The Coronavirus Disease 2019 (COVID-19) pandemic has caused an unprecedented disruption in medical education and healthcare systems worldwide. The disease can cause life-threatening conditions and it presents challenges for medical education, as instructors must deliver lectures safely, while ensuring the integrity and continuity of the medical education process. It is therefore important to assess the usability of online learning methods, and to determine their feasibility and adequacy for medical students. We aimed to provide an overview of the situation experienced by medical students during the COVID-19 pandemic, and to determine the knowledge, attitudes, and practices of medical students regarding electronic medical education. A cross-sectional survey was conducted with medical students from more than 13 medical schools in Libya. A paper-based and online survey was conducted using email and social media. The survey requested demographic and socioeconomic information, as well as information related to medical online learning and electronic devices; medical education status during the COVID-19 pandemic; mental health assessments; and e-learning knowledge, attitudes, and practices. A total of 3,348 valid questionnaires were retrieved. Most respondents (64.7%) disagreed that e-learning could be implemented easily in Libya. While 54.1% of the respondents agreed that interactive discussion is achievable by means of e-learning. However, only 21.1% agreed that e-learning could be used for clinical aspects, as compared with 54.8% who disagreed with this statement and 24% who were neutral. Only 27.7% of the respondents had participated in online medical educational programs during the COVID-19 pandemic, while 65% reported using the internet for participating in study groups and discussions. There is no vaccine for COVID-19 yet. As such, the pandemic will undeniably continue to disrupt medical education and training. As we face the prospect of a second wave of virus transmission, we must take certain measures and make changes to minimize the effects of the COVID-19 outbreak on medical education and on the progression of training. The time for change is now, and there should be support and enthusiasm for providing valid solutions to reduce this disruption, such as online training and virtual clinical experience. These measures could then be followed by hands-on experience that is provided in a safe environment.
It is very difficult to obtain the value of a rock strength along the wellbore. The value of Rock strength utilizing to perform different analysis, for example, preventing failure of the wellbore, deciding a completion design and, control the production of sand. In this study, utilizing sonic log data from (Bu-50) and (BU-47) wells at Buzurgan oil field. Five formations have been studied (Mishrif, Sadia, Middle lower Kirkuk, Upper Kirkuk, and Jaddala) Firstly, calculated unconfined compressive strength (UCS) for each formation, using a sonic log method. Then, the derived confined compressive rock strengthens from (UCS) by entering the effect of bore and hydrostatic pressure for each formation. Evaluations th
... Show MoreThis study was done to determine the concentration of several heavy metals in the water of Al-Saddah agricultural drainage in Al-Saddah District in Babylon Province/Iraq. The concentrations of six heavy metals were measured (Pb, Cd, Cu, Hg, Fe, Zn). It was found that Pb concentration ranged from 0.06 mg/L at St.2 in autumn to 0.13 mg/L at St.2 in winter. Fe concentrations ranged from 0.04 mg/L at St.2 in autumn and winter to 0.41 at St.2 in Summer. Cd concentrations ranged from 0.008 mg/L at St.2 in summer to 0.05 mg/L at St.2 in winter. Cu concentrations ranged from 0.01 mg/L at St.1 in both autumn and winter to 0.63 mg/L at St.2 in winter. Hg concentrations was ranged from 0.002 mg/
The last few years witnessed great and increasing use in the field of medical image analysis. These tools helped the Radiologists and Doctors to consult while making a particular diagnosis. In this study, we used the relationship between statistical measurements, computer vision, and medical images, along with a logistic regression model to extract breast cancer imaging features. These features were used to tell the difference between the shape of a mass (Fibroid vs. Fatty) by looking at the regions of interest (ROI) of the mass. The final fit of the logistic regression model showed that the most important variables that clearly affect breast cancer shape images are Skewness, Kurtosis, Center of mass, and Angle, with an AUCROC of
... Show MoreThis research (communicative values of the visual suggestion in TV advertising) presents a precise description for the process of conveying the communicative message through employing the visual suggestion in TV advertisements. This research consists of four chapters. The first chapter includes the research problem which is summarized by the following question: what are the communicative values accomplished in Tv advertisement which produce visual suggestions that raise strangeness and tension in the advertisement?
The research importance lies in benefiting the researchers and scholars in the field of TV advertisement direction and the visual suggestion is one the main ways for building the advertisement. It also benefits the relevan
The region-based association analysis has been proposed to capture the collective behavior of sets of variants by testing the association of each set instead of individual variants with the disease. Such an analysis typically involves a list of unphased multiple-locus genotypes with potentially sparse frequencies in cases and controls. To tackle the problem of the sparse distribution, a two-stage approach was proposed in literature: In the first stage, haplotypes are computationally inferred from genotypes, followed by a haplotype coclassification. In the second stage, the association analysis is performed on the inferred haplotype groups. If a haplotype is unevenly distributed between the case and control samples, this haplotype is labeled
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Seventy-six urine specimens were collected from of patients suffering from recurrent
urinary tract infections (UTIs). Specimens were bacteriologically analyzed, fifty
(65.8%) of isolated bacterial strains were belonged to E.coli. 100% of isolated
uropathogenic E.coli (UPEC)strains displayed a biofilm positive phenotype under
optimized condition using microtiter plate assay. 21 of E.coli strains classified as highly
positive biofilm producers (42%), and 29 (58%) as weakly positive biofilm producers.