BELL HOOKS’ “ENACTMENT OF NON-DOMINATION” IN THE “PRACTICE OF SPEAKING IN A LOVING AND CARING MANNER”: AN AUTOETHNOGRAPHY OF A SAUDI “WIDOW’S SON”

The Prophet Mohammed lost his parents when he was a child, and because he was an orphan, he believed that anyone caring for an orphan would hold a special place in the hereafter. Often when children in the Kingdom of Saudi Arabia lose the father, as the author did, there is a stigma attached to the boy with no father, and a tremendous hardship is placed on the family. Having married at age 11 to her third cousin 10 years her senior and giving birth to three children, and expecting another child, his mother became a widow. He analyzes his own life and liminal passages—the thresholds to literacy and academic success while raising seven children of his own. The study is also a rhetorical analysis of the material conditions of his mother’s life from age 18 until the author reached college age. He employs bell hooks’ “marginality as a site of resistance” (p. 276) which can be an effective position for self-advocacy. His mother, a Bedouin, has had the perspectives of an outsider—an illiterate widow—and an insider — a Saudi woman with all the Islamic respect the culture gives their women. In Saudi Arabia, however, it is common for a widow to give up her children to her brothers-in-law and to remarry, but in this autoethnography the author reflects on being raised by a young mother who defied all odds and resisted the expectation to remarry. hooks argues that the primary means of creating non-dominating alternatives is enactment….that interactions with family members provide an important arena for enactment, (hooks, 2016, p. 282). She also defines non-dominating ways of living, suggesting that parent-child interactions offer another opportunity to enact non-dominating ways of living” (p. 282). By “speaking in a loving and caring manner” his mother won in court because the judge gave her custody of her four sons when she explained her eldest son’s disability and special needs. At 14, the author became his mother’s guardian but has practiced “nondominating ways” by helping her to raise the siblings and earn a degree

Influence of capital structure on firm performance: Empirical evidence from Jordanian banking industry

This research examines the influence of capital structure on firm performance in the Jordanian context, data is obtained of 15 listed banks on Amman Stock Exchange (ASE) from 2002 to 2015. For this reason the Ordinary Least Squares method of multiple regression is applied in carrying out this analysis. The dependent variable for the research is both accounting and market performance measures, while the independent variable is capital structure measured by debt ratio. In addition to other controlled variables: size, growth opportunities, tangibility, risk, and dividend policy.The main result reveals a significant positive influence of capital structure on banks performance, in general. This implies that profitable Jordanian banks depend more on debt as their main financing option with an average of Debt Ratio equals to about 86%, therefore, a support of Trade-Off theory evidence is provided.Key words: Capital Structure, Firm Performance, Debt Ratio, Banking Sector in Jordan. Cette recherche examine l’influence de la structure du capital sur la performance des entreprises dans le contexte jordanien. Des données ont été obtenues de 15 banques cotées sur Amman Stock Exchange (ASE) de 2002 à 2015. Pour cette raison, la méthode des moindres carrés de régression multiple est appliquée afin de réaliser cette analyse. La variable dépendante de la recherche est à la fois les mesures de comptabilité et du marché pour la performance, tandis que la variable indépendante est la structure du capital mesurée par le ratio d'endettement. En plus des autres variables contrôlées: Taille, Opportunités de Croissance, la Tangibilité, le Risque et la Politique des Dividendes.Le résultat principal révèle une influence positive significative de la structure du capital sur la performance des banques en général. Cela implique que les banques jordaniennes rentables dépendent davantage d'endettement comme leur principale option de financement avec un ratio d'endettement moyen égal à environ 86%; par conséquent, une preuve de la théorie d’arbitrage - Trade-Off - est fournie.Mots clés: La structure du capital, la performance de l’entreprise, le ratio d’endettement, le secteur des banques en Jordanie

Evaluation of Groundwater Quality in Shallow Aquifers Under Cultivated Lands at Al Oha Area, United Arab Emirates

To assess the impact of application of chemical fertilizers in agriculture on the Quaternary aquifer at AI Oha area, United Arab Emirates, 76 groundwater samples were collected during February 1995 - March 1996. Samples were analyzed for major, minor and trace chemical constituents in the Food Control Laboratory, Abu Dhabi. The Total Dissolved Solids (TDS) of collected samples varied between 500 milligrams per liter (mg/l) in the east and 3,500 mg/l in the west. Except for bicarbonate ion (HC03-), concentration of major cations (Ca2+, Mg2+, Na+ and K+) and anions (CO32-, SO42- and Cl-) shows a general increase from east to west. The increase of salinity and concentration of all ions from east to west occurs in the direction of groundwater flow, where ion-depleted water from recharge area in the east becomes progressively loaded with more ions towards discharge areas in the west. Concentration of nitrate ion (NO3- in groundwater within the study area during February 1995 - March 1996 remained below the limits recommended by the World Health Organization (WHO) for drinking water (45 mg/l as NO3- or 10 mg/l as NO3--N). Phosphate ion (PO4-) shows trace concentrations in groundwater within the study area, averaging 0.8 mg/l. With the exception of few local anomalies, concentrations of iron (Fe), manganese (Mn), lead (Pb), zinc (Zn), copper (Cu), cobalt (Co) and chromium (Cr) shows a general increase from east to west. Based on the above results, there is no reason to believe that the chemical fertilizers used on farm lands at AI Oha area has adversely affected groundwater in the Quaternary aquifer

An Implemented Approach for Potentially Breast Cancer Detection Using Extracted Features and Artificial Neural Networks

Breast cancer (B-cancer) detection is still complex and challenging problem, and in that case, we propose and evaluate a four-step approach to segment and detect B-cancer disease. Studies show that relying on pure naked-eye observation of experts to detect such diseases can be prohibitively slow and inaccurate in some cases. Providing automatic, fast, and accurate image-processing-and artificial intelligence-based solutions for that task can be of great realistic significance. The presented approach itself scans the whole mammogram and performs filtering, segmentation, features extraction, and detection in a succession mode. The feasibility of the proposed approach was explored on 32 commonly virulent images, and the recognition rate achieved in the detection step is 100 %; further, the approach is able to give reliable results on distorted medical images, since the approach is subjected to a rectification step. Finally, this study is very effectual in decreasing mortality and increasing the quality of treatment of early onset of B-cancer

New Deal for Minorities

During the Depression years, minority groups in the United States suffered more than the other segments of the American society. Yet, they were not the focus of New Dealers. One may wonder why and how were the lives of women, African Americans, and Indian Americans, impoverished by the Great Depression, enhanced under the New Deal. At the outset, NIRA codes emphasized women’s inferiority to men since they reinforced traditional long-range place in the labor arena. African Americans, too, suffered more because of the NIRA. Likewise, the AAA and the CCC were administrated in segregationist manners. It was until 1935 onwards that things changed in favor of those minorities. Federal relief programs and agencies like the FERA, the WPA, and the NYA; and many other acts and executive orders contributed significantly in enhancing minorities’ conditions of life during the Depression year

A highly adaptable model based – method for colour image interpretation

This Thesis presents a model-based interpretation of images that can vary greatly in appearance. Rather than seek characteristic landmarks to model objects we sample points at regular intervals on the boundary to model objects with a smooth boundary. A statistical model of form in the exponent domain of an extended superellipse is created using sampled points and appearance by sampling inside objects. A colour Maximum Likelihood Ratio criterion (MLR) was used to detect cues to the location of potential pedestrians. The adaptability and specificity of this cue detector was evaluated using over 700 images. A True Positive Rate (TPR) of 0.95 and a False Positive Rate (FPR) of 0.20 were obtained. To detect objects with axes at various orientations a variant method using an interpolated colour MLR has been developed. This had a TPR of 0.94 and an FPR of 0.21 when tested over 700 images of pedestrians. Interpretation was evaluated using over 220 video sequences (640 x 480 pixels per frame) and 1000 images of people alone and people associated with other objects. The objective was not so much to evaluate pedestrian detection but the precision and reliability of object delineation. More than 94% of pedestrians were correctly interpreted

Adherence to the management of type i diabetes among Palestinian patients in Nablus city: a cross-sectional study

The purpose of this study is to investigate the adherence to the management of Type I Diabetes and to investigate factors associated with non-adherence among Palestinian Type 1 Diabetes patients. One hundred and twenty-six patients diagnosed with Type 1 Diabetes were enrolled in an observational cross-sectional study. Diabetes self-care adherence was measured using the Self Care Inventory (SCI). The patients were recruited from a diabetes clinic in Nablus city in Palestine. One-way ANOVA test and simple linear regressions were used in the statistical analysis. Participants age ranged from 3-43 years; 56% of them were females. The mean age at diagnosis for them was 10 years (+/-6.25). The mean glycosylated hemoglobin (A1C) was 9 +/-2.32. 66% of patients reported significant non-adherence to glucose testing, 89% reported non-adherence to diet recommendations, 79% reported non-adherence to exercise, and 21% reported non-adherence to administering insulin on time. Age (r = 0.29, P < 0.05), A1C (r = 0.21, P < 0.05), sex (P < 0.05), and patient educational level (P< 0.05) were significantly related to adherence score. Adherence to treatment among patients with Type 1 Diabetes is poor and is associated with age, sex, A1C, and patient educational level. Designed education programs should be implemented among patients with Type 1 Diabetes, which address the importance of adherence to the management of the diseases. More strategies should focus on monitoring the diet and insulin administration. © 2022, An-Najah National University. All rights reserved

Clinical Characteristics, Prognostic Factors and Treatment Outcomes of Patients with Bone-Only Metastatic Breast Cancer

Introduction: Bone is the most frequent site of breast cancer metastasis. Differences between those who present with de novo bone-only metastasis (BOM) and those who progress to bone-only disease following a diagnosis of early-stage breast cancer are not clear. Such differences in clinical course might have an impact on the aggressiveness of treatment. This study presents the clinical and pathological features, along with treatment outcomes, of breast cancer patients with BOM in relation to the timing and type of bone metastasis. Patients and Methods: Patients with breast cancer and BOM were retrospectively reviewed. De novo BOM was defined as bone metastasis diagnosed at presentation or within the first 4 months of follow-up. Treatment outcomes of patients with de novo, compared to those with subsequent BOM, are presented. Results: 242 patients, median age (range) at diagnosis was 52 (27-80) years were enrolled. The majority of the patients (77.3%) had de novo BOM with multiple sites of bone involvement (82.6%). At a median follow-up of 37.7 months, the median overall survival (OS) for patients with de novo BOM disease was significantly shorter than those who developed so subsequently; 40.8 months (95% CI, 51.1-184.1) compared to 80.9 months (95% CI, 36.4-47.9), p \u3c 0.001. Tumor grade, hormone receptor status and type of bone lesions (lytic versus sclerotic) had a significant impact on survival outcomes. Conclusion: Breast cancer with de novo BOM is a distinct clinical entity with unfavorable prognosis and is associated with shorter survival. Several risk factors for poor outcomes were identified and might inform treatment plans

A Layered Recurrent Neural Network for Imputing Air Pollutants Missing Data and Prediction of <em>NO</em>₂, <em>O</em>₃, <em>PM</em>₁₀, and <em>PM</em>_2.5

To fulfill the national air quality standards, many countries have created emissions monitoring strategies on air quality. Nowadays, policymakers and air quality executives depend on scientific computation and prediction models to monitor that cause air pollution, especially in industrial cities. Air pollution is considered one of the primary problems that could cause many human health problems such as asthma, damage to lungs, and even death. In this study, we present investigated development forecasting models for air pollutant attributes including Particulate Matters (PM2.5, PM10), ground-level Ozone (O3), and Nitrogen Oxides (NO2). The dataset used was collected from Dubrovnik city, which is located in the east of Croatia. The collected data has missing values. Therefore, we suggested the use of a Layered Recurrent Neural Network (L-RNN) to impute the missing value(s) of air pollutant attributes then build forecasting models. We adopted four regression models to forecast air pollutant attributes, which are: Multiple Linear Regression (MLR), Decision Tree Regression (DTR), Artificial Neural Network (ANN) and L-RNN. The obtained results show that the proposed method enhances the overall performance of other forecasting models