Sensibly highlighting the hidden structures of many real-world networks has attracted growing interest and triggered a vast array of techniques on what is called nowadays community detection (CD) problem. Non-deterministic metaheuristics are proved to competitively transcending the limits of the counterpart deterministic heuristics in solving community detection problem. Despite the increasing interest, most of the existing metaheuristic based community detection (MCD) algorithms reflect one traditional language. Generally, they tend to explicitly project some features of real communities into different definitions of single or multi-objective optimization functions. The design of other operators, however, remains canonical lacking any inte

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

Our recent work displays the successful preparation of Schiff_bases that carried out between hexane-2,5-dione and 2 moles of (Z)-3-hydrazineylideneindolin-2-one forming in Schiff-bases-(L), Which in turn allowed combining with each of the next metal ions: (M²⁺) = Ni, Mn, Zn, Cu and Co forming complexes_ in high stability. The formation of resulting Schiff_ bases (L) is detected spectrally using LC_Mss which gave approximately matching results with theoretical incomes, ¹HNMR proves the founding of doublet signal of (2H) for 2NH, FTIR indicates the occurrence of two interfered imine bands and UV-VIS mean is also indecates the formation of ligand. On the other hand, complexes-based-Schiff were characterized using the s

Crabs belong to the crustacean family (Decapods crustacean), and their shells contain natural ingredients from which the bioactive compounds are derived. It has been used as folklore medicine in cancer treatment. We investigate the possible anti-inflammatory and anti-oxidant effects for crab shells and whole crabs. Thirty-six rats (150–200 gm) from both sexes were used, divided into six groups, the anti-inflammatory and anti-oxidant activity measured using cotton pellet induce granuloma model. Detection of tumor necrosis factor alpha (TNF α), Interleukin 1 beta (IL-1β), superoxide (SOD), and malondialdehyde (MDA) levels using ELISA Kits. The data analysis by one-way ANOVA followed by the Tukey test. Values are significant at (p < 0.05).

A thin film of SnSe were deposited by thermal evaporation technique on 400 ±20 nm thick glass substrates of these films were annealed at different temperatures (100,150,200 ⁰C), The effect of annealing on the characteristics of the nano crystalline SnSe thin films was investigated using XRD, UV-VIS absorption spectroscopy, Atomic Force Microscope (AFM), and Hall effect measurements. The results of X-ray displayed that all the thin films have polycrystalline and orthorhombic structure in nature, while UV-VIS study showed that the SnSe has direct band gap of nano crystalline and it is changed from 60.12 to 94.70 nm with increasing annealing temperature. Hall effect measurements showed that all the films have a positive Hall coeffic