We develop a neuro-knowledge-based expert system (NKBES) frame in this work. The system mainly concerns with decision of gating system and die casting machine based on a neuro-inference engine launched under the MATLA...We develop a neuro-knowledge-based expert system (NKBES) frame in this work. The system mainly concerns with decision of gating system and die casting machine based on a neuro-inference engine launched under the MATLAB software environment. For enhancement of reasoning agility, an error back-propagation neural network was applied. A rapidly convergent adaptive learning rate (ALR) and a momentum-based error back-propagation algorithm was used to conduct neuro-reasoning. The working effect of the system was compared to a conventional expert system that is based on a two-way (forward and backward) chaining inference mechanism. As the reference, the present paper provided the neural networks sum-squared error (S5E) and ALR vs iterative epoch curves of process planning case mentioned above. The study suggests that the neuro-modeling optimization application to die casting process design has good feasibility, and based on that a novel and effective intelligent expert system can be launched at low cost.展开更多
The surrogate model serves as an efficient simulation tool during the slope parameter inversion process.However,the creep constitutive model integrated with dynamic damage evolution poses challenges in development of ...The surrogate model serves as an efficient simulation tool during the slope parameter inversion process.However,the creep constitutive model integrated with dynamic damage evolution poses challenges in development of the required surrogate model.In this study,a novel physics knowledge-based surrogate model framework is proposed.In this framework,a Transformer module is employed to capture straindriven softening-hardening physical mechanisms.Positional encoding and self-attention are utilized to transform the constitutive parameters associated with shear strain,which are not directly time-related,into intermediate latent features for physical loss calculation.Next,a multi-layer stacked GRU(gated recurrent unit)network is built to provide input interfaces for time-dependent intermediate latent features,hydraulic boundary conditions,and water-rock interaction degradation equations,with static parameters introduced via external fully-connected layers.Finally,a combined loss function is constructed to facilitate the collaborative training of physical and data loss,introducing time-dependent weight adjustments to focus the surrogate model on accurate deformation predictions during critical phases.Based on the deformation of a reservoir bank landslide triggered by impoundment and subsequent restabilization,an elasto-viscoplastic constitutive model that considers water effect and sliding state dependencies is developed to validate the proposed surrogate model framework.The results indicate that the framework exhibits good performance in capturing physical mechanisms and predicting creep behavior,reducing errors by about 30 times compared to baseline models such as GRU and LSTM(long short-term memory),meeting the precision requirements for parameter inversion.Ablation experiments also confirmed the effectiveness of the framework.This framework can also serve as a reference for constructing other creep surrogate models that involve non-time-related across dimensions.展开更多
Background External knowledge representations play an essential role in knowledge-based visual question and answering to better understand complex scenarios in the open world.Recent entity-relationship embedding appro...Background External knowledge representations play an essential role in knowledge-based visual question and answering to better understand complex scenarios in the open world.Recent entity-relationship embedding approaches are deficient in representing some complex relations,resulting in a lack of topic-related knowledge and redundancy in topic-irrelevant information.Methods To this end,we propose MKEAH:Multimodal Knowledge Extraction and Accumulation on Hyperplanes.To ensure that the lengths of the feature vectors projected onto the hyperplane compare equally and to filter out sufficient topic-irrelevant information,two losses are proposed to learn the triplet representations from the complementary views:range loss and orthogonal loss.To interpret the capability of extracting topic-related knowledge,we present the Topic Similarity(TS)between topic and entity-relations.Results Experimental results demonstrate the effectiveness of hyperplane embedding for knowledge representation in knowledge-based visual question answering.Our model outperformed state-of-the-art methods by 2.12%and 3.24%on two challenging knowledge-request datasets:OK-VQA and KRVQA,respectively.Conclusions The obvious advantages of our model in TS show that using hyperplane embedding to represent multimodal knowledge can improve its ability to extract topic-related knowledge.展开更多
Aiming at the lack of professional knowledge to guide apparel recommendation,an apparel recommendation method based on image design expert knowledge has been proposed.Then,apparel recommendation knowledge graphs have ...Aiming at the lack of professional knowledge to guide apparel recommendation,an apparel recommendation method based on image design expert knowledge has been proposed.Then,apparel recommendation knowledge graphs have been created and a apparel recommendation question and answer(Q&A)system has been designed and implemented.The question templates in the apparel recommendation domain were defined,the task of recognizing the named entities of question sentences was completed by the Bi-directional encoder representations from transformer-Bi-directional long short-term memory-conditional random field(BERT-BiLSTM-CRF)model,and the question template with the highest matching degree to the user’s question was obtained by using term frequency-inverse document frequency(TF-IDF)algorithm.The corresponding cypher graph database query statement was generated to retrieve the knowledge graph for answers,and iFLYTEK’s voice application programming interface(API)was called to implement the Q&A.The experimental results have shown that the Q&A system has a high accuracy rate and application value in the field of apparel recommendations.展开更多
Early correction of childhood malocclusion is timely managing morphological,structural,and functional abnormalities at different dentomaxillofacial developmental stages.The selection of appropriate imaging examination...Early correction of childhood malocclusion is timely managing morphological,structural,and functional abnormalities at different dentomaxillofacial developmental stages.The selection of appropriate imaging examination and comprehensive radiological diagnosis and analysis play an important role in early correction of childhood malocclusion.This expert consensus is a collaborative effort by multidisciplinary experts in dentistry across the nation based on the current clinical evidence,aiming to provide general guidance on appropriate imaging examination selection,comprehensive and accurate imaging assessment for early orthodontic treatment patients.展开更多
The research and development of new traditional Chinese medicine(TCM)drugs have progressively established a novel system founded on the integration of TCM theory,human experience,and clinical trials(termed the“Three ...The research and development of new traditional Chinese medicine(TCM)drugs have progressively established a novel system founded on the integration of TCM theory,human experience,and clinical trials(termed the“Three Combinations”).However,considering TCM's distinctive features of“syndrome differentiation and treatment”and“multicomponent formulations and complex mechanisms”,current TCM drug development faces challenges such as insufficient understanding of the material basis and the overall mechanism of action and an incomplete evidence chain system.Moreover,significant obstacles persist in gathering human experience data,evaluating clinical efficacy,and controlling the quality of active ingredients,which impede the innovation process in TCM drug development.Network pharmacology,centered on the“network targets”theory,transcends the limitations of the conventional“single target”reductionist research model.It emphasizes the comprehensive effects of disease or syndrome biological networks as targets to elucidate the overall regulatory mechanism of TCM prescriptions.This approach aligns with the holistic perspective of TCM,offering a novel method consistent with TCM's holistic view for investigating the complex mechanisms of TCM and developing new TCM drugs.It is internationally recognized as a“next-generation drug research model”.To advance the research of new tools,methods,and standards for TCM evaluation and to overcome fundamental,critical,and cutting-edge technical challenges in TCM regulation,this consensus aims to explore the characteristics,progress,challenges,applicable pathways,and specific applications of network pharmacology as a new theory,method,and tool in TCM drug development.The goal is to enhance the quality of TCM drug research and development and accelerate the efficiency of developing new TCM products.展开更多
The dramatic rise in the number of people living in cities has made many environmental and social problems worse.The search for a productive method for disposing of solid waste is the most notable of these problems.Ma...The dramatic rise in the number of people living in cities has made many environmental and social problems worse.The search for a productive method for disposing of solid waste is the most notable of these problems.Many scholars have referred to it as a fuzzy multi-attribute or multi-criteria decision-making problem using various fuzzy set-like approaches because of the inclusion of criteria and anticipated ambiguity.The goal of the current study is to use an innovative methodology to address the expected uncertainties in the problem of solid waste site selection.The characteristics(or sub-attributes)that decision-makers select and the degree of approximation they accept for various options can both be indicators of these uncertainties.To tackle these problems,a novel mathematical structure known as the fuzzy parameterized possibility single valued neutrosophic hypersoft expert set(ρˆ-set),which is initially described,is integrated with a modified version of Sanchez’s method.Following this,an intelligent algorithm is suggested.The steps of the suggested algorithm are explained with an example that explains itself.The compatibility of solid waste management sites and systems is discussed,and rankings are established along with detailed justifications for their viability.This study’s strengths lie in its application of fuzzy parameterization and possibility grading to effectively handle the uncertainties embodied in the parameters’nature and alternative approximations,respectively.It uses specific mathematical formulations to compute the fuzzy parameterized degrees and possibility grades that are missing from the prior literature.It is simpler for the decisionmakers to look at each option separately because the decision is uncertain.Comparing the computed results,it is discovered that they are consistent and dependable because of their preferred properties.展开更多
Developmental and reproductive toxicity(DART)endpoint entails a toxicological assessment of all developmental stages and reproductive cycles of an organism.In silico tools to predict DART will provide a method to asse...Developmental and reproductive toxicity(DART)endpoint entails a toxicological assessment of all developmental stages and reproductive cycles of an organism.In silico tools to predict DART will provide a method to assess this complex toxicity endpoint and will be valuable for screening emerging pollutants as well as for m anaging new chemicals in China.Currently,there are few published DART prediction models in China,but many related research and development projects are in progress.In 2013,WU et al.published an expert rule-based DART decision tree(DT).This DT relies on known chemical structures linked to DART to forecast DART potential of a given chemical.Within this procedure,an accurate DART data interpretation is the foundation of building and expanding the DT.This paper excerpted case studies demonstrating DART data curation and interpretation of four chemicals(including 8-hydroxyquinoline,3,5,6-trichloro-2-pyridinol,thiacloprid,and imidacloprid)to expand the existing DART DT.Chemicals were first selected from the database of Solid Waste and Chemicals Management Center,Ministry of Ecology and Environment(MEESCC)in China.The structures of these 4 chemicals were analyzed and preliminarily grouped by chemists based on core structural features,functional groups,receptor binding property,metabolism,and possible mode of actions.Then,the DART conclusion was derived by collecting chemical information,searching,integrating,and interpreting DART data by the toxicologists.Finally,these chemicals were classified into either an existing category or a new category via integrating their chemical features,DART conclusions,and biological properties.The results showed that 8-hydroxyquinoline impacted estrous cyclicity,s exual organ weights,and embryonal development,and 3,5,6-trichloro-2-pyridinol caused central nervous system(CNS)malformations,which were added to an existing subcategory 8e(aromatic compounds with multi-halogen and nitro groups)of the DT.Thiacloprid caused dystocia and fetal skeletal malformation,and imidacloprid disrupted the endocrine system and male fertility.They both contain 2-chloro-5-methylpyridine substituted imidazolidine c yclic ring,which were expected to create a new category of neonicotinoids.The current work delineates a t ransparent process of curating toxicological data for the purpose of DART data interpretation.In the presence of sufficient related structures and DART data,the DT can be expanded by iteratively adding chemicals within the a pplicable domain of each category or subcategory.This DT can potentially serve as a tool for screening emerging pollutants and assessing new chemicals in China.展开更多
At the turn of the new spring,as we bid farewell to 2024 and welcome the Spring Festival of 2025,our entire editorial team of Petroleum Exploration and Development extends heartfelt gratitude and sincere New Year'...At the turn of the new spring,as we bid farewell to 2024 and welcome the Spring Festival of 2025,our entire editorial team of Petroleum Exploration and Development extends heartfelt gratitude and sincere New Year's greetings to our editorial board,experts,authors,readers,and friends from all fields!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
Objective:Robot-assisted simple prostatectomy(RASP)is increasingly used as a surgical treatment option for large benign prostatic hyperplasia(BPH)(>80 mL).However,there is no sufficient expert consensus or guidelin...Objective:Robot-assisted simple prostatectomy(RASP)is increasingly used as a surgical treatment option for large benign prostatic hyperplasia(BPH)(>80 mL).However,there is no sufficient expert consensus or guidelines to guide clinical practice.We aimed to obtain expert opinions for RASP for large BPH.Methods:A systematic review of the literature was performed in April 2024 using the PubMed,Embase,and Web of Science databases.Search terms were combined to construct the following search strings:(robotic)AND(simple OR benign)AND(prostatectomy).Search results were filtered by language(English only),species(human),and publication type(original article).This study used a two-phase modified Delphi approach.Results:In this expert consensus,some frequently used RASP techniques,including robot-assisted retropubic prostatectomy,robot-assisted transvesical prostatectomy,and robot-assisted urethra-sparing prostatectomy,are described.RASP offers a short learning curve for surgeons with experience in robotic surgery.Severe complications are rare in patients who undergo RASP.Conclusion:RASP technique can be recommended as a safe and effective minimally invasive treatment for symptomatic BPH patients with large prostate glands.展开更多
This special issue of the Asian Journal of Andrology is fully dedicated to the thematic area of non-obstructive azoospermia(NOA),one of the most complex and challenging conditions in the realm of andrology,urology,and...This special issue of the Asian Journal of Andrology is fully dedicated to the thematic area of non-obstructive azoospermia(NOA),one of the most complex and challenging conditions in the realm of andrology,urology,and reproductive medicine.展开更多
Objective:To establish consensus on Chinese Herbal Medicine(CHM)for rheumatoid arthritis(RA)among 21 Singaporean experts,this study addressed the lack of CHM clinical practice guidelines(CPGs)in Singapore.Despite adva...Objective:To establish consensus on Chinese Herbal Medicine(CHM)for rheumatoid arthritis(RA)among 21 Singaporean experts,this study addressed the lack of CHM clinical practice guidelines(CPGs)in Singapore.Despite advancements in RA therapies,the disease's progressive nature and high costs of novel treatments worsen disparities in management and outcomes.The initiative aimed to bridge this gap by developing expert-backed recommendations for CHM use in RA care.Methods:The group of experts conducted two rounds of Delphi surveys containing 29 items identified from a literature review.Consensus was defined as≥75%of votes in dichotomized ratings on a fivepoint ordinal scale for recognition.Items that did not reach consensus were discussed in a focus group with four selected experts.Results:Nineteen experts completed both rounds of Delphi surveys.A consensus was reached for 27 items,which encompassed Chinese medicine rationale,pattern differentiation,management,CHM prescription,and co-effectiveness with pharmacological therapy.Collective expert opinions were formed for the two remaining items.All items received a recognition score>3.5.Conclusions:The consensus derived from this study provides a foundation for CHM CPGs for RA in Singapore.However,the findings are limited by the demographic composition of the experts and the representativeness of the patient pool.展开更多
A literature review on AI applications in the field of railway safety shows that the implemented approaches mainly concern the operational,maintenance,and feedback phases following railway incidents or accidents.These...A literature review on AI applications in the field of railway safety shows that the implemented approaches mainly concern the operational,maintenance,and feedback phases following railway incidents or accidents.These approaches exploit railway safety data once the transport system has received authorization for commissioning.However,railway standards and regulations require the development of a safety management system(SMS)from the specification and design phases of the railway system.This article proposes a new AI approach for analyzing and assessing safety from the specification and design phases of the railway system with a view to improving the development of the SMS.Unlike some learning methods,the proposed approach,which is dedicated in particular to safety assessment bodies,is based on semi-supervised learning carried out in close collaboration with safety experts who contributed to the development of a database of potential accident scenarios(learning example database)relating to the risk of rail collision.The proposed decision support is based on the use of an expert system whose knowledge base is automatically generated by inductive learning in the form of an association rule(rule base)and whose main objective is to suggest to the safety expert possible hazards not considered during the development of the SMS to complete the initial hazard register.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
Urban transportation planning involves evaluating multiple conflicting criteria such as accessibility,cost-effectiveness,and environmental impact,often under uncertainty and incomplete information.These complex decisi...Urban transportation planning involves evaluating multiple conflicting criteria such as accessibility,cost-effectiveness,and environmental impact,often under uncertainty and incomplete information.These complex decisions require input from various stakeholders,including planners,policymakers,engineers,and community representatives,whose opinions may differ or contradict.Traditional decision-making approaches struggle to effectively handle such bipolar and multivalued expert evaluations.To address these challenges,we propose a novel decisionmaking framework based on Pythagorean fuzzy N-bipolar soft expert sets.This model allows experts to express both positive and negative opinions on a multinary scale,capturing nuanced judgments with higher accuracy.It introduces algebraic operations and a structured aggregation algorithm to systematically integrate and resolve conflicting expert inputs.Applied to a real-world case study,the framework evaluated five urban transport strategies based on key criteria,producing final scores as follows:improving public transit(−0.70),optimizing traffic signal timing(1.86),enhancing pedestrian infrastructure(3.10),expanding bike lanes(0.59),and implementing congestion pricing(0.77).The results clearly identify enhancing pedestrian infrastructure as the most suitable option,having obtained the highest final score of 3.10.Comparative analysis demonstrates the framework’s superior capability in modeling expert consensus,managing uncertainty,and supporting transparent multi-criteria group decision-making.展开更多
The International Federation of Standards Users(IFAN)held the 52nd IFAN Members’Assembly and associated meetings on October 20-22 in Milan,Italy,which was hosted by the Italian standards body UNI.Xia Weijia(Vivian),M...The International Federation of Standards Users(IFAN)held the 52nd IFAN Members’Assembly and associated meetings on October 20-22 in Milan,Italy,which was hosted by the Italian standards body UNI.Xia Weijia(Vivian),Member of the IFAN Board and Director of International Standards Department of China Association for Standardization(CAS),was elected Vice-President of IFAN with a term of office from 2026 to 2028.It is the first time for a Chinese expert to take the position,which marks a further step of China’s participation in international standardization.展开更多
A machine-learning approach was developed for automated building of knowledgebases for soil resources mapping by using a classification tree to generate knowledge from trainingdata. With this method, building a knowle...A machine-learning approach was developed for automated building of knowledgebases for soil resources mapping by using a classification tree to generate knowledge from trainingdata. With this method, building a knowledge base for automated soil mapping was easier than usingthe conventional knowledge acquisition approach. The knowledge base built by classification tree wasused by the knowledge classifier to perform the soil type classification of Longyou County,Zhejiang Province, China using Landsat TM bi-temporal images and CIS data. To evaluate theperformance of the resultant knowledge bases, the classification results were compared to existingsoil map based on a field survey. The accuracy assessment and analysis of the resultant soil mapssuggested that the knowledge bases built by the machine-learning method was of good quality formapping distribution model of soil classes over the study area.展开更多
文摘We develop a neuro-knowledge-based expert system (NKBES) frame in this work. The system mainly concerns with decision of gating system and die casting machine based on a neuro-inference engine launched under the MATLAB software environment. For enhancement of reasoning agility, an error back-propagation neural network was applied. A rapidly convergent adaptive learning rate (ALR) and a momentum-based error back-propagation algorithm was used to conduct neuro-reasoning. The working effect of the system was compared to a conventional expert system that is based on a two-way (forward and backward) chaining inference mechanism. As the reference, the present paper provided the neural networks sum-squared error (S5E) and ALR vs iterative epoch curves of process planning case mentioned above. The study suggests that the neuro-modeling optimization application to die casting process design has good feasibility, and based on that a novel and effective intelligent expert system can be launched at low cost.
基金supported by the National Natural Science Foundation of China(Grant No.41961134032).
文摘The surrogate model serves as an efficient simulation tool during the slope parameter inversion process.However,the creep constitutive model integrated with dynamic damage evolution poses challenges in development of the required surrogate model.In this study,a novel physics knowledge-based surrogate model framework is proposed.In this framework,a Transformer module is employed to capture straindriven softening-hardening physical mechanisms.Positional encoding and self-attention are utilized to transform the constitutive parameters associated with shear strain,which are not directly time-related,into intermediate latent features for physical loss calculation.Next,a multi-layer stacked GRU(gated recurrent unit)network is built to provide input interfaces for time-dependent intermediate latent features,hydraulic boundary conditions,and water-rock interaction degradation equations,with static parameters introduced via external fully-connected layers.Finally,a combined loss function is constructed to facilitate the collaborative training of physical and data loss,introducing time-dependent weight adjustments to focus the surrogate model on accurate deformation predictions during critical phases.Based on the deformation of a reservoir bank landslide triggered by impoundment and subsequent restabilization,an elasto-viscoplastic constitutive model that considers water effect and sliding state dependencies is developed to validate the proposed surrogate model framework.The results indicate that the framework exhibits good performance in capturing physical mechanisms and predicting creep behavior,reducing errors by about 30 times compared to baseline models such as GRU and LSTM(long short-term memory),meeting the precision requirements for parameter inversion.Ablation experiments also confirmed the effectiveness of the framework.This framework can also serve as a reference for constructing other creep surrogate models that involve non-time-related across dimensions.
基金Supported by National Nature Science Foudation of China(61976160,61906137,61976158,62076184,62076182)Shanghai Science and Technology Plan Project(21DZ1204800)。
文摘Background External knowledge representations play an essential role in knowledge-based visual question and answering to better understand complex scenarios in the open world.Recent entity-relationship embedding approaches are deficient in representing some complex relations,resulting in a lack of topic-related knowledge and redundancy in topic-irrelevant information.Methods To this end,we propose MKEAH:Multimodal Knowledge Extraction and Accumulation on Hyperplanes.To ensure that the lengths of the feature vectors projected onto the hyperplane compare equally and to filter out sufficient topic-irrelevant information,two losses are proposed to learn the triplet representations from the complementary views:range loss and orthogonal loss.To interpret the capability of extracting topic-related knowledge,we present the Topic Similarity(TS)between topic and entity-relations.Results Experimental results demonstrate the effectiveness of hyperplane embedding for knowledge representation in knowledge-based visual question answering.Our model outperformed state-of-the-art methods by 2.12%and 3.24%on two challenging knowledge-request datasets:OK-VQA and KRVQA,respectively.Conclusions The obvious advantages of our model in TS show that using hyperplane embedding to represent multimodal knowledge can improve its ability to extract topic-related knowledge.
文摘Aiming at the lack of professional knowledge to guide apparel recommendation,an apparel recommendation method based on image design expert knowledge has been proposed.Then,apparel recommendation knowledge graphs have been created and a apparel recommendation question and answer(Q&A)system has been designed and implemented.The question templates in the apparel recommendation domain were defined,the task of recognizing the named entities of question sentences was completed by the Bi-directional encoder representations from transformer-Bi-directional long short-term memory-conditional random field(BERT-BiLSTM-CRF)model,and the question template with the highest matching degree to the user’s question was obtained by using term frequency-inverse document frequency(TF-IDF)algorithm.The corresponding cypher graph database query statement was generated to retrieve the knowledge graph for answers,and iFLYTEK’s voice application programming interface(API)was called to implement the Q&A.The experimental results have shown that the Q&A system has a high accuracy rate and application value in the field of apparel recommendations.
基金supports by the National Natural Science Foundation of China(Nos.82201135)"2015"Cultivation Program for Reserve Talents for Academic Leaders of Nanjing Stomatological School,Medical School of Nanjing University(No.0223A204).
文摘Early correction of childhood malocclusion is timely managing morphological,structural,and functional abnormalities at different dentomaxillofacial developmental stages.The selection of appropriate imaging examination and comprehensive radiological diagnosis and analysis play an important role in early correction of childhood malocclusion.This expert consensus is a collaborative effort by multidisciplinary experts in dentistry across the nation based on the current clinical evidence,aiming to provide general guidance on appropriate imaging examination selection,comprehensive and accurate imaging assessment for early orthodontic treatment patients.
基金supported by the National Medical Products Administration Commissioned Research Project (No.20211440216)the National Administration of Traditional Chinese Medicine Science and Technology Project (No.GZY-KJS-2024-03)+3 种基金the State Key Laboratory of Drug Regulatory Science Project (No.2023SKLDRS0104)the Basic Research Program Natural Science Fund-Frontier Leading Technology Basic Research Special Project of Jiangsu Province (No.BK20232014)the Programs Foundation for Leading Talents in National Administration of Traditional Chinese Medicine of China“Qihuang scholars”Projectthe Tianjin Administration for Market Regulation Science and Technology Key Projects (No.2022-W35)。
文摘The research and development of new traditional Chinese medicine(TCM)drugs have progressively established a novel system founded on the integration of TCM theory,human experience,and clinical trials(termed the“Three Combinations”).However,considering TCM's distinctive features of“syndrome differentiation and treatment”and“multicomponent formulations and complex mechanisms”,current TCM drug development faces challenges such as insufficient understanding of the material basis and the overall mechanism of action and an incomplete evidence chain system.Moreover,significant obstacles persist in gathering human experience data,evaluating clinical efficacy,and controlling the quality of active ingredients,which impede the innovation process in TCM drug development.Network pharmacology,centered on the“network targets”theory,transcends the limitations of the conventional“single target”reductionist research model.It emphasizes the comprehensive effects of disease or syndrome biological networks as targets to elucidate the overall regulatory mechanism of TCM prescriptions.This approach aligns with the holistic perspective of TCM,offering a novel method consistent with TCM's holistic view for investigating the complex mechanisms of TCM and developing new TCM drugs.It is internationally recognized as a“next-generation drug research model”.To advance the research of new tools,methods,and standards for TCM evaluation and to overcome fundamental,critical,and cutting-edge technical challenges in TCM regulation,this consensus aims to explore the characteristics,progress,challenges,applicable pathways,and specific applications of network pharmacology as a new theory,method,and tool in TCM drug development.The goal is to enhance the quality of TCM drug research and development and accelerate the efficiency of developing new TCM products.
文摘The dramatic rise in the number of people living in cities has made many environmental and social problems worse.The search for a productive method for disposing of solid waste is the most notable of these problems.Many scholars have referred to it as a fuzzy multi-attribute or multi-criteria decision-making problem using various fuzzy set-like approaches because of the inclusion of criteria and anticipated ambiguity.The goal of the current study is to use an innovative methodology to address the expected uncertainties in the problem of solid waste site selection.The characteristics(or sub-attributes)that decision-makers select and the degree of approximation they accept for various options can both be indicators of these uncertainties.To tackle these problems,a novel mathematical structure known as the fuzzy parameterized possibility single valued neutrosophic hypersoft expert set(ρˆ-set),which is initially described,is integrated with a modified version of Sanchez’s method.Following this,an intelligent algorithm is suggested.The steps of the suggested algorithm are explained with an example that explains itself.The compatibility of solid waste management sites and systems is discussed,and rankings are established along with detailed justifications for their viability.This study’s strengths lie in its application of fuzzy parameterization and possibility grading to effectively handle the uncertainties embodied in the parameters’nature and alternative approximations,respectively.It uses specific mathematical formulations to compute the fuzzy parameterized degrees and possibility grades that are missing from the prior literature.It is simpler for the decisionmakers to look at each option separately because the decision is uncertain.Comparing the computed results,it is discovered that they are consistent and dependable because of their preferred properties.
文摘Developmental and reproductive toxicity(DART)endpoint entails a toxicological assessment of all developmental stages and reproductive cycles of an organism.In silico tools to predict DART will provide a method to assess this complex toxicity endpoint and will be valuable for screening emerging pollutants as well as for m anaging new chemicals in China.Currently,there are few published DART prediction models in China,but many related research and development projects are in progress.In 2013,WU et al.published an expert rule-based DART decision tree(DT).This DT relies on known chemical structures linked to DART to forecast DART potential of a given chemical.Within this procedure,an accurate DART data interpretation is the foundation of building and expanding the DT.This paper excerpted case studies demonstrating DART data curation and interpretation of four chemicals(including 8-hydroxyquinoline,3,5,6-trichloro-2-pyridinol,thiacloprid,and imidacloprid)to expand the existing DART DT.Chemicals were first selected from the database of Solid Waste and Chemicals Management Center,Ministry of Ecology and Environment(MEESCC)in China.The structures of these 4 chemicals were analyzed and preliminarily grouped by chemists based on core structural features,functional groups,receptor binding property,metabolism,and possible mode of actions.Then,the DART conclusion was derived by collecting chemical information,searching,integrating,and interpreting DART data by the toxicologists.Finally,these chemicals were classified into either an existing category or a new category via integrating their chemical features,DART conclusions,and biological properties.The results showed that 8-hydroxyquinoline impacted estrous cyclicity,s exual organ weights,and embryonal development,and 3,5,6-trichloro-2-pyridinol caused central nervous system(CNS)malformations,which were added to an existing subcategory 8e(aromatic compounds with multi-halogen and nitro groups)of the DT.Thiacloprid caused dystocia and fetal skeletal malformation,and imidacloprid disrupted the endocrine system and male fertility.They both contain 2-chloro-5-methylpyridine substituted imidazolidine c yclic ring,which were expected to create a new category of neonicotinoids.The current work delineates a t ransparent process of curating toxicological data for the purpose of DART data interpretation.In the presence of sufficient related structures and DART data,the DT can be expanded by iteratively adding chemicals within the a pplicable domain of each category or subcategory.This DT can potentially serve as a tool for screening emerging pollutants and assessing new chemicals in China.
文摘At the turn of the new spring,as we bid farewell to 2024 and welcome the Spring Festival of 2025,our entire editorial team of Petroleum Exploration and Development extends heartfelt gratitude and sincere New Year's greetings to our editorial board,experts,authors,readers,and friends from all fields!
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.
基金funded by National Natural Science Foundation of China(82072846 to Xu B).
文摘Objective:Robot-assisted simple prostatectomy(RASP)is increasingly used as a surgical treatment option for large benign prostatic hyperplasia(BPH)(>80 mL).However,there is no sufficient expert consensus or guidelines to guide clinical practice.We aimed to obtain expert opinions for RASP for large BPH.Methods:A systematic review of the literature was performed in April 2024 using the PubMed,Embase,and Web of Science databases.Search terms were combined to construct the following search strings:(robotic)AND(simple OR benign)AND(prostatectomy).Search results were filtered by language(English only),species(human),and publication type(original article).This study used a two-phase modified Delphi approach.Results:In this expert consensus,some frequently used RASP techniques,including robot-assisted retropubic prostatectomy,robot-assisted transvesical prostatectomy,and robot-assisted urethra-sparing prostatectomy,are described.RASP offers a short learning curve for surgeons with experience in robotic surgery.Severe complications are rare in patients who undergo RASP.Conclusion:RASP technique can be recommended as a safe and effective minimally invasive treatment for symptomatic BPH patients with large prostate glands.
文摘This special issue of the Asian Journal of Andrology is fully dedicated to the thematic area of non-obstructive azoospermia(NOA),one of the most complex and challenging conditions in the realm of andrology,urology,and reproductive medicine.
基金supported by the Nanyang Technological University Start-Up Grant(#022387‒00001).
文摘Objective:To establish consensus on Chinese Herbal Medicine(CHM)for rheumatoid arthritis(RA)among 21 Singaporean experts,this study addressed the lack of CHM clinical practice guidelines(CPGs)in Singapore.Despite advancements in RA therapies,the disease's progressive nature and high costs of novel treatments worsen disparities in management and outcomes.The initiative aimed to bridge this gap by developing expert-backed recommendations for CHM use in RA care.Methods:The group of experts conducted two rounds of Delphi surveys containing 29 items identified from a literature review.Consensus was defined as≥75%of votes in dichotomized ratings on a fivepoint ordinal scale for recognition.Items that did not reach consensus were discussed in a focus group with four selected experts.Results:Nineteen experts completed both rounds of Delphi surveys.A consensus was reached for 27 items,which encompassed Chinese medicine rationale,pattern differentiation,management,CHM prescription,and co-effectiveness with pharmacological therapy.Collective expert opinions were formed for the two remaining items.All items received a recognition score>3.5.Conclusions:The consensus derived from this study provides a foundation for CHM CPGs for RA in Singapore.However,the findings are limited by the demographic composition of the experts and the representativeness of the patient pool.
文摘A literature review on AI applications in the field of railway safety shows that the implemented approaches mainly concern the operational,maintenance,and feedback phases following railway incidents or accidents.These approaches exploit railway safety data once the transport system has received authorization for commissioning.However,railway standards and regulations require the development of a safety management system(SMS)from the specification and design phases of the railway system.This article proposes a new AI approach for analyzing and assessing safety from the specification and design phases of the railway system with a view to improving the development of the SMS.Unlike some learning methods,the proposed approach,which is dedicated in particular to safety assessment bodies,is based on semi-supervised learning carried out in close collaboration with safety experts who contributed to the development of a database of potential accident scenarios(learning example database)relating to the risk of rail collision.The proposed decision support is based on the use of an expert system whose knowledge base is automatically generated by inductive learning in the form of an association rule(rule base)and whose main objective is to suggest to the safety expert possible hazards not considered during the development of the SMS to complete the initial hazard register.
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.
文摘Urban transportation planning involves evaluating multiple conflicting criteria such as accessibility,cost-effectiveness,and environmental impact,often under uncertainty and incomplete information.These complex decisions require input from various stakeholders,including planners,policymakers,engineers,and community representatives,whose opinions may differ or contradict.Traditional decision-making approaches struggle to effectively handle such bipolar and multivalued expert evaluations.To address these challenges,we propose a novel decisionmaking framework based on Pythagorean fuzzy N-bipolar soft expert sets.This model allows experts to express both positive and negative opinions on a multinary scale,capturing nuanced judgments with higher accuracy.It introduces algebraic operations and a structured aggregation algorithm to systematically integrate and resolve conflicting expert inputs.Applied to a real-world case study,the framework evaluated five urban transport strategies based on key criteria,producing final scores as follows:improving public transit(−0.70),optimizing traffic signal timing(1.86),enhancing pedestrian infrastructure(3.10),expanding bike lanes(0.59),and implementing congestion pricing(0.77).The results clearly identify enhancing pedestrian infrastructure as the most suitable option,having obtained the highest final score of 3.10.Comparative analysis demonstrates the framework’s superior capability in modeling expert consensus,managing uncertainty,and supporting transparent multi-criteria group decision-making.
文摘The International Federation of Standards Users(IFAN)held the 52nd IFAN Members’Assembly and associated meetings on October 20-22 in Milan,Italy,which was hosted by the Italian standards body UNI.Xia Weijia(Vivian),Member of the IFAN Board and Director of International Standards Department of China Association for Standardization(CAS),was elected Vice-President of IFAN with a term of office from 2026 to 2028.It is the first time for a Chinese expert to take the position,which marks a further step of China’s participation in international standardization.
基金Project supported by the National Natural Science Foundation of China(Nos.40101014 and 40001008).
文摘A machine-learning approach was developed for automated building of knowledgebases for soil resources mapping by using a classification tree to generate knowledge from trainingdata. With this method, building a knowledge base for automated soil mapping was easier than usingthe conventional knowledge acquisition approach. The knowledge base built by classification tree wasused by the knowledge classifier to perform the soil type classification of Longyou County,Zhejiang Province, China using Landsat TM bi-temporal images and CIS data. To evaluate theperformance of the resultant knowledge bases, the classification results were compared to existingsoil map based on a field survey. The accuracy assessment and analysis of the resultant soil mapssuggested that the knowledge bases built by the machine-learning method was of good quality formapping distribution model of soil classes over the study area.
