Biscuits are a global snack due to their convenience, variety, and durability. Biscuits with nutritious ingredients are in demand as customers become more health conscious. This change led to interest about utilizing agricultural by-products to enhance the nutritional value of widely consumed foods. Mango (Mangifera indica L.), a frequently cultivated tropical fruit, produces vital by-products during its processing, mainly comprising peels and kernels. The by-products, comprising around 35–60% of the mango fruit's weight, are high in bioactive compounds including dietary fiber, polyphenols, carotenoids, and essential fatty acids. Mango peels and kernels, even with their nutritional potential, frequently neglected, resulting in ris

Biscuits are a global snack due to their convenience, variety, and durability. Biscuits with nutritious ingredients are in demand as customers become more health conscious. This change led to interest about utilizing agricultural by-products to enhance the nutritional value of widely consumed foods. Mango (Mangifera indica L.), a frequently cultivated tropical fruit, produces vital by-products during its processing, mainly comprising peels and kernels. The by-products, comprising around 35–60% of the mango fruit's weight, are high in bioactive compounds including dietary fiber, polyphenols, carotenoids, and essential fatty acids. Mango peels and kernels, even with their nutritional potential, frequently neglected, resulting in ris

This study was performd on 50 serum specimens of patients with type 2 diabetes, in addition, 50 normal specimens were investigated as control group. The activity rate of LAP in patients (560.46 10.504) I.U/L and activity rate of LAP in healthy(10.58 4.39)I.U/L.The results of the study reveal that Leucine aminopeptidase (LAP) activity of type 2 diabetes patient s serum shows a high signifiacant increase (p < 0.001) compare to healthy subjects. Addition preparation leucine amide as substrate of LAP, identification melting point and spectra by FTIR. K

The improvement in Direction of Arrival (DOA) estimation when the received signals impinge on Active-Parasitic Antenna (APA) arrays will be studied in this work. An APA array consists of several active antennas; others are parasitic antennas. The responses to the received signals are measured at the loaded terminals of the active element. The terminals of the parasitic element are shorted. The effect of the received signals on the parasites, i.e., the induced short-circuit current, is mutually coupled to the active elements. Eigen decomposition of the covariance matrix of the measurements of the APA array generates a third subspace in addition to the traditional signal and noise subspaces generated by the all-active ante

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol