High Level Of Performance Research Articles

Sports and diabetes - limitations resulting from the disease in people engaging in sports

Diabetes mellitus is a chronic condition that significantly impacts various aspects of daily life, including physical activity and sports participation. This article explores the limitations imposed by diabetes on individuals engaged in sports, examining both type 1 and type 2 diabetes. It discusses how the disease affects physical performance, endurance, and recovery, and highlights the need for careful management of blood glucose levels before, during, and after exercise. The potential risks of hypoglycemia and complications like diabetic neuropathy are addressed, alongside strategies for mitigating these risks through personalized exercise regimens, dietary adjustments, and continuous monitoring. Despite these challenges, the article emphasizes that with proper management and awareness, individuals with diabetes can safely engage in various forms of physical activity, often achieving high levels of performance. The discussion aims to provide athletes, coaches, and healthcare providers with insights into optimizing sports participation for diabetic individuals, promoting both safety and success in athletic endeavors.

Enhanced Immunohistochemistry Interpretation with a Machine Learning-Based Expert System.

In recent decades, machine-learning (ML) technologies have advanced the management of high-dimensional and complex cancer data by developing reliable and user-friendly automated diagnostic tools for clinical applications. Immunohistochemistry (IHC) is an essential staining method that enables the identification of cellular origins by analyzing the expression of specific antigens within tissue samples. The aim of this study was to identify a model that could predict histopathological diagnoses based on specific immunohistochemical markers. The XGBoost learning model was applied, where the input variable (target variable) was the histopathological diagnosis and the predictors (independent variables influencing the target variable) were the immunohistochemical markers. Our study demonstrated a precision rate of 85.97% within the dataset, indicating a high level of performance and suggesting that the model is generally reliable in producing accurate predictions. This study demonstrated the feasibility and clinical efficacy of utilizing the probabilistic decision tree algorithm to differentiate tumor diagnoses according to immunohistochemistry profiles.

A novel method for fully penetrated U-rib-to-deck joints: Single-sided oscillating laser arc hybrid welding

U-rib-to-deck (RTD) joints represent one of the most critical and vulnerable welding details of orthotropic steel decks. Aiming for full penetration and high-level service performance, a novel method with single-sided oscillating laser-arc hybrid welding (OLAHW) technique was proposed for the RTD joint. The weld formation, microstructure and mechanical properties were extensively investigated. The results indicated that the porosity and lack of fusion (LoF) defects effectively suppressed with the beam oscillation during LAHW process. The OLAHW technique has good spatial accessibility with larger laser beam incidence angle of 20° Beam oscillation led to an increase in acicular ferrite in the fusion zone (FZ) while simultaneously a reduction of martensite in the heat effected zone (HAZ). This was related to the cooling time, and the thermal simulation results revealed that the OLAHW sample demonstrated comparable cooling times in both the Laser-FZ and arc-FZ. Consequently, beam oscillation can generated more homogeneous microstructures and microhardness. Although the microhardness of the OLAHW sample in the FZ was increased compared to the conventional arc welding (CAW) and LAHW sample, the highest microhardness value remained within acceptable limits (380 HV). Moreover, the ultimate tensile strength of the OLAHW weld sample increased by 7 % compared to the CAW weld sample. The application of the OLAHW technique demonstrates its feasibility for engineering applications in orthotropic steel decks manufacturing.

Analysing tie-break performance of professional tennis players at Grand Slam matches

ABSTRACT A tiebreak in tennis is one of the critical moments where players are expected to excel under mental pressure and maintain high level of performance. Despite the importance of tiebreak points, research exploring the performance of male and female players during such match phrase remains limited. This study aimed to investigate i) the overall tiebreak performance of male and female players in relation to the outcome, ii) to examine their point-level performance by considering different contextual variables. A total of 535 tiebreaks comprising 6380 points from the 2016–2021 US Open men’s and women’s singles matches were collected. The difference in match performance between winning and losing players within the entire tiebreak game was explored. A subsequent decision tree analysis was then used to analyse the effect of the contextual and performance variables on tiebreak point-by-point outcome. The results showed that male and female Winning players outperformed the Losing players in 1st Serve, Serve Width and Net approach performance. The analysis of point-level performance showed that Net point, Score scene, and Point server substantially impacted tennis players’ tiebreak outcome. These findings provide valuable insight for coaches and players, informing tiebreak tactics tailoring and training in relevance to different match status.

Improving the switching behavior of TaOx/HfO2-based non-volatile memristors by embedded Ti and Pt nano-islands

To investigate the effects of embedded metal nano-island (NI) arrays on reducing the variations of the device switching parameters, we fabricated Pt/HfO2/TiN, Pt/TaOx/HfO2/TiN devices, as well as devices with embedded NI arrays, including Pt/TaOx/HfO2/Pt NI/TiN and Pt/TaOx/HfO2/Ti NI/TiN devices. Compared to devices without nano-islands, the Pt/TaOx/HfO2/Pt NI/TiN devices with abrupt resistive switching behavior exhibit more stable resistance states (coefficient of variations (CVs) of RHRS and RLRS are 11.9 % and 13.0 %, respectively), and a large on/off ratio (>103), representing a high performance level among the HfO2-based non-volatile memristors reported to date, but the devices require a Forming process. The Pt/TaOx/HfO2/Ti NI/TiN devices with analog resistive switching behavior show low operating voltage (≤1 V), low resistance variations (CVs of RHRS, and RLRS are 15.8 %, and 17.6 %, respectively), but their on/off ratio (<10) is significantly reduced. The results indicate that embedding metal nano-island arrays decreases the fluctuations in device switching parameters, the different properties of nano-island materials significantly affect the abrupt/analog switching behavior, on/off ratio and the Forming of the non-volatile memristors. The methods employed in this study can be extended or evolved for other memristors to enhance their performance and applicability.

Auditory System Injury on the Battlefield-Solutions for Point-of-Injury and Prolonged Casualty Care: A DOTmLPF-P Analysis.

"Good hearing" (DoDI 6030.03 6.5&6.6) is a combat multiplier, critical to service members' lethality and survivability on the battlefield. Exposure to an explosive blast or high-intensity continuous noise is common in operational settings with the potential to compromise both hearing and vestibular health and jeopardize safety and high-level mission performance. The Joint Trauma System Acoustic Trauma Clinical Practice Guideline was published in 2018, providing recommendations for the assessment and treatment of aural blast injuries and acoustic trauma in the forward deployed environment. Combat care capabilities responsive to current threat environments emphasize prolonged casualty care. Despite recommendations, auditory system health has not been assessed routinely or in its entirety on the battlefield. This is due primarily to the large footprint of an audiometric booth and to the heavy logistical burden of providing high-quality, comprehensive auditory system (including vestibular) examinations in the combat environment. The Defense Health Agency Hearing Center of Excellence has completed a Doctrine, Organization, Training, Materiel, Leadership & Education, Personnel, Facilities, and Policy (DOTmLPF-P) analysis of battlefield auditory system assessment and treatment, using 67 existing DoD documents and artifacts related to operational medicine. Our analysis found that acoustic trauma is generally not addressed in any of the DOTmLPF-P domains. We recommend that auditory system assessment and treatment be incorporated across the continuum of care on the battlefield. This should be addressed through Prolonged Field Care and Tactical Combat Casualty Care guidance and in all Tactical Combat Casualty Care training programs. Equipment sets should be modified to include boothless technology and associated materiel for auditory system assessment. Policy and Doctrine changes would be required to mandate and support the implementation of these services. Uniformed audiologists should be added to the organizational structure at role 3 or higher to provide direct patient care; consult with other health care providers and commanders; develop and support enforcement of noise hazard guidelines; track hearing readiness; and, when necessary, provide specialized hearing protection devices that can compensate for hearing loss. These recommendations aim to help the DoD bring about necessary assessments and interventions for acoustic trauma so that service members can have better hearing outcomes and maintain critical auditory system function on the battlefield.

A configurational analysis of university ranking, cognitive ability and cultural intelligence in global virtual teams: The role of academic pedigree

Previous research examining the GVTs with business students from different universities and with different characteristics has begun to reveal significant findings on team compositions leading to team performance. However, few studies have addressed academic pedigree at the team level and examined its relationship with team performance. This study explores the configurations of academic pedigree, cognitive ability (IQ), and cultural intelligence (CQ) that lead to high levels of performance in GVTs. We performed a fuzzy-set Qualitative Comparative Analysis on a sample of 3688 students nested within 731 GVTs participating in an international project. The results show that three configurations could achieve the same outcome equally and effectively. In particular, two configurations show that IQ and CQ within teams led to high team performance when either the academic pedigree average or the academic pedigree diversity is not high. The third configuration reveals that IQ combined with academic pedigree average and the presence of a team member from a highly ranked institution results in high levels of team performance when academic pedigree diversity is not high. This study offers insights into configurational relationships between team compositions and performance in GVTs, explaining when and if academic pedigree impacts team performance.

Investigating Students’ Perceived Satisfaction and Performance in Online Class: Basis for Online Learning Improvements

The landscape of education has experienced significant changes as a result of the global COVID-19 pandemic. Central to the recent developments is the increasing concerns related to the levels of student satisfaction and performance in Mathematics within the context of online learning. This study seeks to fill the gaps in existing research literature on how mathematics is taught online during the pandemic. In particular, the goal of this research was to investigate the relationship between students' perceived satisfaction and reported academic performance in a Mathematics online class and suggest important satisfaction factors to improve student online learning experiences. The study was a descriptive research design utilizing mixed methods, and the data were collected from a volunteer sample of ???? = 153 respondents, composed of senior high school students from three private schools, through an adapted online survey instrument. Results showed that the association between satisfaction and performance was significant and positively correlated. Furthermore, there was a low but positive significant correlation between satisfaction with their performance. Regardless of their performance levels, students were generally satisfied with online learning. Students, however, pointed out three (3) additional factors that affect their satisfaction – flexible and considerate task management, effective communication and subject mastery in teaching; and accessibility and clarity of educational resources. To improve online learning, these additional factors are essential to have a high level of satisfaction and performance in online learning.

High Prevalence of Varus Knee Malalignment in Adolescent Football Players-Clinical Lower Leg Axis Measurements of Male Junior Football Players Aged 7 to 18 Years.

Football, as the most popular sport worldwide, has long been under suspicion of causing varus knee alignment as early as adolescence. However, no causal relationship has yet been found. The first step to do so would be to determine the prevalence of lower leg malalignment among male junior football players depending on age, performance level and the number of active seasons played. Leg axis alignment in frontal plane was determined in male junior football players of different age levels between 7 and 18 years by measuring the intercondylar/intermalleolar distance (ICD/IMD) in an upright position. In addition to anthropometric data, multiple sport-specific data such as the start of their football career or training time per week were collected by means of questionnaires (clinical trial registration number: DRKS00020446). 207 male junior football players were included in this survey. The mean age was 12.8 years. Within the group of 15 to 18 year olds, the prevalence of varus knee malalignment was highest at just under a third (32.1%). In the subpopulation that played actively for more than ten seasons, 28.9% showed varus leg axis. Regarding performance level, the highest IMD/ICD values and highest prevalence of varus alignment were found among football players who play on a semi-professional level (16.7%), compared to amateur (11.4%) and high-performance levels (2.8%). Further research is necessary to investigate if this high prevalence of varus knee in children of a higher age and higher playing levels is due to the selection bias of football players with varus knee or a real development of varus knee in individuals.

The importance of positive employee experience and its development through using predictive analytics

Purpose The study aims to explore the organizational benefits of positive employee experience and to provide a framework for measuring it. The positive employee experience has a profound impact on employees’ attitudes; thus, it is particularly important to what extent an organization can create the conditions supporting this. Design/methodology/approach The study is based on literature review and the framework needs to be empirically tested to draw final conclusions. Findings Organizational performance and success are influenced by employees’ well-being, commitment, job satisfaction and the high level of individual performance. However, this grouping of variables is not exhaustive, but in practice, it is often not necessary to fully understand the complex and complicated relationships among the organizational variables. However, a positive employee experience has an impact on all of these variables. According to our understanding and experience, the task of management is not to strengthen the variables describing employee attitudes individually, based on the knowledge of specific relations presented in the management literature and selected for the sake of a single research, but to create an acceptable level of the positive employee experience, which is able to strengthen these variables in a way that is useful for the organization. Originality/value In this study, the authors introduce the concept of the positive employee experience and the ways and steps to measure it. The authors review the methodology of predictive analytics, the main principles of data collection and the types of data with their possible applications. Finally, the limitations of the framework and the risks of enhancing the positive employee experience are also discussed.

High-level performances following low altitude training and tapering in warm environments in elite racewalkers.

Current guidelines for prolonged altitude exposure suggest altitude levels ranging from 2000 to 2500m to optimize an increase in total hemoglobin mass (Hbmass). However, natural low altitude locations (<2000m) remain popular, highlighting the interest to investigate any possible benefit of low altitude camps for endurance athletes. Ten elite racewalkers (4 women and 6 men) underwent a 4-week "live high-train high" (LHTH) camp at an altitude of 1720m (PIO2=121mmHg; 20.1°C; 67% relative humidity [RH]), followed by a 3-week tapering phase (20m; PIO2=150mmHg; 28.3°C; 53% RH) in preparation for the World Athletics Championships (WC). Venous blood samples were withdrawn weekly during the entire observation period. In addition, blood volumes were determined weekly by carbon monoxide rebreathing during altitude exposure and 2weeks after return to sea level. High-level performances were achieved at the WC (five placings among the Top 10 WC races and three all-time career personal bests). A slight but significant increase in absolute (+1.7%, p=0.03) and relative Hbmass (+2.3%, p=0.02) was observed after 4-week LHTH. In addition, as usually observed during LHTH protocols, weekly training distance (+28%, p=0.02) and duration (+30%, p=0.04) significantly increased during altitude compared to the pre-LHTH period. Therefore, although direct causation cannot be inferred, these results suggest that the combination of increased training load at low altitudes with a subsequent tapering period in a warm environment is a suitable competition-preparation strategy for elite endurance athletes.

Job satisfaction and performance among employed Bangladeshi women working from home during COVID-19 pandemic: A cross-sectional study.

The emergence of the COVID-19 pandemic led to the adoption of telework modalities by individuals in Bangladesh. The study's objective was to determine the job satisfaction and performance level of employed Bangladeshi women working from home during the COVID-19 pandemic lockdown. A cross-sectional study was conducted among women employees of different professions in Dhaka city. The Minnesota Satisfaction Questionnaire (MSQ) was used to measure job satisfaction. Work arrangement satisfaction and self-reported performance were measured by two separate subscales which contain five items each. Responses from 118 employed women were analyzed using descriptive statistics, Pearson Chi-square tests, Independent t-tests, one-way analysis of variance, and Pearson Correlation tests through the Statistical Package for Social Science (SPSS), version 26. The findings indicated that 51.7% of women reported a high degree of satisfaction on the MSQ scale; 61.9% expressed high satisfaction with their work arrangements at home and 66.9% reported a high level of performance. Job satisfaction was significantly associated with the number of children and the number of family members. A positive association was found between job satisfaction and total working experience and work arrangements. Work performance was strongly associated with higher educational qualifications. A statistically significant association between job satisfaction and performance was revealed. The findings from this study indicated a high degree of job satisfaction and a high level of performance found in women employees who worked from home during the COVID-19 pandemic. These findings encourage organizations to foster more policies for telework alternatives for employed women to help them keep a balance between work responsibilities and household chores.

TDSQL: Tencent Distributed Database System

Distributed databases have become indispensable in contemporary computing and data processing, owing to their pivotal role in ensuring high availability and scalability. They effectively cater to the requirements of data management and high-concurrency access. However, developing a distributed database system that is well-suited for diverse application scenarios, particularly for large-scale applications, presents several challenges. These challenges include ensuring data consistency and achieving high levels of performance. This paper presents TDSQL, a distributed database system that prioritizes core design principles of distributed systems, including high availability, strong consistency, and scalability. In particular, TDSQL has achieved high performance through over a decade of practical experience and optimization in various modules, such as the kernel, synchronous replication, and transaction processing, in large-scale application scenarios. By conducting the TPC-C benchmark test, TDSQL demonstrated outstanding performance, achieving a throughput of 814 million tpmC across 1650 database nodes, with a jitter rate of less than 0.2%. This jitter rate is an order of magnitude lower than the standard required, showcasing the system's stability and reliability. During the 8-hour TPC-C standard stress test, TDSQL successfully completed over 860 billion transactions and processed 40 trillion order details, with zero forced rollbacks and zero data inconsistency.

Nodule Detection and Generation on Chest X-Rays: NODE21 Challenge.

Pulmonary nodules may be an early manifestation of lung cancer, the leading cause of cancer-related deaths among both men and women. Numerous studies have established that deep learning methods can yield high-performance levels in the detection of lung nodules in chest X-rays. However, the lack of gold-standard public datasets slows down the progression of the research and prevents benchmarking of methods for this task. To address this, we organized a public research challenge, NODE21, aimed at the detection and generation of lung nodules in chest X-rays. While the detection track assesses state-of-the-art nodule detection systems, the generation track determines the utility of nodule generation algorithms to augment training data and hence improve the performance of the detection systems. This paper summarizes the results of the NODE21 challenge and performs extensive additional experiments to examine the impact of the synthetically generated nodule training images on the detection algorithm performance.

Unified control of diverse actions in a wastewater treatment activated sludge system using reinforcement learning for multi-objective optimization

The operation of modern wastewater treatment facilities is a balancing act in which a multitude of variables are controlled to achieve a wide range of objectives, many of which are conflicting. This is especially true within secondary activated sludge systems, where significant research and industry effort has been devoted to advance control optimization strategies, both domain-driven and data-driven. Among data-driven control strategies, reinforcement learning (RL) stands out for its ability to achieve better than human performance in complex environments. While RL has been applied to activated sludge process optimization in existing literature, these applications are typically limited in scope, and never for the control of more than three actions. Expanding the scope of RL control has the potential to increase the optimization potential while concurrently reducing the number of control systems that must be tuned and maintained by operations staff. This study examined several facets of the implementation of multi-action, multi-objective RL agents, namely how many actions a single agent could successfully control and what extent of environment data was necessary to train such agents. This study observed improved control optimization with increasing action scope, though control of waste activated sludge remains a challenge. Furthermore, agents were able to maintain a high level of performance under decreased observation scope, up to a point. When compared to baseline control of the Benchmark Simulation Model No. 1 (BSM1), an RL agent controlling seven individual actions improved the average BSM1 performance metric by 8.3 %, equivalent to an annual cost savings of $40,200 after accounting for the cost of additional sensors.

Teacher’s Feedback on Students Motivation and Academic Engagement

This study aimed to explore the effects of teacher’s feedback on students’ motivation and academic engagement of Grade 12-TVL (Home Economics) students of Baguio City National Science High School, Baguio City, Philippines. Specifically, the study answered the following queries: 1) Level of performance of the learners before the use of the teacher’s feedback; 2)Level of performance of the learners after the use of the teacher’s feedback; and 3) To determine if there is significant difference in the performance of the learners before and after the use of the teacher’s feedback. This study made use of the Descriptive-Quantitative Research Design with documentary analysis using the students’ grades in their 3rd Quarter Report Card before the use of the teacher’s feedback and their grades in the 4th Quarter after the use of the teacher’s feedback. The following are the findings of the study: 1) The average grade of the learners before the use of the teacher’s feedback is 87.08 interpreted as “Very Satisfactory”; 2) The level of performance of the learners after the use of the teacher’s feedback is 90.76 interpreted as “Outstanding”, 3) The computed t of 3.066 is much higher than the critical value of t=1.687, df-37 at 0.05 level of significance. This shows that there is significant difference in the performance of the learners before and after the use of the teacher’s feedback. The following conclusions are hereby made based on the findings of the study: 1) The learners demonstrated a high level of performance before the use of the teacher’s feedback; 2) The learners exhibited a much higher performance after the use of the teacher’s feedback; and 3) The teacher’s feedback had a very high impact on the level of performance of the learners.

Firm-level climate risk and accounting conservatism: International evidence

We examine the impact of climate-risk exposure on accounting conservatism, and document a significant positive association. Utilizing a firm-level climate-exposure measure (CRI) for a large international sample covering 46 countries from 2002 to 2021, we find that firms facing climate risk tend to adopt more conservative reporting practices. This effect is notably stronger during pivotal periods of climate awareness, such as that around the Paris Climate Agreement, and in jurisdictions governed by common law. Our results remain valid under a series of robustness tests and after addressing endogeneity concerns. Further analyses indicate that this positive association is more pronounced in well-governed firms and in firms with high levels of environmental and social performance, but less pronounced in firms with high degrees of complexity and information asymmetry. Additional tests reveal that firms in environmentally sensitive industries and those operating in developed countries adopt more conservative reporting than counterparts in non-environmentally sensitive industries or in developing countries. Our final analysis suggests that regulatory risks have a greater effect on accounting conservatism than physical risks. Our paper contributes to the ongoing discourse on climate change, documenting the ‘bright side’ of firms' exposure to climate risk.

High Neural Efficiency in Unconscious Perceptual Processing among Table Tennis Athletes: An Event-Related Potential Study.

Neural efficiency refers to the brain's ability to function with reduced resource expenditure while maintaining high performance levels. Previous research has demonstrated that table tennis athletes have greater neural efficiency at the conscious level. However, it is unknown whether they exhibit greater neural efficiency at the unconscious level. Therefore, this study aims to investigate unconscious perceptual processing and neural efficiency in elite table tennis athletes through tasks involving the judgment of spin serves. Fifty healthy, right-handed individuals participated in this study, including 25 elite table tennis athletes and 25 control participants without professional training experience. To evaluate the unconscious perceptual characteristics of both groups, we used a combination of masked priming paradigm and event-related potential techniques. The behavioral results reveal that, compared to the control group, the table tennis athletes displayed reduced reaction times (p < 0.001) and increased priming effects (p < 0.001) under unconscious conditions. The electrophysiological findings indicated that both groups elicited N1, N2, and P2 components. Notably, compared to the control group, the table tennis athletes exhibited significantly lower amplitude responses at the occipital lobe electrodes PO3, POz, PO4, O1, Oz, and O2 (p < 0.001). These results further support the neural efficiency hypothesis, indicating that prolonged professional training enhances athletes' capacities for specialized unconscious cognitive processing.

Effect of Heat Treatment on Chemical Plating of Ni-Cr-P on 65Mn Alloy Steel

The chemical plating of Ni-Cr-P significantly affects the improvement of the structure and characteristics of the metal surface. This study aimed to investigate the impact of various plating solution components and process parameters on the deposition rate and surface hardness of Ni-Cr-P coatings on 65Mn alloy steel. Additionally, the study examined the changes in coating properties resulting from different heat treatment temperatures. The specimens coated with Ni-Cr-P underwent heat treatment at temperatures of 180°C, 200°C, 220°C, and 240°C, respectively. The testing results indicate that the plating layer achieves its highest level of performance when subjected to a heat treatment temperature of 200°C. The heat-treated coating exhibits superior wear and corrosion resistance compared to the 65Mn steel substrate. Additionally, the coefficient of friction decreases from 0.5 to 0.4. The self-corrosion potential shifts positively from -569 mV to -389 mV, and the corrosion current decreases from 61.4 μA to 14.48 μA. Furthermore, the impedance improves from 234 Ω·cm2 to 3512 Ω·cm2.

Distributed and Multi-Agent Reinforcement Learning Framework for Optimal Electric Vehicle Charging Scheduling

The increasing number of electric vehicles (EVs) necessitates the installation of more charging stations. The challenge of managing these grid-connected charging stations leads to a multi-objective optimal control problem where station profitability, user preferences, grid requirements and stability should be optimized. However, it is challenging to determine the optimal charging/discharging EV schedule, since the controller should exploit fluctuations in the electricity prices, available renewable resources and available stored energy of other vehicles and cope with the uncertainty of EV arrival/departure scheduling. In addition, the growing number of connected vehicles results in a complex state and action vectors, making it difficult for centralized and single-agent controllers to handle the problem. In this paper, we propose a novel Multi-Agent and distributed Reinforcement Learning (MARL) framework that tackles the challenges mentioned above, producing controllers that achieve high performance levels under diverse conditions. In the proposed distributed framework, each charging spot makes its own charging/discharging decisions toward a cumulative cost reduction without sharing any type of private information, such as the arrival/departure time of a vehicle and its state of charge, addressing the problem of cost minimization and user satisfaction. The framework significantly improves the scalability and sample efficiency of the underlying Deep Deterministic Policy Gradient (DDPG) algorithm. Extensive numerical studies and simulations demonstrate the efficacy of the proposed approach compared with Rule-Based Controllers (RBCs) and well-established, state-of-the-art centralized RL (Reinforcement Learning) algorithms, offering performance improvements of up to 25% and 20% in reducing the energy cost and increasing user satisfaction, respectively.