Copula modeling is widely used in modern statistics. The boundary bias problem is one of the problems faced when estimating by nonparametric methods, as kernel estimators are the most common in nonparametric estimation. In this paper, the copula density function was estimated using the probit transformation nonparametric method in order to get rid of the boundary bias problem that the kernel estimators suffer from. Using simulation for three nonparametric methods to estimate the copula density function and we proposed a new method that is better than the rest of the methods by five types of copulas with different sample sizes and different levels of correlation between the copula variables and the different parameters for the function. The results showed that the best method is to combine probit transformation and mirror reflection kernel estimator (PTMRKE) and followed by the (IPE) method when using all copula functions and for all sample sizes if the correlation is strong (positive or negative). But in the case of using weak and medium correlations, it turns out that the (IPE) method is the best, followed by the proposed method(PTMRKE), depending on (RMSE, LOGL, Akaike)criteria. The results also indicated that the mirror kernel reflection method when using the five copulas is weak.
This study was aimed to evaluate the effect of conventional ingredients replacement with alternative ingredients on growth performance, carcass quality, nutrient digestibility and intestinal microbial of broilers. One hundred twenty Cobb500 broiler chicks were randomly assigned to four diets. Corn, soybean meal and fish meal were replaced with rice waste, meat and bone waste and black soldier fly larvae (BSFL) at 0, 10, 30 and 50% to form four treatments. Body weight gain, feed conversion ratio and digestibility of crude protein and fat were improved in broilers fed the replacement diets. Feed intake was not affected by the treatments suggesting that the replacement diets were well accepted by the chicken. Escherichia coli was decre
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The harmonic oscillator (HO) and Gaussian (GS) wave functions within the binary cluster model (BCM) have been employ to investigate the ground state neutron, proton and matter densities as well as the elastic form factors of two- neutron 6He and 16C halo nuclei. The long tail is a property that is clearly revealed in the density of the neutrons since it is found in halo orbits. The existence of a long tail in the neutron density distributions of 6He and 16C indicating that these nuclei have a neutron halo structure. Moreover, the matter rms radii and the reaction cross section (𝜎𝑅 ) of these nuclei have been calculated using the Glauber model.
The electronic properties (such as energy gap HOMO levels. LUMO levels, density of state and density of bonds in addition to spectroscopic properties like IR spectra, Raman spectra, force constant and reduced masses as a function of frequency) of coronene C24 and reduced graphene oxide C24OX , where x=1-5, were studied.. The methodology employed was Density Functional Theory (DFT) with Hybrid function B3LYP and 6-311G** basis sets. The energy gap was calculated for C24 to be 3.5 eV and for C24Ox was from 0.89 to 1.6862 eV for x=1-5 ,respectively. These energy gaps values are comparable to the measured gap of Graphene (1-2.2 eV). The spectroscopic properties were compared with experimental measurements, specificall
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The partial level density PLD of pre-equilibrium reactions that are described by Ericson’s formula has been studied using different formulae of single particle level density . The parameter was used from the equidistant spacing model (ESM) model and the non- equidistant spacing model (non-ESM) and another formula of are derived from the relation between and level density parameter . The formulae used to derive are the Roher formula, Egidy formula, Yukawa formula, and Thomas –Fermi formula. The partial level density results that depend on from the Thomas-Fermi formula show a good agreement with the experimental data.
Surface electromyography (sEMG) and accelerometer (Acc) signals play crucial roles in controlling prosthetic and upper limb orthotic devices, as well as in assessing electrical muscle activity for various biomedical engineering and rehabilitation applications. In this study, an advanced discrimination system is proposed for the identification of seven distinct shoulder girdle motions, aimed at improving prosthesis control. Feature extraction from Time-Dependent Power Spectrum Descriptors (TDPSD) is employed to enhance motion recognition. Subsequently, the Spectral Regression (SR) method is utilized to reduce the dimensionality of the extracted features. A comparative analysis is conducted between the Linear Discriminant Analysis (LDA) class
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The possible effect of the collective motion in heavy nuclei has been investigated in the framework of Nilson model. This effect has been searched realistically by calculating the level density, which plays a significant role in the description of the reaction cross sections in the statistical nuclear theory. The nuclear level density parameter for some deformed radioisotopes of (even- even) target nuclei (Dy, W and Os) is calculated, by taking into consideration the collective motion for excitation modes for the observed nuclear spectra near the neutron binding energy. The method employed in the present work assumes equidistant spacing of the collective coupled state bands of the considered isotopes. The present calculated results for f
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