By March 2020, a pandemic had been emerged Corona Virus Infection in 2019 (COVID-19), which was triggered through the sensitive pulmonary syndrome (SARS disease corona virus- 2 (SARS COV-2). Overall precise path physiology of SARS COV-2 still unknown, as does the involvement of every element of the acute or adaptable immunity systems. Additionally, evidence from additional corona virus groups, including SARS COV as well as the Middle East pulmonary disease, besides that, fresh discoveries might help researchers fully comprehend SARS CoV-2. Toll-like receptors (TLRs) serve a critical part in both detection of viral particles as well as the stimulation of the body's immune response. When TLR systems are activated, pro-inflammatory cy

     This paper attempts to develop statistical modeling for air-conditioning analysis in Jakarta, Indonesia, during an emergency state of community activity restrictions enforcement (Emergency CARE), using a variety of parameters such as PM₁₀, PM_2.5, SO₂, CO, O₃, and NO₂ from five IoT-based air monitoring systems. The parameters mentioned above are critical for assessing the air quality conditions and concentration of air pollutants.  Outdoor air pollution concentration variations before and after the Emergency CARE, which was held in Indonesia during the COVID-19 pandemic on July 3-21, 2021, were studied. An air quality monitoring system based on the IoT generates sensor data

     By the time we conducted the current study,- COVID-19 epidemic has already become a global challenge, paralyzing socio-economic activity dramatically.

 Hence   , this study aimed to identify the most valuable prognostic indicators for COVID19 patients' early and accurate diagnosis by comparing laboratory biomarkers like C -reactive protein between non-severe and severe groups of patients. Depending on clinical symptoms, ---337 COVID-19 patients were enrolled at the Basra City Hospital from March 29 to April 29,2020   were classified into severe and non severe groups.

        A total of 337 patients were diagnosed with C

Cervical Uterine Cancer is a disease that explains the vulnerability in which women are in terms of reproductive health with an impact on occupational health and public health, even when in Mexico the prevalence rate is lower than the other member countries of the OECD, its impact on Human Development and Local Development shows the importance that the disease have in communities more than in cities where prevention policies through check-ups and medical examinations seem to curb the trend, but show the lack of opportunities and capacities of health centers in rural areas.   To establish the reliability, validity, and correlations between the variables reported in the literature with respect to their weighting in a public hospital. A

The most common cause of upper respiratory tract infection is coronavirus, which has a crown appearance due to the existence of spikes on its envelope. D-dimer levels in the plasma have been considered a prognostic factor for COVID-19 patients.

      The aim of the present study is to compare the biochemical action of the three vaccines taken in Iraq: Pfizer Biontech, AstraZeneca Oxford and Sinopharm based on biochemical parameters. Seventy COVID-19 Iraqi patients ( males and females ) were participated in the present study and classified into 7 groups : Gc :  COVID-19 patients ( without vaccine ) , Gp₁: COVID-19 patients took one dose of Pfizer Biontech, Gp₂ : COVID-19 patients took two doses of Pfizer Biontech, Ga₁ : patients took one dose of AstraZeneca Oxford vaccine , Ga₂: patients took two doses of AstraZeneca Oxford vaccine , Gs₁ : patients took one dose of Sinopharm vaccine and Gs₂:

      Coronavirus is considered the first virus to sweep the world in the twenty-first century, it appeared by the end of 2019. It started in the Chinese city of Wuhan and began to spread in different regions around the world too quickly and uncontrollable due to the lack of medical examinations and their inefficiency. So, the process of detecting the disease needs an accurate and quickly detection techniques and tools. The X-Ray images are good and quick in diagnosing the disease, but an automatic and accurate diagnosis is needed. Therefore, this paper presents an automated methodology based on deep learning in diagnosing COVID-19. In this paper, the proposed system is using a convolutional neural network, which is considered one o

‎  Since the first outbreak in Wuhan, China, in December 31, 2019, COVID-19    pandemic  ‎has been spreading to many countries in the world. The ongoing COVID-19 pandemic has caused a ‎major global crisis, with 554,767 total confirmed cases, 484,570 total recovered cases, and ‎‎12,306 deaths in Iraq as of February 2, 2020. In the absence of any effective therapeutics or drugs ‎and with an unknown epidemiological life cycle, predictive mathematical models can aid in ‎the understanding of both control and management of coronavirus disease. Among the important ‎factors that helped the rapid spread of the ep