Diesel engine oil was subjected to thermal oxidization (TO) for six periods of time (0 h, 24 h, 48 h, 72 h, 96 h, and 120 h) and was subsequently characterized by terahertz time domain spectroscopy (THz-TDS). The THz refractive index generally increased with oxidation time. The measurement method illustrated the potential of THz-TDS when a fixed setup with a single cuvette is used. A future miniaturized setup installed in an engine would be an example of a fixed setup. For the refractive index, there were highly significant differences among the oxidation times across most of the 0.3–1.7 THz range.

Abstract:

                In light of the development in the banking environment and the increasing reliance on electronic systems in providing banking services and due to the intense competition witnessed by the banking sector, the need has emerged to apply the comprehensive electronic banking system, which works on the Internet in providing new and diverse banking services regardless of time and place by linking all branches to one central database, and despite the advantages achieved from the application of the comprehensive system, there is a set of risks that accompany the use of that system, What requires the auditors to develop the audit method in line with the size of the development in the

The recent advancements in security approaches have significantly increased the ability to identify and mitigate any type of threat or attack in any network infrastructure, such as a software-defined network (SDN), and protect the internet security architecture against a variety of threats or attacks. Machine learning (ML) and deep learning (DL) are among the most popular techniques for preventing distributed denial-of-service (DDoS) attacks on any kind of network. The objective of this systematic review is to identify, evaluate, and discuss new efforts on ML/DL-based DDoS attack detection strategies in SDN networks. To reach our objective, we conducted a systematic review in which we looked for publications that used ML/DL approach

Aerial Robot Arms (ARAs) enable aerial drones to interact and influence objects in various environments. Traditional ARA controllers need the availability of a high-precision model to avoid high control chattering. Furthermore, in practical applications of aerial object manipulation, the payloads that ARAs can handle vary, depending on the nature of the task. The high uncertainties due to modeling errors and an unknown payload are inversely proportional to the stability of ARAs. To address the issue of stability, a new adaptive robust controller, based on the Radial Basis Function (RBF) neural network, is proposed. A three-tier approach is also followed. Firstly, a detailed new model for the ARA is derived using the Lagrange–d’A

Upper limb amputation is a condition that severely limits the amputee’s movement. Patients who have lost the use of one or more of their upper extremities have difficulty performing activities of daily living. To help improve the control of upper limb prosthesis with pattern recognition, non-invasive approaches (EEG and EMG signals) is proposed in this paper and are integrated with machine learning techniques to recognize the upper-limb motions of subjects. EMG and EEG signals are combined, and five features are utilized to classify seven hand movements such as (wrist flexion (WF), outward part of the wrist (WE), hand open (HO), hand close (HC), pronation (PRO), supination (SUP), and rest (RST)). Experiments demonstrate that usin

Background: Inflammatory bowel disease (IBD) is a collection of chronic, recurrent inflammatory illnesses of the gastrointestinal system, including Crohn's disease (CD). Infliximab is one of the biological medications used to treat CD. Therapeutic drug monitoring has evolved as a treatment in IBD, aiming to optimize benefit while meeting more demanding, objective end criteria. Objective: To determine the achievement of target trough level (TL), develop anti-drug antibodies (ADAs) to infliximab, assess response to therapy, and study TL relations with different variables. Methods: The present study was cross-sectional and conducted from May 2022 to November 2022. It included 40 CD patients allotted into 2 groups: group 1 patients ach

Traumatic Brain Injury (TBI) is still considered a worldwide leading cause of mortality and morbidity. Within the last decades, different modalities were used to assess severity and outcome including Glasgow Coma Scale (GCS), imaging modalities, and even genetic polymorphism, however, determining the prognosis of TBI victims is still challenging requiring the emerging of more accurate and more applicable tools to surrogate other old modalities

The ability of the human brain to communicate with its environment has become a reality through the use of a Brain-Computer Interface (BCI)-based mechanism. Electroencephalography (EEG) has gained popularity as a non-invasive way of brain connection. Traditionally, the devices were used in clinical settings to detect various brain diseases. However, as technology advances, companies such as Emotiv and NeuroSky are developing low-cost, easily portable EEG-based consumer-grade devices that can be used in various application domains such as gaming, education. This article discusses the parts in which the EEG has been applied and how it has proven beneficial for those with severe motor disorders, rehabilitation, and as a form of communi