915 resultados para Lifetime warranties, Warranty policies, Cost models


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In this dissertation, we apply mathematical programming techniques (i.e., integer programming and polyhedral combinatorics) to develop exact approaches for influence maximization on social networks. We study four combinatorial optimization problems that deal with maximizing influence at minimum cost over a social network. To our knowl- edge, all previous work to date involving influence maximization problems has focused on heuristics and approximation. We start with the following viral marketing problem that has attracted a significant amount of interest from the computer science literature. Given a social network, find a target set of customers to seed with a product. Then, a cascade will be caused by these initial adopters and other people start to adopt this product due to the influence they re- ceive from earlier adopters. The idea is to find the minimum cost that results in the entire network adopting the product. We first study a problem called the Weighted Target Set Selection (WTSS) Prob- lem. In the WTSS problem, the diffusion can take place over as many time periods as needed and a free product is given out to the individuals in the target set. Restricting the number of time periods that the diffusion takes place over to be one, we obtain a problem called the Positive Influence Dominating Set (PIDS) problem. Next, incorporating partial incentives, we consider a problem called the Least Cost Influence Problem (LCIP). The fourth problem studied is the One Time Period Least Cost Influence Problem (1TPLCIP) which is identical to the LCIP except that we restrict the number of time periods that the diffusion takes place over to be one. We apply a common research paradigm to each of these four problems. First, we work on special graphs: trees and cycles. Based on the insights we obtain from special graphs, we develop efficient methods for general graphs. On trees, first, we propose a polynomial time algorithm. More importantly, we present a tight and compact extended formulation. We also project the extended formulation onto the space of the natural vari- ables that gives the polytope on trees. Next, building upon the result for trees---we derive the polytope on cycles for the WTSS problem; as well as a polynomial time algorithm on cycles. This leads to our contribution on general graphs. For the WTSS problem and the LCIP, using the observation that the influence propagation network must be a directed acyclic graph (DAG), the strong formulation for trees can be embedded into a formulation on general graphs. We use this to design and implement a branch-and-cut approach for the WTSS problem and the LCIP. In our computational study, we are able to obtain high quality solutions for random graph instances with up to 10,000 nodes and 20,000 edges (40,000 arcs) within a reasonable amount of time.

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Biogeochemical-Argo is the extension of the Argo array of profiling floats to include floats that are equipped with biogeochemical sensors for pH, oxygen, nitrate, chlorophyll, suspended particles, and downwelling irradiance. Argo is a highly regarded, international program that measures the changing ocean temperature (heat content) and salinity with profiling floats distributed throughout the ocean. Newly developed sensors now allow profiling floats to also observe biogeochemical properties with sufficient accuracy for climate studies. This extension of Argo will enable an observing system that can determine the seasonal to decadal-scale variability in biological productivity, the supply of essential plant nutrients from deep-waters to the sunlit surface layer, ocean acidification, hypoxia, and ocean uptake of CO2. Biogeochemical-Argo will drive a transformative shift in our ability to observe and predict the effects of climate change on ocean metabolism, carbon uptake, and living marine resource management. Presently, vast areas of the open ocean are sampled only once per decade or less, with sampling occurring mainly in summer. Our ability to detect changes in biogeochemical processes that may occur due to the warming and acidification driven by increasing atmospheric CO2, as well as by natural climate variability, is greatly hindered by this undersampling. In close synergy with satellite systems (which are effective at detecting global patterns for a few biogeochemical parameters, but only very close to the sea surface and in the absence of clouds), a global array of biogeochemical sensors would revolutionize our understanding of ocean carbon uptake, productivity, and deoxygenation. The array would reveal the biological, chemical, and physical events that control these processes. Such a system would enable a new generation of global ocean prediction systems in support of carbon cycling, acidification, hypoxia and harmful algal blooms studies, as well as the management of living marine resources. In order to prepare for a global Biogeochemical-Argo array, several prototype profiling float arrays have been developed at the regional scale by various countries and are now operating. Examples include regional arrays in the Southern Ocean (SOCCOM ), the North Atlantic Sub-polar Gyre (remOcean ), the Mediterranean Sea (NAOS ), the Kuroshio region of the North Pacific (INBOX ), and the Indian Ocean (IOBioArgo ). For example, the SOCCOM program is deploying 200 profiling floats with biogeochemical sensors throughout the Southern Ocean, including areas covered seasonally with ice. The resulting data, which are publically available in real time, are being linked with computer models to better understand the role of the Southern Ocean in influencing CO2 uptake, biological productivity, and nutrient supply to distant regions of the world ocean. The success of these regional projects has motivated a planning meeting to discuss the requirements for and applications of a global-scale Biogeochemical-Argo program. The meeting was held 11-13 January 2016 in Villefranche-sur-Mer, France with attendees from eight nations now deploying Argo floats with biogeochemical sensors present to discuss this topic. In preparation, computer simulations and a variety of analyses were conducted to assess the resources required for the transition to a global-scale array. Based on these analyses and simulations, it was concluded that an array of about 1000 biogeochemical profiling floats would provide the needed resolution to greatly improve our understanding of biogeochemical processes and to enable significant improvement in ecosystem models. With an endurance of four years for a Biogeochemical-Argo float, this system would require the procurement and deployment of 250 new floats per year to maintain a 1000 float array. The lifetime cost for a Biogeochemical-Argo float, including capital expense, calibration, data management, and data transmission, is about $100,000. A global Biogeochemical-Argo system would thus cost about $25,000,000 annually. In the present Argo paradigm, the US provides half of the profiling floats in the array, while the EU, Austral/Asia, and Canada share most the remaining half. If this approach is adopted, the US cost for the Biogeochemical-Argo system would be ~$12,500,000 annually and ~$6,250,000 each for the EU, and Austral/Asia and Canada. This includes no direct costs for ship time and presumes that float deployments can be carried out from future research cruises of opportunity, including, for example, the international GO-SHIP program (http://www.go-ship.org). The full-scale implementation of a global Biogeochemical-Argo system with 1000 floats is feasible within a decade. The successful, ongoing pilot projects have provided the foundation and start for such a system.

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We estimate a dynamic model of mortgage default for a cohort of Colombian debtors between 1997 and 2004. We use the estimated model to study the effects on default of a class of policies that affected the evolution of mortgage balances in Colombia during the 1990's. We propose a framework for estimating dynamic behavioral models accounting for the presence of unobserved state variables that are correlated across individuals and across time periods. We extend the standard literature on the structural estimation of dynamic models by incorporating an unobserved common correlated shock that affects all individuals' static payoffs and the dynamic continuation payoffs associated with different decisions. Given a standard parametric specification the dynamic problem, we show that the aggregate shocks are identified from the variation in the observed aggregate behavior. The shocks and their transition are separately identified, provided there is enough cross-sectionavl ariation of the observeds tates.

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European-wide conservation policies are based on the identification of priority habitats. However, research on conservation biogeography often relies on the results and projections of species distribution models to assess species' vulnerability to global change. We assess whether the distribution and structure of threatened communities can be predicted by the suitability of the environmental conditions for their indicator species. We present some preliminary results elucidating if using species distribution models of indicator species at a regional scale is a valid approach to predict these endangered communities. Dune plant assemblages, affected by severe conditions, are excellent models for studying possible interactions among their integrating species and the environment. We use data from an extensive survey of xerophytic inland sand dune scrub communities from Portugal, one of the most threatened habitat types of Europe. We identify indicator shrub species of different types of communities, model their geographical response to the environment, and evaluate whether the output of these niche models are able to predict the distribution of each type of community in a different region.

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Abstract During the last few decades, there has been an increasing international recognition of the studies related to the analysis of the family models change, the focus being the determinants of the female employment and the problems related to the work family balance (Lewis, 2001; Petit & Hook, 2005Saraceno, Crompton & Lyonette, 20062008; Pfau-Effinger, 2012). The majority of these studies have been focused on the analysis of the work-family balance problems as well as the effectiveness of the family and gender policies in order to encourage female employment (Korpi et al., 2013). In Spain, special attention has been given to the family policies implemented, the employability of women and on the role of the father in the family (Flaquer et al., 2015; Meil, 2015); however, there has been far less emphasis on the analysis of the family cultural models (González and Jurado, 2012; Crespi and Moreno, 2016). The purpose of this paper is to present some of the first results on the influence of the socio-demographic factors on the expectations and attitudes about the family models. This study offers an analytical reflection upon the foundation of the determinants of the family ambivalence in Spain from the cultural and the institutional dimension. This study shows the Spanish family models of preferences following the Pfau-Effinger (2004) classification of the famiy living arrangements. The reason for this study is twofold; on the one hand, there is confirmed the scarcity of studies that have focused their attention on this objective in Spain; on the other hand, the studies carried out in the international context have confirmed the analytical effectiveness of researching on the attitude and value changes to explain the meaning and trends of the family changes. There is also presented some preliminary results that have been obtained from the multinomial analysis related to the influence of the socio-demographic factors on the family model chosen by the individuals in Spain (father and mother working full time; mother part-time father full-time; mother not at work father full-time; mother and father part-time). 3 The database used has been the International Social Survey Programme: Family and Changing Gender Roles IV- ISSP 2012-. Spain is the only country of South Europe that has participated in the survey. For this reason it has been considered as a representative case study.

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Firms in China within the same industry but with different ownership and size have very different production functions and can face very different emission regulations and financial conditions. This fact has largely been ignored in most of the existing literature on climate change. Using a newly augmented Chinese input–output table in which information about firm size and ownership are explicitly reported, this paper employs a dynamic computable general equilibrium (CGE) model to analyze the impact of alternative climate policy designs with respect to regulation and financial conditions on heterogeneous firms. The simulation results indicate that with a business-as-usual regulatory structure, the effectiveness and economic efficiency of climate policies is significantly undermined. Expanding regulation to cover additional firms has a first-order effect of improving efficiency. However, over-investment in energy technologies in certain firms may decrease the overall efficiency of investments and dampen long-term economic growth by competing with other fixed-capital investments for financial resources. Therefore, a market-oriented arrangement for sharing emission reduction burden and a mechanism for allocating green investment is crucial for China to achieve a more ambitious emission target in the long run.

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Early water resources modeling efforts were aimed mostly at representing hydrologic processes, but the need for interdisciplinary studies has led to increasing complexity and integration of environmental, social, and economic functions. The gradual shift from merely employing engineering-based simulation models to applying more holistic frameworks is an indicator of promising changes in the traditional paradigm for the application of water resources models, supporting more sustainable management decisions. This dissertation contributes to application of a quantitative-qualitative framework for sustainable water resources management using system dynamics simulation, as well as environmental systems analysis techniques to provide insights for water quality management in the Great Lakes basin. The traditional linear thinking paradigm lacks the mental and organizational framework for sustainable development trajectories, and may lead to quick-fix solutions that fail to address key drivers of water resources problems. To facilitate holistic analysis of water resources systems, systems thinking seeks to understand interactions among the subsystems. System dynamics provides a suitable framework for operationalizing systems thinking and its application to water resources problems by offering useful qualitative tools such as causal loop diagrams (CLD), stock-and-flow diagrams (SFD), and system archetypes. The approach provides a high-level quantitative-qualitative modeling framework for "big-picture" understanding of water resources systems, stakeholder participation, policy analysis, and strategic decision making. While quantitative modeling using extensive computer simulations and optimization is still very important and needed for policy screening, qualitative system dynamics models can improve understanding of general trends and the root causes of problems, and thus promote sustainable water resources decision making. Within the system dynamics framework, a growth and underinvestment (G&U) system archetype governing Lake Allegan's eutrophication problem was hypothesized to explain the system's problematic behavior and identify policy leverage points for mitigation. A system dynamics simulation model was developed to characterize the lake's recovery from its hypereutrophic state and assess a number of proposed total maximum daily load (TMDL) reduction policies, including phosphorus load reductions from point sources (PS) and non-point sources (NPS). It was shown that, for a TMDL plan to be effective, it should be considered a component of a continuous sustainability process, which considers the functionality of dynamic feedback relationships between socio-economic growth, land use change, and environmental conditions. Furthermore, a high-level simulation-optimization framework was developed to guide watershed scale BMP implementation in the Kalamazoo watershed. Agricultural BMPs should be given priority in the watershed in order to facilitate cost-efficient attainment of the Lake Allegan's TP concentration target. However, without adequate support policies, agricultural BMP implementation may adversely affect the agricultural producers. Results from a case study of the Maumee River basin show that coordinated BMP implementation across upstream and downstream watersheds can significantly improve cost efficiency of TP load abatement.

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Michigan depends heavily on fossil fuels to generate electricity. Compared with fossil fuels, electricity generation from renewable energy produces less pollutants emissions. A Renewable Portfolio Standard (RPS) is a mandate that requires electric utilities to generate a certain amount of electricity from renewable energy sources. This thesis applies the Cost-Benefits Analysis (CBA) method to investigate the impacts of implementing a 25% in Michigan by 2025. It is found that a 25% RPS will create about $20.12 billion in net benefits to the State. Moreover, if current tax credit policies will not change until 2025, its net present value will increase to about $26.59 billion. Based on the results of this CBA, a 25% RPS should be approved. The result of future studies on the same issue can be improved if more state specific data become available.

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The reduction of Greenhouse Gases (GHG) plays a central role in the environmental policies considered by countries for implementation not only at its own level but also at supranational levels. This thesis is dedicated to investigate some aspects of two of the most relevant climate change policies. The first part is dedicated to emission permit markets and the second part to optimal carbon taxes. On emission permit markets we explore the strategic behavior of oligopolistic firms operating in polluting industrial sectors that are regulated by cap and trade systems. Our aim is to identify how market power influences the main results obtained under perfect competition assumptions and to understand how actions taken in one market affects the outcome of the other related market. A partial equilibrium model is developed for this purpose with specific abatement cost functions. In Chapter 2 we use the model to explain some of the most relevant literature results. In Chapter 3 the model is used to analyze different oligopolistic structures in the product market under the assumption of competitive permits market. There are two significant findings. Firstly, under the assumption of a Stackelberg oligopoly, firms have no incentives for lobbying in order to manipulate permit prices up, as they have under Cournot competition...

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One particular field of Social Enterprise – WISEs or Work Integration Social Enterprises – has become increasingly recognised as being emblematic of the dynamics of social enterprises and now constitutes a major sphere of their activity globally. From their early roots, focusing on providing productive activity for the blind and those with other physical and/or intellectual disabilities, WISEs are pioneers in promoting the integration of excluded persons through a productive activity. In recent decades, WISEs have incrementally evolved as a tool for implementing national and regional labour market policies. The papers in this special edition explore how populations of WISEs in different country contexts have emerged, and in some instances, shifted in their identities over time in relation to changing national or regional public policies. This special issue is part of the ICSEM project, a worldwide research project aiming to identify, analyze and compare social enterprise models across countries, regions and fields. The special issue features five country specific analyses from the first stage of the ICSEM project where researchers focusing on WISEs examined the policy environment surrounding WISEs and the heterogeneity of the organizational WISE models that have emerged in different contexts: Ireland, the United States, Japan, Austria and Switzerland.

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Background: Oral cancer is a significant public health problem world-wide and exerts high economic, social, psychological, and physical burdens on patients, their families, and on their primary care providers. We set out to describe the changing trends in incidence and survival rates of oral cancer in Ireland between 1994 and 2009. Methods: National data on incident oral cancers [ICD 10 codes C01-C06] were obtained from the National Cancer Registry Ireland from 1994 to 2009. We estimated annual percentage change (APC) in oral cancer incidence during 1994–2009 using joinpoint regression software (version 4.2.0.2). The lifetime risk of oral cancer to age 79 was estimated using Irish incidence and population data from 2007 to 2009. Survival rates were also examined using Kaplan-Meier curves and Cox proportional hazard models to explore the influence of several demographic/lifestyle covariates with follow-up to end 2012. Results: Data were obtained on 2,147 oral cancer incident cases. Men accounted for two-thirds of oral cancer cases (n = 1,430). Annual rates in men decreased significantly during 1994–2001 (APC = -4.8 %, 95 % CI: −8.7 to −0.7) and then increased moderately (APC = 2.3 %, 95 % CI: −0.9 to 5.6). In contrast, annual incidence increased significantly in women throughout the study period (APC = 3.2 %, 95 % CI: 1.9 to 4.6). There was an elevated risk of death among oral cancer patients who were: older than 60 years of age; smokers; unemployed or retired; those living in the most deprived areas; and those whose tumour was sited in the base of the tongue. Being married and diagnosed in more recent years were associated with reduced risk of death. Conclusion: Oral cancer increased significantly in both sexes between 1999 and 2009 in Ireland. Our analyses demonstrate the influence of measured factors such as smoking, time of diagnosis and age on observed trends. Unmeasured factors such as alcohol use, HPV and dietary factors may also be contributing to increased trends. Several of these are modifiable risk factors which are crucial for informing public health policies, and thus more research is needed.

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Incorporation of thymidine analogues in replicating DNA, coupled with antibody and fluorophore staining, allows analysis of cell proliferation, but is currently limited to monolayer cultures, fixed cells and end-point assays. We describe a simple microscopy imaging method for live real-time analysis of cell proliferation, S phase progression over several division cycles, effects of anti-proliferative drugs and other applications. It is based on the prominent (~ 1.7-fold) quenching of fluorescence lifetime of a common cell-permeable nuclear stain, Hoechst 33342 upon the incorporation of 5-bromo-2’-deoxyuridine (BrdU) in genomic DNA and detection by fluorescence lifetime imaging microscopy (FLIM). We show that quantitative and accurate FLIM technique allows high-content, multi-parametric dynamic analyses, far superior to the intensity-based imaging. We demonstrate its uses with monolayer cell cultures, complex 3D tissue models of tumor cell spheroids and intestinal organoids, and in physiological study with metformin treatment.

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Fluvial sediment transport is controlled by hydraulics, sediment properties and arrangement, and flow history across a range of time scales. This physical complexity has led to ambiguous definition of the reference frame (Lagrangian or Eulerian) in which sediment transport is analysed. A general Eulerian-Lagrangian approach accounts for inertial characteristics of particles in a Lagrangian (particle fixed) frame, and for the hydrodynamics in an independent Eulerian frame. The necessary Eulerian-Lagrangian transformations are simplified under the assumption of an ideal Inertial Measurement Unit (IMU), rigidly attached at the centre of the mass of a sediment particle. Real, commercially available IMU sensors can provide high frequency data on accelerations and angular velocities (hence forces and energy) experienced by grains during entrainment and motion, if adequately customized. IMUs are subjected to significant error accu- mulation but they can be used for statistical parametrisation of an Eulerian-Lagrangian model, for coarse sediment particles and over the temporal scale of individual entrainment events. In this thesis an Eulerian-Lagrangian model is introduced and evaluated experimentally. Absolute inertial accelerations were recorded at a 4 Hz frequency from a spherical instrumented particle (111 mm diameter and 2383 kg/m3 density) in a series of entrainment threshold experiments on a fixed idealised bed. The grain-top inertial acceleration entrainment threshold was approximated at 44 and 51 mg for slopes 0.026 and 0.037 respectively. The saddle inertial acceleration entrainment threshold was at 32 and 25 mg for slopes 0.044 and 0.057 respectively. For the evaluation of the complete Eulerian-Lagrangian model two prototype sensors are presented: an idealised (spherical) with a diameter of 90 mm and an ellipsoidal with axes 100, 70 and 30 mm. Both are instrumented with a complete IMU, capable of sampling 3D inertial accelerations and 3D angular velocities at 50 Hz. After signal analysis, the results can be used to parametrize sediment movement but they do not contain positional information. The two sensors (spherical and ellipsoidal) were tested in a series of entrainment experiments, similar to the evaluation of the 111 mm prototype, for a slope of 0.02. The spherical sensor entrained at discharges of 24.8 ± 1.8 l/s while the same threshold for the ellipsoidal sensor was 45.2 ± 2.2 l/s. Kinetic energy calculations were used to quantify the particle-bed energy exchange under fluvial (discharge at 30 l/s) and non-fluvial conditions. All the experiments suggest that the effect of the inertial characteristics of coarse sediments on their motion is comparable to the effect hydrodynamic forces. The coupling of IMU sensors with advanced telemetric systems can lead to the tracking of Lagrangian particle trajectories, at a frequency and accuracy that will permit the testing of diffusion/dispersion models across the range of particle diameters.

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Introducción: El cáncer colorrectal es una patología con alto impacto en la salud pública, debido a su prevalencia, incidencia, severidad, costo e impacto en la salud mental y física del individuo y la familia. Ensayos clínicos realizados en pacientes con antecedente de infarto al miocardio que consumían ácido acetil salicílico (asa), calcio con y sin vitamina D, mostraron asociación entre el consumo de estos medicamentos y disminución en la incidencia en cáncer colorrectal y pólipos adenomatosos. Objetivo: Evaluar la literatura sobre el uso de asa, calcio con y sin vitamina D con relación a su impacto en la prevención del cáncer colorrectal y pólipos adenomatosos. Métodos: Se realizó revisión sistemática buscando ensayos clínicos realizados en pacientes con factores de riesgo para cáncer colorrectal y pólipos adenomatosos que usaron asa, calcio con y sin vitamina D fueron incluidos. Resultados: se escogieron 105 para la revisión sistemática. Conclusiones: Es necesario desarrollar más estudios que lleven a evaluar el efecto protector de la aspirina, calcio y vitamina D. En los artículos revisados la aspirina a dosis de 81 a 325 mg día se correlaciona con reducción de riesgo de aparición de CRC aunque la dosis ideal, el tiempo de inicio y la duración de la ingesta continua no son claros. Hacen falta estudios que comparen poblaciones con ingesta de asa a diferentes dosis.

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Las enfermedades raras o huérfanas corresponden a aquellas con baja prevalencia en la población, y en varios países tienen una definición distinta de acuerdo con el número de pacientes que afectan en la población. La Organización Mundial de la Salud (OMS), las define como un trastorno que afecta de 650 a 1.000 personas por millón de habitantes, de las que se han identificado alrededor de 7.000. En Colombia su prevalencia es menor de 1 por cada 5.000 personas y comprenden: las enfermedades raras, las ultra-huérfanas y las olvidadas. Los pacientes con este tipo de enfermedades imponen retos a los sistemas sanitarios, pues si bien afectan a un bajo porcentaje de la población, su atención implica una alta carga económica por los costos que involucra su atención, la complejidad en su diagnóstico, tratamiento, seguimiento y rehabilitación. El abordaje de las enfermedades raras requiere un manejo interdisciplinar e intersectorial, lo que implica la organización de cada actor del sistema sanitario para su manejo a través de un modelo que abraque las dinámicas posibles entre ellos y las competencias de cada uno. Por lo anterior, y teniendo en cuenta la necesidad de formular políticas sanitarias específicas para la gestión de estas enfermedades, el presente trabajo presenta una aproximación a la formulación de un modelo de gestión para la atención integral de pacientes con enfermedades raras en Colombia. Esta investigación describe los distintos elementos y características de los modelos de gestión clínica y de las enfermedades raras a través de una revisión de literatura, en la que se incluye la descripción de los distintos actores del Sistema de Salud Colombiano, relacionados con la atención integral de estos pacientes para la documentación de un modelo de gestión integral.