Prediction Equations Research Articles

Developing normative values and predictive models for the 6-minute walk test across diverse adolescent developmental stages.

The six-minute walking test (6MWT) is commonly used to measure functional capacity in field settings, primarily through the distance covered. This study aims to establish reference curves for the six-minute walking distance (6MWD) and peak heart rate (PHR) and develop a predictive equation for cardiovascular capacity in Tunisian children and adolescents. A total of 1501 participants (706 boys and 795 girls), aged 10-18years, were recruited from schools in Tunisia. The Lambda (L), Mu (M), and Sigma (S) methods (LMS method) were employed to develop smoothed percentile curves for 6MWD and PHR. Multivariate linear regression was utilized to formulate a prediction equation for 6MWD. Smoothed percentiles (3rd, 10th, 25th, 50th, 75th, 90th, and 97th) for 6MWD and PHR were presented with age. All variables showed a strong positive correlation (p<0.001) with a six-minute walking distance (r ranged from 0.227 to 0.558 for girls and from 0.309 to 0.610 for boys), except resting heart rate, which showed a strong negative correlation (girls: r=-0.136; boys: r=-0.201; p<0.001). Additionally, PHR showed a weak correlation (p>0.05). The prediction equations, based on age as the primary variable, were established for both genders. For boys: 6MWD=66.181+38.142×Age (years) (R2=0.372; Standard Error of Estimate (SEE)=122.13), and for girls: 6MWD=105.535+28.390×Age (years) (R2=0.312; SEE=103.66). The study provides normative values and predictive equations for 6MWD and PHR in Tunisian children and adolescents. These findings offer essential tools for identifying, monitoring, and interpreting cardiovascular functional deficits in clinical and research settings.

Probabilistic Seismic Hazard Assessment of the Southwestern Region of Saudi Arabia

In relation to its rapid infrastructure expansion, exemplified by projects like the Najran Valley Dam or the rehabilitation of agricultural terraces, Saudi Arabia stands out among the Arabian Gulf nations. To mitigate the earthquake-related risks effectively, it is imperative to conduct an exhaustive analysis of its natural hazards. The southwesternmost region of Saudi Arabia is the main subject area of this study for the probabilistic seismic hazard assessment (PSHA), which aims to identify the peak ground acceleration (PGA) and spectral acceleration (SA) values. The investigation encompasses a 10% and 5% probability of occurrence over a 50-year exposure time for both B/C and C NEHRP soils. In order to take into account the earthquake activity that takes place in the vicinity of the Red Sea Rift, which in fact may have an impact on the seismic hazard in this active tectonic region, different seismic source zones were especially designed for this evaluation. Various characteristics such as the uncertainties related to the b-value, the expected maximum magnitude, and different ground motion prediction equations (GMPEs) were integrated using a logic tree scheme. Additionally, regression relationships between the computed ground motion values were established, and a novel design response spectrum was developed and recommended for several cities. Regarding the key findings, it is significant to highlight that the seismic hazard decreases towards the northeast, when moving away from the Red Sea Rift, confirming anticipated trends where proximity to the rift corresponds to increased seismic hazard. Notably, cities such as Farasan Island, Jazan, Al Qunfundhah, Al Lith and Al Birk present the highest observed hazard values among all the cities analyzed. For these cities, the obtained maximum SA values for both 475 and 975 years under B/C site conditions are as follows: 0.268 g and 0.412 g, 0.121 g and 0.167 g, 0.099 g and 0.150 g, 0.083 g and 0.135 g, and 0.066 g and 0.118 g, respectively. These results emphasize the crucial necessity of adequately evaluating and thoroughly updating the seismic hazard inherent to these particular areas to enhance the risk reduction and disaster readiness initiatives.

Evaluating predictive equations for energy requirements throughout breast cancer trajectory: A comparative study

Background & AimsAccurately estimating resting energy requirements is crucial for optimizing energy intake, particularly in the context of patients with varying energy needs, such as individuals with cancer. We sought to evaluate the agreement between resting energy expenditure (REE) predicted by 40 equations and that measured by reference methods in women undergoing active breast cancer treatment stage (I-IV) and post-completion (i.e., survivors). MethodsData from 4 studies were combined. REE values estimated from 40 predictive equations identified by a systematic search were compared with REE assessed by indirect calorimetry (IC) using a metabolic cart (MC-REE N=46) or a whole-room indirect calorimeter (WRIC-REE N=44). Agreement between methods was evaluated using Bland-Altman and Lin's concordance coefficient correlation (Lin's CCC). Results90 participants (24 % survivors, 61.1% had early-stage breast cancer I or II, mean age: 56.8 ± 11 years; body mass index: 28.7 ± 6.4 kg/m2) were included in this analysis. Mean MC-REE and WRIC-REE values were 1389 ± 199 kcal/day and 1506 ± 247 kcal/day, respectively. Limits of agreement were wide for all equations compared to both MC and WRIC (∼ 300kcal for both methods), including the most commonly used ones, such as Harris-Benedict and Mifflin ST. Jeor equations; none had a bias within ±10% of measured REE, and all had low agreement per Lin's CCC analysis (< 0.90). The Korth equation exhibited the best performance against WRIC and the Lvingston-Kohlstadt equation against MC. Similar patterns of bias were observed between survivors and patients and between patients with stages I-III versus IV cancer. ConclusionMost equations failed to accurately predict REE at the group level, and none were effective at the individual level. This inaccuracy has significant implications for women with or surviving breast cancer, who may experience weight gain, maintenance, or loss due to inaccurate energy needs estimations. Therefore, our research underscores the need for further efforts to improve REE estimation.

Rapid predictive method for the deterioration depth of cement solidified marine soft soil

The deterioration depth (D) is a relatively simple index used to evaluate the deterioration degree of solidified soil. Based on the equivalent relationship between the accelerated deterioration tests and the conventional deterioration tests and the power function form of the D prediction equation, a rapid prediction method is proposed in this study for predicting the D of cement solidified marine soft soil. Deterioration test results of the cement solidified marine soft soil showed that increases in the concentration of seawater accelerated the rate of cement soil deterioration. Deterioration test results of the cement solidified marine soft soil showed that increases in the concentration of seawater accelerated the rate of cement soil deterioration. Additionally, the D obtained from indoor and in-site conventional deterioration tests is almost the same. A rapid prediction method for the D of cement stabilized marine soft soil was established with the equivalent relationship between the accelerated and conventional deterioration tests and a power function form of the deterioration depth prediction equation. The predicted D and the development trend were more consistent with the results of the indoor and in-site conventional deterioration tests.

Tumor morphology evaluation using 3D-morphometric features of renal masses.

To assess the correlation between the general (gender, age, and maximum tumor size) and 3D morphotopometric features of the renal tumor node, following the MSCT data post-processing, and the tumor histological structure; to propose an equation allowing for kidney malignancy assessment based on general and morphometric features. In total, 304 patients with unilateral solitary renal neoplasms underwent laparoscopic (retroperitoneoscopic) or robotic partial or radical nephrectomy. Before the procedure, kidney contrast-enhanced MSCT followed by the tumor 3D-modeling was performed. 3D model of the kidney tumor, and its morphotopometric features, and histological structure were analyzed. The morphotopometric ones include the side of the lesion, location by segments, the surface where the tumor, the depth of the tumor invasion into the kidney, and the shape of tumor. Out of 304 patients, 254 (83.6%) had malignant kidney tumors and 50 (16.4%) benign kidney tumors. In total, 231 patients, out of 254 (90.9%) were assessed for the degree of malignant tumor differentiation. Malignant tumors were more frequent in men than in women (p < 0.001). Mushroom-shaped tumors were the most common shapes among benign renal masses (35.2%). The most common malignant kidney tumors had spherical with a partially uneven surface (27.6%), multinodular (tuberous (27.2%)), and spherical with a conical base (24.8%) shapes. Logistic regression model enabled the development of prognostic equation for tumor malignancy prediction ("low" or "high"). The univariate analysis revealed the correlation only between high differentiation (G1) and a spherical tumor with a conical base (p = 0.029). The resulting logistic model, based on the analysis of such predictors as gender and form of kidney lesions, demonstrated a large share (87.6%) of correct predictions of the kidney tumor malignancy.

Prediction of stress level in military submariners, based on physical conditioning and sleep quality variables

The objective of the study was to predict the level of stress in military submariners based on physical fitness and sleep quality variables. Cross-sectional and correlational research, with a sample of 40 male submariners (28.70±3.98 years old). Body mass and composition data were analyzed (MCT), height, BMI, waist, body fat (%G), dominant handgrip (PMDom), cardiorespiratory fitness (VO2max), squats, sit-ups, relative power of lower limbs (PotRel MMII), stress (PSS-10), Epworth Sleepiness Assessment (ESE) and Pittsburgh Sleep Quality Index (PSQI). Overall, negative associations (p&lt;0.05) were observed between VO2max and MCT, BMI, %BF, and waist; PotRel MMII and age and %BF; squat and %G; sit-up and MCT, BMI, %BF and waist; and finally, stress and VO2max and sit-up. Furthermore, positive associations (p&lt;0.05) between BMI and MCT; %BF and MCT and BMI; waist and age, BMI, MCT, and %BF; squats and PMdom., VO2max and PotRel MMII; sit-ups and VO2max, PotRel LL and squats; ending with PSQI and stress. Furthermore, among the stress level prediction equation models developed, the equation Stress=15.92+1.538(PSQI)-0.497(VO2max)+0.188(Squat) met the proposed requirements, which is based on sleep quality, cardiorespiratory fitness, and number of squats. Keywords: Submariner; stress, physical fitness, sleep quality, military personal.

The Relationship Between Some Anthropometric Measurements and Pulmonary Volumes to the Numerical Achievement of 800-Meter Event Runners in Palestine

The study aimed to identify the contribution of some anthropometric measurements and pulmonary volumes to the Numerical Achievement of runners in the 800-meter running event at Palestine. The study was conducted on a purposely-designed sample of (17) runners in Palestine, aged between (18-22) years. The researchers used the descriptive analytical approach because it suits the nature of the study. Anthropometric measurements were performed related to (age, body mass, height, arm length, leg length, thigh length, lower leg length, instep length, chest circumference, chest circumference with inspiration, abdominal circumference, thigh circumference, and Leg calf, upper arm circumference, and related Pulmonary volume measurements. Related Pulmonary volume measurements were performed (VC, FVC, FEV1, FWV1/FVC%, MVV, TV, RV), and after the data was collected, it was processed statistically using SPSS. The results of the study showed that the anthropometric measurement that have the most contribution In the Numerical Achievement of 800 meters running event runners in Palestine was Height, which contributed to explaining (43.1 %) of the finishing time. The study also found that Pulmonary volume measurements contributed most to the Numerical Achievement For runners of the 800- meter running event in Palestine, was Vital Capacity (VC)which explained (39.1%) of the time Achievement. Researchers recommend that the predictive equations that have been developed should be used as predictors for the numerical achievement of the 800-meter running event.

Collar plate effect on local joint flexibility of tubular K-joints under IPB moments: Parametric study and predictive equations

This study delves into the Local Joint Flexibility (LJF) of tubular K-joints reinforced with the collar plates under in-plane bending moments (IPBMs). 348 reinforced K-joints were simulated to analyze the impacts of the loading conditions (balanced and unbalanced moments), collar plate size (like the length and thickness) alongside the joints’ parameters (θ, γ, β, ξ) on the fLJF and its proportionality (ψ). The research outcomes demonstrate that factors such as η, λ, and β play a significant role in determining ψ, whereas the influence of ξ, and γ on ψ appears to be negligible. Also, in the reinforced joints, the fLJF is decreased by 77.4 % compared to the equivalent un-reinforced joint. While the role of the collar plate on the fLJF is remarkable, the matter had not been investigated on K-joints. Therefore, following the detailed parametric study, two novel equations are proposed to safety estimate the fLJF for such scenarios.

Sex estimation using Magnetic Resonance Imaging measurements of hand and foot in Egyptian population

BackgroundThe identification of skeletal remains begins with a sex evaluation since other biological profile elements, such as size and age, are sex-specific. The pelvis is the favored element for sex assessment since it is very sexually dimorphic.Aim of the studyDelivering hand and foot bones sex estimate criteria for Egyptian population identification was the goal of this work.Subject and methodsEighty-two Egyptian adult subjects (41 males and 41 females) aged ≥ 21 years old were subjected to MRI scan on the right hand and foot to assess 9 measurements: hand length, hand width, four measurements of middle metacarpal bone (length, breadth, head breadth and base breadth), first metatarsal bone length, first metatarsal bone width and (first metatarsal bone length x first metatarsal bone width).ResultsAll the measured parameters in the right hand and foot were higher in males than females. First metatarsal bone length x first metatarsal bone width in the foot and middle metacarpal bone breadth in the hand were the most sexually dimorphic parameters, with accuracy of 86.6 percent and 84.1 percent, respectively. In stepwise discriminant analysis, three of nine measurements were selected: First metatarsal bone length x first metatarsal bone width, middle metacarpal bone breadth and hand width for the sex prediction equation in the Egyptian population, with a cross-validated sex classification accuracy of 90.2%.ConclusionSex can be assessed from hand and foot metric parameters measured by MRI with high accuracy.

Development of a novel Bluetooth Low Energy device for proximity and location monitoring in grazing sheep

Monitoring animal location and proximity can provide useful information on behaviour and activity, which can act as a health and welfare indicator. However, tools such as global navigation satellite systems (GNSS) can be costly, power−hungry and often heavy, thus not viable for commercial uptake in small ruminant systems. Developments in Bluetooth Low Energy (BLE) could offer another option for animal monitoring, however, BLE signal strength can be variable, and further information is needed to understand the relationship between signal strength and distance in an outdoor environment and assess factors which might affect its interpretation in on-animal scenarios. A calibration of a purpose-built device containing a BLE reader, alongside commercial BLE beacons, was conducted in a field environment to explore how signal strength changed with distance and investigate whether this was affected by device height, and thus animal behaviour. From this calibration, distance prediction equations were developed whereby beacon distance from a reader could be estimated based on signal strength. BLE as a means of localisation was then trialled, firstly using a multilateration approach to locate 16 static beacons within an ∼5 400 m2 section of paddock using 6 BLE readers, followed by an on-sheep validation where two localisation approaches were trialled in the localisation of a weaned lamb within ∼1.4 ha of adjoining paddocks, surrounded by nine BLE readers. Validation was conducted using 1 days’ worth of data from a lamb fitted with both a BLE beacon and separate GNSS device. The calibration showed a decline in signal strength with increasing beacon distance from a reader, with a reduced range and earlier decline in the proportion of beacons reported at lower reader and beacon heights. The distance prediction equations indicated a mean underestimation of 12.13 m within the static study, and mean underestimation of 1.59 m within the on-sheep validation. In the static beacon localisation study, the multilateration method produced a mean localisation error of 22.02 m, whilst in the on-sheep validation, similar mean localisation errors were produced by both methods – 19.00 m using the midpoint and 23.77 m using the multilateration method. Our studies demonstrate the technical feasibility of localising sheep in an outdoor environment using BLE technology; however, potential commercial application of such a system would require improvements in BLE range and accuracy.

Resting Energy Expenditure Equations Have Lower Accuracy for Adolescents with Overweight/Obesity Versus Healthy-Weight Adolescents.

Objective: The objectives of the study were (1) to assess whether resting energy expenditure (REE) equations have comparable validity for adolescents with overweight/obesity vs. adolescents with healthy weight and (2) to examine determinants of measured REE in adolescents with overweight/obesity vs. adolescents with healthy weight. Methods: Ten equations were used to predict REE for 109 adolescents (70% males; 36.7% with overweight/obesity); 95% equivalence testing was used to assess how well each equation agreed with the criterion measure of indirect calorimetry. Linear regression models were fitted to examine how much REE variance was accounted for by age, sex, race, fat-free mass (FFM), and fat mass. Results: For adolescents with healthy weight, all ten equations were significantly equivalent to the criterion measure within ±8.4% (p < 0.05), whereas for participants with overweight/obesity, only three equations were equivalent within the same range (p < 0.05). Controlling for age, sex, race, fat mass, and FFM accounted for 74% of REE variance. FFM explained the greatest amount (26%) of variance in REE, while weight status itself explained an additional 22%. Conclusions: Prediction equations tend to be more accurate for adolescents with healthy weight than adolescents with overweight/obesity unless the original sample specifically included participants with overweight/obesity. Determinants of REE are similar regardless of weight status.

Valid and accurate simple equation to predict 3,000-m steeplechase performance.

Predict running performances is very important for athletes and trainers. Sport researchers have therefore developed certain tools to predict running performances, but only in non-obstacle races. This study aimed to develop and test the validity and accuracy of an equation for predicting 3,000-m steeplechase performance (PerfSteeple ). The official rankings of French runners for the 3,000-m track-running (Perf3000 ) and 3,000-m steeplechase events were examined. Age, height and body mass were collected. From 146 included athletes, two groups were randomly composed: one comprising 80% of the sample (n = 117) to develop a simple equation to predict PerfSteeple (i.e., development group) and the other comprising the remaining 20% (n = 29) to test the validity and accuracy of the developed prediction equation (i.e., cross-validation group). The simple prediction equation included Perf3000 and age: . No significant difference was noted between the actual and predicted performances. Predicted performances were significantly correlated with the actual ones, with a very high correlation coefficient (p < 0.001; r = 0.929). Bias and 95% limits of agreement were -5 ± 24 s, i.e., -0.8 ± 7.6%. In 95 of 100 new predictions, the difference between actual and predicted performance would be less or equal to-5 ± 24 s. The study confirms the validity and accuracy of the equation for predicting PerfSteeple . Predictions using this simple equation may be used in training and competitions for athletes and coaches. PerfSteeple = -57,165 + 1,147 X Perf3000 + 0,955 X age.

Morphological human bone features and demography controlling damage accumulation and fracture: a finite element study

Prediction of bone fracture risk is clinically challenging. Computational modeling plays a vital role in understanding bone structure and diagnosing bone diseases, leading to novel therapies. The research objectives were to demonstrate the anisotropic structure of the bone at the micro-level taking into consideration the density and subject demography, such as age, gender, body mass index (BMI), height, weight, and their roles in damage accumulation. Out of 438 developed 3D bone models at the micro-level, 46.12% were female. The age distribution ranged from 23 to 95 years. The research unfolds in two phases: micro-morphological features examination and stress distribution investigation. Models were developed using Mimics 22.0 and SolidWorks. The anisotropic material properties were defined before importing into Ansys for simulation. Computational simulations further uncovered variations in maximum von-Misses stress, highlighting that young Black males experienced the highest stress at 127.852 ± 10.035 MPa, while elderly Caucasian females exhibited the least stress at 97.224 ± 14.504 MPa. Furthermore, age-related variations in stress levels for both normal and osteoporotic bone micro models were elucidated, emphasizing the intricate interplay of demographic factors in bone biomechanics. Additionally, a prediction equation for bone density incorporating demographic variables was proposed, offering a personalized modeling approach. In general, this study, which carefully examines the complexities of how bones behave at the micro-level, emphasizes the need for an enhanced approach in orthopedics. We suggest taking individual characteristics into account to make therapeutic interventions more precise and effective.

Post-earthquake rapid seismic demand estimation at unmonitored locations via Bayesian networks

Post-earthquake safety assessment of buildings and infrastructure poses significant challenges, often relying on time-consuming visual inspections. To expedite this process, safety criteria based on a demand-capacity model are utilized. However, rapid assessment frameworks require accurate estimations of intensity measures (IMs) to estimate seismic demand and assess structural health. Unfortunately, post-earthquake IM values are typically only available at monitored locations equipped with sensors or monitoring systems, limiting broader assessments. Simple spatial interpolation methods, while possible, struggle to consider crucial physical factors such as earthquake magnitude, epicentral distance, and soil type, leading to substantial estimation errors, especially in areas with insufficient or non-uniform seismic station coverage. To address these issues, a novel framework, BN-GMPE, combining a Bayesian network (BN) and a ground motion prediction equation (GMPE), is proposed. BN-GMPE enables inference and prediction under uncertainty, incorporating physical parameters in seismic wave propagation. A further novelty introduced in this work regards separating the near and far seismic fields in the updating process to attain a clearer understanding of uncertainty and more accurate IM estimation. In the proposed approach, a GMPE is employed for the estimation, and the bias and standard deviation of the prediction error are updated after any new information is entered into the network. The proposed method is benchmarked against a classic Kriging interpolator technique, considering some recent earthquake shocks in Italy. The proposed BN framework can naturally extend for estimating the probability of failure of various structures in a targeted region, which represents the ultimate aim of this research.

Novel approach for energy-spectrum-based probabilistic seismic hazard analysis in regions with limited strong earthquake data

With the rapid development of energy-based seismic design, probabilistic seismic hazard analysis (PSHA) in terms of the input energy spectrum, E I, has become increasingly important. Generally, implementing E I-based PSHA requires a ground-motion prediction equation (GMPE) for E I. However, although a GMPE for E I can be constructed in regions with abundant earthquake data based on regression analyses, it is difficult to obtain in regions lacking strong ground-motion records. Therefore, this study proposes a new approach for performing E I-based PSHA in regions with limited earthquake data. Instead of using a GMPE for E I directly, a model of Fourier amplitude spectrum (FAS) is adopted, which can be determined using a small number of earthquake data with small-to-moderate magnitudes. Then, the E I of the ground motion is obtained from FAS based on the relationship between E I and FAS. Furthermore, to calculate the annual intensity exceedance rate within the proposed framework of adopting the FAS model, a highly efficient method, namely, the moment method, is applied. Several numerical examples indicate that the proposed approach not only is suitable for regions lacking strong ground-motion records but also performs very efficiently in calculating the annual intensity exceedance rate.

Variations in bioelectrical impedance devices impact raw measures comparisons and subsequent prediction of body composition using recommended estimation equations

Background & AimsBioelectrical impedance analysis (BIA) for body composition estimation is increasingly used in clinical and field settings to guide nutrition and training programs. Due to variations among BIA devices and the proprietary prediction equations used, studies have recommended the use of raw measures of resistance (R) and reactance (Xc) within population-specific equations to predict body composition. ObjectiveWe compared raw measures from three BIA devices to assess inter-device variation and the impact of differences on body composition estimations. MethodsRaw R, Xc, impedance (Z) parameters were measured on a calibrated phantom and athletes using tetrapolar supine (BIASUP4), octapolar supine (BIASUP8), and octapolar standing (BIASTA8) devices. Measures of R and Xc were compared across devices and graphed using BIA vector analysis (BIVA) and raw parameters were entered into recommended athlete-specific equations for predicting fat-free mass (FFM) and appendicular lean soft tissue (ALST). Whole-body FFM and regional ALST were compared across devices and to a criterion five-compartment (5C) model and dual energy X-ray absorptiometry for ALST. ResultsData from 73 (23.2 ± 4.8y) athletes were included in the analyses. Technical differences were observed between Z (range 12.2 - 50.1Ω) measures on the calibrated phantom. Differences in whole-body impedance were apparent due to posture (technological) and electrode placement (biological) factors. This resulted in raw measures for all three devices showing greater dehydration on BIVA compared to published norms for athletes using a separate BIA device. Compared to the 5C FFM, significant differences (p < 0.05) were observed on all three equations for BIASUP8 and BIASTA8, with constant error (CE) from -2.7 to -4.6 kg; no difference was observed for BIASUP4 or when device-specific algorithms were used. Published equations resulted in differences as large as 8.8 kg FFM among BIA devices. For ALST, even after a correction in the error of the published empirical equations, all three devices showed significant (p<0.01) CE from -1.6 to -2.9 kg. ConclusionsRaw bioimpedance measurements differ among devices due to technical, technological, and biological factors, limiting interchangeability of data across BIA systems. Professionals should be aware of these factors when purchasing systems, comparing data to published reference ranges, or when applying published empirical body composition prediction equations

The Development of Normative Fitness Data and Analyzing the Relationships Between 20MSFT and 2.4-km Run Performance in Australian Police Recruits.

Campbell, P, Maupin, D, Lockie, RG, Dawes, JJ, Simas, V, Canetti, E, Schram, B, and Orr, R. The development of normative fitness data and analyzing the relationships between 20MSFT and 2.4-km run performance in Australian police recruits. J Strength Cond Res XX(X): 000-000, 2024-Aerobic fitness testing plays a significant role in the academy training of law enforcement recruits. There is a lack of normative data for law enforcement recruits and substantial interchangeability for choice of field-based aerobic tests. Therefore, this study aimed to develop normative percentile rankings for the 20-m multistage fitness tests (20MSFT) and 2.4-km run specific to law enforcement recruits; and to analyze the relationship between the 2 tests by linear regression. Data from 5 cohorts of law enforcement recruits completing 20MSFT (n = 1,536) and 2.4-km run (n = 1,499) testing during basic training at an Australian Police Academy were retrospectively analyzed. Percentile ranks were calculated (20th, 40th, 50th, 60th, 80th, and 99th) based on the number of shuttles completed and time (seconds) to complete the 2.4-km run. Results were split by sex and age (i.e., <20 years, 20-29 years, 30-39 years, and 40-49 years). Linear regression analyzed the relationship between the 20MSFT to the 2.4-km run (using both seconds and km·h-1), producing predictive equations to translate scores between the 2 assessments. These data presented the first detailed normative values by age and sex for Australian law enforcement recruits. Furthermore, the results demonstrated regression models could explain 65-74% of the variance observed (r2 = 0.649-0.741) between 20MSFT performance and 2.4-km run performance. This study's findings allow for normative performance for the purpose of benchmarking fitness, setting performance goal, and rehabilitation from injury. In addition, a valid conversion through a linear regression affords cross-agency comparisons and temporal changes in test selection/recruit cohorts.

Population-specific equations of age-related maximum handgrip force: a comprehensive review.

The measurement of handgrip force responses is important in many aspects, for example: to complement neurological assessments, to investigate the contribution of muscle mass in predicting functional outcomes, in setting realistic treatment goals, evaluating rehabilitation strategies. Normative data about handgrip force can assist the therapist in interpreting a patient's results compared with healthy individuals of the same age and gender and can serve as key decision criteria. In this context, establishing normative values of handgrip strength is crucial. Hence, the aim of the this study is to develop a tool that could be used both in rehabilitation and in the prevention of work-related musculoskeletal disorders. This tool takes the form of population-specific predictive equations, which express maximum handgrip force as a function of age. In order to collect data from studies measuring maximum handgrip force, three databases were searched. The search yielded 5,058 articles. Upon the removal of duplicates, the screening of abstracts and the full-text review of potentially relevant articles, 143 publications which focussed on experimental studies on various age groups were considered as fulfilling the eligibility criteria. A comprehensive literature review produced 1,276 mean values of maximum handgrip force. A meta-analysis resulted in gender- and world region-specific (general population, USA, Europe and Asia) equations expressing maximum force as a function of age. The equations showed quantitative differences and trends in maximum handgrip force among age, gender and national groups. They also showed that values of maximum handgrip force are about 40% higher for males than for females and that age-induced decrease in force differs between males and females, with a proved 35% difference between the ages of 35 and 75. The difference was lowest for the 60-64 year olds and highest for the 18-25 year-olds. The equations also showed that differences due to region are smaller than those due to age or gender. The equations that were developed for this study can be beneficial in setting population-specific thresholds for rehabilitation programmes and workstation exposure. They can also contribute to the modification of commonly used methods for assessing musculoskeletal load and work-related risk of developing musculoskeletal disorders by scaling their limit values.

Layup design and mechanical properties of an optimal dome profile

AbstractThe development of lightweight and high‐performance composite pressure vessels have become a popular research objective. The purpose of this study is to the layup design and improve the mechanical properties of pressure vessel structure with optimal dome profile under an internal pressure of 70 MPa. First, the prediction equations of fiber thickness for the cylindrical and dome sections are provided. Second, the influence laws of linear parameters on fiber layer thickness distribution are analyzed. Third, the optimal dome profile is used as the pressure vessel structure for the layup design, and the variable polar hole process is applied to solve the fiber thickness accumulation problem near the polar holes. Finally, the composite pressure vessel is modeled using Abaqus finite element software, and the stress and strain distributions of the liner and the composite layer under different internal pressure loads are analyzed under self‐tightening pressure. Results show that the variable polar hole process reduces the maximum thickness value by nearly 50.16% at the maximum fiber thickness of the dome. Under working pressure, the maximum stress of the liner is reduced by 43.41% after applying self‐tightening pressure. In addition, the variable polar hole process can effectively realize the lightweighting of composite pressure vessels while self‐tightening pressure can effectively improve the mechanical properties of the liner. This research provides a valuable reference for the design of composite pressure vessels.Highlights Fiber accumulation occurs in two bandwidth regions near the polar hole. The variable polar hole process can solve the fiber accumulation problem. The optimum dome profile geometric parameters are m = 0.8 and rc = 0.4R. The self‐tightening pressure improves liner loading capacity.

What the hay: predicting equine voluntary forage intake using a meta-analysis approach

To properly formulate diets, the ability to accurately estimate feed intake is critical as the amount of feed consumed will influence the amount of nutrients delivered to the animal. Inaccurate intake estimates may lead to under- or over-feeding of nutrients to the animal. Individual differences in equine forage intake are well-known, but predictive equations based on animal and nutritional factors are not comprehensive. The objective of the present study was to consolidate the current body of knowledge in the published literature on voluntary forage DM intake (VFDMI) in equines and conduct a meta-analysis to identify driving factors, sources of heterogeneity, and develop predictive equations. Therefore, a systematic literature search was applied and identified 61 publications which met the inclusion criteria. From each study, the outcomes of interest (e.g., forage intake), diet composition (e.g., forage information, nutrient composition), and animal factors (e.g., sex, age, breed, BW, exercise level) were extracted. Forage intake was analyzed as two different outcome variables: (1) VFDMI in kg/d and (2) VFDMI in g/kg BW. Linear mixed model analysis treating study as a random effect was applied, using a backward−stepping approach to identifying potential driving variables for VFDMI (both units) where all terms have P < 0.1. The best fitting models for VFDMI included similar factors (also across kg/d and g/kg BW) such as forage quality (i.e., neutral detergent fiber or CP content), forage type (i.e., grass, legume, or mixed), the animals’ size category (i.e., horses vs ponies), and some management factors (i.e., pasture access). As anticipated, forage intake increased when higher quality forages were fed (i.e., lower neutral detergent fiber or higher CP), potentially due to improved digestibility. Additionally, VFDMI increased as BW increased but ponies increased their VFDMI more per every kg increase in BW compared to horses. Lastly, pasture access (i.e., grazing) may influence VFDMI such that pastured animals consume less than stalled animals, possibly due to the time it takes to graze forage. In conclusion, equations to predict equine VFDMI with high accuracy and precision (concordance correlation coefficient = 0.82 – 0.95; root mean squared error RMSE = 0.82–5.49) were developed which could be applied in practice by equine nutritionists or owners and managers. The results of this meta-analysis confirm that animal traits and forage quality have a significant impact on the VFDMI of equines and should be accounted for when formulating diets to ensure nutritional requirements are met.