bluuebunny/crossref_metadata_2025_split huggingface dataset:
Biomechanical behaviour – Anisotropy of eye cornea through experimental strip tests
Authors: Arsalan Khan Mohammad , Elsheikh Ahmed , Ahmad Khan Iqtedar 
Published: March 2018

Abstract
With the advent of research it was identified that material properties are responsible for errors in tonometry pressure (referred to as Goldmann IOP or IOPG) with the stiffening of a composite structure of corneal tissue in particular. Strip tensile tests are conducted to determine their stress–strain relationship for the purpose to study the behaviour of material properties of cornea. Specimens are taken from the superior–inferior (vertical) and temporal– nasal (horizontal) directions. Testing is performed on an Instron machine, under different rate of loading conditions. First set of experiment, with single strain rate, is executed on eyes having random population. While the second set of experiment is executed on eyes of the same animal in both directions, and different strain rates are applied each specimen. Relatively, the first set of experiment is found to be slightly different and less accurate. In general, it is found that the vertical specimen is 34% on an average stiffer than the horizontal specimen compared to Kampmeier et al. of 20% (studied in 2000) and Defu Wang of 15% (studied in 2007). Curve fitting coefficients are also evaluated for 4–degree polynomial. The anisotropy is evident by plotting the ratio of E–tangent value of vertical Ev and horizontal Eh against stresses with individual strain rates. The value of Ev/Eh increases with slightly slow rate with stresses as compared to achieved through slow strain rates.
Performance evaluation of Mn and Fe doped SrCo0.9Nb0.1O3-δ cathode for IT-SOFC application
Authors: Bele Lokesh , Lenka R K , Patro P K , Muhmood L , Mahata T , Sinha P K 
Published: March 2018

Abstract
Cathode materials of Mn and Fe doped SrCo0.9Nb0.1O3-δ, are synthesized by solid state route for intermediate temperature fuel cell applications. Phase pure material is obtained after calcining the precursors at 1100 °C. Phase compatibility is observed between this novel cathode material with gadolinia doped ceria (GDC) electrolyte material as reflected in the diffraction pattern. The state of art YSZ electrolyte is not compatible with this cathode material. Average thermal expansion coefficient of the material varies between 17 to 22 X 10-6 K-1 on doping, from room temperature to 800 °C. Increase in thermal expansion coefficient is observed with Mn and Fe doping associated with the loss of oxygen from the crystal. The electrical conductivity of the cathode material decreases with Fe and Mn doping. Mn doped samples show lowest conductivity. From the symmetric cell measurement lower area specific resistance (0.16 Ω-cm2) is obtained for un-doped samples, at 850 °C. From the initial results it can be inferred that Mn/Fe doping improves neither the thermal expansion co-efficient nor the electrochemical activity.
The Impact of Cash and Food Transfers: Evidence from a Randomized Intervention in Niger
Authors: Hoddinott John , Sandström Susanna , Upton Joanna 
Published: March 2018

AbstractWe contribute to debates regarding the use of cash and in‐kind transfers by providing new evidence from a very low income setting, rural Niger. We motivate our findings through the use of a conceptual model that emphasizes that the impact of cash and food transfers on dimensions of food consumption—both quantity and quality—will differ by the income level of the household and whether or not the food transfer is extra‐marginal. Consistent with this model, households in localities randomized to receive the food basket experienced larger, positive impacts on measures of dietary diversity than those receiving the cash transfer. By contrast, households receiving cash were more likely to make bulk purchases of grains and spent more money on private transfers and debts. Despite the seasonal dimensions to food insecurity in Niger, the relative impact of food and cash transfers on our measures of dietary diversity did not vary markedly by season.
History, Prophecy and the Apocalypse in the Chronicles of Matthew Paris
Authors: Weiler Björn 
Published: March 2018

Abstract
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This article offers the first comprehensive investigation into the role of prophecy in the writings of the English Benedictine artist, mapmaker and chronicler Matthew Paris (c.1200–1259). It takes his accounts of visions, dreams, prophetic texts and other prognostic incidents as the starting-point for an exploration of Matthew’s conception of truth and of his understanding of the relationship between the natural and the supernatural, and between history and prophecy. In the process, it challenges widely held assumptions about the role of eschatological thinking in Matthew’s approach to the past, and suggests implications for our understanding of ideas about prophecy and the Apocalypse in the intellectual, literary and religious culture of high medieval Europe.
Understanding Australian policies on public health using social and political science theories: reflections from an Academy of the Social Sciences in Australia Workshop
Authors: Baum Fran , Graycar Adam , Delany-Crowe Toni , de Leeuw Evelyne , Bacchi Carol , Popay Jennie , Orchard Lionel , Colebatch Hal , Friel Sharon , MacDougall Colin , Harris Elizabeth , Lawless Angela , McDermott Dennis , Fisher Matthew , Harris Patrick , Phillips Clare , Fitzgerald Jane 
Published: March 2018

AbstractThere is strong, and growing, evidence documenting health inequities across the world. However, most governments do not prioritize policies to encourage action on the social determinants of health and health equity. Furthermore, despite evidence concerning the benefits of joined-up, intersectoral policy to promote health and health equity, it is rare for such policy approaches to be applied systematically. To examine the usefulness of political and social science theory in understanding the reasons for this disjuncture between evidence and practice, researchers and public servants gathered in Adelaide for an Academy of the Social Sciences in Australia (ASSA) Workshop. This paper draws together the learnings that emerged from the Workshop, including key messages about the usefulness of various theories as well as insights drawn from policy practice. Discussions during the Workshop highlighted that applying multiple theories is particularly helpful in directing attention to, and understanding, the influence of all stages of the policy process; from the construction and framing of policy problems, to the implementation of policy and evaluation of outcomes, including those outcomes that may be unintended. In addition, the Workshop emphasized the value of collaborations among public health researchers, political and social scientists and public servants to open up critical discussion about the intersections between theory, research evidence and practice. Such critique is vital to render visible the processes through which particular sources of knowledge may be privileged over others and to examine how political and bureaucratic environments shape policy proposals and implementation action.
Atlantic mackerel daily spawning dynamics and implications for batch fecundity estimations
Authors: Ganias K , Marmara D , Solla A , Garabana D , Dominguez-Petit R 
Published: March 2018

Abstract
The present study contributes to a better understanding of the daily spawning dynamics of southern NEA mackerel (Scomber scombrus) with implications for the estimation of batch fecundity. It shows that there is a time window during the day, mainly in the afternoon, during which the advanced oocyte mode in imminent spawners separates from the remaining, smaller oocytes. This synchronicity in the separation of the spawning batch amongst imminent spawners corroborates evidence for the existence of daily spawning synchronicity in the population. This is particularly important for applications of the daily egg production method, DEPM, because such pattern facilitates both the ageing of eggs for the estimation of the daily egg production at sea and the ageing of postovulatory follicles for the estimation of spawning frequency. For NEA mackerel, batch fecundity could only be measured when a clear hiatus was established between the spawning batch and the smaller oocytes. Hydrated females that do not show such hiatus would not be valid for batch fecundity measurements suggesting that the “hydrated oocytes method” is not fully applicable for this stock. Knowing the time of day at which the batch is separated, will facilitate the sampling of valid females for the estimation of batch fecundity.
The Impact of Interviewer Effects on Regression Coefficients
Authors: Fischer Micha , West Brady T , Elliott Michael R , Kreuter Frauke 
Published: March 2018

Abstract
This article examines the influence of interviewers on the estimation of regression coefficients from survey data. First, we present theoretical considerations with a focus on measurement errors and nonresponse errors due to interviewers. Then, we show via simulation which of several nonresponse and measurement error scenarios has the biggest impact on the estimate of a slope parameter from a simple linear regression model. When response propensity depends on the dependent variable in a linear regression model, bias in the estimated slope parameter is introduced. We find no evidence that interviewer effects on the response propensity have a large impact on the estimated regression parameters. We do find, however, that interviewer effects on the predictor variable of interest explain a large portion of the bias in the estimated regression parameter. Simulation studies suggest that standard measurement error adjustments using the reliability ratio (i.e., the ratio of the measurement-error-free variance to the observed variance with measurement error) can correct most of the bias introduced by these interviewer effects in a variety of complex settings, suggesting that more routine adjustment for such effects should be considered in regression analysis using survey data.
Precision inhibitory stimulation of individual-specific cortical hubs disrupts information processing in humans
Authors: Lynch Charles J. , Breeden Andrew L. , Gordon Evan M. , Cherry Joseph B. C. , Turkeltaub Peter E. , Vaidya Chandan J. 
Published: March 2018

ABSTRACTNon-invasive brain stimulation (NIBS) is a promising treatment for psychiatric and neurologic conditions, but outcomes are variable across treated individuals. This variability may be due in part to uncertainty in the selection of the stimulation site – a challenge complicated further by the variable organization of individual human brains. In principle, precise targeting of individual-specific brain areas serving outsized roles in cognition could improve the efficacy of NIBS. Network theory predicts that the importance of a node in network can be inferred from its connections; as such, we hypothesized that targeting individual-specific “hub” brain areas with NIBS would impact cognition more than non-hub brain areas. We first demonstrate that the spatial positioning of hubs is variable across individuals, but highly-reproducible when mapped with sufficient per-individual rsfMRI data. We then tested our hypothesis in healthy individuals using a prospective, within-subject, double-blind design. We found that inhibiting a hub with NIBS disrupted information processing during working-memory to a greater extent than inhibiting a non-hub area of the same gyrus. Furthermore, inhibition of hubs linking specific control networks and sensorimotor systems was retrospectively found to be most impactful. Based on these findings, we propose that precise mapping of individual-specific brain network features could inform future interventions in patients.SIGNIFICANCE STATEMENTThe network organization of every person’s brain is different, but non-invasive brain stimulation (NIBS) interventions do not take this variation into account. Here we demonstrate that the spatial positions of brain areas theoretically serving important roles in cognition, called hubs, differs across individual humans, but are stable within an individual upon repeated neuroimaging. We found that administering NIBS to these individual-specific hub brain areas impacted cognition more than stimulation of non-hub areas. This finding indicates that future NIBS interventions can target individual-specific, but cognitively-relevant features of human brains.
Fluorescence-based detection of natural transformation in drug resistant Acinetobacter baumannii
Authors: Godeux Anne-Sophie , Lupo Agnese , Haenni Marisa , Guette-Marquet Simon , Wilharm Gottfried , Laaberki Maria-Halima , Charpentier Xavier 
Published: March 2018

ABSTRACTAcinetobacter baumannii is a nosocomial agent with a high propensity for developing resistance to antibiotics. This ability relies on horizontal gene transfer mechanisms occurring in the Acinetobacter genus, including natural transformation. To study natural transformation in bacteria, the most prevalent method uses selection for the acquisition of an antibiotic resistance marker in a target chromosomal locus by the recipient cell. Most clinical isolates of A. baumannii are resistant to multiple antibiotics limiting the use of such selection-based method. Here we report the development of a phenotypic and selection-free method based on flow cytometry to detect transformation events in multidrug resistant (MDR) clinical A. baumannii isolates. To this end, we engineered a translational fusion between the abundant and conserved A. baumannii nucleoprotein (HU) and the superfolder green fluorescent protein (sfGFP). The new method was benchmarked against the conventional antibiotic selection-based method. Using this new method, we investigated several parameters affecting transformation efficiencies and identified conditions of transformability one hundred times higher than those previously reported. Using optimized transformation conditions, we probed natural transformation in a set of MDR clinical and non-clinical animal A. baumannii isolates. Regardless of their origin, the majority of the isolates displayed natural transformability, indicative of a conserved trait in the species. Overall, this new method and optimized protocol will greatly facilitate the study of natural transformation in the opportunistic pathogen A. baumannii.
Development and Validation of a Nomogram Prognostic Model for Small-Cell Lung Cancer Patients
Authors: Wang Shidan , Yang Lin , Maclean Matthew , Gerber David E. , Xiao Guanghua , Xie Yang 
Published: March 2018

AbstractBackgroundSmall-cell lung cancer (SCLC) accounts for almost 15% of lung cancer cases in the United States. Nomogram prognostic models could greatly facilitate risk stratification and treatment planning, as well as more refined enrollment criteria for clinical trials. We developed and validated a new nomogram prognostic model for SCLC patients using a large SCLC patient cohort from the National Cancer Database (NCDB).MethodsClinical data of 24,680 SCLC patients diagnosed from 2004 to 2011 were used to develop the nomogram prognostic model. The model was then validated using an independent cohort of 9,700 SCLC patients diagnosed from 2012 to 2013. The prognostic performance was evaluated using p value, concordance index and integrated Area Under the (time dependent Receiver Operating Characteristic) Curve.ResultsThe following variables were contained in the final prognostic model: age, gender, race, ethnicity, Charlson/Deyo Score, TNM Stage (assigned according to the AJCC 8th edition), treatment type (combination of surgery, radiation therapy and chemotherapy), and laterality. The model was validated in an independent testing group with a concordance index of 0.722 ± 0.004 and an integrated AUC of 0.79. The nomogram model has a significantly higher prognostic accuracy than previously developed models, including the AJCC 8th edition TNM-staging system. We implemented the proposed nomogram and two previously published nomograms in an online webserver.ConclusionsWe developed a nomogram prognostic model for SCLC patients, and validated the model using an independent patient cohort. The nomogram performs better than earlier models, including AJCC staging.
Unsupervised discovery of temporal sequences in high-dimensional datasets, with applications to neuroscience
Authors: Mackevicius Emily L. , Bahle Andrew H. , Williams Alex H. , Gu Shijie , Denissenko Natalia I. , Goldman Mark S. , Fee Michale S. 
Published: March 2018

AbstractIdentifying low-dimensional features that describe large-scale neural recordings is a major challenge in neuroscience. Repeated temporal patterns (sequences) are thought to be a salient feature of neural dynamics, but are not succinctly captured by traditional dimensionality reduction techniques. Here we describe a software toolbox—called seqNMF—with new methods for extracting informative, non-redundant, sequences from high-dimensional neural data, testing the significance of these extracted patterns, and assessing the prevalence of sequential structure in data. We test these methods on simulated data under multiple noise conditions, and on several real neural and behavioral data sets. In hippocampal data, seqNMF identifies neural sequences that match those calculated manually by reference to behavioral events. In songbird data, seqNMF discovers neural sequences in untutored birds that lack stereotyped songs. Thus, by identifying temporal structure directly from neural data, seqNMF enables dissection of complex neural circuits without relying on temporal references from stimuli or behavioral outputs.
Variability and reliability of effective connectivity within the core default mode network: A longitudinal spectral DCM study
Authors: Almgren Hannes , de Steen Frederik Van , Kühn Simone , Razi Adeel , Friston Karl , Marinazzo Daniele 
Published: March 2018

AbstractDynamic causal modelling (DCM) for resting state fMRI – namely spectral DCM – is a recently developed and widely adopted method for inferring effective connectivity in intrinsic brain networks. Most research applying spectral DCM has focused on group-averaged connectivity within large-scale intrinsic brain networks; however, the consistency of subject- and session-specific estimates of effective connectivity has not been evaluated. Establishing reliability (within subjects) is crucial for its clinical use; e.g., as a neurophysiological phenotype of disease progression. Effective connectivity during rest is likely to vary due to changes in cognitive, behavioural, and physical states. Determining the sources of fluctuations in effective connectivity may yield greater understanding of brain processes and inform clinical applications about potential confounds. In the present study, we investigated the consistency of effective connectivity within and between subjects, as well as potential sources of variability (e.g., hemispheric asymmetry). We further investigated how standard procedures for data processing and signal extraction affect this consistency. DCM analyses were applied to four longitudinal resting state fMRI datasets. Our sample consisted of 20 subjects with 653 resting state fMRI sessions in total. These data allowed to quantify the robustness of connectivity estimates for each subject, and to draw conclusions beyond specific data features. We found that subjects contributing to all datasets showed systematic and reliable patterns of hemispheric asymmetry. When asymmetry was taken into account, subjects showed very similar connectivity patterns. We also found that various processing procedures (e.g. global signal regression and ROI size) had little effect on inference and reliability of connectivity for the majority of subjects. Bayesian model reduction increased reliability (within-subjects) and stability (between-subjects) of connectivity patterns.
Attention and Emotion-Enhanced Memory: A Systematic Review and Meta-Analysis of Behavioural and Neuroimaging Evidence
Authors: Cross Zachariah R. , Santamaria Amanda , Kohler Mark J. 
Published: March 2018

ABSTRACTThe interaction between attention and emotion is posited to influence long-term memory consolidation. We systematically reviewed experiments investigating the influence of attention on emotional memory to determine: (i) the reported effect of attention on memory for emotional stimuli, and (ii) whether there is homogeneity between behavioural and neuroimaging based effects. Over half of the 47 included experiments found a moderate-to-large effect of attention on emotional memory as measured behaviourally. However, eye-tracking research provide mixed support for the role of attention-related processes in facilitating emotional information into long-term memory. Similarly, modulations in sensory-related components at encoding were not predictive of long-term memory formation, whereas later components appear to differentially reflect the allocation of attention to heterogeneous emotional stimuli. This dissociation in neurophysiology is paralleled by the activation of distinct neural networks under full- and divided-attention conditions. We quantified the effects of the behavioural, eye-tracking and neuroimaging findings via meta-analysis to show that the neural substrates of attention-related emotional memory enhancement may be sensitive to specific methodological parameters.
SoS Notebook: An Interactive Multi-Language Data Analysis Environment
Authors: Peng Bo , Wang Gao , Ma Jun , Leong Man Chong , Wakefield Chris , James Melott , Chiu Yulun , Du Di , Weinstein John N. 
Published: March 2018

AbstractMotivationComplex bioinformatic data analysis workflows involving multiple scripts in different languages can be difficult to consolidate, share, and reproduce. An environment that streamlines the entire processes of data collection, analysis, visualization and reporting of such multi-language analyses is currently lacking.ResultsWe developed Script of Scripts (SoS) Notebook, a web-based notebook environment that allows the use of multiple scripting language in a single notebook, with data flowing freely within and across languages. SoS Notebook enables researchers to perform sophisticated bioinformatic analysis using the most suitable tools for different parts of the workflow, without the limitations of a particular language or complications of cross-language communications.AvailabilitySoS Notebook is hosted at http://vatlab.github.io/SoS/ and is distributed under a BSD license.Contactbpeng@mdanderson.org
Clustering trees: a visualisation for evaluating clusterings at multiple resolutions
Authors: Zappia Luke , Oshlack Alicia 
Published: March 2018

AbstractClustering techniques are widely used in the analysis of large data sets to group together samples with similar properties. For example, clustering is often used in the field of single-cell RNA-sequencing in order to identify different cell types present in a tissue sample. There are many algorithms for performing clustering and the results can vary substantially. In particular, the number of groups present in a data set is often unknown and the number of clusters identified by an algorithm can change based on the parameters used. To explore and examine the impact of varying clustering resolution we present clustering trees. This visualisation shows the relationships between clusters at multiple resolutions allowing researchers to see how samples move as the number of clusters increases. In addition, meta-information can be overlaid on the tree to inform the choice of resolution and guide in identification of clusters. We illustrate the features of clustering trees using a series of simulations as well as two real examples, the classical iris dataset and a complex single-cell RNA-sequencing dataset. Clustering trees can be produced using the clustree R package available from CRAN (https://CRAN.R-project.org/package=clustree) and developed on GitHub (https://github.com/lazappi/clustree).