This study attempts to address the importance of communicative digitization in the field of various arts for the sake of continuity of shopping and aesthetic, artistic and intellectual appreciation of artistic achievements by the recipient on various places of their residence in light of the COVID 19 crisis, and to highlight the importance of the plastic arts of the Iraqi painter exclusively and how it expresses in a contemporary way the environment or life reality in Iraq in light of this crisis. With all its implications affecting the life reality from various aspects and methods of its negative and positive employment. As for the research procedures, the researcher reviewed the research methodology represented by the descriptive ana

Nearly, in the middle of 1970s the split-brain theory became the only theory that explains human creativity used in all fine art and art education schools. In fact, this theory- which appeared for first time in the middle of 1940s – faced many radical changes including its concepts and structures, and these changes affected both teaching art and art criticism. To update people awareness within art field of study, this paper reviews the split-brain theory and its relationship with teaching art from its appearance to its decay in 2013 and after.

Information from 54 Magnetic Resonance Imaging (MRI) brain tumor images (27 benign and 27 malignant) were collected and subjected to multilayer perceptron artificial neural network available on the well know software of IBM SPSS 17 (Statistical Package for the Social Sciences). After many attempts, automatic architecture was decided to be adopted in this research work. Thirteen shape and statistical characteristics of images were considered. The neural network revealed an 89.1 % of correct classification for the training sample and 100 % of correct classification for the test sample. The normalized importance of the considered characteristics showed that kurtosis accounted for 100 % which means that this variable has a substantial effect

The behaviour of certain dynamical nonlinear systems are described in term as chaos, i.e., systems' variables change with the time, displaying very sensitivity to initial conditions of chaotic dynamics. In this paper, we study archetype systems of ordinary differential equations in two-dimensional phase spaces of the Rössler model. A system displays continuous time chaos and is explained by three coupled nonlinear differential equations. We study its characteristics and determine the control parameters that lead to different behavior of the system output, periodic, quasi-periodic and chaos. The time series, attractor, Fast Fourier Transformation and bifurcation diagram for different values have been described.

Checkpoint inhibitors are a type of immune therapy used to treat different types of cancers. These drugs block different checkpoint proteins, for example, CTLA-4, PD-1, and PD-L1 inhibitors.

They block proteins that stop the immune system from attacking the cancer cells.  Checkpoints are also described as a type of monoclonal antibody that antagonizes binding between B7 to CTLA-4 and PD-L1 to PD-1.

 Immune checkpoint inhibitors are used to treat BARCA mutated triple-negative breast cancer (TNBCS) in patients who do not respond to chemotherapy, and also in the treatment of highly mutated and solid tumors such as brain tumors, liver, and pancreatic cancers.

Immune checkpoint inhibitors exhibit an effect on solid tumo

Abstract

                  The study aimed to prepare a practical guide for procedures for auditing the strategies of municipal institutions in achieving sustainable development by adopting the idea of ​​the audit matrix through which a classified report is prepared according to the dimensions of sustainable development, by preparing a specialized audit program for the purpose of auditing strategies for achieving sustainable development and emptying the results of the application of each of the paragraphs The program in the audit matrix that was prepared for the purpose of determining the impact of each observation and linkin

The diabetic foot is considered one of the long term diabetes complications caused by a defect in blood vessel and nerve system. This requires dealing with diabetic foot with professional medical care, so as to prevent its development in advanced stages which could end to gangrene and amputation of the foot. This study has been initiated through follow-up of twelve patients with diabetes and the presence various occlusions in lower limb artery. One patient from them was chosen for investigation, this patient has stenosis in popliteal artery and presence multiple stenosis in superficial femoral artery. This study based on analysis present case of patient and prediction for progress stenosis in superficial femoral artery till arrive semi t

Abstract:

 This research aims to compare Bayesian Method and Full Maximum Likelihood to estimate hierarchical Poisson regression model.

The comparison was done by  simulation  using different sample sizes (n = 30, 60, 120) and different Frequencies (r = 1000, 5000) for the experiments as was the adoption of the  Mean Square Error to compare the preference estimation methods and then choose the best way to appreciate model and concluded that hierarchical Poisson regression model that has been appreciated Full Maximum Likelihood Full Maximum Likelihood  with sample size  (n = 30) is the best to represent the maternal mortality data after it has been reliance value param

Within the framework of big data, energy issues are highly significant. Despite the significance of energy, theoretical studies focusing primarily on the issue of energy within big data analytics in relation to computational intelligent algorithms are scarce. The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amo