Pathology reports are necessary for specialists to make an appropriate diagnosis of diseases in general and blood diseases in particular. Therefore, specialists check blood cells and other blood details. Thus, to diagnose a disease, specialists must analyze the factors of the patient’s blood and medical history. Generally, doctors have tended to use intelligent agents to help them with CBC analysis. However, these agents need analytical tools to extract the parameters (CBC parameters) employed in the prediction of the development of life-threatening bacteremia and offer prognostic data. Therefore, this paper proposes an enhancement to the Rabin–Karp algorithm and then mixes it with the fuzzy ratio to make this algorithm suitable

Background: The aryl hydrocarbon receptor (AhR) is a ligand-activated transcription factor historically recognized for its role in the regulation of toxicity mediated by environmental chemicals. Recent research points to AhR's critical participation in male reproductive physiology, particularly in spermatogenesis, hormone signaling, and the maintenance of sperm quality. Both endogenous ligands (e.g., dietary and gut microbiota-derived metabolites) and exogenous pollutants (e.g., dioxins and benzo-α-pyrene) influence AhR-mediated pathways, making it a key link between environmental exposures and male fertility. Results: This review highlights AhR's influence on the male reproductive system, emphasizing the role of endogenous AhR ligands an

Cassava, a significant crop in Africa, Asia, and South America, is a staple food for millions. However, classifying cassava species using conventional color, texture, and shape features is inefficient, as cassava leaves exhibit similarities across different types, including toxic and non-toxic varieties. This research aims to overcome the limitations of traditional classification methods by employing deep learning techniques with pre-trained AlexNet as the feature extractor to accurately classify four types of cassava: Gajah, Manggu, Kapok, and Beracun. The dataset was collected from local farms in Lamongan Indonesia. To collect images with agricultural research experts, the dataset consists of 1,400 images, and each type of cassava has

Hyperprolactinemia is a common endocrine abnormality caused by physiological factors like pregnancy and lactation, drug-induced factors like antipsychotics, pituitary adenomas that secrete prolactin, or stalk compression or section that reduces dopamine inhibition. Dopamine agonists cure most prolactinomas.