Buoyancy-driven motion of a deformable drop toward a planar wall at low Reynolds number

The slow viscous motion of a deformable drop moving normal to a planar wall is studied numerically. In particular, a boundary integral technique employing the Green's function appropriate to a no-slip planar wall is used. Beginning with spherical drop shapes far from the wall, highly deformed and ‘dimpled’ drop configurations are obtained as the planar wall is approached. The initial stages of dimpling and their evolution provide information and insight into the basic assumptions of film-drainage theory

An implementation of the rothermel fire spread model in the R programming language

This note describes an implementation of the Rothermel fire spread model in the R programming language. The main function, ros(), computes the forward rate of spread at the head of a surface fire according to Rothermel fire behavior model. Additional functions are described to illustrate the potential use and expansions of the package. The function rosunc() carries out uncertainty analysis of fire behavior, that has the ability of generating information-rich, probabilistic predictions, and can be coupled to spatially-explicit fire growth models using an ensemble forecasting technique. The function bestFM() estimates the fit of Standard Fuel Models to observed fire rate of spread, based on absolute bias and root mean square error. Advantages of the R implementation of Rothermel model include: open-source coding, cross-platform availability, high computational efficiency, and linking to other R packages to perform complex analyses on Rothermel fire predictions

Application of vegetation index time series to value fire effect on primary production in a Southern European rare wetland

Fire disturbance is an intrinsic component of the Mediterranean biome playing an important role in ecosystem dynamics and processes. However, frequent and severe anthropogenic wildfires can be detrimental to natural ecosystems, particularly in small natural protected areas, where they may hamper the flow of ecosystem services (ES). While post-fire dynamics of individual ES are heavily context-dependent, the primary productivity of the ecosystem can be regarded as a generic driver of several provisioning and regulating ES, as it represents the amount of energy available to plants for storage, growth, and reproduction, which drives future ecosystem structure and functions. The aim of this study was to evaluate the effect of anthropogenic wildfire on the primary productivity of a rare wetland ecosystem in the Natura 2000 site \u201cTorre Guaceto\u201d in Southern Europe. Productivity was estimated by calculating a 15-year time series of vegetation indices (EVI and NDWI)from remotely sensed MODIS imagery. Our results in terms of PP trends may be relevant to assess the change in ecosystems services provided by wetlands. Interactions between wildfire, ecosystem productivity and climate were then analyzed. During the selected period, climate did not play a significant effect on primary productivity, which was mainly driven by post-fire vegetation recovery. Findings of the present study demonstrate that the wildfire affecting the Natural Protected Area of Torre Guaceto in summer 2007 had a major effect on primary productivity, inducing the regeneration of Phragmites australis and the replacement of old individuals by structurally and functionally better ones

About v-i pinched hysteresis of some non-memristive systems

A special subset of two-terminal elements providing pinched hysteresis loops in the voltage-current plane with the lobe area increasing with the frequency is analysed. These devices are identified as non-memristive systems and the sufficient condition for their hysteresis loop to be pinched at the origin is derived. It turns out that the analysed behaviour can be observed only for just one concrete initial state of the device.This knowledge is conclusive for understanding why such devices cannot be regarded as memristors

Metrics for comparing neuronal tree shapes based on persistent homology

As more and more neuroanatomical data are made available through efforts such as NeuroMorpho.Org and FlyCircuit.org, the need to develop computational tools to facilitate automatic knowledge discovery from such large datasets becomes more urgent. One fundamental question is how best to compare neuron structures, for instance to organize and classify large collection of neurons. We aim to develop a flexible yet powerful framework to support comparison and classification of large collection of neuron structures efficiently. Specifically we propose to use a topological persistence-based feature vectorization framework. Existing methods to vectorize a neuron (i.e, convert a neuron to a feature vector so as to support efficient comparison and/or searching) typically rely on statistics or summaries of morphometric information, such as the average or maximum local torque angle or partition asymmetry. These simple summaries have limited power in encoding global tree structures. Based on the concept of topological persistence recently developed in the field of computational topology, we vectorize each neuron structure into a simple yet informative summary. In particular, each type of information of interest can be represented as a descriptor function defined on the neuron tree, which is then mapped to a simple persistence-signature. Our framework can encode both local and global tree structure, as well as other information of interest (electrophysiological or dynamical measures), by considering multiple descriptor functions on the neuron. The resulting persistence-based signature is potentially more informative than simple statistical summaries (such as average/mean/max) of morphometric quantities-Indeed, we show that using a certain descriptor function will give a persistence-based signature containing strictly more information than the classical Sholl analysis. At the same time, our framework retains the efficiency associated with treating neurons as points in a simple Euclidean feature space, which would be important for constructing efficient searching or indexing structures over them. We present preliminary experimental results to demonstrate the effectiveness of our persistence-based neuronal feature vectorization framework

Human herpesvirus 8-associated primary effusion lymphoma in human immunodeficiency virus-negative patients: a clinico-epidemiologic variant resembling classic Kaposi's sarcoma

No abstract availabl

HHV-8 transmission via saliva to soothe blood-sucking arthropod bites

The British Journal of Cance