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
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
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
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
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
Two new complexes,[Zn_(2)(L1)(HL1)(NO_(3))]·CH_(3)OH(1)and[Zn_(3)(L2)(L3)_(3)Cl]·CH_(3)OH(2),were successfully synthesized by‘one-pot’method based on cinnoline-3-ylhydrazine ligand and zinc with 2-hydroxy-...Two new complexes,[Zn_(2)(L1)(HL1)(NO_(3))]·CH_(3)OH(1)and[Zn_(3)(L2)(L3)_(3)Cl]·CH_(3)OH(2),were successfully synthesized by‘one-pot’method based on cinnoline-3-ylhydrazine ligand and zinc with 2-hydroxy-4-methoxybenzaldehyde and 2-hydroxy-3-methoxybenzaldehyde ligands,respectively,where H_(2)L1=5-methoxy-2-(phthalazin-1-ylhydrazonomethyl)-phenol,H_(2)L2=2-methoxy-6-(phthalazin-1-yl-hydrazonomethyl)-phenol,HL3=2-(1,8-dihydro-[1,2,4]triazolo[3,4-α]phthalazin-3-yl)-6-methoxy-phenol.Complexes 1 and 2 were characterized by infrared spectroscopy,elemental analysis,single-crystal X-ray diffraction,powder X-ray diffraction,etc.It is worth noting that the cinnolin-3-yl-hydrazine ligand and 2-hydroxy-3-methoxybenzaldehyde form two types of Schiff bases(H_(2)L2 and HL3)when in situ reacting and coordinating with Zn(Ⅱ),and HL3 also has two coordination modes.In addition,the fluorescence performance showed that complex 1 can achieve selective and sensitive sensing of Al^(3+)in water with a detection limit of 6.37μmol·L^(-1).CCDC:2413978,1;2413979,2.展开更多
Two Gd_(2)complexes,namely[Gd_(2)(dbm)_(2)(HL_(1))_(2)(CH_(3)OH)_(2)]·4CH_(3)OH(1)and[Gd_(2)(dbm)_(2)(L_(2))_(2)(CH_(3)OH)_(2)]·2CH_(3)OH(2),where H_(3)L_(1)=(Z)-N'-[4-(diethylamino)-2-hydroxybenzylidene...Two Gd_(2)complexes,namely[Gd_(2)(dbm)_(2)(HL_(1))_(2)(CH_(3)OH)_(2)]·4CH_(3)OH(1)and[Gd_(2)(dbm)_(2)(L_(2))_(2)(CH_(3)OH)_(2)]·2CH_(3)OH(2),where H_(3)L_(1)=(Z)-N'-[4-(diethylamino)-2-hydroxybenzylidene]-2-hydroxyacetohydrazide,H_(2)L_(2)=(E)-N'-(5-bromo-2-hydroxy-3-methoxybenzylidene)nicotinohydrazide,Hdbm=dibenzoylmethane,have been constructed by adopting the solvothermal method.Structural characterization unveils that both complexes 1 and 2 are constituted by two Gd^(3+)ions,two dbm-ions,two CH_(3)OH molecules,and two polydentate Schiff-base ligands(HL_(1)^(2-)or L_(2)^(2-)).In addition,complex 1 contains four free methanol molecules,whereas complex 2 harbors two free methanol molecules.By investigating the interactions between complexes 1 and 2 and four types of bacteria(Bacillus subtilis,Escherichia coli,Staphylococcus aureus,Candida albicans),it was found that both complexes 1 and 2 exhibited potent antibacte-rial activities.The interaction mechanisms between the ligands H_(3)L_(1),H_(2)L_(2),complexes 1 and 2,and calf thymus DNA(CT-DNA)were studied using ultraviolet-visible spectroscopy,fluorescence titration,and cyclic voltammetry.The results demonstrated that both complexes 1 and 2 can intercalate into CT-DNA molecules,thereby inhibiting bacterial proliferation to achieve the antibacterial effects.CCDC:2401116,1;2401117,2.展开更多
There is curiosity and awareness throughout the world regarding the role of Information and Communication technologies. This is felt in each and every section of society. Several studies have confirmed and considered ...There is curiosity and awareness throughout the world regarding the role of Information and Communication technologies. This is felt in each and every section of society. Several studies have confirmed and considered information and communication technology’s significance in the field of education. It has not only affected learners but also to the teachers. This paper explores how ICT-based projects affect teachers’ and students’ attitudes. The data was collected through self-prepared attitude scale. It was distributed among the teachers and students of various schools. Two hundred students and one hundred twenty teachers responded to the questionnaire. Analysis was done through the data collected from the teachers as well as from students. The study’s conclusions demonstrated that while there was no significant variation in the attitudes of teachers utilizing different ICT-based programs, there was a substantial difference in the students’ attitude toward learning with different ICT-based programs.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
A tetranuclear Ln(Ⅲ)-based complex:[Dy_(4)(dbm)_(4)(L)_(6)(μ_(3)-OH)_(2)]·CH_(3)CN(1)(HL=5-[(4-methylbenzylidene)amino]quinolin-8-ol,Hdbm=dibenzoylmethane)was manufactured and its structure was characterized in...A tetranuclear Ln(Ⅲ)-based complex:[Dy_(4)(dbm)_(4)(L)_(6)(μ_(3)-OH)_(2)]·CH_(3)CN(1)(HL=5-[(4-methylbenzylidene)amino]quinolin-8-ol,Hdbm=dibenzoylmethane)was manufactured and its structure was characterized in detail.Xray diffraction analysis shows that complex 1 belongs to the monoclinic crystal system and its space group is P2_1/n,which contains a rhombic Dy_(4)core.Magnetic measurements of 1 suggest it possesses extraordinary single-molecule magnet(SMM)behavior.Its energy barrier U_(eff)/k_(B)was 116.7 K,and the pre-exponential coefficient τ_(0)=1.05×10~(-8)s.CCDC:2359322.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
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
Traditional rule-based IntrusionDetection Systems(IDS)are commonly employed owing to their simple design and ability to detect known threats.Nevertheless,as dynamic network traffic and a new degree of threats exist in...Traditional rule-based IntrusionDetection Systems(IDS)are commonly employed owing to their simple design and ability to detect known threats.Nevertheless,as dynamic network traffic and a new degree of threats exist in IoT environments,these systems do not perform well and have elevated false positive rates—consequently decreasing detection accuracy.In this study,we try to overcome these restrictions by employing fuzzy logic and machine learning to develop an Enhanced Rule-Based Model(ERBM)to classify the packets better and identify intrusions.The ERBM developed for this approach improves data preprocessing and feature selections by utilizing fuzzy logic,where three membership functions are created to classify all the network traffic features as low,medium,or high to remain situationally aware of the environment.Such fuzzy logic sets produce adaptive detection rules by reducing data uncertainty.Also,for further classification,machine learning classifiers such as Decision Tree(DT),Random Forest(RF),and Neural Networks(NN)learn complex ways of attacks and make the detection process more precise.A thorough performance evaluation using different metrics,including accuracy,precision,recall,F1 Score,detection rate,and false-positive rate,verifies the supremacy of ERBM over classical IDS.Under extensive experiments,the ERBM enables a remarkable detection rate of 99%with considerably fewer false positives than the conventional models.Integrating the ability for uncertain reasoning with fuzzy logic and an adaptable component via machine learning solutions,the ERBM systemprovides a unique,scalable,data-driven approach to IoT intrusion detection.This research presents a major enhancement initiative in the context of rule-based IDS,introducing improvements in accuracy to evolving IoT threats.展开更多
COMPUTATIONAL experiments method is an essential tool for analyzing,designing,managing,and integrating complex systems.However,a significant challenge arises in constructing agents with human-like characteristics to f...COMPUTATIONAL experiments method is an essential tool for analyzing,designing,managing,and integrating complex systems.However,a significant challenge arises in constructing agents with human-like characteristics to form an AI society.Agent modeling typically encompasses four levels:1)The autonomy features of agents,e.g.,perception,behavior,and decision-making;2)The evolutionary features of agents,e.g.,bounded rationality,heterogeneity,and learning evolution;3)The social features of agents,e.g.,interaction,cooperation,and competition;4)The emergent features of agents,e.g.,gaming with environments or regulatory strategies.Traditional modeling techniques primarily derive from ABMs(Agent-based Models)and incorporate various emerging technologies(e.g.,machine learning,big data,and social networks),which can enhance modeling capabilities,while amplifying the complexity[1].展开更多
Dear Editor,This letter presents a novel approach to the data-driven control of unknown nonlinear systems.By leveraging online sparse identification based on the Koopman operator,a high-dimensional linear system model...Dear Editor,This letter presents a novel approach to the data-driven control of unknown nonlinear systems.By leveraging online sparse identification based on the Koopman operator,a high-dimensional linear system model approximating the actual system is obtained online.The upper bound of the discrepancy between the identified model and the actual system is estimated using real-time prediction error,which is then utilized in the design of a tube-based robust model predictive controller.The effectiveness of the proposed approach is validated by numerical simulation.展开更多
Economic violence is a form of domestic violence that extends beyond physical harm,affecting victims’economic stability and independence.This situation perpetuates gender inequality and also reinforces the cycle of g...Economic violence is a form of domestic violence that extends beyond physical harm,affecting victims’economic stability and independence.This situation perpetuates gender inequality and also reinforces the cycle of gender-based violence.With definitions of economic violence broadening to encompass a range of coercive and manipulative behaviors-from financial abuse in domestic violence scenarios to the economic harassment faced by stay-at-home moms-understanding this form of exploitation is crucial for crafting effective interventions.This article aims to delve into various facets of economic violence,including its definition,prevalence,and the stark realities it creates for its victims.Following the search of international databases:Social Work Abstracts(EBSCO),Psychology Abstracts,Family and Women Studies Worldwide,Psychiatry Online,Psych INFO(including Psych ARTICLES),PubMed,Wiley,and Scopus,60 peer-reviewed articles that met all inclusion criteria were included in the paper.Our review clarifies that looking forward,the call for a comprehensive understanding of economic violence,enhanced legal frameworks,and the strengthening of supportive networks underscore the multidisciplinary approach required to combat this issue effectively.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
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
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.
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.
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.
文摘Two new complexes,[Zn_(2)(L1)(HL1)(NO_(3))]·CH_(3)OH(1)and[Zn_(3)(L2)(L3)_(3)Cl]·CH_(3)OH(2),were successfully synthesized by‘one-pot’method based on cinnoline-3-ylhydrazine ligand and zinc with 2-hydroxy-4-methoxybenzaldehyde and 2-hydroxy-3-methoxybenzaldehyde ligands,respectively,where H_(2)L1=5-methoxy-2-(phthalazin-1-ylhydrazonomethyl)-phenol,H_(2)L2=2-methoxy-6-(phthalazin-1-yl-hydrazonomethyl)-phenol,HL3=2-(1,8-dihydro-[1,2,4]triazolo[3,4-α]phthalazin-3-yl)-6-methoxy-phenol.Complexes 1 and 2 were characterized by infrared spectroscopy,elemental analysis,single-crystal X-ray diffraction,powder X-ray diffraction,etc.It is worth noting that the cinnolin-3-yl-hydrazine ligand and 2-hydroxy-3-methoxybenzaldehyde form two types of Schiff bases(H_(2)L2 and HL3)when in situ reacting and coordinating with Zn(Ⅱ),and HL3 also has two coordination modes.In addition,the fluorescence performance showed that complex 1 can achieve selective and sensitive sensing of Al^(3+)in water with a detection limit of 6.37μmol·L^(-1).CCDC:2413978,1;2413979,2.
文摘Two Gd_(2)complexes,namely[Gd_(2)(dbm)_(2)(HL_(1))_(2)(CH_(3)OH)_(2)]·4CH_(3)OH(1)and[Gd_(2)(dbm)_(2)(L_(2))_(2)(CH_(3)OH)_(2)]·2CH_(3)OH(2),where H_(3)L_(1)=(Z)-N'-[4-(diethylamino)-2-hydroxybenzylidene]-2-hydroxyacetohydrazide,H_(2)L_(2)=(E)-N'-(5-bromo-2-hydroxy-3-methoxybenzylidene)nicotinohydrazide,Hdbm=dibenzoylmethane,have been constructed by adopting the solvothermal method.Structural characterization unveils that both complexes 1 and 2 are constituted by two Gd^(3+)ions,two dbm-ions,two CH_(3)OH molecules,and two polydentate Schiff-base ligands(HL_(1)^(2-)or L_(2)^(2-)).In addition,complex 1 contains four free methanol molecules,whereas complex 2 harbors two free methanol molecules.By investigating the interactions between complexes 1 and 2 and four types of bacteria(Bacillus subtilis,Escherichia coli,Staphylococcus aureus,Candida albicans),it was found that both complexes 1 and 2 exhibited potent antibacte-rial activities.The interaction mechanisms between the ligands H_(3)L_(1),H_(2)L_(2),complexes 1 and 2,and calf thymus DNA(CT-DNA)were studied using ultraviolet-visible spectroscopy,fluorescence titration,and cyclic voltammetry.The results demonstrated that both complexes 1 and 2 can intercalate into CT-DNA molecules,thereby inhibiting bacterial proliferation to achieve the antibacterial effects.CCDC:2401116,1;2401117,2.
文摘There is curiosity and awareness throughout the world regarding the role of Information and Communication technologies. This is felt in each and every section of society. Several studies have confirmed and considered information and communication technology’s significance in the field of education. It has not only affected learners but also to the teachers. This paper explores how ICT-based projects affect teachers’ and students’ attitudes. The data was collected through self-prepared attitude scale. It was distributed among the teachers and students of various schools. Two hundred students and one hundred twenty teachers responded to the questionnaire. Analysis was done through the data collected from the teachers as well as from students. The study’s conclusions demonstrated that while there was no significant variation in the attitudes of teachers utilizing different ICT-based programs, there was a substantial difference in the students’ attitude toward learning with different ICT-based programs.
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.
文摘A tetranuclear Ln(Ⅲ)-based complex:[Dy_(4)(dbm)_(4)(L)_(6)(μ_(3)-OH)_(2)]·CH_(3)CN(1)(HL=5-[(4-methylbenzylidene)amino]quinolin-8-ol,Hdbm=dibenzoylmethane)was manufactured and its structure was characterized in detail.Xray diffraction analysis shows that complex 1 belongs to the monoclinic crystal system and its space group is P2_1/n,which contains a rhombic Dy_(4)core.Magnetic measurements of 1 suggest it possesses extraordinary single-molecule magnet(SMM)behavior.Its energy barrier U_(eff)/k_(B)was 116.7 K,and the pre-exponential coefficient τ_(0)=1.05×10~(-8)s.CCDC:2359322.
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.
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.
基金A research grant from the Multimedia University,Malaysia supports this work。
文摘Traditional rule-based IntrusionDetection Systems(IDS)are commonly employed owing to their simple design and ability to detect known threats.Nevertheless,as dynamic network traffic and a new degree of threats exist in IoT environments,these systems do not perform well and have elevated false positive rates—consequently decreasing detection accuracy.In this study,we try to overcome these restrictions by employing fuzzy logic and machine learning to develop an Enhanced Rule-Based Model(ERBM)to classify the packets better and identify intrusions.The ERBM developed for this approach improves data preprocessing and feature selections by utilizing fuzzy logic,where three membership functions are created to classify all the network traffic features as low,medium,or high to remain situationally aware of the environment.Such fuzzy logic sets produce adaptive detection rules by reducing data uncertainty.Also,for further classification,machine learning classifiers such as Decision Tree(DT),Random Forest(RF),and Neural Networks(NN)learn complex ways of attacks and make the detection process more precise.A thorough performance evaluation using different metrics,including accuracy,precision,recall,F1 Score,detection rate,and false-positive rate,verifies the supremacy of ERBM over classical IDS.Under extensive experiments,the ERBM enables a remarkable detection rate of 99%with considerably fewer false positives than the conventional models.Integrating the ability for uncertain reasoning with fuzzy logic and an adaptable component via machine learning solutions,the ERBM systemprovides a unique,scalable,data-driven approach to IoT intrusion detection.This research presents a major enhancement initiative in the context of rule-based IDS,introducing improvements in accuracy to evolving IoT threats.
基金supported in part by National Key Research and Development Program of China(2021YFF0900800)National Natural Science Foundation of China(62472306,62441221,62206116)+2 种基金Tianjin University’s 2024 Special Project on Disciplinary Development(XKJS-2024-5-9)Tianjin University Talent Innovation Reward Program for Literature&Science Graduate Student(C1-2022-010)Shanxi Province Social Science Foundation(2020F002).
文摘COMPUTATIONAL experiments method is an essential tool for analyzing,designing,managing,and integrating complex systems.However,a significant challenge arises in constructing agents with human-like characteristics to form an AI society.Agent modeling typically encompasses four levels:1)The autonomy features of agents,e.g.,perception,behavior,and decision-making;2)The evolutionary features of agents,e.g.,bounded rationality,heterogeneity,and learning evolution;3)The social features of agents,e.g.,interaction,cooperation,and competition;4)The emergent features of agents,e.g.,gaming with environments or regulatory strategies.Traditional modeling techniques primarily derive from ABMs(Agent-based Models)and incorporate various emerging technologies(e.g.,machine learning,big data,and social networks),which can enhance modeling capabilities,while amplifying the complexity[1].
基金supported by the National Natural Science Foundation of China(62473020).
文摘Dear Editor,This letter presents a novel approach to the data-driven control of unknown nonlinear systems.By leveraging online sparse identification based on the Koopman operator,a high-dimensional linear system model approximating the actual system is obtained online.The upper bound of the discrepancy between the identified model and the actual system is estimated using real-time prediction error,which is then utilized in the design of a tube-based robust model predictive controller.The effectiveness of the proposed approach is validated by numerical simulation.
文摘Economic violence is a form of domestic violence that extends beyond physical harm,affecting victims’economic stability and independence.This situation perpetuates gender inequality and also reinforces the cycle of gender-based violence.With definitions of economic violence broadening to encompass a range of coercive and manipulative behaviors-from financial abuse in domestic violence scenarios to the economic harassment faced by stay-at-home moms-understanding this form of exploitation is crucial for crafting effective interventions.This article aims to delve into various facets of economic violence,including its definition,prevalence,and the stark realities it creates for its victims.Following the search of international databases:Social Work Abstracts(EBSCO),Psychology Abstracts,Family and Women Studies Worldwide,Psychiatry Online,Psych INFO(including Psych ARTICLES),PubMed,Wiley,and Scopus,60 peer-reviewed articles that met all inclusion criteria were included in the paper.Our review clarifies that looking forward,the call for a comprehensive understanding of economic violence,enhanced legal frameworks,and the strengthening of supportive networks underscore the multidisciplinary approach required to combat this issue effectively.
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.
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.
