Standard Error Of The Estimate Research Articles

Predicting the higher heating value of microalgae biomass based on proximate and ultimate analysis

Microalgae biomass is a unique feedstock capable of effluent bioremediation and thermochemical conversion. Energetic valorization routes require higher heating values (HHV) as an important parameter for system design. Equations to predict the HHV of various biomass are proposed in the literature, but none is found for microalgae biomass. This study aimed to propose equations to predict the HHV of microalgae biomass based on results from proximate (ash, volatile matter — Vm, fixed carbon — fC, and moisture — M) and ultimate analysis (carbon — C, hydrogen — H, oxygen — O, nitrogen — N, and sulfur — S). The equation based on proximate and ultimate analysis combined (HHV (MJ kg−1) = 20.6 − 0.352 C + 2114 N − 0.379 Vm + 0.1131 fC − 0.0394C N + 0.01166 C Vm) presented the highest statistical fit in terms of determination coefficient (R2 = 0.83), standard error of the estimate (SEy = 1.31 MJ kg−1), predicted residual error sum of squares (PRESS = 77.7), mean absolute error (MAE = 5.55%) and mean bias error (MBE = 0.46%).

Prediction of maximal oxygen uptake from 6-min walk test in pulmonary hypertension.

Maximal oxygen uptake (V′O2max), assessed by cardiopulmonary exercise testing (CPET), is an important parameter for risk assessment in patients with pulmonary hypertension (PH). However, CPET may not be available for all PH patients. Thus, we aimed to test previously published predictive models of V′O2max from the 6-min walk distance (6MWD) for their accuracy and to create a new model.We tested four models (two by Ross et al. (2010), one by Miyamoto et al. (2000) and one by Zapico et al. (2019)). To derive a new model, data were split into a training and testing dataset (70:30) and step-wise linear regression was performed. To compare the different models, the standard error of the estimate (SEE) was calculated and the models graphically compared by Bland–Altman plots. Sensitivity and specificity for correct prediction into low-risk classification (V′O2max >15 mL/min/kg) was calculated for all models.A total of 276 observations were included in the analysis (194/82 training/testing dataset); 6MWD and V′O2max were significantly correlated (r=0.65, p<0.001). Linear regression showed significant correlation of 6MWD, weight and heart rate response (HRR) with V′O2max and the best fitting prediction equation was: V′O2max = 1.83 + 0.031 × 6MWD (m) – 0.023 × weight (kg) – 0.015 × HRR (bpm). SEEs for the different models were 3.03, 3.22, 4.36 and 3.08 mL/min/kg for the Ross et al., Miyamoto et al., Zapico et al. models and the new model, respectively. Predicted mean V′O2max was 16.5 mL/min/kg (versus observed 16.1 mL/min/kg).6MWD and V′O2max reveal good correlation in all models. However, the accuracy of all models is inadequate for clinical use. Thus, CPET and 6MWD both remain valuable risk assessment tools in the management of PH.

Development and Cross-Validation of a Predictive Equation for Fat-Free Mass in Brazilian Adolescents by Bioelectrical Impedance.

The bioelectrical impedance analysis (BIA) is one of the most commonly used techniques for assessing body composition in a clinical setting and in field approaches, as it has the advantages of easy application, fast, and non-invasive, in addition to its relatively low cost. However, the available predictive equations need to be valid for the evaluated subjects. The aim of this study was to verify the validity of several published BIA equations in estimating fat-free mass (FFM) among Brazilian adolescents, in addition to developing and cross-validating a BIA equation to estimate FFM appropriate for Brazilian adolescents. This is a cross-sectional study with 257 adolescents (128 girls) aged 10–19 years, randomly divided into two groups, namely, development (n = 172) and cross-validation (n = 85). The standard technique for assessing FFM was dual X-ray absorptiometry (DXA). The paired t-test, multiple regression, and the Bland-Altman plots were used to test the validity of the proposed models and to perform cross-validation of the model. The equation derived in this study was as follows: FFM = −17.189 + 0.498 (Height2/Resistance) + 0.226 Weight + 0.071 Reactance − 2.378 Sex + 0.097 Height + 0.222 Age; r2 = 0.92; standard error of the estimate = 2.49 kg; the new equation for FFM showed better agreement when compared with that of the equations developed in other countries. In conclusion, the newly developed equations provide a valid FFM estimation and are recommended for Brazilian adolescents with similar characteristics.

KINETICS AND MATHEMATICAL MODELING OF THE DRYING PROCESS OF MACAÚBA ALMONDS

ABSTRACT The study of drying kinetics is fundamental for making the correct choice of time and temperature to be used in the drying process. In addition, mathematical modeling enables the simulation, optimization, sizing, and determination of the commercial application of the drying system. Therefore, the objective of this study was to investigate the kinetics and mathematical modeling of the drying process of macaúba almond [Acrocomia aculeata (Jacq.) Lodd. ex Mart] performed at different temperatures. For this purpose, the drying was performed under three different temperatures: 40 °C, 50 °C, and 60 °C. Four repetitions were performed for each temperature. The experimental data were fitted by nine different mathematical models. The choice of the best model was based on the following statistical parameters: magnitude of the adjusted coefficient of determination, magnitude of the mean relative error, and standard error of the estimate. It was observed that an increase in the drying temperature resulted in a reduction of drying time. The shortest drying time was observed in the treatment performed under 60 °C in which the almonds attained equilibrium moisture content at 34.08 h. The longest drying time was observed in the treatment performed under 40 °C, with the almonds attaining equilibrium moisture content at 404.40 h. Approximation of Diffusion, Midilli, Page, and Modified Page were the models that best described the drying process of macaúba almonds with the aim of subsidizing the design of industrial dryers.

The validation of contemporary body composition methods in various races and ethnicities.

Few investigations have evaluated the validity of current body composition technology among racially and ethnically diverse populations. This study assessed the validity of common body composition methods in a multi-ethnic sample stratified by race and ethnicity. One hundred and ten individuals (55 % female, age: 26·5 (sd 6·9) years) identifying as Asian, African American/Black, Caucasian/White, Hispanic, Multi-racial and Native American were enrolled. Seven body composition models (dual-energy X-ray absorptiometry (DXA), air displacement plethysmography (ADP), two bioelectrical impedance devices (BIS, IB) and three multi-compartment models) were evaluated against a four-compartment criterion model by assessing total error (TE) and standard error of the estimate. For the total sample, measures of % fat and fat-free mass (FFM) from multi-compartment models were all excellent to ideal (% fat: TE = 0·94-2·37 %; FFM: TE = 0·72-1·78 kg) compared with the criterion. % fat measures were very good to excellent for DXA, ADP and IB (TE = 2·52-2·89 %) and fairly good for BIS (TE = 4·12 %). For FFM, single device estimates were good (BIS; TE = 3·12 kg) to ideal (DXA, ADP, IB; TE = 1·21-2·15 kg). Results did not vary meaningfully between each race and ethnicity, except BIS was not valid for African American/Black, Caucasian/White and Multi-racial participants for % fat (TE = 4·3-4·9 %). The multi-compartment models evaluated can be utilised in a multi-ethnic sample and in each individual race and ethnicity to obtain highly valid results for % fat and FFM. Estimates from DXA, ADP and IB were also valid. The BIS may demonstrate greater TE for all racial and ethnic cohorts and results should be interpreted cautiously.

Individual models for diameter and height projection with contribution of competition index in Pinus taeda L. stands

The aim if this work was to assess and propose projection models for diameter at breast height and total height of individual pine trees and the contribution of competition indexes in these models. Data was obtained from 1056 permanent sampling units of non-thinned Pinus taeda L. stands located in the Telêmaco Borba region, Paraná, Brazil, with ages between 3.4 and 19.5 years. In order to project the diameter and total height of the trees, linear models were tested according to the variable in the current age, the projection age in the future, the basal area, and the site index, as well as their transformations. The Spearman correlation was obtained between competition indexes and dendrometric and stand variables, with the GH (Glover and Hool), LO (Lorimer) and ST (Stage) indexes being selected. These indexes were assessed as independent variables in the models, whose contributions were verified through the “F ci ” test on the incremental contribution. The models were assessed through the adjusted coefficient of determination, standard error of the estimate, and boxplots of residuals. The models provided precise and bias-free projections. The competition indexes statistically contributed to diameter and total height projection according to the “F ci ” test, increasing the precision of projected values for the majority of models tested. The indexes with major contributions to individual tree modelling for diameter and total height projection of Pinus taeda were Glover and Hool (GH) and Lorimer (LO), respectively.

HYPSOMETRY AND VOLUMETRY OF Eucalyptus urograndis IN A CROP-FOREST INTEGRATION SYSTEM

Due to the positive impact that the eucalyptus species has on the Brazilian economy, it is currently the most used forest essence. The objective of this work was to evaluate different hypsometric and volumetric models for Eucalyptus urograndis clones (Eucalyptus urophylla S.T. Blak and Eucalyptus grandis W. Hill ex Maiden) in a Crop-Forest Integration (CFI) system. The trees were evaluated at 7 years of age and arranged in double rows, occupying 20.76% of the total system area. The individuals were subjected to rigorous volumetric cubing according to the Smalian method at intervals of one meter up to full height. The following models were evaluated for the collected height data: Linear, Trorey, Stofels, Curtis, Henriksen, Prodan, Chapman &amp; Richards, Petterson and Bailey &amp; Clutter. Furthermore, the Spurr, Hohenald-Krenn, Stoate, Schumacher Hall, Meyer, Husch, Ogaya and Takata models were used for volume data. The results were determined through the coefficient of determination (R2), standard error of the estimate in percentage (Syx%), significance of the regression coefficients (𝛽) and graphical distribution. The hypsometric model which best fit the database among tested models was the Prodan equation, with a coefficient of determination (R²) of 0.89, while the best result for volumetric models was found using the Meyer model, with a coefficient of determination (R²) of 0.99. All evaluated models were efficient in estimating the height and volume of the Crop-Forest Integration (CFI) system, thus demonstrating that GG100 eucalyptus is a good option in integrated systems.

Estimation of stature from foot print: A study on medical students of Bihar

Height and sex from different parts of the body help in solving crime mysteries related to human identity. Similarly, foot or shoe prints if present at the scene of the crime may provide a clue regarding the height and the sex of the person that helps in establishing the partial identity of the suspect. Aims & Objectives is to investigate the relationship between footprint length with sex and to derive a regression equation from footprint length. Footprints of200 subjects (100 males and 100 females), from among asymptomatic, apparently healthy, young adults studying in All India Institute of Medical Sciences (AIIMS), Patna, Bihar, India were taken as a subject for the study. Maximum footprint length and the height of each subject were measured. Predictive equations using linear regression were then derived separately for males, and females and for the combined data with the purpose of estimating the height when only the subject's footprint length is known. It was found that males were taller and have longer feet than females. A correlation coefficient (r) of0.739 in males and 0.6958 in females was obtained between the height and footprint length of the subjects. The standard error of the estimate was 4.6815 in males and 5.081 in females. The study revealed a highly significant degree of correlation between the measurements of footprint lengths and stature.

Optimisation of onion bulb curing using a heat and mass transfer model

Improper curing of onion bulbs leads to high losses during storage. The aim of curing is to seal the onion by drying its outer scales and the neck, limiting weight loss. A coupled heat and mass transfer model was established for the prediction of the moisture and temperature distribution inside onion bulbs. A finite element method was used for discretising the governing equations of transient heat and mass transfer. The predicted results were compared with experimental data of moisture and temperature profiles under controlled curing conditions at temperatures from 30 to 50 °C, and relative humidity values from 30 to 70%. The simulation results agreed well with the experimental data with a small standard error of the estimate varying from 0.06 to 0.042 (decimal, w.b.) and from 0.8 to 2 °C, for moisture content and temperature, respectively. The model revealed sharp moisture gradients establishing near the surface and neck and mostly uniform temperature throughout curing. The validated model was then used to optimise the curing process targeting low overall weight loss, high neck dehydration, and low skin diffusivity. Different relative humidity and curing time combinations were found to be optimal depending on harvesting stage and size of the bulbs and values for the set target criteria. The harvesting stage and relative humidity had a more pronounced effect than other parameters. The model can serve as a digital twin to monitor and control the curing process using measured inputs of curing conditions such as temperature, humidity, and air velocity.

Predictive model specific to young adults for estimating thoracic gas volume for air-displacement plethysmography.

Thoracic gas volume either measured (mTGV) or predicted by the BodPod® (bpTGV) is used during air-displacement plethysmography to obtain a better estimate of percent body fat. Evidence suggests that bpTGV underestimates mTGV for young adults and this is especially evident for young males. We developed, validated, and cross-validated a TGV prediction model (pTGV) for males and females 18-30 years of age to address this underestimation. Participants (N = 181; 18-30 years) that had their body composition assessed with the BodPod® were retrospectively randomly assigned to one of two independent subgroups, a validation (n = 145) or cross-validation (n = 36) sample. Ten iterations of the k-fold validation procedure were performed to assess the internal replicability of pTGV within the validation sample. External replicability of pTGV was evaluated by assessing the difference and standard error of the estimate (SEE) compared to mTGV in the cross-validation group. The model using height, sex and body mass yielded the highest adjusted R2 (0.627) and the lowest SEE (0.56 L): pTGV = 0.615338 × Sex (0 = Female, 1 = Male) + 0.056267 × Height (cm) - 0.011006 × Body Mass (kg) - 5.358839. R2 remained stable across 10 iterations of the k-fold procedure (average R2 = 0.64). Differences between pTGV and mTGV were not significantly different than zero for the total cross-validation sample (-0.06 ± 0.7 L; SEE = 3.0%), for males (-0.11 ± 0.7 L; SEE = 3.7%), or for females (-0.02 ± 0.7 L; SEE = 5.3%). We recommend that when it is impractical to obtain mTGV, the strong internal and external replicability of the new prediction model supports its use for males and females ages 18-30 years old during air-displacement plethysmography.

In silico Prediction of Novel SARS-CoV 3CL pro Inhibitors: a Combination of 3D-QSAR, Molecular Docking, ADMET Prediction, and Molecular Dynamics Simulation

The Chymotrypsin-like protease (3CLpro) is a drug target in the coronavirus because of its role in processing the polyproteins that are translated from the viral RNA. This study applied 3D quantitative structure-activity relationship (3D-QSAR), molecular docking, and ADMET prediction on a series of SARS-CoV 3CLpro inhibitors. The 3D-QSAR study was applied using Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) methods, which gave the cross-validation coefficient (Q2) values of 0.64 and 0.80, the determination coefficient (R2) values of 0.998 and 0.993 and the standard error of the estimate (SEE) values of 0.046 and 0.091, respectively. The acceptable values of the determination coefficient (R2 test) to CoMFA and CoMSIA respectively corresponding to values of 0.725 and 0.690 utilizing a test set of seven molecules prove the high predictive ability of this model. Molecular docking analysis was utilized to validate 3D-QSAR methods and explain the binding site interactions and affinity between the most active ligands and the SARS-CoV 3CLpro receptor. Based on these results, a novel series of compounds were predicted, and their pharmacokinetic properties were verified using drug-likeness and ADMET prediction. Finally, the best-docked candidate molecules were subjected to molecular dynamics (MD) simulation to affirm their dynamic behavior and stability.

3D-QSAR and molecular docking studies of 4-methyl quinazoline derivatives as PI3Kα inhibitors

A new series of 4- methyl quinazoline derivatives was synthesized and its anti-cancer activity was assessed. It was revealed that its compounds have potent inhibition on related phosphoinositide 3-kinases alpha (PI3Kα). In this study, the three-dimensional quantitative structure-activity relationship (3D-QSAR) and molecular docking approaches were performed on a series of 4-methyl quinazoline derivatives with PI3Kα inhibitors. The 3D-QSAR study was applied using Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) methods, which gave the cross-validation coefficient (Q2) values of 0.850 and 0.92, the determination coefficient (R2) values of 0.998 and 0.987, and the standard error of the estimate (SEE) values of 0.017 and 0.105, respectively. The acceptable values of determination coefficient (R2 test) to CoMFA and CoMSIA respectively corresponding to values of 0.793 and 0.804 utilizing a test set of seven molecules prove the high predictive ability of this model. Using AutoDock tools, Molecular docking analysis was utilized to validate 3D-QSAR methods and to explain the binding site interactions and energy between the most active ligands and the PI3Kα (PDB ID: 4JPS) receptor. Based on these results, a novel series of 4- methyl quinazoline derivatives was predicted.

Reference standards for facial measurements in early third trimester South African fetuses, and the effect of maternal and fetal characteristics

abstract Fetal alcohol spectrum disorder (FASD) is a major problem worldwide and dysmorphic facial features may be a prenatal biomarker for FASD. Deviations from normal facial development cannot be explored before establishing the normal variation in a specific population, since ethnic differences may exist. Objectives: Main objective: to establish reference standards for 23 facial measurements on 3D ultrasound volumes obtained between days 196 and 224 of gestation in healthy unexposed South African fetuses from an area with historically high alcohol consumption prevalence and a population group with no existing normative values. Secondary objective: to assess the confounding effect of maternal and fetal characteristics. Design: This study involves 97 women (including 43 smokers) who had been enrolled in the Safe Passage Study (SPS), a large prospective multinational cohort study assessing the effects of prenatal alcohol exposure. They had adequate 3 D ultrasound volumes of the fetal face acquired at 28+0–31+6 weeks in singleton pregnancies without comorbidities, congenital abnormalities or exposure to alcohol, marijuana, or methamphetamines from 4 weeks before conception. Participants, materials, setting, methods: The participants were recruited from two residential areas of low socioeconomic status in Cape Town. Meticulous information was collected on maternal and pregnancy characteristics, including alcohol use at different time points. Gestational age (GA) was based on ultrasound biometry before 24 weeks, and 3D ultrasound volumes were acquired trans-abdominally from a sagittal and axial plane of the fetal face. Volumes were independently assessed offline by two observers and the image with the best landmark definition was used for 23 facial measurements, representing features previously described in children with FASD. The relation to the exact GA was assessed by regression analysis, the expected mean value and standard error of the estimate (SEE) was determined to transform all raw measurements into z-scores, and the effect of possible confounders on z-scores was assessed by ANOVA. Results: Ten variables changed significantly with advancing GA (extraocular diameter, anteroposterior, medio-lateral and supero-inferior ocular diameter, ocular volume, interlens distance, prenasal thickness, nasal bone length, nose length and nose protrusion) and thirteen did not (interocular distance; interocular: extraocular diameter ratio, prenasal thickness: nasal bone length ratio, pronasal-subnasal distance, subnasal-mouth distance, philtrum length, upper vermillion thickness, nose-philtrum angle, maxillary angle, facial height, facial protrusion, frontomaxillary facial angle and maxilla-nasion-mandible angle). Reference values (expected mean and SEE) for the 23 measurements were established for each day. The z-scores of all facial measurements were not independently affected by maternal age, parity, gravidity, smoking or body mass index, but infant sex and birthweight z-score significantly influenced several z-scores (infant sex for extraocular, medio-lateral, and supero-inferior ocular diameter, ocular volume, prenasal thickness and nose protrusion; birthweight z-score for extraocular diameter, interocular and interlens distance, nose protrusion and maxillary angle). Limitations: GA was not always confirmed by first trimester ultrasound and some measurements could not be obtained in all cases due to suboptimal image quality. The cohort included few heavy smokers so an effect of heavy or continued smoking cannot be ruled out, and the effect of ethnicity was not assessed. Conclusions: These are the first local reference standards for fetal facial measurements and, to our knowledge, the first reference standards for the supero-inferior ocular diameter, face protrusion, upper vermillion thickness, maxillary angle, and nose-philtrum angle. They were broadly in keeping with published references, with small discrepancies explained by minor differences in technique. Even in this narrow GA window, the distribution of many variables changed over time and normal variation was significantly influenced by fetal sex and birthweight z-score. The possible confounding effect of these factors needs to be considered when assessing the impact of harmful exposures like alcohol on facial development.

Detoxification of aflatoxin M1 in sarshir by viable and nonviable Limosilactobacillus reuteri and Limosilactobacillus rhamnosus: Kinetic, equilibrium and desorption studies

The main aim of this study was to assess the ability of viable and nonviable Limosilactobacillus strains consisting of L. reuteri and Limosilactobacillus rhamnosus on AFM1 detoxification from Sarshir. Nonviable L. reuteri was the most effective adsorbent and lowered the AFM1 concentration from 0.5 μg kg−1 to 0.02 μg kg−1, followed by nonviable L. rhamnosus, viable L. reuteri and viable L. rhamnosus. The equilibrium data analysis indicated that the Redlich–Peterson gave the best fit with the highest coefficient of determination (R2 = 0.9959–0.9967%) and the lowest standard error of the estimate (SEE = 0.0097–0.0118). In both Limosilactobacillus strains, the kinetics of AFM1 adsorption obeyed pseudo-first-order model with R2 and Chi-square (χ2) values equal to 98.55–99.94% and 0.0062–0.0578, respectively. The desorption efficiency of AFM1 through the regenerated nonviable L. reuteri using distilled water was 72.72% after three cycles, suggesting it could be a preferred recyclable candidate for the detoxification of AFM1.

Development and validation of a simple anthropometric equation to predict appendicular skeletal muscle mass

A limited number of studies have developed simple anthropometric equations that can be implemented for predicting muscle mass in the local community. Several studies have suggested calf circumference as a simple and accurate surrogate maker for muscle mass. We aimed to develop and cross-validate a simple anthropometric equation, which incorporates calf circumference, to predict appendicular skeletal muscle mass (ASM) using dual-energy X-ray absorptiometry (DXA). Furthermore, we conducted a comparative validity assessment of our equation with bioelectrical impedance analysis (BIA) and two previously reported equations using similar variables. ASM measurements were recorded for 1262 participants (837 men, 425 women) aged 40 years or older. Participants were randomly divided into the development or validation group. Stepwise multiple linear regression was applied to develop the DXA-measured ASM prediction equation. Parameters including age, sex, height, weight, waist circumference, and calf circumference were incorporated as predictor variables. Total error was calculated as the square root of the sum of the square of the difference between DXA-measured and predicted ASMs divided by the total number of individuals. The most optimal ASM prediction equation developed was: ASM (kg)=2.955×sex (men=1, women=0)+0.255×weight (kg)-0.130×waist circumference (cm)+0.308×calf circumference (cm)+0.081×height (cm)-11.897 (adjusted R2=0.94, standard error of the estimate=1.2kg). Our equation had smaller total error and higher intraclass correlation coefficient (ICC) values than those for BIA and two previously reported equations, for both men and women (men, total error=1.2kg, ICC=0.91; women, total error=1.1kg, ICC=0.80). The correlation between DXA-measured ASM and predicted ASM by the present equation was not significantly different from the correlation between DXA-measured ASM and BIA-measured ASM. The equation developed in this study can predict ASM more accurately as compared to equations where calf circumference is used as the sole variable and previously reported equations; it holds potential as a reliable and an effective substitute for estimating ASM.

Efficacy of estimating VO2max with the Heart Rate Ratio Method in middle-aged and older adults.

Investigate difference, agreement, and bias between maximal oxygen consumption (VO2max) measured by indirect calorimetry and the Heart Rate Ratio Method (HRRM) for estimating VO2max using measured and age-predicted maximum heart rate (HRmax) in a sample of middle-aged and older adults. Eleven men and nine women (age: 61.8 ± 8.5years, VO2max: 36.6 ± 9.5mL/kg/min, N = 20) had their VO2max measured via a maximal graded exercise test and confirmed using a verification bout on a treadmill ergometer. Participants' VO2max was estimated via the HRRM using measured and age-predicted HRmax. Difference, agreement, and bias between methods were assessed using a one-way repeated measures Analysis of Variance (ANOVA), Lin's concordance correlation coefficient, and Bland-Altman plots, respectively. There were no statistical differences between methods of assessing VO2max, F(1.13, 21.47) = 0.583, p = 0.473, generalized eta-squared = 0.012. The standard error of the estimate (SEE) for the HRRM using measured or predicted HRmax was 5.2% and 5.6% of the mean VO2max, respectively. Both HRRM predictions had poor agreement with VO2max (rc ≤ 0.40). There was a systematic bias to underestimate as VO2max increased for HRRM using measured HRmax, F(1, 18) = 17.40, p < 0.001, and when using an age-predicted HRmax, F(1, 18) = 13.39, p = 0.002. Both versions of the HRRM have poor agreement, relatively large SEEs, and a bias to misrepresent VO2max. When possible, VO2max should be measured via a maximal graded exercise test with indirect calorimetry for middle-aged and older adults.

Validity and Effects of Placement of Velocity-Based Training Devices.

Velocity-based training (VBT) is a resistance training method by which training variables are manipulated based on kinematic outcomes, e.g., barbell velocity. The better precision for monitoring and manipulating training variables ascribed to VBT assumes that velocity is measured and communicated correctly. This study assessed the validity of several mobile and one stationary VBT device for measuring mean and peak concentric barbell velocity over a range of velocities and exercises, including low- and high-velocity, ballistic and non-ballistic, and plyometric and non-plyometric movements, and to quantify the isolated effect of device attachment point on measurement validity. GymAware (r = 0.90–1, standard error of the estimate, SEE = 0.01–0.08 m/s) and Quantum (r = 0.88–1, SEE = 0.01–0.18 m/s) were most valid for mean and peak velocity, with Vmaxpro (r = 0.92–0.99, SEE = 0.02–0.13 m/s) close behind. Push (r = 0.69–0.96, SEE = 0.03–0.17 m/s) and Flex (r = 0.60–0.94, SEE = 0.02–0.19 m/s) showed poorer validity (especially for higher-velocity exercises), although typical errors for mean velocity in exercises other than hang power snatch were acceptable. Effects of device placement were detectable, yet likely small enough (SEE < 0.1 m/s) to be negligible in training settings.

Urban tree measurement variability and the contribution to uncertainty in estimates of ecosystem services

The collection and analysis of urban forest inventory data has been steadily increasing in recent decades. In addition to typical assessments such as number of trees, size distribution, and species composition, estimates of ecosystem services provide empirical indicators of quantity and monetary value to anthropologic populations. As most urban inventories are sample-based, sources of uncertainty and their magnitude provide important information for judging the reliability of estimated population parameters. Most modern analysis tools provide an indication of uncertainty via a sampling error statistic, but other types of uncertainty due to measurements or statistical models are not accounted for. In this study, we examined measurement variation for a suite of urban tree attributes and found measurements were equally or less variable than those taken on forest-grown trees. The notable exception was tree diameter which was more highly variable. In addition to quantifying the measurement variability, simulations that propagate the variation were conducted to assess the additional variance incurred for estimates of ecosystem services and associated valuations. The results generally indicated an increase of about 1% or less in the standard error of the estimate for most ecosystem services and their value. Measurement variation may contribute larger amounts of uncertainty for urban inventories lacking adequate field crew training and quality assurance processes.

Predicting Confidence Intervals for the Age-Period-Cohort Model

Forecasting incidence and/or mortality rates of cancer is of special inter est to epidemiologists, health researchers and other planners in predicting the demand for health care. This paper proposes a methodology for devel oping prediction intervals using forecasts from Poisson APC models. The annual Canadian age-specific prostate cancer mortality rates among males aged 45 years or older for the period between 1950 and 1990 are calculated using 5-year intervals. The data were analyzed by fitting an APC model to the logarithm of the mortality rate. Based on the fit of the 1950 to 1979 data, the known prostate mortality in 1980 to 1990 is estimated. The period effects, for 1970-1979, are extended linearly to estimate the next ten period effects. With the aims of parsimony, scientific validity, and a reasonable fit to existing data two different possible forms are evaluated namely, the age period and the age-period-cohort models. The asymptotic 95% prediction intervals are based on the standard errors using an assumption of normality (estimate ±1.96× standard error of the estimate)

Validity of ultrasonography-derived predictions for estimating skeletal muscle volume: a systematic literature review

BackgroundThe amount of muscle volume (MV) varies between individuals and is important for health, well-being and performance. Therefore, the monitoring of MV using different imaging modalities is important. Magnetic resonance imaging (MRI) is considered the gold standard, but is not always easily accessible, and the examinations are expensive. Ultrasonography (US) is a much less expensive imaging method widely used to measure changes in muscle thickness (MT). Whether MT may translate into MV needs further investigation.PurposeThe aim of this review is to clarify whether US-derived equations based on MT predict MV based on MRI.MethodsA systematic literature review was conducted according to the PRISMA statement, searching the electronic databases PubMed, CINAHL and Web of Science, for currently published equations to estimate MV with US.ResultsThe literature search resulted in 363 citations. Twelve articles met the eligibility criteria. Ten articles scored eight out of eleven on QUADAS and two scored nine. Thirty-six prediction equations were identified. R values ranged between 0.53 and 0.961 and the standard error of the estimate (SEE) ranged between 6 and 12% for healthy adult populations, and up to 25.6% for children with cerebral palsy. Eight studies evaluated the results with a Bland–Altman plot and found no systematic errors. The overall strength and quality of the evidence was rated “low quality” as defined by the GRADE system.ConclusionsThe validity of US-derived equations based on MT is specific to the populations from which it is developed. The agreement with MV based on MRI is moderate with the SEE ranging between 6 and 12% in healthy adult populations. Suggestions for future research include investigations as to whether testing positions or increasing the number of measuring sites could improve the validity for prediction equations.