bluuebunny/crossref_metadata_2025_split huggingface dataset:
Demographic and clinical variables affecting mid‐ to late‐life trajectories of plasma ceramide and dihydroceramide species
Authors: Mielke Michelle M. , Bandaru Veera Venkata Ratnam , Han Dingfen , An Yang , Resnick Susan M. , Ferrucci Luigi , Haughey Norman J. 
Published: July 2015

SummaryIt has been increasingly recognized at the basic science level that perturbations in ceramide metabolism are associated with the development and progression of many age‐related diseases. However, the translation of this work to the clinic has lagged behind. Understanding the factors longitudinally associated with plasma ceramides and dihydroceramides (DHCer) at the population level and how these lipid levels change with age, and by sex, is important for the clinical development of future therapeutics and biomarkers focused on ceramide metabolism. We, therefore, examined factors cross‐sectionally and longitudinally associated with plasma concentrations of ceramides and DHCer among Baltimore Longitudinal Study of Aging participants (n = 992; 3960 total samples), aged 55 years and older, with plasma at a mean of 4.1 visits (range 2–6). Quantitative analyses were performed on a high‐performance liquid chromatography‐coupled electrospray ionization tandem mass spectrometer. Linear mixed models were used to assess the relationships between plasma ceramide and DHCer species and demographics, diseases, medications, and lifestyle factors. Women had higher plasma concentrations of most ceramide and DHCer species and showed steeper trajectories of age‐related increases compared to men. Ceramides and DHCer were more associated with waist–hip ratio than body mass index. Plasma cholesterol and triglycerides, prediabetes, and diabetes were associated with ceramides and DHCer, but the relationship showed specificity to the acyl chain length and saturation. These results demonstrate the importance of examining the individual species of ceramides and DHCer, and of establishing whether intra‐individual age‐ and sex‐specific changes occur in synchrony to disease onset and progression.
Assessing Incremental Value of Biomarkers with Multi-phase Nested Case-control Studies
Authors: Zhou Qian M. , Zheng Yingye , Chibnik Lori B. , Karlson Elizabeth W. , Cai Tianxi 
Published: July 2015

Summary
Accurate risk prediction models are needed to identify different risk groups for individualized prevention and treatment strategies. In the Nurses’ Health Study, to examine the effects of several biomarkers and genetic markers on the risk of rheumatoid arthritis (RA), a three-phase nested case-control (NCC) design was conducted, in which two sequential NCC subcohorts were formed with one nested within the other, and one set of new markers measured on each of the subcohorts. One objective of the study is to evaluate clinical values of novel biomarkers in improving upon existing risk models because of potential cost associated with assaying biomarkers. In this paper, we develop robust statistical procedures for constructing risk prediction models for RA and estimating the incremental value (IncV) of new markers based on three-phase NCC studies. Our method also takes into account possible time-varying effects of biomarkers in risk modeling, which allows us to more robustly assess the biomarker utility and address the question of whether a marker is better suited for short-term or long-term risk prediction. The proposed procedures are shown to perform well in finite samples via simulation studies.
Identifying Longitudinal Trends within EEG Experiments
Authors: Hasenstab Kyle , Sugar Catherine A. , Telesca Donatello , McEvoy Kevin , Jeste Shafali , Şentürk Damla 
Published: July 2015

Summary
Differential brain response to sensory stimuli is very small (a few microvolts) compared to the overall magnitude of spontaneous electroencephalogram (EEG), yielding a low signal-to-noise ratio (SNR) in studies of event-related potentials (ERP). To cope with this phenomenon, stimuli are applied repeatedly and the ERP signals arising from the individual trials are averaged at the subject level. This results in loss of information about potentially important changes in the magnitude and form of ERP signals over the course of the experiment. In this article, we develop a meta-preprocessing step utilizing a moving average of ERP across sliding trial windows, to capture such longitudinal trends. We embed this procedure in a weighted linear mixed effects model to describe longitudinal trends in features such as ERP peak amplitude and latency across trials while adjusting for the inherent heteroskedasticity created at the meta-preprocessing step. The proposed unified framework, including the meta-processing and the weighted linear mixed effects modeling steps, is referred to as MAP-ERP (moving-averaged-processed ERP). We perform simulation studies to assess the performance of MAP-ERP in reconstructing existing longitudinal trends and apply MAP-ERP to data from young children with autism spectrum disorder (ASD) and their typically developing counterparts to examine differences in patterns of implicit learning, providing novel insights about the mechanisms underlying social and/or cognitive deficits in this disorder.
The quantifiable clinothem – types, shapes and geometric relationships in the Plio‐Pleistocene Giant Foresets Formation, Taranaki Basin, New Zealand
Authors: Anell Ingrid , Midtkandal Ivar 
Published: July 2015

AbstractThe understanding of how clinoforms develop is approached based on shape and dimensions, correlation between geometric parameters, and internal characteristics of clinothems bounded by clinoform surfaces in high‐resolution 2D seismic data from the Giant Foresets Formation, Taranaki Basin, offshore New Zealand. The study subdivides the observed clinothems to identify nine types: 1. Oblique 2. Tangential oblique 3. Tangential oblique chaotic 4. Sigmoidal symmetrical 5. Sigmoidal divergent 6. Sigmoidal chaotic 7. Asymmetrical top‐heavy 8. Asymmetrical bottom‐heavy 9. Complex. Accommodation is a dominant control on the type of clinothem that develops, whereby limited accommodation promotes clinothems with significant shelf‐edge advance and low trajectory angles, while increasing accommodation promotes higher trajectory angles and increased deposition on the shelf. Further variations in shape, slope and deposition are influenced by many factors of which sediment influx appears be a fundamental driver. Sigmoidal clinothems tend to show a strong relationship between their maximum thickness and average thickness, their overall slope and maximum foreset angle, along with a high correlation between average thickness and toe advance. This suggests that they distribute sediment in a manner that may be possible to predict and quantify. The increasing steepness of the foreset slope from bottom‐heavy to symmetrical to top‐heavy clinothems, respectively, is dominantly the result of decreasing sediment influx. The clinothems with the steepest slopes, along with chaotic clinothems, are associated with comparatively large toe advance suggesting a strong link between over‐steepened slopes and/or collapse, and processes promoting sediment deposition along the basin floor. Apart from toe advance, the two types of chaotic clinothems develop differently from each other, and from their assumed parent‐clinothem. Tangential oblique chaotic forms steepen, and shelf‐edge advance is limited, suggesting upper slope collapse. Sigmoidal chaotic clinothems have comparatively higher shelf‐edge advance, lower shelf‐edge trajectories and gentler slopes and profiles, suggesting different processes are responsible for their development and resulting shape.
Unusual prolongation of radiation‐induced G2 arrest in tumor xenografts derived from HeLa cells
Authors: Kaida Atsushi , Miura Masahiko 
Published: July 2015

The effect of ionizing radiation on cell cycle kinetics in solid tumors remains largely unknown because of technical limitations and these tumors' complicated structures. In this study, we analyzed intratumoral cell cycle kinetics after X‐irradiation of tumor xenografts derived from HeLa cells expressing the fluorescent ubiquitination‐based cell cycle indicator (Fucci), a novel system to visualize cell cycle kinetics in vivo. Cell cycle kinetics after X‐irradiation was examined by using tumor sections and in vivo real‐time imaging system in tumor xenografts derived from HeLa cells expressing Fucci. We found that G2 arrest was remarkably prolonged, up to 5 days after 10‐Gy irradiation, in contrast to monolayer cultures where G2 arrest returned within 24 h. Cells isolated from tumors 5 days after irradiation exhibited a higher surviving fraction than those isolated immediately or one day after irradiation. In this study, we clearly demonstrated unusual post‐irradiation cell cycle kinetics in tumor xenografts derived from HeLa‐Fucci cells. Our findings imply that prolonged G2 arrest occurring in tumor microenvironments following irradiation may function as a radioresistance mechanism.
Evaluation of job satisfaction and working atmosphere of dental nurses in Germany
Authors: Goetz Katja , Hasse Philipp , Campbell Stephen M. , Berger Sarah , Dörfer Christof E. , Hahn Karolin , Szecsenyi Joachim 
Published: July 2015

AbstractObjectivesThe purpose of the study was to assess the level of job satisfaction of dental nurses in ambulatory care and to explore the impact of aspects of working atmosphere on and their association with job satisfaction.MethodsThis cross‐sectional study was based on a job satisfaction survey. Data were collected from 612 dental nurses working in 106 dental care practices. Job satisfaction was measured with the 10‐item Warr–Cook–Wall job satisfaction scale. Working atmosphere was measured with five items. Linear regression analyses were performed in which each item of the job satisfaction scale was handled as dependent variables. A stepwise linear regression analysis was performed with overall job satisfaction and the five items of working atmosphere, job satisfaction, and individual characteristics.ResultsThe response rate was 88.3%. Dental nurses were satisfied with ‘colleagues’ and least satisfied with ‘income.’ Different aspects of job satisfaction were mostly associated with the following working atmosphere issues: ‘responsibilities within the practice team are clear,’ ‘suggestions for improvement are taken seriously,’ ‘working atmosphere in the practice team is good,’ and ‘made easier to admit own mistakes.’ Within the stepwise linear regression analysis, the aspect ‘physical working condition’ (β = 0.304) showed the highest association with overall job satisfaction. The total explained variance of the 14 associated variables was 0.722 with overall job satisfaction.ConclusionsWorking atmosphere within this discrete sample of dental care practice seemed to be an important influence on reported working condition and job satisfaction for dental nurses. Because of the high association of job satisfaction with physical working condition, the importance of paying more attention to an ergonomic working position for dental nurses to ensure optimal quality of care is highlighted.
Clinicopathological features and prognosis of familial papillary thyroid carcinoma – a large‐scale, matched, case–control study
Authors: Cao Jun , Chen Can , Chen Chao , Wang Qing‐Liang , Ge Ming‐Hua 
Published: July 2015

SummaryObjectiveIt remains controversial whether or not the aggressiveness of familial nonmedullary thyroid cancer (FNMTC) differs from sporadic carcinoma. The aim of this study was to determine the clinicopathological features and prognosis of FNMTC.DesignA matched‐case comparative study.MethodsThree hundred and seventy‐two patients with familial papillary thyroid carcinoma (FPTC) were enrolled as the study group, and another 372 patients with sporadic PTC were enrolled as controls and matched for gender, age, tumour/node/metastasis (TNM) staging and approximate duration of follow‐up. We compared the differences in the clinicopathological features and prognosis between the subgroups.ResultsCompared with sporadic PTC, patients with FPTC were more likely to present tumour multicentricity, bilateral growth and a concomitant nodular goitre (P < 0·05). In papillary thyroid microcarcinoma (PTMC), a higher recurrence rate was noted in patients with a family history of PTC, and this remained independently predictive on multivariate analysis. The patients with FPTC in the second generation showed an earlier age of onset, more frequent Hashimoto's thyroiditis and a higher recurrence rate than the first generation, while the first‐generation offspring of patients had a higher incidence of nodular goitre than the second generation.ConclusionsThe presence of familial history in PTC indicates an increase in biological aggressiveness, and patients in the second generation may exhibit the ‘genetic anticipation’ phenomenon. At present, the available data are not sufficient to support a more aggressive approach for FPTC. However, a family history of PTC is an independent risk factor for recurrence in patients with PTMC.
Guided Volume Editing based on Histogram Dissimilarity
Authors: Karimov A. , Mistelbauer G. , Auzinger T. , Bruckner S. 
Published: July 2015

AbstractSegmentation of volumetric data is an important part of many analysis pipelines, but frequently requires manual inspection and correction. While plenty of volume editing techniques exist, it remains cumbersome and errorprone for the user to find and select appropriate regions for editing. We propose an approach to improve volume editing by detecting potential segmentation defects while considering the underlying structure of the object of interest. Our method is based on a novel histogram dissimilarity measure between individual regions, derived from structural information extracted from the initial segmentation. Based on this information, our interactive system guides the user towards potential defects, provides integrated tools for their inspection, and automatically generates suggestions for their resolution. We demonstrate that our approach can reduce interaction effort and supports the user in a comprehensive investigation for high‐quality segmentations.
Visualization of Particle‐based Data with Transparency and Ambient Occlusion
Authors: Staib Joachim , Grottel Sebastian , Gumhold Stefan 
Published: July 2015

AbstractParticle‐based simulation techniques, like the discrete element method or molecular dynamics, are widely used in many research fields. In real‐time explorative visualization it is common to render the resulting data using opaque spherical glyphs with local lighting only. Due to massive overlaps, however, inner structures of the data are often occluded rendering visual analysis impossible. Furthermore, local lighting is not sufficient as several important features like complex shapes, holes, rifts or filaments cannot be perceived well.To address both problems we present a new technique that jointly supports transparency and ambient occlusion in a consistent illumination model. Our approach is based on the emission‐absorption model of volume rendering. We provide analytic solutions to the volume rendering integral for several density distributions within a spherical glyph. Compared to constant transparency our approach preserves the three‐dimensional impression of the glyphs much better. We approximate ambient illumination with a fast hierarchical voxel cone‐tracing approach, which builds on a new real‐time voxelization of the particle data.Our implementation achieves interactive frame rates for millions of static or dynamic particles without any preprocessing. We illustrate the merits of our method on real‐world data sets gaining several new insights.
Data‐driven Evaluation of Visual Quality Measures
Authors: Sedlmair M. , Aupetit M. 
Published: July 2015

AbstractVisual quality measures seek to algorithmically imitate human judgments of patterns such as class separability, correlation, or outliers. In this paper, we propose a novel data‐driven framework for evaluating such measures. The basic idea is to take a large set of visually encoded data, such as scatterplots, with reliable human “ground truth” judgements, and to use this human‐labeled data to learn how well a measure would predict human judgements on previously unseen data. Measures can then be evaluated based on predictive performance—an approach that is crucial for generalizing across datasets but has gained little attention so far. To illustrate our framework, we use it to evaluate 15 state‐of‐the‐art class separation measures, using human ground truth data from 828 class separation judgments on color‐coded 2D scatterplots.
An Evaluation of the Impact of Visual Embellishments in Bar Charts
Authors: Skau Drew , Harrison Lane , Kosara Robert 
Published: July 2015

AbstractAs data visualization becomes further intertwined with the field of graphic design and information graphics, small graphical alterations are made to many common chart formats. Despite the growing prevalence of these embellishments, their effects on communication of the charts’ data is unknown. From an overview of the design space, we have outlined some of the common embellishments that are made to bar charts. We have studied the effects of these chart embellishments on the communication of the charts’ data through a series of user studies on Amazon's Mechanical Turk platform. The results of these studies lead to a better understanding of how each chart type is perceived, and help provide guiding principles for the graphic design of charts.
Visualizing Time‐Specific Hurricane Predictions, with Uncertainty, from Storm Path Ensembles
Authors: Liu L. , Mirzargar M. , Kirby R.M. , Whitaker R. , House D. H. 
Published: July 2015

AbstractThe U.S. National Hurricane Center (NHC) issues advisories every six hours during the life of a hurricane. These advisories describe the current state of the storm, and its predicted path, size, and wind speed over the next five days. However, from these data alone, the question “What is the likelihood that the storm will hit Houston with hurricane strength winds between 12:00 and 14:00 on Saturday?” cannot be directly answered. To address this issue, the NHC has recently begun making an ensemble of potential storm paths available as part of each storm advisory. Since each path is parameterized by time, predicted values such as wind speed associated with the path can be inferred for a specific time period by analyzing the statistics of the ensemble. This paper proposes an approach for generating smooth scalar fields from such a predicted storm path ensemble, allowing the user to examine the predicted state of the storm at any chosen time. As a demonstration task, we show how our approach can be used to support a visualization tool, allowing the user to display predicted storm position – including its uncertainty – at any time in the forecast. In our approach, we estimate the likelihood of hurricane risk for a fixed time at any geospatial location by interpolating simplicial depth values in the path ensemble. Adaptivelysized radial basis functions are used to carry out the interpolation. Finally, geometric fitting is used to produce a simple graphical visualization of this likelihood. We also employ a non‐linear filter, in time, to assure frame‐to‐frame coherency in the visualization as the prediction time is advanced. We explain the underlying algorithm and definitions, and give a number of examples of how our algorithm performs for several different storm predictions, and for two different sources of predicted path ensembles.
Feature‐Driven Visual Analytics of Chaotic Parameter‐Dependent Movement
Authors: Luboschik M. , Röhlig M. , Bittig A.T. , Andrienko N. , Schumann H. , Tominski C. 
Published: July 2015

AbstractAnalyzing movements in their spatial and temporal context is a complex task. We are additionally interested in understanding the movements’ dependency on parameters that govern the processes behind the movement. We propose a visual analytics approach combining analytic, visual, and interactive means to deal with the added complexity. The key idea is to perform an analytical extraction of features that capture distinct movement characteristics. Different parameter configurations and extracted features are then visualized in a compact fashion to facilitate an overview of the data. Interaction enables the user to access details about features, to compare features, and to relate features back to the original movement. We instantiate our approach with a repository of more than twenty accepted and novel features to help analysts in gaining insight into simulations of chaotic behavior of thousands of entities over thousands of data points. Domain experts applied our solution successfully to study dynamic groups in such movements in relation to thousands of parameter configurations.
Vector Field Visualization of Advective‐Diffusive Flows
Authors: Hochstetter H. , Wurm M. , Kolb A. 
Published: July 2015

AbstractWe propose a framework for unified visualization of advective and diffusive concentration fluxes, which play a key role in many phenomena like, e.g. Marangoni convection and microscopic mixing. The main idea is the decomposition of fluxes into their concentration and velocity parts. Using this flux decomposition, we are able to convey advective‐diffusive concentration transport using integral lines. In order to visualize superimposed flux effects, we introduce a new graphical metaphor, the stream feather, which adds extensions to stream tubes pointing in the directions of deviating fluxes. The resulting unified visualization of macroscopic advection and microscopic diffusion allows for deeper insight into complex flow scenarios that cannot be achieved with current volume and surface rendering techniques alone.Our approach for flux decomposition and visualization of advective‐diffusive flows can be applied to any kind of (simulation) data if velocity and concentration data are available. We demonstrate that our techniques can easily be integrated into Smoothed Particle Hydrodynamics (SPH) based simulations.
Visualization of Coherent Structures of Light Transport
Authors: Zirr Tobias , Ament Marco , Dachsbacher Carsten 
Published: July 2015

AbstractInspired by vector field topology, an established tool for the extraction and identification of important features of flows and vector fields, we develop means for the analysis of the structure of light transport. For that, we derive an analogy to vector field topology that defines coherent structures in light transport. We also introduce Finite‐Time Path Deflection (FTPD), a scalar quantity that represents the deflection characteristic of all light transport paths passing through a given point in space. For virtual scenes, the FTPD can be computed directly using path‐space Monte Carlo integration. We visualize the FTPD field for several example scenes and discuss the revealed structures. Lastly, we show that the coherent regions visualized by the FTPD are closely related to the coherent regions in our new topologically‐motivated analysis of light transport. FTPD visualizations are thus also visualizations of the structure of light transport.