Abstract The main purpose of the research is to clarify and investigate in details about Susan Glaspell’s role in shedding light on the predicament of women in American society in the early twentieth century showing how sense of the place played an important role in limiting the opportunities of female protagonists who try to escape the roles imposed upon them by society. Glaspell lived in the early twentieth century in the Midwest and tackled the important issues like: women's suffrage, birth control, socialism, union organizing when women were not able to vote or sit as a member on juries. Her Feminist cause is quite obvious through her works from her first one act play Suppressed Desire to the final three act play, Alison’s House. The paper analyses Glaspell's Trifle (1916) from the perspectives of regionalism that defined the American literature of the era its effect on gender .Thus, shedding light on Suzan Glaspell as a feminist and a regionalist who recorded an important period of American history. The paper tries to show how Glaspell who was a regionalist, local colorist and a realist succeeded to deal with issues of social justice and how she used literature as a weapon to fight the ills of society as an adherent believer in school of "art for the sake of life".
This research addresses a problem manifested in a main question: what is the role of the digital media in marketing the artistic products? in order to determine the role played by the digital media in the disclosure and promotion of the artistic product, its price and places of distribution, as the basic elements of the marketing mixture.
This is a descriptive research in which the researcher used the survey method to check the opinions of a sample chosen according to the (proportion) method from the research community represented by instructors and students of the college of Fine Arts- University of Dayala.
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Mental disorders (MDs) are a common problem in Primary Health Care Centers (PHCCs). Many people with serious MDs are challenged by symptoms and disabilities that result from the disease and by stereotypes and prejudice due to misconceptions about mental illness. This study aims at evaluating the knowledge, and attitude toward mental health concepts and services and causes of the reluctance to seek those services among people attending PHCCs. A descriptive cross-sectional study was conducted. The random sampling technique was used to include (10) of Directorates of Health (DoHs) coverage north, middle, and south of Iraq. The study was executed in (50) selected PHCs, (5) PHCCs in each DoH involved randomly selected (30) people attending th
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In this paper, we study some cases of a common fixed point theorem for classes of firmly nonexpansive and generalized nonexpansive maps. In addition, we establish that the Picard-Mann iteration is faster than Noor iteration and we used Noor iteration to find the solution of delay differential equation.
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Because the Coronavirus epidemic spread in Iraq, the COVID-19 epidemic of people quarantined due to infection is our application in this work. The numerical simulation methods used in this research are more suitable than other analytical and numerical methods because they solve random systems. Since the Covid-19 epidemic system has random variables coefficients, these methods are used. Suitable numerical simulation methods have been applied to solve the COVID-19 epidemic model in Iraq. The analytical results of the Variation iteration method (VIM) are executed to compare the results. One numerical method which is the Finite difference method (FD) has been used to solve the Coronavirus model and for comparison purposes. The numerical simulat
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
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Objective Thalassemic patients present with multiple immune abnormalities that may predispose them to oral Candida, however this has not been investigated. The aim of this study was to assess oral candidal colonization in a group of patients with β-thalassemia major both qualitatively and quantitatively. Study design The oral mycologic flora of 50 β-thalassemia major patients and 50 age- and sex-matched control subjects was assessed using the concentrated oral rinse technique. Candida species were identified using the germ tube test and the Vitek yeast identification system. Results Oral Candida was isolated from 37 patients (74%) and 28 healthy subjects (56%; P = .04). The mean candidal count was significantly higher in thalassemic patie
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