Smoking and central obesity have both been linked to periodontitis, but their combined relationship with periodontal disease may be influenced by demographic and behavioral factors. This cross-sectional study analyzed records of 420 adult dental patients attending the College of Dentistry at the University of Baghdad. Data included demographic characteristics, smoking status, periodontal clinical findings, body mass index (BMI), and waist-to-height ratio (WHtR). Periodontitis was defined according to the 2018 classification framework, and logistic regression models were used to examine the associations of smoking and obesity-related indicators with periodontitis. The overall prevalence of periodontitis was 36.4%. Participants with p

Background: Mycoplasma pneumoniae (M. pneumoniae) is an important respiratory bacterial pathogen, especially among children. It causes acute upper and lower respiratory infections.Objective: This study was aimed to measure anti- M. pneumoniae antibodies among hospitalized children who were admitted to hospital diagnosed with acute respiratory tract infections.Method: Automated ELISA technique was performed to detect anti- M. pneumoniae antibodies (IgM and IgG antibodies) in serum from 108 children less than 5 years old. The children were admitted to the Pediatric Teaching Hospital in Suleimani city/Kurdistan Region/Iraq because of acute respiratory tract infections. A questionnaire was designed to collect demographic and clinical data fr

Sensibly highlighting the hidden structures of many real-world networks has attracted growing interest and triggered a vast array of techniques on what is called nowadays community detection (CD) problem. Non-deterministic metaheuristics are proved to competitively transcending the limits of the counterpart deterministic heuristics in solving community detection problem. Despite the increasing interest, most of the existing metaheuristic based community detection (MCD) algorithms reflect one traditional language. Generally, they tend to explicitly project some features of real communities into different definitions of single or multi-objective optimization functions. The design of other operators, however, remains canonical lacking any inte

Background: Ankylosing spondylitis is a chronic inflammatory disease that mostly involves the spine and sacroiliac joints. It is associated with a decreased quality of life. Biological medicines such as infliximab and its biosimilar are the mainstay treatments for active ankylosing spondylitis.

Objective: The study objective was to conduct a pharmacoeconomic study comparing the cost-effectiveness of the reference infliximab with its biosimilar in ankylosing spondylitis patients visiting public hospitals.

Subjects and Method: This is a two-center pharmacoeconomic study performed at two large teaching governmental hospitals in Baghdad, Iraq, which s

Autorías: Omar Khalid Yasir, Marwa Husein Ali, Aws Miqdad Jafar Hassan Alhusseini. Localización: Retos: nuevas tendencias en educación física, deporte y recreación. Nº. 70, 2025. Artículo de Revista en Dialnet.

Earth dams are constructed mainly from soil. A homogenous earth dam is composed of only one material. The seepage through such dams is quite high. Upstream impervious blanket is one of the methods used to control seepage through the dam foundations. Bennet's method is one of the commonly used methods to design an impervious upstream blanket. Design charts are developed relating the length of blanket, total reservoir head, total base width of the dam (excluding downstream drainage), the coefficient of permeability of the blanket material, blanket thickness, foundation thickness, and coefficient of permeability of the foundation soil, based on the equations governing the Bennet's method for a homogenous earth dam with a blanket of uniform

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a