Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

Background: Diabetes mellitus is one of the commonest chronic disorders worldwide with a rapid rise in prevalence. In Iraq its prevalence is high especially in elderly age group. Patients with type 2 diabetes mellitus have higher vulnerability for complications, whether microvascular or macrovascular. Ocular complications are common in diabetes mellitus, and comprise diabetic retinopathy, diabetic papillopathy, cataract, glaucoma, dry eye disease and diabetic keratopathy. Diabetic keratopathy involves endothelial and epithelial tissues of the cornea, leading to persistent epithelial defect, corneal erosion, or corneal ulcers.

Aim of the Study: To compare the mean corneal endothelial cell count between patients wi

Diarrhea is one of the most commonly encountered minor ailments in the community pharmacies. It is associated with significant morbidity and mortality. However, the majority of pharmacists in Iraq did not manage diarrheal cases in a proper way. Therefore, the current study aimed to evaluate the benefit of a new mobile application (diarrhea management step by step) to improve the pharmacist's role in the management of diarrhea. The study was conducted from 21th September to 21th October 2021 using a pre-post design via a simulated patient (SP) technique. A validated diarrhea scenario was presented to each pharmacist by the SP twice, once before and the other after giving the mobile application to the pharmacist. Furthermore, pharmaci

Recently, Qatar, a well-known oil production country, has been convinced as a successful case in attracting foreign direct investment (FDI) as a smaller economy. This paper aims to investigate how FDI inflows affect Qatar’s business cycles. Time series data was selected from 1990 to 2010 as available. The VAR Impulse Responses and the Granger Causality test were mainly employed by using Eviews. The derived result shows that the FDI inflows and the economic growth in Qatar interact with each other in a relatively long term.

Recognizing speech emotions is an important subject in pattern recognition. This work is about studying the effect of extracting the minimum possible number of features on the speech emotion recognition (SER) system. In this paper, three experiments performed to reach the best way that gives good accuracy. The first one extracting only three features: zero crossing rate (ZCR), mean, and standard deviation (SD) from emotional speech samples, the second one extracting only the first 12 Mel frequency cepstral coefficient (MFCC) features, and the last experiment applying feature fusion between the mentioned features. In all experiments, the features are classified using five types of classification techniques, which are the Random Forest (RF),

Pseudoephedrine (PSE) or (Sudafed) is one of the sympathomimetic group of drugs (ephedrine, PSE and amphetamines) which effects cardiovascular system, respiratory system, and gastrointestinal tract. However, only little researches had supported its effect on solid abdominal organs. This study aims to investigate the effects of different doses of Sudafed in the liver and kidney of albino mice. The current study included 18 albino mice grouped into 2 groups: control (3 mice), and acute group (15 mice). The acute group was further subdivided into 5 subgroups, each subgroup of 3mice wasgiven a lonely intaperitonial injection of 0.3ml of the following conc. (500mg/kg, 250mg/kg, 125mg/kg, 62.52mg/kg, and 31.24mg/kg) for 24hrs. After the m

Cultivation of the green seaweed Enteromorpha compressa was performed under natural laboratory spring environmental conditions of temperature, light intensity and photoperiod to study the salinity tolerance of this intertidal green macroalga. Cultivation was carried out under artificial seawater (ASW) of different concentrations (18, 35, 53 and 106 g/l sea salt) compared to the control using natural seawater (NSW). Growth rate and pigment content of the cultivated alga were recorded at regular intervals during the experimental duration. Antioxidant activity of the crude ethanolic extract and its fractions (petroleum ether, chloroform, ethyl acetate and acetone) was performed against DPPH radical scavenging assay and compared to

Endophytic bacteria produced analogous secondary metabolites of their hosts. Similarly, the ability to generate antioxidants is not an exception. Dragon scales (Pyrrosia piloselloides), an epiphytic plant of the Polypodiaceae family, are frequently overlooked. This research aims to isolate antioxidant-producing bacteria from dragon-scale fern leaves. The antioxidant activities were tested after the extraction procedure using ethanolic extract. Bacteria were characterized and selected as candidates for antioxidant production by screening for the production of total phenolic compounds. Antioxidant levels were determined utilizing the ABTS, FRAP, and DPPH techniques. The preliminary findings of the entire phenolic compound test rev

Levan is an exopolysaccharide produced by various microorganisms and has a variety of applications. In this research, the aim was to demonstrate the biological activity of levan which produced from B. phenoliresistens KX139300. These were done via study the antioxidant, anti-inflammatory, anticancer and antileishmanial activities in vitro. The antioxidant levan was shown 80.9% activity at 1250 µg/mL concentration. The efficient anti-inflammatory activity of 88% protein inhibition was noticed with levan concentration at 35 µg/mL. The cytotoxic activity of levan at 2500 µg/mL concentration showed a maximum cytotoxic effect on L20B cell line and promastigotes of Leishmani tropica. Levan has dose-dependent anticancer and antileishman

A first step in this research was to synthesize Schiff's bases(1-3)using an Amoxcilline intensification reaction with different aromatic aldehydes in absolute ethanol. In benzene and refluxing conditions,Schiff's bases were cyclized with succinic and Phthalic anhydride to give a new sequence of 1,3-oxazepine derivatives(4-6) and (7-9),respectively.The last step,cyclization reactions with sodium azide in THF solvent resulted in the formation of [10 and 11], which are supposed to be biologically significant.FT.IR, 1H-NMR and 13C-NMR (for compound 4,7,9, and 11),as well as melting points reported, were used to characterize these prepared compounds ,Bacillus (G+), Staphylococcus (G+), and E.Coli (G-)were screened against these compounds. . To i