bluuebunny/crossref_metadata_2025_split huggingface dataset:
Re-examining the effects of word writing on vocabulary learning
Authors: Webb Stuart , Piasecki Anna 
Published: April 2018

Abstract
This study investigated the effects of word writing on vocabulary learning by comparing three conditions in which there was (a) limited time to write words, (b) unlimited time to write words, and (c) a non-writing word-picture pairs comparison. Non-native speakers studying English as a second language encountered 8 word-picture pairs in each condition and were administered a test measuring form recall and another measuring receptive knowledge of written form. The results indicated that there was little difference between scores on both tests when time on task was the same. However, when the participants had as much time as they needed to write and learn words they had higher scores on both dependent measures than when learning in the other two conditions. The findings suggest that an ecologically valid approach to word writing may facilitate vocabulary learning.
The guessing from context test
Authors: Sasao Yosuke , Webb Stuart 
Published: April 2018

Abstract
This study aims to develop two equivalent forms of the Guessing from Context Test (GCT) and provide its preliminary validity evidence. The GCT is a diagnostic test of the guessing skill and measures the following three important steps in guessing: identifying the part of speech of an unknown word, finding its discourse clue, and deriving its meaning. The test was administered to 428 Japanese learners of English. The results indicate that the two forms each with 20 question sets are equivalent in terms of item difficulty distribution and representativeness of the construct being measured. A wide range of validity evidence was provided using Messick’s validation framework, the Rasch model, qualitative investigations into the relationships to actual guessing, and proposals for score interpretation.
Vocabulary knowledge and listening comprehension at an intermediate level in English and French as foreign
languages
Authors: Noreillie Ann-Sophie , Kestemont Britta , Heylen Kris , Desmet Piet , Peters Elke 
Published: April 2018

Abstract
The present study aims to replicate Stæhr’s (2009) study on the relationship between
vocabulary knowledge and listening comprehension. To explore the generalizability of Stæhr’s findings, two experiments were
conducted. However, the study changed the population (Flemish learners) and proficiency level of the materials in the first
experiment (intermediate) and also the language in the second experiment (French). Our results generally confirm Stæhr’s findings.
We also found a positive correlation between vocabulary knowledge and listening comprehension. Although our findings reveal that
learners probably need fewer words for adequate listening comprehension at an intermediate proficiency level, our study also
showed that learners who knew more words had higher listening comprehension scores. Finally, our study seems to suggest that
learners might need less lexical coverage for intermediate listening.
Irony and semantic prosody revisited
Authors: McIntyre Dan 
Published: April 2018

Abstract
This chapter explore Louw’s (1993) claim that deviation from conventionalised semantic prosodies can be indicative of irony. Taking account of criticisms of the concept of semantic prosody, I analyse a short extract from a sketch from the 1960 satirical revue Beyond the Fringe. I argue that the satire in the sketch derives in part from the projected irony and that semantic prosody can be a useful tool in uncovering this. However, I argue that to fully reveal the source of the ironic effects, it is necessary to utilise a more nuanced approach to semantic prosody, as well as to consider how semantic prosodies clash with each other, and how concepts such as semantic preference and Gricean implicature act as further triggers of irony.
Expressiveness and evaluation in Arabic
Authors: Taine-Cheikh Catherine 
Published: April 2018

AbstractOld Arabic had many expressive derived forms: firstly, the forms with radical repetition, consonant reduplication and/or vowel lengthening; secondly, the forms with prefixes, suffixes or infixes. Most of these formatives survived in the Arabic dialects, but Arabic scholars generally focus on diminutive noun forms (nominal and adjectival forms) namedtaṣġīrin Arabic. This article presents the rules of formation of the diminutive in the Ḥassāniyya Arabic dialect, in which this derivation applies to the whole lexicon, including verbal forms. The derivational morphology of the diminutive constitutes a kind of double derivation, characterized mainly by the infixation of-(a)y- – the position of which varies depending on the patterns and on the nature of the base lexeme. The article then analyzes the use and meaning of diminutives in context, studied within two corpora: a corpus of traditional tales and a corpus of courteous poems. The study of these corpora shows that in Ḥassāniyya, pejorative uses of the diminutive are as prominent as meliorative ones. Finally, the article discusses the “root-and-pattern” mode of formation in Arabic and the diverse derivations attested in Arabic dialects, comparing their values with those reported for other languages in the world. Evaluative morphology is shown to be particularly prevalent in Ḥassāniyya, and it is hypothesized that this correlates with the pragmatic function endorsed by the diminutive in this language. This function allows for both positive or negative interpretations of diminutive forms, depending on the context, so that diminutives can express a broad range of emotions.
Detoxification process of tolaasins, lipodepsipeptides, by Microbacterium sp. K3-5
Authors: Tomita Shun , Sue Masayuki , Kajikawa Akinobu , Igimi Shizunobu , Shinohara Hirosuke , Yokota Kenji 
Published: April 2018

ABSTRACT
Tolaasins are antimicrobial lipodepsipeptides. Here, we report the tolaasins-detoxifying properties of Microbacterium sp. K3-5 (K3-5). The detoxification of tolaasins by K3-5 was performed by hydrolyzation of cyclic structure of tolaasins depending on the tolaasin-K3-5 cell interaction. Our data suggest that the cyclic structure of tolaasins is critical for its interaction to target cells.
Free‐riding on Product Quality in Cooperatives: Lessons from an Experiment
Authors: Bonroy Olivier , Garapin Alexis , Hamilton Stephen F. , Souza Monteiro Diogo M. 
Published: April 2018

AbstractAn important issue facing marketing cooperatives is that the overall quality of the product depends on the quality of farm products provided by individual members. We conduct an experiment to empirically investigate producer incentives to free‐ride on quality among the members of a marketing cooperative in a setting where the average quality provided by cooperative members results in a collective rent that is distributed back to members in a patronage dividend levied in proportion to the quantity produced. Hidden actions by cooperative members that impact quality are imperfectly monitored, but free‐riding, when detected, results in exclusion from cooperative returns. The randomized payoff structure of our game results in a novel experimental design that nests public good games and multi‐player assurance games. Our findings indicate that free‐riding on product quality is deterred when (a) cooperatives base patronage dividends on quality outcomes of smaller groups; (b) payoffs from free‐riding are randomized by the possibility of exclusion from cooperative returns; and (c) cooperatives distribute a larger share of returns to members through indirect payments such as capital pooling and cost‐sharing arrangements unrelated to product quality.
Immigration Reform and Farm Labor Markets
Authors: Richards Timothy J 
Published: April 2018

AbstractFarmers throughout the United States report a shortage of workers. At the same time, there are proposals to strengthen the enforcement of existing immigration laws. In this paper, we develop an equilibrium approach to examine the impact of removing undocumented workers from the California agricultural labor market, and to infer whether there is evidence of shortages using individual‐worker data. We find evidence that is consistent with a persistent shortage in some sub‐sectors of the California farm labor market. Further, we conduct counter‐factual policy simulations over a range of possible policy alternatives, and find that removing 50% all undocumented farm workers from the state would lead to an increase in wages of over 22%.
SIMPLE: Sparse Interaction Model over Peaks of moLEcules for fast, interpretable metabolite identification from tandem mass spectra
Authors: Nguyen Dai Hai , Nguyen Canh Hao , Mamitsuka Hiroshi 
Published: April 2018

AbstractMotivationRecent success in metabolite identification from tandem mass spectra has been led by machine learning, which has two stages: mapping mass spectra to molecular fingerprint vectors and then retrieving candidate molecules from the database. In the first stage, i.e. fingerprint prediction, spectrum peaks are features and considering their interactions would be reasonable for more accurate identification of unknown metabolites. Existing approaches of fingerprint prediction are based on only individual peaks in the spectra, without explicitly considering the peak interactions. Also the current cutting-edge method is based on kernels, which are computationally heavy and difficult to interpret.ResultsWe propose two learning models that allow to incorporate peak interactions for fingerprint prediction. First, we extend the state-of-the-art kernel learning method by developing kernels for peak interactions to combine with kernels for peaks through multiple kernel learning (MKL). Second, we formulate a sparse interaction model for metabolite peaks, which we call SIMPLE, which is computationally light and interpretable for fingerprint prediction. The formulation of SIMPLE is convex and guarantees global optimization, for which we develop an alternating direction method of multipliers (ADMM) algorithm. Experiments using the MassBank dataset show that both models achieved comparative prediction accuracy with the current top-performance kernel method. Furthermore SIMPLE clearly revealed individual peaks and peak interactions which contribute to enhancing the performance of fingerprint prediction.Availability and implementationThe code will be accessed through http://mamitsukalab.org/tools/SIMPLE/.
Enumerating consistent sub-graphs of directed acyclic graphs: an insight into biomedical ontologies
Authors: Peng Yisu , Jiang Yuxiang , Radivojac Predrag 
Published: April 2018

Abstract

Motivation
Modern problems of concept annotation associate an object of interest (gene, individual, text document) with a set of interrelated textual descriptors (functions, diseases, topics), often organized in concept hierarchies or ontologies. Most ontology can be seen as directed acyclic graphs (DAGs), where nodes represent concepts and edges represent relational ties between these concepts. Given an ontology graph, each object can only be annotated by a consistent sub-graph; that is, a sub-graph such that if an object is annotated by a particular concept, it must also be annotated by all other concepts that generalize it. Ontologies therefore provide a compact representation of a large space of possible consistent sub-graphs; however, until now we have not been aware of a practical algorithm that can enumerate such annotation spaces for a given ontology.

Results
We propose an algorithm for enumerating consistent sub-graphs of DAGs. The algorithm recursively partitions the graph into strictly smaller graphs until the resulting graph becomes a rooted tree (forest), for which a linear-time solution is computed. It then combines the tallies from graphs created in the recursion to obtain the final count. We prove the correctness of this algorithm, propose several practical accelerations, evaluate it on random graphs and then apply it to characterize four major biomedical ontologies. We believe this work provides valuable insights into the complexity of concept annotation spaces and its potential influence on the predictability of ontological annotation.

Availability and implementation
https://github.com/shawn-peng/counting-consistent-sub-DAG

Supplementary information
Supplementary data are available at Bioinformatics online.
A graph-based approach to diploid genome assembly
Authors: Garg Shilpa , Rautiainen Mikko , Novak Adam M , Garrison Erik , Durbin Richard , Marschall Tobias 
Published: April 2018

Abstract

Motivation
Constructing high-quality haplotype-resolved de novo assemblies of diploid genomes is important for revealing the full extent of structural variation and its role in health and disease. Current assembly approaches often collapse the two sequences into one haploid consensus sequence and, therefore, fail to capture the diploid nature of the organism under study. Thus, building an assembler capable of producing accurate and complete diploid assemblies, while being resource-efficient with respect to sequencing costs, is a key challenge to be addressed by the bioinformatics community.

Results
We present a novel graph-based approach to diploid assembly, which combines accurate Illumina data and long-read Pacific Biosciences (PacBio) data. We demonstrate the effectiveness of our method on a pseudo-diploid yeast genome and show that we require as little as 50× coverage Illumina data and 10× PacBio data to generate accurate and complete assemblies. Additionally, we show that our approach has the ability to detect and phase structural variants.

Availability and implementation
https://github.com/whatshap/whatshap

Supplementary information
Supplementary data are available at Bioinformatics online.
TiSAn: estimating tissue-specific effects of coding and non-coding variants
Authors: Vervier Kévin , Michaelson Jacob J 
Published: April 2018

Abstract

Motivation
Model-based estimates of general deleteriousness, like CADD, DANN or PolyPhen, have become indispensable tools in the interpretation of genetic variants. However, these approaches say little about the tissues in which the effects of deleterious variants will be most meaningful. Tissue-specific annotations have been recently inferred for dozens of tissues/cell types from large collections of cross-tissue epigenomic data, and have demonstrated sensitivity in predicting affected tissues in complex traits. It remains unclear, however, whether including additional genome-scale data specific to the tissue of interest would appreciably improve functional annotations.

Results
Herein, we introduce TiSAn, a tool that integrates multiple genome-scale data sources, defined by expert knowledge. TiSAn uses machine learning to discriminate variants relevant to a tissue from those with no bearing on the function of that tissue. Predictions are made genome-wide, and can be used to contextualize and filter variants of interest in whole genome sequencing or genome-wide association studies. We demonstrate the accuracy and flexibility of TiSAn by producing predictive models for human heart and brain, and detecting tissue-relevant variations in large cohorts for autism spectrum disorder (TiSAn-brain) and coronary artery disease (TiSAn-heart). We find the multiomics TiSAn model is better able to prioritize genetic variants according to their tissue-specific action than the current state-of-the-art method, GenoSkyLine.

Availability and implementation
Software and vignettes are available at http://github.com/kevinVervier/TiSAn.

Supplementary information
Supplementary data are available at Bioinformatics online.
Regulation of the heat shock transcription factor Hsf1 in fungi: implications for temperature-dependent virulence traits
Authors: Veri Amanda O , Robbins Nicole , Cowen Leah E 
Published: April 2018

AbstractThe impact of fungal pathogens on human health is devastating. For fungi and other pathogens, a key determinant of virulence is the capacity to thrive at host temperatures, with elevated temperature in the form of fever as a ubiquitous host response to defend against infection. A prominent feature of cells experiencing heat stress is the increased expression of heat shock proteins (Hsps) that play pivotal roles in the refolding of misfolded proteins in order to restore cellular homeostasis. Transcriptional activation of this heat shock response is orchestrated by the essential heat shock transcription factor, Hsf1. Although the influence of Hsf1 on cellular stress responses has been studied for decades, many aspects of its regulation and function remain largely enigmatic. In this review, we highlight our current understanding of how Hsf1 is regulated and activated in the model yeast Saccharomyces cerevisiae, and highlight exciting recent discoveries related to its diverse functions under both basal and stress conditions. Given that thermal adaption is a fundamental requirement for growth and virulence in fungal pathogens, we also compare and contrast Hsf1 activation and function in other fungal species with an emphasis on its role as a critical regulator of virulence traits.
Patterns of SES Health Disparities Among Older Adults in Three Upper Middle- and Two High-Income Countries
Authors: McEniry Mary , Samper-Ternent Rafael , Flórez Carmen Elisa , Pardo Renata , Cano-Gutierrez Carlos 
Published: April 2018

Abstract

Objectives
To examine the socioeconomic status (SES) health gradient for obesity, diabetes, and hypertension within a diverse group of health outcomes and behaviors among older adults (60+) in upper middle-income countries benchmarked with high-income countries.

Method
We used data from three upper middle-income settings (Colombia-SABE-Bogotá, Mexico-SAGE, and South Africa-SAGE) and two high-income countries (England-ELSA and US-HRS) to estimate logistic regression models using age, gender, and education to predict health and health behaviors.

Results
The sharpest gradients appear in middle-income settings but follow expected patterns found in high-income countries for poor self-reported health, functionality, cognitive impairment, and depression. However, weaker gradients appear for obesity, hypertension, diabetes, and other chronic conditions in Colombia and Mexico and the gradient reverses in South Africa. Strong disparities exist in risky health behaviors and in early nutritional status in the middle-income settings.

Discussion
Rapid demographic and nutritional transitions, urbanization, poor early life conditions, social mobility, negative health behavior, and unique country circumstances provide a useful framework for understanding the SES health gradient in middle-income settings. In contrast with high-income countries, the increasing prevalence of obesity, an important risk factor for chronic conditions and other aspects of health, may ultimately change the SES gradient for diseases in the future.
Limits on turbulent propagation of energy in cool-core clusters of galaxies
Authors: Bambic C J , Pinto C , Fabian A C , Sanders J , Reynolds C S 
Published: April 2018

Abstract
We place constraints on the propagation velocity of bulk turbulence within the intracluster medium of three clusters and an elliptical galaxy. Using Reflection Grating Spectrometer measurements of turbulent line broadening, we show that for these clusters, the 90 per cent upper limit on turbulent velocities when accounting for instrumental broadening is too low to propagate energy radially to the cooling radius of the clusters within the required cooling time. In this way, we extend previous Hitomi-based analysis on the Perseus cluster to more clusters, with the intention of applying these results to a future, more extensive catalogue. These results constrain models of turbulent heating in active galactic nucleus feedback by requiring a mechanism which can not only provide sufficient energy to offset radiative cooling but also resupply that energy rapidly enough to balance cooling at each cluster radius.
Gravitational waves from neutron stars and asteroseismology
Authors: Ho Wynn C. G. 
Published: April 2018

Neutron stars are born in the supernova explosion of massive stars. Neutron stars rotate as stably as atomic clocks and possess densities exceeding that of atomic nuclei and magnetic fields millions to billions of times stronger than those created in laboratories on the Earth. The physical properties of neutron stars are determined by many areas of fundamental physics, and detection of gravitational waves can provide invaluable insights into our understanding of these areas. Here, we describe some of the physics and astrophysics of neutron stars and how traditional electromagnetic wave observations provide clues to the sorts of gravitational waves we expect from these stars. We pay particular attention to neutron star fluid oscillations, examining their impact on electromagnetic and gravitational wave observations when these stars are in a wide binary or isolated system, then during binary inspiral right before merger, and finally at times soon after merger.
This article is part of a discussion meeting issue ‘The promises of gravitational-wave astronomy’.
Robust and clinically relevant prediction of response to anti-cancer drugs via network integration of molecular profiles
Authors: Franco Marcela , Jeggari Ashwini , Peuget Sylvain , Böttger Franziska , Selivanova Galina , Alexeyenko Andrey 
Published: April 2018

ABSTRACTIn order to tackle heterogeneity of cancer samples and high data space dimensionality, we propose a method NEAmarker for finding sensitive and robust biomarkers at the pathway level. In this method, scores from network enrichment analysis transform the original space of altered genes into a lower-dimensional space of pathways, which is then correlated with phenotype variables. The analysis was first done onin vitroanti-cancer drug screen datasets and then on clinical data. In parallel, we tested a panel of state-of-the-art enrichment methods. In this comparison, our method proved superior in terms of 1) universal applicability to different data types with a possibility of cross-platform integration, 2) consistency of the discovered correlates between independent drug screens, and 3) ability to explain differential survival of treated patients. Our new in vitro screen validated performance of the discovered multivariate models. Finally, NEAmarker was the only method to discover predictors of bothin vitroresponse and patient survival given administration of the same drug.