Understanding energy metabolism and intracellular energy transmission requires knowledge of the function and structure of the mitochondria. Issues with mitochondrial morphology, structure, and function are the most prevalent symptoms. They can damage organs such as the heart, brain, and muscle due to a variety of factors, such as oxidative damage, incorrect metabolism of energy, or genetic conditions. The control of cell metabolism and physiology depends on functional connections between mitochondrial and biological surroundings. Therefore, it is essential to research mitochondria in situ or in vivo without isolating them from their surrounding biological environment. Finding and spotting abnormal alterations in mitochondria is the

Detection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with

The concept of education is not actually restricted to children or school students, but rather  every person   should be educated and followed up if he  is intended to grow and prove, with effort and time allocation  as to fulfill that goal.  Thus , the current paper aims to a thinking education and to educate that thinking in teacher  and it is not new to deal with the personal characteristics of teacher  in the different  scientific , and educational researches . But ,these research did not address the necessity of acquiring the skill of thinking, especially as it affects teacher's presentation of the content of the curriculum or even content outside the curriculum, and therefore, there is n

Micro-perforated panel (MPP) absorber is increasingly gaining popularity as an alternative sound absorber in buildings compared to the well-known synthetic porous materials. A single MPP has a typical feature of a Helmholtz resonator with a high amplitude of absorption but a narrow absorption frequency bandwidth. To improve the bandwidth, a single MPP can be cascaded with another single MPP to form a double-layer MPP. This paper proposes the introduction of inhomogeneous perforation in the double-layer MPP system (DL-iMPP) to enhance the absorption bandwidth of a double-layer MPP. Mathematical models are proposed using the equivalent electrical circuit model and are validated with experiments with good agreement. It is revealed that the DL-

Increasing hydrocarbon recovery from tight reservoirs is an essential goal of oil industry in the recent years. Building real dynamic simulation models and selecting and designing suitable development strategies for such reservoirs need basically to construct accurate structural static model construction. The uncertainties in building 3-D reservoir models are a real challenge for such micro to nano pore scale structure. Based on data from 24 wells distributed throughout the Sadi tight formation. An application of building a 3-D static model for a tight limestone oil reservoir in Iraq is presented in this study. The most common uncertainties confronted while building the model were illustrated. Such as accurate estimations of cut-off permeab