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Law and Economics


The economic analysis of law (also known as law and economics) is an analysis of law applying methods of economics. Economic concepts are used to explain the effects of laws, to assess which legal rules are economically efficient, and to predict which legal rules will be promulgated.

 
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The Manufacturer and Builder : Volume 0026, Issue 5 May 1894: The ...

By: Western and Company

Description: The Manufacturer and Builder was a practical journal of industrial progress published monthly in the 19th century by Western and Company.

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The North American Review : Volume 0082, Issue 171 April 1856: Nor...

By: University of Northern Iowa

Description:The North American Review is a is a journal of literature and culture, published starting in the 19th century.

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The North American Review : Volume 0090, Issue 186 January 1860: N...

By: University of Northern Iowa

Description:The North American Review is a is a journal of literature and culture, published starting in the 19th century.

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The North American Review : Volume 0091, Issue 188 July 1860: Nort...

By: University of Northern Iowa

Description:The North American Review is a is a journal of literature and culture, published starting in the 19th century.

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The United States Democratic Review : Volume 0024, Issue 127 Janua...

By: J. and H. G. Langley

Description:The United States Magazine and Democratic Review was also (perhaps even primarily) a literary magazine, promoting the development of American literature

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The United States Democratic Review : Volume 0025, Issue 134 Aug 1...

By: J. and H. G. Langley

Description:The United States Magazine and Democratic Review was also (perhaps even primarily) a literary magazine, promoting the development of American literature

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The United States Democratic Review : Volume 0025, Issue 135 Sept ...

By: J. and H. G. Langley

Description:The United States Magazine and Democratic Review was also (perhaps even primarily) a literary magazine, promoting the development of American literature

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Quantifying Population Exposure to Airborne Particulate Matter Dur...

By: M. J. Kleeman; M. Hixson; A. Mahmud

Description: Department of Civil and Environmental Engineering, University of California at Davis, One Shields Ave, Davis CA 95616, USA. The effect of climate change on population-weighted concentrations of particulate matter (PM) during extreme events was studied using the Parallel Climate Model (PCM), the Weather Research and Forecasting (WRF) model and the UCD/CIT 3-D photochemical air quality model. A business as usual (B06.44) global emissions scenario was dynam...

Aw, J. and Kleeman, M. J.: Evaluating the first-order effect of intraannual temperature variability on urban air pollution, J. Geophys. Res., 108, D12, doi:10.1029/2002JD002688, 2003.; Brabson, B. B. and Palutikof, J. P.: Tests of the Generalized Pareto Distribution for Predicting Extreme Wind Speeds, J. Appl. Meteorol., 39, 1627–1640, 2000.; Coles, S. G. and Tawn, J. A.: Modelling extreme multivariate events, J. Roy. St...

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How Small is a Small Cloud? : Volume 8, Issue 2 (28/03/2008)

By: G. Feingold; L. A. Remer; L. Oreopoulos; I. Koren; O. Altaratz

Description: Department of Environmental Sciences Weizmann Institute, Rehovot 76100, Israel. The interplay between clouds and aerosols and their contribution to the radiation budget is one of the largest uncertainties of climate change. Most work to date has separated cloudy and cloud-free areas in order to evaluate the individual radiative forcing of aerosols, clouds, and aerosol effects on clouds.

Here we examine the size distribution and the optical pro...

Cahalan, R. F. and Joseph J. H.: Fractal Statistics of Cloud Fields, Mon. Weather Rev., 117, 261–272, 1989.; Feingold, G., Jiang, H. and Harrington, J. Y.: On smoke suppression of clouds in Amazonia, Geophys. Res. Lett., 32(2), L02804, doi:10.1029/2004GL021369, 2005.; Kaufman, Y. J., Smirnov, A., Holben, B. and Dubovik, O.: Baseline maritime aerosol methodology to derive the optical thickness and scattering properties, Geophys Res. Lett., 28, 3251–3254, 2001.; Koren, I. ...

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Semi-autonomous Sounding Selection for Oco-2 : Volume 6, Issue 10 ...

By: C. W. O'Dell; C. Frankenberg; D. Wunch; G. Osterman; L. Mandrake; P. Wennberg

Description: Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA. Many modern instruments generate more data than may be fully processed in a timely manner. For some atmospheric sounders, much of the raw data cannot be processed into meaningful observations due to suboptimal viewing conditions, such as the presence of clouds. Conventional solutions are quick, empirical-threshold filters hand-created by domain experts to weed out unlikely...

Boesch, H., Backer, D., Connor, B., Crips, D., and Miller, C.: Global Characterization of CO2 Column Retrievals from Shortwave-Infrared Satellite Observations of thet Orbiting Carbon Observatory-2 Mission, Remote Sens., 3, 270–304, 2011.; Conner, B., Boesch, H., Toon, G., Sen, B., Miller, C., and Crisp, D.: Orbiting Carbon Observatory: Inverse method and prospective error analysis, J. Geophys. Res.-Atmos., 113, D05305,

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Semi-autonomous Sounding Selection for Oco-2 : Volume 6, Issue 3 (...

By: C. Frankenberg; C. W. O'Dell; D. Wunch; G. Osterman; L. Mandrake; P. Wennberg

Description: Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA. Many modern instruments generate more data than may be fully processed in a timely manner. For some atmospheric sounders, much of the raw data cannot be processed into meaningful observations due to suboptimal viewing conditions, such as the presence of clouds. Conventional solutions are quick, empirical-threshold filters hand-created by domain experts to weed out unlikely...

Boesch, H., Backer, D., Connor, B., Crips, D., and Miller, C.: Global Characterization of CO2 Column Retrievals from Shortwave-Infrared Satellite Observations of thet Orbiting Carbon Observatory-2 Mission, Remote Sens., 3, 270–304, 2011.; Crisp, D., Atlas, R. M., Breon, F.-M., Brown, L. R., Burrows, J. P., Ciais, P., Connor, B. J., Doney, S. C., Fung, I. Y., Jacob, D. J., Miller, C. E., O'Brien, D., Pawson, S., Randerson, J. T., Rayner, P., Salawitch, R. J., S...

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Feature Selection with Acquisition Cost for Optimizing Sensor Syst...

By: A. Koenig; K. Iswandy

Description: Institute of Integrated Sensor Systems, University of Kaiserslautern, Erwin-Schroedinger-Str., 67663 Kaiserslautern, Germany. Selection of variables from large sets of measurements is a common problem of data analysis and signal processing in many disciplines. In engineering and sensor technology the design of recognition systems can be optimized by judicious choice of subsets of relevant features. In particular, the effort required for signal processing...

Agrafiotis, D K. and Cedeno, W J.: Feature Selection for Structure - Activitiy Correlation Using Binary Particle Swarms, J. Med. Chem., 45, 1098–1107, 2002; Aha, D W.: Feature Weighting for Lazy Learning Algorithms, edited by: Liu and Motoda, Kluwer Acad. Publ., 13–29, 1998.; Goldberg, D E.: Genetic Algorithms in Search, Optimization, and Machine Learning, Addison-Wesley Publishing Comp. Inc., 1989.; Iswandy, K., Koenig, A., Fricke, T., Baumbach, M., and Schuetze, A.: To...

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Modeling and Analysis of Collective Management of Water Resources ...

By: P. Fortemps; P. Van Der Zaag; A. Tilmant

Description: UNESCO-IHE, Department of Management and Institution, Delft, The Netherlands. Integrated Water Resources Management (IWRM) recommends, among other things, that the management of water resources systems be carried out at the lowest appropriate level in order to increase the transparency, acceptability and efficiency of the decision-making process. Empowering water users and stakeholders transforms the decision-making process by enlarging the number of po...

Bellman, R. and Zadeh, L.: Decision-making in a fuzzy environment, Management Sciences, 17, 141–164, 1970.; Beroggi, G.: Decision modeling in policy management - An introduction to the analytic concepts, Kluwer Academic Publisher, Dordrecht, The Netherlands, 1999.; Dinar, A., Rosegrant, M., and Meinzen-Dick, R.: Water allocation mechanisms: Principles and examples, World Bank Technical Paper, 1997.; Choo, E., Schoner, B., and Wedley, W.: Interpretation of criteria weight...

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A Space-time Hybrid Hourly Rainfall Model for Derived Flood Freque...

By: I. Buchwald; A.-d. Ebner Von Eschenbach; U. Haberlandt

Description: Institute of Water Resources Management, Hydrology and Agricultural Hydraulic Engineering, Leibniz University of Hannover, Hannover, Germany. For derived flood frequency analysis based on hydrological modelling long continuous precipitation time series with high temporal resolution are needed. Often, the observation network with recording rainfall gauges is poor, especially regarding the limited length of the available rainfall time series. Stochastic pr...

Aarts, E. and Korst, J.: Simulated Annealing and Boltzmann Machines: A Stochastic Approach to Combinatorial Optimization and Neural Computing, John Wiley, New York, 284 pp., 1989.; Acreman, M. C.: Simple Stochastic Model of Hourly Rainfall for Farnborough, England, Hydrol. Sci. J., 35, 119–148, 1990.; Ahmad, M. I., Sinclair, C. D., and Spurr, B. D.: Assessment of Flood Frequency Models Using Empirical Distribution Function Statistics, Water Resour. Res., 24, 1323–1328, 1...

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Copula-based Downscaling of Spatial Rainfall: a Proof of Concept :...

By: N. E. C. Verhoest; B. De Baets; S. Vandenberghe; M. J. Van Den Berg

Description: Laboratory of Hydrology and Water Management, Ghent University, Coupure links 653, 9000 Ghent, Belgium. Fine-scale rainfall data is important for many hydrological applications. However, often the only data available is at a coarse scale. To bridge this gap in resolution, stochastic disaggregation methods can be used. Such methods generally assume that the distribution of the field is stationary, i.e. the distribution for the entire (fine-scale) field is...

Allcroft, D. and Glasbey, C.: A latent Gaussian Markov random-field model for spatiotemporal rainfall disaggregation, J. R. Stat. Soc. C-App., 52, 487–498, doi:10.1111/1467-9876.00419, 2003.; Burton, A., Kilsby, C. G., Fowler, H. J., Cowpertwait, P. S. P., and Connell, P. E. O.: RainSim : A spatial temporal stochastic rainfall modelling system, Environ. Modell. Softw., 23, 1356–1369,

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Copula-based Statistical Refinement of Precipitation in Rcm Simula...

By: W. Qiu; S. Vogl; H. R. Knoche; P. Laux; H. Kunstmann

Description: Karlsruhe Institute of Technology (KIT), Institute for Meteorology and Climate Research (IMK-IFU), Kreuzeckbahnstrasse 19, 82467 Garmisch-Partenkirchen, Germany. This paper presents a new Copula-based method for further downscaling regional climate simulations. It is developed, applied and evaluated for selected stations in the alpine region of Germany. Apart from the common way to use Copulas to model the extreme values, a strategy is proposed which all...

AghaKouchak, A., Bárdossy, A., and Habib, H.: Copula-based uncertainty modeling: Application to multi-sensor precipitation estimates, Hydrol. Process., 24(15), 2111–2124, doi:10.1002/hyp.7632, 2010a.; AghaKouchak, A., Bárdossy, A., and Habib, H.: Conditional simulation of remotely sensed rainfall data using a non-gaussian v-transformed copula, Adv. Water Resour., 33(6), 624–634,

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Simplifying a Hydrological Ensemble Prediction System with a Backw...

By: F. Anctil; C. Gagné; D. Brochero

Description: Chaire de recherche EDS en prévisions et actions hydrologiques, Department of Civil Engineering and Water Engineering, Université Laval, Québec, G1V 0A6, Canada. An uncertainty cascade model applied to stream flow forecasting seeks to evaluate the different sources of uncertainty of the complex rainfall-runoff process. The current trend focuses on the combination of Meteorological Ensemble Prediction Systems (MEPS) and hydrological model(s). However, the ...

Alpaydin, E.: Introduction to Machine Learning. Adaptive Computation and Machine Learning, 2nd Edn., The MIT Press, Cambridge, 2010.; Beven, K. and Binley, A.: The future of distributed models: Model calibration and uncertainty prediction, Hydrol. Process., 6, 279–298, doi:10.1002/hyp.3360060305, 1992.; Bishop, C. M.: Pattern Recognition and Machine Learning (Information Science and Statistics), ISBN0387310738, Springe...

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Technical Note: the Normal Quantile Transformation and Its Applica...

By: H. L. Cloke; F. Pappenberger; K. Bogner

Description: Institute for Environment and Sustainability, European Commission Joint Research Centre, Via E. Fermi, 2749, 21027 Ispra, VA, Italy. The Normal Quantile Transform (NQT) has been used in many hydrological and meteorological applications in order to make the Cumulated Distribution Function (CDF) of the observed, simulated and forecast river discharge, water level or precipitation data Gaussian. It is also the heart of the meta-Gaussian model for assessing ...

Ailliot, P., Thompson, C., and Thomson, P.: Mixed methods for fitting the GEV distribution, Water Resour. Res., 47, W0551, doi:10.1029/2010WR009417, 2011.; Bartholmes, J. C., Thielen, J., Ramos, M. H., and Gentilini, S.: The european flood alert system EFAS – Part 2: Statistical skill assessment of probabilistic and deterministic operational forecasts, Hydrol. Earth Syst. Sci., 13, 141–153,

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Copula-based Assimilation of Radar and Gauge Information to Derive...

By: W. Qiu; G. Mao; P. Laux; S. Vogl; H. Kunstmann

Description: University of Augsburg, Institute for Geography, Regional Climate and Hydrology, 86135 Augsburg, Germany. This study addresses the problem of combining radar information and gauge measurements. Gauge measurements are the best available source of absolute rainfall intensity albeit their spatial availability is limited. Precipitation information obtained by radar mimics well the spatial patterns but is biased for their absolute values.

In this s...

AghaKouchak, A., Habib, E., and Bárdossy, A.: Modeling Radar Rainfall Estimation Uncertainties: Random Error Model, J. Hydrol. Eng., 15, 265–275, 2010a.; AghaKouchak, A., Bárdossy, A., and Habib, H.: Copula-based uncertainty modeling: Application to multi-sensor precipitation estimates, Hydrol. Process., 24, 2111–2124, doi:10.1002/hyp.7632, 2010b.; AghaKouchak, A., Bárdossy, A., and Habib, H.: Conditional simulation of remot...

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Multiobjective Sensitivity Analysis and Optimization of Distribute...

By: Y. Chen; J. Yang; F. Castelli

Description: State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Xinjiang, 830011, China. Calibration of distributed hydrologic models usually involves how to deal with the large number of distributed parameters and optimization problems with multiple but often conflicting objectives that arise in a natural fashion. This study presents a multiobjective sensitivity and optimization approach to han...

Bekele, E. G. and Nicklow, J. W.: Multi-objective automatic calibration of SWAT using NSGA-II, J. Hydrol., 341, 165–176, 2007; Beven, K. and Binley, A.: The future of distributed models – model calibration and uncertainty prediction, Hydrol. Process., 6, 279–298, 1992.; Blasco, X., Herrero, J. M., Sanchis, J., and Martínez, M.: A new graphical visualization of n-dimensional Pareto front for decision-making in multiobjective optimization, Inform. Sciences, 178, 3908–3924,...

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