Standard Error Of The Estimate Research Articles

Regression Equations for Spirometry in Children Aged 6 to 17 Years in Delhi Region

Most of the studies carried out in India to develop regression equations for spirometry in children are now several years-to-decades old and had used equipment and measurement protocols that have since changed. Prediction equations using the current standardisation protocols for spirometry are not available. The lung health of the population may have changed too. To develop regression equations for spirometry for children aged 6 to 17 years of north Indian origin in Delhi region. School children of north Indian origin, as determined by mother tongue and parentage, aged 6 to 17 years were screened by a health questionnaire and physical examination and those found "normal" underwent spirometry according to the standardised procedure recommended by the American Thoracic Society/European Respiratory Society (ATS/ERS) task force in 2005. Pearson's correlation analysis was carried out to identify the predictor variables for spirometric parameters. Prediction equations were developed using the multiple linear regression procedure. The independent variables were entered in sequence of height, age and weight. R2, adjusted R2 and R2 change, standard errors of the estimate (SEE), and estimates of regression coefficients were obtained and the goodness of fit was examined. Data was obtained in 365 boys and 305 girls. Forced vital capacity (FVC), forced expiratory volume in one second (FEV1) peak expiratory flow rate (PEFR), forced expiratory flow rate at 50% and 75% exhalation of vial capacity (F50 and F75) and mean forced expiratory flow rate over the middle 50% of the vital capacity (F25-75) showed moderate to strong correlations with age, height and weight in both boys and girls. In both genders, the equations explained very high variability of FVC, FEV1 and PEFR as shown by the R2 values. The explained variability for flow rates was lesser, with that for F75 being the least. Regression equations for spirometry variables for children of north Indian origin in Delhi region have been developed. These represent the first such effort from India after the publication of the ATS/ERS task force 2005 guidelines on standardisation of spirometry.

Bioconcentration Lead (Pb) Green Mussel (Perna viridis) in Semarang Bay

The coastal waters of Semarang Bay have been polluted by heavy metal lead (Pb). The research was conducted from September 2015 to March 2016 with 3 stations at the Tambaklorok green mussel cultivation location. Analysis of the concentration of heavy metal Pb using the AAS (Atomic Absorption Spectrophotometer) method. Data processing using SPSS and Excel. The results showed that the average concentration of heavy metal Pb in the air ranged from 0.51 to 0.76 mg/L. The average concentration of heavy metal Pb in three observations obtained an average concentration of Pb between 4.975-20.43 mg/kg. Green mussels taken in the waters were sorted and separated according to the length of the shell and weighed 1 kg each according to the length of the shell. Small (2-3 cm), medium (3-4 cm) and large shells with long shells (5-6 cm). The results of the measurement of the concentration of heavy metal Pb in P. viridis showed that the average green mussel shell size 4-5 cm at the location of station III had the lowest concentration of heavy metal Pb at 0.24 mg/kg. Meanwhile, the highest average concentration of Pb in P. viridis was found at station I at 0.89 mg/kg with a shell length of 2-3 cm. The correlation equation between shell length and Pb concentration is Y= - 0.131 + 1.13 X. Standard error of the Estimate (SEE) is 0.19. While the standard deviation of 0.20 means that the predictor variable (water) to predict the dependent variable (shellfish) is feasible because SEE is greater than the standard deviation. The average value of the Bioconcentration Factor (BCF) of green mussels is smaller than that of medium-sized green mussels and large green mussels. Green mussels can be consumed by someone if the body weight is 60 kg, then as much as 5.8 kg in a week because it contains Pb

Characterization and frequency analysis of long-term maximum rainfall from São Martinho, Santa Catarina, Brazil

The study of the frequency of intense rainfall is important for agricultural and environmental planning and the dimensioning of drainage works. This study aimed to characterize and determine the relationships of intensity, duration, and frequency of long-term rainfall in São Martinho, Santa Catarina. The series of annual maximums lasting from one to ten days, observed in the period from 1977 to 2020, were determined. The probability distributions Gumbel, GEV, Log-Normal with two parameters, Log-Normal with three parameters, Pearson type III, and Log-Pearson Type III were evaluated. The parameters were estimated by the method of moments, maximum likelihood method, method of L-Moments, and for the Gumbel distribution, the Chow method was used. The Kolmogorov-Smirnov, Anderson-Darling, and Filliben fitting tests were used, and for the selection of the distribution, the standard error of the estimate was also used. The Log-Normal distribution with three parameters was selected for series lasting one, five and six days. The Pearson III distribution was selected for a duration of three and four days and the GEV distribution for the other five series. The adjusted IDF equation allows the estimation of rainfall intensity with duration from24 hours to 240 hours and a return period ranging from 2 to 100 years.

BISON fuel performance modeling optimization for experiment X447 and X447A using axial swelling and cladding strain measurements

With the recent need to qualify new reactor designs, such as the Versatile Test Reactor, researchers need fuel performance calculations to determine the safety criteria of proposed designs. In order to validate the fuel performance results obtained by the fuel performance code BISON for new reactor designs, legacy fuel from EBR-II and Fast Flux Test Facility MFF with post-irradiation examination (PIE) data need to be used as validation cases to benchmark models. In this work, BISON has been paired with the Fuels Irradiation & Physics Database (FIPD) and the Integral Fast Reactor Materials Information System (IMIS) to supply PIE data for comparison with simulations of EBR-II experiments X447/X447A. X447/X447A were assessed by implementing models for a fuel-cladding chemical interaction (FCCI) within BISON and optimizing the friction coefficient between the fuel surface and the cladding, the anisotropic swelling factor, and the HT9 first thermal creep scalar (which scales the first term in the HT9 creep equation) to best match the PIE axial fuel swelling height and cladding profilometry for all pins in X447/X447A. The optimal values were found using a generic algorithm developed to select different values for the three parameters until end criteria was met and error couldn’t be reduced further. The BISON-simulated cladding profilometry was evaluated using a standard error of the estimate to account for the profile shape of the cladding profilometry. Optimal values for the friction coefficient, anisotropic fuel swelling factor, and HT9 first thermal creep scalar were found to best fit the BISON simulation results to the PIE measurements found in IMIS and FIPD. Possible improvements to current models to account for the underprediction of fuel swelling at low burnups and the overprediction of fuel swelling at higher burnups that is observed for the axial fuel swelling height are discussed. Although two pins in EBR-II, X447/X447A (DP70 and DP75), were known to fail due to FCCI, none of the pins simulated in BISON reached a cumulative damage fraction above 0.008 with FCCI correlations coupled in the BISON simulations. The error estimate generated for all pins in X447/X447A using optimal values was 209 µm, which is deemed acceptable.

Marketing Strategies and Customer Satisfaction: A Study on the Higher Education Institutions in Johor

The future of education industry is dependent on the university’s ability to develop an effective marketing strategies, especially during the Covid-19 pandemic. Marketing strategies are the plans that enables university to achieve competitive advantage. Therefore, this study examines the relationship between marketing strategies, namely packaging, relationship marketing, price, and brand image and customer satisfaction at the higher education institutions in Johor, Malaysia. Questionnaires were distributed to 90 students who currently studying in universities in Johor, Malaysia. SmartPLS 3.0 (M3) was applied to test the hypotheses and subsequently bootstrapping was conducted to investigate the standard error of the estimate and t-values. The findings indicated that relationship marketing and price have positive relationship with customer satisfaction. On the other hand, findings revealed that packaging and brand image does not show positive relationship on customer satisfaction. It is believed that packaging has a short lifespan and the respondents does not really concern about the popularity of the brand. There is limited research on this topic to guide the universities to cope up with the current situation. Thus, this research findings have provided significant insights that help stakeholders to better strategize and position universities, particularly in the scenario of Johor, Malaysia.

Old and new equations for maximal heart rate prediction in patients with heart failure and reduced ejection fraction on beta-blockers treatment: results from the MECKI score data set.

Predicting maximal heart rate (MHR) in heart failure with reduced ejection fraction (HFrEF) still remains a major concern. In such a context, the Keteyian equation is the only one derived in a HFrEF cohort on optimized β-blockers treatment. Therefore, using the Metabolic Exercise combined with Cardiac and Kidney Indexes (MECKI) data set, we looked for a possible MHR equation, for an external validation of Keteyien formula and, contextually, for accuracy of the historical MHR formulas and their relationship with the HR measured at the anaerobic threshold (AT). Data from 3487 HFrEF outpatients on optimized β-blockers treatment from the MECKI data set were analyzed. Besides excluding all possible confounders, the new equation was derived by using HR data coming from maximal cardiopulmonary exercise test. The simplified derived equation was [109-(0.5*age) + (0.5*HR rest) + (0.2*LVEF)-(5 if haemoglobin <11 g/dL)]. The R2 and the standard error of the estimate were 0.24 and 17.5 beats min-1 with a mean absolute percentage error (MAPE) = 11.9%. The Keteyian equation had a slightly higher MAPE = 12.3%. Conversely, the Fox and Tanaka equations showed extremely higher MAPE values. The range 75-80% of MHR according to the new and the Keteyian equations was the most accurate in identifying the HR at the AT (MAPEs = 11.3-11.6%). The derived equation to estimate the MHR in HFrEF patients, by accounting also for the systolic dysfunction degree and anaemia, improved slightly the Keteyian formula. Both formulas might be helpful in identifying the true maximal effort during an exercise test and the intensity domain during a rehabilitation programme.

Necropsy Validation of a Novel Method for Left Ventricular Mass Quantification in Porcine Transthoracic and Transdiaphragmal Echocardiography.

IntroductionIncreased left ventricular mass (LVM) is one of the most powerful predictors of adverse cardiovascular events. Clinical evaluation requires reliable, accurate and reproducible echocardiographic LVM-quantification to manage patients. For this purpose, we have developed a novel two-dimensional (2D) method based on adding the mean wall thickness to the left ventricular volume acquired by the biplane method of disks, which has recently been validated in humans using cardiac magnetic resonance as reference value. We assessed the hypothesis that the novel method has better accuracy than conventional one-dimensional (1D) methods, when compared to necropsy LVM in pigs.Materials and MethodsEchocardiography was performed during anesthesia in 34 Danish Landrace pigs, weight 47–59 kg. All pigs were euthanized, cardiac necropsy was performed and the left ventricle was trimmed and weighed for necropsy LVM. Trans-thoracic echocardiography was applied for parasternal images. Transdiaphragmal echocardiography was applied for the apical images, which are otherwise difficult to obtain in pigs. We compared the conventional 1D- and 2D-methods and the novel 2D-method to the LVM from cardiac necropsy.ResultsNecropsy LVM was 132 ± 11 g (mean ± SD). The novel method had better accuracy than other methods (mean difference ± 95% limits of agreement; coefficients of variation; standard error of the estimate, Pearson's correlation). Novel (−1 ± 20 g; 8%; 11 g; r = 0.70), Devereux (+26 ± 37 g; 15%; 33 g; r = 0.52), Area-Length (+27 ± 34 g; 13 %; 33 g; r = 0.63), Truncated Ellipsoid (+10 ± 30 g; 12%; 19 g; r = 0.63), biplane endo-/epicardial tracing (−3 ± 2 g; 10%; 14 g; r = 0.57). No proportional bias in linear regression was detected for any method, when compared to necropsy LVM.ConclusionWe confirm high accuracy of the novel 2D-based method compared to conventional 1D/2D-methods.

Single‐fit bootstrapping: A simple alternative to the delta method

AbstractIn many environmental and ecological settings, the analysis of data involves calculation of a confidence interval for a nonlinear function of the model parameters. In the frequentist approach, this is often achieved by using a Wald interval in which the standard error of the estimate of the function is obtained using the delta method.The purpose of this paper is to promote a simple alternative to the delta method that will provide better coverage properties when the estimates of the model parameters have a distribution that is approximately multivariate normal, as will be the case asymptotically for maximum likelihood estimates in regular models. We propose a simple diagnostic tool that can be used to assess the reliability of this assumption.The method we promote can be thought of as a computationally efficient version of parametric bootstrapping, as it mimics such bootstrapping without a need to refit the model.We provide two examples to illustrate use of the new method and present simulation results which show that its coverage properties are superior to those for a Wald interval based on the delta method when the assumption of normality for the estimates of the model parameters is reliable. We also compare its coverage properties and computational effort with those of parametric bootstrapping.

Simple linear regression approach for evaluating models to estimate stature based on upper limb dimensions of adult Bangladeshi males

BackgroundThe stature of a living human reflects the nutritional, genetic, and disease patterns of individual experiences. This study adopted a simple linear regression method and R2 values to identify the preferred model for stature estimation based on the lengths of the arm, radius, ulna, and hand; breadth of the hand; and circumference of the wrist of the adult Bangladeshi male population. This cross-sectional study was performed in the Anatomy Department of Sir Salimullah Medical College, Dhaka, from January 2009 to June 2011. One hundred right-handed adult Muslim Bangladeshi males aged 25 to 45 years participated in the study.ResultsThe regression model using right and left ulnar length explained 63% of the measured stature with the least standard error of the estimate (0.435 and 0.436), the model using left and right arm length explained 60%, the model using left and right radius length explained 51%, and the model using left- and right-hand length explained 44% of the measured stature. However, the models using left and right handbreadth and wrist circumference explained only 11 to 13% of the measured stature with a higher standard error of the estimate (6.66 to 6.73). For 25- to 45-year-old Bangladeshi Muslim males, the ulnar length of both sides was the best predictor of stature.ConclusionsLinear regression equations in estimating stature effectively may encourage its application in future studies addressing different age groups, sexes, nutritional statuses, religions, and ethnicities of Bangladesh.

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.