A method for solving moving boundary problems in heat flow Part I: Using cubic splines

A new approach to a heat-flow problem involving a moving boundary makes use of a grid system which moves with the boundary. The necessary interpolations are performed by using cubic splines. The method smooths out irregularities in the motion of the boundary which were evident in previous calculations based on a fixed grid system

A method for solving moving boundary problems in heat flow part ii: Using cubic polynomials

A moving grid system has been used to get the solution of the moving boundary problem discussed earlier in Part I, but basing the necessary interpolations on ordinary cubic polynomials rather than splines. The computations are much more economical and the results obtained are also found to he more satiafactory

Fe and N self-diffusion in non-magnetic Fe:N

Fe and N self-diffusion in non-magnetic FeN has been studied using neutron reflectivity. The isotope labelled multilayers, FeN/57Fe:N and Fe:N/Fe:15N were prepared using magnetron sputtering. It was remarkable to observe that N diffusion was slower compared to Fe while the atomic size of Fe is larger compared to N. An attempt has been made to understand the diffusion of Fe and N in non-magnetic Fe:N

Interpretation of Semantic Tweet Representations

Research in analysis of microblogging platforms is experiencing a renewed surge with a large number of works applying representation learning models for applications like sentiment analysis, semantic textual similarity computation, hashtag prediction, etc. Although the performance of the representation learning models has been better than the traditional baselines for such tasks, little is known about the elementary properties of a tweet encoded within these representations, or why particular representations work better for certain tasks. Our work presented here constitutes the first step in opening the black-box of vector embeddings for tweets. Traditional feature engineering methods for high-level applications have exploited various elementary properties of tweets. We believe that a tweet representation is effective for an application because it meticulously encodes the application-specific elementary properties of tweets. To understand the elementary properties encoded in a tweet representation, we evaluate the representations on the accuracy to which they can model each of those properties such as tweet length, presence of particular words, hashtags, mentions, capitalization, etc. Our systematic extensive study of nine supervised and four unsupervised tweet representations against most popular eight textual and five social elementary properties reveal that Bi-directional LSTMs (BLSTMs) and Skip-Thought Vectors (STV) best encode the textual and social properties of tweets respectively. FastText is the best model for low resource settings, providing very little degradation with reduction in embedding size. Finally, we draw interesting insights by correlating the model performance obtained for elementary property prediction tasks with the highlevel downstream applications.Comment: Accepted at ASONAM 2017; Initial version presented at NIPS 2016 workshop can be found at arXiv:1611.0488

Topological Density and Instantons on a Lattice

We present an update on the study of topological structure of QCD. Issues addressed include a comparison between the plaquette and the geometric methods of calculating the topological density. We show that the improved gauge action based on sqrt(3) blocking transformation suppresses the formation of topologically charged dislocations with low action. Using a cooling method we identify the instantons' location, estimate their size and density, and calculate the renormalization constant Z_Q for the plaquette method.Comment: 3 Pages, submitted to Proceedings of XII International Symposium on Lattice Field Theory (Lattice 94, Bielefeld). uuencoded tar file includes figures as TeXDraw (.tex) file

HI gas in rejuvenated radio galaxies: GMRT observations of the DDRG J1247+6723

We report the detection of HI absorption towards the inner double of the double-double radio galaxy (DDRG) J1247+6723 with the Giant Metrewave Radio Telescope (GMRT). The inner double is a Giga-hertz peaked spectrum (GPS) source with a linear size of 14 pc while the overall size defined by the outer double is 1195 kpc, making it a giant radio source. The absorption profile is well resolved and consists of a number of components on either side of the optical systemic velocity. The neutral hydrogen column density is estimated to be N(HI)=6.73*10^{20}(T_s/100)(f_c/1.0) cm^{-2}, where T_s and f_c are the spin temperature and covering factor of the background source respectively. We explore any correlation between the occurrence of HI absorption and rejuvenation of radio activity and suggest that there could be a strong relationship between them.Comment: 5 pages, 2 figures, accepted for publication in MNRAS Letter