Many studies of the relationship between COVID-19 and different factors have been conducted since the beginning of the corona pandemic. The relationship between COVID-19 and different biomarkers including ABO blood groups, D-dimer, Ferritin and CRP, was examined. Six hundred (600) patients, were included in this trial among them, 324 (56%) females and the rest 276 (46%) were males. The frequencies of blood types A, B, AB, and O were 25.33, 38.00, 31.33, and 5.33%, respectively, in the case group. Association analysis between the ABO blood group and D-dimer, Ferritin and CRP of COVID-19 patients indicated that there was a statistically significant difference for Ferritin (P≤0.01), but no-significant differences for both D-dimer and CRP.

Introduction Periodontal diseases are ranked among the most common health problems affecting mankind. These conditions are initiated by bacterial biofilm, which is further modulated by several risk factors. Objectives To investigate the association of different risk factors with periodontal...

    The Love Creek Nature Center, one of the three nature centers located within the boundaries of Berrien County, is owned and operated by the county for public enjoyment and instruction of nature. The 44.5 ha study area, located seven km east of Berrien Springs, and two km southwest of Berrien Center, on Huckleberry Road, in T6S, R17W, sections 16, 17 (Lat. 41° 56' N; Long. 86° 18' W) is made up of deciduous woods and abandoned fields at various stages of succession. It is bounded on the east by the Berrien County Dog Pound and Huckleberry Road, to the north by cultivated Berrien County land and the Berrien General Hospital, to the west by the recently closed Berrien - Oronoko Township Landfill Dump; and to the south b

There is a scarcity of data regarding algal flora of Tigris River in the territory of Baghdad. The present study deals with Tigris River in Al-Dora site in Baghdad province from November 2014 to June 2015 in order to shed light on its epiphytic Algae on (Phragmites australis) and epipelic algae. An amount of 183 and 154 species of epiphytic and epipelic algae are identified respectfully. The Bacillariophyceae (diatoms) are the dominant algal group followed by Cyanophyceae and Chlorophyceae. Moreover, 90 species are shared between two groups of algae (epiphytic and epipelic) and identified at the study site. Additionally, the seasonal variations and diversity of algal species are noticed. The highest number of epiphytic algae is 772.05 x 104

Background & objective: Difficult intubation remains a risk for patients undergoing general anesthesia (GA) or mechanical ventilation in an intensive care unit (ICU). Macroglossia is a known factor for difficult intubation. But it is not routine to assess the tongue size to predict difficult intubation. Studies are found deficient in comparing usefulness of measuring thyromental distance and the tongue thickness (TT) measured by ultrasonography to estimate difficult intubation. We compared tongue thickness measured by ultrasonography and thyromental distance as a means to anticipate difficult intubation. Methodology: A convenient sample of 60 patients; 32 males and 28 females, who were undergoing elective surgery with GA were i

This study presents a linguistic analysis of how Russian and American mainstream media and official statements deployed speech acts of accusation during the 2022 Russian invasion of Ukraine. Using Speech Act Theory (Austin, 1962; Searle, 1976) as the framework. The study analyzes 50 texts of English-language official statements and media headlines from both sides. In this research utterances are categorized into assertives, expressives, directives, commissives, and declarations, and analyzes their pragmatic force in shaping narratives. The analysis reveals contrasts in tone and rhetorical strategy: U.S. officials and media overwhelmingly use assertive accusations and expressive condemnations to morally indict Russia, while Russian counterpa

Wireless sensor networks (WSNs) represent one of the key technologies in internet of things (IoTs) networks. Since WSNs have finite energy sources, there is ongoing research work to develop new strategies for minimizing power consumption or enhancing traditional techniques. In this paper, a novel Gaussian mixture models (GMMs) algorithm is proposed for mobile wireless sensor networks (MWSNs) for energy saving. Performance evaluation of the clustering process with the GMM algorithm shows a remarkable energy saving in the network of up to 92%. In addition, a comparison with another clustering strategy that uses the K-means algorithm has been made, and the developed method has outperformed K-means with superior performance, saving ener