The effect of using grinded rocks of (quartzite and porcelanite) as powder of (10 and 20) % replacement by weight of cement for self-compacting concrete slabs was investigated in this study. Five slabs with 15 concrete cubes were tested experimentally at 28 days to study the compressive strength, ultimate load, ultimate deflection, ductility, crack load and steel strain. The test results show that, the compressive strength improvement when replacement of local rock powder reached to (7.3, 4.22) % for (10 and 20) % quartzite powder and (11.3, 16.1) % for (10 and 20) % porcelanite powder, respectively compared to the reference specimen. The ultimate load percentage increase for slabs with (10 and 20) % rep

Actinomycetes are free, spore-forming, high (G+C) ratio (>55%) saprophytic microorganisms that are widely distributed in most soils, colonize plants, and are prevalent in water. This is frequently accompanied by the production of filament airborne mycelium. Actinomycetes are well-known microcolonies for creating antibiotics and other critical bioactive components that are beneficial to humans. Approximately 70% to 80% of commercially available medications and antiviral active compounds have been synthesized so far. Secondary metabolites produced by microbes have the potential to be used in a variety of sectors, including antimicrobial agents, enzyme technology, pigment manufacture, antitumor agents against cancer cells, and toxin pr

This theoretical research explores the fundamental differences between human literary writing and artificial intelligence–generated texts by examining how language, style, and narrative structure function in each form of authorship. Using Toni Morrison’s Beloved (1987) as the primary literary example, the study analyzes how human writing draws on lived experience, cultural memory, emotional depth, and intentional creativity. In contrast, AI-generated texts rely on statistical patterns rather than consciousness or authentic meaning-making, resulting in writing that may be linguistically coherent but lacks symbolic richness and emotional resonance. Through a descriptive and analytical methodology, supported by insights from Narr

The research seeks to identify the effectiveness of a selective program in modifying irrational thinking that causes anger among an important class of societies in general. namely teachers. Specifically female teachers because of the pressures they suffer because of the nature of this profession. It may develop into anger outburst, which may cause irrational thinking arose as a result of the different situations they are going through. The sample of the program consisted of (12) teachers in Egypt, from different educational sectors. The researcher intended to clarify the emotion of anger and the irrational thoughts associated with it and the contribution of the selective counseling program in modifying those irrational thinking. This was

A QR code is a type of barcode that can hold more information than the familiar kind scanned at checkouts around the world. The “QR” stands for “Quick Response”, a reference to the speed at which the large amounts of information they contain can be decoded by scanners. They are being widely used for advertising campaigns, linking to company websites, contest sign-up pages and online menus. In this paper, we propose an efficient module to extract QR code from background and solve problem of rotation in case of inaccurate image taken from mobile camera.

With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se

Most recognition system of human facial emotions are assessed solely on accuracy, even if other performance criteria are also thought to be important in the evaluation process such as sensitivity, precision, F-measure, and G-mean. Moreover, the most common problem that must be resolved in face emotion recognition systems is the feature extraction methods, which is comparable to traditional manual feature extraction methods. This traditional method is not able to extract features efficiently. In other words, there are redundant amount of features which are considered not significant, which affect the classification performance. In this work, a new system to recognize human facial emotions from images is proposed. The HOG (Histograms of Or