The Experts below are selected from a list of 19773 Experts worldwide ranked by ideXlab platform
Marco A Janssen - One of the best experts on this subject based on the ideXlab platform.
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environmental responsibility and policy in a two country dynamic input output model
Economic Systems Research, 2006Co-Authors: Rutger Hoekstra, Marco A JanssenAbstract:Increased Spatial Dependency of economic activities, as well as Spatial differentiation of production and consumption, has implication for environmental policy. One of the issues that has gained importance is the responsibility for the emissions from products that cross national boundaries during its life cycle. This paper discusses the different ethical views of environmental responsibility. Furthermore, the policy measures that are associated with the different viewpoints on environmentally responsibility are analyzed in a novel dynamic two-country two-sector dynamic input-output model. A numerical example is used to illustrate that an ethically preferable tax, which takes account of environmental damages throughout the lifecycle of the product, is less effective that the current policy of taxing consumers of products. Therefore, we might conclude that policies that are based on ethically superior standpoints may have detrimental distortionary effects in the dynamic setting.
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environmental responsibility and policy in a two country dynamic input output model
Economic Systems Research, 2006Co-Authors: Rutger Hoekstra, Marco A JanssenAbstract:Abstract Increased Spatial Dependency of economic activities, as well as Spatial differentiation of production and consumption, has implications for environmental policy. One of the issues that has gained importance is the responsibility for the emissions from products that cross national boundaries during the environmental policy's lifetime. This paper discusses the different ethical views of environmental responsibility. Furthermore, the policy measures that are associated with the different viewpoints are analyzed in a novel dynamic two-country two-sector dynamic input–output model. A numerical example is modeled to assess taxing schemes that are based on these ethical viewpoints. The results show that a tax on the ‘embodied’ environmental pressure, which is generally viewed as ethically preferable, is less effective that the current policy of taxing consumers of products. Our discussion however shows that these results are very dependent on the model structure and initial parameters that are used. Nev...
Rutger Hoekstra - One of the best experts on this subject based on the ideXlab platform.
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environmental responsibility and policy in a two country dynamic input output model
Economic Systems Research, 2006Co-Authors: Rutger Hoekstra, Marco A JanssenAbstract:Increased Spatial Dependency of economic activities, as well as Spatial differentiation of production and consumption, has implication for environmental policy. One of the issues that has gained importance is the responsibility for the emissions from products that cross national boundaries during its life cycle. This paper discusses the different ethical views of environmental responsibility. Furthermore, the policy measures that are associated with the different viewpoints on environmentally responsibility are analyzed in a novel dynamic two-country two-sector dynamic input-output model. A numerical example is used to illustrate that an ethically preferable tax, which takes account of environmental damages throughout the lifecycle of the product, is less effective that the current policy of taxing consumers of products. Therefore, we might conclude that policies that are based on ethically superior standpoints may have detrimental distortionary effects in the dynamic setting.
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environmental responsibility and policy in a two country dynamic input output model
Economic Systems Research, 2006Co-Authors: Rutger Hoekstra, Marco A JanssenAbstract:Abstract Increased Spatial Dependency of economic activities, as well as Spatial differentiation of production and consumption, has implications for environmental policy. One of the issues that has gained importance is the responsibility for the emissions from products that cross national boundaries during the environmental policy's lifetime. This paper discusses the different ethical views of environmental responsibility. Furthermore, the policy measures that are associated with the different viewpoints are analyzed in a novel dynamic two-country two-sector dynamic input–output model. A numerical example is modeled to assess taxing schemes that are based on these ethical viewpoints. The results show that a tax on the ‘embodied’ environmental pressure, which is generally viewed as ethically preferable, is less effective that the current policy of taxing consumers of products. Our discussion however shows that these results are very dependent on the model structure and initial parameters that are used. Nev...
Zhang C - One of the best experts on this subject based on the ideXlab platform.
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Graph WaveNet for Deep Spatial-Temporal Graph Modeling
'International Joint Conferences on Artificial Intelligence', 2020Co-Authors: Wu Z, Pan S, Long G, Jiang J, Zhang CAbstract:© 2019 International Joint Conferences on Artificial Intelligence. All rights reserved. Spatial-temporal graph modeling is an important task to analyze the Spatial relations and temporal trends of components in a system. Existing approaches mostly capture the Spatial Dependency on a fixed graph structure, assuming that the underlying relation between entities is pre-determined. However, the explicit graph structure (relation) does not necessarily reflect the true Dependency and genuine relation may be missing due to the incomplete connections in the data. Furthermore, existing methods are ineffective to capture the temporal trends as the RNNs or CNNs employed in these methods cannot capture long-range temporal sequences. To overcome these limitations, we propose in this paper a novel graph neural network architecture, Graph WaveNet, for Spatial-temporal graph modeling. By developing a novel adaptive Dependency matrix and learn it through node embedding, our model can precisely capture the hidden Spatial Dependency in the data. With a stacked dilated 1D convolution component whose receptive field grows exponentially as the number of layers increases, Graph WaveNet is able to handle very long sequences. These two components are integrated seamlessly in a unified framework and the whole framework is learned in an end-to-end manner. Experimental results on two public traffic network datasets, METR-LA and PEMS-BAY, demonstrate the superior performance of our algorithm
Christian Vernière - One of the best experts on this subject based on the ideXlab platform.
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Deciphering how plant pathogenic bacteria disperse and meet: Molecular epidemiology of Xanthomonas citri pv. citri at microgeographic scales in a tropical area of Asiatic citrus canker endemicity
Evolutionary Applications, 2019Co-Authors: Olivier Pruvost, Karine Boyer, Virginie Ravigné, Damien Richard, Christian VernièreAbstract:Although some plant pathogenic bacteria represent a significant threat to agriculture, the determinants of their ecological success and evolutionary potential are still poorly understood. Refining our understanding of bacterial strain circulation at small Spatial scales and the biological significance and evolutionary consequences of co-infections are key questions. The study of bacterial population biology can be challenging, because it requires high-resolution markers that can be genotyped with a high throughput. Here, we overcame this difficulty for Xanthomonas citri pv. citri, a genetically monomorphic bacterium causing Asiatic citrus canker (ACC). Using a genotyping method that did not require cultivating the bacterium or purifying DNA, we deciphered the pathogen's Spatial genetic structure at several microgeographic scales, down to single lesion, in a situation of ACC endemicity. In a grove where copper was recurrently applied for ACC management, copper-susceptible and copper-resistant X. citri pv. citri coexisted and the bacterial population structured as three genetic clusters, suggesting a polyclonal contamination. The range of Spatial Dependency, estimated for the two largest clusters, was four times greater for the cluster predominantly composed of copper-resistant bacteria. Consistently, the evenness value calculated for this cluster was indicative of increased transmission. Linkage disequilibrium was high even at a tree scale, probably due to a combination of clonality and admixture. Approximately 1% of samples exhibited within-lesion multilocus polymorphism, explained at least in part by polyclonal infections. Canker lesions, which are of major biological significance as an inoculum source, may also represent a preferred niche for horizontal gene transfer. This study points out the potential of genotyping data for estimating the range of Spatial Dependency of plant bacterial pathogens, an important parameter for guiding disease management strategies.
Leta F Huntsinger - One of the best experts on this subject based on the ideXlab platform.
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improving the prediction of annual average daily traffic for nonfreeway facilities by applying a Spatial statistical method
Transportation Research Record, 2006Co-Authors: Man Sik Park, Leta F HuntsingerAbstract:Annual average daily traffic (AADT) data are important for various transportation research areas, including travel model calibration and validation, pavement design, roadway design, and air quality compliance. Specifically for model calibration and validation in long-range transportation planning, a base-year model requires numerous count locations across the study region. Sometimes count data for the lower classified roadways are not readily available. Detailed models require traffic counts for not only higher classifications of roadways such as freeways and arterials but also collector and, in some instances, local roadways. To predict AADT better for desired count locations on nonfreeway facilities, Spatial Dependency is considered. The theory behind the use of Spatial Dependency is that the traffic volume at one monitoring station is correlated with the volumes at neighboring stations. The Spatial regression model takes into account both Spatial trend (mean) and Spatial correlation, which is modeled by a geostatistical approach called kriging. The Spatial regression model is applied to AADT in Wake County, North Carolina. Results indicate that the overall predictive capability of the Spatial regression model is much better than that of the ordinary regression model. In addition, the urban area has more reliable prediction than the rural area. Finally, the Spatial regression model is expected to provide better predictions for desired count locations where no observed data currently exists due to budget limitations.