Droplets displacement and oscillations induced by ultrasonic surface acoustic waves: a quantitative study

We present an experimental study of a droplet interacting with an ultrasonic surface acoustic wave (SAW). Depending on the amplitude of the wave, the drop can either experience an internal flow with its contact-line pinned, or (at higher amplitude) move along the direction of the wave also with internal flow. Both situations appear together with oscillations of the drop free-surface. The physical origins of the internal mixing flow as well as the drop displacement and surface waves are still not well understood. In order to give insights of the underlying physics involved in these phenomena, we carried out an experimental and numerical study. The results suggest that the surface deformation of the drop can be related as a combination between acoustic streaming effect and radiation pressure inside the drop.Comment: 9 pages, 14 figures. To appear in Physical Review

Conceptual Frameworks for Multimodal Social Signal Processing

This special issue is about a research area which is developing rapidly. Pentland gave it a name which has become widely used, ‘Social Signal Processing’ (SSP for short), and his phrase provides the title of a European project, SSPnet, which has a brief to consolidate the area. The challenge that Pentland highlighted was understanding the nonlinguistic signals that serve as the basis for “subconscious discussions between humans about relationships, resources, risks, and rewards”. He identified it as an area where computational research had made interesting progress, and could usefully make more

A Compositional Deadlock Detector for Android Java

We develop a static deadlock analysis for commercial Android Java applications, of sizes in the tens of millions of LoC, under active development at Facebook. The analysis runs primarily at code-review time, on only the modified code and its dependents; we aim at reporting to developers in under 15 minutes. To detect deadlocks in this setting, we first model the real language as an abstract language with balanced re-entrant locks, nondeterministic iteration and branching, and non-recursive procedure calls. We show that the existence of a deadlock in this abstract language is equivalent to a certain condition over the sets of critical pairs of each program thread; these record, for all possible executions of the thread, which locks are currently held at the point when a fresh lock is acquired. Since the critical pairs of any program thread is finite and computable, the deadlock detection problem for our language is decidable, and in NP. We then leverage these results to develop an open-source implementation of our analysis adapted to deal with real Java code. The core of the implementation is an algorithm which computes critical pairs in a compositional, abstract interpretation style, running in quasi-exponential time. Our analyser is built in the INFER verification framework and has been in industrial deployment for over two years; it has seen over two hundred fixed deadlock reports with a report fix rate of ∼54%

A rescued dataset of sub-daily meteorological observations for Europe and the southern Mediterranean region, 1877–2012

Sub-daily meteorological observations are needed for input to and assessment of high-resolution reanalysis products to improve understanding of weather and climate variability. While there are millions of such weather observations that have been collected by various organisations, many are yet to be transcribed into a useable format. Under the auspices of the Uncertainties in Ensembles of Regional ReAnalyses (UERRA) project, we describe the compilation and development of a digital dataset of 8.8 million meteorological observations of essential climate variables (ECVs) rescued across the European and southern Mediterranean region. By presenting the entire chain of data preparation, from the identification of regions lacking in digitised sub-daily data and the location of original sources, through the digitisation of the observations to the quality control procedures applied, we provide a rescued dataset that is as traceable as possible for use by the research community. Data from 127 stations and of 15 climate variables in the northern African and European sectors have been prepared for the period 1877 to 2012. Quality control of the data using a two-step semi-automatic statistical approach identified 3.5 % of observations that required correction or removal, on par with previous data rescue efforts. In addition to providing a new sub-daily meteorological dataset for the research community, our experience in the development of this sub-daily dataset gives us an opportunity to share some suggestions for future data rescue projects. All versions of the dataset, from the raw digitised data to data that have been quality controlled and converted to standard units, are available on PANGAEA: https://doi.org/10.1594/PANGAEA.886511 (Ashcroft et al., 2018)

Statistics at the tip of a branching random walk and the delay of traveling waves

We study the limiting distribution of particles at the frontier of a branching random walk. The positions of these particles can be viewed as the lowest energies of a directed polymer in a random medium in the mean-field case. We show that the average distances between these leading particles can be computed as the delay of a traveling wave evolving according to the Fisher-KPP front equation. These average distances exhibit universal behaviors, different from those of the probability cascades studied recently in the context of mean field spin-glasses.Comment: 4 pages, 2 figure

Anderson transition on the Cayley tree as a traveling wave critical point for various probability distributions

For Anderson localization on the Cayley tree, we study the statistics of various observables as a function of the disorder strength $W$ and the number $N$ of generations. We first consider the Landauer transmission $T_N$. In the localized phase, its logarithm follows the traveling wave form $\ln T_N \simeq \bar{\ln T_N} + \ln t^*$ where (i) the disorder-averaged value moves linearly $\bar{\ln (T_N)} \simeq - \frac{N}{\xi_{loc}}$ and the localization length diverges as $\xi_{loc} \sim (W-W_c)^{-\nu_{loc}}$ with $\nu_{loc}=1$ (ii) the variable $t^*$ is a fixed random variable with a power-law tail $P^*(t^*) \sim 1/(t^*)^{1+\beta(W)}$ for large $t^*$ with $0<\beta(W) \leq 1/2$, so that all integer moments of $T_N$ are governed by rare events. In the delocalized phase, the transmission $T_N$ remains a finite random variable as $N \to \infty$, and we measure near criticality the essential singularity $\bar{\ln (T)} \sim - | W_c-W |^{-\kappa_T}$ with $\kappa_T \sim 0.25$. We then consider the statistical properties of normalized eigenstates, in particular the entropy and the Inverse Participation Ratios (I.P.R.). In the localized phase, the typical entropy diverges as $(W-W_c)^{- \nu_S}$ with $\nu_S \sim 1.5$, whereas it grows linearly in $N$ in the delocalized phase. Finally for the I.P.R., we explain how closely related variables propagate as traveling waves in the delocalized phase. In conclusion, both the localized phase and the delocalized phase are characterized by the traveling wave propagation of some probability distributions, and the Anderson localization/delocalization transition then corresponds to a traveling/non-traveling critical point. Moreover, our results point towards the existence of several exponents $\nu$ at criticality.Comment: 28 pages, 21 figures, comments welcom

The Universal Gaussian in Soliton Tails

We show that in a large class of equations, solitons formed from generic initial conditions do not have infinitely long exponential tails, but are truncated by a region of Gaussian decay. This phenomenon makes it possible to treat solitons as localized, individual objects. For the case of the KdV equation, we show how the Gaussian decay emerges in the inverse scattering formalism.Comment: 4 pages, 2 figures, revtex with eps

Eddy Current Detection of Nucleation and Early Growth of Semiconductor Crystals

Single crystal CdTe and its solid solution Cd1-x ZnxTe alloys (0.0

Living IoT: A Flying Wireless Platform on Live Insects

Sensor networks with devices capable of moving could enable applications ranging from precision irrigation to environmental sensing. Using mechanical drones to move sensors, however, severely limits operation time since flight time is limited by the energy density of current battery technology. We explore an alternative, biology-based solution: integrate sensing, computing and communication functionalities onto live flying insects to create a mobile IoT platform. Such an approach takes advantage of these tiny, highly efficient biological insects which are ubiquitous in many outdoor ecosystems, to essentially provide mobility for free. Doing so however requires addressing key technical challenges of power, size, weight and self-localization in order for the insects to perform location-dependent sensing operations as they carry our IoT payload through the environment. We develop and deploy our platform on bumblebees which includes backscatter communication, low-power self-localization hardware, sensors, and a power source. We show that our platform is capable of sensing, backscattering data at 1 kbps when the insects are back at the hive, and localizing itself up to distances of 80 m from the access points, all within a total weight budget of 102 mg.Comment: Co-primary authors: Vikram Iyer, Rajalakshmi Nandakumar, Anran Wang, In Proceedings of Mobicom. ACM, New York, NY, USA, 15 pages, 201

How Many Topics? Stability Analysis for Topic Models

Topic modeling refers to the task of discovering the underlying thematic structure in a text corpus, where the output is commonly presented as a report of the top terms appearing in each topic. Despite the diversity of topic modeling algorithms that have been proposed, a common challenge in successfully applying these techniques is the selection of an appropriate number of topics for a given corpus. Choosing too few topics will produce results that are overly broad, while choosing too many will result in the "over-clustering" of a corpus into many small, highly-similar topics. In this paper, we propose a term-centric stability analysis strategy to address this issue, the idea being that a model with an appropriate number of topics will be more robust to perturbations in the data. Using a topic modeling approach based on matrix factorization, evaluations performed on a range of corpora show that this strategy can successfully guide the model selection process.Comment: Improve readability of plots. Add minor clarification