Comparison of different objective functions for parameterization of simple respiration models

The eddy covariance measurements of carbon dioxide fluxes collected around the world offer a rich source for detailed data analysis. Simple, aggregated models are attractive tools for gap filling, budget calculation, and upscaling in space and time. Key in the application of these models is their parameterization and a robust estimate of the uncertainty and reliability of their predictions. In this study we compared the use of ordinary least squares (OLS) and weighted absolute deviations (WAD, which is the objective function yielding maximum likelihood parameter estimates with a double exponential error distribution) as objective functions within the annual parameterization of two respiration models: the Q10 model and the Lloyd and Taylor model. We introduce a new parameterization method based on two nonparametric tests in which model deviation (Wilcoxon test) and residual trend analyses (Spearman test) are combined. A data set of 9 years of flux measurements was used for this study. The analysis showed that the choice of the objective function is crucial, resulting in differences in the estimated annual respiration budget of up to 40%. The objective function should be tested thoroughly to determine whether it is appropriate for the application for which the model will be used. If simple models are used to estimate a respiration budget, a trend test is essential to achieve unbiased estimates over the year. The analyses also showed that the parameters of the Lloyd and Taylor model are highly correlated and difficult to determine precisely, thereby limiting the physiological interpretability of the parameter

The role of different sliding resistances in limit analysis of hemispherical masonry domes

A limit analysis method for masonry domes composed of interlocking blocks with non-isotropic sliding resistance is under development. This paper reports the first two steps of that work. It first introduces a revision to an existing limit analysis approach using the membrane theory with finite hoop stresses to find the minimum thickness of a hemispherical dome under its own weight and composed of conventional blocks with finite isotropic friction. The coordinates of an initial axisymmetric membrane surface are the optimization variables. During the optimization, the membrane satisfies the equilibrium conditions and meets the sliding constraints where intersects the block interfaces. The results of the revised procedure are compared to those obtained by other approaches finding the thinnest dome. A heuristic method using convex contact model is then introduced to find the sliding resistance of the corrugated interlocking interfaces. Sliding of such interfaces is constrained by the Coulomb’s friction law and by the shear resistance of the locks keeping the blocks together along two orthogonal directions. The role of these two different sliding resistances is discussed and the heuristic method is applied to the revised limit analysis method

Interpolation of nonstationary high frequency spatial-temporal temperature data

The Atmospheric Radiation Measurement program is a U.S. Department of Energy project that collects meteorological observations at several locations around the world in order to study how weather processes affect global climate change. As one of its initiatives, it operates a set of fixed but irregularly-spaced monitoring facilities in the Southern Great Plains region of the U.S. We describe methods for interpolating temperature records from these fixed facilities to locations at which no observations were made, which can be useful when values are required on a spatial grid. We interpolate by conditionally simulating from a fitted nonstationary Gaussian process model that accounts for the time-varying statistical characteristics of the temperatures, as well as the dependence on solar radiation. The model is fit by maximizing an approximate likelihood, and the conditional simulations result in well-calibrated confidence intervals for the predicted temperatures. We also describe methods for handling spatial-temporal jumps in the data to interpolate a slow-moving cold front.Comment: Published in at http://dx.doi.org/10.1214/13-AOAS633 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Improving machine dynamics via geometry optimization

The central thesis of this paper is that the dynamic performance of machinery can be improved dramatically in certain cases through a systematic and meticulous evolutionary algorithm search through the space of all structural geometries permitted by manufacturing, cost and functional constraints. This is a cheap and elegant approach in scenarios where employing active control elements is impractical for reasons of cost and complexity. From an optimization perspective the challenge lies in the efficient, yet thorough global exploration of the multi-dimensional and multi-modal design spaces often yielded by such problems. Morevoer, the designs are often defined by a mixture of continuous and discrete variables - a task that evolutionary algorithms appear to be ideally suited for. In this article we discuss the specific case of the optimization of crop spraying machinery for improved uniformity of spray deposition, subject to structural weight and manufacturing constraints. Using a mixed variable evolutionary algorithm allowed us to optimize both shape and topology. Through this process we have managed to reduce the maximum roll angle of the sprayer by an order of magnitude , whilst allowing only relatively inexpensive changes to the baseline design. Further (though less dramatic) improvements were shown to be possible when we relaxed the cost constraint. We applied the same approach to the inverse problem of reducing the mass while maintaining an acceptable roll angle - a 2% improvement proved possible in this cas

Rapid, solid-phase based automated analysis of chromatin structure and transcription factor occupancy in living eukaryotic cells

Transcription factors, chromatin components and chromatin modification activities are involved in many diseases including cancer. However, the means by which alterations in these factors influence the epigenotype of specific cell types is poorly understood. One problem that limits progress is that regulatory regions of eukaryotic genes sometimes extend over large regions of DNA. To improve chromatin structure–function analysis over such large regions, we have developed an automated, relatively simple procedure that uses magnetic beads and a capillary sequencer for ligation-mediated-PCR (LM-PCR). We show that the procedure can be used for the rapid examination of chromatin fine-structure, nucleosome positioning as well as changes in transcription factor binding-site occupancy during cellular differentiation