Modeling Sexual Differences of Body Size Variation in Ground Beetles in Geographical Gradients: A Case Study of Pterostichus melanarius (Illiger, 1798) (Coleoptera, Carabidae)

The aim of this study was to test the steepness of body size variation in males and females in the widespread ground beetle Pterostichus melanarius in geographical gradients. Beetles were sampled in 15 regions of Europe and Asia, and sampling territories differed 17° in latitude and 121° in longitude. We measured six linear traits in every captured beetle and formed a data set that included 2154 individuals. Body size variation in all traits in general was sawtooth, both in latitude and in longitude gradients. Regression analysis showed slight trends: in the latitude gradient, elytra parameters increased, pronotum length did not change but the width increased, and head parameters decreased. In the longitude gradient, the changes were as follows: elytra length increased, but its width did not change; pronotum length did not change, but its width increased; the head parameters decreased. Thus, we observed the elytra length increase and the head parameters decrease northwards and eastwards. We compared female and male regression curves (trait size on latitude/longitude): p-levels were significant only in four cases out of 12. Thus, we conclude that, in general, there is no evidence for the steepness in trait variation in males compared with females.

Analysis of Measured Parameters in Relation to the Amount of Fibre in Lightweight Red Ceramic Waste Aggregate Concrete

The present study provides a correlation and regression analysis of lightweight waste aggregate concretes with varying degrees of fibre reinforcement. The concrete mix contains pre-soaked red ceramic waste aggregate, expanded clay coarse aggregate and Portland cement. Copper-coated crimped steel fibre was used as the reinforcement. The experimental results included properties measured by destructive test methods—compressive strength, splitting tensile strength, static modulus of elasticity, the limit of proportionality, shear strength; and by non-destructive test methods—dynamic modulus of elasticity and surface electrical resistivity. These properties were analysed to study the relevancy and significance between non-destructive and destructive methods of measurement in the case of different amounts of fibre. The results show differences in the degree of fit to the linear and quadratic regression curves for pairs of destructive and non-destructive test results. As expected, the linear relationship can be applied in a few cases, but the quadratic curve must be used for a few pairs. Another observation is that it is not possible to neglect the amount of fibre in the correlation analyses of the measured properties.

Effect of weather on rice crop in Bhandara district. A curvilinear approach

Curvilinear technique has been applied to rice crop in Bhandara district (Maharashtra) to examine effects of rainfall, maximum temperature and relative humidity. Partial regression curves for estimating the rice yield by taking into account the .combined effect of these three factors have been worked out. It is observed that during the period of active growth rainfall is the most significant factor followed by maximum temperature and relative humidity in that order. The optimum value of total rainfall during the active growth phase was found as 1000 mm and those for maximum temperature and relative humidity as 30.5° C and 81% respectively.

Arithmetic Relationship between Fracture Load and Material Thickness of Resin-Based CAD-CAM Restorative Materials

Data on the long-term behavior of computer-aided designed/computer-aided manufactured (CAD-CAM) resin-based composites are sparse. To achieve higher predictability on the mechanical behavior of these materials, the aim of the study was to establish a mathematical relationship between the material thickness of resin-based materials and their fracture load. The tested materials were Lava Ultimate (LU), Cerasmart (GC), Enamic (EN), and Telio CAD (TC). For this purpose, 60 specimens were prepared, each with five different material thicknesses between 0.4 mm and 1.6 mm (N = 60, n = 12). The fracture load of all specimens was determined using the biaxial flexural strength test (DIN EN ISO 6872). Regression curves were fitted to the results and their coefficient of determination (R2) was computed. Cubic regression curves showed the best R2 approximation (LU R2 = 0.947, GC R2 = 0.971, VE R2 = 0.981, TC R2 = 0.971) to the fracture load values. These findings imply that the fracture load of all tested resin-based materials has a cubic relationship to material thickness. By means of a cubic equation and material-specific fracture load coefficients, the fracture load can be calculated when material thickness is given. The approach enables a better predictability for resin-based restorations for the individual patient. Hence, the methodology might be reasonably applied to other restorative materials.

Quantitative HBsAg versus HBV DNA in Predicting Significant Hepatitis Activity of HBeAg-Positive Chronic HBV Infection

(1) Background: As specialparameters in predicting significant hepatitis activity of hepatitis B e antigen (HBeAg)-positive chronic hepatitis B virus (HBV) infection, the quantitative standard of HBV DNA has not been agreed and that of hepatitis B surface antigen(HBsAg) has not been formed. Our objective is to evaluate the validity of HBsAg and HBV DNA in predicting the significant hepatitis activity of HBeAg-positive patients. (2) Methods: A population of 516 patients with HBeAg-positive chronic HBV infection was enrolled. Serum ALT was measured using an Abbott Architect c16000 autoanalyzer; diagnoses of liver pathological grade and stage referred to the Scheuer standard. Three levels of significant hepatitis activity were preset, which were successively “ALT ≥ 20 IU/L or Grade > G1 or Stage > S1”, “ALT ≥ 30 IU/L or Grade > G1 or Stage > S1” and “ALT ≥ 40 IU/L or Grade > G1 or Stage > S1”. (3) Results: A subpopulation of 288 patients with possible high HBV replication was selected based on locally weighted scatterplot smoothing regression curves between ALT and HBsAg, HBeAg and HBV DNA. In the subpopulation with possible high HBV replication, areas under receiver operating characteristic curves of HBsAg for predicting the three levels of significant hepatitis activity were successively 0.868, 0.839 and 0.789, which were all significantly greater than those of HBV DNA, as those were successively 0.553, 0.550 and 0.574 (p = 0.0002, p < 0.0001 and p < 0.0001). With the standard of HBsAg ≤ 4.699 log10 IU/mL, the sensitivity and specificity of HBsAg for predicting the three levels of significant hepatitis activity were successively 75.81% and 81.82%, 79.23% and 78.57% and 80.82% and 67.44%. (4) Conclusion: Quantitative HBsAg instead of HBV DNA is valuable in predicting significant hepatitis activity of HBeAg-positive chronic HBV infection.

Optimal Designs for Comparing Regression Curves: Dependence Within and Between Groups

We consider the problem of designing experiments for the comparison of two regression curves describing the relation between a predictor and a response in two groups, where the data between and within the group may be dependent. In order to derive efficient designs we use results from stochastic analysis to identify the best linear unbiased estimator (BLUE) in a corresponding continuous model. It is demonstrated that in general simultaneous estimation using the data from both groups yields more precise results than estimation of the parameters separately in the two groups. Using the BLUE from simultaneous estimation, we then construct an efficient linear estimator for finite sample size by minimizing the mean squared error between the optimal solution in the continuous model and its discrete approximation with respect to the weights (of the linear estimator). Finally, the optimal design points are determined by minimizing the maximal width of a simultaneous confidence band for the difference of the two regression functions. The advantages of the new approach are illustrated by means of a simulation study, where it is shown that the use of the optimal designs yields substantially narrower confidence bands than the application of uniform designs.

Prediction of record values by using quantile regression curves and distortion functions

The purpose of the paper is to provide a general method based on conditional quantile curves to predict record values from preceding records. The predictions are based on conditional median (or median regression) curves. Moreover, conditional quantiles curves are used to provide confidence bands for these predictions. The method is based on the recently introduced concept of multivariate distorted distributions that are used instead of copulas to represent the dependence structure. This concept allows us to compute the conditional quantile curves in a simple way. The theoretical findings are illustrated with a non-parametric model (standard uniform), two parametric models (exponential and Pareto), and a non-parametric procedure for the general case. A real data set and a simulated case study in reliability are analysed.

Utility of miR-155, miR-21 and miR-16 in plasma as biomarkers of atrial fibrillation

Background Atrial fibrillation (AF) is associated with increased morbidity and mortality. MicroRNAs (miRs) are post-transcriptional regulators that could be useful in the study of AF. Purpose To investigate whether miR-16, miR-21 and miR-155 may differentiate between AF and sinus rhythm. Methods 29 controls and 42 AF (June 2019-May 2020). Lipid profile, hsCRP were measured. Serum RNA extraction was performed. Hsa-miR-21, hsa-miR-16, hsa-miR-155, and cel-miR-39 were amplified RT-PCR. Quantitative results for miR levels were generated according to the 2-ΔCt method using cel-miR-39 for normalization. Correlations were assessed by Spearman rank test. Logistic regression analysis was adjusted by age, sex, and BMI vs miR's. A p&lt;0.05 was set for significance. Results (controls vs AF): age (56 [52–63] vs 60 [64–67] years, p=0.122), BMI (30.52 [27.69–32.67] vs 29.65 [26.3–32.9] kg/m2 p=0.779), female 17 (58.6%) vs 19 (45.2%), p=0.268; total cholesterol (198.4 [17.2–215] vs 171.3 [150.3–216.8] mg/dL, p=0.066), LDL (126.6 [114.7–141.6] vs 99.2 [80.7–124] mg/dL, p=0.005) HDL (40.4 [36.8–45.8] vs 43.8 [36.9–48.5] p=0.326) and CRP (2.69 [1.22–4.72] vs 2.92 [1.4–4.76] mg/L p=0.835). The CHA2DS2VASC score in AF was &lt;2=11 (45.2%) and ≥2= 26 (54.8%). MicroRNA levels (controls vs AF): miR-21 0.0195 (0.0095–0.0275) vs 0.042 (0.028–0.098) p&lt;0.001; miR-155 0.0178 (0.0108–0.0309) vs 0.01 (0.0056–0.0169) p&lt;0.001, and miR-16 0.5238 (0.2618–1.992) vs 0.1652 (0.0765–0.3816) p&lt;0.001. In the logistic regression miR-21 had a positive correlation with AF, c=0.851 p=0.002, Wald=9.89. miR-16 and miR-155 a negative relation (c=0.76,0.72; p=0.036, 0.043, Wald=4.39, 4.085; respectively) (Fig. 1A, B, C). For multivariable analysis we used miR-16, miR-21, and miR-155 as previous analysis demonstrated significance with an overall model c=0.90 p=0.028 (Wald=14.2) and significance was seen in the miR-21 Wald= 9.33 (p=0.002); and miR-155 Wald=4.7 (p=0.03); miR-16 was not significant (Wald=2.7, p=0.1). A ternary plot was performed using the predicted outputs of the model. (Fig. 2) Conclusion miR-16, miR-21 and miR-155 are useful for the discrimination of AF vs sinus rhythm and may be part of important physiopathological pathways in AF. FUNDunding Acknowledgement Type of funding sources: Public hospital(s). Main funding source(s): Instituto Nacional de Cardiología Ignacio Chávez Figure 1. Logistic regression curves Figure 2. Multivariate ternary plot of miRs

Generation of Proton- and Alpha-Induced Nuclear Cross-Section Data via Random Forest Algorithm: Production of Radionuclide 111In

We investigated the generation of proton- and alpha-induced nuclear cross-section data in the production of Indium-111 (111In) for application in nuclear medicine. Here, we are interested in three reaction channels, which are 109Ag (α, 2n), 111Cd (p, n) and 112Cd (p, 2n), in the production of 111In. A random forest algorithm was used to generate nuclear cross-section data by using an experimental nuclear cross-section from the Experimental Nuclear Reaction Data (EXFOR) database as input. Hence, reasonably accurate regression curves of nuclear cross-section data could be produced with the evaluated nuclear data library ENDF/B-VII.0 set as the benchmark.