Classification of Internal and External Distractions in an Educational VR Environment Using Multimodal Features.

Virtual reality (VR) can potentially enhance student engagement and memory retention in the classroom. However, distraction among participants in a VR-based classroom is a significant concern. Several factors, including mind wandering, external noise, stress, etc., can cause students to become internally and/or externally distracted while learning. To detect distractions, single or multi-modal features can be used. A single modality is found to be insufficient to detect both internal and external distractions, mainly because of individual variability. In this work, we investigated multi-modal features: eye tracking and EEG data, to classify the internal and external distractions in an educational VR environment. We set up our educational VR environment and equipped it for multi-modal data collection. We implemented different machine learning (ML) methods, including k-nearest-neighbors (kNN), Random Forest (RF), one-dimensional convolutional neural network - long short-term memory (1D-CNN-LSTM), and two-dimensional convolutional neural networks (2D-CNN) to classify participants' internal and external distraction states using the multi-modal features. We performed cross-subject, cross-session, and gender-based grouping tests to evaluate our models. We found that the RF classifier achieves the highest accuracy over 83% in the cross-subject test, around 68% to 78% in the cross-session test, and around 90% in the gender-based grouping test compared to other models. SHAP analysis of the extracted features illustrated greater contributions from the occipital and prefrontal regions of the brain, as well as gaze angle, gaze origin, and head rotation features from the eye tracking data.

A multimodal sensor dataset for continuous stress detection of nurses in a hospital.

Advances in wearable technologies provide the opportunity to monitor many physiological variables continuously. Stress detection has gained increased attention in recent years, mainly because early stress detection can help individuals better manage health to minimize the negative impacts of long-term stress exposure. This paper provides a unique stress detection dataset created in a natural working environment in a hospital. This dataset is a collection of biometric data of nurses during the COVID-19 outbreak. Studying stress in a work environment is complex due to many social, cultural, and psychological factors in dealing with stressful conditions. Therefore, we captured both the physiological data and associated context pertaining to the stress events. We monitored specific physiological variables such as electrodermal activity, Heart Rate, and skin temperature of the nurse subjects. A periodic smartphone-administered survey also captured the contributing factors for the detected stress events. A database containing the signals, stress events, and survey responses is publicly available on Dryad.

Mutational mechanisms shaping the coding and noncoding genome of germinal center derived B-cell lymphomas.

B cells have the unique property to somatically alter their immunoglobulin (IG) genes by V(D)J recombination, somatic hypermutation (SHM) and class-switch recombination (CSR). Aberrant targeting of these mechanisms is implicated in lymphomagenesis, but the mutational processes are poorly understood. By performing whole genome and transcriptome sequencing of 181 germinal center derived B-cell lymphomas (gcBCL) we identified distinct mutational signatures linked to SHM and CSR. We show that not only SHM, but presumably also CSR causes off-target mutations in non-IG genes. Kataegis clusters with high mutational density mainly affected early replicating regions and were enriched for SHM- and CSR-mediated off-target mutations. Moreover, they often co-occurred in loci physically interacting in the nucleus, suggesting that mutation hotspots promote increased mutation targeting of spatially co-localized loci (termed hypermutation by proxy). Only around 1% of somatic small variants were in protein coding sequences, but in about half of the driver genes, a contribution of B-cell specific mutational processes to their mutations was found. The B-cell-specific mutational processes contribute to both lymphoma initiation and intratumoral heterogeneity. Overall, we demonstrate that mutational processes involved in the development of gcBCL are more complex than previously appreciated, and that B cell-specific mutational processes contribute via diverse mechanisms to lymphomagenesis.

Fronto-parietal coding of goal-directed actions performed by artificial agents.

With advances in technology, artificial agents such as humanoid robots will soon become a part of our daily lives. For safe and intuitive collaboration, it is important to understand the goals behind their motor actions. In humans, this process is mediated by changes in activity in fronto-parietal brain areas. The extent to which these areas are activated when observing artificial agents indicates the naturalness and easiness of interaction. Previous studies indicated that fronto-parietal activity does not depend on whether the agent is human or artificial. However, it is unknown whether this activity is modulated by observing grasping (self-related action) and pointing actions (other-related action) performed by an artificial agent depending on the action goal. Therefore, we designed an experiment in which subjects observed human and artificial agents perform pointing and grasping actions aimed at two different object categories suggesting different goals. We found a signal increase in the bilateral inferior parietal lobule and the premotor cortex when tool versus food items were pointed to or grasped by both agents, probably reflecting the association of hand actions with the functional use of tools. Our results show that goal attribution engages the fronto-parietal network not only for observing a human but also a robotic agent for both self-related and social actions. The debriefing after the experiment has shown that actions of human-like artificial agents can be perceived as being goal-directed. Therefore, humans will be able to interact with service robots intuitively in various domains such as education, healthcare, public service, and entertainment.

Single-Pass Composable 3D Lens Rendering and Spatiotemporal 3D Lenses.

We present a new 3D lens rendering technique and a new spatiotemporal lens. Interactive 3D lenses, often called volumetric lenses, provide users with alternative views of data sets within 3D lens boundaries while maintaining the surrounding overview (context). In contrast to previous multipass rendering work, we discuss the strengths, limitations, and performance costs of a single-pass technique especially suited to fragment-level lens effects, such as color mapping, lighting, and clipping. Some object-level effects, such as a data set selection lens, are also incorporated, with each object's geometry being processed once by the graphics pipeline. For a substantial range of effects, our approach supports several composable lenses at interactive frame rates without performance loss during increasing lens intersections or manipulation by a user. Other cases, for which this performance cannot be achieved, are also discussed. We illustrate possible applications of our lens system, including Time Warp lenses for exploring time-varying data sets.

Real-time rendering method and performance evaluation of composable 3D lenses for interactive VR.

We present and evaluate a new approach for real-time rendering of composable 3D lenses for polygonal scenes. Such lenses, usually called "volumetric lenses," are an extension of 2D Magic Lenses to 3D volumes in which effects are applied to scene elements. Although the composition of 2D lenses is well known, 3D composition was long considered infeasible due to both geometric and semantic complexity. Nonetheless, for a scene with multiple interactive 3D lenses, the problem of intersecting lenses must be considered. Intersecting 3D lenses in meaningful ways supports new interfaces such as hierarchical 3D windows, 3D lenses for managing and composing visualization options, or interactive shader development by direct manipulation of lenses providing component effects. Our 3D volumetric lens approach differs from other approaches and is one of the first to address efficient composition of multiple lenses. It is well-suited to head-tracked VR environments because it requires no view-dependent generation of major data structures, allowing caching and reuse of full or partial results. A Composite Shader Factory module composes shader programs for rendering composite visual styles and geometry of intersection regions. Geometry is handled by Boolean combinations of region tests in fragment shaders, which allows both convex and nonconvex CSG volumes for lens shape. Efficiency is further addressed by a Region Analyzer module and by broad-phase culling. Finally, we consider the handling of order effects for composed 3D lenses.

Establishment and characterization of two distinct malignant mesothelioma cell lines with common clonal origin.

We describe two newly established malignant mesothelioma (MM) cell lines derived from a pleural effusion of a male. One cell line, designated as MM-Z03E, reveals an epithelioid cobblestone morphology, while the second one, designated as MM-Z03S and subcloned after in vivo selection, exhibits a sarcomatoid storiform growth pattern. Both cell lines showed the immunologic profile characteristic for MM (i.e., expression of cytokeratin, CK18, calretinin, and vimentin in both phenotypes). Cytogenetics, multicolor fluorescence in situ hybridization, comparative genomic hybridization, and oligonucleotide array CGH were performed on both cell lines. Aberrations shared by both cell lines included chromosomal losses of 1q34 approximately qter, 4, 9p, 10p, 13, 14, 16q, 18, and 22, as well as a complex structural aberration involving chromosome 17. Aberrations exclusive to MM-Z03E included gains of 3q11q27 and 5p, while gain of 9q and losses of 3q27qter, 11q, and 18 in MM-Z03S were exclusive to MM-Z03E. Both cell lines were able to develop solid transplant tumors in nude mice within 16 weeks, and immunophenotyping of tumor xenografts revealed an overall retained expression profile of the markers used. Remarkably, one xenograft from MM-Z03E revealed overexpression of p53 and widely invasive growth. In conclusion, both cell lines are useful in vivo and in vitro model systems to study the underlying genetic mechanisms of biphasic differentiation in MM, which can be of certain value considering the increasing relevance of assessing MM tumor biology for the clinical management of this disease.