The study determined the roles of agricultural extension in hybrid rice technology decision-making process by extension agents,Nay Pyi Taw,Myanmar.The specific objectives were:to study personal characteristics of agri...The study determined the roles of agricultural extension in hybrid rice technology decision-making process by extension agents,Nay Pyi Taw,Myanmar.The specific objectives were:to study personal characteristics of agricultural extension agents,experiences and their roles,to identify extension agents’opinion on hybrid rice technology decision-making process,and to determine relationship between the roles of agricultural extension agents and decision-making process of hybrid rice production.One hundred and eight extension agents were collected who were working in Department of Agriculture,Nay Pyi Taw area and surveyed and interviewed by questionnaires.The study revealed that majority of agricultural extension agents(65.7%)were female staffs and most of extension agents(40.7%)were under 30 years as young staffs.Majority of extension agents(81.5%)were educated only Agri-Diploma.More than half(54.6%)had one to five-year experiences in employment and 58.3%had no hybrid rice training experience and source of information regarding the hybrid rice production was received 63.9%from Department of Agriculture(DOA).Study found that there was highly significant relationship between most of the roles of agricultural extension agents and hybrid rice technology decision-making process of stages 4 and 5.And then most of the extension agents’roles singnificantly related with stage 2 except role of conducting introduction of hybrid seeds and distribution through by Seed Co.Ltds which was highly significant.Beside,most of the roles of extension agents significantly related with stage 3.However stages 1 and 6 were no singnificantly related.Finally above all,a well structure seed business,Good Agricultural Practices and farm level mechanization and quality extension service are very important to increase the adoption of hybrid rice in Myanmar.展开更多
Background:Despite the promise shown by large language models(LLMs)for standardized tasks,their multidimensional performance in real-world oncology decision-making remains unevaluated.This study aims to introduce a fr...Background:Despite the promise shown by large language models(LLMs)for standardized tasks,their multidimensional performance in real-world oncology decision-making remains unevaluated.This study aims to introduce a framework for evaluating LLMs and physician decisions in challenging lung cancer cases.Methods:We curated 50 challenging lung cancer cases(25 local and 25 published)classified as complex,rare,or refractory.Blinded three-dimensional,five-point Likert evaluations(1–5 for comprehensiveness,specificity,and readability)compared standalone LLMs(DeepSeek R1,Claude 3.5,Gemini 1.5,and GPT-4o),physicians by experience level(junior,intermediate,and senior),and AI-assisted juniors;intergroup differences and augmentation effects were analyzed statistically.Results:Of 50 challenging cases(18 complex,17 rare,and 15 refractory)rated by three experts,DeepSeek R1 achieved scores of 3.95±0.33,3.71±0.53,and 4.26±0.18 for comprehensiveness,specificity,and readability,respectively,positioning it between intermediate(3.68,3.68,3.75)and senior(4.50,4.64,4.53)physicians.GPT-4o and Claude 3.5 reached intermediate physician–level comprehensiveness(3.76±0.39,3.60±0.39)but junior-to-intermediate physician–level specificity(3.39±0.39,3.39±0.49).All LLMs scored higher on rare cases than intermediate physicians but fell below junior physicians in refractory-case specificity.AIassisted junior physicians showed marked gains in rare cases,with comprehensiveness rising from 2.32 to 4.29(84.8%),specificity from 2.24 to 4.26(90.8%),and readability from 2.76 to 4.59(66.0%),while specificity declined by 3.2%(3.17 to 3.07)in refractory cases.Error analysis showed complementary strengths,with physicians demonstrating reasoning stability and LLMs excelling in knowledge updating and risk management.Conclusions:LLMs performed variably in clinical decision-making tasks depending on case type,performing better in rare cases and worse in refractory cases requiring longitudinal reasoning.Complementary strengths between LLMs and physicians support case-and task-tailored human–AI collaboration.展开更多
Environmental problems are intensifying due to the rapid growth of the population,industry,and urban infrastructure.This expansion has resulted in increased air and water pollution,intensified urban heat island effect...Environmental problems are intensifying due to the rapid growth of the population,industry,and urban infrastructure.This expansion has resulted in increased air and water pollution,intensified urban heat island effects,and greater runoff from parks and other green spaces.Addressing these challenges requires prioritizing green infrastructure and other sustainable urban development strategies.This study introduces a novel Integrated Decision Support System that combines Pythagorean Fuzzy Sets with the Advanced Alternative Ranking Order Method allowing for Two-Step Normalization(AAROM-TN),enhanced by a dual weighting strategy.The weighting approach integrates the Criteria Importance Through Intercriteria Correlation(CRITIC)method with the Criteria Importance through Means and Standard Deviation(CIMAS)technique.The originality of the proposed framework lies in its ability to objectively quantify criteria importance using CRITIC,incorporate decision-makers’preferences through CIMAS,and capture the uncertainty and hesitation inherent in human judgment via Pythagorean Fuzzy Sets.A case study evaluating green infrastructure alternatives in metropolitan regions demonstrates the applicability and effectiveness of the framework.A sensitivity analysis is conducted to examine how variations in criteria weights affect the rankings and to evaluate the robustness of the results.Furthermore,a comparative analysis highlights the practical and financial implications of each alternative by assessing their respective strengths and weaknesses.展开更多
With the rapid development of artificial intelligence,intelligent air combat maneuver decision-making(ACMD)has garnered global attention.Although deep reinforcement learning provides a promising approach to ACMD,exist...With the rapid development of artificial intelligence,intelligent air combat maneuver decision-making(ACMD)has garnered global attention.Although deep reinforcement learning provides a promising approach to ACMD,existing methods often suffer from rigid reward functions and limited adaptability to evolving adversarial strategies.Moreover,most research assumes open airspace,overlooking the influence of potential obstacles.In this paper,we address one-on-one within-visual-range ACMD in obstructed environments,and propose an improved Soft Actor-Critic(SAC)algorithm trained under a curriculum self-play framework.A maneuver strategy mirroring inference module is integrated to estimate each other's likely positions when visual obstruction occurs.By leveraging curriculum learning to guide progressive experience accumulation and self-play for adversarial evolution,our method enhances both training efficiency and tactical diversity.We further integrate an attention mechanism that dynamically adjusts the weights of sub-rewards,enabling the learned policy to adapt to rapidly changing air combat situations.Numerical simulations demonstrate that our enhanced SAC converges more quickly and achieves higher win rates than other baseline methods.An animation is available at bilibili.com/video/BV1BHVszHE98 for better illustration.展开更多
With the increasing complexity of industrial automation,planetary gearboxes play a vital role in largescale equipment transmission systems,directly impacting operational efficiency and safety.Traditional maintenance s...With the increasing complexity of industrial automation,planetary gearboxes play a vital role in largescale equipment transmission systems,directly impacting operational efficiency and safety.Traditional maintenance strategies often struggle to accurately predict the degradation process of equipment,leading to excessive maintenance costs or potential failure risks.However,existing prediction methods based on statistical models are difficult to adapt to nonlinear degradation processes.To address these challenges,this study proposes a novel condition-based maintenance framework for planetary gearboxes.A comprehensive full-lifecycle degradation experiment was conducted to collect raw vibration signals,which were then processed using a temporal convolutional network autoencoder with multi-scale perception capability to extract deep temporal degradation features,enabling the collaborative extraction of longperiod meshing frequencies and short-term impact features from the vibration signals.Kernel principal component analysis was employed to fuse and normalize these features,enhancing the characterization of degradation progression.A nonlinear Wiener process was used to model the degradation trajectory,with a threshold decay function introduced to dynamically adjust maintenance strategies,and model parameters optimized through maximum likelihood estimation.Meanwhile,the maintenance strategy was optimized to minimize costs per unit time,determining the optimal maintenance timing and preventive maintenance threshold.The comprehensive indicator of degradation trends extracted by this method reaches 0.756,which is 41.2%higher than that of traditional time-domain features;the dynamic threshold strategy reduces the maintenance cost per unit time to 55.56,which is 8.9%better than that of the static threshold optimization.Experimental results demonstrate significant reductions in maintenance costs while enhancing system reliability and safety.This study realizes the organic integration of deep learning and reliability theory in the maintenance of planetary gearboxes,provides an interpretable solution for the predictive maintenance of complex mechanical systems,and promotes the development of condition-based maintenance strategies for planetary gearboxes.展开更多
With the accelerating aging process of China’s population,the demand for community elderly care services has shown diversified and personalized characteristics.However,problems such as insufficient total care service...With the accelerating aging process of China’s population,the demand for community elderly care services has shown diversified and personalized characteristics.However,problems such as insufficient total care service resources,uneven distribution,and prominent supply-demand contradictions have seriously affected service quality.Big data technology,with core advantages including data collection,analysis and mining,and accurate prediction,provides a new solution for the allocation of community elderly care service resources.This paper systematically studies the application value of big data technology in the allocation of community elderly care service resources from three aspects:resource allocation efficiency,service accuracy,and management intelligence.Combined with practical needs,it proposes optimal allocation strategies such as building a big data analysis platform and accurately grasping the elderly’s care needs,striving to provide operable path references for the construction of community elderly care service systems,promoting the early realization of the elderly care service goal of“adequate support and proper care for the elderly”,and boosting the high-quality development of China’s elderly care service industry.展开更多
In response to the Ministry of Education’s requirements for building distinctive model software schools,Software College of Northeastern University and Shenzhen Kingdom Technology Co.,Ltd.jointly developed the specia...In response to the Ministry of Education’s requirements for building distinctive model software schools,Software College of Northeastern University and Shenzhen Kingdom Technology Co.,Ltd.jointly developed the specialized course“Application and Practice of RPA Technology in FinTech”.Addressing pain points in financial digital transformation,the course integrates robotic process automation(RPA)principles,financial domain knowledge,and RPA platform practice into a“technology-scenario-capability”trinity teaching system.Through 64 credit hours of integrated theory and practice,it covers RPA fundamentals,financial applications,RPA operations(including core skills like Web/desktop automation),and AI integration,cultivating students’ability to design and implement automated financial workflows.It innovatively features a RPA simulation platform,30+financial case studies,and modular task resources,creating a“teacher-machine-student”interactive model.Practice demonstrates the course effectively enhances students’integration of technical application and business acumen,providing a scalable paradigm for cultivating interdisciplinary FinTech talent.展开更多
The moment a media delegation from the Republic of the Congo arrived at the Othello Kitchenware Museum on 18 November 2025,they were greeted with a vivid show of Guangdong’s industrial strength.Standing before them w...The moment a media delegation from the Republic of the Congo arrived at the Othello Kitchenware Museum on 18 November 2025,they were greeted with a vivid show of Guangdong’s industrial strength.Standing before them was not a typical exhibition hall,but a building shaped like a gleaming stainless-steel cooking pot.展开更多
Jeanologia celebrated its 30th anniversary reaffirming the mission it was born with in 1994,to transform the textile industry into a more sustainable,efficient,and human-centered sector.Three decades later,that vision...Jeanologia celebrated its 30th anniversary reaffirming the mission it was born with in 1994,to transform the textile industry into a more sustainable,efficient,and human-centered sector.Three decades later,that vision has become a global reality.Today,more than 40 percent of all jeans produced worldwide are made using technologies developed by the Valencia-based company.What started in a small laboratory in Valencia(Spain),with a pioneering team and a visionary idea,has evolved into a global benchmark in sustainable innovation.From the beginning,Jeanologia believed in technology as a driver of change,introducing solutions that eliminated harmful practices and opened the door to a new,cleaner way of making garments.展开更多
Rare earth(RE)Y-type zeolite was synthesized in situ by acidic co-hydrolysis route and hydrothermal method.The key process parameters were optimized based on the RE utilization rate.The effect of inducing a rotating p...Rare earth(RE)Y-type zeolite was synthesized in situ by acidic co-hydrolysis route and hydrothermal method.The key process parameters were optimized based on the RE utilization rate.The effect of inducing a rotating packed bed(RPB)in premixing and crystallization on crystallinity and RE utilization rate was further investigated.The results indicate that lanthanide(La)cations are successfully introduced into the sodalite cage of Y-type zeolite.The optimized conditions are that the molar ratio of Si/La is 150,premixing for 5 h,crystallization at 90℃ for 18 h,and calcination at 550℃ for 3.5 h.At this stage,the RE utilization rate reaches 74.5%.Compared with the conventional stirred tank reactor(STR),RPB can effectively shorten the premixing time and crystallization time by 4.3 h and 6 h,improve the crystallinity by 23%and RE utilization rate by 7.5%.The RE utilization rate is more than 80%by RPB,surpassing the effectiveness of using the one-exchange one-calcination process in the traditional liquid ion exchange process.It is expected to provide a reference for the in-situ efficient and green synthesis of RE zeolite.展开更多
Aiming at the problems of lagging curriculum,weak practice,and single evaluation in the cultivation of HarmonyOS Development talents,this study constructs a“teacher-machine-student”ternary interactive teaching model...Aiming at the problems of lagging curriculum,weak practice,and single evaluation in the cultivation of HarmonyOS Development talents,this study constructs a“teacher-machine-student”ternary interactive teaching model based on the Congyou platform.Through the building block curriculum system,the HarmonyOS technology stack is decoupled into dynamic capability units,and a multi-disciplinary cross-case library is jointly built with Huawei,which significantly improves the synchronization of teaching content and industrial technology.This paper innovatively designs an AI collaborative teaching system,which employs knowledge graphs to plan learning paths,utilizes virtual equipment clusters to simulate development environments,and establishes a“diagnosis-feedback-enhancement”closed loop through AI-based review,thereby effectively improving students’development efficiency and code reuse rate.A three-dimensional evaluation model integrating task outcomes,process performance,and innovation is constructed,incorporating indicators such as code standardization and an innovation index to strengthen the cultivation of engineering thinking and innovative ability.Furthermore,a data-driven support platform is built to generate student competency profiles,open up the“credit-competency-certification”pathway,promote the transformation of course achievements into contributions to the Huawei ecosystem,and significantly shorten the job adaptation cycle for graduates.The research results provide a replicable paradigm for the cultivation of domestic operating system talents.展开更多
Given the growing importance of social media in digital rural development, this study systematically investigated the influence pathways of social media use among rural women in China, drawing on the Technology Accept...Given the growing importance of social media in digital rural development, this study systematically investigated the influence pathways of social media use among rural women in China, drawing on the Technology Acceptance Model(TAM). Employing quantitative research methods, the study conducted empirical tests based on 367 valid questionnaires using Partial Least Squares Structural Equation Modeling(PLS-SEM) via SmartPLS 4.0 software. Results indicate that significant associations exist between perceived ease of use, perceived usefulness, attitudes toward use, behavioral intention, and actual usage behavior. Specifically, the study finds that rural women's perceived ease of use of social media has a significant and positive influence on both perceived usefulness and attitudes toward use. Perceived usefulness further significantly promotes attitudes toward use and behavioral intention. Moreover, positive attitudes toward usage and strong behavioral intentions were effectively converted into actual social media usage behaviors. This study not only validates the applicability and explanatory power of the TAM model in understanding the digital behavior of Chinese rural women but also provides quantitative evidence for how social media enhances their “digital visibility.” These findings offer practical insights for governments and platform providers to optimize user experiences and strengthen digital skills training. Despite its limitations, including a cross-sectional design and a regional sample, this research holds significant theoretical and practical implications.展开更多
This study analyzes the evolution of China's green technology innovation cooperation network from 2011 to 2020,utilizing green patent application data.Employing a Spatial Durbin Model(SDM),we scrutinized the netwo...This study analyzes the evolution of China's green technology innovation cooperation network from 2011 to 2020,utilizing green patent application data.Employing a Spatial Durbin Model(SDM),we scrutinized the network's influence on urban carbon emissions,utilizing panel data encompassing 323 city nodes.Results show network expansion and a shift in central nodes from eastern coastal areas to interior cities,with Beijing,Shenzhen,Nanjing,and Shanghai consistently acting as key innovation hubs.A core-periphery structure emerged,clustering cities into high-and low-cooperation clusters.Core cities,particularly Beijing,which gain informational advantages by bridging non-overlapping nodes and exhibit distinct characteristics in terms of the structural hole indexes,reflecting their multifaceted roles within the network.SDM analysis indicates that the green technology innovation cooperation network has a significant positive impact on urban carbon reduction efforts.Specifically,degree centrality,closeness centrality,effective size,efficiency,and hierarchy of node cities exhibit a negative correlation with carbon emissions,suggesting that higher centrality and efficiency within the network correlate with lower emissions.Conversely,betweenness centrality and constraint have a positive impact on emissions,indicating that cities that act as bridges in the network may paradoxically contribute to higher emissions.Moreover,the network's influence on carbon emissions is nuanced across different green technology sectors.Cooperation in areas such as waste management,alternative energy production,energy conservation,agriculture and forestry,and transportation is found to have a more substantial impact on carbon reduction than cooperation in nuclear power,and administrative,regulatory,and design fields.展开更多
Against the backdrop of integrated development between technical education and higher vocational education,the teaching of Chinese Medicine Processing Technology courses faces new opportunities and challenges.This pap...Against the backdrop of integrated development between technical education and higher vocational education,the teaching of Chinese Medicine Processing Technology courses faces new opportunities and challenges.This paper analyzes the existing problems in the current teaching of Chinese Medicine Processing Technology courses,discusses the necessity of reforming the teaching model under the context of integration,and proposes the construction of a"Dual-Capability Progression,Six-Dimensional Empowerment"teaching model.The aim is to enhance the teaching quality of Chinese Medicine Processing Technology courses and cultivate high-quality skilled talents in Chinese medicine processing who can meet industry demands.展开更多
Background:With the rapid development of modern emerging technologies,the ethical dilemmas and social controversies triggered by scientific and technological activities have become increasingly prominent.How to guide ...Background:With the rapid development of modern emerging technologies,the ethical dilemmas and social controversies triggered by scientific and technological activities have become increasingly prominent.How to guide technology for good and prevent and control technological risks has become an important issue of global concern.Research on science and technology ethics is dedicated to integrating ethical theories into governance practices and constructing ethical models that adapt to the development of the times.Methods:This article systematically reviews the six core approaches of scientific and technological ethics thought,including technological autonomy and political philosophy criticism,responsibility ethics and intergenerational obligations,technological intermediation and the integration of life and the world,ethical principles and normative frameworks,participatory governance and ethical practice innovation,as well as domain-specific ethical norms,thereby constructing an ethical analysis framework applicable to medical technology risks.And cross-analysis was conducted by taking medical events such as gene editing and xenotransplantation as examples.Results:Research shows that a single ethical approach has limitations in addressing complex medical ethical challenges,while the six approaches are complementary and synergistic.By criticizing technological autonomy,establishing a responsibility ethics orientation,setting the bottom line of ethical principles,promoting participatory governance,formulating domain norms,and continuously reflecting on the intermediary nature of technology,a multi-level and dynamically adaptive governance system for scientific and technological ethics can be constructed.Conclusion:The key to addressing contemporary medical ethics challenges lies in the comprehensive application of science and technology ethics theories and the integration of ethical considerations throughout the entire process of scientific and technological research and development.In the future,a governance framework that adapts to the development of new technologies should be established to promote cross-cultural and cross-disciplinary ethical dialogue and public participation,ensuring that scientific and technological innovation always serves the dignity of human life and overall well-being.展开更多
Detecting biomarkers in body fluids by optical lateral flow immune assay(LFIA) technology provides rapid access to disease information for early diagnosis.LFIA is based on an antigen-antibody reaction and is rapidly b...Detecting biomarkers in body fluids by optical lateral flow immune assay(LFIA) technology provides rapid access to disease information for early diagnosis.LFIA is based on an antigen-antibody reaction and is rapidly becoming the preferred choice of physicians and patients for point-of-care testing due to its simplicity,cost-effectiveness,and rapid detection.Observing the optical signal change from the colloidal gold of the traditional LFIA strip has been widely applied for various biomarkers detection in body fluids.Despite the significant progress,rapid real-time detection of color changes in the colloidal gold by the naked eye still faces many limitations,such as large errors and the inability to quantify and accurately detect.New optical LFIA strip technology has emerged in recent years to extend its application scenarios for achieving quantitative detection such as fluorescence,afterglow,and chemiluminescence.Herein,we summarized the development of optical LFIA technology from single to hyphenated optical signals for biomarkers detection in body fluids from invasive and non-invasive sources.Moreover,the challenge and outlook of optical LFIA strip technology are highlighted to inspire the designing of next-generation diagnostic platforms.展开更多
Whole Slide Imaging (WSI) technology, as a revolutionary digital technology in the field of pathology, is gradually changing the traditional clinical pathological diagnosis model. By converting traditional glass patho...Whole Slide Imaging (WSI) technology, as a revolutionary digital technology in the field of pathology, is gradually changing the traditional clinical pathological diagnosis model. By converting traditional glass pathological sections into complete digital images through high-resolution scanning, it provides a new method for pathological diagnosis. Based on this, this paper studies the application of WSI technology in clinical pathological diagnosis, elaborates on its application value, analyzes the current application status, and proposes corresponding application countermeasures, aiming to provide reference for the standardized and popularized development of this technology in clinical pathological diagnosis.展开更多
This year marks the third anniversary of China’s Global Civilisation Initiative.Over the past three years,cultural exchange and mutual learning have flourished across continents,from Asia to Africa.At the archaeologi...This year marks the third anniversary of China’s Global Civilisation Initiative.Over the past three years,cultural exchange and mutual learning have flourished across continents,from Asia to Africa.At the archaeological site of Memphis in Egypt,Chinese-developed digital technology is now creating“annual rings”of memory for a civilisation dating back to the pharaohs.展开更多
Defence Technology(ISSN 2214-9147(O);2096-3459(P)),sponsored by China Ordnance Society,is published monthly and aims to become one of the well-known comprehensive journals in the world,which reports on the breakthroug...Defence Technology(ISSN 2214-9147(O);2096-3459(P)),sponsored by China Ordnance Society,is published monthly and aims to become one of the well-known comprehensive journals in the world,which reports on the breakthroughs in defence technology by building up an international academic exchange platform for the defence technology related research.It publishes original research papers having direct bearing on defence,with a balanced coverage on analytical,experimental,numerical simulation and applied investigations.It covers various disciplines of science,technology and engineering.展开更多
The Sn−2Al filler metal was utilized to bond W90 tungsten heavy alloys by the ultrasonic-assisted coating technology in atmospheric environment at 250℃.The effects of ultrasonic power and ultrasonic time on microstru...The Sn−2Al filler metal was utilized to bond W90 tungsten heavy alloys by the ultrasonic-assisted coating technology in atmospheric environment at 250℃.The effects of ultrasonic power and ultrasonic time on microstructure and interfacial strength of Sn−2Al/W90 interface were investigated.The ultrasound improved the wettability of Sn−2Al filler metal on W90 surface.As the ultrasonic power increased and ultrasonic time increased,the size of Al phase in seam decreased.The maximum value of Sn−2Al/W90 interfacial strength reached 30.1 MPa.Based on the acoustic pressure simulation and bubble dynamics,the intensity of cavitation effect was proportional to ultrasonic power.The generated high temperature and high pressure by cavitation effect reached 83799.6 K and 1.26×10^(14) Pa,respectively.展开更多
文摘The study determined the roles of agricultural extension in hybrid rice technology decision-making process by extension agents,Nay Pyi Taw,Myanmar.The specific objectives were:to study personal characteristics of agricultural extension agents,experiences and their roles,to identify extension agents’opinion on hybrid rice technology decision-making process,and to determine relationship between the roles of agricultural extension agents and decision-making process of hybrid rice production.One hundred and eight extension agents were collected who were working in Department of Agriculture,Nay Pyi Taw area and surveyed and interviewed by questionnaires.The study revealed that majority of agricultural extension agents(65.7%)were female staffs and most of extension agents(40.7%)were under 30 years as young staffs.Majority of extension agents(81.5%)were educated only Agri-Diploma.More than half(54.6%)had one to five-year experiences in employment and 58.3%had no hybrid rice training experience and source of information regarding the hybrid rice production was received 63.9%from Department of Agriculture(DOA).Study found that there was highly significant relationship between most of the roles of agricultural extension agents and hybrid rice technology decision-making process of stages 4 and 5.And then most of the extension agents’roles singnificantly related with stage 2 except role of conducting introduction of hybrid seeds and distribution through by Seed Co.Ltds which was highly significant.Beside,most of the roles of extension agents significantly related with stage 3.However stages 1 and 6 were no singnificantly related.Finally above all,a well structure seed business,Good Agricultural Practices and farm level mechanization and quality extension service are very important to increase the adoption of hybrid rice in Myanmar.
文摘Background:Despite the promise shown by large language models(LLMs)for standardized tasks,their multidimensional performance in real-world oncology decision-making remains unevaluated.This study aims to introduce a framework for evaluating LLMs and physician decisions in challenging lung cancer cases.Methods:We curated 50 challenging lung cancer cases(25 local and 25 published)classified as complex,rare,or refractory.Blinded three-dimensional,five-point Likert evaluations(1–5 for comprehensiveness,specificity,and readability)compared standalone LLMs(DeepSeek R1,Claude 3.5,Gemini 1.5,and GPT-4o),physicians by experience level(junior,intermediate,and senior),and AI-assisted juniors;intergroup differences and augmentation effects were analyzed statistically.Results:Of 50 challenging cases(18 complex,17 rare,and 15 refractory)rated by three experts,DeepSeek R1 achieved scores of 3.95±0.33,3.71±0.53,and 4.26±0.18 for comprehensiveness,specificity,and readability,respectively,positioning it between intermediate(3.68,3.68,3.75)and senior(4.50,4.64,4.53)physicians.GPT-4o and Claude 3.5 reached intermediate physician–level comprehensiveness(3.76±0.39,3.60±0.39)but junior-to-intermediate physician–level specificity(3.39±0.39,3.39±0.49).All LLMs scored higher on rare cases than intermediate physicians but fell below junior physicians in refractory-case specificity.AIassisted junior physicians showed marked gains in rare cases,with comprehensiveness rising from 2.32 to 4.29(84.8%),specificity from 2.24 to 4.26(90.8%),and readability from 2.76 to 4.59(66.0%),while specificity declined by 3.2%(3.17 to 3.07)in refractory cases.Error analysis showed complementary strengths,with physicians demonstrating reasoning stability and LLMs excelling in knowledge updating and risk management.Conclusions:LLMs performed variably in clinical decision-making tasks depending on case type,performing better in rare cases and worse in refractory cases requiring longitudinal reasoning.Complementary strengths between LLMs and physicians support case-and task-tailored human–AI collaboration.
基金supported by the Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2026R259)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.Ashit Kumar Dutta would like to thank AlMaarefa University for supporting this research under project number MHIRSP2025017.
文摘Environmental problems are intensifying due to the rapid growth of the population,industry,and urban infrastructure.This expansion has resulted in increased air and water pollution,intensified urban heat island effects,and greater runoff from parks and other green spaces.Addressing these challenges requires prioritizing green infrastructure and other sustainable urban development strategies.This study introduces a novel Integrated Decision Support System that combines Pythagorean Fuzzy Sets with the Advanced Alternative Ranking Order Method allowing for Two-Step Normalization(AAROM-TN),enhanced by a dual weighting strategy.The weighting approach integrates the Criteria Importance Through Intercriteria Correlation(CRITIC)method with the Criteria Importance through Means and Standard Deviation(CIMAS)technique.The originality of the proposed framework lies in its ability to objectively quantify criteria importance using CRITIC,incorporate decision-makers’preferences through CIMAS,and capture the uncertainty and hesitation inherent in human judgment via Pythagorean Fuzzy Sets.A case study evaluating green infrastructure alternatives in metropolitan regions demonstrates the applicability and effectiveness of the framework.A sensitivity analysis is conducted to examine how variations in criteria weights affect the rankings and to evaluate the robustness of the results.Furthermore,a comparative analysis highlights the practical and financial implications of each alternative by assessing their respective strengths and weaknesses.
基金support of the National Key Research and Development Plan(No.2021YFB3302501)the financial support of the National Science Foundation of China(No.12161076)the financial support of the Fundamental Research Funds for the Central Universities(No.DUT25GF207).
文摘With the rapid development of artificial intelligence,intelligent air combat maneuver decision-making(ACMD)has garnered global attention.Although deep reinforcement learning provides a promising approach to ACMD,existing methods often suffer from rigid reward functions and limited adaptability to evolving adversarial strategies.Moreover,most research assumes open airspace,overlooking the influence of potential obstacles.In this paper,we address one-on-one within-visual-range ACMD in obstructed environments,and propose an improved Soft Actor-Critic(SAC)algorithm trained under a curriculum self-play framework.A maneuver strategy mirroring inference module is integrated to estimate each other's likely positions when visual obstruction occurs.By leveraging curriculum learning to guide progressive experience accumulation and self-play for adversarial evolution,our method enhances both training efficiency and tactical diversity.We further integrate an attention mechanism that dynamically adjusts the weights of sub-rewards,enabling the learned policy to adapt to rapidly changing air combat situations.Numerical simulations demonstrate that our enhanced SAC converges more quickly and achieves higher win rates than other baseline methods.An animation is available at bilibili.com/video/BV1BHVszHE98 for better illustration.
基金funded by scientific research projects under Grant JY2024B011.
文摘With the increasing complexity of industrial automation,planetary gearboxes play a vital role in largescale equipment transmission systems,directly impacting operational efficiency and safety.Traditional maintenance strategies often struggle to accurately predict the degradation process of equipment,leading to excessive maintenance costs or potential failure risks.However,existing prediction methods based on statistical models are difficult to adapt to nonlinear degradation processes.To address these challenges,this study proposes a novel condition-based maintenance framework for planetary gearboxes.A comprehensive full-lifecycle degradation experiment was conducted to collect raw vibration signals,which were then processed using a temporal convolutional network autoencoder with multi-scale perception capability to extract deep temporal degradation features,enabling the collaborative extraction of longperiod meshing frequencies and short-term impact features from the vibration signals.Kernel principal component analysis was employed to fuse and normalize these features,enhancing the characterization of degradation progression.A nonlinear Wiener process was used to model the degradation trajectory,with a threshold decay function introduced to dynamically adjust maintenance strategies,and model parameters optimized through maximum likelihood estimation.Meanwhile,the maintenance strategy was optimized to minimize costs per unit time,determining the optimal maintenance timing and preventive maintenance threshold.The comprehensive indicator of degradation trends extracted by this method reaches 0.756,which is 41.2%higher than that of traditional time-domain features;the dynamic threshold strategy reduces the maintenance cost per unit time to 55.56,which is 8.9%better than that of the static threshold optimization.Experimental results demonstrate significant reductions in maintenance costs while enhancing system reliability and safety.This study realizes the organic integration of deep learning and reliability theory in the maintenance of planetary gearboxes,provides an interpretable solution for the predictive maintenance of complex mechanical systems,and promotes the development of condition-based maintenance strategies for planetary gearboxes.
文摘With the accelerating aging process of China’s population,the demand for community elderly care services has shown diversified and personalized characteristics.However,problems such as insufficient total care service resources,uneven distribution,and prominent supply-demand contradictions have seriously affected service quality.Big data technology,with core advantages including data collection,analysis and mining,and accurate prediction,provides a new solution for the allocation of community elderly care service resources.This paper systematically studies the application value of big data technology in the allocation of community elderly care service resources from three aspects:resource allocation efficiency,service accuracy,and management intelligence.Combined with practical needs,it proposes optimal allocation strategies such as building a big data analysis platform and accurately grasping the elderly’s care needs,striving to provide operable path references for the construction of community elderly care service systems,promoting the early realization of the elderly care service goal of“adequate support and proper care for the elderly”,and boosting the high-quality development of China’s elderly care service industry.
文摘In response to the Ministry of Education’s requirements for building distinctive model software schools,Software College of Northeastern University and Shenzhen Kingdom Technology Co.,Ltd.jointly developed the specialized course“Application and Practice of RPA Technology in FinTech”.Addressing pain points in financial digital transformation,the course integrates robotic process automation(RPA)principles,financial domain knowledge,and RPA platform practice into a“technology-scenario-capability”trinity teaching system.Through 64 credit hours of integrated theory and practice,it covers RPA fundamentals,financial applications,RPA operations(including core skills like Web/desktop automation),and AI integration,cultivating students’ability to design and implement automated financial workflows.It innovatively features a RPA simulation platform,30+financial case studies,and modular task resources,creating a“teacher-machine-student”interactive model.Practice demonstrates the course effectively enhances students’integration of technical application and business acumen,providing a scalable paradigm for cultivating interdisciplinary FinTech talent.
文摘The moment a media delegation from the Republic of the Congo arrived at the Othello Kitchenware Museum on 18 November 2025,they were greeted with a vivid show of Guangdong’s industrial strength.Standing before them was not a typical exhibition hall,but a building shaped like a gleaming stainless-steel cooking pot.
文摘Jeanologia celebrated its 30th anniversary reaffirming the mission it was born with in 1994,to transform the textile industry into a more sustainable,efficient,and human-centered sector.Three decades later,that vision has become a global reality.Today,more than 40 percent of all jeans produced worldwide are made using technologies developed by the Valencia-based company.What started in a small laboratory in Valencia(Spain),with a pioneering team and a visionary idea,has evolved into a global benchmark in sustainable innovation.From the beginning,Jeanologia believed in technology as a driver of change,introducing solutions that eliminated harmful practices and opened the door to a new,cleaner way of making garments.
基金supported by the NationalKey Research and Development Program of China(2023YFA1507701)National Natural Science Foundation of China(U22B6011,22288102)“Announcement and Challenge”Science and Technology Project of Xinjiang Uygur Autonomous Region(XJKJTJBGS-2023).
文摘Rare earth(RE)Y-type zeolite was synthesized in situ by acidic co-hydrolysis route and hydrothermal method.The key process parameters were optimized based on the RE utilization rate.The effect of inducing a rotating packed bed(RPB)in premixing and crystallization on crystallinity and RE utilization rate was further investigated.The results indicate that lanthanide(La)cations are successfully introduced into the sodalite cage of Y-type zeolite.The optimized conditions are that the molar ratio of Si/La is 150,premixing for 5 h,crystallization at 90℃ for 18 h,and calcination at 550℃ for 3.5 h.At this stage,the RE utilization rate reaches 74.5%.Compared with the conventional stirred tank reactor(STR),RPB can effectively shorten the premixing time and crystallization time by 4.3 h and 6 h,improve the crystallinity by 23%and RE utilization rate by 7.5%.The RE utilization rate is more than 80%by RPB,surpassing the effectiveness of using the one-exchange one-calcination process in the traditional liquid ion exchange process.It is expected to provide a reference for the in-situ efficient and green synthesis of RE zeolite.
文摘Aiming at the problems of lagging curriculum,weak practice,and single evaluation in the cultivation of HarmonyOS Development talents,this study constructs a“teacher-machine-student”ternary interactive teaching model based on the Congyou platform.Through the building block curriculum system,the HarmonyOS technology stack is decoupled into dynamic capability units,and a multi-disciplinary cross-case library is jointly built with Huawei,which significantly improves the synchronization of teaching content and industrial technology.This paper innovatively designs an AI collaborative teaching system,which employs knowledge graphs to plan learning paths,utilizes virtual equipment clusters to simulate development environments,and establishes a“diagnosis-feedback-enhancement”closed loop through AI-based review,thereby effectively improving students’development efficiency and code reuse rate.A three-dimensional evaluation model integrating task outcomes,process performance,and innovation is constructed,incorporating indicators such as code standardization and an innovation index to strengthen the cultivation of engineering thinking and innovative ability.Furthermore,a data-driven support platform is built to generate student competency profiles,open up the“credit-competency-certification”pathway,promote the transformation of course achievements into contributions to the Huawei ecosystem,and significantly shorten the job adaptation cycle for graduates.The research results provide a replicable paradigm for the cultivation of domestic operating system talents.
文摘Given the growing importance of social media in digital rural development, this study systematically investigated the influence pathways of social media use among rural women in China, drawing on the Technology Acceptance Model(TAM). Employing quantitative research methods, the study conducted empirical tests based on 367 valid questionnaires using Partial Least Squares Structural Equation Modeling(PLS-SEM) via SmartPLS 4.0 software. Results indicate that significant associations exist between perceived ease of use, perceived usefulness, attitudes toward use, behavioral intention, and actual usage behavior. Specifically, the study finds that rural women's perceived ease of use of social media has a significant and positive influence on both perceived usefulness and attitudes toward use. Perceived usefulness further significantly promotes attitudes toward use and behavioral intention. Moreover, positive attitudes toward usage and strong behavioral intentions were effectively converted into actual social media usage behaviors. This study not only validates the applicability and explanatory power of the TAM model in understanding the digital behavior of Chinese rural women but also provides quantitative evidence for how social media enhances their “digital visibility.” These findings offer practical insights for governments and platform providers to optimize user experiences and strengthen digital skills training. Despite its limitations, including a cross-sectional design and a regional sample, this research holds significant theoretical and practical implications.
基金supported by the National Natural Science Foundation of China(72573020,72103022).
文摘This study analyzes the evolution of China's green technology innovation cooperation network from 2011 to 2020,utilizing green patent application data.Employing a Spatial Durbin Model(SDM),we scrutinized the network's influence on urban carbon emissions,utilizing panel data encompassing 323 city nodes.Results show network expansion and a shift in central nodes from eastern coastal areas to interior cities,with Beijing,Shenzhen,Nanjing,and Shanghai consistently acting as key innovation hubs.A core-periphery structure emerged,clustering cities into high-and low-cooperation clusters.Core cities,particularly Beijing,which gain informational advantages by bridging non-overlapping nodes and exhibit distinct characteristics in terms of the structural hole indexes,reflecting their multifaceted roles within the network.SDM analysis indicates that the green technology innovation cooperation network has a significant positive impact on urban carbon reduction efforts.Specifically,degree centrality,closeness centrality,effective size,efficiency,and hierarchy of node cities exhibit a negative correlation with carbon emissions,suggesting that higher centrality and efficiency within the network correlate with lower emissions.Conversely,betweenness centrality and constraint have a positive impact on emissions,indicating that cities that act as bridges in the network may paradoxically contribute to higher emissions.Moreover,the network's influence on carbon emissions is nuanced across different green technology sectors.Cooperation in areas such as waste management,alternative energy production,energy conservation,agriculture and forestry,and transportation is found to have a more substantial impact on carbon reduction than cooperation in nuclear power,and administrative,regulatory,and design fields.
基金Supported by Scientific Research Fund Project of Yunnan Provincial Department of Education(2025J1950).
文摘Against the backdrop of integrated development between technical education and higher vocational education,the teaching of Chinese Medicine Processing Technology courses faces new opportunities and challenges.This paper analyzes the existing problems in the current teaching of Chinese Medicine Processing Technology courses,discusses the necessity of reforming the teaching model under the context of integration,and proposes the construction of a"Dual-Capability Progression,Six-Dimensional Empowerment"teaching model.The aim is to enhance the teaching quality of Chinese Medicine Processing Technology courses and cultivate high-quality skilled talents in Chinese medicine processing who can meet industry demands.
基金supported by the National Key Research and Development Program(Grant No.2024YFA0917200)the Projects of the Chinese Center for Disease Control and Prevention(Grant No.BB2110240093)World Medical History under the Education Innovation Plan of the University of Science and Technology of China(Grant No.2024YCHX07).
文摘Background:With the rapid development of modern emerging technologies,the ethical dilemmas and social controversies triggered by scientific and technological activities have become increasingly prominent.How to guide technology for good and prevent and control technological risks has become an important issue of global concern.Research on science and technology ethics is dedicated to integrating ethical theories into governance practices and constructing ethical models that adapt to the development of the times.Methods:This article systematically reviews the six core approaches of scientific and technological ethics thought,including technological autonomy and political philosophy criticism,responsibility ethics and intergenerational obligations,technological intermediation and the integration of life and the world,ethical principles and normative frameworks,participatory governance and ethical practice innovation,as well as domain-specific ethical norms,thereby constructing an ethical analysis framework applicable to medical technology risks.And cross-analysis was conducted by taking medical events such as gene editing and xenotransplantation as examples.Results:Research shows that a single ethical approach has limitations in addressing complex medical ethical challenges,while the six approaches are complementary and synergistic.By criticizing technological autonomy,establishing a responsibility ethics orientation,setting the bottom line of ethical principles,promoting participatory governance,formulating domain norms,and continuously reflecting on the intermediary nature of technology,a multi-level and dynamically adaptive governance system for scientific and technological ethics can be constructed.Conclusion:The key to addressing contemporary medical ethics challenges lies in the comprehensive application of science and technology ethics theories and the integration of ethical considerations throughout the entire process of scientific and technological research and development.In the future,a governance framework that adapts to the development of new technologies should be established to promote cross-cultural and cross-disciplinary ethical dialogue and public participation,ensuring that scientific and technological innovation always serves the dignity of human life and overall well-being.
基金supported by the National Natural Science Foundation of China (Nos.22234005,22494632,22404081)the Natural Science Foundation of Jiangsu Province (Nos.BK20222015,BK20240534)。
文摘Detecting biomarkers in body fluids by optical lateral flow immune assay(LFIA) technology provides rapid access to disease information for early diagnosis.LFIA is based on an antigen-antibody reaction and is rapidly becoming the preferred choice of physicians and patients for point-of-care testing due to its simplicity,cost-effectiveness,and rapid detection.Observing the optical signal change from the colloidal gold of the traditional LFIA strip has been widely applied for various biomarkers detection in body fluids.Despite the significant progress,rapid real-time detection of color changes in the colloidal gold by the naked eye still faces many limitations,such as large errors and the inability to quantify and accurately detect.New optical LFIA strip technology has emerged in recent years to extend its application scenarios for achieving quantitative detection such as fluorescence,afterglow,and chemiluminescence.Herein,we summarized the development of optical LFIA technology from single to hyphenated optical signals for biomarkers detection in body fluids from invasive and non-invasive sources.Moreover,the challenge and outlook of optical LFIA strip technology are highlighted to inspire the designing of next-generation diagnostic platforms.
文摘Whole Slide Imaging (WSI) technology, as a revolutionary digital technology in the field of pathology, is gradually changing the traditional clinical pathological diagnosis model. By converting traditional glass pathological sections into complete digital images through high-resolution scanning, it provides a new method for pathological diagnosis. Based on this, this paper studies the application of WSI technology in clinical pathological diagnosis, elaborates on its application value, analyzes the current application status, and proposes corresponding application countermeasures, aiming to provide reference for the standardized and popularized development of this technology in clinical pathological diagnosis.
文摘This year marks the third anniversary of China’s Global Civilisation Initiative.Over the past three years,cultural exchange and mutual learning have flourished across continents,from Asia to Africa.At the archaeological site of Memphis in Egypt,Chinese-developed digital technology is now creating“annual rings”of memory for a civilisation dating back to the pharaohs.
文摘Defence Technology(ISSN 2214-9147(O);2096-3459(P)),sponsored by China Ordnance Society,is published monthly and aims to become one of the well-known comprehensive journals in the world,which reports on the breakthroughs in defence technology by building up an international academic exchange platform for the defence technology related research.It publishes original research papers having direct bearing on defence,with a balanced coverage on analytical,experimental,numerical simulation and applied investigations.It covers various disciplines of science,technology and engineering.
基金supported by the National Natural Science Foundation of China(Nos.52105330,52175307)the Natural Science Foundation of Shandong Province,China(No.ZR2023JQ021)。
文摘The Sn−2Al filler metal was utilized to bond W90 tungsten heavy alloys by the ultrasonic-assisted coating technology in atmospheric environment at 250℃.The effects of ultrasonic power and ultrasonic time on microstructure and interfacial strength of Sn−2Al/W90 interface were investigated.The ultrasound improved the wettability of Sn−2Al filler metal on W90 surface.As the ultrasonic power increased and ultrasonic time increased,the size of Al phase in seam decreased.The maximum value of Sn−2Al/W90 interfacial strength reached 30.1 MPa.Based on the acoustic pressure simulation and bubble dynamics,the intensity of cavitation effect was proportional to ultrasonic power.The generated high temperature and high pressure by cavitation effect reached 83799.6 K and 1.26×10^(14) Pa,respectively.
