Objective: To analyze the effect of continuous nursing on self-care ability and quality of life of patients with permanent artificial pacemaker implantation. Methods: A total of 90 patients receiving permanent artific...Objective: To analyze the effect of continuous nursing on self-care ability and quality of life of patients with permanent artificial pacemaker implantation. Methods: A total of 90 patients receiving permanent artificial pacemaker treatment in our hospital during the first 8 months of November 2021 were selected as samples to compare the data differences between the two groups (control group and intervention group were 45 patients /n = 45 patients/group, respectively). Results: The compliance of the intervention group was higher than that of the control group (P;There was no significant difference in EDCA score between groups before intervention (P>0.05). After intervention, EDCA score in the intervention group was higher than that in the control group (P<0.05). The nursing quality score of intervention group was higher than that of control group (P;The compliance score of intervention group was higher than that of control group (P<0.05). After intervention, SRSS and MNA scores in the intervention group were higher than those in the control group (P<0.05). The scores of the four items in the intervention group were higher than those in the control group (P < 0.05). Discussion: Continuous nursing intervention can effectively improve the quality and effect of nursing, and has significant application value.展开更多
The usability assessment of a pacemaker is a complex task where the dedicated programmer for testing programmed algorithms is necessary.This paper provides the outcomes of development and complex testing of the artifi...The usability assessment of a pacemaker is a complex task where the dedicated programmer for testing programmed algorithms is necessary.This paper provides the outcomes of development and complex testing of the artificial cardiac system to evaluate the pacemaker’s functionality.In this work,we used the modular laboratory platform ELVIS II and created graphical user interface in LabVIEW programming environment.The electrical model of the heart allows signals generation(right atrium,right ventricle)and the monitoring of the stimulation pulses.The LabVIEW user interface allows to set the parameters of the generated signals and the simulation of the cardiac rhythm disorders as well as the monitoring and visualization of the pacemaker behavior in real-time.The results demonstrate the capability of proposed system to evaluate the paced and sensed pulses.The proposed solution allows the scientists to test the behavior of any cardiac pacemaker for its pre-programmed settings and pacing mode.In addition,the proposed system can simulate various disorders and test cardiac pacemakers in different working modes.展开更多
This review comprehensively summarized the potential of artificial intelligence(AI)in the management of esophageal cancer.It highlighted the significance of AI-assisted endoscopy in Japan where endoscopy is central to...This review comprehensively summarized the potential of artificial intelligence(AI)in the management of esophageal cancer.It highlighted the significance of AI-assisted endoscopy in Japan where endoscopy is central to both screening and diagnosis.For the clinical adaptation of AI,several challenges remain for its effective translation.The establishment of high-quality clinical databases,such as the National Clinical Database and Japan Endoscopy Database in Japan,which covers almost all cases of esophageal cancer,is essential for validating multimodal AI models.This requires rigorous external validation using diverse datasets,including those from different endoscope manufacturers and image qualities.Furthermore,endoscopists’skills significantly affect diagnostic accuracy,suggesting that AI should serve as a supportive tool rather than a replacement.Addressing these challenges,along with country-specific legal and ethical considerations,will facilitate the successful integration of multimodal AI into the management of esophageal cancer,particularly in endoscopic diagnosis,and contribute to improved patient outcomes.Although this review focused on Japan as a case study,the challenges and solutions described are broadly applicable to other high-incidence regions.展开更多
Background:Medical artificial intelligence(MAI)is a synthesis of medical science and artificial intelligence development,serving as a crucial field in the current advancement and application of AI.In the process of de...Background:Medical artificial intelligence(MAI)is a synthesis of medical science and artificial intelligence development,serving as a crucial field in the current advancement and application of AI.In the process of developing medical AI,there may arise not only legal risks such as infringement of privacy rights and health rights but also ethical risks stemming from violations of the principles of beneficence and non-maleficence.Methods:To effectively address the damages caused by MAI in the future,it is necessary to establish a hierarchical governance system with MAI.This paper examines the systematic collection of local practices in China and the induction and integration of legal remedies for the damage of MAI.Results:To effectively address the ethical and legal challenges of medical artificial intelligence,a hierarchical regulatory system should be established,which based on the impact of intervention measures on natural rights and differences in intervention timing.This paper finally obtains a legal hierarchical governance system corresponding to the ethical risks and legal risks of MAI in China.Conclusion:The Chinese government has formed a multi-agent governance system based on the impact of risks on rights and the timing of legal intervention,which provides a reference for other countries to follow up on the research on MAI risk management.展开更多
The integration of machine learning(ML)into geohazard assessment has successfully instigated a paradigm shift,leading to the production of models that possess a level of predictive accuracy previously considered unatt...The integration of machine learning(ML)into geohazard assessment has successfully instigated a paradigm shift,leading to the production of models that possess a level of predictive accuracy previously considered unattainable.However,the black-box nature of these systems presents a significant barrier,hindering their operational adoption,regulatory approval,and full scientific validation.This paper provides a systematic review and synthesis of the emerging field of explainable artificial intelligence(XAI)as applied to geohazard science(GeoXAI),a domain that aims to resolve the long-standing trade-off between model performance and interpretability.A rigorous synthesis of 87 foundational studies is used to map the intellectual and methodological contours of this rapidly expanding field.The analysis reveals that current research efforts are concentrated predominantly on landslide and flood assessment.Methodologically,tree-based ensembles and deep learning models dominate the literature,with SHapley Additive exPlanations(SHAP)frequently adopted as the principal post-hoc explanation technique.More importantly,the review further documents how the role of XAI has shifted:rather than being used solely as a tool for interpreting models after training,it is increasingly integrated into the modeling cycle itself.Recent applications include its use in feature selection,adaptive sampling strategies,and model evaluation.The evidence also shows that GeoXAI extends beyond producing feature rankings.It reveals nonlinear thresholds and interaction effects that generate deeper mechanistic insights into hazard processes and mechanisms.Nevertheless,several key challenges remain unresolved within the field.These persistent issues are especially pronounced when considering the crucial necessity for interpretation stability,the demanding scholarly task of reliably distinguishing correlation from causation,and the development of appropriate methods for the treatment of complex spatio-temporal dynamics.展开更多
Legged robots have considerable potential for traversing unstructured situations;nonetheless,their inflexible frameworks often constrain adaptability and obstacle negotiation.The study article presents a revolutionary...Legged robots have considerable potential for traversing unstructured situations;nonetheless,their inflexible frameworks often constrain adaptability and obstacle negotiation.The study article presents a revolutionary Soft Tri-Legged Robot(STLR)that improves movement and obstacle-avoidance skills by using a bio-inspired pneumatic artificial muscle(Bubble Artificial Muscles)and a bio-inspired tactile sensor(TacTip).The STLR is activated by BAMs,which are flexible,pneu-matic-driven actuators that provide fine control over forward,backward,and steering movements.Obstacle identification and avoidance are facilitated by the TacTip sensor,which delivers tactile input for traversing unstructured terrains.We delineate the mechanical features of the BAMs,assess the functionality of the robot's legs,and elaborate on the incorpora-tion of the tactile sensing system.Experimental results demonstrate that the STLR can effectively achieve multi-directional flexible movement and obstacle avoidance through a cross-modal perception-actuation mechanism.This study highlights the promise of soft robotics for search and rescue,medical aid,and autonomous exploration,while delineating difficulties and opportunities for future improvements in functionality and efficiency.展开更多
This paper presents a novel artificial intelligence(AI)-assisted two-stage method for optimising rock slope stability by integrating advanced 3D modelling with rock support design,aiming at minimising risks,material u...This paper presents a novel artificial intelligence(AI)-assisted two-stage method for optimising rock slope stability by integrating advanced 3D modelling with rock support design,aiming at minimising risks,material usage,and costs.In the first stage,an extended key block analysis identifies key blocks and key block groups,accounting for progressive failure and force interactions.The second stage uses AI algorithms to optimise rockbolting design,balancing stability,cost,and material use.The most efficient algorithms include the multi-objective tree-structured Parzen estimator(MOTPE)and non-dominated sorting genetic algorithms(NSGA-II and NSGA-III).Applied to the Larvik rock slope,the optimised solution uses 18 pre-tensioned cablebolts,providing 13.2 MN of active force and achieving a factor of safety of 1.31 while reducing the average anchorage length by approximately 16%compared to traditional design.The AI-assisted approach also reduces computation time by over 90%compared to Quasi-Monte Carlo(QMC)methods,demonstrating its efficiency for small-scale civil engineering projects and large-scale mining operations.The developed tool is practical,compatible with Building Information Modelling(BIM),and ready for engineering implementation,supporting sustainable and cost-effective rock slope stabilisation.While the method is largely automated,professional judgement remains crucial for verifying ground conditions and selecting the final solution.Future work will focus on integrating data uncertainties,addressing complex block deformation mechanisms,refining optimisation objectives,and improving the performance of multi-objective optimisation for slope rockboling applications to further enhance the method's versatility.展开更多
Gastrointestinal tumors require personalized treatment strategies due to their heterogeneity and complexity.Multimodal artificial intelligence(AI)addresses this challenge by integrating diverse data sources-including ...Gastrointestinal tumors require personalized treatment strategies due to their heterogeneity and complexity.Multimodal artificial intelligence(AI)addresses this challenge by integrating diverse data sources-including computed tomography(CT),magnetic resonance imaging(MRI),endoscopic imaging,and genomic profiles-to enable intelligent decision-making for individualized therapy.This approach leverages AI algorithms to fuse imaging,endoscopic,and omics data,facilitating comprehensive characterization of tumor biology,prediction of treatment response,and optimization of therapeutic strategies.By combining CT and MRI for structural assessment,endoscopic data for real-time visual inspection,and genomic information for molecular profiling,multimodal AI enhances the accuracy of patient stratification and treatment personalization.The clinical implementation of this technology demonstrates potential for improving patient outcomes,advancing precision oncology,and supporting individualized care in gastrointestinal cancers.Ultimately,multimodal AI serves as a transformative tool in oncology,bridging data integration with clinical application to effectively tailor therapies.展开更多
Gibberellins(GAs)and auxin play central regulatory roles in seed germination and root system development,respectively,so that the application of these phytohormones to crops would be worthwhile,with an increasing pote...Gibberellins(GAs)and auxin play central regulatory roles in seed germination and root system development,respectively,so that the application of these phytohormones to crops would be worthwhile,with an increasing potential demand in agriculture.However,there are few effective chemicals that simultaneously enhance both GA and auxin signaling.Here,we report on an artificial thiourea derivative chemical,Y21,that serves as both a GA-signaling agonist and an auxin analog,promoting seed germination and root development,as well as low-phosphorus tolerance.Phenotypic,biochemical,and genetic evidence demonstrated that Y21 enhances the interaction between GA and its receptor GID1C via the Val239 amino acid residue and consequently promotes degradation of the DELLA proteins REPRESSOR OF ga1-3(RGA)and RGA-LIKE 2.Furthermore,we found that Y21 interacts with the auxin receptor TIR1 via the Cys405 residue and thus promotes the turnover of the auxinresponsive Aux/IAA proteins.Consequently,Y21significantly increases low-phosphorus tolerance of treated plants by positively regulating lateral root development.To our knowledge,Y21 is the first GA-signaling agonist to be identified,and our results also demonstrate that this potent synthetic chemical,identified by chemical genetic screening,is effective at modulating plant development and stress tolerance.展开更多
This study addresses the challenges confronting the ideological and political construction of general artificial intelligence curriculum-namely,the dilution of value guidance amid pluralistic intellectual currents,the...This study addresses the challenges confronting the ideological and political construction of general artificial intelligence curriculum-namely,the dilution of value guidance amid pluralistic intellectual currents,the superficial internalization of concepts resulting from didactic pedagogy,and the ineffectiveness of character cultivation stemming from fragmented and decontextualized techno-ethical cases.This paper proposes centering the value proposition on“Serving the Nation through Science and Technology”.Leveraging the deeply integrated industry-academia-research-application synergy,we integrate ideological and political elements into the comprehensive technological practice workflow.To achieve this,we(1)incorporate authentic enterprise project practicums to foster students’sense of responsibility;(2)construct a virtual debate platform on technology ethics dilemmas to develop ethical discernment;and(3)organize solution competitions targeting urgent social problems to incubate technology-for-good initiatives.Collectively,these approaches enhance students’technological mission awareness,ethical sensitivity,and social responsibility.展开更多
A methodology for the reduction of radar cross section(RCS)of cambered platforms within the target airspace is presented,which utilizes a dual-polarized ultra-wide-angle artificial electromagnetic absorbing surface.By...A methodology for the reduction of radar cross section(RCS)of cambered platforms within the target airspace is presented,which utilizes a dual-polarized ultra-wide-angle artificial electromagnetic absorbing surface.By applying the theory of generalized Brewster complex wave impedance matching,five distinct unit cell designs are developed to attain more than95%absorption rate for dual-polarized incident waves within five angular ranges:0°-30°,30°-50°,50°-60°,60°-70°,and 70°-80°.To optimally reduce the RCS of a cambered platform,the five types of units can be evenly distributed on the surface based on the local incident angles of plane waves originating from the target airspace.As an illustrative example,the leading edge of an airfoil is taken into account,and experimental measurements validate the efficiency of the proposed structure.Specifically,the absorbing surface achieves more than 10 dB of RCS reduction in the frequency ranges from 5-10 GHz(about66.7%relative bandwidth)for dual polarizations.展开更多
BACKGROUND Gastrointestinal stromal tumors(GISTs)are rare mesenchymal neoplasms primarily originating in the stomach or small intestine.Duodenal GISTs are particularly uncommon,accounting for only a small fraction of ...BACKGROUND Gastrointestinal stromal tumors(GISTs)are rare mesenchymal neoplasms primarily originating in the stomach or small intestine.Duodenal GISTs are particularly uncommon,accounting for only a small fraction of GIST cases.These tumors often present with nonspecific symptoms,making early detection challenging.This case discusses a duodenal GIST misdiagnosed as pancreatic cancer due to obstructive jaundice.CASE SUMMARY A 40-year-old male with jaundice and abdominal symptoms underwent imaging,which suggested a malignant periampullary tumor.Preoperative misdiagnosis of pancreatic cancer was made,and surgery was performed.Postoperative histopathology confirmed a duodenal GIST.The role of artificial intelligence in the diagnostic pathway is explored,emphasizing its potential to differentiate between duodenal GISTs and other similar conditions using advanced imaging analysis.CONCLUSION Artificial intelligence in radiomic imaging holds significant promise in enhancing the diagnostic process for rare cancers like duodenal GISTs,ensuring timely and accurate treatment.展开更多
Aqueous zinc metal batteries(AZMBs)are promising candidates for next-generation energy storage,but their commercialization is hindered by zinc anode challenges,notably parasitic reactions and dendrite growth.Herein,we...Aqueous zinc metal batteries(AZMBs)are promising candidates for next-generation energy storage,but their commercialization is hindered by zinc anode challenges,notably parasitic reactions and dendrite growth.Herein,we present a biodegradable biomass-derived protective layer,primarily composed of curcumin,as a zincophilic interface for AZMBs.The curcumin-based layer,fabricated via a homogeneous solution process,exhibits strong adhesion,uniform coverage,and robust mechanical integrity.Rich polar functional groups in curcumin facilitate homogeneous Zn~(2+)flux and suppress side reactions.The curcumin-based layer shows a favorable affinity for zinc trifluoromethanesulfonate(Zn(OTf)_(2))electrolyte,which is the representative of organic zinc salts,enabling optimal thickness for both protection and ion transport.The protected Zn anodes demonstrate an extended lifespan of 2500 h in symmetrical cells and a high Coulombic efficiency of 99.15%.Furthermore,Zn(OTf)_(2)-based system typically exhibits poor stability at high current densities.Fortunately,the lifespan of symmetrical cells was extended by 40-fold at the high current density.When paired with an Na V_(3)O_(8)·1.5H_(2)O(NVO)cathode,the system achieves 86.5%capacity retention after 3000 cycles at a large specific current density of 10 A g^(-1).These results underscore the efficacy of the curcumin-based protective layer in enhancing the reversibility and stability of metal electrodes,specifically relieving the instability of Zn(OTf)_(2)-based systems at high current densities,advancing its commercial viability.展开更多
Nursing education is undergoing a paradigm shift from skill training to clinical thinking cultivation.The integration of artificial intelligence technology offers technical possibilities for this transformation,but it...Nursing education is undergoing a paradigm shift from skill training to clinical thinking cultivation.The integration of artificial intelligence technology offers technical possibilities for this transformation,but it also brings about a deep tension between the cultivation of humanistic qualities and a standardized training.Based on the analysis of the practical forms of nursing smart education,this paper examines the cognitive gap between the deterministic feedback of virtual simulation systems and the complexity of real clinical scenarios,reveals the potential narrowing effect of data-driven ability profiling on the all-round development of nursing students,and then proposes the design logic of intelligent teaching resources centered on real clinical problems,a hierarchical teaching model with clear human-machine division of labor,and a dynamic assessment mechanism for technology application led by professional nursing teachers,in an attempt to find a balance between technological empowerment and humanistic commitment in smart nursing education.展开更多
Providing safe and quality food is crucial for every household and is of extreme significance in the growth of any society.It is a complex procedure that deals with all issues focusing on the development of food proce...Providing safe and quality food is crucial for every household and is of extreme significance in the growth of any society.It is a complex procedure that deals with all issues focusing on the development of food processing from seed to harvest,storage,preparation,and consumption.This current paper seeks to demystify the importance of artificial intelligence,machine learning(ML),deep learning(DL),and computer vision(CV)in ensuring food safety and quality.By stressing the importance of these technologies,the audience will feel reassured and confident in their potential.These are very handy for such problems,giving assurance over food safety.CV is incredibly noble in today's generation because it improves food processing quality and positively impacts firms and researchers.Thus,at the present production stage,rich in image processing and computer visioning is incorporated into all facets of food production.In this field,DL and ML are implemented to identify the type of food in addition to quality.Concerning data and result-oriented perceptions,one has found similarities regarding various approaches.As a result,the findings of this study will be helpful for scholars looking for a proper approach to identify the quality of food offered.It helps to indicate which food products have been discussed by other scholars and lets the reader know papers by other scholars inclined to research further.Also,DL is accurately integrated with identifying the quality and safety of foods in the market.This paper describes the current practices and concerns of ML,DL,and probable trends for its future development.展开更多
Healthy behavior has long been linked to mental health outcomes.However,the role of artificial intelligence(AI)literacy in shaping healthy behaviors and its potential impact on mental health remains underexplored.This...Healthy behavior has long been linked to mental health outcomes.However,the role of artificial intelligence(AI)literacy in shaping healthy behaviors and its potential impact on mental health remains underexplored.This paper presents a scoping review offering a novel perspective on the intersection of healthy behaviors,mental health,and AI literacy.By examining how individuals’understanding of AI influences their choices regarding nutrition and their susceptibility to mental health issues,the current study explores emerging trends in health behavior decision-making.This emphasizes the need for integrating AI literacy into mental health and health behaviors education,as well as the development of AI-driven tools to support healthier behavior choices.It highlights that individuals with low AI literacy may misinterpret or overly depend on AI guidance,resulting in maladaptive health choices,while those with high AI literacy may be more likely to engage reflectively and sustain positive behaviors.The paper outlines the importance of inclusive education,user-centered design,and community-based support systems to enhance AI literacy for digitally marginalized groups.AI literacy may be positioned as a key determinant of health equity,better allowing for interdisciplinary strategies that empower individuals to make informed,autonomous decisions that promote both physical and mental health.展开更多
Artificial intelligence(AI)is increasingly recognized as a transformative force in the field of solid organ transplantation.From enhancing donor-recipient matching to predicting clinical risks and tailoring immunosupp...Artificial intelligence(AI)is increasingly recognized as a transformative force in the field of solid organ transplantation.From enhancing donor-recipient matching to predicting clinical risks and tailoring immunosuppressive therapy,AI has the potential to improve both operational efficiency and patient outcomes.Despite these advancements,the perspectives of transplant professionals-those at the forefront of critical decision-making-remain insufficiently explored.To address this gap,this study utilizes a multi-round electronic Delphi approach to gather and analyses insights from global experts involved in organ transplantation.Participants are invited to complete structured surveys capturing demographic data,professional roles,institutional practices,and prior exposure to AI technologies.The survey also explores perceptions of AI’s potential benefits.Quantitative responses are analyzed using descriptive statistics,while open-ended qualitative responses undergo thematic analysis.Preliminary findings indicate a generally positive outlook on AI’s role in enhancing transplantation processes,particularly in areas such as donor matching and post-operative care.These mixed views reflect both optimism and caution among professionals tasked with integrating new technologies into high-stakes clinical workflows.By capturing a wide range of expert opinions,the findings will inform future policy development,regulatory considerations,and institutional readiness frameworks for the integration of AI into organ transplantation.展开更多
In this study, the ground potential rise(GPR) phenomenon caused by a lightning current injected into a field-shaped artificial grounding grid, as well as the potential difference between two different nodes at the edg...In this study, the ground potential rise(GPR) phenomenon caused by a lightning current injected into a field-shaped artificial grounding grid, as well as the potential difference between two different nodes at the edge of the grounding grid, was observed and analyzed under artificially triggered lightning conditions. Based on circuit theory and measured current data, a π-equivalent circuit was established to simulate the transient response of the grounding grid.Nineteen return strokes from three artificially triggered lightning events were analyzed. The peak currents of the 19 return strokes range from -6.7 to -25.1 kA, and the mean value was -14.3 kA. The GPR decreased rapidly and formed a subpeak after reaching the initial peak, with the mean value of the initial peak being -148.65 kV and the mean value of the subpeak being -92.87 kV. The GPR induced by the triggered lightning currents exhibited a subpeak phenomenon. Simulation results indicate that the subpeak phenomenon is related to localized corrosion of the vertical grounding electrode. The potential difference at the grounding grid edge exhibited a multi-pulse waveform with alternating polarity, dominated by positive pulses. The peak values of both the positive and negative polarity pulses gradually decreased, with the first positive pulse displaying a significantly higher intensity than that of subsequent pulses.展开更多
Objectives This study aimed to explore the research trends,thematic structures,and core competency domains in the field of nursing-related digital and artificial intelligence(AI)technologies.Methods A bibliometric ana...Objectives This study aimed to explore the research trends,thematic structures,and core competency domains in the field of nursing-related digital and artificial intelligence(AI)technologies.Methods A bibliometric analysis was conducted in accordance with the PRISMA 2020 statement.Peer-reviewed articles published in English from 2015 to 2025 were retrieved from Scopus,Web of Science,and PubMed.Thematic clustering was conducted using the Louvain algorithm and cosine similarity.A subset of 66 frequently cited articles was then qualitatively synthesized to capture core competencies across clusters.Results A total of 83,807 articles were included for bibliometric analysis.Of these,66 articles were chosen for thematic analysis.Five major thematic clusters were identified:remote care in primary settings,oncology and palliative care,nurse education and training,safety and quality in nursing practice,and geriatric and dementia care.Additionally,four competency domains were identified:telehealth and remote communication,health systems and informatics,digital tools in practice,and AI-powered decision support.A clear shift in research focus was observed,with the emphasis transitioning from foundational digital skills before the COVID-19 pandemic to more advanced competencies during the post-pandemic digital transformation,encompassing ethical reasoning,immersive technology use,and AI integration.Conclusions Integrating digital and AI technologies is reshaping nursing practice across various thematic areas and competency domains,highlighting a transition from foundational digital tasks to AI-supported decision-making and ethically informed technology use.This study provides a structured overview of evolving competencies in digital nursing and synthesizes evidence to support future research,curriculum design,and policy planning.展开更多
The rapid advancement of Artificial Intelligence(AI)has transformed educational practices,yet its integration with experiential pedagogies such as drama remains underexplored in English Language Teaching(ELT),particul...The rapid advancement of Artificial Intelligence(AI)has transformed educational practices,yet its integration with experiential pedagogies such as drama remains underexplored in English Language Teaching(ELT),particularly in pre-service teacher education.This study examines how AI-supported drama pedagogy contributes to the professional development of pre-service English teachers,focusing on reflective practice,pedagogical adaptability,creativity,intercultural awareness,and sustainability-oriented teaching perspectives.Grounded in sociocultural theory,experiential learning,and Education for Sustainable Development(ESD),the research adopts an interpretive qualitative case study design conducted over a 12-week elective course titled“Drama in ELT”at a foundation university in Istanbul,Türkiye.Participants included 40 second-year pre-service teachers,with 15 volunteers taking part in semi-structured focus group interviews.Data were collected through open-ended questionnaires and focus groups and analyzed using reflexive thematic analysis.Four interrelated themes emerged:creativity and pedagogical innovation,intercultural awareness and empathy,problem-solving and adaptability,and reflective professional growth with ethical awareness.Findings suggest that AI acted as a mediational scaffold that enriched drama-based learning while preserving human agency.The study concludes that integrating AI with drama offers a meaningful model for sustainable teacher education aligned with SDG 4(Quality Education)and SDG 9(Industry,Innovation and Infrastructure).展开更多
文摘Objective: To analyze the effect of continuous nursing on self-care ability and quality of life of patients with permanent artificial pacemaker implantation. Methods: A total of 90 patients receiving permanent artificial pacemaker treatment in our hospital during the first 8 months of November 2021 were selected as samples to compare the data differences between the two groups (control group and intervention group were 45 patients /n = 45 patients/group, respectively). Results: The compliance of the intervention group was higher than that of the control group (P;There was no significant difference in EDCA score between groups before intervention (P>0.05). After intervention, EDCA score in the intervention group was higher than that in the control group (P<0.05). The nursing quality score of intervention group was higher than that of control group (P;The compliance score of intervention group was higher than that of control group (P<0.05). After intervention, SRSS and MNA scores in the intervention group were higher than those in the control group (P<0.05). The scores of the four items in the intervention group were higher than those in the control group (P < 0.05). Discussion: Continuous nursing intervention can effectively improve the quality and effect of nursing, and has significant application value.
基金Thework and the contributions were supported by the project SV4502261/SP2022/98‘Biomedical Engineering systems XVIII’.
文摘The usability assessment of a pacemaker is a complex task where the dedicated programmer for testing programmed algorithms is necessary.This paper provides the outcomes of development and complex testing of the artificial cardiac system to evaluate the pacemaker’s functionality.In this work,we used the modular laboratory platform ELVIS II and created graphical user interface in LabVIEW programming environment.The electrical model of the heart allows signals generation(right atrium,right ventricle)and the monitoring of the stimulation pulses.The LabVIEW user interface allows to set the parameters of the generated signals and the simulation of the cardiac rhythm disorders as well as the monitoring and visualization of the pacemaker behavior in real-time.The results demonstrate the capability of proposed system to evaluate the paced and sensed pulses.The proposed solution allows the scientists to test the behavior of any cardiac pacemaker for its pre-programmed settings and pacing mode.In addition,the proposed system can simulate various disorders and test cardiac pacemakers in different working modes.
基金Supported by Japan Society for the Promotion of Science,No.24K11935.
文摘This review comprehensively summarized the potential of artificial intelligence(AI)in the management of esophageal cancer.It highlighted the significance of AI-assisted endoscopy in Japan where endoscopy is central to both screening and diagnosis.For the clinical adaptation of AI,several challenges remain for its effective translation.The establishment of high-quality clinical databases,such as the National Clinical Database and Japan Endoscopy Database in Japan,which covers almost all cases of esophageal cancer,is essential for validating multimodal AI models.This requires rigorous external validation using diverse datasets,including those from different endoscope manufacturers and image qualities.Furthermore,endoscopists’skills significantly affect diagnostic accuracy,suggesting that AI should serve as a supportive tool rather than a replacement.Addressing these challenges,along with country-specific legal and ethical considerations,will facilitate the successful integration of multimodal AI into the management of esophageal cancer,particularly in endoscopic diagnosis,and contribute to improved patient outcomes.Although this review focused on Japan as a case study,the challenges and solutions described are broadly applicable to other high-incidence regions.
基金funded by China Law Society 2025 Annual Legal Research,Project grant number:CLS(2025)Y04.
文摘Background:Medical artificial intelligence(MAI)is a synthesis of medical science and artificial intelligence development,serving as a crucial field in the current advancement and application of AI.In the process of developing medical AI,there may arise not only legal risks such as infringement of privacy rights and health rights but also ethical risks stemming from violations of the principles of beneficence and non-maleficence.Methods:To effectively address the damages caused by MAI in the future,it is necessary to establish a hierarchical governance system with MAI.This paper examines the systematic collection of local practices in China and the induction and integration of legal remedies for the damage of MAI.Results:To effectively address the ethical and legal challenges of medical artificial intelligence,a hierarchical regulatory system should be established,which based on the impact of intervention measures on natural rights and differences in intervention timing.This paper finally obtains a legal hierarchical governance system corresponding to the ethical risks and legal risks of MAI in China.Conclusion:The Chinese government has formed a multi-agent governance system based on the impact of risks on rights and the timing of legal intervention,which provides a reference for other countries to follow up on the research on MAI risk management.
文摘The integration of machine learning(ML)into geohazard assessment has successfully instigated a paradigm shift,leading to the production of models that possess a level of predictive accuracy previously considered unattainable.However,the black-box nature of these systems presents a significant barrier,hindering their operational adoption,regulatory approval,and full scientific validation.This paper provides a systematic review and synthesis of the emerging field of explainable artificial intelligence(XAI)as applied to geohazard science(GeoXAI),a domain that aims to resolve the long-standing trade-off between model performance and interpretability.A rigorous synthesis of 87 foundational studies is used to map the intellectual and methodological contours of this rapidly expanding field.The analysis reveals that current research efforts are concentrated predominantly on landslide and flood assessment.Methodologically,tree-based ensembles and deep learning models dominate the literature,with SHapley Additive exPlanations(SHAP)frequently adopted as the principal post-hoc explanation technique.More importantly,the review further documents how the role of XAI has shifted:rather than being used solely as a tool for interpreting models after training,it is increasingly integrated into the modeling cycle itself.Recent applications include its use in feature selection,adaptive sampling strategies,and model evaluation.The evidence also shows that GeoXAI extends beyond producing feature rankings.It reveals nonlinear thresholds and interaction effects that generate deeper mechanistic insights into hazard processes and mechanisms.Nevertheless,several key challenges remain unresolved within the field.These persistent issues are especially pronounced when considering the crucial necessity for interpretation stability,the demanding scholarly task of reliably distinguishing correlation from causation,and the development of appropriate methods for the treatment of complex spatio-temporal dynamics.
基金the Natural Science Foundation of China(Project for Young Scientists:Grant No.52105010,Regular Project:Grant No.62173096)Natural Science Foundationof Guangdong Province(Regular Project:Grant No.2025A1515012124,Grant No.2022A1515010327)Guangdong-Hong Kong-Macao Key Laboratory of Multi-scaleInformation Fusion and Collaborative Optimization Control Manufacturing Process.
文摘Legged robots have considerable potential for traversing unstructured situations;nonetheless,their inflexible frameworks often constrain adaptability and obstacle negotiation.The study article presents a revolutionary Soft Tri-Legged Robot(STLR)that improves movement and obstacle-avoidance skills by using a bio-inspired pneumatic artificial muscle(Bubble Artificial Muscles)and a bio-inspired tactile sensor(TacTip).The STLR is activated by BAMs,which are flexible,pneu-matic-driven actuators that provide fine control over forward,backward,and steering movements.Obstacle identification and avoidance are facilitated by the TacTip sensor,which delivers tactile input for traversing unstructured terrains.We delineate the mechanical features of the BAMs,assess the functionality of the robot's legs,and elaborate on the incorpora-tion of the tactile sensing system.Experimental results demonstrate that the STLR can effectively achieve multi-directional flexible movement and obstacle avoidance through a cross-modal perception-actuation mechanism.This study highlights the promise of soft robotics for search and rescue,medical aid,and autonomous exploration,while delineating difficulties and opportunities for future improvements in functionality and efficiency.
基金support from Research Council of Norway via STIPINST PhD grant(Grant No.323307),Bever Control AS,and Bane NOR.
文摘This paper presents a novel artificial intelligence(AI)-assisted two-stage method for optimising rock slope stability by integrating advanced 3D modelling with rock support design,aiming at minimising risks,material usage,and costs.In the first stage,an extended key block analysis identifies key blocks and key block groups,accounting for progressive failure and force interactions.The second stage uses AI algorithms to optimise rockbolting design,balancing stability,cost,and material use.The most efficient algorithms include the multi-objective tree-structured Parzen estimator(MOTPE)and non-dominated sorting genetic algorithms(NSGA-II and NSGA-III).Applied to the Larvik rock slope,the optimised solution uses 18 pre-tensioned cablebolts,providing 13.2 MN of active force and achieving a factor of safety of 1.31 while reducing the average anchorage length by approximately 16%compared to traditional design.The AI-assisted approach also reduces computation time by over 90%compared to Quasi-Monte Carlo(QMC)methods,demonstrating its efficiency for small-scale civil engineering projects and large-scale mining operations.The developed tool is practical,compatible with Building Information Modelling(BIM),and ready for engineering implementation,supporting sustainable and cost-effective rock slope stabilisation.While the method is largely automated,professional judgement remains crucial for verifying ground conditions and selecting the final solution.Future work will focus on integrating data uncertainties,addressing complex block deformation mechanisms,refining optimisation objectives,and improving the performance of multi-objective optimisation for slope rockboling applications to further enhance the method's versatility.
基金Supported by Xuhui District Health Commission,No.SHXH202214.
文摘Gastrointestinal tumors require personalized treatment strategies due to their heterogeneity and complexity.Multimodal artificial intelligence(AI)addresses this challenge by integrating diverse data sources-including computed tomography(CT),magnetic resonance imaging(MRI),endoscopic imaging,and genomic profiles-to enable intelligent decision-making for individualized therapy.This approach leverages AI algorithms to fuse imaging,endoscopic,and omics data,facilitating comprehensive characterization of tumor biology,prediction of treatment response,and optimization of therapeutic strategies.By combining CT and MRI for structural assessment,endoscopic data for real-time visual inspection,and genomic information for molecular profiling,multimodal AI enhances the accuracy of patient stratification and treatment personalization.The clinical implementation of this technology demonstrates potential for improving patient outcomes,advancing precision oncology,and supporting individualized care in gastrointestinal cancers.Ultimately,multimodal AI serves as a transformative tool in oncology,bridging data integration with clinical application to effectively tailor therapies.
基金supported by grants from the National Natural Science Foundation of China(32470364,31872850,and 31872804)the Natural Science Basic Research Program of Shaanxi(2025JC-JCQN-056 and 2024JC-YBMS-151)+2 种基金the Guangdong Basic and Applied Basic Research Foundation(2025A1515012749)the China Postdoctoral Science Foundation(2025M774348)the Shaanxi Fundamental Science Research Project for Chemistry&Biology(22JHZ007and 22JHQ054)。
文摘Gibberellins(GAs)and auxin play central regulatory roles in seed germination and root system development,respectively,so that the application of these phytohormones to crops would be worthwhile,with an increasing potential demand in agriculture.However,there are few effective chemicals that simultaneously enhance both GA and auxin signaling.Here,we report on an artificial thiourea derivative chemical,Y21,that serves as both a GA-signaling agonist and an auxin analog,promoting seed germination and root development,as well as low-phosphorus tolerance.Phenotypic,biochemical,and genetic evidence demonstrated that Y21 enhances the interaction between GA and its receptor GID1C via the Val239 amino acid residue and consequently promotes degradation of the DELLA proteins REPRESSOR OF ga1-3(RGA)and RGA-LIKE 2.Furthermore,we found that Y21 interacts with the auxin receptor TIR1 via the Cys405 residue and thus promotes the turnover of the auxinresponsive Aux/IAA proteins.Consequently,Y21significantly increases low-phosphorus tolerance of treated plants by positively regulating lateral root development.To our knowledge,Y21 is the first GA-signaling agonist to be identified,and our results also demonstrate that this potent synthetic chemical,identified by chemical genetic screening,is effective at modulating plant development and stress tolerance.
基金supported by 2024 General Program from the Beijing Association of Higher Education(MS2024232).
文摘This study addresses the challenges confronting the ideological and political construction of general artificial intelligence curriculum-namely,the dilution of value guidance amid pluralistic intellectual currents,the superficial internalization of concepts resulting from didactic pedagogy,and the ineffectiveness of character cultivation stemming from fragmented and decontextualized techno-ethical cases.This paper proposes centering the value proposition on“Serving the Nation through Science and Technology”.Leveraging the deeply integrated industry-academia-research-application synergy,we integrate ideological and political elements into the comprehensive technological practice workflow.To achieve this,we(1)incorporate authentic enterprise project practicums to foster students’sense of responsibility;(2)construct a virtual debate platform on technology ethics dilemmas to develop ethical discernment;and(3)organize solution competitions targeting urgent social problems to incubate technology-for-good initiatives.Collectively,these approaches enhance students’technological mission awareness,ethical sensitivity,and social responsibility.
基金supported by the National Key Research and Development Program of China(2023YFB3907304-3)the National Natural Science Foundation of China(NSFC)(62271050)。
文摘A methodology for the reduction of radar cross section(RCS)of cambered platforms within the target airspace is presented,which utilizes a dual-polarized ultra-wide-angle artificial electromagnetic absorbing surface.By applying the theory of generalized Brewster complex wave impedance matching,five distinct unit cell designs are developed to attain more than95%absorption rate for dual-polarized incident waves within five angular ranges:0°-30°,30°-50°,50°-60°,60°-70°,and 70°-80°.To optimally reduce the RCS of a cambered platform,the five types of units can be evenly distributed on the surface based on the local incident angles of plane waves originating from the target airspace.As an illustrative example,the leading edge of an airfoil is taken into account,and experimental measurements validate the efficiency of the proposed structure.Specifically,the absorbing surface achieves more than 10 dB of RCS reduction in the frequency ranges from 5-10 GHz(about66.7%relative bandwidth)for dual polarizations.
文摘BACKGROUND Gastrointestinal stromal tumors(GISTs)are rare mesenchymal neoplasms primarily originating in the stomach or small intestine.Duodenal GISTs are particularly uncommon,accounting for only a small fraction of GIST cases.These tumors often present with nonspecific symptoms,making early detection challenging.This case discusses a duodenal GIST misdiagnosed as pancreatic cancer due to obstructive jaundice.CASE SUMMARY A 40-year-old male with jaundice and abdominal symptoms underwent imaging,which suggested a malignant periampullary tumor.Preoperative misdiagnosis of pancreatic cancer was made,and surgery was performed.Postoperative histopathology confirmed a duodenal GIST.The role of artificial intelligence in the diagnostic pathway is explored,emphasizing its potential to differentiate between duodenal GISTs and other similar conditions using advanced imaging analysis.CONCLUSION Artificial intelligence in radiomic imaging holds significant promise in enhancing the diagnostic process for rare cancers like duodenal GISTs,ensuring timely and accurate treatment.
基金the financial support from Research Institute for Smart Energy at the Hong Kong Polytechnic University(Grant No.CDB2)the support of the Hong Kong PhD Fellowship Scheme(Grant No.PF21-65328)。
文摘Aqueous zinc metal batteries(AZMBs)are promising candidates for next-generation energy storage,but their commercialization is hindered by zinc anode challenges,notably parasitic reactions and dendrite growth.Herein,we present a biodegradable biomass-derived protective layer,primarily composed of curcumin,as a zincophilic interface for AZMBs.The curcumin-based layer,fabricated via a homogeneous solution process,exhibits strong adhesion,uniform coverage,and robust mechanical integrity.Rich polar functional groups in curcumin facilitate homogeneous Zn~(2+)flux and suppress side reactions.The curcumin-based layer shows a favorable affinity for zinc trifluoromethanesulfonate(Zn(OTf)_(2))electrolyte,which is the representative of organic zinc salts,enabling optimal thickness for both protection and ion transport.The protected Zn anodes demonstrate an extended lifespan of 2500 h in symmetrical cells and a high Coulombic efficiency of 99.15%.Furthermore,Zn(OTf)_(2)-based system typically exhibits poor stability at high current densities.Fortunately,the lifespan of symmetrical cells was extended by 40-fold at the high current density.When paired with an Na V_(3)O_(8)·1.5H_(2)O(NVO)cathode,the system achieves 86.5%capacity retention after 3000 cycles at a large specific current density of 10 A g^(-1).These results underscore the efficacy of the curcumin-based protective layer in enhancing the reversibility and stability of metal electrodes,specifically relieving the instability of Zn(OTf)_(2)-based systems at high current densities,advancing its commercial viability.
基金Funding Project for Ideological and Political Model Courses of“Epidemic Fighting”Courses in Henan Province(Project No.:531,2020)University-level Curriculum Ideological and Political Demonstration Course Support Project of Zhengzhou Sias University(Project No.:34,2024)+2 种基金University-level Key Discipline Support Project of Zhengzhou Sias University(Project No.:1,2022)2025 Key Scientific Research Projects of Henan Universities(Project No.:25B360003)Henan Province Private Brand Professional Support Project(Project No.:527,2019)。
文摘Nursing education is undergoing a paradigm shift from skill training to clinical thinking cultivation.The integration of artificial intelligence technology offers technical possibilities for this transformation,but it also brings about a deep tension between the cultivation of humanistic qualities and a standardized training.Based on the analysis of the practical forms of nursing smart education,this paper examines the cognitive gap between the deterministic feedback of virtual simulation systems and the complexity of real clinical scenarios,reveals the potential narrowing effect of data-driven ability profiling on the all-round development of nursing students,and then proposes the design logic of intelligent teaching resources centered on real clinical problems,a hierarchical teaching model with clear human-machine division of labor,and a dynamic assessment mechanism for technology application led by professional nursing teachers,in an attempt to find a balance between technological empowerment and humanistic commitment in smart nursing education.
文摘Providing safe and quality food is crucial for every household and is of extreme significance in the growth of any society.It is a complex procedure that deals with all issues focusing on the development of food processing from seed to harvest,storage,preparation,and consumption.This current paper seeks to demystify the importance of artificial intelligence,machine learning(ML),deep learning(DL),and computer vision(CV)in ensuring food safety and quality.By stressing the importance of these technologies,the audience will feel reassured and confident in their potential.These are very handy for such problems,giving assurance over food safety.CV is incredibly noble in today's generation because it improves food processing quality and positively impacts firms and researchers.Thus,at the present production stage,rich in image processing and computer visioning is incorporated into all facets of food production.In this field,DL and ML are implemented to identify the type of food in addition to quality.Concerning data and result-oriented perceptions,one has found similarities regarding various approaches.As a result,the findings of this study will be helpful for scholars looking for a proper approach to identify the quality of food offered.It helps to indicate which food products have been discussed by other scholars and lets the reader know papers by other scholars inclined to research further.Also,DL is accurately integrated with identifying the quality and safety of foods in the market.This paper describes the current practices and concerns of ML,DL,and probable trends for its future development.
文摘Healthy behavior has long been linked to mental health outcomes.However,the role of artificial intelligence(AI)literacy in shaping healthy behaviors and its potential impact on mental health remains underexplored.This paper presents a scoping review offering a novel perspective on the intersection of healthy behaviors,mental health,and AI literacy.By examining how individuals’understanding of AI influences their choices regarding nutrition and their susceptibility to mental health issues,the current study explores emerging trends in health behavior decision-making.This emphasizes the need for integrating AI literacy into mental health and health behaviors education,as well as the development of AI-driven tools to support healthier behavior choices.It highlights that individuals with low AI literacy may misinterpret or overly depend on AI guidance,resulting in maladaptive health choices,while those with high AI literacy may be more likely to engage reflectively and sustain positive behaviors.The paper outlines the importance of inclusive education,user-centered design,and community-based support systems to enhance AI literacy for digitally marginalized groups.AI literacy may be positioned as a key determinant of health equity,better allowing for interdisciplinary strategies that empower individuals to make informed,autonomous decisions that promote both physical and mental health.
文摘Artificial intelligence(AI)is increasingly recognized as a transformative force in the field of solid organ transplantation.From enhancing donor-recipient matching to predicting clinical risks and tailoring immunosuppressive therapy,AI has the potential to improve both operational efficiency and patient outcomes.Despite these advancements,the perspectives of transplant professionals-those at the forefront of critical decision-making-remain insufficiently explored.To address this gap,this study utilizes a multi-round electronic Delphi approach to gather and analyses insights from global experts involved in organ transplantation.Participants are invited to complete structured surveys capturing demographic data,professional roles,institutional practices,and prior exposure to AI technologies.The survey also explores perceptions of AI’s potential benefits.Quantitative responses are analyzed using descriptive statistics,while open-ended qualitative responses undergo thematic analysis.Preliminary findings indicate a generally positive outlook on AI’s role in enhancing transplantation processes,particularly in areas such as donor matching and post-operative care.These mixed views reflect both optimism and caution among professionals tasked with integrating new technologies into high-stakes clinical workflows.By capturing a wide range of expert opinions,the findings will inform future policy development,regulatory considerations,and institutional readiness frameworks for the integration of AI into organ transplantation.
基金National Natural Science Foundation of China(42575091)Marine Meteorological Science and Data Center Program (2024B1212070014)。
文摘In this study, the ground potential rise(GPR) phenomenon caused by a lightning current injected into a field-shaped artificial grounding grid, as well as the potential difference between two different nodes at the edge of the grounding grid, was observed and analyzed under artificially triggered lightning conditions. Based on circuit theory and measured current data, a π-equivalent circuit was established to simulate the transient response of the grounding grid.Nineteen return strokes from three artificially triggered lightning events were analyzed. The peak currents of the 19 return strokes range from -6.7 to -25.1 kA, and the mean value was -14.3 kA. The GPR decreased rapidly and formed a subpeak after reaching the initial peak, with the mean value of the initial peak being -148.65 kV and the mean value of the subpeak being -92.87 kV. The GPR induced by the triggered lightning currents exhibited a subpeak phenomenon. Simulation results indicate that the subpeak phenomenon is related to localized corrosion of the vertical grounding electrode. The potential difference at the grounding grid edge exhibited a multi-pulse waveform with alternating polarity, dominated by positive pulses. The peak values of both the positive and negative polarity pulses gradually decreased, with the first positive pulse displaying a significantly higher intensity than that of subsequent pulses.
基金supported by grants for development of new faculty staff,Ratchadaphiseksomphot Fund,Chulalongkorn University,Thailand.
文摘Objectives This study aimed to explore the research trends,thematic structures,and core competency domains in the field of nursing-related digital and artificial intelligence(AI)technologies.Methods A bibliometric analysis was conducted in accordance with the PRISMA 2020 statement.Peer-reviewed articles published in English from 2015 to 2025 were retrieved from Scopus,Web of Science,and PubMed.Thematic clustering was conducted using the Louvain algorithm and cosine similarity.A subset of 66 frequently cited articles was then qualitatively synthesized to capture core competencies across clusters.Results A total of 83,807 articles were included for bibliometric analysis.Of these,66 articles were chosen for thematic analysis.Five major thematic clusters were identified:remote care in primary settings,oncology and palliative care,nurse education and training,safety and quality in nursing practice,and geriatric and dementia care.Additionally,four competency domains were identified:telehealth and remote communication,health systems and informatics,digital tools in practice,and AI-powered decision support.A clear shift in research focus was observed,with the emphasis transitioning from foundational digital skills before the COVID-19 pandemic to more advanced competencies during the post-pandemic digital transformation,encompassing ethical reasoning,immersive technology use,and AI integration.Conclusions Integrating digital and AI technologies is reshaping nursing practice across various thematic areas and competency domains,highlighting a transition from foundational digital tasks to AI-supported decision-making and ethically informed technology use.This study provides a structured overview of evolving competencies in digital nursing and synthesizes evidence to support future research,curriculum design,and policy planning.
文摘The rapid advancement of Artificial Intelligence(AI)has transformed educational practices,yet its integration with experiential pedagogies such as drama remains underexplored in English Language Teaching(ELT),particularly in pre-service teacher education.This study examines how AI-supported drama pedagogy contributes to the professional development of pre-service English teachers,focusing on reflective practice,pedagogical adaptability,creativity,intercultural awareness,and sustainability-oriented teaching perspectives.Grounded in sociocultural theory,experiential learning,and Education for Sustainable Development(ESD),the research adopts an interpretive qualitative case study design conducted over a 12-week elective course titled“Drama in ELT”at a foundation university in Istanbul,Türkiye.Participants included 40 second-year pre-service teachers,with 15 volunteers taking part in semi-structured focus group interviews.Data were collected through open-ended questionnaires and focus groups and analyzed using reflexive thematic analysis.Four interrelated themes emerged:creativity and pedagogical innovation,intercultural awareness and empathy,problem-solving and adaptability,and reflective professional growth with ethical awareness.Findings suggest that AI acted as a mediational scaffold that enriched drama-based learning while preserving human agency.The study concludes that integrating AI with drama offers a meaningful model for sustainable teacher education aligned with SDG 4(Quality Education)and SDG 9(Industry,Innovation and Infrastructure).
