Objective To investigate methods for constructing a high-quality instructional dataset for traditional Chinese medicine(TCM)mental disorders and to validate its efficacy.Methods We proposed the Fine-Med-Mental-T&P...Objective To investigate methods for constructing a high-quality instructional dataset for traditional Chinese medicine(TCM)mental disorders and to validate its efficacy.Methods We proposed the Fine-Med-Mental-T&P methodology for constructing high-quality instruction datasets in TCM mental disorders.This approach integrates theoretical knowledge and practical case studies through a dual-track strategy.(i)Theoretical track:textbooks and guidelines on TCM mental disorders were manually segmented.Initial responses were generated using DeepSeek-V3,followed by refinement by the Qwen3-32B model to align the expression with human preferences.A screening algorithm was then applied to select 16000 high-quality instruction pairs.(ii)Practical track:starting from over 600 real clinical case seeds,diagnostic and therapeutic instruction pairs were generated using DeepSeek-V3 and subsequently screened through manual evaluation,resulting in 4000 high-quality practiceoriented instruction pairs.The integration of both tracks yielded the Med-Mental-Instruct-T&P dataset,comprising a total of 20000 instruction pairs.To validate the dataset’s effectiveness,three experimental evaluations(both manual and automated)were conducted:(i)comparative studies to compare the performance of models fine-tuned on different datasets;(ii)benchmarking to compare against mainstream TCM-specific large language models(LLMs);(iii)data ablation study to investigate the relationship between data volume and model performance.Results Experimental results demonstrate the superior performance of T&P-model finetuned on the Med-Mental-Instruct-T&P dataset.In the comparative study,the T&P-model significantly outperformed the baseline models trained solely on self-generated or purely human-curated baseline data.This superiority was evident in both automated metrics(ROUGEL>0.55)and expert manual evaluations(scoring above 7/10 across accuracy).In benchmark comparisons,the T&P-model also excelled against existing mainstream TCM LLMs(e.g.,HuatuoGPT and ZuoyiGPT).It showed particularly strong capabilities in handling diverse clinical presentations,including challenging disorders such as insomnia and coma,showcasing its robustness and versatility.Data ablation studies showed that T&P-model performance had an overall upward trend with minor fluctuations when training data increased from 10%to 50%;beyond 50%,performance improvement slowed significantly,with metrics plateauing and approaching a saturation point.展开更多
Parkinson’s disease(PD)is a debilitating neurological disorder affecting over 10 million people worldwide.PD classification models using voice signals as input are common in the literature.It is believed that using d...Parkinson’s disease(PD)is a debilitating neurological disorder affecting over 10 million people worldwide.PD classification models using voice signals as input are common in the literature.It is believed that using deep learning algorithms further enhances performance;nevertheless,it is challenging due to the nature of small-scale and imbalanced PD datasets.This paper proposed a convolutional neural network-based deep support vector machine(CNN-DSVM)to automate the feature extraction process using CNN and extend the conventional SVM to a DSVM for better classification performance in small-scale PD datasets.A customized kernel function reduces the impact of biased classification towards the majority class(healthy candidates in our consideration).An improved generative adversarial network(IGAN)was designed to generate additional training data to enhance the model’s performance.For performance evaluation,the proposed algorithm achieves a sensitivity of 97.6%and a specificity of 97.3%.The performance comparison is evaluated from five perspectives,including comparisons with different data generation algorithms,feature extraction techniques,kernel functions,and existing works.Results reveal the effectiveness of the IGAN algorithm,which improves the sensitivity and specificity by 4.05%–4.72%and 4.96%–5.86%,respectively;and the effectiveness of the CNN-DSVM algorithm,which improves the sensitivity by 1.24%–57.4%and specificity by 1.04%–163%and reduces biased detection towards the majority class.The ablation experiments confirm the effectiveness of individual components.Two future research directions have also been suggested.展开更多
Soybean(Glycine max L.)is a globally vital crop for oil production and food security.High-quality genomic resources are instrumental for both functional genomics and breeding.Here,we report a near-complete,high-qualit...Soybean(Glycine max L.)is a globally vital crop for oil production and food security.High-quality genomic resources are instrumental for both functional genomics and breeding.Here,we report a near-complete,high-quality genome assembly of the elite cultivar Tianlong 1(TL1),featuring fully resolved telomeres and centromeres,as well as a gap-free assembly of 14 of its 20 chromosomes.On the basis of the genome assembly,we generate an ethyl methanesulfonate(EMS)-mutagenized population comprising 2555 M7 plants.Whole-genome resequencing of 288 EMS mutants uncovers 1,163,869 high-confidence single-nucleotide polymorphisms(SNPs)and 542,709 insertions/deletions(InDels),achieving 91.89%coverage of predicted protein-coding genes.Phenotypic screening demonstrates robust genotype–phenotype associations,with two nonsynonymous mutants displaying pronounced defects in seed and leaf development.Collectively,the chromosome-scale TL1 genome assembly and the extensively characterized mutant population establish valuable resources for functional genomics and precision breeding in soybean and related legume species.展开更多
Objective: To explore the impact of high-quality nursing on the nursing effect of patients with hepatic encephalopathy, and provide a basis for optimizing clinical nursing plans. Methods: A total of 80 patients with h...Objective: To explore the impact of high-quality nursing on the nursing effect of patients with hepatic encephalopathy, and provide a basis for optimizing clinical nursing plans. Methods: A total of 80 patients with hepatic encephalopathy admitted to a hospital from April 2023 to April 2024 were selected and randomly divided into a conventional group (37 cases, receiving conventional nursing) and an observation group (43 cases, receiving high-quality nursing) using a blind selection method. The incidence of complications, nursing satisfaction, changes in quality of life (SF-36 scale) and liver function indicators (ALT, AST, TBIL, ALB) before and after nursing were compared between the two groups. Results: The incidence of complications in the observation group (6.98%) was significantly lower than that in the conventional group (24.32%), and the nursing satisfaction (97.67%) was significantly higher than that in the conventional group (81.08), with statistically significant differences (p < 0.05);after nursing, the scores of each dimension and total score of the SF-36 scale, and the improvement range of liver function indicators in the observation group were significantly better than those in the conventional group, with statistically significant differences (p < 0.05). Conclusion: High-quality nursing can effectively reduce the risk of complications in patients with hepatic encephalopathy, improve nursing satisfaction and quality of life, and enhance liver function, which has important clinical promotion value.展开更多
Accurate purchase prediction in e-commerce critically depends on the quality of behavioral features.This paper proposes a layered and interpretable feature engineering framework that organizes user signals into three ...Accurate purchase prediction in e-commerce critically depends on the quality of behavioral features.This paper proposes a layered and interpretable feature engineering framework that organizes user signals into three layers:Basic,Conversion&Stability(efficiency and volatility across actions),and Advanced Interactions&Activity(crossbehavior synergies and intensity).Using real Taobao(Alibaba’s primary e-commerce platform)logs(57,976 records for 10,203 users;25 November–03 December 2017),we conducted a hierarchical,layer-wise evaluation that holds data splits and hyperparameters fixed while varying only the feature set to quantify each layer’s marginal contribution.Across logistic regression(LR),decision tree,random forest,XGBoost,and CatBoost models with stratified 5-fold cross-validation,the performance improvedmonotonically fromBasic to Conversion&Stability to Advanced features.With LR,F1 increased from 0.613(Basic)to 0.962(Advanced);boosted models achieved high discrimination(0.995 AUC Score)and an F1 score up to 0.983.Calibration and precision–recall analyses indicated strong ranking quality and acknowledged potential dataset and period biases given the short(9-day)window.By making feature contributions measurable and reproducible,the framework complements model-centric advances and offers a transparent blueprint for production-grade behavioralmodeling.The code and processed artifacts are publicly available,and future work will extend the validation to longer,seasonal datasets and hybrid approaches that combine automated feature learning with domain-driven design.展开更多
Objective: To analyze the value of high-quality nursing care for patients with kidney stones undergoing percutaneous nephrolithotomy with holmium laser lithotripsy (PCNL). Methods: A total of 72 patients with kidney s...Objective: To analyze the value of high-quality nursing care for patients with kidney stones undergoing percutaneous nephrolithotomy with holmium laser lithotripsy (PCNL). Methods: A total of 72 patients with kidney stones treated with PCNL from November 2024 to November 2025 were selected as samples and randomly divided into groups using a random number table. Group A received high-quality nursing care, while Group B received conventional nursing care. Indicators such as pain, anxiety, nursing satisfaction, and complications were compared between the two groups. Results: The Visual Analog Scale (VAS) scores for pain and Self-Rating Anxiety Scale (SAS) scores for anxiety in Group A were lower than those in Group B (p < 0.05). The nursing satisfaction rate in Group A was higher than that in Group B (p < 0.05). The complication rate of PCNL in Group A was lower than that in Group B (p < 0.05). Conclusion: For patients with kidney stones treated with PCNL, receiving high-quality nursing care can alleviate anxiety, relieve pain, and reduce the risk of postoperative complications.展开更多
Taking the Changli Institute of Pomology,Hebei Academy of Agriculture and Forestry Sciences(hereinafter referred to as the Changli Institute of Pomology)as a case study,this paper explores the practical pathways throu...Taking the Changli Institute of Pomology,Hebei Academy of Agriculture and Forestry Sciences(hereinafter referred to as the Changli Institute of Pomology)as a case study,this paper explores the practical pathways through which Party building leads to the high-quality development of fruit tree research from three dimensions:theoretical convergence points,current development status,and functional mechanisms.It proposes that Party building should focus on its core roles of steering political direction,enhancing team cohesion,and upholding ethical standards.Deep integration of Party building and scientific research should be achieved through concrete platforms,with the effectiveness measured by breakthroughs in critical"bottleneck"technologies and increased income for fruit growers.The study aims to provide a practical reference for integrating Party building with professional work in the agricultural research sector.展开更多
Lithology identification is a critical aspect of geoenergy exploration,including geothermal energy development,gas hydrate extraction,and gas storage.In recent years,artificial intelligence techniques based on drill c...Lithology identification is a critical aspect of geoenergy exploration,including geothermal energy development,gas hydrate extraction,and gas storage.In recent years,artificial intelligence techniques based on drill core images have made significant strides in lithology identification,achieving high accuracy.However,the current demand for advanced lithology identification models remains unmet due to the lack of high-quality drill core image datasets.This study successfully constructs and publicly releases the first open-source Drill Core Image Dataset(DCID),addressing the need for large-scale,high-quality datasets in lithology characterization tasks within geological engineering and establishing a standard dataset for model evaluation.DCID consists of 35 lithology categories and a total of 98,000 high-resolution images(512×512 pixels),making it the most comprehensive drill core image dataset in terms of lithology categories,image quantity,and resolution.This study also provides lithology identification accuracy benchmarks for popular convolutional neural networks(CNNs)such as VGG,ResNet,DenseNet,MobileNet,as well as for the Vision Transformer(ViT)and MLP-Mixer,based on DCID.Additionally,the sensitivity of model performance to various parameters and image resolution is evaluated.In response to real-world challenges,we propose a real-world data augmentation(RWDA)method,leveraging slightly defective images from DCID to enhance model robustness.The study also explores the impact of real-world lighting conditions on the performance of lithology identification models.Finally,we demonstrate how to rapidly evaluate model performance across multiple dimensions using low-resolution datasets,advancing the application and development of new lithology identification models for geoenergy exploration.展开更多
In machine vision,elliptical targets frequently appear within the camera's region of interest(ROI).Ellipse detection is essential for shape detection and geometric measurements in machine vision.However,existing e...In machine vision,elliptical targets frequently appear within the camera's region of interest(ROI).Ellipse detection is essential for shape detection and geometric measurements in machine vision.However,existing ellipse detection algorithms often face issues such as high computational complexity,strong dependence on initial conditions,sensitivity to noise,and lack of robustness to occlusions.In this paper,we propose a fast and robust ellipse detection method to address these challenges.This method first utilizes edge gradient and curvature information to segment the curve into circular arcs.Next,based on the convexity of the arcs,it divides them into different quadrants of the ellipse,groups and fits the arcs according to multiple geometric constraints at a low computational cost.Finally,it reduces the parameter space for hierarchical clustering and then segments the complete ellipse into several sectors for verification.We compare our method across seven datasets,including five public image datasets and two from industrial camera scenes.Experimental results show that our method achieves a precision ranging from 67.1%to 98.9%,a recall ranging from 48.1%to 92.9%,and an F-measure ranging from 58.0%to 95.8%.The average execution time per image ranges from 25 ms to 192 ms,demonstrating both high accuracy and efficiency.展开更多
Digital-intelligent technologies represent the advanced direction of new quality productive forces and are becoming a driving force for the digital transformation and high-quality development of the cultural industry....Digital-intelligent technologies represent the advanced direction of new quality productive forces and are becoming a driving force for the digital transformation and high-quality development of the cultural industry.Empowered by new quality productive forces,the digital cultural industry has demonstrated diverse characteristics,including the innovation of cultural production subjects,the intelligentization of production tools,the digitization of production objects,the systematization of production methods,and the diversification of production factors.Leveraging technologies such as AIGC,virtual-physical integration,and DAOs based on Web 3.0,the digital cultural industry has established an innovative paradigm,fostering a new method of AIGC production in the digital cultural industry,a new business format of virtual-physical integration,and a new collaborative ecosystem characterized by co-creation,co-building,and co-governance.Meanwhile,the innovative paradigm of the digital cultural industry also faces a series of new challenges,such as the adaptability issues with AIGC algorithm models,creative bottlenecks,and content quality control problems.Additionally,there are obstacles like the immaturity of international development channels for new business formats,the lack of cultural connotations in creative products,and the lag of the digital-intelligent governance of the industry ecosystem behind digital practices.In light of this,there is an urgent need to establish an optimization mechanism for the high-quality development of digital cultural industries driven by new quality productive forces.This includes optimizing the content production mechanism for AIGC-led high-quality innovation in the digital cultural industry;improving the leapfrog development mechanism for new digital cultural business formats through global-regional collaboration;and enhancing the accurate,high-quality governance mechanism for the digital cultural industry that is aligned with the goals of Chinese modernization.展开更多
Based on the requirements of local high-quality economic development and addressing the critical task of transformation and upgrading in the tea industry,this paper systematically discusses the necessity and feasibili...Based on the requirements of local high-quality economic development and addressing the critical task of transformation and upgrading in the tea industry,this paper systematically discusses the necessity and feasibility of constructing an optimal industrialization operation system driven by the dual wheels of"branding+standardization".The article first clarifies the connotation of high-quality development and the synergistic mechanism between branding and standardization.It then analyzes the current situation and bottlenecks of China's tea industry development.Subsequently,it proposes a dual-wheel drive strategy where branding enhances value and standardization guarantees quality,and designs a systematic implementation plan involving industrial chain synergy optimization and integrated support from government,industry,academia,research,and application.On this basis,strategies and suggestions are proposed,encompassing the starting point,standard focal points,key effort areas,innovation points,and target achievement points.The aim is to promote the tea industry to break through homogeneous competition,achieve value ascent,and provide important industrial support for regional high-quality development through the construction of the aforementioned system.展开更多
With the rapid development of China's insurance market,the high-quality development of the insurance market is faced with many different challenges and various problems.This paper aims to deeply analyze the actual...With the rapid development of China's insurance market,the high-quality development of the insurance market is faced with many different challenges and various problems.This paper aims to deeply analyze the actual problems in China's insurance market and put forward supporting countermeasures.First,by understanding the background of highquality insurance development,we can explain the research significance of this paper in combination with the existing national policies.Secondly,by summarizing the current situation of high-quality insurance development,the paper puts forward the shortage of insurance talents in the expansion of insurance scale,the continuous improvement of insurance density and depth,and the growth of insurance compensation in the development of high-quality insurance.Finally,from the perspective of differentiated customized insurance products,training professionals,and providing financial subsidies,we will put forward the corresponding suggestions for the problem and look forward to the future development prospects.展开更多
High-quality clinical evidence is the basis of evidence-based medical practice.Acupuncture is the most widely used complementary and alternative medicine in the world.However,the improvement in the quality of acupunct...High-quality clinical evidence is the basis of evidence-based medical practice.Acupuncture is the most widely used complementary and alternative medicine in the world.However,the improvement in the quality of acupuncture clinical research does not match the rapid increase in the number of acupuncture clinical research in recent years.At present,the number of high-quality acupuncture clinical research in the world remains low.Taking the trial of acupuncture for chronic spontaneous urticaria published in Annals of Internal Medicine as an example,this paper discusses the factors that contribute to producing high-quality clinical evidence for acupuncture from the aspects of selecting the topic of study,formulating the study method,designing the study plan,controlling the study process,writing the study report,and selecting the journal in the process of before,during,and after the research.It emphasizes the necessity to start from the benefit of global people's health,take practical clinical problems as guidance,cleverly choose the research entry point,and conduct high-quality research with clinical value.After the accomplishment of the study,the results must be faithfully described,the scientific conclusions accurately sublimated,and appropriate scientific journals selected for publication.展开更多
Objective:To explore the effects of high-quality nursing intervention on negative emotions and quality of life in gynecological patients after laparoscopy.Methods:A total of 132 gynecological patients after laparoscop...Objective:To explore the effects of high-quality nursing intervention on negative emotions and quality of life in gynecological patients after laparoscopy.Methods:A total of 132 gynecological patients after laparoscopy were randomly divided into an observation group(n=66)and a control group(n=66)in a prospective study.The con-trol group received routine nursing care,while the observation group received high-quality nursing intervention.Anxiety,depression,quality of life,postoperative pain,self-care ability,and patient satisfaction were compared between the two groups.Results:The Self-Rating Anxiety Scale and Self-Rating Depression Scale scores were sig-nificantly lower in the observation group compared to the control group(both P<0.001).Pain scores at 6,24,48,and 72 hours post-surgery were also lower in the observation group(all P<0.001).The observation group showed significantly higher scores in physical function,general health,social function,emotional role,and mental health(all P<0.001).Furthermore,the observation group demonstrated better self-care skills,self-concept,self-care responsibility,and health knowledge(all P<0.001).Nursing satisfaction during hospitalization was significantly higher in the observation group than in the control group(P<0.05).Conclusion:High-quality nursing intervention is effective in improving depression,anxiety,postoperative pain,and quality of life in gynecological patients after laparoscopy.It also enhances self-care ability and patient satisfaction,making it worthy of clinical promotion and application.展开更多
Highly crystalline perovskite absorbers with low defect-state densities minimizing nonradiative recombination losses are a critical prerequisite for fabricating state-of-the-art photovoltaics.Here,we use a tartaric ac...Highly crystalline perovskite absorbers with low defect-state densities minimizing nonradiative recombination losses are a critical prerequisite for fabricating state-of-the-art photovoltaics.Here,we use a tartaric acid(TA)molecule with two carboxyl and two hydroxyl groups as an additive to improve the performance and stability of the device simultaneously.The strong carboxyl-Pb2+coordination slows nucleation kinetics and passivates Pb-related traps,whereas hydroxyl-I-hydrogen bonding can modulate grain growth and stabilize the lattice structure,collectively enabling low-defect-density and high-quality perovskite films.Besides,we also conducted quantitively loss analysis and confirmed that the TA addition effectively reduces trap-assisted non-radiative recombination.Consequently,the champion efficiency of the n-i-p structure is up to 24.77% with outstanding operational and humidity stability.Remarkably,in the triple-cation perovskite system,the incorporation of the TA additive similarly enabled the fabrication of high-quality films,ultimately yielding a p-i-n configuration with a champion efficiency of 26.11%.展开更多
Songji Ancient Town in Yongchuan District,Chongqing,is a famous historical and cultural town in China and a national AAAA-level tourist attraction.In recent years,combining its unique historical and cultural heritage,...Songji Ancient Town in Yongchuan District,Chongqing,is a famous historical and cultural town in China and a national AAAA-level tourist attraction.In recent years,combining its unique historical and cultural heritage,the scenic area has developed research travel products themed on intangible cultural heritage and red tourism,attracting students from across the country to experience it.On the other hand,in the context of the deepening of the“double reduction”policy and the concept of a“high-quality education system,”the educational connotation of Songji Ancient Town’s research products is constantly enriching.Based on this,this article will combine the RMP theory to explore strategies for improving satisfaction with Yongchuan District’s“Songji Ancient Town Research Products”under a high-quality education system,to promote the development of the scenic area’s research experience projects and overall tourism service levels.展开更多
Standardized datasets are foundational to healthcare informatization by enhancing data quality and unleashing the value of data elements.Using bibliometrics and content analysis,this study examines China's healthc...Standardized datasets are foundational to healthcare informatization by enhancing data quality and unleashing the value of data elements.Using bibliometrics and content analysis,this study examines China's healthcare dataset standards from 2011 to 2025.It analyzes their evolution across types,applications,institutions,and themes,highlighting key achievements including substantial growth in quantity,optimized typology,expansion into innovative application scenarios such as health decision support,and broadened institutional involvement.The study also identifies critical challenges,including imbalanced development,insufficient quality control,and a lack of essential metadata—such as authoritative data element mappings and privacy annotations—which hampers the delivery of intelligent services.To address these challenges,the study proposes a multi-faceted strategy focused on optimizing the standard system's architecture,enhancing quality and implementation,and advancing both data governance—through authoritative tracing and privacy protection—and intelligent service provision.These strategies aim to promote the application of dataset standards,thereby fostering and securing the development of new productive forces in healthcare.展开更多
Under the background of"Digital Commerce for Rural Vitalization",rural E-commerce has experienced rapid development.However,agricultural products like strawberries,often produced by small-scale,fragmented,an...Under the background of"Digital Commerce for Rural Vitalization",rural E-commerce has experienced rapid development.However,agricultural products like strawberries,often produced by small-scale,fragmented,and less competitive individual farmers,struggle to meet the compliance and scalability demands of E-commerce,thereby constraining high-quality local economic development.Aiming to address this issue,this paper,guided by relevant policies and strategies,employs case analysis and logical deduction to explore the industrialization path of the"Cooperative+E-commerce"model for the strawberry industry.The research finds that by optimizing the cooperative's organizational structure,implementing multi-channel E-commerce strategies,upgrading the supply chain(including cold chain and quality traceability),and engaging in collaborative brand building,a robust industrial system can be formed.Supplemented by benefit evaluation,policy support,and regulatory oversight,this system can effectively bridge small-scale production with the broader market.This study concludes that this pathway can enhance the added value of the strawberry industry,increase farmer incomes,and provide practical insights for promoting high-quality local economic development.展开更多
When dealing with imbalanced datasets,the traditional support vectormachine(SVM)tends to produce a classification hyperplane that is biased towards the majority class,which exhibits poor robustness.This paper proposes...When dealing with imbalanced datasets,the traditional support vectormachine(SVM)tends to produce a classification hyperplane that is biased towards the majority class,which exhibits poor robustness.This paper proposes a high-performance classification algorithm specifically designed for imbalanced datasets.The proposed method first uses a biased second-order cone programming support vectormachine(B-SOCP-SVM)to identify the support vectors(SVs)and non-support vectors(NSVs)in the imbalanced data.Then,it applies the synthetic minority over-sampling technique(SV-SMOTE)to oversample the support vectors of the minority class and uses the random under-sampling technique(NSV-RUS)multiple times to undersample the non-support vectors of the majority class.Combining the above-obtained minority class data set withmultiple majority class datasets can obtainmultiple new balanced data sets.Finally,SOCP-SVM is used to classify each data set,and the final result is obtained through the integrated algorithm.Experimental results demonstrate that the proposed method performs excellently on imbalanced datasets.展开更多
基金Key Scientific Research Project of the Hunan Provincial Department of Education(23A312).
文摘Objective To investigate methods for constructing a high-quality instructional dataset for traditional Chinese medicine(TCM)mental disorders and to validate its efficacy.Methods We proposed the Fine-Med-Mental-T&P methodology for constructing high-quality instruction datasets in TCM mental disorders.This approach integrates theoretical knowledge and practical case studies through a dual-track strategy.(i)Theoretical track:textbooks and guidelines on TCM mental disorders were manually segmented.Initial responses were generated using DeepSeek-V3,followed by refinement by the Qwen3-32B model to align the expression with human preferences.A screening algorithm was then applied to select 16000 high-quality instruction pairs.(ii)Practical track:starting from over 600 real clinical case seeds,diagnostic and therapeutic instruction pairs were generated using DeepSeek-V3 and subsequently screened through manual evaluation,resulting in 4000 high-quality practiceoriented instruction pairs.The integration of both tracks yielded the Med-Mental-Instruct-T&P dataset,comprising a total of 20000 instruction pairs.To validate the dataset’s effectiveness,three experimental evaluations(both manual and automated)were conducted:(i)comparative studies to compare the performance of models fine-tuned on different datasets;(ii)benchmarking to compare against mainstream TCM-specific large language models(LLMs);(iii)data ablation study to investigate the relationship between data volume and model performance.Results Experimental results demonstrate the superior performance of T&P-model finetuned on the Med-Mental-Instruct-T&P dataset.In the comparative study,the T&P-model significantly outperformed the baseline models trained solely on self-generated or purely human-curated baseline data.This superiority was evident in both automated metrics(ROUGEL>0.55)and expert manual evaluations(scoring above 7/10 across accuracy).In benchmark comparisons,the T&P-model also excelled against existing mainstream TCM LLMs(e.g.,HuatuoGPT and ZuoyiGPT).It showed particularly strong capabilities in handling diverse clinical presentations,including challenging disorders such as insomnia and coma,showcasing its robustness and versatility.Data ablation studies showed that T&P-model performance had an overall upward trend with minor fluctuations when training data increased from 10%to 50%;beyond 50%,performance improvement slowed significantly,with metrics plateauing and approaching a saturation point.
基金The work described in this paper was fully supported by a grant from Hong Kong Metropolitan University(RIF/2021/05).
文摘Parkinson’s disease(PD)is a debilitating neurological disorder affecting over 10 million people worldwide.PD classification models using voice signals as input are common in the literature.It is believed that using deep learning algorithms further enhances performance;nevertheless,it is challenging due to the nature of small-scale and imbalanced PD datasets.This paper proposed a convolutional neural network-based deep support vector machine(CNN-DSVM)to automate the feature extraction process using CNN and extend the conventional SVM to a DSVM for better classification performance in small-scale PD datasets.A customized kernel function reduces the impact of biased classification towards the majority class(healthy candidates in our consideration).An improved generative adversarial network(IGAN)was designed to generate additional training data to enhance the model’s performance.For performance evaluation,the proposed algorithm achieves a sensitivity of 97.6%and a specificity of 97.3%.The performance comparison is evaluated from five perspectives,including comparisons with different data generation algorithms,feature extraction techniques,kernel functions,and existing works.Results reveal the effectiveness of the IGAN algorithm,which improves the sensitivity and specificity by 4.05%–4.72%and 4.96%–5.86%,respectively;and the effectiveness of the CNN-DSVM algorithm,which improves the sensitivity by 1.24%–57.4%and specificity by 1.04%–163%and reduces biased detection towards the majority class.The ablation experiments confirm the effectiveness of individual components.Two future research directions have also been suggested.
基金supported by the National Natural Science Foundation of China(31970344)Joint Funds of the Natural Science Foundation of Hainan Province,China(2021JJLH0065).
文摘Soybean(Glycine max L.)is a globally vital crop for oil production and food security.High-quality genomic resources are instrumental for both functional genomics and breeding.Here,we report a near-complete,high-quality genome assembly of the elite cultivar Tianlong 1(TL1),featuring fully resolved telomeres and centromeres,as well as a gap-free assembly of 14 of its 20 chromosomes.On the basis of the genome assembly,we generate an ethyl methanesulfonate(EMS)-mutagenized population comprising 2555 M7 plants.Whole-genome resequencing of 288 EMS mutants uncovers 1,163,869 high-confidence single-nucleotide polymorphisms(SNPs)and 542,709 insertions/deletions(InDels),achieving 91.89%coverage of predicted protein-coding genes.Phenotypic screening demonstrates robust genotype–phenotype associations,with two nonsynonymous mutants displaying pronounced defects in seed and leaf development.Collectively,the chromosome-scale TL1 genome assembly and the extensively characterized mutant population establish valuable resources for functional genomics and precision breeding in soybean and related legume species.
基金Chongqing Vocational Education Teaching Reform Research Project,Exploration and Practice of Psychological Education System in Higher Vocational Colleges from the Perspective of Fostering Morality and Cultivating People(Project No.:Z2241421)。
文摘Objective: To explore the impact of high-quality nursing on the nursing effect of patients with hepatic encephalopathy, and provide a basis for optimizing clinical nursing plans. Methods: A total of 80 patients with hepatic encephalopathy admitted to a hospital from April 2023 to April 2024 were selected and randomly divided into a conventional group (37 cases, receiving conventional nursing) and an observation group (43 cases, receiving high-quality nursing) using a blind selection method. The incidence of complications, nursing satisfaction, changes in quality of life (SF-36 scale) and liver function indicators (ALT, AST, TBIL, ALB) before and after nursing were compared between the two groups. Results: The incidence of complications in the observation group (6.98%) was significantly lower than that in the conventional group (24.32%), and the nursing satisfaction (97.67%) was significantly higher than that in the conventional group (81.08), with statistically significant differences (p < 0.05);after nursing, the scores of each dimension and total score of the SF-36 scale, and the improvement range of liver function indicators in the observation group were significantly better than those in the conventional group, with statistically significant differences (p < 0.05). Conclusion: High-quality nursing can effectively reduce the risk of complications in patients with hepatic encephalopathy, improve nursing satisfaction and quality of life, and enhance liver function, which has important clinical promotion value.
基金supported by the research fund of Hanyang University(HY-202500000001616).
文摘Accurate purchase prediction in e-commerce critically depends on the quality of behavioral features.This paper proposes a layered and interpretable feature engineering framework that organizes user signals into three layers:Basic,Conversion&Stability(efficiency and volatility across actions),and Advanced Interactions&Activity(crossbehavior synergies and intensity).Using real Taobao(Alibaba’s primary e-commerce platform)logs(57,976 records for 10,203 users;25 November–03 December 2017),we conducted a hierarchical,layer-wise evaluation that holds data splits and hyperparameters fixed while varying only the feature set to quantify each layer’s marginal contribution.Across logistic regression(LR),decision tree,random forest,XGBoost,and CatBoost models with stratified 5-fold cross-validation,the performance improvedmonotonically fromBasic to Conversion&Stability to Advanced features.With LR,F1 increased from 0.613(Basic)to 0.962(Advanced);boosted models achieved high discrimination(0.995 AUC Score)and an F1 score up to 0.983.Calibration and precision–recall analyses indicated strong ranking quality and acknowledged potential dataset and period biases given the short(9-day)window.By making feature contributions measurable and reproducible,the framework complements model-centric advances and offers a transparent blueprint for production-grade behavioralmodeling.The code and processed artifacts are publicly available,and future work will extend the validation to longer,seasonal datasets and hybrid approaches that combine automated feature learning with domain-driven design.
文摘Objective: To analyze the value of high-quality nursing care for patients with kidney stones undergoing percutaneous nephrolithotomy with holmium laser lithotripsy (PCNL). Methods: A total of 72 patients with kidney stones treated with PCNL from November 2024 to November 2025 were selected as samples and randomly divided into groups using a random number table. Group A received high-quality nursing care, while Group B received conventional nursing care. Indicators such as pain, anxiety, nursing satisfaction, and complications were compared between the two groups. Results: The Visual Analog Scale (VAS) scores for pain and Self-Rating Anxiety Scale (SAS) scores for anxiety in Group A were lower than those in Group B (p < 0.05). The nursing satisfaction rate in Group A was higher than that in Group B (p < 0.05). The complication rate of PCNL in Group A was lower than that in Group B (p < 0.05). Conclusion: For patients with kidney stones treated with PCNL, receiving high-quality nursing care can alleviate anxiety, relieve pain, and reduce the risk of postoperative complications.
基金Supported by Qinhuangdao Social Sciences Development Research Project(2025LX378).
文摘Taking the Changli Institute of Pomology,Hebei Academy of Agriculture and Forestry Sciences(hereinafter referred to as the Changli Institute of Pomology)as a case study,this paper explores the practical pathways through which Party building leads to the high-quality development of fruit tree research from three dimensions:theoretical convergence points,current development status,and functional mechanisms.It proposes that Party building should focus on its core roles of steering political direction,enhancing team cohesion,and upholding ethical standards.Deep integration of Party building and scientific research should be achieved through concrete platforms,with the effectiveness measured by breakthroughs in critical"bottleneck"technologies and increased income for fruit growers.The study aims to provide a practical reference for integrating Party building with professional work in the agricultural research sector.
基金support from the National Natural Science Foundation of China(Nos.U24B2034,U2139204)the China Petroleum Science and Technology Innovation Fund(2021DQ02-0501)the Science and Technology Support Project of Langfang(2024011073).
文摘Lithology identification is a critical aspect of geoenergy exploration,including geothermal energy development,gas hydrate extraction,and gas storage.In recent years,artificial intelligence techniques based on drill core images have made significant strides in lithology identification,achieving high accuracy.However,the current demand for advanced lithology identification models remains unmet due to the lack of high-quality drill core image datasets.This study successfully constructs and publicly releases the first open-source Drill Core Image Dataset(DCID),addressing the need for large-scale,high-quality datasets in lithology characterization tasks within geological engineering and establishing a standard dataset for model evaluation.DCID consists of 35 lithology categories and a total of 98,000 high-resolution images(512×512 pixels),making it the most comprehensive drill core image dataset in terms of lithology categories,image quantity,and resolution.This study also provides lithology identification accuracy benchmarks for popular convolutional neural networks(CNNs)such as VGG,ResNet,DenseNet,MobileNet,as well as for the Vision Transformer(ViT)and MLP-Mixer,based on DCID.Additionally,the sensitivity of model performance to various parameters and image resolution is evaluated.In response to real-world challenges,we propose a real-world data augmentation(RWDA)method,leveraging slightly defective images from DCID to enhance model robustness.The study also explores the impact of real-world lighting conditions on the performance of lithology identification models.Finally,we demonstrate how to rapidly evaluate model performance across multiple dimensions using low-resolution datasets,advancing the application and development of new lithology identification models for geoenergy exploration.
基金supported by National Major Scientific Research Instrument Development Project of China(No.51927804)Science Fund for Shaanxi Provincial Department of Education's Youth Innovation Team Research Plan under Grant(No.23JP169).
文摘In machine vision,elliptical targets frequently appear within the camera's region of interest(ROI).Ellipse detection is essential for shape detection and geometric measurements in machine vision.However,existing ellipse detection algorithms often face issues such as high computational complexity,strong dependence on initial conditions,sensitivity to noise,and lack of robustness to occlusions.In this paper,we propose a fast and robust ellipse detection method to address these challenges.This method first utilizes edge gradient and curvature information to segment the curve into circular arcs.Next,based on the convexity of the arcs,it divides them into different quadrants of the ellipse,groups and fits the arcs according to multiple geometric constraints at a low computational cost.Finally,it reduces the parameter space for hierarchical clustering and then segments the complete ellipse into several sectors for verification.We compare our method across seven datasets,including five public image datasets and two from industrial camera scenes.Experimental results show that our method achieves a precision ranging from 67.1%to 98.9%,a recall ranging from 48.1%to 92.9%,and an F-measure ranging from 58.0%to 95.8%.The average execution time per image ranges from 25 ms to 192 ms,demonstrating both high accuracy and efficiency.
基金funded by Research on Policy Design and Implementation Path for High-Quality Development of Digital Cultural Industry(23&ZD087),a major project of the National Social Science Foundation of China.
文摘Digital-intelligent technologies represent the advanced direction of new quality productive forces and are becoming a driving force for the digital transformation and high-quality development of the cultural industry.Empowered by new quality productive forces,the digital cultural industry has demonstrated diverse characteristics,including the innovation of cultural production subjects,the intelligentization of production tools,the digitization of production objects,the systematization of production methods,and the diversification of production factors.Leveraging technologies such as AIGC,virtual-physical integration,and DAOs based on Web 3.0,the digital cultural industry has established an innovative paradigm,fostering a new method of AIGC production in the digital cultural industry,a new business format of virtual-physical integration,and a new collaborative ecosystem characterized by co-creation,co-building,and co-governance.Meanwhile,the innovative paradigm of the digital cultural industry also faces a series of new challenges,such as the adaptability issues with AIGC algorithm models,creative bottlenecks,and content quality control problems.Additionally,there are obstacles like the immaturity of international development channels for new business formats,the lack of cultural connotations in creative products,and the lag of the digital-intelligent governance of the industry ecosystem behind digital practices.In light of this,there is an urgent need to establish an optimization mechanism for the high-quality development of digital cultural industries driven by new quality productive forces.This includes optimizing the content production mechanism for AIGC-led high-quality innovation in the digital cultural industry;improving the leapfrog development mechanism for new digital cultural business formats through global-regional collaboration;and enhancing the accurate,high-quality governance mechanism for the digital cultural industry that is aligned with the goals of Chinese modernization.
基金Supported by General Project of Philosophy and Social Sciences Research in Universities of Jiangsu Province,2024(2024SJYB1650).
文摘Based on the requirements of local high-quality economic development and addressing the critical task of transformation and upgrading in the tea industry,this paper systematically discusses the necessity and feasibility of constructing an optimal industrialization operation system driven by the dual wheels of"branding+standardization".The article first clarifies the connotation of high-quality development and the synergistic mechanism between branding and standardization.It then analyzes the current situation and bottlenecks of China's tea industry development.Subsequently,it proposes a dual-wheel drive strategy where branding enhances value and standardization guarantees quality,and designs a systematic implementation plan involving industrial chain synergy optimization and integrated support from government,industry,academia,research,and application.On this basis,strategies and suggestions are proposed,encompassing the starting point,standard focal points,key effort areas,innovation points,and target achievement points.The aim is to promote the tea industry to break through homogeneous competition,achieve value ascent,and provide important industrial support for regional high-quality development through the construction of the aforementioned system.
文摘With the rapid development of China's insurance market,the high-quality development of the insurance market is faced with many different challenges and various problems.This paper aims to deeply analyze the actual problems in China's insurance market and put forward supporting countermeasures.First,by understanding the background of highquality insurance development,we can explain the research significance of this paper in combination with the existing national policies.Secondly,by summarizing the current situation of high-quality insurance development,the paper puts forward the shortage of insurance talents in the expansion of insurance scale,the continuous improvement of insurance density and depth,and the growth of insurance compensation in the development of high-quality insurance.Finally,from the perspective of differentiated customized insurance products,training professionals,and providing financial subsidies,we will put forward the corresponding suggestions for the problem and look forward to the future development prospects.
基金Supported by Sichuan Province science and technology education joint fund project:2024NSFSC1976Science and Technology Research Project of Sichuan Ad-ministration of Traditional Chinese Medicine:2021MS320.
文摘High-quality clinical evidence is the basis of evidence-based medical practice.Acupuncture is the most widely used complementary and alternative medicine in the world.However,the improvement in the quality of acupuncture clinical research does not match the rapid increase in the number of acupuncture clinical research in recent years.At present,the number of high-quality acupuncture clinical research in the world remains low.Taking the trial of acupuncture for chronic spontaneous urticaria published in Annals of Internal Medicine as an example,this paper discusses the factors that contribute to producing high-quality clinical evidence for acupuncture from the aspects of selecting the topic of study,formulating the study method,designing the study plan,controlling the study process,writing the study report,and selecting the journal in the process of before,during,and after the research.It emphasizes the necessity to start from the benefit of global people's health,take practical clinical problems as guidance,cleverly choose the research entry point,and conduct high-quality research with clinical value.After the accomplishment of the study,the results must be faithfully described,the scientific conclusions accurately sublimated,and appropriate scientific journals selected for publication.
文摘Objective:To explore the effects of high-quality nursing intervention on negative emotions and quality of life in gynecological patients after laparoscopy.Methods:A total of 132 gynecological patients after laparoscopy were randomly divided into an observation group(n=66)and a control group(n=66)in a prospective study.The con-trol group received routine nursing care,while the observation group received high-quality nursing intervention.Anxiety,depression,quality of life,postoperative pain,self-care ability,and patient satisfaction were compared between the two groups.Results:The Self-Rating Anxiety Scale and Self-Rating Depression Scale scores were sig-nificantly lower in the observation group compared to the control group(both P<0.001).Pain scores at 6,24,48,and 72 hours post-surgery were also lower in the observation group(all P<0.001).The observation group showed significantly higher scores in physical function,general health,social function,emotional role,and mental health(all P<0.001).Furthermore,the observation group demonstrated better self-care skills,self-concept,self-care responsibility,and health knowledge(all P<0.001).Nursing satisfaction during hospitalization was significantly higher in the observation group than in the control group(P<0.05).Conclusion:High-quality nursing intervention is effective in improving depression,anxiety,postoperative pain,and quality of life in gynecological patients after laparoscopy.It also enhances self-care ability and patient satisfaction,making it worthy of clinical promotion and application.
基金funding support from the National Key Research and Development Program of China(2022YFE0137400)the National Natural Science Foundation of China(62274040)+3 种基金funding support from the National Natural Science Foundation of China(62304046)the National Key Research and Development Program of China(2022YFB2802802)the Key Laboratory of Rare Earths,Ganjiang Innovation Academy,Chinese Academy of Sciencessupport from the Shanghai Science and Technology Innovation Action Plan 2023 Special Project for Supporting Carbon Peak Carbon Neutrality Project(23DZ1200400)。
文摘Highly crystalline perovskite absorbers with low defect-state densities minimizing nonradiative recombination losses are a critical prerequisite for fabricating state-of-the-art photovoltaics.Here,we use a tartaric acid(TA)molecule with two carboxyl and two hydroxyl groups as an additive to improve the performance and stability of the device simultaneously.The strong carboxyl-Pb2+coordination slows nucleation kinetics and passivates Pb-related traps,whereas hydroxyl-I-hydrogen bonding can modulate grain growth and stabilize the lattice structure,collectively enabling low-defect-density and high-quality perovskite films.Besides,we also conducted quantitively loss analysis and confirmed that the TA addition effectively reduces trap-assisted non-radiative recombination.Consequently,the champion efficiency of the n-i-p structure is up to 24.77% with outstanding operational and humidity stability.Remarkably,in the triple-cation perovskite system,the incorporation of the TA additive similarly enabled the fabrication of high-quality films,ultimately yielding a p-i-n configuration with a champion efficiency of 26.11%.
文摘Songji Ancient Town in Yongchuan District,Chongqing,is a famous historical and cultural town in China and a national AAAA-level tourist attraction.In recent years,combining its unique historical and cultural heritage,the scenic area has developed research travel products themed on intangible cultural heritage and red tourism,attracting students from across the country to experience it.On the other hand,in the context of the deepening of the“double reduction”policy and the concept of a“high-quality education system,”the educational connotation of Songji Ancient Town’s research products is constantly enriching.Based on this,this article will combine the RMP theory to explore strategies for improving satisfaction with Yongchuan District’s“Songji Ancient Town Research Products”under a high-quality education system,to promote the development of the scenic area’s research experience projects and overall tourism service levels.
文摘Standardized datasets are foundational to healthcare informatization by enhancing data quality and unleashing the value of data elements.Using bibliometrics and content analysis,this study examines China's healthcare dataset standards from 2011 to 2025.It analyzes their evolution across types,applications,institutions,and themes,highlighting key achievements including substantial growth in quantity,optimized typology,expansion into innovative application scenarios such as health decision support,and broadened institutional involvement.The study also identifies critical challenges,including imbalanced development,insufficient quality control,and a lack of essential metadata—such as authoritative data element mappings and privacy annotations—which hampers the delivery of intelligent services.To address these challenges,the study proposes a multi-faceted strategy focused on optimizing the standard system's architecture,enhancing quality and implementation,and advancing both data governance—through authoritative tracing and privacy protection—and intelligent service provision.These strategies aim to promote the application of dataset standards,thereby fostering and securing the development of new productive forces in healthcare.
基金General Project of Philosophy and Social Sciences Research in Universities of Jiangsu Province,2024(2024SJYB1650).
文摘Under the background of"Digital Commerce for Rural Vitalization",rural E-commerce has experienced rapid development.However,agricultural products like strawberries,often produced by small-scale,fragmented,and less competitive individual farmers,struggle to meet the compliance and scalability demands of E-commerce,thereby constraining high-quality local economic development.Aiming to address this issue,this paper,guided by relevant policies and strategies,employs case analysis and logical deduction to explore the industrialization path of the"Cooperative+E-commerce"model for the strawberry industry.The research finds that by optimizing the cooperative's organizational structure,implementing multi-channel E-commerce strategies,upgrading the supply chain(including cold chain and quality traceability),and engaging in collaborative brand building,a robust industrial system can be formed.Supplemented by benefit evaluation,policy support,and regulatory oversight,this system can effectively bridge small-scale production with the broader market.This study concludes that this pathway can enhance the added value of the strawberry industry,increase farmer incomes,and provide practical insights for promoting high-quality local economic development.
基金supported by the Natural Science Basic Research Program of Shaanxi(Program No.2024JC-YBMS-026).
文摘When dealing with imbalanced datasets,the traditional support vectormachine(SVM)tends to produce a classification hyperplane that is biased towards the majority class,which exhibits poor robustness.This paper proposes a high-performance classification algorithm specifically designed for imbalanced datasets.The proposed method first uses a biased second-order cone programming support vectormachine(B-SOCP-SVM)to identify the support vectors(SVs)and non-support vectors(NSVs)in the imbalanced data.Then,it applies the synthetic minority over-sampling technique(SV-SMOTE)to oversample the support vectors of the minority class and uses the random under-sampling technique(NSV-RUS)multiple times to undersample the non-support vectors of the majority class.Combining the above-obtained minority class data set withmultiple majority class datasets can obtainmultiple new balanced data sets.Finally,SOCP-SVM is used to classify each data set,and the final result is obtained through the integrated algorithm.Experimental results demonstrate that the proposed method performs excellently on imbalanced datasets.
