This paper is summarized with one of the applications of adsorption behavior; A UV-Vis method has been applied to survey the isotherm of adsorption. Results for experimental showed the applicability of Langmuir equation. The effect of temperature on the adsorption of cobalt (II) Complex by bentonite surface was studied. The results shown that the amount of adsorption was formed to increase, such as the temperature increase (Endothermic process). Cobalt (II) Complex has adsorption studies by bentonite surface at different pH values (1.6-10); these studies displayed an increase in adsorption with increasing pH. ∆G, ∆H, and ∆S thermodynamic functions of the cobalt (II) Complex for their adsorption have been calculated

This paper is summarized with one of the applications of adsorption behavior; A UV-Vis method has been applied to survey the isotherm of adsorption. Results for experimental showed the applicability of Langmuir equation. The effect of temperature on the adsorption of cobalt (II) Complex by bentonite surface was studied. The results shown that the amount of adsorption was formed to increase, such as the temperature increase (Endothermic process). Cobalt (II) Complex has adsorption studies by bentonite surface at different pH values (1.6-10); these studies displayed an increase in adsorption with increasing pH. ΔG, ΔH, and ΔS thermodynamic functions of the cobalt (II) Complex for their adsorption have been calculated.

Atorvastatin calcium (ATR) is an antihyperlipidemic agent used for lowering blood cholesterol levels. However, it is very slightly soluble in water with poor oral bioavailability, which interferes with its therapeutic action. It is classified as a class II drug according to Biopharmaceutical Classification System (low solubility and high permeability).

In this paper, a fusion of K models of full-rank weighted nonnegative tensor factor two-dimensional deconvolution (K-wNTF2D) is proposed to separate the acoustic sources that have been mixed in an underdetermined reverberant environment. The model is adapted in an unsupervised manner under the hybrid framework of the generalized expectation maximization and multiplicative update algorithms. The derivation of the algorithm and the development of proposed full-rank K-wNTF2D will be shown. The algorithm also encodes a set of variable sparsity parameters derived from Gibbs distribution into the K-wNTF2D model. This optimizes each sub-model in K-wNTF2D with the required sparsity to model the time-varying variances of the sources in the s

Early diagnosis and clinical decision-making depend on accurate brain tumor classification using magnetic resonance imaging (MRI). However, traditional deep learning methods usually rely on centralized medical data, which raises privacy concerns and limits the use of distributed clinical data. This research proposes a privacy-preserving federated learning framework for MRI image-based binary brain tumor classification using a decentralized ResNet-18 architecture that enables collaborative training without sharing raw patient data. To reflect realistic clinical conditions, the framework integrates heterogeneous multi-source datasets in different image formats (PNG and JPG) and evaluates performance under both IID and non-IID settings

In this work, the nano particles of Na-A zeolite were synthesized by sol –gel method. The samples were characterized by X-ray diffraction (XRD), X-ray  luorescence (XRF), Surface  area and pore volume, Atomic Force Microscope (AFM) and Fourier Transform Infrared Spectroscopy (FTIR). Results show that the nano A zeolite is with average crystal size is 74.77 nm., Si/Al ratio 1.03, BET surface area was 581.211m2/g and the pore volume for NaA was found equal to 0.355cm3/g.
 
 
 

     By definition, the detection of protein complexes that form protein-protein interaction networks (PPINs) is an NP-hard problem. Evolutionary algorithms (EAs), as global search methods, are proven in the literature to be more successful than greedy methods in detecting protein complexes. However, the design of most of these EA-based approaches relies on the topological information of the proteins in the PPIN. Biological information, as a key resource for molecular profiles, on the other hand, acquired a little interest in the design of the components in these EA-based methods. The main aim of this paper is to redesign two operators in the EA based on the functional domain rather than the graph topological domain. The perturb