Adaptive Mesh Refinement (AMR) is a highly effective computation method for simulations that span a large range of spatiotemporal scales, such as astrophysical simulations, which must accommodate ranges from interstellar to sub-planetary. Most mainstream visualization tools still lack support for AMR grids as a first class data type and AMR code teams use custom built applications for AMR visua...

A new method is presented to compute age estimates from theoretical isochrones using temperature, luminosity and metallicity data for individual stars. Based on Bayesian probability theory, this method avoids the systematic biases affecting simpler strategies, and provides reliable estimates of the age probability distribution function for late-type dwarfs. Basic assumptions about the a priori ...

BACKGROUND Antimicrobial resistance (AMR) is a major global public health concern and its surveillance is a fundamental tool for monitoring the development of AMR. In 1998, the Nepalese Ministry of Health (MOH) launched an Infectious Disease (ID) programme. The key components of the programme were to establish a surveillance programme for AMR and to develop awareness among physicians regarding ...

Development of antimicrobial resistance (AMR) threatens our ability to treat common and life threatening infections. Identifying the emergence of AMR requires strengthening of surveillance for AMR, particularly in low and middle-income countries (LMICs) where the burden of infection is highest and health systems are least able to respond. This work aimed, through a combination of desk-based inv...

We explore the basic physical origins of the noncrystalline and crystalline components of the anisotropic magnetoresistance (AMR) in (Ga,Mn)As. The sign of the noncrystalline AMR is found to be determined by the form of spin-orbit coupling in the host band and by the relative strengths of the nonmagnetic and magnetic contributions to the Mn impurity potential. We develop experimental methods yi...

We present a method for generating English sentences from Abstract Meaning Representation (AMR) graphs, exploiting a parallel corpus of AMRs and English sentences. We treat AMR-to-English generation as phrase-based machine translation (PBMT). We introduce a method that learns to linearize tokens of AMR graphs into an English-like order. Our linearization reduces the amount of distortion in PBMT...

Automatic Meter Reading (AMR) is the remote collection of consumption data from customer’s utility meters over telecommunications, radio, power line and other links. AMR provides water, electric and gas utility service companies the opportunity to streamline metering, billing and collection activities, increase operational efficiency and improve customer service. The AMR system consists of thre...

Abstract Meaning Representation (AMR) is a semantic representation language used to capture the meaning of English sentences. In this work, we propose an AMR parser based on dependency parse rewrite rules. This approach transfers dependency parses into AMRs by integrating the syntactic dependencies, semantic arguments, named entity and co-reference information. A dependency parse to AMR graph a...

This paper proposes to tackle the AMR parsing bottleneck by improving two components of an AMR parser: concept identification and alignment. We first build a Bidirectional LSTM based concept identifier that is able to incorporate richer contextual information to learn sparse AMR concept labels. We then extend an HMM-based word-to-concept alignment model with graph distance distortion and a resc...