A simulation model of time-dependent plasma-spacecraft interactions

A plasma simulation code is presented that models the time-dependent plasma properties in the vicinity of a spherical, charged spacecraft. After showing agreement with analytic, steady-state theories and ATS-6 satellite data, the following three problems are treated: (1) transient pulses from photoemission at various emission temperatures and ambient plasma conditions, (2) spacecharge limited emission, and (3) simulated plasma oscillations in the long wavelength limit

Using Multi-Sense Vector Embeddings for Reverse Dictionaries

Popular word embedding methods such as word2vec and GloVe assign a single vector representation to each word, even if a word has multiple distinct meanings. Multi-sense embeddings instead provide different vectors for each sense of a word. However, they typically cannot serve as a drop-in replacement for conventional single-sense embeddings, because the correct sense vector needs to be selected for each word. In this work, we study the effect of multi-sense embeddings on the task of reverse dictionaries. We propose a technique to easily integrate them into an existing neural network architecture using an attention mechanism. Our experiments demonstrate that large improvements can be obtained when employing multi-sense embeddings both in the input sequence as well as for the target representation. An analysis of the sense distributions and of the learned attention is provided as well

One-degree-of-freedom motion induced by modeled vortex shedding

The motion of an elastically supported cylinder forced by a nonlinear, quasi-static, aerodynamic model with the unusual feature of a motion-dependent forcing frequency was studied. Numerical solutions for the motion and the Lyapunov exponents are presented for three forcing amplitudes and two frequencies (1.0 and 1.1 times the Strouhal frequency). Initially, positive Lyapunov exponents occur and the motion can appear chaotic. After thousands of characteristic times, the motion changes to a motion (verified analytically) that is periodic and damped. This periodic, damped motion was not observed experimentally, thus raising questions concerning the modeling

On some aspects of the noise propagation from supersonic aircraft

The noise problem associated with an aircraft flying at supersonic speeds is shown to depend primarily on the shock wave pattern formed by the aircraft. The noise intensity received by a ground observer from a supersonic aircraft flying at high as well as low altitudes, is shown to be high although it is of a transient nature. Continues

Recycling random numbers in the stochastic simulation algorithm

The stochastic simulation algorithm (SSA) was introduced by Gillespie and in a different form by Kurtz. Since its original formulation there have been several attempts at improving the efficiency and hence the speed of the algorithm. We briefly discuss some of these methods before outlining our own simple improvement, the recycling direct method (RDM), and demonstrating that it is capable of increasing the speed of most stochastic simulations. The RDM involves the statistically acceptable recycling of random numbers in order to reduce the computational cost associated with their generation and is compatible with several of the pre-existing improvements on the original SSA. Our improvement is also sufficiently simple (one additional line of code) that we hope will be adopted by both trained mathematical modelers and experimentalists wishing to simulate their model systems

You Get What You Chat: Using Conversations to Personalize Search-based Recommendations

Prior work on personalized recommendations has focused on exploiting explicit signals from user-specific queries, clicks, likes, and ratings. This paper investigates tapping into a different source of implicit signals of interests and tastes: online chats between users. The paper develops an expressive model and effective methods for personalizing search-based entity recommendations. User models derived from chats augment different methods for re-ranking entity answers for medium-grained queries. The paper presents specific techniques to enhance the user models by capturing domain-specific vocabularies and by entity-based expansion. Experiments are based on a collection of online chats from a controlled user study covering three domains: books, travel, food. We evaluate different configurations and compare chat-based user models against concise user profiles from questionnaires. Overall, these two variants perform on par in terms of NCDG@20, but each has advantages in certain domains

Listening between the Lines: Learning Personal Attributes from Conversations

Open-domain dialogue agents must be able to converse about many topics while incorporating knowledge about the user into the conversation. In this work we address the acquisition of such knowledge, for personalization in downstream Web applications, by extracting personal attributes from conversations. This problem is more challenging than the established task of information extraction from scientific publications or Wikipedia articles, because dialogues often give merely implicit cues about the speaker. We propose methods for inferring personal attributes, such as profession, age or family status, from conversations using deep learning. Specifically, we propose several Hidden Attribute Models, which are neural networks leveraging attention mechanisms and embeddings. Our methods are trained on a per-predicate basis to output rankings of object values for a given subject-predicate combination (e.g., ranking the doctor and nurse professions high when speakers talk about patients, emergency rooms, etc). Experiments with various conversational texts including Reddit discussions, movie scripts and a collection of crowdsourced personal dialogues demonstrate the viability of our methods and their superior performance compared to state-of-the-art baselines

The morphology of Sersic-Pastoriza galaxies

The authors present the preliminary results of their radio-continuum and neutral hydrogen observations of Sersic-Pastoriza (S-P) galaxies. They show that the central regions contain a population of compact features thought to be young supernova remnants (SNRs) and discuss the overall morphology of the nuclei

A five year record of high-frequency in situ measurements of non-methane hydrocarbons at Mace Head, Ireland

Continuous high-frequency in situ measurements of a range of non-methane hydrocarbons have been made at Mace Head since January 2005. Mace Head is a background Northern Hemispheric site situated on the eastern edge of the Atlantic. Five year measurements (2005–2009) of six C<sub>2</sub>–C<sub>5</sub> non-methane hydrocarbons have been separated into baseline Northern Hemispheric and European polluted air masses, among other sectors. Seasonal cycles in baseline Northern Hemispheric air masses and European polluted air masses arriving at Mace Head have been studied. Baseline air masses show a broad summer minima between June and September for shorter lived species, longer lived species show summer minima in July/August. All species displayed a winter maxima in February. European air masses showed baseline elevated mole fractions for all non-methane hydrocarbons. Largest elevations (of up to 360 ppt for ethane maxima) from baseline data were observed in winter maxima, with smaller elevations observed during the summer. Analysis of temporal trends using the Mann-Kendall test showed small (<6 % yr<sup>−1</sup>) but statistically significant decreases in the butanes and <i>i</i>-pentane between 2005 and 2009 in European air. No significant trends were found for any species in baseline air