Residency Octree: A Hybrid Approach for Scalable Web-Based Multi-Volume Rendering.

We present a hybrid multi-volume rendering approach based on a novel Residency Octree that combines the advantages of out-of-core volume rendering using page tables with those of standard octrees. Octree approaches work by performing hierarchical tree traversal. However, in octree volume rendering, tree traversal and the selection of data resolution are intrinsically coupled. This makes fine-grained empty-space skipping costly. Page tables, on the other hand, allow access to any cached brick from any resolution. However, they do not offer a clear and efficient strategy for substituting missing high-resolution data with lower-resolution data. We enable flexible mixed-resolution out-of-core multi-volume rendering by decoupling the cache residency of multi-resolution data from a resolution-independent spatial subdivision determined by the tree. Instead of one-to-one node-to-brick correspondences, each residency octree node is mapped to a set of bricks from different resolution levels. This makes it possible to efficiently and adaptively choose and mix resolutions, adapt sampling rates, and compensate for cache misses. At the same time, residency octrees support fine-grained empty-space skipping, independent of the data subdivision used for caching. Finally, to facilitate collaboration and outreach, and to eliminate local data storage, our implementation is a web-based, pure client-side renderer using WebGPU and WebAssembly. Our method is faster than prior approaches and efficient for many data channels with a flexible and adaptive choice of data resolution.

Structural and biophysical characterization of the multidomain xylanase Xyl.

The depletion of fossil fuels, associated pollution, and resulting health hazards are of concern worldwide. Woody biomass constitutes an alternative source of cleaner and renewable energy. The efficient use of woody biomass depends on xylan depolymerisation as the endo-ß-1,4-xylopyranosyl homopolymer is the main component of hemicellulose, the second most abundant component of wood. Xylan depolymerisation is achieved by hemicellulolytic xylanases of glycoside hydrolase (GH) families 5, 8, 10, 11, 30 and 43 of the CAZY database. We analysed a multidomain xylanase (Xyl) from the hindgut metagenome of the snouted harvester termite Trinervitermes trinervoides that releases xylobiose and xylotriose from beech and birch xylan and wheat arabinoxylan. The four domains of Xyl include an N-terminal GH11 xylanase domain, two family 36-like carbohydrate-binding domains CBM36-1 and 2, and a C-terminal CE4 esterase domain. Previous analyses indicated that CBM36-1 deletion slightly increased GH11 catalysis at low pH whereas removal of both CBMs decreased xylanase activity at 60°C from 90 to 56%. Possible cooperativity between the domains suggested by these observations was explored. A crystal structure of the two-domain construct, GH11-CBM36-1, confirmed the structure of the GH11 domain whereas the CBM36-1 domain lacked electron density, possibly indicating a random orientation of the CBM36-1 domain around the GH11 domain. Isothermal titration calorimetry (ITC) experiments similarly did not indicate specific interactions between the individual domains of Xyl supporting a "beads-on-a-string" model for Xyl domains.

Visual Interaction with Deep Learning Models through Collaborative Semantic Inference.

Automation of tasks can have critical consequences when humans lose agency over decision processes. Deep learning models are particularly susceptible since current black-box approaches lack explainable reasoning. We argue that both the visual interface and model structure of deep learning systems need to take into account interaction design. We propose a framework of collaborative semantic inference (CSI) for the co-design of interactions and models to enable visual collaboration between humans and algorithms. The approach exposes the intermediate reasoning process of models which allows semantic interactions with the visual metaphors of a problem, which means that a user can both understand and control parts of the model reasoning process. We demonstrate the feasibility of CSI with a co-designed case study of a document summarization system.

Development of an Interprofessional Educational Electronic Health Record.

This paper identifies issues relating to academic health record systems and outlines a project currently underway to develop an open source educational clinical information system to better support interprofessional health education.

Visual Interactive Map Matching.

Map matching is the process of assigning observed geographic positions of vehicles and their trajectories to the actual road links in a road network. In this paper, we present Visual Interactive Map Matching, a visual analytics approach to fine-tune the data preprocessing and matching process. It is based on ST-matching, a state-of-the-art and easy-to-understand map matching algorithm. Parameters of the preprocessing step and algorithm can be optimized with immediate visual feedback. Visualizations show current matching issues and performance metrics on a map and in diagrams. Manual and computer-supported editing of the road network model leads to a refined alignment of trajectories and roads. We demonstrate our approach with large-scale taxi trajectory data. We show that optimizing the matching on a subsample results in considerably improved matching quality, also when later scaled to the full dataset. An optimized matching ensures data faithfulness and prevents misinterpretation when the matched data might be investigated in follow-up analysis.

Visual Pattern-Driven Exploration of Big Data.

Pattern extraction algorithms are enabling insights into the ever-growing amount of today's datasets by translating reoccurring data properties into compact representations. Yet, a practical problem arises: With increasing data volumes and complexity also the number of patterns increases, leaving the analyst with a vast result space. Current algorithmic and especially visualization approaches often fail to answer central overview questions essential for a comprehensive understanding of pattern distributions and support, their quality, and relevance to the analysis task. To address these challenges, we contribute a visual analytics pipeline targeted on the pattern-driven exploration of result spaces in a semi-automatic fashion. Specifically, we combine image feature analysis and unsupervised learning to partition the pattern space into interpretable, coherent chunks, which should be given priority in a subsequent in-depth analysis. In our analysis scenarios, no ground-truth is given. Thus, we employ and evaluate novel quality metrics derived from the distance distributions of our image feature vectors and the derived cluster model to guide the feature selection process. We visualize our results interactively, allowing the user to drill down from overview to detail into the pattern space and demonstrate our techniques in two case studies on Earth observation and biomedical genomic data.

Mapping Retinal and Choroidal Thickness in Unilateral Nongranulomatous Acute Anterior Uveitis Using Three-Dimensional 1060-nm Optical Coherence Tomography.

Purpose: To analyze retinal thickness (RT) and choroidal thickness (ChT) changes in patients with unilateral nongranulomatous acute anterior uveitis (AAU) using three-dimensional (3D) 1060-nm optical coherence tomography (OCT). Methods: Retinal and choroidal thickness maps were statistically analyzed for 24 patients with newly diagnosed unilateral AAU before therapy. A total of 17 patients were followed until resolution of inflammatory activity (twice in the first week, then weekly). Resolution occurred in all subjects within 6 weeks after the initial diagnosis. After resolution, thickness maps were again generated. All patients were imaged by high-speed spectral-domain (SD) 3D 1060-nm OCT over a 10 × 10-mm field of view. The spatial distribution of retinal and choroidal thickness was mapped and analyzed using the Early Treatment Diabetic Retinopathy Study (ETDRS) grid. Results: The choroid was significantly thicker in eyes affected by AAU than in fellow eyes before therapy with a mean thickness difference of 37 ± 11.44 µm (mean ± SD, Bonferroni correction, α = 0.0125). Following therapy, ChT significantly decreased with a mean change of 24 ± 6.9 µm (mean ± SD, Bonferroni correction, α = 0.0125). There was no significant difference in RT between AAU and fellow eyes before therapy or in AAU eyes before and after therapy. Conclusions: Eyes affected by AAU demonstrate an increase in ChT before and a subsequent decrease after therapy while retinal thickness seems unaltered by disease and therapy. ChT might be a useful biomarker in monitoring posterior involvement and response to therapy in patients with AAU.

Can Twitter Save Lives? A Broad-Scale Study on Visual Social Media Analytics for Public Safety.

The use of social media monitoring for public safety is on the brink of commercialization and practical adoption. To close the gap between research and application, this paper presents results of a two-phase study on visual analytics of social media for public safety. For the first phase, we conducted a large field study, in which 29 practitioners from disaster response and critical infrastructure management were asked to investigate crisis intelligence tasks based on Twitter data recorded during the 2013 German Flood. To this end, the ScatterBlogs visual analytics system, a platform that provides reference implementations of tools and techniques popular in research, was given to them as an integrated toolbox. We reviewed the domain experts' individual performances with the system as well as their comments about the usefulness of techniques. In the second phase, we built on this feedback about ScatterBlogs in order to sketch out a system and create additional tools specifically adapted to the collected requirements. The performance of the old lab prototype is finally compared against the re-design in a controlled user study.

Dedicated 3D photoacoustic breast imaging.

PURPOSE: To report the design and imaging methodology of a photoacoustic scanner dedicated to imaging hemoglobin distribution throughout a human breast. METHODS: The authors developed a dedicated breast photoacoustic mammography (PAM) system using a spherical detector aperture based on our previous photoacoustic tomography scanner. The system uses 512 detectors with rectilinear scanning. The scan shape is a spiral pattern whose radius varies from 24 to 96 mm, thereby allowing a field of view that accommodates a wide range of breast sizes. The authors measured the contrast-to-noise ratio (CNR) using a target comprised of 1-mm dots printed on clear plastic. Each dot absorption coefficient was approximately the same as a 1-mm thickness of whole blood at 756 nm, the output wavelength of the Alexandrite laser used by this imaging system. The target was immersed in varying depths of an 8% solution of stock Liposyn II-20%, which mimics the attenuation of breast tissue (1.1 cm(-1)). The spatial resolution was measured using a 6 µm-diameter carbon fiber embedded in agar. The breasts of four healthy female volunteers, spanning a range of breast size from a brassiere C cup to a DD cup, were imaged using a 96-mm spiral protocol. RESULTS: The CNR target was clearly visualized to a depth of 53 mm. Spatial resolution, which was estimated from the full width at half-maximum of a profile across the PAM image of a carbon fiber, was 0.42 mm. In the four human volunteers, the vasculature was well visualized throughout the breast tissue, including to the chest wall. CONCLUSIONS: CNR, lateral field-of-view and penetration depth of our dedicated PAM scanning system is sufficient to image breasts as large as 1335 mL, which should accommodate up to 90% of the women in the United States.

ScatterBlogs2: real-time monitoring of microblog messages through user-guided filtering.

The number of microblog posts published daily has reached a level that hampers the effective retrieval of relevant messages, and the amount of information conveyed through services such as Twitter is still increasing. Analysts require new methods for monitoring their topic of interest, dealing with the data volume and its dynamic nature. It is of particular importance to provide situational awareness for decision making in time-critical tasks. Current tools for monitoring microblogs typically filter messages based on user-defined keyword queries and metadata restrictions. Used on their own, such methods can have drawbacks with respect to filter accuracy and adaptability to changes in trends and topic structure. We suggest ScatterBlogs2, a new approach to let analysts build task-tailored message filters in an interactive and visual manner based on recorded messages of well-understood previous events. These message filters include supervised classification and query creation backed by the statistical distribution of terms and their co-occurrences. The created filter methods can be orchestrated and adapted afterwards for interactive, visual real-time monitoring and analysis of microblog feeds. We demonstrate the feasibility of our approach for analyzing the Twitter stream in emergency management scenarios.

Photoacoustic angiography of the breast.

PURPOSE: The authors report a noninvasive technique and instrumentation for visualizing vasculature in the breast in three dimensions without using either ionizing radiation or exogenous contrast agents, such as iodine or gadolinium. Vasculature is visualized by virtue of its high hemoglobin content compared to surrounding breast parenchyma. The technique is compatible with dynamic contrast-enhanced studies. METHODS: Photoacoustic sonic waves were stimulated in the breast with a pulsed laser operating at 800 nm and a mean exposure of 20 mJ/pulse over an area of approximately 20 cm2. These waves were subsequently detected by a hemispherical array of piezoelectric transducers, the temporal signals from which were filtered and backprojected to form three-dimensional images with nearly uniform k-space sampling. RESULTS: Three-dimensional vascular images of a human volunteer demonstrated a clear visualization of vascular anatomy with submillimeter spatial resolution to a maximum depth of 40 mm using a 24 s image acquisition protocol. Spatial resolution was nearly isotropic and approached 250 microm over a 64 x 64 x 50 mm field of view. CONCLUSIONS: The authors have successfully visualized submillimeter breast vasculature to a depth of 40 mm using an illumination intensity that is 32 times less than the maximum permissible exposure according to the American National Standard for Safe Use of Lasers. Clearly, the authors can achieve greater penetration depth in the breast by increasing the intensity and the cross-sectional area of the illumination beam. Given the 24 s image acquisition time without contrast agent, dynamic, contrast-enhanced, photoacoustic breast imaging using optically absorbing contrast agents is conceivable in the future.