BACKGROUND Neck pain,a primary symptom of cervical spondylosis,affects patients'physical and mental health,reducing their quality of life.Pain and emotional state interact;however,their longitudinal interrelations...BACKGROUND Neck pain,a primary symptom of cervical spondylosis,affects patients'physical and mental health,reducing their quality of life.Pain and emotional state interact;however,their longitudinal interrelationship remains unclear.In this study,we applied a dual-trajectory model to assess how neck pain and emotional state evolve together over time and how clinical interventions,particularly acupuncture,influence these trajectories.AIM To investigate the longitudinal relationship between neck pain and emotional state in patients with cervical spondylosis.METHODS This prospective cohort study included 472 patients with cervical spondylosis from eight Chinese hospitals.Participants received acupuncture or medication and were followed up at baseline,and at 1,2,4,6,and 8 weeks.Neck pain and emotional distress were assessed using the Northwick Park Neck Pain Questionnaire(NPQ)and the affective subscale of the Short-Form McGill Pain Questionnaire(SF-MPQ),respectively.Group-based trajectory models and dual trajectory analysis were used to identify and correlate pain-emotion trajectories.Multivariate logistic regression identified predictors of group membership.RESULTS Three trajectory groups were identified for NPQ and SF-MPQ scores(low,medium,and high).Higher NPQ trajectory was associated with older age(OR=1.058,P<0.001)and was significantly reduced by acupuncture(OR=0.382,P<0.001).Similarly,acupuncture lowered the odds of high SF-MPQ trajectory membership(OR=0.336,P<0.001),while age increased it(OR=1.037,P<0.001).Dual-trajectory analysis revealed bidirectional associations:69.1%of patients with low NPQ had low SF-MPQ scores,and 42.6%of patients with high SF-MPQ also had high NPQ scores.Gender was a predictor for medium SF-MPQ trajectory(OR=1.629,P=0.094).Occupation and education levels differed significantly across the trajectory groups(P<0.05).CONCLUSION Over time,neck pain and emotional distress are closely associated in patients with cervical spondylosis.Acupuncture alleviates both outcomes significantly,while age is a risk factor.Integrated approaches to pain and emotional management are encouraged.展开更多
Ionic Polymer-Metal Composite （IPMC） is a new electro-active polymer, which has the advantages of light weight, flexibility, and large stroke with low driving voltage. Because of these features, IPMC can be applied ...Ionic Polymer-Metal Composite （IPMC） is a new electro-active polymer, which has the advantages of light weight, flexibility, and large stroke with low driving voltage. Because of these features, IPMC can be applied to bionic robotic actuators, artificial muscles, as well as dynamic sensors. However, IPMC has the major drawback of low generative blocking force. In this paper, in order to enhance the blocking force, the Nation membranes with thickness of 0.22 mm, 0.32 mm, 0.42 mm, 0.64 mm and 0.8 mm were prepared by casting from liquid solution. By employing these Nation membranes, IPMCs with varying thickness were fabricated by electroless plating. The elastic modulus of the casted Nation membranes were obtained by a nano-indenter, and the current, the displacement and the blocking force were respectively measured by the apparatus for actuation test. Finally, the effects of the thickness on the performance of IPMC were analyzed with an electromechanical model. Experimental study and theory analysis indicate that as the thickness increases, the elastic modulus of Nation membrane and the blocking force of IPMC increase, however, the current and the displacement decrease.展开更多
Computer-based conceptual design for routine design has made great strides, yet non-routine design has not been given due attention, and it is still poorly automated. Considering that the function-behavior-structure（...Computer-based conceptual design for routine design has made great strides, yet non-routine design has not been given due attention, and it is still poorly automated. Considering that the function-behavior-structure（FBS） model is widely used for modeling the conceptual design process, a computer-based creativity enhanced conceptual design model（CECD） for non-routine design of mechanical systems is presented. In the model, the leaf functions in the FBS model are decomposed into and represented with fine-grain basic operation actions（BOA）, and the corresponding BOA set in the function domain is then constructed. Choosing building blocks from the database, and expressing their multiple functions with BOAs, the BOA set in the structure domain is formed. Through rule-based dynamic partition of the BOA set in the function domain, many variants of regenerated functional schemes are generated. For enhancing the capability to introduce new design variables into the conceptual design process, and dig out more innovative physical structure schemes, the indirect function-structure matching strategy based on reconstructing the combined structure schemes is adopted. By adjusting the tightness of the partition rules and the granularity of the divided BOA subsets, and making full use of the main function and secondary functions of each basic structure in the process of reconstructing of the physical structures, new design variables and variants are introduced into the physical structure scheme reconstructing process, and a great number of simpler physical structure schemes to accomplish the overall function organically are figured out. The creativity enhanced conceptual design model presented has a dominant capability in introducing new deign variables in function domain and digging out simpler physical structures to accomplish the overall function, therefore it can be utilized to solve non-routine conceptual design problem.展开更多
Co-occurrence pattern of fish species plays an important role in understanding the spatio-temporal structure and the stability of fish community.Species coexistence may vary with time and space.The co-occurrence patte...Co-occurrence pattern of fish species plays an important role in understanding the spatio-temporal structure and the stability of fish community.Species coexistence may vary with time and space.The co-occurrence patterns of fish species were examined using the C-score under fixed-fixed null model for fish communities in spring and autumn over different years in the Haizhou Bay,China.The results showed that fish assemblages in the whole bay had non-random patterns in spring and autumn over different years.However,the fish co-occurrence patterns were different for the northern and southern fish assemblages in spring and autumn.The northern fish assemblage showed structured pattern,whereas the southern assemblage were randomly assembled in spring.The co-occurrence patterns of fish communities were relatively stable over different years,and the number of significant species pairs in northern assemblage was more than that in the southern assemblage.Environmental heterogeneity played an important role in determining the distributions of fish species that formed significant species pairs,which might affect the co-occurrence patterns of northern and southern assemblages further in the Haizhou Bay.展开更多
This study was undertaken to examine which factors contributed to the correction of crowding in two patients who underwent nonextraction orthodontic treatment. A study model analysis was conducted to determine the eff...This study was undertaken to examine which factors contributed to the correction of crowding in two patients who underwent nonextraction orthodontic treatment. A study model analysis was conducted to determine the effects of the orthodontic treatment for crowding with high canines on crown angulation and dental arch width in two patients. The results showed that the crown angulation was significantly increased, indicating distal tipping in the maxillary dental arch. This tendency was most commonly observed in the premolars among the lateral teeth. With respect to the dental arch width, the largest change was evident in the first molar and first premolar regions in cases 1 and 2, respectively. On the basis of these results, up-righting of mesially tipped lateral teeth and expansion of narrow dental arches could prove to be the keys to the success of space regaining or correction of high canines and mild crowding.展开更多
The aim of this research was to analyze the PPM of Armenian Premier League using 25 GPS 10 Hz(K-Sport,Montelabbate,Italy),in order to compare data from literature from major European championship.In total 25 matches w...The aim of this research was to analyze the PPM of Armenian Premier League using 25 GPS 10 Hz(K-Sport,Montelabbate,Italy),in order to compare data from literature from major European championship.In total 25 matches were analyzed from one team militant in Armenian Premier League(10 wins,10 loses and 5 draws),33 different players(age 24.3±4.2,height 1.76±4.2 and weight 74±3.5)and in total 270 performances(10.8 for matches).Matches were divided in First Half(T1),Second Half(T2),Second Half Substitution(T2 Sub),Full Match,Full Match Substitution(Full Match Sub)and Total Match(Total)that include all the players detected during a games.Furthermore,all matches were divided even by quarters 0-15,15-30,30-45,45-60,60-75 and 75-90,only players that played all match were included in this analyses,in order to check the performance decreasing during the time.All data were added in an Excel Spreadsheet in order to build a database,to organize and better analyze data,cataloging events for data,results,and role of players.Average data from Armenian Premier League in comparison with literature data from European and Italian Championship show that in every parameter,the Armenian Premier League is under the average.This is obviously related to the non-high level of the Armenian football that is in fact placed at the 106°place of the FIFA ranking(update 7 June 2019).Physical data represent an indicator of performance but also of the qualitative level of the league and of individual players.For this reason,the use of the match analysis can be decisive to verify the PPM,in order to better evaluate the championships,teams,and players,in order to build an easier search and discovery of talents.展开更多
Fundamental studies of the combustion characteristics and the de HCl behavior of a single refuse derived fuel(RDF) pellet were carried out to explain the de HCl phenomena of RDF during fluidized bed combustion and to ...Fundamental studies of the combustion characteristics and the de HCl behavior of a single refuse derived fuel(RDF) pellet were carried out to explain the de HCl phenomena of RDF during fluidized bed combustion and to provide data for the development of high efficiency power generation technology using RDF previously. For further interpreting the devolatilization and the char combustion processes of RDF quantitatively, an unsteady combustion model for single RDF pellet, involving reaction rates, heat transfer and oxygen diffusion in the RDF pellet, was developed. Comparisons of simulation results with experimental data for mass loss of the RDF samples made from municipal solid waste, wood chips and poly propylene when they were heated at 10K/min or put into the furnace under 1?073?K show the verifiability of the model. Using this model, the distributions of the temperature and the reaction ratio along the radius of RDF pellet during the devolatilization process and the char combustion process were presented, and discussion about the inference of heating rate on the combustion characteristics were performed.展开更多
Objective: To study the evaluation value of three-dimensional finite element model analysis for bone mineral density (BMD) and bone metabolism activity in patients with osteoporosis. Methods: A total of 218 patients w...Objective: To study the evaluation value of three-dimensional finite element model analysis for bone mineral density (BMD) and bone metabolism activity in patients with osteoporosis. Methods: A total of 218 patients who were diagnosed with osteoporosis in the hospital between February 2014 and January 2017 were collected as observation group, and 100 healthy volunteers who received physical examination in the hospital during the same period were selected as normal control group. The femoral head of the two groups was analyzed by three-dimensional finite element model, and the femoral head BMD levels and serum bone metabolism index contents were measured. Pearson test was used to evaluate the evaluation value of femoral head three-dimensional finite element model for osteoporosis. Results: The cancellous bone and cortical bone Von Mises stress value of observation group were lower than those of normal control group, and femoral neck BMD value of observation group was lower than that of normal control group;serum bone metabolism index BGP content was lower than that of normal control group while NBAP, TRACP-5b and CTX-1 contents were higher than those of normal control group. Pearson test showed that the cancellous bone and cortical bone Von Mises stress value of patients with osteoporosis were directly correlated with BMD value and bone metabolism index contents. Conclusion: The three-dimensional finite element model analysis resultsof patients with osteoporosis can objectively reflect the femoral headBMD value and bone metabolism activity, and is a reliable way to evaluate the risk of long-term fractures.展开更多
The biogeochemical dynamics of carbon in the ocean is a subject of fundamental interest to environmental studies. In this context, we have implemented a ten year run of the Brazilian Earth System Coupled Ocean-Atmosph...The biogeochemical dynamics of carbon in the ocean is a subject of fundamental interest to environmental studies. In this context, we have implemented a ten year run of the Brazilian Earth System Coupled Ocean-Atmosphere Model (BESM-OA2.3) integrated with TOPAZ biogeochemical model for the Atlantic basin. The modeled ΔpCO2 for the tropical Atlantic shows very clearly a high dominance of positive fluxes, that is, the CO2 fluxes are sea-to-air throughout the tropical region and for both winter and summer periods. In the mid-latitudes regions negatives fluxes (air-to-sea) were observed for both seasons. An exception to this pattern is an extensive negative tongue on the latitude 10N. The occurrence of this negative ΔpCO2 tongue region in the Tropical Atlantic is highly correlated to negative Evaporation-Precipitation values during this season. In the northern hemisphere (NH) summer the negative values of ΔpCO2 in the tropical Atlantic region are concentrated in the adjacent zone of the Amazon river mouth due to the North Equatorial Counter Current intensification. This process favors the formation of a carbon sink in the adjacent region of the Amazon river mouth. Model results show lowest values of dissolved inorganic carbon (DIC) in a surface layer (100 - 150 m). Highest DIC values are observed in deeper layers and concentrated in an equatorial band. The chlorophyll bloom in equatorial zones was well represented by the model. These blooms are the result of equatorial upwelling that brings the high concentration tongues of DIC present in the equatorial band towards the euphotic zone. This is the first published paper about the BESM-OA2.3 integrated with TOPAZ. The presented results suggest that this modeling system is able to reproduce the main regional carbon dynamics features of the mid-latitude/tropical Atlantic.展开更多
Detecting geomagnetic anomalies preceding earthquakes is a challenging yet promising area of research that has gained increasing attention in recent years.This study introduces a novel reconstruction-based modeling ap...Detecting geomagnetic anomalies preceding earthquakes is a challenging yet promising area of research that has gained increasing attention in recent years.This study introduces a novel reconstruction-based modeling approach enhanced by negative learning,employing a Bidirectional Long Short-Term Memory(BiLSTM)network explicitly trained to accurately reconstruct non-seismic geomagnetic signals while intentionally amplifying reconstruction errors for seismic signals.By penalizing the model for accurately reconstructing seismic anomalies,the negative learning approach effectively magnifies the differences between normal and anomalous data.This strategic differentiation enhances the sensitivity of the BiLSTM network,enabling improved detection of subtle geomagnetic anomalies that may serve as earthquake precursors.Experimental validation clearly demonstrated statistically significant higher reconstruction errors for seismic signals compared to non-seismic signals,confirmed through the Mann-Whitney U test with a p-value of 0.0035 for Root Mean Square Error(RMSE).These results provide compelling evidence of the enhanced anomaly detection capability achieved through negative learning.Unlike traditional classification-based methods,negative learning explicitly encourages sensitivity to subtle precursor signals embedded within complex geomagnetic data,establishing a robust basis for further development of reliable earthquake prediction methods.展开更多
Children are the flowers of the motherland, their physical and mental development and education by today's society attaches great importance to. In the stage of preschool education for children, fine arts is a sub...Children are the flowers of the motherland, their physical and mental development and education by today's society attaches great importance to. In the stage of preschool education for children, fine arts is a subject that stimulates children's imagination and creativity, and plays an important role in stimulating their intelligence and thinking. This paper briefly introduces the status quo of art teaching in preschool education, and expounds the importance and strategy of encouraging children to exert their imagination and creativity in art teaching.展开更多
In the field of natural language processing,the rapid development of large language model(LLM)has attracted increasing attention.LLMs have shown a high level of creativity in various tasks,but the methods for assessin...In the field of natural language processing,the rapid development of large language model(LLM)has attracted increasing attention.LLMs have shown a high level of creativity in various tasks,but the methods for assessing such creativity are inadequate.Assessment of LLM creativity needs to consider differences from humans,requiring multiple dimensional measurement while balancing accuracy and efficiency.This paper aims to establish an efficient framework for assessing the level of creativity in LLMs.By adapting the modified Torrance tests of creative thinking,the research evaluates the creative performance of various LLMs across 7 tasks,emphasizing 4 criteria including fluency,flexibility,originality,and elaboration.In this context,we develop a comprehensive dataset of 700 questions for testing and an LLM-based evaluation method.In addition,this study presents a novel analysis of LLMs'responses to diverse prompts and role-play situations.We found that the creativity of LLMs primarily falls short in originality,while excelling in elaboration.In addition,the use of prompts and role-play settings of the model significantly influence creativity.Additionally,the experimental results also indicate that collaboration among multiple LLMs can enhance originality.Notably,our findings reveal a consensus between human evaluations and LLMs regarding the personality traits that influence creativity.The findings underscore the significant impact of LLM design on creativity and bridge artificial intelligence and human creativity,offering insights into LLMs'creativity and potential applications.展开更多
We analyzed accident factors in a 2020 ship collision case that occurred off Kii Oshima Island using the SHELL model analysis and examined corresponding collision prevention measures.The SHELL model analysis is a fram...We analyzed accident factors in a 2020 ship collision case that occurred off Kii Oshima Island using the SHELL model analysis and examined corresponding collision prevention measures.The SHELL model analysis is a framework for identifying accident factors related to human abilities and characteristics,hardware,software,and the environment.Beyond assessing the accident factors in each element,we also examined the interrelationship between humans and each element.This study highlights the importance of(1)training to enhance situational awareness,(2)improving decision-making skills,and(3)establishing structured decision-making procedures to prevent maritime collision accidents.Additionally,we considered safety measures through(4)hardware enhancements and(5)environmental measures.Furthermore,to prevent accidents,implementing measures grounded in(6)predictions is deemed effective.This study identified accident factors through prediction alongside the SHELL model analysis and proposed countermeasures based on the findings.By applying these predictions,more countermeasures can be derived,which,when combined strategically,can significantly aid in preventing maritime collision accidents.展开更多
Anti-jamming performance evaluation has recently received significant attention. For Link-16, the anti-jamming performance evaluation and selection of the optimal anti-jamming technologies are urgent problems to be so...Anti-jamming performance evaluation has recently received significant attention. For Link-16, the anti-jamming performance evaluation and selection of the optimal anti-jamming technologies are urgent problems to be solved. A comprehensive evaluation method is proposed, which combines grey relational analysis (GRA) and cloud model, to evaluate the anti-jamming performances of Link-16. Firstly, on the basis of establishing the anti-jamming performance evaluation indicator system of Link-16, the linear combination of analytic hierarchy process(AHP) and entropy weight method (EWM) are used to calculate the combined weight. Secondly, the qualitative and quantitative concept transformation model, i.e., the cloud model, is introduced to evaluate the anti-jamming abilities of Link-16 under each jamming scheme. In addition, GRA calculates the correlation degree between evaluation indicators and the anti-jamming performance of Link-16, and assesses the best anti-jamming technology. Finally, simulation results prove that the proposed evaluation model can achieve the objective of feasible and practical evaluation, which opens up a novel way for the research of anti-jamming performance evaluations of Link-16.展开更多
Shotcrete is one of the common solutions for shallow sliding.It works by forming a protective layer with high strength and cementing the loose soil particles on the slope surface to prevent shallow sliding.However,the...Shotcrete is one of the common solutions for shallow sliding.It works by forming a protective layer with high strength and cementing the loose soil particles on the slope surface to prevent shallow sliding.However,the solidification time of conventional cement paste is long when shotcrete is used to treat cohesionless soil landslide.The idea of reinforcing slope with polyurethane solidified soil(i.e.,mixture of polyurethane and sand)was proposed.Model tests and finite element analysis were carried out to study the effectiveness of the proposed new method on the emergency treatment of cohesionless soil landslide.Surcharge loading on the crest of the slope was applied step by step until landslide was triggered so as to test and compare the stability and bearing capacity of slope models with different conditions.The simulated slope displacements were relatively close to the measured results,and the simulated slope deformation characteristics were in good agreement with the observed phenomena,which verifies the accuracy of the numerical method.Under the condition of surcharge loading on the crest of the slope,the unreinforced slope slid when the surcharge loading exceeded 30 k Pa,which presented a failure mode of local instability and collapse at the shallow layer of slope top.The reinforced slope remained stable even when the surcharge loading reached 48 k Pa.The displacement of the reinforced slope was reduced by more than 95%.Overall,this study verifies the effectiveness of polyurethane in the emergency treatment of cohesionless soil landslide and should have broad application prospects in the field of geological disasters concerning the safety of people's live.展开更多
Large-scale Language Models(LLMs)have achieved significant breakthroughs in Natural Language Processing(NLP),driven by the pre-training and fine-tuning paradigm.While this approach allows models to specialize in speci...Large-scale Language Models(LLMs)have achieved significant breakthroughs in Natural Language Processing(NLP),driven by the pre-training and fine-tuning paradigm.While this approach allows models to specialize in specific tasks with reduced training costs,the substantial memory requirements during fine-tuning present a barrier to broader deployment.Parameter-Efficient Fine-Tuning(PEFT)techniques,such as Low-Rank Adaptation(LoRA),and parameter quantization methods have emerged as solutions to address these challenges by optimizing memory usage and computational efficiency.Among these,QLoRA,which combines PEFT and quantization,has demonstrated notable success in reducing memory footprints during fine-tuning,prompting the development of various QLoRA variants.Despite these advancements,the quantitative impact of key variables on the fine-tuning performance of quantized LLMs remains underexplored.This study presents a comprehensive analysis of these key variables,focusing on their influence across different layer types and depths within LLM architectures.Our investigation uncovers several critical findings:(1)Larger layers,such as MLP layers,can maintain performance despite reductions in adapter rank,while smaller layers,like self-attention layers,aremore sensitive to such changes;(2)The effectiveness of balancing factors depends more on specific values rather than layer type or depth;(3)In quantization-aware fine-tuning,larger layers can effectively utilize smaller adapters,whereas smaller layers struggle to do so.These insights suggest that layer type is a more significant determinant of fine-tuning success than layer depth when optimizing quantized LLMs.Moreover,for the same discount of trainable parameters,reducing the trainable parameters in a larger layer is more effective in preserving fine-tuning accuracy than in a smaller one.This study provides valuable guidance for more efficient fine-tuning strategies and opens avenues for further research into optimizing LLM fine-tuning in resource-constrained environments.展开更多
DNA microarray technology is an extremely effective technique for studying gene expression patterns in cells, and the main challenge currently faced by this technology is how to analyze the large amount of gene expres...DNA microarray technology is an extremely effective technique for studying gene expression patterns in cells, and the main challenge currently faced by this technology is how to analyze the large amount of gene expression data generated. To address this, this paper employs a mixed-effects model to analyze gene expression data. In terms of data selection, 1176 genes from the white mouse gene expression dataset under two experimental conditions were chosen, setting up two conditions: pneumococcal infection and no infection, and constructing a mixed-effects model. After preprocessing the gene chip information, the data were imported into the model, preliminary results were calculated, and permutation tests were performed to biologically validate the preliminary results using GSEA. The final dataset consists of 20 groups of gene expression data from pneumococcal infection, which categorizes functionally related genes based on the similarity of their expression profiles, facilitating the study of genes with unknown functions.展开更多
With the rapid development of generative artificial intelligence technologies,represented by large language models,university-level computer science education is undergoing a critical transition-from knowledge-based i...With the rapid development of generative artificial intelligence technologies,represented by large language models,university-level computer science education is undergoing a critical transition-from knowledge-based instruction to competency-oriented teaching.A postgraduate student competency evaluation model can serve as a framework to organize and guide both teaching and research activities at the postgraduate level.A number of relevant research efforts have already been conducted in this area.Graduate education plays a vital role not only as a continuation and enhancement of undergraduate education but also as essential preparation for future research endeavors.An analysis of the acceptance of competency evaluation models refers to the assessment of how various stakeholders perceive the importance of different components within the model.Investigating the degree of acceptance among diverse groups-such as current undergraduate students,current postgraduate students,graduates with less than three years of work experience,and those with more than three years of work experience-can offer valuable insights for improving and optimizing postgraduate education and training practices.展开更多
The dynamic,heterogeneous nature of Edge computing in the Internet of Things(Edge-IoT)and Industrial IoT(IIoT)networks brings unique and evolving cybersecurity challenges.This study maps cyber threats in Edge-IoT/IIoT...The dynamic,heterogeneous nature of Edge computing in the Internet of Things(Edge-IoT)and Industrial IoT(IIoT)networks brings unique and evolving cybersecurity challenges.This study maps cyber threats in Edge-IoT/IIoT environments to the Adversarial Tactics,Techniques,and Common Knowledge(ATT&CK)framework by MITRE and introduces a lightweight,data-driven scoring model that enables rapid identification and prioritization of attacks.Inspired by the Factor Analysis of Information Risk model,our proposed scoring model integrates four key metrics:Common Vulnerability Scoring System(CVSS)-based severity scoring,Cyber Kill Chain–based difficulty estimation,Deep Neural Networks-driven detection scoring,and frequency analysis based on dataset prevalence.By aggregating these indicators,the model generates comprehensive risk profiles,facilitating actionable prioritization of threats.Robustness and stability of the scoring model are validated through non-parametric correlation analysis using Spearman’s and Kendall’s rank correlation coefficients,demonstrating consistent performance across diverse scenarios.The approach culminates in a prioritized attack ranking that provides actionable guidance for risk mitigation and resource allocation in Edge-IoT/IIoT security operations.By leveraging real-world data to align MITRE ATT&CK techniques with CVSS metrics,the framework offers a standardized and practically applicable solution for consistent threat assessment in operational settings.The proposed lightweight scoring model delivers rapid and reliable results under dynamic cyber conditions,facilitating timely identification of attack scenarios and prioritization of response strategies.Our systematic integration of established taxonomies with data-driven indicators strengthens practical risk management and supports strategic planning in next-generation IoT deployments.Ultimately,this work advances adaptive threat modeling for Edge/IIoT ecosystems and establishes a robust foundation for evidence-based prioritization in emerging cyber-physical infrastructures.展开更多
Background:With the rapid development of artificial intelligence(AI),large language models(LLMs)have emerged as a potent tool for invigorating ophthalmology across clinical,educational,and research fields.Their accura...Background:With the rapid development of artificial intelligence(AI),large language models(LLMs)have emerged as a potent tool for invigorating ophthalmology across clinical,educational,and research fields.Their accuracy and reliability have undergone tested.This bibliometric analysis aims to provide an overview of research on LLMs in ophthalmology from both thematic and geographical perspectives.Methods:All existing and highly cited LLM-related ophthalmology research papers published in English up to 24th April 2025 were sourced from Scopus,PubMed,and Web of Science.The characteristics of these publications,including publication output,authors,journals,countries,institutions,citations,and research domains,were analyzed using Biblioshiny and VOSviewer software.Results:A total of 277 articles from 1,459 authors and 89 journals were included in this study.Although relevant publications began to appear in 2019,there was a significant increase starting from 2023.He M and Shi D are the most prolific authors,while Investigative Ophthalmology&Visual Science stands out as the most prominent journal.Most of the top-publishing countries are high-income economies,with the USA taking the lead,and the University of California is the leading institution.VOSviewer identified 5 clusters in the keyword co-occurrence analysis,indicating that current research focuses on the clinical applications of LLMs,particularly in diagnosis and patient education.Conclusions:While LLMs have demonstrated effectiveness in retaining knowledge,their accuracy in image-based diagnosis remains limited.Therefore,future research should investigate fine-tuning strategies and domain-specific adaptations to close this gap.Although research on the applications of LLMs in ophthalmology is still in its early stages,it holds significant potential for advancing the field.展开更多
基金Supported by 2022 Chinese Medicine Scientific Research Project of Hebei Administration of Traditional Chinese Medicine,No.20221572025 Annual Scientific Research Project of Higher Education Institutions in Hebei Province,No.QN2025654.
文摘BACKGROUND Neck pain,a primary symptom of cervical spondylosis,affects patients'physical and mental health,reducing their quality of life.Pain and emotional state interact;however,their longitudinal interrelationship remains unclear.In this study,we applied a dual-trajectory model to assess how neck pain and emotional state evolve together over time and how clinical interventions,particularly acupuncture,influence these trajectories.AIM To investigate the longitudinal relationship between neck pain and emotional state in patients with cervical spondylosis.METHODS This prospective cohort study included 472 patients with cervical spondylosis from eight Chinese hospitals.Participants received acupuncture or medication and were followed up at baseline,and at 1,2,4,6,and 8 weeks.Neck pain and emotional distress were assessed using the Northwick Park Neck Pain Questionnaire(NPQ)and the affective subscale of the Short-Form McGill Pain Questionnaire(SF-MPQ),respectively.Group-based trajectory models and dual trajectory analysis were used to identify and correlate pain-emotion trajectories.Multivariate logistic regression identified predictors of group membership.RESULTS Three trajectory groups were identified for NPQ and SF-MPQ scores(low,medium,and high).Higher NPQ trajectory was associated with older age(OR=1.058,P<0.001)and was significantly reduced by acupuncture(OR=0.382,P<0.001).Similarly,acupuncture lowered the odds of high SF-MPQ trajectory membership(OR=0.336,P<0.001),while age increased it(OR=1.037,P<0.001).Dual-trajectory analysis revealed bidirectional associations:69.1%of patients with low NPQ had low SF-MPQ scores,and 42.6%of patients with high SF-MPQ also had high NPQ scores.Gender was a predictor for medium SF-MPQ trajectory(OR=1.629,P=0.094).Occupation and education levels differed significantly across the trajectory groups(P<0.05).CONCLUSION Over time,neck pain and emotional distress are closely associated in patients with cervical spondylosis.Acupuncture alleviates both outcomes significantly,while age is a risk factor.Integrated approaches to pain and emotional management are encouraged.
基金Acknowledgement The authors thank the financial support from the National Natural Science Foundation of China （Grant No. 50705043, 60535020 and 60910007）.
文摘Ionic Polymer-Metal Composite （IPMC） is a new electro-active polymer, which has the advantages of light weight, flexibility, and large stroke with low driving voltage. Because of these features, IPMC can be applied to bionic robotic actuators, artificial muscles, as well as dynamic sensors. However, IPMC has the major drawback of low generative blocking force. In this paper, in order to enhance the blocking force, the Nation membranes with thickness of 0.22 mm, 0.32 mm, 0.42 mm, 0.64 mm and 0.8 mm were prepared by casting from liquid solution. By employing these Nation membranes, IPMCs with varying thickness were fabricated by electroless plating. The elastic modulus of the casted Nation membranes were obtained by a nano-indenter, and the current, the displacement and the blocking force were respectively measured by the apparatus for actuation test. Finally, the effects of the thickness on the performance of IPMC were analyzed with an electromechanical model. Experimental study and theory analysis indicate that as the thickness increases, the elastic modulus of Nation membrane and the blocking force of IPMC increase, however, the current and the displacement decrease.
基金Supported by National Natural Science Foundation of China (Grant Nos.51375496,51205409)
文摘Computer-based conceptual design for routine design has made great strides, yet non-routine design has not been given due attention, and it is still poorly automated. Considering that the function-behavior-structure（FBS） model is widely used for modeling the conceptual design process, a computer-based creativity enhanced conceptual design model（CECD） for non-routine design of mechanical systems is presented. In the model, the leaf functions in the FBS model are decomposed into and represented with fine-grain basic operation actions（BOA）, and the corresponding BOA set in the function domain is then constructed. Choosing building blocks from the database, and expressing their multiple functions with BOAs, the BOA set in the structure domain is formed. Through rule-based dynamic partition of the BOA set in the function domain, many variants of regenerated functional schemes are generated. For enhancing the capability to introduce new design variables into the conceptual design process, and dig out more innovative physical structure schemes, the indirect function-structure matching strategy based on reconstructing the combined structure schemes is adopted. By adjusting the tightness of the partition rules and the granularity of the divided BOA subsets, and making full use of the main function and secondary functions of each basic structure in the process of reconstructing of the physical structures, new design variables and variants are introduced into the physical structure scheme reconstructing process, and a great number of simpler physical structure schemes to accomplish the overall function organically are figured out. The creativity enhanced conceptual design model presented has a dominant capability in introducing new deign variables in function domain and digging out simpler physical structures to accomplish the overall function, therefore it can be utilized to solve non-routine conceptual design problem.
基金funded by the National Natural Science Foundation of China (No. 31772852)the Fundamental Research Funds for the Central Universities (Nos. 2015 62030, 201612004)the Public Science and Technology Research Funds Projects of Ocean (No. 201305030)
文摘Co-occurrence pattern of fish species plays an important role in understanding the spatio-temporal structure and the stability of fish community.Species coexistence may vary with time and space.The co-occurrence patterns of fish species were examined using the C-score under fixed-fixed null model for fish communities in spring and autumn over different years in the Haizhou Bay,China.The results showed that fish assemblages in the whole bay had non-random patterns in spring and autumn over different years.However,the fish co-occurrence patterns were different for the northern and southern fish assemblages in spring and autumn.The northern fish assemblage showed structured pattern,whereas the southern assemblage were randomly assembled in spring.The co-occurrence patterns of fish communities were relatively stable over different years,and the number of significant species pairs in northern assemblage was more than that in the southern assemblage.Environmental heterogeneity played an important role in determining the distributions of fish species that formed significant species pairs,which might affect the co-occurrence patterns of northern and southern assemblages further in the Haizhou Bay.
文摘This study was undertaken to examine which factors contributed to the correction of crowding in two patients who underwent nonextraction orthodontic treatment. A study model analysis was conducted to determine the effects of the orthodontic treatment for crowding with high canines on crown angulation and dental arch width in two patients. The results showed that the crown angulation was significantly increased, indicating distal tipping in the maxillary dental arch. This tendency was most commonly observed in the premolars among the lateral teeth. With respect to the dental arch width, the largest change was evident in the first molar and first premolar regions in cases 1 and 2, respectively. On the basis of these results, up-righting of mesially tipped lateral teeth and expansion of narrow dental arches could prove to be the keys to the success of space regaining or correction of high canines and mild crowding.
文摘The aim of this research was to analyze the PPM of Armenian Premier League using 25 GPS 10 Hz(K-Sport,Montelabbate,Italy),in order to compare data from literature from major European championship.In total 25 matches were analyzed from one team militant in Armenian Premier League(10 wins,10 loses and 5 draws),33 different players(age 24.3±4.2,height 1.76±4.2 and weight 74±3.5)and in total 270 performances(10.8 for matches).Matches were divided in First Half(T1),Second Half(T2),Second Half Substitution(T2 Sub),Full Match,Full Match Substitution(Full Match Sub)and Total Match(Total)that include all the players detected during a games.Furthermore,all matches were divided even by quarters 0-15,15-30,30-45,45-60,60-75 and 75-90,only players that played all match were included in this analyses,in order to check the performance decreasing during the time.All data were added in an Excel Spreadsheet in order to build a database,to organize and better analyze data,cataloging events for data,results,and role of players.Average data from Armenian Premier League in comparison with literature data from European and Italian Championship show that in every parameter,the Armenian Premier League is under the average.This is obviously related to the non-high level of the Armenian football that is in fact placed at the 106°place of the FIFA ranking(update 7 June 2019).Physical data represent an indicator of performance but also of the qualitative level of the league and of individual players.For this reason,the use of the match analysis can be decisive to verify the PPM,in order to better evaluate the championships,teams,and players,in order to build an easier search and discovery of talents.
文摘Fundamental studies of the combustion characteristics and the de HCl behavior of a single refuse derived fuel(RDF) pellet were carried out to explain the de HCl phenomena of RDF during fluidized bed combustion and to provide data for the development of high efficiency power generation technology using RDF previously. For further interpreting the devolatilization and the char combustion processes of RDF quantitatively, an unsteady combustion model for single RDF pellet, involving reaction rates, heat transfer and oxygen diffusion in the RDF pellet, was developed. Comparisons of simulation results with experimental data for mass loss of the RDF samples made from municipal solid waste, wood chips and poly propylene when they were heated at 10K/min or put into the furnace under 1?073?K show the verifiability of the model. Using this model, the distributions of the temperature and the reaction ratio along the radius of RDF pellet during the devolatilization process and the char combustion process were presented, and discussion about the inference of heating rate on the combustion characteristics were performed.
基金National Science Foundation of China No:81301292.
文摘Objective: To study the evaluation value of three-dimensional finite element model analysis for bone mineral density (BMD) and bone metabolism activity in patients with osteoporosis. Methods: A total of 218 patients who were diagnosed with osteoporosis in the hospital between February 2014 and January 2017 were collected as observation group, and 100 healthy volunteers who received physical examination in the hospital during the same period were selected as normal control group. The femoral head of the two groups was analyzed by three-dimensional finite element model, and the femoral head BMD levels and serum bone metabolism index contents were measured. Pearson test was used to evaluate the evaluation value of femoral head three-dimensional finite element model for osteoporosis. Results: The cancellous bone and cortical bone Von Mises stress value of observation group were lower than those of normal control group, and femoral neck BMD value of observation group was lower than that of normal control group;serum bone metabolism index BGP content was lower than that of normal control group while NBAP, TRACP-5b and CTX-1 contents were higher than those of normal control group. Pearson test showed that the cancellous bone and cortical bone Von Mises stress value of patients with osteoporosis were directly correlated with BMD value and bone metabolism index contents. Conclusion: The three-dimensional finite element model analysis resultsof patients with osteoporosis can objectively reflect the femoral headBMD value and bone metabolism activity, and is a reliable way to evaluate the risk of long-term fractures.
基金partly funded by Rede Brasileira de Pesquisas sobre Mudancas Climaticas Globais(Rede CLIMA)through a National Council for Scientific and Technological Development(CNPq)postdoctoral fellowship for the first author at CPTEC/INPE
文摘The biogeochemical dynamics of carbon in the ocean is a subject of fundamental interest to environmental studies. In this context, we have implemented a ten year run of the Brazilian Earth System Coupled Ocean-Atmosphere Model (BESM-OA2.3) integrated with TOPAZ biogeochemical model for the Atlantic basin. The modeled ΔpCO2 for the tropical Atlantic shows very clearly a high dominance of positive fluxes, that is, the CO2 fluxes are sea-to-air throughout the tropical region and for both winter and summer periods. In the mid-latitudes regions negatives fluxes (air-to-sea) were observed for both seasons. An exception to this pattern is an extensive negative tongue on the latitude 10N. The occurrence of this negative ΔpCO2 tongue region in the Tropical Atlantic is highly correlated to negative Evaporation-Precipitation values during this season. In the northern hemisphere (NH) summer the negative values of ΔpCO2 in the tropical Atlantic region are concentrated in the adjacent zone of the Amazon river mouth due to the North Equatorial Counter Current intensification. This process favors the formation of a carbon sink in the adjacent region of the Amazon river mouth. Model results show lowest values of dissolved inorganic carbon (DIC) in a surface layer (100 - 150 m). Highest DIC values are observed in deeper layers and concentrated in an equatorial band. The chlorophyll bloom in equatorial zones was well represented by the model. These blooms are the result of equatorial upwelling that brings the high concentration tongues of DIC present in the equatorial band towards the euphotic zone. This is the first published paper about the BESM-OA2.3 integrated with TOPAZ. The presented results suggest that this modeling system is able to reproduce the main regional carbon dynamics features of the mid-latitude/tropical Atlantic.
基金funded by the Ministry of Higher Education through Universiti Putra Malaysia(UPM)under Grant FRGS/1/2023/STG07/UPM/02/4.
文摘Detecting geomagnetic anomalies preceding earthquakes is a challenging yet promising area of research that has gained increasing attention in recent years.This study introduces a novel reconstruction-based modeling approach enhanced by negative learning,employing a Bidirectional Long Short-Term Memory(BiLSTM)network explicitly trained to accurately reconstruct non-seismic geomagnetic signals while intentionally amplifying reconstruction errors for seismic signals.By penalizing the model for accurately reconstructing seismic anomalies,the negative learning approach effectively magnifies the differences between normal and anomalous data.This strategic differentiation enhances the sensitivity of the BiLSTM network,enabling improved detection of subtle geomagnetic anomalies that may serve as earthquake precursors.Experimental validation clearly demonstrated statistically significant higher reconstruction errors for seismic signals compared to non-seismic signals,confirmed through the Mann-Whitney U test with a p-value of 0.0035 for Root Mean Square Error(RMSE).These results provide compelling evidence of the enhanced anomaly detection capability achieved through negative learning.Unlike traditional classification-based methods,negative learning explicitly encourages sensitivity to subtle precursor signals embedded within complex geomagnetic data,establishing a robust basis for further development of reliable earthquake prediction methods.
文摘Children are the flowers of the motherland, their physical and mental development and education by today's society attaches great importance to. In the stage of preschool education for children, fine arts is a subject that stimulates children's imagination and creativity, and plays an important role in stimulating their intelligence and thinking. This paper briefly introduces the status quo of art teaching in preschool education, and expounds the importance and strategy of encouraging children to exert their imagination and creativity in art teaching.
基金partially supported by the National Natural Science Foundation of China(Nos.U22A2028,61925208,62102399,62302478,62302483,62222214,62372436,62302482 and 62302480)CAS Project for Young Scientists in Basic Research,China(No.YSBR-029)Youth Innovation Promotion Association CAS and Xplore Prize,China.
文摘In the field of natural language processing,the rapid development of large language model(LLM)has attracted increasing attention.LLMs have shown a high level of creativity in various tasks,but the methods for assessing such creativity are inadequate.Assessment of LLM creativity needs to consider differences from humans,requiring multiple dimensional measurement while balancing accuracy and efficiency.This paper aims to establish an efficient framework for assessing the level of creativity in LLMs.By adapting the modified Torrance tests of creative thinking,the research evaluates the creative performance of various LLMs across 7 tasks,emphasizing 4 criteria including fluency,flexibility,originality,and elaboration.In this context,we develop a comprehensive dataset of 700 questions for testing and an LLM-based evaluation method.In addition,this study presents a novel analysis of LLMs'responses to diverse prompts and role-play situations.We found that the creativity of LLMs primarily falls short in originality,while excelling in elaboration.In addition,the use of prompts and role-play settings of the model significantly influence creativity.Additionally,the experimental results also indicate that collaboration among multiple LLMs can enhance originality.Notably,our findings reveal a consensus between human evaluations and LLMs regarding the personality traits that influence creativity.The findings underscore the significant impact of LLM design on creativity and bridge artificial intelligence and human creativity,offering insights into LLMs'creativity and potential applications.
文摘We analyzed accident factors in a 2020 ship collision case that occurred off Kii Oshima Island using the SHELL model analysis and examined corresponding collision prevention measures.The SHELL model analysis is a framework for identifying accident factors related to human abilities and characteristics,hardware,software,and the environment.Beyond assessing the accident factors in each element,we also examined the interrelationship between humans and each element.This study highlights the importance of(1)training to enhance situational awareness,(2)improving decision-making skills,and(3)establishing structured decision-making procedures to prevent maritime collision accidents.Additionally,we considered safety measures through(4)hardware enhancements and(5)environmental measures.Furthermore,to prevent accidents,implementing measures grounded in(6)predictions is deemed effective.This study identified accident factors through prediction alongside the SHELL model analysis and proposed countermeasures based on the findings.By applying these predictions,more countermeasures can be derived,which,when combined strategically,can significantly aid in preventing maritime collision accidents.
基金Heilongjiang Provincial Natural Science Foundation of China (LH2021F009)。
文摘Anti-jamming performance evaluation has recently received significant attention. For Link-16, the anti-jamming performance evaluation and selection of the optimal anti-jamming technologies are urgent problems to be solved. A comprehensive evaluation method is proposed, which combines grey relational analysis (GRA) and cloud model, to evaluate the anti-jamming performances of Link-16. Firstly, on the basis of establishing the anti-jamming performance evaluation indicator system of Link-16, the linear combination of analytic hierarchy process(AHP) and entropy weight method (EWM) are used to calculate the combined weight. Secondly, the qualitative and quantitative concept transformation model, i.e., the cloud model, is introduced to evaluate the anti-jamming abilities of Link-16 under each jamming scheme. In addition, GRA calculates the correlation degree between evaluation indicators and the anti-jamming performance of Link-16, and assesses the best anti-jamming technology. Finally, simulation results prove that the proposed evaluation model can achieve the objective of feasible and practical evaluation, which opens up a novel way for the research of anti-jamming performance evaluations of Link-16.
基金the financial support from the Fujian Science Foundation for Outstanding Youth(2023J06039)the National Natural Science Foundation of China(Grant No.41977259,U2005205,41972268)the Independent Research Project of Technology Innovation Center for Monitoring and Restoration Engineering of Ecological Fragile Zone in Southeast China(KY-090000-04-2022-019)。
文摘Shotcrete is one of the common solutions for shallow sliding.It works by forming a protective layer with high strength and cementing the loose soil particles on the slope surface to prevent shallow sliding.However,the solidification time of conventional cement paste is long when shotcrete is used to treat cohesionless soil landslide.The idea of reinforcing slope with polyurethane solidified soil(i.e.,mixture of polyurethane and sand)was proposed.Model tests and finite element analysis were carried out to study the effectiveness of the proposed new method on the emergency treatment of cohesionless soil landslide.Surcharge loading on the crest of the slope was applied step by step until landslide was triggered so as to test and compare the stability and bearing capacity of slope models with different conditions.The simulated slope displacements were relatively close to the measured results,and the simulated slope deformation characteristics were in good agreement with the observed phenomena,which verifies the accuracy of the numerical method.Under the condition of surcharge loading on the crest of the slope,the unreinforced slope slid when the surcharge loading exceeded 30 k Pa,which presented a failure mode of local instability and collapse at the shallow layer of slope top.The reinforced slope remained stable even when the surcharge loading reached 48 k Pa.The displacement of the reinforced slope was reduced by more than 95%.Overall,this study verifies the effectiveness of polyurethane in the emergency treatment of cohesionless soil landslide and should have broad application prospects in the field of geological disasters concerning the safety of people's live.
基金supported by the National Key R&D Program of China(No.2021YFB0301200)National Natural Science Foundation of China(No.62025208).
文摘Large-scale Language Models(LLMs)have achieved significant breakthroughs in Natural Language Processing(NLP),driven by the pre-training and fine-tuning paradigm.While this approach allows models to specialize in specific tasks with reduced training costs,the substantial memory requirements during fine-tuning present a barrier to broader deployment.Parameter-Efficient Fine-Tuning(PEFT)techniques,such as Low-Rank Adaptation(LoRA),and parameter quantization methods have emerged as solutions to address these challenges by optimizing memory usage and computational efficiency.Among these,QLoRA,which combines PEFT and quantization,has demonstrated notable success in reducing memory footprints during fine-tuning,prompting the development of various QLoRA variants.Despite these advancements,the quantitative impact of key variables on the fine-tuning performance of quantized LLMs remains underexplored.This study presents a comprehensive analysis of these key variables,focusing on their influence across different layer types and depths within LLM architectures.Our investigation uncovers several critical findings:(1)Larger layers,such as MLP layers,can maintain performance despite reductions in adapter rank,while smaller layers,like self-attention layers,aremore sensitive to such changes;(2)The effectiveness of balancing factors depends more on specific values rather than layer type or depth;(3)In quantization-aware fine-tuning,larger layers can effectively utilize smaller adapters,whereas smaller layers struggle to do so.These insights suggest that layer type is a more significant determinant of fine-tuning success than layer depth when optimizing quantized LLMs.Moreover,for the same discount of trainable parameters,reducing the trainable parameters in a larger layer is more effective in preserving fine-tuning accuracy than in a smaller one.This study provides valuable guidance for more efficient fine-tuning strategies and opens avenues for further research into optimizing LLM fine-tuning in resource-constrained environments.
文摘DNA microarray technology is an extremely effective technique for studying gene expression patterns in cells, and the main challenge currently faced by this technology is how to analyze the large amount of gene expression data generated. To address this, this paper employs a mixed-effects model to analyze gene expression data. In terms of data selection, 1176 genes from the white mouse gene expression dataset under two experimental conditions were chosen, setting up two conditions: pneumococcal infection and no infection, and constructing a mixed-effects model. After preprocessing the gene chip information, the data were imported into the model, preliminary results were calculated, and permutation tests were performed to biologically validate the preliminary results using GSEA. The final dataset consists of 20 groups of gene expression data from pneumococcal infection, which categorizes functionally related genes based on the similarity of their expression profiles, facilitating the study of genes with unknown functions.
文摘With the rapid development of generative artificial intelligence technologies,represented by large language models,university-level computer science education is undergoing a critical transition-from knowledge-based instruction to competency-oriented teaching.A postgraduate student competency evaluation model can serve as a framework to organize and guide both teaching and research activities at the postgraduate level.A number of relevant research efforts have already been conducted in this area.Graduate education plays a vital role not only as a continuation and enhancement of undergraduate education but also as essential preparation for future research endeavors.An analysis of the acceptance of competency evaluation models refers to the assessment of how various stakeholders perceive the importance of different components within the model.Investigating the degree of acceptance among diverse groups-such as current undergraduate students,current postgraduate students,graduates with less than three years of work experience,and those with more than three years of work experience-can offer valuable insights for improving and optimizing postgraduate education and training practices.
基金supported by the“Regional Innovation System&Education(RISE)”through the Seoul RISE Center,funded by the Ministry of Education(MOE)and the Seoul Metropolitan Government(2025-RISE-01-018-05)supported by Quad Miners Corp。
文摘The dynamic,heterogeneous nature of Edge computing in the Internet of Things(Edge-IoT)and Industrial IoT(IIoT)networks brings unique and evolving cybersecurity challenges.This study maps cyber threats in Edge-IoT/IIoT environments to the Adversarial Tactics,Techniques,and Common Knowledge(ATT&CK)framework by MITRE and introduces a lightweight,data-driven scoring model that enables rapid identification and prioritization of attacks.Inspired by the Factor Analysis of Information Risk model,our proposed scoring model integrates four key metrics:Common Vulnerability Scoring System(CVSS)-based severity scoring,Cyber Kill Chain–based difficulty estimation,Deep Neural Networks-driven detection scoring,and frequency analysis based on dataset prevalence.By aggregating these indicators,the model generates comprehensive risk profiles,facilitating actionable prioritization of threats.Robustness and stability of the scoring model are validated through non-parametric correlation analysis using Spearman’s and Kendall’s rank correlation coefficients,demonstrating consistent performance across diverse scenarios.The approach culminates in a prioritized attack ranking that provides actionable guidance for risk mitigation and resource allocation in Edge-IoT/IIoT security operations.By leveraging real-world data to align MITRE ATT&CK techniques with CVSS metrics,the framework offers a standardized and practically applicable solution for consistent threat assessment in operational settings.The proposed lightweight scoring model delivers rapid and reliable results under dynamic cyber conditions,facilitating timely identification of attack scenarios and prioritization of response strategies.Our systematic integration of established taxonomies with data-driven indicators strengthens practical risk management and supports strategic planning in next-generation IoT deployments.Ultimately,this work advances adaptive threat modeling for Edge/IIoT ecosystems and establishes a robust foundation for evidence-based prioritization in emerging cyber-physical infrastructures.
基金supported by Health and Medical Research Fund,Hong Kong(11220386,12230246).
文摘Background:With the rapid development of artificial intelligence(AI),large language models(LLMs)have emerged as a potent tool for invigorating ophthalmology across clinical,educational,and research fields.Their accuracy and reliability have undergone tested.This bibliometric analysis aims to provide an overview of research on LLMs in ophthalmology from both thematic and geographical perspectives.Methods:All existing and highly cited LLM-related ophthalmology research papers published in English up to 24th April 2025 were sourced from Scopus,PubMed,and Web of Science.The characteristics of these publications,including publication output,authors,journals,countries,institutions,citations,and research domains,were analyzed using Biblioshiny and VOSviewer software.Results:A total of 277 articles from 1,459 authors and 89 journals were included in this study.Although relevant publications began to appear in 2019,there was a significant increase starting from 2023.He M and Shi D are the most prolific authors,while Investigative Ophthalmology&Visual Science stands out as the most prominent journal.Most of the top-publishing countries are high-income economies,with the USA taking the lead,and the University of California is the leading institution.VOSviewer identified 5 clusters in the keyword co-occurrence analysis,indicating that current research focuses on the clinical applications of LLMs,particularly in diagnosis and patient education.Conclusions:While LLMs have demonstrated effectiveness in retaining knowledge,their accuracy in image-based diagnosis remains limited.Therefore,future research should investigate fine-tuning strategies and domain-specific adaptations to close this gap.Although research on the applications of LLMs in ophthalmology is still in its early stages,it holds significant potential for advancing the field.
