The fusion of VlSI (visual identity system Internet), digital maps and Web GIS is presented. Web GIS interface interactive design with VISI needs to consider more new factors. VISI can provide the design principle, ...The fusion of VlSI (visual identity system Internet), digital maps and Web GIS is presented. Web GIS interface interactive design with VISI needs to consider more new factors. VISI can provide the design principle, elements and contents for the Web GIS. The design of the Wuhan Bus Search System is fulfilled to confirm the validity and practicability of the fusion.展开更多
In this paper, we conduct research on the man-machine interactive environment VR and the applications on vocational educationand training under the perspective of interactivity. With the increase in the general standa...In this paper, we conduct research on the man-machine interactive environment VR and the applications on vocational educationand training under the perspective of interactivity. With the increase in the general standard of social knowledge level and competition intensifi es,more and more people have a goal to build a lifelong learning system, according to their own hobbies, work and the needs of the marketcompetition. Under this condition, the vocational education is becoming more and more essential. This paper integrates the VR and man-machineinteractive concept to propose the new education paradigm that is innovative.展开更多
Porous hydrogel sensors have attracted significant attention in fields such as smart wearables and medical monitoring due to their high sensitivity.However,existing fabrication methods typically degrade the surface sm...Porous hydrogel sensors have attracted significant attention in fields such as smart wearables and medical monitoring due to their high sensitivity.However,existing fabrication methods typically degrade the surface smoothness of hydrogels when introducing porous structures and face significant challenges in removing fillers completely.To address these challenges,we herein introduce a novel one-step,thermosensitive spray-coating technique for the preparation of aircell hydrogel(ACH).This method leverages the rapid cooling of a thermoresponsive gelatin methacryloyl solution through atomization,enabling rapid cross-linking within seconds and air bubbles encapsulated in situ.Additionally,the transient flow of the pre-gel facilitates the repair of voids formed by ruptured surface bubbles,leading to the creation of the ACH with uniformly distributed inner air bubbles and a smooth outer surface.The mold-free fabrication method is independent of substrate surface properties,enabling the creation of a porous hydrogel film with a thickness as thin as 163 µm.Furthermore,the dual-crosslinked network endows the ACH with excellent anti-swelling properties,and the physical crosslinking between gelatin molecules allows the ACH to self-heal.The ACH exhibits excellent sensitivity in deformation sensing and can even successfully track minor external forces,which enables it to effectively complete various tasks such as facial expression recognition,pitch differentiation,and motion detection.By integrating the ACH into a sensing glove,we also demonstrate the significant potential of the ACH for applications in human-machine interaction and tactile sensing.Ultimately,the ACH sensors are also applied to motion mapping and machine tactile feedback,indicating their promising potential in human-machine interaction.展开更多
Conductive hydrogel-based strain sensors,as key components of electronic skins,have garnered significant attention for the development of advanced human-machine interfaces and flexible electronics.However,their intrin...Conductive hydrogel-based strain sensors,as key components of electronic skins,have garnered significant attention for the development of advanced human-machine interfaces and flexible electronics.However,their intrinsic limitations of large hysteresis and poor mechanical robustness pose significant challenges for achieving the high accuracy and long-term stability required for advanced sensing systems.Here,we achieve hysteresis suppression and structural stability by constructing a microphase-separated interlocking network within a 3D-printable poly(vinyl alcohol)(PVA)/conductive carbon black(CCB)hydrogel.The resulting conductive hydrogel strain sensor possesses low electrical hysteresis(0.82%)and high cycle stability(>1×104cycles),enabling real-time and precise monitoring of joint bending and muscle contraction.By converting finger motion into machine-learnable signal patterns,the sensor enables an identification system that decodes continuous strain signals into alphabetical information,offering a novel human-machine interaction modality.This work provides a promising conductive hydrogel platform with enhanced sensing fidelity and interaction capability towards intelligent human-machine interactions.展开更多
Polymer-based piezoelectric films can be assembled into piezoelectric nanogenerators(PENGs),which can simultaneously serve as flexible pressure sensors and energy harvesting devices.However,the low piezoelectric outpu...Polymer-based piezoelectric films can be assembled into piezoelectric nanogenerators(PENGs),which can simultaneously serve as flexible pressure sensors and energy harvesting devices.However,the low piezoelectric output of PENGs is a major limitation for their practical applications.Herein,we propose a coaxial electrospinning strategy to generate a core-shell structured nanofiber film,which could significantly enhance the piezoelectric output compared to the traditional nanofiber film via conventional single-axial electrospinning.Notably,the as-prepared PENGs based on the core-shell structured Cs Cu Cl3/poly(vinylidene fluoride)(PVDF)nanofiber composite film(2 wt%)produced via coaxial spinneret exhibit a 60%increase in output voltage(increase from 48 V to 75 V)and a 50%increase in short-circuit current(increase from 0.2μA to0.3μA)compared to those prepared using a single-needle spinneret.More interestingly,this enhancement in piezoelectric performance is a universal phenomenon because the coaxial electrospinning process can induce greater polymer chain alignment in the shell layer and lead to increased crystallinity and a higher proportion of the piezoelectric-activeβ-phase.Owing to their enhanced piezoelectric output and high sensitivity to subtle pressure variations,the resulting PENGs demonstrate promising potential for human-machine interaction applications.This study offers a novel and broadly applicable approach to boost the piezoelectric performance of polymer-based PENGs.展开更多
The dust cycle is a crucial component of the present-day Martian climate system.This study examines its multitimescale variability using an optimized 50-year simulation with the fully interactive scheme from the Globa...The dust cycle is a crucial component of the present-day Martian climate system.This study examines its multitimescale variability using an optimized 50-year simulation with the fully interactive scheme from the Global Open Planetary Atmospheric Model for Mars(GoMars),a newly developed Mars General Circulation Model(MGCM).GoMars is able to reproduce the diurnal,seasonal,and interannual characteristics of the dust cycle in several key aspects,with high repeatability in diurnal and seasonal variations during non-global dust storm(non-GDS)years.The model’s“climatology”(non-GDS years ensemble mean)captures the seasonal pattern and magnitude of the vertical–meridional dust distribution,validated against Mars Climate Database and Mars Climate Sounder observations.In the absence of direct observations,the GoMars-simulated near-surface wind stress lifting flux is evaluated through comparisons with other MGCMs(e.g.,MarsWRF),revealing consistent seasonal and spatial patterns.As for the diurnal cycle,the peak dust devil lifting flux occurs at 1200–1300 local time,matching the Mars Pathfinder measurements.The model also successfully captures the intense dust devil activity in Amazonis,a region identified as a major dust devil hotspot based on observational data.In GDS years,GoMars effectively reproduces spontaneous GDSs,capturing their observed onset times,locations,and dust transport patterns as exhibited in specific Martian years.The model also simulates significant interannual variability,with irregular GDS intervals along with reasonable dust–atmosphere interactions.展开更多
Idiosyncratic drug-induced liver injury(iDILI)is a rare,dose-independent and unpredictable adverse reaction occurring at therapeutic drug exposure,and it presents a significant challenge for drug development and patie...Idiosyncratic drug-induced liver injury(iDILI)is a rare,dose-independent and unpredictable adverse reaction occurring at therapeutic drug exposure,and it presents a significant challenge for drug development and patient safety.Despite extensive research,genetic susceptibility to iDILI remains poorly understood.We conducted a comprehensive systematic study of 139 human genetic studies to identify and characterize genetic polymorphisms associated with increased risk or protection against iDILI.Our study included candidate gene studies and genome-wide association studies(GWAS),encompassing 83 risk and 25 protective genes,with NAT2,HLA-B,and SLCO1B1 among the most frequently reported.We performed functional enrichment analyses using KEGG and Gene Ontology,revealing key biological pathways related to immune response,xenobiotic metabolism,and bile secretion.To enhance data accessibility and interpretation,we developed iDILInet,a publicly available web application that enables interactive exploration and network-based visualization of iDILI-associated gene-variant-drug relationships,enriched with liver-specific expression data from the Human Protein Atlas(HPA).Our work provides a novel integrative resource that supports ongoing efforts in precision medicine and pharmacogenomics and represents a significant advancement in implementing living systematic reviews in toxicogenomics.展开更多
Autonomous driving depends on successful interactions among humans,vehicles,and roads.However,people often lack an understanding of autonomous vehicle(AV)behaviours and decisions.Moreover,AVs have difficulty aligning ...Autonomous driving depends on successful interactions among humans,vehicles,and roads.However,people often lack an understanding of autonomous vehicle(AV)behaviours and decisions.Moreover,AVs have difficulty aligning with human intentions in their interactions.To overcome the obstacles associated with the absence of interactive intelligence,especially in complex and uncertain environments,we introduce the concept of embodied interactive intelligence towards autonomous driving(EIIAD),which establishes representation and learning methods aligned with the physical world,enhancing human-machine integration.Building on this concept,we propose an end-to-end unified constrained vehicle environment interaction(UniCVE)model,which involves the construction of an end-to-end perception-cognition-behaviour closed-loop feedback paradigm and continuous learning through accumulated split driving scenarios.This model realizes interaction cognition through networks designed for pedestrians and vehicles,and it unifies the cognition as a value network of AVs to generate socially compatible behaviours.The UniCVE model is implemented on Dongfeng autonomous buses,which have successfully travelled 22 thousand kilometres and completed 45 thousand navigation tasks in Xiong’an New Area,China,demonstrating its general applicability in various driving scenarios.In addition,we highlight the high-level interactive intelligence of the UniCVE model in selected simulated complex interaction scenarios,demonstrating that it makes AVs more intelligent,more reliable,and more attuned to human relationships.Furthermore,the UniCVE model’s capacity for self-learning and self-growth allows it to infinitely approximate true intelligence,even with limited experience.展开更多
Continuous and highly accurate navigation of long-endurance flight vehicles continues to be a substantial challenge in Global Navigation Satellite Systems(GNSS)-denied environments.Though the integrated navigation bas...Continuous and highly accurate navigation of long-endurance flight vehicles continues to be a substantial challenge in Global Navigation Satellite Systems(GNSS)-denied environments.Though the integrated navigation based on multiple sensors is used to improve the navigation performance,the existing methods are prone to model mismatch and error accumulation under heterogeneous conditions of sensors.In this paper,a Tightly-coupled Interactive Multi-Model Factor Graph Optimization(TIMMFGO) navigation method is proposed to solve the problem.The developed integrated navigation framework consists of Inertial Navigation Systems(INS),Celestial Navigation Systems(CNS),Radio Navigation Systems(RNS),and Barometric Altimeters(BA).We propose a CNS/INS tightly-coupled graph architecture that integrates star vector observations with INS pre-integration,enabling dynamic compensation of gyroscopic bias while correcting the attitude update accuracy of INS.Then,an Interactive Multi-Model(IMM) adaptive weighting strategy is used to combine the vertical RNS factor with the BA factor for position,which can effectively reduce the altitude bias induced by the spatial configuration constraints of RNS.The simulation demonstrates that compared to the Huber M-estimation-based FGO(HMFGO),Windowing Anomaly-Detection-based FGO(WADFGO) and IMM Unscented Kalman Filter(IMMUKF)methods,the TIMMFGO method improves attitude accuracy by 46.49 %,25.68 % and 20.67 %,respectively,while correspondingly reducing position accuracy by 29.29 %,10.79 % and 6.96 %.展开更多
Rock discontinuities control rock mechanical behaviors and significantly influence the stability of rock masses.However,existing discontinuity mapping algorithms are susceptible to noise,and the calculation results ca...Rock discontinuities control rock mechanical behaviors and significantly influence the stability of rock masses.However,existing discontinuity mapping algorithms are susceptible to noise,and the calculation results cannot be fed back to users timely.To address this issue,we proposed a human-machine interaction(HMI)method for discontinuity mapping.Users can help the algorithm identify the noise and make real-time result judgments and parameter adjustments.For this,a regular cube was selected to illustrate the workflows:(1)point cloud was acquired using remote sensing;(2)the HMI method was employed to select reference points and angle thresholds to detect group discontinuity;(3)individual discontinuities were extracted from the group discontinuity using a density-based cluster algorithm;and(4)the orientation of each discontinuity was measured based on a plane fitting algorithm.The method was applied to a well-studied highway road cut and a complex natural slope.The consistency of the computational results with field measurements demonstrates its good accuracy,and the average error in the dip direction and dip angle for both cases was less than 3.Finally,the computational time of the proposed method was compared with two other popular algorithms,and the reduction in computational time by tens of times proves its high computational efficiency.This method provides geologists and geological engineers with a new idea to map rapidly and accurately rock structures under large amounts of noises or unclear features.展开更多
The toxicity of 6PPD(N-(1,3-Dimethylbutyl)-N'-phenyl-p-phenylenediamine) to algae raises concern due to its potential to disrupt primary productivity in aquatic ecosystems. This study investigates the interactive ...The toxicity of 6PPD(N-(1,3-Dimethylbutyl)-N'-phenyl-p-phenylenediamine) to algae raises concern due to its potential to disrupt primary productivity in aquatic ecosystems. This study investigates the interactive toxicity of6PPD and Cd(Ⅱ) to algae in the presence and absence of other microorganisms, evaluated 48 h after exposure. In pure culture, Cd(Ⅱ) exhibited dominant toxicity, while the toxicity of 6PPD was minimal. In contrast, in microbial community stock culture, the toxicity of 6PPD significantly increased with concentration, resulting in decreased algae growth, reduced chlorophyll a content, and suppression of key photosynthesis parameters. Notably, the addition of 2 mg/L Cd(Ⅱ) significantly attenuated the toxicity of 6PPD to algae, suggesting an antagonistic interaction. However, at 4 mg/L Cd(Ⅱ), the toxicity of 6PPD to algae remained significant at higher concentrations.Gene expression analysis revealed that 6PPD upregulated oxidative stress genes and photosynthetic genes, indicating a stress response, while Cd(Ⅱ) inhibited these responses. Additionally, Cd(Ⅱ) downregulated the P450enzyme, suggesting potential inhibition of microbial transform of 6PPD into more toxic metabolites, such as6PPD-quinone. Fluorescence spectroscopy showed that 2 mg/L Cd(Ⅱ) reduced humic acid-like and tryptophanlike dissolved organic matter(DOM) in the culture supernatants, potentially affecting the bioavailability of 6PPD.The findings suggest that the presence of other microorganisms amplifies the toxicity of 6PPD, with effects may be mitigated by Cd(Ⅱ) via microbial transformation inhibition or DOM complexation. Overall, this study provides a comprehensive understanding of how the interaction of 6PPD and Cd(Ⅱ) impacts the health and function of aquatic plants.展开更多
Ensuring operational safety for autonomous vehicles is a critical challenge in modern engineering,particularly due to the intricate interactions among diverse traffic participants.Traditional approaches often treat pl...Ensuring operational safety for autonomous vehicles is a critical challenge in modern engineering,particularly due to the intricate interactions among diverse traffic participants.Traditional approaches often treat planning and prediction as unidirectional processes,failing to capture the dynamic,game-theoretic nature of realworld traffic.In the context of Digital Twins,there is an urgent need for high-fidelity virtual representations that can model the continuous,bidirectional evolution of the ego vehicle and surrounding agents to support robust decisionmaking under uncertainty.To address these limitations,a novel framework named Planning by Simulation with mutual influence prediction is proposed,which functions as a high-fidelity simulation-based predictive planner for autonomous driving decision-making.This framework explicitly models the iterative interplay between the ego vehicle’s planning and the predicted trajectories of surrounding agents within a virtual environment.By integrating a querycentric trajectory prediction mechanism with Monte Carlo Tree Search,the proposed approach orchestrates intelligent model exploration.It iteratively refines the ego vehicle’s actions by simulating future scenarios and adapting to the dynamic behaviors of other agents,thereby tightly coupling data-driven predictions with physics-based planning constraints.Comprehensive evaluations on the Argoverse 1 and Argoverse 2 dataset in Metadrive simulator demonstrate the efficacy of this simulation-based approach.The framework successfully captures complex interaction dynamics that static models overlook.The results indicate that the proposed method generates significantly safer,more rational,and human-like trajectories compared to existing baselines,validating the system’s high-fidelity predictive capabilities.The proposed framework illustrates the transformative potential of advanced virtual simulation technologies in autonomous mobility.By enabling the continuous integration of predictive data into the planning loop,this study provides a powerful foundation for interpretable and reliable decision-making in virtual engineering systems.It highlights how coupling generative simulation with interactive planning can resolve critical safety challenges in the lifecycle of intelligent autonomous systems.展开更多
Aiming at the problems of lagging curriculum,weak practice,and single evaluation in the cultivation of HarmonyOS Development talents,this study constructs a“teacher-machine-student”ternary interactive teaching model...Aiming at the problems of lagging curriculum,weak practice,and single evaluation in the cultivation of HarmonyOS Development talents,this study constructs a“teacher-machine-student”ternary interactive teaching model based on the Congyou platform.Through the building block curriculum system,the HarmonyOS technology stack is decoupled into dynamic capability units,and a multi-disciplinary cross-case library is jointly built with Huawei,which significantly improves the synchronization of teaching content and industrial technology.This paper innovatively designs an AI collaborative teaching system,which employs knowledge graphs to plan learning paths,utilizes virtual equipment clusters to simulate development environments,and establishes a“diagnosis-feedback-enhancement”closed loop through AI-based review,thereby effectively improving students’development efficiency and code reuse rate.A three-dimensional evaluation model integrating task outcomes,process performance,and innovation is constructed,incorporating indicators such as code standardization and an innovation index to strengthen the cultivation of engineering thinking and innovative ability.Furthermore,a data-driven support platform is built to generate student competency profiles,open up the“credit-competency-certification”pathway,promote the transformation of course achievements into contributions to the Huawei ecosystem,and significantly shorten the job adaptation cycle for graduates.The research results provide a replicable paradigm for the cultivation of domestic operating system talents.展开更多
Reliable traffic flow prediction is crucial for mitigating urban congestion.This paper proposes Attentionbased spatiotemporal Interactive Dynamic Graph Convolutional Network(AIDGCN),a novel architecture integrating In...Reliable traffic flow prediction is crucial for mitigating urban congestion.This paper proposes Attentionbased spatiotemporal Interactive Dynamic Graph Convolutional Network(AIDGCN),a novel architecture integrating Interactive Dynamic Graph Convolution Network(IDGCN)with Temporal Multi-Head Trend-Aware Attention.Its core innovation lies in IDGCN,which uniquely splits sequences into symmetric intervals for interactive feature sharing via dynamic graphs,and a novel attention mechanism incorporating convolutional operations to capture essential local traffic trends—addressing a critical gap in standard attention for continuous data.For 15-and 60-min forecasting on METR-LA,AIDGCN achieves MAEs of 0.75%and 0.39%,and RMSEs of 1.32%and 0.14%,respectively.In the 60-min long-term forecasting of the PEMS-BAY dataset,the AIDGCN out-performs the MRA-BGCN method by 6.28%,4.93%,and 7.17%in terms of MAE,RMSE,and MAPE,respectively.Experimental results demonstrate the superiority of our pro-posed model over state-of-the-art methods.展开更多
At nomaly detectors are used to distinguish differences between normal and abnormal data,which are usually implemented by evaluating and ranking the anomaly scores of each instance.A static unsupervised streaming anom...At nomaly detectors are used to distinguish differences between normal and abnormal data,which are usually implemented by evaluating and ranking the anomaly scores of each instance.A static unsupervised streaming anomaly detector is difficult to dynamically adjust anomaly score calculation.In real scenarios,anomaly detection often needs to be regulated by human feedback,which benefits adjusting anomaly detectors.In this paper,we propose a human-machine interactive streaming anomaly detection method,named ISPForest,which can be adaptively updated online under the guidance of human feedback.In particular,the feedback will be used to adjust the anomaly score calculation and structure of the detector,ideally attaining more accurate anomaly scores in the future.Our main contribution is to improve the tree-based streaming anomaly detection model that can be updated online from perspectives of anomaly score calculation and model structure.Our approach is instantiated for the powerful class of tree-based streaming anomaly detectors,and we conduct experiments on a range of benchmark datasets.The results demonstrate that the utility of incorporating feedback can improve the performance of anomaly detectors with a few human efforts.展开更多
Background With an increasing number of vehicles becoming autonomous,intelligent,and connected,paying attention to the future usage of car human-machine interface with these vehicles should become more relevant.Severa...Background With an increasing number of vehicles becoming autonomous,intelligent,and connected,paying attention to the future usage of car human-machine interface with these vehicles should become more relevant.Several studies have addressed car HMI but were less attentive to designing and implementing interactive glazing for every day(autonomous)driving contexts.Methods Reflecting on the literature,we describe an engineering psychology practice and the design of six novel future user scenarios,which envision the application of a specific set of augmented reality(AR)support user interactions.Additionally,we conduct evaluations on specific scenarios and experiential prototypes,which reveal that these AR scenarios aid the target user groups in experiencing a new type of interaction.The overall evaluation is positive with valuable assessment results and suggestions.Conclusions This study can interest applied psychology educators who aspire to teach how AR can be operationalized in a human-centered design process to students with minimal pre-existing expertise or minimal scientific knowledge in engineering psychology.展开更多
Research on original children’s picture books that are already existing has not yet been completely explored formally. When it comes to the locally produced picture books, they do not match the young children’s cogn...Research on original children’s picture books that are already existing has not yet been completely explored formally. When it comes to the locally produced picture books, they do not match the young children’s cognitive level, and also the interaction is not deep enough. Also there are still few researches related to the ones based on regional culture pictures book. The authors choose parents with kids under 12 from Shanxi Province to investigate the present situation of integrating interactive picture books with local culture in Shanxi. This study explores different aspects such as children’s reading behavior, mode of interaction preference, and the preference for picture book content and theme, so as to discover the true need and creativity direction of children’s picture book in Shanxi. It can be seen from the results that children prefer interactive forms that involve doing things themselves as well as stories which are interesting and full of make believe. From those, it is hoped that this paper could give some practical advice and directions for the creation of homegrown Chinese children’s picture books (Zhou, 2025).展开更多
Virtual reality scenes oriented towards immersive interaction have strict requirements for real-time rendering,such as high frame rate,low latency,and visual consistency.Traditional rendering methods are difficult to ...Virtual reality scenes oriented towards immersive interaction have strict requirements for real-time rendering,such as high frame rate,low latency,and visual consistency.Traditional rendering methods are difficult to ensure both real-time performance and immersive experience under limited computing resources.This article systematically explores the key technologies and implementation paths of intelligent rendering methods:firstly,it analyzes the rendering pressure bottleneck,multi view continuity,and visual dual constraints caused by immersive interaction;Furthermore,an intelligent rendering mechanism based on gaze point prediction,scene semantic modeling,and closed-loop resource allocation will be constructed;On this basis,adaptive strategies such as behavior driven detail level adjustment,dynamic and static differentiation processing,spatiotemporal consistency,and load coordination are proposed;Finally,the evaluation indicators,stability analysis,and scalability verification of real-time performance and immersion are discussed.This article provides a system framework for the theoretical construction and engineering implementation of intelligent rendering methods.展开更多
Objective: To investigate the nursing care outcomes for patients undergoing blood purification and analyze the impact of the Cox Health Behavior Interactive Nursing Model. Methods: The study was conducted at Yangzhong...Objective: To investigate the nursing care outcomes for patients undergoing blood purification and analyze the impact of the Cox Health Behavior Interactive Nursing Model. Methods: The study was conducted at Yangzhong People's Hospital from January 2023 to December 2024. A total of 90 eligible blood purification patients were randomly selected and divided into two groups using a random number table: the control group (n=45) received conventional nursing care, while the study group (n=45) received the Cox Health Behavior Interactive Nursing Model in addition to conventional care. Outcomes were compared. Results: Post-intervention, (1) SAS and SDS scores: study group <control group (P<0.05); (2) Self-management ability scores: study group> control group (P<0.05); (3) Complication rates: total incidence in the study group <control group (P<0.05); (4) PSQI total score and RPFS scores: study group <control group (P<0.05); (5) Quality of life: study group> control group (P<0.05); (6) Nursing satisfaction: study group> control group (P<0.05). Conclusion: Compared with conventional nursing care, the Cox Health Behavior Interactive Nursing Model demonstrated superior overall efficacy, effectively reducing negative emotions, enhancing self-management abilities, minimizing complications, alleviating fatigue, improving sleep and quality of life, and increasing patient satisfaction.展开更多
In recent years,railway construction in China has developed vigorously.With continuous improvements in the highspeed railway network,the focus is gradually shifting from large-scale construction to large-scale operati...In recent years,railway construction in China has developed vigorously.With continuous improvements in the highspeed railway network,the focus is gradually shifting from large-scale construction to large-scale operations.However,several challenges have emerged within the high-speed railway dispatching and command system,including the heavy workload faced by dispatchers,the difficulty of quantifying subjective expertise,and the need for effective training of professionals.Amid the growing application of artificial intelligence technologies in railway systems,this study leverages Large Language Model(LLM)technology.LLMs bring enhanced intelligence,predictive capabilities,robust memory,and adaptability to diverse real-world scenarios.This study proposes a human-computer interactive intelligent scheduling auxiliary training system built on LLM technology.The system offers capabilities including natural dialogue,knowledge reasoning,and human feedback learning.With broad applicability,the system is suitable for vocational education,guided inquiry,knowledge-based Q&A,and other training scenarios.Validation results demonstrate its effectiveness in auxiliary training,providing substantial support for educators,students,and dispatching personnel in colleges and professional settings.展开更多
基金Supported by the National Natural Science Foundation of China (No. 40071071).
摘要The fusion of VlSI (visual identity system Internet), digital maps and Web GIS is presented. Web GIS interface interactive design with VISI needs to consider more new factors. VISI can provide the design principle, elements and contents for the Web GIS. The design of the Wuhan Bus Search System is fulfilled to confirm the validity and practicability of the fusion.
摘要In this paper, we conduct research on the man-machine interactive environment VR and the applications on vocational educationand training under the perspective of interactivity. With the increase in the general standard of social knowledge level and competition intensifi es,more and more people have a goal to build a lifelong learning system, according to their own hobbies, work and the needs of the marketcompetition. Under this condition, the vocational education is becoming more and more essential. This paper integrates the VR and man-machineinteractive concept to propose the new education paradigm that is innovative.
基金financially supported by the National Key R&D Program of China(Grant No.2023YFE0108900)EU HORIZON 2021 L4DNANO(No.101086227)。
摘要Porous hydrogel sensors have attracted significant attention in fields such as smart wearables and medical monitoring due to their high sensitivity.However,existing fabrication methods typically degrade the surface smoothness of hydrogels when introducing porous structures and face significant challenges in removing fillers completely.To address these challenges,we herein introduce a novel one-step,thermosensitive spray-coating technique for the preparation of aircell hydrogel(ACH).This method leverages the rapid cooling of a thermoresponsive gelatin methacryloyl solution through atomization,enabling rapid cross-linking within seconds and air bubbles encapsulated in situ.Additionally,the transient flow of the pre-gel facilitates the repair of voids formed by ruptured surface bubbles,leading to the creation of the ACH with uniformly distributed inner air bubbles and a smooth outer surface.The mold-free fabrication method is independent of substrate surface properties,enabling the creation of a porous hydrogel film with a thickness as thin as 163 µm.Furthermore,the dual-crosslinked network endows the ACH with excellent anti-swelling properties,and the physical crosslinking between gelatin molecules allows the ACH to self-heal.The ACH exhibits excellent sensitivity in deformation sensing and can even successfully track minor external forces,which enables it to effectively complete various tasks such as facial expression recognition,pitch differentiation,and motion detection.By integrating the ACH into a sensing glove,we also demonstrate the significant potential of the ACH for applications in human-machine interaction and tactile sensing.Ultimately,the ACH sensors are also applied to motion mapping and machine tactile feedback,indicating their promising potential in human-machine interaction.
基金supported by the National Natural Science Foundation of China(Nos.82100877 and 52473179)Research Project of the State Key Laboratory of Mechanical System and Vibration(No.MSV202013)+2 种基金Training Program of the Natural Science Foundation of China Youth Fund(No.20202ZDB01007)the Natural Science Foundation of Jiangxi Province(Nos.20252BAC200300 and 20252BEJ730346)the Research Startup Grant of Jiangxi Science&Technology Normal University(No.2024BSQD15)。
摘要Conductive hydrogel-based strain sensors,as key components of electronic skins,have garnered significant attention for the development of advanced human-machine interfaces and flexible electronics.However,their intrinsic limitations of large hysteresis and poor mechanical robustness pose significant challenges for achieving the high accuracy and long-term stability required for advanced sensing systems.Here,we achieve hysteresis suppression and structural stability by constructing a microphase-separated interlocking network within a 3D-printable poly(vinyl alcohol)(PVA)/conductive carbon black(CCB)hydrogel.The resulting conductive hydrogel strain sensor possesses low electrical hysteresis(0.82%)and high cycle stability(>1×104cycles),enabling real-time and precise monitoring of joint bending and muscle contraction.By converting finger motion into machine-learnable signal patterns,the sensor enables an identification system that decodes continuous strain signals into alphabetical information,offering a novel human-machine interaction modality.This work provides a promising conductive hydrogel platform with enhanced sensing fidelity and interaction capability towards intelligent human-machine interactions.
基金supported by the Key Project of Jiangsu Provincial Key Laboratory of Biomass Energy and Materials(No.JSBEM-S-202303)the National Natural Science Foundation of China(No.52273070)the Natural Science Fund of Zhejiang Province(No.LRG25E030003).
摘要Polymer-based piezoelectric films can be assembled into piezoelectric nanogenerators(PENGs),which can simultaneously serve as flexible pressure sensors and energy harvesting devices.However,the low piezoelectric output of PENGs is a major limitation for their practical applications.Herein,we propose a coaxial electrospinning strategy to generate a core-shell structured nanofiber film,which could significantly enhance the piezoelectric output compared to the traditional nanofiber film via conventional single-axial electrospinning.Notably,the as-prepared PENGs based on the core-shell structured Cs Cu Cl3/poly(vinylidene fluoride)(PVDF)nanofiber composite film(2 wt%)produced via coaxial spinneret exhibit a 60%increase in output voltage(increase from 48 V to 75 V)and a 50%increase in short-circuit current(increase from 0.2μA to0.3μA)compared to those prepared using a single-needle spinneret.More interestingly,this enhancement in piezoelectric performance is a universal phenomenon because the coaxial electrospinning process can induce greater polymer chain alignment in the shell layer and lead to increased crystallinity and a higher proportion of the piezoelectric-activeβ-phase.Owing to their enhanced piezoelectric output and high sensitivity to subtle pressure variations,the resulting PENGs demonstrate promising potential for human-machine interaction applications.This study offers a novel and broadly applicable approach to boost the piezoelectric performance of polymer-based PENGs.
基金jointly supported by the National Natural Science Foundation of China(Grant No.42475135)the Key Technology Research Project of TW-3(TW3006)the IAP’s basic scientific research project during the 14th Five-Year Plan Period.
摘要The dust cycle is a crucial component of the present-day Martian climate system.This study examines its multitimescale variability using an optimized 50-year simulation with the fully interactive scheme from the Global Open Planetary Atmospheric Model for Mars(GoMars),a newly developed Mars General Circulation Model(MGCM).GoMars is able to reproduce the diurnal,seasonal,and interannual characteristics of the dust cycle in several key aspects,with high repeatability in diurnal and seasonal variations during non-global dust storm(non-GDS)years.The model’s“climatology”(non-GDS years ensemble mean)captures the seasonal pattern and magnitude of the vertical–meridional dust distribution,validated against Mars Climate Database and Mars Climate Sounder observations.In the absence of direct observations,the GoMars-simulated near-surface wind stress lifting flux is evaluated through comparisons with other MGCMs(e.g.,MarsWRF),revealing consistent seasonal and spatial patterns.As for the diurnal cycle,the peak dust devil lifting flux occurs at 1200–1300 local time,matching the Mars Pathfinder measurements.The model also successfully captures the intense dust devil activity in Amazonis,a region identified as a major dust devil hotspot based on observational data.In GDS years,GoMars effectively reproduces spontaneous GDSs,capturing their observed onset times,locations,and dust transport patterns as exhibited in specific Martian years.The model also simulates significant interannual variability,with irregular GDS intervals along with reasonable dust–atmosphere interactions.
基金supported by grants from the Consejeria de Salud de Andalucia,and the Instituto de Salud Carlos III,cofounded by Fondo Europeo de Desarrollo Regional(FEDER)(PI21/01248,PT23/00137,PI24/01205,FORT23/00013)Agencia Española del Medicamento y Productos Sanitarios+6 种基金from Ministerio de Ciencia e InnovacionAgencia Estatal de Investigacion(PID2022-140169OB-C21/MCIN/AEI/10.13039/501100011033/FEDER)HORIZON-HLTH-2022-STAYHLTH-02,grant number 101095679,and from University of Malaga(PPRO-CTS649-G-2023 and PPRO-CTS1032-G-2023)Marina Villanueva-Paz holds a postdoctoral research contract from Consejeria de Salud y Consumo de la Junta de Andalucia(RHJ-0052-2024)Gonzalo Matilla-Cabello holds an FPU PhD fellowship from the Spanish Ministry of Science,Innovation,and Universities(FPU22/03868)Antonio Segovia-Zafra holds a Jaume Bosch predoctoral contract(CECO-EHD002)funded by CIBEREHDAngela Remesal-Doblado holds an FPI PhD contract associated with Proyecto Generacion de Conocimiento 2022(PREP2022-000511).CIBERehd is funded by ISCIII.
摘要Idiosyncratic drug-induced liver injury(iDILI)is a rare,dose-independent and unpredictable adverse reaction occurring at therapeutic drug exposure,and it presents a significant challenge for drug development and patient safety.Despite extensive research,genetic susceptibility to iDILI remains poorly understood.We conducted a comprehensive systematic study of 139 human genetic studies to identify and characterize genetic polymorphisms associated with increased risk or protection against iDILI.Our study included candidate gene studies and genome-wide association studies(GWAS),encompassing 83 risk and 25 protective genes,with NAT2,HLA-B,and SLCO1B1 among the most frequently reported.We performed functional enrichment analyses using KEGG and Gene Ontology,revealing key biological pathways related to immune response,xenobiotic metabolism,and bile secretion.To enhance data accessibility and interpretation,we developed iDILInet,a publicly available web application that enables interactive exploration and network-based visualization of iDILI-associated gene-variant-drug relationships,enriched with liver-specific expression data from the Human Protein Atlas(HPA).Our work provides a novel integrative resource that supports ongoing efforts in precision medicine and pharmacogenomics and represents a significant advancement in implementing living systematic reviews in toxicogenomics.
基金supported by the National Natural Science Foundation of China(62371013)the National Key Research and Development Program of China(2023YFF0615800)+1 种基金the National Natural Science Foundation of China-Research Grants Council(NSFC-RGC)Joint Research Scheme(62461160309)the Beijing Natural Science Foundation(L247007).
摘要Autonomous driving depends on successful interactions among humans,vehicles,and roads.However,people often lack an understanding of autonomous vehicle(AV)behaviours and decisions.Moreover,AVs have difficulty aligning with human intentions in their interactions.To overcome the obstacles associated with the absence of interactive intelligence,especially in complex and uncertain environments,we introduce the concept of embodied interactive intelligence towards autonomous driving(EIIAD),which establishes representation and learning methods aligned with the physical world,enhancing human-machine integration.Building on this concept,we propose an end-to-end unified constrained vehicle environment interaction(UniCVE)model,which involves the construction of an end-to-end perception-cognition-behaviour closed-loop feedback paradigm and continuous learning through accumulated split driving scenarios.This model realizes interaction cognition through networks designed for pedestrians and vehicles,and it unifies the cognition as a value network of AVs to generate socially compatible behaviours.The UniCVE model is implemented on Dongfeng autonomous buses,which have successfully travelled 22 thousand kilometres and completed 45 thousand navigation tasks in Xiong’an New Area,China,demonstrating its general applicability in various driving scenarios.In addition,we highlight the high-level interactive intelligence of the UniCVE model in selected simulated complex interaction scenarios,demonstrating that it makes AVs more intelligent,more reliable,and more attuned to human relationships.Furthermore,the UniCVE model’s capacity for self-learning and self-growth allows it to infinitely approximate true intelligence,even with limited experience.
基金co-supported by the Open Fund of National Natural Science Foundation of China(No.62401042)the Young Elite Scientists Sponsorship Program by China Association for Science and Technology(No.2023QNRC001)。
摘要Continuous and highly accurate navigation of long-endurance flight vehicles continues to be a substantial challenge in Global Navigation Satellite Systems(GNSS)-denied environments.Though the integrated navigation based on multiple sensors is used to improve the navigation performance,the existing methods are prone to model mismatch and error accumulation under heterogeneous conditions of sensors.In this paper,a Tightly-coupled Interactive Multi-Model Factor Graph Optimization(TIMMFGO) navigation method is proposed to solve the problem.The developed integrated navigation framework consists of Inertial Navigation Systems(INS),Celestial Navigation Systems(CNS),Radio Navigation Systems(RNS),and Barometric Altimeters(BA).We propose a CNS/INS tightly-coupled graph architecture that integrates star vector observations with INS pre-integration,enabling dynamic compensation of gyroscopic bias while correcting the attitude update accuracy of INS.Then,an Interactive Multi-Model(IMM) adaptive weighting strategy is used to combine the vertical RNS factor with the BA factor for position,which can effectively reduce the altitude bias induced by the spatial configuration constraints of RNS.The simulation demonstrates that compared to the Huber M-estimation-based FGO(HMFGO),Windowing Anomaly-Detection-based FGO(WADFGO) and IMM Unscented Kalman Filter(IMMUKF)methods,the TIMMFGO method improves attitude accuracy by 46.49 %,25.68 % and 20.67 %,respectively,while correspondingly reducing position accuracy by 29.29 %,10.79 % and 6.96 %.
基金supported by the National Key R&D Program of China(No.2023YFC3081200)the National Natural Science Foundation of China(No.42077264)the Scientific Research Project of PowerChina Huadong Engineering Corporation Limited(HDEC-2022-0301).
摘要Rock discontinuities control rock mechanical behaviors and significantly influence the stability of rock masses.However,existing discontinuity mapping algorithms are susceptible to noise,and the calculation results cannot be fed back to users timely.To address this issue,we proposed a human-machine interaction(HMI)method for discontinuity mapping.Users can help the algorithm identify the noise and make real-time result judgments and parameter adjustments.For this,a regular cube was selected to illustrate the workflows:(1)point cloud was acquired using remote sensing;(2)the HMI method was employed to select reference points and angle thresholds to detect group discontinuity;(3)individual discontinuities were extracted from the group discontinuity using a density-based cluster algorithm;and(4)the orientation of each discontinuity was measured based on a plane fitting algorithm.The method was applied to a well-studied highway road cut and a complex natural slope.The consistency of the computational results with field measurements demonstrates its good accuracy,and the average error in the dip direction and dip angle for both cases was less than 3.Finally,the computational time of the proposed method was compared with two other popular algorithms,and the reduction in computational time by tens of times proves its high computational efficiency.This method provides geologists and geological engineers with a new idea to map rapidly and accurately rock structures under large amounts of noises or unclear features.
基金supported by the National Natural Science Foundation of China(Nos.31870432 and 31370421)the National Key Research and Development Program of China(No.2018YFC1801703)the Natural Science Foundation Joint Fund Project of Hubei province in China(No.2024AFD351).
摘要The toxicity of 6PPD(N-(1,3-Dimethylbutyl)-N'-phenyl-p-phenylenediamine) to algae raises concern due to its potential to disrupt primary productivity in aquatic ecosystems. This study investigates the interactive toxicity of6PPD and Cd(Ⅱ) to algae in the presence and absence of other microorganisms, evaluated 48 h after exposure. In pure culture, Cd(Ⅱ) exhibited dominant toxicity, while the toxicity of 6PPD was minimal. In contrast, in microbial community stock culture, the toxicity of 6PPD significantly increased with concentration, resulting in decreased algae growth, reduced chlorophyll a content, and suppression of key photosynthesis parameters. Notably, the addition of 2 mg/L Cd(Ⅱ) significantly attenuated the toxicity of 6PPD to algae, suggesting an antagonistic interaction. However, at 4 mg/L Cd(Ⅱ), the toxicity of 6PPD to algae remained significant at higher concentrations.Gene expression analysis revealed that 6PPD upregulated oxidative stress genes and photosynthetic genes, indicating a stress response, while Cd(Ⅱ) inhibited these responses. Additionally, Cd(Ⅱ) downregulated the P450enzyme, suggesting potential inhibition of microbial transform of 6PPD into more toxic metabolites, such as6PPD-quinone. Fluorescence spectroscopy showed that 2 mg/L Cd(Ⅱ) reduced humic acid-like and tryptophanlike dissolved organic matter(DOM) in the culture supernatants, potentially affecting the bioavailability of 6PPD.The findings suggest that the presence of other microorganisms amplifies the toxicity of 6PPD, with effects may be mitigated by Cd(Ⅱ) via microbial transformation inhibition or DOM complexation. Overall, this study provides a comprehensive understanding of how the interaction of 6PPD and Cd(Ⅱ) impacts the health and function of aquatic plants.
摘要Ensuring operational safety for autonomous vehicles is a critical challenge in modern engineering,particularly due to the intricate interactions among diverse traffic participants.Traditional approaches often treat planning and prediction as unidirectional processes,failing to capture the dynamic,game-theoretic nature of realworld traffic.In the context of Digital Twins,there is an urgent need for high-fidelity virtual representations that can model the continuous,bidirectional evolution of the ego vehicle and surrounding agents to support robust decisionmaking under uncertainty.To address these limitations,a novel framework named Planning by Simulation with mutual influence prediction is proposed,which functions as a high-fidelity simulation-based predictive planner for autonomous driving decision-making.This framework explicitly models the iterative interplay between the ego vehicle’s planning and the predicted trajectories of surrounding agents within a virtual environment.By integrating a querycentric trajectory prediction mechanism with Monte Carlo Tree Search,the proposed approach orchestrates intelligent model exploration.It iteratively refines the ego vehicle’s actions by simulating future scenarios and adapting to the dynamic behaviors of other agents,thereby tightly coupling data-driven predictions with physics-based planning constraints.Comprehensive evaluations on the Argoverse 1 and Argoverse 2 dataset in Metadrive simulator demonstrate the efficacy of this simulation-based approach.The framework successfully captures complex interaction dynamics that static models overlook.The results indicate that the proposed method generates significantly safer,more rational,and human-like trajectories compared to existing baselines,validating the system’s high-fidelity predictive capabilities.The proposed framework illustrates the transformative potential of advanced virtual simulation technologies in autonomous mobility.By enabling the continuous integration of predictive data into the planning loop,this study provides a powerful foundation for interpretable and reliable decision-making in virtual engineering systems.It highlights how coupling generative simulation with interactive planning can resolve critical safety challenges in the lifecycle of intelligent autonomous systems.
摘要Aiming at the problems of lagging curriculum,weak practice,and single evaluation in the cultivation of HarmonyOS Development talents,this study constructs a“teacher-machine-student”ternary interactive teaching model based on the Congyou platform.Through the building block curriculum system,the HarmonyOS technology stack is decoupled into dynamic capability units,and a multi-disciplinary cross-case library is jointly built with Huawei,which significantly improves the synchronization of teaching content and industrial technology.This paper innovatively designs an AI collaborative teaching system,which employs knowledge graphs to plan learning paths,utilizes virtual equipment clusters to simulate development environments,and establishes a“diagnosis-feedback-enhancement”closed loop through AI-based review,thereby effectively improving students’development efficiency and code reuse rate.A three-dimensional evaluation model integrating task outcomes,process performance,and innovation is constructed,incorporating indicators such as code standardization and an innovation index to strengthen the cultivation of engineering thinking and innovative ability.Furthermore,a data-driven support platform is built to generate student competency profiles,open up the“credit-competency-certification”pathway,promote the transformation of course achievements into contributions to the Huawei ecosystem,and significantly shorten the job adaptation cycle for graduates.The research results provide a replicable paradigm for the cultivation of domestic operating system talents.
摘要Reliable traffic flow prediction is crucial for mitigating urban congestion.This paper proposes Attentionbased spatiotemporal Interactive Dynamic Graph Convolutional Network(AIDGCN),a novel architecture integrating Interactive Dynamic Graph Convolution Network(IDGCN)with Temporal Multi-Head Trend-Aware Attention.Its core innovation lies in IDGCN,which uniquely splits sequences into symmetric intervals for interactive feature sharing via dynamic graphs,and a novel attention mechanism incorporating convolutional operations to capture essential local traffic trends—addressing a critical gap in standard attention for continuous data.For 15-and 60-min forecasting on METR-LA,AIDGCN achieves MAEs of 0.75%and 0.39%,and RMSEs of 1.32%and 0.14%,respectively.In the 60-min long-term forecasting of the PEMS-BAY dataset,the AIDGCN out-performs the MRA-BGCN method by 6.28%,4.93%,and 7.17%in terms of MAE,RMSE,and MAPE,respectively.Experimental results demonstrate the superiority of our pro-posed model over state-of-the-art methods.
基金supported in part by the National Science Fund for Distinguished Young Scholars(61725205)the National Natural Science Foundation of China(Grant Nos.61960206008,61772428,61972319,and61902320).
摘要At nomaly detectors are used to distinguish differences between normal and abnormal data,which are usually implemented by evaluating and ranking the anomaly scores of each instance.A static unsupervised streaming anomaly detector is difficult to dynamically adjust anomaly score calculation.In real scenarios,anomaly detection often needs to be regulated by human feedback,which benefits adjusting anomaly detectors.In this paper,we propose a human-machine interactive streaming anomaly detection method,named ISPForest,which can be adaptively updated online under the guidance of human feedback.In particular,the feedback will be used to adjust the anomaly score calculation and structure of the detector,ideally attaining more accurate anomaly scores in the future.Our main contribution is to improve the tree-based streaming anomaly detection model that can be updated online from perspectives of anomaly score calculation and model structure.Our approach is instantiated for the powerful class of tree-based streaming anomaly detectors,and we conduct experiments on a range of benchmark datasets.The results demonstrate that the utility of incorporating feedback can improve the performance of anomaly detectors with a few human efforts.
基金Supported by the‘Automotive Glazing Application in Intelligent Cockpit Human-Machine Interface’project(SKHX2021049)a collaboration between the Saint-Go Bain Research and the Beijing Normal University。
摘要Background With an increasing number of vehicles becoming autonomous,intelligent,and connected,paying attention to the future usage of car human-machine interface with these vehicles should become more relevant.Several studies have addressed car HMI but were less attentive to designing and implementing interactive glazing for every day(autonomous)driving contexts.Methods Reflecting on the literature,we describe an engineering psychology practice and the design of six novel future user scenarios,which envision the application of a specific set of augmented reality(AR)support user interactions.Additionally,we conduct evaluations on specific scenarios and experiential prototypes,which reveal that these AR scenarios aid the target user groups in experiencing a new type of interaction.The overall evaluation is positive with valuable assessment results and suggestions.Conclusions This study can interest applied psychology educators who aspire to teach how AR can be operationalized in a human-centered design process to students with minimal pre-existing expertise or minimal scientific knowledge in engineering psychology.
基金funded by National College Students’Innovation and Entrepreneurship Training Program(2025)“Bilingual Picture Books of Lyuliang:A Study on the Creation of Parent-Child Reading Picture Books Integrating the‘Three Cultures’”(Grant No.202510812006).
摘要Research on original children’s picture books that are already existing has not yet been completely explored formally. When it comes to the locally produced picture books, they do not match the young children’s cognitive level, and also the interaction is not deep enough. Also there are still few researches related to the ones based on regional culture pictures book. The authors choose parents with kids under 12 from Shanxi Province to investigate the present situation of integrating interactive picture books with local culture in Shanxi. This study explores different aspects such as children’s reading behavior, mode of interaction preference, and the preference for picture book content and theme, so as to discover the true need and creativity direction of children’s picture book in Shanxi. It can be seen from the results that children prefer interactive forms that involve doing things themselves as well as stories which are interesting and full of make believe. From those, it is hoped that this paper could give some practical advice and directions for the creation of homegrown Chinese children’s picture books (Zhou, 2025).
摘要Virtual reality scenes oriented towards immersive interaction have strict requirements for real-time rendering,such as high frame rate,low latency,and visual consistency.Traditional rendering methods are difficult to ensure both real-time performance and immersive experience under limited computing resources.This article systematically explores the key technologies and implementation paths of intelligent rendering methods:firstly,it analyzes the rendering pressure bottleneck,multi view continuity,and visual dual constraints caused by immersive interaction;Furthermore,an intelligent rendering mechanism based on gaze point prediction,scene semantic modeling,and closed-loop resource allocation will be constructed;On this basis,adaptive strategies such as behavior driven detail level adjustment,dynamic and static differentiation processing,spatiotemporal consistency,and load coordination are proposed;Finally,the evaluation indicators,stability analysis,and scalability verification of real-time performance and immersion are discussed.This article provides a system framework for the theoretical construction and engineering implementation of intelligent rendering methods.
摘要Objective: To investigate the nursing care outcomes for patients undergoing blood purification and analyze the impact of the Cox Health Behavior Interactive Nursing Model. Methods: The study was conducted at Yangzhong People's Hospital from January 2023 to December 2024. A total of 90 eligible blood purification patients were randomly selected and divided into two groups using a random number table: the control group (n=45) received conventional nursing care, while the study group (n=45) received the Cox Health Behavior Interactive Nursing Model in addition to conventional care. Outcomes were compared. Results: Post-intervention, (1) SAS and SDS scores: study group <control group (P<0.05); (2) Self-management ability scores: study group> control group (P<0.05); (3) Complication rates: total incidence in the study group <control group (P<0.05); (4) PSQI total score and RPFS scores: study group <control group (P<0.05); (5) Quality of life: study group> control group (P<0.05); (6) Nursing satisfaction: study group> control group (P<0.05). Conclusion: Compared with conventional nursing care, the Cox Health Behavior Interactive Nursing Model demonstrated superior overall efficacy, effectively reducing negative emotions, enhancing self-management abilities, minimizing complications, alleviating fatigue, improving sleep and quality of life, and increasing patient satisfaction.
基金the Talent Fund of Beijing Jiaotong University(Grant No.2024XKRC055).
摘要In recent years,railway construction in China has developed vigorously.With continuous improvements in the highspeed railway network,the focus is gradually shifting from large-scale construction to large-scale operations.However,several challenges have emerged within the high-speed railway dispatching and command system,including the heavy workload faced by dispatchers,the difficulty of quantifying subjective expertise,and the need for effective training of professionals.Amid the growing application of artificial intelligence technologies in railway systems,this study leverages Large Language Model(LLM)technology.LLMs bring enhanced intelligence,predictive capabilities,robust memory,and adaptability to diverse real-world scenarios.This study proposes a human-computer interactive intelligent scheduling auxiliary training system built on LLM technology.The system offers capabilities including natural dialogue,knowledge reasoning,and human feedback learning.With broad applicability,the system is suitable for vocational education,guided inquiry,knowledge-based Q&A,and other training scenarios.Validation results demonstrate its effectiveness in auxiliary training,providing substantial support for educators,students,and dispatching personnel in colleges and professional settings.