With the rapid development of artificial intelligence technology,the education sector is gradually exploring how AI tools to empower subject teaching.In this paper,the first lesson of Japan published by People s Educa...With the rapid development of artificial intelligence technology,the education sector is gradually exploring how AI tools to empower subject teaching.In this paper,the first lesson of Japan published by People s Education Press in the second semester of seventh grade is taken as an example,focusing on the feasibility of using AI tools for lesson preparation.Through the Meta Sota AI special topic,Kimi,deepseek,and Baidu AI images,lesson preparation is completed.Using Coze intelligent agents,interactive learning scenarios are developed to complete teaching design.Research has shown that AI technology can effectively improve the efficiency and quality of lesson preparation,and can assist in the implementation of core competencies in geography.This paper can provide a reference for the operability of AI empowering educational and teaching activities.展开更多
To enable distributed PV to adapt to variations in power grid strength and achieve stable grid connection while enhancing operational flexibility,it is essential to configure grid-connected inverters with an integrate...To enable distributed PV to adapt to variations in power grid strength and achieve stable grid connection while enhancing operational flexibility,it is essential to configure grid-connected inverters with an integrated grid-following control mode,allowing smooth switching between GFL and GFM modes.First,impedance models of GFL and GFM PV energy storage VSG systems were established,and grid stability was analyzed.Second,an online impedance identification method based on voltage fluctuation data screening was proposed to enhance the accuracy of impedance identification.Additionally,a PV energy storage GFM/GFL VSG smooth switching method based on current inner loop compensation was introduced to achieve stable grid-connected operation of distributed photovoltaics under changes in strong and weak power grids.Finally,a grid stability analysis was conducted on the multi-machine parallel PV ESS,and a simulation model of a multi-machine parallel PV ESS based on current inner loop compensation was established for testing.Results showed that,compared to using a single GFM or single GFL control for the PV VSG system,the smooth switching method of multi-machine parallel PV ESS effectively suppresses system resonance under variations in power grid strength,enabling adaptive and stable grid-connected operations of distributed PV.展开更多
In recent years, with the development of technologies such as the Internet of Things(Io T), big data and cloud computing, digital twin technology has gradually been applied in marine research. The digital twin realize...In recent years, with the development of technologies such as the Internet of Things(Io T), big data and cloud computing, digital twin technology has gradually been applied in marine research. The digital twin realizes real-time monitoring, analysis and optimization of the state and behavior of a physical object or system by creating a virtual model. Research shows that digital twin technology has extensive application potential in ship design, marine resource development, marine equipment engineering design and optimization, marine ecological protection and early warning of disasters. Although digital twin technology has great potential in marine research, it also faces many challenges, including the complexity of data acquisition and processing, the accuracy and real-time performance of model construction, and the need for multidisciplinary cross-integration. An in-depth analysis of the technical bottlenecks and future development directions will provide an important reference for subsequent research and promote the further application and development of digital twin technology in marine research.展开更多
With the rapid development of transportation infrastructure,ensuring road safety through timely and accurate highway inspection has become increasingly critical.Traditional manual inspection methods are not only time-...With the rapid development of transportation infrastructure,ensuring road safety through timely and accurate highway inspection has become increasingly critical.Traditional manual inspection methods are not only time-consuming and labor-intensive,but they also struggle to provide consistent,high-precision detection and realtime monitoring of pavement surface defects.To overcome these limitations,we propose an Automatic Recognition of PavementDefect(ARPD)algorithm,which leverages unmanned aerial vehicle(UAV)-based aerial imagery to automate the inspection process.The ARPD framework incorporates a backbone network based on the Selective State Space Model(S3M),which is designed to capture long-range temporal dependencies.This enables effective modeling of dynamic correlations among redundant and often repetitive structures commonly found in road imagery.Furthermore,a neck structure based on Semantics and Detail Infusion(SDI)is introduced to guide cross-scale feature fusion.The SDI module enhances the integration of low-level spatial details with high-level semantic cues,thereby improving feature expressiveness and defect localization accuracy.Experimental evaluations demonstrate that theARPDalgorithm achieves a mean average precision(mAP)of 86.1%on a custom-labeled pavement defect dataset,outperforming the state-of-the-art YOLOv11 segmentation model.The algorithm also maintains strong generalization ability on public datasets.These results confirm that ARPD is well-suited for diverse real-world applications in intelligent,large-scale highway defect monitoring and maintenance planning.展开更多
Transient electromagnetic methods are increasingly adopted for field investigation of oil pollution because they provide rapid,non-invasive imaging of subsurface electrical conductivity across depths relevant to vados...Transient electromagnetic methods are increasingly adopted for field investigation of oil pollution because they provide rapid,non-invasive imaging of subsurface electrical conductivity across depths relevant to vadose-zone impacts,groundwater plumes,and coastal transition zones.This review synthesizes recent advances that have expanded TEM(Transient Electromagnetic Method)’s environmental applicability,including higher dynamic range receivers,multi-moment acquisition that improves shallow-to-deep sensitivity,and diversified deployment platforms spanning ground,mobile/towed,airborne,and coastal/marine configurations,with emerging UAV(Unmanned Aerial Vehicle)options for constrained access.We emphasize the electrical and geochemical basis of hydrocarbon-related signatures,showing why fresh releases may appear resistive through NAPL(Non-Aqueous Phase Liquid)displacement of conductive pore water,whereas aged contamination often produces conductive responses driven by biodegradation,redox evolution,and elevated ionic strength.Because these responses are non-unique and can be confounded by clay-rich lithology,salinity gradients,temperature variability,and cultural infrastructure,contemporary interpretation has shifted toward process-consistent conceptual site models and uncertainty-aware products that communicate depth of investigation and resolution limits.A thematic synthesis of field applications indicates TEM is most reliable for mapping hydrogeological architecture,delineating plausible plume corridors,prioritizing intrusive sampling,and supporting monitoring where repeatability and background variability are controlled.The review concludes that TEM delivers the greatest decision value when integrated in a weight-of-evidence framework with hydrogeology,geochemistry,and targeted ground truth,and it highlights future needs in standardized reporting,robust time-lapse appraisal,and stronger petrophysical links to hydrocarbon transformation.展开更多
To address the issue of transient low-voltage instability in AC-DC hybrid power systems following large disturbances,conventional voltage assessment and control strategies typically adopt a sequential“assess-then-act...To address the issue of transient low-voltage instability in AC-DC hybrid power systems following large disturbances,conventional voltage assessment and control strategies typically adopt a sequential“assess-then-act”paradigm,which struggles to simultaneously meet the requirements for both high accuracy and rapid response.This paper proposes a transient voltage assessment and control method based on a hybrid neural network incorporated with an improved snow ablation optimization(ISAO)algorithm.The core innovation of the proposed method lies in constructing an intelligent“physics-informed and neural network-integrated”framework,which achieves the integration of stability assessment and control strategy generation.Firstly,to construct a highly correlated input set,response characteristics reflecting the system’s voltage stable/unstable states are screened.Simultaneously,the transient voltage severity index(TVSI)is introduced as a comprehensive metric to quantify the system’s post-disturbance transient voltage performance.Furthermore,the load bus voltage sensitivity index(LVSI)is defined as the ratio of the voltage change magnitude at a load node(or bus)to the change in the system-level TVSI,thereby pinpointing the response characteristics of critical load nodes.Secondly,both the transient voltage stability assessment result and its corresponding under-voltage load shedding(UVLS)control amount are jointly utilized as the outputs of the response-driven model.Subsequently,the snow ablation optimization(SAO)algorithm is enhanced using a good point set strategy and a Gaussian mutation strategy.This improved algorithm is then employed to optimize the key hyperparameters of the hybrid neural network.Finally,the superiority of the proposed method is validated on a modified CEPRI-36 system and an actual power grid case.Comparisons with various artificial intelligence methods demonstrate its significant advantages in model speed and accuracy.Additionally,when compared to traditional emergency control schemes and UVLS strategies,the proposed method exhibits exceptional rapidness and real-time capability in control decision-making.展开更多
Caffeic acid-O-methyltransferase(COMT)is a crucial enzyme in the phenylpropanoid metabolic pathway,with significant roles in both the lignin and coumarin pathways.The function of COMT in plant disease resistance has b...Caffeic acid-O-methyltransferase(COMT)is a crucial enzyme in the phenylpropanoid metabolic pathway,with significant roles in both the lignin and coumarin pathways.The function of COMT in plant disease resistance has been demonstrated in several species.Our research identified the potato COMT gene family on a genome-wide scale and StCOMT1 as a candidate gene for enhancing potato disease resistance under DON induction through phylogenetic analyses combined with previously identified metabolic differences and weighted gene co-expression network analysis(WGCNA)results.In order to better understand the function of StCOMT1,heterologous expression and overexpression assays were conducted.StCOMT1 is localized in chloroplasts and was found to catalyze the methylation of substrates to produce ferulic acid and melatonin in vitro.Physiological parameters showed that,compared with wild-type potato plants,StCOMT1-overexpressing plants infected with Fusarium sporotrichioides exhibited smaller lesion areas and lower reactive oxygen species(ROS)levels.High-performance liquid chromatography(HPLC)and RT-qPCR analyses revealed organ-specific accumulation of coumarin-related compounds and organ-specific expression of their corresponding genes in StCOMT1-overexpressing plants post-inoculation.The results indicate that StCOMT1 overexpression in potatoes enhanced resistance to F.sporotrichioides by enhancing reactive oxygen species clearance and promoting organ-specific accumulation of coumarin-related compounds.展开更多
Based on multi-source time-series data from 2017 to 2024,this study comprehensively employed Theil-Sen trend analysis,Mann-Kendall test,random forest regression model,and spatial and temporal lag correlation analysis ...Based on multi-source time-series data from 2017 to 2024,this study comprehensively employed Theil-Sen trend analysis,Mann-Kendall test,random forest regression model,and spatial and temporal lag correlation analysis to systematically investigate the variation characteristics of NDVI and their associated mechanisms with land use changes and groundwater depth in the study area.The results indicate that vegetation activity showed overall significant improvement during the study period,with 60.93%of the area exhibiting significant greening trends and only 6.55%showing degradation.The trajectory characteristics of land use changes could explain approximately 79.64%of the variation in NDVI trends,but their driving effects demonstrated significant spatial heterogeneity,with core driving zones accounting for 79.22%of the area.Groundwater depth showed an overall weak negative correlation with NDVI(r=-0.0464),but exhibited significant lag effects,and the correlation coefficient increased to-0.1763 when there was a lag of 3 months.The study concludes that regional vegetation changes were primarily driven by land use activities,while the influences of groundwater showed spatial and temporal lag characteristics.Ecological restoration policies should integrate land use optimization with water resource management,and fully consider the spatial heterogeneity and temporal lag effects of driving mechanisms.展开更多
This paper proposes an equivalent modeling method for photovoltaic(PV)power stations via a particle swarm optimization(PSO)K-means clustering(KMC)algorithm with passive filter parameter clustering to address the compl...This paper proposes an equivalent modeling method for photovoltaic(PV)power stations via a particle swarm optimization(PSO)K-means clustering(KMC)algorithm with passive filter parameter clustering to address the complexities,simulation time cost and convergence problems of detailed PV power station models.First,the amplitude–frequency curves of different filter parameters are analyzed.Based on the results,a grouping parameter set for characterizing the external filter characteristics is established.These parameters are further defined as clustering parameters.A single PV inverter model is then established as a prerequisite foundation.The proposed equivalent method combines the global search capability of PSO with the rapid convergence of KMC,effectively overcoming the tendency of KMC to become trapped in local optima.This approach enhances both clustering accuracy and numerical stability when determining equivalence for PV inverter units.Using the proposed clustering method,both a detailed PV power station model and an equivalent model are developed and compared.Simulation and hardwarein-loop(HIL)results based on the equivalent model verify that the equivalent method accurately represents the dynamic characteristics of PVpower stations and adapts well to different operating conditions.The proposed equivalent modeling method provides an effective analysis tool for future renewable energy integration research.展开更多
Understanding the molecular responses of tea leaves to mechanical stress is crucial for elucidating the mechanisms of post-harvest quality formation during oolong tea processing.This study employed an integrated multi...Understanding the molecular responses of tea leaves to mechanical stress is crucial for elucidating the mechanisms of post-harvest quality formation during oolong tea processing.This study employed an integrated multi-omics strategy to characterize the changes and interactions among metabolomic(MB),transcriptomic(TX),and proteomic(PT)profiles in mechanically stressed tea leaves.Mechanical stress initially activated damage-associated molecular patterns(DAMPs),including Ca^(2+)signaling,jasmonic acid signaling,and glutathione metabolism pathways.These processes subsequently induced quality-related metabolic pathways(QRMPs),particularly α-linolenic acid and phenylalanine metabolism.Upregulated expression of LOX,ADH1,and PAR genes,together with the increased abundance of their encoded proteins,respectively promoted the accumulation of jasmine lactone,benzyl alcohol,and 2-phenylethanol.These findings indicate that mechanical stress influences the metabolite biosynthesis in tea leaves through coordinated molecular responses.This study provides new insights into the molecular mechanisms underlying tea leaf responses to mechanical stress and a foundation for future investigations into how early molecular events may contribute to post-harvest metabolic changes during oolong tea processing.展开更多
The impact of spinal cord injury(SCI)on the immune system is increasingly recognized in a field traditionally focused on motor impairments.SCI can seriously affect the immune system by progressively disrupting the reg...The impact of spinal cord injury(SCI)on the immune system is increasingly recognized in a field traditionally focused on motor impairments.SCI can seriously affect the immune system by progressively disrupting the regulatory mechanisms that control immune responses.This dysregulation varies widely among patients and can evolve over time,ranging from systemic inflammatory responses to immunosuppression,greatly contributing to the morbidity and mortality of individuals with SCI(Bao et al.,2011;Brennan et al.,2024).展开更多
With the growing complexity and decentralization of network systems,the attack surface has expanded,which has led to greater concerns over network threats.In this context,artificial intelligence(AI)-based network intr...With the growing complexity and decentralization of network systems,the attack surface has expanded,which has led to greater concerns over network threats.In this context,artificial intelligence(AI)-based network intrusion detection systems(NIDS)have been extensively studied,and recent efforts have shifted toward integrating distributed learning to enable intelligent and scalable detection mechanisms.However,most existing works focus on individual distributed learning frameworks,and there is a lack of systematic evaluations that compare different algorithms under consistent conditions.In this paper,we present a comprehensive evaluation of representative distributed learning frameworks—Federated Learning(FL),Split Learning(SL),hybrid collaborative learning(SFL),and fully distributed learning—in the context of AI-driven NIDS.Using recent benchmark intrusion detection datasets,a unified model backbone,and controlled distributed scenarios,we assess these frameworks across multiple criteria,including detection performance,communication cost,computational efficiency,and convergence behavior.Our findings highlight distinct trade-offs among the distributed learning frameworks,demonstrating that the optimal choice depends strongly on systemconstraints such as bandwidth availability,node resources,and data distribution.This work provides the first holistic analysis of distributed learning approaches for AI-driven NIDS and offers practical guidelines for designing secure and efficient intrusion detection systems in decentralized environments.展开更多
After coal seam mining,the overlying rock strata above the goaf are subjected to long-term stress and eventually undergo failure.Under mining-induced disturbances,the strata develop fractures at various angles,which s...After coal seam mining,the overlying rock strata above the goaf are subjected to long-term stress and eventually undergo failure.Under mining-induced disturbances,the strata develop fractures at various angles,which significantly influence failure modes and the morphology of gas flow channels.This study employed multistage loading experiments,numerical simulations,three-dimensional reconstruction,and image recognition to investigate the fragmentation process of rocks with different initial fracture angles under multistage loading.The results show that variations in the initial fracture angle affect the transmission of contact forces among rock particles.As the angle increases,the transmission pattern shifts from a uniform distribution to one extending along the direction of the fracture.Rocks with small initial fracture angles tend to experience tensile-dominated failure,with most of the material subjected to longitudinal loading,resulting in reduced strength.Fractures propagate from the central region of the initial fracture,producing a complex internal fracture network.The proportion of fracture channels varies considerably across regions,creating multiple zones of velocity variation in the gas flow.In contrast,rocks with large initial fracture angles are more susceptible to shear failure,with the primary load-bearing zones aligned along the inclined fracture direction.As a result,the influence on surrounding regions is limited,improving the rock's load-bearing capacity under multistage loading.In these cases,the distribution and proportion of fracture channels become more uniform,promoting more stable gas flow within the channels.Overall,these findings provide theoretical insights into how initial fracture angles govern rock failure patterns and gas flow characteristics.展开更多
The electric double layer(EDL)at the electrochemical interface is crucial for ion transport,charge transfer,and surface reactions in aqueous rechargeable zinc batteries(ARZBs).However,Zn anodes routinely encounter per...The electric double layer(EDL)at the electrochemical interface is crucial for ion transport,charge transfer,and surface reactions in aqueous rechargeable zinc batteries(ARZBs).However,Zn anodes routinely encounter persistent dendrite growth and parasitic reactions,driven by the inhomogeneous charge distribution and water-dominated environment within the EDL.Compounding this,classical EDL theory,rooted in meanfield approximations,further fails to resolve molecular-scale interfacial dynamics under battery-operating conditions,limiting mechanistic insights.Herein,we established a multiscale theoretical calculation framework from single molecular characteristics to interfacial ion distribution,revealing the EDL’s structure and interactions between different ions and molecules,which helps us understand the parasitic processes in depth.Simulations demonstrate that water dipole and sulfate ion adsorption at the inner Helmholtz plane drives severe hydrogen evolution and by-product formation.Guided by these insights,we engineered a“water-poor and anion-expelled”EDL using 4,1’,6’-trichlorogalactosucrose(TGS)as an electrolyte additive.As a result,Zn||Zn symmetric cells with TGS exhibited stable cycling for over 4700 h under a current density of 1 mA cm^(−2),while NaV_(3)O_(8)·1.5H_(2)O-based full cells kept 90.4%of the initial specific capacity after 800 cycles at 5 A g^(−1).This work highlights the power of multiscale theoretical frameworks to unravel EDL complexities and guide high-performance ARZB design through integrated theory-experiment approaches.展开更多
Aqueous zinc-ion batteries(AZIBs)offer promising safety and affordability,but suffer from dendritic Zn growth and parasitic side reactions at the electrode-electrolyte interface.Herein,we construct a dual-region inter...Aqueous zinc-ion batteries(AZIBs)offer promising safety and affordability,but suffer from dendritic Zn growth and parasitic side reactions at the electrode-electrolyte interface.Herein,we construct a dual-region interfacial modulation framework by molecularly reconfiguring the Helmholtz double layer via trace methyl methacrylate(MMA).Exploiting its amphiphilic and functionally asymmetric architecture,MMA enables a coordinated interfacial reconstruction that disrupts Zn^(2+)solvation in the outer Helmholtz plane,builds a chemisorbed coordination layer in the inner plane,and modulates local interfacial chemistry with spatial precision.This dualregion regulation collectively suppresses water reactivity,facilitates Zn^(2+)desolvation,and drives crystallo-graphically preferred deposition along the(101)plane,promoting lateral growth and mitigating dendrite for-mation.As a result,symmetric Zn||Zn cells exhibit over 4200 h of stable cycling at 1 mA cm^(-2) and maintain 1100 h of operation at 2 mA cm^(-2),even at 0℃.Zn||Ti half-cells achieve a Coulombic efficiency of 99.83%,while Zn||NH_(4)V_(4)O_(10) full cells deliver 93.92%capacity retention after 400 cycles at 2 A g^(-1),and preserve 85.3%after 300 cycles at 0℃.This work demonstrates a scalable,mechanism-driven electrolyte design paradigm for dendrite-free and high-performance aqueous Zn metal batteries.展开更多
Atmospheric carbon dioxide(CO_(2))levels are escalating at an unprecedented rate,leading to the phenomenon of ocean acidification(OA).Parental exposure to acidification has the potential to enhance offspring resilienc...Atmospheric carbon dioxide(CO_(2))levels are escalating at an unprecedented rate,leading to the phenomenon of ocean acidification(OA).Parental exposure to acidification has the potential to enhance offspring resilience through cross-generation plasticity.In this study,we analyzed larval growth and transcriptomic profiles in the Pacific oyster,Crassostrea gigas,a species of significant ecological relevance,under both control and elevated CO_(2)conditions experienced by their parental generation.Our findings indicate that the oyster populations exposed to OA exhibited a higher incidence of abnormalities during the D-shaped larval stage,followed by accelerated growth at the eyed stage.Through a comparative transcriptomic investigation of eyed larvae(25 d after fertilization),we observed that parental exposure to OA substantially influenced the gene expression in the offspring.Genes associated with lipid catabolism and shell formation were notably upregulated in oysters with parental OA exposure,potentially playing a role in cross-generational conditioning and conferring resilience to OA stressors.These results underscore the profound impact of OA on oyster larval development via cross-generational mechanisms and shed light on the molecular underpinnings of cross-generation plasticity.展开更多
Laser-induced aerosols,predominantly submicron in size,pose significant environmental and health risks during the decommissioning of nuclear reactors.This study experimentally investigated the removal of laser-generat...Laser-induced aerosols,predominantly submicron in size,pose significant environmental and health risks during the decommissioning of nuclear reactors.This study experimentally investigated the removal of laser-generated aerosol particles using a water spray system integrated with an innovative system for pre-injecting electrically charged mist in our facility.To simulate aerosol generation in reactor decommissioning,a high-power laser was used to irradiate various materials(including stainless steel,carbon steel,and concrete),generating aerosol particles that were agglomerated with injected water mist and subsequently scavenged by water spray.Experimental results demonstrate enhanced aerosol removal via aerosol-mist agglomeration,with charged mist significantly improving particle capture by increasing wettability and size.The average improvements for the stainless steel,carbon steel,and concrete were 40%,44%,and 21%,respectively.The results of experiments using charged mist with different polarities(both positive and negative)and different surface coatings reveal that the dominant polarity of aerosols varies with the irradiated materials,influenced by their crystal structure and electron emission properties.Notably,surface coatings such as ZrO_(2)and CeO_(2)were found to possibly alter aerosol charging characteristics,thereby affecting aerosol removal efficiency with charged mist configurations.The innovative aerosol-mist agglomeration approach shows promise in mitigating radiation exposure,ensuring environmental safety,and reducing contaminated water during reactor dismantling.This study contributes critical knowledge for the development of advanced aerosol management strategies for nuclear reactor decommissioning.The understanding obtained in this work is also expected to be useful for various environmental and chemical engineering applications such as gas decontamination,air purification,and pollution control.展开更多
Challenges in the prevention and treatment of mild cognitive impairment associated with Alzheimer's disease:Increased life expectancy due to advancements in medical care has given rise to an aging population,accom...Challenges in the prevention and treatment of mild cognitive impairment associated with Alzheimer's disease:Increased life expectancy due to advancements in medical care has given rise to an aging population,accompanied by a surge in the incidence of incurable neurodegenerative diseases(NDDs).These diseases primarily affect the cognitive and behavioral functions of older adults by impacting brain activity.Mild cognitive impairment(MCI)is a neurodegenerative condition that affects a significant portion of the population.展开更多
Lithium-oxygen(Li-O2)batteries are perceived as a promising breakthrough in sustainable electrochemical energy storage,utilizing ambient air as an energy source,eliminating the need for costly cathode materials,and of...Lithium-oxygen(Li-O2)batteries are perceived as a promising breakthrough in sustainable electrochemical energy storage,utilizing ambient air as an energy source,eliminating the need for costly cathode materials,and offering the highest theoretical energy density(~3.5 k Wh kg^(-1))among discussed candidates.Contributing to the poor cycle life of currently reported Li-O_(2)cells is singlet oxygen(1O_(2))formation,inducing parasitic reactions,degrading key components,and severely deteriorating cell performance.Here,we harness the chirality-induced spin selectivity effect of chiral cobalt oxide nanosheets(Co_(3)O_(4)NSs)as cathode materials to suppress 1O_(2)in Li-O_(2)batteries for the first time.Operando photoluminescence spectroscopy reveals a 3.7-fold and 3.23-fold reduction in 1O_(2)during discharge and charge,respectively,compared to conventional carbon paperbased cells,consistent with differential electrochemical mass spectrometry results,which indicate a near-theoretical charge-to-O_(2)ratio(2.04 e-/O_(2)).Density functional theory calculations demonstrate that chirality induces a peak shift near the Fermi level,enhancing Co 3d-O 2p hybridization,stabilizing reaction intermediates,and lowering activation barriers for Li_(2)O_(2)formation and decomposition.These findings establish a new strategy for improving the stability and energy efficiency of sustainable Li-O_(2)batteries,abridging the current gap to commercialization.展开更多
AIM: To provide a comprehensive overview of clinical studies on the clinical picture of Internet-use related addictions from a holistic perspective. A literature search was conducted using the database Web of Science....AIM: To provide a comprehensive overview of clinical studies on the clinical picture of Internet-use related addictions from a holistic perspective. A literature search was conducted using the database Web of Science.METHODS: Over the last 15 years, the number of Internet users has increased by 1000%, and at the same time, research on addictive Internet use has proliferated. Internet addiction has not yet been understood very well, and research on its etiology and natural history is still in its infancy. In 2013, the American Psychiatric Association included Internet Gaming Disorder in the appendix of the updated version of the Diagnostic and Statistical Manual for Mental Disorders(DSM-5) as condition that requires further research prior to official inclusion in the main manual, with important repercussions for research and treatment. To date, reviews have focused on clinical and treatment studies of Internet addiction and Internet Gaming Disorder. This arguably limits the analysis to a specific diagnosis of a potential disorder that has not yet been officially recognised in the Western world, rather than a comprehensive and inclusive investigation of Internet-use related addictions(including problematic Internet use) more generally. RESULTS: The systematic literature review identified a total of 46 relevant studies. The included studies used clinical samples, and focused on characteristics of treatment seekers and online addiction treatment. Four main types of clinical research studies were identified, namely research involving(1) treatment seeker characteristics;(2) psychopharmacotherapy;(3) psychological therapy; and(4) combined treatment. CONCLUSION: A consensus regarding diagnostic criteria and measures is needed to improve reliability across studies and to develop effective and efficient treatment approaches for treatment seekers.展开更多
文摘With the rapid development of artificial intelligence technology,the education sector is gradually exploring how AI tools to empower subject teaching.In this paper,the first lesson of Japan published by People s Education Press in the second semester of seventh grade is taken as an example,focusing on the feasibility of using AI tools for lesson preparation.Through the Meta Sota AI special topic,Kimi,deepseek,and Baidu AI images,lesson preparation is completed.Using Coze intelligent agents,interactive learning scenarios are developed to complete teaching design.Research has shown that AI technology can effectively improve the efficiency and quality of lesson preparation,and can assist in the implementation of core competencies in geography.This paper can provide a reference for the operability of AI empowering educational and teaching activities.
基金supported by National Key Research and Development Technology Project program(SQ2022YFB2400136).
文摘To enable distributed PV to adapt to variations in power grid strength and achieve stable grid connection while enhancing operational flexibility,it is essential to configure grid-connected inverters with an integrated grid-following control mode,allowing smooth switching between GFL and GFM modes.First,impedance models of GFL and GFM PV energy storage VSG systems were established,and grid stability was analyzed.Second,an online impedance identification method based on voltage fluctuation data screening was proposed to enhance the accuracy of impedance identification.Additionally,a PV energy storage GFM/GFL VSG smooth switching method based on current inner loop compensation was introduced to achieve stable grid-connected operation of distributed photovoltaics under changes in strong and weak power grids.Finally,a grid stability analysis was conducted on the multi-machine parallel PV ESS,and a simulation model of a multi-machine parallel PV ESS based on current inner loop compensation was established for testing.Results showed that,compared to using a single GFM or single GFL control for the PV VSG system,the smooth switching method of multi-machine parallel PV ESS effectively suppresses system resonance under variations in power grid strength,enabling adaptive and stable grid-connected operations of distributed PV.
基金financially supported by the Key R&D Program of Shandong Province,China (Grant No. 2023ZLYS01)the National Natural Science Foundation of China (Grant No. 42106172)+8 种基金the Natural Science Foundation of Shandong Province (Grant Nos.ZR2024MD003, ZR2023QD023, ZR2023QD066 and ZR2023QD018)the Consulting and Researching Project of the Chinese Academy of Engineering(Grant Nos. 2024-DFZD-29, 2022-DFZD-35, 2022-XY-21, and 2021-XBZD-13-31)Qingdao Marine Science and Technology Innovation Project (Grant No. 23-1-3-hygg-6-hy)the Natural Science Foundation of Qingdao (Grant Nos. 23-2-1-58-zyyd-jch and 23-2-1-72-zyyd-jch)Project Plan of Pilot Project of Integration of Science,Education and Industry of Qilu University of Technology (Shandong Academy of Sciences)(Grant No. 2023PX035)the Visiting and Training Program for Teachers from Ordinary Undergraduate Universities in Shandong Provincethe Open Fund of Shandong Key Laboratory of Marine Ecological Environment and Disaster Prevention and Mitigation (Grant No. 202302)Major Innovation Project for the Science Education Industry Integration Pilot Project of Qilu University of Technology (Shandong Academy of Sciences)(Grant Nos. 2023HYZX01, and2023JBZ03)University-Industry Collaborative Education Program (Grant No. 202102245036)。
文摘In recent years, with the development of technologies such as the Internet of Things(Io T), big data and cloud computing, digital twin technology has gradually been applied in marine research. The digital twin realizes real-time monitoring, analysis and optimization of the state and behavior of a physical object or system by creating a virtual model. Research shows that digital twin technology has extensive application potential in ship design, marine resource development, marine equipment engineering design and optimization, marine ecological protection and early warning of disasters. Although digital twin technology has great potential in marine research, it also faces many challenges, including the complexity of data acquisition and processing, the accuracy and real-time performance of model construction, and the need for multidisciplinary cross-integration. An in-depth analysis of the technical bottlenecks and future development directions will provide an important reference for subsequent research and promote the further application and development of digital twin technology in marine research.
基金supported in part by the Technical Service for the Development and Application of an Intelligent Visual Management Platformfor Expressway Construction Progress Based on BIM Technology(grant NO.JKYZLX-2023-09)in partby the Technical Service for the Development of an Early Warning Model in the Research and Application of Key Technologies for Tunnel Operation Safety Monitoring and Early Warning Based on Digital Twin(grant NO.JK-S02-ZNGS-202412-JISHU-FA-0035)sponsored by Yunnan Transportation Science Research Institute Co.,Ltd.
文摘With the rapid development of transportation infrastructure,ensuring road safety through timely and accurate highway inspection has become increasingly critical.Traditional manual inspection methods are not only time-consuming and labor-intensive,but they also struggle to provide consistent,high-precision detection and realtime monitoring of pavement surface defects.To overcome these limitations,we propose an Automatic Recognition of PavementDefect(ARPD)algorithm,which leverages unmanned aerial vehicle(UAV)-based aerial imagery to automate the inspection process.The ARPD framework incorporates a backbone network based on the Selective State Space Model(S3M),which is designed to capture long-range temporal dependencies.This enables effective modeling of dynamic correlations among redundant and often repetitive structures commonly found in road imagery.Furthermore,a neck structure based on Semantics and Detail Infusion(SDI)is introduced to guide cross-scale feature fusion.The SDI module enhances the integration of low-level spatial details with high-level semantic cues,thereby improving feature expressiveness and defect localization accuracy.Experimental evaluations demonstrate that theARPDalgorithm achieves a mean average precision(mAP)of 86.1%on a custom-labeled pavement defect dataset,outperforming the state-of-the-art YOLOv11 segmentation model.The algorithm also maintains strong generalization ability on public datasets.These results confirm that ARPD is well-suited for diverse real-world applications in intelligent,large-scale highway defect monitoring and maintenance planning.
文摘Transient electromagnetic methods are increasingly adopted for field investigation of oil pollution because they provide rapid,non-invasive imaging of subsurface electrical conductivity across depths relevant to vadose-zone impacts,groundwater plumes,and coastal transition zones.This review synthesizes recent advances that have expanded TEM(Transient Electromagnetic Method)’s environmental applicability,including higher dynamic range receivers,multi-moment acquisition that improves shallow-to-deep sensitivity,and diversified deployment platforms spanning ground,mobile/towed,airborne,and coastal/marine configurations,with emerging UAV(Unmanned Aerial Vehicle)options for constrained access.We emphasize the electrical and geochemical basis of hydrocarbon-related signatures,showing why fresh releases may appear resistive through NAPL(Non-Aqueous Phase Liquid)displacement of conductive pore water,whereas aged contamination often produces conductive responses driven by biodegradation,redox evolution,and elevated ionic strength.Because these responses are non-unique and can be confounded by clay-rich lithology,salinity gradients,temperature variability,and cultural infrastructure,contemporary interpretation has shifted toward process-consistent conceptual site models and uncertainty-aware products that communicate depth of investigation and resolution limits.A thematic synthesis of field applications indicates TEM is most reliable for mapping hydrogeological architecture,delineating plausible plume corridors,prioritizing intrusive sampling,and supporting monitoring where repeatability and background variability are controlled.The review concludes that TEM delivers the greatest decision value when integrated in a weight-of-evidence framework with hydrogeology,geochemistry,and targeted ground truth,and it highlights future needs in standardized reporting,robust time-lapse appraisal,and stronger petrophysical links to hydrocarbon transformation.
基金supported by the State Grid Shanxi Electric Power Company science and technology project“Research on Key Technologies for Voltage Stability Analysis and Control of UHV Transmission Sending-End Grid with Large-Scale Integration of Wind-Solar-Storage Systems”(520530240026).
文摘To address the issue of transient low-voltage instability in AC-DC hybrid power systems following large disturbances,conventional voltage assessment and control strategies typically adopt a sequential“assess-then-act”paradigm,which struggles to simultaneously meet the requirements for both high accuracy and rapid response.This paper proposes a transient voltage assessment and control method based on a hybrid neural network incorporated with an improved snow ablation optimization(ISAO)algorithm.The core innovation of the proposed method lies in constructing an intelligent“physics-informed and neural network-integrated”framework,which achieves the integration of stability assessment and control strategy generation.Firstly,to construct a highly correlated input set,response characteristics reflecting the system’s voltage stable/unstable states are screened.Simultaneously,the transient voltage severity index(TVSI)is introduced as a comprehensive metric to quantify the system’s post-disturbance transient voltage performance.Furthermore,the load bus voltage sensitivity index(LVSI)is defined as the ratio of the voltage change magnitude at a load node(or bus)to the change in the system-level TVSI,thereby pinpointing the response characteristics of critical load nodes.Secondly,both the transient voltage stability assessment result and its corresponding under-voltage load shedding(UVLS)control amount are jointly utilized as the outputs of the response-driven model.Subsequently,the snow ablation optimization(SAO)algorithm is enhanced using a good point set strategy and a Gaussian mutation strategy.This improved algorithm is then employed to optimize the key hyperparameters of the hybrid neural network.Finally,the superiority of the proposed method is validated on a modified CEPRI-36 system and an actual power grid case.Comparisons with various artificial intelligence methods demonstrate its significant advantages in model speed and accuracy.Additionally,when compared to traditional emergency control schemes and UVLS strategies,the proposed method exhibits exceptional rapidness and real-time capability in control decision-making.
基金supported by the National Natural Science Foundation of China(U22A20443)the Heilongjiang Provincial Research Institutes Scientific Research Operating Expenses Project,China(CZKYF2023-1-B020)+1 种基金the Key Research and Development Plan Project of Heilongjiang Province,China(GA23B015)the Young Scientists Fund of the National Natural Science Foundation of China(32201717)。
文摘Caffeic acid-O-methyltransferase(COMT)is a crucial enzyme in the phenylpropanoid metabolic pathway,with significant roles in both the lignin and coumarin pathways.The function of COMT in plant disease resistance has been demonstrated in several species.Our research identified the potato COMT gene family on a genome-wide scale and StCOMT1 as a candidate gene for enhancing potato disease resistance under DON induction through phylogenetic analyses combined with previously identified metabolic differences and weighted gene co-expression network analysis(WGCNA)results.In order to better understand the function of StCOMT1,heterologous expression and overexpression assays were conducted.StCOMT1 is localized in chloroplasts and was found to catalyze the methylation of substrates to produce ferulic acid and melatonin in vitro.Physiological parameters showed that,compared with wild-type potato plants,StCOMT1-overexpressing plants infected with Fusarium sporotrichioides exhibited smaller lesion areas and lower reactive oxygen species(ROS)levels.High-performance liquid chromatography(HPLC)and RT-qPCR analyses revealed organ-specific accumulation of coumarin-related compounds and organ-specific expression of their corresponding genes in StCOMT1-overexpressing plants post-inoculation.The results indicate that StCOMT1 overexpression in potatoes enhanced resistance to F.sporotrichioides by enhancing reactive oxygen species clearance and promoting organ-specific accumulation of coumarin-related compounds.
基金Supported by the Key Special Project for Water Conservancy Science and Technology of Ordos City(ESKJ2023-001).
文摘Based on multi-source time-series data from 2017 to 2024,this study comprehensively employed Theil-Sen trend analysis,Mann-Kendall test,random forest regression model,and spatial and temporal lag correlation analysis to systematically investigate the variation characteristics of NDVI and their associated mechanisms with land use changes and groundwater depth in the study area.The results indicate that vegetation activity showed overall significant improvement during the study period,with 60.93%of the area exhibiting significant greening trends and only 6.55%showing degradation.The trajectory characteristics of land use changes could explain approximately 79.64%of the variation in NDVI trends,but their driving effects demonstrated significant spatial heterogeneity,with core driving zones accounting for 79.22%of the area.Groundwater depth showed an overall weak negative correlation with NDVI(r=-0.0464),but exhibited significant lag effects,and the correlation coefficient increased to-0.1763 when there was a lag of 3 months.The study concludes that regional vegetation changes were primarily driven by land use activities,while the influences of groundwater showed spatial and temporal lag characteristics.Ecological restoration policies should integrate land use optimization with water resource management,and fully consider the spatial heterogeneity and temporal lag effects of driving mechanisms.
基金supported by the Research Project of China Southern Power Grid(No.056200KK52222031).
文摘This paper proposes an equivalent modeling method for photovoltaic(PV)power stations via a particle swarm optimization(PSO)K-means clustering(KMC)algorithm with passive filter parameter clustering to address the complexities,simulation time cost and convergence problems of detailed PV power station models.First,the amplitude–frequency curves of different filter parameters are analyzed.Based on the results,a grouping parameter set for characterizing the external filter characteristics is established.These parameters are further defined as clustering parameters.A single PV inverter model is then established as a prerequisite foundation.The proposed equivalent method combines the global search capability of PSO with the rapid convergence of KMC,effectively overcoming the tendency of KMC to become trapped in local optima.This approach enhances both clustering accuracy and numerical stability when determining equivalence for PV inverter units.Using the proposed clustering method,both a detailed PV power station model and an equivalent model are developed and compared.Simulation and hardwarein-loop(HIL)results based on the equivalent model verify that the equivalent method accurately represents the dynamic characteristics of PVpower stations and adapts well to different operating conditions.The proposed equivalent modeling method provides an effective analysis tool for future renewable energy integration research.
基金supported by the National Key Research and Development Program of China(2022YFD2101101)the Earmarked Fund for CARS-19+2 种基金the National Natural Science Foundation of China(32402634)the Modern Agricultural(Tea)Industry Technology System of Fujian Province,China(2025 No.593)the Special Fund for Science and Technology Innovation of Fujian Zhang Tianfu Tea Development Foundation,China(FJZTF01)。
文摘Understanding the molecular responses of tea leaves to mechanical stress is crucial for elucidating the mechanisms of post-harvest quality formation during oolong tea processing.This study employed an integrated multi-omics strategy to characterize the changes and interactions among metabolomic(MB),transcriptomic(TX),and proteomic(PT)profiles in mechanically stressed tea leaves.Mechanical stress initially activated damage-associated molecular patterns(DAMPs),including Ca^(2+)signaling,jasmonic acid signaling,and glutathione metabolism pathways.These processes subsequently induced quality-related metabolic pathways(QRMPs),particularly α-linolenic acid and phenylalanine metabolism.Upregulated expression of LOX,ADH1,and PAR genes,together with the increased abundance of their encoded proteins,respectively promoted the accumulation of jasmine lactone,benzyl alcohol,and 2-phenylethanol.These findings indicate that mechanical stress influences the metabolite biosynthesis in tea leaves through coordinated molecular responses.This study provides new insights into the molecular mechanisms underlying tea leaf responses to mechanical stress and a foundation for future investigations into how early molecular events may contribute to post-harvest metabolic changes during oolong tea processing.
基金funded by the Santa Casa Neuroscience Awards—Prize Melo e Castro for Spinal Cord Injury Research(MC-18-2021)(to AJS and NAS)by the Wings for Life Spinal Cord Research Foundation(WFL-PT-14/23)(to NAS)+2 种基金funded by national funds through the Foundation for Science and Technology(FCT)—projects UIDB/50026/2020,UIDP/50026/2020,and EXPL/MED-PAT/0931/2021-http://doi.org/10.54499/EXPL/MED PAT/0931/2021supported by the Norte Portugal Regional Operational Programme(NORTE 2020)under the PORTUGAL 2020 Partnership Agreement through the European Regional Development Fund(ERDF)(to SM)the support given by the Portuguese Foundation of Science and Technology to SM(CEECIND/01902/2017-Doi:10.54499/CEECIND/01902/2017/CP1458/CT0024),and NAS(CEECIND/04794/2007)。
文摘The impact of spinal cord injury(SCI)on the immune system is increasingly recognized in a field traditionally focused on motor impairments.SCI can seriously affect the immune system by progressively disrupting the regulatory mechanisms that control immune responses.This dysregulation varies widely among patients and can evolve over time,ranging from systemic inflammatory responses to immunosuppression,greatly contributing to the morbidity and mortality of individuals with SCI(Bao et al.,2011;Brennan et al.,2024).
基金supported by the Research year project of the KongjuNational University in 2025 and the Institute of Information&Communications Technology Planning&Evaluation(IITP)grant funded by the Korea government(MSIT)(No.RS-2024-00444170,Research and International Collaboration on Trust Model-Based Intelligent Incident Response Technologies in 6G Open Network Environment).
文摘With the growing complexity and decentralization of network systems,the attack surface has expanded,which has led to greater concerns over network threats.In this context,artificial intelligence(AI)-based network intrusion detection systems(NIDS)have been extensively studied,and recent efforts have shifted toward integrating distributed learning to enable intelligent and scalable detection mechanisms.However,most existing works focus on individual distributed learning frameworks,and there is a lack of systematic evaluations that compare different algorithms under consistent conditions.In this paper,we present a comprehensive evaluation of representative distributed learning frameworks—Federated Learning(FL),Split Learning(SL),hybrid collaborative learning(SFL),and fully distributed learning—in the context of AI-driven NIDS.Using recent benchmark intrusion detection datasets,a unified model backbone,and controlled distributed scenarios,we assess these frameworks across multiple criteria,including detection performance,communication cost,computational efficiency,and convergence behavior.Our findings highlight distinct trade-offs among the distributed learning frameworks,demonstrating that the optimal choice depends strongly on systemconstraints such as bandwidth availability,node resources,and data distribution.This work provides the first holistic analysis of distributed learning approaches for AI-driven NIDS and offers practical guidelines for designing secure and efficient intrusion detection systems in decentralized environments.
基金supported by the National Natural Science Foundation of China(Grant No.52522405)Key R&D Project of Sichuan Province of China(Regional Innovation Coop-eration)(Grant No.2025YFHZ0314).
文摘After coal seam mining,the overlying rock strata above the goaf are subjected to long-term stress and eventually undergo failure.Under mining-induced disturbances,the strata develop fractures at various angles,which significantly influence failure modes and the morphology of gas flow channels.This study employed multistage loading experiments,numerical simulations,three-dimensional reconstruction,and image recognition to investigate the fragmentation process of rocks with different initial fracture angles under multistage loading.The results show that variations in the initial fracture angle affect the transmission of contact forces among rock particles.As the angle increases,the transmission pattern shifts from a uniform distribution to one extending along the direction of the fracture.Rocks with small initial fracture angles tend to experience tensile-dominated failure,with most of the material subjected to longitudinal loading,resulting in reduced strength.Fractures propagate from the central region of the initial fracture,producing a complex internal fracture network.The proportion of fracture channels varies considerably across regions,creating multiple zones of velocity variation in the gas flow.In contrast,rocks with large initial fracture angles are more susceptible to shear failure,with the primary load-bearing zones aligned along the inclined fracture direction.As a result,the influence on surrounding regions is limited,improving the rock's load-bearing capacity under multistage loading.In these cases,the distribution and proportion of fracture channels become more uniform,promoting more stable gas flow within the channels.Overall,these findings provide theoretical insights into how initial fracture angles govern rock failure patterns and gas flow characteristics.
基金supported by the National Natural Science Foundation of China(52471240)the Natural Science Foundation of Zhejiang Province(LZ23B030003)+2 种基金the Fundamental Research Funds for the Central Universities(226-2024-00075)support from the Engineering and Physical Sciences Research Council(EPSRC,UK)RiR grant-RIR18221018-1EU COST CA23155。
文摘The electric double layer(EDL)at the electrochemical interface is crucial for ion transport,charge transfer,and surface reactions in aqueous rechargeable zinc batteries(ARZBs).However,Zn anodes routinely encounter persistent dendrite growth and parasitic reactions,driven by the inhomogeneous charge distribution and water-dominated environment within the EDL.Compounding this,classical EDL theory,rooted in meanfield approximations,further fails to resolve molecular-scale interfacial dynamics under battery-operating conditions,limiting mechanistic insights.Herein,we established a multiscale theoretical calculation framework from single molecular characteristics to interfacial ion distribution,revealing the EDL’s structure and interactions between different ions and molecules,which helps us understand the parasitic processes in depth.Simulations demonstrate that water dipole and sulfate ion adsorption at the inner Helmholtz plane drives severe hydrogen evolution and by-product formation.Guided by these insights,we engineered a“water-poor and anion-expelled”EDL using 4,1’,6’-trichlorogalactosucrose(TGS)as an electrolyte additive.As a result,Zn||Zn symmetric cells with TGS exhibited stable cycling for over 4700 h under a current density of 1 mA cm^(−2),while NaV_(3)O_(8)·1.5H_(2)O-based full cells kept 90.4%of the initial specific capacity after 800 cycles at 5 A g^(−1).This work highlights the power of multiscale theoretical frameworks to unravel EDL complexities and guide high-performance ARZB design through integrated theory-experiment approaches.
基金supported by the National Natural Science Foundation of China(Grant Nos.52125405 and U22A20108)Thailand Science Research and Innovation Fund Chulalongkorn University,National Research Council of Thailand(NRCT)and Chulalongkorn University(N42A660383).D.D.Zhang would like to thank the financial support from the Scientific Research Fund of Liaoning Provincial Education Department of China(No.JYTQN2023289)+3 种基金Liaoning Provincial Science and Technology Joint Plan(Fund)Project(No.2023-BSBA-259)and the opening project of State Key Laboratory of Metastable Materials Science and Technology,Yanshan University(No.202404).J.Cao would like to acknowledge the support from National Natural Science Foundation of China(Grant No.52402279)China Postdoctoral Science Foundation Special Funding(Grant Nos.2025T180002,2024M751753)the opening project of State Key Laboratory of Metastable Materials Science and Technology(Yanshan University)(No.202401).
文摘Aqueous zinc-ion batteries(AZIBs)offer promising safety and affordability,but suffer from dendritic Zn growth and parasitic side reactions at the electrode-electrolyte interface.Herein,we construct a dual-region interfacial modulation framework by molecularly reconfiguring the Helmholtz double layer via trace methyl methacrylate(MMA).Exploiting its amphiphilic and functionally asymmetric architecture,MMA enables a coordinated interfacial reconstruction that disrupts Zn^(2+)solvation in the outer Helmholtz plane,builds a chemisorbed coordination layer in the inner plane,and modulates local interfacial chemistry with spatial precision.This dualregion regulation collectively suppresses water reactivity,facilitates Zn^(2+)desolvation,and drives crystallo-graphically preferred deposition along the(101)plane,promoting lateral growth and mitigating dendrite for-mation.As a result,symmetric Zn||Zn cells exhibit over 4200 h of stable cycling at 1 mA cm^(-2) and maintain 1100 h of operation at 2 mA cm^(-2),even at 0℃.Zn||Ti half-cells achieve a Coulombic efficiency of 99.83%,while Zn||NH_(4)V_(4)O_(10) full cells deliver 93.92%capacity retention after 400 cycles at 2 A g^(-1),and preserve 85.3%after 300 cycles at 0℃.This work demonstrates a scalable,mechanism-driven electrolyte design paradigm for dendrite-free and high-performance aqueous Zn metal batteries.
基金Supported by the Key Research and Development Program of Shandong(No.2022LZGC015)the National Key R&D Program of China(No.2022YFD2401400)+1 种基金the Taishan Scholars Program,the National Key R&D Program of China(No.2022YFD2400304)the Agricultural Seed Project of Shandong Key R&D Program(No.2024LZGCQY003)。
文摘Atmospheric carbon dioxide(CO_(2))levels are escalating at an unprecedented rate,leading to the phenomenon of ocean acidification(OA).Parental exposure to acidification has the potential to enhance offspring resilience through cross-generation plasticity.In this study,we analyzed larval growth and transcriptomic profiles in the Pacific oyster,Crassostrea gigas,a species of significant ecological relevance,under both control and elevated CO_(2)conditions experienced by their parental generation.Our findings indicate that the oyster populations exposed to OA exhibited a higher incidence of abnormalities during the D-shaped larval stage,followed by accelerated growth at the eyed stage.Through a comparative transcriptomic investigation of eyed larvae(25 d after fertilization),we observed that parental exposure to OA substantially influenced the gene expression in the offspring.Genes associated with lipid catabolism and shell formation were notably upregulated in oysters with parental OA exposure,potentially playing a role in cross-generational conditioning and conferring resilience to OA stressors.These results underscore the profound impact of OA on oyster larval development via cross-generational mechanisms and shed light on the molecular underpinnings of cross-generation plasticity.
基金financial support from the Nuclear Energy Science&Technology and Human Resource Development Project of the Japan Atomic Energy Agency/Collaborative Laboratories for Advanced Decommissioning Science(No.R04I034)The author Ruicong Xu appreciates the scholarship(financial support)from the China Scholarship Council(CSC,No.202106380073).
文摘Laser-induced aerosols,predominantly submicron in size,pose significant environmental and health risks during the decommissioning of nuclear reactors.This study experimentally investigated the removal of laser-generated aerosol particles using a water spray system integrated with an innovative system for pre-injecting electrically charged mist in our facility.To simulate aerosol generation in reactor decommissioning,a high-power laser was used to irradiate various materials(including stainless steel,carbon steel,and concrete),generating aerosol particles that were agglomerated with injected water mist and subsequently scavenged by water spray.Experimental results demonstrate enhanced aerosol removal via aerosol-mist agglomeration,with charged mist significantly improving particle capture by increasing wettability and size.The average improvements for the stainless steel,carbon steel,and concrete were 40%,44%,and 21%,respectively.The results of experiments using charged mist with different polarities(both positive and negative)and different surface coatings reveal that the dominant polarity of aerosols varies with the irradiated materials,influenced by their crystal structure and electron emission properties.Notably,surface coatings such as ZrO_(2)and CeO_(2)were found to possibly alter aerosol charging characteristics,thereby affecting aerosol removal efficiency with charged mist configurations.The innovative aerosol-mist agglomeration approach shows promise in mitigating radiation exposure,ensuring environmental safety,and reducing contaminated water during reactor dismantling.This study contributes critical knowledge for the development of advanced aerosol management strategies for nuclear reactor decommissioning.The understanding obtained in this work is also expected to be useful for various environmental and chemical engineering applications such as gas decontamination,air purification,and pollution control.
基金supported by The Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(RS-2023-00244901)(to RB)。
文摘Challenges in the prevention and treatment of mild cognitive impairment associated with Alzheimer's disease:Increased life expectancy due to advancements in medical care has given rise to an aging population,accompanied by a surge in the incidence of incurable neurodegenerative diseases(NDDs).These diseases primarily affect the cognitive and behavioral functions of older adults by impacting brain activity.Mild cognitive impairment(MCI)is a neurodegenerative condition that affects a significant portion of the population.
基金supported by Basic Science Research Program(Priority Research Institute)through the NRF of Korea funded by the Ministry of Education(2021R1A6A1A10039823)by the Korea Basic Science Institute(National Research Facilities and Equipment Center)grant funded by the Ministry of Education(2020R1A6C101B194)。
文摘Lithium-oxygen(Li-O2)batteries are perceived as a promising breakthrough in sustainable electrochemical energy storage,utilizing ambient air as an energy source,eliminating the need for costly cathode materials,and offering the highest theoretical energy density(~3.5 k Wh kg^(-1))among discussed candidates.Contributing to the poor cycle life of currently reported Li-O_(2)cells is singlet oxygen(1O_(2))formation,inducing parasitic reactions,degrading key components,and severely deteriorating cell performance.Here,we harness the chirality-induced spin selectivity effect of chiral cobalt oxide nanosheets(Co_(3)O_(4)NSs)as cathode materials to suppress 1O_(2)in Li-O_(2)batteries for the first time.Operando photoluminescence spectroscopy reveals a 3.7-fold and 3.23-fold reduction in 1O_(2)during discharge and charge,respectively,compared to conventional carbon paperbased cells,consistent with differential electrochemical mass spectrometry results,which indicate a near-theoretical charge-to-O_(2)ratio(2.04 e-/O_(2)).Density functional theory calculations demonstrate that chirality induces a peak shift near the Fermi level,enhancing Co 3d-O 2p hybridization,stabilizing reaction intermediates,and lowering activation barriers for Li_(2)O_(2)formation and decomposition.These findings establish a new strategy for improving the stability and energy efficiency of sustainable Li-O_(2)batteries,abridging the current gap to commercialization.
基金Supported by A grant from the European Commission("Tech Use Disorders"Grant ID:FP7-PEOPLE-2013-IEF-627999)awarded to Olatz Lopez-Fernandez
文摘AIM: To provide a comprehensive overview of clinical studies on the clinical picture of Internet-use related addictions from a holistic perspective. A literature search was conducted using the database Web of Science.METHODS: Over the last 15 years, the number of Internet users has increased by 1000%, and at the same time, research on addictive Internet use has proliferated. Internet addiction has not yet been understood very well, and research on its etiology and natural history is still in its infancy. In 2013, the American Psychiatric Association included Internet Gaming Disorder in the appendix of the updated version of the Diagnostic and Statistical Manual for Mental Disorders(DSM-5) as condition that requires further research prior to official inclusion in the main manual, with important repercussions for research and treatment. To date, reviews have focused on clinical and treatment studies of Internet addiction and Internet Gaming Disorder. This arguably limits the analysis to a specific diagnosis of a potential disorder that has not yet been officially recognised in the Western world, rather than a comprehensive and inclusive investigation of Internet-use related addictions(including problematic Internet use) more generally. RESULTS: The systematic literature review identified a total of 46 relevant studies. The included studies used clinical samples, and focused on characteristics of treatment seekers and online addiction treatment. Four main types of clinical research studies were identified, namely research involving(1) treatment seeker characteristics;(2) psychopharmacotherapy;(3) psychological therapy; and(4) combined treatment. CONCLUSION: A consensus regarding diagnostic criteria and measures is needed to improve reliability across studies and to develop effective and efficient treatment approaches for treatment seekers.
