Using Marxan and Marxan with Zones to support marine planning

With the growth in human pressures on the marine environment and the increase in competition for space and resources there has been recognition by many governments of the need to use the marine environment sustainably and allow for its acceptable allocation for each sector. The aim of this thesis is to evaluate the use of Marxan and Marxan with Zones as practical tools to enable the production of marine plans that integrate environmental and socioeconomic data and to suggest best practice in the types of data used. In this thesis three key aspects of data type and integration were identified and evaluated. The resolution and complexity of data required to protected marine biodiversity was assessed. The effects of using different substrate data resolution on the selection of sites to protect a range of biotopes using Marxan are determined. The nature of the data used in marine planning has significant implications for the protection of marine biodiversity. Using less complex data, of any resolution, did not adequately protect marine biodiversity. There is a need to determine what is an acceptable allocation of marine resource to each sector. Two case study areas were used to determine how to integrate conservation and socioeconomic data and objectives in a marine plan. Objectives for all the sectors could not be met completely in a single marine plan and each sector had to compromise. This research highlighted the potential compromises required and indicates that if marine heritage and biodiversity are to be protected each sector will have to change the impact it has on the marine environment. Currently marine conservation assumes that all data on habitats and species presented for use in marine planning are equal, in accuracy, precision and value. This is not always the case, with data based on a wide range of sources including routine government monitoring, specific innovative research and stakeholder based data gathering. A case study area was used to evaluate the impacts of using confidence levels in habitat data on marine biodiversity. It was found that data outputs that best protected marine biodiversity used data over 20% and over 30% confidence. With the data currently available for the UK marine environment it is not possible to be confident that a representative MPA network can be created. Together these studies contribute key recommendations for best practice in marine planning and demonstrate that the use of spatial decision support tools (Marxan and Marxan with Zones) are essential for the integration of data in marine planning, to assess how using different types of data will impact marine planning and marine biodiversity protection and to explore implications of different management actions

Relationships and growth in families of children with developmental disabilities : new ways of intervening

This research examined relationships and positive growth in families of children who have a developmental disability. Chapter one is a critical review of the literature relating to positive growth in parents of children who have a developmental disability. Past studies have indicated that having a child with a developmental disability can be both stressful for parents and place increased pressures on their time, energy and resources. However, this review of more recent research about the experience of having a child with a developmental disability highlights the range of positive growth experiences parents undergo and some of the possible processes involved. Positive growth experiences reported included changes in parental perceptions of their growth, changes in belief systems, increased sense of coherence and increased hope. Resilience, reframing coping strategies, meaning-making and social support were all implicated in this positive growth process. Clinically, the value of strengths-based services for families emerged. Chapter two is an empirical study, focusing on the maternal experience of a family based Lego Therapy intervention amongst five families who have a child who is on the autism spectrum. Qualitative analysis of interview data resulted in themes of family specific factors (communication, new perspectives, deeper relationships), child-specific factors (impact of the child's ASD, child-specific developments) and intervention-specific factors (ambivalence about the intervention, time). Methodological· and clinical implications are discussed, alongside recommendations for future research. Chapter three is a reflective paper focusing on the individual differences to emerge amongst families and the clinical and methodological implications of this

Land use and climate change in Miami-Dade County

Thesis (M.C.P.)--Massachusetts Institute of Technology, Dept. of Urban Studies and Planning, 2009.Includes bibliographical references (p. 69-77).Miami-Dade County, Florida, was one of the earliest jurisdictions to adopt a climate change plan in 1993. Land use features prominently in this plan as a means to reduce greenhouse gases through development patterns that allow people to lower their Vehicle Miles Traveled (VMT). Travel data show that average per capita VMT for the Miami area increased approximately 24% between 1993 and 2005, signifying that the land-use policies are not meeting their goal of VMT reduction. One apparent explanation is that land-use policies are not adequately implemented and enforced. The Board of County Commissioners is the most powerful decision-making body and holds responsibility for land-use policy enforcement. The Board is constrained by a governmental structure in which each commissioner is accountable only to residents of his or her district. Commissioners make decisions based on immediate benefits for their districts with little incentive to consider the long-term issues of land use and climate change. The Urban Development Boundary illustrates how the competing agendas of economic development and affordable housing compel commissioners to approve developments that contradict existing land-use policies. The financial crisis of the Miami-Dade Transit system was exacerbated by district-based conflicts and limited commissioner accountability. The district-based structure evolved from a history of racial and ethnic under-representation, which complicates the introduction of structural change.(cont.) Instead, the County should introduce incentives that encourage commissioners to include long-term County needs in policy enforcement decisions. Recommendations include: * Strengthened land-use advisory board * Transparent calculation of the long-term impacts of proposed developments * Temporary moratorium on 2011 UDB applications * Strategic funding allocation to promote smart growth land use.by Haley Rose Peckett.M.C.P

Pyomyositis of tensor fascia lata: a case report

<p>Abstract</p> <p>Introduction</p> <p>Pyomyositis is a disease in which an abscess is formed deep within large striated muscles.</p> <p>Case presentation</p> <p>We report the case of a 10-year-old boy who presented with fever and a painful hip and was subsequently diagnosed with pyomyositis of the tensor fascia lata. In children with clinical and laboratory findings of inflammation in the vicinity of the hip joint, the differential diagnosis includes transient synovitis, an early stage of Legg-Calvé-Perthes disease, infectious arthritis of the hip, rheumatologic diseases and extracapsular infection such as osteomyelitis.</p> <p>Conclusion</p> <p>To the best of the authors' knowledge, this is the first report of pyomyositis of the tensor fascia lata. Although pyomyositis is a rare disease and the differential diagnosis includes a variety of other commonly observed diseases, pyomyositis should be considered in cases where children present with fever, leukocytosis and localized pain.</p

Insight into glucocorticoid receptor signalling through interactome model analysis

Glucocorticoid hormones (GCs) are used to treat a variety of diseases because of their potent anti-inflammatory effect and their ability to induce apoptosis in lymphoid malignancies through the glucocorticoid receptor (GR). Despite ongoing research, high glucocorticoid efficacy and widespread usage in medicine, resistance, disease relapse and toxicity remain factors that need addressing. Understanding the mechanisms of glucocorticoid signalling and how resistance may arise is highly important towards improving therapy. To gain insight into this we undertook a systems biology approach, aiming to generate a Boolean model of the glucocorticoid receptor protein interaction network that encapsulates functional relationships between the GR, its target genes or genes that target GR, and the interactions between the genes that interact with the GR. This model named GEB052 consists of 52 nodes representing genes or proteins, the model input (GC) and model outputs (cell death and inflammation), connected by 241 logical interactions of activation or inhibition. 323 changes in the relationships between model constituents following in silico knockouts were uncovered, and steady-state analysis followed by cell-based microarray genome-wide model validation led to an average of 57% correct predictions, which was taken further by assessment of model predictions against patient microarray data. Lastly, semi-quantitative model analysis via microarray data superimposed onto the model with a score flow algorithm has also been performed, which demonstrated significantly higher correct prediction ratios (average of 80%), and the model has been assessed as a predictive clinical tool using published patient microarray data. In summary we present an in silico simulation of the glucocorticoid receptor interaction network, linked to downstream biological processes that can be analysed to uncover relationships between GR and its interactants. Ultimately the model provides a platform for future development both by directing laboratory research and allowing for incorporation of further components, encapsulating more interactions/genes involved in glucocorticoid receptor signalling

The Leveson inquiry should encourage more sensitive media coverage of suicides to help prevent copycat deaths

Much of the evidence given at the Leveson Inquiry so far has focused on invasion of privacy and harassment by the press and press intrusion into grief and shock. These issues are currently laid out in the Editors’ Code of Practice, regulated by the Press Complaints Commission. Nicola Peckett, Head of Communications at Samaritans, looks at how suicides are reported by the media, which hasn’t yet come under the spotlight at the Leveson Inquiry, and explains why it shoul

Adaptive Markov decision control of high-frequency drip irrigation systems

Global demand for food increases every year, despite this increase, productive farming land is limited. Meeting the demands of the future are dependent on improving the productivity of the land in use and a key factor behind this is intelligent agriculture. Fresh water remains in many situations the primary constraint on agriculture. This paper seeks to investigate machine intelligence irrigation scheduling methods in order to increase yield and improve crop irrigation efficiency. For the purposes of research the model organism Arabidopsis Thaliana was selected primarily due to its rapid life cycle and historical significance. Research began with the development of a water balance crop model for emphArabidopsis Thaliana. Upon completion of the model several experiments were performed to weakly verify its behaviour. The final step looked at implementing an artificially intelligent control algorithm for maximizing crop yield in water constrained environments. Several possible approaches were identified. The winning approach utilized a Markov decision process implementing a Radial Basis Function network as a value estimator. Performance was seen to exceed the best hand coded algorithms by up to 10% and it successfully outperformed the normal irrigation schedule control by a factor of 6.5x far exceeding the initial goals of the project! This solution was developed using a highly optimized, high performance computing MDP solver programmed by the author. Utilizing an Amazon Cluster Compute server possessing 32 Intel Xeon cores the author was able to outperform an initial naive, yet straight from the textbook, MATLAB MDP solver by a factor of 104