Hands have consistently been an important vehicle in the transmission of disease (1). Thus, thorough hand-washing remains the single most important factor in preventing infection specially in hospitals and labs.Twenty-nine non-clinical volunteers (do not work or come in contact with a clinical or hospital setting) that lacked visible skin injuries, eczema or apparent skin disease were used, those subjects were all tested by a material of each of the three used in the study weekly and laboratory tests were done pre- and post washing.All three material were effective , Eugenol extract as effective as the bar and lotion soap. And this was confirmed statistically.Eugenol has a great antibacterial action even in small concentration and t

Surrealism is a twentieth-century literary and artistic movement oriented toward the liberation of the mind. Surrealism is a reaction to the philosophy of rationalism which was believed to be the cause of the disaster of World War I. It emphasizes the expression of the imagination as revealed in dreams and presented without conscious control, the unexpected juxtapositions of objects, the withdrawal of the self, and the exploitation of chance effects.
Surrealism began in Paris in the early 1920s, as Europe emerged from the devastation of World War I. A group of writers, artists, and filmmakers, led by the poet André Breton, adopted the word surréaliste (meaning, roughly, "super-real") as a label for their artistic activities. Influen

Nowadays, Wheeled Mobile Robots (WMRs) have found many applications as industry, transportation, inspection, and other fields. Therefore, the trajectory tracking control of the nonholonomic wheeled mobile robots have an important problem. This work focus on the application of model-based on Fractional Order  PI^aD^b (FOPID) controller for trajectory tracking problem. The control algorithm based on the errors in postures of mobile robot which feed to FOPID controller to generate correction signals that transport to  torque for each driven wheel, and by means of dynamics model of mobile robot these torques used to compute the linear and angular speed to reach the desired pose. In this work a dynamics model of

Mobile-based human emotion recognition is very challenging subject, most of the approaches suggested and built in this field utilized various contexts that can be derived from the external sensors and the smartphone, but these approaches suffer from different obstacles and challenges. The proposed system integrated human speech signal and heart rate, in one system, to leverage the accuracy of the human emotion recognition. The proposed system is designed to recognize four human emotions; angry, happy, sad and normal. In this system, the smartphone is used to   record user speech and send it to a server. The smartwatch, fixed on user wrist, is used to measure user heart rate while the user is speaking and send it, via Bluetooth,

The factors influencing the financial market are rapidly becoming more complex. The impact of non-financial factors on the performance of a company’s common stock can increase in ways that were not previously expected. This study investigated how brand capital affects the risk of stock prices in Iraqi private banks listed on the Iraq Stock Exchange failing by identifying the likelihood of a crash caused by a negative deviation in the distribution of returns on ordinary shares. As a result, the current study’s concept is to review an analytical knowledge framework of the nature of that relationship, its changes, and its impact on the pricing of ordinary shares of the banks of the researched sector for the years 2009 to 2017, as w

AHA Al-Hilali, AAH Hamid, The Journal of Law Research, 2022

In high-dimensional semiparametric regression, balancing accuracy and interpretability often requires combining dimension reduction with variable selection. This study intro- duces two novel methods for dimension reduction in additive partial linear models: (i) minimum average variance estimation (MAVE) combined with the adaptive least abso- lute shrinkage and selection operator (MAVE-ALASSO) and (ii) MAVE with smoothly clipped absolute deviation (MAVE-SCAD). These methods leverage the flexibility of MAVE for sufficient dimension reduction while incorporating adaptive penalties to en- sure sparse and interpretable models. The performance of both methods is evaluated through simulations using the mean squared error and variable selection cri

Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D