French academies almost all implement reactivity drills and small-sided games (SSG) the day preceding a match (MD-1). The present study aimed to determine the physical impact of different training durations on MD-1 on the subsequent matchday performance (MD). Eleven elite U19 academy soccer players con-ducted three typical training sessions lasting 45min (TS45), 60min (TS60), and 75min (TS75) on MD-1. Dur-ing TS60, warm-up, reactivity and SSG were 10, 15, and 24min, respectively, plus coaches' feedback or wa-ter breaks. Durations decreased and increased by 25% for TS45 and TS75, respectively. Tests were con-ducted on MD-4 (CONTROL) and MD before the match (TEST). Tests consisted of a counter movement jump (CMJ), 20m sprint, Illinois agility test (IAT), and Hooper questionnaire. CONTROL values were simi-lar over the three experimental conditions. TEST on MD revealed greater CMJ for TS45 (42.7 ± 5.1cm) compared to TS60 (40.5 ± 5.5cm, p=0.032) and TS75 (40.9 ± 5.7cm, p=0.037). 20m time was lower for TS45 (3.07 ± 0.10s, p<0.001) and TS60 (3.13 ± 0.10s, p=0.017) compared to TS75 (3.20 ± 0.10s). IAT time was lower on TS45 (14.82 ± 0.49s) compared to TS60 (15.43 ± 0.29s, p<0.001) and TS75 (15.24 ± 0.33s, p=0.006). Further-more, the Hooper index was lower at TEST for TS45 (7.64 ± 1.50) compared to TS60 (11.00 ± 3.49, p=0.014) and TS75 (9.73 ± 2.41, p=0.045) indicating a better readiness level. We concluded that as training session duration increases, performance decreases on MD. A 45min training session including reactivity and SSG exercises is therefore recommended on MD-1.

The primary attraction of IaaS is providing elastic resources on demand. It becomes imperative that IaaS-users have an effective methodology for learning what resources they require, how many resources and for how long they need. However, the heterogeneity of resources, the diversity resource demands of different cloud applications and the variation of application-user behaviors pose IaaS-users big challenge. In this paper, we purpose a unified resource demand forecasting model suiting for different applications, various resources and diverse time-varying workload patterns. With the model, taking input from parameterized applications, resources and workload scenarios, the corresponding resources demands during any time interval can be deduced as output. The experiments configure concrete functions and parameters to help understanding the above model.

The mental workload induced by a Web page is essential for improving the user’s browsing experience. However, continuously assessing the mental workload during a browsing task is challenging. In order to face this issue, this paper leverages the correlation between stimuli and physiological responses, which are measured with high-frequency, non-invasive psychophysiological sensors during very short span windows. An experiment was conducted to identify levels of mental workload through the analysis of pupil dilation measured by an eye-tracking sensor. In addition, a method was developed to classify real-time mental workload by appropriately combining different signals (electrodermal activity (EDA), electrocardiogram, photoplethysmography (PPG), electroencephalogram (EEG), temperature and eye gaze) obtained with non-invasive psychophysiological sensors. The results show that the Web browsing task involves on average four levels of mental workload. Also, by combining EEG with the PPG and EDA, the accuracy of the classification reaches 95.73 %.

This study analyzed the levels of mental workload and the presence of burnout on a sample of fashion retailing workers from Spain and its relationship with the actual Covid-19 pandemic by exploring Covid-19 pandemic predictors of burnout and mental workload. We established a prospective cross-sectional design. Participants (n = 360) answered an online survey including questions about sociodemographic data, perception of Covid-19, CarMen-Q questionnaire (workload), and MBI (burnout syndrome). We obtained data throughout October-November 2020. The results showed that participants exhibit deep concern about the Covid-19 pandemic and its influence at the work level. Although the mental workload was near the middle point of the scale, participants showed moderate to high burnout levels, revealing that the sample is at risk of experiencing higher burnout levels over time as the pandemic and associated economic crisis continue. The multidimensional regression analysis results indicated that environmental changes, work overload, somatic symptoms, insomnia, negative job expectations, and uncertainty constituted significant mental workload predictors. Insomnia, somatic symptoms, and negative job expectations constituted significant predictors for burnout. In conclusion, the uncertainty at work derived from the Covid-19 pandemic is harming the psychological wellbeing of fashion retailing workers in Spain.

The effect of stress on task performance is complex, too much or too little negatively affects performance; and there exists an optimal level of stress to drive optimal performance. Task difficulty and external affective factors are distinct stressors that impact cognitive performance. Neuroimaging studies showed that mood affects working memory performance and the correlates are changes in haemodynamic activity in the prefrontal cortex (PFC). We investigate the interactive effects of affective states and working memory load (WML) on working memory task performance and haemodynamic activity using functional near-infrared spectroscopy (fNIRS) neuroimaging on the PFC of healthy participants. We seek to understand if haemodynamic responses could tell apart workload related stress from situational stress arising from external affective distraction. We found that the haemodynamic changes towards affective stressor and workload related stress were more dominant in the medial and lateral PFC respectively. Our study reveals distinct affective state-dependent modulations of haemodynamic activity with increasing WML in n-back tasks, which correlate with decreasing performance. The influence of negative affect on performance is greater at higher WML, and haemodynamic activity showed evident changes in temporal, and both spatial and strength of activation differently with WML.

This study employed a deductive research approach and a survey strategy to assess risk perception and its influencing factors among construction workers in Malawi. Three specific construction hazards and their associated risks were selected. The hazards were ‘working at height (WAH) ‘manual handling of loads (MHL)’ and ‘heavy workload or intense pressure to be more productive (HWP)’. The study engaged multistage sampling of 376 subjects. Univariate analysis, factor analysis and multiple linear regressions were performed in order to determine the main influencing factors among the independent variables. The study established that workers were aware of risks posed by their work. They perceived the risk associated with WAH, MHL and HWP as very high (62.7%, = 8.80 ± 1.95); (48.5%, = 8.10 ± 2.38); (57.9%, = 8.49 ± 2.22) respectively. The study identified six factors as variables that showed significant effect on workers’ perception of risk (p < 0.05). These factors were “dreaded factor”, “avoidability and controllability”, “expert knowledge”, “personal knowledge”, education level and age. It is concluded that contractors in the Malawian construction industry should integrate analysis of behaviors and risk perception of the workers and other players to guide the identification of better health and safety interventions at their worksites.

Despite the rapid adoption of bilingual programs (English-Chinese) in China's higher education institutions (HEIs), concerns have been raised on perceived language hindrance to students’ academic comprehension and then performance. In response to this, this paper investigates the effects of bilingual instruction on content-based learning and provides empirical evidence after testing related influential factors in bilingual environment. Analyzing a sample of 498 undergraduate students enrolling in a fundamental business course in a sample university in China, we find insignificant statistical difference in students' academic performance between bilingual and L1 classes. We attribute this to the English language support provided by the university and show that learning competence can help students to minimize language barrier and furthermore solve the common learning problems confronted by both bilingual and L1 students. Overall, our paper aims to identify key determinants of students' academic performance in bilingual instruction and provide policy implication for developing desirable bilingual programs in HEIs.

Background: Tele-emergency physicians (TEPs) take an increasingly important role in the need-oriented provision of emergency patient care. To improve emergency medicine in rural areas, we set up the project Land|Rettung (English: Rural|Rescue), which uses TEPs to restructure professional rescue services using information and communication technologies (ICTs) in order to reduce the therapy-free interval. Successful implementation of ICTs relies on user acceptance and knowledge sharing behavior. Methods and findings: We conducted a factorial design with active knowledge transfer and technology acceptance as a function of work satisfaction (high vs. low), workload (high vs. low) and point in time (prior to vs. after digitalization). Data were collected via machine readable questionnaires issued to 755 persons (411 pre, 344 post), of which 304 or 40.3% of these persons responded (194 pre, 115 post).Technology acceptance was higher after the implementation of TEP for nurses but not for other professional groups, and it was higher when the workload was high. Regarding active communication and knowledge sharing, employees with low work satisfaction are more likely to share their digital knowledge as compared to employees with high work satisfaction. Additional and more detailed analyses reveal that this is an effect of previous knowledge concerning digitalization. After implementing the new technology, work satisfaction increased for the more experienced employees, but not for the less experienced ones. Results are discussed considering the Dunning-Kruger effect. The Dunning-Kruger effect describes a cognitive bias. People with high expertise often underestimate their actual skill level. They have a more critical attitude towards their performance and feel the urgent need to fill possible knowledge gaps they notice. Conclusions: Our research illustrates that employees’ workload has an impact on the intention of using digital applications. The higher the workload, the more people are willing to use TEPs. Regarding active knowledge sharing, we see that employees with low work satisfaction are more likely to share their digital knowledge compared to employees with high work satisfaction. This might be attributed to the Dunning-Kruger effect. Highly knowledgeable employees initially feel uncertain about the change, which translates into temporarily lower work satisfaction. They feel the urge to fill even small knowledge gaps, which in return leads to higher work satisfaction. Those responsible need to acknowledge that digital change affects their employees’ workflow and work satisfaction. During such times, employees need time and support to gather information and knowledge in order to cope with digitally changed tasks.

Workloads may be classified as either internal or external. Internal workloads (heart rate, blood lactate, session rate of perceived exertion (sRPE) are categorised as the individual’s response to an external workload (volume, intensity). sRPE is an easily monitored variable which has been shown to have possible associations with other internal (1) and injury rates (2, 3) in contact sports. This case study describes the internal workload monitoring of a schoolboy rugby player during the entirety of his season (September to March) with the subsequent relationships between workload and time loss injuries being explored. Time loss injuries are defined as injuries which caused the individual to miss training or match play time (4). Acute to chronic workload ratio (ACWR) and exponentially weighted moving average (EWMA) were monitored, a novel ACWR:EWMA ratio was also calculated. High ACWR and low EWMA values were associated with injury occurrence, the ACWR:EWMA ratio may account for this. EWMA may be a better predictor of “time loss” injuries than ACWR. The ACWR:EWMA ratio may merit further scientific exploration in the future.

Building on the job demands-resources (JD-R) and the allostatic load (AL) models, in this study we investigated the role of smart working (SW) in the longitudinal association between workload/job autonomy (JA) and a possible biomarker of work-related stress (WRS) in the hair, namely the cortisol to dehydroepiandrosterone sulphate (DHEA(S)) ratio, during the COVID-19 pandemic. Overall, 124 workers completed a self-report questionnaire (i.e., psychological data) at Time 1 (T1) and collected a strand of hair (i.e., biological data) three months later (Time 2, T2). Results from moderated multiple regression analysis showed that smart working at T1 was negatively associated with hair cortisol/DHEA(S) ratio at T2. Additionally, the interaction between workload and SW was significant, with workload at T1 being positively associated with hair cortisol/DHEA(S) ratio at T2 among smart workers. Overall, this study indicates that SW can be conceived as a double-edged sword, with both positive and negative consequences on employee well-being. Furthermore, our findings suggest that hair cortisol/DHEA(S) ratio is a promising biomarker of WRS. Practical implications that organizations and practitioners can adopt to promote organizational well-being are discussed.

Background: At altitudes beyond 2500 m the risk of developing high altitude pulmonary edema (HAPE) grows with the increases in pulmonary arterial pressure. HAPE is characterized by severe pulmonary hypertension, though the incidence and relevance of individual risk factors are not yet predictable. However, the systolic pulmonary pressure (SPAP) and peak in tricuspid regurgitation velocity (TVR) are crucial factors when diagnosing pulmonary hypertension by echocardiography. Methods: The SPAP and TVR of 27 trekkers aged 20-65 years en route in the Solu Khumbu region of Nepal was assessed. Echocardiograph measurements were performed at Lukla (2,860 m), Gorak Shep (5170 m), and the summit of Kala Patthar (5,675 m). The altitude profile and the participant’s characteristics were also compiled for correlation with the measured data. Results: The results showed a highly significant increase of SPAP and TVR after ascending Kala Patthar. The study revealed a lower increase of SPAP and TVR in the group of older participants, although the initial respective measurements in Gorak Shep were significantly higher for this group. A similar finding occurred in those using Diamox® as prophylaxis. There was an inverse relationship between TVR and SPAP, the peripheral capillary oxygen saturation and heart rate. Conclusions: The echocardiograph results indicate that older people are a risk group for developing a HAPE. The prophylactic use of acetazolamid led to higher initial SPAP values in Gorak Shep, and a lower increase of SPAP as well as TRV after ascending Kala Patthar. Arterial oxygen saturation measurements can provide an indicator for the self-assessment for the risk of developing HAPE and provide a rule of thumb for the altitude profile but does not replace a HAPE diagnosis. The collected data variables concerning backpack weight, sex, workload (actual ascent speed), and pre-existing diseases were not statistically significant factors related to SPAP and TVR (p=<0.05).

Drivers of L3 automated vehicles (AVs) are not required to continuously monitor the AV system. However, they must be prepared to take over when requested. Therefore, it is necessary to design an in-vehicle environment that allows drivers to adapt their levels of preparedness to the likelihood of control transition. This study evaluates ambient in-vehicle lighting that continuously communicates the current level of AV reliability, specifically on how it could influence drivers' take-over performance and mental workload (MW). We conducted an experiment in a driving simulator with 42 participants who experienced 10 take-over requests (TORs). The experimental group experienced a four-stage ambient light display that communicated the current level of AV reliability, which was not provided to the control group. The experimental group demonstrated better take-over performance, based on lower vehicle jerks. Notably, perceived MW did not differ between the groups, and the EEG indices of MW (frontal theta power, parietal alpha power, Task-Load Index) did not differ between the groups. These findings suggest that communicating the current level of reliability using ambient light might help drivers be better prepared for TORs and perform better without increasing their MW.

Introduction. The main task of the study was to measure the workload of nurses in the care of a patient with a developmental defect–congenital diaphragmatic hernia (CDH)–in the neonatal intensive care unit, which was evaluated on the basis of standardized tools Therapeutic Intervention Scoring System (TISS–28), Nine Equivalents of Nursing Manpower use Score (NEMS) and Nursing activities Score (NAS). Methods. Retrospective study. The workload was measured using TISS–28, NEMS and NAS tools. Descriptive statistics were used to analyze the data, and a single-sample test was used to verify the research hypotheses. Results. The sample consisted of medical records of 33 patients; 592 observations were analyzed. Studies prove the need for research on the workload of nurses in neonatal intensive care units. A patient with CDH should receive nursing care as required. Conclusion. It is necessary to implement a model for measuring the workload of nurses in neonatal intensive care units, taking into account the evaluation of work and its optimization.

Nurses’ caring behaviors are affected by several determinants. The aim of this study was to explore the factors affecting nurses’ caring behaviors. Nurses (N=309) from three public general hospitals in Greece completed the Factors of Nurses’ Caring Behaviors Scale. The data analysis was carried out with the Statistical Package for the Social Sciences (SPSS), version 26.0. Demographic and occupational data were, also, recorded. The statistical significance level was set at &lt;0.05. The total mean score on the FNCB Scale was 100.4 (SD±26). The dimensions of Workplace Circumstances (Mean: 24.6, SD±8.0) and Workload/Management (Mean: 24.5, SD±6.4) were the most important factors of caring behaviors. On the opposite, nurses perceived the dimensions of Patients’ Demographic Characteristics (Mean: 9.3, SD± 4.4) and Patients’ Clinical Characteristics (Mean: 12.5 SD±4.2) as the least important factors. Men scored higher than women in the dimension of Patients’ Demographic Characteristics (t=3.022, p=0.003). Secondary Education Graduates scored lower in the dimensions of Workplace Circumstances (Tukey, p=0.035) and Workload/Management (Tukey, p=0.033) than MSc/Ph.D. Graduates. Nurses of surgical departments scored lower in total score than ICU nurses (Tukey, p = 0.026). Workplace conditions, workload, and management seem to be the most important factors in nurses’ caring behaviors.

Transportation tasks in nursing are common and shorten the time for direct patient care in times of nursing shortage and an aging society. There is a lack of research on transportation needs, with most studies focusing on overall nursing task analysis without a deeper analysis of transportation tasks. In July and September 2023, we conducted weekly observations of nurses to assess clinical transportation needs. We aim to understand the economic impact and the methods nurses use for transportation tasks. We conducted a participant observation using a standardized app-based form over a seven-day observation period in two rural clinics. N=1,830 transports were made by nurses and examined by descriptive analysis. Non-medical supplies account for 27.05 % (n=495) of all transports, followed by medical supplies at 17.32 % (n=317), pharmacotherapy at 14.10 % (n=258) and other other categories like meals or drinks contributing 12.68 % (n=232). Most transports had a factual transport time of under a minute, with patient transport and lab samples displaying more variability. In total, 77.15 % of all transports were made by hand. Requirements to collect items or connect transports with patient care were included in 5 % of all transports. Our economic evaluation spotlighted meals as the most costly transport, with 9,596.16€ p.a. in the observed clinics. Budget-friendly robots would amortize over one year by transporting meals. We support understanding nurses’ transportation needs via further research on assistive robots to validate our findings and determine the feasibility of transport robots.

The objective of this study was to analyze the mental workload using EEG and eye tracking data and classify it using machine learning algorithms. The machine learning model was developed based on the simultaneous recording of eye tracking and EEG measurements during the experimental process. The experiments involved 15 university students, consisting of 7 women and 8 men. Throughout the experiments, the researchers utilized the n-back memory task and the NASA-Task Load Index (TLX) subjective rating scale to assess various levels of mental workload. The findings revealed that as the task difficulty increased, there was an increase in the diameter of both the right and left pupils, the number of fixations, the number and duration of saccades, and the number and duration of blinks. Conversely, variables related to fixation duration decreased. The EEG results indicated that theta power in the prefrontal, frontal, and front central regions increased with task difficulty. Additionally, alpha power increased in the frontal regions but decreased in the temporal, parietal, and occipital regions as the task became more challenging. Furthermore, low beta power significantly decreased in almost all brain regions as the task difficulty increased. In terms of the four-class classification problem, the mental workload level can be predicted with an accuracy rate of 76.59% using 34 selected features. This study has made a significant contribution to the literature by presenting a four-class mental workload estimation model that utilizes different machine learning algorithms.

With the rapid development of the Internet of Things, massive amounts of data will be generated at the network edge, resulting in increased latency of the traditional cloud computing model. Cloud service providers deploy edge servers near the users to improve the quality of service. Due to the large scale of networks, the inefficiency of edge server deployment and task scheduling will result in excessive latency and severe workload imbalance among edge servers. In this paper, we propose a Server Deployment and Task Scheduling (SDTS) framework in multi-edge collaborative computing, which can effectively reduce latency and ensure workload balancing. First, a metropolitan area network (MAN) is divided into dense candidate regions (DCRs) based on the density characteristics of mobile end devices, and then servers are deployed independently in each sub-region. Then, a two-step clustering algorithm is designed to deploy servers as close as possible to the mobile devices. Finally, a task scheduling algorithm is presented based on an edge scheduling layer in DCRs, which can leverage collaboration between edge servers to improve the performance of the entire edge computing system. The experimental results based on the Cellular Base Station (CBS) dataset of Shanghai Telecom indicate that the proposed approach outperforms several representative strategies in terms of latency and workload balancing.

The aim of the work was to carry out an ergonomic assessment of the workload when working with a chainsaw during motor-manual tree processing. Wearable technology was used, namely Garmin, Biostrap and Whoop devices, which are generally available. The dependence of the heart rate (HR) on physical workload was examined to calculate Heart Rate Index. The case study was done with one worker, three variations of chainsaw devices cutting the poplar wood. It was proved that the use of a heavier work tool, MS 500i /90 cm 9,3 kg, significantly contributes both to the creation of a non-physiological working position and to an increase in the energy required to perform work, which was represented by an increase in heart rate. With a lighter work tool and a shorter cutting blade, both a decrease in heart rate and a reduction in the working time were performed in a non-physiological position. The results can be used in common practice for workers´ self-assessment to increase safety and health protection at work or work productivity not only in motor-manual processing in forestry related professions.

The purpose of the research was to examine and assess the relation between the pilot’s concentration and reaction time with specific brain activity during short-haul flights. In order to obtain this task, participants took part in 1-hour long flight sessions performed on FNPT II class flight simulator. During the flight auto–pilot was activated and subjects were instructed to give response to unexpected events that were occurring during the flight. Brainwaves of each participant were recorded with Emotiv EPOC+ Scientific Contextual EEG device. Statistical analyses of the results were presented in the article.

Background The workload of nurses in the intensive care unit (ICU) can affect the quality of nursing services. Aim This study aimed to determine the relationship between the nursing activity score and missed care in patients hospitalized in the ICU in Zanjan, Iran. Methods This observational and prospective study was conducted from April 3 to September 18 in 2021. In this study, the tools used included a patient and nurses' profile questionnaire, Nursing Activity Score (NAS). Missed care was observed in the 301 patients for whom the NAS was calculated. Analysis of variance (ANOVA) was used to investigate the differences in mean levels of missed care. Logistic regression models were used to assess the association between factors and missed nursing care. Results Results show that the Medical ICU's mean NAS was 76.31 (95% CI: -13.06 -14.89). In 9 dimensions of care, the extent of missed care was 40.7%. In the care dimensions of assessment, hand hygiene, and infection control, the mean NAS had a statistically significant increase at higher levels of missed care (P<.5). Furthermore, work experience was identified as a protective factor for missed care (OR =.59, 95% CI: .37–.94, χ2= =4.97, p =.026). Conclusion The study revealed a high incidence of missed care. The study revealed that the mean workload was high in certain dimensions of care such as assessment, hand hygiene, and infection control. The increase in workload for nurses results in lost care. Nonetheless, the utilization of experienced nurses can help mitigate this problem. However, utilizing experienced nurses can help reduce this problem.

This paper studies the pilot control strategy and workload of tilt-rotor aircraft dynamic conversion procedure between helicopter mode and fixed-wing mode. A nonlinear flight dynamics model of tilt-rotor aircraft with full flight modes is established. On this basis, a nonlinear optimal control model of dynamic conversion is constructed, considering factors such as conversion corridor limitations, pilot control, flight attitude, engine rated power, and wing stall effects. To assess pilot workload, an analytical method based on wavelet transform is proposed, which examines the mapping relationship between pilot control input's amplitude, constituent frequencies, and control tasks. By integrating the nonlinear optimal control model and the pilot workload evaluation method, the analysis of pilot control strategy and workload during the conversion procedure is conducted, leading to the identification of strategies to reduce pilot workload. The results indicate that incorporating the item of pilot workload in the performance index results in a notable reduction in the magnitude of collective stick inputs and longitudinal stick inputs. Moreover, it facilitates smoother adjustments in altitude and pitch attitude. Additionally, the conversion of the engine nacelle can be achieved at a lower and constant angular velocity. In summary, the conversion and reconversion procedures are estimated to have a low workload (Level 1 ~ Level 2), with relatively simple and easy manipulation for the pilot.

Abstract The of this study was to analyze the variation between within-week and between-playing positions on the locomotor and mechanical demands of soccer players. 19 elite soccer players of a team competing in the Turkish First League were included in the research. 86 training sessions of this team were evaluated. The differences between training performance metrics among microcycles for each position are revealed with repeated ANOVA and the differences between training performance metrics among positions in each microcycle are revealed with ANOVA. All the number of deceleration and acceleration per minute variables show statistical differences among the cycles for the defenders and midfielders but not for the forwards. These data suggested that there is a need to plan for different position-specific training stimuli in elite soccer teams for high performance outputs. We believe that these results can be used to determine positional demands by sports scientists and data analysts. Keywords: Soccer, TRIMP, Workload, Players, Heart Rate, GPS, Microcycles.