In this study, a different design of passive air Solar Chimney(SC)was tested by installing it in the south wall of insulated test room in Baghdad city. The SC was designed from vertical and inclined parts connected serially together, the vertical SC (first part) has a single pass and Thermal Energy Storage Box Collector (TESB (refined paraffin wax as Phase Change Material(PCM)-Copper Foam Matrix(CFM))), while the inclined SC was designed in single pass, double passes and double pass with TESB (semi refined paraffin wax with copper foam matrix) with selective working angle ((30^o, 45^o and 60^o). A computational model was employed and solved by Finite Volume Method (FVM) to simulate the air i

This  investigation was conducted to recognize the structure for (RHETI version 2.5  1999) by using exploratory and confirmatory factor analysis. Sample of (620) student of Al-Mustansrya University were administered the (RHETI).

The data of their responses was analyzed by using (PAF) and oblique rotating .

The findings explored (9) factors as one factor for each type and (184) items were loaded by the factors: (60) item for feeling center, (61) items for instinctive center and (63) items for thinking center.

Results of confirmatory factorial analysis supported a model designed by the researcher depended upon a theoretical views of Riso and Hudson

This research takes up address the practical side by taking case studies for construction projects that include the various Iraqi governorates, as it includes conducting a field survey to identify the impact of parametric costs on construction projects and compare them with what was reached during the analysis and the extent of their validity and accuracy, as well as adopting the approach of personal interviews to know the reality of the state of construction projects. The results showed, after comparing field data and its measurement in construction projects for the sectors (public and private), the correlation between the expected and actual cost change was (97.8%), and this means that the data can be adopted in the re

In this research study the synodic month for the moon and their
relationship with the mean anomaly for the moon orbit and date A.D
and for long periods of time (100 years), we was design a computer
program that calculates the period of synodic months, and the
coordinates of the moon at the moment of the new moon with high
accuracy. During the 100 year, there are 1236 period of synodic
months.
We found that the when New Moon occurs near perigee (mean
anomaly = 0°), the length of the synodic month at a minimum.
Similarly, when New Moon occurs near apogee (mean anomaly =
180°), the length of the synodic month reaches a maximum. The
shortest synodic month on 2053 /1/ 16 and lasted (29.27436) days.
The lo

Introduction: Methadone hydrochloride (MDN) is an effective pharmacological substitution treatment for opioids dependence, adopted in different countries as methadone maintenance treatment (MMT) programmes. However, MDN can exacerbate the addiction problem if it is abused and injected intravenously, and the frequent visits to the MMT centres can reduce patient compliance. The overall aim of this study is to develop a novel extended-release capsule of MDN using the sol-gel silica (SGS) technique that has the potential to counteract medication-tampering techniques and associated health risks and reduce the frequent visits to MMT centres. Methods: For MDN recrystallisation, a closed container method (CCM) and hot-stage method (HSM) were conduc

Abstract Bilastine, a second-generation antihistamine, is commonly prescribed for managing allergic rhinoconjunctivitis and urticaria due to its prolonged action. However, its therapeutic potential is constrained by poor water solubility and low oral bioavailability. This study aimed to enhance bilastine dissolution and patient compliance by formulating a nanosuspension-based orodispersible film (ODF). An anti-solvent precipitation method was employed to produce nanosuspension using different hydrophilic stabilizers (Soluplus®, Poloxamer 188, and PEG 6000). The influence of formulation parameters, such as the stabilizer ratio, the anti-solvent ratio, stirring speed, and the stabilizer type, on particle size and polydispersity index (PDI)

Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes

A new pavement technology has been developed in Highway engineering: asphalt pavement production is less susceptible to oxidation and the consequent damages. The warm mix asphalt (WMA) is produced at a temperature of about (10-40) ^oC lower than the hot asphalt paving. This is done using one of the methods of producing a WMA. Although WMA's performance is rather good, according to previous studies, as it is less susceptible to oxidation, it is possible to modify some of its properties using different materials, including polymers. Waste tires of vehicles are one of the types of polymers because of their flexible properties. The production of HMA, WMA, and WMA modified with proportions of (1, 1.5, and 2%) of rub

This paper proposes a new structure of the hybrid neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number