Standing Swells Surveyed Showing Surprisingly Stable Solutions for the Lorenz '96 Model

The Lorenz '96 model is an adjustable dimension system of ODEs exhibiting chaotic behavior representative of dynamics observed in the Earth's atmosphere. In the present study, we characterize statistical properties of the chaotic dynamics while varying the degrees of freedom and the forcing. Tuning the dimensionality of the system, we find regions of parameter space with surprising stability in the form of standing waves traveling amongst the slow oscillators. The boundaries of these stable regions fluctuate regularly with the number of slow oscillators. These results demonstrate hidden order in the Lorenz '96 system, strengthening the evidence for its role as a hallmark representative of nonlinear dynamical behavior.Comment: 10 pages, 8 figure

The Lotic Intersite Nitrogen Experiments: an example of successful ecological research collaboration

Collaboration is an essential skill for modern ecologists because it brings together diverse expertise, viewpoints, and study systems. The Lotic Intersite Nitrogen eXperiments (LINX I and II), a 17-y research endeavor involving scores of early- to late-career stream ecologists, is an example of the benefits, challenges, and approaches of successful collaborative research in ecology. The scientific success of LINX reflected tangible attributes including clear scientific goals (hypothesis-driven research), coordinated research methods, a team of cooperative scientists, excellent leadership, extensive communication, and a philosophy of respect for input from all collaborators. Intangible aspects of the collaboration included camaraderie and strong team chemistry. LINX further benefited from being part of a discipline in which collaboration is a tradition, clear data-sharing and authorship guidelines, an approach that melded field experiments and modeling, and a shared collaborative goal in the form of a universal commitment to see the project and resulting data products through to completion

An Inverse Compton Scattering Origin of X-ray Flares from Sgr A*

The X-ray and near-IR emission from Sgr A* is dominated by flaring, while a quiescent component dominates the emission at radio and sub-mm wavelengths. The spectral energy distribution of the quiescent emission from Sgr A* peaks at sub-mm wavelengths and is modeled as synchrotron radiation from a thermal population of electrons in the accretion flow, with electron temperatures ranging up to $\sim 5-20$\,MeV. Here we investigate the mechanism by which X-ray flare emission is produced through the interaction of the quiescent and flaring components of Sgr A*. The X-ray flare emission has been interpreted as inverse Compton, self-synchrotron-Compton, or synchrotron emission. We present results of simultaneous X-ray and near-IR observations and show evidence that X-ray peak flare emission lags behind near-IR flare emission with a time delay ranging from a few to tens of minutes. Our Inverse Compton scattering modeling places constraints on the electron density and temperature distributions of the accretion flow and on the locations where flares are produced. In the context of this model, the strong X-ray counterparts to near-IR flares arising from the inner disk should show no significant time delay, whereas near-IR flares in the outer disk should show a broadened and delayed X-ray flare.Comment: 22 pages, 6 figures, 2 tables, AJ (in press

Drivers of success in implementing sustainable tourism policies in urban areas

The existing literature in the field of sustainable tourism highlights a number of barriers that impede the implementation of policies in this area. Yet, not many studies have so far considered the factors that would contribute to putting this concept into practice, and few address the case of urban areas. The concept of sustainability has only received limited attention in urban tourism research, even though large cities are recognised as one of the most important tourist destinations that attract vast numbers of visitors. Adopting a case study approach, this paper discusses a number of drivers of success identified by policy-makers in London to contribute to the implementation of sustainable tourisms policies at the local level, and briefly looks at the relationship between these drivers and the constraints perceived by the respondents to hinder the implementation of such policies in practice. These findings may help policy-makers in other large cities to successfully develop and implement policies towards sustainable development of tourism in their area

Geometry of River Networks I: Scaling, Fluctuations, and Deviations

This article is the first in a series of three papers investigating the detailed geometry of river networks. Large-scale river networks mark an important class of two-dimensional branching networks, being not only of intrinsic interest but also a pervasive natural phenomenon. In the description of river network structure, scaling laws are uniformly observed. Reported values of scaling exponents vary suggesting that no unique set of scaling exponents exists. To improve this current understanding of scaling in river networks and to provide a fuller description of branching network structure, we report here a theoretical and empirical study of fluctuations about and deviations from scaling. We examine data for continent-scale river networks such as the Mississippi and the Amazon and draw inspiration from a simple model of directed, random networks. We center our investigations on the scaling of the length of sub-basin's dominant stream with its area, a characterization of basin shape known as Hack's law. We generalize this relationship to a joint probability density and show that fluctuations about scaling are substantial. We find strong deviations from scaling at small scales which can be explained by the existence of linear network structure. At intermediate scales, we find slow drifts in exponent values indicating that scaling is only approximately obeyed and that universality remains indeterminate. At large scales, we observe a breakdown in scaling due to decreasing sample space and correlations with overall basin shape. The extent of approximate scaling is significantly restricted by these deviations and will not be improved by increases in network resolution.Comment: 16 pages, 13 figures, Revtex4, submitted to PR

Positivity of the English language

Over the last million years, human language has emerged and evolved as a fundamental instrument of social communication and semiotic representation. People use language in part to convey emotional information, leading to the central and contingent questions: (1) What is the emotional spectrum of natural language? and (2) Are natural languages neutrally, positively, or negatively biased? Here, we report that the human-perceived positivity of over 10,000 of the most frequently used English words exhibits a clear positive bias. More deeply, we characterize and quantify distributions of word positivity for four large and distinct corpora, demonstrating that their form is broadly invariant with respect to frequency of word use.Comment: Manuscript: 9 pages, 3 tables, 5 figures; Supplementary Information: 12 pages, 3 tables, 8 figure

Happiness and the patterns of life: A study of geolocated tweets

The patterns of life exhibited by large populations have been described and modeled both as a basic science exercise and for a range of applied goals such as reducing automotive congestion, improving disaster response, and even predicting the location of individuals. However, these studies have had limited access to conversation content, rendering changes in expression as a function of movement invisible. In addition, they typically use the communication between a mobile phone and its nearest antenna tower to infer position, limiting the spatial resolution of the data to the geographical region serviced by each cellphone tower. We use a collection of 37 million geolocated tweets to characterize the movement patterns of 180,000 individuals, taking advantage of several orders of magnitude of increased spatial accuracy relative to previous work. Employing the recently developed sentiment analysis instrument known as the hedonometer, we characterize changes in word usage as a function of movement, and find that expressed happiness increases logarithmically with distance from an individual\u27s average location

The Stream Biome Gradient Concept: factors controlling lotic systems across broad biogeographic scales

Citation: Dodds, W. K., Gido, K., Whiles, M. R., Daniels, M. D., & Grudzinski, B. P. (2015). The Stream Biome Gradient Concept: factors controlling lotic systems across broad biogeographic scales. Freshwater Science, 34(1), 1-19. doi:10.1086/679756We propose the Stream Biome Gradient Concept as a way to predict macroscale biological patterns in streams. This concept is based on the hypothesis that many abiotic and biotic features of streams change predictably along climate (temperature and precipitation) gradients because of direct influences of climate on hydrology, geomorphology, and interactions mediated by terrestrial vegetation. The Stream Biome Gradient Concept generates testable hypotheses related to continental variation among streams worldwide and allows aquatic scientists to understand how results from one biome might apply to a less-studied biome. Some predicted factors change monotonically across the biome/climate gradients, whereas others have maxima or minima in the central portion of the gradient. For example, predictions across the gradient from drier deserts through grasslands to wetter forests include more permanent flow, less bare ground, lower erosion and sediment transport rates, decreased importance of autochthonous C inputs to food webs, and greater stream animal species richness. In contrast, effects of large ungulate grazers on streams are expected to be greater in grasslands than in forests or deserts, and fire is expected to have weaker effects in grassland streams than in desert and forest streams along biome gradients with changing precipitation and constant latitude or elevation. Understanding historic patterns among biomes can help describe the evolutionary template at relevant biogeographic scales, can be used to broaden other conceptual models of stream ecology, and could lead to better management and conservation across the broadest scales

An Evolutionary Algorithm Approach to Link Prediction in Dynamic Social Networks

Many real world, complex phenomena have underlying structures of evolving networks where nodes and links are added and removed over time. A central scientific challenge is the description and explanation of network dynamics, with a key test being the prediction of short and long term changes. For the problem of short-term link prediction, existing methods attempt to determine neighborhood metrics that correlate with the appearance of a link in the next observation period. Recent work has suggested that the incorporation of topological features and node attributes can improve link prediction. We provide an approach to predicting future links by applying the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) to optimize weights which are used in a linear combination of sixteen neighborhood and node similarity indices. We examine a large dynamic social network with over $10^6$ nodes (Twitter reciprocal reply networks), both as a test of our general method and as a problem of scientific interest in itself. Our method exhibits fast convergence and high levels of precision for the top twenty predicted links. Based on our findings, we suggest possible factors which may be driving the evolution of Twitter reciprocal reply networks.Comment: 17 pages, 12 figures, 4 tables, Submitted to the Journal of Computational Scienc