The precise classification of DNA sequences is pivotal in genomics, holding significant implications for personalized medicine. The stakes are particularly high when classifying key genetic markers such as BRAC, related to breast cancer susceptibility; BRAF, associated with various malignancies; and KRAS, a recognized oncogene. Conventional machine learning techniques often necessitate intricate feature engineering and may not capture the full spectrum of sequence dependencies. To ameliorate these limitations, this study employs an adapted UNet architecture, originally designed for biomedical image segmentation, to classify DNA sequences.The attention mechanism was also tested LONG WITH u-Net architecture to precisely classify DNA sequences

Some relations of inclusion and their properties are investigated for functions of type " -valent that involves the generalized operator of Srivastava-Attiya by using the principle of strong differential subordination.

Giardiasis is an infection caused by the protozoan flagellate parasite Giardia spp. in the intestine. G duodenalis, a species complex of diverse genotypes that tend to demonstrate host specificity, is responsible for most veterinary health related infections; production animals, companion animals, and wildlife can all be infected. Abdominal pain and diarrhea, typically accompanied by steatorrhea, are the most common symptoms of Giardiasis. Cysts or antigens in feces are commonly used to diagnose the disease. Treatment regimens vary and are dependent on the indication. Control methods must include hygiene measures. Despite direct evidence of Giardia sp transmission to humans via polluted water supplies, our analysis will focus on some r

In this study, the sonochemical degradation of phenol in water was investigated using two types of ultrasonic wave generators; 20 kHz ultrasonic processor and 40 kHz ultrasonic cleaner bath. Mineralization rates were determined as a function of phenol concentration, contact time, pH, power density, and type of ultrasonic generator. Results revealed that sonochemical degradation of the phenol conversion was enhanced at increased applied power densities and acidic conditions. At 10 mg/L initial concentration of phenol, pH 7, and applied power density of 3000 W/L, the maximum removal efficiency of phenol was 93% using ultrasonic processor at 2h contact time. Whereby, it was 87% using and ultrasonic cleaner bath at 16h contact time and 150 W

KE Sharquie, AA Noaimi, SD Hameed, Journal of Cosmetics, Dermatological Sciences and Applications, 2013 - Cited by 15