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The Coronavirus disease 2019 (COVID-19) pandemic is caused by the transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which was first identified in December 2019 in Wuhan, China. The outbreak was declared as a Public Health Emergency of International Concern in January 2020 and a pandemic in March 2020. In this study, a complete statistical analysis for SARS-CoV-2 pandemic in entire Iraq, as well as for each governorate separately, is performed for the first time. The study covers a period that starts from the beginning of the pandemic, in the 24th of February 2020, until the 16th of July 2020. It was clear that, although the average number of the reported infection cases was low during February and March, the average infection rate (R0) was >1 (1.3- 2.1), indicating a high spreading rate. During April, when there was a complete lockdown, there was a slight decrease in the RO when the lockdown was lifted, the RO and the number of new cases started to increase rapidly until the 16th of July, when the average number of new cases for every 6 days reached 2281. The cumulative average number of new cases for every six days since the beginning of the pandemic in Iraq on 16 July was 598.4 ±862.4 (Mean± SD). The higher standard deviation than mean value (SD > mean) for most of the analyzes indicates that the official statistics are not reliable. This may be due to the need to conduct further studies as well as the presence of several cases that were not officially reported. In addition, the overall six-day average RO for entire Iraq was 1.4±0.5, with unstable values after the start of the pandemic and absence of monitoring at any time. On the other hand, this study reflects the variations in average RO, average new cases, average recovery rates, average death rates for every 6 days between the Iraqi provinces. Bagdad reported the highest average number of new cases; Babil and Salah aldin reported the highest RO values (2.8± 7.6, 2.5±7.7, respectively). Erbil and Kurkuk reported the highest average recovery rates (372.3± 1340.8, 158±433%, respectively). Babil and Dhiqar reported the highest average death rates (12.2± 63.3, 10.0± 25.8%, respectively), although Duhock did not record any deaths at the time of the study. The data require the attention of the Ministry of Health and Environment to fill in performance holes, as demonstrated by an out-of-control pandemic in Iraq.

How can Marxism, a theory and practice that emerged from the European experience, speak to contexts outside that experience? Recent scholarship has returned to the moment of the 1960s and 1970s to examine how political movements in the global South that embraced Marxism grappled with this question, aiming to reformulate Marxist theories and categories of analysis for postcolonial realities. Whereas this scholarship focuses on the writings of intellectuals, in this article, the authors supplement prose with oral history and ethnography to also identify the theory immanent in practice. They show how the translation of Marxist theory for political practice in the peripheries instantiated what the authors call a worldly Marxism: that is, a Marxism that is constantly renewed as it exceeds its origins in Europe and attends to the specificities of settler-colonies, (post-)colonies and metropoles. Worldly Marxism thus entails theorizing in the conjuncture, that is, from a particular historical moment, and involves arranging multiple conceptual elements to clarify and understand the political task at hand. The authors illustrate how such worldly Marxism was produced in Pakistan by examining the Mazdoor Kisan Party (MKP), the country's historically largest communist party, as it engaged with agrarian transitions, religion, and gender.

The paper of Rusconi, in 1928, on the discovery of two indigenous locations was one of the first archeological researchs in the area surrounding the Matanza River. In the present work we establish the spatial location of the sites mentioned through an intensive literature and geospatial research, which used the topographic surveys of the own Rusconi and the satellites charts of the City of Buenos Aires from the Military Geographic Institute (actually National Geographic Institute) combining them with the gvSIG 1.11.0 program. The results showed that the site listed as location A to the author is in the current South Park Municipal Workers' Union, and the location B, under the Autódromo Oscar Galvez city. ; La publicación de Rusconi, en 1928, sobre el hallazgo de dos paraderos indígenas en Villa Riachuelo constituyó una de las primeras investigaciones realizadas en el área circundante al río Matanza. En el presente trabajo establecemos la ubicación espacial de los sitios mencionados a través de una búsqueda bibliográfica y geoespacial intensiva, en la cual se utilizaron los relevamientos topográficos del propio Rusconi y las cartas satelitales de la Ciudad de Buenos Aires del Instituto Geográfico Militar (actual Instituto Geográfico Nacional) combinándolas con el programa gvSIG 1.11.0. Los resultados demostraron que el sitio mencionado como Paradero A por el autor se encuentra en el actual Parque Sur del Sindicato de Trabajadores Municipales, y el Paradero B, bajo el Autódromo Municipal Oscar Gálvez.

Recent technological advancements have changed significantly the way news is produced, consumed, and disseminated. Frequent and on-spot news reporting has been enabled, which smartphones can access anywhere and anytime. News categorization or classification can significantly help in its proper and timely dissemination. This study evaluates and compares news category predictors' performance based on four supervised machine learning models. We choose a standard dataset of British Broadcasting Corporation (BBC) news consisting of five categories: business, sports, technology, politics, and entertainment. Four multi-class news category predictors have been developed and trained on the same dataset: Naïve Bayes, Random Forest, K-Nearest Neighbors (KNN), and Support Vector Machine (SVM). Each category predictor's performance was evaluated by analyzing the confusion matrix and quantifying the test dataset's precision, recall, and overall accuracy. In the end, the performance of all category predictors was studied and compared. The results show that all category predictors have achieved satisfactory accuracy grades. However, the SVM model performed better than the four supervised learning models, categorizing news articles with 98.3% accuracy. In contrast, the lowest accuracy was obtained by the KNN model. However, the KNN model's performance can be enhanced by investigating the optimal number of neighbors (K) value.

Abstract Objective: To evaluate the prevalence of deleterious oral habits and its effect on occlusion in school going children from 7 to 13 years old, in Aseer region of Saudi Arabia. Material and Methods: A cross-sectional study was conducted by clinical examination for the total sample of 750, who were attending private/ government schools in Aseer region school. Students were selected by stratified cluster random sampling. Clinical findings of each oral habits, including assessment of malocclusion, were examined involving the following parameters, i.e., crowding, spacing, open bite, crossbite and deep bite. Logistic regression analysis was conducted. Results: Boys had 26.2 % of crowded teeth, while 16.3% of girls were found to have crowded teeth; the difference was found to be significant (p=0.002). Spacing was present in 26.4% of boys and 16.7% girls; a significant difference was found between the two (p=0.002). Sleep bruxism was observed more among male subjects than females with a statistically significant difference in detrimental habits (p<0.001). Those subjects having tongue thrusting are 1.264 times at more risk of having crowded teeth than those with no tongue thrusting. Conclusion: There was a high prevalence of malocclusion associated with harmful oral habits in children. This highlighted the need to implement programs of oral care and health education for preventive orthodontic treatment at an early age.