The -multiple mixing ratios of γ-transitions from levels of populated in the are calculated in the present work by using the a2-ratio methods. We used the experimental coefficient (a2) for two γ-transitions from the same initial state, the statistical tensor, which is related to the a2-coefficient would be the same for the two transitions. This method was used in a previous work for pure transitions or which can be considered pure. In these cases the multiple mixing ratios for the second transition ( ) equal zero, but in our work we applied this method for mixed γ-transitions and then the multiple mixing ratio ( ) is known for one transition. Then we calculate the ( ) value and versareversa. The weight average of the -values calcu

For modeling a photovoltaic module, it is necessary to calculate the basic parameters which control the current-voltage characteristic curves, that is not provided by the manufacturer. Generally, for mono crystalline silicon module, the shunt resistance is generally high, and it is neglected in this model. In this study, three methods are presented for four parameters model. Explicit simplified method based on an analytical solution, slope method based on manufacturer data, and iterative method based on a numerical resolution. The results obtained for these methods were compared with experimental measured data. The iterative method was more accurate than the other two methods but more complexity. The average deviation of

Coblatcomplex has been prepared by reaction between C16H19N3O3S (L) as ligand and metal salt (II). The prepared complex were characterized by infrared spectra, electromic spectra, magnetic susceptibility, molar conductivity measurement and metal analysis by atomic absorption and (C.H.N) analysis. From these studies tetrahedral geometry structure for the complex was suggested. The photodegredation of complex were study using photoreaction cell and preparednanoTiO2 catalyst in different conditions (concentration, temperatures, pH).The results show that the recation is of a first order with activation energy equal to (6.6512 kJ /mol).

In this paper we use non-polynomial spline functions to develop numerical methods to approximate the solution of 2nd kind Volterra integral equations. Numerical examples are presented to illustrate the applications of these method, and to compare the computed results with other known methods.

The ability to produce load-bearing masonry units adopting ACI 211.1 mix design using (1:3.2:2.5) as (cement: fine aggregate: coarse aggregate) with slump range (25-50mm) which can conform (dimension, absorption, and compressive strength) within IQS 1077/1987 requirements type A was our main goal of the study. The ability to use low cement content (300 kg/m3) to handle our market price products since the most consumption in wall construction for low-cost buildings was encouraging. The use of (10 and 20%) of LECA as partial volume replacement of coarse aggregate to reduce the huge weight of masonry blocks can also be recommended. The types of production of the load-bearing masonry units were A and B for (

                The characteristics of sulfur nanoparticles were studied by using atomic force microscope (AFM) analysis. The atomic force microscope (AFM) measurements showed that the average size of sulfur nanoparticles synthesized using thiosulfate sodium solution through the extract of cucurbita pepo extra was 93.62 nm. Protecting galvanized steel from corrosion in salt media was achieved by using sulfur nanoparticles in different temperatures. The obtained data of thermodynamic in the presence of sulfur nanoparticles referred to high value as compares to counterpart in the absence of sulfur nanoparticles, the high inhibition efficiency (%IE) and corrosion resistance were at high temperature, the corrosion rate or weig

Breast cancer is a heterogeneous disease characterized by molecular complexity. This research utilized three genetic expression profiles—gene expression, deoxyribonucleic acid (DNA) methylation, and micro ribonucleic acid (miRNA) expression—to deepen the understanding of breast cancer biology and contribute to the development of a reliable survival rate prediction model. During the preprocessing phase, principal component analysis (PCA) was applied to reduce the dimensionality of each dataset before computing consensus features across the three omics datasets. By integrating these datasets with the consensus features, the model's ability to uncover deep connections within the data was significantly improved. The proposed multimodal deep