Eight of ten patients return to daily activities, work, and sports after total knee arthroplasty

BACKGROUND Besides return to work(RTW)and return to sports(RTS),patients also prefer to return to daily activities(RTA)such as walking,sleeping,grocery shopping,and domestic work following total knee arthroplasty(TKA).However,evidence on the timelines and probability of patients’RTA is sparse.AIM To assess the percentage of patients able to RTA,RTW,and RTS after TKA,as well as the timeframe and influencing factors of this return.METHODS A retrospective cohort study with prospectively collected data was conducted at a medium-sized Dutch orthopedic hospital.Assessments of RTA,RTW,and RTS were performed at 3 mo and/or 6 mo following TKA.Investigated factors en-compassed patient characteristics,surgical characteristics,and preoperative patient-reported outcomes.RESULTS TKA patients[n=2063;66 years old(interquartile range[IQR]:7 years);47%male;28 kg/m2(IQR:4 kg/m2)]showed RTA ranging from 28%for kneeling to 94%for grocery shopping,with 20 d(IQR:27 d)spent for putting on shoes to 74 d(IQR:57 d)for kneeling.RTW rates varied from 62%for medium-impact work to 87%for low-impact work,taking 33 d(IQR:29 d)to 78 d(IQR:55 d).RTS ranged from 48%for medium-impact sports to 90%for low-impact sports,occurring within 43 d(IQR:24 d)to 90 d(IQR:60 d).One or more of the investigated factors influenced the return to each of the 14 activities examined,with R²values ranging from 0.013 to 0.127.CONCLUSION Approximately 80%of patients can RTA,RTW,and RTS within 6 mo after TKA.Return is not consistently in-fluenced by predictive factors.Results help set realistic pre-and postoperative expectations.

“liberal arts”的源与流——古今之变中的审视

“古今之变”是审视liberal arts流变的中心线索。古典liberal arts是具有内在统一性并指向完满品格的整全性知识体系。欧洲三次文艺复兴对liberal arts的再造展现了其历史流变中的不变逻辑,即为特定时代的受教育者提供共同价值。德国古典大学赋予了liberal arts在古典意义上的完美形态,而新人文主义的自我塑造观念孕育了博雅教育的现代转向。科学革命终结了古典学术的内在统一性与道德理想,瓦解了古典liberal arts。美国现代大学则借助古典资源,经由三次改革浪潮重建了liberal arts。然而,古典教育凝聚文明精华的共同价值、塑造意义与学术整合力量,同现代科学的智识自由、价值分殊与学科分化特性相冲突,这是古今之变为现代大学再造liberal arts所深植的困境,liberal arts只能在钟摆的两端之间不断权衡。

医护-社会组织一体化模式对HIV/AIDS患者ART及自我管理能力的影响

探究接受高效抗反转录病毒治疗确诊HIV/AIDS患者接受医护-社会组织一体化模式干预价值。方法 从2022年1月至2022年12月南昌市某定点医院接受抗病毒治疗及随访管理的新确诊HIV/AIDS患者100例,50例接受传统医护合作模式对照组、50例接受医护-社会组织一体化模式观察组,两组各项临床指标差异进行分析对比(从HIV抗体初筛阳性到启动ART治疗时间、抗病毒治疗一年后HIV病毒载量的指标及病毒抑制率、抗病毒治疗一年后自我管理能力)。结果 干预后与对照组比较,观察组HIV抗体初筛阳性到启动ART治疗时间显著偏低,HIV病毒载量指标水平显著偏低,病毒抑制率显著偏高,一年后自我管理能力评分显著偏高,用药依从性显著偏高(P<0.05)。结论 接受抗病毒治疗及随访管理的确诊HIV/AIDS患者接受医护-社会组织一体化模式干预后,可显著提高患者自我管理能力。此外,还能保障高病毒抑制率,缩短患者治疗时间,提升患者用药依从性。

UAV-assisted data collection for wireless sensor networks with dynamic working modes

Wireless Sensor Network(WSN)is a cornerstone of Internet of Things(IoT)and has rich application scenarios.In this work,we consider a heterogeneous WSN whose sensor nodes have a diversity in their Residual Energy(RE).In this work,to protect the sensor nodes with low RE,we investigate dynamic working modes for sensor nodes which are determined by their RE and an introduced energy threshold.Besides,we employ an Unmanned Aerial Vehicle(UAV)to collect the stored data from the heterogeneous WSN.We aim to jointly optimize the cluster head selection,energy threshold and sensor nodes’working mode to minimize the weighted sum of energy con-sumption from the WSN and UAV,subject to the data collection rate constraint.To this end,we propose an efficient search method to search for an optimal energy threshold,and develop a penalty-based successive convex approximation algorithm to select the cluster heads.Then we present a low-complexity iterative approach to solve the joint optimization problem and discuss the implementation procedure.Numerical results justify that our proposed approach is able to reduce the energy consumption of the sensor nodes with low RE significantly and also saves energy for the whole WSN.

Flow characteristics and hot workability of a typical low-alloy high-strength steel during multi-pass deformation

Heavy components of low-alloy high-strength(LAHS) steels are generally formed by multi-pass forging. It is necessary to explore the flow characteristics and hot workability of LAHS steels during the multi-pass forging process, which is beneficial to the formulation of actual processing parameters. In the study, the multi-pass hot compression experiments of a typical LAHS steel are carried out at a wide range of deformation temperatures and strain rates. It is found that the work hardening rate of the experimental material depends on deformation parameters and deformation passes, which is ascribed to the impacts of static and dynamic softening behaviors. A new model is established to describe the flow characteristics at various deformation passes. Compared to the classical Arrhenius model and modified Zerilli and Armstrong model, the newly proposed model shows higher prediction accuracy with a confidence level of 0.98565. Furthermore, the connection between power dissipation efficiency(PDE) and deformation parameters is revealed by analyzing the microstructures. The PDE cannot be utilized to reflect the efficiency of energy dissipation for microstructure evolution during the entire deformation process, but only to assess the efficiency of energy dissipation for microstructure evolution in a specific deformation parameter state.As a result, an integrated processing map is proposed to better study the hot workability of the LAHS steel, which considers the effects of instability factor(IF), PDE, and distribution and size of grains. The optimized processing parameters for the multi-pass deformation process are the deformation parameters of 1223–1318 K and 0.01–0.08 s^(-1). Complete dynamic recrystallization occurs within the optimized processing parameters with an average grain size of 18.36–42.3 μm. This study will guide the optimization of the forging process of heavy components.

Teamwork Optimization with Deep Learning Based Fall Detection for IoT-Enabled Smart Healthcare System

The current advancement in cloud computing,Artificial Intelligence(AI),and the Internet of Things(IoT)transformed the traditional healthcare system into smart healthcare.Healthcare services could be enhanced by incorporating key techniques like AI and IoT.The convergence of AI and IoT provides distinct opportunities in the medical field.Fall is regarded as a primary cause of death or post-traumatic complication for the ageing population.Therefore,earlier detection of older person falls in smart homes is required to improve the survival rate of an individual or provide the necessary support.Lately,the emergence of IoT,AI,smartphones,wearables,and so on making it possible to design fall detection(FD)systems for smart home care.This article introduces a new Teamwork Optimization with Deep Learning based Fall Detection for IoT Enabled Smart Healthcare Systems(TWODLFDSHS).The TWODL-FDSHS technique’s goal is to detect fall events for a smart healthcare system.Initially,the presented TWODL-FDSHS technique exploits IoT devices for the data collection process.Next,the TWODLFDSHS technique applies the TWO with Capsule Network(CapsNet)model for feature extraction.At last,a deep random vector functional link network(DRVFLN)with an Adam optimizer is exploited for fall event detection.A wide range of simulations took place to exhibit the enhanced performance of the presentedTWODL-FDSHS technique.The experimental outcomes stated the enhancements of the TWODL-FDSHS method over other models with increased accuracy of 98.30%on the URFD dataset.

基于ART的集装箱运输防损策略优化探究

本论文结合人工智能运输机器人在港口应用的案例,从问题现象入手,分析急停可能导致的损失,通过对ART急停原因分析,制定出急停改缓停的解决方案,结果显示缓停策略大大地降低了ART急停概率,可为其他自动化集装箱码头水平运输作业或使用自动化车辆的工程项目提供借鉴。

CAFIU Vice-President Xu Li's Art Works Collection Exhibition "Shining Hong Kong" Held in Hong Kong

On December 19,2023,Exhibition"Shining Hong Kong-Xu Li's Art Works Collection"was grandly opened at the Hong Kong Convention and Exhibition Centre.This exhibition displays more than 80 oil paintings and Chinese paintings by Mr.Xu Li.

Formulation of Work-Study Combined and Result-Oriented Integrated Curriculum Standards

According to the Annex Technical Regulations for Integrated Curriculum Development(Trial)in Document No.30 of the General Office of the Ministry of Human Resources and Social Security(2012),this paper studies the formulation of the curriculum standards for the integration of Chinese medicinal materials production.We focus on the formulation ideas of the curriculum standards for the integration of Chinese medicinal materials production,the formulation process of the curriculum standards for the integration of Chinese medicinal materials production,including the description of typical work tasks,the determination of curriculum objectives,the analysis of study content,the description of referential study tasks,teaching implementation suggestions,assessment and evaluation suggestions,which can provide a reference for the development and research of other related integrated courses.

Application of Modern Construction Art in Landscape Architecture Planning and Design

The continuous progress of urbanization has driven the continuous development and innovation of landscape planning and design.Focused on the important design method of modern construction art,this study analyzed its concepts and characteristics,and made deep exploration to its application in landscape planning and design.The results indicated that modern construction art had a significant impact on landscape spatial planning and layout,spatial design forms,and spatial ornaments.The use of modern construction art concepts could make landscape design more scientific,artistic,and humane,creating higher quality leisure and entertainment venues for audiences.

A Discussion of Artificial Intelligence in Visual Art Education

Since ChatGPT emerged on November 30, 2022, Artificial Intelligence (AI) has been increasingly discussed as a radical force that will change our world. People have become used to AI in which such ubiquitous technologies as Siri, Google, and Netflix deploy AI algorithms to answer questions, impart information, and provide recommendations. However, many individuals including originators and backers of AI have recently expressed grave concerns. In this paper, the authors will assess what is occurring with AI in Visual Arts Education, outline positives and negatives, and provide recommendations addressed specifically for teachers working in the field regarding emerging AI usage from kindergarten to grade twelve levels as well as in higher education.

Design and optimization of fluid lubricated bearings operated with extreme working performances——a comprehensive review

Fluid lubricated bearings have been widely adopted as support components for high-end equipment in metrology,semiconductor devices,aviation,strategic defense,ultraprecision manufacturing,medical treatment,and power generation.In all these applications,the equipment must deliver extreme working performances such as ultraprecise movement,ultrahigh rotation speed,ultraheavy bearing loads,ultrahigh environmental temperatures,strong radiation resistance,and high vacuum operation,which have challenged the design and optimization of reliable fluid lubricated bearings.Breakthrough of any related bottlenecks will promote the development course of high-end equipment.To promote the advancement of high-end equipment,this paper reviews the design and optimization of fluid lubricated bearings operated at typical extreme working performances,targeting the realization of extreme working performances,current challenges and solutions,underlying deficiencies,and promising developmental directions.This paper can guide the selection of suitable fluid lubricated bearings and optimize their structures to meet their required working performances.

Exploring the Factors Associated with 12-Month Non-Return to Work among Motorcyclists Involved in Road Accidents

Introduction: Motorcyclists bear a disproportionate burden of morbidity and mortality from road accidents. In addition, the consequences of these accidents affect the ability of victims to return to work. This study aimed to determine the prevalence and factors associated with non-return to work among surviving motorcyclists involved in road accidents 12 months after the event. Materials and Methods: It was a cross-sectional study conducted using data from a cohort of motorcyclists involved in accidents and recruited in five hospitals in Benin from July 2019 to January 2020. The dependent variable was non-return to work 12 months after the accident (yes vs no). The independent variables were categorized into two groups: baseline and 12-month follow-up variables. Logistic regression was used to determine the factors associated with non-return to work at 12 months among the participants. Results: Among the 362 participants, 55 (15.19%, 95% CI = 11.84 - 19.29) had not returned to work 12 months after the accident. Risk factors for non-return to work identified were: smoking (aOR = 4.41, 95% CI = 1.44 - 13.56, p = 0.010), hospitalization (aOR = 2.87, 95% CI = 1.14 - 7.24, p Conclusion: The prevalence of non-return to work at 12 months was high among surviving motorcyclists involved in road accidents in Benin. Integrated support for patients based on identified risk factors should effectively improve their return to work.

A Review on Technologies for the Use of CO2 as a Working Fluid in Refrigeration and Power Cycles

The use of carbon dioxide as a working fluid has been the subject of extensive studies in recent years, particularly in the field of refrigeration where it is at the heart of research to replace CFC and HCFC. Its thermodynamic properties make it a fluid of choice in the efficient use of energy at low and medium temperatures in engine cycles. However, the performance of transcritical CO2 cycles weakens under high temperature and pressure conditions, especially in refrigeration systems;On the other hand, this disadvantage becomes rather interesting in engine cycles where CO2 can be used as an alternative to the organic working fluid in small and medium-sized electrical systems for low quality or waste heat sources. In order to improve the performance of systems operating with CO2 in the field of refrigeration and electricity production, research has made it possible to develop several concepts, of which this article deals with a review of the state of the art, followed by analyzes in-depth and critical of the various developments to the most recent modifications in these fields. Detailed discussions on the performance and technical characteristics of the different evolutions are also highlighted as well as the factors affecting the overall performance of the systems studied. Finally, perspectives on the future development of the use of CO2 in these different cycles are presented.

Relationship between physical activity and specific working memory indicators of depressive symptoms in university students

BACKGROUND The detection rate of depression among university students has been increasing in recent years,becoming one of the main psychological diseases that endangers their physical and mental health.According to statistics,self-harm and suicide,for which there is no effective intervention,are the second leading causes of death.AIM To explore the relationship between different elements and levels of physical activity and college students’depression-symptom-specific working memory indicators.METHODS Of 143 college students were analyzed using the Beck Depression Self-Rating Scale,the Physical Activity Rating Scale,and the Working Memory Task.RESULTS There was a significant difference between college students with depressive symptoms and healthy college students in completing verbal and spatial working memory(SWM)tasks correctly(all P<0.01).Physical Activity Scale-3 scores were significantly and positively correlated with the correct rate of the verbal working memory task(r=0.166)and the correct rate of the SWM task(r=0.210)(all P<0.05).There were significant differences in the correct rates of verbal and SWM tasks according to different exercise intensities(all P<0.05)and different exercise durations(all P<0.05),and no significant differences in the correct rates of verbal and SWM tasks by exercise frequency(all P>0.05).CONCLUSION An increase in physical exercise among college students,particularly medium-and high-intensity exercise and exercise of 30 min or more,can improve the correct rate of completing working memory tasks.

Use of cognitive-behavioral career coaching to reduce work anxiety and depression in public employees

BACKGROUND Public employees worldwide are increasingly concerned about work anxiety and depression.Cognitive-behavioral career coaching has emerged as a promising strategy for addressing these mental health disorders,which can negatively impact on a person's overall well-being and performance.AIM To examine whether cognitive-behavioral career coaching reduces work anxiety and depression among Nigerian public employees.METHODS A total of 120 public employees(n=60)suffering from severe anxiety and depression were randomly assigned to the treatment or control groups in this study.Cognitive behavioral coaching was provided twice a week to those in the treatment group,whereas no treatment was given to those in the control group.As part of the study,the Hamilton Anxiety Rating Scales and Beck Depression Inventory were used to collect data.RESULTS Analysis of covariance of the data from participants indicates a significant effect of cognitive-behavioral career coaching on work anxiety and depression.CONCLUSION Insights into the underlying mechanisms by which cognitive behavior career coaching exerts its effects have been gained from this study.Also,the study has gathered valuable data that can inform future practice and guide the development of strategies for supporting mental health at work.

Working condition recognition of sucker rod pumping system based on 4-segment time-frequency signature matrix and deep learning

High-precision and real-time diagnosis of sucker rod pumping system(SRPS)is important for quickly mastering oil well operations.Deep learning-based method for classifying the dynamometer card(DC)of oil wells is an efficient diagnosis method.However,the input of the DC as a two-dimensional image into the deep learning framework suffers from low feature utilization and high computational effort.Additionally,different SRPSs in an oil field have various system parameters,and the same SRPS generates different DCs at different moments.Thus,there is heterogeneity in field data,which can dramatically impair the diagnostic accuracy.To solve the above problems,a working condition recognition method based on 4-segment time-frequency signature matrix(4S-TFSM)and deep learning is presented in this paper.First,the 4-segment time-frequency signature(4S-TFS)method that can reduce the computing power requirements is proposed for feature extraction of DC data.Subsequently,the 4S-TFSM is constructed by relative normalization and matrix calculation to synthesize the features of multiple data and solve the problem of data heterogeneity.Finally,a convolutional neural network(CNN),one of the deep learning frameworks,is used to determine the functioning conditions based on the 4S-TFSM.Experiments on field data verify that the proposed diagnostic method based on 4S-TFSM and CNN(4S-TFSM-CNN)can significantly improve the accuracy of working condition recognition with lower computational cost.To the best of our knowledge,this is the first work to discuss the effect of data heterogeneity on the working condition recognition performance of SRPS.

Positive Effect of Transcranial Direct Current Stimulation on Visual Verbal Working Memory in Patients with Attention-Deficit/Hyperactivity Disorder

Background: Working memory is an executive function that plays an important role in many aspects of daily life, and its impairment in patients with attention-deficit/hyperactivity disorder (ADHD) affects quality of life. The dorsolateral prefrontal cortex (DLPFC) has been a good target site for transcranial direct current stimulation (tDCS) due to its intense involvement in working memory. In our 2018 study, tDCS improved visual-verbal working memory in healthy subjects. Objective: This study examines the effects of tDCS on ADHD patients, particularly on verbal working memory. Methods: We conducted an experiment involving verbal working memory of two modalities, visual and auditory, and a sustained attention task that could affect working memory in 9 ADHD patients. Active or sham tDCS was applied to the left DLPFC in a single-blind crossover design. Results: tDCS significantly improved the accuracy of visual-verbal working memory. In contrast, tDCS did not affect auditory-verbal working memory and sustained attention. Conclusion: tDCS to the left DLPFC improved visual-verbal working memory in ADHD patients, with important implications for potential ADHD treatments.

Application of Midjournal and Stable Diffusion in Environmental Art and Design Courses in Higher Education Institutions

This study was aimed to explore the feasibility of introducing two mainstream AI drawing applications,Midjournal and Stable Diffusion,into the environmental art and design courses in higher education institutions.On the basis of introducing the development history of AI drawing technology,the characteristics of Midjournal and Stable Diffusion and their applications in teaching were described in detail.The analysis on its practical application in public space design courses showed that AI drawing technology could significantly improve students’creative efficiency and the possibility of artistic creation,while also enriching the expressive power of design.In spite of the challenges such as technical accuracy,response to complex design requirements,hardware dependencies,and student dependencies,the application of AI drawing technology had an overall positive prospects in the field of education.Finally,the value of AI drawing technology in teaching was emphasized,and the challenges it brought were discussed,as well as how to fully utilize this technology while maintaining teaching objectives and educational principles.

Determinants of Satisfaction at Work and Its Reflections on Performance

This study examines the relationship between job satisfaction and performance,investigating personality traits and satisfaction aspects among employees of a Federal Higher Education Institution.A questionnaire was administered to 658 participants,using structural equation modeling for analysis.Results highlighted that challenging work,neuroticism,and self-esteem significantly influenced overall workplace satisfaction,while general satisfaction,self-efficacy,and lack of attention were key determinants of work performance.This emphasizes the importance for managers to prioritize factors enhancing employee satisfaction,as it positively correlates with job performance.