AN EVALUATION OF THE SCHOOL-BASED MANAGEMENT PRACTICES IN THE NEW SCHOOL MODEL: A STUDY ON AL AIN SCHOOLS

In 2005, the government of Abu Dhabi started a reform initiative by establishing the Abu Dhabi Education Council (ADEC). ADEC became responsible for efforts to improve the performance of schools and increase students’ achievement in the emirate. One way to do this was by creating the New School Model (NSM). Part of the NSM reform was a shift from the centralized system of managing the schools into a decentralized system that delegates and sometimes devolves decision-making authority to schools themselves. The purpose of this study is to investigate the degree to which School-Based Management (SBM) has been practiced in the New School Model (NSM) schools in Al Ain. The other purpose is to investigate the influence of staff position on the practices of the SBM. The third purpose is to identify the main areas of SBM practices that need improvement based on the perceptions of the participants. A descriptive quantitative research method in the form of a questionnaire was utilized to obtain the perceptions of 351 school staff. The conceptual framework for the SBM practices that guided this study was built from a synthesis of literature related to SBM and the features of NSM. The framework identified six critical areas of SBM practices: (a) effective school leadership, (b) budget allocation, (c) management strategies, (d) staff development, (e) curriculum and instruction, and (f) resources. ADEC grants authority in the areas of management strategies, staff development, curriculum and instruction, and resources. The areas of effective leadership and budget allocation have no or little authority. The results indicate that participation of school staff in SBM practices in areas where staff has more authority was greater than their participation in areas with no or little authority. In addition, the staff desire to participate in decision-making was strong and compatible with their actual participation in both areas. Moreover, the staff desire vii and actual participation was stronger in the areas that have direct relations to teaching than to the administrative tasks. The variable of position played a significant role in determining staff perceptions on practices in the areas of curriculum and instruction, management strategies, and resources. Finally, the study found that all areas of SBM need improvement, except for preparing school development plan, which has acceptable practice

Nesting parameters of Turtle Doves Streptopelia turtur arenicola breeding in Bahrain.

The Turtle Dove Streptopelia turtur arenicola (E Hartert, 1894) breeds from Morocco east to Tripoli, and from Iraq and Iran east through Afghanistan, Turkestan and Khirgiz steppes to northwest China (del Hoyo et al 1997). Within the Arabian peninsula it has been recorded breeding in Kuwait, Saudi Arabia, United Arab Emirates, Oman and Yemen in addition to Bahrain. It has not been recorded breeding in Qatar though suitable habitat exists there (Jennings 2010). Turtle Doves are widespread and common migrants throughout Arabia. They are thought to spend the winter in the Sahel and Ethiopia, returning north March–May to breed. Post breeding movements occur July–October and there is no evidence of wintering in Arabia (del Hoyo et al 1997, Beaman \u26 Madge 1998, Jennings 2010). The earliest record of breeding in Bahrain dates back to 1969, with additional records from 1982, 1985 and 1993 (Nightingale \u26 Hill 1993). The largest estimate was of 30 nests in Al Areen wildlife park in July 1985 (Nightingale \u26 Hill 1993). The colony monitored in the current study is immediately south of Al Areen wildlife park, in a group of mature desert broom Leptadenia pyrotechnica bushes, and may be the only Turtle Dove colony in Bahrain. Anecdotal evidence suggests that this breeding colony has been present annually for several decades at least, though recent evidence of birds breeding within the park was not available. The aims of the study were to gather information on the breeding parameters of this Turtle Dove colony, to estimate colony size and to conduct ringing of the chicks in the hope of getting recoveries to elucidate movement patterns of these Bahrain birds

Modelling traffic accidents using duration analysis techniques: a case study of Abu Dhabi

PhD ThesisOne of the main aims of Traffic Incident Management (TIM) is to reduce the duration of the disruption to traffic caused by an accident. Several approaches have been applied in the past in order to analyse and predict this. Incident duration can be broken down into four time intervals: reporting, response, clearance and recovery. Accurate models of each interval allow traffic controllers to deploy resources efficiently, thereby minimising an accident’s effect on traffic flow and congestion. This may, in turn, lead to a reduction in other adverse impacts of traffic accidents such as air pollution, fuel consumption and secondary crashes. A new approach to this problem, based on the accidents’ characteristics, was developed using a fully parametric hazard based modelling technique to predict accident durations. The road network around Abu Dhabi, capital of the UAE, was used as a case study. Data was obtained from the UAE Federal Traffic Statistics System (FTSS) and the Abu Dhabi Serious Collision Investigation Section (ASCIS). These data included the start and end of each time interval, the total accident duration, temporal, geographical, environmental and other accident characteristics. To analyse the total duration, the analysis was conducted using three time intervals. Accordingly, fully parametric Accelerated Failure Time (AFT) models were created for the purpose of reporting time, response time, and clearance time (all urban roads) and response time (rural freeways), depending on the data available. Analysis showed that the time intervals had different distributions. In addition, there was no similarity in the variable that affected each interval. The results also revealed that weaknesses exist in the current practices of TIM in Abu Dhabi. The results of the analysis were used to create decision trees to aid traffic controllers with decisions regarding traffic diversion and disseminating traffic information to travellers

Towards a Smart Electric Grid in Abu Dhabi: Models\u27 analysis and an Infrastructure and Architecture Proposition

A smart grid is an intelligent electrical grid that includes technological and technical components and operations to measure and distribute energy resources effectively and efficiently among beneficiaries in a smart city. Those components, including advanced metering system, load controllers and balancers, and other network components (infrastructure) are designed to present the structure of a smart grid and how those components are interconnected through rules to describe the functionality and management of that grid. Thus, and in order to build a a smart grid to a city (Abu Dhabi in this case), popular smart grid models are reviewed and compared from the US, Australia and China. Afterwards, the infrastructure and the architecture of Abu Dhabi\u27s smart grid are proposed to fit the current and visioned Abu Dhabi\u27s technological domain, based on the requirements (needs analysis) and available resources. In addition, the cyber security measures are also assessed to identify security grid threats and countermeasures. Finally, limitations are determined and future work are suggested

The geography of air freight and metropolitan economies: potential connections

Despite the recent remarkable growth of air freight shipments, much of the existing literature on the geography of air transportation has paid more attention to passenger travel than freight shipments. The purpose of this dissertation is to elevate our understanding of spatial hierarchies and nodal connectivity by determining which specific variables most influence and shape the geographic distribution of air freight by metropolitan area using stepwise regression analysis. The empirical results suggested a regression model of five independent variables is the most simple, effective, and parsimonious solution; 71.1% of the variation in the dependent variable was explained by the independent variables. The traffic shadow effect was the most important predictor in predicting the natural log of air freight, where small metropolitan areas within the traffic shadow of larger metropolitan areas tended to generate lower levels of freight. The model also suggested that other key predictors included per capita personal income, the transportation-shipping-logistics employment market share, the number of medical diagnostic establishments, and average high technology wages. Thus, metropolitan markets with more affluent people, diverse and efficient ground support systems, freight forwarders and other transportation services, an intense agglomeration of hospitals and medical universities, a highly skilled hi-tech workforce engaged in providing computer systems design and manufacturing generate high volumes of air freight

Air Passenger Demand and Skilled Labor Markets by U.S. Metropolitan Area

This paper examines the relationships that exist between skilled labor markets and air transportation by US metropolitan area. The goal is to enhance the current literature by conducting a more specific investigation of the links that exist between air passenger demand and employment levels within metropolitan economies focusing especially on employment patterns and the number of establishments for both the professional, scientific, and technical (PST) services sector and the high-technology sector. The results suggest that employment opportunities and the number of establishments in both sectors are systematically linked to the geography of air passenger demand

Clinical Phenotypes of PCOS: a Cross-Sectional Study

This cross-sectional study examines the Doi-Alshoumer PCOS clinical phenotype classification in relation to measured clinical and biochemical characteristics of women with polycystic ovary syndrome (PCOS). Two cohorts of women (Kuwait and Rotterdam) diagnosed with PCOS (FAI > 4.5%) were examined. These phenotypes were created using neuroendocrine dysfunction (IRMA LH/FSH ratio > 1 or LH > 6 IU/L) and menstrual cycle status (oligo/amenorrhea) to create three phenotypes: (A) neuroendocrine dysfunction and oligo/amenorrhea, (B) without neuroendocrine dysfunction but with oligo/amenorrhea, and (C) without neuroendocrine dysfunction and with regular cycles. These phenotypes were compared in terms of hormonal, biochemical, and anthropometric measures. The three suggested phenotypes (A, B, and C) were shown to be sufficiently distinct in terms of hormonal, biochemical, and anthropometric measures. Patients who were classified as phenotype A had neuroendocrine dysfunction, excess LH (and LH/FSH ratio), irregular cycles, excess A4, infertility, excess T, highest FAI and E2, and excess 17αOHPG when compared to the other phenotypes. Patients classified as phenotype B had irregular cycles, no neuroendocrine dysfunction, obesity, acanthosis nigricans, and insulin resistance. Lastly, patients classified as phenotype C had regular cycles, acne, hirsutism, excess P4, and the highest P4 to E2 molar ratio. The differences across phenotypes suggested distinct phenotypic expression of this syndrome, and the biochemical and clinical correlates of each phenotype are likely to be useful in the management of women with PCOS. These phenotypic criteria are distinct from criteria used for diagnosis

Qatar - Longitudinal Assessment of Mental Health in Pandemics (Q-LAMP)

Aims: QLAMP aims to identify risk factors and resilience factors for symptoms of psychiatric illness during the pandemic. Study strengths include the 1-year longitudinal design and the use of standardised instruments already available in English and Arabic. The results will increase understanding of the impact of the pandemic on mental health for better support of the population during the pandemic and in future epidemics. Until an effective vaccine is available or herd immunity is achieved, countries are likely to encounter repeated ‘waves’ of infection. The identification of at-risk groups for mental illness will inform the planning and delivery of individualized treatment including primary prevention. Methodology: Longitudinal online survey; SMS-based recruitment and social media platforms advertisements e.g. Facebook, Instagram; Online consent; Completion time for questionnaires: approx. 20 to 30 minute; Baseline questionnaire with follow up at 3, 6, 9 and 12 months; Study completion date: Sept. 2021. Inclusion Criteria: Currently living in Qatar; Qatar residents: citizens and expatriates; Age 18 years; Read Arabic or English (questionnaire and consent form available in both languages). Instruments: Sociodemographic questionnaire including personal and family experience of COVID-19 infection; Standard instruments to assess psychiatric morbidity including depression, anxiety and PTSD; Research team-designed instruments to assess social impact of pandemic; Standard questionnaires to assess resilience, personality, loneliness, religious beliefs and social networks. Results: The analysis was based on 181 observations. Approximately, 3.5% of the sample was from the sms-recruitment method. The sample of completed surveys consisted of 65.0% females and 35.0% males. Qatari respondents comprised 27.0% of the total sample, while 52% of the sample were married, 25% had Grade 12 or lower level of educational attainment, and 46.0% were unemployed. Covid-19 appears to have affected different aspects of people’s lives from personal health to living arrangements, employment, and health of family and friends. Approximately, 41% to 55% of those who responded to the survey perceived changes in their stress levels, mental health, and loneliness to be worse than before the pandemic. Additionally, the wide-availability of information about the pandemic on the internet and social media was perceived as source of pandemic-related worries among members of the public. Conclusions: The continued provision of mental health service and educational campaigns about effective stress and mental health management is warranted

Global prevalence and genotype distribution of hepatitis C virus infection in 2015 : A modelling study

Publisher Copyright: © 2017 Elsevier LtdBackground The 69th World Health Assembly approved the Global Health Sector Strategy to eliminate hepatitis C virus (HCV) infection by 2030, which can become a reality with the recent launch of direct acting antiviral therapies. Reliable disease burden estimates are required for national strategies. This analysis estimates the global prevalence of viraemic HCV at the end of 2015, an update of—and expansion on—the 2014 analysis, which reported 80 million (95% CI 64–103) viraemic infections in 2013. Methods We developed country-level disease burden models following a systematic review of HCV prevalence (number of studies, n=6754) and genotype (n=11 342) studies published after 2013. A Delphi process was used to gain country expert consensus and validate inputs. Published estimates alone were used for countries where expert panel meetings could not be scheduled. Global prevalence was estimated using regional averages for countries without data. Findings Models were built for 100 countries, 59 of which were approved by country experts, with the remaining 41 estimated using published data alone. The remaining countries had insufficient data to create a model. The global prevalence of viraemic HCV is estimated to be 1·0% (95% uncertainty interval 0·8–1·1) in 2015, corresponding to 71·1 million (62·5–79·4) viraemic infections. Genotypes 1 and 3 were the most common cause of infections (44% and 25%, respectively). Interpretation The global estimate of viraemic infections is lower than previous estimates, largely due to more recent (lower) prevalence estimates in Africa. Additionally, increased mortality due to liver-related causes and an ageing population may have contributed to a reduction in infections. Funding John C Martin Foundation.publishersversionPeer reviewe