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A significant challenge on an exascale computer is the speed at which we compute results exceeds by many orders of magnitude the speed at which we save these results. Therefore the Exascale Computing Project (ECP) ALPINE project focuses on providing exascale-ready visualization solutions including in situ processing. In situ visualization and analysis runs as the simulation is run, on simulations results are they are generated avoiding the need to save entire simulations to storage for later analysis. The ALPINE project made post hoc visualization tools, ParaView and VisIt, exascale ready and developed in situ algorithms and infrastructures. The suite of ALPINE algorithms developed under ECP includes novel approaches to enable automated data analysis and visualization to focus on the most important aspects of the simulation. Many of the algorithms also provide data reduction benefits to meet the I/O challenges at exascale. ALPINE developed a new lightweight in situ infrastructure, Ascent. [ABSTRACT FROM AUTHOR]

Copyright of University Chemistry is the property of Peking University, College of Chemistry & Molecular Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Quantifying the global reach of planetarium dome shows presents significant challenges due to the lack of standardized viewership tracking mechanisms across diverse planetarium venues. We present an analysis of the global impact of dome shows, presenting data regarding four documentary films from a single visualization lab. Specifically, we designed and administered a viewership survey of four long-running shows that contained cinematic scientific visualizations. Reported survey data shows that between 1.2 - 2.6 million people have viewed these four films across the 68 responding planetariums (mean: 1.9 million). When we include estimates and extrapolate for the 315 planetariums that licensed these shows, we arrive at an estimate of 16.5 - 24.1 million people having seen these films (mean: 20.3 million). [ABSTRACT FROM AUTHOR]

Considering urbanization's effects, quantifying individual components of the hydrological cycle, especially at the catchment scale, has been challenging due to the influence of climate change and human activities. Accordingly, the study assesses the impacts of Land Use and Land Cover Changes (LULCC) on the water quantity degradation. It evaluates the effect of urbanization on water balance configuration between the period 2000-2020. The resultant result of LULC reflected a long-term increase in bare land by 11.72% and a marginal increase in built-up areas (0.52%). In contrast, the annual water balance results show an annual negative water deficit ranging from −19.40 mm to −624.955 mm. The result has demonstrated the use of QSWAT and SWMM in a Quick geographic information systems (QGIS) environment to drive the socio-hydrological framework to model spatially distributed and time-varying hydrologic and meteorologic datasets as an effective scientific visualization technique in water balance evaluation. [ABSTRACT FROM AUTHOR]

Copyright of TAY Journal / Türk Akademik Yayınlar Dergisi is the property of Turk Akademik Yayinlar Dergisi (TAY Journal) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Tracking time-variant vortex features in unsteady flow fields represents a significant challenge in scientific visualization. In this paper, we propose an innovative new method based on attribute fusion that leverages unsupervised clustering techniques to track time-variant vortex features. This method has the potential for use in large-scale flow field analysis. We apply an attribute matrix integrating the spatial and physical variables of vortex feature points. We then fuse and reduce the dimensionality of this original matrix to create an attribute fusion matrix. Subsequently, we apply coarse clustering to the fusion matrices across time steps. By defining a distribution curve, we derive a similarity measurement matrix among different vortices. Vortex matching is performed based on this similarity measurement to enable the tracking of time-variant vortices. Multiple experimental datasets demonstrate the effectiveness and matching efficiency of the proposed method. [ABSTRACT FROM AUTHOR]

Volume visualization plays a crucial role in both academia and industry, as volumetric data is extensively utilized in fields such as medicine, geosciences, and engineering. Addressing the complexities of volume rendering, neural rendering has emerged as a potential solution, facilitating the production of high-quality volume rendered images. In this paper, we propose TwineNet, a neural network architecture specifically designed for volume rendering. TwineNet combines features extracted from volume data, transfer functions, and viewpoints by utilizing twining skip connections across multiple feature layers. Building upon the TwineNet architecture, we introduce two neural networks, VolTFNet and PosTFNet, which leverage convolutional encoder–decoders and multilayer perceptrons to synthesize volume rendered images with novel transfer functions and viewpoints. Our experimental findings demonstrate the superiority of our models compared to state-of-the-art approaches in generating high-quality volume rendered images with novel transfer functions and viewpoints. This research contributes to advancing the field of volume rendering and showcases the potential of neural rendering techniques in scientific visualization. [ABSTRACT FROM AUTHOR]

Recently, implicit neural representations (INRs) have demonstrated significant capabilities in handling 3D volume data, especially in the context of data compression. However, the majority of research has predominantly focused on structured grids, which are not commonly found in scientific domains, particularly in physics. To address this limitation, we propose an unstructured grid reduction method via implicit neural representation (UGINR). UGINR employs a divide-and-conquer approach; specifically, we segment the large-scale data into pieces based on values. Subsequently, we employ an INR network for each piece to learn its distinctive features. Finally, we integrate these individual networks to achieve the compression goal. To ensure compatibility with established research methods, we sample only the vertices of each cell in the unstructured grid. Through weight quantization, our model can achieve a high compression ratio. To illustrate the effectiveness of the proposed method, we conduct experiments on various datasets, demonstrating our approach's robustness in scientific visualization and large-scale data compression. [ABSTRACT FROM AUTHOR]

Interactive scientific visualization applications have been more and more used to observe, analyze and understand the complex phenomena studied in several scientific disciplines such as (nano-sciences, fluid simulations, etc.). To facilitate the coupling of the different computation, visualization and exploration codes, which are often heterogeneous and difficult to cooperate, scientists must be able to use and reuse the different parts of the applications already built in order to interchange and enrich certain parts without being experts. In this context, a middleware called FlowVR has been developed by the scientific community leading to make applications divided into set of components exchanging messages. Moreover, this middleware enables to encapsulate existing codes in components, interconnect them via data links, and deploy them on distributed computing resources. Nevertheless, FlowVR does not offer any capability to check the functional correctness of new developed component-based applications. This paper presents a framework called Model and Component-based framework for Scientific Applications (MCSA) based on a interplay of model-driven and component-based software engineering. On the one hand, we provide a domain specific language dedicated to physics/chemistry scientists in order to built their MCSA applications. This language also allows to capitalize efforts by proposing existing components that have been already developed. On the other hand, we propose a model transformation to check the correctness of instantiated models, for this, we use a new subclass of Petri net called strict Colored FIFO Nets (sCFN). Our approach has been backed by a case study relies on a molecular dynamics application. [ABSTRACT FROM AUTHOR]

With the advent of low-power ultra-fast hardware and GPUs, virtual reality (VR) has gained a lot of prominence in the past few years and is being used in various areas, such as education, entertainment, scientific visualization, and computer-aided design. VR-based applications are highly interactive, and one of the most important performance metrics for these applications is the motion-to-photon-delay (MPD). MPD is the delay from the user's head movement to the time at which the image gets updated on the VR screen. Since the human visual system can even detect an error of a few pixels (very spatially sensitive), the MPD should be as small as possible. Popular VR vendors use the GPU-accelerated Asynchronous Time Warp (ATW) algorithm to reduce the MPD. ATW reduces the MPD if and only if the warping operation finishes just before the display refreshes. However, due to the competition between the different constituent applications for the single, shared GPU, the GPU-accelerated ATW algorithm suffers from an unpredictable ATW latency, making it challenging to find the ideal time instance for starting the time warp and ensuring that it completes with the least amount of lag relative to the screen refresh. Hence, the state-of-the-art is to use a separate hardware unit for the time-warping operation. Our approach, PredATW, uses an ML-based hardware predictor to predict the ATW latency for a VR application, and then schedule it as late as possible while running the time-warping operation on the GPU itself. As far as we know, this is the first work to do so. Our predictor achieves an error of only 0.22 ms across several popular VR applications for predicting the ATW latency. As compared to the baseline architecture, we reduce deadline misses by 80.6%. [ABSTRACT FROM AUTHOR]

We introduce time‐varying extremum graph (tveg), a topological structure to support visualization and analysis of a time‐varying scalar field. The extremum graph is a sub‐structure of the Morse–Smale complex. It captures the adjacency relationship between cells in the Morse decomposition of a scalar field. We define the tveg as a time‐varying extension of the extremum graph and demonstrate how it captures salient feature tracks within a dynamic scalar field. We formulate the construction of the tveg as an optimization problem and describe an algorithm for computing the graph. We also demonstrate the capabilities of tveg towards identification and exploration of topological events such as deletion, generation, split and merge within a dynamic scalar field via comprehensive case studies including a viscous fingers and a 3D von Kármán vortex street dataset. [ABSTRACT FROM AUTHOR]

The VTK-m software library enables scientific visualization on exascale-class supercomputers. Exascale machines are particularly challenging for software development in part because they use GPU accelerators to provide the vast majority of their computational throughput. Algorithmic designs for GPUs and GPU-centric computing often deviate from those that worked well on previous generations of high-performance computers that relied on traditional CPUs. Fortunately, VTK-m provides scientific visualization algorithms for GPUs and other accelerators. VTK-m also provides a framework that simplifies the implementation of new algorithms and adds a porting layer to work across multiple processor types. This paper describes the main challenges encountered when making scientific visualization available at exascale. We document the surprises and obstacles faced when moving from pre-exascale platforms to the final exascale designs and the performance on those systems including scaling studies on Frontier, an exascale machine with over 37,000 AMD GPUs. We also report on the integration of VTK-m with other exascale software technologies. Finally, we show how VTK-m helps scientific discovery for applications such as fusion and particle acceleration that leverage an exascale supercomputer. [ABSTRACT FROM AUTHOR]

Copyright of Revista Foco (Interdisciplinary Studies Journal) is the property of Revista Foco and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The contour depth methodology enables non‐parametric summarization of contour ensembles by extracting their representatives, confidence bands, and outliers for visualization (via contour boxplots) and robust downstream procedures. We address two shortcomings of these methods. Firstly, we significantly expedite the computation and recomputation of Inclusion Depth (ID), introducing a linear‐time algorithm for epsilon ID, a variant used for handling ensembles with contours with multiple intersections. We also present the inclusion matrix, which contains the pairwise inclusion relationships between contours, and leverage it to accelerate the recomputation of ID. Secondly, extending beyond the single distribution assumption, we present the Relative Depth (ReD), a generalization of contour depth for ensembles with multiple modes. Building upon the linear‐time eID, we introduce CDclust, a clustering algorithm that untangles ensemble modes of variation by optimizing ReD. Synthetic and real datasets from medical image segmentation and meteorological forecasting showcase the speed advantages, illustrate the use case of progressive depth computation and enable non‐parametric multimodal analysis. To promote research and adoption, we offer the contour‐depth Python package. [ABSTRACT FROM AUTHOR]

Adaptive Mesh Refinement (AMR) is becoming a prevalent data representation for HPC, and thus also for scientific visualization. AMR data is usually cell centric (which imposes numerous challenges), complex, and generally hard to render. Recent work on GPU‐accelerated AMR rendering has made much progress towards real‐time volume and isosurface rendering of such data, but so far this work has focused exclusively on ray marching, with simple lighting models and without scattering events or global illumination. True high‐quality rendering requires a modified approach that is able to trace arbitrary incoherent paths; but this may not be a perfect fit for the types of data structures recently developed for ray marching. In this paper, we describe a novel approach to high‐quality path tracing of complex AMR data, with a specific focus on analyzing and comparing different data structures and algorithms to achieve this goal. [ABSTRACT FROM AUTHOR]

Exploratory analysis of scalar fields on surface meshes presents significant challenges in identifying and visualizing important regions, particularly on the surface's backside. Previous visualization methods achieved only a limited visibility of significant features, i.e., regions with high or low scalar values, during interactive exploration. In response to this, we propose a novel technique, InverseVis, which leverages curved sphere tracing and uses the otherwise unused space to enhance visibility. Our approach combines direct and indirect rendering, allowing camera rays to wrap around the surface and reveal information from the backside. To achieve this, we formulate an energy term that guides the image synthesis in previously unused space, highlighting the most important regions of the backside. By quantifying the amount of visible important features, we optimize the camera position to maximize the visibility of the scalar field on both the front and backsides. InverseVis is benchmarked against state‐of‐the‐art methods and a derived technique, showcasing its effectiveness in revealing essential features and outperforming existing approaches. [ABSTRACT FROM AUTHOR]

Russia's "Electronic Structure of Atoms" information and reference system for atomic spectroscopy is described. Its main characteristics and capabilities for supporting scientific research and training of specialists are explained. The data array contains more than 234 000 levels, with great attention given to experimental data and uniform filling across Z, including classified levels and transitions of all rare earth and transuranium elements and their ions. Original means of visualizing scientific data in the form of spectrograms, quantograms, and Grotrian diagrams are proposed. Presenting spectral data in the form of color interactive diagrams promotes understanding and analysis of the properties of an atomic system. In combination with its functionality, the use of spectral data from the "Electronic Structure of Atoms" information system is an effective way of solving different scientific problems and training specialists. [ABSTRACT FROM AUTHOR]

In the field of scientific visualization, the upscaling of time‐varying volume is meaningful. It can be used in in situ visualization to help scientists overcome the limitations of I/O speed and storage capacity when analysing and visualizing large‐scale, time‐varying simulation data. This paper proposes self‐attention residual network‐based spatial super‐resolution (SARN‐SSR), a spatial super‐resolution model based on self‐attention residual networks that can generate time‐varying data with temporal coherence. SARN‐SSR consists of two components: a generator and a discriminator. The generator takes the low‐resolution volume sequences as the input and gives the corresponding high‐resolution volume sequences as the output. The discriminator takes both synthesized and real high‐resolution volume sequence as the input and gives a matrix to predict the realness as the output. To verify the validity of SARN‐SSR, four sets of time‐varying volume datasets are applied from scientific simulation. In addition, SARN‐SSR is compared on these datasets, both qualitatively and quantitatively, with two deep learning‐based techniques and one traditional technique. The experimental results show that by using this method, the closest time‐varying data to the ground truth can be obtained. [ABSTRACT FROM AUTHOR]

Insightful visualization of multidimensional scalar fields, in particular parameter spaces, is key to many computational science and engineering disciplines. We propose a principal component-based approach to visualize such fields that accurately reflects their sensitivity to their input parameters. The method performs dimensionality reduction on the space formed by all possible partial functions (i.e., those defined by fixing one or more input parameters to specific values), which are projected to low-dimensional parameterized manifolds such as 3D curves, surfaces, and ensembles thereof. Our mapping provides a direct geometrical and visual interpretation in terms of Sobol's celebrated method for variance-based sensitivity analysis. We furthermore contribute a practical realization of the proposed method by means of tensor decomposition, which enables accurate yet interactive integration and multilinear principal component analysis of high-dimensional models. [ABSTRACT FROM AUTHOR]

This study presents a comprehensive bibliometric review aimed at examining the effectiveness and applicability of the pavement condition index (PCI) method, particularly in assessing airport pavement distress and guiding maintenance and rehabilitation (M&R) strategies. Through bibliometric analysis spanning the last two decades, we investigate the evolution of the PCI method in both road and airport pavement contexts, exploring patterns of keyword co-occurrence, co-authorship, geographical distribution, and publication trends. Our findings reveal significant advancements in the PCI model and associated M&R strategies, largely driven by technological innovations. However, limitations are identified in current bibliometric analysis tools, such as Harzing's Publish or Perish, particularly concerning handling large datasets. Practical implications highlight the importance of integrating bibliometric analysis tools with automated big data handling to enhance research efficiency and reliability. Future research should focus on improving methodological integration to streamline the visualization of scientific network techniques with minimal effort and time investment. [ABSTRACT FROM AUTHOR]

Digital twins, an innovative technology propelled by data and models, play a seminal role in the digital transformation and intelligent upgrade of ships. This study introduces a digital twin methodology for the real-time monitoring of ship structure deformation fields, based on finite discrete strain data, and a visualization tool framework is developed using virtual reality technology. First, the inverse Finite Element Method (iFEM) is employed to derive the deformation field of the ship structure in real time using sensor strain data. Secondly, the deformation field data obtained based on the iFEM algorithm is converted into general visualization data conducive to interpretation within virtual reality (VR) applications. Lastly, a digital twin software tool is built to enable synchronous responses and interactions between the virtual scene and the physical scene, directly superposing particular virtual objects (data acquired by sensors, computer-aided design (CAD) virtual models, and deformation field cloud images) onto the physical scene in real time. The digital twin tool embodies a virtual reality visualization system framework integrating the physical data measurement, reconstruction, analysis, expression, storage, rendering, and interaction of deformation field data. Through practical application, the flexibility, effectiveness, and compatibility of the developed prototype tool are verified. According to the results, the system can enhance the efficiency of scientific communication, model validation, and interdisciplinary sharing during the analysis and evaluation of the mechanical properties of ship structures. [ABSTRACT FROM AUTHOR]

Aim: The purpose of this article is to give an analysis of developing trends and research hotspots within the KLE Academy of Higher Education and Research (KAHER) Group using bibliometric methodologies. Materials and Methods: Using co-authorship, co-citation, and co-occurrence analysis, publications from the Scopus database for the years 1973–2022 are examined and analyzed on a variety of factors. R-Programming (Biblioshiny) and VOSViewer, an application for scientific visualization, are used to do the analysis. Results: There were 1721 publications in Scopus throughout the study period, with 83.9% of those being journal articles and the remaining 6% being letters and case studies. Research generally shows a constant rise with growing multi-authorship. The most sought-after magazine for publishing by the writers at KAHER is "Reproductive Health," and they prefer to collaborate on research pieces. In addition, health-care science services and medical informatics have steadily developed into new areas of scientific interest. Originality: This study offers a thorough and comprehensive analysis of the KAHERs' formative environment. This study can serve as a solid starting point for future research and can be used to analyze how health science research has changed overtime. Conclusion: The study reveals KAHER's robust publishing productivity and impact, with a diverse output among authors and a consistent growth in the number of publications. The dominance of collaborative research, high citation rates, and the prevalence of medical research suggest the importance of international collaborations and the implementation of an institutional online repository system for enhanced research efficacy and accessibility. [ABSTRACT FROM AUTHOR]

This essay reads Anna Atkins's Photographs of British Algae: Cyanotype Impressions (1843–1853) as an example of Victorian imitative art by reading it through the lens of Victorian domestic handicraft. It does so in order to resituate Atkins's work within the history of scientific visualization and to contribute to the increasing complexity scholars of visual culture and of the scientific image have added to prevailing accounts of the rise of the "objective" scientific image in the nineteenth‐century. Building on the work of historians of photography, art, science, and literature, it argues that her cyanotypes point toward an alternative history of scientific image as a form of craft and collection that resonates with recent calls in the study of the scientific image and scientific practices to move "beyond representation." [ABSTRACT FROM AUTHOR]

The problem of determining the wave function of a physical system based on the graphical representation of its zeros is considered. It can be dealt with by invoking the Bargmann representation in which the wave functions are represented by analytic functions with an appropriate definition of the scalar product. The Weierstrass factorization theorem can then be applied. Examples of states that can be guessed from the pictorial representation of zeros by both the human eye and, possibly, by machine learning systems are given. The quality of recognition by the latter has been tested using Convolutional Neural Networks. [ABSTRACT FROM AUTHOR]

Taking the identification of glucose as an example, this article outlines the instructional design and video production process for integrating scientific visualization into the pharmaceutical analysis experiment. The principle, procedure, and phenomenon of the experiment are vividly demonstrated through the pictures and videos, enhancing the interest and attraction of the experiment course. A series of related videos have been applied to classroom teaching and uploaded to the video website, achieving favorable educational outcomes and facilitating broader sharing and communication. [ABSTRACT FROM AUTHOR]

Utilizing data visualization facilitates the analysis and comprehension of common data provided by the media, individuals, governments, and other sectors. Python is a well-known programming language that excels at scientific data visualization. This thesis utilizes a variety of Python modules, including Pandas, NumPy, Matplotlib, Seaborn, Plotly, and Bokeh, to illustrate female genital mutilation. The purpose of this thesis is to illustrate female genital mutilation and explain its performance pattern using a complex, interactive diagram that integrates multiple types of Python libraries. In comparison to other libraries, Plotly is the simplest, yet it performs at the highest level. NumPy and Matplotlib are combined to produce Hexbins charts. NumPy provides an N-dimensional plot, and Matplotlib allows for the plot's colours to be customized. Despite its limited customization options, the Seaborn library is suitable for both data visualization and statistical modelling. Due to this deficiency, the Seaborn library is frequently combined with Matplotlib to generate superior visualizations. As a result, this thesis will be recommended to both specialists and novices as worthwhile reading. In addition, it will assist the government in drafting legislation to end female genital mutilation. They will comprehend the significance of combining multiple Python modules to generate intricate interactive diagrams for data visualization in the field of data science. This information will be posted online to contribute to the corpus of knowledge. [ABSTRACT FROM AUTHOR]

In this paper, we propose a correlation-aware probabilistic data summarization technique to efficiently analyze and visualize large-scale multi-block volume data generated by massively parallel scientific simulations. The core of our technique is correlation modeling of distribution representations of adjacent data blocks using copula functions and accurate data value estimation by combining numerical information, spatial location, and correlation distribution using Bayes' rule. This effectively preserves statistical properties without merging data blocks in different parallel computing nodes and repartitioning them, thus significantly reducing the computational cost. Furthermore, this enables reconstruction of the original data more accurately than existing methods. We demonstrate the effectiveness of our technique using six datasets, with the largest having one billion grid points. The experimental results show that our approach reduces the data storage cost by approximately one order of magnitude compared to state-of-the-art methods while providing a higher reconstruction accuracy at a lower computational cost. [ABSTRACT FROM AUTHOR]

Despite the increasing concern on workplace diversity, no research has been conducted to providing an objective visualization of the development of this fast-developing area and to complementing prior qualitative and meta-analytic reviews in the Asia-Pacific region. This research uses co-citation and co-occurrence analyses to trace how the landscape of diversity evolved from January 1993 to August 2021, using the scientific visualization tool CiteSpace. Based on a dataset of 636 diversity-related publications in the Asia-Pacific region collected from the Web of Science database, we conduct a bibliometric review to map the landscape, with the focus on identifying landmark researchers, articles, and journals, and the intellectual structure of, and changes in, diversity-related research themes. Further, a narrative review was adopted to summarize the frequently studied diversity themes, to capture the developing trends of diversity research, and to build an integrated model of workplace diversity in the Asia-Pacific context. Based on these findings, this review displays the evolution of diversity literature and uncovers future research directions to spur follow-up diversity studies. [ABSTRACT FROM AUTHOR]

Visualization plays a crucial role in molecular and structural biology. It has been successfully applied to a variety of tasks, including structural analysis and interactive drug design. While some of the challenges in this area can be overcome with more advanced visualization and interaction techniques, others are challenging primarily due to the limitations of the hardware devices used to interact with the visualized content. Consequently, visualization researchers are increasingly trying to take advantage of new technologies to facilitate the work of domain scientists. Some typical problems associated with classic 2D interfaces, such as regular desktop computers, are a lack of natural spatial understanding and interaction, and a limited field of view. These problems could be solved by immersive virtual environments and corresponding hardware, such as virtual reality head‐mounted displays. Thus, researchers are investigating the potential of immersive virtual environments in the field of molecular visualization. There is already a body of work ranging from educational approaches to protein visualization to applications for collaborative drug design. This review focuses on molecular visualization in immersive virtual environments as a whole, aiming to cover this area comprehensively. We divide the existing papers into different groups based on their application areas, and types of tasks performed. Furthermore, we also include a list of available software tools. We conclude the report with a discussion of potential future research on molecular visualization in immersive environments. [ABSTRACT FROM AUTHOR]

With the increasing demand for high precision in numerical simulations using computational fluid dynamics (CFD), the use of large-scale grids for discretized solutions has become a trend, resulting in an explosive growth of flow-field data size. To address the challenges posed by large-scale flow-field data for real-time interactive visualization, this paper proposes novel strategies for data partitioning and communication management. Firstly, we propose a data-partitioning strategy based on grid segmentation. This approach constructs metadata to create file viewports for each process and performs grid partitioning. Subsequently, it reconstructs sub-grids within each process and utilizes a coordinate-mapping algorithm to map global coordinates to local process coordinates, facilitating access to attribute variables through a lookup table. Secondly, we introduce a real-time interactive method for large-scale flow fields. This method leverages the system architecture of high-speed interconnection among compute nodes in a cluster environment and low-speed interconnection between service nodes and rendering nodes. It enables coordinated management of parallel rendering and synchronized rendering methods. The experimental results on typical flow-field data demonstrate that the proposed data-partitioning strategy improves the loading speed of millions of grid-level data by a factor of 7, surpassing ParaView's performance by 1.5 times. Furthermore, it achieves system load balancing. Real-time interaction experiments with datasets containing 500 million and 800 million grid cells exhibit millisecond-level latencies, demonstrating the effectiveness of the proposed communication management method in meeting the real-time interactive visualization demands of large-scale flow-field data. [ABSTRACT FROM AUTHOR]

The interest in real-time volume graphics has grown rapidly in the last few years, driven by the increasing demands from both academia and industry. GPU-based volume rendering has been used in a wide variety of fields, including scientific visualization, visual effects, and video games. Similarly, real-time volume editing has been used to build terrain and create visual effects during game development; it has even become an integral part of gameplay in various video games (e.g., Minecraft). Nowadays, as the size of volume data increases, processing large volume data in real time is inevitable in many modern application scenarios. However, manipulation and editing of large volume data are associated with various challenges, such as dramatically increasing memory usage and computational burden. In this paper, we present a framework for interactive manipulation and editing of large volume data to address these challenges. A robust and efficient method for large signed distance function (SDF) volume generation is presented and incorporated into the framework. Also, a complete implementation with specialized GPU optimization is introduced to demonstrate its usefulness and effectiveness—it is included in the framework as well. The framework can be an easy-to-use middleware or a plugin that is able to integrate into game engines for the development of various types of applications (e.g., video games). It can also contribute to the research looking at large volume data from a user-centered perspective (e.g., for human–computer interaction researchers). [ABSTRACT FROM AUTHOR]

Programmatic processing, analysis, and visualization of scientific research data necessitate computational skills that scientists do not consistently acquire during their education. Python is a programming language currently in the ascendant among the scientific community. In early 2022, 25 marine scientists and marine biology graduate students were introduced to the fundamentals of Python programming in a 10.5-hour workshop series offered over seven weeks. A functional, web-based Python environment using Jupyter Notebooks, JupyterLab, Binder, and GitHub was paired with scaffolding and active learning pedagogy, to ensure an engaging learning experience. We describe the course design, adaptations, and outcomes, and offer recommendations for developing a similar introductory programming workshop. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to review and analyse the literature on psychological contract (PC) phenomena to date as well as give future research directions in this research area. Design/methodology/approach: The authors have conducted a bibliometric analysis of 33 years of research on PC. The bibliometric findings have identified various perspectives by drawing the landscape and developmental trajectory of PC research over time. A specific bibliographic analysis and visualization tool VOSviewer was employed to evaluate and process 1999 publications in the Scopus and Web of Science (WoS) database from 1989 to 2022, also author citation analysis, journal co-citation analysis, reference analysis and analysis of 100 milestone articles. Findings: The authors detected and visualized the landscape of PC area and track how this landscape has developed. Secondly, the authors present the findings emerged from this study's bibliometric review, with emphasize on future research directions and implications. Originality/value: This paper presents bibliometric analysis of more than 1,000 research articles from main databases and review of 100 most prominent papers on PC research topic. This article offers academicians and researchers a more sophisticated understanding of the intellectual and conceptual framework of the research body. The authors are providing insights about its structural body of knowledge through an overview of the current state of scholarly development in the field of PC. [ABSTRACT FROM AUTHOR]

The article presents the discussion on exploring the intersection of science and art in visual representation, emphasizing the subjective nature of scientific imagery and the potential for artists to enhance scientific visualization. Topics include role of imagination in scientific imagery, the collaboration between artists and scientists in visualizing technologies, and the expressive potential of visual art in expanding scientific understanding.

In this paper, based on height field surface example, an efficient technology of real-time modeling of complex procedural objects on the ray tracing pipeline (RT-pipeline) is proposed. The proposed technology doesn't overload the I-shader stage (intersection shader), but distributes the computational load between the I-shader and the AH-shader (any-hit shader). The key innovations of the technology are the early rejection at the I-shader stage of the bounding boxes (AABBs) extracted by the RT-pipeline hardware unit, and the "transparent AABB" concept which allows transferring costly computing of the "ray-procedural object" intersection to a later AH-shader stage. The paper also describes a number of modifications that reduce the amount of such calculations. The proposed technology was implemented in a software complex in C++, GLSL and using the Vulkan API. The performance of the developed solution was studied under various ray tracing conditions on the task of modeling the surface of a detailed Puget Sound height field. The obtained results confirmed efficiency of the developed technology and the possibility of its application in virtual environment systems, simulators, scientific visualization, etc. [ABSTRACT FROM AUTHOR]

Lava domes and lava flows are major manifestations of effusive volcanic eruptions. Less viscous lava tends to flow long distances depending on the volcanic slope topography, the eruption rate, and the viscosity of the erupted magma. When magma is highly viscous, its eruption to the surface leads to the formation of lava domes and their growth. The meshless smoothed particle hydrodynamics (SPH) method is used in this paper to simulate lava dynamics. We describe the SPH method and present a numerical algorithm to compute lava dynamics models. The numerical method is verified by solving a model of cylindrical dam-break fluid flow, and the modelled results are compared to the analytical solution of the axisymmetric thin-layer viscous current problem. The SPH method is applied to study three models of lava advancement along the volcanic slope, when the lava viscosity is constant, depends on time and on the volume fraction of crystals in the lava. Simulation results show characteristic features of lava flows, such as lava channel and tube formation, and lava domes, such as the formation of a highly viscous carapace versus a less viscous dome core. Finally, the simulation results and their dependence on a particle size in the SPH method are discussed. [ABSTRACT FROM AUTHOR]

Volume data these days is usually massive in terms of its topology, multiple fields, or temporal component. With the gap between compute and memory performance widening, the memory subsystem becomes the primary bottleneck for scientific volume visualization. Simple, structured, regular representations are often infeasible because the buses and interconnects involved need to accommodate the data required for interactive rendering. In this state‐of‐the‐art report, we review works focusing on large‐scale volume rendering beyond those typical structured and regular grid representations. We focus primarily on hierarchical and adaptive mesh refinement representations, unstructured meshes, and compressed representations that gained recent popularity. We review works that approach this kind of data using strategies such as out‐of‐core rendering, massive parallelism, and other strategies to cope with the sheer size of the ever‐increasing volume of data produced by today's supercomputers and acquisition devices. We emphasize the data management side of large‐scale volume rendering systems and also include a review of tools that support the various volume data types discussed. [ABSTRACT FROM AUTHOR]

Authors use various media formats to convey disease information to a broad audience, from articles and videos to interviews or documentaries. These media often include human characters, such as patients or treating physicians, who are involved with the disease. While artistic media, such as hand‐crafted illustrations and animations are used for health communication in many cases, our goal is to focus on data‐driven visualizations. Over the last decade, narrative visualization has experienced increasing prominence, employing storytelling techniques to present data in an understandable way. Similar to classic storytelling formats, narrative medical visualizations may also take a human character‐centered design approach. However, the impact of this form of data communication on the user is largely unexplored. This study investigates the protagonist's influence on user experience in terms of engagement, identification, self‐referencing, emotional response, perceived credibility, and time spent in the story. Our experimental setup utilizes a character‐driven story structure for disease stories derived from Joseph Campbell's Hero's Journey. Using this structure, we generated three conditions for a cerebral small vessel disease story that vary by their protagonist: (1) a patient, (2) a physician, and (3) a base condition with no human protagonist. These story variants formed the basis for our hypotheses on the effect of a human protagonist in disease stories, which we evaluated in an online study with 30 participants. Our findings indicate that a human protagonist exerts various influences on the story perception and that these also vary depending on the type of protagonist. [ABSTRACT FROM AUTHOR]

Histopathology research quickly evolves thanks to advances in whole slide imaging (WSI) and artificial intelligence (AI). However, existing WSI viewers are tailored either for clinical or research environments, but none suits both. This hinders the adoption of new methods and communication between the researchers and clinicians. The paper presents xOpat, an open‐source, browser‐based WSI viewer that addresses these problems. xOpat supports various data sources, such as tissue images, pathologists' annotations, or additional data produced by AI models. Furthermore, it provides efficient rendering of multiple data layers, their visual representations, and tools for annotating and presenting findings. Thanks to its modular, protocol‐agnostic, and extensible architecture, xOpat can be easily integrated into different environments and thus helps to bridge the gap between research and clinical practice. To demonstrate the utility of xOpat, we present three case studies, one conducted with a developer of AI algorithms for image segmentation and two with a research pathologist. [ABSTRACT FROM AUTHOR]

Interpolation is a foundational concept in scientific computing and is at the heart of many scientific visualization techniques. There is usually a tradeoff between the approximation capabilities of an interpolation scheme and its evaluation efficiency. For many applications, it is important for a user to navigate their data in real time. In practice, evaluation efficiency outweighs any incremental improvements in reconstruction fidelity. We first analyze, from a general standpoint, the use of compact piece-wise polynomial basis functions to efficiently interpolate data that is sampled on a lattice. We then detail our automatic code-generation framework on both CPU and GPU architectures. Specifically, we propose a general framework that can produce a fast evaluation scheme by analyzing the algebro-geometric structure of the convolution sum for a given lattice and basis function combination. We demonstrate the utility and generality of our framework by providing fast implementations of various box splines on the Body Centered and Face Centered Cubic lattices, as well as some non-separable box splines on the Cartesian lattice. We also provide fast implementations for certain Voronoi-splines that have not yet appeared in the literature. Finally, we demonstrate that this framework may also be used for non-Cartesian lattices in 4D. [ABSTRACT FROM AUTHOR]

Copyright of Rock & Mineral Analysis is the property of Editorial Board of Rock & Mineral Analysis and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This essay presents a real-world demonstration of the evidence-based science communication process, showing how it can be used to create scientific data visualizations for public audiences. Visualizing research data can be an important science communication tool. Maximizing its effectiveness has the potential to benefit millions of viewers. As with many forms of science communication, creators of such data visualizations typically rely on their own judgments and the views of the scientists providing the data to inform their science communication decision-making. But that leaves out a critical stakeholder in the communications pipeline: the intended audience. Here, we show the practical steps that our team, the Advanced Visualization Lab at the University of Illinois at Urbana-Champaign, has taken to shift toward more evidence-based practice to enhance our science communication impact. We do this by using concrete examples from our work on two scientific documentary films, one on the theme of "solar superstorms" and the other focusing on the black hole at the center of the Milky Way galaxy. We used audience research with each of these films to inform our strategies and designs. Findings revealed specific techniques that were effective in information labels. For example, audiences appreciated the use of an outline of the Earth to demonstrate scale in scientific visualizations relating to the Sun. We describe how such research evidence informed our understanding of "what works and why" with cinematic-style data visualizations for the public. We close the essay with our key take-home messages from this evidence-based science communication process. [ABSTRACT FROM AUTHOR]

Visual representations serve a multitude of crucial functions in the creation and dissemination of knowledge and information. They may take many different forms and refer to different phenomena or processes. Making valid decisions how particular visuals should look like presupposes a thorough insight in the nature of the referent or subject of the visual representation, the complex intermediate processes and technologies that are used to produce it, the final form and context of the visual, and the purposes it needs to serve. While often oblivious to its producers and their users or consumers, these insights and practices are firmly grounded in cultural processes of meaning-making, and therefore benefit from a socio-semiotic approach. The proposed socio-semiotic instrument builds upon my earlier taxonomic work in visualization practices. It incorporates many aspects and observations into a practical model that can be used to guide the production of new materials, or as a tool to interrogate the usefulness of existing visual representations for distinct purposes. [ABSTRACT FROM AUTHOR]

Background: Benign prostatic hyperplasia (BPH) is a common urological disorder leading to dysuria in middle-aged and elderly men and significantly reduces the quality of life of patients. Technology for BPH has made a great progress, while there is still a lack of visual and summary literature to make the summary. Summary: The aims of the study were to identify the cooperation of authors, countries, institutions, and explore hot topics' prospects regarding research of BPH. Relevant original articles were obtained from the Web of Science (WoS) database between 2016 and 2022. CiteSpace software was used to perform the analysis and visualization of scientific productivity and emerging trends. Key Messages: A total of 4,738 articles related to study of BPH were identified. We observed a gradual increase in the number of publications from 2016 to 2022. The USA dominated the field in all countries. Shanghai Jiao Tong University was the most productive institution in 6 years. Active cooperation between countries and between institutions was not observed. Journal of Urology was the most co-cited journal. Roehrborn CG (41 papers) was the most productive author and had the largest numbers of citations (820 co-citations) during the past 6 years. Close collaboration was not observed between the different authors. The main hot topics included matters related to BPH, urinary tract symptom, prostatic urethral lift, thermal therapy, and prostatic neoplasms. This scientometric study comprehensively reviewed publications related to BPH during the past 6 years using quantitative and qualitative methods, which can be used to forecast future research developments in BPH. [ABSTRACT FROM AUTHOR]

Scientific visualization is important in modern technological activities and engineering exploration. Due to the dark and high-pressure characteristics of deep sea, it is difficult to visualize the entire operation of deep-sea equipment. Thus, it is of great necessity to use virtual simulation technology to help people understand the operation process of some deep-sea exploration equipment on the sea floor. In this paper, science, art, and new media are combined through artistic rendering, visual processing, and the technology of virtual reality (VR) and holography, which makes the exploration of the latest deep-sea lander and intelligent submersible named "Luling" look more intuitive and smart and have more visual impact and expression. Apart from that, automatic manipulation videos of the rover robot in the deep sea captured by the Luling are effectively nested to realize the goal of virtual and real presentation. The designed scientific visualization of deep-sea equipment can not only adapt to the display output of VR, mobile phones, TV, 360° showcase, and other platforms, but also achieve immersive experience and virtual simulation learning through HTC Vive VR equipment. The technology and design way of scientific visualization in this paper is universal and suitable to the same kind of engineering simulation. [ABSTRACT FROM AUTHOR]

Copyright of Revista de Comunicación de la SEECI is the property of Sociedad Espanola de Estudios de la Comunicacion Iberoamericana and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Pamukkale University Journal of Social Sciences Institute / Pamukkale Üniversitesi Sosyal Bilimler Enstitüsü Dergisi is the property of Pamukkale University, Social Sciences Institute and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This research paper examines the Information Visualization in Library and Information Science: Exploring Principles, Types, and Tools for Effective Data Communication. The paper provides a historical overview of information visualization, including its evolution, milestones, and key figures. It also explores different types of information visualization, including data visualization, scientific visualization, information design, visual analytics, infographics, and geospatial visualization. The paper then discusses the principles of information visualization, including visual perception, cognitive load, design principles, interaction principles, and usability principles. It also reviews different data visualization tools, such as web-based visualization tools, open-source visualization tools, and commercial visualization tools, and emerging technologies in information visualization. Additionally, the paper highlights challenges and opportunities in information visualization research, such as data quality and reliability, user-cantered design, ethical considerations, interdisciplinary collaboration, and emerging trends. Finally, the paper provides a summary of findings, implications for LIS practice, recommendations for future research, and a conclusion. [ABSTRACT FROM AUTHOR]

Background: Thrombophilia is a group of disorders that result in a blood hypercoagulable state and induce thrombosis, which was found widely existed in recurrent pregnancy loss (RPL). More and more research about thrombophilia has been conducted but the association between thrombophilia and RPL remains uncertain. Thus, it's necessary to combine relevant literature to find the research hotspots and analyze the internal link between different study points, and then predict the development trend in RPL with thrombophilia. Methods: Relevant articles between 1970 and 2022 were obtained from the Web of Science (WoS) database. Software VOSviewer and CiteSpace were used to perform the analysis and conduct visualization of scientific productivity and emerging trends. Results: Seven hundred twenty-five articles published in recent 30 years by 3205 authors from 1139 organizations and 68 countries were analyzed. 37authors, 38 countries, and 53 organizations published papers ≥5. The United States was the most productive country and Univ Amsterdam was the most productive institution. Journal thrombosis and haemostasis had the most total citations. In keyword and clusters, factor-v-Leiden, inherited thrombophilia, activated protein-c, low-dose aspirin, molecular-weigh heparin, polymorphism had high-frequency focus on its etiology, diagnostics, and therapeutics. The strongest keyword bursts showed the research hotspots changed over time. Conclusions: There could be differences in the clinical relevance of different type of thrombophilia, as well as single and multiple thrombophilic factors. Anticoagulation and immunotherapy are currently the main treatment options. More clinical trials and basic research are expected and we should attach more attention to the whole management of in-vitro fertilization in the future. [ABSTRACT FROM AUTHOR]