The enhancement of the thermal and thermo-hydraulic performance of a semi-circular solar air collector (SCSAC) is numerically investigated using porous semi-circular obstacles made of metal foam with and without longitudinal porous Y-shaped fins. Two 10 and 40 PPI porous material samples are examined. Three-dimensional models are built to simulate the performance of SCSAC: model (I) with clear air passage; model (II) with only metal foam obstacles, and model (III) with metal foam obstacles as well as porous Y-fins. COMSOL Multiphysics software version 6.2 based on finite element methodology is employed. A conjugate heat transfer with a (k-ε) turbulence model is selected to simulate both heat transfer and fluid flow across the entir

oday deep ocean life has not been discovered by humans including many secret world things to be explored. The researcher has focused on underwater optical wireless communications using various kinds of complex digital Signal processing most of them used in air and starting applied in underwater communication. The Internet of Things (IoT) uses underwater called Internet of Underwater Things (IoUT) applications to explore the underwater world with other devices. However, the difference in concentration between air and water surfaces is not easy making wireless communication more complicated. Visible light passes the water's surface with scattering and distortion inside the water and each color of light has different attenuation the blue laser

In this paper we proposed the method of X-ray fluorescence (XRF) determination of some essential trace elements in medicinal herbs and vitamin-mineral complexes at the level of 10⁰-10¹ mg/ml. To increase sensitivity and selectivity of the determination we simple and effective approach based on the extraction of metal ions from aqueous solutions with chemically modified polyurethane foam sorbents followed by direct XRF analysis. The conditions of sorption preconcentration of Co(II), Ni(II) and Zn(II) ions with modified sorbents were optimized. The proposed approach is used for the determination of trace elements in several kinds of medicinal herbs (coltsfoot leaves, nettle leaves and yarrow herb) and vitamin-mineral

An environmentally begnin second derivative spectrometric approach was developed for the estimation of the dissociation constants pKa(s) of metformin, a common anti-diabetic drug.  The ultraviolet spectra of the aqueous solution of metformin were measured at different acidities, then the second derivative of each spectrum was graphed. The overlaid second derivative graphs exhibited two isobestic points at 225.5 nm and 244 nm pointing out to the presence of two dissociation constants for metformin pKa1 and pKa2, respectively. The method was validated by evaluating the reproducibility of the acquired results by comparing the estimated values of the dissociation constants of two different strategies that show excellent matching. As we

The use of real-time machine learning to optimize passport control procedures at airports can greatly improve both the efficiency and security of the processes. To automate and optimize these procedures, AI algorithms such as character recognition, facial recognition, predictive algorithms and automatic data processing can be implemented. The proposed method is to use the R-CNN object detection model to detect passport objects in real-time images collected by passport control cameras. This paper describes the step-by-step process of the proposed approach, which includes pre-processing, training and testing the R-CNN model, integrating it into the passport control system, and evaluating its accuracy and speed for efficient passenger flow

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

Bacteriocin is an important antimicrobial peptide that can be used in industrial and medical fields due to its characteristics of antibacterial, food preservation and anticancer activities. Fifty isolates of Bacillus sp were collected from different soil samples which were already recognized via morphological and biochemical identification process. The isolates were screened for bacteriocin production effective against Staphylococcus spp in order to select the highest producing isolate. The isolate NK16 showed the maximum bacteriocin production (80 AU/ml) which was further characterized as Bacillus subtilis NK 16 through using API identification system (API 20E and API 50CHB). Then, next step was to detect the optimal conditions for maximum