The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system

Most intrusion detection systems are signature based that work similar to anti-virus but they are unable to detect the zero-day attacks. The importance of the anomaly based IDS has raised because of its ability to deal with the unknown attacks. However smart attacks are appeared to compromise the detection ability of the anomaly based IDS. By considering these weak points the proposed
system is developed to overcome them. The proposed system is a development to the well-known payload anomaly detector (PAYL). By
combining two stages with the PAYL detector, it gives good detection ability and acceptable ratio of false positive. The proposed system improve the models recognition ability in the PAYL detector, for a filtered unencrypt

The current study aimed to evaluate the effect of the heavy metals copper, cadmium and cobalt when added individually, in combination and in combination on the growth and reproduction of the aquatic fungus Saprolegnia hypogyna.

Bacteria could produce bacterial nanocellulose through a procedure steps: polymerization and crystallization, that occur in the cytoplasm of the bacteria, the residues of glucose polymerize to (β-1,4) lineal glucan chains that produced from bacterial cell extracellularly, these lineal glucan are converted to microfbrils, after that these microfbrils collected together to shape very pure three dimensional pored net. It could be obtained a pure cellulose that created by some M.O, from the one of the active producer organism like Acetic acid bacteria (AAB), that it is a gram -ve, motile and live in aerobic condition. The bacterial nanocellulose (BNC) have great consideration in many fields because of its flexible properties, features

The combination of high protein content and a soft seed coat makes the wheat-rye hybrid Triticale (Triticosecale) vulnerable to attack by rice weevils. Drying triticale grain to moisture contents safe for storage can prevent infestation by rice weevils, but if grain is being stored for seed, high drying temperatures can affect seed germination. Grain can be effectively dried at low temperatures, but low-temperature drying is difficult in hot, humid regions such as the Gulf Coast. This study nvestigated the effects of drying temperatures from 35°C to 45°C on triticale seed germination and found no statistical differences between the germination rates of the seed at any of the drying temperatures and the germination rates of controls. Final