Dandruff and seborrheic dermatitis (SD) are common skin disorders affecting the scalp and extending to other body sites in the case of SD. They are associated with pruritus and scaling, causing an esthetical disturbance in the population affected.   Treatment of such conditions involves using a variety of drugs for long terms, thus optimizing drug formulation is essential to improve therapeutic efficacy and patient compliance. Conventional topical formulations like shampoos and creams have been widely used but their use is associated with disadvantages. To overcome such effects, novel topical nanotechnology-based formulations are currently under investigation. In the following article, we highlight recently published formulatio

The control of prostheses and their complexities is one of the greatest challenges limiting wide amputees’ use of upper limb prostheses. The main challenges include the difficulty of extracting signals for controlling the prostheses, limited number of degrees of freedom (DoF), and cost-prohibitive for complex controlling systems. In this study, a real-time hybrid control system, based on electromyography (EMG) and voice commands (VC) is designed to render the prosthesis more dexterous with the ability to accomplish amputee’s daily activities proficiently. The voice and EMG systems were combined in three proposed hybrid strategies, each strategy had different number of movements depending on the combination protocol between voic

One of the most significant challenges of medical care is the infection of postoperative wounds, and conventional visual examination often fails to detect it early. This research proposes the design of an innovative, passive wireless telemetry system for non-intrusive monitoring of the wound-healing process.  The system integrates a biocompatible resonance circuit (LC) with a high-sensitivity piezoresistive sensor based on MXene (Ti3C2Tx). It operates within the standard industrial and medical (ISM) band at 13.56 MHz.The detection mechanism in the system is based on the principle of "impedance modulation" (Impedance Modulation), which arises from changes in the sensor's resistance under physiological tissue pressure. The system was

The support vector machine, also known as SVM, is a type of supervised learning model that can be used for classification or regression depending on the datasets. SVM is used to classify data points by determining the best hyperplane between two or more groups. Working with enormous datasets, on the other hand, might result in a variety of issues, including inefficient accuracy and time-consuming. SVM was updated in this research by applying some non-linear kernel transformations, which are: linear, polynomial, radial basis, and multi-layer kernels. The non-linear SVM classification model was illustrated and summarized in an algorithm using kernel tricks. The proposed method was examined using three simulation datasets with different sample

Background: With the start of the current century, increased the interest in the role of the adipose tissue derived substances that named adipokines in the inflammatory diseases of the human being including the inflammatory periodontal disease, but scientific evidences were not clearly demonstrate the association between these adipokines and periodontal pathologies. Materials and Methods: Forty two subjects male only with normal body mass index were selected for the study with an age ranged (30-39 years). Samples were divided into three groups of 14 subjects in each group based on clinical periodontal parameters; clinically healthy gingiva (group I), gingivitis group (group II) and chronic periodontitis patients group (group III), from whom

Excessive skewness which occurs sometimes in the data is represented as an obstacle against normal distribution. So, recent studies have witnessed activity in studying the skew-normal distribution (SND) that matches the skewness data which is regarded as a special case of the normal distribution with additional skewness parameter (α), which gives more flexibility to the normal distribution. When estimating the parameters of (SND), we face the problem of the non-linear equation and by using the method of Maximum Likelihood estimation (ML) their solutions will be inaccurate and unreliable. To solve this problem, two methods can be used that are: the genetic algorithm (GA) and the iterative reweighting algorithm (IR) based on the M

In this paper, a mathematical model consisting of a prey-predator system incorporating infectious disease in the prey has been proposed and analyzed. It is assumed that the predator preys upon the nonrefugees prey only according to the modified Holling type-II functional response. There is a harvesting process from the predator. The existence and uniqueness of the solution in addition to their bounded are discussed. The stability analysis of the model around all possible equilibrium points is investigated. The persistence conditions of the system are established. Local bifurcation analysis in view of the Sotomayor theorem is carried out. Numerical simulation has been applied to investigate the global dynamics and specify the effect