To synergistically recover alumina and alkali from red mud(RM),the structural stability and conversion mechanism of hydroandradite(HA)from hydrogarnet(HG)were investigated via the First-principles,XRF,XRD,PSD and SEM ...To synergistically recover alumina and alkali from red mud(RM),the structural stability and conversion mechanism of hydroandradite(HA)from hydrogarnet(HG)were investigated via the First-principles,XRF,XRD,PSD and SEM methods,and a novel hydrothermal process based on the conversion principle was finally proposed.The crystal structure simulation shows that the HA with varied silicon saturation coefficients is more stable than HG,and the HA with a high iron substitution coefficient is more difficult to be converted from HG.The(110)plane of Fe_(2)O_(3) is easier to combine with HG to form HA,and the binding energy is 81.93 kJ/mol.The effects of raw material ratio,solution concentration and hydrothermal parameters on the conversion from HG to HA were revealed,and the optimal conditions for the alumina recovery were obtained.The recovery efficiencies of alumina and Na_(2)O from the RM are 63.06%and 97.34%,respectively,and the Na_(2)O content in the treated RM is only 0.13%.展开更多
Photocatalysis is an important technology for using solar energy to produce hydrogen,convert CO_(2) to synthetic fuels,and decrease persistent pollutant.However,conventional photocatalysts have limitations,including p...Photocatalysis is an important technology for using solar energy to produce hydrogen,convert CO_(2) to synthetic fuels,and decrease persistent pollutant.However,conventional photocatalysts have limitations,including poor spectral absorption,inefficient charge separation,and structural instability under operational stress,which demand innovative durable materials with tailored electronic properties.Nanodiamond(ND)has recently been recognized as a suitable material because of its exceptional chemical stability,superior charge carrier mobility,and possible surface functionalization.While its intrinsic wide bandgap limits its response to visible-light,different methods have been demonstrated to activate its catalytic potential.Here,several emerging strategies for improving the catalytic performance of ND-based photocatalytic systems are summarized,including surface functionalization,plasmonic hybridization,heteroatom doping,and heterostructure design.And the structure-activity relationship and design principle are proposed to improve the light harvesting,charge transport,and redox kinetics for constructing high efficiency ND-based photocatalysts used in the renewable energy and environmental industries.展开更多
CO_(2)reduction technology can promote the resource utilization of carbon and help alleviate global warming and energy supply pressure.It is an effective way to achieve energy conversion and utilization.Covalent organ...CO_(2)reduction technology can promote the resource utilization of carbon and help alleviate global warming and energy supply pressure.It is an effective way to achieve energy conversion and utilization.Covalent organic frameworks(COFs)are porous crystalline materials formed by connecting organic monomers through covalent bonds.They have the characteristics of functional diversity and rich chemical properties.Their advantages,such as high porosity,a wide range of visible light absorption,and excellent charge separation efficiency,give them good potential in CO_(2)capture,separation,and conversion.Currently,Cu is a key metal in the catalytic CO_(2)reduction reaction(CO_(2)RR)for the preparation of high-value-added chemicals.The preparation of highly stable and large-pore Cu-based COFs using COFs as an ideal sacrificial template for loading Cu can be used to develop high-performance electrocatalysts and photocatalysts.In this review,we discuss the latest advancements in this field,including the development of various Cu-based COFs and their applications as catalysts for CO_(2)RR.Here,we mainly introduce the synthesis strategies,some important characterization information,and the applications of electrocatalytic and photocatalytic CO_(2)conversion using these previously reported Cu-based COFs.展开更多
Direct conversion of syngas to light olefins(STO)on bifunctional catalysts has garnered significant attention,yet a comprehensive understanding of the reaction pathway and reaction kinetics remains elusive.Herein,we t...Direct conversion of syngas to light olefins(STO)on bifunctional catalysts has garnered significant attention,yet a comprehensive understanding of the reaction pathway and reaction kinetics remains elusive.Herein,we theoretically addressed the kinetics of the direct STO reaction on typical ZnAl_(2)O_(4)/zeolite catalysts by establishing a complete reaction network,consisting of methanol synthesis and conversion,water gas shift(WGS)reaction,olefin hydrogenation,and other relevant steps.The WGS reaction occurs very readily on ZnAl_(2)O_(4) surface whereas which is less active towards alkane formation via olefin hydrogenation,and the latter can be attributed to the characteristics of the H_(2) heterolytic activation and the weak polarity of olefins.The driving effect of zeolite component towards CO conversion was demonstrated by microkinetic simulations,which is sensitive to reaction conditions like space velocity and reaction temperature.Under a fixed ratio of active sites between oxide and zeolite components,the concept of the“impossible trinity”of high CO conversion,high olefin selectivity,and high space velocity can thus be manifested.This work thus provides a comprehensive kinetic picture on the direct STO conversion,offering valuable insights for the design of each component of bifunctional catalysts and the optimization of reaction conditions.展开更多
Artificial synthesis is an environment friendly photocatalytic strategy to converse carbon dioxide(CO_(2))into useful chemicals.However,water(H_(2)O)splitting,producing(hydrogen)H_(2) strongly,is always a competitive ...Artificial synthesis is an environment friendly photocatalytic strategy to converse carbon dioxide(CO_(2))into useful chemicals.However,water(H_(2)O)splitting,producing(hydrogen)H_(2) strongly,is always a competitive reaction to CO_(2) conversion.Therefore,proper cocatalysts are generally needed to enhance CO_(2) conversion but suppress H_(2) production.In this work,zinc/gallium(Zn/Ga)dual co-catalysts consisting of Zn0 and amorphous ZnGa_(2)O_(4) species were found to selectively produce carbon monoxide(CO)during the photocatalytic conversion of carbon dioxide(CO_(2))using water(H_(2)O)as an electron donor over photocatalysts such as NaTaO_(3),Ga_(2)O_(3),and ZnGa_(2)O_(4),and in the electrochemical reduction of CO_(2) over Zn0 electrodes.It is considered that there are two effects associated with the Zn/Ga dual co-catalysts:(1)a galvanic cell effect between Zn0 and amorphous ZnGa_(2)O_(4),and(2)a Z-scheme effect in NaTaO_(3)/Zn0/amorphous ZnGa_(2)O_(4).The coupling of these two effects favored the active and selective evolution of CO during the photocatalytic conversion of CO_(2) by H_(2)O.In the case of Ga_(2)O_(3) photocatalyst,480.8μmol/h of CO was produced with the presence of Zn/Ga dual cocatalysts.Moreover,the Zn/Ga dual cocatalysts universally worked in the electrochemical reduction of CO_(2).The partial current toward CO_(2) conversion was increased from 2.6 to 6.6 mA/cm,and the selectivity toward CO was promoted to from 46.4%to 74.2%.展开更多
Transcription factor-mediated cell conversion has been reported in the central nervous system of both rodents and nonhuman primates.In particular,glia-to-neuron conversion has been achieved in the brain and spinal cor...Transcription factor-mediated cell conversion has been reported in the central nervous system of both rodents and nonhuman primates.In particular,glia-to-neuron conversion has been achieved in the brain and spinal cord of animal models for neural regeneration and repair.However,whether glia-to-neuron conversion can be used for brain repair in humans needs to be explored.To investigate the use of glia-to-neuron conversion technology in the human brain,we established a long-term ex vivo culture system using human brain tissue that was surgically removed from epileptic patients to test glia-to-neuron conversion directly.We found that neural transcription factors NeuroD1 and Ascl1 both converted human glial cells into neurons.Immunostaining and electrophysiological recordings showed that the glia-converted neurons demonstrated immature properties during the initial 7-14 days of conversion,and then acquired more mature neuronal properties after 21-27 days of conversion.These ex vivo conversion studies in human brain tissue pave the way toward future clinical trials using a transcription factor-based glia-to-neuron conversion approach to treat neurological disorders.展开更多
Eco-driving behaviors have been recommended around the world because the transport is a key factor of energy use and pollution emissions.Therefore,based on the driving decision model,this paper introduces three aspect...Eco-driving behaviors have been recommended around the world because the transport is a key factor of energy use and pollution emissions.Therefore,based on the driving decision model,this paper introduces three aspects of the driving decisions(strategic decision,tactical decision and operation decision)to analyze the economy of vehicle energy.The analytic hierarchy process(AHP)is used to assign the weight of the internal evaluation indexes,so as to form a complete assessment for drivers'eco-driving behaviors.The research result can not only quantitatively describe the energy-saving effect of drivers'decisions,but also put forward targeted driving suggestions to optimize drivers'eco-driving behaviors.This assessment model helps to clarify the potential of eco-driving on energy economy of transportation in a hierarchical way,and provides a valuable theoretical basis for the further promotion and application of eco-driving education.展开更多
This article studies the problem of image segmentation-based semantic communication in autonomous driving.In real traffic scenes,the detecting of objects(e.g.,vehicles and pedestrians)is more important to guarantee dr...This article studies the problem of image segmentation-based semantic communication in autonomous driving.In real traffic scenes,the detecting of objects(e.g.,vehicles and pedestrians)is more important to guarantee driving safety,which is always ignored in existing works.Therefore,we propose a vehicular image segmentation-oriented semantic communication system,termed VIS-SemCom,focusing on transmitting and recovering image semantic features of high-important objects to reduce transmission redundancy.First,we develop a semantic codec based on Swin Transformer architecture,which expands the perceptual field thus improving the segmentation accuracy.To highlight the important objects'accuracy,we propose a multi-scale semantic extraction method by assigning the number of Swin Transformer blocks for diverse resolution semantic features.Also,an importance-aware loss incorporating important levels is devised,and an online hard example mining(OHEM)strategy is proposed to handle small sample issues in the dataset.Finally,experimental results demonstrate that the proposed VIS-SemCom can achieve a significant mean intersection over union(mIoU)performance in the SNR regions,a reduction of transmitted data volume by about 60%at 60%mIoU,and improve the segmentation accuracy of important objects,compared to baseline image communication.展开更多
Landslides pose a formidable natural hazard across the Qinghai-Tibet Plateau(QTP),endangering both ecosystems and human life.Identifying the driving factors behind landslides and accurately assessing susceptibility ar...Landslides pose a formidable natural hazard across the Qinghai-Tibet Plateau(QTP),endangering both ecosystems and human life.Identifying the driving factors behind landslides and accurately assessing susceptibility are key to mitigating disaster risk.This study integrated multi-source historical landslide data with 15 predictive factors and used several machine learning models—Random Forest(RF),Gradient Boosting Regression Trees(GBRT),Extreme Gradient Boosting(XGBoost),and Categorical Boosting(CatBoost)—to generate susceptibility maps.The Shapley additive explanation(SHAP)method was applied to quantify factor importance and explore their nonlinear effects.The results showed that:(1)CatBoost was the best-performing model(CA=0.938,AUC=0.980)in assessing landslide susceptibility,with altitude emerging as the most significant factor,followed by distance to roads and earthquake sites,precipitation,and slope;(2)the SHAP method revealed critical nonlinear thresholds,demonstrating that historical landslides were concentrated at mid-altitudes(1400-4000 m)and decreased markedly above 4000 m,with a parallel reduction in probability beyond 700 m from roads;and(3)landslide-prone areas,comprising 13%of the QTP,were concentrated in the southeastern and northeastern parts of the plateau.By integrating machine learning and SHAP analysis,this study revealed landslide hazard-prone areas and their driving factors,providing insights to support disaster management strategies and sustainable regional planning.展开更多
With the continuous progress of automatic driving technology,automatic driving technology standards are gradually affecting the determination of criminal responsibility for traffic accidents in China.At present,the ch...With the continuous progress of automatic driving technology,automatic driving technology standards are gradually affecting the determination of criminal responsibility for traffic accidents in China.At present,the characteristics and tendency of China's automatic driving technology standards present the situation of high policy relevance coexisting with low normative binding,professionalism coexist with barriers,forefront coexist with ambiguity.Therefore,challenges are presented both theoretically and practically on the determination of criminal responsibility based on automatic driving technology standard..In this regard,the misunderstanding should be clarified in theory:The legal order under the automatic driving technology standard has constitutionality and systematic,and there is a balance between the frontier of automatic driving technology development and the lagging of criminal law.The automatic driving technology risk level system should be built to clarify the boundary of the effectiveness of criminal law norms,seeking fora breakthrough in the application of the establishment of a comprehensive judgment system of the risks and accidents and the system of evidence to prove the system,which clarifies the determination of criminal responsibility under the automatic driving technology standard.This essay hopes to pursue breakthroughs in the application-to establish a comprehensive judgment system of risks and accidents as well as an evidence proof system,so as to clarify the determination of criminal responsibility under automatic driving technology standards.展开更多
This study aimed to enhance the performance of semantic segmentation for autonomous driving by improving the 2DPASS model.Two novel improvements were proposed and implemented in this paper:dynamically adjusting the lo...This study aimed to enhance the performance of semantic segmentation for autonomous driving by improving the 2DPASS model.Two novel improvements were proposed and implemented in this paper:dynamically adjusting the loss function ratio and integrating an attention mechanism(CBAM).First,the loss function weights were adjusted dynamically.The grid search method is used for deciding the best ratio of 7:3.It gives greater emphasis to the cross-entropy loss,which resulted in better segmentation performance.Second,CBAM was applied at different layers of the 2Dencoder.Heatmap analysis revealed that introducing it after the second block of 2D image encoding produced the most effective enhancement of important feature representation.The training epoch was chosen for optimizing the best value by experiments,which improved model convergence and overall accuracy.To evaluate the proposed approach,experiments were conducted based on the SemanticKITTI database.The results showed that the improved model achieved higher segmentation accuracy by 64.31%,improved 11.47% in mIoU compared with the conventional 2DPASS model(baseline:52.84%).It was more effective at detecting small and distant objects and clearly identifying boundaries between different classes.Issues such as noise and variations in data distribution affected its accuracy,indicating the need for further refinement.Overall,the proposed improvements to the 2DPASS model demonstrated the potential to advance semantic segmentation technology and contributed to a more reliable perception of complex,dynamic environments in autonomous vehicles.Accurate segmentation enhances the vehicle’s ability to distinguish different objects,and this improvement directly supports safer navigation,robust decision-making,and efficient path planning,making it highly applicable to real-world deployment of autonomous systems in urban and highway settings.展开更多
Zirconium-based conversion coatings have emerged as an environmentally friendly alternative to traditional phosphate coatings in the automotive industry,offering excellent corrosion resistance and effective protection...Zirconium-based conversion coatings have emerged as an environmentally friendly alternative to traditional phosphate coatings in the automotive industry,offering excellent corrosion resistance and effective protection for metal substrates.However,due to their relatively recent use in industrial applications,process control during zirconium conversion coating remains underdeveloped.In this study,the reaction kinetics of galvanized steel during the zirconium conversion coating were investigated systematically.The findings reveal an optimal coating time,after which the corrosion resistance of galvanized steel decreases.This decline results from the formation of corrosion cavities that cause discontinuities in the protective zirconium layer.These insights provide guidance for optimizing zirconium conversion coating processes in industrial manufacturing.展开更多
Catalytic CO_(2)-to-methanol conversion presents a synergistic approach for concurrent greenhouse gas abatement and sustainable energy carrier synthesis.Single-atom catalysts(SACs)with maximized atomic utilization,tai...Catalytic CO_(2)-to-methanol conversion presents a synergistic approach for concurrent greenhouse gas abatement and sustainable energy carrier synthesis.Single-atom catalysts(SACs)with maximized atomic utilization,tailored electronic configurations and unique metal-support interactions,exhibit superior performance in CO_(2) activation and methanol synthesis.This review systematically compares reaction mechanisms and pathways across thermal,photocatalytic and electrocatalytic systems,emphasizing structure-activity relationships governed by active sites,coordination microenvironments and support functionalities.Through case studies of representative SACs,we elucidate how metal-support synergies dictate intermediate binding energetics and methanol selectivity.A critical analysis of reaction parameters(e.g.,temperature,pressure)reveals condition-dependent catalytic behaviors in thermal system,with fewer studies in photo/electrocatalytic systems identified as key knowledge gaps.While thermal catalysis achieves industrially viable methanol yields,the scalability is constrained by energy-intensive operation and catalyst sintering.Conversely,photo/electrocatalytic routes offer renewable energy integration but suffer from inefficient charge dynamics and mass transport limitations.To address the challenges,we propose strategic research priorities on precise design of active sites,synergy of multiple technological pathways,development of intelligent catalytic systems and diverse CO_(2) feedstock compatibility.These insights establish a framework for developing next-generation SACs,offering both theoretical foundations and technological blueprints for developing carbon-negative catalytic technologies.展开更多
Laser-induced graphene(LIG)has emerged as a versatile,sustainable material for advanced energy technologies,offering a scalable,catalyst-free,and programmable method to directly convert carbon-rich substrates into por...Laser-induced graphene(LIG)has emerged as a versatile,sustainable material for advanced energy technologies,offering a scalable,catalyst-free,and programmable method to directly convert carbon-rich substrates into porous,conductive graphene.This single-step laser writing approach enables flexible,patternable electrodes without complex post-processing.With its high conductivity,large surface area,and tunable chemistry,LIG is well-suited for diverse applications including batteries,supercapacitors,dyesensitized solar cells(DSSCs),dual cells,water-splitting electrocatalysis,and triboelectric nanogenerators(TENGs).In energy storage,LIG improves charge transport,buffer volume changes,and provides a robust framework,enhancing capacitance,cycling stability,and rate capability.Its catalytic activity is further boosted through heteroatom doping or transition-metal incorporation,achieving HER/OER performance comparable to noble metals.In DSSCs,LIG functions as a flexible,low-cost alternative to platinum counter electrodes,while in TENGs,its strong triboelectric response and mechanical durability enable integration into self-powered,wearable systems.Despite the immense recent progress in this field,challenges remain regarding the scalability,long-term operational stability,and interfacial engineering of LIGbased composites.Further exploration into multi-laser systems,substrate diversity,and synergistic composite architectures will be crucial to optimizing device performance and reliability.Nevertheless,the green,cost-efficient,rapid,and programmable synthesis of LIG poses it as a cornerstone potential building block material in the development of future sustainable and multifunctional energy systems.Throughout the review we compare fabrication strategies,summarize performance metrics against relevant benchmarks,and identifying common mechanistic advantages conferred by the laser writing process.Remaining challenges-such as scale-up,precursor diversity,long-term environmental stability,and integration into complex device architectures-are outlined alongside prospective research directions.Collectively,this review article provides an in-depth perspective on the multifunctional nature of LIG,underscoring its promise in next-generation energy storage,conversion,harvesting applications,and laying the groundwork for future research directions.展开更多
Bottom-up and top-down endogenous automobile clusters exhibit distinct evolutionary traits and driving mechanisms,yet their comparative analysis remains understudied.Therefore,using Taizhou automobile industry cluster...Bottom-up and top-down endogenous automobile clusters exhibit distinct evolutionary traits and driving mechanisms,yet their comparative analysis remains understudied.Therefore,using Taizhou automobile industry cluster(TAIC)and Wuhu automobile industry cluster(WAIC)as cases,using historical statistical data and field interview data from the 1980s to 2023,combined with qualitative research methods of thematic and diachronic analysis,and quantitative research methods of social network analysis,we compare both endogenous automobile clusters’evolutionary traits and driving mechanisms.The results confirm both clusters undergo multi-scale spatial reconfiguration,organizational complexification,and intelligent networking technological transformation,yet diverge fundamentally:TAIC evolves through market-driven progressive expansion,transitioning from single to dual-core structures via private enterprise networking,with innovation following market-integrated logic and institutional thickness built on demand-driven evolution.Conversely,WAIC follows planned expansion,maintaining state-led hierarchical single-core stability through policy-driven breakthrough innovation and supply-dominated institutional construction-though both ultimately require formal-informal system synergy.Their coevolution is driven by dynamic interactions of path dependence(weakening influence),learning-innovation(strengthening influence),and relationship selection(inverted U-shaped trajectory),with divergent development paths rooted in TAIC’s grassroots self-organization genes versus WAIC’s top-level design genes,amplified by core enterprises’strategic disparities.The research findings can not only provide decision-making support for China’s industrial upgrading,but also contribute China’s insights to global economic governance.展开更多
The promising prospects for all-day building thermal management are driving widespread research into spectrally selective manipulation materials.This article first summarizes the evolution path of metal reversible dep...The promising prospects for all-day building thermal management are driving widespread research into spectrally selective manipulation materials.This article first summarizes the evolution path of metal reversible deposition technology,noting its advantages of cost-effectiveness and scientific rigor.It then highlights the groundbreaking work by Wang et al.(published in ACS Energy Letters,2025,10,3231)on coupling metastructured photothermal conversion electrodes and reversible Cu deposition for all-day energy management.Finally,the commercial viability of Wang et al.'s approach for building energy saving and its potential applicability to other scenarios are elaborated.展开更多
Two-dimensional nanofluidic membranes have garnered considerable interest due to their potential for cost-effective osmotic energy harvesting.One promising approach to enhancing ion conductivity and selectivity is the...Two-dimensional nanofluidic membranes have garnered considerable interest due to their potential for cost-effective osmotic energy harvesting.One promising approach to enhancing ion conductivity and selectivity is the incorporation of vip additives.However,the traditional host-vip configuration can undermine the structural integrity of nanochannels owing to the inconsistent size and shape of these additives.Drawing inspiration from the intricate design of biological protein channels,which utilize small amino acid molecules as vips,we have addressed this issue by incorporating glycine,a common amino acid,into a vermiculite membrane using a simple vacuum-assisted infiltration method.The resulting vermiculite-glycine membrane demonstrates 1.8 times greater ionic conductivity and twice the power density compared to pure vermiculite membranes.Analysis based on glycine content,coupled with spectroscopic examination,reveals that ion conductivity is linked to the distribution of glycine molecules across three specific sites within the membrane.This suggests that glycine molecules—whether confined in voids,adsorbed onto nanochannel surfaces,or intercalated within multilayered vermiculite nanoparticles—enhance nanofluidic ion transport by modulating surface and space charge density,as well as strengthening hydrogen bonding,electrostatic interactions,and steric effects.This work reveals the specific interactions between amino acids and vermiculite,offering a novel path for advancing nanofluidic composite membranes and highlighting critical considerations for the proposed strategy.展开更多
Analyzing the driving behavior of autonomous vehicles(AV)in mixed traffic conditions at urban intersections has become increasingly important for improving intersection design,providing infrastructure-based guidance i...Analyzing the driving behavior of autonomous vehicles(AV)in mixed traffic conditions at urban intersections has become increasingly important for improving intersection design,providing infrastructure-based guidance information,and developing capability-enhanced AV perception systems.This study investigated the contributing factors affecting AV driving behavior using theWaymo Open Dataset.Binarized autonomous driving stability metrics,derived via a kernel density estimation,served as the target variables for a random forest classification model.The model’s input variables included 15 factors divided into four types:intersection-related,surrounding object-related,road infrastructure-related,and time-of-day-related types.The random forest classification model was employed to identify the key factors affecting autonomous driving behavior.In addition,the identified factors were further ranked based on feature importance.SHAP analysis was utilized to enhance model interpretability by quantifying the contribution of each factor and identifying their directional impacts.The type of intersection factor was found to have an importance of 0.243 and was the most influential factor on autonomous driving behavior.On average,intersection-related factors had an importance of 0.196,which is approximately a 31.1%margin over the average importance of surrounding object-related factors.Additionally,the surrounding object-related factors that were collected through sensors on the autonomous vehicle had a high degree of feature importance,especially with the number of pedestrians having the highest importance(0.107)of the types of objects.The correlation between these findings can contribute to the development of various treatments to improvemore harmonized AVs’maneuvering with other road users and facilities in urban mixed traffic environments.展开更多
To address soil salinization’s significant impact on human production and livelihood in arid regions,especially in high-salinity areas like salt lake regions,this study used multi-source remote sensing data to extrac...To address soil salinization’s significant impact on human production and livelihood in arid regions,especially in high-salinity areas like salt lake regions,this study used multi-source remote sensing data to extract 52 surface factors.Combined with measured soil salinity data,correlation analysis,multicollinearity testing,and projection importance analysis identified eight dominant factors.Subsequently,four machine learning algorithms were applied for modeling,and the optimal models were selected to study the spatiotemporal variation of soil salinization.The results indicate that the average soil salt content in the study area was 20.74%in 2020.LST(land surface temperature)can effectively identify areas with high salinity,such as saline-alkali land and salt flats.Among inversion models,the GBDT(gradient boosting decision trees)model demonstrated the highest predictive ability and minimal errors.The optimal inversion results revealed that soil salinization distribution was influenced by topographic elevation,distance from Qarhan Salt Lake,and river network density.Over the past 21 years,there was significant fluctuation in soil salinity observed in the concentrated area of grassland within the groundwater overflow zone,indicating strong variation in salinization.This fluctuation correlates with changes in groundwater levels in the groundwater overflow zone,which are influenced by temperature variations that determine the amount of snow and ice meltwater,and the precipitation in the upstream area.This study enhances understanding of soil salinization and its drivers in extremely arid salt lake regions.展开更多
The safe driving and operation of trains is a necessary condition for ensuring the safe operation of trains.In particular,heavy-haul trains are characterized by the difficulty in driving and operation.Considering the ...The safe driving and operation of trains is a necessary condition for ensuring the safe operation of trains.In particular,heavy-haul trains are characterized by the difficulty in driving and operation.Considering the uncertainties in train driving and operation,this paper analyzes the relationship between the safety of heavy-haul electric locomotive hauled trains and driving and operation.It studies the auxiliary intelligent driving safety operation control methods.Through K-means to identify the characteristics of drivers'driving manipulation,the hidden Markov model adaptively adjusts the train driving and operation sequence,and conducts auxiliary driving reconstruction for heavy-haul locomotive driving and operation.Based on the train running curve and the locomotive traction/braking characteristics,it smoothly controls the exertion of the traction/braking force of heavy-haul locomotives,thereby optimizing the driving safety control of heavy-haul trains in the vehicle-environment-track system.Finally,the train operation simulation and optimized driving verification are carried out by simulating some track sections.The results show that the proposed method can correct and pre-optimize driving operations,improving the smoothness of heavy-haul trains by approximately 10%.It verifies the effectiveness of the proposed train assisted driving control reconstruction method,facilitating the smooth and safe operation of heavy-haul trains.展开更多
基金the financial support from the National Key R&D Program of China(No.2022YFC2904405)the National Natural Science Foundation of China(Nos.22078055,51774079)。
文摘To synergistically recover alumina and alkali from red mud(RM),the structural stability and conversion mechanism of hydroandradite(HA)from hydrogarnet(HG)were investigated via the First-principles,XRF,XRD,PSD and SEM methods,and a novel hydrothermal process based on the conversion principle was finally proposed.The crystal structure simulation shows that the HA with varied silicon saturation coefficients is more stable than HG,and the HA with a high iron substitution coefficient is more difficult to be converted from HG.The(110)plane of Fe_(2)O_(3) is easier to combine with HG to form HA,and the binding energy is 81.93 kJ/mol.The effects of raw material ratio,solution concentration and hydrothermal parameters on the conversion from HG to HA were revealed,and the optimal conditions for the alumina recovery were obtained.The recovery efficiencies of alumina and Na_(2)O from the RM are 63.06%and 97.34%,respectively,and the Na_(2)O content in the treated RM is only 0.13%.
文摘Photocatalysis is an important technology for using solar energy to produce hydrogen,convert CO_(2) to synthetic fuels,and decrease persistent pollutant.However,conventional photocatalysts have limitations,including poor spectral absorption,inefficient charge separation,and structural instability under operational stress,which demand innovative durable materials with tailored electronic properties.Nanodiamond(ND)has recently been recognized as a suitable material because of its exceptional chemical stability,superior charge carrier mobility,and possible surface functionalization.While its intrinsic wide bandgap limits its response to visible-light,different methods have been demonstrated to activate its catalytic potential.Here,several emerging strategies for improving the catalytic performance of ND-based photocatalytic systems are summarized,including surface functionalization,plasmonic hybridization,heteroatom doping,and heterostructure design.And the structure-activity relationship and design principle are proposed to improve the light harvesting,charge transport,and redox kinetics for constructing high efficiency ND-based photocatalysts used in the renewable energy and environmental industries.
文摘CO_(2)reduction technology can promote the resource utilization of carbon and help alleviate global warming and energy supply pressure.It is an effective way to achieve energy conversion and utilization.Covalent organic frameworks(COFs)are porous crystalline materials formed by connecting organic monomers through covalent bonds.They have the characteristics of functional diversity and rich chemical properties.Their advantages,such as high porosity,a wide range of visible light absorption,and excellent charge separation efficiency,give them good potential in CO_(2)capture,separation,and conversion.Currently,Cu is a key metal in the catalytic CO_(2)reduction reaction(CO_(2)RR)for the preparation of high-value-added chemicals.The preparation of highly stable and large-pore Cu-based COFs using COFs as an ideal sacrificial template for loading Cu can be used to develop high-performance electrocatalysts and photocatalysts.In this review,we discuss the latest advancements in this field,including the development of various Cu-based COFs and their applications as catalysts for CO_(2)RR.Here,we mainly introduce the synthesis strategies,some important characterization information,and the applications of electrocatalytic and photocatalytic CO_(2)conversion using these previously reported Cu-based COFs.
文摘Direct conversion of syngas to light olefins(STO)on bifunctional catalysts has garnered significant attention,yet a comprehensive understanding of the reaction pathway and reaction kinetics remains elusive.Herein,we theoretically addressed the kinetics of the direct STO reaction on typical ZnAl_(2)O_(4)/zeolite catalysts by establishing a complete reaction network,consisting of methanol synthesis and conversion,water gas shift(WGS)reaction,olefin hydrogenation,and other relevant steps.The WGS reaction occurs very readily on ZnAl_(2)O_(4) surface whereas which is less active towards alkane formation via olefin hydrogenation,and the latter can be attributed to the characteristics of the H_(2) heterolytic activation and the weak polarity of olefins.The driving effect of zeolite component towards CO conversion was demonstrated by microkinetic simulations,which is sensitive to reaction conditions like space velocity and reaction temperature.Under a fixed ratio of active sites between oxide and zeolite components,the concept of the“impossible trinity”of high CO conversion,high olefin selectivity,and high space velocity can thus be manifested.This work thus provides a comprehensive kinetic picture on the direct STO conversion,offering valuable insights for the design of each component of bifunctional catalysts and the optimization of reaction conditions.
基金supported by the National Key R&D Program of China(No.2023YFC3710800)the National Natural Science Foundation of China(No.22376207)+1 种基金the Research Fund of High-Level Training Talents of“333”Project in Jiangsu provinceFunding for school-level research projects of Yancheng Institute of Technology(Nos.xjr2024008 and xjr2023055).
文摘Artificial synthesis is an environment friendly photocatalytic strategy to converse carbon dioxide(CO_(2))into useful chemicals.However,water(H_(2)O)splitting,producing(hydrogen)H_(2) strongly,is always a competitive reaction to CO_(2) conversion.Therefore,proper cocatalysts are generally needed to enhance CO_(2) conversion but suppress H_(2) production.In this work,zinc/gallium(Zn/Ga)dual co-catalysts consisting of Zn0 and amorphous ZnGa_(2)O_(4) species were found to selectively produce carbon monoxide(CO)during the photocatalytic conversion of carbon dioxide(CO_(2))using water(H_(2)O)as an electron donor over photocatalysts such as NaTaO_(3),Ga_(2)O_(3),and ZnGa_(2)O_(4),and in the electrochemical reduction of CO_(2) over Zn0 electrodes.It is considered that there are two effects associated with the Zn/Ga dual co-catalysts:(1)a galvanic cell effect between Zn0 and amorphous ZnGa_(2)O_(4),and(2)a Z-scheme effect in NaTaO_(3)/Zn0/amorphous ZnGa_(2)O_(4).The coupling of these two effects favored the active and selective evolution of CO during the photocatalytic conversion of CO_(2) by H_(2)O.In the case of Ga_(2)O_(3) photocatalyst,480.8μmol/h of CO was produced with the presence of Zn/Ga dual cocatalysts.Moreover,the Zn/Ga dual cocatalysts universally worked in the electrochemical reduction of CO_(2).The partial current toward CO_(2) conversion was increased from 2.6 to 6.6 mA/cm,and the selectivity toward CO was promoted to from 46.4%to 74.2%.
基金supported by the Key Project of Guangzhou City,No.202206060002(to GC)the Guangdong Province Science and Technology Project of China,No.2018B030332001(to GC)+1 种基金the Natural Science Foundation of Guangdong Province of China,No.2020A1515010854(to QW)the Yi-Liang Liu Endowment Fund from Jinan University Education Development Foundation。
文摘Transcription factor-mediated cell conversion has been reported in the central nervous system of both rodents and nonhuman primates.In particular,glia-to-neuron conversion has been achieved in the brain and spinal cord of animal models for neural regeneration and repair.However,whether glia-to-neuron conversion can be used for brain repair in humans needs to be explored.To investigate the use of glia-to-neuron conversion technology in the human brain,we established a long-term ex vivo culture system using human brain tissue that was surgically removed from epileptic patients to test glia-to-neuron conversion directly.We found that neural transcription factors NeuroD1 and Ascl1 both converted human glial cells into neurons.Immunostaining and electrophysiological recordings showed that the glia-converted neurons demonstrated immature properties during the initial 7-14 days of conversion,and then acquired more mature neuronal properties after 21-27 days of conversion.These ex vivo conversion studies in human brain tissue pave the way toward future clinical trials using a transcription factor-based glia-to-neuron conversion approach to treat neurological disorders.
文摘Eco-driving behaviors have been recommended around the world because the transport is a key factor of energy use and pollution emissions.Therefore,based on the driving decision model,this paper introduces three aspects of the driving decisions(strategic decision,tactical decision and operation decision)to analyze the economy of vehicle energy.The analytic hierarchy process(AHP)is used to assign the weight of the internal evaluation indexes,so as to form a complete assessment for drivers'eco-driving behaviors.The research result can not only quantitatively describe the energy-saving effect of drivers'decisions,but also put forward targeted driving suggestions to optimize drivers'eco-driving behaviors.This assessment model helps to clarify the potential of eco-driving on energy economy of transportation in a hierarchical way,and provides a valuable theoretical basis for the further promotion and application of eco-driving education.
基金National Natural Science Foundation of China under Grants No.62171047,U22B2001,62271065,62001051Beijing Natural Science Foundation under Grant L223027BUPT Excellent Ph.D Students Foundation under Grants CX2021114。
文摘This article studies the problem of image segmentation-based semantic communication in autonomous driving.In real traffic scenes,the detecting of objects(e.g.,vehicles and pedestrians)is more important to guarantee driving safety,which is always ignored in existing works.Therefore,we propose a vehicular image segmentation-oriented semantic communication system,termed VIS-SemCom,focusing on transmitting and recovering image semantic features of high-important objects to reduce transmission redundancy.First,we develop a semantic codec based on Swin Transformer architecture,which expands the perceptual field thus improving the segmentation accuracy.To highlight the important objects'accuracy,we propose a multi-scale semantic extraction method by assigning the number of Swin Transformer blocks for diverse resolution semantic features.Also,an importance-aware loss incorporating important levels is devised,and an online hard example mining(OHEM)strategy is proposed to handle small sample issues in the dataset.Finally,experimental results demonstrate that the proposed VIS-SemCom can achieve a significant mean intersection over union(mIoU)performance in the SNR regions,a reduction of transmitted data volume by about 60%at 60%mIoU,and improve the segmentation accuracy of important objects,compared to baseline image communication.
基金The National Key Research and Development Program of China,No.2023YFC3206601。
文摘Landslides pose a formidable natural hazard across the Qinghai-Tibet Plateau(QTP),endangering both ecosystems and human life.Identifying the driving factors behind landslides and accurately assessing susceptibility are key to mitigating disaster risk.This study integrated multi-source historical landslide data with 15 predictive factors and used several machine learning models—Random Forest(RF),Gradient Boosting Regression Trees(GBRT),Extreme Gradient Boosting(XGBoost),and Categorical Boosting(CatBoost)—to generate susceptibility maps.The Shapley additive explanation(SHAP)method was applied to quantify factor importance and explore their nonlinear effects.The results showed that:(1)CatBoost was the best-performing model(CA=0.938,AUC=0.980)in assessing landslide susceptibility,with altitude emerging as the most significant factor,followed by distance to roads and earthquake sites,precipitation,and slope;(2)the SHAP method revealed critical nonlinear thresholds,demonstrating that historical landslides were concentrated at mid-altitudes(1400-4000 m)and decreased markedly above 4000 m,with a parallel reduction in probability beyond 700 m from roads;and(3)landslide-prone areas,comprising 13%of the QTP,were concentrated in the southeastern and northeastern parts of the plateau.By integrating machine learning and SHAP analysis,this study revealed landslide hazard-prone areas and their driving factors,providing insights to support disaster management strategies and sustainable regional planning.
基金The National Social Science Foundation Youth Project of China:Research on the collaborative govemance path of administrative law and criminal law against dangerous driving behaviors in the digital-intelligent society(25CFX108)。
文摘With the continuous progress of automatic driving technology,automatic driving technology standards are gradually affecting the determination of criminal responsibility for traffic accidents in China.At present,the characteristics and tendency of China's automatic driving technology standards present the situation of high policy relevance coexisting with low normative binding,professionalism coexist with barriers,forefront coexist with ambiguity.Therefore,challenges are presented both theoretically and practically on the determination of criminal responsibility based on automatic driving technology standard..In this regard,the misunderstanding should be clarified in theory:The legal order under the automatic driving technology standard has constitutionality and systematic,and there is a balance between the frontier of automatic driving technology development and the lagging of criminal law.The automatic driving technology risk level system should be built to clarify the boundary of the effectiveness of criminal law norms,seeking fora breakthrough in the application of the establishment of a comprehensive judgment system of the risks and accidents and the system of evidence to prove the system,which clarifies the determination of criminal responsibility under the automatic driving technology standard.This essay hopes to pursue breakthroughs in the application-to establish a comprehensive judgment system of risks and accidents as well as an evidence proof system,so as to clarify the determination of criminal responsibility under automatic driving technology standards.
文摘This study aimed to enhance the performance of semantic segmentation for autonomous driving by improving the 2DPASS model.Two novel improvements were proposed and implemented in this paper:dynamically adjusting the loss function ratio and integrating an attention mechanism(CBAM).First,the loss function weights were adjusted dynamically.The grid search method is used for deciding the best ratio of 7:3.It gives greater emphasis to the cross-entropy loss,which resulted in better segmentation performance.Second,CBAM was applied at different layers of the 2Dencoder.Heatmap analysis revealed that introducing it after the second block of 2D image encoding produced the most effective enhancement of important feature representation.The training epoch was chosen for optimizing the best value by experiments,which improved model convergence and overall accuracy.To evaluate the proposed approach,experiments were conducted based on the SemanticKITTI database.The results showed that the improved model achieved higher segmentation accuracy by 64.31%,improved 11.47% in mIoU compared with the conventional 2DPASS model(baseline:52.84%).It was more effective at detecting small and distant objects and clearly identifying boundaries between different classes.Issues such as noise and variations in data distribution affected its accuracy,indicating the need for further refinement.Overall,the proposed improvements to the 2DPASS model demonstrated the potential to advance semantic segmentation technology and contributed to a more reliable perception of complex,dynamic environments in autonomous vehicles.Accurate segmentation enhances the vehicle’s ability to distinguish different objects,and this improvement directly supports safer navigation,robust decision-making,and efficient path planning,making it highly applicable to real-world deployment of autonomous systems in urban and highway settings.
基金express their sincere gratitude to the Jiangsu Key Laboratory of Advanced Metallic Materials of Southeast University for providing the complete laboratory facilities required for this research project.
文摘Zirconium-based conversion coatings have emerged as an environmentally friendly alternative to traditional phosphate coatings in the automotive industry,offering excellent corrosion resistance and effective protection for metal substrates.However,due to their relatively recent use in industrial applications,process control during zirconium conversion coating remains underdeveloped.In this study,the reaction kinetics of galvanized steel during the zirconium conversion coating were investigated systematically.The findings reveal an optimal coating time,after which the corrosion resistance of galvanized steel decreases.This decline results from the formation of corrosion cavities that cause discontinuities in the protective zirconium layer.These insights provide guidance for optimizing zirconium conversion coating processes in industrial manufacturing.
基金supported by the National Natural Science Foundation of China(No.52300170).
文摘Catalytic CO_(2)-to-methanol conversion presents a synergistic approach for concurrent greenhouse gas abatement and sustainable energy carrier synthesis.Single-atom catalysts(SACs)with maximized atomic utilization,tailored electronic configurations and unique metal-support interactions,exhibit superior performance in CO_(2) activation and methanol synthesis.This review systematically compares reaction mechanisms and pathways across thermal,photocatalytic and electrocatalytic systems,emphasizing structure-activity relationships governed by active sites,coordination microenvironments and support functionalities.Through case studies of representative SACs,we elucidate how metal-support synergies dictate intermediate binding energetics and methanol selectivity.A critical analysis of reaction parameters(e.g.,temperature,pressure)reveals condition-dependent catalytic behaviors in thermal system,with fewer studies in photo/electrocatalytic systems identified as key knowledge gaps.While thermal catalysis achieves industrially viable methanol yields,the scalability is constrained by energy-intensive operation and catalyst sintering.Conversely,photo/electrocatalytic routes offer renewable energy integration but suffer from inefficient charge dynamics and mass transport limitations.To address the challenges,we propose strategic research priorities on precise design of active sites,synergy of multiple technological pathways,development of intelligent catalytic systems and diverse CO_(2) feedstock compatibility.These insights establish a framework for developing next-generation SACs,offering both theoretical foundations and technological blueprints for developing carbon-negative catalytic technologies.
文摘Laser-induced graphene(LIG)has emerged as a versatile,sustainable material for advanced energy technologies,offering a scalable,catalyst-free,and programmable method to directly convert carbon-rich substrates into porous,conductive graphene.This single-step laser writing approach enables flexible,patternable electrodes without complex post-processing.With its high conductivity,large surface area,and tunable chemistry,LIG is well-suited for diverse applications including batteries,supercapacitors,dyesensitized solar cells(DSSCs),dual cells,water-splitting electrocatalysis,and triboelectric nanogenerators(TENGs).In energy storage,LIG improves charge transport,buffer volume changes,and provides a robust framework,enhancing capacitance,cycling stability,and rate capability.Its catalytic activity is further boosted through heteroatom doping or transition-metal incorporation,achieving HER/OER performance comparable to noble metals.In DSSCs,LIG functions as a flexible,low-cost alternative to platinum counter electrodes,while in TENGs,its strong triboelectric response and mechanical durability enable integration into self-powered,wearable systems.Despite the immense recent progress in this field,challenges remain regarding the scalability,long-term operational stability,and interfacial engineering of LIGbased composites.Further exploration into multi-laser systems,substrate diversity,and synergistic composite architectures will be crucial to optimizing device performance and reliability.Nevertheless,the green,cost-efficient,rapid,and programmable synthesis of LIG poses it as a cornerstone potential building block material in the development of future sustainable and multifunctional energy systems.Throughout the review we compare fabrication strategies,summarize performance metrics against relevant benchmarks,and identifying common mechanistic advantages conferred by the laser writing process.Remaining challenges-such as scale-up,precursor diversity,long-term environmental stability,and integration into complex device architectures-are outlined alongside prospective research directions.Collectively,this review article provides an in-depth perspective on the multifunctional nature of LIG,underscoring its promise in next-generation energy storage,conversion,harvesting applications,and laying the groundwork for future research directions.
基金Under the auspices of National Natural Science Foundation of China(No.42571219)Key Project of Zhejiang Province Soft Science Research Plan(No.2023C25014)。
文摘Bottom-up and top-down endogenous automobile clusters exhibit distinct evolutionary traits and driving mechanisms,yet their comparative analysis remains understudied.Therefore,using Taizhou automobile industry cluster(TAIC)and Wuhu automobile industry cluster(WAIC)as cases,using historical statistical data and field interview data from the 1980s to 2023,combined with qualitative research methods of thematic and diachronic analysis,and quantitative research methods of social network analysis,we compare both endogenous automobile clusters’evolutionary traits and driving mechanisms.The results confirm both clusters undergo multi-scale spatial reconfiguration,organizational complexification,and intelligent networking technological transformation,yet diverge fundamentally:TAIC evolves through market-driven progressive expansion,transitioning from single to dual-core structures via private enterprise networking,with innovation following market-integrated logic and institutional thickness built on demand-driven evolution.Conversely,WAIC follows planned expansion,maintaining state-led hierarchical single-core stability through policy-driven breakthrough innovation and supply-dominated institutional construction-though both ultimately require formal-informal system synergy.Their coevolution is driven by dynamic interactions of path dependence(weakening influence),learning-innovation(strengthening influence),and relationship selection(inverted U-shaped trajectory),with divergent development paths rooted in TAIC’s grassroots self-organization genes versus WAIC’s top-level design genes,amplified by core enterprises’strategic disparities.The research findings can not only provide decision-making support for China’s industrial upgrading,but also contribute China’s insights to global economic governance.
基金supported by grants from the National Natural Science Foundation of China(no.62175248,U24A2061)Shanghai Science and Technology Funds(no.23ZR1481900,25ZR1401373)Science Foundation for Youth Scholar of State Key Laboratory of High Performance Ceramics and Superfine Microstructures(no.SKL202202).
文摘The promising prospects for all-day building thermal management are driving widespread research into spectrally selective manipulation materials.This article first summarizes the evolution path of metal reversible deposition technology,noting its advantages of cost-effectiveness and scientific rigor.It then highlights the groundbreaking work by Wang et al.(published in ACS Energy Letters,2025,10,3231)on coupling metastructured photothermal conversion electrodes and reversible Cu deposition for all-day energy management.Finally,the commercial viability of Wang et al.'s approach for building energy saving and its potential applicability to other scenarios are elaborated.
基金supported by the National Natural Science Foundation of China(Grant No.22479097)the Shanghai Science and Technology Committee(Grant Nos.23ZR1433000)the National High-Level Talent Program for Young Scholars,the Start-up Fund(F.S.)from Shanghai Jiao Tong University,China.We also acknowledge the SJTU Instrument Analysis Centre for the measurements.
文摘Two-dimensional nanofluidic membranes have garnered considerable interest due to their potential for cost-effective osmotic energy harvesting.One promising approach to enhancing ion conductivity and selectivity is the incorporation of vip additives.However,the traditional host-vip configuration can undermine the structural integrity of nanochannels owing to the inconsistent size and shape of these additives.Drawing inspiration from the intricate design of biological protein channels,which utilize small amino acid molecules as vips,we have addressed this issue by incorporating glycine,a common amino acid,into a vermiculite membrane using a simple vacuum-assisted infiltration method.The resulting vermiculite-glycine membrane demonstrates 1.8 times greater ionic conductivity and twice the power density compared to pure vermiculite membranes.Analysis based on glycine content,coupled with spectroscopic examination,reveals that ion conductivity is linked to the distribution of glycine molecules across three specific sites within the membrane.This suggests that glycine molecules—whether confined in voids,adsorbed onto nanochannel surfaces,or intercalated within multilayered vermiculite nanoparticles—enhance nanofluidic ion transport by modulating surface and space charge density,as well as strengthening hydrogen bonding,electrostatic interactions,and steric effects.This work reveals the specific interactions between amino acids and vermiculite,offering a novel path for advancing nanofluidic composite membranes and highlighting critical considerations for the proposed strategy.
基金supported by Korea Institute of Police Technology(KIPoT)grant funded by the Korea government(KNPA)(Project Name:Development of Lv.4 Driving Ability Evaluation Technology for Autonomous Vehicles Based on Real Roads/Project Number:RS-2023-00238253).
文摘Analyzing the driving behavior of autonomous vehicles(AV)in mixed traffic conditions at urban intersections has become increasingly important for improving intersection design,providing infrastructure-based guidance information,and developing capability-enhanced AV perception systems.This study investigated the contributing factors affecting AV driving behavior using theWaymo Open Dataset.Binarized autonomous driving stability metrics,derived via a kernel density estimation,served as the target variables for a random forest classification model.The model’s input variables included 15 factors divided into four types:intersection-related,surrounding object-related,road infrastructure-related,and time-of-day-related types.The random forest classification model was employed to identify the key factors affecting autonomous driving behavior.In addition,the identified factors were further ranked based on feature importance.SHAP analysis was utilized to enhance model interpretability by quantifying the contribution of each factor and identifying their directional impacts.The type of intersection factor was found to have an importance of 0.243 and was the most influential factor on autonomous driving behavior.On average,intersection-related factors had an importance of 0.196,which is approximately a 31.1%margin over the average importance of surrounding object-related factors.Additionally,the surrounding object-related factors that were collected through sensors on the autonomous vehicle had a high degree of feature importance,especially with the number of pedestrians having the highest importance(0.107)of the types of objects.The correlation between these findings can contribute to the development of various treatments to improvemore harmonized AVs’maneuvering with other road users and facilities in urban mixed traffic environments.
基金The Second Tibetan Plateau Scientific Expedition and Research Program,No.2019QZKK0805-02The Innovation Team Foundation of Qinghai Office of Science and Technology,No.2022-ZJ-903+2 种基金The Comprehensive Development and Utilization of Salt Lake Resources,No.2023ZXKYA05100The Special Research Assistant of Chinese Academy of Sciences(Han Jinjun)The Kunlun Talented People of Qinghai Province,High-end Innovation and Entrepreneurship Talents,2023(Han Jinjun)。
文摘To address soil salinization’s significant impact on human production and livelihood in arid regions,especially in high-salinity areas like salt lake regions,this study used multi-source remote sensing data to extract 52 surface factors.Combined with measured soil salinity data,correlation analysis,multicollinearity testing,and projection importance analysis identified eight dominant factors.Subsequently,four machine learning algorithms were applied for modeling,and the optimal models were selected to study the spatiotemporal variation of soil salinization.The results indicate that the average soil salt content in the study area was 20.74%in 2020.LST(land surface temperature)can effectively identify areas with high salinity,such as saline-alkali land and salt flats.Among inversion models,the GBDT(gradient boosting decision trees)model demonstrated the highest predictive ability and minimal errors.The optimal inversion results revealed that soil salinization distribution was influenced by topographic elevation,distance from Qarhan Salt Lake,and river network density.Over the past 21 years,there was significant fluctuation in soil salinity observed in the concentrated area of grassland within the groundwater overflow zone,indicating strong variation in salinization.This fluctuation correlates with changes in groundwater levels in the groundwater overflow zone,which are influenced by temperature variations that determine the amount of snow and ice meltwater,and the precipitation in the upstream area.This study enhances understanding of soil salinization and its drivers in extremely arid salt lake regions.
基金Project(U2034211)supported by the National Natural Science Foundation of ChinaProject(20232ACE01013)supported by the Major Scientific and Technological Research and Development Special Project of Jiangxi Province,China。
文摘The safe driving and operation of trains is a necessary condition for ensuring the safe operation of trains.In particular,heavy-haul trains are characterized by the difficulty in driving and operation.Considering the uncertainties in train driving and operation,this paper analyzes the relationship between the safety of heavy-haul electric locomotive hauled trains and driving and operation.It studies the auxiliary intelligent driving safety operation control methods.Through K-means to identify the characteristics of drivers'driving manipulation,the hidden Markov model adaptively adjusts the train driving and operation sequence,and conducts auxiliary driving reconstruction for heavy-haul locomotive driving and operation.Based on the train running curve and the locomotive traction/braking characteristics,it smoothly controls the exertion of the traction/braking force of heavy-haul locomotives,thereby optimizing the driving safety control of heavy-haul trains in the vehicle-environment-track system.Finally,the train operation simulation and optimized driving verification are carried out by simulating some track sections.The results show that the proposed method can correct and pre-optimize driving operations,improving the smoothness of heavy-haul trains by approximately 10%.It verifies the effectiveness of the proposed train assisted driving control reconstruction method,facilitating the smooth and safe operation of heavy-haul trains.
