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

Amputation of the upper limb significantly hinders the ability of patients to perform activities of daily living. To address this challenge, this paper introduces a novel approach that combines non-invasive methods, specifically Electroencephalography (EEG) and Electromyography (EMG) signals, with advanced machine learning techniques to recognize upper limb movements. The objective is to improve the control and functionality of prosthetic upper limbs through effective pattern recognition. The proposed methodology involves the fusion of EMG and EEG signals, which are processed using time-frequency domain feature extraction techniques. This enables the classification of seven distinct hand and wrist movements. The experiments conducte

Background: In type 2 diabetes mellitus there is a progressive loss of beta cell function. One new
approach yielding promising results is the use of the orally active dipeptidyl peptidase-4 (DPP-4)
inhibitors for type 2 diabetes mellitus.
Objective: This study aims at comparing the possible occurrence of macrovascular & microvascular
complications in Iraqis patients with type 2 diabetes mellitus using two combinations of drugs
metformin + glibenclamide and metformin + sitagliptin.
Methodology: Sixty eight T2DM patients and 34 normal healthy individuals as control group were
enrolled in this study and categorized in to two treatment groups. The group 1 (34 patients ) received
metformin 500 mg three times daily

The study aimed to evaluate educational programs efficiency in applying the best educational practices to educate students from the dangers of indecent behaviors, in line with higher education policy and the appropriateness of educational program dimensions to spread awareness among students to not fall into the indecent behaviors clutches. The study adopted the inductive exploratory approach through structural equation modeling and the descriptive analysis of the collected data from randomly selected sample (n=385) from educational academics at Northern Border University in the Saudi Arabia using a specially designed survey tool to meet study purposes to evaluate dimensions of teaching methods, evaluation tools, training courses, course

The aim of this paper is to derive a posteriori error estimates for semilinear parabolic interface problems. More specifically, optimal order a posteriori error analysis in the - norm for semidiscrete semilinear parabolic interface problems is derived by using elliptic reconstruction technique introduced by Makridakis and Nochetto in (2003). A key idea for this technique is the use of error estimators derived for elliptic interface problems to obtain parabolic estimators that are of optimal order in space and time.

This study was designed to investigate the hepatoprotective activity and antioxidant enzymes of purified Bauhinia variegate leaves extract and purified flowers extract were administered (200 mg/kg, orally once daily) to reduce the effect of carbon tetrachloride-damage in rat’sliver for three weeks. Thereafter, the levels of some serum biochemical factorssuch as alanine aminotransferase, aspartate aminotransferase, alkaline phosphatase,and the activity of three different antioxidant enzymes (glutathione, superoxide dismutase, and catalase) were investigated.Liver homogenate can used to estimated antioxidant parameters: glutathione, superoxide dismutase and catalase. The purified Bauhinia variegate leaves and purified flowers significantly