In this paper, thin films of undoped and nickel oxide (NiO) doped titanium dioxide (TiO2) were prepared using the chemical spray pyrolysis deposition (CSP) technique, with different concentrations of nickel oxide (NiO) in the range (3-9) wt%. The morphological, structural, electrical, and sensing properties of a gas of the prepared thin films were examined. XRD measurements showed that TiO2 films have a polycrystalline structure. AFM analysis showed that these films have a regular structure both before and after doping . The roughness of these films  decreased after adding  impurities but then the opposite of that took  place. The electrical and gas sensing properties of titanium dioxide  was also affected after dopin

It is widely accepted that early diagnosis of Alzheimer's disease (AD) makes it possible for patients to gain access to appropriate health care services and would facilitate the development of new therapies. AD starts many years before its clinical manifestations and a biomarker that provides a measure of changes in the brain in this period would be useful for early diagnosis of AD. Given the rapid increase in the number of older people suffering from AD, there is a need for an accurate, low-cost and easy to use biomarkers that could be used to detect AD in its early stages. Potentially, the electroencephalogram (EEG) can play a vital role in this but at present, no reliable EEG biomarker exists for early diagnosis of AD. The gradual s

Accurate estimation of permeability is essential for reliable reservoir characterization and simulation. However, core data are often limited due to their high cost and operational constraints, leading to significant uncertainty in uncored intervals. This study aims to reduce the dependence on core data for permeability estimation by integrating electrofacies derived from well logs and flow zone indicator analysis in the Mishrif Formation, Nasiriyah oil field. Electrofacies were generated using dynamic clustering based on the log data from 13 wells. This led to the identification of five electrofacies units that represent intervals with similar log responses, formed by merging 75 electrofacies, where flow zone indicators analysis id

For several applications, it is very important to have an edge detection technique matching human visual contour perception and less sensitive to noise. The edge detection algorithm describes in this paper based on the results obtained by Maximum a posteriori (MAP) and Maximum Entropy (ME) deblurring algorithms. The technique makes a trade-off between sharpening and smoothing the noisy image. One of the advantages of the described algorithm is less sensitive to noise than that given by Marr and Geuen techniques that considered to be the best edge detection algorithms in terms of matching human visual contour perception.

The research aims to diagnose the shortcomings and weaknesses in applying the dimensions of the quality of work life and the extent of their impact on employees’ attitudes and behaviors, and thus their relationship to enhancing their core competencies. The scientific value of the research stems from highlighting the importance of the dimensions of the quality of professional life in improving the productive efficiency of workers in the public sector and raising the level of organizational performance. Because the quality of working life plays an important role in enhancing the core competencies of employees in the public sector, it can also be an incentive or a disincentive for any employee by adapting to the economic and social condit

The influence of 5-10 kHz audio frequency on the power dissipation in ac discharge of argon gas was studied experimentally, at pressures 50-80 mTorr and electrodes separation 10 cm (pd range 0.5-0.8 Torr.
cm). The measurements have shown that the discharge behavior in the ac circuit is equivalent to a series RC circuit. It is observed that the variation curve of discharge power P with the frequency f is approximately has a Gaussian shape. It is also observed that the curve of Pm- pd is the inverse of Paschen curve, where Pm is the maximum power in the frequency range. The time of breakdown is estimated from the curve of P- f.

Significant advances in the automated glaucoma detection techniques have been made through the employment of the Machine Learning (ML) and Deep Learning (DL) methods, an overview of which will be provided in this paper. What sets the current literature review apart is its exclusive focus on the aforementioned techniques for glaucoma detection using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines for filtering the selected papers. To achieve this, an advanced search was conducted in the Scopus database, specifically looking for research papers published in 2023, with the keywords "glaucoma detection", "machine learning", and "deep learning". Among the multiple found papers, the ones focusing