bluuebunny/crossref_metadata_2025_split huggingface dataset:
Porosity Maps – Interactive Exploration and Visual Analysis of Porosity in Carbon Fiber Reinforced Polymers
Authors: Reh A. , Plank B. , Kastner J. , Gröller E. , Heinzl C. 
Published: June 2012

AbstractIn this work a novel method for the characterization of porosity in carbon fiber reinforced polymers (CFRP) is presented. A visualization pipeline for the interactive exploration and visual analysis of CFRP specimens is developed to enhance the evaluation workflow for non‐destructive testing (NDT) practitioners based on specified tasks. Besides quantitative porosity determination and the calculation of local pore properties, i.e., volume, surface, dimensions and shape factors, we employ a drill‐down approach to explore pores in a CFRP specimen. We introduce Porosity Maps (PM), to allow for a fast porosity evaluation of the specimen. Pores are filtered in two stages. First a region of interest is selected in the porosity maps. Second, pores are filtered with parallel coordinates according to their local properties. Furthermore a histogram‐based best‐viewpoint widget was implemented to visualize the quality of viewpoints on a sphere. The advantages of our approach are demonstrated using real world CFRP specimens. We are able to show that our visualization‐driven approach leads to a better evaluation of CFRP components than existing reference methods.
Comparative Visual Analysis of 2D Function Ensembles
Authors: Piringer H. , Pajer S. , Berger W. , Teichmann H. 
Published: June 2012

AbstractIn the development process of powertrain systems, 2D function ensembles frequently occur in the context of multi‐run simulations. An analysis has many facets, including distributions of extracted features, comparisons between ensemble members and target functions, and details‐on‐demand. The primary contribution of this paper is a design study of an interactive approach for a comparative visual analysis of 2D function ensembles. The design focuses on a tight integration of domain‐oriented and member‐oriented visualization techniques, and it seeks to preserve the mental model of 2D functions on multiple levels of detail. In this context, we propose a novel focus+context approach for visualizations relying on data‐driven placement which is based on labeling. We also extend work on feature‐preserving downsampling of 2D functions. Our design supports a comparison of 2D functions based on juxtaposition, overlay, and explicit differences. It also enables an analysis in terms of extracted scalar features and 1D aggregations. An evaluation illustrates a workflow in our application context. User feedback indicates a time saving of 70% for common tasks and a qualitative gain for the entire development process.
MarketAnalyzer: An Interactive Visual Analytics System for Analyzing Competitive Advantage Using Point of Sale Data
Authors: Ko S. , Maciejewski R. , Jang Y. , Ebert D. S. 
Published: June 2012

AbstractCompetitive intelligence is a systematic approach for gathering, analyzing, and managing information to make informed business decisions. Many companies use competitive intelligence to identify risks and opportunities within markets. Point of sale data that retailers share with vendors is of critical importance in developing competitive intelligence. However, existing tools do not easily enable the analysis of such large and complex data. therefore, new approaches are needed in order to facilitate better analysis and decision making. In this paper, we present MarketAnalyzer, an interactive visual analytics system designed to allow vendors to increase their competitive intelligence. MarketAnalyzer utilizes pixel‐based matrices to present sale data, trends, and market share growths of products of the entire market within a single display. These matrices are augmented by advanced underlying analytical methods to enable the quick evaluation of growth and risk within market sectors. Furthermore, our system enables the aggregation of point of sale data in geographical views that provide analysts with the ability to explore the impact of regional demographics and trends. Additionally, overview and detailed information is provided through a series of coordinated multiple views. In order to demonstrate the effectiveness of our system, we provide two use‐case scenarios as well as feedback from market analysts.
PORGY: A Visual Graph Rewriting Environment for Complex Systems
Authors: Pinaud B. , Melançon G. , Dubois J. 
Published: June 2012

AbstractGraph rewriting systems (GRSs) operate on graphs by substituting local patterns according to a set of rewriting rules. The apparent simplicity of GRSs hides an incredible complexity and turns the study of these systems into an involved task requiring high‐level expertise. We designed PORGY, an interactive visual environment to fully support GRSs related tasks, exploiting a long historical tradition of GRSs with node‐link representations of graphs. PORGY enables rule‐based modeling and simulation steering through graphical representations and direct manipulation of all GRSs components. This paper contributes a design study and task taxonomy relevant to the interactive visualization of GRSs.
I‐SI: Scalable Architecture for Analyzing Latent Topical‐Level Information From Social Media Data
Authors: Wang X. , Dou W. , Ma Z. , Villalobos J. , Chen Y. , Kraft T. , Ribarsky W. 
Published: June 2012

AbstractWe present a general visual analytics architecture that is designed and implemented to effectively analyze unstructured social media data on a large scale. Pipelined on a high‐performance cluster configuration, MPI processing, and interactive visual analytics interfaces, our architecture, I‐SI, closely integrates data‐driven analytical methods and user‐centered visual analytics. It creates a coherent analysis environment for identifying event structures, geographical distributions, and key indicators of emerging events. This environment supports monitoring, analyzing, and responding to latent information extracted from social media. We have applied the I‐SI architecture to collect social media data, analyze the data on a large scale and uncover the latent social phenomena. To demonstrate the efficacy and applicability of I‐SI, we describe several social media use cases in multiple domains that were evaluated by experts. The use cases demonstrate that I‐SI can benefit a range of users by constructing meaningful event structures and identifying precursors to critical events within a rich, evolving set of topics.
Automating Transfer Function Design with Valley Cell‐Based Clustering of 2D Density Plots
Authors: Wang Yunhai , Zhang Jian , Lehmann Dirk J. , Theisel Holger , Chi Xuebin 
Published: June 2012

AbstractTwo‐dimensional transfer functions are an effective and well‐accepted tool in volume classification. The design of them mostly depends on the user's experience and thus remains a challenge. Therefore, we present an approach in this paper to automate the transfer function design based on 2D density plots. By exploiting their smoothness, we adopted the Morse theory to automatically decompose the feature space into a set of valley cells. We design a simplification process based on cell separability to eliminate cells which are mainly caused by noise in the original volume data. Boundary persistence is first introduced to measure the separability between adjacent cells and to suitably merge them. Afterward, a reasonable classification result is achieved where each cell represents a potential feature in the volume data. This classification procedure is automatic and facilitates an arbitrary number and shape of features in the feature space. The opacity of each feature is determined by its persistence and size. To further incorporate the user's prior knowledge, a hierarchical feature representation is created by successive merging of the cells. With this representation, the user is allowed to merge or split features of interest and set opacity and color freely. Experiments on various volumetric data sets demonstrate the effectiveness and usefulness of our approach in transfer function generation.
COVRA: A compression‐domain output‐sensitive volume rendering architecture based on a sparse representation of voxel blocks
Authors: Gobbetti Enrico , Iglesias Guitián José Antonio , Marton Fabio 
Published: June 2012

AbstractWe present a novel multiresolution compression‐domain GPU volume rendering architecture designed for interactive local and networked exploration of rectilinear scalar volumes on commodity platforms. In our approach, the volume is decomposed into a multiresolution hierarchy of bricks. Each brick is further subdivided into smaller blocks, which are compactly described by sparse linear combinations of prototype blocks stored in an overcomplete dictionary. The dictionary is learned, using limited computational and memory resources, by applying the K‐SVD algorithm to a re‐weighted non‐uniformly sampled subset of the input volume, harnessing the recently introduced method of coresets. The result is a scalable high quality coding scheme, which allows very large volumes to be compressed off‐line and then decompressed on‐demand during real‐time GPU‐accelerated rendering. Volumetric information can be maintained in compressed format through all the rendering pipeline. In order to efficiently support high quality filtering and shading, a specialized real‐time renderer closely coordinates decompression with rendering, combining at each frame images produced by raycasting selectively decompressed portions of the current view‐ and transfer‐function‐dependent working set. The quality and performance of our approach is demonstrated on massive static and time‐varying datasets.
Procedural Texture Synthesis for Zoom‐Independent Visualization of Multivariate Data
Authors: Khlebnikov R. , Kainz B. , Steinberger M. , Streit M. , Schmalstieg D. 
Published: June 2012

AbstractSimultaneous visualization of multiple continuous data attributes in a single visualization is a task that is important for many application areas. Unsurprisingly, many methods have been proposed to solve this task. However, the behavior of such methods during the exploration stage, when the user tries to understand the data with panning and zooming, has not been given much attention.In this paper, we propose a method that uses procedural texture synthesis to create zoom‐independent visualizations of three scalar data attributes. The method is based on random‐phase Gabor noise, whose frequency is adapted for the visualization of the first data attribute. We ensure that the resulting texture frequency lies in the range that is perceived well by the human visual system at any zoom level. To enhance the perception of this attribute, we also apply a specially constructed transfer function that is based on statistical properties of the noise. Additionally, the transfer function is constructed in a way that it does not introduce any aliasing to the texture. We map the second attribute to the texture orientation. The third attribute is color coded and combined with the texture by modifying the value component of the HSV color model. The necessary contrast needed for texture and color perception was determined in a user study. In addition, we conducted a second user study that shows significant advantages of our method over current methods with similar goals. We believe that our method is an important step towards creating methods that not only succeed in visualizing multiple data attributes, but also adapt to the behavior of the user during the data exploration stage.
Interactive Rendering of Materials and Biological Structures on Atomic and Nanoscopic Scale
Authors: Lindow N. , Baum D. , Hege H.‐C. 
Published: June 2012

AbstractThe properties of both inorganic and organic materials and the function of biological structures can often only be understood by analyzing them simultaneously on atomic and nanoscopic, if not mesoscopic, scale. Here, the problem arises to render millions to billions of atoms. We propose a method by which it is possible to interactively visualize atomic data, bridging five orders of magnitude in length scale. For this, we propose a simple yet efficient GPU rendering method that enables interactive visualization of biological structures consisting of up to several billions of atoms. To be able to load all atomic data onto the GPU, we exploit the fact that biological structures often consist of recurring molecular substructures. We also exploit that these objects typically are rendered opaquely, so that only a fraction of the atoms is visible. The method is demonstrated on both biological structures as well as atom probe tomography data of an inorganic specimen. We conclude with a discussion about when ‐during ascension from atomic to mesoscopic scale – level‐of‐detail representations become necessary.
Neurological opportunistic infections and neurological immune reconstitution syndrome: impact of one decade of highly active antiretroviral treatment in a tertiary hospital
Authors: Riveiro‐Barciela M , Falcó V , Burgos J , Curran A , Van den Eynde E , Navarro J , Villar del Saz S , Ocaña I , Ribera E , Crespo M , Pahissa A 
Published: June 2012

BackgroundDespite the reported decrease in the incidence and mortality rates of central nervous system (CNS) infections after the introduction of highly active antiretroviral therapy (HAART), few studies have focused on the global incidence and the relationship of these diseases with immune reconstitution inflammatory syndrome (IRIS) in the developed world.MethodsA descriptive cohort study of all consecutive adult HIV‐infected patients with CNS opportunistic infections diagnosed between 2000 and 2010 in a tertiary hospital in Spain was carried out. Demographic, clinical, laboratory, and microbiological data were recorded. Patients were followed up until death or loss to follow‐up or until 30 July 2011, when the study finished. The significance of differences in the incidence rate between early and late HAART periods was determined using the Mantel–Haenszel test. Survival distribution was estimated using the Kaplan–Meier method.ResultsA total of 110 cases of CNS infections were diagnosed. The incidence of CNS opportunistic infections decreased from 9 cases per 1000 HIV‐infected patients per year in the early HAART period to 3.8 in the late HAART period (P = 0.04). Overall, the estimated mean survival time was 58.8 months (95% confidence interval 47.1–70.6 months). Of the 110 patients, 18 (16.4%) met the criteria of IRIS, 10 (55.6%) were paradoxical and eight (44.4%) were unmasking. IRIS was not associated with a higher mortality rate.ConclusionsThe annual incidence of CNS infections decreased progressively during the period of study. The mortality rate associated with these diseases remains high despite HAART. The development of IRIS associated with neurological infections had no influence on prognosis.
Serum levels of anti‐type VII collagen antibodies detected by enzyme‐linked immunosorbent assay in patients with epidermolysis bullosa acquisita are correlated with the severity of skin lesions
Authors: Kim J.H. , Kim Y.H. , Kim S. , Noh E.B. , Kim S‐E. , Vorobyev A. , Schmidt E. , Zillikens D. , Kim S‐C. 
Published: June 2012

AbstractBackground  Epidermolysis bullosa acquisita (EBA) is a chronic autoimmune subepidermal bullous disease characterized by circulating autoantibodies against type VII collagen. Detecting these autoantibodies is crucial for the diagnosis of this disease, and is also useful for measuring disease activity. Enzyme‐linked immunosorbent assay (ELISA), a quantitative method to measure anti‐type VII collagen antibody levels, is currently available to diagnose EBA.Objective  The aim of this study was to investigate the relationship of ELISA with overall clinical severity.Methods  Sera from patients with EBA (n = 30), bullous pemphigoid (n = 20), anti‐laminin γ1 pemphigoid (n = 9) and healthy donors (n = 24) were tested using ELISA, using the recombinant non‐collagenous 1 (NC1) and 2 (NC2) domains of type VII collagen. Relationships between clinical characteristics, indirect immunofluoroscence (IIF) titres and ELISA values were investigated.Results  The sensitivity and specificity of the EBA ELISA were 96.7% and 98.1%, respectively. There was no significant difference between ELISA results for classic and inflammatory types. The severity of skin involvement was positively correlated with both ELISA value (r = 0.87, P < 0.01) and IIF titre (r = 0.59, P < 0.01). Time sequence analysis in four patients with EBA showed that ELISA values reflect disease activity better than IIF titres.Conclusions Type VII collagen ELISA using the NC1 and NC2 domains is useful for diagnosing EBA and monitoring disease severity.
Transforming Growth Factor β1‐509C/T and +869T/C Polymorphisms on the Risk of Upper Digestive Tract Cancer: A Meta‐Analysis Based on 10,917 Participants
Authors: Zhang Cai‐Feng , Wang Zhong‐Wei , Hou Meng‐Xia , Li Kun , Zhou Xiang , Xia Yong‐Hua 
Published: June 2012

SummaryThe aim of this study was to assess the relationships between transforming growth factor β1‐509C/T (rs1800469) and +869T/C (rs1800470) polymorphisms and the risk of upper digestive tract cancer (UDT cancer) by using a meta‐analysis. We interrogated the databases of Medline, Embase and Wanfang (Chinese literature database) (latest update; December 15, 2011). Odds ratios (OR) and corresponding 95% confidence intervals (95% CI) were used to assess the strength of the associations. In total, 20 case‐control studies were included in this meta‐analysis. Overall, both TGF β1‐509C/T and +869T/C polymorphisms were not associated with risk of UDT cancer [‐509C/T: OR (95%CI) = 1.10 (0.99–1.22) for TT vs. C carries, Pheterogeneity= 0.10; +869T/C: OR (95%CI) = 1.04 (0.88–1.23) for CC vs. T carriers, Pheterogeneity= 0.02]. Subgroup analyses indicated that the ‐509T allele was associated with increased risk of UDT cancer in population‐based studies (OR = 1.16 (1.04–1.31), Pheterogeneity= 0.31 for TT vs. C carriers) and in small sample‐sized studies (OR = 1.45 (1.15–1.84), Pheterogeneity= 0.56 TT vs. C carriers). All subgroup analyses for the TGF β1+869T/C polymorphism indicated null association except for hepatocellular carcinoma. Interestingly, both the TGF β1‐509T allele and the +869C allele were associated with decreased risk of hepatocellular cancer based on limited original studies. This meta‐analysis indicated that TGF β1‐509C/T rather than +869T/C is a potential risk factor for UDT cancer.
Statistical Tests for Detecting Rare Variants Using Variance‐Stabilising Transformations
Authors: Wang Kai , Fingert John H. 
Published: June 2012

SummaryNext generation sequencing holds great promise for detecting rare variants underlying complex human traits. Due to their extremely low allele frequencies, the normality approximation for a proportion no longer works well. The Fisher’s exact method appears to be suitable but it is conservative. We investigate the utility of various variance‐stabilising transformations in single marker association analysis on rare variants. Unlike a proportion itself, the variance of the transformed proportions no longer depends on the proportion, making application of such transformations to rare variant association analysis extremely appealing. Simulation studies demonstrate that tests based on such transformations are more powerful than the Fisher’s exact test while controlling for type I error rate. Based on theoretical considerations and results from simulation studies, we recommend the test based on the Anscombe transformation over tests with other transformations.
Fear of childbirth and duration of labour: a study of 2206 women with intended vaginal delivery
Authors: Adams SS , Eberhard‐Gran M , Eskild A 
Published: June 2012

Please cite this paper as: Adams S, Eberhard‐Gran M, Eskild A. Fear of childbirth and duration of labour: a study of 2206 women with intended vaginal delivery. BJOG 2012;119:1238–1246.Objective  To assess the association between fear of childbirth and duration of labour.Design  A prospective study of women from 32 weeks of gestation through to delivery.Setting  Akershus University Hospital, Norway.Population  A total of 2206 pregnant women with a singleton pregnancy and intended vaginal delivery during the period 2008–10.Methods  Fear of childbirth was assessed by the Wijma Delivery Expectancy Questionnaire (W‐DEQ) version A at 32 weeks of gestation, and defined as a W‐DEQ sum score ≥ 85. Information on labour duration, use of epidural analgesia and mode of delivery was obtained from the maternal ward electronic birth records.Main outcome measures   Labour duration in hours: from 3–4 cm cervical dilatation and three uterine contractions per 10 minutes lasting ≥1 minute, until delivery of the child.Results  Fear of childbirth (W‐DEQ sum score ≥ 85) was present in 7.5% (165) of women. Labour duration was significantly longer in women with fear of childbirth compared with women with no such fear using a linear regression model (crude unstandardised coefficient 1.54; 95% confidence interval 0.87–2.22, corresponding to a difference of 1 hour and 32 minutes). After adjustment for parity, counselling for pregnancy concern, epidural analgesia, labour induction, labour augmentation, emergency caesarean delivery, instrumental vaginal delivery, offspring birthweight and maternal age, the difference attenuated, but remained statistically significant (adjusted unstandardised coefficient 0.78; 95% confidence interval 0.20–1.35, corresponding to a 47‐minute difference).Conclusion  Duration of labour was longer in women with fear of childbirth than in women without fear of childbirth.
3,6′‐Dithiothalidomide, a new TNF‐α synthesis inhibitor, attenuates the effect of Aβ1–42intracerebroventricular injection on hippocampal neurogenesis and memory deficit
Authors: Russo Isabella , Caracciolo Luca , Tweedie David , Choi Sang‐Ho , Greig Nigel H. , Barlati Sergio , Bosetti Francesca 
Published: June 2012

J. Neurochem. (2012)122, 1181–1192.AbstractEvidence indicates altered neurogenesis in neurodegenerative diseases associated with inflammation, including Alzheimer’s disease (AD). Neuroinflammation and its propagation have a critical role in the degeneration of hippocampal neurons, cognitive impairment, and altered neurogenesis. Particularly, tumor necrosis factor (TNF)‐α plays a central role in initiating and regulating the cytokine cascade during an inflammatory response and is up‐regulated in brain of AD patients. In this study, we investigated the effects of a novel thalidomide‐based TNF‐α lowering drug, 3,6′‐dithiothalidomide, on hippocampal progenitor cell proliferation, neurogenesis and, memory tasks after intracerebroventricular injection of β‐amyloid (Aß)1–42peptide. Seven days after Aβ1–42injection, a significant proliferation of hippocampal progenitor cells and memory impairment were evident. Four weeks after Aβ1–42peptide injection, elevated numbers of surviving 5‐bromo‐2′‐deoxyuridine cells and newly formed neurons were detected. Treatment with 3,6′‐dithiothalidomide attenuated these Aβ1–42provoked effects. Our data indicate that although treatment with 3,6′‐dithiothalidomide in part attenuated the increase in hippocampal neurogenesis caused by Aβ1–42‐induced neuroinflammation, the drug prevented memory deficits associated with increased numbers of activated microglial cells and inflammatory response. Therefore, 3,6′‐dithiothalidomide treatment likely reduced neuronal tissue damage induced by neuroinflammation following Aβ1–42injection. Understanding the modulation of neurogenesis, and its relationship with memory function could open new therapeutic interventions for AD and other neurodegenerative disorders with an inflammatory component.