Introduction: Carrier-based gutta-percha is an effective method of root canal obturation creating a 3-dimensional filling; however, retrieval of the plastic carrier is relatively difficult, particularly with smaller sizes. The purpose of this study was to develop composite carriers consisting of polyethylene (PE), hydroxyapatite (HA), and strontium oxide (SrO) for carrier-based root canal obturation. Methods: Composite fibers of HA, PE, and SrO were fabricated in the shape of a carrier for delivering gutta-percha (GP) using a melt-extrusion process. The fibers were characterized using infrared spectroscopy and the thermal properties determined using differential scanning calorimetry. The elastic modulus and tensile strength tests were dete

       The current research aims to build a training program for chemistry teachers based on the knowledge economy and its impact on the productive thinking of their students. To achieve the objectives of the research, the following hypothesis was formulated:

   There is no statistically significant difference at (0.05) level of significance between the average grades of the students participating in the training program according to the knowledge economy and the average grades of the students who did not participate in the training program in the test of productive thinking. The study sample consisted of (288) second intermediate grade students divided into (152) for the control group

In a hybrid cooling solar thermal systems , a solar collector is used to convert solar energy into heat energy in order to super heat the refrigerant leaving the compressor, and this process helps in the transformation of refrigerant state from gaseous state to the liquid state in upper two-thirds of the condenser instead of the lower two-thirds such as in the traditional air-conditioning systems and this will reduce the energy needed to run the process of cooling .In this research two systems with a capacity of 2 tons each were used, a hybrid air-conditioning system with an evacuated tubes solar collector and a traditional air-conditioning system . The refrigerant of each type was R22.The comparison was in the amou

          The subject of marketing culture and mental image is one of the important topics in the field of management. There is no study that combines these two variables. The research is important because of the increasing importance of the subject. The future direction of the company in question will support the company's economic and marketing responsibilities. And reflect the company's mental image, as a culture that contributes to changing the reality of the organization investigated by polling the views of a sample of managers in the General Company for Vegetable Oil Industry, which (30) out of the (65) individual, and There are two hypotheses of research: There is a significant

represent websites link support of human communicate and cohesion of cultures different depending on their languages and their environments around, it was the evolution of one of the most important means of communication of services for electronic networks, the Internet active role in containing the world Bbodqh science and knowledge to Taatlaqah cultures from which derives its intellectual and cognitive cupboards continuity and as a link language for each those environmental Altdadat, linguistic, religious, political, economic . We all know that these electronic means difficult promise ring intellectual and mental connectivity for the masses polarized without being of the image as an element Kravekaa supporter of the electronic media an

The aim of this work is to study the effect of diesel fuel percentage on the combustion processes in compression ignition engine using dual – fuel (diesel and LPG).

 The brake thermal efficiency increased with the increase of diesel fuel rate at low loads, and decreased when load increased. To get sufficient operation in engine fueled with dual fuel, it required sufficient flow rate of diesel fuel, if the engine fueled with insufficient diesel fuel erratic operation with miss fire cycles presented.

Dual-fuel operation at part load showed higher specific fuel consumption than straight diesl operation. At full loads, brake specific fuel consumption of duel fuel engine approaches that for diesel fuel values.

The complexity and variety of language included in policy and academic documents make the automatic classification of research papers based on the United Nations Sustainable Development Goals (SDGs) somewhat difficult. Using both pre-trained and contextual word embeddings to increase semantic understanding, this study presents a complete deep learning pipeline combining Bidirectional Long Short-Term Memory (BiLSTM) and Convolutional Neural Network (CNN) architectures which aims primarily to improve the comprehensibility and accuracy of SDG text classification, thereby enabling more effective policy monitoring and research evaluation. Successful document representation via Global Vector (GloVe), Bidirectional Encoder Representations from Tra

This study employs evolutionary optimization and Artificial Intelligence algorithms to determine an individual’s age using a single-faced image as the basis for the identification process. Additionally, we used the WIKI dataset, widely considered the most comprehensive collection of facial images to date, including descriptions of age and gender attributes. However, estimating age from facial images is a recent topic of study, even though much research has been undertaken on establishing chronological age from facial photographs. Retrained artificial neural networks are used for classification after applying reprocessing and optimization techniques to achieve this goal. It is possible that the difficulty of determining age could be reduce

A new and hybrid deep learning-based approach for diagnosing faults in electric vehicle (EV) drive motors is proposed in this article. This article presents a new and hybrid deep learning-based method of diagnosing faults in the drive motors of electric vehicles (EV). In contrast to standard CNNLSTM approaches that depend on SoftMax classification, the introduced framework combines a Random Forest (RF) classifier to enhance the generalization, interpretability, and robustness of fault prediction. Furthermore meant for use on edge computing equipment with IoT integration, the design allows for real-time monitoring in resource-limited settings. The introduced algorithm utilizes a Random Forest (RF) classifier for accurate fault classification