El Niño-related summer precipitation anomalies in Southeast Asia modulated by the Atlantic multidecadal oscillation

AbstractHow the Atlantic Multidecadal Oscillation (AMO) affects El Niño-related signals in Southeast Asia is investigated in this study on a subseasonal scale. Based on observational and reanalysis data, as well as numerical model simulations, El Niño-related precipitation anomalies are analyzed for AMO positive and negative phases, which reveals a time-dependent modulation of the AMO: (i) In May?June, the AMO influences the precipitation in Southern China (SC) and the Indochina peninsula (ICP) by modulating the El Niño-related air-sea interaction over the western North Pacific (WNP). During negative AMO phases, cold sea surface temperature anomalies (SSTAs) over the WNP favor the maintaining of the WNP anomalous anticyclone (WNPAC). The associated southerly (westerly) anomalies on the northwest (southwest) flank of the WNPAC enhance (reduce) the climatological moisture transport to SC (the ICP) and result in wetter (drier) than normal conditions. In contrast, during positive AMO phases, weak SSTAs over the WNP lead to limited influence of El Niño on precipitation in Southeast Asia. (ii) In July?August, the teleconnection impact from the North Atlantic is more manifest than that in May?June. During positive AMO phases, the warmer than normal North Atlantic favors anomalous wave trains, which propagate along the ?great circle route? and result in positive pressure anomalies over SC, consequently suppressing precipitation in SC and the ICP. During negative AMO phases, the anomalous wave trains tend to propagate eastward from Europe to Northeast Asia along the summer Asian jet, exerting limited influence on Southeast Asia

Modeling two-state cooperativity in protein folding

A protein model with the pairwise interaction energies varying as local environment changes, i.e., including some kinds of collective effect between the contacts, is proposed. Lattice Monte Carlo simulations on the thermodynamical characteristics and free energy profile show a well-defined two-state behavior and cooperativity of folding for such a model. As a comparison, related simulations for the usual G\={o} model, where the interaction energies are independent of the local conformations, are also made. Our results indicate that the evolution of interactions during the folding process plays an important role in the two-state cooperativity in protein folding.Comment: 5 figure

Computing Topological Persistence for Simplicial Maps

Algorithms for persistent homology and zigzag persistent homology are well-studied for persistence modules where homomorphisms are induced by inclusion maps. In this paper, we propose a practical algorithm for computing persistence under $\mathbb{Z}_2$ coefficients for a sequence of general simplicial maps and show how these maps arise naturally in some applications of topological data analysis. First, we observe that it is not hard to simulate simplicial maps by inclusion maps but not necessarily in a monotone direction. This, combined with the known algorithms for zigzag persistence, provides an algorithm for computing the persistence induced by simplicial maps. Our main result is that the above simple minded approach can be improved for a sequence of simplicial maps given in a monotone direction. A simplicial map can be decomposed into a set of elementary inclusions and vertex collapses--two atomic operations that can be supported efficiently with the notion of simplex annotations for computing persistent homology. A consistent annotation through these atomic operations implies the maintenance of a consistent cohomology basis, hence a homology basis by duality. While the idea of maintaining a cohomology basis through an inclusion is not new, maintaining them through a vertex collapse is new, which constitutes an important atomic operation for simulating simplicial maps. Annotations support the vertex collapse in addition to the usual inclusion quite naturally. Finally, we exhibit an application of this new tool in which we approximate the persistence diagram of a filtration of Rips complexes where vertex collapses are used to tame the blow-up in size.Comment: This is the revised and full version of the paper that is going to appear in the Proceedings of 30th Annual Symposium on Computational Geometr

A numerical algorithm for endochronic plasticity and comparison with experiment

A numerical algorithm based on the finite element method of analysis of the boundary value problem in a continuum is presented, in the case where the plastic response of the material is given in the context of endochronic plasticity. The relevant constitutive equation is expressed in incremental form and plastic effects are accounted for by the method of an induced pseudo-force in the matrix equations. The results of the analysis are compared with observed values in the case of a plate with two symmetric notches and loaded longitudinally in its own plane. The agreement between theory and experiment is excellent

Dimension Detection with Local Homology

Detecting the dimension of a hidden manifold from a point sample has become an important problem in the current data-driven era. Indeed, estimating the shape dimension is often the first step in studying the processes or phenomena associated to the data. Among the many dimension detection algorithms proposed in various fields, a few can provide theoretical guarantee on the correctness of the estimated dimension. However, the correctness usually requires certain regularity of the input: the input points are either uniformly randomly sampled in a statistical setting, or they form the so-called $(\varepsilon,\delta)$-sample which can be neither too dense nor too sparse. Here, we propose a purely topological technique to detect dimensions. Our algorithm is provably correct and works under a more relaxed sampling condition: we do not require uniformity, and we also allow Hausdorff noise. Our approach detects dimension by determining local homology. The computation of this topological structure is much less sensitive to the local distribution of points, which leads to the relaxation of the sampling conditions. Furthermore, by leveraging various developments in computational topology, we show that this local homology at a point $z$ can be computed \emph{exactly} for manifolds using Vietoris-Rips complexes whose vertices are confined within a local neighborhood of $z$. We implement our algorithm and demonstrate the accuracy and robustness of our method using both synthetic and real data sets