Both traditional and novel techniques were employed in this work for magnetic shielding evaluation to shed new light on the magnetic and aromaticity properties of benzene and 12 [n]paracyclophanes with n = 3–14. Density functional theory (DFT) with the B3LYP functional and all-electron Jorge-ATZP and x2c-TZVPPall-s basis sets was utilized for geometry optimization and magnetic shielding calculations, respectively. Additionally, the 6-311+G(d,p) basis set was incorporated for the purpose of comparing the magnetic shielding results. In addition to traditional evaluations such as NICS/NICSzz-Scan, and 2D-3D σiso(r)/σzz(r) maps, two new techniques were implemented: bendable grids (BGs) and cylindrical grids (CGs) of ghost atoms (Bqs). BGs allow for the recording of magnetic shielding from the bent ring levels of [n]pCPs, while CGs provide tubular magnetic shielding scan (TMSS) maps detailing the magnetic shielding from a cylindrical region above and below the ring frame. Our findings suggest that smaller [n]pCPs with n < 6 exhibit deviations in the magnetic shielding above and below the ring, indicating a broken electron delocalization under the ring. In contrast, larger [n]pCPs tend to behave similarly to benzene in terms of magnetic shielding. Moreover, we found that shorter polymethylene chains of [n]pCPs exhibit significantly higher magnetic shielding interactions with the ring. Both of the above techniques offer new and promising tools for characterizing nonplanar aromatic compounds, thereby contributing to a deeper understanding of their magnetic and electronic properties.
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
... Show MoreImage 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
... Show MoreCoronary artery disease (CAD) is the leading cause of death worldwide. Certain genetic polymorphisms play an important role in this multifactorial disease, being linked with increased risk of early onset CAD.
To assess six genetic polymorphisms and clinical risk factors in relation to early onset nondiabetic Iraqi Arab CAD patients compared to controls.
This case–contro
The prostaglandins inside inflamed tissues are produced by cyclooxygenase-2 (COX-2), making it an important target for improving anti-inflammatory medications over a long period. Adverse effects have been related to the traditional usage of non-steroidal anti-inflammatory drugs (NSAIDs) for the treatment of inflammation, mainly centered around gastrointestinal (GI) complications. The current research involves the creation of a virtual library of innovative molecules showing similar drug properties via a structure-based drug design. A library that includes five novel derivatives of Diclofenac was designed. Subsequently, molecular docking through the Glide module and determining the binding free energy implementing the P
... Show MoreElectronic banking services appeared as a result of laying the foundations for the application of electronic automation in the banking field, and despite the clear expansion in its adoption and implementation as an inevitable necessity imposed by international and national developments, its application was not ideal according to the level that was expected to occur after the abandonment of traditional banking services, which produced some risks Which is evident in the absence of a legal system, whether at the level of proving and authoritative electronic banking services such as electronic signature, Or at the level of protecting the confidentiality of these services and ensuring that they are not exp
... Show MoreThis study employs evolutionary optimization and Artificial Intelligence algorithms to determine an individual’s age using a single-faced image as the basis for the identification process. Additionally, we used the WIKI dataset, widely considered the most comprehensive collection of facial images to date, including descriptions of age and gender attributes. However, estimating age from facial images is a recent topic of study, even though much research has been undertaken on establishing chronological age from facial photographs. Retrained artificial neural networks are used for classification after applying reprocessing and optimization techniques to achieve this goal. It is possible that the difficulty of determining age could be reduce
... Show MoreThe advancements in Information and Communication Technology (ICT), within the previous decades, has significantly changed people’s transmit or store their information over the Internet or networks. So, one of the main challenges is to keep these information safe against attacks. Many researchers and institutions realized the importance and benefits of cryptography in achieving the efficiency and effectiveness of various aspects of secure communication.This work adopts a novel technique for secure data cryptosystem based on chaos theory. The proposed algorithm generate 2-Dimensional key matrix having the same dimensions of the original image that includes random numbers obtained from the 1-Dimensional logistic chaotic map for given con
... Show MoreThe virtual decomposition control (VDC) is an efficient tool suitable to deal with the full-dynamics-based control problem of complex robots. However, the regressor-based adaptive control used by VDC to control every subsystem and to estimate the unknown parameters demands specific knowledge about the system physics. Therefore, in this paper, we focus on reorganizing the equation of the VDC for a serial chain manipulator using the adaptive function approximation technique (FAT) without needing specific system physics. The dynamic matrices of the dynamic equation of every subsystem (e.g. link and joint) are approximated by orthogonal functions due to the minimum approximation errors produced. The contr