845 research outputs found

    Ready or Not? Protecting the Public's Health in the Age of Bioterrorism, 2004

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    Examines ten key indicators to evaluate state preparedness to respond to bioterrorist attacks and other public health emergencies. Evaluates the federal government's role and performance, and offers recommendations for improving readiness

    A review of operations research methods applicable to wildfire management

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    Across the globe, wildfire-related destruction appears to be worsening despite increased fire suppression expenditure. At the same time, wildfire management is becoming increasingly complicated owing to factors such as an expanding wildland-urban interface, interagency resource sharing and the recognition of the beneficial effects of fire on ecosystems. Operations research is the use of analytical techniques such as mathematical modelling to analyse interactions between people, resources and the environment to aid decision-making in complex systems. Fire managers operate in a highly challenging decision environment characterised by complexity, multiple conflicting objectives and uncertainty. We assert that some of these difficulties can be resolved with the use of operations research methods. We present a range of operations research methods and discuss their applicability to wildfire management with illustrative examples drawn from the wildfire and disaster operations research literature

    F as in Fat: How Obesity Policies Are Failing in America, 2004

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    Examines national and state obesity rates and government policies. Focuses on setting a baseline of current policies and programs, and offers a comprehensive look at their range and quality

    F as in Fat: How Obesity Policies Are Failing in America, 2005

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    Examines national and state obesity rates and government policies. Challenges the research community to focus on major research questions to inform policy decisions, and policymakers to pursue actions to combat the obesity crisis

    Identifying Market Preferences for High Selenium Beef

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    Selenium is an element found in relatively high concentrations in crops and livestock raised on high-selenium soils located in North and South Dakota. Evidence suggests that a high-selenium diet such as would be obtained from consuming these products can reduce the risk of certain cancers. The region's livestock and grain producers are exploring potential high-selenium product marketing opportunities. A choice experiment was conducted to identify preferred attributes for a high-selenium beef product and the characteristics of potential market segments. In a national survey, participants chose between different levels of health claim approval and research, prices, and selenium origin. A multinomial logit regression model was estimated. Labeling reflecting scientific support linking selenium and reduced cancer risk, and natural-source selenium was ineffective. Marketing opportunities identified are consistent with existing functional food market segments and include consumers with higher income and education, 45 to 55 years of age, and with children.Choice Experiment, FDA approval, Functional Foods, Health Claim, Labeling, Selenium, Consumer/Household Economics, Livestock Production/Industries,

    Fuel treatment planning: Fragmenting high fuel load areas while maintaining availability and connectivity of faunal habitat

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    Reducing the fuel load in fire-prone landscapes is aimed at mitigating the risk of catastrophic wildfires but there are ecological consequences. Maintaining habitat for fauna of both sufficient extent and connectivity while fragmenting areas of high fuel loads presents land managers with seemingly contrasting objectives. Faced with this dichotomy, we propose a Mixed Integer Programming (MIP) model that can optimally schedule fuel treatments to reduce fuel hazards by fragmenting high fuel load regions while considering critical ecological requirements over time and space. The model takes into account both the frequency of fire that vegetation can tolerate and the frequency of fire necessary for fire-dependent species. Our approach also ensures that suitable alternate habitat is available and accessible to fauna affected by a treated area. More importantly, to conserve fauna the model sets a minimum acceptable target for the connectivity of habitat at any time. These factors are all included in the formulation of a model that yields a multi-period spatially-explicit schedule for treatment planning. Our approach is then demonstrated in a series of computational experiments with hypothetical landscapes, a single vegetation type and a group of faunal species with the same habitat requirements. Our experiments show that it is possible to fragment areas of high fuel loads while ensuring sufficient connectivity of habitat over both space and time. Furthermore, it is demonstrated that the habitat connectivity constraint is more effective than neighbourhood habitat constraints. This is critical for the conservation of fauna and of special concern for vulnerable or endangered species

    An optimisation approach for fuel treatment planning to break the connectivity of high-risk regions

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    Uncontrolled wildfires can lead to loss of life and property and destruction of natural resources. At the same time, fire plays a vital role in restoring ecological balance in many ecosystems. Fuel management, or treatment planning by way of planned burning, is an important tool used in many countries where fire is a major ecosystem process. In this paper, we propose an approach to reduce the spatial connectivity of fuel hazards while still considering the ecological fire requirements of the ecosystem. A mixed integer programming (MIP) model is formulated in such a way that it breaks the connectivity of high-risk regions as a means to reduce fuel hazards in the landscape. This multi-period model tracks the age of each vegetation type and determines the optimal time and locations to conduct fuel treatments. The minimum and maximum Tolerable Fire Intervals (TFI), which define the ages at which certain vegetation type can be treated for ecological reasons, are taken into account by the model. Examples from previous work that explicitly disconnect contiguous areas of high fuel load have often been limited to using single vegetation types implemented within rectangular grids. We significantly extend such work by including modelling multiple vegetation types implemented within a polygon-based network to achieve a more realistic representation of the landscape. An analysis of the proposed approach was conducted for a fuel treatment area comprising 711 treatment units in the Barwon-Otway district of Victoria, Australia. The solution of the proposed model can be obtained for 20-year fuel treatment planning within a reasonable computation time of eight hours
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