3,998 research outputs found
Atmospheric water vapor transport: Estimation of continental precipitation recycling and parameterization of a simple climate model
The advective transport of atmospheric water vapor and its role in global hydrology and the water balance of continental regions are discussed and explored. The data set consists of ten years of global wind and humidity observations interpolated onto a regular grid by objective analysis. Atmospheric water vapor fluxes across the boundaries of selected continental regions are displayed graphically. The water vapor flux data are used to investigate the sources of continental precipitation. The total amount of water that precipitates on large continental regions is supplied by two mechanisms: (1) advection from surrounding areas external to the region; and (2) evaporation and transpiration from the land surface recycling of precipitation over the continental area. The degree to which regional precipitation is supplied by recycled moisture is a potentially significant climate feedback mechanism and land surface-atmosphere interaction, which may contribute to the persistence and intensification of droughts. A simplified model of the atmospheric moisture over continents and simultaneous estimates of regional precipitation are employed to estimate, for several large continental regions, the fraction of precipitation that is locally derived. In a separate, but related, study estimates of ocean to land water vapor transport are used to parameterize an existing simple climate model, containing both land and ocean surfaces, that is intended to mimic the dynamics of continental climates
A Realistic Critique of Freedom of Contract in Labor Law Negotiations: Creating More Optimal and Just Outcomes
This Note initially discusses fundamental problems created by the “freedom of contract” principle that arise in an era where the imbalance of both wealth and political power are at their highest rates seen in years. This Note also discusses the principles at work in current labor law: (1) how it is influenced by neoclassical economics and, (2) how, in the alternative, both the related legal doctrine and practice of collective bargaining can improve by incorporating behavioral economics, neuroeconomics, and game theory. Labor law practitioners and shapers should recognize neoclassical economics’ shortcomings and adopt a more efficient contractual process that leads to more just and efficient outcomes
Schur Polynomials and the Yang-Baxter equation
We show that within the six-vertex model there is a parametrized Yang-Baxter
equation with nonabelian parameter group GL(2)xGL(1) at the center of the
disordered regime. As an application we rederive deformations of the Weyl
character formule of Tokuyama and of Hamel and King.Comment: Revised introduction; slightly changed reference
Crystal constructions in Number Theory
Weyl group multiple Dirichlet series and metaplectic Whittaker functions can
be described in terms of crystal graphs. We present crystals as parameterized
by Littelmann patterns and we give a survey of purely combinatorial
constructions of prime power coefficients of Weyl group multiple Dirichlet
series and metaplectic Whittaker functions using the language of crystal
graphs. We explore how the branching structure of crystals manifests in these
constructions, and how it allows access to some intricate objects in number
theory and related open questions using tools of algebraic combinatorics
Non-Gaussian Component Analysis using Entropy Methods
Non-Gaussian component analysis (NGCA) is a problem in multidimensional data
analysis which, since its formulation in 2006, has attracted considerable
attention in statistics and machine learning. In this problem, we have a random
variable in -dimensional Euclidean space. There is an unknown subspace
of the -dimensional Euclidean space such that the orthogonal
projection of onto is standard multidimensional Gaussian and the
orthogonal projection of onto , the orthogonal complement
of , is non-Gaussian, in the sense that all its one-dimensional
marginals are different from the Gaussian in a certain metric defined in terms
of moments. The NGCA problem is to approximate the non-Gaussian subspace
given samples of .
Vectors in correspond to `interesting' directions, whereas
vectors in correspond to the directions where data is very noisy. The
most interesting applications of the NGCA model is for the case when the
magnitude of the noise is comparable to that of the true signal, a setting in
which traditional noise reduction techniques such as PCA don't apply directly.
NGCA is also related to dimension reduction and to other data analysis problems
such as ICA. NGCA-like problems have been studied in statistics for a long time
using techniques such as projection pursuit.
We give an algorithm that takes polynomial time in the dimension and has
an inverse polynomial dependence on the error parameter measuring the angle
distance between the non-Gaussian subspace and the subspace output by the
algorithm. Our algorithm is based on relative entropy as the contrast function
and fits under the projection pursuit framework. The techniques we develop for
analyzing our algorithm maybe of use for other related problems
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