bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Comparison Study of Frying Conditions on Furan Formation in 3 Potato Varieties
Authors: Yuan Yuan , Chen Dongyan , Liu Huangyou , Wu Sijia , Yan Haiyang 
Published: July 2016

AbstractFuran, a typical food contaminant formed by heating process, is classified as a possible carcinogen to humans. Many factors lead to the formation of furan in food processing. In our present study, 3 potato varieties, white potato, sweet potato, and purple potato were selected to investigate the effect of thermal processing temperature and time on furan formation. The results showed that the formation of furan was highly correlated with frying temperature and time. Among the 3 potato varieties, sweet potato resulted in the highest furan concentration when fried at 200 °C for 5 min. In addition, the frying temperature and time also influenced the water activity and the color of the 3 kinds of potato slices, which had significant correlation with the formation of furan. Furan concentration decreased along with the increasing of water activity in the 3 potato varieties and the changes presented regression relationships. Meanwhile, there was an inverse correlation between furan content and color changes in the 3 potato varieties. The level of furan decreased as total color changes (ΔE) increased and the changes also presented regression relationships. These results could be used to estimate the possibility of furan formation in the 3 varieties of potato slices systems.
The red imported fire ant, Solenopsis invicta, modifies predation at the soil surface and in cotton foliage
Authors: Wickings K. , Ruberson J.R. 
Published: July 2016

AbstractRed imported fire ants, Solenopsis invicta, are generalist predators that can have major impacts on foliar arthropod communities in agricultural systems; however, their effects as predators at the soil surface have not been adequately characterized. We examined the contribution of fire ants to predation at the soil surface and in cotton foliage at two sites and over the course of two field seasons in Georgia, using egg masses of the beet armyworm, Spodoptera exigua. To assess interactions between fire ants and other arthropod species, we also measured the densities of edaphic predators and honeydew‐producing hemipterans at both sites. The sites occurred in different growing regions (Piedmont and Coastal Plain), and allowed us to characterize the importance of fire ants as predators under different climatic and soil conditions. Fire ant suppression decreased egg predation at both field sites, and predation by fire ants at the soil surface was equal to if not greater than that in cotton foliage. However, the impact of fire ants on predation varied between sites, likely due to differences in climate and the composition and activity of the extant arthropod communities. Our study also indicates that fire ant suppression is associated with decreases in the density of honeydew‐producing insects, and increasing abundance of whiteflies on the plants coincided with a decrease in egg predation at the soil surface. This finding suggests the mutualism between ants and whiteflies may lead to a shift in predation intensity from edaphic towards plant‐based food webs.
Randomized controlled trial of a messaging intervention to increase fruit and vegetable intake in adolescents: Affective versus instrumental messages
Authors: Carfora Valentina , Caso Daniela , Conner Mark 
Published: July 2016

ObjectiveThe present research aimed to test the efficacy of affective and instrumental text messages compared with a no‐message control as a strategy to increase fruit and vegetable intake (FVI) in adolescents.DesignA randomized controlled trial was used test impact of different text messages compared with no message on FVI over a 2‐week period.MethodA total of 1,065 adolescents (14–19 years) from a high school of the South of Italy completed the baseline questionnaire and were randomly allocated to one of three conditions: instrumental messages (N = 238), affective messages (N = 300), and no messages (N = 521). Students in the message conditions received one message each day over a 2‐week period. The messages targeted affective (affective benefits) or instrumental (instrumental benefits) information about FVI. Self‐reported FVI at 2 weeks was the key dependent variable. Analyses were based on the N = 634 who completed all aspects of the study.ResultsFindings showed that messages significantly increased FVI, particularly in the affective condition and this effect was partially mediated by changes in affective attitude and intentions towards FVI.ConclusionText messages can be used to increase FVI in adolescents. Text messages based on affective benefits are more effective than text messages based on instrumental benefits.
Statement of contribution

What is already known on this subject?

Text messages have been shown to promote positive change in health behaviours. However, the most appropriate target for such text messages is less clear although targeting attitudes may be effective.

What does this study add?

This randomized controlled study shows that text messages targeting instrumental or affective attitudes produce changes in fruit and vegetable intake (FVI) in adolescents.

Text messages targeting affective attitudes are shown to be more effective than text messages targeting instrumental attitudes.

The effect of affective text messages on FVI was partially mediated by changes in affective attitudes.
Reverse migration of lithofacies boundaries and shoreline in response to sea‐level rise
Authors: Baumanis Carolina , Kim Wonsuck 
Published: July 2016

AbstractThe migration of the lithofacies boundaries preserved in the sedimentary record is key to interpreting changes in depositional environments. Grain size is one of the most recognizable physical characteristics of lithofacies. The advance and retreat of grain‐size breaks, as a proxy for lithofacies boundaries (e.g. gravel–sand transition), is commonly attributed to variations in external controls (e.g. climate, sea level and tectonic subsidence). While most models of fluviodeltaic systems focus on predicting the response of the shoreline to these forcings, none have thoroughly incorporated the migration of grain‐size transitions (GST) that coevolve with the shoreline. We present a numerical delta evolution model that treats both the shoreline and GST as moving boundaries to provide quantitative understanding of the dynamic interaction between the downstream boundary (shoreline) and the upstream lithofacies boundaries (GSTs) of the fluviodeltaic system under relative sea‐level rise. We tested a range of relative sea‐level rise rates in the model. The shoreline and GST gradually reduced their progradation rates and eventually retreated landward as the fluviodeltaic topset and foreset elongated. However, their timings of retreat were different, resulting in a counterintuitive case for a quicker retreat of GST while the shoreline still continued to advance. A series of scaled flume experiments with a sand and crushed walnut sediment mixture captured the same behaviours of these two moving boundaries. We found that GST experienced higher relative sea‐level rise (RSLR) rates than the shoreline. This additional RSLR rate scales with the downstream river slope and the shoreline progradation rate to cause earlier GST retreat in comparison to the shoreline. The fundamental understanding from this study of migration of both the GST and shoreline in fluviodeltaic systems will aid in accurately assessing the trajectories of GST in sedimentary strata as a proxy for environmental change.
Natural history, risk factors and clinical features of primary hypogonadism in ageing men: Longitudinal Data from the European Male Ageing Study
Authors: Ahern Tomás , Swiecicka Agnieszka , Eendebak Robert J.A.H. , Carter Emma L. , Finn Joseph D. , Pye Stephen R. , O'Neill Terence W. , Antonio Leen , Keevil Brian , Bartfai György , Casanueva Felipe F. , Forti Gianni , Giwercman Aleksander , Han Thang S. , Kula Krzysztof , Lean Michael E.J. , Pendleton Neil , Punab Margus , Rastrelli Giulia , Rutter Martin K , Vanderschueren Dirk , Huhtaniemi Ilpo T. , Wu Frederick C.W. ,   the EMAS study group
Published: July 2016

SummaryObjectiveIn ageing men, the incidence and clinical significance of testosterone (T) decline accompanied by elevated luteinizing hormone (LH) are unclear. We describe the natural history, risk factors and clinical features associated with the development of biochemical primary hypogonadism (PHG, T < 10·5 nmol/l and LH>9·4U/l) in ageing men.Design, Patients and MeasurementsA prospective observational cohort survey of 3,369 community‐dwelling men aged 40‐79 years, followed up for 4·3 years. Men were classified as incident (i) PHG (eugonadal [EUG, T ≥ 10·5 nmol/l] at baseline, PHG at follow‐up), persistent (p) PHG (PHG at baseline and follow‐up), pEUG (EUG at baseline and follow‐up) and reversed (r) PHG (PHG at baseline, EUG at follow‐up). Predictors and changes in clinical features associated with the development of PHG were analysed by regression models.ResultsOf 1,991 men comprising the analytical sample, 97·5% had pEUG, 1·1% iPHG, 1·1% pPHG and 0·3% rPHG. The incidence of PHG was 0·2%/year. Higher age (>70 years) [OR 12·48 (1·27–122·13), P = 0·030] and chronic illnesses [OR 4·24 (1·08–16·56); P = 0·038] predicted iPHG. Upon transition from EUG to PHG, erectile function, physical vigour and haemoglobin worsened significantly. Men with pPHG had decreased morning erections, sexual thoughts and haemoglobin with increased insulin resistance.ConclusionsPrimary testicular failure in men is uncommon and predicted by old age and chronic illness. Some clinical features attributable to androgen deficiency, but not others, accompanied the T decline in men who developed biochemical PHG. Whether androgen replacement can improve sexual and/or physical function in elderly men with PHG merits further study.
Enhancing Scatterplots with Multi‐Dimensional Focal Blur
Authors: Staib J. , Grottel S. , Gumhold S. 
Published: July 2016

AbstractScatterplots directly depict two dimensions of multi‐dimensional data points, discarding all other information. To visualize all data, these plots are extended to scatterplot matrices, which distribute the information of each data point over many plots. Problems arising from the resulting visual complexity are nowadays alleviated by concepts like filtering and focus and context. We present a method based on depth of field that contains both aspects and injects information from all dimensions into each scatterplot. Our approach is a natural generalization of the commonly known focus effects from optics. It is based on a multidimensional focus selection body. Points outside of this body are defocused depending on their distance. Our method allows for a continuous transition from data points in focus, over regions of blurry points providing contextual information, to visually filtered data. Our algorithm supports different focus selection bodies, blur kernels, and point shapes. We present an optimized GPU‐based implementation for interactive exploration and show the usefulness of our approach on several data sets.
Exploring Items and Features with IF, FI‐Tables
Authors: van der Corput Paul , van Wijk Jarke J. 
Published: July 2016

AbstractThe exploration of high‐dimensional data is challenging because humans have difficulty to understand more than three dimensions. We present a new visualization concept that enables users to explore such data and, specifically, to learn about important items and features that are unknown or overlooked, based on the items and features that are already known. The visualization consists of two juxtaposed tables: an IF‐Table, showing all items with a selection of features; and an FI‐Table, showing all features with a selection of items. This enables the user to limit the number of visible items and features to those needed for the exploration. The interaction is kept simple: each selection of items and features results in a complete overview of similar and relevant items and features.
Arcs, Angles, or Areas: Individual Data Encodings in Pie and Donut Charts
Authors: Skau Drew , Kosara Robert 
Published: July 2016

AbstractPie and donut charts have been a hotly debated topic in the visualization community for some time now. Even though pie charts have been around for over 200 years, our understanding of the perceptual factors used to read data in them is still limited. Data is encoded in pie and donut charts in three ways: arc length, center angle, and segment area. For our first study, we designed variations of pie charts to test the importance of individual encodings for reading accuracy. In our second study, we varied the inner radius of a donut chart from a filled pie to a thin outline to test the impact of removing the central angle. Both studies point to angle being the least important visual cue for both charts, and the donut chart being as accurate as the traditional pie chart.
Visualizing Co‐occurrence of Events in Populations of Viral Genome Sequences
Authors: Sarikaya A. , Correli M. , Dinis J. M. , O'Connor D. H. , Gleicher M. 
Published: July 2016

AbstractVirologists are not only interested in point mutations in a genome, but also in relationships between mutations. In this work, we present a design study to support the discovery of correlated mutation events (called co‐occurrences) in populations of viral genomes. The key challenge is to identify potentially interesting pairs of events within the vast space of event combinations. In our work, we identify analyst requirements and develop a prototype through a participatory process. The key ideas of our approach are to use interest metrics to create dynamic filtering that guides the viewer to interesting and relevant correlations of genome mutations, and to provide visual encodings designed to fit scientists' mental map of the data, along with dynamic filtering techniques. We demonstrate the strength of our approach in virology‐situated case studies, and offer suggestions for extending our strategy to other sequence‐based domains.
Visual Analysis of Tumor Control Models for Prediction of Radiotherapy Response
Authors: Raidou R.G. , Casares‐Magaz O. , Muren L.P. , van der Heide U.A. , Rørvik J. , Breeuwer M. , Vilanova A. 
Published: July 2016

AbstractIn radiotherapy, tumors are irradiated with a high dose, while surrounding healthy tissues are spared. To quantify the probability that a tumor is effectively treated with a given dose, statistical models were built and employed in clinical research. These are called tumor control probability (TCP) models. Recently, TCP models started incorporating additional information from imaging modalities. In this way, patient‐specific properties of tumor tissues are included, improving the radiobiological accuracy of models. Yet, the employed imaging modalities are subject to uncertainties with significant impact on the modeling outcome, while the models are sensitive to a number of parameter assumptions. Currently, uncertainty and parameter sensitivity are not incorporated in the analysis, due to time and resource constraints. To this end, we propose a visual tool that enables clinical researchers working on TCP modeling, to explore the information provided by their models, to discover new knowledge and to confirm or generate hypotheses within their data. Our approach incorporates the following four main components: (1) It supports the exploration of uncertainty and its effect on TCP models; (2) It facilitates parameter sensitivity analysis to common assumptions; (3) It enables the identification of inter‐patient response variability; (4) It allows starting the analysis from the desired treatment outcome, to identify treatment strategies that achieve it. We conducted an evaluation with nine clinical researchers. All participants agreed that the proposed visual tool provides better understanding and new opportunities for the exploration and analysis of TCP modeling.
Dynamic Change Arcs to Explore Model Forecasts
Authors: Jean C. St. , Ware C. , Gamble R. 
Published: July 2016

AbstractIn many planning applications, a computational model is used to make predictions about the effects of management or engineering decisions. To understand the implications of alternative scenarios, a user typically adjusts one or more of the input parameters, runs the model, and examines the outcomes using simple charts. For example, a time series showing changes in productivity or revenue might be generated. While this approach can be effective in showing the projected effects of changes to the model's input parameters, it fails to show the mechanisms that cause those changes. In order to promote understanding of model mechanics using a simple graphical device, we propose dynamic change arcs. Dynamic change arcs graphically reveal the internal model structure as cause and effect linkages. They are signed to show both positive and negative effects. We implemented this concept using a species interaction model developed for fisheries management based on a system of Lotka‐Volterra equations. The model has 10 economically important fish species and incorporates both predation and competition between species. The model predicts that changing the catch of one species can sometimes result in changes in biomass of another species through multi‐step causal chains. The dynamic change arcs make it possible to interpret the resulting complex causal chains and interaction effects. We carried out an experiment to evaluate three alternative forms of arcs for portraying causal connections in the model. The results show that all linkage representations enabled participants to reason better about complex chains of causality than not showing linkages. However, none of them were significantly better than the others.
PhysioEx: Visual Analysis of Physiological Event Streams
Authors: Kamaleswaran Rishikesan , Collins Christopher , James Andrew , McGregor Carolyn 
Published: July 2016

AbstractIn this work, we introduce a novel visualization technique, the Temporal Intensity Map, which visually integrates data values over time to reveal the frequency, duration, and timing of significant features in streaming data. We combine the Temporal Intensity Map with several coordinated visualizations of detected events in data streams to create PhysioEx, a visual dashboard for multiple heterogeneous data streams. We have applied PhysioEx in a design study in the field of neonatal medicine, to support clinical researchers exploring physiologic data streams. We evaluated our method through consultations with domain experts. Results show that our tool provides deep insight capabilities, supports hypothesis generation, and can be well integrated into the workflow of clinical researchers.
There is More to Streamgraphs than Movies: Better Aesthetics via Ordering and Lassoing
Authors: Di Bartolomeo Marco , Hu Yifan 
Published: July 2016

AbstractStreamgraphs were popularized in 2008 when The New York Times used them to visualize box office revenues for 7500 movies over 21 years. The aesthetics of a streamgraph is affected by three components: the ordering of the layers, the shape of the lowest curve of the drawing, known as the baseline, and the labels for the layers. As of today, the ordering and baseline computation algorithms proposed in the paper of Byron and Wattenberg are still considered the state of the art. However, their ordering algorithm exploits statistical properties of the movie revenuedatathat may not hold in otherdata. In addition, the baseline optimization is based on a definition of visual energy that in some cases results in considerable amount of visual distortion. We offer an ordering algorithm that works well regardless of the properties of the inputdata, and propose a 1‐norm based definition of visual energy and the associated solution method that overcomes the limitation of the original baseline optimization procedure. Furthermore, we propose an efficient layer labeling algorithm that scales linearly to thedatasize in place of the brute‐force algorithm adopted by Byron and Wattenberg. We demonstrate the advantage of our algorithms over existing techniques on a number of real worlddatasets.
Similarity Voting based Viewpoint Selection for Volumes
Authors: Tao Yubo , Wang Qirui , Chen Wei , Wu Yingcai , Lin Hai 
Published: July 2016

AbstractPrevious viewpoint selection methods in volume visualization are generally based on some deterministic measures of viewpoint quality. However, they may not express the familiarity and aesthetic sense of users for features of interest. In this paper, we propose an image‐based viewpoint selection model to learn how visualization experts choose representative viewpoints for volumes with similar features. For a given volume, we first collect images with similar features, and these images reflect the viewpoint preferences of the experts when visualizing these features. Each collected image tallies votes to the viewpoints with the best matching based on an image similarity measure, which evaluates the spatial shape and appearance similarity between the collected image and the rendered image from the viewpoint. The optimal viewpoint is the one with the most votes from the collected images, that is, the viewpoint chosen by most visualization experts for similar features. We performed experiments on various volumes available in volume visualization, and made comparisons with traditional viewpoint selection methods. The results demonstrate that our model can select more canonical viewpoints, which are consistent with human perception.
A Visual Analytics Framework for Microblog Data Analysis at Multiple Scales of Aggregation
Authors: Zhang Jiawei , Ahlbrand Benjamin , Malik Abish , Chae Junghoon , Min Zhiyu , Ko Sungahn , Ebert David S. 
Published: July 2016

AbstractReal‐time microblogs can be utilized to provide situational awareness during emergency and disaster events. However, the utilization of these datasets requires the decision makers to perform their exploration and analysis across a range of data scales from local to global, while maintaining a cohesive thematic context of the transition between the different granularity levels. The exploration of different information dimensions at the varied data and human scales remains to be a non‐trivial task. To this end, we present a visual analytics situational awareness environment that supports the real‐time exploration of microblog data across multiple scales of analysis. We classify microblogs based on a fine‐grained, crisis‐related categorization approach, and visualize the spatiotemporal evolution of multiple categories by coupling a spatial lens with a glyph‐based visual design. We propose a transparency‐based spatial context preserving technique that maintains a smooth transition between different spatial scales. To evaluate our system, we conduct user studies and provide domain expert feedback.