Knee osteoarthritis(KOA)represents one of the most common causes of chronic pain.The high prevalence and disability rates of KOA impose a severe burden on both individuals and society.In contrast to cutaneous pain,KOA...Knee osteoarthritis(KOA)represents one of the most common causes of chronic pain.The high prevalence and disability rates of KOA impose a severe burden on both individuals and society.In contrast to cutaneous pain,KOA-induced joint pain is characterized as a deep tissue pain that potentially involves distinct subgroups of peripheral sensory neurons and central processing mechanisms.Furthermore,KOA pain is closely related to locomotion activity.Impaired sensorimotor integration and pain mutually reinforce each other in KOA,forming a vicious cycle that exacerbates disease progression.In this review,we highlight the key differences between KOA pain and cutaneous pain,and the latter has been extensively studied in the pain field.We hope to offer new insights into the central mechanisms and development of new treatment strategies for KOA based on the interactions between impaired sensorimotor integration and chronic joint pain.展开更多
Multi-organ-on-a-chip(MOOC)technology represents a pivotal direction in the organ-on-a-chip field,seeking to emulate the complex interactions of multiple human organs in vitro through microfluidic systems.This technol...Multi-organ-on-a-chip(MOOC)technology represents a pivotal direction in the organ-on-a-chip field,seeking to emulate the complex interactions of multiple human organs in vitro through microfluidic systems.This technology overcomes the limitations of traditional single-organ models,providing a novel platform for investigating complex disease mechanisms and evaluating drug efficacy and toxicity.Although it demonstrates broad application prospects,its development still faces critical bottlenecks,including inadequate physiological coupling between organs,short functional maintenance durations,and limited real-time monitoring capabilities.Contemporary research is advancing along three key directions,including functional coupling,sensor integration,and full-process automation systems,to propel the technology toward enhanced levels of physiological relevance and predictive accuracy.展开更多
Since the first design of tactile sensors was proposed by Harmon in 1982,tactile sensors have evolved through four key phases:industrial applications(1980s,basic pressure detection),miniaturization via MEMS(1990s),fle...Since the first design of tactile sensors was proposed by Harmon in 1982,tactile sensors have evolved through four key phases:industrial applications(1980s,basic pressure detection),miniaturization via MEMS(1990s),flexible electronics(2010s,stretchable materials),and intelligent systems(2020s-present,AI-driven multimodal sensing).With the innovation of material,processing techniques,and multimodal fusion of stimuli,the application of tactile sensors has been continuously expanding to a diversity of areas,including but not limited to medical care,aerospace,sports and intelligent robots.Currently,researchers are dedicated to develop tactile sensors with emerging mechanisms and structures,pursuing high-sensitivity,high-resolution,and multimodal characteristics and further constructing tactile systems which imitate and approach the performance of human organs.However,challenges in the combination between the theoretical research and the practical applications are still significant.There is a lack of comprehensive understanding in the state of the art of such knowledge transferring from academic work to technical products.Scaled-up production of laboratory materials faces fatal challenges like high costs,small scale,and inconsistent quality.Ambient factors,such as temperature,humidity,and electromagnetic interference,also impair signal reliability.Moreover,tactile sensors must operate across a wide pressure range(0.1 k Pa to several or even dozens of MPa)to meet diverse application needs.Meanwhile,the existing algorithms,data models and sensing systems commonly reveal insufficient precision as well as undesired robustness in data processing,and there is a realistic gap between the designed and the demanded system response speed.In this review,oriented by the design requirements of intelligent tactile sensing systems,we summarize the common sensing mechanisms,inspired structures,key performance,and optimizing strategies,followed by a brief overview of the recent advances in the perspectives of system integration and algorithm implementation,and the possible roadmap of future development of tactile sensors,providing a forward-looking as well as critical discussions in the future industrial applications of flexible tactile sensors.展开更多
Ningxia is an ethnic gathering area boasting abundant tourism and cultural resources.Developing the cause of tourism and culture is an important way to encourage all ethnic groups to respect differences,embrace divers...Ningxia is an ethnic gathering area boasting abundant tourism and cultural resources.Developing the cause of tourism and culture is an important way to encourage all ethnic groups to respect differences,embrace diversity,and demonstrate their interactions,exchanges,and integration in tourism activities.As an important preserve of the distinctive cultures of the Chinese nation and a prominent world tourist destination,Ningxia should strive to foster and consolidate the sense of a community with a shared future for the Chinese nation in developing its tourism and culture under the new historical conditions.It is imperative to advance the prosperity and development of tourism and culture in boosting ethnic interactions,exchanges,and integration through the formulation of tourism and cultural policies and plans,as well as the development and design of tourism and cultural projects.展开更多
Promoting urban-rural integration and facilitating the bidirectional flow of urban and rural elements are core spatial objectives in the new era of China.The urban-rural fringe represents the region with the most inte...Promoting urban-rural integration and facilitating the bidirectional flow of urban and rural elements are core spatial objectives in the new era of China.The urban-rural fringe represents the region with the most intense interaction between urban and rural areas,serving as a key zone for breaking down barriers and promoting urban-rural integration.Based on a systematic review of representative case studies and scholarly literature,this paper synthesizes the evolving research perspectives on the urban-rural fringe,with particular attention to how data-driven approaches that integrate official statistics,remote sensing imagery,points of interest,and mobile phone signaling data have advanced the characterization of fringe features,refined identification methods,and revealed emerging developmental trends through spatial clustering and machine learning classification.It proposes an integrated analytical framework encompassing administrative boundaries,economic metabolism,social activities,material infrastructure,and the ecological environment.The paper further examines the characteristics and emerging development trends of urban-rural fringe areas and advances a set of strategic directions to support urban-rural integration and more efficient resource allocation.These include expanding analytical dimensions,enhancing data integration,refining identification criteria,elucidating mechanisms of internal and external interactions,and strengthening interdisciplinary collaboration.Collectively,these efforts offer actionable insights for optimizing public service delivery,directing infrastructure investment in transportation and utilities,delineating ecological conservation boundaries,and implementing place-based socioeconomic revitalization strategies in the urban-rural fringe regions.展开更多
As silicon-based transistors face fundamental scaling limits,the search for breakthrough alternatives has led to innovations in 3D architectures,heterogeneous integration,and sub-3 nm semiconductor body thicknesses.Ho...As silicon-based transistors face fundamental scaling limits,the search for breakthrough alternatives has led to innovations in 3D architectures,heterogeneous integration,and sub-3 nm semiconductor body thicknesses.However,the true effectiveness of these advancements lies in the seamless integration of alternative semiconductors tailored for next-generation transistors.In this review,we highlight key advances that enhance both scalability and switching performance by leveraging emerging semiconductor materials.Among the most promising candidates are 2D van der Waals semiconductors,Mott insulators,and amorphous oxide semiconductors,which offer not only unique electrical properties but also low-power operation and high carrier mobility.Additionally,we explore the synergistic interactions between these novel semiconductors and advanced gate dielectrics,including high-K materials,ferroelectrics,and atomically thin hexagonal boron nitride layers.Beyond introducing these novel material configurations,we address critical challenges such as leakage current and long-term device reliability,which become increasingly crucial as transistors scale down to atomic dimensions.Through concrete examples showcasing the potential of these materials in transistors,we provide key insights into overcoming fundamental obstacles—such as device reliability,scaling down limitations,and extended applications in artificial intelligence—ultimately paving the way for the development of future transistor technologies.展开更多
China is carving out a distinctive development path which features urban-rural integration.This approach has not only yielded tangible results domestically but also drawn the attention of other countries.
Objective:To analyze the application effectiveness of the integrated medical-nursing comprehensive care model in cases of cerebral infarction and clarify its clinical practical value for the patient rehabilitation pro...Objective:To analyze the application effectiveness of the integrated medical-nursing comprehensive care model in cases of cerebral infarction and clarify its clinical practical value for the patient rehabilitation process.Methods:A total of 60 patients with cerebral infarction admitted from June 2024 to December 2024 were selected as the research subjects and randomly divided into a control group and a research group,with 30 cases in each group.Patients in the control group received routine clinical nursing measures,while those in the study group underwent collaborative healthcare intervention in addition to routine nursing.The intervention included joint disease assessment,personalized rehabilitation training guidance,psychological counseling,and continuous nursing services after discharge.A comparative study was conducted by evaluating indicators such as the scores on adverse emotion scales,the extent of neurological recovery,the effectiveness rate of clinical rehabilitation treatment,and the level of satisfaction with nursing services between the two groups.Results:After the intervention,the scores on the Self-Rating Anxiety Scale(SAS)and the Self-Rating Depression Scale(SDS)in the study group decreased to(40.12±5.01)and(41.36±5.20),respectively,both significantly lower than those in the control group,which were(47.36±5.82)and(48.95±5.63),respectively.The differences between the two groups were statistically significant(p<0.05).The improvement in the neurological deficit scores of patients in the study group reached(9.18±2.04),higher than that in the control group,which was(5.17±1.82)(p<0.05).The overall clinical rehabilitation effectiveness rate in the study group was 93.3%,significantly higher than that in the control group,which was 73.3%.The satisfaction rate with nursing services in the study group reached 96.7%,also higher than that in the control group,which was 83.3%.The differences between the two groups were statistically significant(p<0.05).Conclusion:The integrated healthcare nursing model can effectively alleviate adverse emotional states in patients with cerebral infarction,facilitate the repair and reconstruction of neurological function,improve the effectiveness of clinical rehabilitation treatment and satisfaction with nursing services,and thus holds high value for clinical promotion and application.展开更多
Optimization algorithms are crucial for solving NP-hard problems in engineering and computational sciences.Metaheuristic algorithms,in particular,have proven highly effective in complex optimization scenarios characte...Optimization algorithms are crucial for solving NP-hard problems in engineering and computational sciences.Metaheuristic algorithms,in particular,have proven highly effective in complex optimization scenarios characterized by high dimensionality and intricate variable relationships.The Mountain Gazelle Optimizer(MGO)is notably effective but struggles to balance local search refinement and global space exploration,often leading to premature convergence and entrapment in local optima.This paper presents the Improved MGO(IMGO),which integrates three synergistic enhancements:dynamic chaos mapping using piecewise chaotic sequences to boost explo-ration diversity;Opposition-Based Learning(OBL)with adaptive,diversity-driven activation to speed up convergence;and structural refinements to the position update mechanisms to enhance exploitation.The IMGO underwent a comprehensive evaluation using 52 standardised benchmark functions and seven engineering optimization problems.Benchmark evaluations showed that IMGO achieved the highest rank in best solution quality for 31 functions,the highest rank in mean performance for 18 functions,and the highest rank in worst-case performance for 14 functions among 11 competing algorithms.Statistical validation using Wilcoxon signed-rank tests confirmed that IMGO outperformed individual competitors across 16 to 50 functions,depending on the algorithm.At the same time,Friedman ranking analysis placed IMGO with an average rank of 4.15,compared to the baseline MGO’s 4.38,establishing the best overall performance.The evaluation of engineering problems revealed consistent improvements,including an optimal cost of 1.6896 for the welded beam design vs.MGO’s 1.7249,a minimum cost of 5885.33 for the pressure vessel design vs.MGO’s 6300,and a minimum weight of 2964.52 kg for the speed reducer design vs.MGO’s 2990.00 kg.Ablation studies identified OBL as the strongest individual contributor,whereas complete integration achieved superior performance through synergistic interactions among components.Computational complexity analysis established an O(T×N×5×f(P))time complexity,representing a 1.25×increase in fitness evaluation relative to the baseline MGO,validating the favorable accuracy-efficiency trade-offs for practical optimization applications.展开更多
This survey presents a comprehensive examination of sensor fusion research spanning four decades,tracing the methodological evolution,application domains,and alignment with classical hierarchical models.Building on th...This survey presents a comprehensive examination of sensor fusion research spanning four decades,tracing the methodological evolution,application domains,and alignment with classical hierarchical models.Building on this long-term trajectory,the foundational approaches such as probabilistic inference,early neural networks,rulebasedmethods,and feature-level fusion established the principles of uncertainty handling andmulti-sensor integration in the 1990s.The fusion methods of 2000s marked the consolidation of these ideas through advanced Kalman and particle filtering,Bayesian–Dempster–Shafer hybrids,distributed consensus algorithms,and machine learning ensembles for more robust and domain-specific implementations.From 2011 to 2020,the widespread adoption of deep learning transformed the field driving some major breakthroughs in the autonomous vehicles domain.A key contribution of this work is the assessment of contemporary methods against the JDL model,revealing gaps at higher levels-especially in situation and impact assessment.Contemporary methods offer only limited implementation of higher-level fusion.The survey also reviews the benchmark multi-sensor datasets,noting their role in advancing the field while identifying major shortcomings like the lack of domain diversity and hierarchical coverage.By synthesizing developments across decades and paradigms,this survey provides both a historical narrative and a forward-looking perspective.It highlights unresolved challenges in transparency,scalability,robustness,and trustworthiness,while identifying emerging paradigms such as neuromorphic fusion and explainable AI as promising directions.This paves the way forward for advancing sensor fusion towards transparent and adaptive next-generation autonomous systems.展开更多
Background:Giant cell arteritis(GCA),the most common systemic vasculitis affecting elderly individuals,currently lacks specific therapies.This study aimed to systematically identify therapeutic targets for GCA through...Background:Giant cell arteritis(GCA),the most common systemic vasculitis affecting elderly individuals,currently lacks specific therapies.This study aimed to systematically identify therapeutic targets for GCA through integration of large-scale multi-omics datasets.Methods:We constructed a multi-stage analytical framework encompassing 32 proteomic datasets(covering 2914 unique plasma proteins)and 6 transcriptomic datasets.Multi-omics integration strategies,including two-sample Mendelian randomization,colocalization analysis,and functional enrichment analysis,were employed to identify and validate causal relationships between candidate targets and GCA risk across 4 independent European-ancestry GCA cohorts.Single-cell RNA sequencing analysis of peripheral blood mononuclear cells from untreated GCA patients was performed to characterize hub gene-immune cell relationships.Results:We identified 43 plasma proteins causally associated with GCA[false discovery rate(FDR)<0.05],with 17 representing novel therapeutic targets.Through dual validation using proteome-wide association studies and transcriptome-wide association studies,we identified 13 high-confidence candidate targets with distinct tissue-specific expression patterns.Unc-51 like kinase 3(ULK3)emerged as the strongest protective factor(odds ratio=0.47,95%confidence interval:0.37–0.71)through autophagy regulation,while SLAMF7 represents an immediate drug repositioning opportunity as the target of food and drug administration-approved elotuzumab.Five targets have existing approved drugs(SLAMF7,ICAM1,IL18,IL6ST,CTSS).Single-cell analysis revealed profound disruption of hub gene-immune cell relationships in untreated GCA patients,with cell-type-specific alterations in inflammatory gene expression,and TYMP as the most critical hub gene.Conclusions:This study provides a clinically-actionable atlas of 43 potential therapeutic targets in GCA,identifying novel mechanisms including autophagy modulation and metabolic reprogramming,with immediate drug repositioning opportunities and precision medicine strategies based on tissue-specific and cell-type-specific expression patterns.These findings require experimental validation before clinical translation.展开更多
This study aims to promote the optimization and upgrading of the economic structure in rural areas of China by focusing on the coupling coordination mechanism between digital economy–agriculture integration and rural...This study aims to promote the optimization and upgrading of the economic structure in rural areas of China by focusing on the coupling coordination mechanism between digital economy–agriculture integration and rural revitalization.By examining panel data from 30 Chinese provinces,autonomous regions,and municipalities between 2011 and 2022,the research constructs a weight-based evaluation system that integrates subjective and objective methods and a coupling coordination model to reveal its dynamic evolution patterns.Key findings indicate that digital economy–agriculture integration and rural revitalization achieve cross-coupling through critical activities.The impact of digital-agriculture integration on advancing rural revitalization lags by 2–3 years.Although the coupling development degree between the two systems continues to improve,it remains at the stage of primary coordination.Regional disparities are significant,showing a gradient pattern of“high degree of coupling development in the east and low degree of coupling development in the west.”展开更多
The rapid proliferation of microelectronics,coupled with the advent of the internet ofthings(IoT)era,has created an urgent demand for miniaturized,integrable,and reliable on-chip energystorage systems.All-solid-state ...The rapid proliferation of microelectronics,coupled with the advent of the internet ofthings(IoT)era,has created an urgent demand for miniaturized,integrable,and reliable on-chip energystorage systems.All-solid-state thin-film microbatteries(TFMBs),distinguished by their intrinsicsafety,compact design,and compatibility with microfabrication techniques,have emerged as promisingcandidates to power next-generation IoT devices.Nevertheless,in contrast to the well-establisheddevelopment of conventional lithium-ion batteries,the advancement of TFMBs remains at an earlystage,facing persistent challenges in materials innovation,interface optimization,and scalable manufacturing.This review critically examines the pivotal role of vapor deposition technologies,includingmagnetron sputtering,pulsed laser deposition,thermal/electron-beam evaporation,chemical vapordeposition,and atomic layer deposition,in the fabrication and performance modulation of TFMBs.We systematically summarize recent progress in thin-film electrodes and solid-state electrolytes,withparticular emphasis on how deposition parameters dictate crystallinity,lattice orientation,and ionictransport in functional layers.Furthermore,we highlight strategies for solid-solid interface engineering,three-dimensional structural design,andmultifunctional integration to enhance capacity retention,cycling stability,and interfacial compatibility.Looking ahead,TFMBs are expectedto evolve toward multifunctional platforms,exhibiting mechanical flexibility,optical transparency,and hybrid energy-harvesting compatibility,thereby meeting the heterogeneous energy requirements of future IoT ecosystems.Overall,this review provides a comprehensive perspective onvapor-phase-enabled TFMB technologies,delivering both theoretical insights and technological guidelines for the scalable realization of highperformancemicroscale power sources.展开更多
Objectives:Phosphodiesterase 1A(PDE1A)regulates intracellular cyclic nucleotide signaling and has been implicated in tumor progression,but its clinical relevance and functional role in epithelial ovarian cancer(EOC),p...Objectives:Phosphodiesterase 1A(PDE1A)regulates intracellular cyclic nucleotide signaling and has been implicated in tumor progression,but its clinical relevance and functional role in epithelial ovarian cancer(EOC),particularly in relation to the response to platinum remain unclear.This study aimed to evaluate the clinical significance of PDE1A in EOG and to clarify its functional role in tumor progression and response to platinum-based chemotherapy.Methods:PDE1A mRNA and protein levels were analyzed using public databases,RNA sequencing,and immunohistochemistry.Correlations between PDE1A expression,clinicopathological features,and prognosis were assessed.Functional roles were investigated in ovarian cancer cell lines.Results:PDE1A was significantly overexpressed in EOC tissues compared with that in normal ovarian epithelial tissues.Overexpression correlated with advanced International Federation of Gynecology and Obstetrics(FIGO)stage,poor tumor grade,and reduced response to platinum-based chemotherapy.High PDE1A levels were linked to worse disease-free survival and overall survival,and multivariate analysis confirmed PDE1A as an independent prognostic factor.To elucidate its functional role,we performed in vitro experiments showing that PDE1A knockdown suppressed cell proliferation and colony formation,induced G1 arrest,and downregulatedβ-catenin signaling with reduced cyclin D1 and c-Myc expression.Notably,these inhibitory effects were partially rescued by lithium chloride(LiCl),a Wingless-related integration site(Wnt)/β-catenin activator.Conclusions:In conclusion,our findings identify PDE1A as a Wnt/β-catenin-linked biomarker of tumor progression and platinum resistance in EOC and provide a biological rationale for further investigation of PDE1A-targeted strategies in preclinical models.展开更多
Flexible electronics face critical challenges in achieving monolithic three-dimensional(3D)integration,including material compatibility,structural stability,and scalable fabrication methods.Inspired by the tactile sen...Flexible electronics face critical challenges in achieving monolithic three-dimensional(3D)integration,including material compatibility,structural stability,and scalable fabrication methods.Inspired by the tactile sensing mechanism of the human skin,we have developed a flexible monolithic 3D-integrated tactile sensing system based on a holey MXene paste,where each vertical one-body unit simultaneously functions as a microsupercapacitor and pressure sensor.The in-plane mesopores of MXene significantly improve ion accessibility,mitigate the self-stacking of nanosheets,and allow the holey MXene to multifunctionally act as a sensing material,an active electrode,and a conductive interconnect,thus drastically reducing the interface mismatch and enhancing the mechanical robustness.Furthermore,we fabricate a large-scale device using a blade-coating and stamping method,which demonstrates excellent mechanical flexibility,low-power consumption,rapid response,and stable long-term operation.As a proof-of-concept application,we integrate our sensing array into a smart access control system,leveraging deep learning to accurately identify users based on their unique pressing behaviors.This study provides a promising approach for designing highly integrated,intelligent,and flexible electronic systems for advanced human-computer interactions and personalized electronics.展开更多
[Objective]This study aims to investigate the multi-body hydrodynamic interaction mechanisms during offshore lifting operations of aquaculture net cages in wind-fishery integration systems.By integrating numerical sim...[Objective]This study aims to investigate the multi-body hydrodynamic interaction mechanisms during offshore lifting operations of aquaculture net cages in wind-fishery integration systems.By integrating numerical simulations and dynamic analysis methods,this study systematically investigates the coupled dynamic response characteristics during the cage-carrier vessel separation process to reveal its dynamic evolution patterns and key influence mechanisms.[Method]Based on potential flow theory,a fully coupled dynamic analysis model of crane vessel-net cage-semi-submersible barge was established for a marine ranch project in Guangdong.The complete lifting process was dynamically simulated using SESAM software.Five typical operating sea states were configured to investigate the influence of wave parameters on the system's motion response under combined wave-current-wind actions.[Result]The results demonstrate that wave period dominates the system stability.Under short-period conditions,the system maintains stable motion with relatively small horizontal relative displacements,while long-period conditions excite low-frequency resonance,leading to significant slow-drift motions.Vertical response analysis reveals that long-period waves cause severe relative displacement fluctuations between the cage and semi-submersible vessel,with actual displacement amplitudes doubling the preset safety target of 2.045 m.Quantitative analysis further indicates that when significant wave height increases from 1.0 m to 1.5 m,the actual displacement amplitude increases by approximately 20%relative to the target displacement of 2.045 m,demonstrating that its influence is significantly weaker than the displacement variations induced by wave period changes.The complete dynamic simulation successfully captures the continuous dynamic response characteristics during the lifting process.[Conclusion]This research clarifies the influence mechanisms of wave parameters on the cage lifting process,identifying wave period as the crucial factor for operational safety.An operation window assessment method incorporating multi-body coupling effects is established,proposing a safety criterion with peak period not exceeding six seconds as the core requirement.The findings provide theoretical foundation for safe installation of marine ranch net cages and offer valuable references for similar offshore lifting operations.展开更多
A case of imported severe falciparum malaria with spontaneous splenic rupture was reported in this paper.The patient,an African migrant worker,developed hemolytic anemia,sepsis,thrombocytopenia,coagulation dysfunction...A case of imported severe falciparum malaria with spontaneous splenic rupture was reported in this paper.The patient,an African migrant worker,developed hemolytic anemia,sepsis,thrombocytopenia,coagulation dysfunction,liver failure,renal insufficiency,electrolyte disturbance and other clinical manifestations after returning to the local area.Plasmodium falciparum was found by peripheral blood smearscopy and was diagnosed as severe falciparum malaria.After standardized anti-malaria treatment,plasma exchange+cytokine adsorption therapy,the establishment of“forewarning-forewarning-prevention-emergency”predictive nursing management model,the establishment of an integrated nursing team,the division of medical care is clear,professional knowledge is complementary,after three months of regular follow-up,the patient has no malaria recurrence,no refire,the function of all organs returned to normal.展开更多
In reliability analyses,the absence of a priori information on the most probable point of failure(MPP)may result in overlooking critical points,thereby leading to biased assessment outcomes.Moreover,second-order relia...In reliability analyses,the absence of a priori information on the most probable point of failure(MPP)may result in overlooking critical points,thereby leading to biased assessment outcomes.Moreover,second-order reliability methods exhibit limited accuracy in highly nonlinear scenarios.To overcome these challenges,a novel reliability analysis strategy based on a multimodal differential evolution algorithm and a hypersphere integration method is proposed.Initially,the penalty function method is employed to reformulate the MPP search problem as a conditionally constrained optimization task.Subsequently,a differential evolution algorithm incorporating a population delineation strategy is utilized to identify all MPPs.Finally,a paraboloid equation is constructed based on the curvature of the limit-state function at the MPPs,and the failure probability of the structure is calculated by using the hypersphere integration method.The localization effectiveness of the MPPs is compared through multiple numerical cases and two engineering examples,with accuracy comparisons of failure probabilities against the first-order reliability method(FORM)and the secondorder reliability method(SORM).The results indicate that the method effectively identifies existing MPPs and achieves higher solution precision.展开更多
The rapid growth of biomedical data,particularly multi-omics data including genomes,transcriptomics,proteomics,metabolomics,and epigenomics,medical research and clinical decision-making confront both new opportunities...The rapid growth of biomedical data,particularly multi-omics data including genomes,transcriptomics,proteomics,metabolomics,and epigenomics,medical research and clinical decision-making confront both new opportunities and obstacles.The huge and diversified nature of these datasets cannot always be managed using traditional data analysis methods.As a consequence,deep learning has emerged as a strong tool for analysing numerous omics data due to its ability to handle complex and non-linear relationships.This paper explores the fundamental concepts of deep learning and how they are used in multi-omics medical data mining.We demonstrate how autoencoders,variational autoencoders,multimodal models,attention mechanisms,transformers,and graph neural networks enable pattern analysis and recognition across all omics data.Deep learning has been found to be effective in illness classification,biomarker identification,gene network learning,and therapeutic efficacy prediction.We also consider critical problems like as data quality,model explainability,whether findings can be repeated,and computational power requirements.We now consider future elements of combining omics with clinical and imaging data,explainable AI,federated learning,and real-time diagnostics.Overall,this study emphasises the need of collaborating across disciplines to advance deep learning-based multi-omics research for precision medicine and comprehending complicated disorders.展开更多
基金supported by the Natural Science Foundation of Beijing Municipality(No.F252065)the National Natural Science Foundation of China(No.32271190,32571323)the STI 2030 Major Project(No.2021ZD0203202)。
文摘Knee osteoarthritis(KOA)represents one of the most common causes of chronic pain.The high prevalence and disability rates of KOA impose a severe burden on both individuals and society.In contrast to cutaneous pain,KOA-induced joint pain is characterized as a deep tissue pain that potentially involves distinct subgroups of peripheral sensory neurons and central processing mechanisms.Furthermore,KOA pain is closely related to locomotion activity.Impaired sensorimotor integration and pain mutually reinforce each other in KOA,forming a vicious cycle that exacerbates disease progression.In this review,we highlight the key differences between KOA pain and cutaneous pain,and the latter has been extensively studied in the pain field.We hope to offer new insights into the central mechanisms and development of new treatment strategies for KOA based on the interactions between impaired sensorimotor integration and chronic joint pain.
基金supported by the Shenzhen Medical Research Fund(Grant No.A2303049)Guangdong Basic and Applied Basic Research(Grant No.2023A1515010647)+1 种基金National Natural Science Foundation of China(Grant No.22004135)Shenzhen Science and Technology Program(Grant No.RCBS20210706092409020,GXWD20201231165807008,20200824162253002).
文摘Multi-organ-on-a-chip(MOOC)technology represents a pivotal direction in the organ-on-a-chip field,seeking to emulate the complex interactions of multiple human organs in vitro through microfluidic systems.This technology overcomes the limitations of traditional single-organ models,providing a novel platform for investigating complex disease mechanisms and evaluating drug efficacy and toxicity.Although it demonstrates broad application prospects,its development still faces critical bottlenecks,including inadequate physiological coupling between organs,short functional maintenance durations,and limited real-time monitoring capabilities.Contemporary research is advancing along three key directions,including functional coupling,sensor integration,and full-process automation systems,to propel the technology toward enhanced levels of physiological relevance and predictive accuracy.
基金the financial support of the National Natural Science Foundation of China(NO.52173028)。
文摘Since the first design of tactile sensors was proposed by Harmon in 1982,tactile sensors have evolved through four key phases:industrial applications(1980s,basic pressure detection),miniaturization via MEMS(1990s),flexible electronics(2010s,stretchable materials),and intelligent systems(2020s-present,AI-driven multimodal sensing).With the innovation of material,processing techniques,and multimodal fusion of stimuli,the application of tactile sensors has been continuously expanding to a diversity of areas,including but not limited to medical care,aerospace,sports and intelligent robots.Currently,researchers are dedicated to develop tactile sensors with emerging mechanisms and structures,pursuing high-sensitivity,high-resolution,and multimodal characteristics and further constructing tactile systems which imitate and approach the performance of human organs.However,challenges in the combination between the theoretical research and the practical applications are still significant.There is a lack of comprehensive understanding in the state of the art of such knowledge transferring from academic work to technical products.Scaled-up production of laboratory materials faces fatal challenges like high costs,small scale,and inconsistent quality.Ambient factors,such as temperature,humidity,and electromagnetic interference,also impair signal reliability.Moreover,tactile sensors must operate across a wide pressure range(0.1 k Pa to several or even dozens of MPa)to meet diverse application needs.Meanwhile,the existing algorithms,data models and sensing systems commonly reveal insufficient precision as well as undesired robustness in data processing,and there is a realistic gap between the designed and the demanded system response speed.In this review,oriented by the design requirements of intelligent tactile sensing systems,we summarize the common sensing mechanisms,inspired structures,key performance,and optimizing strategies,followed by a brief overview of the recent advances in the perspectives of system integration and algorithm implementation,and the possible roadmap of future development of tactile sensors,providing a forward-looking as well as critical discussions in the future industrial applications of flexible tactile sensors.
文摘Ningxia is an ethnic gathering area boasting abundant tourism and cultural resources.Developing the cause of tourism and culture is an important way to encourage all ethnic groups to respect differences,embrace diversity,and demonstrate their interactions,exchanges,and integration in tourism activities.As an important preserve of the distinctive cultures of the Chinese nation and a prominent world tourist destination,Ningxia should strive to foster and consolidate the sense of a community with a shared future for the Chinese nation in developing its tourism and culture under the new historical conditions.It is imperative to advance the prosperity and development of tourism and culture in boosting ethnic interactions,exchanges,and integration through the formulation of tourism and cultural policies and plans,as well as the development and design of tourism and cultural projects.
基金Under the auspices of the Funding Project of Northeast Geological S&T Innovation Center of China Geological Survey(No.QCJJ2024-11)Natural Science Foundation of Liaoning Province(No.2025-BS-0873)+1 种基金Liaoning Provincial Joint Science and Technology Program(No.2024-MSLH-507)National Social Science Foundation of China(No.23ATJ006)。
文摘Promoting urban-rural integration and facilitating the bidirectional flow of urban and rural elements are core spatial objectives in the new era of China.The urban-rural fringe represents the region with the most intense interaction between urban and rural areas,serving as a key zone for breaking down barriers and promoting urban-rural integration.Based on a systematic review of representative case studies and scholarly literature,this paper synthesizes the evolving research perspectives on the urban-rural fringe,with particular attention to how data-driven approaches that integrate official statistics,remote sensing imagery,points of interest,and mobile phone signaling data have advanced the characterization of fringe features,refined identification methods,and revealed emerging developmental trends through spatial clustering and machine learning classification.It proposes an integrated analytical framework encompassing administrative boundaries,economic metabolism,social activities,material infrastructure,and the ecological environment.The paper further examines the characteristics and emerging development trends of urban-rural fringe areas and advances a set of strategic directions to support urban-rural integration and more efficient resource allocation.These include expanding analytical dimensions,enhancing data integration,refining identification criteria,elucidating mechanisms of internal and external interactions,and strengthening interdisciplinary collaboration.Collectively,these efforts offer actionable insights for optimizing public service delivery,directing infrastructure investment in transportation and utilities,delineating ecological conservation boundaries,and implementing place-based socioeconomic revitalization strategies in the urban-rural fringe regions.
基金supported by the National Research Foundation of Korea(NRF)funded by the Ministry of Science and ICT(MSIT),South Korea(RS-2024-00421181)financially supported in part by National R&D Program(2021M3H4A3A02086430)through NRF(National Research Foundation of Korea)funded by Ministry of Science and ICT+2 种基金the National Research Council of Science&Technology(NST)grant by the Korea government(MSIT)(No.GTL25021-210)The Inter-University Semiconductor Research Center,Institute of Engineering Research,and Soft Foundry Institute at Seoul National University provided research facilities for this workhe grant by the National Research Foundation of Korea(NSF)supported by the Korea government(MIST)(RS-2025-16903034)。
文摘As silicon-based transistors face fundamental scaling limits,the search for breakthrough alternatives has led to innovations in 3D architectures,heterogeneous integration,and sub-3 nm semiconductor body thicknesses.However,the true effectiveness of these advancements lies in the seamless integration of alternative semiconductors tailored for next-generation transistors.In this review,we highlight key advances that enhance both scalability and switching performance by leveraging emerging semiconductor materials.Among the most promising candidates are 2D van der Waals semiconductors,Mott insulators,and amorphous oxide semiconductors,which offer not only unique electrical properties but also low-power operation and high carrier mobility.Additionally,we explore the synergistic interactions between these novel semiconductors and advanced gate dielectrics,including high-K materials,ferroelectrics,and atomically thin hexagonal boron nitride layers.Beyond introducing these novel material configurations,we address critical challenges such as leakage current and long-term device reliability,which become increasingly crucial as transistors scale down to atomic dimensions.Through concrete examples showcasing the potential of these materials in transistors,we provide key insights into overcoming fundamental obstacles—such as device reliability,scaling down limitations,and extended applications in artificial intelligence—ultimately paving the way for the development of future transistor technologies.
文摘China is carving out a distinctive development path which features urban-rural integration.This approach has not only yielded tangible results domestically but also drawn the attention of other countries.
基金Science and Technology Support Program Project of Baoding City,Hebei Province(Project No.:2541ZF107)。
文摘Objective:To analyze the application effectiveness of the integrated medical-nursing comprehensive care model in cases of cerebral infarction and clarify its clinical practical value for the patient rehabilitation process.Methods:A total of 60 patients with cerebral infarction admitted from June 2024 to December 2024 were selected as the research subjects and randomly divided into a control group and a research group,with 30 cases in each group.Patients in the control group received routine clinical nursing measures,while those in the study group underwent collaborative healthcare intervention in addition to routine nursing.The intervention included joint disease assessment,personalized rehabilitation training guidance,psychological counseling,and continuous nursing services after discharge.A comparative study was conducted by evaluating indicators such as the scores on adverse emotion scales,the extent of neurological recovery,the effectiveness rate of clinical rehabilitation treatment,and the level of satisfaction with nursing services between the two groups.Results:After the intervention,the scores on the Self-Rating Anxiety Scale(SAS)and the Self-Rating Depression Scale(SDS)in the study group decreased to(40.12±5.01)and(41.36±5.20),respectively,both significantly lower than those in the control group,which were(47.36±5.82)and(48.95±5.63),respectively.The differences between the two groups were statistically significant(p<0.05).The improvement in the neurological deficit scores of patients in the study group reached(9.18±2.04),higher than that in the control group,which was(5.17±1.82)(p<0.05).The overall clinical rehabilitation effectiveness rate in the study group was 93.3%,significantly higher than that in the control group,which was 73.3%.The satisfaction rate with nursing services in the study group reached 96.7%,also higher than that in the control group,which was 83.3%.The differences between the two groups were statistically significant(p<0.05).Conclusion:The integrated healthcare nursing model can effectively alleviate adverse emotional states in patients with cerebral infarction,facilitate the repair and reconstruction of neurological function,improve the effectiveness of clinical rehabilitation treatment and satisfaction with nursing services,and thus holds high value for clinical promotion and application.
文摘Optimization algorithms are crucial for solving NP-hard problems in engineering and computational sciences.Metaheuristic algorithms,in particular,have proven highly effective in complex optimization scenarios characterized by high dimensionality and intricate variable relationships.The Mountain Gazelle Optimizer(MGO)is notably effective but struggles to balance local search refinement and global space exploration,often leading to premature convergence and entrapment in local optima.This paper presents the Improved MGO(IMGO),which integrates three synergistic enhancements:dynamic chaos mapping using piecewise chaotic sequences to boost explo-ration diversity;Opposition-Based Learning(OBL)with adaptive,diversity-driven activation to speed up convergence;and structural refinements to the position update mechanisms to enhance exploitation.The IMGO underwent a comprehensive evaluation using 52 standardised benchmark functions and seven engineering optimization problems.Benchmark evaluations showed that IMGO achieved the highest rank in best solution quality for 31 functions,the highest rank in mean performance for 18 functions,and the highest rank in worst-case performance for 14 functions among 11 competing algorithms.Statistical validation using Wilcoxon signed-rank tests confirmed that IMGO outperformed individual competitors across 16 to 50 functions,depending on the algorithm.At the same time,Friedman ranking analysis placed IMGO with an average rank of 4.15,compared to the baseline MGO’s 4.38,establishing the best overall performance.The evaluation of engineering problems revealed consistent improvements,including an optimal cost of 1.6896 for the welded beam design vs.MGO’s 1.7249,a minimum cost of 5885.33 for the pressure vessel design vs.MGO’s 6300,and a minimum weight of 2964.52 kg for the speed reducer design vs.MGO’s 2990.00 kg.Ablation studies identified OBL as the strongest individual contributor,whereas complete integration achieved superior performance through synergistic interactions among components.Computational complexity analysis established an O(T×N×5×f(P))time complexity,representing a 1.25×increase in fitness evaluation relative to the baseline MGO,validating the favorable accuracy-efficiency trade-offs for practical optimization applications.
文摘This survey presents a comprehensive examination of sensor fusion research spanning four decades,tracing the methodological evolution,application domains,and alignment with classical hierarchical models.Building on this long-term trajectory,the foundational approaches such as probabilistic inference,early neural networks,rulebasedmethods,and feature-level fusion established the principles of uncertainty handling andmulti-sensor integration in the 1990s.The fusion methods of 2000s marked the consolidation of these ideas through advanced Kalman and particle filtering,Bayesian–Dempster–Shafer hybrids,distributed consensus algorithms,and machine learning ensembles for more robust and domain-specific implementations.From 2011 to 2020,the widespread adoption of deep learning transformed the field driving some major breakthroughs in the autonomous vehicles domain.A key contribution of this work is the assessment of contemporary methods against the JDL model,revealing gaps at higher levels-especially in situation and impact assessment.Contemporary methods offer only limited implementation of higher-level fusion.The survey also reviews the benchmark multi-sensor datasets,noting their role in advancing the field while identifying major shortcomings like the lack of domain diversity and hierarchical coverage.By synthesizing developments across decades and paradigms,this survey provides both a historical narrative and a forward-looking perspective.It highlights unresolved challenges in transparency,scalability,robustness,and trustworthiness,while identifying emerging paradigms such as neuromorphic fusion and explainable AI as promising directions.This paves the way forward for advancing sensor fusion towards transparent and adaptive next-generation autonomous systems.
基金supported by grants from the Fundamental Research Funds for the Central Universities(No.2025ZFJH03)the Central Guidance Fund for Local Science and Technology Development(No.2024ZY01054)the CAMS Innovation Fund for Medical Sciences(No.2019-I2M-5-045).
文摘Background:Giant cell arteritis(GCA),the most common systemic vasculitis affecting elderly individuals,currently lacks specific therapies.This study aimed to systematically identify therapeutic targets for GCA through integration of large-scale multi-omics datasets.Methods:We constructed a multi-stage analytical framework encompassing 32 proteomic datasets(covering 2914 unique plasma proteins)and 6 transcriptomic datasets.Multi-omics integration strategies,including two-sample Mendelian randomization,colocalization analysis,and functional enrichment analysis,were employed to identify and validate causal relationships between candidate targets and GCA risk across 4 independent European-ancestry GCA cohorts.Single-cell RNA sequencing analysis of peripheral blood mononuclear cells from untreated GCA patients was performed to characterize hub gene-immune cell relationships.Results:We identified 43 plasma proteins causally associated with GCA[false discovery rate(FDR)<0.05],with 17 representing novel therapeutic targets.Through dual validation using proteome-wide association studies and transcriptome-wide association studies,we identified 13 high-confidence candidate targets with distinct tissue-specific expression patterns.Unc-51 like kinase 3(ULK3)emerged as the strongest protective factor(odds ratio=0.47,95%confidence interval:0.37–0.71)through autophagy regulation,while SLAMF7 represents an immediate drug repositioning opportunity as the target of food and drug administration-approved elotuzumab.Five targets have existing approved drugs(SLAMF7,ICAM1,IL18,IL6ST,CTSS).Single-cell analysis revealed profound disruption of hub gene-immune cell relationships in untreated GCA patients,with cell-type-specific alterations in inflammatory gene expression,and TYMP as the most critical hub gene.Conclusions:This study provides a clinically-actionable atlas of 43 potential therapeutic targets in GCA,identifying novel mechanisms including autophagy modulation and metabolic reprogramming,with immediate drug repositioning opportunities and precision medicine strategies based on tissue-specific and cell-type-specific expression patterns.These findings require experimental validation before clinical translation.
基金Youth project under the National Social Science Foundation of China(15CJY054)key project in Philosophy and Social Sciences funded by the Chongqing Municipal Education Commission(22SKGH091)。
文摘This study aims to promote the optimization and upgrading of the economic structure in rural areas of China by focusing on the coupling coordination mechanism between digital economy–agriculture integration and rural revitalization.By examining panel data from 30 Chinese provinces,autonomous regions,and municipalities between 2011 and 2022,the research constructs a weight-based evaluation system that integrates subjective and objective methods and a coupling coordination model to reveal its dynamic evolution patterns.Key findings indicate that digital economy–agriculture integration and rural revitalization achieve cross-coupling through critical activities.The impact of digital-agriculture integration on advancing rural revitalization lags by 2–3 years.Although the coupling development degree between the two systems continues to improve,it remains at the stage of primary coordination.Regional disparities are significant,showing a gradient pattern of“high degree of coupling development in the east and low degree of coupling development in the west.”
基金supported by the National Key Research and Development Program of China(2023YFA1608800)Guangdong Basic and Applied Basic Research Foundation(2024A1515012385,2024B1515120042)+5 种基金Shenzhen Foundation Research Fund(JCYJ20240813095004006)the National Natural Science Foundation of China(12426301,12275119,52227802)Shenzhen Science and Technology Program(KQTD20200820113047086)Shenzhen Key Laboratory of Solid State Batteries(SYSPG20241211173726011)Guangdong-Hong Kong-Macao Joint Laboratory for Photonic-Thermal-Electrical Energy Materials and Devices(2019B121205001)Guangdong Provincial Key Laboratory of Energy Materials for Electric Power(2018B030322001)。
文摘The rapid proliferation of microelectronics,coupled with the advent of the internet ofthings(IoT)era,has created an urgent demand for miniaturized,integrable,and reliable on-chip energystorage systems.All-solid-state thin-film microbatteries(TFMBs),distinguished by their intrinsicsafety,compact design,and compatibility with microfabrication techniques,have emerged as promisingcandidates to power next-generation IoT devices.Nevertheless,in contrast to the well-establisheddevelopment of conventional lithium-ion batteries,the advancement of TFMBs remains at an earlystage,facing persistent challenges in materials innovation,interface optimization,and scalable manufacturing.This review critically examines the pivotal role of vapor deposition technologies,includingmagnetron sputtering,pulsed laser deposition,thermal/electron-beam evaporation,chemical vapordeposition,and atomic layer deposition,in the fabrication and performance modulation of TFMBs.We systematically summarize recent progress in thin-film electrodes and solid-state electrolytes,withparticular emphasis on how deposition parameters dictate crystallinity,lattice orientation,and ionictransport in functional layers.Furthermore,we highlight strategies for solid-solid interface engineering,three-dimensional structural design,andmultifunctional integration to enhance capacity retention,cycling stability,and interfacial compatibility.Looking ahead,TFMBs are expectedto evolve toward multifunctional platforms,exhibiting mechanical flexibility,optical transparency,and hybrid energy-harvesting compatibility,thereby meeting the heterogeneous energy requirements of future IoT ecosystems.Overall,this review provides a comprehensive perspective onvapor-phase-enabled TFMB technologies,delivering both theoretical insights and technological guidelines for the scalable realization of highperformancemicroscale power sources.
基金supported by the National Research Foundation of Korea(NRF)grant,funded by the Korean government(MIST),Jae-Hoon Kim(NRF-2020R1A2C2004782)Hanbyoul Cho(NRF-RS-2025-00522191)of Funderssupported by the Bio&Medical Technology Development Program of the National Research Foundation(NRF),funded by the Korean Government(MSIT),Jae-Hoon Kim of Funder(NRF-2017M3A9B 8069610).
文摘Objectives:Phosphodiesterase 1A(PDE1A)regulates intracellular cyclic nucleotide signaling and has been implicated in tumor progression,but its clinical relevance and functional role in epithelial ovarian cancer(EOC),particularly in relation to the response to platinum remain unclear.This study aimed to evaluate the clinical significance of PDE1A in EOG and to clarify its functional role in tumor progression and response to platinum-based chemotherapy.Methods:PDE1A mRNA and protein levels were analyzed using public databases,RNA sequencing,and immunohistochemistry.Correlations between PDE1A expression,clinicopathological features,and prognosis were assessed.Functional roles were investigated in ovarian cancer cell lines.Results:PDE1A was significantly overexpressed in EOC tissues compared with that in normal ovarian epithelial tissues.Overexpression correlated with advanced International Federation of Gynecology and Obstetrics(FIGO)stage,poor tumor grade,and reduced response to platinum-based chemotherapy.High PDE1A levels were linked to worse disease-free survival and overall survival,and multivariate analysis confirmed PDE1A as an independent prognostic factor.To elucidate its functional role,we performed in vitro experiments showing that PDE1A knockdown suppressed cell proliferation and colony formation,induced G1 arrest,and downregulatedβ-catenin signaling with reduced cyclin D1 and c-Myc expression.Notably,these inhibitory effects were partially rescued by lithium chloride(LiCl),a Wingless-related integration site(Wnt)/β-catenin activator.Conclusions:In conclusion,our findings identify PDE1A as a Wnt/β-catenin-linked biomarker of tumor progression and platinum resistance in EOC and provide a biological rationale for further investigation of PDE1A-targeted strategies in preclinical models.
基金supported by the National Natural Science Foundation of China(52272177,12204010)the Foundation for the Introduction of High-Level Talents of Anhui University(S020118002/097)+1 种基金the University Synergy Innovation Program of Anhui Province(GXXT-2023-066)the Scientific Research Project of Anhui Provincial Higher Education Institution(2023AH040008)。
文摘Flexible electronics face critical challenges in achieving monolithic three-dimensional(3D)integration,including material compatibility,structural stability,and scalable fabrication methods.Inspired by the tactile sensing mechanism of the human skin,we have developed a flexible monolithic 3D-integrated tactile sensing system based on a holey MXene paste,where each vertical one-body unit simultaneously functions as a microsupercapacitor and pressure sensor.The in-plane mesopores of MXene significantly improve ion accessibility,mitigate the self-stacking of nanosheets,and allow the holey MXene to multifunctionally act as a sensing material,an active electrode,and a conductive interconnect,thus drastically reducing the interface mismatch and enhancing the mechanical robustness.Furthermore,we fabricate a large-scale device using a blade-coating and stamping method,which demonstrates excellent mechanical flexibility,low-power consumption,rapid response,and stable long-term operation.As a proof-of-concept application,we integrate our sensing array into a smart access control system,leveraging deep learning to accurately identify users based on their unique pressing behaviors.This study provides a promising approach for designing highly integrated,intelligent,and flexible electronic systems for advanced human-computer interactions and personalized electronics.
文摘[Objective]This study aims to investigate the multi-body hydrodynamic interaction mechanisms during offshore lifting operations of aquaculture net cages in wind-fishery integration systems.By integrating numerical simulations and dynamic analysis methods,this study systematically investigates the coupled dynamic response characteristics during the cage-carrier vessel separation process to reveal its dynamic evolution patterns and key influence mechanisms.[Method]Based on potential flow theory,a fully coupled dynamic analysis model of crane vessel-net cage-semi-submersible barge was established for a marine ranch project in Guangdong.The complete lifting process was dynamically simulated using SESAM software.Five typical operating sea states were configured to investigate the influence of wave parameters on the system's motion response under combined wave-current-wind actions.[Result]The results demonstrate that wave period dominates the system stability.Under short-period conditions,the system maintains stable motion with relatively small horizontal relative displacements,while long-period conditions excite low-frequency resonance,leading to significant slow-drift motions.Vertical response analysis reveals that long-period waves cause severe relative displacement fluctuations between the cage and semi-submersible vessel,with actual displacement amplitudes doubling the preset safety target of 2.045 m.Quantitative analysis further indicates that when significant wave height increases from 1.0 m to 1.5 m,the actual displacement amplitude increases by approximately 20%relative to the target displacement of 2.045 m,demonstrating that its influence is significantly weaker than the displacement variations induced by wave period changes.The complete dynamic simulation successfully captures the continuous dynamic response characteristics during the lifting process.[Conclusion]This research clarifies the influence mechanisms of wave parameters on the cage lifting process,identifying wave period as the crucial factor for operational safety.An operation window assessment method incorporating multi-body coupling effects is established,proposing a safety criterion with peak period not exceeding six seconds as the core requirement.The findings provide theoretical foundation for safe installation of marine ranch net cages and offer valuable references for similar offshore lifting operations.
基金“Artificial Liver Special Fund”of Beijing Gan Dan Xiang Zhao Public Welfare Foundation(Project No.:iGandanF-1082024-RGG055)。
文摘A case of imported severe falciparum malaria with spontaneous splenic rupture was reported in this paper.The patient,an African migrant worker,developed hemolytic anemia,sepsis,thrombocytopenia,coagulation dysfunction,liver failure,renal insufficiency,electrolyte disturbance and other clinical manifestations after returning to the local area.Plasmodium falciparum was found by peripheral blood smearscopy and was diagnosed as severe falciparum malaria.After standardized anti-malaria treatment,plasma exchange+cytokine adsorption therapy,the establishment of“forewarning-forewarning-prevention-emergency”predictive nursing management model,the establishment of an integrated nursing team,the division of medical care is clear,professional knowledge is complementary,after three months of regular follow-up,the patient has no malaria recurrence,no refire,the function of all organs returned to normal.
基金National Natural Science Foundation of China(No.52375236)Fundamental Research Funds for the Central Universities of China(No.23D110316)。
文摘In reliability analyses,the absence of a priori information on the most probable point of failure(MPP)may result in overlooking critical points,thereby leading to biased assessment outcomes.Moreover,second-order reliability methods exhibit limited accuracy in highly nonlinear scenarios.To overcome these challenges,a novel reliability analysis strategy based on a multimodal differential evolution algorithm and a hypersphere integration method is proposed.Initially,the penalty function method is employed to reformulate the MPP search problem as a conditionally constrained optimization task.Subsequently,a differential evolution algorithm incorporating a population delineation strategy is utilized to identify all MPPs.Finally,a paraboloid equation is constructed based on the curvature of the limit-state function at the MPPs,and the failure probability of the structure is calculated by using the hypersphere integration method.The localization effectiveness of the MPPs is compared through multiple numerical cases and two engineering examples,with accuracy comparisons of failure probabilities against the first-order reliability method(FORM)and the secondorder reliability method(SORM).The results indicate that the method effectively identifies existing MPPs and achieves higher solution precision.
文摘The rapid growth of biomedical data,particularly multi-omics data including genomes,transcriptomics,proteomics,metabolomics,and epigenomics,medical research and clinical decision-making confront both new opportunities and obstacles.The huge and diversified nature of these datasets cannot always be managed using traditional data analysis methods.As a consequence,deep learning has emerged as a strong tool for analysing numerous omics data due to its ability to handle complex and non-linear relationships.This paper explores the fundamental concepts of deep learning and how they are used in multi-omics medical data mining.We demonstrate how autoencoders,variational autoencoders,multimodal models,attention mechanisms,transformers,and graph neural networks enable pattern analysis and recognition across all omics data.Deep learning has been found to be effective in illness classification,biomarker identification,gene network learning,and therapeutic efficacy prediction.We also consider critical problems like as data quality,model explainability,whether findings can be repeated,and computational power requirements.We now consider future elements of combining omics with clinical and imaging data,explainable AI,federated learning,and real-time diagnostics.Overall,this study emphasises the need of collaborating across disciplines to advance deep learning-based multi-omics research for precision medicine and comprehending complicated disorders.
