This study evaluates the flexural behavior of ultra-thin (50 mm) one‑way reinforced‑concrete (RC) slabs retrofitted with near‑surface mounted (NSM) carbon‑fiber‑reinforced polymer (CFRP) rods under quasi‑static loading. T300‑grade CFRP rods (≈4 mm diameter) were bonded in pre‑cut 7 mm × 7 mm grooves using a two‑part epoxy. As a proof-of-concept experimental baseline, three simply‑supported specimens (1000 mm × 500 mm × 50 mm) were tested in a six‑point bending configuration (four applied loads + two reactions): two conventional controls and one strengthened slab. A load‑control rate of ~15 kN/min was applied; the controls were cycled twice and the strengthened slab four times. Relative to the average of

thin films of se:2.5% as were deposited on a glass substates by thermal coevaporation techniqi=ue under high vacuum at different thikness

In this work, wide band range photo detector operating in UV, Visible and IR was fabricated using carbon nanotubes (MWCNTs, SWCNTs) decorated with silver nanoparticles (Ag NPs). Silicon was used as a substrate to deposited CNTs/Ag NPs by the drop casting technique. Polyamide nylon polymer was used to coat CNTs/Ag NPs to enhance the photo-response of the detector. The electro-exploding wire technology was used to synthesize Ag NPs. Good dispersion of silver NPs achieved by a simple chemistry process on the surface of CNTs. The optical, structure and electrical characteristic of CNTs decorated with Ag NPs were characterized by X-Ray diffraction and Field Emission Scanning Electron Microscopy.  X-ray diffra

Face Recognition Systems (FRS) are increasingly targeted by morphing attacks, where facial features of multiple individuals are blended into a synthetic image to deceive biometric verification. This paper proposes an enhanced Siamese Neural Network (SNN)-based system for robust morph detection. The methodology involves four stages. First, a dataset of real and morphed images is generated using StyleGAN, producing high-quality facial images. Second, facial regions are extracted using Faster Region-based Convolutional Neural Networks (R-CNN) to isolate relevant features and eliminate background noise. Third, a Local Binary Pattern-Convolutional Neural Network (LBP-CNN) is used to build a baseline FRS and assess its susceptibility to d

This paper is an attempt to investigate the syntactic and semantic features of the English phrasal verbs. In this paper, phrasal verbs were classified into subgroups according to their syntactic and semantic characteristics. After giving a survey of literature written on the meaning and definition of phrasal verbs, two sections have been devoted to tackle the most important issues in this category of English verbs. Section one sheds light on the basic definitions of the term ‘phrasal verb’ which are, according to the researcher’s point of view, sufficient to cover the area of the study. In addition, it studies the number and the importance of phrasal verbs in English. Section two deals with the syntactic and semantic features of Engli

In the present study, an attempt has been made to experimentally investigate the flexural performance of ten simply supported reinforced concrete gable roof beams, including solid control specimen (i.e., without openings) and nine beams with web openings of different dimensions and configurations. The nine beams with openings have identical reinforcement details. All beams were monotonically loaded to failure under mid-span loading. The main variables were the number of the created openings, the total area of the created openings, and the inclination angle of the posts between openings. Of interest is the load-carrying capacity, cracking resistance and propagation, deformability, failure mode, and strain development that represent the behav

The aim of this paper is introducing the concept of (ɱ,ɳ) strong full stability B-Algebra-module related to an ideal. Some properties of (ɱ,ɳ)- strong full stability B-Algebra-module related to an ideal have been studied and another characterizations have been given. The relationship of (ɱ,ɳ) strong full stability B-Algebra-module related to an ideal that states,  a B- -module Ӽ is (ɱ,ɳ)- strong full stability B-Algebra-module related to an ideal  , if and only if  for any two ɱ-element sub-sets and of Ӽ^ɳ, if , for each j = 1, …, ɱ,  i = 1,…, ɳ  and   implies _Ạɳ( ) _Ạɳ(  have been proved..