Type 2 diabetes mellitus (T2DM) is the most frequent endocrinal disease commonly associated with thyroid disorders .The study is conducted at the Specialized Center for Endocrinology and Diabetes in Baghdad ,during December 2014 up to October 2015.This study was done to investigate the prevalence of anti- thyroid peroxidase (Anti-TPO) antibody in patients suffered from type 2 diabetes with thyroid disorders .The study groups included a total number of 80 subjects consisting of 60 type 2 diabetic patients divided into 20 hyperthyroidism subjects (group 1) ,20 hypothyroidism subjects (group 2), 20 euthyroidism subjects (group 3) and 20 healthy controls (group 4) . The fasting blood samples were analyzed for (T3,T4,TSH) by using Vitek Immuno d

Background: Phosphodiesterase-5 (PDE-5) inhibitorsrestore nitric oxide (NO) signaling and may reducecirculating inflammatory markers, and improve metabolicparameters through a number of mechanisms. Dailyadministration of the PDE-5 inhibitor, tadalafil (TAD) mayattenuate inflammation; improve fasting plasma glucose andtriglyceride levels and body weight. This study aims toevaluate the efficacy of low dose PDE-5 inhibitor, tadalafil(TAD) in controlling dysglycemia and body weight in obesediabetic men.Methods: Forty obese men with type 2 diabetes aged 30-50years incorporated in this study, all with A1c of 7-8.5%,attending obesity unit in AL-Kindy college of medicine.Weight, height, BMI, FPG, A1c, cholesterol, TG, HDL andLDL measured for all

This study looks into the many methods that are used in the risk assessment procedure that is used in the construction industry nowadays. As a result of the slow adoption of novel assessment methods, professionals frequently resort to strategies that have previously been validated as being successful. When it comes to risk assessment, having a precise analytical tool that uses the cost of risk as a measurement and draws on the knowledge of professionals could potentially assist bridge the gap between theory and practice. This step will examine relevant literature, sort articles according to their published year, and identify domains and qualities. Consequently, the most significant findings have been presented in a manne

EGFR-mutant non–small cell lung cancer (NSCLC) initially responds well to EGFR tyrosine kinase inhibitors (EGFR-TKIs), yet resistance is nearly inevitable and responses to immune checkpoint inhibitors (ICIs) remain limited. In a retrospective cohort of 57 patients with advanced EGFR-mutant NSCLC treated with nivolumab or pembrolizumab, the objective response rate was 12.3%, although responses were concentrated in a small subgroup with concurrent high PD-L1 expression and dense intratumoral CD8⁺ immune-cell infiltration. Emerging evidence links these outcomes to chemokine-network dysregulation that alters immune trafficking and spatial organization. Oncogenic EGFR signaling shifts chemokine networks away from effector T-cell recruitment

This paper proposed a new method for network self-fault management (NSFM) based on two technologies: intelligent agent to automate fault management tasks, and Windows Management Instrumentations (WMI) to identify the fault faster when resources are independent (different type of devices). The proposed network self-fault management reduced the load of network traffic by reducing the request and response between the server and client, which achieves less downtime for each node in state of fault occurring in the client. The performance of the proposed system is measured by three measures: efficiency, availability, and reliability. A high efficiency average is obtained depending on the faults occurred in the system which reaches to

Modern machine-learning applications require GPUs, and modern platforms can leverage numerous GPUs on one or more machines to increase performance. Contemporary deep-learning models are too huge for CPU or GPU training. Training these models with many GPUs without performance degradation is necessary to train them rapidly and maximize GPU consumption. Thus, training deep convolutional neural networks (DCNN) with multiple GPUs has become necessary for improving training. Therefore, we presented a parallel design and development of an efficient model for enhancing face mask CNN performance and improving resource efficiency. This DCNN model is a parallel training system over multiple GPUs, a multi-core CPU, and a multi-process GPU platform wit

Sustainable vegetative management plays a significant role in improving soil quality in degraded agricultural landscapes by enhancing soil microbial biomass. This study investigated the effects of grass buffers (GBs), biomass crops (BCs), grass waterways (GWWs), and agroforestry buffers (ABs) on soil microbial biomass and soil organic C (SOC) compared with continuous corn (Zea mays L.)–soybean [Glycine max (L.) Merr.] rotation (row crop [RC]) on claypan soils. The RC, AB, GB, GWW, and BC treatments were established in 1991, 1997, 1997, 1997, and 2012, respectively, and are located at Greenley Memorial Research Center in Missouri. Soil samples were collected in May 2018 from the 0‐ to

A remarkable correlation between chaotic systems and cryptography has been established with sensitivity to initial states, unpredictability, and complex behaviors. In one development, stages of a chaotic stream cipher are applied to a discrete chaotic dynamic system for the generation of pseudorandom bits. Some of these generators are based on 1D chaotic map and others on 2D ones. In the current study, a pseudorandom bit generator (PRBG) based on a new 2D chaotic logistic map is proposed that runs side-by-side and commences from random independent initial states. The structure of the proposed model consists of the three components of a mouse input device, the proposed 2D chaotic system, and an initial permutation (IP) table. Statist