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
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
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
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
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 advent of the digital age has consistently provided impetus for facilitating global trade,as evidenced by the numerous customs clearance documents and participants involved in the international trade process,inclu...The advent of the digital age has consistently provided impetus for facilitating global trade,as evidenced by the numerous customs clearance documents and participants involved in the international trade process,including enterprises,agents,and government departments.However,the urgent issue that requires immediate attention is how to achieve secure and efficient cross-border data sharing among these government departments and enterprises in complex trade processes.In addressing this need,this paper proposes a data exchange architecture employing Multi-Authority Attribute-Based Encryption(MA-ABE)in combination with blockchain technology.This scheme supports proxy decryption,attribute revocation,and policy update,while allowing each participating entity to manage their keys autonomously,ensuring system security and enhancing trust among participants.In order to enhance system decentralization,a mechanism has been designed in the architecture where multiple institutions interact with smart contracts and jointly participate in the generation of public parameters.Integration with the multi-party process execution engine Caterpillar has been shown to boost the transparency of cross-border information flow and cooperation between different organizations.The scheme ensures the auditability of data access control information and the visualization of on-chain data sharing.The MA-ABE scheme is statically secure under the q-Decisional Parallel Bilinear Diffie-Hellman Exponent(q-DPBDHE2)assumption in the random oracle model,and can resist ciphertext rollback attacks to achieve true backward and forward security.Theoretical analysis and experimental results demonstrate the appropriateness of the scheme for cross-border data collaboration between different institutions.展开更多
Lithium-sulfur(Li-S)batteries are widely deemed to be one of the most potential candidates for future secondary batteries because of their remarkable energy density.Nevertheless,notorious polysulfide shuttling and ret...Lithium-sulfur(Li-S)batteries are widely deemed to be one of the most potential candidates for future secondary batteries because of their remarkable energy density.Nevertheless,notorious polysulfide shuttling and retarded sulfur reaction kinetics pose significant obstacles to the further application of Li-S batteries.While rationally designed highly active electrocatalysts can facilitate polysulfide conversion,the universal and scalable synthesis strategies need to be developed.Herein,a universal synthetic strategy to construct a series of three-dimensional(3D)porous graphene-iron(3DGr-Fe)based electrocatalysts involving 3DGr-FeP,3DGr-Fe_(3)C,and 3DGr-Fe_(3)Se_(4)is exploited for manipulating the Li-S redox reactions.It has been observed that the implementation of a 3D porous Gr architecture leads to the well-designed conductive networks,while the uniformly dispersed iron nanoparticles introduce an abundance of active sites,fostering the lithium polysulfide conversion,thereby bolstering the overall electrochemical performance.The Li-S battery with the 3DGr-Fe based electrocatalyst exhibits remarkable capacity retention of 94.8%upon 100 times at 0.2 C.Moreover,the soft-packaged Li-S pouch cell based on such a 3DGr-Fe electrocatalyst delivers superior capacity of 1060.71 mA h g^(-1)and guarantees for the continuous 30 min work of fan toy.This investigation gives comprehensive insights into the design,synthesis,and mechanism of 3DGr-Fe based electrocatalysts with high activity toward efficient and durable Li-S batteries.展开更多
Objective:To explore the effectiveness of multi-modal teaching based on an online case library in the education of gene methylation combined with spiral computed tomography(CT)screening for pulmonary ground-glass opac...Objective:To explore the effectiveness of multi-modal teaching based on an online case library in the education of gene methylation combined with spiral computed tomography(CT)screening for pulmonary ground-glass opacity(GGO)nodules.Methods:From October 2023 to April 2024,66 medical imaging students were selected and randomly divided into a control group and an observation group,each with 33 students.The control group received traditional lecture-based teaching,while the observation group was taught using a multi-modal teaching approach based on an online case library.Performance on assessments and teaching quality were analyzed between the two groups.Results:The observation group achieved higher scores in theoretical and practical knowledge compared to the control group(P<0.05).Additionally,the teaching quality scores were significantly higher in the observation group(P<0.05).Conclusion:Implementing multi-modal teaching based on an online case library for pulmonary GGO nodule screening with gene methylation combined with spiral CT can enhance students’knowledge acquisition,improve teaching quality,and have significant clinical application value.展开更多
Because of an unfortunate mistake by authors,the Project(5227010679)of Foundation item was wrong.The corrected Project is shown as follows:Project(52271073).
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
Remote sensing and web-based platforms have emerged as vital tools in the effective monitoring of mangrove ecosystems, which are crucial for coastal protection, biodiversity, and carbon sequestration. Utilizing satell...Remote sensing and web-based platforms have emerged as vital tools in the effective monitoring of mangrove ecosystems, which are crucial for coastal protection, biodiversity, and carbon sequestration. Utilizing satellite imagery and aerial data, remote sensing allows researchers to assess the health and extent of mangrove forests over large areas and time periods, providing insights into changes due to environmental stressors like climate change, urbanization, and deforestation. Coupled with web-based platforms, this technology facilitates real-time data sharing and collaborative research efforts among scientists, policymakers, and conservationists. Thus, there is a need to grow this research interest among experts working in this kind of ecosystem. The aim of this paper is to provide a comprehensive literature review on the effective role of remote sensing and web-based platform in monitoring mangrove ecosystem. The research paper utilized the thematic approach to extract specific information to use in the discussion which helped realize the efficiency of digital monitoring for the environment. Web-based platforms and remote sensing represent a powerful tool for environmental monitoring, particularly in the context of forest ecosystems. They facilitate the accessibility of vital data, promote collaboration among stakeholders, support evidence-based policymaking, and engage communities in conservation efforts. As experts confront the urgent challenges posed by climate change and environmental degradation, leveraging technology through web-based platforms is essential for fostering a sustainable future for the forests of the world.展开更多
Objective: In the Healthy Child Action Enhancement Program (2021-2025), it is proposed to ensure the safety and health of newborns and to promote high-quality development of health. Our department established risk ass...Objective: In the Healthy Child Action Enhancement Program (2021-2025), it is proposed to ensure the safety and health of newborns and to promote high-quality development of health. Our department established risk assessment criteria for medical adhesives in neonates by applying the best evidence in the management program for the reduction of medical adhesive-associated skin injuries in neonates, in terms of the use and removal of adhesives. Methods: A systematic search and quality assessment of topics related to medical adhesive-related skin injury in neonates was conducted to summarize the best evidence and to conduct a quality review in the neonatal unit. Results: After 2 rounds of review, medical and nursing staff in the neonatal unit had a 98% compliance rate for the knowledge of neonatal medical adhesive-related skin injury and a satisfactory compliance rate for the other 9 indicators;after the application of the evidence, the incidence of neonatal medical adhesive-related skin injury was significantly lower than that before the application of the evidence, and the differences were statistically significant (P Conclusion: The application of the best evidence-based management program in neonatal medical adhesive-associated skin injury can reduce the incidence of neonatal medical adhesive-associated skin injury, reduce neonatal infections, and improve the integrity of the protective skin barrier in neonates.展开更多
Four powder metallurgy(PM)Ni-based superalloys with different Hf and Ta contents were creep-tested at 650℃ and 970 MPa,700℃ and 770 MPa,and 750℃ and 580 MPa,respectively.The effect of Hf and Ta on creep deformation...Four powder metallurgy(PM)Ni-based superalloys with different Hf and Ta contents were creep-tested at 650℃ and 970 MPa,700℃ and 770 MPa,and 750℃ and 580 MPa,respectively.The effect of Hf and Ta on creep deformation behaviors of the superalloys was studied from multiple scales by SEM,electron backscatter diffraction(EBSD),and aberration-corrected scanning transmission electron microscope(AC-STEM).The results showed that Hf and Ta suppressed the intergranular fracture and initiation of cracks during the acceleration creep stage,which prolonged the creep rupture time.Hf and Ta inhibited the stacking faults extending and the dislocation climbing and promoted the Suzuki segregation of W during the steady-state creep stage,which reduced the minimum creep rate and delayed the start time of the acceleration creep stage.The Suzuki segregation of Co,Cr,Mo,Ti,Nb,W,and Ta along stacking faults was observed after Hf and Ta addition,leading to the localized phase transformation in the γ′phase,and the stacking fault phase was chemically disordered.This study provided ideas for the composition design of novel PM Ni-based superalloys and theoretical foundations for the combined addition of Hf and Ta.展开更多
Carbon dioxide (CO2) is a substantial contributor to global warming owing to its long atmospheric lifetime and high potential for global warming. It is related to the processes of raw material mining and industry, whi...Carbon dioxide (CO2) is a substantial contributor to global warming owing to its long atmospheric lifetime and high potential for global warming. It is related to the processes of raw material mining and industry, which is fundamental to economic development but also has negative impacts on the environment, namely the increase of global temperature and solid waste. To address this, various carbon capture, storage, utilization, and mineralization methods have emerged, but they remain at an early stage of development. This review discusses the applicability of solid waste materials, and slurry form in particular, for CO2 mineralization. It analyzes frequently researched materials, carbonation capabilities, reaction mechanisms, and industrial uses. Industrial waste materials, cement, and demolition waste are widely used in carbonation reactions because of their abundance and high Ca/Mg oxide content. The review also discusses carbonation types, including two major types—direct and indirect—which fall under the ex-situ category. The key factors influencing the carbonation efficiency include the CO2 concentration, temperature, pressure, particle size, and reaction chamber type. The construction sector is the principal beneficiary of carbonated materials due to the cementitious characteristics of recarbonated byproducts and precipitated calcium carbonate (PCC). Other industries, such as paper, plastics, and pharmaceuticals, also find applications for PCC. Future research is recommended to explore new materials for slurry carbonation, with potential applications in underground mine support for carbon sequestration and subsidence control.展开更多
Objective: To develop a best-evidence-based optimal nutrition management plan for patients with chronic heart failure, apply it in clinical practice, and evaluate its effectiveness. Methods: Use the KTA knowledge tran...Objective: To develop a best-evidence-based optimal nutrition management plan for patients with chronic heart failure, apply it in clinical practice, and evaluate its effectiveness. Methods: Use the KTA knowledge translation model to guide evidence-based practice in nutrition management, and compare the nutritional status, cardiac function status, quality of life, and quality review indicators of chronic heart failure patients before and after the application of evidence. Results: After the application of evidence, the nutritional status indicators (MNA-SF score, albumin, hemoglobin) of two groups of heart failure patients significantly increased compared to before the application of evidence, with statistically significant differences (p Conclusion: The KTA knowledge translation model provides methodological guidance for the implementation of evidence-based practice for heart failure patients. This evidence-based practice project is beneficial for improving the outcomes of malnutrition in chronic heart failure patients and is conducive to standardizing nursing pathways, thereby promoting the improvement of nursing quality.展开更多
The rapid growth of technology impacts all aspects of modern life, including banking and financial transactions. While these industries benefit significantly from technological advancements, they also face challenges ...The rapid growth of technology impacts all aspects of modern life, including banking and financial transactions. While these industries benefit significantly from technological advancements, they also face challenges such as credit card fraud, the most prevalent type of financial fraud. Each year, such fraud leads to billions of dollars in losses for banks, financial institutions, and customers. Although many machine learning (ML) and, more recently, deep learning (DL) solutions have been developed to address this issue, most fail to strike an effective balance between speed and performance. Moreover, the reluctance of financial institutions to disclose their fraud datasets due to reputational risks adds further challenges. This study proposes a predictive model for credit card fraud detection that leverages the unique strengths of Energy-based Restricted Boltzmann Machines (EB-RBM) and Extended Long Short-Term Memory (xLSTM) models. EB-RBM is utilized for its ability to detect new and previously unseen fraudulent patterns, while xLSTM focuses on identifying known fraud types. These models are integrated using an ensemble approach to combine their strengths, achieving a balanced and reliable prediction system. The ensemble employs a bootstrap max-voting mechanism, assigning equal voting rights to EB-RBM and xLSTM, followed by result normalization and aggregation to classify transactions as fraudulent or genuine. The model’s performance is evaluated using metrics such as AUC-ROC, AUC-PR, precision, recall, F1-score, confusion matrix, and elapsed time. Experimental results on a real-world European cardholder dataset demonstrate that the proposed approach effectively balances speed and performance, outperforming recent models in the field.展开更多
The pandemic highlighted significant gaps in the public health infrastructure impacted by shortages of public health workers, an undertrained workforce, and years of disinvestment. These gaps required innovative probl...The pandemic highlighted significant gaps in the public health infrastructure impacted by shortages of public health workers, an undertrained workforce, and years of disinvestment. These gaps required innovative problem-solving by public health agencies (PHAs), including local health departments (LHDs), to respond to rapidly changing community conditions during and after the pandemic. Many schools and programs of public health (SPPH) worked with PHAs to mobilize public health (PH) students through practice-based teaching (PBT). Current research indicates PBT benefits all stakeholders—PHAs, students, faculty, SPPH, and ultimately the community served. However, more research is needed on the utility of PBT in addressing a community’s systemic public health issues, the extent to which the academic-community collaboration enhances a PHA’s capacity, and the impact of the pedagogy on preparing the workforce for an evolving PH landscape. This paper examines the process of a semester-long PBT course, guided by the PBT STEPS framework, which includes five steps from collaboration to implementation to evaluation of a PBT course. The collaborating PHA and its student group addressed community trauma and resilience issues during the semester. Additionally, it examines the longer-term impacts after the semester for the PHA, community, and the workforce by 1) conducting a formative evaluation to understand needs and gaps in the community;2) redesigning an intervention that merged the results of the formative evaluation with the intervention developed during the semester;and 3) securing funding and resources for intervention sustainability. Through the documentation of a post-course partnership between an LHD and faculty at a large school of public health, this case study illustrates the potential for PBT to lay the foundation for ongoing research that supports more impactful interventions for PHAs while bolstering the workforce abilities of students as future practitioners.展开更多
Oats, frequently incorporated into skincare formulations for their anti-inflammatory, moisturizing, and barrier-repairing properties, may present an overlooked risk to individuals with celiac disease, particularly whe...Oats, frequently incorporated into skincare formulations for their anti-inflammatory, moisturizing, and barrier-repairing properties, may present an overlooked risk to individuals with celiac disease, particularly when applied to compromised skin. Although pure oats are inherently gluten-free, the widespread contamination with gluten-containing grains like wheat, barley, or rye during agricultural and processing stages introduces the potential for gluten exposure through topical application. This raises important questions about whether gluten proteins, when applied to damaged skin, might penetrate the epidermal barrier and contribute to immune responses in genetically predisposed celiac patients, given that even minute amounts of gluten can trigger systemic symptoms. Emerging evidence suggests that transdermal absorption of gluten peptides through impaired skin integrity might bypass the gastrointestinal route, yet the precise mechanisms and clinical significance of this pathway remain poorly understood. The role of compromised skin in facilitating gluten absorption and the possible activation of CD4+ T-cells, mimicking gastrointestinal pathways, warrants further investigation. Additionally, the ability of gluten peptides to reach deeper dermal layers and potentially enter the systemic circulation remains speculative, though theoretically possible in severely disrupted skin barriers. Without clinical and molecular studies to determine the risk of topical gluten exposure, particularly in celiac patients with skin injuries, there remains a potential for undetected immune activation and subsequent adverse health outcomes in this sensitive population.展开更多
Object-based classification differentiates forest gaps from canopies at large regional scale by using remote sensing data. To study the segmentation and classification processes of object-based forest gaps classificat...Object-based classification differentiates forest gaps from canopies at large regional scale by using remote sensing data. To study the segmentation and classification processes of object-based forest gaps classification at a regional scale, we sampled a natural secondary forest in northeast China at Maoershan Experimental Forest Farm.Airborne light detection and ranging(LiDAR; 3.7 points/m2) data were collected as the original data source and the canopy height model(CHM) and topographic dataset were extracted from the LiDAR data. The accuracy of objectbased forest gaps classification depends on previous segmentation. Thus our first step was to define 10 different scale parameters in CHM image segmentation. After image segmentation, the machine learning classification method was used to classify three kinds of object classes, namely,forest gaps, tree canopies, and others. The common support vector machine(SVM) classifier with the radial basis function kernel(RBF) was first adopted to test the effect of classification features(vegetation height features and some typical topographic features) on forest gap classification.Then the different classifiers(KNN, Bayes, decision tree,and SVM with linear kernel) were further adopted to compare the effect of classifiers on machine learning forest gaps classification. Segmentation accuracy and classification accuracy were evaluated by using Mo¨ller's method and confusion metrics, respectively. The scale parameter had a significant effect on object-based forest gap segmentation and classification. Classification accuracies at different scales revealed that there were two optimal scales(10 and 20) that provided similar accuracy, with the scale of 10 yielding slightly greater accuracy than 20. The accuracy of the classification by using combination of height features and SVM classifier with linear kernel was91% at the optimal scale parameter of 10, and it was highest comparing with other classification classifiers, such as SVM RBF(90%), Decision Tree(90%), Bayes(90%),or KNN(87%). The classifiers had no significant effect on forest gap classification, but the fewer parameters in the classifier equation and higher speed of operation probably lead to a higher accuracy of final classifications. Our results confirm that object-based classification can extract forest gaps at a large regional scale with appropriate classification features and classifiers using LiDAR data. We note, however, that final satisfaction of forest gap classification depends on the determination of optimal scale(s) of segmentation.展开更多
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(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.
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supported by Hainan Provincial Natural Science Foundation of China Nos.622RC617,624RC485Open Foundation of State Key Laboratory of Networking and Switching Technology(Beijing University of Posts and Telecommunications)(SKLNST-2023-1-07).
文摘The advent of the digital age has consistently provided impetus for facilitating global trade,as evidenced by the numerous customs clearance documents and participants involved in the international trade process,including enterprises,agents,and government departments.However,the urgent issue that requires immediate attention is how to achieve secure and efficient cross-border data sharing among these government departments and enterprises in complex trade processes.In addressing this need,this paper proposes a data exchange architecture employing Multi-Authority Attribute-Based Encryption(MA-ABE)in combination with blockchain technology.This scheme supports proxy decryption,attribute revocation,and policy update,while allowing each participating entity to manage their keys autonomously,ensuring system security and enhancing trust among participants.In order to enhance system decentralization,a mechanism has been designed in the architecture where multiple institutions interact with smart contracts and jointly participate in the generation of public parameters.Integration with the multi-party process execution engine Caterpillar has been shown to boost the transparency of cross-border information flow and cooperation between different organizations.The scheme ensures the auditability of data access control information and the visualization of on-chain data sharing.The MA-ABE scheme is statically secure under the q-Decisional Parallel Bilinear Diffie-Hellman Exponent(q-DPBDHE2)assumption in the random oracle model,and can resist ciphertext rollback attacks to achieve true backward and forward security.Theoretical analysis and experimental results demonstrate the appropriateness of the scheme for cross-border data collaboration between different institutions.
基金Key Laboratory of Environment-friendly Energy Materials(SWUST,18ZD320304 and 22fksy23)Doctoral Fund of Henan University of Technology(31401577)+1 种基金Natural Science Foundation of Shandong Province(ZR2023MB053)Technological Innovation Project of Tai’an City(2022GX064)。
文摘Lithium-sulfur(Li-S)batteries are widely deemed to be one of the most potential candidates for future secondary batteries because of their remarkable energy density.Nevertheless,notorious polysulfide shuttling and retarded sulfur reaction kinetics pose significant obstacles to the further application of Li-S batteries.While rationally designed highly active electrocatalysts can facilitate polysulfide conversion,the universal and scalable synthesis strategies need to be developed.Herein,a universal synthetic strategy to construct a series of three-dimensional(3D)porous graphene-iron(3DGr-Fe)based electrocatalysts involving 3DGr-FeP,3DGr-Fe_(3)C,and 3DGr-Fe_(3)Se_(4)is exploited for manipulating the Li-S redox reactions.It has been observed that the implementation of a 3D porous Gr architecture leads to the well-designed conductive networks,while the uniformly dispersed iron nanoparticles introduce an abundance of active sites,fostering the lithium polysulfide conversion,thereby bolstering the overall electrochemical performance.The Li-S battery with the 3DGr-Fe based electrocatalyst exhibits remarkable capacity retention of 94.8%upon 100 times at 0.2 C.Moreover,the soft-packaged Li-S pouch cell based on such a 3DGr-Fe electrocatalyst delivers superior capacity of 1060.71 mA h g^(-1)and guarantees for the continuous 30 min work of fan toy.This investigation gives comprehensive insights into the design,synthesis,and mechanism of 3DGr-Fe based electrocatalysts with high activity toward efficient and durable Li-S batteries.
基金supported by the Autonomous Region Industry-Education Integration Project“Application of DNA Methylation Combined with Spiral CT in the Screening of Pulmonary Ground-Glass Nodules and AI Recognition Systems in Teaching Practice”(Project No.2023210016)the“Open Project of the State Key Laboratory of High Incidence Diseases in Central Asia”(Project No.SKL-HIDCA-2021-28).
文摘Objective:To explore the effectiveness of multi-modal teaching based on an online case library in the education of gene methylation combined with spiral computed tomography(CT)screening for pulmonary ground-glass opacity(GGO)nodules.Methods:From October 2023 to April 2024,66 medical imaging students were selected and randomly divided into a control group and an observation group,each with 33 students.The control group received traditional lecture-based teaching,while the observation group was taught using a multi-modal teaching approach based on an online case library.Performance on assessments and teaching quality were analyzed between the two groups.Results:The observation group achieved higher scores in theoretical and practical knowledge compared to the control group(P<0.05).Additionally,the teaching quality scores were significantly higher in the observation group(P<0.05).Conclusion:Implementing multi-modal teaching based on an online case library for pulmonary GGO nodule screening with gene methylation combined with spiral CT can enhance students’knowledge acquisition,improve teaching quality,and have significant clinical application value.
文摘Because of an unfortunate mistake by authors,the Project(5227010679)of Foundation item was wrong.The corrected Project is shown as follows:Project(52271073).
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Remote sensing and web-based platforms have emerged as vital tools in the effective monitoring of mangrove ecosystems, which are crucial for coastal protection, biodiversity, and carbon sequestration. Utilizing satellite imagery and aerial data, remote sensing allows researchers to assess the health and extent of mangrove forests over large areas and time periods, providing insights into changes due to environmental stressors like climate change, urbanization, and deforestation. Coupled with web-based platforms, this technology facilitates real-time data sharing and collaborative research efforts among scientists, policymakers, and conservationists. Thus, there is a need to grow this research interest among experts working in this kind of ecosystem. The aim of this paper is to provide a comprehensive literature review on the effective role of remote sensing and web-based platform in monitoring mangrove ecosystem. The research paper utilized the thematic approach to extract specific information to use in the discussion which helped realize the efficiency of digital monitoring for the environment. Web-based platforms and remote sensing represent a powerful tool for environmental monitoring, particularly in the context of forest ecosystems. They facilitate the accessibility of vital data, promote collaboration among stakeholders, support evidence-based policymaking, and engage communities in conservation efforts. As experts confront the urgent challenges posed by climate change and environmental degradation, leveraging technology through web-based platforms is essential for fostering a sustainable future for the forests of the world.
文摘Objective: In the Healthy Child Action Enhancement Program (2021-2025), it is proposed to ensure the safety and health of newborns and to promote high-quality development of health. Our department established risk assessment criteria for medical adhesives in neonates by applying the best evidence in the management program for the reduction of medical adhesive-associated skin injuries in neonates, in terms of the use and removal of adhesives. Methods: A systematic search and quality assessment of topics related to medical adhesive-related skin injury in neonates was conducted to summarize the best evidence and to conduct a quality review in the neonatal unit. Results: After 2 rounds of review, medical and nursing staff in the neonatal unit had a 98% compliance rate for the knowledge of neonatal medical adhesive-related skin injury and a satisfactory compliance rate for the other 9 indicators;after the application of the evidence, the incidence of neonatal medical adhesive-related skin injury was significantly lower than that before the application of the evidence, and the differences were statistically significant (P Conclusion: The application of the best evidence-based management program in neonatal medical adhesive-associated skin injury can reduce the incidence of neonatal medical adhesive-associated skin injury, reduce neonatal infections, and improve the integrity of the protective skin barrier in neonates.
基金financially supported by the National Science and Technology Major Project of China(No.2017-Ⅵ-0008-0078)。
文摘Four powder metallurgy(PM)Ni-based superalloys with different Hf and Ta contents were creep-tested at 650℃ and 970 MPa,700℃ and 770 MPa,and 750℃ and 580 MPa,respectively.The effect of Hf and Ta on creep deformation behaviors of the superalloys was studied from multiple scales by SEM,electron backscatter diffraction(EBSD),and aberration-corrected scanning transmission electron microscope(AC-STEM).The results showed that Hf and Ta suppressed the intergranular fracture and initiation of cracks during the acceleration creep stage,which prolonged the creep rupture time.Hf and Ta inhibited the stacking faults extending and the dislocation climbing and promoted the Suzuki segregation of W during the steady-state creep stage,which reduced the minimum creep rate and delayed the start time of the acceleration creep stage.The Suzuki segregation of Co,Cr,Mo,Ti,Nb,W,and Ta along stacking faults was observed after Hf and Ta addition,leading to the localized phase transformation in the γ′phase,and the stacking fault phase was chemically disordered.This study provided ideas for the composition design of novel PM Ni-based superalloys and theoretical foundations for the combined addition of Hf and Ta.
文摘Carbon dioxide (CO2) is a substantial contributor to global warming owing to its long atmospheric lifetime and high potential for global warming. It is related to the processes of raw material mining and industry, which is fundamental to economic development but also has negative impacts on the environment, namely the increase of global temperature and solid waste. To address this, various carbon capture, storage, utilization, and mineralization methods have emerged, but they remain at an early stage of development. This review discusses the applicability of solid waste materials, and slurry form in particular, for CO2 mineralization. It analyzes frequently researched materials, carbonation capabilities, reaction mechanisms, and industrial uses. Industrial waste materials, cement, and demolition waste are widely used in carbonation reactions because of their abundance and high Ca/Mg oxide content. The review also discusses carbonation types, including two major types—direct and indirect—which fall under the ex-situ category. The key factors influencing the carbonation efficiency include the CO2 concentration, temperature, pressure, particle size, and reaction chamber type. The construction sector is the principal beneficiary of carbonated materials due to the cementitious characteristics of recarbonated byproducts and precipitated calcium carbonate (PCC). Other industries, such as paper, plastics, and pharmaceuticals, also find applications for PCC. Future research is recommended to explore new materials for slurry carbonation, with potential applications in underground mine support for carbon sequestration and subsidence control.
文摘Objective: To develop a best-evidence-based optimal nutrition management plan for patients with chronic heart failure, apply it in clinical practice, and evaluate its effectiveness. Methods: Use the KTA knowledge translation model to guide evidence-based practice in nutrition management, and compare the nutritional status, cardiac function status, quality of life, and quality review indicators of chronic heart failure patients before and after the application of evidence. Results: After the application of evidence, the nutritional status indicators (MNA-SF score, albumin, hemoglobin) of two groups of heart failure patients significantly increased compared to before the application of evidence, with statistically significant differences (p Conclusion: The KTA knowledge translation model provides methodological guidance for the implementation of evidence-based practice for heart failure patients. This evidence-based practice project is beneficial for improving the outcomes of malnutrition in chronic heart failure patients and is conducive to standardizing nursing pathways, thereby promoting the improvement of nursing quality.
文摘The rapid growth of technology impacts all aspects of modern life, including banking and financial transactions. While these industries benefit significantly from technological advancements, they also face challenges such as credit card fraud, the most prevalent type of financial fraud. Each year, such fraud leads to billions of dollars in losses for banks, financial institutions, and customers. Although many machine learning (ML) and, more recently, deep learning (DL) solutions have been developed to address this issue, most fail to strike an effective balance between speed and performance. Moreover, the reluctance of financial institutions to disclose their fraud datasets due to reputational risks adds further challenges. This study proposes a predictive model for credit card fraud detection that leverages the unique strengths of Energy-based Restricted Boltzmann Machines (EB-RBM) and Extended Long Short-Term Memory (xLSTM) models. EB-RBM is utilized for its ability to detect new and previously unseen fraudulent patterns, while xLSTM focuses on identifying known fraud types. These models are integrated using an ensemble approach to combine their strengths, achieving a balanced and reliable prediction system. The ensemble employs a bootstrap max-voting mechanism, assigning equal voting rights to EB-RBM and xLSTM, followed by result normalization and aggregation to classify transactions as fraudulent or genuine. The model’s performance is evaluated using metrics such as AUC-ROC, AUC-PR, precision, recall, F1-score, confusion matrix, and elapsed time. Experimental results on a real-world European cardholder dataset demonstrate that the proposed approach effectively balances speed and performance, outperforming recent models in the field.
文摘The pandemic highlighted significant gaps in the public health infrastructure impacted by shortages of public health workers, an undertrained workforce, and years of disinvestment. These gaps required innovative problem-solving by public health agencies (PHAs), including local health departments (LHDs), to respond to rapidly changing community conditions during and after the pandemic. Many schools and programs of public health (SPPH) worked with PHAs to mobilize public health (PH) students through practice-based teaching (PBT). Current research indicates PBT benefits all stakeholders—PHAs, students, faculty, SPPH, and ultimately the community served. However, more research is needed on the utility of PBT in addressing a community’s systemic public health issues, the extent to which the academic-community collaboration enhances a PHA’s capacity, and the impact of the pedagogy on preparing the workforce for an evolving PH landscape. This paper examines the process of a semester-long PBT course, guided by the PBT STEPS framework, which includes five steps from collaboration to implementation to evaluation of a PBT course. The collaborating PHA and its student group addressed community trauma and resilience issues during the semester. Additionally, it examines the longer-term impacts after the semester for the PHA, community, and the workforce by 1) conducting a formative evaluation to understand needs and gaps in the community;2) redesigning an intervention that merged the results of the formative evaluation with the intervention developed during the semester;and 3) securing funding and resources for intervention sustainability. Through the documentation of a post-course partnership between an LHD and faculty at a large school of public health, this case study illustrates the potential for PBT to lay the foundation for ongoing research that supports more impactful interventions for PHAs while bolstering the workforce abilities of students as future practitioners.
文摘Oats, frequently incorporated into skincare formulations for their anti-inflammatory, moisturizing, and barrier-repairing properties, may present an overlooked risk to individuals with celiac disease, particularly when applied to compromised skin. Although pure oats are inherently gluten-free, the widespread contamination with gluten-containing grains like wheat, barley, or rye during agricultural and processing stages introduces the potential for gluten exposure through topical application. This raises important questions about whether gluten proteins, when applied to damaged skin, might penetrate the epidermal barrier and contribute to immune responses in genetically predisposed celiac patients, given that even minute amounts of gluten can trigger systemic symptoms. Emerging evidence suggests that transdermal absorption of gluten peptides through impaired skin integrity might bypass the gastrointestinal route, yet the precise mechanisms and clinical significance of this pathway remain poorly understood. The role of compromised skin in facilitating gluten absorption and the possible activation of CD4+ T-cells, mimicking gastrointestinal pathways, warrants further investigation. Additionally, the ability of gluten peptides to reach deeper dermal layers and potentially enter the systemic circulation remains speculative, though theoretically possible in severely disrupted skin barriers. Without clinical and molecular studies to determine the risk of topical gluten exposure, particularly in celiac patients with skin injuries, there remains a potential for undetected immune activation and subsequent adverse health outcomes in this sensitive population.
基金financially supported by grant from National Natural Science Foundation of China(No.31300533)
文摘Object-based classification differentiates forest gaps from canopies at large regional scale by using remote sensing data. To study the segmentation and classification processes of object-based forest gaps classification at a regional scale, we sampled a natural secondary forest in northeast China at Maoershan Experimental Forest Farm.Airborne light detection and ranging(LiDAR; 3.7 points/m2) data were collected as the original data source and the canopy height model(CHM) and topographic dataset were extracted from the LiDAR data. The accuracy of objectbased forest gaps classification depends on previous segmentation. Thus our first step was to define 10 different scale parameters in CHM image segmentation. After image segmentation, the machine learning classification method was used to classify three kinds of object classes, namely,forest gaps, tree canopies, and others. The common support vector machine(SVM) classifier with the radial basis function kernel(RBF) was first adopted to test the effect of classification features(vegetation height features and some typical topographic features) on forest gap classification.Then the different classifiers(KNN, Bayes, decision tree,and SVM with linear kernel) were further adopted to compare the effect of classifiers on machine learning forest gaps classification. Segmentation accuracy and classification accuracy were evaluated by using Mo¨ller's method and confusion metrics, respectively. The scale parameter had a significant effect on object-based forest gap segmentation and classification. Classification accuracies at different scales revealed that there were two optimal scales(10 and 20) that provided similar accuracy, with the scale of 10 yielding slightly greater accuracy than 20. The accuracy of the classification by using combination of height features and SVM classifier with linear kernel was91% at the optimal scale parameter of 10, and it was highest comparing with other classification classifiers, such as SVM RBF(90%), Decision Tree(90%), Bayes(90%),or KNN(87%). The classifiers had no significant effect on forest gap classification, but the fewer parameters in the classifier equation and higher speed of operation probably lead to a higher accuracy of final classifications. Our results confirm that object-based classification can extract forest gaps at a large regional scale with appropriate classification features and classifiers using LiDAR data. We note, however, that final satisfaction of forest gap classification depends on the determination of optimal scale(s) of segmentation.
