Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D CNNs have shown improved accuracy in the classification of ASD compared to traditional machine learning algorithms, on all these datasets with higher accuracy of 99.45%, 98.66%, and 90% for Autistic Spectrum Disorder Screening in Data for Adults, Children, and Adolescents respectively as they are better suited for the analysis of time series data commonly used in the diagnosis of this disorder
Small ring heterocycles containing nitrogen and sulfur have been under investigation for a long time because of their important medicinal properties. Among the wide range of heterocycles explored to develop pharmaceutically important molecules, thiadiazoles had played an important role in medicinal chemistry. A survey of literature had shown that compounds having thiadiazole nucleus possess a broad range of biological activities such as anti-inflammatory (1), antibacterial (2), and antifungal activities (3). Thiazine-4-one and their derivatives are import classes of compounds in organic and medicinal chemistry. The thiazine-4-one ring system is a core structure in various synthetic pharmaceutical agents, displaying a broad spectrum of biolo
... Show MorePolycystic ovary syndrome (PCOS) is reproductive, endocrine, and metabolic disorder affecting females. The pathology of PCOS is complicated and associated to chronic low-grade inflammation, this includes a disruption in pro-inflammatory factor production, leukocytosis, and endothelial cell dysfunction, also associated with high level of pro-inflammatory cytokines, chemokines and leukocyte count. In addition, PCOS is characterized by hormonal and immunological dysfunction. Inflammation of the ovary affects ovulation and induces or aggravates systemic inflammation. Macrophage inflammatory protein-1 (MIP-1), a pro-inflammatory chemokine, is crucial in the recruitment of inflammatory and immunological cells to the place of inflammation
... Show MoreDiabetic nephropathy is characterized by persistent microalbuminuria and metabolic changes that decline renal functions. Researchers have been prompted to explore new biomarkers such as KIM-1 and nephrin that may enhance the identification of disease. Objective: To Evaluate biomarker levels of kidney injury molculre-1 (KIM-1) concentration and nephrin as early and sensitive markers of nephropathy in type 2 diabetic patients. Method: One hundred T2DM patients were included in a cross-sectional study at the specialized center for endocrinology and diabetes, Baghdad. The first group includes 50 diabetic nephropathy (DN) patients, and the second group includes 50 T2DM patients without DN. Biochemical and clinical parameters were reported for pa
... Show MoreVolunteerism is an element included in many human cultures. It represents a positive cooperative act between individuals and groups. It expresses the social value systems. As a social phenomenon, it develops in societies according to innumerous circumstances and conditions. This study uses a functional approach that assumes that volunteering performs six functions for volunteers. Namely, we assume that volunteering (1) creates a sense of protection (2) meets significant cultural values (3) improves professional status of volunteers, (4) strengthens their social relationships, (5) helps them achieve a better understanding of life, and finally, (6) enhances their outlook and self-esteem. The central aim of the study is to discuss these fun
... Show MoreThe study aims to predict Total Dissolved Solids (TDS) as a water quality indicator parameter at spatial and temporal distribution of the Tigris River, Iraq by using Artificial Neural Network (ANN) model. This study was conducted on this river between Mosul and Amarah in Iraq on five positions stretching along the river for the period from 2001to 2011. In the ANNs model calibration, a computer program of multiple linear regressions is used to obtain a set of coefficient for a linear model. The input parameters of the ANNs model were the discharge of the Tigris River, the year, the month and the distance of the sampling stations from upstream of the river. The sensitivity analysis indicated that the distance and discharge
... Show MoreThis study aimed to compare lysyl oxidase-1 level in diabetic patients with and without renal dysfunction, that LOX-1 may be an indicator for the early stage of diabetic nephropathy (DN). In addition to finding it is a relationship with kidney functions in Iraqi diabetic patients with and without renal dysfunction. Blood was obtained from 25 healthy individuals as a control group (G1), 25 diabetic patients with renal dysfunction, and 25 diabetic patients without renal dysfunction. Age range 40-60 years for all subjects. BMI (25-27) Kg/m2 . The serum was used for the analysis of LOX-1, FBG, urea, creatinine and uric acid. Whole blood is used for the determination of HbA1C. Results of FBG and HbA1C revealed a significant increase in G2 and G
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