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
OBJECTIVE:To develop an expert consensus on kidney deficiency syndrome(KDS)in pregnant women and construct a validated self-reported KDS Patient-Reported Measures Pregnancy Scale(KDS-PRMs-Pregnancy Scale)for early ide...OBJECTIVE:To develop an expert consensus on kidney deficiency syndrome(KDS)in pregnant women and construct a validated self-reported KDS Patient-Reported Measures Pregnancy Scale(KDS-PRMs-Pregnancy Scale)for early identification and management.METHODS:The study was conducted in three phases.First,a comprehensive review of Traditional Chinese Medicine(TCM)literature and diagnostic criteria was performed,generating initial KDS symptoms for pregnancy.Second,a two-round Delphi survey,involving 21 experts from TCM,obstetrics,and gynaecology,assessed importance,relevance,and appropriateness of the items.Third,a psychometric evaluation was conducted,including exploratory factor analysis and internal consistency assessment.RESULTS:In the first Delphi round,19 items were flagged for revision or removal due to expert variability,with 12 items deemed irrelevant.In the second round,consensus was reached,resulting in a 25-item scale.After psychometric evaluation,seven items were removed due to poor factor loadings,leaving an 18-item scale.Three factors—physiological discomfort,fatigue&weakness,and excretion abnormalities—accounted for 78.4%of the variance.The final scale demonstrated excellent internal consistency(Cronbach's alpha=0.959).CONCLUSION:The validated 18-item KDS-PRMsPregnancy Scale is a reliable tool for assessing KDS in pregnant women.Future research should focus on validation in diverse populations and exploring its predictive validity for pregnancy outcomes.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
Experts and officials shared their insights on poverty reduction cooperation and sustainable development during the 2025 International Seminar on Global Poverty Reduction Partnerships.
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
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
The use of AI in medicine began in the 1970s,with early efforts focused on developing expert systems for diagnosis.AI in oncology specifically began with the development of algorithms to analyze large volumes of medic...The use of AI in medicine began in the 1970s,with early efforts focused on developing expert systems for diagnosis.AI in oncology specifically began with the development of algorithms to analyze large volumes of medical data,primarily focusing on cancer diagnosis and early detection through medical imaging.1–3 The evolution of AI in oncology has transitioned from early rule-based systems to the rise and subsequent pivot of high-profile platforms,such as IBM Watson,leading to today's era of deep learning and generative AI for precision medicine.Table 1 below summarizes the selected milestones associated with Oncology Research and Practice.展开更多
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
Time flows with no stop,and seasons change in swift succession.As we bid farewell to 2025 and welcome the Spring Festival of 2026,the Editorial Office of Petroleum Exploration and Development extends our most heartfel...Time flows with no stop,and seasons change in swift succession.As we bid farewell to 2025 and welcome the Spring Festival of 2026,the Editorial Office of Petroleum Exploration and Development extends our most heartfelt gratitude and sincerest New Year wishes to our editorial board members,experts,authors,readers,and friends from all sectors.展开更多
At the IEC,Chinese experts have been contributing their expertise to international standardization.As one of them,Ma Dejun has grown from an inexperienced explorer in the field of standardization into a distinguished ...At the IEC,Chinese experts have been contributing their expertise to international standardization.As one of them,Ma Dejun has grown from an inexperienced explorer in the field of standardization into a distinguished expert driving the development of international standards in key sectors over the past 35 years.He was presented with the 2025 Lord Kelvin Award at the 89th IEC General Meeting held in New Delhi,India,in September 2025.Thus,he became the first Chinese expert to receive the highest honor bestowed by the IEC.In an exclusive interview with Ma Dejun,he reviewed his original aspiration behind his decades-long journey in international standardization,shared his experience and insights on promoting international standards,and looked forward to China's future role on the international standardiz ation stage.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
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
Patients with periodontal disease often require combined periodontal-orthodontic interventions to restore periodontal health,function,and aesthetics,ensuring both patient satisfaction and long-term stability.Managing ...Patients with periodontal disease often require combined periodontal-orthodontic interventions to restore periodontal health,function,and aesthetics,ensuring both patient satisfaction and long-term stability.Managing these patients involving orthodontic tooth movement can be particularly challenging due to compromised periodontal soft and hard tissues,especially in severe cases.Therefore,close collaboration between orthodontists and periodontists for comprehensive diagnosis and sequential treatment,along with diligent patient compliance throughout the entire process,is crucial for achieving favorable treatment outcomes.Moreover,long-term orthodontic retention and periodontal follow-up are essential to sustain treatment success.This expert consensus,informed by the latest clinical research and practical experience,addresses clinical considerations for orthodontic treatment of periodontal patients,delineating indications,objectives,procedures,and principles with the aim of providing clear and practical guidance for clinical practitioners.展开更多
To better complete various missions, it is necessary to plan an optimal trajectory or provide the optimal control law for the multirole missile according to the actual situation, including launch conditions and target...To better complete various missions, it is necessary to plan an optimal trajectory or provide the optimal control law for the multirole missile according to the actual situation, including launch conditions and target location. Since trajectory optimization struggles to meet real-time requirements, the emergence of data-based generation methods has become a significant focus in contemporary research. However, due to the large differences in the characteristics of the optimal control laws caused by the diversity of tasks, it is difficult to achieve good prediction results by modeling all data with one single model.Therefore, the modeling idea of the mixture of experts(MoE) is adopted. Firstly, the K-means clustering algorithm is used to partition the sample data set, and the corresponding neural network classification model is established as the gate switch of MoE. Then, the expert models, i.e., the mappings from the generation conditions to the optimal control law represented by the results of principal component analysis(PCA), are represented by Kriging models. Finally, multiple rounds of accuracy evaluation, sample supplementation, and model updating are conducted to improve the generation accuracy. The Monte Carlo simulation shows that the accuracy of the proposed model reaches 96% and the generation efficiency meets the real-time requirement.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
The article deals with forest communities that develop on small surfaces on steep gradients of the geomorphologically diverse landscape of the Kras plateau.They appear in small depressions called dolines,where a steep...The article deals with forest communities that develop on small surfaces on steep gradients of the geomorphologically diverse landscape of the Kras plateau.They appear in small depressions called dolines,where a steep gradient of ecological conditions appears over a small spatial scale.We tried to detect the turnover of forest communities on this small scale and steep gradient with small plots(microplots)of 4 m^(2)arranged in a continuous transect.We sampled only the ground layer and estimated the cover of each vascular plant species.The main problem was that we could not sample vegetation plots in standard sizes,which would allow a standard classification procedure.We built an expert system based on all of the relevant standard vegetation plots from the region and applied this system on a microplot matrix.We classified one third of microplots in this way,but the remainder were classified by semi-supervised k-means clustering.We thus established 8 communities that appear in dolines and compared their characteristics and ecological conditions by Ellenberg indicator values.Our results show that oak-hornbeam forests can be found in the bottom of dolines.Towards the bottom of deeper dolines,mesophilous ravine forests dominated by sycamore on rocky places,and sessile oak forests on deeper soils appear.On lower slopes,thermophilous ravine forests dominated by limes appear on rocky places.Upper slopes are dominated by Turkey oak,hophornbeam-pubescent oak forests and shrub formations.Turkey oak forests can be found on rather deeper soils than hophornbeam-pubescent oak forests.At the top,hophornbeam-pubescent oak forests can be found that build the zonal vegetation of the region.On rock walls vegetation of rock crevices can be found.The high biodiversity of the region supports the idea that diverse karstic features might have the potential for formation of refugia in future foreseen climate change,related to the potential of karstic relief to create diverse climatic conditions.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
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Supported by the National Natural Science Foundation of China:to Explore the Intergenerational Effects of Bu-Shen-Tian-Jing Therapeutic Principle on the Offspring of Hyper-Androgenic Polycystic Ovary Syndrome Based on Regulating Rhythmic Iron Death in the Ovarian Granulosa Cells Mediated by Fos Proto-OncogeneRetinoic Acid Receptor-Related Orphan Receptor A-Solute Carrier Family 7 Member 11(No.82274564)the National Natural Science Foundation of China:the Underlying Mechanism of Bu-Shen-Jian-Pi Therapeutic Principle in Regulating Ovarian Granulosa Cells Autophagy Mediated by Short-chain Fatty Acids-forkhead Box O1 Pathway and its Effects on the Development of Offspring of Polycystic Ovary Syndrome(No.82074476)the Open Fund Project of Zhejiang Key Laboratory of Maternal and Infant Health,Women’s Hospital,School of Medicine,Zhejiang University:Mediating Role of Kidney Deficiency in the Relationship between Fear of Childbirth and Delivery Modes:an Exploratory Investigation Grounded in the Classic Traditional Chinese Medicine Theories of“Fear Injuring Kidney”and“Kidney Storing Essence”(No.ZDFY2024-MI-2)。
文摘OBJECTIVE:To develop an expert consensus on kidney deficiency syndrome(KDS)in pregnant women and construct a validated self-reported KDS Patient-Reported Measures Pregnancy Scale(KDS-PRMs-Pregnancy Scale)for early identification and management.METHODS:The study was conducted in three phases.First,a comprehensive review of Traditional Chinese Medicine(TCM)literature and diagnostic criteria was performed,generating initial KDS symptoms for pregnancy.Second,a two-round Delphi survey,involving 21 experts from TCM,obstetrics,and gynaecology,assessed importance,relevance,and appropriateness of the items.Third,a psychometric evaluation was conducted,including exploratory factor analysis and internal consistency assessment.RESULTS:In the first Delphi round,19 items were flagged for revision or removal due to expert variability,with 12 items deemed irrelevant.In the second round,consensus was reached,resulting in a 25-item scale.After psychometric evaluation,seven items were removed due to poor factor loadings,leaving an 18-item scale.Three factors—physiological discomfort,fatigue&weakness,and excretion abnormalities—accounted for 78.4%of the variance.The final scale demonstrated excellent internal consistency(Cronbach's alpha=0.959).CONCLUSION:The validated 18-item KDS-PRMsPregnancy Scale is a reliable tool for assessing KDS in pregnant women.Future research should focus on validation in diverse populations and exploring its predictive validity for pregnancy outcomes.
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The use of AI in medicine began in the 1970s,with early efforts focused on developing expert systems for diagnosis.AI in oncology specifically began with the development of algorithms to analyze large volumes of medical data,primarily focusing on cancer diagnosis and early detection through medical imaging.1–3 The evolution of AI in oncology has transitioned from early rule-based systems to the rise and subsequent pivot of high-profile platforms,such as IBM Watson,leading to today's era of deep learning and generative AI for precision medicine.Table 1 below summarizes the selected milestones associated with Oncology Research and Practice.
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Time flows with no stop,and seasons change in swift succession.As we bid farewell to 2025 and welcome the Spring Festival of 2026,the Editorial Office of Petroleum Exploration and Development extends our most heartfelt gratitude and sincerest New Year wishes to our editorial board members,experts,authors,readers,and friends from all sectors.
文摘At the IEC,Chinese experts have been contributing their expertise to international standardization.As one of them,Ma Dejun has grown from an inexperienced explorer in the field of standardization into a distinguished expert driving the development of international standards in key sectors over the past 35 years.He was presented with the 2025 Lord Kelvin Award at the 89th IEC General Meeting held in New Delhi,India,in September 2025.Thus,he became the first Chinese expert to receive the highest honor bestowed by the IEC.In an exclusive interview with Ma Dejun,he reviewed his original aspiration behind his decades-long journey in international standardization,shared his experience and insights on promoting international standards,and looked forward to China's future role on the international standardiz ation stage.
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.
基金supported by the National Key R&D Program of China(2022YFC2504200)Chongqing Young and Middle-aged Medical Excellence Team ProjectJiangsu Province Key Research and Development Program(BE2022670)。
文摘Patients with periodontal disease often require combined periodontal-orthodontic interventions to restore periodontal health,function,and aesthetics,ensuring both patient satisfaction and long-term stability.Managing these patients involving orthodontic tooth movement can be particularly challenging due to compromised periodontal soft and hard tissues,especially in severe cases.Therefore,close collaboration between orthodontists and periodontists for comprehensive diagnosis and sequential treatment,along with diligent patient compliance throughout the entire process,is crucial for achieving favorable treatment outcomes.Moreover,long-term orthodontic retention and periodontal follow-up are essential to sustain treatment success.This expert consensus,informed by the latest clinical research and practical experience,addresses clinical considerations for orthodontic treatment of periodontal patients,delineating indications,objectives,procedures,and principles with the aim of providing clear and practical guidance for clinical practitioners.
基金Defense Industrial Technology Development Program (JCKY2020204B016)National Natural Science Foundation of China (92471206)。
文摘To better complete various missions, it is necessary to plan an optimal trajectory or provide the optimal control law for the multirole missile according to the actual situation, including launch conditions and target location. Since trajectory optimization struggles to meet real-time requirements, the emergence of data-based generation methods has become a significant focus in contemporary research. However, due to the large differences in the characteristics of the optimal control laws caused by the diversity of tasks, it is difficult to achieve good prediction results by modeling all data with one single model.Therefore, the modeling idea of the mixture of experts(MoE) is adopted. Firstly, the K-means clustering algorithm is used to partition the sample data set, and the corresponding neural network classification model is established as the gate switch of MoE. Then, the expert models, i.e., the mappings from the generation conditions to the optimal control law represented by the results of principal component analysis(PCA), are represented by Kriging models. Finally, multiple rounds of accuracy evaluation, sample supplementation, and model updating are conducted to improve the generation accuracy. The Monte Carlo simulation shows that the accuracy of the proposed model reaches 96% and the generation efficiency meets the real-time requirement.
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.
基金supported by the Slovenian Research and Innovation Agency(grant numbers ARIS P1-0236,ARIS P6-0101,ARIS J6-2592).
文摘The article deals with forest communities that develop on small surfaces on steep gradients of the geomorphologically diverse landscape of the Kras plateau.They appear in small depressions called dolines,where a steep gradient of ecological conditions appears over a small spatial scale.We tried to detect the turnover of forest communities on this small scale and steep gradient with small plots(microplots)of 4 m^(2)arranged in a continuous transect.We sampled only the ground layer and estimated the cover of each vascular plant species.The main problem was that we could not sample vegetation plots in standard sizes,which would allow a standard classification procedure.We built an expert system based on all of the relevant standard vegetation plots from the region and applied this system on a microplot matrix.We classified one third of microplots in this way,but the remainder were classified by semi-supervised k-means clustering.We thus established 8 communities that appear in dolines and compared their characteristics and ecological conditions by Ellenberg indicator values.Our results show that oak-hornbeam forests can be found in the bottom of dolines.Towards the bottom of deeper dolines,mesophilous ravine forests dominated by sycamore on rocky places,and sessile oak forests on deeper soils appear.On lower slopes,thermophilous ravine forests dominated by limes appear on rocky places.Upper slopes are dominated by Turkey oak,hophornbeam-pubescent oak forests and shrub formations.Turkey oak forests can be found on rather deeper soils than hophornbeam-pubescent oak forests.At the top,hophornbeam-pubescent oak forests can be found that build the zonal vegetation of the region.On rock walls vegetation of rock crevices can be found.The high biodiversity of the region supports the idea that diverse karstic features might have the potential for formation of refugia in future foreseen climate change,related to the potential of karstic relief to create diverse climatic conditions.
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.
