The 17 Sustainable Development Goals(SDGs)for 2030,adopted by all United Nations member states in 2015,are facing a range of challenges.Factors such as climate change,regional conflicts and economic recession are havi...The 17 Sustainable Development Goals(SDGs)for 2030,adopted by all United Nations member states in 2015,are facing a range of challenges.Factors such as climate change,regional conflicts and economic recession are having a significant impact,particularly on global poverty governance.As a platform for dialogue,exchange and technical cooperation,the 2025 International Seminar on Global Poverty Reduction Partnerships was held in Beijing on 10 December 2025.展开更多
The ISO Central Secretariat and the ISO/TC 314,Ageing societies,awarded Hou Fei,Cao Lili,and Wang Qi from CNIS for their contributions to ISO 25556:2025,Ageing societies-General requirements and guidelines for ageing-...The ISO Central Secretariat and the ISO/TC 314,Ageing societies,awarded Hou Fei,Cao Lili,and Wang Qi from CNIS for their contributions to ISO 25556:2025,Ageing societies-General requirements and guidelines for ageing-inclusive digital economy.展开更多
Background:Physicalfitness in childhood and adolescence is associated with a variety of health outcomes and is a powerful marker of current and future health.However,inconsistencies in tests and protocols limit interna...Background:Physicalfitness in childhood and adolescence is associated with a variety of health outcomes and is a powerful marker of current and future health.However,inconsistencies in tests and protocols limit international monitoring and surveillance.The objective of the study was to seek international consensus on a proposed,evidence-informed,Youth Fitness International Test(YFIT)battery and protocols for health monitoring and surveillance in children and adolescents aged 618 years.Methods:We conducted an international modified Delphi study to evaluate the level of agreement with a proposed,evidence-based,YFIT of core health-relatedfitness tests and protocols to be used worldwide in 6-to 18-year-olds.This proposal was based on previous European and North American projects that systematically reviewed the existing evidence to identify the most valid,reliable,health-related,safe,and feasiblefitness tests to be used in children and adolescents aged 618 years.We designed a single-panel modified Delphi study and invited 216 experts from all around the world to answer this Delphi survey,of whom one-third are from low-to-middle income countries and one-third are women.Four experts were involved in the piloting of the survey and did not participate in the main Delphi study to avoid bias.We pre-defined an agreement of 80%among the expert participants to achieve consensus.Results:We obtained a high response rate(78%)with a total of 169fitness experts from 50 countries and territories,including 63 women and 61 experts from low-or middle-income countries/territories.Consensus(>85%agreement)was achieved for all proposed tests and protocols,supporting the YFIT battery,which includes weight and height(to compute body mass index as a proxy of body size/composition),the 20-m shuttle run(cardiorespiratoryfitness),handgrip strength,and standing long jump(muscularfitness).Conclusion:This study contributes to standardizingfitness tests and protocols used for research,monitoring,and surveillance across the world,which will allow for future data pooling and the development of international and regional sex-and age-specific reference values,health-related cut-points,and a global picture offitness among children and adolescents.展开更多
The modernization of the Traditional East Medicine industry has increasingly emphasized the role of collaborative innovation across the entire industrial chain.This paper investigates the mechanisms by which experts i...The modernization of the Traditional East Medicine industry has increasingly emphasized the role of collaborative innovation across the entire industrial chain.This paper investigates the mechanisms by which experts in cultivation,processing,R&D,production,and clinical application interact to enhance overall efficiency.By analyzing the bottlenecks in resource allocation,knowledge integration,and institutional design,the study proposes a comprehensive framework of collaborative mechanisms.The results highlight that multi-dimensional collaboration not only improves innovation efficiency but also accelerates the translation of scientific research into industrial outcomes.The findings provide theoretical support and practical implications for improving the synergy of experts in the Traditional East Medicine industry and contribute to the sustainable development of traditional medicine under modern industrial demands.展开更多
Experts and officials shared their insights on poverty reduction cooperation and sustainable development during the 2025 International Seminar on Global Poverty Reduction Partnerships.
The World Journal of Gastroenterology Editorial Board Members are composed of 357 distinguished experts active in the relevant field,distributed in 46 countries/regions,including Italy(66),Japan(53),United States(31),...The World Journal of Gastroenterology Editorial Board Members are composed of 357 distinguished experts active in the relevant field,distributed in 46 countries/regions,including Italy(66),Japan(53),United States(31),China(29),South Korea(16),Spain(15),Australia(13),Greece(12),Brazil(11),Romania(8),Germany(7),India(7),Taiwan(7),United Kingdom(7),Türkiye(7),Hungary(5),Russia(5).展开更多
On the occasion of the New Year,I would like to extend my sincere gratitude and New Year greetings to the experts,scholars,author teams,and readers who have long supported the development of Animal Models and Experime...On the occasion of the New Year,I would like to extend my sincere gratitude and New Year greetings to the experts,scholars,author teams,and readers who have long supported the development of Animal Models and Experimental Medicine(AMEM).Over the past year,we have faced challenges together and achieved breakthroughs in academic influence,internationalization,and fulfilling social respon-sibilities.Looking ahead,we are filled with confidence as we strive to build an important bridge connecting laboratory animal science and technology with academic research.展开更多
Pure Experts Portal是一个基于网页的集成化科研信息系统,是一个全新的展示与发现科研信息的工具。用户可以在其中拥有完善的科研信息档案,也可以在全球范围内方便地查找领域内的专家。结合山东大学PureExpertsPortal的实例,详细阐述...Pure Experts Portal是一个基于网页的集成化科研信息系统,是一个全新的展示与发现科研信息的工具。用户可以在其中拥有完善的科研信息档案,也可以在全球范围内方便地查找领域内的专家。结合山东大学PureExpertsPortal的实例,详细阐述了该系统的功能、核心技术及数据基础,介绍了该系统的实施过程和运行维护的相关工作。展开更多
This paper proposes a deep learning-based 3D LiDAR perception framework designed for applications such as autonomous robots and vehicles.To address the high dependency on large-scale annotated data—an inherent limita...This paper proposes a deep learning-based 3D LiDAR perception framework designed for applications such as autonomous robots and vehicles.To address the high dependency on large-scale annotated data—an inherent limitation of deep learning models—this study introduces a hybrid perception architecture that incorporates expertdriven LiDAR processing techniques into the deep neural network.Traditional 3DLiDAR processingmethods typically remove ground planes and apply distance-or density-based clustering for object detection.In this work,such expert knowledge is encoded as feature-level inputs and fused with the deep network,therebymitigating the data dependency issue of conventional learning-based approaches.Specifically,the proposedmethod combines two expert algorithms—Patchwork++for ground segmentation and DBSCAN for clustering—with a PointPillars-based LiDAR detection network.We design four hybrid versions of the network depending on the stage and method of integrating expert features into the feature map of the deep model.Among these,Version 4 incorporates a modified neck structure in PointPillars and introduces a new Cluster 2D Pseudo-Map Branch that utilizes cluster-level pseudo-images generated from Patchwork++and DBSCAN.This version achieved a+3.88%improvement mean Average Precision(mAP)compared to the baseline PointPillars.The results demonstrate that embedding expert-based perception logic into deep neural architectures can effectively enhance performance and reduce dependency on extensive training datasets,offering a promising direction for robust 3D LiDAR object detection in real-world scenarios.展开更多
Accurate prediction of rockburst intensity levels is crucial for ensuring the safety of deep hard rock engineering construction.This paper introduced an expert system for rockburst intensity level prediction that empl...Accurate prediction of rockburst intensity levels is crucial for ensuring the safety of deep hard rock engineering construction.This paper introduced an expert system for rockburst intensity level prediction that employs machine learning algorithms as the basis for its inference rules.The system comprises four modules:a database,a repository,an inference engine,and an interpreter.A database containing 1114 rockburst cases was used to construct 357 datasets that serve as the repository for the expert system.Additionally,19 types of machine learning algorithms were used to establish 6783 micro-models to construct cognitive rules within the inference engine.By integrating probability theory and marginal analysis,a fuzzy scoring method based on the SoftMax function was developed and applied to the interpreter for rockburst intensity level prediction,effectively restoring the continuity of rockburst characteristics.The research results indicate that ensemble algorithms based on decision trees are more effective in capturing the characteristics of rockburst.Key factors for accurate prediction of rockburst intensity include uniaxial compressive strength,elastic energy index,the maximum principal stress,tangential stress,and their composite indicators.The accuracy of the proposed rockburst intensity level prediction expert system was verified using 20 engineering rockburst cases,with predictions aligning closely with the actual rockburst intensity levels.展开更多
Artificial intelligence(AI)is increasingly recognized as a transformative force in the field of solid organ transplantation.From enhancing donor-recipient matching to predicting clinical risks and tailoring immunosupp...Artificial intelligence(AI)is increasingly recognized as a transformative force in the field of solid organ transplantation.From enhancing donor-recipient matching to predicting clinical risks and tailoring immunosuppressive therapy,AI has the potential to improve both operational efficiency and patient outcomes.Despite these advancements,the perspectives of transplant professionals-those at the forefront of critical decision-making-remain insufficiently explored.To address this gap,this study utilizes a multi-round electronic Delphi approach to gather and analyses insights from global experts involved in organ transplantation.Participants are invited to complete structured surveys capturing demographic data,professional roles,institutional practices,and prior exposure to AI technologies.The survey also explores perceptions of AI’s potential benefits.Quantitative responses are analyzed using descriptive statistics,while open-ended qualitative responses undergo thematic analysis.Preliminary findings indicate a generally positive outlook on AI’s role in enhancing transplantation processes,particularly in areas such as donor matching and post-operative care.These mixed views reflect both optimism and caution among professionals tasked with integrating new technologies into high-stakes clinical workflows.By capturing a wide range of expert opinions,the findings will inform future policy development,regulatory considerations,and institutional readiness frameworks for the integration of AI into organ transplantation.展开更多
According to the Action plan of the Ministry of Environmental Protection, Physical Planning and Construction, the engagement of the implementation of the Directive 2002/91/EC to the Croatian legislation has to be comp...According to the Action plan of the Ministry of Environmental Protection, Physical Planning and Construction, the engagement of the implementation of the Directive 2002/91/EC to the Croatian legislation has to be completed in 2009. The final goal of the Directive is the achievement of energy efficiency in buildings, with emphasis on design of building and building elements, heating and cooling systems and use of renewable energy sources. The presentation of energy performances of the building should be visible in energy label that will classify the building in comparison to energy consumption and must be submitted while buying, selling or renting the building. For the realization of energy certification of the building it is required to provide training for wide number of experts. The production of professional basis is ongoing, where besides the building classification and modification or production of correspondingly technical regulations, are determining the conditions and standards for persons who should provide the certification, as well the method of providing.展开更多
The robotic liver resection(RLR)has been increasingly applied in recent years and its benefits shown in some aspects owing to the technical advancement of robotic surgical system,however,controversies still exist.Base...The robotic liver resection(RLR)has been increasingly applied in recent years and its benefits shown in some aspects owing to the technical advancement of robotic surgical system,however,controversies still exist.Based on the foundation of the previous consensus statement,this new consensus document aimed to update clinical recommendations and provide guidance to improve the outcomes of RLR clinical practice.The guideline steering group and guideline expert group were formed by 29 international experts of liver surgery and evidence-based medicine(EBM).Relevant literature was reviewed and analyzed by the evidence evaluation group.According to the WHO Handbook for Guideline Development,the Guidance Principles of Development and Amendment of the Guidelines for Clinical Diagnosis and Treatment in China 2022,a total of 14 recommendations were generated.Among them were 8 recommendations formulated by the GRADE method,and the remaining 6 recommendations were formulated based on literature review and experts’opinion due to insufficient EBM results.This international experts consensus guideline offered guidance for the safe and effective clinical practice and the research direction of RLR in future.展开更多
Spinal pain(SP)is a common condition that has a major negative impact on a patient’s quality of life.Recent developments in ultrasound-guided injections for the treatment of SP are increasingly being used in clinical...Spinal pain(SP)is a common condition that has a major negative impact on a patient’s quality of life.Recent developments in ultrasound-guided injections for the treatment of SP are increasingly being used in clinical practice.This clinical expert consensus describes the purpose,significance,implementation methods,indications,contraindications,and techniques of ultrasound-guided injections.This consensus offers a practical reference point for physicians to implement successfully ultrasound-guided injections in the treatment of chronic SP.展开更多
Due to people’s increasing dependence on social networks,it is essential to develop a consensus model considering not only their own factors but also the interaction between people.Both external trust relationship am...Due to people’s increasing dependence on social networks,it is essential to develop a consensus model considering not only their own factors but also the interaction between people.Both external trust relationship among experts and the internal reliability of experts are important factors in decision-making.This paper focuses on improving the scientificity and effectiveness of decision-making and presents a consensus model combining trust relationship among experts and expert reliability in social network group decision-making(SN-GDM).A concept named matching degree is proposed to measure expert reliability.Meanwhile,linguistic information is applied to manage the imprecise and vague information.Matching degree is expressed by a 2-tuple linguistic model,and experts’preferences are measured by a probabilistic linguistic term set(PLTS).Subsequently,a hybrid weight is explored to weigh experts’importance in a group.Then a consensus measure is introduced and a feedback mechanism is developed to produce some personalized recommendations with higher group consensus.Finally,a comparative example is provided to prove the scientificity and effectiveness of the proposed consensus model.展开更多
Expert opinions have been used in a variety of fields to identify relevant issues and courses of action. This study surveys experts in forestry and climate change from the Asia–Pacific region to gauge their perspecti...Expert opinions have been used in a variety of fields to identify relevant issues and courses of action. This study surveys experts in forestry and climate change from the Asia–Pacific region to gauge their perspectives on the impacts of climate change and on the challenges faced by forest adaptation in the region, and explores recommendations and initiatives for adapting forests to climate change. There was consensus regarding the impacts of climate change on forest ecosystems and on economic sectors such as agriculture and forestry. Respondents also indicated a lack of public awareness and policy and legislation as challenges to addressing climate change. However, the results indicate differences in opinion between regions on the negative impacts of climate change and in satisfaction with actions taken to address climate change,highlighting the need for locally specific policies and research. The study presents specific recommendations to address issues of most concern, based on subregion and professional affiliation throughout the Asia–Pacific region.The results can be used to improve policy and forest management throughout the region. This research will also provide valuable suggestions on how to apply research findings and management recommendations outside of the AP region. The conclusions should be communicated relative to the level of the research and the target audience,ensuring that scientific findings and management recommendations are effectively communicated to ensure successful implementation of forest adaptation strategies.展开更多
IntroductionMore than 1.0 million patients worldwide are diagnosed with space-occupying lesions in the liver every year, with the number approaching 0.5 million per year in China, and only 20% of the lesions are resec...IntroductionMore than 1.0 million patients worldwide are diagnosed with space-occupying lesions in the liver every year, with the number approaching 0.5 million per year in China, and only 20% of the lesions are resectable Due to a lack of available donors, only a limited number of patients underwent allogeneic liver transplantation, the remaining patients simply receive palliative care. Therefore, discovering new options for treating these patients is a high priority. Liver autotransplantation （LAT） is a surgical technique that adopts liver transplantation skills to radically treat spaceoccupying hepatic lesions, benign or malignant,展开更多
ChatGPT,as an emergent technique,has become a heat throughout the world.Currently,it was not known entirely to the public.To gain knowledge of how experts perceive and experience ChatGPT,a semi-structured interview wa...ChatGPT,as an emergent technique,has become a heat throughout the world.Currently,it was not known entirely to the public.To gain knowledge of how experts perceive and experience ChatGPT,a semi-structured interview was conducted.By doing thematic analysis of their interview reports,it found that the experts construed the chatbot not the same as some media advertised.They didn’t regard it as a threat to their occupation,but as a helper or an assistant both in life and work.Neither did they restrict its use in education or other fields.They viewed the challenges of ChatGPT in a welcomed and positive way.展开更多
A method for solving the winner determination problem （WDP） in multi-attribute procurement auctions is proposed, based on technical and business experts＇ evaluation information. Firstly, on the background of procur...A method for solving the winner determination problem （WDP） in multi-attribute procurement auctions is proposed, based on technical and business experts＇ evaluation information. Firstly, on the background of procurements in China, a multi-attribute pro- curement auction mechanism is presented, where technical and business experts participate in the bid evaluation. Then, the concept of TOPSIS is used to determine the positive and negative ideal points of the WDP according to bid prices, the technical and business experts＇ evaluation information. Further, the closeness coefficient of each bidder （candidate supplier） is obtained by calculating the distances to the positive and negative ideal points. Thus, the winning supplier can be determined according to the closeness coefficients. Finally, a numerical example is used to illustrate the use of the proposed method.展开更多
Mixture of Experts(MoE)regression models are widely studied in statistics and machine learning for modeling heterogeneity in data for regression,clustering and classification.Laplace distribution is one of the most im...Mixture of Experts(MoE)regression models are widely studied in statistics and machine learning for modeling heterogeneity in data for regression,clustering and classification.Laplace distribution is one of the most important statistical tools to analyze thick and tail data.Laplace Mixture of Linear Experts(LMoLE)regression models are based on the Laplace distribution which is more robust.Similar to modelling variance parameter in a homogeneous population,we propose and study a new novel class of models:heteroscedastic Laplace mixture of experts regression models to analyze the heteroscedastic data coming from a heterogeneous population in this paper.The issues of maximum likelihood estimation are addressed.In particular,Minorization-Maximization(MM)algorithm for estimating the regression parameters is developed.Properties of the estimators of the regression coefficients are evaluated through Monte Carlo simulations.Results from the analysis of two real data sets are presented.展开更多
文摘The 17 Sustainable Development Goals(SDGs)for 2030,adopted by all United Nations member states in 2015,are facing a range of challenges.Factors such as climate change,regional conflicts and economic recession are having a significant impact,particularly on global poverty governance.As a platform for dialogue,exchange and technical cooperation,the 2025 International Seminar on Global Poverty Reduction Partnerships was held in Beijing on 10 December 2025.
文摘The ISO Central Secretariat and the ISO/TC 314,Ageing societies,awarded Hou Fei,Cao Lili,and Wang Qi from CNIS for their contributions to ISO 25556:2025,Ageing societies-General requirements and guidelines for ageing-inclusive digital economy.
基金supported by the Grant PID2020-120249RB-I00PID2023-148404OB-100funded by MCIN/AEI/10.13039/501100011033+4 种基金by the Andalusian Government(Junta de Andalucía,Plan Andaluz de Investigación,ref.P20_00124)by the Erasmus+Sport Programme of the European Union within the project FitBack4Literacy(No.101089829)Additional support is provided by the University of Granada,Plan Propio de Inves-tigación,Units of ExcellenceUnit of Excellence on Exercise,Nutrition and Health(UCEENS)by theCIBERobn Physiopa-thology of Obesity and Nutrition,and by the Spanish Network in Exercise and Health,EXERNET Network(RED2022-134800-Tand EXP_99828).
文摘Background:Physicalfitness in childhood and adolescence is associated with a variety of health outcomes and is a powerful marker of current and future health.However,inconsistencies in tests and protocols limit international monitoring and surveillance.The objective of the study was to seek international consensus on a proposed,evidence-informed,Youth Fitness International Test(YFIT)battery and protocols for health monitoring and surveillance in children and adolescents aged 618 years.Methods:We conducted an international modified Delphi study to evaluate the level of agreement with a proposed,evidence-based,YFIT of core health-relatedfitness tests and protocols to be used worldwide in 6-to 18-year-olds.This proposal was based on previous European and North American projects that systematically reviewed the existing evidence to identify the most valid,reliable,health-related,safe,and feasiblefitness tests to be used in children and adolescents aged 618 years.We designed a single-panel modified Delphi study and invited 216 experts from all around the world to answer this Delphi survey,of whom one-third are from low-to-middle income countries and one-third are women.Four experts were involved in the piloting of the survey and did not participate in the main Delphi study to avoid bias.We pre-defined an agreement of 80%among the expert participants to achieve consensus.Results:We obtained a high response rate(78%)with a total of 169fitness experts from 50 countries and territories,including 63 women and 61 experts from low-or middle-income countries/territories.Consensus(>85%agreement)was achieved for all proposed tests and protocols,supporting the YFIT battery,which includes weight and height(to compute body mass index as a proxy of body size/composition),the 20-m shuttle run(cardiorespiratoryfitness),handgrip strength,and standing long jump(muscularfitness).Conclusion:This study contributes to standardizingfitness tests and protocols used for research,monitoring,and surveillance across the world,which will allow for future data pooling and the development of international and regional sex-and age-specific reference values,health-related cut-points,and a global picture offitness among children and adolescents.
文摘The modernization of the Traditional East Medicine industry has increasingly emphasized the role of collaborative innovation across the entire industrial chain.This paper investigates the mechanisms by which experts in cultivation,processing,R&D,production,and clinical application interact to enhance overall efficiency.By analyzing the bottlenecks in resource allocation,knowledge integration,and institutional design,the study proposes a comprehensive framework of collaborative mechanisms.The results highlight that multi-dimensional collaboration not only improves innovation efficiency but also accelerates the translation of scientific research into industrial outcomes.The findings provide theoretical support and practical implications for improving the synergy of experts in the Traditional East Medicine industry and contribute to the sustainable development of traditional medicine under modern industrial demands.
文摘Experts and officials shared their insights on poverty reduction cooperation and sustainable development during the 2025 International Seminar on Global Poverty Reduction Partnerships.
文摘The World Journal of Gastroenterology Editorial Board Members are composed of 357 distinguished experts active in the relevant field,distributed in 46 countries/regions,including Italy(66),Japan(53),United States(31),China(29),South Korea(16),Spain(15),Australia(13),Greece(12),Brazil(11),Romania(8),Germany(7),India(7),Taiwan(7),United Kingdom(7),Türkiye(7),Hungary(5),Russia(5).
文摘On the occasion of the New Year,I would like to extend my sincere gratitude and New Year greetings to the experts,scholars,author teams,and readers who have long supported the development of Animal Models and Experimental Medicine(AMEM).Over the past year,we have faced challenges together and achieved breakthroughs in academic influence,internationalization,and fulfilling social respon-sibilities.Looking ahead,we are filled with confidence as we strive to build an important bridge connecting laboratory animal science and technology with academic research.
基金supported by Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(RS-2023-00245084)by Korea Institute for Advancement of Technology(KIAT)grant funded by the Korea Government(MOTIE)(RS-2024-00415938,HRD Program for Industrial Innovation)and Soonchunhyang University.
文摘This paper proposes a deep learning-based 3D LiDAR perception framework designed for applications such as autonomous robots and vehicles.To address the high dependency on large-scale annotated data—an inherent limitation of deep learning models—this study introduces a hybrid perception architecture that incorporates expertdriven LiDAR processing techniques into the deep neural network.Traditional 3DLiDAR processingmethods typically remove ground planes and apply distance-or density-based clustering for object detection.In this work,such expert knowledge is encoded as feature-level inputs and fused with the deep network,therebymitigating the data dependency issue of conventional learning-based approaches.Specifically,the proposedmethod combines two expert algorithms—Patchwork++for ground segmentation and DBSCAN for clustering—with a PointPillars-based LiDAR detection network.We design four hybrid versions of the network depending on the stage and method of integrating expert features into the feature map of the deep model.Among these,Version 4 incorporates a modified neck structure in PointPillars and introduces a new Cluster 2D Pseudo-Map Branch that utilizes cluster-level pseudo-images generated from Patchwork++and DBSCAN.This version achieved a+3.88%improvement mean Average Precision(mAP)compared to the baseline PointPillars.The results demonstrate that embedding expert-based perception logic into deep neural architectures can effectively enhance performance and reduce dependency on extensive training datasets,offering a promising direction for robust 3D LiDAR object detection in real-world scenarios.
基金Project(42077244)supported by the National Natural Science Foundation of ChinaProject(2020-05)supported by the Open Research Fund of Guangdong Provincial Key Laboratory of Deep Earth Sciences and Geothermal Energy Exploitation and Utilization,China。
文摘Accurate prediction of rockburst intensity levels is crucial for ensuring the safety of deep hard rock engineering construction.This paper introduced an expert system for rockburst intensity level prediction that employs machine learning algorithms as the basis for its inference rules.The system comprises four modules:a database,a repository,an inference engine,and an interpreter.A database containing 1114 rockburst cases was used to construct 357 datasets that serve as the repository for the expert system.Additionally,19 types of machine learning algorithms were used to establish 6783 micro-models to construct cognitive rules within the inference engine.By integrating probability theory and marginal analysis,a fuzzy scoring method based on the SoftMax function was developed and applied to the interpreter for rockburst intensity level prediction,effectively restoring the continuity of rockburst characteristics.The research results indicate that ensemble algorithms based on decision trees are more effective in capturing the characteristics of rockburst.Key factors for accurate prediction of rockburst intensity include uniaxial compressive strength,elastic energy index,the maximum principal stress,tangential stress,and their composite indicators.The accuracy of the proposed rockburst intensity level prediction expert system was verified using 20 engineering rockburst cases,with predictions aligning closely with the actual rockburst intensity levels.
文摘Artificial intelligence(AI)is increasingly recognized as a transformative force in the field of solid organ transplantation.From enhancing donor-recipient matching to predicting clinical risks and tailoring immunosuppressive therapy,AI has the potential to improve both operational efficiency and patient outcomes.Despite these advancements,the perspectives of transplant professionals-those at the forefront of critical decision-making-remain insufficiently explored.To address this gap,this study utilizes a multi-round electronic Delphi approach to gather and analyses insights from global experts involved in organ transplantation.Participants are invited to complete structured surveys capturing demographic data,professional roles,institutional practices,and prior exposure to AI technologies.The survey also explores perceptions of AI’s potential benefits.Quantitative responses are analyzed using descriptive statistics,while open-ended qualitative responses undergo thematic analysis.Preliminary findings indicate a generally positive outlook on AI’s role in enhancing transplantation processes,particularly in areas such as donor matching and post-operative care.These mixed views reflect both optimism and caution among professionals tasked with integrating new technologies into high-stakes clinical workflows.By capturing a wide range of expert opinions,the findings will inform future policy development,regulatory considerations,and institutional readiness frameworks for the integration of AI into organ transplantation.
文摘According to the Action plan of the Ministry of Environmental Protection, Physical Planning and Construction, the engagement of the implementation of the Directive 2002/91/EC to the Croatian legislation has to be completed in 2009. The final goal of the Directive is the achievement of energy efficiency in buildings, with emphasis on design of building and building elements, heating and cooling systems and use of renewable energy sources. The presentation of energy performances of the building should be visible in energy label that will classify the building in comparison to energy consumption and must be submitted while buying, selling or renting the building. For the realization of energy certification of the building it is required to provide training for wide number of experts. The production of professional basis is ongoing, where besides the building classification and modification or production of correspondingly technical regulations, are determining the conditions and standards for persons who should provide the certification, as well the method of providing.
文摘The robotic liver resection(RLR)has been increasingly applied in recent years and its benefits shown in some aspects owing to the technical advancement of robotic surgical system,however,controversies still exist.Based on the foundation of the previous consensus statement,this new consensus document aimed to update clinical recommendations and provide guidance to improve the outcomes of RLR clinical practice.The guideline steering group and guideline expert group were formed by 29 international experts of liver surgery and evidence-based medicine(EBM).Relevant literature was reviewed and analyzed by the evidence evaluation group.According to the WHO Handbook for Guideline Development,the Guidance Principles of Development and Amendment of the Guidelines for Clinical Diagnosis and Treatment in China 2022,a total of 14 recommendations were generated.Among them were 8 recommendations formulated by the GRADE method,and the remaining 6 recommendations were formulated based on literature review and experts’opinion due to insufficient EBM results.This international experts consensus guideline offered guidance for the safe and effective clinical practice and the research direction of RLR in future.
文摘Spinal pain(SP)is a common condition that has a major negative impact on a patient’s quality of life.Recent developments in ultrasound-guided injections for the treatment of SP are increasingly being used in clinical practice.This clinical expert consensus describes the purpose,significance,implementation methods,indications,contraindications,and techniques of ultrasound-guided injections.This consensus offers a practical reference point for physicians to implement successfully ultrasound-guided injections in the treatment of chronic SP.
基金the National Natural Science Foundation of China(71871121).
文摘Due to people’s increasing dependence on social networks,it is essential to develop a consensus model considering not only their own factors but also the interaction between people.Both external trust relationship among experts and the internal reliability of experts are important factors in decision-making.This paper focuses on improving the scientificity and effectiveness of decision-making and presents a consensus model combining trust relationship among experts and expert reliability in social network group decision-making(SN-GDM).A concept named matching degree is proposed to measure expert reliability.Meanwhile,linguistic information is applied to manage the imprecise and vague information.Matching degree is expressed by a 2-tuple linguistic model,and experts’preferences are measured by a probabilistic linguistic term set(PLTS).Subsequently,a hybrid weight is explored to weigh experts’importance in a group.Then a consensus measure is introduced and a feedback mechanism is developed to produce some personalized recommendations with higher group consensus.Finally,a comparative example is provided to prove the scientificity and effectiveness of the proposed consensus model.
基金supported by the Asia Pacific Network for Sustainable Forest Management and Rehabilitation(APFNet)under the project ‘‘Adaption of Asia Pacific Forests to Climate Change’’
文摘Expert opinions have been used in a variety of fields to identify relevant issues and courses of action. This study surveys experts in forestry and climate change from the Asia–Pacific region to gauge their perspectives on the impacts of climate change and on the challenges faced by forest adaptation in the region, and explores recommendations and initiatives for adapting forests to climate change. There was consensus regarding the impacts of climate change on forest ecosystems and on economic sectors such as agriculture and forestry. Respondents also indicated a lack of public awareness and policy and legislation as challenges to addressing climate change. However, the results indicate differences in opinion between regions on the negative impacts of climate change and in satisfaction with actions taken to address climate change,highlighting the need for locally specific policies and research. The study presents specific recommendations to address issues of most concern, based on subregion and professional affiliation throughout the Asia–Pacific region.The results can be used to improve policy and forest management throughout the region. This research will also provide valuable suggestions on how to apply research findings and management recommendations outside of the AP region. The conclusions should be communicated relative to the level of the research and the target audience,ensuring that scientific findings and management recommendations are effectively communicated to ensure successful implementation of forest adaptation strategies.
基金supported by the National Natural Science Foundation of China:United Foundation with Xinjiang(U1403222)National Natural Science Foundation of China(81570079)
文摘IntroductionMore than 1.0 million patients worldwide are diagnosed with space-occupying lesions in the liver every year, with the number approaching 0.5 million per year in China, and only 20% of the lesions are resectable Due to a lack of available donors, only a limited number of patients underwent allogeneic liver transplantation, the remaining patients simply receive palliative care. Therefore, discovering new options for treating these patients is a high priority. Liver autotransplantation （LAT） is a surgical technique that adopts liver transplantation skills to radically treat spaceoccupying hepatic lesions, benign or malignant,
文摘ChatGPT,as an emergent technique,has become a heat throughout the world.Currently,it was not known entirely to the public.To gain knowledge of how experts perceive and experience ChatGPT,a semi-structured interview was conducted.By doing thematic analysis of their interview reports,it found that the experts construed the chatbot not the same as some media advertised.They didn’t regard it as a threat to their occupation,but as a helper or an assistant both in life and work.Neither did they restrict its use in education or other fields.They viewed the challenges of ChatGPT in a welcomed and positive way.
基金supported by the National Natural Science Foundation of China(7127105171371002+1 种基金71471032)the Fundamental Research Funds for the Central Universities,NEU,China(N140607001)
文摘A method for solving the winner determination problem （WDP） in multi-attribute procurement auctions is proposed, based on technical and business experts＇ evaluation information. Firstly, on the background of procurements in China, a multi-attribute pro- curement auction mechanism is presented, where technical and business experts participate in the bid evaluation. Then, the concept of TOPSIS is used to determine the positive and negative ideal points of the WDP according to bid prices, the technical and business experts＇ evaluation information. Further, the closeness coefficient of each bidder （candidate supplier） is obtained by calculating the distances to the positive and negative ideal points. Thus, the winning supplier can be determined according to the closeness coefficients. Finally, a numerical example is used to illustrate the use of the proposed method.
基金the National Natural Science Foundation of China(11861041,11261025).
文摘Mixture of Experts(MoE)regression models are widely studied in statistics and machine learning for modeling heterogeneity in data for regression,clustering and classification.Laplace distribution is one of the most important statistical tools to analyze thick and tail data.Laplace Mixture of Linear Experts(LMoLE)regression models are based on the Laplace distribution which is more robust.Similar to modelling variance parameter in a homogeneous population,we propose and study a new novel class of models:heteroscedastic Laplace mixture of experts regression models to analyze the heteroscedastic data coming from a heterogeneous population in this paper.The issues of maximum likelihood estimation are addressed.In particular,Minorization-Maximization(MM)algorithm for estimating the regression parameters is developed.Properties of the estimators of the regression coefficients are evaluated through Monte Carlo simulations.Results from the analysis of two real data sets are presented.
