Processed and red The Western diet, a modern dietary pattern, typically consists of meat, sugar-filled beverages, candies, chocolates, fried foods, prefabricated meals, refined cereals, conventionally produced animal products, high-fat dairy products, and high-fructose items. The goal of this review is to outline how the Western pattern diet affects gut microbiota and mitochondrial fitness, as well as metabolism, inflammation, and antioxidant status. Cancer, mental health, and cardiovascular health; We offer a thorough analysis of how the westernized diet and related nutrients affect immune cell responses as well as the hygienic costs of the Western diet. A consensus critical evaluation utilizing primary sources, including scientifi

Background: Gray-scale sonography is generally
considered as a first-line diagnostic tool for patient with
suspected acute cholecystitis. It is suggested by gallstones,
Murphy's sign, thickening of the gallbladder wall and bile
sludging, but the specificity of these sonographic findings
are not as high as their sensitivity. Blood flow of the
gallbladder wall is increased in acute inflammation.
Objective: To evaluate the sensitivity and specificity of
power Doppler sonography and compared with conventional
color Doppler and gray-scale sonography in diagnosing
patients with acute cholecystitis.
Type of the study: This was a cross sectional study.
Patients and methods: The study was conducted t

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob

Background: Melanin pigmentation of the gingiva appears in all ethnicities. Excessive pigmentation is an esthetic concern that has increased awareness about depigmentation procedures. This epidemiological study aims to find the correlation between skin color and gingival pigmentation in Sulaimani Governorate, Kurdistan/Iraq.

Subjects and Methods: A total of 820 apparently healthy and non-smokers, including 338 males and 482 females with healthy gingiva, aged between (18-40 years old) were enrolled in this study. Clinical examination on the participants’ gingivae was performed to assess color, and the distribution of pigmentations. Afterward the of participants skin color were

Background: Because of the demands for aesthetic orthodontic appliances have increased, aesthetic archwires have been widely used to meet patient's aesthetic needs. The color stability of aesthetic archwires is clinically important, any staining or discoloration will affect patient’s acceptance and satisfaction. This study was designed to evaluate the color stability of different types of aesthetic archwires after immersion into different types of mouth washes. Materials and methods: Four brands of nickel titanium coated aesthetic arch wires: Epoxy coated (Orthotechnology and G&H) and Teflon coated (Dany and Hubit) were evaluated after 1 week, 3 weeks and 6 weeks of immersion into two types of mouthwashes (Listerine with alcohol and

Background: Body image is one of the most important psychological factors that affects adolescents’ personality and behavior. Body image can be defined as the person’s perceptions, thoughts, and feelings about his or her body.

Objectives: to identify the prevalence of body image concerns among secondary school students and its relation to different factors.

Subjects and methods: A cross-sectional study conducted in which 796 secondary school students participated and body shape concerns was investigated using the body shape questionnaire (BSQ-34).

Results: The prevalence of moderate/marked concern was (21.6%). Moderate/ marked body shape concern was significantly associated

Abstract The goal of current study was to identify the relationship between addiction of self-images (Selfie) and personality disorder of narcissus, and the difference of significance the relationship between addiction self-images (selfie) and personality disorder narcissus at students of Mustansiriya university, addiction self- images (selfie) defined: a photograph that one has taken of oneself, typically one taken with a smartphone or webcam and shared via social media, edit and down lowed to social networking sites, and over time, the replacement of normal life virtual world, which is accompanied by a lack of a sense of time, and the formation of repeated patterns increase the risk of social and personal problems. To achieve the goals

This study explores the challenges in Artificial Intelligence (AI) systems in generating image captions, a task that requires effective integration of computer vision and natural language processing techniques. A comparative analysis between traditional approaches such as retrieval- based methods and linguistic templates) and modern approaches based on deep learning such as encoder-decoder models, attention mechanisms, and transformers). Theoretical results show that modern models perform better for the accuracy and the ability to generate more complex descriptions, while traditional methods outperform speed and simplicity. The paper proposes a hybrid framework that combines the advantages of both approaches, where conventional methods prod