976 resultados para environmental cost


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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

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A PhD Dissertation, presented as part of the requirements for the Degree of Doctor of Philosophy from the NOVA - School of Business and Economics

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This epidemiological investigation examines the impact of several environmental sanitation conditions and hygiene practices on diarrhea occurrence among children under five years of age living in an urban area. The case-control design was employed; 997 cases and 999 controls were included in the investigation. Cases were defined as children with diarrhea and controls were randomly selected among children under five years of age. After logistic regression adjustment, the following variables were found to be significantly associated with diarrhea: washing and purifying fruit and vegetables; presence of wastewater in the street; refuse storage, collection and disposal; domestic water reservoir conditions; feces disposal from swaddles; presence of vectors in the house and flooding in the lot. The estimates of the relative risks reached values up to 2.87. The present study revealed the feasibility of developing and implementing an adequate model to establish intervention priorities in the field of environmental sanitation.

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Cash-in-advance models usually require agents to reallocate money and bonds in fixed periods, every month or quarter, for example. I show that fixed periods underestimate the welfare cost of inflation. I use a model in which agents choose how often they exchange bonds for money. In the benchmark specification, the welfare cost of ten percent instead of zero inflation increases from 0.1 percent of income with fixed periods to one percent with optimal periods. The results are robust to different preferences, to different compositions of income in bonds or money, and to the introduction of capital and labor.

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Dissertação para obtenção do Grau de Doutor em Ambiente

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Nowadays, reducing energy consumption is one of the highest priorities and biggest challenges faced worldwide and in particular in the industrial sector. Given the increasing trend of consumption and the current economical crisis, identifying cost reductions on the most energy-intensive sectors has become one of the main concerns among companies and researchers. Particularly in industrial environments, energy consumption is affected by several factors, namely production factors(e.g. equipments), human (e.g. operators experience), environmental (e.g. temperature), among others, which influence the way of how energy is used across the plant. Therefore, several approaches for identifying consumption causes have been suggested and discussed. However, the existing methods only provide guidelines for energy consumption and have shown difficulties in explaining certain energy consumption patterns due to the lack of structure to incorporate context influence, hence are not able to track down the causes of consumption to a process level, where optimization measures can actually take place. This dissertation proposes a new approach to tackle this issue, by on-line estimation of context-based energy consumption models, which are able to map operating context to consumption patterns. Context identification is performed by regression tree algorithms. Energy consumption estimation is achieved by means of a multi-model architecture using multiple RLS algorithms, locally estimated for each operating context. Lastly, the proposed approach is applied to a real cement plant grinding circuit. Experimental results prove the viability of the overall system, regarding both automatic context identification and energy consumption estimation.

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The aims of this study were to carry out a serological survey of canine leishmaniasis and identify the phlebotomine fauna in the urban area of Bonito, Mato Grosso do Sul. The serological survey was conducted on a sample of 303 dogs, by means of the indirect immunofluorescence test. Phlebotomines were captured using automated light traps. The serological survey found that 30% of the dogs were seropositive, both from the center and from all districts of the town. A total of 2,772 specimens of phlebotomines were caught and the species most found was Lutzomyia longipalpis (90.4%), which corroborated its role as the vector of for canine visceral leishmaniasis in the region. Phlebotomines of the species Bichromomyia flaviscutellata (the main vector for Leishmania (Leishmania) amazonensis) and Nyssomyia whitmani (the vector for Leishmania (Viannia) brasiliensis) were also caught. The findings indicate the need for continuous epidemiological surveillance, with attention towards diminishing the vector breeding sites and the transmission of these diseases in that region.

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The Keystone XL has a big role for transforming Canadian oil to the USA. The function of the pipeline is decreasing the dependency of the American oil industry on other countries and it will help to limit external debt. The proposed pipeline seeks the most suitable route which cannot damage agricultural and natural water recourses such as the Ogallala Aquifer. Using the Geographic Information System (GIS) techniques, the suggested path in this study got extremely high correct results that will help in the future to use the least cost analysis for similar studies. The route analysis contains different weighted overlay surfaces, each, was influenced by various criteria (slope, geology, population and land use). The resulted least cost path routes for each weighted overlay surface were compared with the original proposed pipeline and each displayed surface was more effective than the proposed Keystone XL pipeline.

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The reduction of greenhouse gas emissions is one of the big global challenges for the next decades due to its severe impact on the atmosphere that leads to a change in the climate and other environmental factors. One of the main sources of greenhouse gas is energy consumption, therefore a number of initiatives and calls for awareness and sustainability in energy use are issued among different types of institutional and organizations. The European Council adopted in 2007 energy and climate change objectives for 20% improvement until 2020. All European countries are required to use energy with more efficiency. Several steps could be conducted for energy reduction: understanding the buildings behavior through time, revealing the factors that influence the consumption, applying the right measurement for reduction and sustainability, visualizing the hidden connection between our daily habits impacts on the natural world and promoting to more sustainable life. Researchers have suggested that feedback visualization can effectively encourage conservation with energy reduction rate of 18%. Furthermore, researchers have contributed to the identification process of a set of factors which are very likely to influence consumption. Such as occupancy level, occupants behavior, environmental conditions, building thermal envelope, climate zones, etc. Nowadays, the amount of energy consumption at the university campuses are huge and it needs great effort to meet the reduction requested by European Council as well as the cost reduction. Thus, the present study was performed on the university buildings as a use case to: a. Investigate the most dynamic influence factors on energy consumption in campus; b. Implement prediction model for electricity consumption using different techniques, such as the traditional regression way and the alternative machine learning techniques; and c. Assist energy management by providing a real time energy feedback and visualization in campus for more awareness and better decision making. This methodology is implemented to the use case of University Jaume I (UJI), located in Castellon, Spain.

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Intracellular, vertically transmitted bacteria form complex and intimate relationships with their hosts. Wolbachia, maternally transmitted α- proteobacteria, live within the cells of numerous arthropod species. Wolbachia are famous master manipulators of insect reproduction: to favour their own spread they can induce male killing, parthenogenesis or cytoplasmic incompatibility. Wolbachia can also protect various insects from pathogens, which makes them a promising tool for the control of vector-borne diseases. Mosquitoes with Wolbachia have already been released in the wild to eliminate dengue. Yet, how Wolbachia manipulate their hosts remains largely unknown.(...)

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Cash-in-advance models usually require agents to reallocate money and bonds in fixed periods. Every month or quarter, for example. I show that fixed periods underestimate the welfare cost of inflation. I use a model in which agents choose how often they exchange bonds for money. In the benchmark specification, the welfare cost of 10 percent instead of 0 inflation increases from 0.1 percent of income with fixed periods to 1 percent with optimal periods. The results are robust to different references, to different compositions of income in bonds or money, and to the introduction of capital and labor.

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INTRODUCTION: The aim of the present study was to identify the presence of Leishmania (Leishmania) chagasi infection in dogs in the City of Palmas, Tocantins, Brazil, using the PCR technique to list the hot spots of infected dogs in the city and associate their occurrence to significant environmental changes at capture sites. METHODS: DNA was extracted from blood of dogs, and the PCR were performed with primers RV1/RV2. After screening the population studied, the regions of the city that had the highest occurrence of canine infection were detected. These sites were visited, and ecological parameters denoting anthropogenic disturbance were evaluated. RESULTS: Some important features were listed in the regions visited, such as low urbanization, lack of public collection of sewage, limited garbage collection, vacant lots with tall vegetation, decaying organic matter, and, most importantly, the occurrence of stray dogs and poultry in homes. CONCLUSIONS: The methodology for screening the population was very efficient, especially in evaluating a large number of individuals in a short time, with a high degree of automation. The results indicate an association between the observed parameters and the occurrence of infection in dogs. The model presented in the city is ideal for studies of disease progression and expansion and for the evaluation of control measures adopted for canine VL.

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The objective of this work project is to analyse and discuss the importance of the “Cost to Serve” as a differentiation key factor, by accessing cost to serve customers of a Portuguese subsidiary of a multinational company, which is operating in the sector of fast moving consumer goods (FMCG) – Unilever – Jerónimo Martins (UJM). I will also suggest and quantify key proposals to decrease costs and increase customers’ value. Hence, the scope of this work project is focused on logistics and distribution processes of the company supply chain.