Evaluation of suitable spectral intervals for near-IR laboratory detection of water vapour continuum absorption

The water vapour continuum absorption is an important component of molecular absorption of radiation in atmosphere. However, uncertainty in knowledge of the value of the continuum absorption at present can achieve 100% in different spectral regions leading to an error in flux calculation up to 3-5 W/m2 global mean. This work uses line-by-line calculations to reveal the best spectral intervals for experimental verification of the CKD water vapour continuum models in the currently least studied near-infrared spectral region. Possible sources of errors in continuum retrieval taken into account in the simulation include the sensitivity of laboratory spectrometers and uncertainties in the spectral line parameters in HITRAN-2004 and Schwenke-Partridge database. It is shown that a number of micro-windows in near-IR can be used at present for laboratory detection of the water vapour continuum with estimated accuracy from 30 to 5%.

Bayes estimates of distance-to-market: Transactions costs, cooperatives and milk-market development in the Ethiopian highlands

Rationalizing non-participation as a resource deficiency in the household, this paper identifies strategies for milk-market development in the Ethiopian highlands. The additional amounts of covariates required for Positive marketable surplus -'distances-to market'-are computed from a model in which production and sales are correlated; sales are left-censored at some Unobserved thresholds production efficiencies are heterogeneous: and the data are in the form of a panel. Incorporating these features into the modeling exercise ant because they are fundamental to the data-generating environment. There are four reasons. First, because production and sales decisions are enacted within the same household, both decisions are affected by the same exogenous shocks, and production and sales are therefore likely to be correlated. Second. because selling, involves time and time is arguably the most important resource available to a subsistence household, the minimum Sales amount is not zero but, rather, some unobserved threshold that lies beyond zero. Third. the Potential existence of heterogeneous abilities in management, ones that lie latent from the econometrician's perspective, suggest that production efficiencies should be permitted to vary across households. Fourth, we observe a single set of households during multiple visits in a single production year. The results convey clearly that institutional and production) innovations alone are insufficient to encourage participation. Market-precipitating innovation requires complementary inputs, especially improvements in human capital and reductions in risk. Copyright (c) 20 08 John Wiley & Sons, Ltd.

Heat kernel smoothing via Laplace-Beltrami eigenfunctions and its application to subcortical structure modeling

We present a new subcortical structure shape modeling framework using heat kernel smoothing constructed with the Laplace-Beltrami eigenfunctions. The cotan discretization is used to numerically obtain the eigenfunctions of the Laplace-Beltrami operator along the surface of subcortical structures of the brain. The eigenfunctions are then used to construct the heat kernel and used in smoothing out measurements noise along the surface. The proposed framework is applied in investigating the influence of age (38-79 years) and gender on amygdala and hippocampus shape. We detected a significant age effect on hippocampus in accordance with the previous studies. In addition, we also detected a significant gender effect on amygdala. Since we did not find any such differences in the traditional volumetric methods, our results demonstrate the benefit of the current framework over traditional volumetric methods.

Sparse shape representation using the Laplace-Beltrami eigenfunctions and its application to modeling subcortical structures

We present a new sparse shape modeling framework on the Laplace-Beltrami (LB) eigenfunctions. Traditionally, the LB-eigenfunctions are used as a basis for intrinsically representing surface shapes by forming a Fourier series expansion. To reduce high frequency noise, only the first few terms are used in the expansion and higher frequency terms are simply thrown away. However, some lower frequency terms may not necessarily contribute significantly in reconstructing the surfaces. Motivated by this idea, we propose to filter out only the significant eigenfunctions by imposing l1-penalty. The new sparse framework can further avoid additional surface-based smoothing often used in the field. The proposed approach is applied in investigating the influence of age (38-79 years) and gender on amygdala and hippocampus shapes in the normal population. In addition, we show how the emotional response is related to the anatomy of the subcortical structures.

Alternating sums of binomial coefficients with unit fraction arithmetic sequence coefficients

Expressions for finite sums involving the binomial coefficients with unit fraction coefficients whose denominators form an arithmetic sequence are determined.

Bootstrapping prediction intervals for autoregressive models

Methods of improving the coverage of Box–Jenkins prediction intervals for linear autoregressive models are explored. These methods use bootstrap techniques to allow for parameter estimation uncertainty and to reduce the small-sample bias in the estimator of the models’ parameters. In addition, we also consider a method of bias-correcting the non-linear functions of the parameter estimates that are used to generate conditional multi-step predictions.