Background: Diabetic cheiroarthropathy is a term derived from the Greek word “cheiros” meaning “of the hand”, It is characterized by stiff hands with distinctively thick, tight, and waxy skin, especially on the dorsal aspects of the hands. It is part of long term complication of diabetes and many suggest it is associated with microvascular complication. The aim of the study was to determine the prevalence of diabetic cheiroarthropathy in Iraqi patients with diabetes, and to study its association with diabetic retinopathy and glycemic control. Material and Methods: A cross-sectional study in which 110 diabetic patients and 110 non-diabetic healthy people who accepted to take part in the study were ran

Background : Polycystic ovary syndrome (PCOS) is the most common cause of infertility in reproductive-age women , it is an important harbinger of metabolic disorders. It has been reported that hyperamylasemia can be used as marker of ovarian cancer patients . The current study was conducted to evaluate amylase activity and to estimate the correlation of this enzyme with insulin and insulin resistance in PCOS patients. Methods: This study was conducted on forty five patients with PCOS in comparison to twenty five women as control. Fasting blood sample was taken from each subject and analyzed for amylase activity , FSH,LH, Insulin , proteins, and blood sugar , meanwhile insulin resistance was determined by HOMA-IR index. Results: The result

There were two types of plows used widely in agricultural fields in the country. The first plow was moldboard plow, while the second one was chisel plow. There were large numbers of Iraqi farmers that used chisel plow for such farming practices. Researchers found that moldboard plows gave the highest rate of carbon dioxide emission. They observed that that with chisel plows they got the lowest carbon dioxide emission. Chisel plow saved energy as compared to moldboard plow and the cost of using the chisel plows was less than the moldboard plows. Chisel plow decreased carbon dioxide emissions from the soil and improve soil properties. The benefits of using chisel plows were more than using moldboard plows.

This study aims to identify the impact of social support on breast cancer patients’ psychological rigidity using a sample in Ramallah and al-Bireh. A descriptive correlative approach was adopted to fulfill the goals of the study and a questionnaire consisted of two criteria: social support and psychological rigidity, which was adopted as a tool for data collection for the study. In order to achieve the goals of the study, the researcher selected a convenient sample that consisted of 123 female breast cancer patients in Ramallah and al-Bireh. This sample represented 50% of the original patient population. The study showed that the average estimated percentage of social support and psychological rigidity for women with breast cancer, in

As a consequence of a terrorist attack, people may experience posttraumatic stress disorder (PTSD) and lack of feeling secure in relationships. This longitudinal study aimed to examine the prevalence of PTSD symptoms over time, the relationship between adult attachment styles and PTSD, as well as their association with degree of exposure, and finally to consider the distribution and the trajectory of attachment styles. The sample consisted of 235 students (M=125, F=110) who were exposed to different levels of trauma intensity in response to a bombing attack. Participants were recruited and assessed approximately 1 month and 5 months after the attack using a battery of questionnaires. Findings revealed, as expected, that 79.5% of the part

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