Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise

Celiac disease (CD) is an autoimmune disorder characterized by chronic inflammation that essentially affects the small intestine and is caused by eating gluten-containing foods. This study sought to determine gene expression of NLRP3 Inflammasome in peripheral blood of Iraqi CD children using quantitative real-time PCR (qRT-PCR) assay. Thirty children with CD (12 males and 18 females) were enrolled in the study and their age range was 3-15 years. The diagnosis of the disease was confirmed by serological examinations and intestinal endoscopy. A control sample of 20 age-matched healthy children was also included. The children were stratified for age, gender, body max index (BMI), histological findings, and marsh classification. Furthe

Maintaining and breeding fish in a pond are a crucial task for a large fish breeder. The main issues for fish breeders are pond management such as the production of food for fishes and to maintain the pond water quality. The dynamic or technological system for breeders has been invented and becomes important to get maximum profit return for aquaponic breeders in maintaining fishes. This research presents a developed prototype of a dynamic fish feeder based on fish existence. The dynamic fish feeder is programmed to feed where sensors detected the fish's existence. A microcontroller board NodeMCU ESP8266 is programmed for the developed h

the association between celiac disease and viral infection

Celiac disease (CD) is the most common genetically - based disease in correlation with food intolerance. The aim of this study is to measure the activity of ALT enzyme and purify enzyme from sera women with celiac disease. Alanine aminotransferase (ALT) activity has been assayed in (30) women serum samples with celiac disease, age range between (20-40) year and (30) serum of healthy women as control group, age range between (22-38) year. In the present study, the mean value of ALT activity was significantly higher in patients with celiac disease than healthy group (p<0.01). The ALT enzyme was partial purified from sera women with celiac disease by dialysis, gel filtration using Sephadex G- 50 and ion exchange chromatography using DEAE- cell

Celiac disease (CD) is the most common genetically - based disease in correlation with food intolerance. The aim of this study is to measure the activity of ALT enzyme and purify enzyme from sera women with celiac disease. Alanine aminotransferase (ALT) activity has been assayed in (30) women serum samples with celiac disease, age range between (20-40) year and (30) serum of healthy women as control group, age range between (22-38) year. In the present study, the mean value of ALT activity was significantly higher in patients with celiac disease than healthy group (p<0.01). The ALT enzyme was partial purified from sera women with celiac disease by dialysis, gel filtration using Sephadex G- 50 and ion exchange chr

 Active worms have posed a major security threat to the Internet, and many research efforts have focused on them. This paper is interested in internet worm that spreads via TCP, which accounts for the majority of internet traffic. It presents an approach that use a hybrid solution between two detection algorithms: behavior base detection and signature base detection to have the features of each of them. The aim of this study is to have a good solution of detecting worm and stealthy worm with the feature of the speed. This proposal was designed in distributed collaborative scheme based on the small-world network model to effectively improve the system performance.

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The paper presents a neural synchronization into intensive study in order to address challenges preventing from adopting it as an alternative key exchange algorithm. The results obtained from the implementation of neural synchronization with this proposed system address two challenges: namely the verification of establishing the synchronization between the two neural networks, and the public initiation of the input vector for each party. Solutions are presented and mathematical model is developed and presented, and as this proposed system focuses on stream cipher; a system of LFSRs (linear feedback shift registers) has been used with a balanced memory to generate the key. The initializations of these LFSRs are neural weights after achiev