Investigating the impact of postgraduate musculoskeletal physiotherapy education on practitioners’ clinical reasoning skills

Advancing clinical reasoning skills is one of the main outcomes of postgraduate master’s level (M-level) programmes approved by the Musculoskeletal Association of Chartered Physiotherapists (MACP). While, the outcomes of these programmes were investigated in multiple retrospective studies, there is a limited understanding of the learning culture that drives change. Thus, the aim was to examine the learning culture of an MACP approved programme to capture the sociocultural mediators that advanced clinical reasoning skills. An empirical longitudinal mixed-methods theory-seeking case study was conducted over a period of 18 months. Participants included seven educators and six students. Data analysis was premised on the methods of a Constructivist Grounded Theory. Gradual and progressive advancement of clinical reasoning skills was identified. A model of a culture of convergence and synergy was constructed to conceptualise the relationship between students, the programme and the wider context. It demonstrates the value of convergence and synergy in supporting professional learning. This novel conceptual understanding of advancing clinical reasoning through M-level education suggest that pedagogues need to actively seek to create a culture convergence and synergy to achieving successful learning outcomes. The context-bounded knowledge provided in the thesis aid pedagogues to better design M-level curriculums

A NOVEL KNOWLEDGE MANAGEMENT FRAMEWORK FOR MANAGING INFORMATION OVERLOAD IN THE DIABETES CLINICS OF THE HOSPITALS IN JORDAN

This thesis introduces a study for knowledge management of information overload in the healthcare domain. The study selected the diabetes clinics of seven hospitals in Jordan as a case study based on obtaining consent letters from these hospitals. First, a comprehensive literature was conducted in order to explore the existing information overload problem in-depth and to investigate existing solutions that assist in developing a new framework for reducing this problem. The literature findings integrated six theoretical factors adopted from the literature to form a data collection survey representing the initial primary research stage where the mixed approach methodology was considered. The data was collected by approaching the medical staff in person, and was analysed to determine the arising problems affected by information overload, and to find out about the information type that is used, the way information is used/communicated, and how information is going to be held. The findings from the primary research analysis showed that the results were statistically approaching the average indicating to an average problem. The researcher afterwards produced an information flow and processing models for the information that is running into these clinics. Thus, a knowledge management framework is proposed in order to reduce information overload affecting these clinics by enhancing an appropriate existing method from the literature, and by enhancing the analytical primary research findings. The framework is based on sharing the information to the right person at the right time in the right place with the right quantity. Furthermore, a validation of the framework was conducted with the assistance of a subset of medical experts in the field existing in these clinics. In conclusion, the future research is that the framework will form the basis of teaching by future researchers for further possible enhancements

Factors affecting the Value Added Tax Evasion in Palestine

The study aims to identify the phenomenon of tax evasion in Palestine in terms of methods and reasons for evasion. It also aims at identifying and evaluating the mechanisms followed by the VAT Department in the Gaza Strip to combat VAT evasion. The study examines the ability of the legislations and laws to reduce tax invasion and the impact of the current socioeconomic situation on tax evasion. To accomplish the aim of the study, 58 questionnaires were distributed to employees at the VAT Department. Of the questionnaire 50 were valid to analyze. In addition, several heads of divisions were interviewed for the same aim. The most important results of the study are: 83% of the respondents state that training of staff leads to minimizing tax evasion. Also, 76% of the respondents mention that imposing many taxes and double taxation encourage the taxpayer to evade taxes. Further, the economic depression contributes to tax evasion according to 86% of the respondents. The most important recommendations are: the necessity of increasing tax exemption, avoiding double taxation, reviewing tax legislations, improving value added tax laws, enhancing the tax awareness and raising the level of voluntary commitment of the taxpayer

Impact of large block FEC with different queue sizes of drop tail and RED queue policy on video streaming quality over internet

In this paper, we report an investigation on the impact of large block Forward Error Correction (FEC) with Drop Tail (DT) and Random Early Detection (RED) queue policies on network performance and quality of video streaming.FEC is a technique that uses redundant packets to reconstruct dropped packets, while DT and RED are the most popular queue management policies used in network routers.DT mainly depends on the size of the queue buffer to decide on whether to drop a packet or not.RED monitors the average queue size and drops arriving packets probabilistically.The probability of dropping a packet increases as the estimated average queue size grows.In the investigation, we consider simulation settings with varying size of queue buffers.Results obtained from the simulation experiments show that large block FEC and queue size affect the performance the network.Consequently, the qualities of multimedia applications are also affected

The PAC2MAN mission: a new tool to understand and predict solar energetic events

An accurate forecast of flare and CME initiation requires precise measurements of the magnetic energy build up and release in the active regions of the solar atmosphere. We designed a new space weather mission that performs such measurements using new optical instruments based on the Hanle and Zeeman effects. The mission consists of two satellites, one orbiting the L1 Lagrangian point (Spacecraft Earth, SCE) and the second in heliocentric orbit at 1AU trailing the Earth by 80$^\circ$ (Spacecraft 80, SC80). Optical instruments measure the vector magnetic field in multiple layers of the solar atmosphere. The orbits of the spacecraft allow for a continuous imaging of nearly 73\% of the total solar surface. In-situ plasma instruments detect solar wind conditions at 1AU and ahead of our planet. Earth directed CMEs can be tracked using the stereoscopic view of the spacecraft and the strategic placement of the SC80 satellite. Forecasting of geoeffective space weather events is possible thanks to an accurate surveillance of the magnetic energy build up in the Sun, an optical tracking through the interplanetary space, and in-situ measurements of the near-Earth environment.Comment: Accepted for publication in the Journal of Space Weather and Space Climate (SWSC

An intelligent rule-oriented framework for extracting key factors for grants scholarships in higher education

Education is a fundamental sector in all countries, where in some countries students com-pete to get an educational grant due to its high cost. The incorporation of artificial intelli-gence in education holds great promise for the advancement of educational systems and pro-cesses. Educational data mining involves the analysis of data generated within educational environments to extract valuable insights into student performance and other factors that enhance teaching and learning. This paper aims to analyze the factors influencing students' performance and consequently, assist granting organizations in selecting suitable students in the Arab region (Jordan as a use case). The problem was addressed using a rule-based tech-nique to facilitate the utilization and implementation of a decision support system. To this end, three classical rule induction algorithms, namely PART, JRip, and RIDOR, were em-ployed. The data utilized in this study was collected from undergraduate students at the University of Jordan from 2010 to 2020. The constructed models were evaluated based on metrics such as accuracy, recall, precision, and f1-score. The findings indicate that the JRip algorithm outperformed PART and RIDOR in most of the datasets based on f1-score metric. The interpreted decision rules of the best models reveal that both features; the average study years and high school averages play vital roles in deciding which students should receive scholarships. The paper concludes with several suggested implications to support and en-hance the decision-making process of granting agencies in the realm of higher education

The PAC2MAN mission: A new tool to understand and predict solar energetic events

An accurate forecast of flare and coronal mass ejection (CME) initiation requires precise measurements of the magnetic energy buildup and release in the active regions of the solar atmosphere. We designed a new space weather mission that performs such measurements using new optical instruments based on the Hanle and Zeeman effects. The mission consists of two satellites, one orbiting the L1 Lagrangian point (Spacecraft Earth, SCE) and the second in heliocentric orbit at 1AU trailing the Earth by 80° (Spacecraft 80, SC80). Optical instruments measure the vector magnetic field in multiple layers of the solar atmosphere. The orbits of the spacecraft allow for a continuous imaging of nearly 73% of the total solar surface. In-situ plasma instruments detect solar wind conditions at 1AU and ahead of our planet. Earth-directed CMEs can be tracked using the stereoscopic view of the spacecraft and the strategic placement of the SC80 satellite. Forecasting of geoeffective space weather events is possible thanks to an accurate surveillance of the magnetic energy buildup in the Sun, an optical tracking through the interplanetary space, and in-situ measurements of the near-Earth environment

The PAC2MAN mission: A new tool to understand and predict solar energetic events

An accurate forecast of flare and coronal mass ejection (CME) initiation requires precise measurements of the magnetic energy buildup and release in the active regions of the solar atmosphere. We designed a new space weather mission that performs such measurements using new optical instruments based on the Hanle and Zeeman effects. The mission consists of two satellites, one orbiting the L1 Lagrangian point (Spacecraft Earth, SCE) and the second in heliocentric orbit at 1AU trailing the Earth by 80\ub0 (Spacecraft 80, SC80). Optical instruments measure the vector magnetic field in multiple layers of the solar atmosphere. The orbits of the spacecraft allow for a continuous imaging of nearly 73% of the total solar surface. In-situ plasma instruments detect solar wind conditions at 1AU and ahead of our planet. Earth-directed CMEs can be tracked using the stereoscopic view of the spacecraft and the strategic placement of the SC80 satellite. Forecasting of geoeffective space weather events is possible thanks to an accurate surveillance of the magnetic energy buildup in the Sun, an optical tracking through the interplanetary space, and in-situ measurements of the near-Earth environment

Subnational mapping of HIV incidence and mortality among individuals aged 15–49 years in sub-Saharan Africa, 2000–18 : a modelling study

Background: High-resolution estimates of HIV burden across space and time provide an important tool for tracking and monitoring the progress of prevention and control efforts and assist with improving the precision and efficiency of targeting efforts. We aimed to assess HIV incidence and HIV mortality for all second-level administrative units across sub-Saharan Africa. Methods: In this modelling study, we developed a framework that used the geographically specific HIV prevalence data collected in seroprevalence surveys and antenatal care clinics to train a model that estimates HIV incidence and mortality among individuals aged 15–49 years. We used a model-based geostatistical framework to estimate HIV prevalence at the second administrative level in 44 countries in sub-Saharan Africa for 2000–18 and sought data on the number of individuals on antiretroviral therapy (ART) by second-level administrative unit. We then modified the Estimation and Projection Package (EPP) to use these HIV prevalence and treatment estimates to estimate HIV incidence and mortality by second-level administrative unit. Findings: The estimates suggest substantial variation in HIV incidence and mortality rates both between and within countries in sub-Saharan Africa, with 15 countries having a ten-times or greater difference in estimated HIV incidence between the second-level administrative units with the lowest and highest estimated incidence levels. Across all 44 countries in 2018, HIV incidence ranged from 2 ·8 (95% uncertainty interval 2·1–3·8) in Mauritania to 1585·9 (1369·4–1824·8) cases per 100 000 people in Lesotho and HIV mortality ranged from 0·8 (0·7–0·9) in Mauritania to 676· 5 (513· 6–888·0) deaths per 100 000 people in Lesotho. Variation in both incidence and mortality was substantially greater at the subnational level than at the national level and the highest estimated rates were accordingly higher. Among second-level administrative units, Guijá District, Gaza Province, Mozambique, had the highest estimated HIV incidence (4661·7 [2544·8–8120·3]) cases per 100000 people in 2018 and Inhassunge District, Zambezia Province, Mozambique, had the highest estimated HIV mortality rate (1163·0 [679·0–1866·8]) deaths per 100 000 people. Further, the rate of reduction in HIV incidence and mortality from 2000 to 2018, as well as the ratio of new infections to the number of people living with HIV was highly variable. Although most second-level administrative units had declines in the number of new cases (3316 [81· 1%] of 4087 units) and number of deaths (3325 [81·4%]), nearly all appeared well short of the targeted 75% reduction in new cases and deaths between 2010 and 2020. Interpretation: Our estimates suggest that most second-level administrative units in sub-Saharan Africa are falling short of the targeted 75% reduction in new cases and deaths by 2020, which is further compounded by substantial within-country variability. These estimates will help decision makers and programme implementers expand access to ART and better target health resources to higher burden subnational areas