The present research aims to know the relation of Violence on academic Failed and School s’ Drop - out among Intermediate stage Pupils. The sample of the research reached (400) male and female pupils (failed and not failed ), and (69) male and female that Drop – out from Intermediate stage. The researcher used scale of Violence that constructed by (AL- qaysi , 2004) after she got Validity and Reliability to it . So that she used t- test for one sample, t- test for two independent sample, and Person correlation coefficient as a statistical means. The research reached to the results that indicates raising of level of Violence among the Intermediate stage pupils (failed and not failed) and the male and female that Drop – out from Inte

This new azo dye 7-(3-hydroxy-phenylazo)-quinoline-8-ol was subsequently used to prepare a series of complexes with the chlorides of Fe, Co, Zn, Ru, Rh and Cd. The compounds identified by 1H and 13C-NMR, FT-IR, UV-Vis, mass spectroscopy, as well as TGA, DSC, and C.H.N., conductivity, magnetic susceptibility, metal and chlorine content. The results showed that the ligand behaves in a trigonal behavior, and that the complexes gave tetrahedral, except for Fe, Ru and Rh octahedral was given, that all of them are non-electrolytes. The effectiveness of both the compounds in inhibiting free radicals was evaluated by the ability to act as an antioxidant was measured using DPPH as a free radical and gallic acid as a standard substance, the

The behaviour of certain dynamical nonlinear systems are described in term as chaos, i.e., systems' variables change with the time, displaying very sensitivity to initial conditions of chaotic dynamics. In this paper, we study archetype systems of ordinary differential equations in two-dimensional phase spaces of the Rössler model. A system displays continuous time chaos and is explained by three coupled nonlinear differential equations. We study its characteristics and determine the control parameters that lead to different behavior of the system output, periodic, quasi-periodic and chaos. The time series, attractor, Fast Fourier Transformation and bifurcation diagram for different values have been described.

Accurate prediction and optimization of morphological traits in Roselle are essential for enhancing crop productivity and adaptability to diverse environments. In the present study, a machine learning framework was developed using Random Forest and Multi-layer Perceptron algorithms to model and predict key morphological traits, branch number, growth period, boll number, and seed number per plant, based on genotype and planting date. The dataset was generated from a field experiment involving ten Roselle genotypes and five planting dates. Both RF and MLP exhibited robust predictive capabilities; however, RF (R² = 0.84) demonstrated superior performance compared to MLP (R² = 0.80), underscoring its efficacy in capturing the nonlinear genoty