Breast cancer is among the primary causes of death among Iraqi women and is a serious worldwide health concern. ALK or anaplastic lymphoma kinase, is connected to several cancers, including breast cancer.. The goal of this research was to assess the prevalence of anaplastic lymphoma kinase (ALK) with Alkaline phosphatise (ALP) and Lactate dehydrogenase (LDH) together as diagnostic markers. The study comprised 60 patients with metastatic breast cancer and 60 healthy volunteers. The blood levels of the enzymes (ALP), (LDH), and ALK in Iraqi breast cancer patients are compared to those of healthy controls. It was shown that compared to healthy people, patients had breast cancer noticeably greater levels of ALK, ALP, and NDH .These biomarkers m

This study is pointed out to estimate the effectiveness of two solvents in the extraction and evaluating the active ingredients and their antioxidant activity as well as anti-cancer efficiency. Therefore, residues from four different Brassica vegetables viz. broccoli, Brussels sprout, cauliflower, and red cherry radish were extracted using two procedures methods: methanolic and water crude extracts. Methanol extracts showed the highest content of total phenolic (TP), total flavonoids (TF), and total tannins (TT) for broccoli and Brussels sprouts residues. Methanolic extract of broccoli and Brussels sprouts residues showed the highest DPPH· scavenging activity (IC₅₀ = 15.39 and 18.64 µg/ml). The methanol and water ex

Support vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca

The purple pigment violacein is produced by Gram-negative bacteria, mainly from the Chromobacterium violaceum. Violacein is synthesized by fusing two Ltryptophan molecules using five different enzymes encoded by VioA, VioB, VioC, VioD, and VioE genes. These genes have transferred to genetically engineering microorganisms such as E.coli for high production of violacein. It is receiving greater interest because of its significant biological functions and therapeutic potential. The reviews outlining the biosynthesis, production, and biological significance of violacein are being published.

Blastocystosis is symptomatic infection caused by the protozoal parasite Blastocystis , which resides in the intestinal tract of its hosts and it is one of the most common parasites reported in humans. It’s prevalence ranges between (30 - 50%) of the population in developing countries. This genus has a worldwide distribution and often the most commonly reported human intestinal protozoan in children and adults, even infect infants

There have been many writings and discussions that dealt with the details and interpretation of the research methods and the identification of the methods and methodological methods used by researchers and writers as they deal with research topics and problems in all fields of natural and human sciences. But we noticed that the movement of science and its knowledge and development requires the identification of suitable tools and methodological methods appropriate for each type of science. In other words, attempts should be established to build appropriate methodological tools for human and cognitive activity that can be referred to as a specific science that sets out certain paths of the human sciences which is certainly the ori

Emotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In