New azo ligand 2-((4-formyl-3-hydroxynaphthalen-2-yl) diazenyl) benzoic acid (H2L) was synthesized from the reaction of 2-aminobenzoic acid and2-hydroxy-1-naphthaldehyde. Monomeric complexes of this ligand, of general formulae [MII(L)(H2O)] with (MII = Mn, Co, Ni, Cu, Zn, Pd, Cd and Hg ) were reported. The compounds were isolated and characterized in solid state by using 1H-NMR, FT-IR, UV–Vis and mass spectral studies, elemental microanalysis, metal content, magnetic moment measurements, molar conductance and chloride containing. These studies revealed tetrahedral geometries for all complexes except PdII complex is Square planar. The study of complexes formation via molar ratio of (M:L) as (1:1). Theoretical treatments of compounds in gas

A simple, rapid and sensitive spectrophotometric method has been proposed for the determination of La (III) using 3-hydroxy -4-(2-hydroxy-phenyl azo) naphthalene -1- sulfonic acid as a chromogenic reagent. This method is based on the formation of a red-pink colored complex, upon the reaction of La(III) with the reagent in an alkaline medium (pH= 9.50), having a maximum absorbance at 459 nm. Beer's law is valid in the concentration range 0.512 µg.ml-1 with a Sandell's sensitivity value of 0.0188 µg.cm-2 and molar absorptivity of 7376.12 L.mol-1.cm-1. The stoichiometric composition of the chelate is 1:3. The effect of the presence of different cations as interferants in the determination of La(III) under the given optimum conditions wer

Coronavirus 2019 (COVID-19) pandemic led to a massive global socio-economic tragedy that has impacted the ecosystem. This paper aims to contextualize urban and rural environmental situations during the COVID-19 pandemic in the Middle East and North Africa (MENA) Region.

Machine Learning (ML) algorithms are increasingly being utilized in the medical field to manage and diagnose diseases, leading to improved patient treatment and disease management. Several recent studies have found that Covid-19 patients have a higher incidence of blood clots, and understanding the pathological pathways that lead to blood clot formation (thrombogenesis) is critical. Current methods of reporting thrombogenesis-related fluid dynamic metrics for patient-specific anatomies are based on computational fluid dynamics (CFD) analysis, which can take weeks to months for a single patient. In this paper, we propose a ML-based method for rapid thrombogenesis prediction in the carotid artery of Covid-19 patients. Our proposed system aims

Worldwide, there is an increased reliance on COVID-19-related health messages to curb the COVID-19 outbreak. Therefore, it is vital to provide a well-prepared and authentic translation of English-language messages to reach culturally and linguistically diverse audiences. However, few studies, if any, focus on how non-English-speaking readers receive and linguistically accept the lexical choices in the messages translated into their language. The present study tested a sample of translated Arabic COVID-19-related texts that were obtained from the World Health Organization and Australian New South Wales Health websites. This study investigated to that extent Arabic readers would receive translated COVID-19 health messages and whether the t

Objective: The study the association of procalcitonin (PCT) and c-reactive protein (CRP) levels in COVID-19 patients and it's role as a guide in progress and management of those patients. Methodology: This cross-sectional study analyzed 200 CIOVID-19 patients in a single privet center in Baghdad, Iraq from January 1, 2021 to January 1, 2022. Demographic data like age, sex, and clinical symptoms were recorded. High sensitivity CRP and PCT in the serum were measured via dry fluorescence immunoassay (Lansionbio-China). Results: Out of 200 patients, 50 had moderate Covid and 150 had severe disease. Mean serum PCT levels was 0.039±0.05 ng/mL in the moderate group (range 0.011-0.067) and 0.43±0.21 ng/mL in the severe group (range 0.21

The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system

Background: The COVID-19 infection is a more recent pandemic disease all over the world and studying the pulmonary findings on survivors of this disease has lately commenced.

Objective: We aimed to estimate the cumulative percentage of whole radiological resolution after 3 months from recovery and to define the residual chest CT findings and exploring the relevant affecting factors.

Subjects and Methods: Patients who had been previously diagnosed with COVID-19 pneumonia confirmed by RT-PCR test and had radiological evidence of pulmonary involvement by Chest CT during the acute illness were included in the present study. The radiol

Background: There are many congenital anomalies associated with cleft lip and/or palate. This research is to study the prevalence of congenitally missing teeth and supernumerary teeth in this population group. Materials and Method: One hundred eight cleft lip and/or palate Iraqi patients had participated in this study (57 male, 51 female), 3-12 years of age. 26 of them had orthopantomogram were within (6-12) years of age were inspected for congenitally missing teeth and supernumerary teeth. Patients whom age range 3-5 years were checked for the congenitally missing teeth by clinical examination with strongly insisting the teeth were not missed due to caries or trauma. Results: There were 19(73.076%) patients with 41 congenitally missing tee