The First World War (1914-1918) was one of the most atrocious events in human history in which millions of people were killed and injured. Young men were widely recruited through a very strong persuasive propaganda, which portrayed the war as an opportunity for young men to defend their country and raise its banner high in the battlefields, prove their bravery and heroism, enjoy the adventure of action and taste the delight of battles. Military parades were usually held in the streets of towns where crowds, including young beautiful girls, stood along, hailing the new recruits who felt high pride in their uniform amidst the cheering applause of the happy audience. Newspapers and magazines used to publish so many stories of heroism about

In this paper, the Azzallini’s method used to find a weighted distribution derived from the standard Pareto distribution of type I (SPDTI) by inserting the shape parameter (θ) resulting from the above method to cover the period (0, 1] which was neglected by the standard distribution. Thus, the proposed distribution is a modification to the Pareto distribution of the first type, where the probability of the random variable lies within the period  The properties of the modified weighted Pareto distribution of the type I (MWPDTI) as the probability density function ,cumulative distribution function, Reliability function , Moment and  the hazard function are found. The behaviour of probability density function for MWPDTI distrib

In this paper, the path of the extracted and focused ions by the electrostatic lense having three electrodes of the same size and shape have been studied. However, the first and third electrodes had a different potential from the second electrode and the distance between any three electrodes was (d).The beams of the charged particles were controlled by using electrostatic fields which are used for accelerating and focusing. This paper focuses also on the effect of electrodes potentials on ion beam focusing. It is found that the best focusing was achieved when the values of the potential of the first and third electrode are equal to half of the value of the second electrode. Concerning transmiting and acumulating the ions beams, the study sh

In-vitro biological activities of the free new H4L ( indole-7-thiocarbohydrazone) ligand and its Ni(II), Pd(II) , Pt(II), Cu(II), Ag(I), Zn(II) and Cd(II) complexes are screened against two cancerous cell lines, that revealed significant activity only for [Cu2Cl2(H4L)2(PPh3)2] after 72 h treatment by the highest tested concentrations. The Copper(I) complex was characterized by X-ray Crystallography and the NMR spectra, whereas it has been confirmed to have momentous cytotoxicity against ovarian, breast cancerous cell lines (Caov-3, MCF-7). The apoptosis-inducing properties of the Cu(I) complex have been investigated through fluorescence microscopy visualization, DNA fragmentation analysis and propidium iodide flow cytometry.

We aimed to examine the potential protective effects of Iraqi H. tiliaceus L. chloroform leaves extract on DEN-induced HCC in male Wistar Albino rats.

Emotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In

Medicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep lea