We have developed a series of course-based undergraduate research experiences for students integrated into course curriculum centered around the use of 3D visualization and virtual reality for science visualization. One project involves the creation and use of a volumetric renderer for hyperstack images, paired with a biology project in confocal microscopy. Students have worked to develop and test VR enabled tools for confocal microscopy visualization across headset based and CAVE based VR platforms. Two applications of the tool are presented: a rendering of Drosophila primordial germ cells coupled with automated detection and counting, and a database in development of 3D renderings of pollen grains. Another project involves the development and testing of point cloud renderers. Student work has focused on performance testing and enhancement across a range of 2D and 3D hardware, including native Quest apps. Through the process of developing these tools, students are introduced to scientific visualization concepts, while gaining practical experience with programming, software engineering, graphics, shader programming, and cross-platform design.

BACKGROUND: Applications of robotics in daily life are becoming essential by creating new possibilities in different fields, especially in the collaborative environment. The potentials of collaborative robots are tremendous as they can work in the same workspace as humans. A framework employing a top-notch technology for collaborative robots will surely be worthwhile for further research.
OBJECTIVE: This study aims to present the development of a novel framework for the collaborative robot using mixed reality.
METHODS: The framework uses Unity and Unity Hub as a cross-platform gaming engine and project management tool to design the mixed reality interface and digital twin. It also uses the Windows Mixed Reality platform to show digital materials on holographic display and the Azure mixed reality services to capture and expose digital information. Eventually, it uses a holographic device (HoloLens 2) to execute the mixed reality-based collaborative system.
RESULTS: A thorough experiment was conducted to validate the novel framework for mixed reality-based control of a collaborative robot. This framework was successfully applied to implement a collaborative system using a 5-degree of freedom robot (xArm-5) in a mixed reality environment. The framework was stable and worked smoothly throughout the collaborative session. Due to the distributed nature of cloud applications, there is a negligible latency between giving a command and the execution of the physical collaborative robot.
CONCLUSIONS: Opportunities for collaborative robots in telerehabilitation and teleoperation are vital as in any other field. The proposed framework was successfully applied in a collaborative session, and it can also be applied in other similar potential applications for robust and more promising performance.

BACKGROUND: Intracranial EEG data offer a unique spatio-temporal precision to investigate human brain functions. Large datasets have become recently accessible thanks to new iEEG data-sharing practices and tighter collaboration with clinicians. Yet, the complexity of such datasets poses new challenges, especially regarding the visualization and anatomical display of iEEG.
METHODS: We introduce HiBoP, a multi-modal visualization software specifically designed for large groups of patients and multiple experiments. Its main features include the dynamic display of iEEG responses induced by tasks/stimulations, the definition of Regions and electrodes Of Interest, and the shift between group-level and individual-level 3D anatomo-functional data.
RESULTS: We provide a use-case with data from 36 patients to reveal the global cortical dynamics following tactile stimulation. We used HiBoP to visualize high-gamma responses [50-150 Hz], and define three major response components in primary somatosensory and premotor cortices and parietal operculum.
UNASSIGNED: Several iEEG softwares are now publicly available with outstanding analysis features. Yet, most were developed in languages (Python/Matlab) chosen to facilitate the inclusion of new analysis by users, rather than the quality of the visualization. HiBoP represents a visualization tool developed with videogame standards (Unity/C#), and performs detailed anatomical analysis rapidly, across multiple conditions, patients, and modalities with an easy export toward third-party softwares.
CONCLUSIONS: HiBoP provides a user-friendly environment that greatly facilitates the exploration of large iEEG datasets, and helps users decipher subtle structure/function relationships.

The shielding parameters can vary depending on the geometrical structure of the linear accelerators (LINAC), treatment techniques, and beam energies. Recently, the introduction of O-ring type linear accelerators is increasing. The objective of this study is to evaluate the shielding parameters of new type of linac using a dedicated program developed by us named ORSE (O-ring type Radiation therapy equipment Shielding Evaluation). The shielding evaluation was conducted for a total of four treatment rooms including Elekta Unity, Varian Halcyon, and Accuray Tomotherapy. The developed program possesses the capability to calculate transmitted dose, maximum treatable patient capacity, and shielding wall thickness based on patient data. The doses were measured for five days using glass dosimeters to compare with the results of program. The IMRT factors and use factors obtained from patient data showed differences of up to 65.0% and 33.8%, respectively, compared to safety management report. The shielding evaluation conducted in each treatment room showed that the transmitted dose at every location was below 1% of the dose limit. The results of program and measurements showed a maximum difference of 0.003 mSv/week in transmitted dose. The ORSE program allows for the shielding evaluation results to the clinical environment of each institution based on patient data.

Measurement-based verification is impossible for the patient-specific quality assurance (QA) of online adaptive magnetic resonance imaging-guided radiotherapy (oMRgRT) because the patient remains on the couch throughout the session. We assessed a deep learning (DL) system for oMRgRT to predict the gamma passing rate (GPR). This study collected 125 verification plans [reference plan (RP), 100; adapted plan (AP), 25] from patients with prostate cancer treated using Elekta Unity. Based on our previous study, we employed a convolutional neural network that predicted the GPRs of nine pairs of gamma criteria from 1%/1 mm to 3%/3 mm. First, we trained and tested the DL model using RPs (n = 75 and n = 25 for training and testing, respectively) for its optimization. Second, we tested the GPR prediction accuracy using APs to determine whether the DL model could be applied to APs. The mean absolute error (MAE) and correlation coefficient (r) of the RPs were 1.22 ± 0.27% and 0.29 ± 0.10 in 3%/2 mm, 1.35 ± 0.16% and 0.37 ± 0.15 in 2%/2 mm, and 3.62 ± 0.55% and 0.32 ± 0.14 in 1%/1 mm, respectively. The MAE and r of the APs were 1.13 ± 0.33% and 0.35 ± 0.22 in 3%/2 mm, 1.68 ± 0.47% and 0.30 ± 0.11 in 2%/2 mm, and 5.08 ± 0.29% and 0.15 ± 0.10 in 1%/1 mm, respectively. The time cost was within 3 s for the prediction. The results suggest the DL-based model has the potential for rapid GPR prediction in Elekta Unity.

Sensory booths enhanced with VR technology have displayed promising potential for improving sensory evaluation, perception research, and educational experiences. However, there remains an insufficient of data on VR\'s utilization in sensory science. In our research, we designed a virtual sensory booth (SB) utilizing Virtual Reality (VR) to complement sensory analysis and foster applications in the field of sensory science. The experiment involved the utilization of diverse sensory methods and product samples for examination within the virtual SB, which was compared to the traditional SB. A total of forty-three participants took part in the study to scrutinize the implications of the virtual SB. The results of a post-VR questionnaire demonstrated the participants\' positive reception of the virtual SB. The study\'s findings suggest that the virtual SB could serve as a valuable resource for sensory scientists and individuals keen on exploring the emerging opportunities offered by VR. Notably, the virtual SB has proven to have potential applications, particularly within the food industry, with a special focus on sensory science. •Virtualized SB incorporating VR technology is a promising sensory evaluation and perception studies approach.•Virtual SB intends to use various sensory methods in VR applications for sensory analysis.•The creation of new VR-based technological solutions for sensory analysis can serve as a supplement to traditional sensory analysis.

The Elekta Unity magnetic resonance (MR) linac is limited to longitudinal couch motion and a sagittal-only laser, which restricts the ability to perform patient-specific quality assurance (PSQA) intensity-modulated radiotherapy (IMRT) measurements for very lateral targets. This work introduces a simple method to perform PSQA using the Sun Nuclear ArcCheck-MR phantom at left and right lateral positions without additional equipment or in-house construction. The proposed setup places the center of the phantom 1.3 cm vertical and 12.9 cm lateral to isocenter in either the left or right direction. Computed tomography (CT) scans are used to simulate the setup and create a QA plan template in the Monaco treatment planning system (TPS). The workflow is demonstrated for four patients, with an average axial distance from the center of the bore to the planning target volume (PTV) of 12.4 cm. Gamma pass rates were above 94% for all plans using global 3%/2 mm gamma criterion with a 10% threshold. Setup uncertainties are slightly larger for the proposed lateral setup compared to the centered setup on the Elekta platform (∼1 mm compared to ∼0.5 mm), but acceptable pass rates are achievable without optimizing shifts in the gamma analysis software. In general, adding the left and right lateral positions increases the axial area in the bore encompassed by the cylindrical measurement array by 147%, substantially increasing the flexibility of measurements for offset targets. Based on this work, we propose using the lateral QA setup if the closest distance to the PTV edge from isocenter is larger than the array radius (10.5 cm) or the percent of the PTV encompassed by the diode array would be increased with the lateral setup compared to the centered setup.

We characterized the on-board megavoltage imager (MVI) of a magnetic resonance-guided radiotherapy machine for beam output checks. Linearity and repeatability of its dose response were investigated. Alignment relative to the beam under clinical circumstances was evaluated for a year using daily measurements. Linearity and short-term repeatability were excellent. Long-term repeatability drifted 0.8 % per year, which can be overcome by monthly cross calibrations. Long-term alignment was stable. Thus, the MVI has suitable characteristics for beam output checks.

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Rabbi Danya Ruttenberg\'s 2022 book, On Repentance and Repair: Making Amends in an Unapologetic World, questions the conventional wisdom that being quick to forgive is a virtue. Unless the person who has caused harm has acknowledged the harm, started to change, made restitution, apologized, and is now making different choices, forgiveness is not just unwarranted, it is potentially harmful to individuals and societies.