BACKGROUND Return to work(RTW)and resumption of driving(ROD)are critical factors that influence postoperative quality of life in patients undergoing total hip arthroplasty(THA).However,few studies have focused on the ...BACKGROUND Return to work(RTW)and resumption of driving(ROD)are critical factors that influence postoperative quality of life in patients undergoing total hip arthroplasty(THA).However,few studies have focused on the minimally invasive(MIS)approach and its effect on these outcomes.AIM To investigate RTW and ROD's timelines and influencing factors following anterior MIS-THA.METHODS A retrospective analysis was conducted on 124 patients who underwent anterior MIS-THA.Data on the demographics,occupational physical demands,and RTW/ROD timelines were also collected.Clinical outcomes were measured using standardised scoring systems.Statistical analyses were performed to evaluate the differences between the groups based on employment status and physical workload.RESULTS Among employed patients,the RTW rate was 94.7%,with an average return time of five weeks.The average ROD time was 3.5 weeks across all patients.Despite similar postoperative clinical scores,RTW time was significantly influenced by occupations'physical workload,with heavier physical demands associated with delayed RTW.CONCLUSION Anterior MIS-THA facilitates early RTW and ROD,particularly in occupations with lower physical demands.These findings highlight the importance of considering occupational and physical workload in postoperative care planning to optimize recovery outcomes.展开更多
Trajectory prediction is a critical task in autonomous driving systems.It enables vehicles to anticipate the future movements of surrounding traffic participants,which facilitates safe and human-like decision-making i...Trajectory prediction is a critical task in autonomous driving systems.It enables vehicles to anticipate the future movements of surrounding traffic participants,which facilitates safe and human-like decision-making in the planning and control layers.However,most existing approaches rely on end-to-end deep learning architectures that overlook the influence of driving style on trajectory prediction.These methods often lack explicit modeling of semantic driving behavior and effective interaction mechanisms,leading to potentially unrealistic predictions.To address these limitations,we propose the Driving Style Guided Trajectory Prediction framework(DSG-TP),which incorporates a probabilistic representation of driving style into trajectory prediction.Our approach enhances the model’s ability to interact with vehicle behavior characteristics in complex traffic scenarios,significantly improving prediction reliability in critical decision-making situations by incorporating the driving style recognition module.Experimental evaluations on the Argoverse 1 dataset demonstrate that our method outperforms existing approaches in both prediction accuracy and computational efficiency.Through extensive ablation studies,we further validate the contribution of each module to overall performance.Notably,in decision-sensitive scenarios,DSG-TP more accurately captures vehicle behavior patterns and generates trajectory predictions that align with different driving styles,providing crucial support for safe decision-making in autonomous driving systems.展开更多
This study focuses on the spatiotemporal distribution,urban-rural variations,and driving factors of ammonia Vertical Column Densities(VCDs)in China’s Yangtze River Delta region(YRD)from 2008 to 2020.Utilizing data fr...This study focuses on the spatiotemporal distribution,urban-rural variations,and driving factors of ammonia Vertical Column Densities(VCDs)in China’s Yangtze River Delta region(YRD)from 2008 to 2020.Utilizing data from the Infrared Atmospheric Sounding Interfer-ometer(IASI),Generalized Additive Models(GAM),and the GEOS-Chem chemical transport model,we observed a significant increase of NH_(3)VCDs in the YRD between 2014 and 2020.The spatial distribution analysis revealed higher NH_(3)concentrations in the northern part of the YRD region,primarily due to lower precipitation,alkaline soil,and intensive agricul-tural activities.NH_(3)VCDs in the YRD region increased significantly(65.18%)from 2008 to 2020.The highest growth rate occurs in the summer,with an annual average growth rate of 7.2%during the period from 2014 to 2020.Agricultural emissions dominated NH_(3)VCDs during spring and summer,with high concentrations primarily located in the agricultural areas adjacent to densely populated urban zones.Regions within several large urban areas have been discovered to exhibit relatively stable variations in NH_(3)VCDs.The rise in NH_(3)VCDs within the YRD region was primarily driven by the reduction of acidic gases like SO_(2),as emphasized by GAM modeling and sensitivity tests using the GEOS-Chem model.The concentration changes of acidic gases contribute to over 80%of the interannual variations in NH_(3)VCDs.This emphasizes the crucial role of environmental policies targeting the reduction of these acidic gases.Effective emission control is urgent tomitigate environmental hazards and secondary particulate matter,especially in the northern YRD.展开更多
Studying the coupling coordination development of new energy vehicles(NEVs)and the ecological environment in China is helpful in promoting the development of NEVs in the country and is of great significance in promoti...Studying the coupling coordination development of new energy vehicles(NEVs)and the ecological environment in China is helpful in promoting the development of NEVs in the country and is of great significance in promoting high-quality development of new energy in China.This paper constructs an evaluation index system for the development of NEVs and the ecological environment.It uses game theory combining weighting model,particle swarm optimized projection tracking evaluation model,coupling coordination degree model,and machine learning algorithms to calculate and analyze the level of coupling coordination development of NEVs and the ecological environment in China from 2010 to 2021,and identifies the driving factors.The research results show that:(i)From 2010 to 2021,the development index of NEVs in China has steadily increased from 0.085 to 0.634,while the ecological environment level index significantly rose from 0.170 to 0.884,reflecting the continuous development of China in both NEVs and the ecological environment.(ii)From 2010 to 2012,the two systems—new energy vehicle(NEV)development and the ecological environment—were in a period of imbalance and decline.From 2013 to 2016,they underwent a transition period,and from 2017 to 2021,they entered a period of coordinated development showing a trend of benign and continuous improvement.By 2021,they reached a good level of coordination.(iii)Indicators such as the number of patents granted for NEVs,water consumption per unit of GDP,and energy consumption per unit of GDP are the main driving factors affecting the coupling coordination development of NEVs and the ecological environment in China.展开更多
The scientific assessment of ecosystem ser-vice value(ESV)plays a critical role in regional ecologi-cal protection and management,rational land use planning,and the establishment of ecological security barriers.The ec...The scientific assessment of ecosystem ser-vice value(ESV)plays a critical role in regional ecologi-cal protection and management,rational land use planning,and the establishment of ecological security barriers.The ecosystem service value of the Northeast Forest Belt from 2005 to 2020 was assessed,focusing on spatial–temporal changes and the driving forces behind these dynamics.Using multi-source data,the equivalent factor method,and geo-graphic detectors,we analyzed natural and socio-economic factors affecting the region.which was crucial for effective ecological conservation and land-use planning.Enhanced the effectiveness of policy formulation and land use plan-ning.The results show that the ESV of the Northeast Forest Belt exhibits an overall increasing trend from 2005 to 2020,with forests and wetlands contributing the most.However,there are significant differences between forest belts.Driven by natural and socio-economic factors,the ESV of forest belts in Heilongjiang and Jilin provinces showed significant growth.In contrast,the ESV of Forest Belts in Liaoning and Inner Mongolia of China remains relatively stable,but the spatial differentiation within these regions is characterized by significant clustering of high-value and low-value areas.Furthermore,climate regulation and hydrological regulation services were identified as the most important ecological functions in the Northeast Forest Belt,contributing greatly to regional ecological stability and human well-being.The ESV in the Northeast Forest Belt is improved during the study period,but the stability of the ecosystem is still chal-lenged by the dual impacts of natural and socio-economic factors.To further optimize regional land use planning and ecological protection policies,it is recommended to prior-itize the conservation of high-ESV areas,enhance ecological restoration efforts for wetlands and forests,and reasonably control the spatial layout of urban expansion and agricul-tural development.Additionally,this study highlights the importance of tailored ecological compensation policies and strategic land-use planning to balance environmental protec-tion and economic growth.展开更多
Amid ongoing global environmental change and the critical pursuit of sustainable development,human-environment systems are exhibiting increasingly complex dynamic evolutions and spatial relationships,underscoring an u...Amid ongoing global environmental change and the critical pursuit of sustainable development,human-environment systems are exhibiting increasingly complex dynamic evolutions and spatial relationships,underscoring an urgent need for innovative research frameworks.Integrated geography synthesizes physical geography,human geography,and geographic information science,providing key frameworks for understanding complex human-environment systems.This editorial proposes an emerging research framework for integrated geography—“Composite driving-System evolution-Coupling mechanism-Synergistic regulation(CSCS)”—based on key issues such as climate change,biodiversity loss,resource scarcity,and social-ecological interactions,which have been highlighted in both recent critical literature on human-environment systems and UN assessment reports.The framework starts with diverse composite driving forces,extends to the evolution of human-environment system structures,processes,and functions that these drivers induce,explores couplings within human-environment systems,and calls for regulation aimed at sustainable development in synergies.Major research frontiers include understanding the cascading“evolution-coupling”effects of shocks;measuring system resilience,thresholds,and safe and just operating space boundaries;clarifying linkage mechanisms across scales;and achieving synergistic outcomes for multi-objective sustainability.This framework will help promote the interdisciplinary integration and development of integrated geography,and provide geographical solutions for the global sustainable development agenda.展开更多
In recent years,the country has spent significant workforce and material resources to prevent traffic accidents,particularly those caused by fatigued driving.The current studies mainly concentrate on driver physiologi...In recent years,the country has spent significant workforce and material resources to prevent traffic accidents,particularly those caused by fatigued driving.The current studies mainly concentrate on driver physiological signals,driving behavior,and vehicle information.However,most of the approaches are computationally intensive and inconvenient for real-time detection.Therefore,this paper designs a network that combines precision,speed and lightweight and proposes an algorithm for facial fatigue detection based on multi-feature fusion.Specifically,the face detection model takes YOLOv8(You Only Look Once version 8)as the basic framework,and replaces its backbone network with MobileNetv3.To focus on the significant regions in the image,CPCA(Channel Prior Convolution Attention)is adopted to enhance the network’s capacity for feature extraction.Meanwhile,the network training phase employs the Focal-EIOU(Focal and Efficient Intersection Over Union)loss function,which makes the network lightweight and increases the accuracy of target detection.Ultimately,the Dlib toolkit was employed to annotate 68 facial feature points.This study established an evaluation metric for facial fatigue and developed a novel fatigue detection algorithm to assess the driver’s condition.A series of comparative experiments were carried out on the self-built dataset.The suggested method’s mAP(mean Average Precision)values for object detection and fatigue detection are 96.71%and 95.75%,respectively,as well as the detection speed is 47 FPS(Frames Per Second).This method can balance the contradiction between computational complexity and model accuracy.Furthermore,it can be transplanted to NVIDIA Jetson Orin NX and quickly detect the driver’s state while maintaining a high degree of accuracy.It contributes to the development of automobile safety systems and reduces the occurrence of traffic accidents.展开更多
Seagrass beds are crucial coastal ecosystems,functioning as vital blue carbon sinks and natural ecological barriers.However,these ecosystems are increasingly threatened by global climate events,coastal development,and...Seagrass beds are crucial coastal ecosystems,functioning as vital blue carbon sinks and natural ecological barriers.However,these ecosystems are increasingly threatened by global climate events,coastal development,and water eutrophication,making them some of the most endangered ecosystems worldwide.In the Yellow Sea and Bohai Sea regions,seagrass bed assessment and monitoring have been largely overlooked.Thus,strengthening research efforts is necessary to identify current distribution patterns and long-term changes in seagrass bed resources.This study focused on a seagrass bed in Sanggou Bay,Rongcheng,using remote sensing(RS)and geographic information system technologies to analyze multisource satellite data from the US Landsat and Chinese resource satellite series.By combining RS indexes with historical survey data,large-scale temporal and geographic distribution data for seagrass beds were obtained in the study area from 1985 to 2022.The spatial distribution and evolution trends of the seagrass bed were analyzed using a water depth inversion model,and the factors driving its degradation were identified.Results indicated that the seagrass bed area in Sanggou Bay fluctuated between 100 and 140 km^(2) from 1985 to 2010.During 2010–2013,dynamic changes in the seagrass bed area increased,with a considerable decrease in its overall size.After 2014,changes were minimal,indicating a notably stable state.Seagrass bed degradation in Sanggou Bay is influenced by high-intensity human activities,pollution from coastal land sources,raft cultures,underwater terrain conditions,and sedimentary environmental factors.The findings offer essential insights for developing seagrass restoration and protection strategies in Sanggou Bay and contribute to the broader scientific efforts for coastal ecosystem conservation and rehabilitation.展开更多
Ensuring that autonomous vehicles maintain high precision and rapid response capabilities in complex and dynamic driving environments is a critical challenge in the field of autonomous driving.This study aims to enhan...Ensuring that autonomous vehicles maintain high precision and rapid response capabilities in complex and dynamic driving environments is a critical challenge in the field of autonomous driving.This study aims to enhance the learning efficiency ofmulti-sensor feature fusion in autonomous driving tasks,thereby improving the safety and responsiveness of the system.To achieve this goal,we propose an innovative multi-sensor feature fusion model that integrates three distinct modalities:visual,radar,and lidar data.The model optimizes the feature fusion process through the introduction of two novel mechanisms:Sparse Channel Pooling(SCP)and Residual Triplet-Attention(RTA).Firstly,the SCP mechanism enables the model to adaptively filter out salient feature channels while eliminating the interference of redundant features.This enhances the model’s emphasis on critical features essential for decisionmaking and strengthens its robustness to environmental variability.Secondly,the RTA mechanism addresses the issue of feature misalignment across different modalities by effectively aligning key cross-modal features.This alignment reduces the computational overhead associated with redundant features and enhances the overall efficiency of the system.Furthermore,this study incorporates a reinforcement learning module designed to optimize strategies within a continuous action space.By integrating thismodulewith the feature fusion learning process,the entire system is capable of learning efficient driving strategies in an end-to-end manner within the CARLA autonomous driving simulator.Experimental results demonstrate that the proposedmodel significantly enhances the perception and decision-making accuracy of the autonomous driving system in complex traffic scenarios while maintaining real-time responsiveness.This work provides a novel perspective and technical pathway for the application of multi-sensor data fusion in autonomous driving.展开更多
Remote driving,an emergent technology enabling remote operations of vehicles,presents a significant challenge in transmitting large volumes of image data to a central server.This requirement outpaces the capacity of t...Remote driving,an emergent technology enabling remote operations of vehicles,presents a significant challenge in transmitting large volumes of image data to a central server.This requirement outpaces the capacity of traditional communication methods.To tackle this,we propose a novel framework using semantic communications,through a region of interest semantic segmentation method,to reduce the communication costs by transmitting meaningful semantic information rather than bit-wise data.To solve the knowledge base inconsistencies inherent in semantic communications,we introduce a blockchain-based edge-assisted system for managing diverse and geographically varied semantic segmentation knowledge bases.This system not only ensures the security of data through the tamper-resistant nature of blockchain but also leverages edge computing for efficient management.Additionally,the implementation of blockchain sharding handles differentiated knowledge bases for various tasks,thus boosting overall blockchain efficiency.Experimental results show a great reduction in latency by sharding and an increase in model accuracy,confirming our framework's effectiveness.展开更多
Purpose–In recent years,the rapid advancement of artificial intelligence(AI)has exerted profound impacts on and provided strong impetus to numerous fields in the industrial sector.Within the railway industry,AI has d...Purpose–In recent years,the rapid advancement of artificial intelligence(AI)has exerted profound impacts on and provided strong impetus to numerous fields in the industrial sector.Within the railway industry,AI has driven continuous upgrading and optimization of intelligent train control technology,thanks to its enhanced computational capabilities derived from advanced algorithms and models,as well as its role in improving safety performance.Integrating AI technology more extensively into train autonomous driving and control has thus become an inevitable trend in the global development of railways.Design/methodology/approach–This paper,therefore,conducts a comprehensive analysis of the development progress and current status of AI technology applications in the field of train driving and control on a global scale.It systematically sorts out and analyzes the advantages of various AI technologies and the positive impacts they bring to the upgrading of train control technology,elucidates the feasibility and future prospects of applying a range of emerging AI technologies from the perspective of technical theory and provides guidance for the intelligent development of this field from a practical perspective.Findings–The application of AI technology in the train driving and control field is still in its infancy.While a large number of AI technologies have been widely adopted,there remains significant room for further optimization and improvement of these technologies.Additionally,a variety of AI technologies that have been applied in other industrial sectors but not yet widely implemented in training autonomous driving and control have demonstrated tremendous development potential.Originality/value–The research findings provide references and guidance for advancing train control technology,promoting the digital transformation of railways,accelerating the overall optimization and upgrading of railway industry technologies,and facilitating the accelerated development of global railways.展开更多
Congestion control is an inherent challenge of V2X(Vehicle to Everything)technologies.Due to the use of a broadcasting mechanism,channel congestion becomes severe with the increase in vehicle density.The researchers s...Congestion control is an inherent challenge of V2X(Vehicle to Everything)technologies.Due to the use of a broadcasting mechanism,channel congestion becomes severe with the increase in vehicle density.The researchers suggested reducing the frequency of packet dissemination to relieve congestion,which caused a rise in road driving risk.Obviously,high-risk vehicles should be able to send messages timely to alarm surrounding vehicles.Therefore,packet dissemination frequency should be set according to the corresponding vehicle’s risk level,which is hard to evaluate.In this paper,a two-stage fuzzy inference model is constructed to evaluate a vehicle’s risk level,while a congestion control algorithm DRG-DCC(Driving Risk Game-Distributed Congestion Control)is proposed.Moreover,HPSO is employed to find optimal solutions.The simulation results show that the proposed method adjusts the transmission frequency based on driving risk,effectively striking a balance between transmission delay and channel busy rate.展开更多
0 INTRODUCTION.The Asian drylands,encompassing the northern East Asian monsoon region(NMA),the westerlies-dominated arid central Asia(ACA)and arid west Asia(AWA),are ecologically fragile areas and among the most sensi...0 INTRODUCTION.The Asian drylands,encompassing the northern East Asian monsoon region(NMA),the westerlies-dominated arid central Asia(ACA)and arid west Asia(AWA),are ecologically fragile areas and among the most sensitive regions to global change.These regions are significant dust sources of the Northern Hemisphere(e.g.,Uno et al.,2009),playing a vital role in global climate change and marine biogeochemical cycles.展开更多
The exploration of the coupling and coordination between urban innovation capability(IC)and industrial transformation(IF)serves as a novel perspective for interpreting the increasingly severe phenomenon of population ...The exploration of the coupling and coordination between urban innovation capability(IC)and industrial transformation(IF)serves as a novel perspective for interpreting the increasingly severe phenomenon of population shrinkage during the industrialization process.This study investigated the evolutionary characteristics of IC and IF in shrinking and growing cities in Northeast China from 2010 to 2020.It uses entropy weighted model,coupling coordination degree,the Dagum Gini coefficient,and geographic detectors to analyze the coordinated development of IC and IF in the context of population shrinkage.The study analyzed the spatiotemporal patterns and driving mechanisms for their coordinated development.The results show that:1)both urban IC and IF exhibited an overall positive trend during the study period.Shrinking cities depend more on IF to address the challenges of population shrinkage,while growing cities mainly rely on innovation-driven development.2)The coupling gap between IC and IF in shrinking and growing cities has widened over time,with the coordination level of shrinking cities steadily decreasing.Cities with serious disorder are concentrated in northern Heilongjiang Province,while most cities in Jilin Province experience moderate disorder.Liaoning Province,however,shows generally good coupling coordination.3)Human capital is the key factor driving coupling coordination in both types of cities.Shrinking cities rely on economic and financial development,with the‘repair-type’logic that emphasizes short-term economic growth and resource compensation.In contrast,the coupling of growing cities relies on basic support capabilities,with the‘optimization-type’logic focused on enhancing endogenous resilience and systemic coordination.Exploring the coordination between urban innovation capabilities and industrial transformation can provide a new perspective for research on population shrinkage,which holds certain theoretical and practical significance for implementing the new round of revitalization strategy in Northeast China.展开更多
BACKGROUND Acute respiratory distress syndrome(ARDS)is a critical condition characterized by acute hypoxemia,non-cardiogenic pulmonary edema,and decreased lung compliance.The Berlin definition,updated in 2012,classifi...BACKGROUND Acute respiratory distress syndrome(ARDS)is a critical condition characterized by acute hypoxemia,non-cardiogenic pulmonary edema,and decreased lung compliance.The Berlin definition,updated in 2012,classifies ARDS severity based on the partial pressure of arterial oxygen/fractional inspired oxygen fraction ratio.Despite various treatment strategies,ARDS remains a significant public health concern with high mortality rates.AIM To evaluate the implications of driving pressure(DP)in ARDS management and its potential as a protective lung strategy.METHODS We conducted a systematic review using databases including EbscoHost,MEDLINE,CINAHL,PubMed,and Google Scholar.The search was limited to articles published between January 2015 and September 2024.Twenty-three peer-reviewed articles were selected based on inclusion criteria focusing on adult ARDS patients undergoing mechanical ventilation and DP strategies.The literature review was conducted and reported according to PRISMA 2020 guidelines.RESULTS DP,the difference between plateau pressure and positive end-expiratory pressure,is crucial in ARDS management.Studies indicate that lower DP levels are significantly associated with improved survival rates in ARDS patients.DP is a better predictor of mortality than tidal volume or positive end-expiratory pressure alone.Adjusting DP by optimizing lung compliance and minimizing overdistension and collapse can reduce ventilator-induced lung injury.CONCLUSION DP is a valuable parameter in ARDS management,offering a more precise measure of lung stress and strain than traditional metrics.Implementing DP as a threshold for safety can enhance protective ventilation strategies,po-tentially reducing mortality in ARDS patients.Further research is needed to refine DP measurement techniques and validate its clinical application in diverse patient populations.展开更多
This article takes the current autonomous driving technology as the research background and studies the collaborative protection mechanism between its system-on-chip(SoC)functional safety and information security.It i...This article takes the current autonomous driving technology as the research background and studies the collaborative protection mechanism between its system-on-chip(SoC)functional safety and information security.It includes an introduction to the functions and information security of autonomous driving SoCs,as well as the main design strategies for the collaborative prevention and control mechanism of SoC functional safety and information security in autonomous driving.The research shows that in the field of autonomous driving,there is a close connection between the functional safety of SoCs and their information security.In the design of the safety collaborative protection mechanism,the overall collaborative protection architecture,SoC functional safety protection mechanism,information security protection mechanism,the workflow of the collaborative protection mechanism,and its strategies are all key design elements.It is hoped that this analysis can provide some references for the collaborative protection of SoC functional safety and information security in the field of autonomous driving,so as to improve the safety of autonomous driving technology and meet its practical application requirements.展开更多
Scientifically understanding the evolution of urbanization and analysing the coupling mechanism of human-land systems are important foundations for solving spatial conflicts and promoting regional sustainable developm...Scientifically understanding the evolution of urbanization and analysing the coupling mechanism of human-land systems are important foundations for solving spatial conflicts and promoting regional sustainable development.This study analyzed the spatiotemporal evolution and landscape pattern change of construction land in the Yangtze River Delta(YRD)region from 1990 to 2018 by integrating Geographical Information System(GIS)spatial analysis and landscape pattern indices,and revealed its driving mechanism by XGBoost and SHapley Additive ex Planations(SHAP).Moreover,we compared the disparities in the core driving factors for construction land evolution in cities with diverse development orientations within the YRD region.Results show that:1)development intensity of construction land continued to increase from 7.54%in 1990 to 13.44%in 2018,primarily by occupying farmland.The landscape fragmentation of construction land in the YRD region decreased,and landscape dominance increased.Spatially,the eastern part of the YRD exhibits a high degree of spatial agglomeration of construction land,whereas the western part shows a high degree of fragmentation,revealing distinct spatial gradient differentiation characteristics.The landscape dominance of the construction land in the eastern region of the YRD is higher than that in the western and northern regions.2)Transportation and infrastructure exert the highest contribution rate on development intensity changes of construction land in the YRD.The industrial structure significantly influences the conversion of farmland to construction land.Additionally,infrastructure plays a crucial role in shaping the spatial agglomeration patterns of construction land.Population distribution is the dominant factor determining the regularity of the landscape shape of construction land.3)The core driving factors for the development intensity of construction land in central cities primarily lies in transportation,whereas for non-central cities,besides transportation,the year-end balance of per capita savings deposits of urban and rural residents also play a significant role.The area change of construction land occupying farmland in central and non-central cities is mainly driven by industrial structure and economic level,respectively.This study informs refined spatial optimization and regional high-quality integrated development.展开更多
As a major worldwide issue,desertification poses significant threats to ecosystem stability and long-term socioeconomic growth.Within China,the Mu Us Sandy land represents a crucial region for studying desertification...As a major worldwide issue,desertification poses significant threats to ecosystem stability and long-term socioeconomic growth.Within China,the Mu Us Sandy land represents a crucial region for studying desertification phenomena.Comprehending how desertification risks are distributed spatially and what mechanisms drive them remains fundamental for implementing effective strategies in land management and risk mitigation.Our research evaluated desertification vulnerability across the Mu Us Sandy land by applying the MEDALUS model,while investigating causal factors via geographical detector methodology.Findings indicated that territories with high desertification vulnerability extend across 71,401.7 km^(2),constituting 76.87%of the entire region,while zones facing extreme desertification hazard cover 20,578.9 km^(2)(22.16%),primarily concentrated in a band-like pattern along the western boundary of the Mu Us Sandy land.Among the four primary indicators,management quality emerged as the most significant driver of desertification susceptibility,followed by vegetation quality and soil quality.Additionally,drought resistance,land use intensity,and erosion protection were identified as the key factors driving desertification sensitivity.The investigation offers significant theoretical perspectives that can guide the formulation of enhanced strategies for controlling desertification and promoting sustainable land resource utilization within the Mu Us Sandy land region.展开更多
To enhance the recuperation rate of the mine and comply with the stipulations of green mining technology, it is vital to expeditiously recuperate the coal pillar resources in the final stage, thus preventing the consi...To enhance the recuperation rate of the mine and comply with the stipulations of green mining technology, it is vital to expeditiously recuperate the coal pillar resources in the final stage, thus preventing the considerable squandering of resources. The coal pillar resource of the main roadway and its branch roadway constitutes a significant recovery subject. Its coal pillar shape is regular and possesses a considerable strike distance, facilitating the arrangement of the coal pillar recovery working face (CPRWF) for mining operations. However, for the remaining coal pillars with a thick and hard roof (THF) and multiple tectonic zones, CPRWF encounters challenges in selecting an appropriate layout, managing excessive roof pressure, and predicting mining stress. Aiming at the roadway coal pillar group with THF and multi-structural areas in specific projects, a method of constructing multi-stage CPRWF by one side gob-side entry driving (GSED) and one side roadway reusing is proposed. Through theoretical calculation of roof fracture and numerical simulation verification, combined with field engineering experience and economic analysis, the width of the narrow coal pillar (NCP) in the GSED is determined to be 10 m and the length of the CPRWF is 65 m. Concurrently, the potential safety hazard that the roof will fall asymmetrically and THF is difficult to break during CPRWF mining after GSED is analyzed and verified. Then, a control method involving the pre-cutting of the roof in the reused roadway before mining is proposed. This method has been shown to facilitate the complete collapse of THF, reduce the degree of mine pressure, and facilitate the symmetrical breaking of the roof. Accordingly, a roof-cutting scheme based on a directional drilling rig, bidirectional shaped polyvinyl chloride (PVC) pipe, and emulsion explosive was devised, and the pre-splitting of 8.2 m THF was accomplished. Field observations indicate that directional cracks are evident in the roof, the coal wall is flat during CPRWF mining, and the overall level of mining pressure is within the control range. Therefore, the combined application of GSED and roof-cutting technology for coal pillar recovery has been successfully implemented, thereby providing new insights and engineering references for the construction and pressure relief mining of CPRWF.展开更多
Sustainable development,underpinned by robust systemic driving forces,is central to the growth of high-quality tourism.Therefore,identifying these forces at the regional level is crucial for advancing China’s goal of...Sustainable development,underpinned by robust systemic driving forces,is central to the growth of high-quality tourism.Therefore,identifying these forces at the regional level is crucial for advancing China’s goal of becoming a leading nation for tourism.This study accordingly constructs a new evaluation system that covers tourism market demand,industry supply,and structural transformation,and analyzes data from 31 Chinese provincial regions(2010–2019).The entropy method and spatial autocorrelation analysis were applied to examine the driving forces for sustainable regional tourism development.The results revealed that:First,at the national level,the driving forces for sustainable regional tourism development exhibited a clear upward trend from 2010 to 2019,with an acceleration in growth after 2015.However,there was significant regional heterogeneity:The eastern region displayed the highest levels of driving forces,followed by the central and western regions.Second,high-value clusters of these driving forces expanded from the eastern to the western regions,while the central provinces remained relatively balanced.Specifically,provincial regions such as Guangdong,Beijing,and Zhejiang were able to successively enter the high-value clusters,whereas the Xinjiang Uygur autonomous region,Gansu,and Qinghai consistently remained in the low-value clusters.Third,the driving forces exhibited a significant spatial agglomeration effect.The degree of clustering followed an inverted“U”trend over the study period,while the spatial patterns of the provincial regions remained relatively stable.展开更多
基金approved by the Institutional Ethics Committee of Shizuoka Red Cross Hospital(No.2023-36,approval date:January 12,2024).
文摘BACKGROUND Return to work(RTW)and resumption of driving(ROD)are critical factors that influence postoperative quality of life in patients undergoing total hip arthroplasty(THA).However,few studies have focused on the minimally invasive(MIS)approach and its effect on these outcomes.AIM To investigate RTW and ROD's timelines and influencing factors following anterior MIS-THA.METHODS A retrospective analysis was conducted on 124 patients who underwent anterior MIS-THA.Data on the demographics,occupational physical demands,and RTW/ROD timelines were also collected.Clinical outcomes were measured using standardised scoring systems.Statistical analyses were performed to evaluate the differences between the groups based on employment status and physical workload.RESULTS Among employed patients,the RTW rate was 94.7%,with an average return time of five weeks.The average ROD time was 3.5 weeks across all patients.Despite similar postoperative clinical scores,RTW time was significantly influenced by occupations'physical workload,with heavier physical demands associated with delayed RTW.CONCLUSION Anterior MIS-THA facilitates early RTW and ROD,particularly in occupations with lower physical demands.These findings highlight the importance of considering occupational and physical workload in postoperative care planning to optimize recovery outcomes.
基金supported in part by the National Natural Science Foundation of China(NSFC)under Grant No.52267003.
文摘Trajectory prediction is a critical task in autonomous driving systems.It enables vehicles to anticipate the future movements of surrounding traffic participants,which facilitates safe and human-like decision-making in the planning and control layers.However,most existing approaches rely on end-to-end deep learning architectures that overlook the influence of driving style on trajectory prediction.These methods often lack explicit modeling of semantic driving behavior and effective interaction mechanisms,leading to potentially unrealistic predictions.To address these limitations,we propose the Driving Style Guided Trajectory Prediction framework(DSG-TP),which incorporates a probabilistic representation of driving style into trajectory prediction.Our approach enhances the model’s ability to interact with vehicle behavior characteristics in complex traffic scenarios,significantly improving prediction reliability in critical decision-making situations by incorporating the driving style recognition module.Experimental evaluations on the Argoverse 1 dataset demonstrate that our method outperforms existing approaches in both prediction accuracy and computational efficiency.Through extensive ablation studies,we further validate the contribution of each module to overall performance.Notably,in decision-sensitive scenarios,DSG-TP more accurately captures vehicle behavior patterns and generates trajectory predictions that align with different driving styles,providing crucial support for safe decision-making in autonomous driving systems.
基金supported by the Joint Funds of the National Natural Science Foundation of China(No.U21A2027)the New Cornerstone Science Foundation through the XPLORER PRIZE(2023-1033).
文摘This study focuses on the spatiotemporal distribution,urban-rural variations,and driving factors of ammonia Vertical Column Densities(VCDs)in China’s Yangtze River Delta region(YRD)from 2008 to 2020.Utilizing data from the Infrared Atmospheric Sounding Interfer-ometer(IASI),Generalized Additive Models(GAM),and the GEOS-Chem chemical transport model,we observed a significant increase of NH_(3)VCDs in the YRD between 2014 and 2020.The spatial distribution analysis revealed higher NH_(3)concentrations in the northern part of the YRD region,primarily due to lower precipitation,alkaline soil,and intensive agricul-tural activities.NH_(3)VCDs in the YRD region increased significantly(65.18%)from 2008 to 2020.The highest growth rate occurs in the summer,with an annual average growth rate of 7.2%during the period from 2014 to 2020.Agricultural emissions dominated NH_(3)VCDs during spring and summer,with high concentrations primarily located in the agricultural areas adjacent to densely populated urban zones.Regions within several large urban areas have been discovered to exhibit relatively stable variations in NH_(3)VCDs.The rise in NH_(3)VCDs within the YRD region was primarily driven by the reduction of acidic gases like SO_(2),as emphasized by GAM modeling and sensitivity tests using the GEOS-Chem model.The concentration changes of acidic gases contribute to over 80%of the interannual variations in NH_(3)VCDs.This emphasizes the crucial role of environmental policies targeting the reduction of these acidic gases.Effective emission control is urgent tomitigate environmental hazards and secondary particulate matter,especially in the northern YRD.
基金Supported by the Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX24_0102)the China Scholarship Council Program(202406190114)。
文摘Studying the coupling coordination development of new energy vehicles(NEVs)and the ecological environment in China is helpful in promoting the development of NEVs in the country and is of great significance in promoting high-quality development of new energy in China.This paper constructs an evaluation index system for the development of NEVs and the ecological environment.It uses game theory combining weighting model,particle swarm optimized projection tracking evaluation model,coupling coordination degree model,and machine learning algorithms to calculate and analyze the level of coupling coordination development of NEVs and the ecological environment in China from 2010 to 2021,and identifies the driving factors.The research results show that:(i)From 2010 to 2021,the development index of NEVs in China has steadily increased from 0.085 to 0.634,while the ecological environment level index significantly rose from 0.170 to 0.884,reflecting the continuous development of China in both NEVs and the ecological environment.(ii)From 2010 to 2012,the two systems—new energy vehicle(NEV)development and the ecological environment—were in a period of imbalance and decline.From 2013 to 2016,they underwent a transition period,and from 2017 to 2021,they entered a period of coordinated development showing a trend of benign and continuous improvement.By 2021,they reached a good level of coordination.(iii)Indicators such as the number of patents granted for NEVs,water consumption per unit of GDP,and energy consumption per unit of GDP are the main driving factors affecting the coupling coordination development of NEVs and the ecological environment in China.
基金funded by the Central University D Project(HFW230600022)National Natural Science Foundation of China(71973021)+1 种基金National Natural Science Foundation Youth Funding Project(72003022)Heilongjiang Province University Think Tank Open Topic(ZKKF2022173).
文摘The scientific assessment of ecosystem ser-vice value(ESV)plays a critical role in regional ecologi-cal protection and management,rational land use planning,and the establishment of ecological security barriers.The ecosystem service value of the Northeast Forest Belt from 2005 to 2020 was assessed,focusing on spatial–temporal changes and the driving forces behind these dynamics.Using multi-source data,the equivalent factor method,and geo-graphic detectors,we analyzed natural and socio-economic factors affecting the region.which was crucial for effective ecological conservation and land-use planning.Enhanced the effectiveness of policy formulation and land use plan-ning.The results show that the ESV of the Northeast Forest Belt exhibits an overall increasing trend from 2005 to 2020,with forests and wetlands contributing the most.However,there are significant differences between forest belts.Driven by natural and socio-economic factors,the ESV of forest belts in Heilongjiang and Jilin provinces showed significant growth.In contrast,the ESV of Forest Belts in Liaoning and Inner Mongolia of China remains relatively stable,but the spatial differentiation within these regions is characterized by significant clustering of high-value and low-value areas.Furthermore,climate regulation and hydrological regulation services were identified as the most important ecological functions in the Northeast Forest Belt,contributing greatly to regional ecological stability and human well-being.The ESV in the Northeast Forest Belt is improved during the study period,but the stability of the ecosystem is still chal-lenged by the dual impacts of natural and socio-economic factors.To further optimize regional land use planning and ecological protection policies,it is recommended to prior-itize the conservation of high-ESV areas,enhance ecological restoration efforts for wetlands and forests,and reasonably control the spatial layout of urban expansion and agricul-tural development.Additionally,this study highlights the importance of tailored ecological compensation policies and strategic land-use planning to balance environmental protec-tion and economic growth.
基金supported by the National Natural Science Foundation of China(Grants No.W2412144,42271292)the 111 project,and the Fundamental Research Funds for the Central Universities of China.
文摘Amid ongoing global environmental change and the critical pursuit of sustainable development,human-environment systems are exhibiting increasingly complex dynamic evolutions and spatial relationships,underscoring an urgent need for innovative research frameworks.Integrated geography synthesizes physical geography,human geography,and geographic information science,providing key frameworks for understanding complex human-environment systems.This editorial proposes an emerging research framework for integrated geography—“Composite driving-System evolution-Coupling mechanism-Synergistic regulation(CSCS)”—based on key issues such as climate change,biodiversity loss,resource scarcity,and social-ecological interactions,which have been highlighted in both recent critical literature on human-environment systems and UN assessment reports.The framework starts with diverse composite driving forces,extends to the evolution of human-environment system structures,processes,and functions that these drivers induce,explores couplings within human-environment systems,and calls for regulation aimed at sustainable development in synergies.Major research frontiers include understanding the cascading“evolution-coupling”effects of shocks;measuring system resilience,thresholds,and safe and just operating space boundaries;clarifying linkage mechanisms across scales;and achieving synergistic outcomes for multi-objective sustainability.This framework will help promote the interdisciplinary integration and development of integrated geography,and provide geographical solutions for the global sustainable development agenda.
基金supported by the Science and Technology Bureau of Xi’an project(24KGDW0049)the Key Research and Development Programof Shaanxi(2023-YBGY-264)the Key Research and Development Program of Guangxi(GK-AB20159032).
文摘In recent years,the country has spent significant workforce and material resources to prevent traffic accidents,particularly those caused by fatigued driving.The current studies mainly concentrate on driver physiological signals,driving behavior,and vehicle information.However,most of the approaches are computationally intensive and inconvenient for real-time detection.Therefore,this paper designs a network that combines precision,speed and lightweight and proposes an algorithm for facial fatigue detection based on multi-feature fusion.Specifically,the face detection model takes YOLOv8(You Only Look Once version 8)as the basic framework,and replaces its backbone network with MobileNetv3.To focus on the significant regions in the image,CPCA(Channel Prior Convolution Attention)is adopted to enhance the network’s capacity for feature extraction.Meanwhile,the network training phase employs the Focal-EIOU(Focal and Efficient Intersection Over Union)loss function,which makes the network lightweight and increases the accuracy of target detection.Ultimately,the Dlib toolkit was employed to annotate 68 facial feature points.This study established an evaluation metric for facial fatigue and developed a novel fatigue detection algorithm to assess the driver’s condition.A series of comparative experiments were carried out on the self-built dataset.The suggested method’s mAP(mean Average Precision)values for object detection and fatigue detection are 96.71%and 95.75%,respectively,as well as the detection speed is 47 FPS(Frames Per Second).This method can balance the contradiction between computational complexity and model accuracy.Furthermore,it can be transplanted to NVIDIA Jetson Orin NX and quickly detect the driver’s state while maintaining a high degree of accuracy.It contributes to the development of automobile safety systems and reduces the occurrence of traffic accidents.
基金supported by the Marine S&T Fund of Shandong Province for Pilot National Laboratory for Marine Science and Technology(Qingdao)(No.2022QNLM 050302-4)the Geological Survey Project of the China Geological Survey(No.DD20230071)+1 种基金the China Geological Survey Project‘Investigation and Monitoring of the Coastal Geological Environment of the Yangtze River Estuary’(No.DD20242714)the cooperation fund of Collaborative Research on Marine Geological Environment and Hazards in the Yangtze River Delta and Red River Delta.
文摘Seagrass beds are crucial coastal ecosystems,functioning as vital blue carbon sinks and natural ecological barriers.However,these ecosystems are increasingly threatened by global climate events,coastal development,and water eutrophication,making them some of the most endangered ecosystems worldwide.In the Yellow Sea and Bohai Sea regions,seagrass bed assessment and monitoring have been largely overlooked.Thus,strengthening research efforts is necessary to identify current distribution patterns and long-term changes in seagrass bed resources.This study focused on a seagrass bed in Sanggou Bay,Rongcheng,using remote sensing(RS)and geographic information system technologies to analyze multisource satellite data from the US Landsat and Chinese resource satellite series.By combining RS indexes with historical survey data,large-scale temporal and geographic distribution data for seagrass beds were obtained in the study area from 1985 to 2022.The spatial distribution and evolution trends of the seagrass bed were analyzed using a water depth inversion model,and the factors driving its degradation were identified.Results indicated that the seagrass bed area in Sanggou Bay fluctuated between 100 and 140 km^(2) from 1985 to 2010.During 2010–2013,dynamic changes in the seagrass bed area increased,with a considerable decrease in its overall size.After 2014,changes were minimal,indicating a notably stable state.Seagrass bed degradation in Sanggou Bay is influenced by high-intensity human activities,pollution from coastal land sources,raft cultures,underwater terrain conditions,and sedimentary environmental factors.The findings offer essential insights for developing seagrass restoration and protection strategies in Sanggou Bay and contribute to the broader scientific efforts for coastal ecosystem conservation and rehabilitation.
文摘Ensuring that autonomous vehicles maintain high precision and rapid response capabilities in complex and dynamic driving environments is a critical challenge in the field of autonomous driving.This study aims to enhance the learning efficiency ofmulti-sensor feature fusion in autonomous driving tasks,thereby improving the safety and responsiveness of the system.To achieve this goal,we propose an innovative multi-sensor feature fusion model that integrates three distinct modalities:visual,radar,and lidar data.The model optimizes the feature fusion process through the introduction of two novel mechanisms:Sparse Channel Pooling(SCP)and Residual Triplet-Attention(RTA).Firstly,the SCP mechanism enables the model to adaptively filter out salient feature channels while eliminating the interference of redundant features.This enhances the model’s emphasis on critical features essential for decisionmaking and strengthens its robustness to environmental variability.Secondly,the RTA mechanism addresses the issue of feature misalignment across different modalities by effectively aligning key cross-modal features.This alignment reduces the computational overhead associated with redundant features and enhances the overall efficiency of the system.Furthermore,this study incorporates a reinforcement learning module designed to optimize strategies within a continuous action space.By integrating thismodulewith the feature fusion learning process,the entire system is capable of learning efficient driving strategies in an end-to-end manner within the CARLA autonomous driving simulator.Experimental results demonstrate that the proposedmodel significantly enhances the perception and decision-making accuracy of the autonomous driving system in complex traffic scenarios while maintaining real-time responsiveness.This work provides a novel perspective and technical pathway for the application of multi-sensor data fusion in autonomous driving.
基金supported in part by the National Natural Science Foundation of China under Grant No.62062031in part by the MIC/SCOPE#JP235006102+2 种基金in part by JST ASPIRE Grant Number JPMJAP2325in part by ROIS NII Open Collaborative Research under Grant 24S0601in part by collaborative research with Toyota Motor Corporation,Japan。
文摘Remote driving,an emergent technology enabling remote operations of vehicles,presents a significant challenge in transmitting large volumes of image data to a central server.This requirement outpaces the capacity of traditional communication methods.To tackle this,we propose a novel framework using semantic communications,through a region of interest semantic segmentation method,to reduce the communication costs by transmitting meaningful semantic information rather than bit-wise data.To solve the knowledge base inconsistencies inherent in semantic communications,we introduce a blockchain-based edge-assisted system for managing diverse and geographically varied semantic segmentation knowledge bases.This system not only ensures the security of data through the tamper-resistant nature of blockchain but also leverages edge computing for efficient management.Additionally,the implementation of blockchain sharding handles differentiated knowledge bases for various tasks,thus boosting overall blockchain efficiency.Experimental results show a great reduction in latency by sharding and an increase in model accuracy,confirming our framework's effectiveness.
文摘Purpose–In recent years,the rapid advancement of artificial intelligence(AI)has exerted profound impacts on and provided strong impetus to numerous fields in the industrial sector.Within the railway industry,AI has driven continuous upgrading and optimization of intelligent train control technology,thanks to its enhanced computational capabilities derived from advanced algorithms and models,as well as its role in improving safety performance.Integrating AI technology more extensively into train autonomous driving and control has thus become an inevitable trend in the global development of railways.Design/methodology/approach–This paper,therefore,conducts a comprehensive analysis of the development progress and current status of AI technology applications in the field of train driving and control on a global scale.It systematically sorts out and analyzes the advantages of various AI technologies and the positive impacts they bring to the upgrading of train control technology,elucidates the feasibility and future prospects of applying a range of emerging AI technologies from the perspective of technical theory and provides guidance for the intelligent development of this field from a practical perspective.Findings–The application of AI technology in the train driving and control field is still in its infancy.While a large number of AI technologies have been widely adopted,there remains significant room for further optimization and improvement of these technologies.Additionally,a variety of AI technologies that have been applied in other industrial sectors but not yet widely implemented in training autonomous driving and control have demonstrated tremendous development potential.Originality/value–The research findings provide references and guidance for advancing train control technology,promoting the digital transformation of railways,accelerating the overall optimization and upgrading of railway industry technologies,and facilitating the accelerated development of global railways.
基金supported by the special key project of Chongqing Technology Innovation and Application Development under Grant No.cstc2021jscx-gksbX0057the Special Major Project of Chongqing Technology Innovation and Application Development under Grant No.CSTB2022TIADSTX0003.
文摘Congestion control is an inherent challenge of V2X(Vehicle to Everything)technologies.Due to the use of a broadcasting mechanism,channel congestion becomes severe with the increase in vehicle density.The researchers suggested reducing the frequency of packet dissemination to relieve congestion,which caused a rise in road driving risk.Obviously,high-risk vehicles should be able to send messages timely to alarm surrounding vehicles.Therefore,packet dissemination frequency should be set according to the corresponding vehicle’s risk level,which is hard to evaluate.In this paper,a two-stage fuzzy inference model is constructed to evaluate a vehicle’s risk level,while a congestion control algorithm DRG-DCC(Driving Risk Game-Distributed Congestion Control)is proposed.Moreover,HPSO is employed to find optimal solutions.The simulation results show that the proposed method adjusts the transmission frequency based on driving risk,effectively striking a balance between transmission delay and channel busy rate.
基金supported by the National Natural Science Foundation of China(Nos.42261144670,423B2103)。
文摘0 INTRODUCTION.The Asian drylands,encompassing the northern East Asian monsoon region(NMA),the westerlies-dominated arid central Asia(ACA)and arid west Asia(AWA),are ecologically fragile areas and among the most sensitive regions to global change.These regions are significant dust sources of the Northern Hemisphere(e.g.,Uno et al.,2009),playing a vital role in global climate change and marine biogeochemical cycles.
基金Under the auspices of National Natural Science Foundation of China(No.42471227,42171198)。
文摘The exploration of the coupling and coordination between urban innovation capability(IC)and industrial transformation(IF)serves as a novel perspective for interpreting the increasingly severe phenomenon of population shrinkage during the industrialization process.This study investigated the evolutionary characteristics of IC and IF in shrinking and growing cities in Northeast China from 2010 to 2020.It uses entropy weighted model,coupling coordination degree,the Dagum Gini coefficient,and geographic detectors to analyze the coordinated development of IC and IF in the context of population shrinkage.The study analyzed the spatiotemporal patterns and driving mechanisms for their coordinated development.The results show that:1)both urban IC and IF exhibited an overall positive trend during the study period.Shrinking cities depend more on IF to address the challenges of population shrinkage,while growing cities mainly rely on innovation-driven development.2)The coupling gap between IC and IF in shrinking and growing cities has widened over time,with the coordination level of shrinking cities steadily decreasing.Cities with serious disorder are concentrated in northern Heilongjiang Province,while most cities in Jilin Province experience moderate disorder.Liaoning Province,however,shows generally good coupling coordination.3)Human capital is the key factor driving coupling coordination in both types of cities.Shrinking cities rely on economic and financial development,with the‘repair-type’logic that emphasizes short-term economic growth and resource compensation.In contrast,the coupling of growing cities relies on basic support capabilities,with the‘optimization-type’logic focused on enhancing endogenous resilience and systemic coordination.Exploring the coordination between urban innovation capabilities and industrial transformation can provide a new perspective for research on population shrinkage,which holds certain theoretical and practical significance for implementing the new round of revitalization strategy in Northeast China.
文摘BACKGROUND Acute respiratory distress syndrome(ARDS)is a critical condition characterized by acute hypoxemia,non-cardiogenic pulmonary edema,and decreased lung compliance.The Berlin definition,updated in 2012,classifies ARDS severity based on the partial pressure of arterial oxygen/fractional inspired oxygen fraction ratio.Despite various treatment strategies,ARDS remains a significant public health concern with high mortality rates.AIM To evaluate the implications of driving pressure(DP)in ARDS management and its potential as a protective lung strategy.METHODS We conducted a systematic review using databases including EbscoHost,MEDLINE,CINAHL,PubMed,and Google Scholar.The search was limited to articles published between January 2015 and September 2024.Twenty-three peer-reviewed articles were selected based on inclusion criteria focusing on adult ARDS patients undergoing mechanical ventilation and DP strategies.The literature review was conducted and reported according to PRISMA 2020 guidelines.RESULTS DP,the difference between plateau pressure and positive end-expiratory pressure,is crucial in ARDS management.Studies indicate that lower DP levels are significantly associated with improved survival rates in ARDS patients.DP is a better predictor of mortality than tidal volume or positive end-expiratory pressure alone.Adjusting DP by optimizing lung compliance and minimizing overdistension and collapse can reduce ventilator-induced lung injury.CONCLUSION DP is a valuable parameter in ARDS management,offering a more precise measure of lung stress and strain than traditional metrics.Implementing DP as a threshold for safety can enhance protective ventilation strategies,po-tentially reducing mortality in ARDS patients.Further research is needed to refine DP measurement techniques and validate its clinical application in diverse patient populations.
文摘This article takes the current autonomous driving technology as the research background and studies the collaborative protection mechanism between its system-on-chip(SoC)functional safety and information security.It includes an introduction to the functions and information security of autonomous driving SoCs,as well as the main design strategies for the collaborative prevention and control mechanism of SoC functional safety and information security in autonomous driving.The research shows that in the field of autonomous driving,there is a close connection between the functional safety of SoCs and their information security.In the design of the safety collaborative protection mechanism,the overall collaborative protection architecture,SoC functional safety protection mechanism,information security protection mechanism,the workflow of the collaborative protection mechanism,and its strategies are all key design elements.It is hoped that this analysis can provide some references for the collaborative protection of SoC functional safety and information security in the field of autonomous driving,so as to improve the safety of autonomous driving technology and meet its practical application requirements.
基金Under the auspices of the National Natural Science Foundation of China(No.42301470,42171389)。
文摘Scientifically understanding the evolution of urbanization and analysing the coupling mechanism of human-land systems are important foundations for solving spatial conflicts and promoting regional sustainable development.This study analyzed the spatiotemporal evolution and landscape pattern change of construction land in the Yangtze River Delta(YRD)region from 1990 to 2018 by integrating Geographical Information System(GIS)spatial analysis and landscape pattern indices,and revealed its driving mechanism by XGBoost and SHapley Additive ex Planations(SHAP).Moreover,we compared the disparities in the core driving factors for construction land evolution in cities with diverse development orientations within the YRD region.Results show that:1)development intensity of construction land continued to increase from 7.54%in 1990 to 13.44%in 2018,primarily by occupying farmland.The landscape fragmentation of construction land in the YRD region decreased,and landscape dominance increased.Spatially,the eastern part of the YRD exhibits a high degree of spatial agglomeration of construction land,whereas the western part shows a high degree of fragmentation,revealing distinct spatial gradient differentiation characteristics.The landscape dominance of the construction land in the eastern region of the YRD is higher than that in the western and northern regions.2)Transportation and infrastructure exert the highest contribution rate on development intensity changes of construction land in the YRD.The industrial structure significantly influences the conversion of farmland to construction land.Additionally,infrastructure plays a crucial role in shaping the spatial agglomeration patterns of construction land.Population distribution is the dominant factor determining the regularity of the landscape shape of construction land.3)The core driving factors for the development intensity of construction land in central cities primarily lies in transportation,whereas for non-central cities,besides transportation,the year-end balance of per capita savings deposits of urban and rural residents also play a significant role.The area change of construction land occupying farmland in central and non-central cities is mainly driven by industrial structure and economic level,respectively.This study informs refined spatial optimization and regional high-quality integrated development.
基金the National Natural Science Foundation of China(Grant No.42301336)the Open Research Fund of Henan Provincial Key Laboratory of Hydrosphere and Watershed Water Security(Grant No.HWWSF202302).
文摘As a major worldwide issue,desertification poses significant threats to ecosystem stability and long-term socioeconomic growth.Within China,the Mu Us Sandy land represents a crucial region for studying desertification phenomena.Comprehending how desertification risks are distributed spatially and what mechanisms drive them remains fundamental for implementing effective strategies in land management and risk mitigation.Our research evaluated desertification vulnerability across the Mu Us Sandy land by applying the MEDALUS model,while investigating causal factors via geographical detector methodology.Findings indicated that territories with high desertification vulnerability extend across 71,401.7 km^(2),constituting 76.87%of the entire region,while zones facing extreme desertification hazard cover 20,578.9 km^(2)(22.16%),primarily concentrated in a band-like pattern along the western boundary of the Mu Us Sandy land.Among the four primary indicators,management quality emerged as the most significant driver of desertification susceptibility,followed by vegetation quality and soil quality.Additionally,drought resistance,land use intensity,and erosion protection were identified as the key factors driving desertification sensitivity.The investigation offers significant theoretical perspectives that can guide the formulation of enhanced strategies for controlling desertification and promoting sustainable land resource utilization within the Mu Us Sandy land region.
基金Project(52204164) supported by the National Natural Science Foundation of ChinaProject(2023ZKPYSB01) supported by the Fundamental Research Funds for the Central Universities,China。
文摘To enhance the recuperation rate of the mine and comply with the stipulations of green mining technology, it is vital to expeditiously recuperate the coal pillar resources in the final stage, thus preventing the considerable squandering of resources. The coal pillar resource of the main roadway and its branch roadway constitutes a significant recovery subject. Its coal pillar shape is regular and possesses a considerable strike distance, facilitating the arrangement of the coal pillar recovery working face (CPRWF) for mining operations. However, for the remaining coal pillars with a thick and hard roof (THF) and multiple tectonic zones, CPRWF encounters challenges in selecting an appropriate layout, managing excessive roof pressure, and predicting mining stress. Aiming at the roadway coal pillar group with THF and multi-structural areas in specific projects, a method of constructing multi-stage CPRWF by one side gob-side entry driving (GSED) and one side roadway reusing is proposed. Through theoretical calculation of roof fracture and numerical simulation verification, combined with field engineering experience and economic analysis, the width of the narrow coal pillar (NCP) in the GSED is determined to be 10 m and the length of the CPRWF is 65 m. Concurrently, the potential safety hazard that the roof will fall asymmetrically and THF is difficult to break during CPRWF mining after GSED is analyzed and verified. Then, a control method involving the pre-cutting of the roof in the reused roadway before mining is proposed. This method has been shown to facilitate the complete collapse of THF, reduce the degree of mine pressure, and facilitate the symmetrical breaking of the roof. Accordingly, a roof-cutting scheme based on a directional drilling rig, bidirectional shaped polyvinyl chloride (PVC) pipe, and emulsion explosive was devised, and the pre-splitting of 8.2 m THF was accomplished. Field observations indicate that directional cracks are evident in the roof, the coal wall is flat during CPRWF mining, and the overall level of mining pressure is within the control range. Therefore, the combined application of GSED and roof-cutting technology for coal pillar recovery has been successfully implemented, thereby providing new insights and engineering references for the construction and pressure relief mining of CPRWF.
基金funded by the Ministry of Education’s Humanities and Social Sciences Research Planning Project(23YJA790070).
文摘Sustainable development,underpinned by robust systemic driving forces,is central to the growth of high-quality tourism.Therefore,identifying these forces at the regional level is crucial for advancing China’s goal of becoming a leading nation for tourism.This study accordingly constructs a new evaluation system that covers tourism market demand,industry supply,and structural transformation,and analyzes data from 31 Chinese provincial regions(2010–2019).The entropy method and spatial autocorrelation analysis were applied to examine the driving forces for sustainable regional tourism development.The results revealed that:First,at the national level,the driving forces for sustainable regional tourism development exhibited a clear upward trend from 2010 to 2019,with an acceleration in growth after 2015.However,there was significant regional heterogeneity:The eastern region displayed the highest levels of driving forces,followed by the central and western regions.Second,high-value clusters of these driving forces expanded from the eastern to the western regions,while the central provinces remained relatively balanced.Specifically,provincial regions such as Guangdong,Beijing,and Zhejiang were able to successively enter the high-value clusters,whereas the Xinjiang Uygur autonomous region,Gansu,and Qinghai consistently remained in the low-value clusters.Third,the driving forces exhibited a significant spatial agglomeration effect.The degree of clustering followed an inverted“U”trend over the study period,while the spatial patterns of the provincial regions remained relatively stable.
