Methods for Detecting Early Warnings of Critical Transitions in Time Series Illustrated Using Simulated Ecological Data

Many dynamical systems, including lakes, organisms, ocean circulation patterns, or financial markets, are now thought to have tipping points where critical transitions to a contrasting state can happen. Because critical transitions can occur unexpectedly and are difficult to manage, there is a need for methods that can be used to identify when a critical transition is approaching. Recent theory shows that we can identify the proximity of a system to a critical transition using a variety of so-called `early warning signals', and successful empirical examples suggest a potential for practical applicability. However, while the range of proposed methods for predicting critical transitions is rapidly expanding, opinions on their practical use differ widely, and there is no comparative study that tests the limitations of the different methods to identify approaching critical transitions using time-series data. Here, we summarize a range of currently available early warning methods and apply them to two simulated time series that are typical of systems undergoing a critical transition. In addition to a methodological guide, our work offers a practical toolbox that may be used in a wide range of fields to help detect early warning signals of critical transitions in time series data.

Simple and efficient methods for discrimination of chiral diacids and chiral alpha-methyl amines

The three-component chiral derivatization protocols have been developed for H-1, C-13 and F-19 NMR spectroscopic discrimination of chiral diacids by their coordination and self-assembly with optically active (R)-alpha-methylbenzylamine and 2-formylphenylboronic acid or 3-fluoro-2-formylmethylboronic acid. These protocols yield a mixture of diastereomeric imino-boronate esters which are identified by the well-resolved diastereotopic peaks with significant chemical shift differences ranging up to 0.6 and 2.1 ppm in their corresponding H-1 and F-19 NMR spectra, without any racemization or kinetic resolution, thereby enabling the determination of enantiopurity. A protocol has also been developed for discrimination of chiral alpha-methyl amines, using optically pure trans-1,2-cyclohexanedicarboxylic acid in combination with 2-formylphenylboronic acid or 3-fluoro-2-fluoromethylboronic acid. The proposed strategies have been demonstrated on large number of chiral diacids and chiral alpha-methyl amines.

Estimation of heavy rainfall during cyclonic storms from microwave observations using nonlinear approach over Indian Ocean

In this study, an effort has been made to study heavy rainfall events during cyclonic storms over Indian Ocean. This estimate is based on microwave observations from tropical rainfall measuring mission (TRMM) Microwave Imager (TMI). Regional scattering index (SI) developed for Indian region based on measurements at 19-, 21- and 85-GHz brightness temperature and polarization corrected temperature (PCT) at 85 GHz have been utilized in this study. These PCT and SI are collocated against Precipitation Radar (PR) onboard TRMM to establish a relationship between rainfall rate, PCT and SI. The retrieval technique using both linear and nonlinear regressions has been developed utilizing SI, PCT and the combination of SI and PCT. The results have been compared with the observations from PR. It was found that a nonlinear algorithm using combination of SI and PCT is more accurate than linear algorithm or nonlinear algorithm using either SI or PCT. Statistical comparison with PR exhibits the correlation coefficients (CC) of 0.68, 0.66 and 0.70, and root mean square error (RMSE) of 1.78, 1.96 and 1.68 mm/h from the observations of SI, PCT and combination of SI and PCT respectively using linear regressions. When nonlinear regression is used, the CC of 0.73, 0.71, 0.79 and RMSE of 1.64, 1.95, 1.54 mm/h are observed from the observations of SI, PCT and combination of SI and PCT, respectively. The error statistics for high rain events (above 10 mm/h) shows the CC of 0.58, 0.59, 0.60 and RMSE of 5.07, 5.47, 5.03 mm/h from the observations of SI, PCT and combination of SI and PCT, respectively, using linear regression, and on the other hand, use of nonlinear regression yields the CC of 0.66, 0.64, 0.71 and RMSE of 4.68, 5.78 and 4.02 mm/h from the observations of SI, PCT and combined SI and PCT, respectively.

Hydrothermal synthesis of a monoclinic VO2 nanotube-graphene hybrid for use as cathode material in lithium ion batteries

The hydrothermal reaction of a mixture of a colloidal dispersion of graphite oxide and ammonium vanadate yielded a hybrid made of graphene and a nanotubular metastable monoclinic polymorph of VO2, known as VO2(B). The formation of VO2(B) nanotubes is accompanied by the reduction of graphite oxide. Initially the partially scrolled graphite oxide layers act as templates for the crystallization of VO2(B) in the tubular morphology. This is followed by the reduction of graphite oxide to graphene resulting in a hybrid in which VO2(B) nanotubes are dispersed in graphene. Electron microscopic studies of the hybrid reveal that the VO2(B) nanotubes are wrapped by and trapped between graphene sheets. The hybrid shows potential to be a high capacity cathode material for lithium ion batteries. It exhibits a high capacity (similar to 450 mAh/g) and cycling stability. The high capacity of the hybrid is attributed to the interaction between the graphene sheets and the VO2(B) tubes which improves the charge-transfer. The graphene matrix prevents the aggregation of the VO2(B) nanotubes leading to high cycling stability. (C) 2012 Elsevier Ltd. All rights reserved.

Microwave-assisted, surfactant-free synthesis of air-stable copper nanostructures and their SERS study

A simple, rapid, and surfactant-free synthesis of crystalline copper nanostructures has been carried out through microwave irradiation of a solution of copper acetylacetonate in benzyl alcohol. The structures are found to be stable against oxidation in ambient air for several months. High-resolution electron microscopy (SEM and TEM) reveals that the copper samples comprise nanospheres measuring about 150 nm in diameter, each made of copper nanocrystals similar to 7 nm in extension. The nanocrystals are densely packed into spherical aggregates, the driving force being minimization of surface area and surface energy, and are thus immune to oxidation in ambient air. Such aggregates can also be adherently supported on SiO2 and Al2O3 when these substrates are immersed in the irradiated solution. The air-stable copper nanostructures exhibit surface enhanced Raman scattering, as evidenced by the detection of 4-mercaptobenzoic acid at 10(-6) M concentrations.

Ex Situ X-ray Diffraction, X-ray Absorption Near Edge Structure, Electron Spin Resonance, and Transmission Electron Microscopy Study of the Hydrothermal Crystallization of Vanadium Oxide Nanotubes: An Insight into the Mechanism of Formation

The nucleation and growth of vanadium oxide nanotubes (VOx-NT) have been followed by a combination of numerous ex situ techniques. long the hydrothermal process. Intermediate solid phases extracted at different reaction times have been characterized by powder X-ray diffraction, scanning and transmission electron microscopy, electron spin resonance, and V-K edge :X-ray absorption near-edge structure spectroscopy. The supernatant vanadate solutions extracted during the hydrothermal treatment have been studied by liquid V-51 NMR and flame. spectroscopy. For short durations of the hydrothermal synthesis, the initial V2O5-surfactant intercalate. is progressively transformed into VOx-NT whose crystallization starts to be detected after a hydrothermal treatment of 24 h. Upon heating from 24 h to 7 days, VOx-NT are obtained in larger amount and with an improved crystallinity. The detection of soluble amines and cyclic metavanadate V4O12](4-) in the supernatant solution along the hydrothermal process suggests that VOx-NT result from a dissolution precipitation mechanism. Metavanadate species V4O12](4-) could behave as molecular precursors in the polymerization reactions leading to VOx-NT.

Statistical Methods for Accelerated Life Testing with Particular Reference to Resin Impregnated Paper Bushings

Electrical failure of insulation is known to be an extremal random process wherein nominally identical pro-rated specimens of equipment insulation, at constant stress fail at inordinately different times even under laboratory test conditions. In order to be able to estimate the life of power equipment, it is necessary to run long duration ageing experiments under accelerated stresses, to acquire and analyze insulation specific failure data. In the present work, Resin Impregnated Paper (RIP) a relatively new insulation system of choice used in transformer bushings, is taken as an example. The failure data has been processed using proven statistical methods, both graphical and analytical. The physical model governing insulation failure at constant accelerated stress has been assumed to be based on temperature dependent inverse power law model.

Efficient Methods for Robust Classification Under Uncertainty in Kernel Matrices

In this paper we study the problem of designing SVM classifiers when the kernel matrix, K, is affected by uncertainty. Specifically K is modeled as a positive affine combination of given positive semi definite kernels, with the coefficients ranging in a norm-bounded uncertainty set. We treat the problem using the Robust Optimization methodology. This reduces the uncertain SVM problem into a deterministic conic quadratic problem which can be solved in principle by a polynomial time Interior Point (IP) algorithm. However, for large-scale classification problems, IP methods become intractable and one has to resort to first-order gradient type methods. The strategy we use here is to reformulate the robust counterpart of the uncertain SVM problem as a saddle point problem and employ a special gradient scheme which works directly on the convex-concave saddle function. The algorithm is a simplified version of a general scheme due to Juditski and Nemirovski (2011). It achieves an O(1/T-2) reduction of the initial error after T iterations. A comprehensive empirical study on both synthetic data and real-world protein structure data sets show that the proposed formulations achieve the desired robustness, and the saddle point based algorithm outperforms the IP method significantly.

Modified Newton, rank-1 Broyden update and rank-2 BFGS update methods in helicopter trim: A comparative study

Nonlinear equations in mathematical physics and engineering are solved by linearizing the equations and forming various iterative procedures, then executing the numerical simulation. For strongly nonlinear problems, the solution obtained in the iterative process can diverge due to numerical instability. As a result, the application of numerical simulation for strongly nonlinear problems is limited. Helicopter aeroelasticity involves the solution of systems of nonlinear equations in a computationally expensive environment. Reliable solution methods which do not need Jacobian calculation at each iteration are needed for this problem. In this paper, a comparative study is done by incorporating different methods for solving the nonlinear equations in helicopter trim. Three different methods based on calculating the Jacobian at the initial guess are investigated. (C) 2011 Elsevier Masson SAS. All rights reserved.