Fit Test Data Research Articles

The relationship between BMI and physical fitness among 7451 college freshmen: a cross-sectional study in Beijing, China.

To identify trends in physical fitness test scores of college freshmen and their physical fitness from 2018 to 2021, and to analyze the relationship between college students' Body Mass Index (BMI) and Physical Fitness Index (PFI). This study obtained physical fitness test data from 7,541 freshmen at a university in Beijing, China, from 2018 to 2021. Analysis of variance (ANOVA) was used to compare the physical fitness indicators among different BMI levels by gender. A nonlinear quadratic regression model was used to evaluate the relationship between BMI and each indicator within gender groups. The BMI of freshmen in China was generally increased over the study period, and BMI levels influenced students' physical fitness indexes to varying degrees. BMI was significantly correlated with the physical fitness indexes and PFI. The increase in BMI had a greater influence on the PFI of males than females. Students with a normal BMI show better physical fitness. A BMI below or above the normal range may result in poor physical fitness. The relationship between BMI and PFI has an inverted u-shaped curve. Physical education programs should be tailored to students with different fitness levels and fundamentals, including but not limited to the development of strength, speed, and other qualities.

Test research of the relation between velocity and heart rate during evacuation under adverse attitude conditions

Abstract Based on the dynamic cabin emergency evacuation tests environment, emergency evacuation tests under adverse attitude landing conditions are studied. The relation between average velocity and average heart rate under horizontal conditions is achieved by means of fitting test data. The test results show that cabin adverse attitude can both affect the move state and psychology of test members. The change trend of move velocity is different from heart rate change and displays a large difference. Change coefficient correlation with psychology is put forward and the relation with pitch and roll angle is attained by fitting the test data. This coefficient can be used to simulate the scared state at simulation adverse attitude emergency evacuation. The test also demonstrates the behavior of the test member can be analyzed by measuring biological parameters and providing a reference for building or modifying the emergency evacuation simulation model.

Automobile Intelligent Vehicle-machine and Human-computer Interaction System based on Big Data

This paper measures the accelerator, brake pedal, clutch, transmission device and steering wheel under different driving conditions in real-time and accurately on the simulation experiment platform. The goal is to conduct human-machine-road system interaction in a virtual simulation of human-vehicle-road systems. Fitting test data establishes the mathematical model of traffic control parameters. In terms of hardware, the distributed architecture of upper and lower computers is utilized. The system communicates point-to-point with the host computer through the RS-232 serial port. The system adopts multi-thread technology and serial communication technology. The simulation system of driving operation is designed with the visual central controller. The system takes 89S52 as the core. The slave program is written in C language. Then, the system establishes a multi-target coordinated obstacle avoidance method based on a multi-sensor information vehicle cooperation collision avoidance method. The multi-vehicle cooperation obstacle avoidance problem is transformed into an optimal control problem under multiple constraints. Simulation analysis shows that the velocity and displacement obtained by the multi-robot collaborative collision avoidance method are in good agreement with the measured values. Compared with the time series algorithm, the output accuracy of the proposed collaborative collision avoidance algorithm is significantly reduced, and the changes in velocity and displacement in the time domain are more stable.

Physical Fitness Test Data Analysis and Training Program Recommendation Based on Machine Learning

Physical fitness is the state of being physically healthy and capable of performing daily tasks with vigor and resilience. Physical fitness and machine learning intersect in various ways, primarily through the use of wearable devices, fitness apps, and data analysis. Wearable fitness trackers equipped with sensors, such as heart rate monitors, accelerometers, and GPS trackers, collect vast amounts of data on individuals' physical activity, sleep patterns, and vital signs. The paper presents an innovative approach to physical fitness assessment and training program recommendation using the Gradient Probabilistic Automated Recommender System with Machine Learning (GPA-RS-ML). This system utilizes machine learning techniques to assess fitness data from individuals and then suggests training programs that are customized to their specific goals and needs. By incorporating gradient values and probabilistic predictions, the GPA-RS-ML algorithm offers a comprehensive and individualized approach to fitness training, enhancing the efficiency and effectiveness of training interventions. The study demonstrates the efficacy of the GPA-RS-ML system in accurately predicting suitable training programs for participants, considering their unique fitness profiles and preferences. This research contributes to the advancement of automated fitness assessment and recommendation systems, providing a valuable tool for fitness professionals and enthusiasts to optimize fitness outcomes and improve adherence to training regimens.

A review of mask fit testing data associated with protocols utilized in evaluating the efficacy of N95 masks for health care workers

A review of mask fit testing data associated with protocols utilized in evaluating the efficacy of N95 masks for health care workers

Breakdown calculation of zoning tests by positive lightnings

To simulate a natural lightning strike, the breakdown should occur within 1–3 μs in an aircraft lightning zoning test. However, the breakdown voltage–time characteristic of the combined gap is hard to derive because of the complex breakdown process. In this paper, a series of positive lightning impulse discharge tests in a rod electrode–floating aircraft model–plate combined gap were conducted. The leader propagation processes in both sub-gaps were observed using a high-speed camera. The potential of the floating aircraft model was analyzed. We propose a potential calculation model for the floating aircraft during the leader propagation phase. After fitting test data, an empirical formula for the connected streamer plasma was given. Taking that model into account, the calculation result of the average breakdown time of the combined gap has an error of <5.7%.

Physical fitness decline and career paths: a longitudinal study of medical undergraduates

IntroductionExercise enhances one's health and competitiveness. A strong physical fitness status can pave the way for a promising future. This study presents the time-based trends in physical fitness indicators—including height, weight, BMI, lung capacity, dash, long-distance running, and standing long jump—among medical undergraduates during their university years. Additionally, we analyzed the impact of students' physical fitness on their career paths.MethodWe conducted a retrospective database study by collecting physical fitness test data and career paths information for 634 medical students from a university in southwestern China. These students graduated in 2022. The career paths included pursuits in further studies, employment, and unemployment. To detect differences in these aspects, we used the t-test and Chi-square test.ResultsOur study indicates a significant declining trend in the physical fitness of medical students during their university years. The changes observed between the first and fourth tests are as follows:Weight (kg): 58.52 ± 10.48 to 60.73 ± 12.07, P < 0.00BMI (kg/m^2): 20.79 ± 2.74 to 21.24 ± 3.06, P < 0.0050-m dash (s): 8.91 ± 0.99 to 9.25 ± 1.11, P < 0.00Standing long jump (cm): 187.74 ± 30.98 to 182.59 ± 32.25, P < 0.00800-m run for females (min): 3.84 ± 0.47 to 4.48 ± 0.85, P < 0.001000-m run for males (min): 3.98 ± 0.63 to 4.62 ± 0.87, P < 0.00Sit-ups for females (count): 30.39 ± 7.5 to 29.03 ± 8.82, P < 0.00Upon analyzing the correlation between changes in physical fitness and career paths, students with stable or decreased BMI had better post-graduation outcomes compared to students with increased BMI.ConclusionsMedical students show a declining trend in physical fitness during their undergraduate years. A good physical health status is beneficial for achieving better career paths. Medical students should place greater emphasis on physical exercise during their time in school.

The influence of physical literacy of student with different obesity levels on physical fitness: the mediating effect of MVPA.

Perceived physical literacy (PL) is a potential factor for improving health and physical activity, but the relationship between PL and physical fitness (PF) among college students with different obesity levels has not yet been determined. The aim of this study was to explore the correlation between PL, moderate-to-vigorous physical activity (MVPA), and PF among college students with different obesity levels. We recruited Chinese university students to complete a questionnaire and conducted a survey using the Perceived Physical Literacy Instrument Scale (PPLI-SC) and the International Physical Activity Questionnaire Short Form (IPAQ-SF). The physical fitness test data were used for data analysis. The direct and indirect impacts were analyzed using Pearson correlation and the SPSS Hayes process macro (Model 4). The study surveyed 909 boys and 1,668 girls for a total of 2,577 valid questionnaires. Similarly, the MVPA and perceived PL of boys were significantly greater than those of girls (p < 0.01), but the opposite was true for the PF score. The correlation analysis showed that MVPA, perceived PL, and PF were significantly correlated (p < 0.01). For normal weight student, the results showed that the direct effect of PL on PF was still statistically significant (β = 0.076, p < 0.01) after adding MVPA; MVPA had a positive effect on PF after controlling for perceived PL (β = 0.055, p < 0.05). Perceived PL has a positive effect on MVPA (β = 0.123, p < 0.01). The mediating effect of MVPA was notably significant, with a mediation effect percentage of 7.9%. However, it has been found that among the underweight population, there is an absence of a significant relationship between PL, PF, and MVPA (p > 0.05). Contrarily, in the overweight and obese groups, the mediating role of MVPA in the relationship between PL and PF was not statistically supported (-0.002, 0.033). For normal weight student, perceived PL has a positive impact on PF and can also be promoted by increasing the pathway of MVPA. For both underweight individuals and obese populations, further investigation is needed into methods for promoting PA and improving PF.

A study of stratified optimization of college physical education course effects under the perspective of cluster analysis

Abstract Due to the different physical fitness of college students, they have different acceptance abilities for college physical education courses, so a unified teaching method cannot be applied among many students. The article focuses on the student stratification model based on learning characteristics and takes the university physical education course as an example to design a university physical education teaching stratification method based on the improved K-means clustering algorithm with initialization denoising and center-of-mass optimization. Taking the physical education test data of the 2021~2023 sessions of a university as the research object, K-means clustering analysis was carried out on the 8-item physical fitness test data to realize the stratification of students’ learning situation. The experimental results show that the method of this paper clusters 14619 students into three layers, and the cluster centroid distances of Cluster 1~3 are 20.35, 16.97, and 18.39, respectively. The maximum standardized mutual information values are 6.820, 3.105, and 2.931, respectively, and the results of the stratification are reasonable and easy to interpret, and they can provide effective references for the development of personalized physical education for school students.

Information technology-assisted analysis of college students’ physical fitness test data and research on physical education teaching reforms

Abstract Enhancing the physical quality of students in higher education institutions is crucial for ensuring the successful completion of their academic pursuits. This article begins by analyzing the fundamental algorithms of decision trees, subsequently building upon this theoretical foundation to develop an ID3 decision tree model. It employs the decision tree model for data classification, extraction, and other related processes. By integrating the C4.5 algorithm and further segmentation techniques, a more stable decision tree is derived, allowing for a comprehensive analysis of physical fitness test data. The study’s findings indicate that using rope skipping test data as an example, the analytical model maintains an error margin of 3%. Over four years of physical test data, there was a notable classification of 1% of students into the “excellent” category in 2020, with nearly 20% achieving “good” status. The proportions of “excellent” and “good” students in 2021 saw a significant rise from the previous year. Furthermore, the percentage of students categorized as “failing” in 2023 decreased by 0.88%. To enhance the effectiveness of physical education, reforms could focus on multi-faceted collaborative efforts, reinforcing the application of the ID3 decision tree model in analyzing physical fitness data and targeting interventions to boost physical fitness outcomes.

Research on the teaching model of physical education in colleges and universities based on semi-supervised radial basis function neural network

Abstract With the development of the modern sports concept, physical education mode in colleges and universities needs to adapt to the requirements of the new era. In this paper, we studied the feasibility and comparative advantages of exercise prescription physical education, collected physical fitness test data of college students, completed the cluster analysis of student physical test data based on the k-medoids algorithm, used semi-supervised RBF neural network to learn each cluster, and generated an exercise prescription for each class of students. In the comparative teaching, the performance of students in the experimental class improved in standing long jump and 50 m, and the changes were statistically significant with p-values less than 0.05. While the indicators in the control class improved slightly before and after the experiment, the p-values were greater than 0.05, and there was no significant difference.

Bond performance between surface-modified bamboo bars and concrete under pull-out loading

Bamboo is abundant, eco-friendly, and cost-effective, making it an excellent alternative to traditional building materials with limitations such as resource scarcity, pollution, and increasing price. Additionally, bamboo has excellent strength and durability, and can be used to replace steel bars. In this study, central pull-out tests were conducted on forty bamboo bars embedded in concrete specimens to study the bonding performance at the interface between bamboo bars and concrete. The test variables included surface modification (unmodified, epoxy mortar (EM)-modified and polyurethane (PE)-modified), equivalent diameter (d), and development length (L). The results indicated that (1) the specimens with PE-modified bamboo bars mainly exhibited bamboo bar pull-out failure, whereas the specimens with EM-modified bamboo bars primarily underwent tensile failure of the bamboo bar; (2) the bond stress‒slip curve had four stages: micro-scale slip, slip, descending, and residual stages; (3) the average peak bond stress (τ0) of the specimens with EM-modified bamboo bars was the highest; (4) τ0 decreased with increasing L and d values; and (5) the largest strain values were observed near the loading end. Finally, bond stress-slip constitutive models suitable for pull-out specimens with PE-modified bamboo bars with different L values were obtained by fitting test data. The findings of this study broaden the application of bamboo bars in the concrete structures.

Retracted: Student Physical Fitness Test System and Test Data Analysis System Based on Computer Vision

Retracted: Student Physical Fitness Test System and Test Data Analysis System Based on Computer Vision

A plastic-damage material model for foam concrete under blast loads

Foam concrete is a prospective material in defense engineering to protect structures subjected to intense dynamic loadings such as impact and blast through wave impedance mismatch as well as energy absorption. In the near-field of intense dynamic loadings, the foam concrete is always suffered from a high-pressure stress state associating with complex failures such as pore collapse, shear fracture and tensile fracture. A well-established material model is needed to capture above-mentioned behaviors. In this paper, a plastic-damage material model for foam concrete is proposed focused on its mechanical behavior under high pressures. Firstly, a closed form yield function, a partially-associative flow rule and a new piecewise hardening law are introduced. The yield function is composed of a fracture function describing the mechanical behavior due to microcracks and a continuous cap function describing the mechanical behavior due to pores. The partially-associative flow rule is used to avoid the overestimation of plastic strain induced by the classical associative flow rule. In particular, a new piecewise hardening law is proposed instead of frequently-used exponential ‘‘crush curve’’, which is flexible for fitting test data and can capture the experimentally-observed increase of unloading bulk modulus with increase of pressure. The rate dependency of yield surface is considered to capture the strain-rate effect of foam concrete. And then three independent damage indexes with clear physical background are proposed to describe irreversible degradation caused by microcrack growth and pore collapse. The shear damage caused by shear cracks, tensile damage caused by tensile cracks, and hydrostatic compression damage caused by pore collapse, are separately identified and proposed in the framework of continuum damage mechanics. The proposed model is embedded into the LS-DYNA through the subroutine of user-defined material model. Its performances for predicting complex failures under various stress states at a Gaussian point level are numerically evaluated using a single element, and further used to predict blast response of foam concrete. All the numerical predictions agree with test data well.

Evaluating the Variability Between 20-m Multistage Fitness Test Estimating Equations in Law Enforcement Recruits.

Campbell, P, Maupin, D, Lockie, RG, Dawes, JJ, Simas, V, Canetti, E, Schram, B, and Orr, R. Evaluating the variability between 20-m multistage fitness test estimating equations in law enforcement recruits. J Strength Cond Res 38(4): 742-748, 2024-The 20-m multistage fitness test (20MSFT) is commonly used by law enforcement agencies to measure aerobic fitness and to estimate maximal aerobic consumption (V̇ o2 max). These measures are an important occupational variable with aerobic fitness levels linked to employment status, occupational performance, and long-term health in law enforcement officers. There are a multitude of predictive equations used to provide an estimate of V̇ o2 max, with the extent of variability in the estimated V̇ o2 max currently unknown in this population. This has consequences for comparisons between, and across, differing agencies, and in capabilities of deriving normative data. The aim of this investigation was to compare the variability in estimated V̇ o2 max scores derived from different 20MSFT predictive equations. The 20-m multistage fitness test data from 1,094 law enforcement recruits (male n = 741, 25.2 ± 6.3 years; female: n = 353, 25.6 ± 5.6 years) from a single agency were retrospectively analyzed. The 20MSFT scores were transformed into estimated V̇ o2 max scores using 6 different predictive equations. Significance was set at p < 0.05. Results demonstrated significantly different V̇ o2 max scores between each predictive equation ( p < 0.001; d = 0.25-1.53) and between male and female recruits ( p < 0.001, r = 0.55). All estimated V̇ o2 max equations showed small to very strong correlations with each other ( p < 0.001; r = 0.32-0.99). The findings indicate considerable dispersion of V̇ o2 max scores when using differing equations, suggesting raw 20MSFT variables (e.g., shuttles or distance completed) should be preferred to measure and apply results from aerobic fitness tests if standardized approaches are not developed within law enforcement.

Retracted: Status Quo Analysis of Physical Fitness Test Data Based on Health Monitoring.

[This retracts the article DOI: 10.1155/2022/3931404.].

Striving to be the fittest: quantitative P2/N95 respirator fit test results among hospital staff during the COVID-19 pandemic.

To provide fit rates for specific P2/N95 respirators and compare these results by age, sex, clean-shaven status, and fit tester experience. Exploratory audit involving secondary analysis of existing quantitative fit testing data. In response to the COVID-19 pandemic, healthcare services across Australia implemented respiratory protection protocols. This study details healthcare workers' (HCWs) fit testing results from a large Victorian public health service. Fit-tested employees of a large tertiary public health network. Fit rates for ten individual P2/N95 respirators were calculated, and the effect of age, sex, clean-shaven status, and fit tester experience was examined via logistic regression. 4593 employees were included, with 97.98% successfully fitting at least one respirator. Males were found to have significantly increased odds of achieving fit success compared to females (OR 11.61 95%CI 1.60-84.10). Fit rates dropped by 4% with each 1-year age increase (OR 0.96 95%CI 0.94-0.98). Clean-shaven individuals were also more likely to achieve a fit compared to non-clean-shaved individuals (OR 79.23 95%CI 10.21-614.62). More experienced fit testers also yielded significantly higher fit rates (OR 3.95, 95%CI 2.34-6.67). 98% of staff achieved a successful fitting of at least one respirator, with three-panel flat fold models (Industree Trident, 3M Aura 9320A+, and 3M Aura 1870+) performing the most consistently. An individual's ability to achieve a successful fit was associated with; male sex, younger age, clean-shaven status, and fit tester experience.

Modeling of novel RF AlGaN/GaN HEMTs with the structure of n-Si drain extension

In this letter, a novel heterojunction model of RF AlGaN/GaN based high electron mobility transistor (HEMT) combined with n-Si drain extension is proposed and investigated with numerical simulations to decrease the miller capacitance and improve RF power characteristic. Firstly, after verifying the analytical heterojunction model, the simulation model parameters of the traditional HEMTs are extracted by fitting test data of the fabricated device. Then, the extracted model and the n-type silicon structure are combined in the simulation tool to further investigate the mechanism and performance of the proposed HEMTs. It shows that the capacitance effect in the proposed device efficiently reduces by 60% of the original capacitance Cgd. Moreover, the RF characteristic of the proposed device and the traditional device are analyzed, respectively. Both the cut-off frequency and the oscillation frequency of the proposed HEMTs are improved compared to the traditional device and the optimized n-Si width below 0.05 μm. The results show that the proposed device is a potential candidate for high radio frequency (RF) application due to its excellent RF Power properties.

Improving Use of Physical Fitness Testing Data in Middle Schools to Inform Equitable School-wide Physical Activity Practices: A Mixed-methods Approach

ABSTRACT Background Most United States schools include school-based physical fitness testing (SB-PFT), yet little evidence shows how it is implemented, perceived, and used. Purpose 1) Explore stakeholders’ experiences with SB-PFT; 2) identify: challenges in analyzing fitness data, ways schools can use fitness data, and predictors of meeting fitness benchmarks. Methods Data were collected in a partner school district (King County, Washington, USA). We conducted and analyzed qualitative interviews with middle schoolers (n = 30), parents (n = 20), and school staff (n = 5); and identified student-level predictors of meeting fitness benchmarks with two-level mixed effects logistic regression models using district’s fitness assessment data (grades 4–8). Results Stakeholders identified challenges and provided feedback on SB-PFT, and predictors of meeting fitness benchmarks were identified. Discussion Findings suggest SB-PFT has potential to be useful in promoting adolescents’ fitness, but opportunities exist to improve the testing process and the ways that results are shared and utilized. Translation to Health Education Practice: Teachers would benefit from resources to understand and discuss the role of SB-PFT in a physically active lifestyle with students, ensure a positive testing experience by conducting assessments more privately and taking the time to practice assessments beforehand, and track testing outcomes and relevant demographics. A AJHE Self-Study quiz is online for this article via the SHAPE America Online Institute (SAOI) http://portal.shapeamerica.org/trn-Webinars

Simulated workplace protection factor study of a quarter-facepiece elastomeric respirator

The assigned protection factor (APF) for quarter-facepiece respirators is currently 5, based on fit test data from the 1970s with models no longer commercially available. The goal of this project was to evaluate the respirator fit capability of a NIOSH-approved N95 quarter-facepiece elastomeric respirator with a gel-based facial seal design (Envo Mask by Sleepnet Corporation). Human subjects were recruited from healthcare and the general population to satisfy a 25-member NIOSH bivariate panel. Subjects were fit tested with a fast fit protocol using a TSI Portacount Model 8038 in the N95 mode. Second-by-second measures of fit were then collected while subjects performed a 30-min series of simulated healthcare activities. Subjects completed a short comfort questionnaire. The median (5th, 95th percentile) fit factor was 188 (48, 201). Simulated workplace protection factors (SWPFs) had a median (5th, 95th percentile) of 181 (94, 199) (data truncated at 200) and 570 (153, 1508) (non-truncated data). Subjects ranked inhalation and exhalation as “easy” with average scores of 5.0/6.0 and 5.2/6.0, respectively. The facepiece was ranked between slightly comfortable and comfortable (4.8/6.0) and the harness as comfortable (5.0/6.0). Most users agreed (5.2/6.0) that the mask was stable on their faces. The 5th percentile SWPF of 95 supports an APF of at least 10 for this quarter-facepiece elastomeric respirator, similar to the APF for half-facepiece respirators. This study supports increasing the APF for quarter-facepiece respirators, a class that has been largely ignored by manufacturers for the past 40 years. A lightweight, low profile, reusable quarter-facepiece respirator is an effective option for healthcare and other worker protection during a pandemic and similar situations.