Accelerated design of high-performance Mg-Mn-based magnesium alloys based on novel bayesian optimization

Magnesium(Mg),being the lightest structural metal,holds immense potential for widespread applications in various fields.The development of high-performance and cost-effective Mg alloys is crucial to further advancing their commercial utilization.With the rapid advancement of machine learning(ML)technology in recent years,the“data-driven''approach for alloy design has provided new perspectives and opportunities for enhancing the performance of Mg alloys.This paper introduces a novel regression-based Bayesian optimization active learning model(RBOALM)for the development of high-performance Mg-Mn-based wrought alloys.RBOALM employs active learning to automatically explore optimal alloy compositions and process parameters within predefined ranges,facilitating the discovery of superior alloy combinations.This model further integrates pre-established regression models as surrogate functions in Bayesian optimization,significantly enhancing the precision of the design process.Leveraging RBOALM,several new high-performance alloys have been successfully designed and prepared.Notably,after mechanical property testing of the designed alloys,the Mg-2.1Zn-2.0Mn-0.5Sn-0.1Ca alloy demonstrates exceptional mechanical properties,including an ultimate tensile strength of 406 MPa,a yield strength of 287 MPa,and a 23%fracture elongation.Furthermore,the Mg-2.7Mn-0.5Al-0.1Ca alloy exhibits an ultimate tensile strength of 211 MPa,coupled with a remarkable 41%fracture elongation.

Optimization Techniques for GPU-Based Parallel Programming Models in High-Performance

This study embarks on a comprehensive examination of optimization techniques within GPU-based parallel programming models,pivotal for advancing high-performance computing(HPC).Emphasizing the transition of GPUs from graphic-centric processors to versatile computing units,it delves into the nuanced optimization of memory access,thread management,algorithmic design,and data structures.These optimizations are critical for exploiting the parallel processing capabilities of GPUs,addressingboth the theoretical frameworks and practical implementations.By integrating advanced strategies such as memory coalescing,dynamic scheduling,and parallel algorithmic transformations,this research aims to significantly elevate computational efficiency and throughput.The findings underscore the potential of optimized GPU programming to revolutionize computational tasks across various domains,highlighting a pathway towards achieving unparalleled processing power and efficiency in HPC environments.The paper not only contributes to the academic discourse on GPU optimization but also provides actionable insights for developers,fostering advancements in computational sciences and technology.

Expansion Performance and Microstructure of High-performance Concrete using Differently Scaled MgO Agents and Mineral Powder

To investigate the assumptions proposed in this paper,the evolution law governing the strength and expansion performance of MgO and nano-MgO micro-expansive concrete in the environment of mineral powder was firstly observed in this study.Secondly,SEM,XRD,and TG-DSC microscopic tests were conducted to reveal the effects of the active mineral-powder admixture on the hydration degree and expansion performance of MgO and nano-MgO in HPC.Our experimental results successfully verified our hypothesis,which indicated that the expansion performance of macro-MgO and nano-MgO was indeed depressed by the addition of active mineral power admixtures,even though the mechanical property of concrete composites was effectively improved.Furthermore,the hydration test also demonstrated the negative interference on the mineral powders,which was induced by the expansion agents.It is found the amounts of hydrates tend to decrease because the mineral powder ratio reaches and exceeds 40%.Moreover,it is also concluded the effect of expansion agents is governed by the alkalinity cement paste,especially for the nano-MgO.In other words,the expansion performance of nano-MgO will vary more obviously with the hydration process,than MgO.The results of this study provide that effective experimental and theoretical data support the hydration-inhibition mechanism of magnesium expansive agents.

Latest progresses and the application of various electrolytes in high-performance solid-state lithium-sulfur batteries

With the emergence of some solid electrolytes(SSEs)with high ionic conductivity being comparable to liquid electrolytes,solid-state lithium-sulfur batteries(SSLSBs)have been widely regarded as one of the most promising candidates for the next generation of power generation energy storage batteries,and have been extensively researched.Though many fundamental and technological issues still need to be resolved to develop commercially viable technologies,SSLSBs using SSEs are expected to address the present limitations and achieve high energy and power density while improving safety,which is very attractive to large-scale energy storage systems.SSLSBs have been developed for many years.However,there are few systematic discussions related to the working mechanism of action of various electrolytes in SSLSBs and the defects and the corresponding solutions of various electrolytes.To fill this gap,it is very meaningful to review the recent progress of SSEs in SSLSBs.In this review,we comprehensively investigate and summarize the application of SSEs in LSBs to determine the differences which still exist between current progresses and real-world requirements,and comprehensively describe the mechanism of action of SSLSBs,including lithium-ion transport,interfacial contact,and catalytic conversion mechanisms.More importantly,the selection of solid electrolyte materials and the novel design of structures are reviewed and the properties of various SSEs are elucidated.Finally,the prospects and possible future research directions of SSLSBs including designing high electronic/ionic conductivity for cathodes,optimizing electrolytes and developing novel electrolytes with excellent properties,improving electrode/-electrolyte interface stability and enhancing interfacial dynamics between electrolyte and anode,using more advanced test equipment and characterization techniques to analyze conduction mechanism of Li^(+)in SSEs are presented.It is hoped that this review can arouse people’s attention and enlighten the development of functional materials and novel structures of SSEs in the next step.

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.

In teg rati ng organizati on al lear ning with high-performance work system and entrepreneurial orientation: a moderated mediation framework

This study proposes a moderated mediation model to investigate the relationship between organizational learning and firm performance. We argue that entrepreneurial orientation mediates the positive effect of organizational learning on firm performance. Furthermore, the relationship between organizational learning and entrepreneurial orientation is strengthened when firms employ a higher level of high-performance work system. Hypotheses are supported by data from 181 firms operating in the manufacturing and service industries in China. Statistical results further reveal that a high-performance work system has different moderating effects on exploitative learning and exploratory learning. This research extends our understanding of organizational learning theory, entrepreneurship and human resource management literature by cross-fertilizing constructs in these fields with empirical evidence.

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.

High-performance Liquid Chromatographic Determination of Urinary Trans,Trans-Muconic Acid Excreted by Workers Occupationally Exposed to Benzene

Objective To investigate the relationship between trans, trans-muconic acid （ttMA） as benzene metabolite of occupational workers and benzene concentration in air. Methods A rapid and sensitive high-performance liquid chromatography was developed to determine the level of urinary ttMA. ttMA was extrated from urinary samples in liquid-liquid phase a ODS （2） （5u） column （Ф4.6 min× 150 mm） and detected at wavelength 264 nm in a UV detector using vanillic acid as an internal standard. The mobile phase was acetaticacid/tetrahydrofuran/methanol/water （v/v, 1：2：10：87）. The method was validated with 56 urine samples collected from occupationally benzene-exposed individuals. Results A correlation coefficient （r = 0.9963 ） was found for ttMA ranging 0.10-10.00 μg/mL. The limit of detection was 0.10μ g/mL. The recovery and reproducibility were generally over 90%. There was a positive correlation between ttMA and benzene level in air. The equation was Y=0.859＋0.108C （before work, r=0.6200） or Y=1.980＋0.179C （after work, r=0.7930）. Conclusion This method can be used to determine and control the level of urinary ttMA in those who are occupationally exposed to benzene.

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.

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.

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.

The action mechanism of the work done by the electric field force on moving charges to stimulate the emergence of carrier generation/recombination in a PN junction

It is discovered that the product of the current and the electric field in a PN junction should be regarded as the rate of work(power)done by the electric field force on moving charges(hole current and electron current),which was previously misinterpreted as solely a Joule heating effect.We clarify that it is exactly the work done by the electric field force on the moving charges to stimulate the emergence of non-equilibrium carriers,which triggers the novel physical phenomena.As regards to Joule heat,we point out that it should be calculated from Ohm’s law,rather than simply from the product of the current and the electric field.Based on this understanding,we conduct thorough discussion on the role of the electric field force in the process of carrier recombination and carrier generation.The thermal effects of carrier recombination and carrier generation followed are incorporated into the thermal equation of energy.The present study shows that the exothermic effect of carrier recombination leads to a temperature rise at the PN interface,while the endothermic effect of carrier generation causes a temperature reduction at the interface.These two opposite effects cause opposite heat flow directions in the PN junction under forward and backward bias voltages,highlighting the significance of managing device heating phenomena in design considerations.Therefore,this study possesses referential significance for the design and tuning on the performance of piezotronic devices.

The Impact of the Digital Economy on Rural Residents’Working Hours:Mechanisms and Empirical Evidence

The rapid development of the digital economy has provided a new impetus for rural residents to extend their working hours.Based on the data collected by the China Labor-force Dynamics Survey(CLDS)in 2014,2016,and 2018,this paper measured the development level of the digital economy in China from the perspectives of internet development and digital financial inclusion,and tested the mechanisms of how the digital economy affected rural residents’working hours.The results showed that the digital economy extended rural residents’working hours by expanding information channels and enhancing human capital,and this mechanism was affected by heterogeneity in rural residents’educational background,age,and social capital.Building on these findings,this paper holds that to increase rural residents’income by extending their working hours and achieving common prosperity for all,it is necessary to expand the opportunities for rural residents to participate in skills training and promote their accumulation of human capital.

Work Ability Index and Work Ability Score: A Comparation between both Scores in a Persistent COVID-19 Cohort

Aims: The present study aims to compare the assessment of work ability based on the use of the Work Ability Index (WAI) with another questionnaire base only on the use of WAI’s first item, termed as the “Work Ability Score” (WAS). Study design: A cohort of 384 Spanish workers included in a Post COVID-19 condition or persistent COVID-19 multicenter research was utilized. Place and Duration of Study: This cohort was enlisted in four hospitals (Hospital Universitario 12 de Octubre, Madrid;Hospital Universitario Virgen Macarena, Sevilla, Andalucía;Hospital Universitario Gregorio Marañón, Madrid and Complejo Asistencial Universitario de Salamanca, Castilla y León), since 2021 until 2022. Methodology: 384 Spanish workers (176 men and 208 women;aged 20 to 70 years) with Post COVID-19 condition or persistent COVID-19 were included. Descriptive analysis of primary scores was conducted. Given the non-normal distribution of data, the Mann-Whitney and Kruskal-Wallis tests were employed. Spearman and Kendall correlations were employed to assess the relationship between WAI and WAS, also used weighted Kappa to estimate the degree agreement between WAI and WAS. Logistic regression models were utilized to study determinants influencing WAI and WAS, categorized as poor or moderate. Results: WAI had an average score of 32.98 (SD = 10.28), whereas WAS had an average of 5.95 (SD = 2.77). Significant differences were observed in both WAI and WAS across the same variables. Strong and statistically significant correlations were evident between WAI and WAS (rs = 0.83, p < 0.001). All the variables used in the logistic regression model (gender, the sector employment, and previous chronic diseases) were statistically significant in both questionnaires. Conclusion: WAS questionnaire could be used as a tool for reliable assessment of work ability among Spanish workers with Post COVID-19 condition or Persistent CO-VID-19.

Correlation of work function and stacking fault energy through Kelvin probe force microscopy and nanohardness in diluteα-magnesium

Electronic interactions of the Group 2A elements with magnesium have been studied through the dilute solid solutions in binary Mg-Ca,Mg-Sr and Mg-Ba systems.This investigation incorporated the difference in the‘Work Function'(ΔWF)measured via Kelvin Probe Force Microscopy(KPFM),as a property directly affected by interatomic bond types,i.e.the electronic structure,nanoindentation measurements,and Stacking Fault Energy values reported in the literature.It was shown that the nano-hardness of the solid-solutionα-Mg phase changed in the order of Mg-Ca>Mg-Sr>Mg-Ba.Thus,it was shown,by also considering the nano-hardness levels,that SFE of a solid-solution is closely correlated with its‘Work Function'level.Nano-hardness measurements on the eutectics andΔWF difference between eutectic phases enabled an assessment of the relative bond strength and the pertinent electronic structures of the eutectics in the three alloys.Correlation withΔWF and at least qualitative verification of those computed SFE values with some experimental measurement techniques were considered important as those computational methods are based on zero Kelvin degree,relatively simple atomic models and a number of assumptions.As asserted by this investigation,if the results of measurement techniques can be qualitatively correlated with those of the computational methods,it can be possible to evaluate the electronic structures in alloys,starting from binary systems,going to ternary and then multi-elemental systems.Our investigation has shown that such a qualitative correlation is possible.After all,the SFE values are not treated as absolute values but rather become essential in comparative investigations when assessing the influences of alloying elements at a fundamental level,that is,free electron density distributions.Our study indicated that the principles of‘electronic metallurgy'in developing multi-elemental alloy systems can be followed via practical experimental methods,i.e.ΔWF measurements using KPFM and nanoindentation.

Profile of Factors of Arduous Work among Healthcare Professionals in Healthcare Facilities in Northern Benin in 2021

Introduction: Work environments create the basis for arduous nursing work. This is what led us to research the factors of arduousness in the exercise of the health profession in North Benin, through this study. Methods: This is a cross-sectional and descriptive study which focused on health professionals in the health zones of Parakou-N’dali and Tchaourou. The sampling was an exhaustive census. All health workers who had given their free and informed consent were included. The data was collected using a questionnaire. The variables studied were the factors of arduous work and socio-professional characteristics. The data collected was processed and analyzed with the Epi info 7.2.0.1 software. Results: A total of 692 were surveyed, the participation rate was 85.11% and the sex ratio (M/F) equal to 0.7. The average age was 38 years old. Nurses made up 32.66% of the sample. They were 86.42% subject to night work and 82.66% to alternating work. Overall, 70.23% worked more than 40 hours per week. Between 78.12% and 96.46% of non-specialist doctors, nurses, midwives and biomedical analysis technicians were required to work night shifts. Nurses, midwives, radiology and laboratory technicians were between 89.53% and 97.35%, organized in alternating work. In the sample, 55.20% complained about the insufficient number of work materials, 26.29% handled harmful chemical substances. Among those surveyed, 58.14% had been attacked. Conclusion: All professional categories of caregivers are subject to arduous work. Measures are needed to reverse the situation.

High-performance Si-Containing anode materials in lithium-ion batteries: A superstructure of Si@Co-NC composite works effectively

To mitigate the massive volume expansion of Si-based anode during the charge/discharge cycles,we synthesized a superstructure of Si@Co±NC composite via the carbonization of zeolite imidazolate frameworks incorporated with Si nanoparticles.The Si@Co±NC is comprised of Sinanoparticle core and N-doped/Co-incorporated carbon shell,and there is void space between the core and the shell.When using as anode material for LIBs,Si@Co±NC displayed a super performance with a charge/discharge capacity of 191.6/191.4 mA h g^(-1)and a coulombic efficiency of 100.1%at 1000 mA g^(-1)after 3000 cycles,and the capacity loss rate is 0.022%per cycle only.The excellent electrochemical property of Si@Co±NC is because its electronic conductivity is enhanced by doping the carbon shell with N atoms and by incorporating with Co particles,and the pathway of lithium ions transmission is shortened by the hollow structure and abundant mesopores in the carbon shell.Also,the volume expansion of Si nanoparticles is well accommodated in the void space and suppressed by the carbon host matrix.This work shows that,through designing a superstructure for the anode materials,we can synergistically reduce the work function and introduce the confinement effect,thus significantly enhancing the anode materials’electrochemical performance in LIBs.