The support vector machine, also known as SVM, is a type of supervised learning model that can be used for classification or regression depending on the datasets. SVM is used to classify data points by determining the best hyperplane between two or more groups. Working with enormous datasets, on the other hand, might result in a variety of issues, including inefficient accuracy and time-consuming. SVM was updated in this research by applying some non-linear kernel transformations, which are: linear, polynomial, radial basis, and multi-layer kernels. The non-linear SVM classification model was illustrated and summarized in an algorithm using kernel tricks. The proposed method was examined using three simulation datasets with different sample

This paper proposed a new  method to study functional non-parametric regression data analysis with conditional expectation in the case that the covariates  are functional and the Principal Component Analysis was utilized to de-correlate the multivariate response variables. It  utilized the formula of the Nadaraya Watson estimator (K-Nearest Neighbour (KNN)) for prediction with different types of the semi-metrics, (which are based on Second Derivative and Functional Principal Component Analysis (FPCA))  for measureing the closeness between curves.  Root Mean Square Errors is used for the  implementation of this model which is then compared to the independent response method. R program is used for analysing data. Then, when  the cov

Modified algae with nano copper oxide (CuO) were used as adsorption media to remove tetracycline (TEC) from aqueous solutions. Functional groups, morphology, structure, and percentages of surfactants before and after adsorption were characterised through Fourier-transform infrared (FTIR), X-ray diffraction (XRD), scanning electron microscopy (SEM), and energy-dispersive spectroscopy (EDS). Several variables, including pH, connection time, dosage, initial concentrations, and temperature, were controlled to obtain the optimum condition. Thermodynamic studies, adsorption isotherm, and kinetics models were examined to describe and recognise the type of interactions involved. Resultantly, the best operation conditions were at pH 7, contact time

This study was perform to defined the effect of fungus Metarhizium anisopliae Sorokin with concentrations 5x101, 5x103 and 5x105 spore/ ml and Actelic insecticide with concentration 0.001% in pupa stages of Callosobruchus maculatus in pupa ages of 24 and 120 hours the results of the study showed the following: the highest killing rate of treated pupa in age 120 hours 100% at concentration 105 spore/ ml. observation for distortions in the adult insects from the pupa that treated with fungal concentration like wings and abdominal distortion , the concentration of fungal effect on the number of eggs that production from adults and percentage of hatching.

Autorías: Hadeer Idan Ghanim, Ishraq Mahmood. Localización: Revista iberoamericana de psicología del ejercicio y el deporte. Nº. 3, 2021. Artículo de Revista en Dialnet.

Background: Methotrexate is one of the mainstays for treating rheumatoid arthritis (RA) with a wide range of adverse drug reactions, however, it’s the relationship between adverse drug reactions and genetic polymorphism remains to be highlighted, and there is a lack of studies concerning Arabic Iraqi population regarding this aspect.

Objective: Evaluate the association between genetic mutations in the MTHFR gene in SNPs (rs1801133G>A and rs1801131T>G) on the adverse drug reaction for RA Iraqi patients.

Methods: An observational study, that involved 95 Iraqi RA patients with established RA. Patien