Electric double layer structure close to the three-phase contact line in an electrolyte wetting a solid substrate

The electric double layer structure in an electrolyte close to a solid substrate near the three-phase contact line is approximated by considering the linearized Poisson-Boltzmann equation in a wedge geometry. The mathematical approach complements the semi-analytical solutions reported in the literature by providing easily available characteristic information on the double layer structure. In particular, the model contains a length scale that quantifies the distance from the fluid-fluid interface over which this boundary influences the electric double layer. The analysis is based on an approximation for the equipotential lines. Excellent agreement between the model predictions and numerical results is achieved for a significant range of contact angles. The length scale quantifying the influence of the fluid-fluid interface is proportional to the Debye length and depends on the wall contact angle. It is shown that for contact angles approaching 90{\deg} there is a finite range of boundary influence.Comment: 6 pages, 9 figures; http://link.aps.org/doi/10.1103/PhysRevE.86.02260

Designing dark energy afterglow experiments

Chameleon fields, which are scalar field dark energy candidates, can evade fifth force constraints by becoming massive in high-density regions. However, this property allows chameleon particles to be trapped inside a vacuum chamber with dense walls. Afterglow experiments constrain photon-coupled chameleon fields by attempting to produce and trap chameleon particles inside such a vacuum chamber, from which they will emit an afterglow as they regenerate photons. Here we discuss several theoretical and systematic effects underlying the design and analysis of the GammeV and CHASE afterglow experiments. We consider chameleon particle interactions with photons, Fermions, and other chameleon particles, as well as with macroscopic magnetic fields and matter. The afterglow signal in each experiment is predicted, and its sensitivity to various properties of the experimental apparatus is studied. Finally, we use CHASE data to exclude a wide range of photon-coupled chameleon dark energy models.Comment: 29 pages, 31 figures, 1 tabl

On the anomalous afterglow seen in a chameleon afterglow search

We present data from our investigation of the anomalous orange-colored afterglow that was seen in the GammeV Chameleon Afterglow Search (CHASE). These data includes information about the broad band color of the observed glow, the relationship between the glow and the temperature of the apparatus, and other data taken prior to and during the science operations of CHASE. While differing in several details, the generic properties of the afterglow from CHASE are similar to luminescence seen in some vacuum compounds. Contamination from this, or similar, luminescent signatures will likely impact the design of implementation of future experiments involving single photon detectors and high intensity light sources in a cryogenic environment.Comment: 6 pages, 5 figures, submitted to PR

Surface charge deposition by moving drops reduces contact angles

Slide electrification - the spontaneous charge separation by sliding water drops - can lead to an electrostatic potential of 1 kV and change drop motion substantially. To find out, how slide electrification influences the contact angles of moving drops, we analyzed the dynamic contact angles of aqueous drops sliding down tilted plates with insulated surfaces, grounded surfaces, and while grounding the drop. The observed decrease in dynamic contact angles at different salt concentrations is attributed to two effects: An electrocapillary reduction of contact angles caused by drop charging and a change in the free surface energy of the solid due to surface charging

Resonantly-driven nanopores can serve as nanopumps

Inducing transport in electrolyte-filled nanopores with dc fields has led to influential applications ranging from nanosensors to DNA sequencing. Here we use the Poisson-Nernst-Planck and Navier-Stokes equations to show that unbiased ac fields can induce comparable directional flows in gated conical nanopores. This flow exclusively occurs at intermediate driving frequencies and hinges on the resonance of two competing timescales, representing space charge development at the ends and in the interior of the pore. We summarize the physics of resonant nanopumping in an analytical model that reproduces the results of numerical simulations. Our findings provide a generic route towards real-time controllable flow patterns, which might find applications in controlling the translocation of particles such as small molecules or nanocolloids

NBLAST: Rapid, Sensitive Comparison of Neuronal Structure and Construction of Neuron Family Databases.

Neural circuit mapping is generating datasets of tens of thousands of labeled neurons. New computational tools are needed to search and organize these data. We present NBLAST, a sensitive and rapid algorithm, for measuring pairwise neuronal similarity. NBLAST considers both position and local geometry, decomposing neurons into short segments; matched segments are scored using a probabilistic scoring matrix defined by statistics of matches and non-matches. We validated NBLAST on a published dataset of 16,129 single Drosophila neurons. NBLAST can distinguish neuronal types down to the finest level (single identified neurons) without a priori information. Cluster analysis of extensively studied neuronal classes identified new types and unreported topographical features. Fully automated clustering organized the validation dataset into 1,052 clusters, many of which map onto previously described neuronal types. NBLAST supports additional query types, including searching neurons against transgene expression patterns. Finally, we show that NBLAST is effective with data from other invertebrates and zebrafish. VIDEO ABSTRACT.This work was supported by the Medical Research Council [MRC file reference U105188491] and European Research Council Starting and Consolidator Grants to G.S.X.E.J., who is an EMBO Young Investigator.This is the final version of the article. It first appeared from Cell Press via http://dx.doi.org/10.1016/j.neuron.2016.06.01

Dietary intake and peripheral arterial disease incidence in middle-aged adults: the Atherosclerosis Risk in Communities (ARIC) Study

Background: Peripheral arterial disease (PAD) is a costly source of morbidity and mortality among older persons in the United States. Dietary intake plays a role in the development of atherosclerotic cardiovascular disease; however, few studies have examined the relation of food intake or dietary patterns with PAD

Ask the GRU: Multi-Task Learning for Deep Text Recommendations

In a variety of application domains the content to be recommended to users is associated with text. This includes research papers, movies with associated plot summaries, news articles, blog posts, etc. Recommendation approaches based on latent factor models can be extended naturally to leverage text by employing an explicit mapping from text to factors. This enables recommendations for new, unseen content, and may generalize better, since the factors for all items are produced by a compactly-parametrized model. Previous work has used topic models or averages of word embeddings for this mapping. In this paper we present a method leveraging deep recurrent neural networks to encode the text sequence into a latent vector, specifically gated recurrent units (GRUs) trained end-to-end on the collaborative filtering task. For the task of scientific paper recommendation, this yields models with significantly higher accuracy. In cold-start scenarios, we beat the previous state-of-the-art, all of which ignore word order. Performance is further improved by multi-task learning, where the text encoder network is trained for a combination of content recommendation and item metadata prediction. This regularizes the collaborative filtering model, ameliorating the problem of sparsity of the observed rating matrix.Comment: 8 page