583 resultados para Emergency Food Distribution Shelters


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Agent-based modelling (ABM), like other modelling techniques, is used to answer specific questions from real world systems that could otherwise be expensive or impractical. Its recent gain in popularity can be attributed to some degree to its capacity to use information at a fine level of detail of the system, both geographically and temporally, and generate information at a higher level, where emerging patterns can be observed. This technique is data-intensive, as explicit data at a fine level of detail is used and it is computer-intensive as many interactions between agents, which can learn and have a goal, are required. With the growing availability of data and the increase in computer power, these concerns are however fading. Nonetheless, being able to update or extend the model as more information becomes available can become problematic, because of the tight coupling of the agents and their dependence on the data, especially when modelling very large systems. One large system to which ABM is currently applied is the electricity distribution where thousands of agents representing the network and the consumers’ behaviours are interacting with one another. A framework that aims at answering a range of questions regarding the potential evolution of the grid has been developed and is presented here. It uses agent-based modelling to represent the engineering infrastructure of the distribution network and has been built with flexibility and extensibility in mind. What distinguishes the method presented here from the usual ABMs is that this ABM has been developed in a compositional manner. This encompasses not only the software tool, which core is named MODAM (MODular Agent-based Model) but the model itself. Using such approach enables the model to be extended as more information becomes available or modified as the electricity system evolves, leading to an adaptable model. Two well-known modularity principles in the software engineering domain are information hiding and separation of concerns. These principles were used to develop the agent-based model on top of OSGi and Eclipse plugins which have good support for modularity. Information regarding the model entities was separated into a) assets which describe the entities’ physical characteristics, and b) agents which describe their behaviour according to their goal and previous learning experiences. This approach diverges from the traditional approach where both aspects are often conflated. It has many advantages in terms of reusability of one or the other aspect for different purposes as well as composability when building simulations. For example, the way an asset is used on a network can greatly vary while its physical characteristics are the same – this is the case for two identical battery systems which usage will vary depending on the purpose of their installation. While any battery can be described by its physical properties (e.g. capacity, lifetime, and depth of discharge), its behaviour will vary depending on who is using it and what their aim is. The model is populated using data describing both aspects (physical characteristics and behaviour) and can be updated as required depending on what simulation is to be run. For example, data can be used to describe the environment to which the agents respond to – e.g. weather for solar panels, or to describe the assets and their relation to one another – e.g. the network assets. Finally, when running a simulation, MODAM calls on its module manager that coordinates the different plugins, automates the creation of the assets and agents using factories, and schedules their execution which can be done sequentially or in parallel for faster execution. Building agent-based models in this way has proven fast when adding new complex behaviours, as well as new types of assets. Simulations have been run to understand the potential impact of changes on the network in terms of assets (e.g. installation of decentralised generators) or behaviours (e.g. response to different management aims). While this platform has been developed within the context of a project focussing on the electricity domain, the core of the software, MODAM, can be extended to other domains such as transport which is part of future work with the addition of electric vehicles.

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Global awareness for cleaner and renewable energy is transforming the electricity sector at many levels. New technologies are being increasingly integrated into the electricity grid at high, medium and low voltage levels, new taxes on carbon emissions are being introduced and individuals can now produce electricity, mainly through rooftop photovoltaic (PV) systems. While leading to improvements, these changes also introduce challenges, and a question that often rises is ‘how can we manage this constantly evolving grid?’ The Queensland Government and Ergon Energy, one of the two Queensland distribution companies, have partnered with some Australian and German universities on a project to answer this question in a holistic manner. The project investigates the impact the integration of renewables and other new technologies has on the physical structure of the grid, and how this evolving system can be managed in a sustainable and economical manner. To aid understanding of what the future might bring, a software platform has been developed that integrates two modelling techniques: agent-based modelling (ABM) to capture the characteristics of the different system units accurately and dynamically, and particle swarm optimization (PSO) to find the most economical mix of network extension and integration of distributed generation over long periods of time. Using data from Ergon Energy, two types of networks (3 phase, and Single Wired Earth Return or SWER) have been modelled; three-phase networks are usually used in dense networks such as urban areas, while SWER networks are widely used in rural Queensland. Simulations can be performed on these networks to identify the required upgrades, following a three-step process: a) what is already in place and how it performs under current and future loads, b) what can be done to manage it and plan the future grid and c) how these upgrades/new installations will perform over time. The number of small-scale distributed generators, e.g. PV and battery, is now sufficient (and expected to increase) to impact the operation of the grid, which in turn needs to be considered by the distribution network manager when planning for upgrades and/or installations to stay within regulatory limits. Different scenarios can be simulated, with different levels of distributed generation, in-place as well as expected, so that a large number of options can be assessed (Step a). Once the location, sizing and timing of assets upgrade and/or installation are found using optimisation techniques (Step b), it is possible to assess the adequacy of their daily performance using agent-based modelling (Step c). One distinguishing feature of this software is that it is possible to analyse a whole area at once, while still having a tailored solution for each of the sub-areas. To illustrate this, using the impact of battery and PV can have on the two types of networks mentioned above, three design conditions can be identified (amongst others): · Urban conditions o Feeders that have a low take-up of solar generators, may benefit from adding solar panels o Feeders that need voltage support at specific times, may be assisted by installing batteries · Rural conditions - SWER network o Feeders that need voltage support as well as peak lopping may benefit from both battery and solar panel installations. This small example demonstrates that no single solution can be applied across all three areas, and there is a need to be selective in which one is applied to each branch of the network. This is currently the function of the engineer who can define various scenarios against a configuration, test them and iterate towards an appropriate solution. Future work will focus on increasing the level of automation in identifying areas where particular solutions are applicable.

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Electric Energy Storage (EES) is considered as one of the promising options for reducing the need for costly upgrades in distribution networks in Queensland (QLD). However, It is expected, the full potential for storage for distribution upgrade deferral cannot be fully realized due to high cost of EES. On the other hand, EES used for distribution deferral application can support a variety of complementary storage applications such as energy price arbitrage, time of use (TOU) energy cost reduction, wholesale electricity market ancillary services, and transmission upgrade deferral. Aggregation of benefits of these complementary storage applications would have the potential for increasing the amount of EES that may be financially attractive to defer distribution network augmentation in QLD. In this context, this paper analyzes distribution upgrade deferral, energy price arbitrage, TOU energy cost reduction, and integrated solar PV-storage benefits of EES devices in QLD.

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Background Dietary diversity is recognized as a key element of a high quality diet. However, diets that offer a greater variety of energy-dense foods could increase food intake and body weight. The aim of this study was to explore association of diet diversity with obesity in Sri Lankan adults. Methods Six hundred adults aged > 18 years were randomly selected by using multi-stage stratified sample. Dietary intake assessment was undertaken by a 24 hour dietary recall. Three dietary scores, Dietary Diversity Score (DDS), Dietary Diversity Score with Portions (DDSP) and Food Variety Score (FVS) were calculated. Body mass index (BMI) ≥ 25 kg.m-2 is defined as obese and Asian waist circumference cut-offs were used diagnosed abdominal obesity. Results Mean of DDS for men and women were 6.23 and 6.50 (p=0.06), while DDSP was 3.26 and 3.17 respectively (p=0.24). FVS values were significantly different between men and women 9.55 and 10.24 (p=0.002). Dietary diversity among Sri Lankan adults was significantly associated with gender, residency, ethnicity, education level but not with diabetes status. As dietary scores increased, the percentage consumption was increased in most of food groups except starches. Obese and abdominal obese adults had the highest DDS compared to non obese groups (p<0.05). With increased dietary diversity the level of BMI, waist circumference and energy consumption was significantly increased in this population. Conclusion Our data suggests that dietary diversity is positively associated with several socio-demographic characteristics and obesity among Sri Lankan adults. Although high dietary diversity is widely recommended, public health messages should emphasize to improve dietary diversity in selective food items.

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Elaborated Intrusion (EI) Theory proposes that cravings occur when involuntary thoughts about food are elaborated; a key part of elaboration is affectively-charged imagery. Craving can be weakened by working memory tasks that block imagery. EI Theory predicts that cravings should also be reduced by preventing involuntary thoughts being elaborated in the first place. Research has found that imagery techniques such as body scanning and guided imagery can reduce the occurrence of food thoughts. This study tested the prediction that these techniques also reduce craving. We asked participants to abstain from food overnight, and then to carry out 10 min of body scanning, guided imagery, or a control mind wandering task. They rated their craving at 10 points during the task on a single item measure, and before and after the task using the Craving Experience Questionnaire. While craving rose during the task for the mind wandering group, neither the guided imagery nor body scanning group showed an increase. These effects were not detected by the CEQ, suggesting that they are only present during the competing task. As they require no devices or materials and are unobtrusive, brief guided imagery strategies might form useful components of weight loss programmes that attempt to address cravings.

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Food literacy has emerged as a term to describe the everyday practicalities associated with healthy eating. The term is increasingly used in policy, practice, research and by the public; however, there is no shared understanding of its meaning. The purpose of this research was to develop a definition of food literacy which was informed by the identification of its components. This was considered from two perspectives: that of food experts which aimed to reflect the intention of existing policy and investment, and that of individuals, who could be considered experts in the everyday practicalities of food provisioning and consumption. Given that food literacy is likely to be highly contextual, this second study focused on disadvantaged young people living in an urban area who were responsible for feeding themselves. The Expert Study used a Delphi methodology (round one n = 43). The Young People’s Study used semi-structured, life-course interviews (n = 37). Constructivist Grounded Theory was used to analyse results. This included constant comparison of data within and between studies. From this, eleven components of food literacy were identified which fell into the domains of: planning and management; selection; preparation; and eating. These were used to develop a definition for the term “food literacy”.

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A typology of music distribution models is proposed consisting of the ownership model, the access model, and the context model. These models are not substitutes for each other and may co‐exist serving different market niches. The paper argues that increasingly the economic value created from recorded music is based on con‐text rather than on ownership. During this process, access‐based services temporarily generate economic value, but such services are destined to eventually become commoditised.

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Synapses onto dendritic spines in the lateral amygdala formed by afferents from the auditory thalamus represent a site of plasticity in Pavlovian fear conditioning. Previous work has demonstrated that thalamic afferents synapse onto LA spines expressing glutamate receptor (GluR) subunits, but the GluR subunit distribution at the synapse and within the cytoplasm has not been characterized. Therefore, we performed a quantitative analysis for α-amino-3-hydroxy-5-methyl-4-isoxazole propionate (AMPA) receptor subunits GluR2 and GluR3 and N-methyl-D-aspartate (NMDA) receptor subunits NR1 and NR2B by combining anterograde labeling of thalamo-amygdaloid afferents with postembedding immunoelectron microscopy for the GluRs in adult rats. A high percentage of thalamo- amygdaloid spines was immunoreactive for GluR2 (80%), GluR3 (83%), and NR1 (83%), while a smaller proportion of spines expressed NR2B (59%). To compare across the various subunits, the cytoplasmic to synaptic ratios of GluRs were measured within thalamo-amygdaloid spines. Analyses revealed that the cytoplasmic pool of GluR2 receptors was twice as large compared to the GluR3, NR1, and NR2B subunits. Our data also show that in the adult brain, the NR2B subunit is expressed in the majority of in thalamo-amygdaloid spines and that within these spines, the various GluRs are differentially distributed between synaptic and non-synaptic sites. The prevalence of the NR2B subunit in thalamo-amygdaloid spines provides morphological evidence supporting its role in the fear conditioning circuit while the differential distribution of the GluR subtypes may reflect distinct roles for their involvement in this circuitry and synaptic plasticity.

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For a decade, embedded driving assistance systems were mainly dedicated to the management of short time events (lane departure, collision avoidance, collision mitigation). Recently a great number of projects have been focused on cooperative embedded devices in order to extend environment perception. Handling an extended perception range is important in order to provide enough information for both path planning and co-pilot algorithms which need to anticipate events. To carry out such applications, simulation has been widely used. Simulation is efficient to estimate the benefits of Cooperative Systems (CS) based on Inter-Vehicular Communications (IVC). This paper presents a new and modular architecture built with the SiVIC simulator and the RTMaps™ multi-sensors prototyping platform. A set of improvements, implemented in SiVIC, are introduced in order to take into account IVC modelling and vehicles’ control. These 2 aspects have been tuned with on-road measurements to improve the realism of the scenarios. The results obtained from a freeway emergency braking scenario are discussed.

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Food regulations are a series of laws and guidelines that focus on food that can be bought and sold in Australia. This system includes laws and regulations that address, food safety, food handling, what ingredients can go in a food, what a food can be called, what information needs to be included on a label, how a food can be advertised and promoted and developing a food industry that is both economically strong and supports the health of Australia's people and it's environment.

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Contemporary nutrition policies and plans call for focussing efforts to improve nutrition through a closer connection with food and the everyday practicalities of how people live and eat. Various words have been used to articulate what this might mean in practice. More recently, the term “food literacy” has emerged to explain this gap between the policy aims the (in)ability of people to know, understand and use food to meet nutrition recommendations. Despite its increasing use, there is no common understanding of this term or its components. Once established, food literacy could be measured in order to examine its association with nutritional outcomes. A Delphi study of 43 Australian food experts from diverse sectors and settings explored their understanding of the term “food literacy”, the likely components and possible relationship with nutrition. The three round Delphi study began with a semi-structured telephone interview and was followed by two online surveys. Constructivist grounded theory was used to analyse data, from which a conceptual model of the relationship between food literacy and nutrition was developed. The model was then tested and refined following a phenomenological study of 37 young people aged 16-25 years who were responsible for feeding themselves. They were interviewed about their food intake, day-to-day food decision making, the knowledge and skills used and their perceptions of someone who is “good with food”. Analysis from the Delphi study identified, eighty components of food literacy and these were grouped into eight domains: 1)access, 2)planning and management, 3)selection, 4)knowing where food comes from, 5)preparation, 6)eating, 7)nutrition and 8)food related language. When these were compared to results of the Young People’s study it was found that while specific components of food literacy were largely contextual, the importance of all eight domains continued to be relevant. The results of these qualitative studies have set the boundaries and scope of meaning of food literacy and will be used to inform the development of measurable variables to be tested in a quantitative cross-sectional study. This prospective study will examine the relationship between food literacy and nutrition. This research is useful in guiding government strategy and investment, and informing the planning, implementation and evaluation of interventions by practitioners.

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Food literacy” is an emerging term used to describe the relative ability to understand the nature of food and how it is important. It also describes the ability to gather, process, analyse and act upon information about food and to apply it in individual settings. A Delphi study of 43 Australian food experts from diverse sectors and settings in all states and territories explored the meaning of food literacy, its constitutive components and how they relate to nutrition. The three-round Delphi began with a semi-structured telephone interview and was followed by two online surveys. Grounded theory was used to develop a conceptual model of the relationship between food literacy and nutrition. It is proposed that food literacy influences nutrition through three related mechanisms of security, choice and pleasure. These mechanisms will be mediated by the local food supply and individual values. The relative importance of components of food literacy will depend upon these mediators. The level of nutrition outcome being sought (for example, dietary guidelines versus food group serves) will also influence the relative importance of these components. This model will be useful in informing program planning and evaluation and will be tested and refined following a phenomenological study of consumers.

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The growing importance of logistics in increasingly globalised production and consumption systems strengthens the case for explicit consideration of the climate risks that may impact on the operation of ports in the future, as well as the formulation of adaptation responses that act to enhance their resilience. Within a logistics chain, seaports are functional nodes of significant strategic importance, and are considered as critical gateways linking local and national supply chains to global markets. However, they are more likely to be exposed to vagaries of climate-related extreme events due to their coastal locations. As such, they need to be adaptive and respond to the projected impacts of climate change, in particular extreme weather events. These impacts are especially important in the logistics context as they could result in varying degrees of business interruption; including business closure in the worst case scenario. Since trans-shipment of freight for both the import and export of goods and raw materials has a significant impact on Australia’s sustained economic growth it was considered important to undertake a study of port functional assets, to assess their vulnerability to climate change, to model the potential impacts of climate-related extreme events, and to highlight possible adaptation responses.

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The global food system is undergoing unprecedented change. With population increases, demands for food globally will continue to rise at the same time that agricultural environments are compromised through urban encroachment, climate change and environmental degradation. Australia has long identified itself as an agricultural exporting nation—but what will its capacity be in feeding an increasing global population as it also comes to terms with extreme climatic events such as the floods, fires and droughts, and reduced water availability, experienced in recent decades? This chapter traces the history of Australian agricultural exports and evaluates its food production and export capacity against scientific predictions of climate change impacts. With the federal government forecasting declines in the production of wheat, beef, dairy and sugar, Australia’s key export commodities may well be compromised. Calls to produce more food using new technologies are likely to generate significant environmental problems. Yet, a radical reconfiguration of Australian agriculture which incorporates alternative approaches, such as agro-ecology, is rarely considered by government and industry.

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The current view of Australian state and national governments about the effects of climate change on agriculture is that farmers – through the adoption of mitigation and adaptation strategies – will remain resilient, and agricultural production will continue to expand. The assumption is that neoliberalism will provide the best ‘free market’ options for climate change mitigation and adaptation in farming. In contrast, we argue that neoliberalism will increase the move towards productivis (‘high-tech’) agriculture – the very system that has caused major environmental damage to the Australian continent. High-tech farming is highly dependent upon access to water and fossil fuels, both of which would appear to be the main limits to production in future decades. Productivist agriculture is a system highly reliant upon fertilizers and fuels that are derived from the petrochemical industry, and are currently increasing in cost as the price of oil increases.