by 41.1%,and the degree of landscape fragmentation increased from 1997 to 2020.Variations in the Largest Patch Index(LPI)indicated that the S.alterniflora landscape had become the dominant landscape type in the Yellow River Estuary.The res-ults of standard deviation ellipse(SDE)and Pearson’s correlation analyses indicated that a well-developed hydrological connectivity could promote the maintenance of the S.salsa landscape.The degradation of most S.salsa communities is caused by the influence of S.alterniflora on the morphological characteristics of the hydrological connectivity of tidal creek systems.
基金the National Natural Science Foundation of China(Grant No.52374051)the Joint Fund for Enterprise Innovation and Development of NSFC(Grant No.U24B2037).
文摘During oilfield development,a comprehensive model for assessing inter-well connectivity and connected volume within reservoirs is crucial.Traditional capacitance(TC)models,widely used in inter-well data analysis,face challenges when dealing with rapidly changing reservoir conditions over time.Additionally,TC models struggle with complex,random noise primarily caused by measurement errors in production and injection rates.To address these challenges,this study introduces a dynamic capacitance(SV-DC)model based on state variables.By integrating the extended Kalman filter(EKF)algorithm,the SV-DC model provides more flexible predictions of inter-well connectivity and time-lag efficiency compared to the TC model.The robustness of the SV-DC model is verified by comparing relative errors between preset and calculated values through Monte Carlo simulations.Sensitivity analysis was performed to compare the model performance with the benchmark,using the Qinhuangdao Oilfield as a case study.The results show that the SV-DC model accurately predicts water breakthrough times.Increases in the liquid production index and water cut in two typical wells indicate the development time of ineffective circulation channels,further confirming the accuracy and reliability of the model.The SV-DC model offers significant advantages in addressing complex,dynamic oilfield production scenarios and serves as a valuable tool for the efficient and precise planning and management of future oilfield developments.
文摘Infrastructure and energy are two important areas for African countries to achieve sustainable development,as well as are among the priorities in the African Union’s Agenda 2063,the continent’s ambitious development blueprint.In February,Lerato Mataboge was elected as the African Union Commissioner for Infrastructure and Energy.She is a global policy and trade and investment facilitation expert and was the deputy director general in the South African Department of Trade,Industry and Competition when she was elected.
基金supported by the Guangzhou Municipal Key Discipline in Medicine(2021-2023)the Guangzhou High-level Clinical Key Specialty,the Guangzhou Research-oriented Hospital,the Innovative Clinical Technique of Guangzhou(2024-2026)+6 种基金the Guangdong Basic and Applied Basic Research Foundation(grant number 2022A1515011567,2020A1515110565)the Guangzhou Science,Technology Planning Project(grant number 202201010714,202103000032)the National Natural Science Foundation of China(grant number 82471546)the Guangdong College Students Innovation and Entrepreneurship Training Project(grant number S202310570038)the Guangzhou Health Science and Technology Project(grant number 20231A010038)the Guangzhou Traditional Chinese Medicine and Integrated Traditional Chinese and Western Medicine Technology Project(grant number:20232A010013)the Science and Technology Plan Project of Guangzhou(2023A03J0842).
文摘Background The heterogeneity of depression limits the treatment outcomes of intermittent theta burst stimulation(iTBS)and hinders the identification of predictive factors.This study investigated functional network connectivity and predictors of iTBS treatment outcomes in adolescents and young adults with depression.Aim This study aimed to identify default mode network(DMN)-based connectivity patterns associated with varying iTBS treatment outcomes in depression.Methods Data from a randomised controlled trial of iTBS in depression(n=82)were analysed using a data-driven approach to classify homogeneous subgroups based on the DMN.Connectivity subgroups were compared on depressive symptoms and cognitive function at pretreatment and post-treatment.Furthermore,the predictive significance of baseline inflammatory cytokines on post-treatment outcomes was evaluated.Results Two distinct subgroups were identified.Subgroup 1 exhibited high heterogeneity and greater centrality in the posterior cingulate cortex and retrosplenial cortex,while subgroup 2 showed more homogeneous connectivity patterns and greater centrality in the temporoparietal junction and posterior inferior parietal lobule.No main effect for subgroup,treatment or subgroup×treatment interaction was revealed in the improvement of depressive symptoms.A significant subgroup×treatment interaction related to symbol coding improvement was detected(F=5.22,p=0.026).Within subgroup 1,the active group showed significantly greater improvement in symbol coding compared with the sham group(t=2.30,p=0.028),while baseline levels of interleukin-6 and C-reactive protein emerged as significant indicators for predicting improvements in symbolic coding(R2=0.35,RMSE(root-mean-square error)=5.72,p=0.013).Subgroup 2 showed no significant findings in terms of cognitive improvement or inflammatory cytokines predictions.
基金Program‘Geological Reservoir Digital Analogy Study Based on Exploration and Development Data Lake’(No.KJZH2024-2903)。
文摘With the discovery of ultra-deepwater and ultra-shallow large natural gas reservoirs in the South China Sea,unconsolidated sandstone reservoirs have once again become a focal point of research.In response to the unclear controlling factors and the need for connectivity evaluation of unconsolidated sandstone reservoirs in the Ledong formation of the Lingshui A area in the Qiongdongnan Basin,this study employs a range of experimental techniques,namely,cast thin sections,scanning electron microscopy,Xray diffraction mineral analysis,laser granulometry,and nuclear magnetic resonance(NMR),to investigate the microstructural characteristics of these reservoirs.The primary objective is to elucidate the controlling mechanisms behind pore-throat variability and to identify how sedimentary factors,mineral composition,and gas hydrate occurrence modes collectively influence pore-throat structural characteristics.Guided by fractal theory,a multidimensional analysis of pore-throat modal characteristics is conducted using a combination of image analysis,mercury intrusion capillary pressure,and NMR techniques.Furthermore,connectivity evaluation factors(CEFs)are constructed based on reservoir parameters to quantitatively assess reservoir connectivity and to establish connectivity evaluation standards.Results indicate that sedimentary factors are the principal determinants of pore-throat differences in the study area.Coarse grains,low clay content,and enhanced reservoir porosity contribute to improved permeability.At the microscopic level,variations in mineral composition also play a critical role.Higher quartz content and reduced clay mineral content,particularly illite and chlorite,are associated with excellent reservoir properties.By contrast,diagenesis exhibits a limited effect on reservoir quality.The gas hydrate occurrence state is characterized as a pore suspension type,exhibiting a relatively uniform pore-throat distribution.This load-bearing hydrate type may enhance pore-throat heterogeneity.Pore-throat modes are classified into three types:bimodal,multimodalⅠ,and multimodalⅡ.The bimodal hydrate occurrence state is dominated by the pore suspension type and characterized by low sorting coefficients,reduced fractal dimensions,increased uniform pore-throat structures,and improved reservoir connectivity.Five key reservoir parameters are selected,forming the basis of the CEFs,which comprehensively characterize reservoir connectivity.Ultimately,a connectivity evaluation standard and a microscopic connectivity model for typical unconsolidated sandstones in the South China Sea are established,providing critical guidance for future reservoir development strategies.
文摘Indonesia is facing severe congestion and high accident rates as motor vehicle growth continues to outpace road capacity,underscoring the urgent need for alternative mass transportation.A promising solution is the reactivation of the Surabaya–Madura railway,an abandoned infrastructure with significant potential to enhance regional connectivity and urban mobility.However,academic studies on railway reactivation remain limited,particularly in the Madura context where dependence on road-based transport persists.This research gap highlights the importance of examining reactivation not only as a transportation alternative but also as a catalyst for regional development.This study adopts a qualitative approach through descriptive surveys to evaluate infrastructure conditions,identify feasible routes,and analyze broader spatial implications.Findings reveal that railway reactivation could strengthen multimodal integration,reduce congestion,and support sustainable growth.This study provides the first empirical evidence of the strategic value of the Surabaya–Madura railway within Indonesia’s transport and regional development discourse.
基金supported by the Natural Science Foundation of Shandong Province,ZR2024MH072Open Project of Key Laboratory of Medical Imaging and Artificial Intelligence of Hunan Province,Xiangnan University,YXZN2022002+2 种基金Projects of Xiamen Scientific and Technological Plan,3502Z20199096 and 3502Z20209220the National Natural Science Foundation of China,61802330the Yantai City Science and Technology Innovation Development Plan,2023XDRH006.
文摘Background:Previous studies have demonstrated the underlying neurophysiologic mechanism during general anesthesia in adults.However,the mechanism of propofol-induced moderate-deep sedation(PMDS)in modulating pediatric neural activity remains unknown,which therefore was investigated in the present study based on functional magnetic resonance imaging(fMRI).Methods:A total of 41 children(5.10�1.14 years,male/female 21/20)with fMRI were employed to construct the functional connectivity network(FCN).The network communication,graph-theoretic properties,and network hub identification were statistically analyzed(t test and Bonferroni correction)between sedation(21 children)and awake(20 children)groups.All involved analyses were established on the whole-brain FCN and seven sub-networks,which included the default mode network(DMN),dorsal attentional network(DAN),salience network(SAN),auditory network(AUD),visual network(VIS),subcortical network(SUB),and other networks(Other).Results:Under PMDS,significant decreases in network communication were observed between SUB-VIS,SUB-DAN,and VIS-DAN,and between brain regions from the temporal lobe,limbic system,and subcortical tissues.However,no significant decrease in thalamus-related communication was observed.Most graph-theoretic properties were significantly decreased in the sedation group,and all graphical features of the DMN showed significant group differences.The superior parietal cortex with different neurological functions was identified as a network hub that was not greatly affected.Conclusions:Although the children had a depressed level of neural activity under PMDS,the crucial thalamus-related communication was maintained,and the network hub superior parietal cortex stayed active,which highlighted clinical prac-tices that the human body under PMDS is still perceptible to external stimuli and can be awakened by sound or touch.
基金supported by NIMH grant R01105501(PI:MTB and BLK).
文摘In this study,we systematically tested the hypothesis that during the critical developmental period of adolescence,on a macro scale,the concentrations of major excitatory and inhibitory neurotransmitters(glutamate/glutamine andγ‑aminobutyric acid[GABA])in the dorsal and ventral lateral prefrontal cortex are associated with the brain’s functional connectivity and an individual’s psychopathology.Neurotransmitters were measured via magnetic resonance spectroscopy while functional connectivity was measured with resting-state fMRI(n=121).Seed-based and network-based analyses revealed associations of neurotransmitter concentrations and functional connectivities between regions/networks that are connected to prefrontal cortices via structural connections that are thought to be under dynamic development during adolescence.These regions tend to be boundary areas between functional networks.Furthermore,several connectivities were found to be associated with individual’s levels of internalizing psychopathology.These findings provide insights into specific neurochemical mechanisms underlying the brain’s macroscale functional organization,its development during adolescence,and its potential associations with symptoms associated with internalizing psychopathology.
基金supported by the National Key Research and Development Program of China(2023YFF1203502)the National Natural Science Foundation of China(62171300,62301343,and 62394314)+1 种基金the Project of Cultivation for Young Top-Notch Talents of Beijing Municipal Institutions(BPHR202203109)the Capital Medical University Research and Development Fund(PYZ22027).
文摘The ability to localize sound sources rapidly allows human beings to efficiently understand the surrounding environment.Previous studies have suggested that there is an auditory“where”pathway in the cortex for processing sound locations.The neural activation in regions along this pathway encodes sound locations by opponent hemifield coding,in which each unilateral region is activated by sounds coming from the contralateral hemifield.However,it is still unclear how these regions interact with each other to form a unified representation of the auditory space.In the present study,we investigated whether functional connectivity in the auditory“where”pathway encoded sound locations during passive listening.Participants underwent functional magnetic resonance imaging while passively listening to sounds from five distinct horizontal locations(−90°,−45°,0°,45°,90°).We were able to decode sound locations from the functional connectivity patterns of the“where”pathway.Furthermore,we found that such neural representation of sound locations was primarily based on the coding of sound lateralization angles to the frontal midline.In addition,whole-brain analysis indicated that functional connectivity between occipital regions and the primary auditory cortex also encoded sound locations by lateralization angles.Overall,our results reveal a lateralization-angle-based representation of sound locations encoded by functional connectivity patterns,which could add on the activation-based opponent hemifield coding to provide a more precise representation of the auditory space.
