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
Application research of neural networks to geotechnical engineering has become a hotspot nowadays.General model may not reach the predicting precision in practical application due to different characteristics in diffe...Application research of neural networks to geotechnical engineering has become a hotspot nowadays.General model may not reach the predicting precision in practical application due to different characteristics in different fields.In allusion to this,an elasto-plastic constitutive model based on clustering radial basis function neural network(BC-RBFNN) was proposed for moderate sandy clay according to its properties.Firstly,knowledge base was established on triaxial compression testing data;then the model was trained,learned and emulated using knowledge base;finally,predicting results of the BC-RBFNN model were compared and analyzed with those of other intelligent model.The results show that the BC-RBFNN model can alter the training and learning velocity and improve the predicting precision,which provides possibility for engineering practice on demanding high precision.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
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
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
Base editors are essential tools for precise genome editing in plants.However,achieving high efficiency in C-to-G editing while minimizing byproduct and offtarget mutations remains challenging.In this study,we present...Base editors are essential tools for precise genome editing in plants.However,achieving high efficiency in C-to-G editing while minimizing byproduct and offtarget mutations remains challenging.In this study,we present the development and evaluation of a novel glycosylase-based cytosine base editor(gCBE)for efficient C-to-G editing in rice.Unlike traditional cytosine base editors,which rely on cytosine deamination,gCBE directly excises cytosine to generate an apurinic/apyrimidinic(AP)site,thus circumventing the deamination step and reducing the production of C-to-T byproducts.We constructed several gCBE variants,including N-gCBE,M-gCBE,and C-gCBE,by fusing engineered human UDG2(UNG*)to SpCas9 nickase(nSpCas9,D10A)and tested their editing efficiency and specificity in rice.Our results demonstrate that M-gCBE achieved efficient C-to-G editing(6.3%to 37.5%)similar to OsCGBE(9.4%to 28.1%)at most targets,though with site-dependent variations.Notably,gCBE tools showed a marked reduction in C-to-T byproducts,with average C-to-T mutation rates of 12.5%for N-gCBE and 16.7%for M-gCBE,compared to 53.1%for OsCGBE.Notably,both N-gCBE and M-gCBE were capable of generating homozygous C-to-G mutations in the T_(0)generation,a key advantage over OsCGBE,which predominantly generated C-to-T mutations.Off-target analysis revealed minimal off-target effects with M-gCBE,highlighting its potential for high-precision genome editing.These findings suggest that gCBE tools,particularly M-gCBE,are highly efficient and precise,providing an advanced solution for C-to-G editing in plants and offering promising applications for crop improvement.展开更多
Offline policy evaluation,evaluating and selecting complex policies for decision-making by only using offline datasets is important in reinforcement learning.At present,the model-based offline policy evaluation(MBOPE)...Offline policy evaluation,evaluating and selecting complex policies for decision-making by only using offline datasets is important in reinforcement learning.At present,the model-based offline policy evaluation(MBOPE)is widely welcomed because of its easy to implement and good performance.MBOPE directly approximates the unknown value of a given policy using the Monte Carlo method given the estimated transition and reward functions of the environment.Usually,multiple models are trained,and then one of them is selected to be used.However,a challenge remains in selecting an appropriate model from those trained for further use.The authors first analyse the upper bound of the difference between the approximated value and the unknown true value.Theoretical results show that this difference is related to the trajectories generated by the given policy on the learnt model and the prediction error of the transition and reward functions at these generated data points.Based on the theoretical results,a new criterion is proposed to tell which trained model is better suited for evaluating the given policy.At last,the effectiveness of the proposed criterion is demonstrated on both benchmark and synthetic offline datasets.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Project(07031B) supported by the Scientific Research Fund of Central South University of Forestry and TechnologyProject(06C843) supported by the Scientific Research Fund of Hunan Provincial Education Department
文摘Application research of neural networks to geotechnical engineering has become a hotspot nowadays.General model may not reach the predicting precision in practical application due to different characteristics in different fields.In allusion to this,an elasto-plastic constitutive model based on clustering radial basis function neural network(BC-RBFNN) was proposed for moderate sandy clay according to its properties.Firstly,knowledge base was established on triaxial compression testing data;then the model was trained,learned and emulated using knowledge base;finally,predicting results of the BC-RBFNN model were compared and analyzed with those of other intelligent model.The results show that the BC-RBFNN model can alter the training and learning velocity and improve the predicting precision,which provides possibility for engineering practice on demanding high precision.
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.
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.
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supported by the National Natural Science Foundation of China(82404798)the Natural Science Foundation of Sichuan Province(2024NSFSC1831)+1 种基金the National Key Laboratory for Tropical Crop Breeding(NKLTCB-RC202403,NKLTCBZRJJ4)the Hainan Seed Industrial Laboratory(B22C1000P).
文摘Base editors are essential tools for precise genome editing in plants.However,achieving high efficiency in C-to-G editing while minimizing byproduct and offtarget mutations remains challenging.In this study,we present the development and evaluation of a novel glycosylase-based cytosine base editor(gCBE)for efficient C-to-G editing in rice.Unlike traditional cytosine base editors,which rely on cytosine deamination,gCBE directly excises cytosine to generate an apurinic/apyrimidinic(AP)site,thus circumventing the deamination step and reducing the production of C-to-T byproducts.We constructed several gCBE variants,including N-gCBE,M-gCBE,and C-gCBE,by fusing engineered human UDG2(UNG*)to SpCas9 nickase(nSpCas9,D10A)and tested their editing efficiency and specificity in rice.Our results demonstrate that M-gCBE achieved efficient C-to-G editing(6.3%to 37.5%)similar to OsCGBE(9.4%to 28.1%)at most targets,though with site-dependent variations.Notably,gCBE tools showed a marked reduction in C-to-T byproducts,with average C-to-T mutation rates of 12.5%for N-gCBE and 16.7%for M-gCBE,compared to 53.1%for OsCGBE.Notably,both N-gCBE and M-gCBE were capable of generating homozygous C-to-G mutations in the T_(0)generation,a key advantage over OsCGBE,which predominantly generated C-to-T mutations.Off-target analysis revealed minimal off-target effects with M-gCBE,highlighting its potential for high-precision genome editing.These findings suggest that gCBE tools,particularly M-gCBE,are highly efficient and precise,providing an advanced solution for C-to-G editing in plants and offering promising applications for crop improvement.
文摘Offline policy evaluation,evaluating and selecting complex policies for decision-making by only using offline datasets is important in reinforcement learning.At present,the model-based offline policy evaluation(MBOPE)is widely welcomed because of its easy to implement and good performance.MBOPE directly approximates the unknown value of a given policy using the Monte Carlo method given the estimated transition and reward functions of the environment.Usually,multiple models are trained,and then one of them is selected to be used.However,a challenge remains in selecting an appropriate model from those trained for further use.The authors first analyse the upper bound of the difference between the approximated value and the unknown true value.Theoretical results show that this difference is related to the trajectories generated by the given policy on the learnt model and the prediction error of the transition and reward functions at these generated data points.Based on the theoretical results,a new criterion is proposed to tell which trained model is better suited for evaluating the given policy.At last,the effectiveness of the proposed criterion is demonstrated on both benchmark and synthetic offline datasets.
