Abstract

The current research aims to identify the effectiveness of social stories in increasing social interaction among children with an autism spectrum disorder. The researcher used the single-subject design methodology (Single Subject Designs, SSD) with

 (A-B) design to answer the research questions. The study sample consisted of (3) children with autism spectrum disorder enrolled in a transit daycare center in the Asir region, Saudi Arabia. The results of the study showed that there is a positive functional relationship between social stories and play to increase social interaction among children with autism spectrum disorder, which contributed to the acquisition and generalization of this behav

Background: Simultaneous and staged guided bone regeneration (GBR) is one of the several surgical techniques that have been developed in the past two decades to regenerate bone and thus to allow implant placement in compromised sites (fenestration and dehiscence). It is a surgical procedure that consists of the placement of a cell-occlusive physical barrier between the connective tissue and the alveolar bone defect. The treatment concept advocates that regeneration of osseous defects is predictably attainable via the application of occlusive membranes, which mechanically exclude non-osteogenic cell populations from the surrounding soft tissues, thereby allowing osteogenic cell populations originating from the parent bone to inhabi

Germination and field emergence are delayed and their duration is prolonged due to the declining soil temperature during the spring season, which is reflected in the subsequent stages of crop growth, therefore, this study aimed to improve germination. Under a wide range of environmental conditions, a laboratory factorial experiment was carried out to study the effect of seed stimulation with potassium nitrate (distilled water only (0), 2, 4, and 6 mg L-1) and with an aqueous extract of licorice roots (distilled water only (0), 3, 6, and 9 g L-1) on the seed viability and vigor. The laboratory experiment was carried out according to the Completely Randomized Design (CRD) with four repetitions. The results showed the superiority of the intera

Free Radical Copolymerization of Styrene/ Methyl Methacrylate were prepared chemically under Nitrogen ,which was investigated, in the present of Benzoyl Peroxide as Initiator at concentration of 2 × 10-3 molar at 70 °C, which was carried out in Benzene as solvent to a certain low conversion . FT-IR spectra were used for determining of the monomer reactivity ratios ,which was obtained by employing the conventional linearization method of Fineman-Ross (F-R) and Kelen-Tüdos (K- T). The experimental results showed the average value for the Styrene r1 / Methyl Methacrylate r2 system, Sty r1 = 0.45 , MMA r2 = 0.38 in the (F–R) Method and r1 = 0.49 , r2 = 0.35 in the (K–T) Method, The Results of this indicated show the random distri

Transgenic plants offer advantages for the manufacture of recombinant proteins with terminal
mannose residues on their glycan chains. So plants are chosen as source of pharmaceutical products and for
the development of alternative expression systems to produce recombinant lysosomal enzymes. In the
present study the sequence of the natural cDNA encoding for the human lysosomal enzyme
glucocerebrosidase (GCD) was modified to enhance its expression in soybean plants. The glucocerebrosidase
gene signal peptide was substituted with that signal peptide for the Arabidopsis thaliana basic endochitinase
gene to support the co-translational translocation into the endoplasmic reticulum (ER), and the storage
vacuol

Abstract

In this research provide theoretical aspects of one of the most important statistical distributions which it is Lomax, which has many applications in several areas, set of estimation methods was used(MLE,LSE,GWPM) and compare with (RRE) estimation method ,in order to find out best estimation method set of simulation experiment (36) with many replications  in order  to get mean square error and used it to make compare , simulation experiment  contrast with (estimation method, sample size ,value of location and shape parameter) results show that estimation method effected by simulation experiment factors and ability of using other estimation methods such as(Shrinkage, jackknif

Coronavirus disease (COVID-19) is an acute disease that affects the respiratory system which initially appeared in Wuhan, China. In Feb 2019 the sickness began to spread swiftly throughout the entire planet, causing significant health, social, and economic problems. Time series is an important statistical method used to study and analyze a particular phenomenon, identify its pattern and factors, and use it to predict future values. The main focus of the research is to shed light on the study of SARIMA, NARNN, and hybrid models, expecting that the series comprises both linear and non-linear compounds, and that the ARIMA model can deal with the linear component and the NARNN model can deal with the non-linear component. The models

This research aims to study the methods of reduction of dimensions that overcome the problem curse of dimensionality when traditional methods fail to provide a good estimation of the parameters So this problem must be dealt with directly . Two methods were used to solve the problem of high dimensional data, The first method is the non-classical method Slice inverse regression ( SIR ) method and the proposed weight standard Sir (WSIR) method and principal components (PCA) which is the general method used in reducing dimensions,    (SIR ) and (PCA) is based on the work of linear combinations of a subset of the original explanatory variables, which may suffer from the problem of heterogeneity and the problem of linear

Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise