Variation In Performance Research Articles

Research on the aero-hydro coupling characteristics of the floating twin-rotor wind turbine system

The concept of installing two wind turbines on a floating platform, known as a floating twin-rotor wind turbine system, has recently garnered significant interest. This configuration can harness greater wind energy resources, reduce installation and mooring costs by sharing mooring lines, and minimize losses due to wake effects between turbines through yaw control. However, previous research has not sufficiently addressed the dynamic performance analysis of such systems. This study focuses on a high-capacity floating twin-rotor wind turbine system and develops an aero-hydrodynamic coupled analysis method based on the free vortex wake method and potential flow theory, specifically tailored for the twin-rotor configuration. This method facilitates real-time iterative calculations of wind and wave loads acting on the system and suggests optimization strategies for its design. Our findings indicate that the design of high-capacity floating twin-rotor systems can significantly reduce costs. Furthermore, the twin-rotor floating system design enhances wake recovery and achieves optimal comprehensive performance when the rotor spacing ratio (S/D) is 1.2 for the IEA 15 MW turbine. The coupled interactions induce periodic variations in aerodynamic performance, with the amplitude of these variations increasing with turbulence intensity. This research lays a theoretical foundation for advancing the design, platform optimization, and coupled computational analyses of large-capacity, large-scale floating twin-rotor wind turbine systems.

Effects of a sequential square mat walking training program Fisior® on improving physical performance in older adults with Parkinson's disease: A pilot study

BackgroundThis study aimed to assess the efficacy of a 12-week functional walking training program utilizing a sequential square mat (Fisior® Mat) on the physical performance of older adults diagnosed with Parkinson's Disease (PD). MethodsParticipants, aged over 60 and diagnosed with mild to moderate PD, underwent progressive resistance training sessions lasting 30-40 minutes, three times a week, using the Fisior® sequential square mat. A randomized clinical trial was conducted with participants from a patient association. Multiple linear regression models were employed to analyze physical performance variation between intervention and control groups. ResultsTwenty-eight patients (14 in each group) participated, with improvements observed in total Short Physical Performance Battery (SPPB) score, chair test score, gait speed score, and balance test score. Participants in the intervention group showed significant improvement in chair and balance test scores compared to controls. ConclusionThe Fisior® sequential square mat program, as an adjunct to conventional outpatient physiotherapy, effectively enhances physical performance in older adults with PD.

Performance variables and nutritional status analysis from Moroccan professional and adolescent football players during the competition period: a descriptive study

IntroductionNutrition plays an integral role in optimizing football players’ performance during training sessions and matches and maintaining their overall health throughout the season. This study aimed to evaluate how well the dietary practices of professional and adolescent football players in Morocco during the competitive period met international macronutrient recommendations, and to explore the relationship between their nutritional status and aerobic performance, as measured by the Yo-Yo IRL1 test.MethodsA total of 277 footballers from Morocco's professional league, “Botola-Pro”, were monitored over a seven-day (training microcycle) during the competitive period. The dietary intake was assessed through self-reported methods and 24-hour recalls. Relevant body composition was measured with bioelectrical impedance (BI), and aerobic performance was evaluated using the Yo-Yo IR test.ResultsThe results indicated significant variations in performance and nutritional status across different categories and age groups. The nutritional status of the players didn't match the UEFA recommendations (p < 0.001). We found that higher intake levels of carbohydrates and proteins were positively correlated with the total distance covered by the players (p < 0.001, r = 0.63, R2 = 0.4 for carbohydrates; p < 0.001, r = 0.59, R2 = 0.35 for proteins). Conversely, a higher proportion of energy derived from fats in the diet was negatively correlated with the distance covered (p < 0.001, r = −0.64, R2 = 0.41).ConclusionThese findings suggest that optimizing carbohydrates and protein intake while managing fat consumption is crucial for enhancing sporting performance. This information is essential for tailoring training programs and nutritional regimens based on the competition level.

Enhancing hydraulic efficiency in jet impingement sprinklers: Comparative analysis of aperture ratios compared with non-impingement sprinklers

A jet impingement sprinkler was designed based on asymmetric collision between the primary and secondary jets to replace traditional rotating sprinklers that require additional water distribution devices to provide suitable water distribution at low pressures. The study focuses on the ratio of apertures between primary and secondary nozzles, deriving a theoretical relationship based on jet momentum. The factors contributing to the variation in hydraulic performance between jet-impingement and non-impinging sprinklers are elucidated by combining hydraulic performance experiments with experiments using high-speed photography (HSP). The results show that the developed jet impingement sprinkler achieved a smoother water distribution trend. The wetted radius and Christiansen's uniformity coefficient of the jet impingement sprinkler were evaluated using the Criteria Importance via the Intercriteria Correlation (CRITIC) method. A comparison of the average scores shows that an aperture ratio of 1.66 performs best under full pressure. By contrast, an aperture ratio of 1.33 exhibited superior performance at low pressure. Jet deflection angle and jet breakup length were obtained through HSP experiments. The relative error between the measured and theoretical jet deflection angles was less than 5%, demonstrating the reliability of the proposed theoretical calculation method. A non-linear curve was used to establish the relationship among the aperture ratio, diameter of the primary nozzle exit, jet breakup length, average measured jet deflection angle, working pressure, and wetted radius. The relative error between the calculated and measured values was within 4%, indicating the suitability of the new formula for calculating the wetted radius of jet impingement sprinklers.

Cognitive performance in breast cancer survivors: a ten-year follow-up

Abstract Background Cognitive impairment (CI) has been widely reported as a frequent non-fatal cancer outcome. 15% to 25% of breast cancer (BCa) patients may have CI; however long-term variations of cognitive performance during and after the cessation of the treatments remains unclear. The present study aims to describe the evolution of cognitive performance in BCa survivors that are still in follow-up at breast cancer clinic, 10 years after diagnosis. Methods 506 women with BCa admitted to the Portuguese Institute of Oncology, Porto, in 2012, were evaluated with the Montreal Cognitive Assessment (MoCA) before any treatment, after one, three, five, and ten years. Patients with a MoCA score ≤1.5 standard deviation below the mean of age- and education-specific norms were considered to have probable cognitive impairment (PCI). The 10-year follow up started in October 2022, and is still in progress (as of March, 118 were evaluated). All women that are still being followed at IPO-Porto for consultations and treatments were evaluated with MoCA assessment. Results PCI prevalence at the 10 years was 43.0% (95%Confidence Interval: 34.1%-52.7%). Several pathways for cognitive performance were identified throughout the 10-year follow-up: 58 women (49.2%) never had PCI at baseline assessment or during follow-up; 19 women (16.1%) had PCI at baseline, from whom 5 (4.2%) had PCI in all evaluations, 2 (1.7%) did not have PCI in any follow up evaluation, 2 (1.7%) had PCI during follow up, but not at 10 years and 3 (2.5%) had PCI again only at the 10-year follow-up; 5 women (4.2%) did not have PCI at baseline but had PCI at least once during follow-up but not at 10 years, and 24.6% had PCI for the first time at 10 years. Conclusions The results show a high prevalence of PCI 10 years after diagnosis with a significant part being new cases. These results highlight the need for including regular assessments of cognitive performance as a part of the clinical follow-up of BCa survivors. Key messages • There is a high prevalence of cognitive deficits in breast cancer suvivors 10 years after diagnosis. • Including cognitive evaluations of breast cancer survivors during clinical follow up are recommended.

Influence of Strategic Customer Retention Practices on the Performance of Automotive Firms in Nairobi City County, Kenya

Purpose: The main focus of the study was to establish how strategic customer retention practices influences performance of automotive firms in Nairobi City County, Kenya. The study specifically focused on establishing the influence of customer support programs, technological advancements, and strategic communication practices and customer’s motivation programs on performance of automotive firms in Nairobi City County, Kenya. The study was anchored on Expectancy Theory, Diffusion of Innovation Theory, Communication Theory and Customer Service Theory. Methodology: The study employed a descriptive survey research design and targeted 18 franchised automotive firms registered by Kenya Motor Industry Association. The unit of observation comprised of employees in strategic, marketing and IT departments. A total of 80 respondents were involved in the study. Primary data was utilized in the study and was gathered through 5-point Likert scale structured questionnaires. Both descriptive and inferential statistics were adopted in analyzing the collected data. The statistics were generated by help of SPSS software and results presented in form of tables and figures. The study conducted a pilot test before the main study on two randomly selected automotive firms to assess the reliability and validity of questionnaires. Respondents involved in the pilot study was not be included in the main study. Findings: The study established that strategic customer retention practices accounts for 61.8% in variations of performance of automotive firms in Nairobi County. The study further established that strategic customer retention practices comprising of customer support programs, technological advancements, and strategic communication practices and customer’s motivation programs positively and significantly influences performance of the firm. This was depicted by beta values of 0.508, 0.324, 0.216, and 0.196 and significant values of 0.000, 0.000, 0.007, and 0.012. Unique Contribution to theory, Policy and Practice: The study concluded that enhancing the strategic customer retention practices leads to enhanced performance levels of the firms. The study provided recommendations to the management of the automotive firms to enhance aspects of customer support programs, technological advancements, and strategic communication practices and customer’s motivation programs since the practices leads to enhanced performance levels of the firms.

Enhancing Daily Crash Count Prediction using Deep Learning with Window Size Selection and Seasonality Predictor Integration

The escalating need for proactive safety measures, coupled with advancements in data collection and analytical techniques, has significantly refined the accuracy of crash count predictions, shifting from annual scales to finer daily or hourly estimates. This research places emphasis on recurrent neural networks (RNNs), specifically the long short-term memory (LSTM) model, acknowledged for effectively managing sequential data in time series predictions. Paramount considerations encompass the treatment of input data, including the decision to incorporate temporal features alongside endogenous historical target values, and the establishment of an optimal window size for data input. Despite the critical nature of these facets, exhaustive studies concurrently investigating both under controlled conditions are scarce. This research addresses this gap, assessing diverse scenarios featuring distinct temporal treatments and window sizes, and employing an LSTM model with uniform fine-tuned parameters to ensure a fair comparison. Findings indicate a significant variation in performance among models employing different window sizes and month predictor integration, under identical RNN structures and LSTM configurations. The best model outperformed the least effective by roughly 30% concerning root mean square error (RMSE) and ranking correlation between predicted and actual target crash counts in the test datasets. Unlike seasonality predictor treatment, diverse window size selections did not lead to statistically significant differences in model performance. Generally, a window size of 3 performed worst under most conditions, followed by a size of 14. Sizes of 7 and 28 performed best in nearly an equal numbers of cases.

An exploration of the service and crime prevention performance of the municipal police departments of Taiwan’s counties: the perspective of broken windows theory

PurposeThis study aims to evaluate the service and crime prevention performance of law enforcement agencies in Taiwan’s municipalities. By analyzing these performances, the study seeks to improve the efficiency of police services through appropriate resource allocation, ultimately achieving enhanced crime prevention.Design/methodology/approachThe study utilized a two-stage data envelopment analysis (DEA) to construct performance metrics. In the first stage, the service performance of the police force was measured using the number of police officers and police stations as inputs and the number of patrols and temporary patrol boxes as outputs. In the second stage, crime prevention performance was assessed with the number of patrols and temporary patrol boxes as inputs and cases of violence, injury, intimidation and theft as outputs. Additionally, a truncated regression model was employed to analyze the impact of environmental variables such as per capita income, population density, proportion of the population with higher education and the unemployment rate on crime prevention performance.FindingsThe study found significant variations in both service and crime prevention performance across different municipalities. By identifying the most efficient and inefficient units, the analysis revealed critical insights into resource utilization and areas needing improvement. The regression analysis indicated that environmental factors such as higher per capita income, population density, education level and unemployment rate significantly affect crime prevention performance.Originality/valueThis research provides a novel approach to assessing police service efficiency and crime prevention effectiveness using a two-stage DEA model. By incorporating environmental variables through truncated regression, the study offers a comprehensive evaluation framework that can inform policy decisions and resource allocation strategies. This methodology not only highlights the performance metrics of law enforcement agencies but also underscores the influence of socioeconomic factors on crime prevention, contributing to the broader literature on public safety and resource management.

Thermo-hydraulic performance characteristics of novel G-Prime and FRD Triply Periodic Minimal Surface (TPMS) geometries

Efficient thermal management is crucial for numerous applications, from electronics cooling and automobile systems to aerospace systems, necessitating the exploration of advanced heat transfer technologies like TPMS structures. Compared to conventional heat exchangers and heat sinks, lattice structures have improved by around 20–30 % performance. However, the variation in performance of the various lattice structures, such as FRD, G-Prime, etc., is yet unknown. Thus, this study investigates the thermo-hydraulic performance of various Triply Periodic Minimal Surface (TPMS) structures, including novel G-Prime and FRD geometries, through numerical simulations and experimental validation. The TPMS geometries were modeled using LattGen software and voxelized with 20 % relative density. Computational Fluid Dynamics (CFD) simulations were performed using Ansys Fluent with the k-epsilon turbulence model, and experiments were conducted on 3D-printed samples for validation. The numerical results reveal that G-Prime-2 and FRD Prime exhibit the highest heat transfer performance while demonstrating higher pressure drops than other TPMS geometries. Experimental validation agrees with numerical predictions, confirming the superior thermo-hydraulic performance of G-Prime-2 and FRD Prime for heat transfer enhancement applications. The results contribute to understanding TPMS thermo-hydraulic performance and enable informed geometry selection for thermal management applications.

Comparative Study and Modeling of AlGaN/GaN Heterostructure HEMT and MOSHEMT Biosensors

This paper presents a comprehensive comparative study and analytical modelling of electrical performance of AlGaN/GaN high-electron-mobility transistor (HEMT) and metal-oxide-semiconductor high-electron-mobility transistor (MOSHEMT) biosensors. Sensing parameters such as the I-V characteristics and sensitivity parameter for biomolecules detection in the cavity region are taken into consideration. In this paper, the permittivity is varied according to the biomolecule to be sensed by the biosensor. The maximal variation of the electrical performance of the biosensor obtained is higher in HEMT as compared with MOSHEMT. The simulation results of the analytical model obtained by using MATLAB verified by a comparison with experimental data and atlas-technology computer aided design (Atlas-TCAD), and shown good agreement with each other. Thereby, we could improve the validity of the proposed model. The AlGaN/GaN HEMT have shown good sensing of 141.73 at biomolecular permittivity of 2.5 which can be used for biosensing applications effectively.

Flexible TiO2-WO3−x hybrid memristor with enhanced linearity and synaptic plasticity for precise weight tuning in neuromorphic computing

Tungsten oxide (WO3)-based memristors show promising applications in neuromorphic computing. However, single-layer WO3 memristors suffer from issues such as weak memory performance and nonlinear conductance variations. In this work, a functional layer based on the hybrids of WO3−x and TiO2 is proposed for constructing flexible memristors featuring outstanding synaptic characteristics. Applying diverse electrical stimulations to the memristor enables a range of synaptic functions, elucidating its conduction mechanism through the conductive filament model. The incorporation of TiO2 not only enhances the memristor’s memory characteristics but makes its conductance more linear, symmetrical and uniform during the long-term changes. Furthermore, in view of the enhanced device performance by TiO2 doping, the potential of this device for simple behavioral simulation and processing of complex computing problems is explored. The “learning-forgetting-relearning” characteristics and device integrability are visually demonstrated. Applying the device to a convolutional neural network, the recognition accuracy of MNIST handwritten digits reaches 98.7%.

Thermal-gas-elastic coupling modeling and performance analysis of foil cylindrical gas film seal considering speed slip, temperature jump and shaft misalignment

Abstract The Compliant foil cylindrical gas film seal is an advanced sealing technology designed for high-speed and high-temperature conditions in a jet engine. Its design involves using a compliant foil to create a cylindrical sealing surface, achieving adaptive sealing in environments with high pressure differences and rotational speeds. For high-speed and high-temperature operation, a speed slip flow model was established by considering film slip flow, wall temperature jump, foil deformation, and gas viscosity-temperature thermal effects. The variations in the lubrication performance of the foil cylindrical gas film seal with changes in shaft misalignment directions, misalignment angles, and operating parameters were investigated. The speed slip leads to a decrease in gas film lift and an increase in leakage. The wall temperature jump phenomenon caused by speed slip leads to a 2.56% decrease in film temperature. The shaft misalignment angles on the high-pressure and low-pressure sides have different impacts on the flow field, with film pressure and temperature differing by 66.78% and 11.19%, respectively.

Multi-Step Temperature Prognosis of Lithium-Ion Batteries for Real Electric Vehicles Based on a Novel Bidirectional Mamba Network and Sequence Adaptive Correlation

The battery systems of electric vehicles (EVs) are directly impacted by battery temperature in terms of thermal runaway and failure. However, uncertainty about thermal runaway, dynamic conditions, and a dearth of high-quality data sets make modeling and predicting nonlinear multiscale electrochemical systems challenging. In this work, a novel Mamba network architecture called BMPTtery (Bidirectional Mamba Predictive Battery Temperature Representation) is proposed to overcome these challenges. First, a two-step hybrid model of trajectory piecewise–polynomial regression and exponentially weighted moving average is created and used to an operational dataset of EVs in order to handle the problem of noisy and incomplete time-series data. Each time series is then individually labeled to learn the representation and adaptive correlation of the multivariate series to capture battery performance variations in complex dynamic operating environments. Next, a prediction method with multiple steps based on the bidirectional Mamba is suggested. When combined with a failure diagnosis approach, this scheme can accurately detect heat failures due to excessive temperature, rapid temperature rise, and significant temperature differences. The experimental results demonstrate that the technique can accurately detect battery failures on a dataset of real operational EVs and predict the battery temperature one minute ahead of time with an MRE of 0.273%.

Elucidation of the influence of trinitro-diazinotriazine isomerism on the energetic properties and stability: Insights from DFT approach

The exploration of isomeric energetic molecules with high nitrogen content and the examination of their structure–property relationships remains compelling areas of interest within the field of energetic materials. Energetic isomers comprising the same molecular composition but distinct molecular structures potentially lead to notable variations in performance and properties. This study focused on designing and evaluating different forms of diazinotriazine using two molecular compositions: C5H3N5 and C5N8O6, aiming to generate various isomeric structures and to guide the rational design of new molecules. The electronic configurations, energetic properties, and sensitivity prediction of the optimized structures were investigated using the M06-2X/def2-TZVPP level of theory. The trinitro-diazinotriazine isomers exhibit high heat of formation (>486 kJ/mol), high detonation properties (D > 8.7 km/s, P > 34 GPa), high density (>1.81 g/cm3), and better thermal stability (BDE > 230 kJ/mol) making them promising explosive contenders. Among the designed diazinotriazine backbones, the pyridazine-1,2,3-triazine framework is favourable for the heat of formation and detonation properties. The heats of formation, detonation velocity, pressure, and heats of detonation of A4 and B4 outperform the other trinitro-diazinotriazine isomers.

UTILIZATION OF CLASSROOM ENVIRONMENT AND ITS EFFECTS ON ACADEMIC PERFORMANCE IN SUB COUNTY LEVEL SECONDARY SCHOOLS IN UASIN GISHU COUNTY, KENYA

School infrastructure is a key pillar for effective learning process in any educational institution. The purpose of this study was to utilization of classroom environment affect academic performance in Sub County level secondary schools in Uasin Gishu County. This study was guided by Production theory. The study was guided by pragmatism philosophy and adopts descriptive survey research design. The study area was carried out in Uasin Gishu County. The target population of the study was 18960 respondents. Stratified simple random and purposive sampling was employed to select the respondents. The sample size was 530 respondents comprising of 48 principals, 97 teachers, 384 students and a Quality Assurance and Standards Officer The data collection instruments were questionnaire, interview schedules and observation check list. A pilot study was carried out in five public schools in the neighboring Trans Nzoia County to check on the consistence of the instruments. The researcher yielded both quantitative and qualitative data. Quantitative data was analyzed using descriptive statistics that resulted in percentages and frequencies that were represented in tables, pie charts and bar graphs and inferential statistics. Qualitative data was analyzed thematically. Therefore, from the research findings based on the multiple regression models, the coefficient of determination (R squared) of 0.441 showed that 44.1% of the variation in student performance was explained by the utilization of selected school infrastructure. The study found out that the classroom environment influenced academic performance. The study concluded that the more conducive the classroom environment the higher the academic performance. The research recommended that sub county level secondary schools management in Uasin Gishu County should develop infrastructural development initiatives to solve the inadequacy of these facilities and enhance their utilization in the schools. There should be consistent routine supervision of quality of facilities in schools done by the government to ensure that schools are operating with good facilities that would help the learners. KEY WORDS: School infrastructure utilization of classroom environment, academic performance

Assessing the Performance of Initial Public Offerings (IPOs) in Indian Stock Markets: A Longitudinal Study from 2014-2023

This research investigates the performance of Initial Public Offerings (IPOs) in the Indian stock market over a decade (2014-2023). The study aims to assess both short-term and long-term IPO returns and the factors influencing their performance. Using a quantitative, longitudinal approach, data was collected from the National Stock Exchange (NSE) of India, covering 500 IPOs. The analysis examines short-term listing day returns and long-term performance up to five years post-IPO, focusing on variables like firm size, market sentiment, and sector-specific dynamics. The findings reveal substantial variations in IPO performance, with average listing day returns ranging from 18.98% to 26.35%, particularly peaking during market volatility in 2020. However, long-term returns exhibit a decline, with many IPOs underperforming five years after listing. Regression analysis shows that firm size and market sentiment significantly affect IPO performance, with larger firms and favorable market conditions driving better outcomes. The technology and pharmaceutical sectors outperformed, while real estate IPOs lagged. The study highlights the importance of due diligence for investors and the need for continued regulatory reforms to improve market transparency and efficiency. This research fills a gap in the literature by providing a comprehensive, decade-long perspective on IPO performance in India.

Diurnal variation of psychomotor, cognitive and physical performances in schoolchildren: sex comparison

BackgroundThe present study investigated the effect of time of day (08h00 vs. 11h00 vs. 14h00 vs. 17h00) and sex (girls vs. boys) on physical (i.e., five jump test (5JT), push-ball test and 5 m shuttle run test (5mSRT)), cognitive (i.e., attention) and mental (i.e., mental flexibility) performances.MethodsThirty schoolchildren, equally divided in girls (n = 15; age: 9.60 ± 0.51 years) and boys (n = 15; age: 9.40 ± 0.51 years) performed the digit cancellation test, the trail making test, the 5JT, the 2 kg push-ball test and the 5mSRT in a counterbalanced and cross over study design at 08h00, 11h00, 14h00 and 17h00 with 48 h of rest in between. Additionally, rating of perceived exertion (RPE) was determined after each repetition of the 5mSRT and the average of the score (i.e., sum of RPE scores divided by 6) was determined.ResultsResults showed that RPE at the end of the test was significantly higher at 11h00 compared to 08h00 (p = 0.02) and 14h00 (p = 0.001) and average RPE was higher at 11h00 compared to 08h00 (p = 0.001). Likewise, attention was significantly higher at 08h00 compared to 17h00 (p = 0.001) before and after the 5mSRT test only in girls. However, 5JT performance was significantly lower at 17h00, both in girls and boys, compared to at 08h00 (p = 0.02 and p = 0.001 respectively), 11h00 (p = 0.004 and p = 0.001 respectively) and 14h00 (p = 0.001 and p = 0.001 respectively). However, push-ball (p = 0.086) and 5mSRT performances [best distance (p = 0.173), total distance (p = 0.306), mean distance (p = 0.29), fatigue index (p = 0.06)] were time of day independent. Mental flexibility was significantly higher at 08h00, 11h00 and 14h00 compared to 17h00 (p = 0.001).ConclusionMental flexibility, attention and jump performances were time of day dependent and push-ball test and 5mSRT performances did not change according to the time of day. Also, no clear sex effect was found on the diurnal variation of mental, cognitive and physical performances.

Assessment of Physical and Mechanical Parameters of Spun-Bond Nonwoven Fabric.

The selection of an appropriate fabric for technical applications, such as protective masks, hinges on a thorough understanding of the fabric's physical and mechanical properties. This study addresses the challenge of selecting the optimal material structure for the upper layer of a protective mask, aiming to ensure adequate breathability while providing effective filtration against airborne particles and contaminants. We assessed and compared the physical-mechanical properties of five polymer spun-bond nonwoven fabrics from different suppliers. Our comprehensive evaluation included, as follows: a visual inspection; light permeability analysis; mass and thickness measurements; elongation and tensile strength tests; breathing resistance assessments; and filter penetration tests with paraffin oil. The results revealed significant variations in performance among the samples, with one fabric consistently outperforming the others across multiple parameters. Notably, this top-performing fabric met or exceeded the EN 149:2001+A1:2009 standard for breathing resistance and filtration efficiency and, in combination with additional filter layers, met the requirements or exceeded class FFP2 (filtering face piece). This study underscores the importance of meticulous material selection and quality control in optimizing PPE (personal protective equipment) performance and user safety, providing valuable insights for mask manufacturers and healthcare professionals.

An evaluation of the performance of stopping rules in AI-aided screening for psychological meta-analytical research.

Several AI-aided screening tools have emerged to tackle the ever-expanding body of literature. These tools employ active learning, where algorithms sort abstracts based on human feedback. However, researchers using these tools face a crucial dilemma: When should they stop screening without knowing the proportion of relevant studies? Although numerous stopping rules have been proposed to guide users in this decision, they have yet to undergo comprehensive evaluation. In this study, we evaluated the performance of three stopping rules: the knee method, a data-driven heuristic, and a prevalence estimation technique. We measured performance via sensitivity, specificity, and screening cost and explored the influence of the prevalence of relevant studies and the choice of the learning algorithm. We curated a dataset of abstract collections from meta-analyses across five psychological research domains. Our findings revealed performance differences between stopping rules regarding all performance measures and variations in the performance of stopping rules across different prevalence ratios. Moreover, despite the relatively minor impact of the learning algorithm, we found that specific combinations of stopping rules and learning algorithms were most effective for certain prevalence ratios of relevant abstracts. Based on these results, we derived practical recommendations for users of AI-aided screening tools. Furthermore, we discuss possible implications and offer suggestions for future research.

Effects of inter- and intraindividual compensation-sensitive shot styles on performance in Olympic air rifle shooting

Background: Aiming point analysis systems (APAS) are commonly used in sports shooting but face four main challenges: they do not account for intra-session variations, they overlook inter-individual shooter preferences, they ignore compensation mechanisms of technical features, and they do not respect the real shot location at the target. Methods: To address the first three challenges, we developed and validated an automated approach detector algorithm (ADA) for movement phase detection. When compared to three independent expert ratings, the ADA demonstrated a high correlation (r = .811). Building on the ADA and addressing challenge 3 and 4, this study applied cluster-analysis and ANOVA to determine the performance relevance of compensation-sensitive shot styles using datasets from a single athlete and 26 advanced to elite level athletes. Results: Significant performance differences in shot styles for both datasets, with each shot style distinctively differing from the others could be found. Conclusions: Shot styles which allow for compensation and intra-individual movement phase differences exhibit performance variations. Coaches and athletes should emphasize holistic training, focusing on combinations of features that allow for compensation.