Tau plays a crucial role in several neurodegenerative diseases,collectively referred to as tauopathies.Therefore,targeting potential pathological changes in tau could enable useful therapeutic interventions.However,ta...Tau plays a crucial role in several neurodegenerative diseases,collectively referred to as tauopathies.Therefore,targeting potential pathological changes in tau could enable useful therapeutic interventions.However,tau is not an easy target because it dynamically interacts with microtubules and other cellular components,which presents a challenge for tau-targeted drugs.New cellular models could aid the development of mechanism-based tau-targeted therapies.展开更多
Reversible data hiding(RDH)enables secret data embedding while preserving complete cover image recovery,making it crucial for applications requiring image integrity.The pixel value ordering(PVO)technique used in multi...Reversible data hiding(RDH)enables secret data embedding while preserving complete cover image recovery,making it crucial for applications requiring image integrity.The pixel value ordering(PVO)technique used in multi-stego images provides good image quality but often results in low embedding capability.To address these challenges,this paper proposes a high-capacity RDH scheme based on PVO that generates three stego images from a single cover image.The cover image is partitioned into non-overlapping blocks with pixels sorted in ascending order.Four secret bits are embedded into each block’s maximum pixel value,while three additional bits are embedded into the second-largest value when the pixel difference exceeds a predefined threshold.A similar embedding strategy is also applied to the minimum side of the block,including the second-smallest pixel value.This design enables each block to embed up to 14 bits of secret data.Experimental results demonstrate that the proposed method achieves significantly higher embedding capacity and improved visual quality compared to existing triple-stego RDH approaches,advancing the field of reversible steganography.展开更多
Correction to:Journal of Forestry Research(2025)36:124 https://doi.org/10.1007/s11676-025-01918-8 In this article the author’s name Yasutomo Hoshika was incorrectly written as Yasutoma Hoshika.The original article ha...Correction to:Journal of Forestry Research(2025)36:124 https://doi.org/10.1007/s11676-025-01918-8 In this article the author’s name Yasutomo Hoshika was incorrectly written as Yasutoma Hoshika.The original article has been corrected.展开更多
Hebei Province has incorporated targeted assistance services for people with disabilities into livelihood projects,upgrading the quality and efficiency of support services for disadvantaged groups.THE living and nursi...Hebei Province has incorporated targeted assistance services for people with disabilities into livelihood projects,upgrading the quality and efficiency of support services for disadvantaged groups.THE living and nursing allowances provided by the Chinese government for people with disabilities who are unable to work are not only important components of China’s social security system which provide for the needs of its disabled,but also show China’s ability to guarantee the basic living standard and social fairness and justice for this group of people.展开更多
Target-based and phenotype-based methods are the two main approaches for drug screening.Target-based drug screening focuses on specific targets CPA highly correlated with disease mechanisms,by detecting protein-ligand...Target-based and phenotype-based methods are the two main approaches for drug screening.Target-based drug screening focuses on specific targets CPA highly correlated with disease mechanisms,by detecting protein-ligand binding structure,dynamics and affinity.Currently,the four mainstream drug targets are G protein-coupled receptors(GPCRs),kinases,ion channels,and nuclear receptors,accounting for over 70%of effective drug targets,most of which are membrane proteins and enzymes.In recent years,various new drug targets have been continuously discovered,and the research focus has shifted from simple affinity analysis to high-throughput and high-content screening,as well as exploring drug-target interaction modes.These deepen reliance on the analytical techniques to have higher sensitivity,recognition specificity,and applicability to diversified target structures,which promoting the rapid development of novel screening methods.展开更多
The cranial base synchondroses,comprised of opposite-facing bidirectional chondrocyte layers,drive anteroposterior cranial base growth.In humans,RUNX2 haploinsufficiency causes cleidocranial dysplasia associated with ...The cranial base synchondroses,comprised of opposite-facing bidirectional chondrocyte layers,drive anteroposterior cranial base growth.In humans,RUNX2 haploinsufficiency causes cleidocranial dysplasia associated with deficient midfacial growth.However,how RUNX2 regulates chondrocytes in the cranial base synchondroses remains unknown.To address this,we inactivated Runx2 in postnatal synchondrosis chondrocytes using a tamoxifen-inducible Fgfr3-creER(Fgfr3-Runx2cKO)mouse model.Fgfr3-Runx2cKO mice displayed skeletal dwarfism and reduced anteroposterior cranial base growth associated with premature synchondrosis ossification due to impaired chondrocyte proliferation,accelerated hypertrophy,apoptosis,and osteoclast-mediated cartilage resorption.Lineage tracing reveals that Runx2-deficient Fgfr3+cells failed to differentiate into osteoblasts.Notably,Runx2-deficient chondrocytes showed an elevated level of FGFR3 and its downstream signaling components,pERK1/2 and SOX9,suggesting that RUNX2 downregulates FGFR3 in the synchondrosis.This study unveils a new role of Runx2 in cranial base chondrocytes,identifying a possible RUNX2-FGFR3-MAPK-SOX9 signaling axis that may control cranial base growth.展开更多
Bacterial blight(BB),caused by Xanthomonas oryzae pathovar oryzae(Xoo),poses a significant threat to rice production,particularly in Asia and West Africa.Breeding resistance against BB in elite rice varieties is cruci...Bacterial blight(BB),caused by Xanthomonas oryzae pathovar oryzae(Xoo),poses a significant threat to rice production,particularly in Asia and West Africa.Breeding resistance against BB in elite rice varieties is crucial to advancing rice breeding program and supporting smallholder farmers.Transcription Activator-Like effectors(TALes)are key virulence factors in Xoo,with some targeting the susceptibility(S)genes such as the sugar transporter SWEET genes in rice.Among these,SWEET14 is an important S gene,with its promoter bound by the TALe TalC which exists across all sequenced African Xoo isolates.In the present study,we utilized CRISPR/Cas9-based cytidine and adenine base editors to alter the effector binding element(EBE)of TalC in the promoter of SWEET14 in rice cultivars Kitaake,IR24,and Zhonghua 11.Mutations with C to T changes in EBE led to reduced SWEET14 induction by TalC-containing Xoo strains,resulting in resistance to African Xoo isolates reliant on TalC for virulence.Conversely,A to G changes retained SWEET14 inducibility and susceptibility to Xoo in edited lines.Importantly,no off-target mutations were detected at predicted sites,and the edited lines exhibited no obvious defects in major agronomic traits in Kitaake.These results underscore the effectiveness of base editing systems for both molecular biology research and crop improvement endeavors.展开更多
Embodied visual exploration is critical for building intelligent visual agents. This paper presents the neural exploration with feature-based visual odometry and tracking-failure-reduction policy(Ne OR), a framework f...Embodied visual exploration is critical for building intelligent visual agents. This paper presents the neural exploration with feature-based visual odometry and tracking-failure-reduction policy(Ne OR), a framework for embodied visual exploration that possesses the efficient exploration capabilities of deep reinforcement learning(DRL)-based exploration policies and leverages feature-based visual odometry(VO) for more accurate mapping and positioning results. An improved local policy is also proposed to reduce tracking failures of feature-based VO in weakly textured scenes through a refined multi-discrete action space, keyframe fusion, and an auxiliary task. The experimental results demonstrate that Ne OR has better mapping and positioning accuracy compared to other entirely learning-based exploration frameworks and improves the robustness of feature-based VO by significantly reducing tracking failures in weakly textured scenes.展开更多
To further advance the development of the fluorescent dyes for latent fingerprint imaging,two triphenylamine-based Schiff base compounds containing a benzimidazole group(TPA-BZI)and a phenyl unit(TPA-Ph)were designed ...To further advance the development of the fluorescent dyes for latent fingerprint imaging,two triphenylamine-based Schiff base compounds containing a benzimidazole group(TPA-BZI)and a phenyl unit(TPA-Ph)were designed and synthesized.Photoluminescence experiments revealed that both compounds exhibited solvatochromism and intramolecular charge transfer(ICT)characteristics in six organic solvents.Additionally,they showed aggregation-induced emission(AIE)in CH_(3)OH/water mixtures and solid-state fluorescence.These phenomena were further elucidated through time-dependent density functional theory(TD-DFT)calculations.It was also found that the two compounds could be used for latent fingerprints imaging,and could easily distinguish the details of fingerprints from Ⅰ to Ⅲ levels,which could provide the preliminary evidence to match personal identification.展开更多
Component-based Chinese Medicine(CCM)stands as a pivotal endeavor in modernizing traditional Chinese medicine(TCM).By integrating classical TCM theories with modern scientific methodologies,CCM aims to achieve herbal ...Component-based Chinese Medicine(CCM)stands as a pivotal endeavor in modernizing traditional Chinese medicine(TCM).By integrating classical TCM theories with modern scientific methodologies,CCM aims to achieve herbal formulas with“defined components,clarified mechanisms,and controllable quality.”This approach not only transitions TCM development from empirical tradition to evidence-based science but also positions it for global recognition.Drawing on recent advancements in CCM,this editorial explores key insights and challenges shaping its trajectory.展开更多
The“Opinions on Comprehensively Deepening Curriculum Reform to Fulfill the Fundamental Task of Strengthening Moral Education”,issued by China’s Ministry of Education in 2015,explicitly identified Project-Based Lear...The“Opinions on Comprehensively Deepening Curriculum Reform to Fulfill the Fundamental Task of Strengthening Moral Education”,issued by China’s Ministry of Education in 2015,explicitly identified Project-Based Learning(PBL)as a key strategy for cultivating students’core competencies.Since then,PBL has been widely implemented as a pilot initiative in primary and secondary schools,gaining increasing influence.Analyzing the intellectual foundations of PBL research in China can offer valuable insights into its theoretical and practical dimensions.This study uses CiteSpace to examine 156 PBL-related articles from the CSSCI database,revealing that the knowledge base of PBL research is primarily built on two major domains.The first is the theoretical foundation,characterized by frequently cited literature focusing on the conceptual framework,educational value,interdisciplinary approaches,core competency cultivation,and instructional objectives of PBL.The second is empirical research,where highly cited studies include case analyses across K–12 settings,general high schools,and higher education institutions.Moving forward,future research on PBL should explore its meaning and value from a dual-subject and integrated perspective,expand case studies to include vocational education,and further promote the interdisciplinary development of core competencies through PBL.展开更多
As legal cases grow in complexity and volume worldwide,integrating machine learning and artificial intelligence into judicial systems has become a pivotal research focus.This study introduces a comprehensive framework...As legal cases grow in complexity and volume worldwide,integrating machine learning and artificial intelligence into judicial systems has become a pivotal research focus.This study introduces a comprehensive framework for verdict recommendation that synergizes rule-based methods with deep learning techniques specifically tailored to the legal domain.The proposed framework comprises three core modules:legal feature extraction,semantic similarity assessment,and verdict recommendation.For legal feature extraction,a rule-based approach leverages Black’s Law Dictionary and WordNet Synsets to construct feature vectors from judicial texts.Semantic similarity between cases is evaluated using a hybrid method that combines rule-based logic with an LSTM model,analyzing the feature vectors of query cases against a legal knowledge base.Verdicts are then recommended through a rule-based retrieval system,enhanced by predefined legal statutes and regulations.By merging rule-based methodologies with deep learning,this framework addresses the interpretability challenges often associated with contemporary AImodels,thereby enhancing both transparency and generalizability across diverse legal contexts.The system was rigorously tested using a legal corpus of 43,000 case laws across six categories:Criminal,Revenue,Service,Corporate,Constitutional,and Civil law,ensuring its adaptability across a wide range of judicial scenarios.Performance evaluation showed that the feature extraction module achieved an average accuracy of 91.6%with an F-Score of 95%.The semantic similarity module,tested using Manhattan,Euclidean,and Cosine distance metrics,achieved 88%accuracy and a 93%F-Score for short queries(Manhattan),89%accuracy and a 93.7%F-Score for medium-length queries(Euclidean),and 87%accuracy with a 92.5%F-Score for longer queries(Cosine).The verdict recommendation module outperformed existing methods,achieving 90%accuracy and a 93.75%F-Score.This study highlights the potential of hybrid AI frameworks to improve judicial decision-making and streamline legal processes,offering a robust,interpretable,and adaptable solution for the evolving demands of modern legal systems.展开更多
In the context of power generation companies, vast amounts of specialized data and expert knowledge have been accumulated. However, challenges such as data silos and fragmented knowledge hinder the effective utilizati...In the context of power generation companies, vast amounts of specialized data and expert knowledge have been accumulated. However, challenges such as data silos and fragmented knowledge hinder the effective utilization of this information. This study proposes a novel framework for intelligent Question-and-Answer (Q&A) systems based on Retrieval-Augmented Generation (RAG) to address these issues. The system efficiently acquires domain-specific knowledge by leveraging external databases, including Relational Databases (RDBs) and graph databases, without additional fine-tuning for Large Language Models (LLMs). Crucially, the framework integrates a Dynamic Knowledge Base Updating Mechanism (DKBUM) and a Weighted Context-Aware Similarity (WCAS) method to enhance retrieval accuracy and mitigate inherent limitations of LLMs, such as hallucinations and lack of specialization. Additionally, the proposed DKBUM dynamically adjusts knowledge weights within the database, ensuring that the most recent and relevant information is utilized, while WCAS refines the alignment between queries and knowledge items by enhanced context understanding. Experimental validation demonstrates that the system can generate timely, accurate, and context-sensitive responses, making it a robust solution for managing complex business logic in specialized industries.展开更多
Magnesium-based materials,including magnesium alloys,have emerged as a promising class of biodegradable materials with potential applications in cancer therapy due to their unique properties,including biocompatibility...Magnesium-based materials,including magnesium alloys,have emerged as a promising class of biodegradable materials with potential applications in cancer therapy due to their unique properties,including biocompatibility,biodegradability,and the ability to modulate the tumor microenvironment.The main degradation products of magnesium alloys are magnesium ions(Mg^(2+)),hydrogen(H_(2)),and magnesium hydroxide(Mg(OH)_(2)).Magnesium ions can regulate tumor growth and metastasis by mediating the inflammatory response and oxidative stress,maintaining genomic stability,and affecting the tumor microenvironment.Similarly,hydrogen can inhibit tumorigenesis through antioxidant and anti-inflammatory properties.Moreover,Mg(OH)_(2) can alter the pH of the microenvironment,impacting tumorigenesis.Biodegradable magnesium alloys serve various functions in clinical applications,including,but not limited to,bonefixation,coronary stents,and drug carriers.Nonetheless,the anti-tumor mechanism associated with magnesium-based materials has not been thoroughly investigated.This review provides a comprehensive overview of the current state of magnesium-based therapies for cancer.It highlights the mechanisms of action,identifies the challenges that must be addressed,and discusses prospects for oncological applications.展开更多
The wireless signals emitted by base stations serve as a vital link connecting people in today’s society and have been occupying an increasingly important role in real life.The development of the Internet of Things(I...The wireless signals emitted by base stations serve as a vital link connecting people in today’s society and have been occupying an increasingly important role in real life.The development of the Internet of Things(IoT)relies on the support of base stations,which provide a solid foundation for achieving a more intelligent way of living.In a specific area,achieving higher signal coverage with fewer base stations has become an urgent problem.Therefore,this article focuses on the effective coverage area of base station signals and proposes a novel Evolutionary Particle Swarm Optimization(EPSO)algorithm based on collective prediction,referred to herein as ECPPSO.Introducing a new strategy called neighbor-based evolution prediction(NEP)addresses the issue of premature convergence often encountered by PSO.ECPPSO also employs a strengthening evolution(SE)strategy to enhance the algorithm’s global search capability and efficiency,ensuring enhanced robustness and a faster convergence speed when solving complex optimization problems.To better adapt to the actual communication needs of base stations,this article conducts simulation experiments by changing the number of base stations.The experimental results demonstrate thatunder the conditionof 50 ormore base stations,ECPPSOconsistently achieves the best coverage rate exceeding 95%,peaking at 99.4400%when the number of base stations reaches 80.These results validate the optimization capability of the ECPPSO algorithm,proving its feasibility and effectiveness.Further ablative experiments and comparisons with other algorithms highlight the advantages of ECPPSO.展开更多
In general,the rapid growth of α-Fe clusters is a challenge in high Fe-content Fe-based amorphous alloys,negatively affecting their physical properties.Herein,we introduce an efficient and rapid post-treatment techni...In general,the rapid growth of α-Fe clusters is a challenge in high Fe-content Fe-based amorphous alloys,negatively affecting their physical properties.Herein,we introduce an efficient and rapid post-treatment technique known as ultrasonic vibration rapid processing(UVRP),which enables the formation of high-density strong magnetic α-Fe clusters,thereby enhancing the soft magnetic properties of Fe_(78)Si(13)B_(9) amorphous alloy ribbon.展开更多
文摘Tau plays a crucial role in several neurodegenerative diseases,collectively referred to as tauopathies.Therefore,targeting potential pathological changes in tau could enable useful therapeutic interventions.However,tau is not an easy target because it dynamically interacts with microtubules and other cellular components,which presents a challenge for tau-targeted drugs.New cellular models could aid the development of mechanism-based tau-targeted therapies.
基金funded by University of Transport and Communications(UTC)under grant number T2025-CN-004.
文摘Reversible data hiding(RDH)enables secret data embedding while preserving complete cover image recovery,making it crucial for applications requiring image integrity.The pixel value ordering(PVO)technique used in multi-stego images provides good image quality but often results in low embedding capability.To address these challenges,this paper proposes a high-capacity RDH scheme based on PVO that generates three stego images from a single cover image.The cover image is partitioned into non-overlapping blocks with pixels sorted in ascending order.Four secret bits are embedded into each block’s maximum pixel value,while three additional bits are embedded into the second-largest value when the pixel difference exceeds a predefined threshold.A similar embedding strategy is also applied to the minimum side of the block,including the second-smallest pixel value.This design enables each block to embed up to 14 bits of secret data.Experimental results demonstrate that the proposed method achieves significantly higher embedding capacity and improved visual quality compared to existing triple-stego RDH approaches,advancing the field of reversible steganography.
文摘Correction to:Journal of Forestry Research(2025)36:124 https://doi.org/10.1007/s11676-025-01918-8 In this article the author’s name Yasutomo Hoshika was incorrectly written as Yasutoma Hoshika.The original article has been corrected.
文摘Hebei Province has incorporated targeted assistance services for people with disabilities into livelihood projects,upgrading the quality and efficiency of support services for disadvantaged groups.THE living and nursing allowances provided by the Chinese government for people with disabilities who are unable to work are not only important components of China’s social security system which provide for the needs of its disabled,but also show China’s ability to guarantee the basic living standard and social fairness and justice for this group of people.
文摘Target-based and phenotype-based methods are the two main approaches for drug screening.Target-based drug screening focuses on specific targets CPA highly correlated with disease mechanisms,by detecting protein-ligand binding structure,dynamics and affinity.Currently,the four mainstream drug targets are G protein-coupled receptors(GPCRs),kinases,ion channels,and nuclear receptors,accounting for over 70%of effective drug targets,most of which are membrane proteins and enzymes.In recent years,various new drug targets have been continuously discovered,and the research focus has shifted from simple affinity analysis to high-throughput and high-content screening,as well as exploring drug-target interaction modes.These deepen reliance on the analytical techniques to have higher sensitivity,recognition specificity,and applicability to diversified target structures,which promoting the rapid development of novel screening methods.
基金National Institutes of Health grant F30DE030675(S.A.H.)National Institutes of Health grant T32DE007057(S.A.H.)+7 种基金University of Michigan Rackham Graduate School Pre-Candidate Research Grant(S.A.H.)University of Michigan Rackham Graduate School Candidate Research Grant(S.A.H.)National Institutes of Health grant R35DE034348(N.O.)National Institutes of Health grant R01DE026666(N.O.)National Institutes of Health grant R01DE030630(N.O.)National Institutes of Health grant R01DE029465(R.T.F.)Department of Defense grant W81XWH2010571(R.T.F.)National Institutes of Health grant P30 AR069620(The Michigan Integrative Musculoskeletal.Health Core Center).
文摘The cranial base synchondroses,comprised of opposite-facing bidirectional chondrocyte layers,drive anteroposterior cranial base growth.In humans,RUNX2 haploinsufficiency causes cleidocranial dysplasia associated with deficient midfacial growth.However,how RUNX2 regulates chondrocytes in the cranial base synchondroses remains unknown.To address this,we inactivated Runx2 in postnatal synchondrosis chondrocytes using a tamoxifen-inducible Fgfr3-creER(Fgfr3-Runx2cKO)mouse model.Fgfr3-Runx2cKO mice displayed skeletal dwarfism and reduced anteroposterior cranial base growth associated with premature synchondrosis ossification due to impaired chondrocyte proliferation,accelerated hypertrophy,apoptosis,and osteoclast-mediated cartilage resorption.Lineage tracing reveals that Runx2-deficient Fgfr3+cells failed to differentiate into osteoblasts.Notably,Runx2-deficient chondrocytes showed an elevated level of FGFR3 and its downstream signaling components,pERK1/2 and SOX9,suggesting that RUNX2 downregulates FGFR3 in the synchondrosis.This study unveils a new role of Runx2 in cranial base chondrocytes,identifying a possible RUNX2-FGFR3-MAPK-SOX9 signaling axis that may control cranial base growth.
基金supported by a sub-award to the University of Missouri from the Heinrich Heine University of Dusseldorf funded by the Bill&Melinda Gates Foundation(OPP1155704)(Bing Yang)and the China Scholar Council(Chenhao Li,as a joint Ph.D.student).
文摘Bacterial blight(BB),caused by Xanthomonas oryzae pathovar oryzae(Xoo),poses a significant threat to rice production,particularly in Asia and West Africa.Breeding resistance against BB in elite rice varieties is crucial to advancing rice breeding program and supporting smallholder farmers.Transcription Activator-Like effectors(TALes)are key virulence factors in Xoo,with some targeting the susceptibility(S)genes such as the sugar transporter SWEET genes in rice.Among these,SWEET14 is an important S gene,with its promoter bound by the TALe TalC which exists across all sequenced African Xoo isolates.In the present study,we utilized CRISPR/Cas9-based cytidine and adenine base editors to alter the effector binding element(EBE)of TalC in the promoter of SWEET14 in rice cultivars Kitaake,IR24,and Zhonghua 11.Mutations with C to T changes in EBE led to reduced SWEET14 induction by TalC-containing Xoo strains,resulting in resistance to African Xoo isolates reliant on TalC for virulence.Conversely,A to G changes retained SWEET14 inducibility and susceptibility to Xoo in edited lines.Importantly,no off-target mutations were detected at predicted sites,and the edited lines exhibited no obvious defects in major agronomic traits in Kitaake.These results underscore the effectiveness of base editing systems for both molecular biology research and crop improvement endeavors.
基金supported by the National Natural Science Foundation of China (No.62202137)the China Postdoctoral Science Foundation (No.2023M730599)the Zhejiang Provincial Natural Science Foundation of China (No.LMS25F020009)。
文摘Embodied visual exploration is critical for building intelligent visual agents. This paper presents the neural exploration with feature-based visual odometry and tracking-failure-reduction policy(Ne OR), a framework for embodied visual exploration that possesses the efficient exploration capabilities of deep reinforcement learning(DRL)-based exploration policies and leverages feature-based visual odometry(VO) for more accurate mapping and positioning results. An improved local policy is also proposed to reduce tracking failures of feature-based VO in weakly textured scenes through a refined multi-discrete action space, keyframe fusion, and an auxiliary task. The experimental results demonstrate that Ne OR has better mapping and positioning accuracy compared to other entirely learning-based exploration frameworks and improves the robustness of feature-based VO by significantly reducing tracking failures in weakly textured scenes.
文摘To further advance the development of the fluorescent dyes for latent fingerprint imaging,two triphenylamine-based Schiff base compounds containing a benzimidazole group(TPA-BZI)and a phenyl unit(TPA-Ph)were designed and synthesized.Photoluminescence experiments revealed that both compounds exhibited solvatochromism and intramolecular charge transfer(ICT)characteristics in six organic solvents.Additionally,they showed aggregation-induced emission(AIE)in CH_(3)OH/water mixtures and solid-state fluorescence.These phenomena were further elucidated through time-dependent density functional theory(TD-DFT)calculations.It was also found that the two compounds could be used for latent fingerprints imaging,and could easily distinguish the details of fingerprints from Ⅰ to Ⅲ levels,which could provide the preliminary evidence to match personal identification.
文摘Component-based Chinese Medicine(CCM)stands as a pivotal endeavor in modernizing traditional Chinese medicine(TCM).By integrating classical TCM theories with modern scientific methodologies,CCM aims to achieve herbal formulas with“defined components,clarified mechanisms,and controllable quality.”This approach not only transitions TCM development from empirical tradition to evidence-based science but also positions it for global recognition.Drawing on recent advancements in CCM,this editorial explores key insights and challenges shaping its trajectory.
基金Provincial-Level Quality Engineering Project,Preschool Education Teacher Training Base of Fuyang Normal University(Project No.:2023cyts023)University-Level Research Team Project,Collaborative Innovation Center for Basic Education in Northern Anhui(Project No.:kytd202418)。
文摘The“Opinions on Comprehensively Deepening Curriculum Reform to Fulfill the Fundamental Task of Strengthening Moral Education”,issued by China’s Ministry of Education in 2015,explicitly identified Project-Based Learning(PBL)as a key strategy for cultivating students’core competencies.Since then,PBL has been widely implemented as a pilot initiative in primary and secondary schools,gaining increasing influence.Analyzing the intellectual foundations of PBL research in China can offer valuable insights into its theoretical and practical dimensions.This study uses CiteSpace to examine 156 PBL-related articles from the CSSCI database,revealing that the knowledge base of PBL research is primarily built on two major domains.The first is the theoretical foundation,characterized by frequently cited literature focusing on the conceptual framework,educational value,interdisciplinary approaches,core competency cultivation,and instructional objectives of PBL.The second is empirical research,where highly cited studies include case analyses across K–12 settings,general high schools,and higher education institutions.Moving forward,future research on PBL should explore its meaning and value from a dual-subject and integrated perspective,expand case studies to include vocational education,and further promote the interdisciplinary development of core competencies through PBL.
基金funded by the Deanship of Scientific Research at Jouf University under Grant number DSR-2022-RG-0101。
文摘As legal cases grow in complexity and volume worldwide,integrating machine learning and artificial intelligence into judicial systems has become a pivotal research focus.This study introduces a comprehensive framework for verdict recommendation that synergizes rule-based methods with deep learning techniques specifically tailored to the legal domain.The proposed framework comprises three core modules:legal feature extraction,semantic similarity assessment,and verdict recommendation.For legal feature extraction,a rule-based approach leverages Black’s Law Dictionary and WordNet Synsets to construct feature vectors from judicial texts.Semantic similarity between cases is evaluated using a hybrid method that combines rule-based logic with an LSTM model,analyzing the feature vectors of query cases against a legal knowledge base.Verdicts are then recommended through a rule-based retrieval system,enhanced by predefined legal statutes and regulations.By merging rule-based methodologies with deep learning,this framework addresses the interpretability challenges often associated with contemporary AImodels,thereby enhancing both transparency and generalizability across diverse legal contexts.The system was rigorously tested using a legal corpus of 43,000 case laws across six categories:Criminal,Revenue,Service,Corporate,Constitutional,and Civil law,ensuring its adaptability across a wide range of judicial scenarios.Performance evaluation showed that the feature extraction module achieved an average accuracy of 91.6%with an F-Score of 95%.The semantic similarity module,tested using Manhattan,Euclidean,and Cosine distance metrics,achieved 88%accuracy and a 93%F-Score for short queries(Manhattan),89%accuracy and a 93.7%F-Score for medium-length queries(Euclidean),and 87%accuracy with a 92.5%F-Score for longer queries(Cosine).The verdict recommendation module outperformed existing methods,achieving 90%accuracy and a 93.75%F-Score.This study highlights the potential of hybrid AI frameworks to improve judicial decision-making and streamline legal processes,offering a robust,interpretable,and adaptable solution for the evolving demands of modern legal systems.
文摘In the context of power generation companies, vast amounts of specialized data and expert knowledge have been accumulated. However, challenges such as data silos and fragmented knowledge hinder the effective utilization of this information. This study proposes a novel framework for intelligent Question-and-Answer (Q&A) systems based on Retrieval-Augmented Generation (RAG) to address these issues. The system efficiently acquires domain-specific knowledge by leveraging external databases, including Relational Databases (RDBs) and graph databases, without additional fine-tuning for Large Language Models (LLMs). Crucially, the framework integrates a Dynamic Knowledge Base Updating Mechanism (DKBUM) and a Weighted Context-Aware Similarity (WCAS) method to enhance retrieval accuracy and mitigate inherent limitations of LLMs, such as hallucinations and lack of specialization. Additionally, the proposed DKBUM dynamically adjusts knowledge weights within the database, ensuring that the most recent and relevant information is utilized, while WCAS refines the alignment between queries and knowledge items by enhanced context understanding. Experimental validation demonstrates that the system can generate timely, accurate, and context-sensitive responses, making it a robust solution for managing complex business logic in specialized industries.
文摘Magnesium-based materials,including magnesium alloys,have emerged as a promising class of biodegradable materials with potential applications in cancer therapy due to their unique properties,including biocompatibility,biodegradability,and the ability to modulate the tumor microenvironment.The main degradation products of magnesium alloys are magnesium ions(Mg^(2+)),hydrogen(H_(2)),and magnesium hydroxide(Mg(OH)_(2)).Magnesium ions can regulate tumor growth and metastasis by mediating the inflammatory response and oxidative stress,maintaining genomic stability,and affecting the tumor microenvironment.Similarly,hydrogen can inhibit tumorigenesis through antioxidant and anti-inflammatory properties.Moreover,Mg(OH)_(2) can alter the pH of the microenvironment,impacting tumorigenesis.Biodegradable magnesium alloys serve various functions in clinical applications,including,but not limited to,bonefixation,coronary stents,and drug carriers.Nonetheless,the anti-tumor mechanism associated with magnesium-based materials has not been thoroughly investigated.This review provides a comprehensive overview of the current state of magnesium-based therapies for cancer.It highlights the mechanisms of action,identifies the challenges that must be addressed,and discusses prospects for oncological applications.
基金supported by the National Natural Science Foundation of China(Nos.62272418,62102058)Basic Public Welfare Research Program of Zhejiang Province(No.LGG18E050011)the Major Open Project of Key Laboratory for Advanced Design and Intelligent Computing of the Ministry of Education under Grant ADIC2023ZD001,National Undergraduate Training Program on Innovation and Entrepreneurship(No.202410345054).
文摘The wireless signals emitted by base stations serve as a vital link connecting people in today’s society and have been occupying an increasingly important role in real life.The development of the Internet of Things(IoT)relies on the support of base stations,which provide a solid foundation for achieving a more intelligent way of living.In a specific area,achieving higher signal coverage with fewer base stations has become an urgent problem.Therefore,this article focuses on the effective coverage area of base station signals and proposes a novel Evolutionary Particle Swarm Optimization(EPSO)algorithm based on collective prediction,referred to herein as ECPPSO.Introducing a new strategy called neighbor-based evolution prediction(NEP)addresses the issue of premature convergence often encountered by PSO.ECPPSO also employs a strengthening evolution(SE)strategy to enhance the algorithm’s global search capability and efficiency,ensuring enhanced robustness and a faster convergence speed when solving complex optimization problems.To better adapt to the actual communication needs of base stations,this article conducts simulation experiments by changing the number of base stations.The experimental results demonstrate thatunder the conditionof 50 ormore base stations,ECPPSOconsistently achieves the best coverage rate exceeding 95%,peaking at 99.4400%when the number of base stations reaches 80.These results validate the optimization capability of the ECPPSO algorithm,proving its feasibility and effectiveness.Further ablative experiments and comparisons with other algorithms highlight the advantages of ECPPSO.
基金supported by the Major Science and Technology Project of Zhongshan City(No.2022AJ004)the Key Basic and Applied Research Program of Guangdong Province(Nos.2019B030302010 and 2022B1515120082)Guangdong Science and Technology Innovation Project(No.2021TX06C111).
文摘In general,the rapid growth of α-Fe clusters is a challenge in high Fe-content Fe-based amorphous alloys,negatively affecting their physical properties.Herein,we introduce an efficient and rapid post-treatment technique known as ultrasonic vibration rapid processing(UVRP),which enables the formation of high-density strong magnetic α-Fe clusters,thereby enhancing the soft magnetic properties of Fe_(78)Si(13)B_(9) amorphous alloy ribbon.
