A simple setup of random number generator is proposed. The random number generation is based on the shot-noise fluctuations in a p-i-n photodiode. These fluctuations that are defined as shot noise are based on a stationary random process whose statistical properties reflect Poisson statistics associated with photon streams. It has its origin in the quantum nature of light and it is related to vacuum fluctuations. Two photodiodes were used and their shot noise fluctuations were subtracted. The difference was applied to a comparator to obtain the random sequence.

A 3D Geological model was generated using an advanced geostatistical method for the Cretaceous reservoir in the Bai Hassan oil field. In this study, a 3D geological model was built based on data from four wells for the petrophysical property distribution of permeability, porosity, water saturation, and NTG by using Petrel 2021 software. The geological model was divided into a structural model and a property model. The geological structures of the cretaceous reservoir in the Bai Hassan oil field represent elongated anticline folds with two faults, which had been clarified in the 3D Structural model. Thirteen formations represent the Cretaceous reservoir which includes (Shiranish, Mashurah, U.kometan, Kometan Shale, L. Kometan, Gulnen

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

Systemic lupus Erythematosus is an autoimmune disease of unknown aetiology affecting multiple organ system. Reactive nitrogen and oxygen species are claimed to play a role in this disease. However, the potential of Nitrosative/Oxidative Stress to elicit an autoimmune, response remain till now largely unexplored in humans. This study was done to investigate the status and contribution of nitrosative/oxidative stress in Iraqi patients for systemic lupus erythematosus. Blood samples from 19 patients with systemic lupus erythematosus and 19 age-and sex- matched apparently healthy controls were evaluated for serum levels of nitrosative/oxidative stress markers including nitric oxide, peroxynitrite and malondialdehyde. Nitric oxide levels were

The aim of this study is to develop a novel framework for managing risks in smart supply chains by enhancing business continuity and resilience against potential disruptions. This research addresses the growing uncertainty in supply chain environments, driven by both natural phenomena-such as pandemics and earthquakes—and human-induced events, including wars, political upheavals, and societal transformations. Recognizing that traditional risk management approaches are insufficient in such dynamic contexts, the study proposes an adaptive framework that integrates proactive and remedial measures for effective risk mitigation. A fuzzy risk matrix is employed to assess and analyze uncertainties, facilitating the identification of disr

The main risks arising from the WTO Agreement are the inequality and lack of competitiveness of most pharmaceutical goods, as well as the fact that Iraq is a net importer of medicines that are at the core of consumer needs, The subject matter of the Convention on the Protection of Intellectual Property Rights and its implications for the pharmaceutical industry, in particular, coinciding with the situation of financial and administrative corruption, all of which has resulted in drug fraud in the Iraqi market and its impact on public health. The control of medical technology, the persistence of the technological gap and its effects on high price levels, and the fact that domestic drug producers are obliged to obtain production licens

The aim of this paper is to derive a posteriori error estimates for semilinear parabolic interface problems. More specifically, optimal order a posteriori error analysis in the - norm for semidiscrete semilinear parabolic interface problems is derived by using elliptic reconstruction technique introduced by Makridakis and Nochetto in (2003). A key idea for this technique is the use of error estimators derived for elliptic interface problems to obtain parabolic estimators that are of optimal order in space and time.