Tirzepatide is a revolutionary and promising medication with a high impact in the treatment of Obesity and T2DM with their complications. Its efficacy was proven through different trials in achieving favorable weight loss and a significant reduction in glycemic index. It also treated a large diversity of related co-morbidities, including fatty liver, cardiovascular disease, dyslipidemia, and more. Tirzepatide is well tolerated, has a good safety profile, and is highly reliable and suitable for use in a population.

Multiple linear regressions are concerned with studying and analyzing the relationship between the dependent variable and a set of explanatory variables. From this relationship the values of variables are predicted. In this paper the multiple linear regression model and three covariates were studied in the presence of the problem of auto-correlation of errors when the random error distributed the distribution of exponential. Three methods were compared (general least squares, M robust, and Laplace robust method). We have employed the simulation studies and calculated the statistical standard mean squares error with sample sizes (15, 30, 60, 100). Further we applied the best method on the real experiment data representing the varieties of

Wireless sensor applications are susceptible to energy constraints. Most of the energy is consumed in communication between wireless nodes. Clustering and data aggregation are the two widely used strategies for reducing energy usage and increasing the lifetime of wireless sensor networks. In target tracking applications, large amount of redundant data is produced regularly. Hence, deployment of effective data aggregation schemes is vital to eliminate data redundancy. This work aims to conduct a comparative study of various research approaches that employ clustering techniques for efficiently aggregating data in target tracking applications as selection of an appropriate clustering algorithm may reflect positive results in the data aggregati

     A Spectroscopic study has been focused in this article to study one of the main types of active galaxies which are quasars, and to be more precise this research focuses on studying the correlation between the main engine of Quasi-Stellar Objects (QSO), the central black hole mass (SMBH) and other physical properties (e.g. the star formation rate (SFR)). Twelve objects have been randomly selected for “The Half Million Quasars (HMQ) Catalogue” published in 2015 and the data collected from Salon Digital Sky survey (SDSS) Dr. 16. The redshift range of these galaxies were between (0.05 – 0.17). The results show a clear linear proportionality between the SMBH and the SFR, as well as direct proportional between the luminosit

those affected by technological development risks within the scope of medical works. The unprecedented technological development the world witnesses nowadays has been providing brilliant medical service to the human being including examination, diagnosis and the treatment or follow up. However, such works hide behind potential risks threatening people's lives and such risks my be discovered within the limits of now – how and technical knowledge prevailing the time of rendering the medical service. Also this the question is raised on how to keep up between the safety of the patients and such risks are being unknown by the provider and questioning them contradicts the justices. subsequently, can the patients (affected) acquire the compensat

Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes

Periodontal diseases are inflammatory diseases, for which, scaling and root planning is the main approach. Diode laser therapy as an adjunct to non-surgical periodontal treatment has shown some beneficial effects.

Aim: The objective of this single randomized controlled clinical study was to assess the effect of a 940 nm diode laser as an adjunct to SRP therapy in the treatment of periodontal pockets.

 Methods: In this study, twenty patients in need of periodontal treatment with periodontal pocket ≥ 4 mm were selected for this split-mouth clinical study. Test group treated by diode laser 940 nm as an adjunct with SRP, control group treated by SRP in contralateral quadrants. Clinical

  Breast cancer is the most common cancer among women over the world. To reducing reoccurrence and mortality rates, adjuvant hormonal therapy (AHT) is used for a long period. The major barrier to the effectiveness of the treatment is adherence. Adherence to medicines among patients is challenging. Patient beliefs in medications can be positively or negatively correlated to adherence. Objectives: To investigate the extent of adherence and factors affecting adherence, as well as to investigate the association between beliefs and adherence in women with breast cancer taking AHT. Method: A cross-sectional study included 124 Iraqi women with breast cancer recruited from Middle Euphrates

Medical image security is possible using digital watermarking techniques. Important information is included in a host medical image in order to provide integrity, consistency, and authentication in the healthcare information system. This paper introduces a proposed method for embedding invisible watermarking in the 3D medical image. The cover medical image used is DICOM which consists of a number of slices, each one representing a sense, firstly must separate the ROI (Region of Interest) and NROI (Not Region Of Interest) for each slice, the separation process performed by the particular person who selected by hand the ROI. The embedding process is based on a key generated from Arnold's chaotic map used as the position of a pixel in