Lifestyle Medicine is the application of evidence-based lifestyle approaches for the prevention, treatment, and even the reversal of lifestyle-related chronic diseases such as diabetes, hypertension, heart disease, obesity, polycystic ovarian diseases, dementia, arthritis, and cancers

The redevelopment of brownfields participate to sustainable urban development, it can make cities more valuable worth for community and more attractive for companies to settle down their projects through investment, and it can help to reduce expenditures for the construction of infrastructures and other services. Recent studies in brownfield redevelopment and investment have shown great interest in urban planning studies because of their negative effects on cities, they promoted sprawl, pollution, social and economic problems. There is a general agreement among researchers and experts that brownfield sites can be reused as green spaces, commerce centers, and residential projects. To promote sustainable urban development the role of the c

     Game theory problems (GTP) frequently occur in Economy, Business Studies, Sociology, Political Science, Military Activities, and so on are some of the subjects covered. To tackle the uncertainty in Games, the analysis of games in which the payoffs are represented by fuzzy numbers (FN) will benefit from fuzzy set theory (FST).

The purpose of this paper is to develop an efficient technique for solving constraint matrix games (MG) with payoff trapezoidal fuzzy numbers (TFN). The description of the new ranking method is introduced for a constrained matrix with TFN and values. Stock market forecasting has been one of the most important research areas for decades. Stock market values are volatile, non-linear, complicated and ch

      Many neuroscience applications, including understanding the evolution of the brain, rely on neural cell instance segmentation, which seeks to integrate the identification and segmentation of neuronal cells in microscopic imagery. However, the task is complicated by cell adhesion, deformation, vague cell outlines, low-contrast cell protrusion structures, and background imperfections. On the other hand, existing segmentation approaches frequently produce inaccurate findings. As a result, an effective strategy for using the residual network with attention to segment cells is suggested in this paper. The segmentation mask of neural cells may be accurately predicted. This method is built on U-net, with EfficientNet serving as the e

The minimization, treatment and disposal of drilling wastes especially oily wastes are important environmental issues.

In this research two fungal isolates named Pleurotus ostreatus and Trichoderma harzianum were chosen carefully f or the purpose of biotreatment of oily drilled cuttings which resulting from  drilling oil wells using oil based muds (OBMs).

A relationship of total petroleum hydrocarbon degradation in oily drilled cuttings with time has been obtained. The results showed that Pleurotus ostreatus and Trichoderma harzianum can be considered hydrocarbon degrading microorganisms and the used biotreatment is cost effective process since most of the materials used in the cultivation and growth of the present f

The research aims to highlight on the reasons of financial & managerial corruption phenomena and to suggest systems & methods that promote controlling and developing the mechanism to combat corruption it also highlights on the ways that should available to enable the three regulatory agencies to reduce this phenomenon. The research depends on the following hypothesis "the governance of state institutions and the application of electronic government with depending on a correct mechanism to crossing auditing and the equilibrium performance model well help to reduce corruption phenomenon in Iraq" the two researchers have been concluded some conclusions the main one is that so many reasons of corruption starting from the bad

In the United States, the pharmaceutical industry is actively devising strategies to improve the diversity of clinical trial participants. These efforts stem from a plethora of evidence indicating that various ethnic groups respond differently to a given treatment. Thus, increasing the diversity of trial participants would not only provide more robust and representative trial data but also lead to safer and more effective therapies. Further diversifying trial participants appear straightforward, but it is a complex process requiring feedback from multiple stakeholders such as pharmaceutical sponsors, regulators, community leaders, and research sites. Therefore, the objective of this paper is to describe three viable strategies that can p

Biomarkers to detect Alzheimer’s disease (AD) would enable patients to gain access to appropriate services and may facilitate the development of new therapies. Given the large numbers of people affected by AD, there is a need for a low-cost, easy to use method to detect AD patients. Potentially, the electroencephalogram (EEG) can play a valuable role in this, but at present no single EEG biomarker is robust enough for use in practice. This study aims to provide a methodological framework for the development of robust EEG biomarkers to detect AD with a clinically acceptable performance by exploiting the combined strengths of key biomarkers. A large number of existing and novel EEG biomarkers associated with slowing of EEG, reductio

        Artificial Neural networks (ANN) are powerful and effective tools in time-series applications. The first aim of this paper is to diagnose better and more efficient ANN models (Back Propagation, Radial Basis Function Neural networks (RBF), and Recurrent neural networks) in solving the linear and nonlinear time-series behavior. The second aim is dealing with finding accurate estimators as the convergence sometimes is stack in the local minima. It is one of the problems that can bias the test of the robustness of the ANN in time series forecasting. To determine the best or the optimal ANN models, forecast Skill (SS) employed to measure the efficiency of the performance of ANN models. The mean square error and