Self-driving automobiles are prominent in science and technology, which affect social and economic development. Deep learning (DL) is the most common area of study in artificial intelligence (AI). In recent years, deep learning-based solutions have been presented in the field of self-driving cars and have achieved outstanding results. Different studies investigated a variety of significant technologies for autonomous vehicles, including car navigation systems, path planning, environmental perception, as well as car control. End-to-end learning control directly converts sensory data into control commands in autonomous driving. This research aims to identify the most accurate pre-trained Deep Neural Network (DNN) for predicting the steerin

This case series aims to evaluate patients affected with post COVID‐19 mucormycosis from clinical presentation to surgical and pharmacological treatment to improve the disease prognosis.

Background: Preterm labor and related prematurity are predisposing factors that increase perinatal morbidity and mortality. Acute phase reactants are inflammatory markers which are positive and negative reactants explained by the reaction of reactants to the subclinical infection that are commonly associated with preterm labor.

Objectives: To assess the role of acute phase reactants in pregnant women with preterm delivery.

Patients and method: A case control study conducted in Gynecological Department of Baghdad Teaching Hospital from 1st February 2021 to 30th October 2021, on one hundred pregnant women with gestational age (28weeks - 36weeks+6days) who attended outpatient

Background: Preterm labor and related prematurity are predisposing factors that increase perinatal morbidity and mortality. Acute phase reactants are inflammatory markers which are positive and negative reactants explained by the reaction of reactants to the subclinical infection that are commonly associated with preterm labor. Objectives: To assess the role of acute phase reactants in pregnant women with preterm delivery. Patients and method: A case control study conducted in Gynecological Department of Baghdad Teaching Hospital from 1st February 2021 to 30th October 2021, on one hundred pregnant women with gestational age (28weeks - 36weeks+6days) who attended outpatient clinic; fifty pregnant women with established preterm labor

The other day in the Holy Quran and the four Gospels

A simple, fast, selective of a new flow injection analysis method coupled with potentiometric detection was used to determine vitamin B1 in pharmaceutical formulations via the prepared new selective membranes. Two electrodes were constructed for the determination of vitamin B1 based on the ion-pair vitamin B1-phosphotungestic acid (B1-PTA) in a poly (vinyl chloride) supported with a plasticized di-butyl phthalate (DBPH) and di-butyl phosphate (DBP). Applications of these ion selective electrodes for the determination of vitamin B1 in the pharmaceutical preparations for batch and flow injection systems were described. The ion selective membrane exhibited a near-Nernstian slope values 56.88 and 58.53 mV / decade, with the linear dy

This work is concerned with a two stages four beds adsorption chiller utilizing activated carbon-methanol adsorption pair that operates on six separated processes. The four beds that act as thermal compressors are powered by a low grade thermal energy in the form of hot water at a temperature range of 65 to 83 °C.  As well as, the water pumps and control cycle consume insignificant electrical power. This adsorption chiller consists of three water cycles. The first water cycle is the driven hot water cycle. The second cycle is the cold water cycle to cool the carbon, which adsorbs the methanol. Finally, the chilled water cycle that is used to overcome the building load. The theoretical results showed that average cycle cooling power

In this article, we propose a Bayesian Adaptive bridge regression for ordinal model. We developed a new hierarchical model for ordinal regression in the Bayesian adaptive bridge. We consider a fully Bayesian approach that yields a new algorithm with tractable full conditional posteriors. All of the results in real data and simulation application indicate that our method is effective and performs very good compared to other methods. We can also observe that the estimator parameters in our proposed method, compared with other methods, are very close to the true parameter values.