Due to the potential cost saving and minimal temperature stratification, the energy storage based on phase-change materials (PCMs) can be a reliable approach for decoupling energy demand from immediate supply availability. However, due to their high heat resistance, these materials necessitate the introduction of enhancing additives, such as expanded surfaces and fins, to enable their deployment in more widespread thermal and energy storage applications. This study reports on how circular fins with staggered distribution and variable orientations can be employed for addressing the low thermal response rates in a PCM (Paraffin RT-35) triple-tube heat exchanger consisting of two heat-transfer fluids flow in opposites directions throug

Objective Thalassemic patients present with multiple immune abnormalities that may predispose them to oral Candida, however this has not been investigated. The aim of this study was to assess oral candidal colonization in a group of patients with β-thalassemia major both qualitatively and quantitatively. Study design The oral mycologic flora of 50 β-thalassemia major patients and 50 age- and sex-matched control subjects was assessed using the concentrated oral rinse technique. Candida species were identified using the germ tube test and the Vitek yeast identification system. Results Oral Candida was isolated from 37 patients (74%) and 28 healthy subjects (56%; P = .04). The mean candidal count was significantly higher in thalassemic patie

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

This paper performance for preparation and identification of six new complexes of a number of transition metals Cr (lII), Mn (I1), Fe (l), Co (II), Ni (I1), Cu (Il) with: N - (3,4,5-Trimethoxy phenyl-N - benzoyl Thiourea (TMPBT) as a bidentet ligand. The prepared complexes have been characterized, identified on the basis of elemental analysis (C.H.N), atomic absorption, molar conductivity, molar-ratio ,pH effect study, I. Rand UV spectra studies. The complexes have the structural formula ML₂X₃ for Cr (III), Fe (III), and ML₂X₂ for Mn (II), Ni (II), and MLX₂ for Co (Il) , Cu (Il).

Abstract

The research aims to examine the relationship between psychological flow, psychological well-being, and self-management among a sample of fine artists in the Makkah region and its governorates. The research also aims to examine the mean group differences in psychological flow, psychological well-being, and self-management due to demographic variables (sex and years of practicing arts). The sample consists of (110) male and female fine artists. The descriptive correlational approach was performed to collect the data by using the psychological flow scale developed by Payne et al (2011), which was translated by the researcher, the Oxford happiness questionnaire developed by Hills and Argyle (2002), it has t