Results: it was found that labelled cells participated in the formation of myotubes, which formed mature muscle fibers, and possibly new satellite cells. The results of this experiment may eventually revolutionized therapeutic procedures for some form of muscle diseases

Background: Complete denture wearers show lower levels of bite force than dentate subjects. This has a significant influence on their chewing efficiency. In this study an attempt was made to investigate the effect of the impression technique on the maximum bite force in complete denture wearers. Materials and methods: The patients selected for this research were 12 edentulous patients. Three different techniques for registering the final impression were made; the mucostatic, mucofunctional, and the selective pressure impression technique. Two sets of upper and lower denture bases and one set of upper and lower dentures were constructed for each subject. Intraoral and extraoral instruments and devices, as well as a computer program were used

In this work, thermodynamic efficiency of individual cell and stack of cells (two cells) has been computed by studying the variation of voltage produced during an operation time of 30 min as a result of the affected parameters:- stoichiometric feed ratio, flow field design on single cell and feed distribution on stack of cells. The experiments were carried out by using two cells, one with serpentine flow field and the other with spiral flow field. These cells were fed with hydrogen and oxygen at low volumetric flow rates from 1 to 2 ml/sec and stoichiometric ratios of fuel (H₂) to oxidant (O₂) as 1:2, 1:1 and 2:1 respectively. The results showed that

A study that collected 240 samples and divided into two groups: the first 120 samples were for diabetics and the second 120 samples were for healthy people, and each group included (90, 20.10) samples from the mouth, urine and vagina respectively, The results showed positive (28.67, 4.00, 1.67) isolates of Candida. In the mouth, urine and vagina, respectively, of diabetic patients compared to (9.33, 2.33, 5.00) positive isolates in the mouth, urine and vagina, respectively, in the healthy. The rate of positive isolates in women was high in women with diabetes and healthy, and it reached 25.33 and 9.00 isolates, respectively, compared with the rate of isolates in men with Candida disease for diabetic patients and healthy people 14.67 and 2.0

To obtain the approximate solution to Riccati matrix differential equations, a new variational iteration approach was ‎proposed, which is suggested to improve the accuracy and increase the convergence rate of the approximate solutons to the ‎exact solution. This technique was found to give very accurate results in a few number of iterations. In this paper, the ‎modified approaches were derived to give modified solutions of proposed and used and the convergence analysis to the exact ‎solution of the derived sequence of approximate solutions is also stated and proved. Two examples were also solved, which ‎shows the reliability and applicability of the proposed approach. ‎

Text based-image clustering (TBIC) is an insufficient approach for clustering related web images. It is a challenging task to abstract the visual features of images with the support of textual information in a database. In content-based image clustering (CBIC), image data are clustered on the foundation of specific features like texture, colors, boundaries, shapes. In this paper, an effective CBIC) technique is presented, which uses texture and statistical features of the images. The statistical features or moments of colors (mean, skewness, standard deviation, kurtosis, and variance) are extracted from the images. These features are collected in a one dimension array, and then genetic algorithm (GA) is applied for image clustering.

conventional FCM algorithm does not fully utilize the spatial information in the image. In this research, we use a FCM algorithm that incorporates spatial information into the membership function for clustering. The spatial function is the summation of the membership functions in the neighborhood of each pixel under consideration. The advantages of the method are that it is less
sensitive to noise than other techniques, and it yields regions more homogeneous than those of other methods. This technique is a powerful method for noisy image segmentation. 

The increased size of grayscale images or upscale plays a central role in various fields such as medicine, satellite imagery, and photography. This paper presents a technique for improving upscaling gray images using a new mixing wavelet generation by tensor product. The proposed technique employs a multi-resolution analysis provided by a new mixing wavelet transform algorithm to decompose the input image into different frequency components. After processing, the low-resolution input image is effectively transformed into a higher-resolution representation by adding a zeroes matrix. Discrete wavelets transform (Daubechies wavelet Haar) as a 2D matrix is used but is mixed using tensor product with another wavelet matrix’s size. MATLAB R2021

Abstract

 The objective of image fusion is to merge multiple sources of images together in such a way that the final representation contains higher amount of useful information than any input one.. In this paper, a weighted average fusion method is proposed. It depends on using weights that are extracted from source images using counterlet transform. The extraction method is done by making the approximated transformed coefficients equal to zero, then taking the inverse counterlet transform to get the details of the images to be fused. The performance of the proposed algorithm has been verified on several grey scale and color test  images, and compared with some present methods.

 An oil spill is a leakage of pipelines, vessels, oil rigs, or tankers that leads to the release of petroleum products into the marine environment or on land that happened naturally or due to human action, which resulted in severe damages and financial loss. Satellite imagery is one of the powerful tools currently utilized for capturing and getting vital information from the Earth's surface. But the complexity and the vast amount of data make it challenging and time-consuming for humans to process. However, with the advancement of deep learning techniques, the processes are now computerized for finding vital information using real-time satellite images. This paper applied three deep-learning algorithms for satellite image classification