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Collaborative work in social virtual reality often requires an interplay of loosely coupled collaboration from different virtual locations and tightly coupled face-to-face collaboration. Without appropriate system mediation, however, transitioning between these phases requires high navigation and coordination efforts. In this paper, we present an interaction system that allows collaborators in virtual reality to seamlessly switch between different collaboration models known from related work. To this end, we present collaborators with functionalities that let them work on individual sub-tasks in different virtual locations, consult each other using asymmetric interaction patterns while keeping their current location, and temporarily or permanently join each other for face-to-face interaction. We evaluated our methods in a user study with 32 participants working in teams of two. Our quantitative results indicate that delegating the target selection process for a long-distance teleport significantly improves placement accuracy and decreases task load within the team. Our qualitative user feedback shows that our system can be applied to support flexible collaboration. In addition, the proposed interaction sequence received positive evaluations from teams with varying VR experiences.

Objective: The aim of this follow-up study is to compare a manually driven hysteroscopic tissue removal system (Resectr TM 9 Fr) with a motor driven system (Truclear TM ) in terms of long-term clinical outcomes such as abnormal uterine bleeding and polyp recurrence., Study Design: This is a follow-up of a multicenter randomized controlled trial comparing a manually and motor driven hysteroscopic tissue removal system for polypectomy. This prospective cohort study was performed at Ghent University Hospital (Ghent, Belgium) and Catharina Hospital Eindhoven (Eindhoven, the Netherlands). The trial was registered at Clinicaltrials.gov (Trial ID = NCT05337605, April 2022). Seventy-five women with abnormal uterine bleeding who participated in the randomized controlled trial and had pathological confirmation of the diagnosis of an endometrial polyp, were contacted. Fifty-five women (70.67 %) were willing to participate in this follow-up study. The primary outcome was the recurrence and/or persistence of abnormal uterine bleeding and the time to the recurrence of abnormal uterine bleeding. Secondary outcomes were polyp recurrence and time to polyp recurrence, symptom relief, satisfaction score regarding symptom relief and general satisfaction score regarding the surgical procedure., Results: In the manually driven group, the mean time to the recurrence or persistence of abnormal uterine bleeding was 26 months (95 % CI 20 - 32). In the motor driven group, the mean time to the recurrence or persistence of abnormal uterine bleeding was 29 months (95 % CI 23- 34). A log-rank test showed a non-significant difference between both groups (P =.77). There was no significant difference in polyp recurrence (P =.22) or symptom relief between the two groups (P =.67). Additionally, the groups did not differ in satisfaction scores regarding symptoms or polypectomy (P =.16 and P =.61, respectively)., Conclusion: This long-term follow-up study showed no statistically significant difference in the recurrence and persistence of abnormal uterine bleeding between a manually and motor driven hysteroscopic tissue removal system for polypectomy., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: H.v.V received an unrestricted grant from the External Research Program from Medtronic. T.H. reports unrestricted external research support from Medtronic for the ongoing RIGHT trial at Ghent University Hospital. The other authors have nothing to disclose., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The inquiry into the impact of diverse transitions between cross-reality environments on user experience remains a compelling research endeavor. Existing work often offers fragmented perspectives on various techniques or confines itself to a singular segment of the reality-virtuality spectrum, be it virtual reality or augmented reality. This study embarks on bridging this knowledge gap by systematically assessing the effects of six prevalent transitions while users remain immersed in tasks spanning both virtual and physical domains. In particular, we investigate the effect of different transitions while the user is continuously engaged in a demanding task instead of purely focusing on a given transition. As a preliminary step, we evaluate these six transitions within the realm of pure virtual reality to establish a baseline. Our findings reveal a clear preference among participants for brief and efficient transitions in a task-driven experience, instead of transitions that prioritize interactivity and continuity. Subsequently, we extend our investigation into a cross-reality context, encompassing transitions between virtual and physical environments. Once again, our results underscore the prevailing preference for concise and effective transitions. Furthermore, our research offers intriguing insights about the potential mitigation of visual incoherence between virtual and augmented reality environments by utilizing different transitions.

The change of the user's viewpoint in an immersive virtual environment, called locomotion, is one of the key components in a virtual reality interface. Effects of locomotion, such as simulator sickness or disorientation, depend on the specific design of the locomotion method and can influence the task performance as well as the overall acceptance of the virtual reality system. Thus, it is important that a locomotion method achieves the intended effects. The complexity of this task has increased with the growing number of locomotion methods and design choices in recent years. Locomotion taxonomies are classification schemes that group multiple locomotion methods and can aid in the design and selection of locomotion methods. Like locomotion methods themselves, there exist multiple locomotion taxonomies, each with a different focus and, consequently, a different possible outcome. However, there is little research that focuses on locomotion taxonomies. We performed a systematic literature review to provide an overview of possible locomotion taxonomies and analysis of possible decision criteria such as impact, common elements, and use cases for locomotion taxonomies. We aim to support future research on the design, choice, and evaluation of locomotion taxonomies and thereby support future research on virtual reality locomotion.

Although habits are a well-researched topic within psychology, habits enacted at the workplace received limited attention in the organizational literature. In this article we examine habits that employees show at the workplace. Because workplace habits are not always functional for performance or affective outcomes, and because employees themselves may regard specific habits as undesirable, it is important to identify ways of how employees can abandon such unwanted habits. We report findings from a daily-survey study (N = 145 persons) in which we examined if self-regulatory processes predict disengagement from undesirable habits and engagement in more desirable alternative behaviors. Multilevel path analysis showed that day-specific implementation intentions and day-specific vigilant monitoring were negatively related to day-specific habitual behavior and positively related to day-specific alternative behaviors, both in the morning and in the afternoon. Analysis of follow-up data (N = 126 persons) showed that change in habit strength was stable over a 2-month period, suggesting that implementation intentions, vigilant monitoring, and the associated enactment of alternative behavior indeed may help to disengage from unwanted habits, particularly with respect to task-related habits and when consistency in vigilant monitoring is high. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Heartwater, Ehrlichia ruminantium infection in cattle, sheep, goats, and some wild ruminants, is an economically important disease in Africa characterized by high mortality rates in susceptible populations. In South Africa, the current commercial heartwater vaccine is an infection and treatment type of immunization using virulent live E. ruminantium organisms generated from blood of infected sheep with subsequent treatment of the animals with antibiotics at specific times during the course of infection. This vaccine has several inherent problems preventing its wide use as the vaccine must be administered intravenously and it does not protect against all the South African field isolates. A vaccine based on inactivation of Zimbabwean E. ruminantium Mbizi strain organisms produced in endothelial cell cultures can be a sustainable option because it will not require antibiotic treatment and will be safe as there is no potential for reversion to virulence. Previous data generated in laboratory trials and under natural field setting provides support for this vaccine approach. Four inactivated vaccine formulations using the E. ruminantium Mbizi strain were tested for their efficacy in Merino sheep compared to an unvaccinated control group (11 sheep per group). Two vaccines were prepared by beta-propiolactone (BPL) inactivation, and two were inactivated with binary ethylenimine (BEI) while purification was done with both percoll and polyethylene glycol (PEG). The four vaccine preparations were formulated with Montanide ISA 50V2 adjuvant and administered twice subcutaneously (2 ml per dose) at an interval of 4 weeks. All groups were challenged with a virulent homologous cell-cultured E. ruminantium inoculated via the intra-venous route on day 56. The primary variable of efficacy was measured by the percentage survival rate or mortality between the Controls and Vaccine Groups. Three vaccine formulations (BEI/Percoll (Group 3), BEI/PEG (Group 4), BPL/Percoll, (Group 1) had a significantly higher percent of animal surviving challenge compared to the unvaccinated control (p-values 0.001, 0.035, 0.030, respectively). The highest number of survivors was obtained in Group 3 BEI/Percoll; 10/11 (91%). Groups 4 (BEI/PEG) and Group 1 (BPL/Percoll) produced similar percentage of survivals of 64%. In contrast, the lowest survival rate of 50% was observed in Group 2 (BPL/PEG) which was numerically different but not significantly different from the unvaccinated control which had an 18% survival rate (2/11). The inactivated vaccine using BEI or BPL as inactivating agents blended with ISA 50 adjuvant induced protective immunity against challenge. The BEI/Percoll (Group 3) vaccination regimen was most efficacious against a lethal heartwater challenge as it significantly protected sheep against mortality which is the most important aspect of heartwater infections. Future work should be directed towards improvement of this vaccine formulation especially from the down-stream processing point of view as the percoll method is not scalable for commercialization purposes., (Copyright © 2022 Elsevier GmbH. All rights reserved.)

Simulation software for spiking neuronal network models matured in the past decades regarding performance and flexibility. But the entry barrier remains high for students and early career scientists in computational neuroscience since these simulators typically require programming skills and a complex installation. Here, we describe an installation-free Graphical User Interface (GUI) running in the web browser, which is distinct from the simulation engine running anywhere, on the student's laptop or on a supercomputer. This architecture provides robustness against technological changes in the software stack and simplifies deployment for self-education and for teachers. Our new open-source tool, NEST Desktop, comprises graphical elements for creating and configuring network models, running simulations, and visualizing and analyzing the results. NEST Desktop allows students to explore important concepts in computational neuroscience without the need to learn a simulator control language before. Our experiences so far highlight that NEST Desktop helps advancing both quality and intensity of teaching in computational neuroscience in regular university courses. We view the availability of the tool on public resources like the European ICT infrastructure for neuroscience EBRAINS as a contribution to equal opportunities., (Copyright © 2021 Spreizer et al.)

Fluorescence lifetime imaging (FLIm) is an optical spectroscopic imaging technique capable of real-time assessments of tissue properties in clinical settings. Label-free FLIm is sensitive to changes in tissue structure and biochemistry resulting from pathological conditions, thus providing optical contrast to identify and monitor the progression of disease. Technical and methodological advances over the last two decades have enabled the development of FLIm instrumentation for real-time, in situ, mesoscopic imaging compatible with standard clinical workflows. Herein, we review the fundamental working principles of mesoscopic FLIm, discuss the technical characteristics of current clinical FLIm instrumentation, highlight the most commonly used analytical methods to interpret fluorescence lifetime data and discuss the recent applications of FLIm in surgical oncology and cardiovascular diagnostics. Finally, we conclude with an outlook on the future directions of clinical FLIm., (© 2021 Wiley-VCH GmbH.)

Objective: The aim of this study was to evaluate the predictive value of the dynamic morphological development process between cleavage-stage and blastocyst-stage embryos., Study Design: A retrospective study was executed between 2015 and 2017 at Ghent University Hospital. A total of 996 first fresh IVF/ICSI cycles resulting in a single embryo transfer on day 5 were included. Embryos were scored on day 3 and day 5 as excellent, good, moderate or poor based on Alpha/ESHRE guidelines and Gardner and Schoolcraft scoring-system. If embryos changed category between day 3 and 5, the number of steps (between excellent; good; moderate; poor) in positive and negative direction was expressed., Results: On day 5, the ongoing pregnancy rate (OPR) of excellent embryos was 37.4 %. Univariate analyses showed that on day 5, both a higher cell stage, better inner cell mass and better trophectoderm were significantly associated with an ongoing pregnancy. In case of deterioration in quality of individual embryos between day 3 and day 5, the OPR was significantly lower. Conversely, improvement of embryo quality between day 3 and day 5 showed higher ongoing pregnancy rates (overall OPR of good day-3 embryos improving to excellent day-5 embryos: 30 %; moderate day 3 to excellent day 5: 50 %; poor day 3 to excellent day 5: 42 %; poor day 3 to good day 5: 20 %; poor day 3 to moderate day 5: 16 %). When embryos improved from poor on day 3 to excellent day 5 the OPR was significantly higher in comparison with embryos that did not change in quality scoring during development (steady embryos) (OR: 1.785, p < 0.05)., Conclusion: Our results suggest that it is more likely to achieve an ongoing pregnancy when transferring an embryo that has improved in quality between days 3 and 5 as opposed to one that has remained stable., Competing Interests: Declaration of Competing Interest No conflicts of interest declared., (Copyright © 2020 Elsevier B.V. All rights reserved.)

The growing demand for tissue engineered vascular grafts (TEVG) motivates the development of optimized fabrication and monitoring procedures. Bioreactors which provide physiologically-relevant conditions are important for improving holistic TEVG properties and performance. Herein we describe a fiber-based intraluminal imaging system that allows for in situ assessment of vascular materials and re-cellularization processes inside a bioreactor by simultaneous and co-registered measurements of endogenous fluorescence lifetime and exogenous marker fluorescence intensity. The lumen of 6 vascular grafts (∼4 mm diameter) were scanned by reciprocally rotating a 41° angle polished multimode optical fiber inside a protective glass tube with outer diameter of 3 mm. Tubular bovine pericardium constructs were recellularized using enhanced Green Fluorescent Protein (eGFP) transfected cells in a custom bioreactor. The imaging system has resolved consistently the cellular autofluorescence from that of tissue matrix in situ based on the lifetime fluorescence properties of endogenous molecular species. The location of the re-cellularized area was validated by the eGFP emission. Current results demonstrate the potential of this system as a valuable tool in tissue engineering for in situ studies of cell-tissue interactions in cylindrical or other 3-dimensional structures.

Objective: To develop a random forest model (RFM) to predict implantation potential of a transferred embryo and compare it with a multivariate logistic regression model (MvLRM), based on data from a large cohort including in vitro fertilization (IVF) patients treated with the use of single-embryo transfer (SET) of blastocyst-stage embryos., Design: Retrospective study of a 2-year single-center cohort of women undergoing IVF or intracytoplasmatic sperm injection (ICSI)., Setting: Academic hospital., Patient(s): Data from 1,052 women who underwent fresh SET in IVF or ICSI cycles were included., Intervention(s): None., Main Outcome Measure(s): The performance of both RFM and MvLRM to predict pregnancy was quantified in terms of the area under the receiver operating characteristic (ROC) curve (AUC), classification accuracy, specificity, and sensitivity., Result(s): ROC analysis resulted in an AUC of 0.74 ± 0.03 for the proposed RFM and 0.66 ± 0.05 for the MvLRM for the prediction of ongoing pregnancies of ≥11 weeks. This RFM approach and the MvLRM yielded, respectively, sensitivities of 0.84 ± 0.07 and 0.66 ± 0.08 and specificities of 0.48 ± 0.07 and 0.58 ± 0.08., Conclusion(s): The performance to predict ongoing implantation will significantly improve with the use of an RFM approach compared with MvLRM., (Copyright © 2018 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.)

Neuronal network models and corresponding computer simulations are invaluable tools to aid the interpretation of the relationship between neuron properties, connectivity, and measured activity in cortical tissue. Spatiotemporal patterns of activity propagating across the cortical surface as observed experimentally can for example be described by neuronal network models with layered geometry and distance-dependent connectivity. In order to cover the surface area captured by today's experimental techniques and to achieve sufficient self-consistency, such models contain millions of nerve cells. The interpretation of the resulting stream of multi-modal and multi-dimensional simulation data calls for integrating interactive visualization steps into existing simulation-analysis workflows. Here, we present a set of interactive visualization concepts called views for the visual analysis of activity data in topological network models, and a corresponding reference implementation VIOLA (VIsualization Of Layer Activity). The software is a lightweight, open-source, web-based, and platform-independent application combining and adapting modern interactive visualization paradigms, such as coordinated multiple views, for massively parallel neurophysiological data. For a use-case demonstration we consider spiking activity data of a two-population, layered point-neuron network model incorporating distance-dependent connectivity subject to a spatially confined excitation originating from an external population. With the multiple coordinated views, an explorative and qualitative assessment of the spatiotemporal features of neuronal activity can be performed upfront of a detailed quantitative data analysis of specific aspects of the data. Interactive multi-view analysis therefore assists existing data analysis workflows. Furthermore, ongoing efforts including the European Human Brain Project aim at providing online user portals for integrated model development, simulation, analysis, and provenance tracking, wherein interactive visual analysis tools are one component. Browser-compatible, web-technology based solutions are therefore required. Within this scope, with VIOLA we provide a first prototype.

Peroxisome proliferator-activated receptor α (PPARα) is a nuclear receptor of clinical interest as a drug target in various metabolic disorders. PPARα also exhibits marked anti-inflammatory capacities. The first-generation PPARα agonists, the fibrates, have however been hampered by drug-drug interaction issues, statin drop-in, and ill-designed cardiovascular intervention trials. Notwithstanding, understanding the molecular mechanisms by which PPARα works will enable control of its activities as a drug target for metabolic diseases with an underlying inflammatory component. Given its role in reshaping the immune system, the full potential of this nuclear receptor subtype as a versatile drug target with high plasticity becomes increasingly clear, and a novel generation of agonists may pave the way for novel fields of applications.

Simulation models in many scientific fields can have non-unique solutions or unique solutions which can be difficult to find. Moreover, in evolving systems, unique final state solutions can be reached by multiple different trajectories. Neuroscience is no exception. Often, neural network models are subject to parameter fitting to obtain desirable output comparable to experimental data. Parameter fitting without sufficient constraints and a systematic exploration of the possible solution space can lead to conclusions valid only around local minima or around non-minima. To address this issue, we have developed an interactive tool for visualizing and steering parameters in neural network simulation models. In this work, we focus particularly on connectivity generation, since finding suitable connectivity configurations for neural network models constitutes a complex parameter search scenario. The development of the tool has been guided by several use cases-the tool allows researchers to steer the parameters of the connectivity generation during the simulation, thus quickly growing networks composed of multiple populations with a targeted mean activity. The flexibility of the software allows scientists to explore other connectivity and neuron variables apart from the ones presented as use cases. With this tool, we enable an interactive exploration of parameter spaces and a better understanding of neural network models and grapple with the crucial problem of non-unique network solutions and trajectories. In addition, we observe a reduction in turn around times for the assessment of these models, due to interactive visualization while the simulation is computed.

Natural genetic promoters are regulated by multiple cis and trans regulatory factors. For quantitative studies of these promoters, the concentration of only a single factor is typically varied to obtain the dose response or transfer function of the promoters with respect to the factor. Such design of experiments has limited our ability to understand quantitative, combinatorial interactions between multiple regulatory factors at promoters. This limitation is primarily due to the intractable number of experimental combinations that arise from multifactorial design of experiments. To overcome this major limitation, we integrate impact printing and cell-free systems to enable multi-dimensional studies of genetic promoters. We first present a gradient printing system which comprises parallel piezoelectric cantilever beams as a scalable actuator array to generate droplets with tunable volumes in the range of 100 pL-10 nL, which facilitates highly accurate direct dilutions in the range of 1-10 000-fold in a 1 μL drop. Next, we apply this technology to study interactions between three regulatory factors at a synthetic genetic promoter. Finally, a mathematical model of gene regulatory modules is established using the multi-parametric and multi-dimensional data. Our work creates a new frontier in the use of cell-free systems and droplet printing for multi-dimensional studies of synthetic genetic constructs.

Enterotoxaemia (pulpy kidney) is a common bacterial disease of sheep caused by Clostridium perfringens type D epsilon toxin. It has mortality rates of up to 30% in non-vaccinated animals. Current vaccines from whole cell cultures are expensive to manufacture and can induce local inflammatory responses in sheep. They usually have reduced immunogenicity because of the difficulty of standardising the inactivation step in vaccine manufacturing. In the current study, we evaluated the safety and potency of a recombinant plant-made epsilon toxoid protein (r-Etox) as an affordable and safer alternative vaccine for developing countries. Results of injection site reactions, rectal temperature and toxin neutralisation test in single and prime- boost inoculations of mice, guinea pigs and sheep suggest that the product is not toxic to animals and could protect sheep against enterotoxaemia.

To avoid simulator sickness and improve presence in immersive virtual environments (IVEs), high frame rates and low latency are required. In contrast, volume rendering applications typically strive for high visual quality that induces high computational load and, thus, leads to low frame rates. To evaluate this trade-off in IVEs, we conducted a controlled user study with 53 participants. Search and count tasks were performed in a CAVE with varying volume rendering conditions which are applied according to viewer position updates corresponding to head tracking. The results of our study indicate that participants preferred the rendering condition with continuous adjustment of the visual quality over an instantaneous adjustment which guaranteed for low latency and over no adjustment providing constant high visual quality but rather low frame rates. Within the continuous condition, the participants showed best task performance and felt less disturbed by effects of the visualization during movements. Our findings provide a good basis for further evaluations of how to accelerate volume rendering in IVEs according to user's preferences.

When moving through a tracked immersive virtual environment, it is sometimes useful to deviate from the normal one-to-one mapping of real to virtual motion. One option is the application of rotation gain, where the virtual rotation of a user around the vertical axis is amplified or reduced by a factor. Previous research in head-mounted display environments has shown that rotation gain can go unnoticed to a certain extent, which is exploited in redirected walking techniques. Furthermore, it can be used to increase the effective field of regard in projection systems. However, rotation gain has never been studied in CAVE systems, yet. In this work, we present an experiment with 87 participants examining the effects of rotation gain in a CAVE-like virtual environment. The results show no significant effects of rotation gain on simulator sickness, presence, or user performance in a cognitive task, but indicate that there is a negative influence on spatial knowledge especially for inexperienced users. In secondary results, we could confirm results of previous work and demonstrate that they also hold for CAVE environments, showing a negative correlation between simulator sickness and presence, cognitive performance and spatial knowledge, a positive correlation between presence and spatial knowledge, a mitigating influence of experience with 3D applications and previous CAVE exposure on simulator sickness, and a higher incidence of simulator sickness in women.

Data annotation finds increasing use in Virtual Reality applications with the goal to support the data analysis process, such as architectural reviews. In this context, a variety of different annotation systems for application to immersive virtual environments have been presented. While many interesting interaction designs for the data annotation workflow have emerged from them, important details and evaluations are often omitted. In particular, we observe that the process of handling metadata to interactively create and manage complex annotations is often not covered in detail. In this paper, we strive to improve this situation by focusing on the design of data annotation workflows and their evaluation. We propose a workflow design that facilitates the most important annotation operations, i.e., annotation creation, review, and modification. Our workflow design is easily extensible in terms of supported annotation and metadata types as well as interaction techniques, which makes it suitable for a variety of application scenarios. To evaluate it, we have conducted a user study in a CAVE-like virtual environment in which we compared our design to two alternatives in terms of a realistic annotation creation task. Our design obtained good results in terms of task performance and user experience.

Modeling large-scale spiking neural networks showing realistic biological behavior in their dynamics is a complex and tedious task. Since these networks consist of millions of interconnected neurons, their simulation produces an immense amount of data. In recent years it has become possible to simulate even larger networks. However, solutions to assist researchers in understanding the simulation's complex emergent behavior by means of visualization are still lacking. While developing tools to partially fill this gap, we encountered the challenge to integrate these tools easily into the neuroscientists' daily workflow. To understand what makes this so challenging, we looked into the workflows of our collaborators and analyzed how they use the visualizations to solve their daily problems. We identified two major issues: first, the analysis process can rapidly change focus which requires to switch the visualization tool that assists in the current problem domain. Second, because of the heterogeneous data that results from simulations, researchers want to relate data to investigate these effectively. Since a monolithic application model, processing and visualizing all data modalities and reflecting all combinations of possible workflows in a holistic way, is most likely impossible to develop and to maintain, a software architecture that offers specialized visualization tools that run simultaneously and can be linked together to reflect the current workflow, is a more feasible approach. To this end, we have developed a software architecture that allows neuroscientists to integrate visualization tools more closely into the modeling tasks. In addition, it forms the basis for semantic linking of different visualizations to reflect the current workflow. In this paper, we present this architecture and substantiate the usefulness of our approach by common use cases we encountered in our collaborative work.