bluuebunny/crossref_metadata_2025_split huggingface dataset:
A User‐based Visual Analytics Workflow for Exploratory Model Analysis
Authors: Cashman Dylan , Humayoun Shah Rukh , Heimerl Florian , Park Kendall , Das Subhajit , Thompson John , Saket Bahador , Mosca Abigail , Stasko John , Endert Alex , Gleicher Michael , Chang Remco 
Published: July 2019

AbstractMany visual analytics systems allow users to interact with machine learning models towards the goals of data exploration and insight generation on a given dataset. However, in some situations, insights may be less important than the production of an accurate predictive model for future use. In that case, users are more interested in generating of diverse and robust predictive models, verifying their performance on holdout data, and selecting the most suitable model for their usage scenario. In this paper, we consider the concept of Exploratory Model Analysis (EMA), which is defined as the process of discovering and selecting relevant models that can be used to make predictions on a data source. We delineate the differences between EMA and the well‐known term exploratory data analysis in terms of the desired outcome of the analytic process: insights into the data or a set of deployable models. The contributions of this work are a visual analytics system workflow for EMA, a user study, and two use cases validating the effectiveness of the workflow. We found that our system workflow enabled users to generate complex models, to assess them for various qualities, and to select the most relevant model for their task.
The Dependent Vectors Operator
Authors: Hofmann Lutz , Sadlo Filip 
Published: July 2019

AbstractIn this paper, we generalize the parallel vectors operator due to Peikert and Roth to arbitrary dimension, i.e., to four‐dimensional fields and beyond. Whereas the original operator tested for parallelism of two (derived) 2D or 3D vector fields, we reformulate the concept in terms of linear dependency of sets of vector fields, and propose a generic technique to extract and filter the solution manifolds. We exemplify our approach for vortex cores, bifurcations, and ridges as well as valleys in higher dimensions.
Robust Reference Frame Extraction from Unsteady 2D Vector Fields with Convolutional Neural Networks
Authors: Kim Byungsoo , Günther Tobias 
Published: July 2019

AbstractRobust feature extraction is an integral part of scientific visualization. In unsteady vector field analysis, researchers recently directed their attention towards the computation of near‐steady reference frames for vortex extraction, which is a numerically challenging endeavor. In this paper, we utilize a convolutional neural network to combine two steps of the visualization pipeline in an end‐to‐end manner: the filtering and the feature extraction. We use neural networks for the extraction of a steady reference frame for a given unsteady 2D vector field. By conditioning the neural network to noisy inputs and resampling artifacts, we obtain numerically stabler results than existing optimization‐based approaches. Supervised deep learning typically requires a large amount of training data. Thus, our second contribution is the creation of a vector field benchmark data set, which is generally useful for any local deep learning‐based feature extraction. Based on Vatistas velocity profile, we formulate a parametric vector field mixture model that we parameterize based on numerically‐computed example vector fields in near‐steady reference frames. Given the parametric model, we can efficiently synthesize thousands of vector fields that serve as input to our deep learning architecture. The proposed network is evaluated on an unseen numerical fluid flow simulation.
Visualization Support for Developing a Matrix Calculus Algorithm: A Case Study
Authors: Giesen Joachim , Klaus Julien , Laue Sören , Schreck Ferdinand 
Published: July 2019

AbstractThe development of custom interactive visualization tools for specific domains and applications has been made much simpler recently by a surge of visualization tools, libraries and frameworks. Most of these tools are developed for classical data science applications, where a user is supported in analyzing measured or simulated data. But recently, there has also been an increasing interest in visual support for understanding machine learning algorithms and frameworks, especially for deep learning. Many, if not most, of the visualization support for (deep) learning addresses the developer of the learning system and not the end user (data scientist). Here we show on a specific example, namely the development of a matrix calculus algorithm, that supporting visualizations can also greatly benefit the development of algorithms in classical domains like in our case computer algebra. The idea is similar to visually supporting the understanding of learning algorithms, namely provide the developer with an interactive, visual tool that provides insights into the workings and, importantly, also into the failures of the algorithm under development. Developing visualization support for matrix calculus development went similar as the development of more traditional visual support systems for data analysts. First, we had to acquaint ourselves with the problem, its language and challenges by talking to the core developer of the matrix calculus algorithm. Once we understood the challenge, it was fairly easy to develop visual support that streamlined the development of the matrix calculus algorithm significantly.
Ray Tracing Generalized Tube Primitives: Method and Applications
Authors: Han Mengjiao , Wald Ingo , Usher Will , Wu Qi , Wang Feng , Pascucci Valerio , Hansen Charles D. , Johnson Chris R. 
Published: July 2019

AbstractWe present a general high‐performance technique for ray tracing generalized tube primitives. Our technique efficiently supports tube primitives with fixed and varying radii, general acyclic graph structures with bifurcations, and correct transparency with interior surface removal. Such tube primitives are widely used in scientific visualization to represent diffusion tensor imaging tractographies, neuron morphologies, and scalar or vector fields of 3D flow. We implement our approach within the OSPRay ray tracing framework, and evaluate it on a range of interactive visualization use cases of fixed‐ and varying‐radius streamlines, pathlines, complex neuron morphologies, and brain tractographies. Our proposed approach provides interactive, high‐quality rendering, with low memory overhead.
Visual Analysis of Charge Flow Networks for Complex Morphologies
Authors: Kottravel S. , Falk M. , Masood T. Bin , Linares M. , Hotz I. 
Published: July 2019

AbstractIn the field of organic electronics, understanding complex material morphologies and their role in efficient charge transport in solar cells is extremely important. Related processes are studied using the Ising model and Kinetic Monte Carlo simulations resulting in large ensembles of stochastic trajectories. Naive visualization of these trajectories, individually or as a whole, does not lead to new knowledge discovery through exploration. In this paper, we present novel visualization and exploration methods to analyze this complex dynamic data, which provide succinct and meaningful abstractions leading to scientific insights. We propose a morphology abstraction yielding a network composed of material pockets and the interfaces, which serves as backbone for the visualization of the charge diffusion. The trajectory network is created using a novel way of implicitly attracting the trajectories to the skeleton of the morphology relying on a relaxation process. Each individual trajectory is then represented as a connected sequence of nodes in the skeleton. The final network summarizes all of these sequences in a single aggregated network. We apply our method to three different morphologies and demonstrate its suitability for exploring this kind of data.
Kyrix: Interactive Pan/Zoom Visualizations at Scale
Authors: Tao Wenbo , Liu Xiaoyu , Wang Yedi , Battle Leilani , Demiralp Çağatay , Chang Remco , Stonebraker Michael 
Published: July 2019

AbstractPan and zoom are basic yet powerful interaction techniques for exploring large datasets. However, existing zoomable UI toolkits such as Pad++ and ZVTM do not provide the backend database support and data‐driven primitives that are necessary for creating large‐scale visualizations. This limitation in existing general‐purpose toolkits has led to many purpose‐built solutions (e.g. Google Maps and ForeCache) that address the issue of scalability but cannot be easily extended to support visualizations beyond their intended data types and usage scenarios. In this paper, we introduce Kyrix to ease the process of creating general and large‐scale web‐based pan/zoom visualizations. Kyrix is an integrated system that provides the developer with a concise and expressive declarative language along with a backend support for performance optimization of large‐scale data. To evaluate the scalability of Kyrix, we conducted a set of benchmarked experiments and show that Kyrix can support high interactivity (with an average latency of 100 ms or below) on pan/zoom visualizations of 100 million data points. We further demonstrate the accessibility of Kyrix through an observational study with 8 developers. Results indicate that developers can quickly learn Kyrix's underlying declarative model to create scalable pan/zoom visualizations. Finally, we provide a gallery of visualizations and show that Kyrix is expressive and flexible in that it can support the developer in creating a wide range of customized visualizations across different application domains and data types.
Efficient Optimal Overlap Removal: Algorithms and Experiments
Authors: Meulemans W. 
Published: July 2019

AbstractMotivated by visualizing spatial data using proportional symbols, we study the following problem: given a set of overlapping squares of varying sizes, minimally displace the squares as to remove the overlap while maintaining the orthogonal order on their centers. Though this problem is NP‐hard, we show that rotating the squares by 45 degrees into diamonds allows for a linear or convex quadratic program. It is thus efficiently solvable even for relatively large instances.This positive result and the flexibility offered by constraint programming allow us to study various trade‐offs for overlap removal. Specifically, we model and evaluate through computational experiments the relations between displacement, scale and order constraints for static data, and between displacement and temporal coherence for time‐varying data. Finally, we also explore the generalization of our methodology to other shapes.
Agreement on endoscopic ultrasonography‐guided tissue specimens: Comparing a 20‐G fine‐needle biopsy to a 25‐G fine‐needle aspiration needle among academic and non‐academic pathologists
Authors: van Riet Priscilla A. , Cahen Djuna L. , Biermann Katharina , Hansen Bettina , Larghi Alberto , Rindi Guido , Fellegara Giovanni , Arcidiacono Paolo , Doglioni Claudio , Liberta Decarli Nicola , Iglesias‐Garcia Julio , Abdulkader Ihab , Lazare Iglesias Hector , Kitano Masayuki , Chikugo Takaaki , Yasukawa Satoru , van der Valk Hans , Nguyen Nam Quoc , Ruszkiewicz Andrew , Giovannini Marc , Poizat Flora , van der Merwe Schalk , Roskams Tania , Santo Erwin , Marmor Silvia , Chang Kenneth , Lin Fritz , Farrell James , Robert Marie , Bucobo Juan Carlos , Heimann Alan , Baldaque‐Silva Francisco , Fernández Moro Carlos , Bruno Marco J. 
Published: July 2019

Background and AimA recently carried out randomized controlled trial showed the benefit of a novel 20‐G fine‐needle biopsy (FNB) over a 25‐G fine‐needle aspiration (FNA) needle. The current study evaluated the reproducibility of these findings among expert academic and non‐academic pathologists.MethodsThis study was a side‐study of the ASPRO (ASpiration versus PROcore) study. Five centers retrieved 74 (59%) consecutive FNB and 51 (41%) FNA samples from the ASPRO study according to randomization; 64 (51%) pancreatic and 61 (49%) lymph node specimens. Samples were re‐reviewed by five expert academic and five non‐academic pathologists and rated in terms of sample quality and diagnosis. Ratings were compared between needles, expert academic and non‐academic pathologists, target lesions, and cytology versus histological specimens.ResultsBesides a higher diagnostic accuracy, FNB also provided for a better agreement on diagnosing malignancy (ĸ = 0.59 vs ĸ = 0.76, P < 0.001) and classification according to Bethesda (ĸ = 0.45 vs ĸ = 0.61, P < 0.001). This equally applied for expert academic and non‐academic pathologists and for pancreatic and lymph node specimens. Sample quality was also rated higher for FNB, but agreement ranged from poor (ĸ = 0.04) to fair (ĸ = 0.55). Histology provided better agreement than cytology, but only when a core specimen was obtained with FNB (P = 0.004 vs P = 0.432).ConclusionThis study shows that the 20‐G FNB outperforms the 25‐G FNA needle in terms of diagnostic agreement, independent of the background and experience of the pathologist. This endorses use of the 20‐G FNB needle in both expert and lower volume EUS centers.
Creative Leadership: Embedding Global Ideas in a Local Context
Authors: Gadzheva Ivelina 
Published: July 2019

In Bulgaria, design is still seen in terms of “making pretty” or, simply, “making things.” This founder of Design for All Bulgaria is helping people see how design can be a way to address social, economic, environmental, and technical challenges.A Bulgarian designer tackles her country’s attitude about “design as art or product‐making” with a human‐centered approach to big issues like health and ageing.
The resource‐mediated modular structure of a non‐symbiotic ant–plant mutualism
Authors: Ballarin Caio S. , Hachuy‐Filho Leandro , Sanz‐Veiga Priscila A. , Amorim Felipe W. 
Published: July 2019

1. Plant–animal mutualisms are key processes that influence community structure, dynamics, and function. They reflect several neutral and niche‐based mechanisms related to plant–animal interactions.2. However, the strength with which these processes influence community structure depends on functional traits that influence the interactions between mutualistic partners. In mutualisms involving plants and ants, nectar is the most common reward, and traits such as quantity and quality can affect ant species' responses by influencing their recruitment rates and aggressiveness.3. In this study, nectar traits that mediate ant–plant defensive mutualisms were manipulated to test whether resource quantity and quality affect the structure of ant–plant interaction networks. A downscaling approach was used to investigate the interaction network between ant species and individual plants of the extrafloral nectary‐bearing terrestrial orchid Epidendrum secundum.4. We found a short‐term reorganization of the ant assemblage that caused the interaction networks to become more specialised and modular in response to a more rewarding nectar gradient. Furthermore, the ant species tended to narrow their foraging range by limiting their associations to one or a few individual plants.5. This study shows that ant species' responses to variable resource traits play an important role in the structure of the ant–plant interaction network. We suggest that more rewarding nectar enhanced aggressiveness and a massive recruitment of some ant species, leading to lower niche overlap and thus a less connected and more specialised network.
Leaf litter traits predominantly control litter decomposition in streams worldwide
Authors: Zhang Menghua , Cheng Xiaoli , Geng Qinghong , Shi Zheng , Luo Yiqi , Xu Xia 
Published: July 2019

AbstractAimLeaf litter decomposition in freshwater ecosystems is a vital process linking ecosystem nutrient cycling, energy transfer and trophic interactions. In comparison to terrestrial ecosystems, in which researchers find that litter traits predominantly regulate litter decomposition worldwide, the dominant factors controlling its decomposition in aquatic ecosystems are still debated, with global patterns not well documented. Here, we aimed to explore general patterns and key drivers (e.g., litter traits, climate and water characteristics) of leaf litter decomposition in streams worldwide.LocationGlobal.Time period1977–2018.Major taxa studiedLeaf litter.MethodsWe synthesized 1,707 records of litter decomposition in streams from 275 studies. We explored variations in decomposition rates among climate zones and tree functional types and between mesh size groups. Regressions were performed to identify the factors that played dominant roles in litter decomposition globally.ResultsLitter decomposition rates did not differ among tropical, temperate and cold climate zones. Decomposition rates of litter from evergreen conifer trees were much lower than those of deciduous and evergreen broadleaf trees, attributed to the low quality of litter from evergreen conifers. No significant differences were found between decomposition rates of litter from deciduous and evergreen broadleaf trees. Additionally, litter decomposition rates were much higher in coarse‐ than in fine‐mesh bags, which controled the entrance of decomposers of different body sizes. Multiple regressions showed that litter traits (including lignin, C:N ratio) and elevation were the most important factors in regulating leaf litter decomposition.Main conclusionsLitter traits predominantly control leaf litter decomposition in streams worldwide. Although further analyses are necessary to explore whether commonalities of the predominant role of litter traits in decomposition exist in both aquatic and terrestrial ecosystems, our findings could contribute to the use of trait‐based approaches in modelling the decomposition of litter in streams globally and exploring mechanisms of land–water–atmosphere carbon fluxes.
Usual walking and obstacle avoidance are influenced by depressive and anxiety symptoms in patients with Parkinson's disease
Authors: Nóbrega‐Sousa Priscila , Orcioli‐Silva Diego , Lirani‐Silva Ellen , Beretta Victor Spiandor , Vitório Rodrigo , Gobbi Lilian Teresa Bucken 
Published: July 2019

AimThe aim of the present study was to analyze the association of depressive and anxiety symptoms with usual walking and obstacle avoidance in patients with Parkinson's disease.MethodsPatients were divided into three groups: without depressive and anxiety symptoms (n = 28); depressive symptoms only (n = 15); and depressive and anxiety symptoms (n = 19). Symptoms of depression and anxiety were evaluated by the Hospital Anxiety and Depression scale. Participants walked across a pathway in two experimental conditions: usual walking and obstacle avoidance. Kinematic data were recorded using an optoelectronic three‐dimensional system.ResultsDuring usual walking, the depressive and anxiety symptoms group presented shorter stride length and longer double support phase compared with the without depressive and anxiety symptoms group, and lower velocity than the without depressive and anxiety symptoms and depressive symptoms groups. During the approach phase of obstacle avoidance, the depressive and anxiety symptoms group decreased the stride length and velocity, whereas the without depressive and anxiety symptoms and depressive symptoms groups did not modulate these parameters. The depressive and anxiety symptoms group also showed shorter step length and velocity, longer step duration, and wider step width during obstacle crossing. Additionally, the depressive and anxiety symptoms group presented shorter foot‐to‐obstacle horizontal distances, and lower horizontal mean velocities during obstacle crossing. Partial correlation analyses showed that both depressive and anxiety symptoms were associated with spatiotemporal gait parameters.ConclusionCombined symptoms of depression and anxiety are associated with walking impairments in patients with Parkinson's disease in both usual walking and obstacle avoidance. Geriatr Gerontol Int 2019; 19: 868–873.
Durable BaO–ZnO–P2O5 glass with small stress‐induced birefringence for lead‐free polarization light‐controlling devices
Authors: Kishimoto Kaoru , Tricot Grégory , Atsumi Taisuke , Murai Shunsuke , Tanaka Katsuhisa , Takebe Hiromichi , Saitoh Akira 
Published: July 2019

AbstractBarium zinc phosphate glasses formulated in the xBaO–(60 − x)ZnO–40P2O5 composition line are investigated for their optical, thermal, and chemical characteristics. These as well as small stress‐induced birefringence were found to be governed by the BaO/ZnO substitution. In addition to the characterization of the properties, the phosphate network was qualitatively and quantitatively described in terms of Q2 and Q1 ratios by 1D 31P magic angle spinning nuclear magnetic resonance spectroscopy experiments that also showed the presence of Q0 sites. It turns out that the small perturbations of their photoelastic, magnetic, and chemical characteristics made these glasses very good candidates for use in polarization‐controlling optical devices.
Oversight and accountability in the social auditing industry: The role of social compliance initiatives
Authors: TERWINDT Carolijn , ARMSTRONG Amy 
Published: July 2019

AbstractThe 2013 Rana Plaza collapse led to increased awareness of abusive working conditions in the garment industry. Much attention has since been paid to the role and responsibility of retailing companies. The responsibility of social auditing companies, however, has often been overlooked. The authors investigate the systems in place to detect and address substandard auditing that fails to detect violations of workers' rights. They find that, in practice, oversight of social auditors and sanctions for substandard audits are both limited. In this light, this article explores how social compliance initiatives can play a role in improving verification of audit quality and ensuring accountability.
Parkin expression reverses mitochondrial dysfunction in fused in sarcoma‐induced amyotrophic lateral sclerosis
Authors: Cha S. J. , Choi H.‐J. , Kim H.‐J. , Choi E. J. , Song K.‐H. , Im D. S. , Kim K. 
Published: July 2019

AbstractFused in sarcoma (FUS) is a DNA/RNA‐binding protein associated with amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration. The exact molecular mechanisms by which FUS results in neurotoxicity have not yet been fully elucidated. Here, we found that parkin is a genetic suppressor of defective phenotypes induced by exogenous human wild type FUS in Drosophila. Although parkin overexpression did not modulate the FUS protein expression level, the locomotive defects in FUS‐expressing larvae and adult flies were rescued by parkin expression. We found that FUS expression in muscle tissues resulted in a reduction of the levels and assembly of mitochondrial complex I and III subunits, as well as decreased ATP. Remarkably, expression of parkin suppressed these mitochondrial dysfunctions. Our results indicate parkin as a neuroprotective regulator of FUS‐induced proteinopathy by recovering the protein levels of mitochondrial complexes I and III. Our findings on parkin‐mediated neuroprotection may expand our understanding of FUS‐induced ALS pathogenesis.