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Accurately quantifying cardiorespiratory fitness (CRF) through cardiopulmonary exercise testing (CPET) is increasingly important for improving risk assessment and guiding clinical decisions. However, research on V̇O 2 peak reference values and predictive equations for the Chinese population remains limited. This study aimed to establish a V̇O 2 peak predictive equation for Chinese adults. This study analyzed healthy participants who underwent CPET at Peking University Third Hospital (PUTH) from September 1, 2017, to September 1, 2023. Data from September 1, 2017, and August 31, 2021 were used as the derivation cohort, and September 1, 2021, to September 1, 2023 were utilized as an external validation cohort for temporal validation. The derivation cohort underwent backward multivariate regression analysis to generate the V̇O 2 peak prediction equation, which was compared with the widely-used Wasserman, FRIEND and Xiangya equations. The PUTH derivation cohort (N = 4531, mean age: 50.7 years, 18–88 years) and validation cohort (N = 4624, mean age: 46.1 years, 18–89 years) included 48.8 and 48.5% men, respectively. With increasing age, both men and women V̇O 2 peak exhibited a general decline. The predictive equation for V̇O 2 peak was established based on the derivation cohort: V̇O 2 peak (mL·min −1 ) =  −24364.9 − 621.3 × Sex (Women = 1, Men = 2) −10.7 × Age + 0.2 × Height 2 (cm) + 6464.7 × Log(BMI) −24997.2 × Log(BSA) +12388.6 × Log(LBM) (adjusted R 2  = 0.624, p  < 0.001). It demonstrated higher consistency between measured and predicted results compared to Xiangya, Wasserman, and FRIEND equations. This study presents the PUTH equation, a new V̇O 2 peak prediction equation for Chinese adults. Compared to existing equations, the PUTH equation shows reduced bias and improved accuracy, providing a more reliable tool for assessing CRF and guiding clinical interventions in the Chinese population.

This study was included 155 records of Awassi ewes and 199 records of lambs born during two seasons (2011-2012), belonging to the College of Agriculture and Forestry, Mosul University. The effect of year was highly significant on all traits except for weight gain from weaning to 180 days (GW180d). Age of dam was significantly affected daily milk yield (DMY), birth weight (BW), weaning weight (WW) and gain from birth to weaning (GBW). Type of birth had significant  effect on DMY, BW,WW and weight at 180 days. The effect of lamb sex on WW, GBW was significant. Significant correlations coefficient were observed between DMY and total milk yield (TMY), months weight of lambs, GBW and GB180d being ranged from 0.46 to 0.99 and -0.44 to 0.99 respectively. The R2 values of prediction equations were high and ranged between 0.81 to 0.99 to predict TMY, and 0.97 to predict lamb weight at 180 days.

This study investigates the influence of various dielectric fluids on the performance of Electric Discharge Machining (EDM) in machining Waspaloy, a corrosion-resistant superalloy known for its high hardness and enhanced corrosion resistance. The purpose of this work is to fill the knowledge gap about the machining of Waspaloy using different dielectric fluids by using a Copper-5Graphite (CuGr5) composite tools. Experiments were conducted using a EDM machine with copper graphite composite electrodes and five distinct dielectric fluids, including hydrocarbon oil, kerosene, sunflower oil, used motor oil, and groundnut oil. The effects of key process parameters such as current, voltage, pulse on time, pulse off time, and gap distance on Material Removal Rate (MRR) and Surface Roughness (Ra) were evaluated. Dielectric fluid properties, including viscosity, density, thermal conductivity, and dielectric strength, were comprehensively characterized. Results revealed that MRR increased with current and pulse-on time up to a threshold, beyond which thermal damage reduced efficiency. Sunflower oil demonstrated the most favorable performance, achieving an MRR of up to 0.570 mm³/min and Ra as low as 1.012 μm, attributed to its high dielectric strength (40 kVA), moderate viscosity, and superior thermal conductivity. In contrast, kerosene and hydrocarbon oil, while effective in debris flushing, resulted in inconsistent spark stability and increased surface roughness at higher energy settings due to lower dielectric strength and flash points. Used motor oil and groundnut oil, though sustainable, exhibited higher surface roughness and limited MRR under elevated parameter settings owing to their higher viscosity and lower heat dissipation capabilities. A novel predictive equation for MRR and Ra, integrating dielectric fluid properties and machining parameters, was developed to enhance process optimization. Surface morphology analysis using SEM revealed characteristic features such as craters, recast layers, microcracks, and resolidified debris, highlighting the interplay between thermal, electrical, and mechanical effects during EDM. This research promotes sustainable manufacturing by assessing bio-based and waste-derived dielectric fluids as environmentally responsible alternatives to conventional EDM oil.

Current prediction models for risk of cardiovascular disease (CVD) incidence incorporate smoking as a dichotomous yes/no measure. However, the risk of CVD associated with smoking also varies with the intensity and duration of smoking and there is a strong association between time since quitting and the risk of disease onset. This study aims to develop improved risk prediction equations for CVD incidence incorporating intensity and duration of smoking and time since quitting.The risk of developing a first CVD event was evaluated using a Cox's model for participants in the Framingham offspring cohort who attended the fourth examination (1988-92) between the ages of 30 and 74 years and were free of CVD (n=3751). The full models based on the smoking variables and other risk factors, and reduced models based on the smoking variables and non-laboratory risk factors demonstrated good discrimination, calibration and global fit. The incorporation of both time since quitting among past smokers and pack-years among current smokers resulted in better predictive performance as compared to a dichotomous current/non-smoker measure and a current/quitter/never smoker measure. Compared to never smokers, the risk of CVD incidence increased with pack-years. Risk among those quitting more than five years prior to the baseline exam and within five years prior to the baseline exam were similar and twice as high as that of never smokers. A CVD risk equation incorporating the effects of pack-years and time since quitting provides an improved tool to quantify risk and guide preventive care.

•Fat-free mass predictive equation was developed and cross-validated using single-frequency bioelectrical impedance and age at peak height velocity.•The new fat-free mass predictive equation is accurate for male adolescent athletes.•The new equation was developed using more economical and less complex variables. This is a cross-sectional study, aimed to develop and cross-validate a fat-free mass (FFM) predictive equation using single-frequency bioelectrical impedance (BIA), considering the predicted age at peak height velocity (PHV) as a variable. Additionally, the study aims to test the FFM-BIA obtained using a previous predictive equation that used skeletal maturity as a variable. The participants (n = 169 male adolescent athletes) were randomly divided into two groups: development of a new predictive equation (n = 113), and cross-validation (n = 56). The concordance test between the FFM values obtained by Koury et al. predictive equation and DXA data was determined (n = 169). Bioelectrical data was obtained using a single-frequency analyzer. Among the models tested, the new predictive equation has resistance index (height2/resistance) and predictive age at PHV as variables and presented R2 = 0.918. The frequency of maturity status using skeletal maturity and PHV diagnosis was inadequate (Kappa = 0.4257; 95%CI = 0.298–0.553). Bland-Altman plots and concordance correlation coefficient showed substantial concordance between the FFM-DXA values (48.8 ± 11.2 kg) and the new predictive equation (CCC = 0.960). The results showed that the new equation performed better than the equation developed by Koury et al. (CCC = 0.901). Our results show that it is feasible to predict FFM in male adolescent athletes using predictive age at PHV, with moderate concordance. The calculation of FFM using more economical and less complex variables is viable and should be further explored.

Resting metabolic rate (RMR), which accounts for 60% to 75% of total daily energy expenditure, is critical for formulating appropriate nutrition plans and for the prevention of overweight and obesity. The aim of this study was to systematically consider dietary and other factors affecting RMR and propose a predictive equation for the older adults. A total of 373 elderly participants aged 60 to 89 years (205 males) were included in this study. RMR was measured using indirect calorimetry (IC). One-on-one measurements and questionnaires were used to collect data on height, weight, waist circumference, physical activity, sleep duration, and food consumption frequency. Multiple linear regression was used to construct models, which were compared with existing equations. The RMR values of the study participants ranged from 652 to 1635 kcal/d. The average RMR for males and fe-males was 1175.3 ± 167.9 kcal/d and 1001.5 ± 159.7 kcal/d, respectively. Two models were constructed using multiple regression, with variables including sex, weight, fat-free mass (FFM), fat mass (FM), age, and animal offal consumption. The newly established formula demonstrated better accuracy than the other formulas based on comparisons of biases, Lin’s Concordance Correlation Coefficient (CCC), root mean square errors (RMSE), accuracies, and Bland-Altman plots. This study developed new RMR predictive equations for individuals aged 60 and above. The newly developed equations in-corporates animal offal consumption and demonstrates higher predictive performance compared to other equations. •A new predictive equation for estimating resting metabolic rate (RMR) in elderly Chinese adults has been developed.•Dietary factor, specifically animal offal intake, has been integrated, alongside traditional variables such as sex, weight, fat-free mass (FFM), fat mass (FM), and age.•The new equation outperforms existing RMR equations in terms of accuracy, bias, Lin’s Concordance Correlation Coefficient (CCC), and root mean square error (RMSE), with the latter tend to overestimate RMR.

This study aimed to develop a predictive equation for basal metabolic rate (BMR) in normal-weight Chinese adults and provide a reference for establishing the national recommended dietary energy intake. A new equation for BMR was derived from a sample of 516 normal-weight Chinese adults (men = 253, women = 263), and this sample was collected from two previous studies. Furthermore, the accuracy of this new equation and eight other previous predictive equations was reviewed. The agreement and reliability were compared in terms of bias, accuracy, the intraclass correlation coefficient, and Bland–Altman plots between predictive equations. In addition, the newly developed equation was further verified using a small independent sample, which contained 41 healthy Chinese adults (men = 21, women = 20). The measured BMR (mBMR) of all participants, measured using indirect calorimetry, was 1346.2 ± 358.0 kcal/d. Thirty participants were excluded based on Cook’s distance criteria (Cook’s distance of ≥0.008). Previous equations developed by Henry, Schofield, Harris–Benedict (H-B), Yang, and Hong overestimated the BMR of healthy Chinese adults. The present equation displayed the smallest average bias (0.2 kcal/d) between the mBMR and predicted basal metabolic rate (pBMR). The limits of agreement of the present equation from Bland–Altman plots were −514.3 kcal/d and 513.9 kcal/d, which is the most narrow and balanced limit of agreement. Moreover, in the verification of the testing database, the pBMR of the new equation was not significantly different from the mBMR, and the accuracy was 75.6%. Compared with pre-existing equations, the present equation is more applicable to the prediction of BMR in healthy Chinese adults. However, further studies are required to verify the accuracy of this new equation.

Purpose Patients after metabolic bariatric surgery (MBS) require attention to maintain energy balance and avoid weight regain. Predictive equations for resting energy expenditure (REE) and total energy expenditure (TEE) are needed since gold standard methods like calorimetry and doubly labeled water are rarely available in routine clinical practice. This study aimed to determine which predictive equation for REE and TEE has the lowest bias in subjects after MBS. Methods MEDLINE, Embase, Web of Science, and CENTRAL searches were performed. Meta-analyses were performed with the data calculated by the predictive equations and measured by the gold standard methods for those equations that had at least two studies with these data. The DerSimonian and Laird random-effects model and the I 2 statistic were used to quantify heterogeneity in the quantitative analyses. The risk of bias was assessed using the Joanna Briggs Institute critical appraisal checklist. Results Seven studies were included. The present study found that the Mifflin St. Jeor (1990) equation had the lowest bias (mean difference =  − 39.71 kcal [95%CI =  − 128.97; 49.55]) for calculating REE in post-BS individuals. The Harris-Benedict (1919) equation also yielded satisfactory results (mean difference =  − 54.60 kcal [95%CI =  − 87.92; − 21.28]). Conclusion The predictive equation of Mifflin St. Jeor (1990) was the one that showed the lowest bias for calculating the REE of patients following MBS. Graphical Abstract

Investigating the downstream bed configuration of culverts is vital for assessing the integrity and performance of hydraulic structures. This study examined the bed topography downstream of a box culvert with a fixed bottom through a series of controlled experiments, investigating the effects of wing-wall angles, particle Froude numbers, and relative tailwater depths on scour. The results reveal that as the experiments approach equilibrium, the fluctuation in maximum scour depth becomes less pronounced, emphasizing the role of temporal factors. Notably, increasing the wing-wall angle results in more extensive scour hole and sediment formations, with significant differences identified between wing-wall angles of 15° and 45°/75°. Additionally, novel equations were developed to estimate critical scour parameters. These findings are crucial for engineers engaged in the design and maintenance of culverts.

Resting energy expenditure (REE) is often estimated in athletes using equations developed from the general population however, the application in athletic-specific populations is questionable. The aim of this systematic review was to compare measured REE and estimations of REE obtained from non-sport participants and athletes. Inclusion criteria met PICO criteria: population - participants involved in organized sport; intervention - resting energy expenditure was obtained by calorimetry; comparator - equations to estimate REE; outcomes - comparisons between measured REE and predicted REE. The search was conducted in Web of Science all databases, PubMed and Scopus. Comparisons between measured REE and predicted REE as well the potential models to estimate REE developed among athletes were summarized. Allowing for variation among studies, equations developed within general populations were not comparable to REE measured by calorimetry in athletes. Equations across athletic samples were obtained but, few studies tested their validity across independent samples of sport participants. Nevertheless, equations developed within athlete populations seem to be widely unused in sports nutrition literature and practice. De Lorenzo and ten Haaf equations appear to present an acceptable agreement with measured REE. Finally, equations used among adults should not be generalised for youth sport participants.