Michael Cassidy - lay apostle to the cities of Africa

This work is a reflection about and case study in Apostolicity. It is also about the power of an individual to be a change agent in socio-political contexts. Its subject is Dr. Michael Cassidy who is founder and former international team leader of African Enterprise, an international Evangelistic organisation, that partner with churches in Africa to foster the growth of the Christian movement in cities through its ten national indigenous teams spread through Africa. Cassidy is also regarded as a prominent Evangelical leader at home and abroad, and is a strong influence in the Lausanne movement. The thesis traces the ministry of Cassidy in his years leading up to the founding of the work and his nearly 50 years of witness in the turbulence of Africa and South Africa during and after the Apartheid years. This historical review has special interest for the ecumenical witness of the church in its fight against Apartheid through great conferences like The Durban Congress on Mission and Evangelism 1973, The South African Christian Leadership Assembly (SACLA l and SACLA ll), the National Initiative for Reconciliation and the Rustenburg Church Consultation. In the research the theological, missiological and philosophical motifs of Cassidy’s work are discussed, with special attention to the issues of truth and the socio-political implications of love. The thesis also describes Cassidy’s involvement in the Marriage Alliance and the struggle to bring a biblically based outcome to the South African legislation on the matter of gay marriage. Cassidy’s worldview and his spirituality, weighed against the current debate on these issues, are examined. A primary interest expressed in the thesis is the concept of Lay Apostolicity, a concept that was powerfully raised by Cassidy whose ministry has been as a layman who has not been ordained. The structures for mission are deeply examined from Protestant and Catholic perspectives. The writer argues that Cassidy’s ministry has special value as a model and example for others in understanding and participating in the apostolic ministry of the ordinary Christian man and woman in the local church or in the working context. The thesis takes as its leitmotif the Prayer of Jesus in John 17 - and the life of Cassidy is discussed alongside reflections of and in relation to Jesus’ prayer for in his Apostles ( and those who follow) in the hours before his passion. The ‘marks’ in Jesus’ prayer have been identified as: Mission, Glory, Unity, Love, Truth, Holiness, Spirituality, Joy, Successive Chapters on each of these appear in the thesis. An analysis of Cassidy’s witness and mission was made through a survey with 120 respondents to measure the effect of Cassidy’s ministry. The chapter on Joy deals with this. The final chapters deal with an assessment of Cassidy’s life and work. The first of these looks at the dynamics of leadership and a critical assessment of his peers and others. The last chapter on “The measure of the man” attempts to list and clarify special significances, abilities and characteristics that have contributed to a unique calling and contribution to our understanding of Lay Apostolicity.Thesis (PhD)--University of Pretoria, 2010.Science of Religion and Missiologyunrestricte

Who Owns the Data? Open Data for Healthcare.

Research on large shared medical datasets and data-driven research are gaining fast momentum and provide major opportunities for improving health systems as well as individual care. Such open data can shed light on the causes of disease and effects of treatment, including adverse reactions side-effects of treatments, while also facilitating analyses tailored to an individual's characteristics, known as personalized or "stratified medicine." Developments, such as crowdsourcing, participatory surveillance, and individuals pledging to become "data donors" and the "quantified self" movement (where citizens share data through mobile device-connected technologies), have great potential to contribute to our knowledge of disease, improving diagnostics, and delivery of -healthcare and treatment. There is not only a great potential but also major concerns over privacy, confidentiality, and control of data about individuals once it is shared. Issues, such as user trust, data privacy, transparency over the control of data ownership, and the implications of data analytics for personal privacy with potentially intrusive inferences, are becoming increasingly scrutinized at national and international levels. This can be seen in the recent backlash over the proposed implementation of care.data, which enables individuals' NHS data to be linked, retained, and shared for other uses, such as research and, more controversially, with businesses for commercial exploitation. By way of contrast, through increasing popularity of social media, GPS-enabled mobile apps and tracking/wearable devices, the IT industry and MedTech giants are pursuing new projects without clear public and policy discussion about ownership and responsibility for user-generated data. In the absence of transparent regulation, this paper addresses the opportunities of Big Data in healthcare together with issues of responsibility and accountability. It also aims to pave the way for public policy to support a balanced agenda that safeguards personal information while enabling the use of data to improve public health

Who owns the data? Open data for healthcare

Research on large shared medical datasets and data-driven research are gaining fast momentum and provide major opportunities for improving health systems as well as individual care. Such open data can shed light on the causes of disease and effects of treatment, including adverse reactions side-effects of treatments, while also facilitating analyses tailored to an individual’s characteristics, known as personalized or “stratified medicine.” Developments, such as crowdsourcing, participatory surveillance, and individuals pledging to become “data donors” and the “quantified self” movement (where citizens share data through mobile device-connected technologies), have great potential to contribute to our knowledge of disease, improving diagnostics, and delivery of ­healthcare and treatment. There is not only a great potential but also major concerns over privacy, confidentiality, and control of data about individuals once it is shared. Issues, such as user trust, data privacy, transparency over the control of data ownership, and the implications of data analytics for personal privacy with potentially intrusive inferences, are becoming increasingly scrutinized at national and international levels. This can be seen in the recent backlash over the proposed implementation of care.data, which enables individuals’ NHS data to be linked, retained, and shared for other uses, such as research and, more controversially, with businesses for commercial exploitation. By way of contrast, through increasing popularity of social media, GPS-enabled mobile apps and tracking/wearable devices, the IT industry and MedTech giants are pursuing new projects without clear public and policy discussion about ownership and responsibility for user-generated data. In the absence of transparent regulation, this paper addresses the opportunities of Big Data in healthcare together with issues of responsibility and accountability. It also aims to pave the way for public policy to support a balanced agenda that safeguards personal information while enabling the use of data to improve public health

Vegetation Cover Analysis of Hazardous Waste Sites in Utah and Arizona Using Hyperspectral Remote Sensing

This study investigated the usability of hyperspectral remote sensing for characterizing vegetation at hazardous waste sites. The specific objectives of this study were to: (1) estimate leaf-area-index (LAI) of the vegetation using three different methods (i.e., vegetation indices, red-edge positioning (REP), and machine learning regression trees), and (2) map the vegetation cover using machine learning decision trees based on either the scaled reflectance data or mixture tuned matched filtering (MTMF)-derived metrics and vegetation indices. HyMap airborne data (126 bands at 2.3 x 2.3 m spatial resolution), collected over the U. S. Department of Energy uranium processing sites near Monticello, Utah and Monument Valley, Arizona, were used. Grass and shrub species were mixed on an engineered disposal cell cover at the Monticello site while shrub species were dominant in the phytoremediation plantings at the Monument Valley site. Regression trees resulted in the best calibration performance of LAI estimation (R-2 > 0.80. The use of REPs failed to accurately predict LAI (R-2 < 0.2). The use of the MTMF-derived metrics (matched filter scores and infeasibility) and a range of vegetation indices in decision trees improved the vegetation mapping when compared to the decision tree classification using just the scaled reflectance. Results suggest that hyperspectral imagery are useful for characterizing biophysical characteristics (LAI) and vegetation cover on capped hazardous waste sites. However, it is believed that the vegetation mapping would benefit from the use of higher spatial resolution hyperspectral data due to the small size of many of the vegetation patches (<1 m) found on the sites.open111

Translating research into practice in Leeds and Bradford (TRiPLaB): a protocol for a programme of research

Background The National Institute for Health Research (NIHR) has funded nine Collaborations for Leadership in Applied Health Research and Care (CLAHRCs). Each CLAHRC is a partnership between higher education institutions (HEIs) and the NHS in nine UK regional health economies. The CLAHRC for Leeds, York, and Bradford comprises two 'research themes' and three 'implementation themes.' One of these implementation themes is Translating Research into Practice in Leeds and Bradford (TRiPLaB). TRiPLaB aims to develop, implement, and evaluate methods for inducing and sustaining the uptake of research knowledge into practice in order to improve the quality of health services for the people of Leeds and Bradford. Methods TRiPLaB is built around a three-stage, sequential, approach using separate, longitudinal case studies conducted with collaborating NHS organisations, TRiPLaB will select robust innovations to implement, conduct a theory-informed exploration of the local context using a variety of data collection and analytic methods, and synthesise the information collected to identify the key factors influencing the uptake and adoption of targeted innovations. This synthesis will inform the development of tailored, multifaceted, interventions designed to increase the translation of research findings into practice. Mixed research methods, including time series analysis, quasi-experimental comparison, and qualitative process evaluation, will be used to evaluate the impact of the implementation strategies deployed. Conclusion TRiPLaB is a theory-informed, systematic, mixed methods approach to developing and evaluating tailored implementation strategies aimed at increasing the translation of research-based findings into practice in one UK health economy. Through active collaboration with its local NHS, TRiPLaB aims to improve the quality of health services for the people of Leeds and Bradford and to contribute to research knowledge regarding the interaction between context and adoption behaviour in health services