This article utilizes Katherine Mansfield’s short story The Garden Party as the research object to explore the narrative generation conditions of ethical experience in the text. Through a close analysis of the novel...This article utilizes Katherine Mansfield’s short story The Garden Party as the research object to explore the narrative generation conditions of ethical experience in the text. Through a close analysis of the novel’s narrative structure and key scenes, the article argues that ethical discomfort does not evolve into enduring moral judgments within the text;rather, it is continually managed and deferred through the interplay of aesthetic order, familial discourse, and the distribution of social roles. The novel eschews a linear trajectory of ethical awakening, instead crafting a narrative mechanism that keeps ethical experience palpable yet inarticulable. The female subject is given the role of sensing ethical incongruity, but lacks the narrative position from which to articulate it as judgment. Consequently, ethics remains confined to the level of personalization and unimplementability. Far from a narrative of moral growth or awakening, The Garden Party exposes why ethical judgment has become structurally unrealizable in modern narratives.展开更多
The pseudo-two-dimensional(P2D)model plays an important role in exploring physicochemical mechanisms,predicting the state of health,and improving the fast charge capability for Li-ion batteries(LIBs).However,the fast ...The pseudo-two-dimensional(P2D)model plays an important role in exploring physicochemical mechanisms,predicting the state of health,and improving the fast charge capability for Li-ion batteries(LIBs).However,the fast charge leads to the lithium concentration gradient in the solid and electrolyte phases and the non-uniform electrochemical reaction at the solid/electrolyte interface.In order to decouple charge transfer reactions in LIBs under dynamic conditions,understanding the spatio-temporal resolution of the P2D model is urgently required.Till now,the study of this aspect is still insufficient.This work studies the spatio-temporal resolution for dynamic/static electrochemical impedance spectroscopy(DEIS/SEIS)on multiple scales.In detail,DEIS and SEIS with spatio-temporal resolutions are used to decouple charge transfer reactions in LIBs based on the numerical solution of the P2D model in the frequency domain.The calculated results indicate that decoupling solid diffusion requires a high spatial resolution along the r-direction in particles,decoupling electrolyte diffusion and interfacial transfer reaction requires a high spatial resolution along the x-direction,and decoupling charge transfer reactions in LIBs at an extremely low state of charge(SOC)requires an extremely high temporal resolution along the t-direction.Finally,the optimal range of spatio-temporal resolutions for DEIS/SEIS is derived,and the method to decouple charge transfer reactions with spatio-temporal resolutions is developed.展开更多
Background:In mental health,recovery is emphasized,and qualitative analyses of service users’narratives have accumulated;however,while qualitative approaches excel at capturing rich context and generating new concept...Background:In mental health,recovery is emphasized,and qualitative analyses of service users’narratives have accumulated;however,while qualitative approaches excel at capturing rich context and generating new concepts,they are limited in generalizability and feasible data volume.This study aimed to quantify the subjective life history narratives of users of psychiatric home-visit nursing using natural language processing(NLP)and to clarify the relationships between linguistic features and recovery-related indicators.Methods:We conducted audio-recorded and transcribed semi-structured interviews on daily life verbatim and collected self-report questionnaires(Recovery Assessment Scale[RAS])and clinician ratings(Global Assessment of Functioning[GAF])from Japanese users of psychiatric home-visit nursing.Using the artificial intelligence-based topic-modeling method BERTopic,we extracted topics from the interview texts and calculated each participant’s topic proportions,and then examined associations between topic proportions and recovery-related indicators using Pearson correlation analyses.Results:“School”showed a significant positive correlation with RAS(r=0.39,p=0.05),whereas“Family”showed a significant negative correlation(r=–0.46,p=0.02).GAF was positively correlated with word count(r=0.44,p=0.02)and“Hospital”(r=0.42,p=0.03),and negatively correlated with“Backchannels”(aizuchi)(r=–0.41,p=0.03).Conclusion:The present results suggest that the quantity,quality,and content of narratives can serve as useful indicators of mental health and recovery,and that objective NLP-based analysis of service users’narratives can complement traditional self-report scales and clinician ratings to inform the design of recovery-oriented care in psychiatric home-visit nursing.展开更多
This narrative review examines recent advances in salivary biomarkers for oral squamous cell carcinoma(OSCC),a major subtype of oral cancer with persistently low five-year survival rates due to delayed diagnosis.Saliv...This narrative review examines recent advances in salivary biomarkers for oral squamous cell carcinoma(OSCC),a major subtype of oral cancer with persistently low five-year survival rates due to delayed diagnosis.Saliva has emerged as a noninvasive diagnostic medium capable of reflecting both local tumor activity and systemic physiological changes.Various salivary biomarkers,including microRNAs,cytokines,proteins,metabolites,and exosomes,have been linked to oncogenic signaling pathways involved in tumor progression,immune modulation,and therapeutic resistance.Advances in quantitative polymerase chain reaction,mass spectrometry,and next-generation sequencing have enabled comprehensive biomarker profiling,while point-of-care detection systems and saliva-based omics platforms are accelerating clinical translation.Remaining challenges include variability in salivary composition,lack of standardized collection protocols,and insufficient validation across large patient cohorts.This review highlights the mechanistic relevance,diagnostic potential,and translational challenges of salivary biomarkers in OSCC.展开更多
This study proposes a novel forecasting framework that simultaneously captures the strong periodicity and irregular meteorological fluctuations inherent in solar radiation time series.Existing approaches typically def...This study proposes a novel forecasting framework that simultaneously captures the strong periodicity and irregular meteorological fluctuations inherent in solar radiation time series.Existing approaches typically define inter-regional correlations using either simple correlation coefficients or distance-based measures when applying spatio-temporal graph neural networks(STGNNs).However,such definitions are prone to generating spurious correlations due to the dominance of periodic structures.To address this limitation,we adopt the Elastic-Band Transform(EBT)to decompose solar radiation into periodic and amplitude-modulated components,which are then modeled independently with separate graph neural networks.The periodic component,characterized by strong nationwide correlations,is learned with a relatively simple architecture,whereas the amplitude-modulated component is modeled with more complex STGNNs that capture climatological similarities between regions.The predictions from the two components are subsequently recombined to yield final forecasts that integrate both periodic patterns and aperiodic variability.The proposed framework is validated with multiple STGNN architectures,and experimental results demonstrate improved predictive accuracy and interpretability compared to conventional methods.展开更多
Due to water conflicts and allocation in the Lancang-Mekong River Basin(LMRB),the spatio-temporal differentiation of total water resources and the natural-human influence need to be clarified.This work investigated LM...Due to water conflicts and allocation in the Lancang-Mekong River Basin(LMRB),the spatio-temporal differentiation of total water resources and the natural-human influence need to be clarified.This work investigated LMRB's terrestrial water storage anomaly(TWSA)and its spatio-temporal dynamics during 2002–2020.Considering the effects of natural factors and human activities,the respective contributions of climate variability and human activities to terrestrial water storage change(TWSC)were separated.Results showed that:(1)LMRB's TWSA decreased by 0.3158 cm/a.(2)TWSA showed a gradual increase in distribution from southwest of MRB to middle LMRB and from northeast of LRB to middle LMRB.TWSA positively changed in Myanmar while slightly changed in Laos and China.It negatively changed in Vietnam,Thailand and Cambodia.(3)TWSA components decreased in a descending order of soil moisture,groundwater and precipitation.(4)Natural factors had a substantial and spatial differentiated influence on TWSA over the LMRB.(5)Climate variability contributed 79%of TWSC in the LMRB while human activities contributed 21%with an increasing impact after 2008.The TWSC of upstream basin countries was found to be controlled by climate variability while Vietnam and Cambodia's TWSC has been controlled by human activities since 2012.展开更多
The ability to accurately predict urban traffic flows is crucial for optimising city operations.Consequently,various methods for forecasting urban traffic have been developed,focusing on analysing historical data to u...The ability to accurately predict urban traffic flows is crucial for optimising city operations.Consequently,various methods for forecasting urban traffic have been developed,focusing on analysing historical data to understand complex mobility patterns.Deep learning techniques,such as graph neural networks(GNNs),are popular for their ability to capture spatio-temporal dependencies.However,these models often become overly complex due to the large number of hyper-parameters involved.In this study,we introduce Dynamic Multi-Graph Spatial-Temporal Graph Neural Ordinary Differential Equation Networks(DMST-GNODE),a framework based on ordinary differential equations(ODEs)that autonomously discovers effective spatial-temporal graph neural network(STGNN)architectures for traffic prediction tasks.The comparative analysis of DMST-GNODE and baseline models indicates that DMST-GNODE model demonstrates superior performance across multiple datasets,consistently achieving the lowest Root Mean Square Error(RMSE)and Mean Absolute Error(MAE)values,alongside the highest accuracy.On the BKK(Bangkok)dataset,it outperformed other models with an RMSE of 3.3165 and an accuracy of 0.9367 for a 20-min interval,maintaining this trend across 40 and 60 min.Similarly,on the PeMS08 dataset,DMST-GNODE achieved the best performance with an RMSE of 19.4863 and an accuracy of 0.9377 at 20 min,demonstrating its effectiveness over longer periods.The Los_Loop dataset results further emphasise this model’s advantage,with an RMSE of 3.3422 and an accuracy of 0.7643 at 20 min,consistently maintaining superiority across all time intervals.These numerical highlights indicate that DMST-GNODE not only outperforms baseline models but also achieves higher accuracy and lower errors across different time intervals and datasets.展开更多
Convergent journalism constitutes a systematic investigation into emergent journalistic forms,conceptual frameworks,and practices emerging within media convergence context,characterized by its inherent attributes of c...Convergent journalism constitutes a systematic investigation into emergent journalistic forms,conceptual frameworks,and practices emerging within media convergence context,characterized by its inherent attributes of convergence,datacentricity,and interactivity.Grounded in the theoretical discourse of digital narratology,this monograph crystallizes its analytical focus on the triadic conceptual constellation of"convergence""mediaticity"and"narrativity",By positioning""convergence"as the central problematique,it systematically constructs an epistemological framework for convergent journalistic narrative through three dimensions:narrative theory,narrative language,and narrative praxis,thereby elucidates the ontological foundations and operational logics intrinsic to contemporary journalism studies.展开更多
Jātaka story paintings are common narrative subjects in Dunhuang murals.Based on corresponding scriptures,they present all kinds of good deeds that Sakyamuni sacrificed his life to save sentient beings in his previou...Jātaka story paintings are common narrative subjects in Dunhuang murals.Based on corresponding scriptures,they present all kinds of good deeds that Sakyamuni sacrificed his life to save sentient beings in his previous life.Dunhuang Jātaka story paintings are highly consistent with the scriptures in content,but their intuitiveness and expressiveness are more prominent.By comparing the narrative relationship between Jātaka story paintings in the Mogao Grottoes of Dunhuang and their corresponding scriptures,this study finds that the two have unity in reproducing artistic images and restoring key plots of classic Buddhist scripture stories,but there are great differences in the narrative effect.Dunhuang Jātaka story paintings have three prominent features in narrative,including visualization of key elements,concretization of expressions and movements,and contextualization of cause and effect.This study aims to reveal the intertextual narrative relationship between Dunhuang Jātaka story paintings and their corresponding scriptures.展开更多
Objective To investigate the spatiotemporal patterns and socioeconomic factors influencing the incidence of tuberculosis(TB)in the Guangdong Province between 2010 and 2019.Method Spatial and temporal variations in TB ...Objective To investigate the spatiotemporal patterns and socioeconomic factors influencing the incidence of tuberculosis(TB)in the Guangdong Province between 2010 and 2019.Method Spatial and temporal variations in TB incidence were mapped using heat maps and hierarchical clustering.Socioenvironmental influencing factors were evaluated using a Bayesian spatiotemporal conditional autoregressive(ST-CAR)model.Results Annual incidence of TB in Guangdong decreased from 91.85/100,000 in 2010 to 53.06/100,000in 2019.Spatial hotspots were found in northeastern Guangdong,particularly in Heyuan,Shanwei,and Shantou,while Shenzhen,Dongguan,and Foshan had the lowest rates in the Pearl River Delta.The STCAR model showed that the TB risk was lower with higher per capita Gross Domestic Product(GDP)[Relative Risk(RR),0.91;95%Confidence Interval(CI):0.86–0.98],more the ratio of licensed physicians and physician(RR,0.94;95%CI:0.90-0.98),and higher per capita public expenditure(RR,0.94;95%CI:0.90–0.97),with a marginal effect of population density(RR,0.86;95%CI:0.86–1.00).Conclusion The incidence of TB in Guangdong varies spatially and temporally.Areas with poor economic conditions and insufficient healthcare resources are at an increased risk of TB infection.Strategies focusing on equitable health resource distribution and economic development are the key to TB control.展开更多
Narrative nursing has emerged as a vital approach in patient-centered care,and emphasize the importance of understanding patients’emotional experiences in addition to their physical health needs.In this article,we co...Narrative nursing has emerged as a vital approach in patient-centered care,and emphasize the importance of understanding patients’emotional experiences in addition to their physical health needs.In this article,we comment on the article by Zhou et al.Diseases such as acute pancreatitis can cause significant suffering and severely impact patients’quality of life.During treatment,routine nursing procedures such as gastric tube placement,oxygen therapy,monitoring,and nasogastric feeding often lack effective communication,which can adversely affect patients’recovery.This article highlights how narrative nursing can provide deeper insights into patients’emotional experiences,ultimately resulting in improved care outcomes.We also emphasize the role of narrative nursing in understanding and addressing these emotional needs to achieve personalized care,which can strengthen the therapeutic relationship between healthcare providers and patients.By recognizing the critical role of emotional well-being in patient care,we can develop comprehensive strategies that facilitate recovery and enhance overall quality of life.展开更多
This study examines the effects of rapid land use changes in India,with a specific focus on Sonipat District in Haryana—a region undergoing significant urban expansion.Over the past two decades,rural landscapes in So...This study examines the effects of rapid land use changes in India,with a specific focus on Sonipat District in Haryana—a region undergoing significant urban expansion.Over the past two decades,rural landscapes in Sonipat have undergone notable transformation,as open spaces and agricultural lands are increasingly converted into residential colonies,commercial hubs,and industrial zones.While such changes reflect economic development and urban growth,they also raise critical concerns about sustainability,especially in terms of food security,groundwater depletion,and environmental degradation.The study examines land use changes between 2000 and 2024 using remote sensing techniques and spatial analysis.It further incorporates secondary data and insights from community-level interactions to assess the socio-economic and ecological impacts of this transformation.The findings indicate rising land fragmentation,loss of agricultural livelihoods,pressure on civic infrastructure,and increasing pollution—factors that threaten long-term regional sustainability.The study underscores the urgent need to reconcile urban development with environmental and social sustainability.By offering a detailed case study of Sonipat,this research contributes to the broader discourse on India’s urbanisation pathways.It aims to provide policymakers,planners,and researchers with evidence-based recommendations to manage land transitions more responsibly,promoting urban growth models that ensure ecological integrity,equitable development,and long-term resilience.展开更多
The theory of spatial narrative enhances the connotation of architectural design and broadens the interaction between architecture and its users.Drawing upon a literature review of relevant keywords related to“archit...The theory of spatial narrative enhances the connotation of architectural design and broadens the interaction between architecture and its users.Drawing upon a literature review of relevant keywords related to“architectural space narrative”from the China National Knowledge Infrastructure(CNKI)over the past two decades,alongside an analysis and content identification of high-frequency keywords,clustering,timelines,and other knowledge graphs generated by CiteSpace,this study summarizes the evolution path of spatial narrative theory.This approach offers diverse perspectives for examining emerging trends and key issues within spatial narrative research.展开更多
As Deepfake technology continues to evolve,the distinction between real and fake content becomes increasingly blurred.Most existing Deepfake video detectionmethods rely on single-frame facial image features,which limi...As Deepfake technology continues to evolve,the distinction between real and fake content becomes increasingly blurred.Most existing Deepfake video detectionmethods rely on single-frame facial image features,which limits their ability to capture temporal differences between frames.Current methods also exhibit limited generalization capabilities,struggling to detect content generated by unknown forgery algorithms.Moreover,the diversity and complexity of forgery techniques introduced by Artificial Intelligence Generated Content(AIGC)present significant challenges for traditional detection frameworks,whichmust balance high detection accuracy with robust performance.To address these challenges,we propose a novel Deepfake detection framework that combines a two-stream convolutional network with a Vision Transformer(ViT)module to enhance spatio-temporal feature representation.The ViT model extracts spatial features from the forged video,while the 3D convolutional network captures temporal features.The 3D convolution enables cross-frame feature extraction,allowing the model to detect subtle facial changes between frames.The confidence scores from both the ViT and 3D convolution submodels are fused at the decision layer,enabling themodel to effectively handle unknown forgery techniques.Focusing on Deepfake videos and GAN-generated images,the proposed approach is evaluated on two widely used public face forgery datasets.Compared to existing state-of-theartmethods,it achieves higher detection accuracy and better generalization performance,offering a robust solution for deepfake detection in real-world scenarios.展开更多
BACKGROUND Narrative nursing uses narrative methods to establish an interaction between nursing staff and patients,in which the experience of the patient’s illness is understood and comprehended.By listening,the pati...BACKGROUND Narrative nursing uses narrative methods to establish an interaction between nursing staff and patients,in which the experience of the patient’s illness is understood and comprehended.By listening,the patient’s understanding,comprehension,and acceptance of their own disease symptoms,quality of life,and living conditions are understood,thereby providing a basis for formulating corresponding nursing plans for the patient,further promoting the psychological and physical rehabilitation of the patient.AIM To explore the impact of the new narrative nursing model on postoperative recovery,psychological status,and satisfaction of patients.METHODS A total of 108 patients with resectable gastric cancer who were treated from January 2024 to December 2024 were selected as the study subjects.They were divided into a routine nursing group and a narrative nursing group using a random number table method.Postoperative recovery indicators were compared between the two groups,and questionnaires and position and postoperative nausea and vomiting were conducted on the day of discharge.RESULTS There were statistically significant differences in visual analogue scale pain scores at 12-96 hours postoperatively,the time of first ambulation postoperatively,and the length of postoperative hospital stay between the two groups(P<0.05).There were statistically significant differences in postoperative self-rating anxiety scale,self-rating depression scale,and satisfaction scores between the two groups(P<0.05).Further analysis using a binary logistic regression model found that the new narrative nursing model adopted postoperatively could improve patients’satisfaction with the work of nursing staff during their hospitalization.CONCLUSION The new narrative nursing model not only eliminated the negative emotions of patients,but also further promoted their postoperative recovery,and gained patients’trust and satisfaction with the nursing staff.展开更多
Sandfly fever is a viral infectious disease transmitted by sand flies that is widely prevalent in tropical and subtropical regions.Previous studies on its infection mechanism,immune response and diagnosis and treatmen...Sandfly fever is a viral infectious disease transmitted by sand flies that is widely prevalent in tropical and subtropical regions.Previous studies on its infection mechanism,immune response and diagnosis and treatment methods were lack of systematic.This study applied spatio-temporal omics technology to comprehensively explain the dynamic changes of immunity in the incubation period,exacerbation period,peak period and recovery period of Sandfl y fever,and integrated with diff erent coping strategies.To provide new research ideas for its overall research.展开更多
Agriculture holds a pivotal position in the economic fabric of every nation,yet concerns about agricultural carbon emission intensity(ACI)have become a major hurdle to achieving global economic sustainability.Focusing...Agriculture holds a pivotal position in the economic fabric of every nation,yet concerns about agricultural carbon emission intensity(ACI)have become a major hurdle to achieving global economic sustainability.Focusing on 31 provincial-level regions in China,this study uses the Exploratory Spatio-temporal Data Analysis(ESTDA)and Panel Quantile Regression(PQR)model to analyze the spatio-temporal interaction characteristics and influencing factors of ACI in China from 2004 to 2023.The findings are as follows:(1)ACI showed an overall downward trend,and the spatial distribution pattern was characterized by“high in the western region and low along the southeastern coast”.Although the overall disparity tended to converge,some high-carbon-intensity regions exhibited extreme trends.ACI displayed clear spatial directionality,with the spatial center shifting steadily toward the northeast.(2)Regions in the northwest,northeast,and central-south parts exhibited strong local spatial structural dynamics,and the local spatial dependence of ACI in each region showed a nonlinear trend.Generally speaking,the spatial association pattern demonstrated a certain degree of inertia in spatial transfer,reflecting strong path dependence or spatial lock-in characteristics.(3)Optimization of industrial structure and improvement in agricultural mechanization will increase ACI,while economic development can effectively reduce it.The impact of urbanization on ACI exhibits a nonlinear pattern.The coordinated development of economic growth and urbanization significantly reduces ACI,with a stronger emission reduction observed in regions with low ACI.The optimization of industrial structure,when combined with urbanization and environmental regulation,contributes to significant emission reductions particularly in high-ACI areas.Similarly,the synergy between agricultural mechanization and urbanization effectively lowers emissions in low-ACI regions,though this effect diminishes in areas with higher ACI.展开更多
Sloping farmland,particularly in mountainous and hilly areas,constitutes a significant component of regional farmland resources.An investigation into the spatio-temporal pattern of sloping farmland and its influencing...Sloping farmland,particularly in mountainous and hilly areas,constitutes a significant component of regional farmland resources.An investigation into the spatio-temporal pattern of sloping farmland and its influencing factors in China is imperative for the efficient utilization of farmland and the optimization of land space.We used land use transfer matrix,geographically weighted regression model and geographical detector to conduct this study.Results showed that sloping farmland in China firstly decreased and then increased from 2000 to 2020.The proportion of sloping farmland decreased radially outward from Sichuan basin to the surrounding areas.Change rates of sloping farmland with different slopes varied and the slope with 6°-15°underwent the fastest changes.The influencing factors of farmland at various slope degrees were different.For sloping farmland below 15°,land use intensity and elevation had the greatest contribution.For sloping farmland between 15°and 25°,elevation,land use intensity,and population density were the main influencing factors.Sloping farmland above 25°was mostly affected by natural factors.This study can provide scientific basis for rational development and protection of sloping farmland.展开更多
At present,strengthening China’s international communication capabilities and enhancing China’s global influence have become important tasks.This study selects 60 pieces of soft news from China Daily from March 2023...At present,strengthening China’s international communication capabilities and enhancing China’s global influence have become important tasks.This study selects 60 pieces of soft news from China Daily from March 2023 to February 2024 as research objects and explores China’s national image from the source texts.Then,based on Mona Baker’s narrative theory,it analyzes the translation strategies to reconstruct the image of China,further revealing the regular characteristics of their application.Through translation,the reconstructed national image of China becomes more positive and more acceptable to foreign readers,effectively promoting the dissemination of Chinese stories in the international community.It is significant for promoting international understanding and cooperation,as well as effectively utilizing translation as a tool to enhance China’s national image.展开更多
Current spatio-temporal action detection methods lack sufficient capabilities in extracting and comprehending spatio-temporal information. This paper introduces an end-to-end Adaptive Cross-Scale Fusion Encoder-Decode...Current spatio-temporal action detection methods lack sufficient capabilities in extracting and comprehending spatio-temporal information. This paper introduces an end-to-end Adaptive Cross-Scale Fusion Encoder-Decoder (ACSF-ED) network to predict the action and locate the object efficiently. In the Adaptive Cross-Scale Fusion Spatio-Temporal Encoder (ACSF ST-Encoder), the Asymptotic Cross-scale Feature-fusion Module (ACCFM) is designed to address the issue of information degradation caused by the propagation of high-level semantic information, thereby extracting high-quality multi-scale features to provide superior features for subsequent spatio-temporal information modeling. Within the Shared-Head Decoder structure, a shared classification and regression detection head is constructed. A multi-constraint loss function composed of one-to-one, one-to-many, and contrastive denoising losses is designed to address the problem of insufficient constraint force in predicting results with traditional methods. This loss function enhances the accuracy of model classification predictions and improves the proximity of regression position predictions to ground truth objects. The proposed method model is evaluated on the popular dataset UCF101-24 and JHMDB-21. Experimental results demonstrate that the proposed method achieves an accuracy of 81.52% on the Frame-mAP metric, surpassing current existing methods.展开更多
文摘This article utilizes Katherine Mansfield’s short story The Garden Party as the research object to explore the narrative generation conditions of ethical experience in the text. Through a close analysis of the novel’s narrative structure and key scenes, the article argues that ethical discomfort does not evolve into enduring moral judgments within the text;rather, it is continually managed and deferred through the interplay of aesthetic order, familial discourse, and the distribution of social roles. The novel eschews a linear trajectory of ethical awakening, instead crafting a narrative mechanism that keeps ethical experience palpable yet inarticulable. The female subject is given the role of sensing ethical incongruity, but lacks the narrative position from which to articulate it as judgment. Consequently, ethics remains confined to the level of personalization and unimplementability. Far from a narrative of moral growth or awakening, The Garden Party exposes why ethical judgment has become structurally unrealizable in modern narratives.
基金supported by the National Natural Science Foundation of China(Nos.22479092 and 22078190)。
文摘The pseudo-two-dimensional(P2D)model plays an important role in exploring physicochemical mechanisms,predicting the state of health,and improving the fast charge capability for Li-ion batteries(LIBs).However,the fast charge leads to the lithium concentration gradient in the solid and electrolyte phases and the non-uniform electrochemical reaction at the solid/electrolyte interface.In order to decouple charge transfer reactions in LIBs under dynamic conditions,understanding the spatio-temporal resolution of the P2D model is urgently required.Till now,the study of this aspect is still insufficient.This work studies the spatio-temporal resolution for dynamic/static electrochemical impedance spectroscopy(DEIS/SEIS)on multiple scales.In detail,DEIS and SEIS with spatio-temporal resolutions are used to decouple charge transfer reactions in LIBs based on the numerical solution of the P2D model in the frequency domain.The calculated results indicate that decoupling solid diffusion requires a high spatial resolution along the r-direction in particles,decoupling electrolyte diffusion and interfacial transfer reaction requires a high spatial resolution along the x-direction,and decoupling charge transfer reactions in LIBs at an extremely low state of charge(SOC)requires an extremely high temporal resolution along the t-direction.Finally,the optimal range of spatio-temporal resolutions for DEIS/SEIS is derived,and the method to decouple charge transfer reactions with spatio-temporal resolutions is developed.
文摘Background:In mental health,recovery is emphasized,and qualitative analyses of service users’narratives have accumulated;however,while qualitative approaches excel at capturing rich context and generating new concepts,they are limited in generalizability and feasible data volume.This study aimed to quantify the subjective life history narratives of users of psychiatric home-visit nursing using natural language processing(NLP)and to clarify the relationships between linguistic features and recovery-related indicators.Methods:We conducted audio-recorded and transcribed semi-structured interviews on daily life verbatim and collected self-report questionnaires(Recovery Assessment Scale[RAS])and clinician ratings(Global Assessment of Functioning[GAF])from Japanese users of psychiatric home-visit nursing.Using the artificial intelligence-based topic-modeling method BERTopic,we extracted topics from the interview texts and calculated each participant’s topic proportions,and then examined associations between topic proportions and recovery-related indicators using Pearson correlation analyses.Results:“School”showed a significant positive correlation with RAS(r=0.39,p=0.05),whereas“Family”showed a significant negative correlation(r=–0.46,p=0.02).GAF was positively correlated with word count(r=0.44,p=0.02)and“Hospital”(r=0.42,p=0.03),and negatively correlated with“Backchannels”(aizuchi)(r=–0.41,p=0.03).Conclusion:The present results suggest that the quantity,quality,and content of narratives can serve as useful indicators of mental health and recovery,and that objective NLP-based analysis of service users’narratives can complement traditional self-report scales and clinician ratings to inform the design of recovery-oriented care in psychiatric home-visit nursing.
基金supported by the College of Oral Medicine,Taipei Medical University,Taipei,Taiwan(Grant No.TMUCOM202502)supported by Taipei Medical University Hospital,Taipei,Taiwan(Grant No.114TMUH-NE-05).
文摘This narrative review examines recent advances in salivary biomarkers for oral squamous cell carcinoma(OSCC),a major subtype of oral cancer with persistently low five-year survival rates due to delayed diagnosis.Saliva has emerged as a noninvasive diagnostic medium capable of reflecting both local tumor activity and systemic physiological changes.Various salivary biomarkers,including microRNAs,cytokines,proteins,metabolites,and exosomes,have been linked to oncogenic signaling pathways involved in tumor progression,immune modulation,and therapeutic resistance.Advances in quantitative polymerase chain reaction,mass spectrometry,and next-generation sequencing have enabled comprehensive biomarker profiling,while point-of-care detection systems and saliva-based omics platforms are accelerating clinical translation.Remaining challenges include variability in salivary composition,lack of standardized collection protocols,and insufficient validation across large patient cohorts.This review highlights the mechanistic relevance,diagnostic potential,and translational challenges of salivary biomarkers in OSCC.
基金supported by Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(RS-2023-00249743).
文摘This study proposes a novel forecasting framework that simultaneously captures the strong periodicity and irregular meteorological fluctuations inherent in solar radiation time series.Existing approaches typically define inter-regional correlations using either simple correlation coefficients or distance-based measures when applying spatio-temporal graph neural networks(STGNNs).However,such definitions are prone to generating spurious correlations due to the dominance of periodic structures.To address this limitation,we adopt the Elastic-Band Transform(EBT)to decompose solar radiation into periodic and amplitude-modulated components,which are then modeled independently with separate graph neural networks.The periodic component,characterized by strong nationwide correlations,is learned with a relatively simple architecture,whereas the amplitude-modulated component is modeled with more complex STGNNs that capture climatological similarities between regions.The predictions from the two components are subsequently recombined to yield final forecasts that integrate both periodic patterns and aperiodic variability.The proposed framework is validated with multiple STGNN architectures,and experimental results demonstrate improved predictive accuracy and interpretability compared to conventional methods.
基金National Natural Science Foundation of China,No.42161006Yunnan Fundamental Research Projects No.202201AT070094,No.202301BF070001-004+1 种基金Special Project for High-level Talents of Yunnan Province for Young Top Talents,No.C6213001159European Research Council(ERC)Starting-Grant STORIES,No.101040939。
文摘Due to water conflicts and allocation in the Lancang-Mekong River Basin(LMRB),the spatio-temporal differentiation of total water resources and the natural-human influence need to be clarified.This work investigated LMRB's terrestrial water storage anomaly(TWSA)and its spatio-temporal dynamics during 2002–2020.Considering the effects of natural factors and human activities,the respective contributions of climate variability and human activities to terrestrial water storage change(TWSC)were separated.Results showed that:(1)LMRB's TWSA decreased by 0.3158 cm/a.(2)TWSA showed a gradual increase in distribution from southwest of MRB to middle LMRB and from northeast of LRB to middle LMRB.TWSA positively changed in Myanmar while slightly changed in Laos and China.It negatively changed in Vietnam,Thailand and Cambodia.(3)TWSA components decreased in a descending order of soil moisture,groundwater and precipitation.(4)Natural factors had a substantial and spatial differentiated influence on TWSA over the LMRB.(5)Climate variability contributed 79%of TWSC in the LMRB while human activities contributed 21%with an increasing impact after 2008.The TWSC of upstream basin countries was found to be controlled by climate variability while Vietnam and Cambodia's TWSC has been controlled by human activities since 2012.
文摘The ability to accurately predict urban traffic flows is crucial for optimising city operations.Consequently,various methods for forecasting urban traffic have been developed,focusing on analysing historical data to understand complex mobility patterns.Deep learning techniques,such as graph neural networks(GNNs),are popular for their ability to capture spatio-temporal dependencies.However,these models often become overly complex due to the large number of hyper-parameters involved.In this study,we introduce Dynamic Multi-Graph Spatial-Temporal Graph Neural Ordinary Differential Equation Networks(DMST-GNODE),a framework based on ordinary differential equations(ODEs)that autonomously discovers effective spatial-temporal graph neural network(STGNN)architectures for traffic prediction tasks.The comparative analysis of DMST-GNODE and baseline models indicates that DMST-GNODE model demonstrates superior performance across multiple datasets,consistently achieving the lowest Root Mean Square Error(RMSE)and Mean Absolute Error(MAE)values,alongside the highest accuracy.On the BKK(Bangkok)dataset,it outperformed other models with an RMSE of 3.3165 and an accuracy of 0.9367 for a 20-min interval,maintaining this trend across 40 and 60 min.Similarly,on the PeMS08 dataset,DMST-GNODE achieved the best performance with an RMSE of 19.4863 and an accuracy of 0.9377 at 20 min,demonstrating its effectiveness over longer periods.The Los_Loop dataset results further emphasise this model’s advantage,with an RMSE of 3.3422 and an accuracy of 0.7643 at 20 min,consistently maintaining superiority across all time intervals.These numerical highlights indicate that DMST-GNODE not only outperforms baseline models but also achieves higher accuracy and lower errors across different time intervals and datasets.
文摘Convergent journalism constitutes a systematic investigation into emergent journalistic forms,conceptual frameworks,and practices emerging within media convergence context,characterized by its inherent attributes of convergence,datacentricity,and interactivity.Grounded in the theoretical discourse of digital narratology,this monograph crystallizes its analytical focus on the triadic conceptual constellation of"convergence""mediaticity"and"narrativity",By positioning""convergence"as the central problematique,it systematically constructs an epistemological framework for convergent journalistic narrative through three dimensions:narrative theory,narrative language,and narrative praxis,thereby elucidates the ontological foundations and operational logics intrinsic to contemporary journalism studies.
文摘Jātaka story paintings are common narrative subjects in Dunhuang murals.Based on corresponding scriptures,they present all kinds of good deeds that Sakyamuni sacrificed his life to save sentient beings in his previous life.Dunhuang Jātaka story paintings are highly consistent with the scriptures in content,but their intuitiveness and expressiveness are more prominent.By comparing the narrative relationship between Jātaka story paintings in the Mogao Grottoes of Dunhuang and their corresponding scriptures,this study finds that the two have unity in reproducing artistic images and restoring key plots of classic Buddhist scripture stories,but there are great differences in the narrative effect.Dunhuang Jātaka story paintings have three prominent features in narrative,including visualization of key elements,concretization of expressions and movements,and contextualization of cause and effect.This study aims to reveal the intertextual narrative relationship between Dunhuang Jātaka story paintings and their corresponding scriptures.
基金supported by the Guangdong Provincial Clinical Research Center for Tuberculosis(No.2020B1111170014)。
文摘Objective To investigate the spatiotemporal patterns and socioeconomic factors influencing the incidence of tuberculosis(TB)in the Guangdong Province between 2010 and 2019.Method Spatial and temporal variations in TB incidence were mapped using heat maps and hierarchical clustering.Socioenvironmental influencing factors were evaluated using a Bayesian spatiotemporal conditional autoregressive(ST-CAR)model.Results Annual incidence of TB in Guangdong decreased from 91.85/100,000 in 2010 to 53.06/100,000in 2019.Spatial hotspots were found in northeastern Guangdong,particularly in Heyuan,Shanwei,and Shantou,while Shenzhen,Dongguan,and Foshan had the lowest rates in the Pearl River Delta.The STCAR model showed that the TB risk was lower with higher per capita Gross Domestic Product(GDP)[Relative Risk(RR),0.91;95%Confidence Interval(CI):0.86–0.98],more the ratio of licensed physicians and physician(RR,0.94;95%CI:0.90-0.98),and higher per capita public expenditure(RR,0.94;95%CI:0.90–0.97),with a marginal effect of population density(RR,0.86;95%CI:0.86–1.00).Conclusion The incidence of TB in Guangdong varies spatially and temporally.Areas with poor economic conditions and insufficient healthcare resources are at an increased risk of TB infection.Strategies focusing on equitable health resource distribution and economic development are the key to TB control.
基金Supported by National Natural Science Foundation of China,No.82100123。
文摘Narrative nursing has emerged as a vital approach in patient-centered care,and emphasize the importance of understanding patients’emotional experiences in addition to their physical health needs.In this article,we comment on the article by Zhou et al.Diseases such as acute pancreatitis can cause significant suffering and severely impact patients’quality of life.During treatment,routine nursing procedures such as gastric tube placement,oxygen therapy,monitoring,and nasogastric feeding often lack effective communication,which can adversely affect patients’recovery.This article highlights how narrative nursing can provide deeper insights into patients’emotional experiences,ultimately resulting in improved care outcomes.We also emphasize the role of narrative nursing in understanding and addressing these emotional needs to achieve personalized care,which can strengthen the therapeutic relationship between healthcare providers and patients.By recognizing the critical role of emotional well-being in patient care,we can develop comprehensive strategies that facilitate recovery and enhance overall quality of life.
文摘This study examines the effects of rapid land use changes in India,with a specific focus on Sonipat District in Haryana—a region undergoing significant urban expansion.Over the past two decades,rural landscapes in Sonipat have undergone notable transformation,as open spaces and agricultural lands are increasingly converted into residential colonies,commercial hubs,and industrial zones.While such changes reflect economic development and urban growth,they also raise critical concerns about sustainability,especially in terms of food security,groundwater depletion,and environmental degradation.The study examines land use changes between 2000 and 2024 using remote sensing techniques and spatial analysis.It further incorporates secondary data and insights from community-level interactions to assess the socio-economic and ecological impacts of this transformation.The findings indicate rising land fragmentation,loss of agricultural livelihoods,pressure on civic infrastructure,and increasing pollution—factors that threaten long-term regional sustainability.The study underscores the urgent need to reconcile urban development with environmental and social sustainability.By offering a detailed case study of Sonipat,this research contributes to the broader discourse on India’s urbanisation pathways.It aims to provide policymakers,planners,and researchers with evidence-based recommendations to manage land transitions more responsibly,promoting urban growth models that ensure ecological integrity,equitable development,and long-term resilience.
基金Sponsored by General Project of the Modern Design and Culture Research Center,Sichuan Provincial Key Research Base for Social Sciences(MD24E019)General Project of the Digital Culture and Media Research Base,Sichuan Provincial Key Research Base for Philosophy and Social Sciences(SC23DCMB006).
文摘The theory of spatial narrative enhances the connotation of architectural design and broadens the interaction between architecture and its users.Drawing upon a literature review of relevant keywords related to“architectural space narrative”from the China National Knowledge Infrastructure(CNKI)over the past two decades,alongside an analysis and content identification of high-frequency keywords,clustering,timelines,and other knowledge graphs generated by CiteSpace,this study summarizes the evolution path of spatial narrative theory.This approach offers diverse perspectives for examining emerging trends and key issues within spatial narrative research.
基金supported by National Natural Science Foundation of China(Nos.62477026,62177029,61807020)Humanities and Social Sciences Research Program of the Ministry of Education of China(No.23YJAZH047)the Startup Foundation for Introducing Talent of Nanjing University of Posts and Communications under Grant NY222034.
文摘As Deepfake technology continues to evolve,the distinction between real and fake content becomes increasingly blurred.Most existing Deepfake video detectionmethods rely on single-frame facial image features,which limits their ability to capture temporal differences between frames.Current methods also exhibit limited generalization capabilities,struggling to detect content generated by unknown forgery algorithms.Moreover,the diversity and complexity of forgery techniques introduced by Artificial Intelligence Generated Content(AIGC)present significant challenges for traditional detection frameworks,whichmust balance high detection accuracy with robust performance.To address these challenges,we propose a novel Deepfake detection framework that combines a two-stream convolutional network with a Vision Transformer(ViT)module to enhance spatio-temporal feature representation.The ViT model extracts spatial features from the forged video,while the 3D convolutional network captures temporal features.The 3D convolution enables cross-frame feature extraction,allowing the model to detect subtle facial changes between frames.The confidence scores from both the ViT and 3D convolution submodels are fused at the decision layer,enabling themodel to effectively handle unknown forgery techniques.Focusing on Deepfake videos and GAN-generated images,the proposed approach is evaluated on two widely used public face forgery datasets.Compared to existing state-of-theartmethods,it achieves higher detection accuracy and better generalization performance,offering a robust solution for deepfake detection in real-world scenarios.
文摘BACKGROUND Narrative nursing uses narrative methods to establish an interaction between nursing staff and patients,in which the experience of the patient’s illness is understood and comprehended.By listening,the patient’s understanding,comprehension,and acceptance of their own disease symptoms,quality of life,and living conditions are understood,thereby providing a basis for formulating corresponding nursing plans for the patient,further promoting the psychological and physical rehabilitation of the patient.AIM To explore the impact of the new narrative nursing model on postoperative recovery,psychological status,and satisfaction of patients.METHODS A total of 108 patients with resectable gastric cancer who were treated from January 2024 to December 2024 were selected as the study subjects.They were divided into a routine nursing group and a narrative nursing group using a random number table method.Postoperative recovery indicators were compared between the two groups,and questionnaires and position and postoperative nausea and vomiting were conducted on the day of discharge.RESULTS There were statistically significant differences in visual analogue scale pain scores at 12-96 hours postoperatively,the time of first ambulation postoperatively,and the length of postoperative hospital stay between the two groups(P<0.05).There were statistically significant differences in postoperative self-rating anxiety scale,self-rating depression scale,and satisfaction scores between the two groups(P<0.05).Further analysis using a binary logistic regression model found that the new narrative nursing model adopted postoperatively could improve patients’satisfaction with the work of nursing staff during their hospitalization.CONCLUSION The new narrative nursing model not only eliminated the negative emotions of patients,but also further promoted their postoperative recovery,and gained patients’trust and satisfaction with the nursing staff.
基金College Students Innovation and Entrepreneurship Training Program(X202511049398)College Students Innovation and Entrepreneurship Training Program(X202511049201)+1 种基金College Students Innovation and Entrepreneurship Training Program(X202511258005S)University-Level Research Funding Program of Hainan Science and Technology Vocational University(HKKY2024-87)。
文摘Sandfly fever is a viral infectious disease transmitted by sand flies that is widely prevalent in tropical and subtropical regions.Previous studies on its infection mechanism,immune response and diagnosis and treatment methods were lack of systematic.This study applied spatio-temporal omics technology to comprehensively explain the dynamic changes of immunity in the incubation period,exacerbation period,peak period and recovery period of Sandfl y fever,and integrated with diff erent coping strategies.To provide new research ideas for its overall research.
基金National Natural Science Foundation of China,No.42230106,No.42171250State Key Laboratory of Earth Surface Processes and Resource Ecology,No.2022-ZD-04。
文摘Agriculture holds a pivotal position in the economic fabric of every nation,yet concerns about agricultural carbon emission intensity(ACI)have become a major hurdle to achieving global economic sustainability.Focusing on 31 provincial-level regions in China,this study uses the Exploratory Spatio-temporal Data Analysis(ESTDA)and Panel Quantile Regression(PQR)model to analyze the spatio-temporal interaction characteristics and influencing factors of ACI in China from 2004 to 2023.The findings are as follows:(1)ACI showed an overall downward trend,and the spatial distribution pattern was characterized by“high in the western region and low along the southeastern coast”.Although the overall disparity tended to converge,some high-carbon-intensity regions exhibited extreme trends.ACI displayed clear spatial directionality,with the spatial center shifting steadily toward the northeast.(2)Regions in the northwest,northeast,and central-south parts exhibited strong local spatial structural dynamics,and the local spatial dependence of ACI in each region showed a nonlinear trend.Generally speaking,the spatial association pattern demonstrated a certain degree of inertia in spatial transfer,reflecting strong path dependence or spatial lock-in characteristics.(3)Optimization of industrial structure and improvement in agricultural mechanization will increase ACI,while economic development can effectively reduce it.The impact of urbanization on ACI exhibits a nonlinear pattern.The coordinated development of economic growth and urbanization significantly reduces ACI,with a stronger emission reduction observed in regions with low ACI.The optimization of industrial structure,when combined with urbanization and environmental regulation,contributes to significant emission reductions particularly in high-ACI areas.Similarly,the synergy between agricultural mechanization and urbanization effectively lowers emissions in low-ACI regions,though this effect diminishes in areas with higher ACI.
基金supported by the Key Laboratory of Natural Resources Monitoring and Supervision in Southern Hilly Region,Ministry of Natural Resources(NRMSSHR2023Y02)Yunnan Key Laboratory of Plateau Geographic Processes and Environmental Changes,Faculty of Geography,Yunnan Normal University(PGPEC2304)China Scholarship Council。
文摘Sloping farmland,particularly in mountainous and hilly areas,constitutes a significant component of regional farmland resources.An investigation into the spatio-temporal pattern of sloping farmland and its influencing factors in China is imperative for the efficient utilization of farmland and the optimization of land space.We used land use transfer matrix,geographically weighted regression model and geographical detector to conduct this study.Results showed that sloping farmland in China firstly decreased and then increased from 2000 to 2020.The proportion of sloping farmland decreased radially outward from Sichuan basin to the surrounding areas.Change rates of sloping farmland with different slopes varied and the slope with 6°-15°underwent the fastest changes.The influencing factors of farmland at various slope degrees were different.For sloping farmland below 15°,land use intensity and elevation had the greatest contribution.For sloping farmland between 15°and 25°,elevation,land use intensity,and population density were the main influencing factors.Sloping farmland above 25°was mostly affected by natural factors.This study can provide scientific basis for rational development and protection of sloping farmland.
文摘At present,strengthening China’s international communication capabilities and enhancing China’s global influence have become important tasks.This study selects 60 pieces of soft news from China Daily from March 2023 to February 2024 as research objects and explores China’s national image from the source texts.Then,based on Mona Baker’s narrative theory,it analyzes the translation strategies to reconstruct the image of China,further revealing the regular characteristics of their application.Through translation,the reconstructed national image of China becomes more positive and more acceptable to foreign readers,effectively promoting the dissemination of Chinese stories in the international community.It is significant for promoting international understanding and cooperation,as well as effectively utilizing translation as a tool to enhance China’s national image.
基金support for this work was supported by Key Lab of Intelligent and Green Flexographic Printing under Grant ZBKT202301.
文摘Current spatio-temporal action detection methods lack sufficient capabilities in extracting and comprehending spatio-temporal information. This paper introduces an end-to-end Adaptive Cross-Scale Fusion Encoder-Decoder (ACSF-ED) network to predict the action and locate the object efficiently. In the Adaptive Cross-Scale Fusion Spatio-Temporal Encoder (ACSF ST-Encoder), the Asymptotic Cross-scale Feature-fusion Module (ACCFM) is designed to address the issue of information degradation caused by the propagation of high-level semantic information, thereby extracting high-quality multi-scale features to provide superior features for subsequent spatio-temporal information modeling. Within the Shared-Head Decoder structure, a shared classification and regression detection head is constructed. A multi-constraint loss function composed of one-to-one, one-to-many, and contrastive denoising losses is designed to address the problem of insufficient constraint force in predicting results with traditional methods. This loss function enhances the accuracy of model classification predictions and improves the proximity of regression position predictions to ground truth objects. The proposed method model is evaluated on the popular dataset UCF101-24 and JHMDB-21. Experimental results demonstrate that the proposed method achieves an accuracy of 81.52% on the Frame-mAP metric, surpassing current existing methods.
