POVERTY AND THE DETERIORATION OF NATURAL SOIL CAPITAL IN THE PERUVIAN ALTIPLANO

The most severe challenges to sustainable development occur where many poor people struggle to eke out a living from marginal lands. In some cases, high human populations on fragile lands have led agricultural productivity to deteriorate (García-Barrios and García-Barrios, 1990, Mink, 1993, Zimmerer, 1993), but likewise intensification in some locales has led to sustainable productivity increases (Boserup, 1965, Tiffen, et al., 1994). These mixed results beg closer inquiry, in order to understand how contrary outcomes can come about. For the context of Peru's chilly high plain surrounding Lake Titicaca, this paper examines changes in the stock of natural capital in agricultural soils, how that came about, and what policy tools might contribute to sustaining this key natural capital stock and the agricultural productivity that it enables.Food Security and Poverty, Land Economics/Use,

Numerical and experimental study of the effects of noise on the permutation entropy

We analyze the effects of noise on the permutation entropy of dynamical systems. We take as numerical examples the logistic map and the R\"ossler system. Upon varying the noise strengthfaster, we find a transition from an almost-deterministic regime, where the permutation entropy grows slower than linearly with the pattern dimension, to a noise-dominated regime, where the permutation entropy grows faster than linearly with the pattern dimension. We perform the same analysis on experimental time-series by considering the stochastic spiking output of a semiconductor laser with optical feedback. Because of the experimental conditions, the dynamics is found to be always in the noise-dominated regime. Nevertheless, the analysis allows to detect regularities of the underlying dynamics. By comparing the results of these three different examples, we discuss the possibility of determining from a time series whether the underlying dynamics is dominated by noise or not

Quadratic Dynamical Decoupling with Non-Uniform Error Suppression

We analyze numerically the performance of the near-optimal quadratic dynamical decoupling (QDD) single-qubit decoherence errors suppression method [J. West et al., Phys. Rev. Lett. 104, 130501 (2010)]. The QDD sequence is formed by nesting two optimal Uhrig dynamical decoupling sequences for two orthogonal axes, comprising N1 and N2 pulses, respectively. Varying these numbers, we study the decoherence suppression properties of QDD directly by isolating the errors associated with each system basis operator present in the system-bath interaction Hamiltonian. Each individual error scales with the lowest order of the Dyson series, therefore immediately yielding the order of decoherence suppression. We show that the error suppression properties of QDD are dependent upon the parities of N1 and N2, and near-optimal performance is achieved for general single-qubit interactions when N1=N2.Comment: 17 pages, 22 figure

Optimized multi-objective design of herringbone micromixers

This paper was presented at the 2nd Micro and Nano Flows Conference (MNF2009), which was held at Brunel University, West London, UK. The conference was organised by Brunel University and supported by the Institution of Mechanical Engineers, IPEM, the Italian Union of Thermofluid dynamics, the Process Intensification Network, HEXAG - the Heat Exchange Action Group and the Institute of Mathematics and its Applications.A design method which systematically integrates Computational Fluids Dynamics (CFD) with an optimization scheme based on the use of the techniques Design of Experiments (DOE), Function Approximation technique (FA) and Multi-Objective Genetic Algorithm (MOGA), has been applied to the shape optimization of the staggered herringbone micromixer (SHM) at different Reynolds numbers. To quantify the mixing intensity in the mixer a Mixing index is defined on the basis of the intensity of segregation of the mass concentration on the outlet section. Four geometric parameters, i.e., aspect ratio of the mixing channel, ratio of groove depth to channel height, ratio of groove width to groove pitch and the asymmetry factor (offset) of groove, are the design variables selected for optimization. The mixing index at the outlet section and the pressure drop in the mixing channel are the performance criteria used as objective functions. The Pareto front with the optimum trade-offs, maximum mixing index with minimum pressure drop, is obtained. Experiments for qualitative and quantitative validation have been implemented.This study is supported by the Dorothy Hodgkin Postgraduate Award (DHPA) of the Engineering and Physical Sciences Research Council (EPSRC) of United Kingdom and Ebara Research Co. Ltd. of Japan

Soft-Pulse Dynamical Decoupling with Markovian Decoherence

We consider the effect of broadband decoherence on the performance of refocusing sequences, having in mind applications of dynamical decoupling in concatenation with quantum error correcting codes as the first stage of coherence protection. Specifically, we construct cumulant expansions of effective decoherence operators for a qubit driven by a pulse of a generic symmetric shape, and for several sequences of $\pi$- and $\pi/2$-pulses. While, in general, the performance of soft pulses in decoupling sequences in the presence of Markovian decoherence is worse than that of the ideal $\delta$-pulses, it can be substantially improved by shaping.Comment: New version contains minor content clarification

Machine learning techniques to select Be star candidates. An application in the OGLE-IV Gaia south ecliptic pole field

Statistical pattern recognition methods have provided competitive solutions for variable star classification at a relatively low computational cost. In order to perform supervised classification, a set of features is proposed and used to train an automatic classification system. Quantities related to the magnitude density of the light curves and their Fourier coefficients have been chosen as features in previous studies. However, some of these features are not robust to the presence of outliers and the calculation of Fourier coefficients is computationally expensive for large data sets. We propose and evaluate the performance of a new robust set of features using supervised classifiers in order to look for new Be star candidates in the OGLE-IV Gaia south ecliptic pole field. We calculated the proposed set of features on six types of variable stars and on a set of Be star candidates reported in the literature. We evaluated the performance of these features using classification trees and random forests along with K-nearest neighbours, support vector machines, and gradient boosted trees methods. We tuned the classifiers with a 10-fold cross-validation and grid search. We validated the performance of the best classifier on a set of OGLE-IV light curves and applied this to find new Be star candidates. The random forest classifier outperformed the others. By using the random forest classifier and colour criteria we found 50 Be star candidates in the direction of the Gaia south ecliptic pole field, four of which have infrared colours consistent with Herbig Ae/Be stars. Supervised methods are very useful in order to obtain preliminary samples of variable stars extracted from large databases. As usual, the stars classified as Be stars candidates must be checked for the colours and spectroscopic characteristics expected for them