Model evaluation using benchmark datasets is an important method to measure the capability of large language models(LLMs)in specific domains,and it is mainly used to assess the knowledge and reasoning abilities of LLM...Model evaluation using benchmark datasets is an important method to measure the capability of large language models(LLMs)in specific domains,and it is mainly used to assess the knowledge and reasoning abilities of LLMs.Therefore,in order to better assess the capability of LLMs in the agricultural domain,Agri-Eval was proposed as a benchmark for assessing the knowledge and reasoning ability of LLMs in agriculture.The assessment dataset used in Agri-Eval covered seven major disciplines in the agricultural domain:crop science,horticulture,plant protection,animal husbandry,forest science,aquaculture science,and grass science,and contained a total of 2283 questions.Among domestic general-purpose LLMs,DeepSeek R1 performed best with an accuracy rate of 75.49%.In the realm of international general-purpose LLMs,Gemini 2.0 pro exp 0205 standed out as the top performer,achieving an accuracy rate of 74.28%.As an LLMs in agriculture vertical,Shennong V2.0 outperformed all the LLMs in China,and the answer accuracy rate of agricultural knowledge exceeded that of all the existing general-purpose LLMs.The launch of Agri-Eval helped the LLM developers to comprehensively evaluate the model's capability in the field of agriculture through a variety of tasks and tests to promote the development of the LLMs in the field of agriculture.展开更多
Dear Editor,Psoriasis is increasingly recognized as a systemic inflammatory disease associated with several comorbidities,including metabolic syndrome,depression,and malignancies[1].Colorectal cancer(CRC)is the third ...Dear Editor,Psoriasis is increasingly recognized as a systemic inflammatory disease associated with several comorbidities,including metabolic syndrome,depression,and malignancies[1].Colorectal cancer(CRC)is the third most common cancer worldwide and ranks second in mortality among all malignancies.Currently,it has become one of the most severe challenges faced by healthcare systems in many countries[2].A previous study has found that patients with psoriasis have a significantly increased risk of developing CRC[3].展开更多
Radiative cooling systems(RCSs)possess the distinctive capability to dissipate heat energy via solar and thermal radiation,making them suitable for thermal regulation and energy conservation applications,essential for...Radiative cooling systems(RCSs)possess the distinctive capability to dissipate heat energy via solar and thermal radiation,making them suitable for thermal regulation and energy conservation applications,essential for mitigating the energy crisis.A comprehensive review connecting the advancements in engineered radiative cooling systems(ERCSs),encompassing material and structural design as well as thermal and energy-related applications,is currently absent.Herein,this review begins with a concise summary of the essential concepts of ERCSs,followed by an introduction to engineered materials and structures,containing nature-inspired designs,chromatic materials,meta-structural configurations,and multilayered constructions.It subsequently encapsulates the primary applications,including thermal-regulating textiles and energy-saving devices.Next,it highlights the challenges of ERCSs,including maximized thermoregulatory effects,environmental adaptability,scalability and sustainability,and interdisciplinary integration.It seeks to offer direction for forthcoming fundamental research and industrial advancement of radiative cooling systems in real-world applications.展开更多
A novel siphon-based divide-and-conquer(SbDaC)policy is presented in this paper for the synthesis of Petri net(PN)based liveness-enforcing supervisors(LES)for flexible manufacturing systems(FMS)prone to deadlocks or l...A novel siphon-based divide-and-conquer(SbDaC)policy is presented in this paper for the synthesis of Petri net(PN)based liveness-enforcing supervisors(LES)for flexible manufacturing systems(FMS)prone to deadlocks or livelocks.The proposed method takes an uncontrolled and bounded PN model(UPNM)of the FMS.Firstly,the reduced PNM(RPNM)is obtained from the UPNM by using PN reduction rules to reduce the computation burden.Then,the set of strict minimal siphons(SMSs)of the RPNM is computed.Next,the complementary set of SMSs is computed from the set of SMSs.By the union of these two sets,the superset of SMSs is computed.Finally,the set of subnets of the RPNM is obtained by applying the PN reduction rules to the superset of SMSs.All these subnets suffer from deadlocks.These subnets are then ordered from the smallest one to the largest one based on a criterion.To enforce liveness on these subnets,a set of control places(CPs)is computed starting from the smallest subnet to the largest one.Once all subnets are live,this process provides the LES,consisting of a set of CPs to be used for the UPNM.The live controlled PN model(CPNM)is constructed by merging the LES with the UPNM.The SbDaC policy is applicable to all classes of PNs related to FMS prone to deadlocks or livelocks.Several FMS examples are considered from the literature to highlight the applicability of the SbDaC policy.In particular,three examples are utilized to emphasize the importance,applicability and effectiveness of the SbDaC policy to realistic FMS with very large state spaces.展开更多
Microorganisms constitute an essential component in the indoor environment,which is closely related to hu-man health.However,there is limited evidence regarding the associations between indoor airborne microbiome and ...Microorganisms constitute an essential component in the indoor environment,which is closely related to hu-man health.However,there is limited evidence regarding the associations between indoor airborne microbiome and systemic inflammation,as well as whether this association is modified by indoor particulate matter and the underlying mechanisms.In this prospective repeated-measure study among 66 participants,indoor airborne mi-crobiome was characterized using amplicon sequencing and qPCR.Indoor fine particulate matter(PM_(2.5))and inhalable particulate matter(PM10)were measured.Systemic inflammatory biomarkers were assessed,including white blood cell(WBC),neutrophil(NEUT),monocyte,eosinophil counts,and their proportions.Targeted serum amino acid metabolomics were conducted to explore the underlying mechanisms.Linear mixed-effect models re-vealed that bacterial and fungal Simpson diversity were significantly associated with decreased WBC and NEUT.For example,for each interquartile range increase in the bacterial Simpson diversity,WBC and NEUT changed by-4.53%(95%CI:-8.25%,-0.66%)and-5.95%(95%CI:-11.3%,-0.27%),respectively.Notably,increased inflammatory risks of airborne microbial exposure were observed when indoor PM_(2.5) and PM10 levels were below the WHO air quality guidelines.Mediation analyses indicated that dopamine metabolism partially mediated the anti-inflammatory effects of fungal diversity exposure.Overall,our study indicated protection from a diverse indoor microbial environment on cardiovascular health and proposed an underlying mechanism through amino acid metabolism.Additionally,health risks associated with microbial exposure deserve more attention in con-texts of low indoor particulate matter pollution.Further research is necessary to fully disentangle the complex relationships between indoor microbiome,air pollutants,and human health.展开更多
As urban landscapes evolve and vehicular volumes soar,traditional traffic monitoring systems struggle to scale,often failing under the complexities of dense,dynamic,and occluded environments.This paper introduces a no...As urban landscapes evolve and vehicular volumes soar,traditional traffic monitoring systems struggle to scale,often failing under the complexities of dense,dynamic,and occluded environments.This paper introduces a novel,unified deep learning framework for vehicle detection,tracking,counting,and classification in aerial imagery designed explicitly for modern smart city infrastructure demands.Our approach begins with adaptive histogram equalization to optimize aerial image clarity,followed by a cutting-edge scene parsing technique using Mask2Former,enabling robust segmentation even in visually congested settings.Vehicle detection leverages the latest YOLOv11 architecture,delivering superior accuracy in aerial contexts by addressing occlusion,scale variance,and fine-grained object differentiation.We incorporate the highly efficient ByteTrack algorithm for tracking,enabling seamless identity preservation across frames.Vehicle counting is achieved through an unsupervised DBSCAN-based method,ensuring adaptability to varying traffic densities.We further introduce a hybrid feature extraction module combining Convolutional Neural Networks(CNNs)with Zernike Moments,capturing both deep semantic and geometric signatures of vehicles.The final classification is powered by NASNet,a neural architecture search-optimized model,ensuring high accuracy across diverse vehicle types and orientations.Extensive evaluations of the VAID benchmark dataset demonstrate the system’s outstanding performance,achieving 96%detection,94%tracking,and 96.4%classification accuracy.On the UAVDT dataset,the system attains 95%detection,93%tracking,and 95%classification accuracy,confirming its robustness across diverse aerial traffic scenarios.These results establish new benchmarks in aerial traffic analysis and validate the framework’s scalability,making it a powerful and adaptable solution for next-generation intelligent transportation systems and urban surveillance.展开更多
Gastric ulcer(GU)represents a clinically significant manifestation of peptic ulcer disease,driven by a complex interplay of microbial,environmental,and immuneinflammatory factors.A recent cross-sectional study by Shen...Gastric ulcer(GU)represents a clinically significant manifestation of peptic ulcer disease,driven by a complex interplay of microbial,environmental,and immuneinflammatory factors.A recent cross-sectional study by Shen et al systematically evaluated six complete blood count-derived inflammatory indices:Neutrophil-tolymphocyte ratio,monocyte-to-lymphocyte ratio,platelet-to-lymphocyte ratio,systemic immune-inflammation index,systemic inflammatory response index(SIRI),and aggregate index of systemic inflammation and demonstrated their positive associations with GU prevalence,identifying SIRI as the strongest predictor.This editorial contextualizes these findings within the broader literature,clarifies that these indices reflect systemic rather than GU-specific inflammation,highlights methodological strengths and major limitations,and proposes a conceptual clinical algorithm for integrating SIRI into GU risk assessment.Future multicenter studies incorporating Helicobacter pylori infection,non-steroidal antiinflammatory drug exposure,and prospective design are essential to validate and translate these findings into clinical practice.展开更多
Curtain wall systems have evolved from aesthetic facade elements into multifunctional building envelopes that actively contribute to energy efficiency and climate responsiveness.This reviewpresents a comprehensive exa...Curtain wall systems have evolved from aesthetic facade elements into multifunctional building envelopes that actively contribute to energy efficiency and climate responsiveness.This reviewpresents a comprehensive examination of curtain walls from an energy-engineering perspective,highlighting their structural typologies(Stick and Unitized),material configurations,and integration with smart technologies such as electrochromic glazing,parametric design algorithms,and Building Management Systems(BMS).Thestudy explores the thermal,acoustic,and solar performance of curtain walls across various climatic zones,supported by comparative analyses and iconic case studies including Apple Park,Burj Khalifa,and Milad Tower.Key challenges—including installation complexity,high maintenance costs,and climate sensitivity—are critically assessed alongside proposed solutions.A central innovation of this work lies in framing curtain walls not only as passive architectural elements but as dynamic interfaces that modulate energy flows,reduce HVAC loads,and enhance occupant comfort.The reviewed data indicate that optimized curtain wall configurations—especially those integrating electrochromic glazing and BIPV modules—can achieve annual energy consumption reductions ranging fromapproximately 5%to 27%,depending on climate,control strategy,and facade typology.The findings offer a valuable reference for architects,energy engineers,and decision-makers seeking to integrate high-performance facades into future-ready building designs.展开更多
This letter introduces the novel concept of Painlevé solitons—waves arising from the interaction between Painlevé waves and solitons in integrable systems.Painlevé solitons can also be viewed as solito...This letter introduces the novel concept of Painlevé solitons—waves arising from the interaction between Painlevé waves and solitons in integrable systems.Painlevé solitons can also be viewed as solitons propagating against a Painlevé wave background,in analogy to the established notion of elliptic solitons,which refers to solitons on an elliptic wave background.By employing a novel symmetry decomposition method aided by nonlocal residual symmetries,we explicitly construct (extended) Painlevé Ⅱ solitons for the Korteweg-de Vries equation and (extended) Painlevé Ⅳ solitons for the Boussinesq equation.展开更多
The human retina,a complex and highly specialized structure,includes multiple cell types that work synergistically to generate and transmit visual signals.However,genetic predisposition or age-related degeneration can...The human retina,a complex and highly specialized structure,includes multiple cell types that work synergistically to generate and transmit visual signals.However,genetic predisposition or age-related degeneration can lead to retinal damage that severely impairs vision or causes blindness.Treatment options for retinal diseases are limited,and there is an urgent need for innovative therapeutic strategies.Cell and gene therapies are promising because of the efficacy of delivery systems that transport therapeutic genes to targeted retinal cells.Gene delivery systems hold great promise for treating retinal diseases by enabling the targeted delivery of therapeutic genes to affected cells or by converting endogenous cells into functional ones to facilitate nerve regeneration,potentially restoring vision.This review focuses on two principal categories of gene delivery vectors used in the treatment of retinal diseases:viral and non-viral systems.Viral vectors,including lentiviruses and adeno-associated viruses,exploit the innate ability of viruses to infiltrate cells,which is followed by the introduction of therapeutic genetic material into target cells for gene correction.Lentiviruses can accommodate exogenous genes up to 8 kb in length,but their mechanism of integration into the host genome presents insertion mutation risks.Conversely,adeno-associated viruses are safer,as they exist as episomes in the nucleus,yet their limited packaging capacity constrains their application to a narrower spectrum of diseases,which necessitates the exploration of alternative delivery methods.In parallel,progress has also occurred in the development of novel non-viral delivery systems,particularly those based on liposomal technology.Manipulation of the ratios of hydrophilic and hydrophobic molecules within liposomes and the development of new lipid formulations have led to the creation of advanced non-viral vectors.These innovative systems include solid lipid nanoparticles,polymer nanoparticles,dendrimers,polymeric micelles,and polymeric nanoparticles.Compared with their viral counterparts,non-viral delivery systems offer markedly enhanced loading capacities that enable the direct delivery of nucleic acids,mRNA,or protein molecules into cells.This bypasses the need for DNA transcription and processing,which significantly enhances therapeutic efficiency.Nevertheless,the immunogenic potential and accumulation toxicity associated with non-viral particulate systems necessitates continued optimization to reduce adverse effects in vivo.This review explores the various delivery systems for retinal therapies and retinal nerve regeneration,and details the characteristics,advantages,limitations,and clinical applications of each vector type.By systematically outlining these factors,our goal is to guide the selection of the optimal delivery tool for a specific retinal disease,which will enhance treatment efficacy and improve patient outcomes while paving the way for more effective and targeted therapeutic interventions.展开更多
Functional neurological recovery remains the primary objective when treating ischemic stroke.However,current therapeutic approaches often fall short of achieving optimal outcomes.One of the most significant challenges...Functional neurological recovery remains the primary objective when treating ischemic stroke.However,current therapeutic approaches often fall short of achieving optimal outcomes.One of the most significant challenges in stroke treatment is the effective delivery of neuroprotective agents across the blood–brain barrier to ischemic regions within the brain.The blood–brain barrier,while essential for protecting the brain from harmful substances,also restricts the passage of many therapeutic compounds,thus limiting their efficacy.In this review,we summarizes the emerging role of nanoparticle-based therapies for the treatment of ischemic stroke and investigate their potential to revolutionize drug delivery,enhance neuroprotection,and promote functional recovery.Recent advancements in nanotechnology have led to the development of engineered nanoparticles specifically designed to overcome the blood–brain barrier,thus enabling the targeted delivery of therapeutic agents directly to the affected brain areas.Preclinical studies have demonstrated the remarkable potential of nanoparticle-based therapies to activate key neuroprotective pathways,such as the phosphoinositide 3-kinase/protein kinase B/c AMP response element-binding protein signaling cascade,which is crucial for neuronal survival,synaptic plasticity,and post-stroke recovery.By modulating these pathways,nanoparticles could mitigate neuronal damage,reduce inflammation,and promote tissue repair.Furthermore,nanoparticles offer a unique advantage by enabling multimodal therapeutic strategies that simultaneously target multiple pathological mechanisms of ischemic stroke,including oxidative stress,neuroinflammation,and apoptosis.This multifaceted approach enhances the overall efficacy of treatment,addressing the complex and interconnected processes that contribute to stroke-related brain injury.Surface modifications,such as functionalization with specific ligands or targeting molecules,further improve the precision of drug delivery,enhance targeting specificity,and prolong systemic circulation,thereby optimizing therapeutic outcomes.Nanoparticlebased therapeutics represent a paradigm shift for the management of stroke and provide a promising avenue for reducing post-stroke disability and improving the outcomes of long-term rehabilitation.By combining targeted drug delivery with the ability to modulate critical neuroprotective pathways,nanoparticles hold the potential to transform the treatment landscape for ischemic stroke.However,while preclinical data are highly encouraging,significant challenges remain in translating these advancements into clinical practice.Further research is needed to refine nanoparticle designs,optimize their safety profiles,and ensure their scalability for widespread application.Rigorous clinical trials are essential to validate their efficacy,assess long-term biocompatibility,and address potential off-target effects.The integration of interdisciplinary approaches,combining insights from nanotechnology,neuroscience,and pharmacology,will be critical if we are to overcome these challenges.Ultimately,nanoparticle-based therapies offer a foundation for innovative,precision-based treatments that could significantly improve outcomes for stroke patients,thus paving the way for a new era in stroke care and neurological rehabilitation.展开更多
Rapid regional population shifts and spatial polarization have heightened pressure on cultivated land—a critical resource demanding urgent attention amid ongoing urban-rural transition.This study selects Jiangsu prov...Rapid regional population shifts and spatial polarization have heightened pressure on cultivated land—a critical resource demanding urgent attention amid ongoing urban-rural transition.This study selects Jiangsu province,a national leader in both economic and agricultural development,as a case area to construct a multidimensional framework for assessing the recessive morphological characteristics of multifunctional cultivated land use.We examine temporal dynamics,spatial heterogeneity,and propose an integrated zoning strategy based on empirical analysis.The results reveal that:(1)The recessive morphology index shows a consistent upward trend,with structural breaks in 2007 and 2013,and a spatial shift from“higher in the east and lower in the west”to“higher in the south and lower in the north.”(2)Coordination among sub-dimensions of the index has steadily improved.(3)The index is expected to continue rising in the next decade,though at a slower pace.(4)To promote coordinated multidimensional land-use development,we recommend a policy framework that reinforces existing strengths,addresses weaknesses,and adapts zoning schemes to current spatial conditions.This research offers new insights into multifunctional cultivated land systems and underscores their role in enhancing human well-being,securing food supply,and supporting sustainable urban-rural integration.展开更多
Cardiovascular disease(CVD)is often accompanied by chronic kidney disease(CKD)and metabolic disorders such as obesity and type 2 diabetes^([1]).The coexistence of these conditions can lead to systemic dysfunction and ...Cardiovascular disease(CVD)is often accompanied by chronic kidney disease(CKD)and metabolic disorders such as obesity and type 2 diabetes^([1]).The coexistence of these conditions can lead to systemic dysfunction and substantially increase adverse cardiovascular outcomes.To describe this interplay,the American Heart Association(AHA)recently proposed the concept of cardiovascular-kidney-metabolic(CKM)syndrome^([1]).However,its risk-enhancing factors and underlying mechanisms remain unclear.展开更多
The rise of the aging population parallels the rapidly increasing cases of neurological disorders. This puts pressure on scientists and physicians to find novel methods that can prevent and treat neurodegeneration. Th...The rise of the aging population parallels the rapidly increasing cases of neurological disorders. This puts pressure on scientists and physicians to find novel methods that can prevent and treat neurodegeneration. The brain is made up of a complex network of different cell types that work in tandem to maintain systemic homeostasis.展开更多
The evolution of cities into digitally managed environments requires computational systems that can operate in real time while supporting predictive and adaptive infrastructure management.Earlier approaches have often...The evolution of cities into digitally managed environments requires computational systems that can operate in real time while supporting predictive and adaptive infrastructure management.Earlier approaches have often advanced one dimension—such as Internet of Things(IoT)-based data acquisition,Artificial Intelligence(AI)-driven analytics,or digital twin visualization—without fully integrating these strands into a single operational loop.As a result,many existing solutions encounter bottlenecks in responsiveness,interoperability,and scalability,while also leaving concerns about data privacy unresolved.This research introduces a hybrid AI–IoT–Digital Twin framework that combines continuous sensing,distributed intelligence,and simulation-based decision support.The design incorporates multi-source sensor data,lightweight edge inference through Convolutional Neural Networks(CNN)and Long ShortTerm Memory(LSTM)models,and federated learning enhanced with secure aggregation and differential privacy to maintain confidentiality.A digital twin layer extends these capabilities by simulating city assets such as traffic flows and water networks,generating what-if scenarios,and issuing actionable control signals.Complementary modules,including model compression and synchronization protocols,are embedded to ensure reliability in bandwidth-constrained and heterogeneous urban environments.The framework is validated in two urban domains:traffic management,where it adapts signal cycles based on real-time congestion patterns,and pipeline monitoring,where it anticipates leaks through pressure and vibration data.Experimental results show a 28%reduction in response time,a 35%decrease in maintenance costs,and a marked reduction in false positives relative to conventional baselines.The architecture also demonstrates stability across 50+edge devices under federated training and resilience to uneven node participation.The proposed system provides a scalable and privacy-aware foundation for predictive urban infrastructure management.By closing the loop between sensing,learning,and control,it reduces operator dependence,enhances resource efficiency,and supports transparent governance models for emerging smart cities.展开更多
Based on the Smit-Suhl formula,we propose a universal approach for solving the magnon-magnon coupling problem in bilayer coupled systems(e.g.,antiferromagnets).This method requires only the energy expression,enabling ...Based on the Smit-Suhl formula,we propose a universal approach for solving the magnon-magnon coupling problem in bilayer coupled systems(e.g.,antiferromagnets).This method requires only the energy expression,enabling the automatic derivation of analytical expressions for the eigenmatrix elements via symbolic computation,eliminating the need for tedious manual calculations.Using this approach,we investigate the impact of magnetic hysteresis on magnon-magnon coupling in a system with interlayer Dzyaloshinskii-Moriya interaction(DMI).The magnetic hysteresis leads to an asymmetric magnetic field dependence of the resonance frequency and alters the number of degeneracy points between the pure optical and acoustic modes.Moreover,it can result in the coupling strength at the gap of the f–H phase diagram being nearly vanishing,contrary to the conventionally expected maximum.These results deepen the understanding of the effect of interlayer DMI on magnon–magnon coupling and the proposed universal method significantly streamlines the solving process of magnon–magnon coupling problems.展开更多
Two international conferences in November 2025 jointly outlined a profound transformation of climate governance.The Committee on Trade and Environment(CTE)of the World Trade Organization(WTO)held a conference in Genev...Two international conferences in November 2025 jointly outlined a profound transformation of climate governance.The Committee on Trade and Environment(CTE)of the World Trade Organization(WTO)held a conference in Geneva,Switzerland,on November 4,where the topic of cooperation on trade-related carbon standards aroused heated discussions.The Leaders'Summit of the 30th Conference of the Parties(COP)to the UN Framework Convention on Climate Change(UNFCCC)was held in Belém,Brazil,on November 7.At the meeting,the Open Coalition on Compliance Carbon Markets was officially launched with the initial membership of 11 economies including Brazil,China,and the EU.As the world's first transnational alliance on compliant carbon markets,the coalition aims to coordinate carbon pricing mechanisms,emission trading systems and related policies in various countries,and realize the interconnection of global compliance carbon market networks.展开更多
Climate model prediction has been improved by enhancing model resolution as well as the implementation of sophisticated physical parameterization and refinement of data assimilation systems[section 6.1 in Wang et al.(...Climate model prediction has been improved by enhancing model resolution as well as the implementation of sophisticated physical parameterization and refinement of data assimilation systems[section 6.1 in Wang et al.(2025)].In relation to seasonal forecasting and climate projection in the East Asian summer monsoon season,proper simulation of the seasonal migration of rain bands by models is a challenging and limiting factor[section 7.1 in Wang et al.(2025)].展开更多
The 193 nm deep-ultraviolet(DUV)laser plays a critical role in advanced semiconductor chip manufacturing[1,2],micro-nano material characterization[3,4]and biomedical analysis[5,6],due to its high spatial resolution an...The 193 nm deep-ultraviolet(DUV)laser plays a critical role in advanced semiconductor chip manufacturing[1,2],micro-nano material characterization[3,4]and biomedical analysis[5,6],due to its high spatial resolution and short wavelength.Efficient and compact 193 nm DUV laser source thus becomes a hot research area.Currently,193 nm Ar F excimer gas laser is widely employed in DUV lithography systems and serves as the enabling technology for 7 and 5 nm semiconductor fabrication.展开更多
Mental health is a significant issue worldwide,and the utilization of technology to assist mental health has seen a growing trend.This aims to alleviate the workload on healthcare professionals and aid individuals.Num...Mental health is a significant issue worldwide,and the utilization of technology to assist mental health has seen a growing trend.This aims to alleviate the workload on healthcare professionals and aid individuals.Numerous applications have been developed to support the challenges in intelligent healthcare systems.However,because mental health data is sensitive,privacy concerns have emerged.Federated learning has gotten some attention.This research reviews the studies on federated learning and mental health related to solving the issue of intelligent healthcare systems.It explores various dimensions of federated learning in mental health,such as datasets(their types and sources),applications categorized based on mental health symptoms,federated mental health frameworks,federated machine learning,federated deep learning,and the benefits of federated learning in mental health applications.This research conducts surveys to evaluate the current state of mental health applications,mainly focusing on the role of Federated Learning(FL)and related privacy and data security concerns.The survey provides valuable insights into how these applications are emerging and evolving,specifically emphasizing FL’s impact.展开更多
文摘Model evaluation using benchmark datasets is an important method to measure the capability of large language models(LLMs)in specific domains,and it is mainly used to assess the knowledge and reasoning abilities of LLMs.Therefore,in order to better assess the capability of LLMs in the agricultural domain,Agri-Eval was proposed as a benchmark for assessing the knowledge and reasoning ability of LLMs in agriculture.The assessment dataset used in Agri-Eval covered seven major disciplines in the agricultural domain:crop science,horticulture,plant protection,animal husbandry,forest science,aquaculture science,and grass science,and contained a total of 2283 questions.Among domestic general-purpose LLMs,DeepSeek R1 performed best with an accuracy rate of 75.49%.In the realm of international general-purpose LLMs,Gemini 2.0 pro exp 0205 standed out as the top performer,achieving an accuracy rate of 74.28%.As an LLMs in agriculture vertical,Shennong V2.0 outperformed all the LLMs in China,and the answer accuracy rate of agricultural knowledge exceeded that of all the existing general-purpose LLMs.The launch of Agri-Eval helped the LLM developers to comprehensively evaluate the model's capability in the field of agriculture through a variety of tasks and tests to promote the development of the LLMs in the field of agriculture.
基金supported by the National Natural Science Foundation of China(Grant No.82373475).
文摘Dear Editor,Psoriasis is increasingly recognized as a systemic inflammatory disease associated with several comorbidities,including metabolic syndrome,depression,and malignancies[1].Colorectal cancer(CRC)is the third most common cancer worldwide and ranks second in mortality among all malignancies.Currently,it has become one of the most severe challenges faced by healthcare systems in many countries[2].A previous study has found that patients with psoriasis have a significantly increased risk of developing CRC[3].
基金support from the Contract Research(“Development of Breathable Fabrics with Nano-Electrospun Membrane”,CityU ref.:9231419“Research and application of antibacterial and healing-promoting smart nanofiber dressing for children’s burn wounds”,CityU ref:PJ9240111)+1 种基金the National Natural Science Foundation of China(“Study of Multi-Responsive Shape Memory Polyurethane Nanocomposites Inspired by Natural Fibers”,Grant No.51673162)Startup Grant of CityU(“Laboratory of Wearable Materials for Healthcare”,Grant No.9380116).
文摘Radiative cooling systems(RCSs)possess the distinctive capability to dissipate heat energy via solar and thermal radiation,making them suitable for thermal regulation and energy conservation applications,essential for mitigating the energy crisis.A comprehensive review connecting the advancements in engineered radiative cooling systems(ERCSs),encompassing material and structural design as well as thermal and energy-related applications,is currently absent.Herein,this review begins with a concise summary of the essential concepts of ERCSs,followed by an introduction to engineered materials and structures,containing nature-inspired designs,chromatic materials,meta-structural configurations,and multilayered constructions.It subsequently encapsulates the primary applications,including thermal-regulating textiles and energy-saving devices.Next,it highlights the challenges of ERCSs,including maximized thermoregulatory effects,environmental adaptability,scalability and sustainability,and interdisciplinary integration.It seeks to offer direction for forthcoming fundamental research and industrial advancement of radiative cooling systems in real-world applications.
基金The authors extend their appreciation to King Saud University,Saudi Arabia for funding this work through the Ongoing Research Funding Program(ORF-2025-704),King Saud University,Riyadh,Saudi Arabia.
文摘A novel siphon-based divide-and-conquer(SbDaC)policy is presented in this paper for the synthesis of Petri net(PN)based liveness-enforcing supervisors(LES)for flexible manufacturing systems(FMS)prone to deadlocks or livelocks.The proposed method takes an uncontrolled and bounded PN model(UPNM)of the FMS.Firstly,the reduced PNM(RPNM)is obtained from the UPNM by using PN reduction rules to reduce the computation burden.Then,the set of strict minimal siphons(SMSs)of the RPNM is computed.Next,the complementary set of SMSs is computed from the set of SMSs.By the union of these two sets,the superset of SMSs is computed.Finally,the set of subnets of the RPNM is obtained by applying the PN reduction rules to the superset of SMSs.All these subnets suffer from deadlocks.These subnets are then ordered from the smallest one to the largest one based on a criterion.To enforce liveness on these subnets,a set of control places(CPs)is computed starting from the smallest subnet to the largest one.Once all subnets are live,this process provides the LES,consisting of a set of CPs to be used for the UPNM.The live controlled PN model(CPNM)is constructed by merging the LES with the UPNM.The SbDaC policy is applicable to all classes of PNs related to FMS prone to deadlocks or livelocks.Several FMS examples are considered from the literature to highlight the applicability of the SbDaC policy.In particular,three examples are utilized to emphasize the importance,applicability and effectiveness of the SbDaC policy to realistic FMS with very large state spaces.
基金supported by the National Key Research and Development Program of China(No.2022YFC3702704)the National Natural Science Foundation of China(Nos.22376005,22076006 and 82073506).
文摘Microorganisms constitute an essential component in the indoor environment,which is closely related to hu-man health.However,there is limited evidence regarding the associations between indoor airborne microbiome and systemic inflammation,as well as whether this association is modified by indoor particulate matter and the underlying mechanisms.In this prospective repeated-measure study among 66 participants,indoor airborne mi-crobiome was characterized using amplicon sequencing and qPCR.Indoor fine particulate matter(PM_(2.5))and inhalable particulate matter(PM10)were measured.Systemic inflammatory biomarkers were assessed,including white blood cell(WBC),neutrophil(NEUT),monocyte,eosinophil counts,and their proportions.Targeted serum amino acid metabolomics were conducted to explore the underlying mechanisms.Linear mixed-effect models re-vealed that bacterial and fungal Simpson diversity were significantly associated with decreased WBC and NEUT.For example,for each interquartile range increase in the bacterial Simpson diversity,WBC and NEUT changed by-4.53%(95%CI:-8.25%,-0.66%)and-5.95%(95%CI:-11.3%,-0.27%),respectively.Notably,increased inflammatory risks of airborne microbial exposure were observed when indoor PM_(2.5) and PM10 levels were below the WHO air quality guidelines.Mediation analyses indicated that dopamine metabolism partially mediated the anti-inflammatory effects of fungal diversity exposure.Overall,our study indicated protection from a diverse indoor microbial environment on cardiovascular health and proposed an underlying mechanism through amino acid metabolism.Additionally,health risks associated with microbial exposure deserve more attention in con-texts of low indoor particulate matter pollution.Further research is necessary to fully disentangle the complex relationships between indoor microbiome,air pollutants,and human health.
基金funded by the Open Access Initiative of the University of Bremen and the DFG via SuUB BremenThe authors extend their appreciation to the Deanship of Research and Graduate Studies at King Khalid University for funding this work through Large Group Project under grant number(RGP2/367/46)+1 种基金This research is supported and funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2025R410)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘As urban landscapes evolve and vehicular volumes soar,traditional traffic monitoring systems struggle to scale,often failing under the complexities of dense,dynamic,and occluded environments.This paper introduces a novel,unified deep learning framework for vehicle detection,tracking,counting,and classification in aerial imagery designed explicitly for modern smart city infrastructure demands.Our approach begins with adaptive histogram equalization to optimize aerial image clarity,followed by a cutting-edge scene parsing technique using Mask2Former,enabling robust segmentation even in visually congested settings.Vehicle detection leverages the latest YOLOv11 architecture,delivering superior accuracy in aerial contexts by addressing occlusion,scale variance,and fine-grained object differentiation.We incorporate the highly efficient ByteTrack algorithm for tracking,enabling seamless identity preservation across frames.Vehicle counting is achieved through an unsupervised DBSCAN-based method,ensuring adaptability to varying traffic densities.We further introduce a hybrid feature extraction module combining Convolutional Neural Networks(CNNs)with Zernike Moments,capturing both deep semantic and geometric signatures of vehicles.The final classification is powered by NASNet,a neural architecture search-optimized model,ensuring high accuracy across diverse vehicle types and orientations.Extensive evaluations of the VAID benchmark dataset demonstrate the system’s outstanding performance,achieving 96%detection,94%tracking,and 96.4%classification accuracy.On the UAVDT dataset,the system attains 95%detection,93%tracking,and 95%classification accuracy,confirming its robustness across diverse aerial traffic scenarios.These results establish new benchmarks in aerial traffic analysis and validate the framework’s scalability,making it a powerful and adaptable solution for next-generation intelligent transportation systems and urban surveillance.
基金Supported by the National Natural Science Foundation of China,No.82170406 and No.81970238.
文摘Gastric ulcer(GU)represents a clinically significant manifestation of peptic ulcer disease,driven by a complex interplay of microbial,environmental,and immuneinflammatory factors.A recent cross-sectional study by Shen et al systematically evaluated six complete blood count-derived inflammatory indices:Neutrophil-tolymphocyte ratio,monocyte-to-lymphocyte ratio,platelet-to-lymphocyte ratio,systemic immune-inflammation index,systemic inflammatory response index(SIRI),and aggregate index of systemic inflammation and demonstrated their positive associations with GU prevalence,identifying SIRI as the strongest predictor.This editorial contextualizes these findings within the broader literature,clarifies that these indices reflect systemic rather than GU-specific inflammation,highlights methodological strengths and major limitations,and proposes a conceptual clinical algorithm for integrating SIRI into GU risk assessment.Future multicenter studies incorporating Helicobacter pylori infection,non-steroidal antiinflammatory drug exposure,and prospective design are essential to validate and translate these findings into clinical practice.
文摘Curtain wall systems have evolved from aesthetic facade elements into multifunctional building envelopes that actively contribute to energy efficiency and climate responsiveness.This reviewpresents a comprehensive examination of curtain walls from an energy-engineering perspective,highlighting their structural typologies(Stick and Unitized),material configurations,and integration with smart technologies such as electrochromic glazing,parametric design algorithms,and Building Management Systems(BMS).Thestudy explores the thermal,acoustic,and solar performance of curtain walls across various climatic zones,supported by comparative analyses and iconic case studies including Apple Park,Burj Khalifa,and Milad Tower.Key challenges—including installation complexity,high maintenance costs,and climate sensitivity—are critically assessed alongside proposed solutions.A central innovation of this work lies in framing curtain walls not only as passive architectural elements but as dynamic interfaces that modulate energy flows,reduce HVAC loads,and enhance occupant comfort.The reviewed data indicate that optimized curtain wall configurations—especially those integrating electrochromic glazing and BIPV modules—can achieve annual energy consumption reductions ranging fromapproximately 5%to 27%,depending on climate,control strategy,and facade typology.The findings offer a valuable reference for architects,energy engineers,and decision-makers seeking to integrate high-performance facades into future-ready building designs.
基金supported by the National Natural Science Foundations of China (Grant Nos.12235007,12001424,12271324,and 12501333)the Natural Science Basic research program of Shaanxi Province (Grant Nos.2021JZ-21 and 2024JC-YBQN-0069)+3 种基金the China Postdoctoral Science Foundation (Grant Nos.2020M673332 and 2024M751921)the Fundamental Research Funds for the Central Universities (Grant No.GK202304028)the 2023 Shaanxi Province Postdoctoral Research Project (Grant No.2023BSHEDZZ186)Xi’an University,Xi’an Science and Technology Plan Wutongshu Technology Transfer Action Innovation Team(Grant No.25WTZD07)。
文摘This letter introduces the novel concept of Painlevé solitons—waves arising from the interaction between Painlevé waves and solitons in integrable systems.Painlevé solitons can also be viewed as solitons propagating against a Painlevé wave background,in analogy to the established notion of elliptic solitons,which refers to solitons on an elliptic wave background.By employing a novel symmetry decomposition method aided by nonlocal residual symmetries,we explicitly construct (extended) Painlevé Ⅱ solitons for the Korteweg-de Vries equation and (extended) Painlevé Ⅳ solitons for the Boussinesq equation.
基金Hongguang Wu,Both authors contributed equally to this work and share first authorshipLing Dong,Both authors contributed equally to this work and share first authorship。
文摘The human retina,a complex and highly specialized structure,includes multiple cell types that work synergistically to generate and transmit visual signals.However,genetic predisposition or age-related degeneration can lead to retinal damage that severely impairs vision or causes blindness.Treatment options for retinal diseases are limited,and there is an urgent need for innovative therapeutic strategies.Cell and gene therapies are promising because of the efficacy of delivery systems that transport therapeutic genes to targeted retinal cells.Gene delivery systems hold great promise for treating retinal diseases by enabling the targeted delivery of therapeutic genes to affected cells or by converting endogenous cells into functional ones to facilitate nerve regeneration,potentially restoring vision.This review focuses on two principal categories of gene delivery vectors used in the treatment of retinal diseases:viral and non-viral systems.Viral vectors,including lentiviruses and adeno-associated viruses,exploit the innate ability of viruses to infiltrate cells,which is followed by the introduction of therapeutic genetic material into target cells for gene correction.Lentiviruses can accommodate exogenous genes up to 8 kb in length,but their mechanism of integration into the host genome presents insertion mutation risks.Conversely,adeno-associated viruses are safer,as they exist as episomes in the nucleus,yet their limited packaging capacity constrains their application to a narrower spectrum of diseases,which necessitates the exploration of alternative delivery methods.In parallel,progress has also occurred in the development of novel non-viral delivery systems,particularly those based on liposomal technology.Manipulation of the ratios of hydrophilic and hydrophobic molecules within liposomes and the development of new lipid formulations have led to the creation of advanced non-viral vectors.These innovative systems include solid lipid nanoparticles,polymer nanoparticles,dendrimers,polymeric micelles,and polymeric nanoparticles.Compared with their viral counterparts,non-viral delivery systems offer markedly enhanced loading capacities that enable the direct delivery of nucleic acids,mRNA,or protein molecules into cells.This bypasses the need for DNA transcription and processing,which significantly enhances therapeutic efficiency.Nevertheless,the immunogenic potential and accumulation toxicity associated with non-viral particulate systems necessitates continued optimization to reduce adverse effects in vivo.This review explores the various delivery systems for retinal therapies and retinal nerve regeneration,and details the characteristics,advantages,limitations,and clinical applications of each vector type.By systematically outlining these factors,our goal is to guide the selection of the optimal delivery tool for a specific retinal disease,which will enhance treatment efficacy and improve patient outcomes while paving the way for more effective and targeted therapeutic interventions.
基金supported by the National Natural Science Foundations of China,Nos.82272163,82472164(both MF)。
文摘Functional neurological recovery remains the primary objective when treating ischemic stroke.However,current therapeutic approaches often fall short of achieving optimal outcomes.One of the most significant challenges in stroke treatment is the effective delivery of neuroprotective agents across the blood–brain barrier to ischemic regions within the brain.The blood–brain barrier,while essential for protecting the brain from harmful substances,also restricts the passage of many therapeutic compounds,thus limiting their efficacy.In this review,we summarizes the emerging role of nanoparticle-based therapies for the treatment of ischemic stroke and investigate their potential to revolutionize drug delivery,enhance neuroprotection,and promote functional recovery.Recent advancements in nanotechnology have led to the development of engineered nanoparticles specifically designed to overcome the blood–brain barrier,thus enabling the targeted delivery of therapeutic agents directly to the affected brain areas.Preclinical studies have demonstrated the remarkable potential of nanoparticle-based therapies to activate key neuroprotective pathways,such as the phosphoinositide 3-kinase/protein kinase B/c AMP response element-binding protein signaling cascade,which is crucial for neuronal survival,synaptic plasticity,and post-stroke recovery.By modulating these pathways,nanoparticles could mitigate neuronal damage,reduce inflammation,and promote tissue repair.Furthermore,nanoparticles offer a unique advantage by enabling multimodal therapeutic strategies that simultaneously target multiple pathological mechanisms of ischemic stroke,including oxidative stress,neuroinflammation,and apoptosis.This multifaceted approach enhances the overall efficacy of treatment,addressing the complex and interconnected processes that contribute to stroke-related brain injury.Surface modifications,such as functionalization with specific ligands or targeting molecules,further improve the precision of drug delivery,enhance targeting specificity,and prolong systemic circulation,thereby optimizing therapeutic outcomes.Nanoparticlebased therapeutics represent a paradigm shift for the management of stroke and provide a promising avenue for reducing post-stroke disability and improving the outcomes of long-term rehabilitation.By combining targeted drug delivery with the ability to modulate critical neuroprotective pathways,nanoparticles hold the potential to transform the treatment landscape for ischemic stroke.However,while preclinical data are highly encouraging,significant challenges remain in translating these advancements into clinical practice.Further research is needed to refine nanoparticle designs,optimize their safety profiles,and ensure their scalability for widespread application.Rigorous clinical trials are essential to validate their efficacy,assess long-term biocompatibility,and address potential off-target effects.The integration of interdisciplinary approaches,combining insights from nanotechnology,neuroscience,and pharmacology,will be critical if we are to overcome these challenges.Ultimately,nanoparticle-based therapies offer a foundation for innovative,precision-based treatments that could significantly improve outcomes for stroke patients,thus paving the way for a new era in stroke care and neurological rehabilitation.
基金National Natural Science Foundation of China,No.42101252。
文摘Rapid regional population shifts and spatial polarization have heightened pressure on cultivated land—a critical resource demanding urgent attention amid ongoing urban-rural transition.This study selects Jiangsu province,a national leader in both economic and agricultural development,as a case area to construct a multidimensional framework for assessing the recessive morphological characteristics of multifunctional cultivated land use.We examine temporal dynamics,spatial heterogeneity,and propose an integrated zoning strategy based on empirical analysis.The results reveal that:(1)The recessive morphology index shows a consistent upward trend,with structural breaks in 2007 and 2013,and a spatial shift from“higher in the east and lower in the west”to“higher in the south and lower in the north.”(2)Coordination among sub-dimensions of the index has steadily improved.(3)The index is expected to continue rising in the next decade,though at a slower pace.(4)To promote coordinated multidimensional land-use development,we recommend a policy framework that reinforces existing strengths,addresses weaknesses,and adapts zoning schemes to current spatial conditions.This research offers new insights into multifunctional cultivated land systems and underscores their role in enhancing human well-being,securing food supply,and supporting sustainable urban-rural integration.
基金supported by the Natural Science Foundation of Beijing Municipality(Grant No.7234401)the Postdoctoral Research Foundation of China(Grant No.88014Y0226)。
文摘Cardiovascular disease(CVD)is often accompanied by chronic kidney disease(CKD)and metabolic disorders such as obesity and type 2 diabetes^([1]).The coexistence of these conditions can lead to systemic dysfunction and substantially increase adverse cardiovascular outcomes.To describe this interplay,the American Heart Association(AHA)recently proposed the concept of cardiovascular-kidney-metabolic(CKM)syndrome^([1]).However,its risk-enhancing factors and underlying mechanisms remain unclear.
文摘The rise of the aging population parallels the rapidly increasing cases of neurological disorders. This puts pressure on scientists and physicians to find novel methods that can prevent and treat neurodegeneration. The brain is made up of a complex network of different cell types that work in tandem to maintain systemic homeostasis.
基金The researchers would like to thank the Deanship of Graduate Studies and Scientific Research at Qassim University for financial support(QU-APC-2025)。
文摘The evolution of cities into digitally managed environments requires computational systems that can operate in real time while supporting predictive and adaptive infrastructure management.Earlier approaches have often advanced one dimension—such as Internet of Things(IoT)-based data acquisition,Artificial Intelligence(AI)-driven analytics,or digital twin visualization—without fully integrating these strands into a single operational loop.As a result,many existing solutions encounter bottlenecks in responsiveness,interoperability,and scalability,while also leaving concerns about data privacy unresolved.This research introduces a hybrid AI–IoT–Digital Twin framework that combines continuous sensing,distributed intelligence,and simulation-based decision support.The design incorporates multi-source sensor data,lightweight edge inference through Convolutional Neural Networks(CNN)and Long ShortTerm Memory(LSTM)models,and federated learning enhanced with secure aggregation and differential privacy to maintain confidentiality.A digital twin layer extends these capabilities by simulating city assets such as traffic flows and water networks,generating what-if scenarios,and issuing actionable control signals.Complementary modules,including model compression and synchronization protocols,are embedded to ensure reliability in bandwidth-constrained and heterogeneous urban environments.The framework is validated in two urban domains:traffic management,where it adapts signal cycles based on real-time congestion patterns,and pipeline monitoring,where it anticipates leaks through pressure and vibration data.Experimental results show a 28%reduction in response time,a 35%decrease in maintenance costs,and a marked reduction in false positives relative to conventional baselines.The architecture also demonstrates stability across 50+edge devices under federated training and resilience to uneven node participation.The proposed system provides a scalable and privacy-aware foundation for predictive urban infrastructure management.By closing the loop between sensing,learning,and control,it reduces operator dependence,enhances resource efficiency,and supports transparent governance models for emerging smart cities.
基金supported by the National Key Research and Development Program of China (MOST)(Grant No.2022YFA1402800)the Chinese Academy of Sciences (CAS) Presidents International Fellowship Initiative (PIFI)(Grant No.2025PG0006)+3 种基金the National Natural Science Foundation of China (NSFC)(Grant Nos.51831012,12274437,and 52161160334)the CAS Project for Young Scientists in Basic Research (Grant No.YSBR-084)the CAS Youth Interdisciplinary Teamthe China Postdoctoral Science Foundation (Grant No.2025M773402)。
文摘Based on the Smit-Suhl formula,we propose a universal approach for solving the magnon-magnon coupling problem in bilayer coupled systems(e.g.,antiferromagnets).This method requires only the energy expression,enabling the automatic derivation of analytical expressions for the eigenmatrix elements via symbolic computation,eliminating the need for tedious manual calculations.Using this approach,we investigate the impact of magnetic hysteresis on magnon-magnon coupling in a system with interlayer Dzyaloshinskii-Moriya interaction(DMI).The magnetic hysteresis leads to an asymmetric magnetic field dependence of the resonance frequency and alters the number of degeneracy points between the pure optical and acoustic modes.Moreover,it can result in the coupling strength at the gap of the f–H phase diagram being nearly vanishing,contrary to the conventionally expected maximum.These results deepen the understanding of the effect of interlayer DMI on magnon–magnon coupling and the proposed universal method significantly streamlines the solving process of magnon–magnon coupling problems.
文摘Two international conferences in November 2025 jointly outlined a profound transformation of climate governance.The Committee on Trade and Environment(CTE)of the World Trade Organization(WTO)held a conference in Geneva,Switzerland,on November 4,where the topic of cooperation on trade-related carbon standards aroused heated discussions.The Leaders'Summit of the 30th Conference of the Parties(COP)to the UN Framework Convention on Climate Change(UNFCCC)was held in Belém,Brazil,on November 7.At the meeting,the Open Coalition on Compliance Carbon Markets was officially launched with the initial membership of 11 economies including Brazil,China,and the EU.As the world's first transnational alliance on compliant carbon markets,the coalition aims to coordinate carbon pricing mechanisms,emission trading systems and related policies in various countries,and realize the interconnection of global compliance carbon market networks.
文摘Climate model prediction has been improved by enhancing model resolution as well as the implementation of sophisticated physical parameterization and refinement of data assimilation systems[section 6.1 in Wang et al.(2025)].In relation to seasonal forecasting and climate projection in the East Asian summer monsoon season,proper simulation of the seasonal migration of rain bands by models is a challenging and limiting factor[section 7.1 in Wang et al.(2025)].
基金supported by the National Natural Science Foundation of China(Grant Nos.62450006,62304217,62274157,62127807,62234011,62034008,62074142,62074140)Tianshan Innovation Team Program(Grant No.2022TSYCTD0005)+1 种基金Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDB0880000)Youth Innovation Promotion Association of the Chinese Academy of Sciences(Grant Nos.2023124,Y2023032)。
文摘The 193 nm deep-ultraviolet(DUV)laser plays a critical role in advanced semiconductor chip manufacturing[1,2],micro-nano material characterization[3,4]and biomedical analysis[5,6],due to its high spatial resolution and short wavelength.Efficient and compact 193 nm DUV laser source thus becomes a hot research area.Currently,193 nm Ar F excimer gas laser is widely employed in DUV lithography systems and serves as the enabling technology for 7 and 5 nm semiconductor fabrication.
文摘Mental health is a significant issue worldwide,and the utilization of technology to assist mental health has seen a growing trend.This aims to alleviate the workload on healthcare professionals and aid individuals.Numerous applications have been developed to support the challenges in intelligent healthcare systems.However,because mental health data is sensitive,privacy concerns have emerged.Federated learning has gotten some attention.This research reviews the studies on federated learning and mental health related to solving the issue of intelligent healthcare systems.It explores various dimensions of federated learning in mental health,such as datasets(their types and sources),applications categorized based on mental health symptoms,federated mental health frameworks,federated machine learning,federated deep learning,and the benefits of federated learning in mental health applications.This research conducts surveys to evaluate the current state of mental health applications,mainly focusing on the role of Federated Learning(FL)and related privacy and data security concerns.The survey provides valuable insights into how these applications are emerging and evolving,specifically emphasizing FL’s impact.
