This study evaluated the effect of spore suspension and fungal filtrate against different developmental stages of Tribolium castaneum third and fifth larval instars and adults. Two isolates of entomopathogenic fungus Metarhizium anisopliae were used (commercially (Met 52 EC), and domesticly). For the two isolates, the effectiveness of various conidial concentrations were (1 × 104 ; 1 × 106 ; 1 × 108  conidia/ ml) and various concentrations of fungal filtrate (100,75,50%) were evaluated. It is observed that the fungal filtrate at a concentration of 75% and the conidial concentration of 1 x 108 conidia /ml for both isolates were the most effective in causing the highest mortality rates to the third and fifth instar larva and adult

The plant Conyza canadensis, which belongs to Asteraceae (Compositae) family and known as Canadian horseweed. It was used as traditional medicine in China, Pakistan, India, and Africa for the treatment of various diseases causing by bacteria, fungi, or viruses. The plant has antimicrobial, antioxidant, anticoagulant, anti-inflammatory, and anticancer pharmacological activity. This study provides the first phytochemical investigation of the plant in Iraq and is concerned with extraction, fractionation, isolation, and purification of some of the important phytochemicals detected in the plant-like phenolic acids, flavonoids, and alkaloids. Also, the literature survey has revealed that the plant has a substantial antimicrobial activity, so it w

The aim of the study was extraction of arial part of Euphorbia cyathophora constituents with methanol and evaluate its effect on mitotic index and total chromosomal aberration bone marrow cell and spleen cell in mice  200 gm of E. cyathophora fine powder was defatted then extracted by cold maceration 80% ethanol for seven days. The extract was filtered and dried in a rotary evaporator then the dried extract was suspended with water and consecutively extracted using chloroform, ethyl acetate for each. The aqueous layer was then mixed with 100ml methanol. These fractions are dried under reduced pressure to obtain the dry extract. Twenty-four Albino mice were used for the experiment. The animals were divided into four groups: Gr

Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Decision Tre

Honeywords are fake passwords that serve as an accompaniment to the real password, which is called a “sugarword.” The honeyword system is an effective password cracking detection system designed to easily detect password cracking in order to improve the security of hashed passwords. For every user, the password file of the honeyword system will have one real hashed password accompanied by numerous fake hashed passwords. If an intruder steals the password file from the system and successfully cracks the passwords while attempting to log in to users’ accounts, the honeyword system will detect this attempt through the honeychecker. A honeychecker is an auxiliary server that distinguishes the real password from the fake passwords and t

In recent years, with the rapid development of the current classification system in digital content identification, automatic classification of images has become the most challenging task in the field of computer vision. As can be seen, vision is quite challenging for a system to automatically understand and analyze images, as compared to the vision of humans. Some research papers have been done to address the issue in the low-level current classification system, but the output was restricted only to basic image features. However, similarly, the approaches fail to accurately classify images. For the results expected in this field, such as computer vision, this study proposes a deep learning approach that utilizes a deep learning algorithm.

Fractal image compression depends on representing an image using affine transformations. The main concern for researches in the discipline of fractal image compression (FIC) algorithm is to decrease encoding time needed to compress image data. The basic technique is that each portion of the image is similar to other portions of the same image. In this process, there are many models that were developed. The presence of fractals was initially noticed and handled using Iterated Function System (IFS); that is used for encoding images. In this paper, a review of fractal image compression is discussed with its variants along with other techniques. A summarized review of contributions is achieved to determine the fulfillment of fractal ima