bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mapping at external interfaces
Authors: Leal Tania 
Published: August 2018

Abstract
This study investigates embedded clitic left dislocation (CLLD), a syntax-discourse interface structure expressing topicalization, in a group of native and L2 Spanish speakers (beginners, intermediate, advanced). The Interface Hypothesis (Sorace, 2011) proposes that external interfaces pose inordinate difficulty for bilinguals, even at near-native levels. Results did not show evidence of such difficulty although differences in methodology (tasks imposing time pressure vs. not) could account for divergences. Additionally, not all syntax-discourse interface properties might be equally problematic: CLLD might not intrinsically place the same processing burden as other structures (e.g., anaphora resolution). Finally, results showed input quality was positively correlated to native-like outcomes, beyond proficiency. Hence, results are in broad agreement with accounts proposing input is the key factor for acquisition.
The Bottleneck Hypothesis as applied to the Spanish DP
Authors: Judy Tiffany 
Published: August 2018

Abstract
By examining knowledge of interpretive constraints that obtain from new DP feature acquisition in Spanish, this chapter tests the Bottleneck Hypothesis’s claim (Slabakova, 2013, 2014, 2016) that functional morphology is the “bottleneck” of SLA. Individual data from two language groups (Romance (Italian n = 35) and Germanic (English n = 41; German n = 19)) across three tasks testing for knowledge of Spanish DP morphology, syntax and semantics reveal that participants demonstrate knowledge of DP functional morphology before knowledge of the syntax-semantics of adjectival position. The import is twofold: first, individual L2 data is examined across tasks; second, comparing distinct L1 groups makes it possible to ask whether the “bottleneck” is equally problematic for all language pairings, an issue not currently addressed by the hypothesis.
Proficiency and transfer effects in the acquisition of gender agreement by L2 and L3 English learners
Authors: Imaz Agirre Ainara , García Mayo María del Pilar 
Published: August 2018

Abstract
The present study examines proficiency and transfer effects in the acquisition of gender agreement in third person singular possessives (his/her) by second (L2) and third language (L3) learners of English. Within current generative second language acquisition research, gender agreement has been found to be a complicated feature to acquire for non-native language learners. A group of Basque/Spanish speakers (n = 117) and a group of Spanish speakers (n = 70) divided into three proficiency levels (elementary, intermediate and advanced) completed two written (a fill in the gap task and a written description task) two oral production tasks (an oral elicitation and a picture description). Our findings show that previous linguistic knowledge and proficiency level in English seem to have an influence on the type of errors attested in the L2 and the L3 groups.
Generative second language acquisition and language teaching
Authors: Marsden Heather 
Published: August 2018

Abstract
Though language teaching concerns lie outside the core aim of generative second language acquisition (GenSLA) research, consideration of how GenSLA findings might be useful for the language classroom has nonetheless been a consistent sub-theme within Roumyana Slabakova’s work. This paper reports on a recent body of “applied GenSLA” research and teacher-researcher networking activities that address this theme by explicitly aiming to investigate applications of GenSLA research in a language teaching context. The applied GenSLA work is then discussed in the broader context of engagement between language teachers and SLA research generally (E. Marsden & Kasprowicz 2017; Nassaji, 2012), and concludes with proposals for how applied GenSLA can contribute towards advancing the teacher-researcher dialogue.
Seasonal management.
Authors: Creasy G. L. , Creasy L. L. 
Published: August 2018

Abstract

Once a vineyard has been established there is ongoing management to keep it in top producing form. In many ways this process starts at pruning and matching the vine to the trellising system, as this sets the vine up for producing fruit in the following year. There are then many other management interventions that can be used during the growing season, including those dealing with frost, canopy, any cover crop, water application and other methods (such as girdling, fruit and flower cluster thinning, application of plant growth regulators and harvesting) that fine-tune the grape product. Finally, determining when and how to harvest the crop caps off a season of preparation.
Grapevine pests, diseases and disorders.
Authors: Creasy G. L. , Creasy L. L. 
Published: August 2018

Abstract

This chapter concentrates on the more ubiquitous, global pests: those causing problems in many grape-growing areas. These include fungal, bacterial and viral diseases; other disorders; insect pests; mites; animal pests, including nematodes and birds; and weeds. Some methods of controlling these pests are discussed, focusing on application of pesticides and quarantines. Topics on pesticide application and resistance as well as on pest and disease control in organic grape production are also included.
An evaluation of supervised methods for identifying differentially methylated regions in Illumina methylation arrays
Authors: Mallik Saurav , Odom Gabriel J , Gao Zhen , Gomez Lissette , Chen Xi , Wang Lily 
Published: August 2018

AbstractEpigenome-wide association studies (EWASs) have become increasingly popular for studying DNA methylation (DNAm) variations in complex diseases. The Illumina methylation arrays provide an economical, high-throughput and comprehensive platform for measuring methylation status in EWASs. A number of software tools have been developed for identifying disease-associated differentially methylated regions (DMRs) in the epigenome. However, in practice, we found these tools typically had multiple parameter settings that needed to be specified and the performance of the software tools under different parameters was often unclear. To help users better understand and choose optimal parameter settings when using DNAm analysis tools, we conducted a comprehensive evaluation of 4 popular DMR analysis tools under 60 different parameter settings. In addition to evaluating power, precision, area under precision-recall curve, Matthews correlation coefficient, F1 score and type I error rate, we also compared several additional characteristics of the analysis results, including the size of the DMRs, overlap between the methods and execution time. The results showed that none of the software tools performed best under their default parameter settings, and power varied widely when parameters were changed. Overall, the precision of these software tools were good. In contrast, all methods lacked power when effect size was consistent but small. Across all simulation scenarios, comb-p consistently had the best sensitivity as well as good control of false-positive rate.
admetSAR 2.0: web-service for prediction and optimization of chemical ADMET properties
Authors: Yang Hongbin , Lou Chaofeng , Sun Lixia , Li Jie , Cai Yingchun , Wang Zhuang , Li Weihua , Liu Guixia , Tang Yun 
Published: August 2018

Abstract

Summary
admetSAR was developed as a comprehensive source and free tool for the prediction of chemical ADMET properties. Since its first release in 2012 containing 27 predictive models, admetSAR has been widely used in chemical and pharmaceutical fields. This update, admetSAR 2.0, focuses on extension and optimization of existing models with significant quantity and quality improvement on training data. Now 47 models are available for either drug discovery or environmental risk assessment. In addition, we added a new module named ADMETopt for lead optimization based on predicted ADMET properties.

Availability and implementation
Free available on the web at http://lmmd.ecust.edu.cn/admetsar2/

Supplementary information
Supplementary data are available at Bioinformatics online.
Variable selection and validation in multivariate modelling
Authors: Shi Lin , Westerhuis Johan A , Rosén Johan , Landberg Rikard , Brunius Carl 
Published: August 2018

Abstract

Motivation
Validation of variable selection and predictive performance is crucial in construction of robust multivariate models that generalize well, minimize overfitting and facilitate interpretation of results. Inappropriate variable selection leads instead to selection bias, thereby increasing the risk of model overfitting and false positive discoveries. Although several algorithms exist to identify a minimal set of most informative variables (i.e. the minimal-optimal problem), few can select all variables related to the research question (i.e. the all-relevant problem). Robust algorithms combining identification of both minimal-optimal and all-relevant variables with proper cross-validation are urgently needed.

Results
We developed the MUVR algorithm to improve predictive performance and minimize overfitting and false positives in multivariate analysis. In the MUVR algorithm, minimal variable selection is achieved by performing recursive variable elimination in a repeated double cross-validation (rdCV) procedure. The algorithm supports partial least squares and random forest modelling, and simultaneously identifies minimal-optimal and all-relevant variable sets for regression, classification and multilevel analyses. Using three authentic omics datasets, MUVR yielded parsimonious models with minimal overfitting and improved model performance compared with state-of-the-art rdCV. Moreover, MUVR showed advantages over other variable selection algorithms, i.e. Boruta and VSURF, including simultaneous variable selection and validation scheme and wider applicability.

Availability and implementation
Algorithms, data, scripts and tutorial are open source and available as an R package (‘MUVR’) at https://gitlab.com/CarlBrunius/MUVR.git.

Supplementary information
Supplementary data are available at Bioinformatics online.
PhenoSpD: an integrated toolkit for phenotypic correlation estimation and multiple testing correction using GWAS summary statistics
Authors: Zheng Jie , Richardson Tom G , Millard Louise A C , Hemani Gibran , Elsworth Benjamin L , Raistrick Christopher A , Vilhjalmsson Bjarni , Neale Benjamin M , Haycock Philip C , Smith George Davey , Gaunt Tom R 
Published: August 2018

Abstract

Background
Identifying phenotypic correlations between complex traits and diseases can provide useful etiological insights. Restricted access to much individual-level phenotype data makes it difficult to estimate large-scale phenotypic correlation across the human phenome. Two state-of-the-art methods, metaCCA and LD score regression, provide an alternative approach to estimate phenotypic correlation using only genome-wide association study (GWAS) summary results.

Results
Here, we present an integrated R toolkit, PhenoSpD, to use LD score regression to estimate phenotypic correlations using GWAS summary statistics and to utilize the estimated phenotypic correlations to inform correction of multiple testing for complex human traits using the spectral decomposition of matrices (SpD). The simulations suggest that it is possible to identify nonindependence of phenotypes using samples with partial overlap; as overlap decreases, the estimated phenotypic correlations will attenuate toward zero and multiple testing correction will be more stringent than in perfectly overlapping samples. Also, in contrast to LD score regression, metaCCA will provide approximate genetic correlations rather than phenotypic correlation, which limits its application for multiple testing correction. In a case study, PhenoSpD using UK Biobank GWAS results suggested 399.6 independent tests among 487 human traits, which is close to the 352.4 independent tests estimated using true phenotypic correlation. We further applied PhenoSpD to an estimated 5,618 pair-wise phenotypic correlations among 107 metabolites using GWAS summary statistics from Kettunen's publication and PhenoSpD suggested the equivalent of 33.5 independent tests for these metabolites.

Conclusions
PhenoSpD extends the use of summary-level results, providing a simple and conservative way to reduce dimensionality for complex human traits using GWAS summary statistics. This is particularly valuable in the age of large-scale biobank and consortia studies, where GWAS results are much more accessible than individual-level data.
Particle acceleration in relativistic magnetic reconnection with strong inverse-Compton cooling in pair plasmas
Authors: Werner Gregory R , Philippov Alexander A , Uzdensky Dmitri A 
Published: August 2018

ABSTRACT
Particle-in-cell (PIC) simulations have shown that relativistic collisionless magnetic reconnection drives non-thermal particle acceleration (NTPA), potentially explaining high-energy (X-ray/γ-ray) synchrotron and/or inverse Compton (IC) radiation observed from various astrophysical sources. The radiation back-reaction force on radiating particles has been neglected in most of these simulations, even though radiative cooling considerably alters particle dynamics in many astrophysical environments where reconnection may be important. We present a radiative PIC study examining the effects of external IC cooling on the basic dynamics, NTPA, and radiative signatures of relativistic reconnection in pair plasmas. We find that, while the reconnection rate and overall dynamics are basically unchanged, IC cooling significantly influences NTPA: the particle spectra still show a hard power law (index ≥ −2) as in non-radiative reconnection, but transition to a steeper power law that extends to a cooling-dependent cut-off. The steep power-law index fluctuates in time between roughly −3 and −5. The time-integrated photon spectra display corresponding power laws with indices ≈−0.5 and ≈−1.1, similar to those observed in hard X-ray spectra of accreting black holes.
Use of Cigarettes With Flavor-Changing Capsules Among Smokers in the United Kingdom: An Online Survey
Authors: Moodie Crawford , MacKintosh Anne Marie , Thrasher James F , McNeill Ann , Hitchman Sara 
Published: August 2018

Abstract

Introduction
Cigarettes with flavor-changing capsules in the filter have experienced phenomenal global growth in the last decade. We explore sociodemographic and smoking-related factors associated with using capsule cigarettes, how frequently users burst the capsule, and reasons for using them.

Methods
An online survey was conducted in the United Kingdom between April and May 2016 with 6234 factory-made and/or hand-rolled cigarette smokers. This analysis focuses on 3620 factory-made cigarette smokers, aged 18 years and over, who had smoked in the past month.

Results
Thirteen percent smoked capsule cigarettes, with younger smokers more likely than older smokers to do so. Capsule use was significantly more common among White non-British than White British and among those planning to quit in the next 6 months than those not planning to quit. Most capsule users who crushed the capsule did so always (51%) or most of the time (18%), with more frequent crushing of capsules more common among females, younger and middle-aged participants, White British, and those with a lower score on the Heaviness of Smoking Index. The most common reasons for using capsule cigarettes were that they taste better (52%), are smoother (41%), provide a choice of flavors (32%), and the enjoyment of clicking the capsule (25%). Capsule and noncapsule smokers did not differ significantly in their perceptions of the harmfulness of their brand relative to other brands.

Conclusions
Our study provides an insight into how and why smokers of capsule cigarettes use these products, with the key drivers of use being taste, flavor choice, and interactivity.

Implications
Cigarettes with capsules in the filter that can be burst to change the flavor have experienced remarkable growth since being introduced in 2007, but little is known about how and why smokers use these products. Thirteen percent of factory-made cigarette smokers in our sample smoked a brand with a capsule in the filter, with approximately two-thirds crushing the capsule all or most of the time. Capsule use was more likely among younger participants. The main reasons for smoking capsule cigarettes were related to how they taste, having a choice of flavors, and enjoyment of clicking the capsule (interactivity).
Association of antibodies against myelin and neuronal antigens with neuroinflammation in systemic lupus erythematosus
Authors: Pröbstel Anne-Katrin , Thanei Madlaina , Erni Barbara , Lecourt Anne-Catherine , Branco Léonore , André Raphaël , Roux-Lombard Pascal , Koenig Katrin F , Huynh-Do Uyen , Ribi Camillo , Chizzolini Carlo , Kappos Ludwig , Trendelenburg Marten , Derfuss Tobias ,   Swiss Systemic Lupus Erythematosus Cohort Study Group
Published: August 2018

Abstract

Objectives
To determine frequency and syndrome specificity of novel and known nervous system (NS)-directed antibodies in a large, unbiased cohort of SLE patients in the Swiss SLE Cohort Study.

Methods
This retrospective pilot study included 174 patients in a cross-sectional and 102 in a longitudinal study. Antibodies against 12 NS antigens [myelin oligodendrocyte glycoprotein (MOG), neurofascin 186 (NF186), aquaporin-4 (AQP4), N-methyl-D-aspartate receptor (subunit NR1) (NMDAR-NR1), α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (subunits 1 and 2) (AMPAR1/2), gamma-aminobutyric acid B receptor (subunits B1 and B2) (GABABR1/2), glutamate decarboxylase 65 (GAD65), glycine receptor (GlyR), contactin-associated protein-like 2 (CASPR2), leucine-rich glioma-inactivated 1 (LGI1), metabotropic glutamate receptor 5 (mGluR5) and dipeptidyl-peptidase-like protein 6 (DPPX)] were screened with validated cell-based assays and correlated with clinical and diagnostic findings.

Results
Twenty-three of one hundred and seventy-four (13.2%) patients harboured antibodies against MOG (n = 14), NF186 (n = 6), GAD65 (n = 2), AQP4 and GlyR (n = 1). Anti-MOG antibodies were most frequently found in the cohort (8%). Thirteen of the anti-NS antibody-positive patients showed clinical symptoms of NS involvement, a subgroup of which (n = 8) resembled the syndrome associated with the antibody. Nine patients harboured antibodies without neurological symptoms and one patient was lost to follow-up. The frequency of NPSLE was significantly higher in the anti-NS antibody-positive patients (13/23, 56.5%: MOG 6/14, 42.9%; NF186 5/6, 83.3%; GAD65 2/2, 100%; AQP4/GlyR 0/1, 0%) compared with the antibody-negative cohort (21/151, 13.9%) (chi-square test, P < 0.0001).

Conclusion
Anti-NS antibodies, most prevalently anti-MOG antibodies, are significantly associated with NPSLE and manifest with the distinct neurological syndrome associated with the antibody in a subgroup. Follow-up studies in large, independent cohorts will reveal whether these anti-NS antibodies could serve as a diagnostic and prognostic biomarker for NPSLE and enable tailored treatment decisions in this challenging and diverse patient cohort.
Delirium Monitoring in Neurocritically Ill Patients: A Systematic Review*
Authors: Patel Mayur B. , Bednarik Josef , Lee Patricia , Shehabi Yahya , Salluh Jorge I. , Slooter Arjen J. , Klein Kate E. , Skrobik Yoanna , Morandi Alessandro , Spronk Peter E. , Naidech Andrew M. , Pun Brenda T. , Bozza Fernando A. , Marra Annachiara , John Sayona , Pandharipande Pratik P. , Ely E. Wesley 
Published: August 2018

Objectives:
The Society of Critical Care Medicine recommends routine delirium monitoring, based on data in critically ill patients without primary neurologic injury. We sought to answer whether there are valid and reliable tools to monitor delirium in neurocritically ill patients and whether delirium is associated with relevant clinical outcomes (e.g., survival, length of stay, functional independence, cognition) in this population.

Data Sources:
We systematically reviewed Cumulative Index to Nursing and Allied Health Literature, Web of Science, and PubMed.

Study Selection and Data Extraction:
Inclusion criteria allowed any study design investigating delirium monitoring in neurocritically ill patients (e.g., neurotrauma, ischemic, and/or hemorrhagic stroke) of any age. We extracted data relevant to delirium tool sensitivity, specificity, negative predictive value, positive predictive value, interrater reliability, and associated clinical outcomes.

Data Synthesis:
Among seven prospective cohort studies and a total of 1,173 patients, delirium was assessed in neurocritically patients using validated delirium tools after considering primary neurologic diagnoses and associated complications, finding a pooled prevalence rate of 12–43%. When able to compare against a common reference standard, Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, the test characteristics showed a sensitivity of 62–76%, specificity of 74–98%, positive predictive value of 63–91%, negative predictive value of 70–94%, and reliability kappa of 0.64–0.94. Among four studies reporting multivariable analyses, delirium in neurocritically patients was associated with increased hospital length of stay (n = 3) and ICU length of stay (n = 1), as well as worse functional independence (n = 1) and cognition (n = 2), but not survival.

Conclusions:
These data from studies of neurocritically ill patients demonstrate that patients with primary neurologic diagnoses can meet diagnostic criteria for delirium and that delirious features may predict relevant untoward clinical outcomes. There is a need for ongoing investigations regarding delirium in these complicated neurocritically ill patients.
Association of Postoperative Antibiotics With Surgical Site Infection in Mohs Micrographic Surgery
Authors: Levin Ethan C. , Chow Conroy , Makhzoumi Zaineb , Jin Chengshi , Shiboski Stephen C. , Arron Sarah T. 
Published: August 2018

BACKGROUND
Surgical site infection (SSI) is the most frequent complication of Mohs micrographic surgery. Previous studies have identified risk factors for SSI, but it is not known whether antibiotic prophylaxis mitigates this risk.

OBJECTIVE
To measure the association between antibiotic prophylaxis and SSI in a convenience sample of Mohs cases and to report on the utility of propensity scoring to control for confounding by indication in registry data.

METHODS
Data were drawn from a pilot quality improvement registry of 816 Mohs cases. The relationship between antibiotic prophylaxis and SSI was assessed with logistic regression modeling using propensity score methods to adjust for confounding.

RESULTS
One hundred fifty-one cases were prescribed antibiotic prophylaxis (18.5%). Of 467 cases with follow-up, 16 (3.4%) developed SSI. Infection rates were higher in subjects prescribed prophylaxis, but propensity adjustment reduced this effect. Adjusted odds of infection were 1.47-fold higher in subjects prescribed antibiotics and not statistically significant (95% confidence interval 0.29–7.39; p = .64).

CONCLUSION
Although there was no significant difference in SSI among patients prescribed prophylactic antibiotics, statistical precision was limited by the low incidence of infection. Larger population-based prospective registry studies including propensity adjustment are needed to confirm the benefit of prophylactic antibiotics in high-risk surgical cases.