The aim of the currnet study to examine the effect of subclinical hypothyroidism (SCH) in diabetic patients on coagulation parameters. This retrospective case–control study involves 130 patients diagnosed with type 2 diabetes mellitus (T2DM), divided into 65 T2DM with newly diagnosed SCH and 65 euthyroid (EUT) T2DM patients without SCH. Fibrinogen (FIB) was significantly higher in SCH (508.2 ± 63.0 mg/dL) than EUT (428.1 ± 44.8 mg/dL). In the SCH patients, FIB correlated with several parameters, such as age (β = 0.396), body mass index (β = 0.578), glycated hemoglobin (β = 0.281), and activated partial thromboplastin time (β = 0.276). In conclusion SCH in DM patients appears to increase the magnitude of coagulopathy.

The uptake of Cd(II) ions from simulated wastewater onto olive pips was modeled using artificial neural network (ANN) which consisted of three layers. Based on 112 batch experiments, the effect of contact time (10-240 min), initial pH (2-6), initial concentration (25-250 mg/l), biosorbent dosage (0.05-2 g/100 ml), agitation speed (0-250 rpm) and temperature (20-60ºC) were studied. The maximum uptake (=92 %) of Cd(II) was achieved at optimum parameters of 60 min, 6, 50 mg/l, 1 g/100 ml, 250 rpm and 25ºC respectively.

Tangent sigmoid and linear transfer functions of ANN for hidden and output layers respectively with 7 neurons were sufficient to present good predictions for cadmium removal efficiency with coefficient of correlatio

Leishmania parasites reproduce wherever there are cells of the mononuclear phagocyte system, almost in macrophages. These are most copious in the liver and spleen;therefore, infection leads to an expansion of both of them. This study determined the burden of visceral leishmaniasis (VL) infection on liver and spleen. A total of 20 mice were infected peritoneally with 2x107promastigotes of Leishmania donovani / ml and other 12 mice left without infection as a healthy control. The weight of whole body, liver and spleen were measured and the histological development using hematoxylin and eosin stains were determined after 15, 30, 45-and 60-days post infection. The results represent that the mean weights of liver and spleen were increased in inf

Double hydrothermal method was used to prepare nano gamma alumina   using aluminum nitrate nano hydrate and sodium aluminate as an aluminum source, CTAB (cetyltrimethylammonium bromide) as surfactant, and variable acids: weak acids like; citric, and acitic acids, and strong acids like; hydrochloric and nitric acids as a bridge between aluminum salts and surfactant. Different crystallization times  12, 24, 48, and 72 hrs were applied. All the batches were prepared at pH equals to 9. XRD diffraction technique was used to investigate the crystalline nano gamma alumina pure from surfactant. N₂ adsorption-desorption (BET) was used to measure the surface area and pore volume of the prepared nano alumina, the average p

       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

Objective: The study aimed to evaluate knowledge and practices of nursing staff at the orthopedic units
regarding the existing care of patient with skin traction.
Methodology: The sample consists of (40) nurses, (20) of them from Emergency Teaching Hospital in Duhok
and the other (20) of them from Erbil Teaching Hospital in Erbil from 1st Dec. 2004 to the end of June 2005 in
Kurdistan Region.
Two instruments were constructed to evaluate knowledge and practices. Evaluation of knowledge was done by
using of multiple choice questions composed of (25) questions, and evaluation of practice was done by using the
observational check list which consist of four main category (pre skin traction, during skin traction, post skin

We have provided in this research model multi assignment  with  fuzzy function goal has been to build programming model is correct Integer Programming fogging  after removing the case from the objective function data and convert it to real data .Pascal triangular graded mean using Pascal way to the center of the triangular.

The data processing to get rid of the case fogging which is surrounded by using an Excel 2007 either model multi assignment  has been used program LNDO to reach the optimal solution, which represents less than what can be from time to accomplish a number of tasks by the number of employees on the specific amount of the Internet, also included a search on some of the

This research study of influence of Chinese thought on porcelain in the tang and song period, the study came into four sections, which are:
* First section contains general framework of the research, which include the problem, which is represented by following of questions:
1- Is there intellectual and ideological dimensions in Chinese porcelain?
2-What are the mechanisms and techniques of Chinese porcelain?
.the importance of this research and the need counted as a study providing cognitive addition into the Chinese arts field, especially ceramics of the Chinese. The aim of the research included of areas of artistic creativity in Chinese pottery and ceramics according to the bases of construction and composition. As the impo

Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature