Paraphrastic language models

In natural languages multiple word sequences can represent the same underlying meaning. Only modelling the observed surface word sequence can result in poor context coverage, for example, when using n-gram language models (LM). To handle this issue, this paper presents a novel form of language model, the paraphrastic LM. A phrase level transduction model that is statistically learned from standard text data is used to generate paraphrase variants. LM probabilities are then estimated by maximizing their marginal probability. Significant error rate reductions of 0.5%-0.6% absolute were obtained on a state-ofthe-art conversational telephone speech recognition task using a paraphrastic multi-level LM modelling both word and phrase sequences.

Paraphrastic language models and combination with neural network language models

In natural languages multiple word sequences can represent the same underlying meaning. Only modelling the observed surface word sequence can result in poor context coverage, for example, when using n-gram language models (LM). To handle this issue, paraphrastic LMs were proposed in previous research and successfully applied to a US English conversational telephone speech transcription task. In order to exploit the complementary characteristics of paraphrastic LMs and neural network LMs (NNLM), the combination between the two is investigated in this paper. To investigate paraphrastic LMs' generalization ability to other languages, experiments are conducted on a Mandarin Chinese broadcast speech transcription task. Using a paraphrastic multi-level LM modelling both word and phrase sequences, significant error rate reductions of 0.9% absolute (9% relative) and 0.5% absolute (5% relative) were obtained over the baseline n-gram and NNLM systems respectively, after a combination with word and phrase level NNLMs. © 2013 IEEE.

First-principles energetics of water clusters and ice: a many-body analysis.

Standard forms of density-functional theory (DFT) have good predictive power for many materials, but are not yet fully satisfactory for cluster, solid, and liquid forms of water. Recent work has stressed the importance of DFT errors in describing dispersion, but we note that errors in other parts of the energy may also contribute. We obtain information about the nature of DFT errors by using a many-body separation of the total energy into its 1-body, 2-body, and beyond-2-body components to analyze the deficiencies of the popular PBE and BLYP approximations for the energetics of water clusters and ice structures. The errors of these approximations are computed by using accurate benchmark energies from the coupled-cluster technique of molecular quantum chemistry and from quantum Monte Carlo calculations. The systems studied are isomers of the water hexamer cluster, the crystal structures Ih, II, XV, and VIII of ice, and two clusters extracted from ice VIII. For the binding energies of these systems, we use the machine-learning technique of Gaussian Approximation Potentials to correct successively for 1-body and 2-body errors of the DFT approximations. We find that even after correction for these errors, substantial beyond-2-body errors remain. The characteristics of the 2-body and beyond-2-body errors of PBE are completely different from those of BLYP, but the errors of both approximations disfavor the close approach of non-hydrogen-bonded monomers. We note the possible relevance of our findings to the understanding of liquid water.

Effect of high dietary starch levels on the growth performance, blood chemistry and body composition of gibel carp (Carassius auratus var. gibelio)

An 8-week growth trial was carried out in a semi-recirculation system to investigate the effect of high dietary starch levels on the growth performance, blood chemistry, starch utilization and body composition of gibel carp (Carassius auratus var. gibelio). Five isonitrogenous and isocarloric experimental diets were formulated to contain different starch levels (24%, 28%, 32%, 36% and 40% respectively). Triplicate groups of fish (24 fish per tank with an average body weight, of 8.5 g) were assigned to each diet. The results showed that dietary carbohydrate levels significantly affected the growth performance, hepatopancreatic lipid content, pyruvate kinase (PK) activity and whole-body lipid content. Growth performance, body crude lipid and plasma glucose concentrations showed a decreasing trend with an increase in dietary starch from 24% to 40%. Pyruvate kinase activities and hepatopancreatic lipid content showed an increasing trend with the dietary starch increasing from 24% to 32%, and then a decreasing trend with the dietary starch increasing from 32% to 40%. No significant difference in the hepatopancreatic hexokinase (HK) activity, plasma triglyceride contents, body crude protein, ash and calcium (Ca) and phosphorus (P) contents was observed between different treatments. In conclusion, higher dietary starch levels (32-40%) significantly (P < 0.05) decreased the growth of gibel carp in the present study.

Reactive Many-Body Expansion for a Protonated Water Cluster.

We generalize the standard many-body expansion technique that is used to approximate the total energy of a molecular system to enable the treatment of chemical reactions by quantum chemical techniques. By considering all possible assignments of atoms to monomer units of the many-body expansion and associating suitable weights with each, we construct a potential energy surface that is a smooth function of the nuclear positions. We derive expressions for this reactive many-body expansion energy and describe an algorithm for its evaluation, which scales polynomially with system size, and therefore will make the method feasible for future condensed phase simulations. We demonstrate the accuracy and smoothness of the resulting potential energy surface on a molecular dynamics trajectory of the protonated water hexamer, using the Hartree-Fock method for the many-body term and Møller-Plesset theory for the low order terms of the many-body expansion.

Automatic construction and natural-language description of nonparametric regression models

Copyright © 2014, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved. This paper presents the beginnings of an automatic statistician, focusing on regression problems. Our system explores an open-ended space of statistical models to discover a good explanation of a data set, and then produces a detailed report with figures and natural- language text. Our approach treats unknown regression functions non- parametrically using Gaussian processes, which has two important consequences. First, Gaussian processes can model functions in terms of high-level properties (e.g. smoothness, trends, periodicity, changepoints). Taken together with the compositional structure of our language of models this allows us to automatically describe functions in simple terms. Second, the use of flexible nonparametric models and a rich language for composing them in an open-ended manner also results in state- of-the-art extrapolation performance evaluated over 13 real time series data sets from various domains.

Body loadings and health risk assessment of polychlorinated dibenzo-p-dioxins and dibenzofurans at an intensive electronic waste recycling site in China

This study is one of the very few investigating the dioxin body burden of a group of child-bearing-aged women at an electronic waste (e-waste) recycling site (Taizhou, Zhejiang Province) (24 +/- 2.83 years of age, 40% were primiparae) and a reference site (Lin'an city, Zhejiang Province, about 245 km away from Taizhou) (24 +/- 2.35 years of age, 100% were primiparae) in China. Five sets of samples (each set consisted of human milk, placenta, and hair) were collected from each site. Body burdens of people from the e-waste processing site (human milk, 21.02 +/- 13.81 pg WHO-TEQ(1998/g) fat (World Health Organization toxic equivalency 1998); placenta, 31.15 +/- 15.67 pg WHO-TEQ(1998/g) fat; hair, 33.82 +/- 17.74 pg WHO-TEQ(1998/g) dry wt) showed significantly higher levels of polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurnas (PCDD/Fs) than those from the reference site (human milk, 9.35 +/- 7.39 pg WHO-TEQ(1998/g) fat, placenta, 11.91 +/- 7.05 pg WHO-TEQ(1998/g) fat; hair, 5.59 +/- 4.36 pg WHO-TEQ(1998/g) dry wt) and were comparatively higher than other studies. The difference between the two sites was due to e-waste recycling operations, for example, open burning, which led to high background levels. Moreover, mothers from the e-waste recycling site consumed more foods of animal origin. The estimated daily intake of PCDD/Fs within 6 months by breast-fed infants from the e-waste processing site was 2 times higher than that from the reference site. Both values exceeded the WHO tolerable daily intake for adults by at least 25 and 11 times, respectively. Our results implicated that e-waste recycling operations cause prominent PCDD/F levels in the environment and in humans. The elevated body burden may have health implications for the next generation.

Unified form language: A domain-specific language for weak formulations of partial differential equations

We present the Unified Form Language (UFL), which is a domain-specific language for representing weak formulations of partial differential equations with a view to numerical approximation. Features of UFL include support for variational forms and functionals, automatic differentiation of forms and expressions, arbitrary function space hierarchies formultifield problems, general differential operators and flexible tensor algebra. With these features, UFL has been used to effortlessly express finite element methods for complex systems of partial differential equations in near-mathematical notation, resulting in compact, intuitive and readable programs. We present in this work the language and its construction. An implementation of UFL is freely available as an open-source software library. The library generates abstract syntax tree representations of variational problems, which are used by other software libraries to generate concrete low-level implementations. Some application examples are presented and libraries that support UFL are highlighted. © 2014 ACM.

When is a symmetric body-hinge structure isostatic?

A symmetry-extended mobility rule is formulated for body-hinge frameworks and used to derive necessary symmetry conditions for isostatic (statically and kinematically indeterminate) frameworks. Constructions for symmetric body-hinge frameworks with an isostatic scalar count are reported, and symmetry counts are used to examine these structures for hidden, symmetry-detectable mechanisms. Frameworks of this type may serve as examples for exploration of a symmetry extension of the (now proven) 'molecular conjecture'. © 2014 Elsevier Ltd. All rights reserved.