Hard-grade asphalt binders, such as AC 20–30, offer excellent resistance to permanent deformation but are inherently brittle, making them highly susceptible to fatigue and low-temperature cracking. While polymer modification addresses these issues, virgin polymers remain expensive. Despite the growing interest in recycled plastics, the rheological impact of complex waste streams, specifically polyvinyl chloride (PVC) derived from flex banners containing plasticizers, on excessively stiff binders within the complete Superpave Performance Grading (PG) framework remains critically underexplored. This study introduces a novel valorization approach by utilizing solvent-extracted flex banner waste (WPVC) as a dual-action modifier. It leverages

This paper presents a modified training method for Recurrent Neural Networks. This method depends on the Non linear Auto Regressive (NARX) model with Modified Wavelet Function as activation function (MSLOG) in the hidden layer. The modified model is known as Modified Recurrent Neural (MRN). It is used for identification Forward dynamics of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot. This model is also used in the design of Direct Inverse Control (DIC). This method is compared with Recurrent Neural Networks that used Sigmoid activation function (RS) in the hidden layer and Recurrent Neural Networks with Wavelet activation function (RW). Simulation results shows that the MRN model is bett

     The objective of this study is to attempt to provide a quantitative analysis to the causes of unemployment  in Iraq and its mechanisms of generation, as well as a review of the most important  types of both visible and invisible unemployment, and an attempt to measure the disguised  unemployment  and analyze the causes. The problem of the research lies in the fact that the Iraqi Economy has been suffered  for  a long time although its characterized by abundant  physical and natural  resources, from the existence of the  phenomenon of unemployment  in the previous two types. Causing a lot of economic problems, represented by the great waste of resources and

Background: Non-nutritive sucking habits are common in infants and toddlers. One of the most common non-nutritive sucking habits is pacifier; its prevalence varies from one population to another. This study was conducted to determine the prevalence of pacifier sucking habit among children aged 1-5 years old in Baghdad city and to assess its effect on the occlusion of primary dentition concerning posterior crossbite. Materials and methods: The study was carried out among 1222 children aged 1-5 years old, from which 50 children with continues pacifier sucking habit were chosen to be the study group, compared to 50 children without any sucking habit (control group) matching the study group in age and gender. Children were examined clinically t

antimicrobial solutions against Coliforms, E. coli O157: H7, yeasts and molds were evaluated by agar well diffusion method. Chitosan (CH) exhibited best antimicrobial activity against the treated microorganisms at concentration of (5%) with contact time for 6hrs at refrigeration temperature (4ÚC), zones of inhibition for (GA) and (CH) for each solution alone ranging from (0 to 10 mm), chitosan solution (CH) exhibited both antibacterial and antifungal activities, Gum Arabic washing solution showed significant antibacterial activity (P < 0.05) against the microorganisms at concentration (15%), without inhibitory effect against E. coli O157:H7 at concentration (10%), in the current study the results confirmed that (15%) (w/v) of GA and 5%

Human posture estimation is a crucial topic in the computer vision field and has become a hotspot for research in many human behaviors related work. Human pose estimation can be understood as the human key point recognition and connection problem. The paper presents an optimized symmetric spatial transformation network designed to connect with single-person pose estimation network to propose high-quality human target frames from inaccurate human bounding boxes, and introduces parametric pose non-maximal suppression to eliminate redundant pose estimation, and applies an elimination rule to eliminate similar pose to obtain unique human pose estimation results. The exploratory outcomes demonstrate the way that the proposed technique can pre

Steganography is a technique of concealing secret data within other quotidian files of the same or different types. Hiding data has been essential to digital information security. This work aims to design a stego method that can effectively hide a message inside the images of the video file.  In this work, a video steganography model has been proposed through training a model to hiding video (or images) within another video using convolutional neural networks (CNN). By using a CNN in this approach, two main goals can be achieved for any steganographic methods which are, increasing security (hardness to observed and broken by used steganalysis program), this was achieved in this work as the weights and architecture are randomized. Thus,