This paper describes the design principles and functionality of a MicrocomputerSupervising Devlce(MSD)developed by us on a kind of Jig BoringMachine(JBM) Some Interference-free methods both in software and hardwareare...This paper describes the design principles and functionality of a MicrocomputerSupervising Devlce(MSD)developed by us on a kind of Jig BoringMachine(JBM) Some Interference-free methods both in software and hardwareare also presented.As our MSD implemented,machining the frames of raplerlooms on acommon JBM can meet the technological requlrements suceessfully.Thedesign ideas and the circuit principles of our MSD may also be applied to othersimllar machlnes.展开更多
According to practical hydrological emergency supervising program design,we have discovered and held a design principle with a method to get information promptly and accurately,monitor safely and conveniently,and coll...According to practical hydrological emergency supervising program design,we have discovered and held a design principle with a method to get information promptly and accurately,monitor safely and conveniently,and collect information systematically,expounded the emergency hydrological monitoring program towards hydrometry,which shall be taken full analysis on the special geological environment around the site,aimed at damming body monitoring,and also the construction of hydrological emergency supervising networks in the area,the live video acquisition towards special point of the dammed barrier,then carried out monitoring measures which were suitable to contemporary economy and technology to get complete hydrological information we require. Finally,we put forward a concrete designing method for precluding disaster and reducing the loss of disaster based on the information above.展开更多
Clinical supervision of cognitive behavioral therapy(CBT) with youth ensures better patient care and fosters trainees' professional development. However,often insufficient attention is directed toward disseminatin...Clinical supervision of cognitive behavioral therapy(CBT) with youth ensures better patient care and fosters trainees' professional development. However,often insufficient attention is directed toward disseminating best practices in supervision of CBT with youth. This Therapeutic Advances contribution aims to communicate the core content of supervision. Additionally, the key supervisory practices associated with CBT with youth are described. Supervisory outcomes are summarized and recommendations for supervisory practices are made.展开更多
Objectives This study aimed to analyse the benefits of a gamified clinical supervision strategy during hospital-based training,particularly regarding the development of critical and reflective thinking among undergrad...Objectives This study aimed to analyse the benefits of a gamified clinical supervision strategy during hospital-based training,particularly regarding the development of critical and reflective thinking among undergraduate nursing students.Methods From April to July 2023,second-year nursing students who undertaking a nine-week clinical placement in a cardiology ward in northern Portugal were selected.Following a two-week diagnostic phase,students participated in a six-week gamified supervision programme comprising weekly 60-min sessions:infection-control decision-making;technical-procedural reasoning;guided emotional and ethical reflection;and clinical reasoning quiz on cardiology topics.Students completed weekly Structured Reflection Guide entries;supervisors recorded structured field notes after each session;and,after the intervention,students answered a post-intervention questionnaire and participated in focus groups.Qualitative data(reflections,field notes,open-ended questionnaire items,and focus-group transcripts)were analyzed using Bardin’s content analysis;quantitative questionnaire items were summarized descriptively.Results All seven students completed the six gamified sessions and submitted weekly reflection entries.Five students(71.4%)completed the questionnaire.Across data sources,students reported that gamified activities supported knowledge consolidation,teamwork,and clinical reasoning.Questionnaire data showed that all respondents(n=5,100%)strongly agreed that gamification enhanced their learning and should be maintained in clinical training.Reflections and focus groups revealed recurring themes related to emotional expression,sense of belonging,and difficulties using structured reflection tools,particularly in terms of comprehension and timing.Conclusion The gamified supervision strategy integrated into clinical training provided structured opportunities for practical engagement,collaborative work,and guided reflection.These findings suggest that gamification may support the development of reflective and critical-thinking processes in authentic clinical environments.展开更多
The rapid digitalization of the energy sector has led to the deployment of large-scale smart metering systems that generate high-frequency time series data,creating new opportunities and challenges for energy anomaly ...The rapid digitalization of the energy sector has led to the deployment of large-scale smart metering systems that generate high-frequency time series data,creating new opportunities and challenges for energy anomaly detection.Accurate identification of anomalous patterns in building energy consumption is essential for optimizing operations,improving energy efficiency,and supporting grid reliability.This study investigates advanced feature engineering and machine learning modeling techniques for large-scale time series anomaly detection in building energy systems.Expanding upon previous benchmark frameworks,we introduce additional features such as oil price indices and solar cycle indicators,including sunset and sunrise times,to enhance the contextual understanding of consumption patterns.Our comparative modeling approach encompasses an extensive suite of algorithms,including KNeighborsUnif,KNeighborsDist,LightGBMXT,LightGBM,RandomForestMSE,CatBoost,ExtraTreesMSE,NeuralNetFastAI,XGBoost,NeuralNetTorch,and LightGBMLarge.Data preprocessing includes rigorous handling of missing values and normalization,while feature engineering focuses on temporal,environmental,and value-change attributes.The models are evaluated on a comprehensive dataset of smart meter readings,with performance assessed using metrics such as the Area Under the Receiver Operating Characteristic Curve(AUC-ROC).The results demonstrate that the integration of diverse exogenous variables and a hybrid ensemble of traditional tree-based and neural network models can significantly improve anomaly detection performance.This work provides new insights into the design of robust,scalable,and generalizable frameworks for energy anomaly detection in complex,real-world settings.展开更多
Weakly Supervised Semantic Segmentation(WSSS),which relies only on image-level labels,has attracted significant attention for its cost-effectiveness and scalability.Existing methods mainly enhance inter-class distinct...Weakly Supervised Semantic Segmentation(WSSS),which relies only on image-level labels,has attracted significant attention for its cost-effectiveness and scalability.Existing methods mainly enhance inter-class distinctions and employ data augmentation to mitigate semantic ambiguity and reduce spurious activations.However,they often neglect the complex contextual dependencies among image patches,resulting in incomplete local representations and limited segmentation accuracy.To address these issues,we propose the Context Patch Fusion with Class Token Enhancement(CPF-CTE)framework,which exploits contextual relations among patches to enrich feature repre-sentations and improve segmentation.At its core,the Contextual-Fusion Bidirectional Long Short-Term Memory(CF-BiLSTM)module captures spatial dependencies between patches and enables bidirectional information flow,yield-ing a more comprehensive understanding of spatial correlations.This strengthens feature learning and segmentation robustness.Moreover,we introduce learnable class tokens that dynamically encode and refine class-specific semantics,enhancing discriminative capability.By effectively integrating spatial and semantic cues,CPF-CTE produces richer and more accurate representations of image content.Extensive experiments on PASCAL VOC 2012 and MS COCO 2014 validate that CPF-CTE consistently surpasses prior WSSS methods.展开更多
Objectives This study aimed to explore and clarify the concept of reflective supervision as a professional self-care strategy to create a positive Intensive Care Unit(ICU)practice environment.Methods Walker and Avant...Objectives This study aimed to explore and clarify the concept of reflective supervision as a professional self-care strategy to create a positive Intensive Care Unit(ICU)practice environment.Methods Walker and Avant’s eight-step concept analysis approach was utilized to identify and define the attributes,antecedents,and consequences of reflective supervision in the ICU.An extensive literature search was conducted across various databases,including Google Scholar,CINAHL,PubMed.Articles published from 2005 to 2025 were identified.We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses(PRISMA)2020 statement to indicate the included articles and extract related data based on relevance.Results Forty articles were included in the analysis.The identified attributes included the supervisor-supervisee relationship,effective communication,teamwork,collaborations,reflection,competencies,feedback,continuous support,and autonomous choice.The identified antecedents included participation,supportive supervision,flexibility,open-door policy,training,and motivation.Consequences impacting the success of reflective supervision were identified as promotion of resiliency,autonomy,work-life balance,self-awareness,increased self-esteem,professional development,critical thinking,increased job satisfaction,and enhanced commitment.Conclusions Reflective supervision is a complex professional self-care strategy that enhances ICU practice,by promoting nurses’well-being,self-awareness,therapeutic skills,and professional development.展开更多
As a fundamental component in computer vision,edges can be categorized into four types based on discontinuities in reflectance,illumination,surface normal,or depth.While deep CNNs have significantly advanced generic e...As a fundamental component in computer vision,edges can be categorized into four types based on discontinuities in reflectance,illumination,surface normal,or depth.While deep CNNs have significantly advanced generic edge detection,real-time multi-class semantic edge detection under resource constraints remains challenging.To address this,we propose a lightweight framework based on PiDiNet that enables fine-grained semantic edge detection.Our model simultaneously predicts background and four edge categories from full-resolution inputs,balancing accuracy and efficiency.Key contributions include:a multi-channel output structure expanding binary edge prediction to five classes,supported by a deep supervision mechanism;a dynamic class-balancing strategy combining adaptive weighting with physical priors to handle extreme class imbalance;and maintained architectural efficiency enabling real-time inference.Extensive evaluations on BSDS-RIND show our approach achieves accuracy competitive with state-of-the-art methods while operating in real time.展开更多
Accurate prediction of rockburst intensity levels is crucial for ensuring the safety of deep hard rock engineering construction.This paper introduced an expert system for rockburst intensity level prediction that empl...Accurate prediction of rockburst intensity levels is crucial for ensuring the safety of deep hard rock engineering construction.This paper introduced an expert system for rockburst intensity level prediction that employs machine learning algorithms as the basis for its inference rules.The system comprises four modules:a database,a repository,an inference engine,and an interpreter.A database containing 1114 rockburst cases was used to construct 357 datasets that serve as the repository for the expert system.Additionally,19 types of machine learning algorithms were used to establish 6783 micro-models to construct cognitive rules within the inference engine.By integrating probability theory and marginal analysis,a fuzzy scoring method based on the SoftMax function was developed and applied to the interpreter for rockburst intensity level prediction,effectively restoring the continuity of rockburst characteristics.The research results indicate that ensemble algorithms based on decision trees are more effective in capturing the characteristics of rockburst.Key factors for accurate prediction of rockburst intensity include uniaxial compressive strength,elastic energy index,the maximum principal stress,tangential stress,and their composite indicators.The accuracy of the proposed rockburst intensity level prediction expert system was verified using 20 engineering rockburst cases,with predictions aligning closely with the actual rockburst intensity levels.展开更多
To address the severe challenges of PM_(2.5) and ozone co-control during the"14^(th) Five-Year Plan"period and to enhance the precision and intelligence level of air environment governance,it is imperative t...To address the severe challenges of PM_(2.5) and ozone co-control during the"14^(th) Five-Year Plan"period and to enhance the precision and intelligence level of air environment governance,it is imperative to build an efficient comprehensive management platform for regional air quality.In this paper,the specific practice in Zibo City,Shandong Province is as an example to systematically analyze the top-level design,technical implementation,and innovative application of a comprehensive management platform for regional air quality integrating"perception monitoring,data fusion,research judgment of early warnings,analysis of sources,collaborative dispatching,and evaluation assessment".Through the construction of an"sky-air-ground"integrated three-dimensional monitoring network,the platform integrates multi-source heterogeneous environmental data,and employs big data,cloud computing,artificial intelligence,CALPUFF/CMAQ,and other numerical model technologies to achieve comprehensive perception,precise prediction,intelligent source tracing,and closed-loop management of air pollution.The platform innovatively establishes a full-process closed-loop management mechanism of"data-early warning-disposition-evaluation",and achieves a fundamental transformation from passive response to active anticipation and from experience-based judgment to data driving in environmental supervision.The application results show that this platform significantly improves the scientific decision-making ability and collaborative execution efficiency of air pollution governance in Zibo City,providing a replicable and scalable comprehensive solution for similar industrial cities to achieve the continuous improvement of air quality.展开更多
Weakly supervised semantic segmentation(WSSS)is a tricky task,which only provides category information for segmentation prediction.Thus,the key stage of WSSS is to generate the pseudo labels.For convolutional neural n...Weakly supervised semantic segmentation(WSSS)is a tricky task,which only provides category information for segmentation prediction.Thus,the key stage of WSSS is to generate the pseudo labels.For convolutional neural network(CNN)based methods,in which class activation mapping(CAM)is proposed to obtain the pseudo labels,and only concentrates on the most discriminative parts.Recently,transformer-based methods utilize attention map from the multi-headed self-attention(MHSA)module to predict pseudo labels,which usually contain obvious background noise and incoherent object area.To solve the above problems,we use the Conformer as our backbone,which is a parallel network based on convolutional neural network(CNN)and Transformer.The two branches generate pseudo labels and refine them independently,and can effectively combine the advantages of CNN and Transformer.However,the parallel structure is not close enough in the information communication.Thus,parallel structure can result in poor details about pseudo labels,and the background noise still exists.To alleviate this problem,we propose enhancing convolution CAM(ECCAM)model,which have three improved modules based on enhancing convolution,including deeper stem(DStem),convolutional feed-forward network(CFFN)and feature coupling unit with convolution(FCUConv).The ECCAM could make Conformer have tighter interaction between CNN and Transformer branches.After experimental verification,the improved modules we propose can help the network perceive more local information from images,making the final segmentation results more refined.Compared with similar architecture,our modules greatly improve the semantic segmentation performance and achieve70.2%mean intersection over union(mIoU)on the PASCAL VOC 2012 dataset.展开更多
Graduation project courses refer to the culmination of the learning experiences of higher education. These courses consolidate the disciplinary knowledge gained during architectural education while they integrate most...Graduation project courses refer to the culmination of the learning experiences of higher education. These courses consolidate the disciplinary knowledge gained during architectural education while they integrate most of the learning outcomes of a program, which are intended to prepare students for their transition to the profession of architecture. The educational methods of these courses require constant attention, regular review, and continuous development to remain consistent with the changing standards of the profession given the significance of these courses. The problem lies in the diversity and controversy of these methods, thereby implying inconsistency in the best practices. In this study, several questions are raised in terms of the nature of these courses, enrollment criteria, topic selection, learning experience, and assessment methods. This study aims to investigate the best practices of managing, supervising, and assessing architectural graduation projects to provide guidelines for establishing and/or developing these courses. An analytical deductive methodology is adopted. This methodology is supported by a survey of a sample of 105 worldwide academic architects and is structured into four sections, namely, the analysis of the components of graduation projects, the survey and its procedures, the quantitative findings of the survey, and a discussion of the issues and results. This study draws conclusions to its research questions, thereby extending its influence on the quality of architectural programs and the benefits for individuals who are concerned with their development.展开更多
In order to keep crew healthy during their journey and preventing diseases which cause by eating unqualified food. An investigation on sanitary condition of provision over ships have implemented from January to Octobe...In order to keep crew healthy during their journey and preventing diseases which cause by eating unqualified food. An investigation on sanitary condition of provision over ships have implemented from January to October of 1995. 109 out of 951 units provision were unqualfled (11.48%). Over time and improper storage and unqualified sanitary environment of store rooms were the main reasons for this case. The authors presented the discussion on supervision and control over ships’ provision in this article.展开更多
Hygiene supervision and control over the manufacturing plants supplying flight food, the cabin service department of Air China and food supply on aircraft have been implemented by the Beijing Airport Health and Quaran...Hygiene supervision and control over the manufacturing plants supplying flight food, the cabin service department of Air China and food supply on aircraft have been implemented by the Beijing Airport Health and Quarantine Bureau. Fifty—three specific problems of various kinds have been detected in a 12 month experimental period from August of 1991 to August of 1992. This paper has discussed the legal basis, supervision unit, work procedures and work content of supervision and control over air catering.展开更多
Background The potential of exercise as a concurrent therapy for actively treated primary tumors has been suggested by emerging preclinical and observational studies.However,clinical trials regarding this question are...Background The potential of exercise as a concurrent therapy for actively treated primary tumors has been suggested by emerging preclinical and observational studies.However,clinical trials regarding this question are scarce.Therefore,we conducted a randomized controlled trial investigating the effects of aerobic or resistance exercise concomitant to neoadjuvant chemotherapy(NACT)on tumor size.Methods In the BENEFIT study(German title:Bewegung bei neoadjuvanter chemotherapie zur verbesserung der fitness),patients with breast cancer scheduled for NACT were randomly assigned to supervised resistance training(RT,n=60)or aerobic training(AT,n=60)twice weekly during NACT or to a waitlist control group(WCG,n=60).The primary outcome,“change in tumor size”,as well as the secondary clinical outcomes pathologic complete response(pCR),type of surgery(breast conserving/mastectomy),axillary lymph node dissection(ALND,yes/no),premature discontinuation of chemotherapy(yes/no),and relative dose intensity(RDI)were derived from clinical records.Due to the highly skewed distribution,the primary outcome was categorized.Multiple(ordinal)logistic regression analyses were performed.Results Overall,there was no significant difference in post-intervention tumor size between RT or AT and WCG.However,there was a significant effect modification by hormone receptor(HR)status(P_(interaction)=0.030).Among patients with HR+tumors,results suggest a beneficial effect of AT on tumor shrinkage(odds ratio(OR)=2.37,95%confidence interval(95%CI):0.97‒5.78),on pCR(OR=3.21,95%CI:0.97‒10.61);and on ALND(OR=3.76,95%CI:0.78‒18.06)compared to WCG.The effects of RT were slightly less pronounced.For HR−subtypes,beneficial effects on RDI were found for AT(OR=3.71,95%CI:1.20‒11.50)and similarly for RT(OR=2.58,95%CI:0.88‒7.59).Both AT and RT had favorable effects on premature discontinuation of chemotherapy(OR(no vs.yes)=2.34,95%CI:1.10‒5.06),irrespective of tumor receptor status.Conclusion While there was no significant effect on the primary outcome in the overall group,aerobic and resistance exercise concomitant to NACT seem to beneficially affect tumor shrinkage and pCR,reduce the need for ALND among patients with HR+breast cancers,and prevent low RDI among patients with HR–breast cancers.These results warrant confirmation in further trials.展开更多
High-entropy alloys(HEAs)have emerged as promising catalysts for the hydrogen evolution reaction(HER)due to their compositional diversity and synergistic effects.In this study,machine learning-accelerated density func...High-entropy alloys(HEAs)have emerged as promising catalysts for the hydrogen evolution reaction(HER)due to their compositional diversity and synergistic effects.In this study,machine learning-accelerated density functional theory(DFT)calculations were employed to assess the catalytic performance of PtPd-based HEAs with the formula PtPdXYZ(X,Y,Z=Fe,Co,Ni,Cu,Ru,Rh,Ag,Au;X≠Y≠Z).Among 56 screened HEA(111)surfaces,PtPdRuCoNi(111)was identified as the most promising,with adsorption energies(E_(ads))between−0.50 and−0.60 eV and high d-band center of−1.85 eV,indicating enhanced activity.This surface showed the hydrogen adsorption free energy(ΔG_(H^(*)))of−0.03 eV for hydrogen adsorption,outperforming Pt(111)by achieving a better balance between adsorption and desorption.Machine learning models,particularly extreme gradient boosting regression(XGBR),significantly reduced computational costs while maintaining high accuracy(root-mean-square error,RMSE=0.128 eV).These results demonstrate the potential of HEAs for efficient and sustainable hydrogen production.展开更多
In the field of optoelectronics,certain types of data may be difficult to accurately annotate,such as high-resolution optoelectronic imaging or imaging in certain special spectral ranges.Weakly supervised learning can...In the field of optoelectronics,certain types of data may be difficult to accurately annotate,such as high-resolution optoelectronic imaging or imaging in certain special spectral ranges.Weakly supervised learning can provide a more reliable approach in these situations.Current popular approaches mainly adopt the classification-based class activation maps(CAM)as initial pseudo labels to solve the task.展开更多
Background Evidence on the effects of different exercise interventions on cognitive function is insufficient.Aims To evaluate the feasibility and effects of remotely supervised aerobic exercise(AE)and resistance exerc...Background Evidence on the effects of different exercise interventions on cognitive function is insufficient.Aims To evaluate the feasibility and effects of remotely supervised aerobic exercise(AE)and resistance exercise(RE)interventions in older adults with mild cognitive impairment(MCI).Methods This study is a 6-month pilot three-arm randomised controlled trial.Eligible participants(n=108)were recruited and randomised to the AE group,RE group or control(CON)group with a 1:1:1 ratio.Interventions were delivered at home with remote supervision.We evaluated participants’global cognition,memory,executive function,attention,physical activity levels,physical performance and muscle strength of limbs at baseline,3 months(T1)and 6 months(T2)after randomisation.A linear mixed-effects model was adopted for data analyses after controlling for covariates.Tukey’s method was used for adjusting for multiple comparisons.Sensitivity analyses were performed after excluding individuals with low compliance rates.Results 15(13.89%)participants dropped out.The median compliance rates in the AE group and RE group were 67.31%and 93.27%,respectively.After adjusting for covariates,the scores of the Alzheimer’s Disease Assessment Scale-Cognitive subscale in the AE group decreased by 2.04(95%confidence interval(CI)−3.41 to−0.67,t=−2.94,p=0.004)and 1.53(95%CI−2.88 to−0.17,t=−2.22,p=0.028)points more than those in the CON group at T1 and T2,respectively.The effects of AE were still significant at T1(estimate=−1.70,95%CI−3.20 to−0.21,t=−2.69,p=0.021),but lost statistical significance at T2 after adjusting for multiple comparisons.As for executive function,the Stroop time interference in the RE group decreased by 11.76 s(95%CI−21.62 to−1.90,t=−2.81,p=0.015)more than that in the AE group at T2 after Tukey’s adjustment.No other significant effects on cognitive functions were found.Conclusions Both remotely supervised AE and RE programmes are feasible in older adults with MCI.AE has positive effects on global cognition,and RE improves executive function.展开更多
The code of the list of sea and island problems is the unique identification code of the regulatory files,which is accompanied by the whole life cycle of the regulatory"discovery,verification and disposal".S...The code of the list of sea and island problems is the unique identification code of the regulatory files,which is accompanied by the whole life cycle of the regulatory"discovery,verification and disposal".Standardized coding of problems found by supervision and tracking and recording the whole life cycle of supervision can quickly guide supervisors to find problems,identify problems,initiate responses and carry out follow-up disposal,which is a reflection of whole-process management of supervision.Combining with sea and island regulatory systems and mechanisms,combed the supervision business flow,divides the supervision link,based on the existing coding system,from the Angle of supervision refinement,puts forward a whole lifetime oriented regulatory system of sea and island issues list for coding,coding through to find and stop and disposal of the three links all process application scenarios,The implementation of the whole business"one code"association,the whole process of"one code"management,practice verification shows the effectiveness of the method,compared with the original coding rules for the supervision of all links and results reflect more intuitive,comprehensive,can be better applied to the practice of supervision.展开更多
Teaching quality is the core guarantee for universities to achieve their talent cultivation goals,and teaching supervision,as an important means of monitoring teaching quality,runs through the entire process of teachi...Teaching quality is the core guarantee for universities to achieve their talent cultivation goals,and teaching supervision,as an important means of monitoring teaching quality,runs through the entire process of teaching management.Based on the teaching quality report of School A at University Z for the autumn semester of 2024,this paper systematically analyzes the current situation,problems,and causes of the teaching supervision mechanism through multi-dimensional data analysis of expert classroom observation,peer evaluation,and classroom feedback.On this basis,combined with the application prospects of artificial intelligence technology,it proposes paths to optimize the teaching supervision mechanism,including improving the classroom observation feedback mechanism,increasing supervision coverage,and strengthening the linkage between feedback and teaching reform,providing practical experience and theoretical support for improving teaching quality in universities.展开更多
文摘This paper describes the design principles and functionality of a MicrocomputerSupervising Devlce(MSD)developed by us on a kind of Jig BoringMachine(JBM) Some Interference-free methods both in software and hardwareare also presented.As our MSD implemented,machining the frames of raplerlooms on acommon JBM can meet the technological requlrements suceessfully.Thedesign ideas and the circuit principles of our MSD may also be applied to othersimllar machlnes.
文摘According to practical hydrological emergency supervising program design,we have discovered and held a design principle with a method to get information promptly and accurately,monitor safely and conveniently,and collect information systematically,expounded the emergency hydrological monitoring program towards hydrometry,which shall be taken full analysis on the special geological environment around the site,aimed at damming body monitoring,and also the construction of hydrological emergency supervising networks in the area,the live video acquisition towards special point of the dammed barrier,then carried out monitoring measures which were suitable to contemporary economy and technology to get complete hydrological information we require. Finally,we put forward a concrete designing method for precluding disaster and reducing the loss of disaster based on the information above.
文摘Clinical supervision of cognitive behavioral therapy(CBT) with youth ensures better patient care and fosters trainees' professional development. However,often insufficient attention is directed toward disseminating best practices in supervision of CBT with youth. This Therapeutic Advances contribution aims to communicate the core content of supervision. Additionally, the key supervisory practices associated with CBT with youth are described. Supervisory outcomes are summarized and recommendations for supervisory practices are made.
文摘Objectives This study aimed to analyse the benefits of a gamified clinical supervision strategy during hospital-based training,particularly regarding the development of critical and reflective thinking among undergraduate nursing students.Methods From April to July 2023,second-year nursing students who undertaking a nine-week clinical placement in a cardiology ward in northern Portugal were selected.Following a two-week diagnostic phase,students participated in a six-week gamified supervision programme comprising weekly 60-min sessions:infection-control decision-making;technical-procedural reasoning;guided emotional and ethical reflection;and clinical reasoning quiz on cardiology topics.Students completed weekly Structured Reflection Guide entries;supervisors recorded structured field notes after each session;and,after the intervention,students answered a post-intervention questionnaire and participated in focus groups.Qualitative data(reflections,field notes,open-ended questionnaire items,and focus-group transcripts)were analyzed using Bardin’s content analysis;quantitative questionnaire items were summarized descriptively.Results All seven students completed the six gamified sessions and submitted weekly reflection entries.Five students(71.4%)completed the questionnaire.Across data sources,students reported that gamified activities supported knowledge consolidation,teamwork,and clinical reasoning.Questionnaire data showed that all respondents(n=5,100%)strongly agreed that gamification enhanced their learning and should be maintained in clinical training.Reflections and focus groups revealed recurring themes related to emotional expression,sense of belonging,and difficulties using structured reflection tools,particularly in terms of comprehension and timing.Conclusion The gamified supervision strategy integrated into clinical training provided structured opportunities for practical engagement,collaborative work,and guided reflection.These findings suggest that gamification may support the development of reflective and critical-thinking processes in authentic clinical environments.
文摘The rapid digitalization of the energy sector has led to the deployment of large-scale smart metering systems that generate high-frequency time series data,creating new opportunities and challenges for energy anomaly detection.Accurate identification of anomalous patterns in building energy consumption is essential for optimizing operations,improving energy efficiency,and supporting grid reliability.This study investigates advanced feature engineering and machine learning modeling techniques for large-scale time series anomaly detection in building energy systems.Expanding upon previous benchmark frameworks,we introduce additional features such as oil price indices and solar cycle indicators,including sunset and sunrise times,to enhance the contextual understanding of consumption patterns.Our comparative modeling approach encompasses an extensive suite of algorithms,including KNeighborsUnif,KNeighborsDist,LightGBMXT,LightGBM,RandomForestMSE,CatBoost,ExtraTreesMSE,NeuralNetFastAI,XGBoost,NeuralNetTorch,and LightGBMLarge.Data preprocessing includes rigorous handling of missing values and normalization,while feature engineering focuses on temporal,environmental,and value-change attributes.The models are evaluated on a comprehensive dataset of smart meter readings,with performance assessed using metrics such as the Area Under the Receiver Operating Characteristic Curve(AUC-ROC).The results demonstrate that the integration of diverse exogenous variables and a hybrid ensemble of traditional tree-based and neural network models can significantly improve anomaly detection performance.This work provides new insights into the design of robust,scalable,and generalizable frameworks for energy anomaly detection in complex,real-world settings.
文摘Weakly Supervised Semantic Segmentation(WSSS),which relies only on image-level labels,has attracted significant attention for its cost-effectiveness and scalability.Existing methods mainly enhance inter-class distinctions and employ data augmentation to mitigate semantic ambiguity and reduce spurious activations.However,they often neglect the complex contextual dependencies among image patches,resulting in incomplete local representations and limited segmentation accuracy.To address these issues,we propose the Context Patch Fusion with Class Token Enhancement(CPF-CTE)framework,which exploits contextual relations among patches to enrich feature repre-sentations and improve segmentation.At its core,the Contextual-Fusion Bidirectional Long Short-Term Memory(CF-BiLSTM)module captures spatial dependencies between patches and enables bidirectional information flow,yield-ing a more comprehensive understanding of spatial correlations.This strengthens feature learning and segmentation robustness.Moreover,we introduce learnable class tokens that dynamically encode and refine class-specific semantics,enhancing discriminative capability.By effectively integrating spatial and semantic cues,CPF-CTE produces richer and more accurate representations of image content.Extensive experiments on PASCAL VOC 2012 and MS COCO 2014 validate that CPF-CTE consistently surpasses prior WSSS methods.
文摘Objectives This study aimed to explore and clarify the concept of reflective supervision as a professional self-care strategy to create a positive Intensive Care Unit(ICU)practice environment.Methods Walker and Avant’s eight-step concept analysis approach was utilized to identify and define the attributes,antecedents,and consequences of reflective supervision in the ICU.An extensive literature search was conducted across various databases,including Google Scholar,CINAHL,PubMed.Articles published from 2005 to 2025 were identified.We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses(PRISMA)2020 statement to indicate the included articles and extract related data based on relevance.Results Forty articles were included in the analysis.The identified attributes included the supervisor-supervisee relationship,effective communication,teamwork,collaborations,reflection,competencies,feedback,continuous support,and autonomous choice.The identified antecedents included participation,supportive supervision,flexibility,open-door policy,training,and motivation.Consequences impacting the success of reflective supervision were identified as promotion of resiliency,autonomy,work-life balance,self-awareness,increased self-esteem,professional development,critical thinking,increased job satisfaction,and enhanced commitment.Conclusions Reflective supervision is a complex professional self-care strategy that enhances ICU practice,by promoting nurses’well-being,self-awareness,therapeutic skills,and professional development.
基金supported by the National Natural Science Foundation of China 62402171.
文摘As a fundamental component in computer vision,edges can be categorized into four types based on discontinuities in reflectance,illumination,surface normal,or depth.While deep CNNs have significantly advanced generic edge detection,real-time multi-class semantic edge detection under resource constraints remains challenging.To address this,we propose a lightweight framework based on PiDiNet that enables fine-grained semantic edge detection.Our model simultaneously predicts background and four edge categories from full-resolution inputs,balancing accuracy and efficiency.Key contributions include:a multi-channel output structure expanding binary edge prediction to five classes,supported by a deep supervision mechanism;a dynamic class-balancing strategy combining adaptive weighting with physical priors to handle extreme class imbalance;and maintained architectural efficiency enabling real-time inference.Extensive evaluations on BSDS-RIND show our approach achieves accuracy competitive with state-of-the-art methods while operating in real time.
基金Project(42077244)supported by the National Natural Science Foundation of ChinaProject(2020-05)supported by the Open Research Fund of Guangdong Provincial Key Laboratory of Deep Earth Sciences and Geothermal Energy Exploitation and Utilization,China。
文摘Accurate prediction of rockburst intensity levels is crucial for ensuring the safety of deep hard rock engineering construction.This paper introduced an expert system for rockburst intensity level prediction that employs machine learning algorithms as the basis for its inference rules.The system comprises four modules:a database,a repository,an inference engine,and an interpreter.A database containing 1114 rockburst cases was used to construct 357 datasets that serve as the repository for the expert system.Additionally,19 types of machine learning algorithms were used to establish 6783 micro-models to construct cognitive rules within the inference engine.By integrating probability theory and marginal analysis,a fuzzy scoring method based on the SoftMax function was developed and applied to the interpreter for rockburst intensity level prediction,effectively restoring the continuity of rockburst characteristics.The research results indicate that ensemble algorithms based on decision trees are more effective in capturing the characteristics of rockburst.Key factors for accurate prediction of rockburst intensity include uniaxial compressive strength,elastic energy index,the maximum principal stress,tangential stress,and their composite indicators.The accuracy of the proposed rockburst intensity level prediction expert system was verified using 20 engineering rockburst cases,with predictions aligning closely with the actual rockburst intensity levels.
文摘To address the severe challenges of PM_(2.5) and ozone co-control during the"14^(th) Five-Year Plan"period and to enhance the precision and intelligence level of air environment governance,it is imperative to build an efficient comprehensive management platform for regional air quality.In this paper,the specific practice in Zibo City,Shandong Province is as an example to systematically analyze the top-level design,technical implementation,and innovative application of a comprehensive management platform for regional air quality integrating"perception monitoring,data fusion,research judgment of early warnings,analysis of sources,collaborative dispatching,and evaluation assessment".Through the construction of an"sky-air-ground"integrated three-dimensional monitoring network,the platform integrates multi-source heterogeneous environmental data,and employs big data,cloud computing,artificial intelligence,CALPUFF/CMAQ,and other numerical model technologies to achieve comprehensive perception,precise prediction,intelligent source tracing,and closed-loop management of air pollution.The platform innovatively establishes a full-process closed-loop management mechanism of"data-early warning-disposition-evaluation",and achieves a fundamental transformation from passive response to active anticipation and from experience-based judgment to data driving in environmental supervision.The application results show that this platform significantly improves the scientific decision-making ability and collaborative execution efficiency of air pollution governance in Zibo City,providing a replicable and scalable comprehensive solution for similar industrial cities to achieve the continuous improvement of air quality.
文摘Weakly supervised semantic segmentation(WSSS)is a tricky task,which only provides category information for segmentation prediction.Thus,the key stage of WSSS is to generate the pseudo labels.For convolutional neural network(CNN)based methods,in which class activation mapping(CAM)is proposed to obtain the pseudo labels,and only concentrates on the most discriminative parts.Recently,transformer-based methods utilize attention map from the multi-headed self-attention(MHSA)module to predict pseudo labels,which usually contain obvious background noise and incoherent object area.To solve the above problems,we use the Conformer as our backbone,which is a parallel network based on convolutional neural network(CNN)and Transformer.The two branches generate pseudo labels and refine them independently,and can effectively combine the advantages of CNN and Transformer.However,the parallel structure is not close enough in the information communication.Thus,parallel structure can result in poor details about pseudo labels,and the background noise still exists.To alleviate this problem,we propose enhancing convolution CAM(ECCAM)model,which have three improved modules based on enhancing convolution,including deeper stem(DStem),convolutional feed-forward network(CFFN)and feature coupling unit with convolution(FCUConv).The ECCAM could make Conformer have tighter interaction between CNN and Transformer branches.After experimental verification,the improved modules we propose can help the network perceive more local information from images,making the final segmentation results more refined.Compared with similar architecture,our modules greatly improve the semantic segmentation performance and achieve70.2%mean intersection over union(mIoU)on the PASCAL VOC 2012 dataset.
文摘Graduation project courses refer to the culmination of the learning experiences of higher education. These courses consolidate the disciplinary knowledge gained during architectural education while they integrate most of the learning outcomes of a program, which are intended to prepare students for their transition to the profession of architecture. The educational methods of these courses require constant attention, regular review, and continuous development to remain consistent with the changing standards of the profession given the significance of these courses. The problem lies in the diversity and controversy of these methods, thereby implying inconsistency in the best practices. In this study, several questions are raised in terms of the nature of these courses, enrollment criteria, topic selection, learning experience, and assessment methods. This study aims to investigate the best practices of managing, supervising, and assessing architectural graduation projects to provide guidelines for establishing and/or developing these courses. An analytical deductive methodology is adopted. This methodology is supported by a survey of a sample of 105 worldwide academic architects and is structured into four sections, namely, the analysis of the components of graduation projects, the survey and its procedures, the quantitative findings of the survey, and a discussion of the issues and results. This study draws conclusions to its research questions, thereby extending its influence on the quality of architectural programs and the benefits for individuals who are concerned with their development.
文摘In order to keep crew healthy during their journey and preventing diseases which cause by eating unqualified food. An investigation on sanitary condition of provision over ships have implemented from January to October of 1995. 109 out of 951 units provision were unqualfled (11.48%). Over time and improper storage and unqualified sanitary environment of store rooms were the main reasons for this case. The authors presented the discussion on supervision and control over ships’ provision in this article.
文摘Hygiene supervision and control over the manufacturing plants supplying flight food, the cabin service department of Air China and food supply on aircraft have been implemented by the Beijing Airport Health and Quarantine Bureau. Fifty—three specific problems of various kinds have been detected in a 12 month experimental period from August of 1991 to August of 1992. This paper has discussed the legal basis, supervision unit, work procedures and work content of supervision and control over air catering.
基金supported by an intramural proof of concept grant of the NCT Heidelberg.
文摘Background The potential of exercise as a concurrent therapy for actively treated primary tumors has been suggested by emerging preclinical and observational studies.However,clinical trials regarding this question are scarce.Therefore,we conducted a randomized controlled trial investigating the effects of aerobic or resistance exercise concomitant to neoadjuvant chemotherapy(NACT)on tumor size.Methods In the BENEFIT study(German title:Bewegung bei neoadjuvanter chemotherapie zur verbesserung der fitness),patients with breast cancer scheduled for NACT were randomly assigned to supervised resistance training(RT,n=60)or aerobic training(AT,n=60)twice weekly during NACT or to a waitlist control group(WCG,n=60).The primary outcome,“change in tumor size”,as well as the secondary clinical outcomes pathologic complete response(pCR),type of surgery(breast conserving/mastectomy),axillary lymph node dissection(ALND,yes/no),premature discontinuation of chemotherapy(yes/no),and relative dose intensity(RDI)were derived from clinical records.Due to the highly skewed distribution,the primary outcome was categorized.Multiple(ordinal)logistic regression analyses were performed.Results Overall,there was no significant difference in post-intervention tumor size between RT or AT and WCG.However,there was a significant effect modification by hormone receptor(HR)status(P_(interaction)=0.030).Among patients with HR+tumors,results suggest a beneficial effect of AT on tumor shrinkage(odds ratio(OR)=2.37,95%confidence interval(95%CI):0.97‒5.78),on pCR(OR=3.21,95%CI:0.97‒10.61);and on ALND(OR=3.76,95%CI:0.78‒18.06)compared to WCG.The effects of RT were slightly less pronounced.For HR−subtypes,beneficial effects on RDI were found for AT(OR=3.71,95%CI:1.20‒11.50)and similarly for RT(OR=2.58,95%CI:0.88‒7.59).Both AT and RT had favorable effects on premature discontinuation of chemotherapy(OR(no vs.yes)=2.34,95%CI:1.10‒5.06),irrespective of tumor receptor status.Conclusion While there was no significant effect on the primary outcome in the overall group,aerobic and resistance exercise concomitant to NACT seem to beneficially affect tumor shrinkage and pCR,reduce the need for ALND among patients with HR+breast cancers,and prevent low RDI among patients with HR–breast cancers.These results warrant confirmation in further trials.
基金the Second Century Fund(C2F),Chulalongkorn UniversityThailand Science Research and Innovation Fund Chulalongkorn University(No.IND_FF_68_054_2100_009)National Science and Technology Development Agency,Thailand,Hub of Knowledge funding,and the Mid-Career Research Grant 2024,National Research Council of Thailand(No.N42A670295).
文摘High-entropy alloys(HEAs)have emerged as promising catalysts for the hydrogen evolution reaction(HER)due to their compositional diversity and synergistic effects.In this study,machine learning-accelerated density functional theory(DFT)calculations were employed to assess the catalytic performance of PtPd-based HEAs with the formula PtPdXYZ(X,Y,Z=Fe,Co,Ni,Cu,Ru,Rh,Ag,Au;X≠Y≠Z).Among 56 screened HEA(111)surfaces,PtPdRuCoNi(111)was identified as the most promising,with adsorption energies(E_(ads))between−0.50 and−0.60 eV and high d-band center of−1.85 eV,indicating enhanced activity.This surface showed the hydrogen adsorption free energy(ΔG_(H^(*)))of−0.03 eV for hydrogen adsorption,outperforming Pt(111)by achieving a better balance between adsorption and desorption.Machine learning models,particularly extreme gradient boosting regression(XGBR),significantly reduced computational costs while maintaining high accuracy(root-mean-square error,RMSE=0.128 eV).These results demonstrate the potential of HEAs for efficient and sustainable hydrogen production.
文摘In the field of optoelectronics,certain types of data may be difficult to accurately annotate,such as high-resolution optoelectronic imaging or imaging in certain special spectral ranges.Weakly supervised learning can provide a more reliable approach in these situations.Current popular approaches mainly adopt the classification-based class activation maps(CAM)as initial pseudo labels to solve the task.
基金funded by the National Natural Science Foundation of China(81871854,72374014)the National Key R&D Program of China(2020YFC2008804)+1 种基金the Shanghai Jiao Tong University Young Talent Cultivation Program in Liberal Arts(2024QN041)the Shanghai Jiao Tong University School of Medicine:Nursing Development Program(SJTUHLXK2024).
文摘Background Evidence on the effects of different exercise interventions on cognitive function is insufficient.Aims To evaluate the feasibility and effects of remotely supervised aerobic exercise(AE)and resistance exercise(RE)interventions in older adults with mild cognitive impairment(MCI).Methods This study is a 6-month pilot three-arm randomised controlled trial.Eligible participants(n=108)were recruited and randomised to the AE group,RE group or control(CON)group with a 1:1:1 ratio.Interventions were delivered at home with remote supervision.We evaluated participants’global cognition,memory,executive function,attention,physical activity levels,physical performance and muscle strength of limbs at baseline,3 months(T1)and 6 months(T2)after randomisation.A linear mixed-effects model was adopted for data analyses after controlling for covariates.Tukey’s method was used for adjusting for multiple comparisons.Sensitivity analyses were performed after excluding individuals with low compliance rates.Results 15(13.89%)participants dropped out.The median compliance rates in the AE group and RE group were 67.31%and 93.27%,respectively.After adjusting for covariates,the scores of the Alzheimer’s Disease Assessment Scale-Cognitive subscale in the AE group decreased by 2.04(95%confidence interval(CI)−3.41 to−0.67,t=−2.94,p=0.004)and 1.53(95%CI−2.88 to−0.17,t=−2.22,p=0.028)points more than those in the CON group at T1 and T2,respectively.The effects of AE were still significant at T1(estimate=−1.70,95%CI−3.20 to−0.21,t=−2.69,p=0.021),but lost statistical significance at T2 after adjusting for multiple comparisons.As for executive function,the Stroop time interference in the RE group decreased by 11.76 s(95%CI−21.62 to−1.90,t=−2.81,p=0.015)more than that in the AE group at T2 after Tukey’s adjustment.No other significant effects on cognitive functions were found.Conclusions Both remotely supervised AE and RE programmes are feasible in older adults with MCI.AE has positive effects on global cognition,and RE improves executive function.
文摘The code of the list of sea and island problems is the unique identification code of the regulatory files,which is accompanied by the whole life cycle of the regulatory"discovery,verification and disposal".Standardized coding of problems found by supervision and tracking and recording the whole life cycle of supervision can quickly guide supervisors to find problems,identify problems,initiate responses and carry out follow-up disposal,which is a reflection of whole-process management of supervision.Combining with sea and island regulatory systems and mechanisms,combed the supervision business flow,divides the supervision link,based on the existing coding system,from the Angle of supervision refinement,puts forward a whole lifetime oriented regulatory system of sea and island issues list for coding,coding through to find and stop and disposal of the three links all process application scenarios,The implementation of the whole business"one code"association,the whole process of"one code"management,practice verification shows the effectiveness of the method,compared with the original coding rules for the supervision of all links and results reflect more intuitive,comprehensive,can be better applied to the practice of supervision.
基金Research on the Quality Verification of Applied University Talent Cultivation Based on the“Five Degrees,”a major project of university-level talent training quality and teaching reform in 2023(TFCJGZD202303)。
文摘Teaching quality is the core guarantee for universities to achieve their talent cultivation goals,and teaching supervision,as an important means of monitoring teaching quality,runs through the entire process of teaching management.Based on the teaching quality report of School A at University Z for the autumn semester of 2024,this paper systematically analyzes the current situation,problems,and causes of the teaching supervision mechanism through multi-dimensional data analysis of expert classroom observation,peer evaluation,and classroom feedback.On this basis,combined with the application prospects of artificial intelligence technology,it proposes paths to optimize the teaching supervision mechanism,including improving the classroom observation feedback mechanism,increasing supervision coverage,and strengthening the linkage between feedback and teaching reform,providing practical experience and theoretical support for improving teaching quality in universities.
