Recursive Neural Networks Can Learn Logical Semantics

Tree-structured recursive neural networks (TreeRNNs) for sentence meaning have been successful for many applications, but it remains an open question whether the fixed-length representations that they learn can support tasks as demanding as logical deduction. We pursue this question by evaluating whether two such models---plain TreeRNNs and tree-structured neural tensor networks (TreeRNTNs)---can correctly learn to identify logical relationships such as entailment and contradiction using these representations. In our first set of experiments, we generate artificial data from a logical grammar and use it to evaluate the models' ability to learn to handle basic relational reasoning, recursive structures, and quantification. We then evaluate the models on the more natural SICK challenge data. Both models perform competitively on the SICK data and generalize well in all three experiments on simulated data, suggesting that they can learn suitable representations for logical inference in natural language

Examining collusion and voting biases between countries during the Eurovision song contest since 1957

The Eurovision Song Contest (ESC) is an annual event which attracts millions of viewers. It is an interesting activity to examine since the participants of the competition represent a particular country's musical performance that will be awarded a set of scores from other participating countries based upon a quality assessment of a performance. There is a question of whether the countries will vote exclusively according to the artistic merit of the song, or if the vote will be a public signal of national support for another country. Since the competition aims to bring people together, any consistent biases in the awarding of scores would defeat the purpose of the celebration of expression and this has attracted researchers to investigate the supporting evidence for biases. This paper builds upon an approach which produces a set of random samples from an unbiased distribution of score allocation, and extends the methodology to use the full set of years of the competition's life span which has seen fundamental changes to the voting schemes adopted. By building up networks from statistically significant edge sets of vote allocations during a set of years, the results display a plausible network for the origins of the culture anchors for the preferences of the awarded votes. With 60 years of data, the results support the hypothesis of regional collusion and biases arising from proximity, culture and other irrelevant factors in regards to the music which that alone is intended to affect the judgment of the contest.Comment: to be published in JASS

Relativistic magnetohydrodynamics in one dimension

We derive a number of solution for one-dimensional dynamics of relativistic magnetized plasma that can be used as benchmark estimates in relativistic hydrodynamic and magnetohydrodynamic numerical codes. First, we analyze the properties of simple waves of fast modes propagating orthogonally to the magnetic field in relativistically hot plasma. The magnetic and kinetic pressures obey different equations of state, so that the system behaves as a mixture of gases with different polytropic indices. We find the self-similar solutions for the expansion of hot strongly magnetized plasma into vacuum. Second, we derive linear hodograph and Darboux equations for the relativistic Khalatnikov potential, which describe arbitrary one-dimensional isentropic relativistic motion of cold magnetized plasma and find their general and particular solutions. The obtained hodograph and Darboux equations are very powerful: system of highly non-linear, relativistic, time dependent equations describing arbitrary (not necessarily self-similar) dynamics of highly magnetized plasma reduces to a single linear differential equation.Comment: accepted by Phys. Rev.

A large annotated corpus for learning natural language inference

Understanding entailment and contradiction is fundamental to understanding natural language, and inference about entailment and contradiction is a valuable testing ground for the development of semantic representations. However, machine learning research in this area has been dramatically limited by the lack of large-scale resources. To address this, we introduce the Stanford Natural Language Inference corpus, a new, freely available collection of labeled sentence pairs, written by humans doing a novel grounded task based on image captioning. At 570K pairs, it is two orders of magnitude larger than all other resources of its type. This increase in scale allows lexicalized classifiers to outperform some sophisticated existing entailment models, and it allows a neural network-based model to perform competitively on natural language inference benchmarks for the first time.Comment: To appear at EMNLP 2015. The data will be posted shortly before the conference (the week of 14 Sep) at http://nlp.stanford.edu/projects/snli

The pulsar spectral index distribution

The flux density spectra of radio pulsars are known to be steep and, to first order, described by a power-law relationship of the form S_{\nu} \propto \nu^{\alpha}, where S_{\nu} is the flux density at some frequency \nu and \alpha is the spectral index. Although measurements of \alpha have been made over the years for several hundred pulsars, a study of the intrinsic distribution of pulsar spectra has not been carried out. From the result of pulsar surveys carried out at three different radio frequencies, we use population synthesis techniques and a likelihood analysis to deduce what underlying spectral index distribution is required to replicate the results of these surveys. We find that in general the results of the surveys can be modelled by a Gaussian distribution of spectral indices with a mean of -1.4 and unit standard deviation. We also consider the impact of the so-called "Gigahertz-peaked spectrum" pulsars. The fraction of peaked spectrum sources in the population with significant turn-over at low frequencies appears to be at most 10%. We demonstrate that high-frequency (>2 GHz) surveys preferentially select flatter-spectrum pulsars and the converse is true for lower-frequency (<1 GHz) surveys. This implies that any correlations between \alpha and other pulsar parameters (for example age or magnetic field) need to carefully account for selection biases in pulsar surveys. We also expect that many known pulsars which have been detected at high frequencies will have shallow, or positive, spectral indices. The majority of pulsars do not have recorded flux density measurements over a wide frequency range, making it impossible to constrain their spectral shapes. We also suggest that such measurements would allow an improved description of any populations of pulsars with 'non-standard' spectra.Comment: 8 pages, 5 figures. Accepted by MNRA

Beam alignment techniques based on the current multiplication effect in photoconductors First phase technical summary report

Current multiplication effects in cadmium sulfide photoconductive cell

High-Energy theory for close Randall Sundrum branes

We obtain an effective theory for the radion dynamics of the two-brane Randall Sundrum model, correct to all orders in brane velocity in the limit of close separation, which is of interest for studying brane collisions and early Universe cosmology. Obtained via a recursive solution of the Bulk equation of motions, the resulting theory represents a simple extension of the corresponding low-energy effective theory to the high energy regime. The four-dimensional low-energy theory is indeed not valid when corrections at second order in velocity are considered. This extension has the remarkable property of including only second derivatives and powers of first order derivatives. This important feature makes the theory particularly easy to solve. We then extend the theory by introducing a potential and detuning the branes.Comment: Version published in the Physical Review

Micropattern traction microscopy: a technique for the simplification of cellular traction force measurements

Thesis (Ph.D.)--Boston UniversityCells respond to a number of cues that affect how they interact with their surrounding environment, such as topology, the presentation of adhesive ligands, and stiffness. Recent advancements in the field ofmechanobiology have revealed that one of the main ways in which cells sense these cues is through contractile forces. Mechanobiology research seeks to understand how environmental cues affect the forces that cells exert on their surronnding environment and how these mechanical forces are communicated to the cell and transformed into biochemical signals. Therefore, quantitative methods have been developed to determine cell contractility on soft, optically transparent, deformable surfaces by quantifying substrate deformation in terms of cellular traction forces. However, the currently available tools that are used to study cell interactions are limited in their applicability due to the need for specialized technical expertise that is not amenable to the widespread adaptation of these techniques. Therefore, we have sought to develop a novel traction force microscopy technique known as micropattem traction microscopy. With this technique, we hope to greatly simplify the current traction force microscopy techniques and provide a method which will be able to be adopted by a wide range of laboratories. This dissertation describes the process ofthe development and application of this novel traction force technique to probe questions in mechanobiology that have not been previously broached due to the lack of appropriate tools. The technique itself uses indirect microcontact printing to create a regularized array of fluorescent protein onto a glass substrate, which is then transferred to an optically transparent, soft, elastic polyacrylamide hydrogel. Cells, limited by their ability to adhere only to patterned regions, will deform the pattern at these defined points. Thus, with knowledge of the bulk elastic properties ofthe substrate and a priori knowledge of the pattern, we are able to quantify the force a cell is exerting without its removal. We also developed and released a robust, automated MATLAB program that will aid users in the calculation of traction forces so that people with limited experience with programming can utilize the program without significant investments into training. This indirect approach allows for not only individual proteins, but also for multiple, spatially distinct, fluorescent proteins such as fibronectin and gelatin to be simultaneously patterned onto this surface as well. The ability to pattern multiple proteins in a spatially defmed region significantly aids in giving users control over as many parameters as possible. Finally, we will explore the current and future potential that this technique has to offer to researchers in the field of mechanobiology