Quality Metrics and Reordering Strategies for Revealing Patterns in BioFabric Visualizations.

Visualizing relational data is crucial for understanding complex connections between entities in social networks, political affiliations, or biological interactions. Well-known representations like node-link diagrams and adjacency matrices offer valuable insights, but their effectiveness relies on the ability to identify patterns in the underlying topological structure. Reordering strategies and layout algorithms play a vital role in the visualization process since the arrangement of nodes, edges, or cells influences the visibility of these patterns.

An Analysis of the Interplay and Mutual Benefits of Grounded Theory and Visualization.

Grounded theory (GT) is a research methodology that entails a systematic workflow for theory generation grounded on emergent data. In this paper, we juxtapose GT workflows with typical workflows in visualization and visual analytics (VIS), unveiling the characteristics shared by these workflows. We explore the research landscape of VIS to study where GT is applied to generate VIS theories, explicitly as well as implicitly.

AI-smartphone markerless motion capturing of hip, knee, and ankle joint kinematics during countermovement jumps.

Recently, AI-driven skeleton reconstruction tools that use multistage computer vision pipelines were designed to estimate 3D kinematics from 2D video sequences. In the present study, we validated a novel markerless, smartphone video-based artificial intelligence (AI) motion capture system for hip, knee, and ankle angles during countermovement jumps (CMJs). Eleven participants performed six CMJs.

Complications and Long-Term Outcome in 30 Canine Total Hip Arthroplasties Using a Second-Generation Selective Laser Melted Screw Cup.

Objective:  The aim of this study was to report complications and outcomes of a cementless total hip arthroplasty (THA) system with a second-generation selective laser-melted screw cup (SCSL).

Study Design:  All THA using the SCSL performed at a single institution between January 2017 and November 2022 were retrospectively evaluated. Patients with a minimum follow-up period of 12 months and complete medical records were included and analyzed for radiographic and clinical outcomes.

TreEducation: A Visual Education Platform for Teaching Treemap Layout Algorithms.

Treemaps are a powerful tool for representing hierarchical data in a space-efficient manner and are used in various domains, including network security or software development. However, interpreting the topology encoded by nested rectangles can be challenging, particularly compared to tree-structured representations like node-link diagrams or icicle plots. To address this challenge, we introduce TreEducation, a visual education platform designed to improve the visualization literacy skills required for reading treemaps among non-expert users.