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

The NIF LinkOut Broker: A Web Resource to Facilitate Federated Data Integration using NCBI Identifiers

This paper describes the NIF LinkOut Broker (NLB) that has been built as part of the Neuroscience Information Framework (NIF) project. The NLB is designed to coordinate the assembly of links to neuroscience information items (e.g., experimental data, knowledge bases, and software tools) that are (1) accessible via the Web, and (2) related to entries in the National Center for Biotechnology Information’s (NCBI’s) Entrez system. The NLB collects these links from each resource and passes them to the NCBI which incorporates them into its Entrez LinkOut service. In this way, an Entrez user looking at a specific Entrez entry can LinkOut directly to related neuroscience information. The information stored in the NLB can also be utilized in other ways. A second approach, which is operational on a pilot basis, is for the NLB Web server to create dynamically its own Web page of LinkOut links for each NCBI identifier in the NLB database. This approach can allow other resources (in addition to the NCBI Entrez) to LinkOut to related neuroscience information. The paper describes the current NLB system and discusses certain design issues that arose during its implementation

The Electrostatic Instability of a Beam of Charged Particles Penetrating a Plasma

Coordinated Science Laboratory was formerly known as Control Systems LaboratorySignal Corps Contract DA-36-039-SC-8512

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

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

Uncovering current pyroregions in Italy using wildfire metrics

Background: Pyrogeography is a major field of investigation in wildfire science because of its capacity to describe the spatial and temporal variations of fire disturbance. We propose a systematic pyrogeographic analytical approach to cluster regions on the basis of their pyrosimilarities. We employed the Affinity Propagation algorithm to cluster pyroregions using Italian landscape as a test bed and its current wildfire metrics in terms of density, seasonality and stand replacing fire ratio. A discussion follows on how pyrogeography varies according to differences in the human, biophysical, socioeconomic, and climatic spheres. Results: The algorithm identified seven different pyroregion clusters. Two main gradients were identified that partly explain the variability of wildfire metrics observed in the current pyroregions. First, a gradient characterized by increasing temperatures and exposure to droughts, which coincides with a decreasing latitude, and second, a human pressure gradient displaying increasing population density in areas at lower elevation. These drivers exerted a major influence on wildfire density, burnt area over available fuels and stand replacing, which were associated to warm-dry climate and high human pressure. The study statistically highlighted the importance of a North–South gradient, which represents one of the most important drivers of wildfire regimes resulting from the variations in climatic conditions but showing collinearity with socioeconomic aspects as well. Conclusion: Our fully replicable analytical approach can be applied at multiple scales and used for the entire European continent to uncover new and larger pyroregions. This could create a basis for the European Commission to promote innovative and collaborative funding programs between regions that demonstrate pyrosimilarities

Inter-annual and decadal changes in teleconnections drive continental-scale synchronization of tree reproduction

Climate teleconnections drive highly variable and synchronous seed production (masting) over large scales. Disentangling the effect of high-frequency (inter-annual variation) from low-frequency (decadal trends) components of climate oscillations will improve our understanding of masting as an ecosystem process. Using century-long observations on masting (the MASTREE database) and data on the Northern Atlantic Oscillation (NAO), we show that in the last 60 years both high-frequency summer and spring NAO, and low-frequency winter NAO components are highly correlated to continent-wide masting in European beech and Norway spruce. Relationships are weaker (non-stationary) in the early twentieth century. This finding improves our understanding on how climate variation affects large-scale synchronization of tree masting. Moreover, it supports the connection between proximate and ultimate causes of masting: indeed, large-scale features of atmospheric circulation coherently drive cues and resources for masting, as well as its evolutionary drivers, such as pollination efficiency, abundance of seed dispersers, and natural disturbance regimes

The 40s Omega-loop plays a critical role in the stability and the alkaline conformational transition of cytochrome c

The structural and redox properties of a non-covalent complex reconstituted upon mixing two non-contiguous fragments of horse cytochrome c, the residues 1 - 38 heme-containing N-fragment with the residues 57 - 104 C-fragment, have been investigated. With respect to native cyt c, the complex lacks a segment of 18 residues, corresponding, in the native protein, to an omega ( W)loop region. The fragment complex shows compact structure, native-like alpha-helix content but a less rigid atomic packing and reduced stability with respect to the native protein. Structural heterogeneity is observed at pH 7.0, involving formation of an axially misligated low-spin species and consequent partial displacement of Met80 from the sixth coordination position of the heme-iron. Spectroscopic data suggest that a lysine ( located in the Met80-containing loop, namely Lys72, Lys73, or Lys79) replaces the methionine residue. The residues 1 - 38/57 - 104 fragment complex shows an unusual biphasic alkaline titration characterized by a low (pK(a1)= 6.72) and a high pK(a)-associated state transition (pK(a2)= 8.56); this behavior differs from that of native cyt c, which shows a monophasic alkaline transition ( pK(a)= 8.9). The data indicate that the 40s Omega-loop plays an important role in the stability of cyt c and in ensuring a correct alkaline conformational transition of the protein