Abstract
Despite significant efforts dedicated to exploring the potential applications of collaborative mixed reality, the focus of the existing works is mostly related to the creation of shared virtual/mixed environments resolving concurrent manipulation issues rather than supporting an effective collaboration strategy for the design procedure. For this reason, we present CIDER, a system for the collaborative editing of 3D augmented scenes allowing two or more users to manipulate the virtual scene elements independently and without unexpected changes. CIDER is based on the use of "layers"encapsulating the state of the environment with private layers that can be edited independently and a global one collaboratively updated with "commit"operations. Using this system, implemented for the HoloLens 2 headsets and supporting multiple users, we performed a user test on a realistic interior design task, evaluating the general usability and comparing two different approaches for the management of the atomic commit: forced (single-phase) and voting (requiring consensus), analyzing the effects of this choice on the collaborative behavior. © 2023 ACM.

Abstract
Virtual Reality (VR) has opened avenues for users to immerse themselves in virtual 3D environments, simulating reality across various domains like health, education, and entertainment. Haptic feedback plays a pivotal role in achieving lifelike experiences. However, the accessibility of haptic devices poses challenges, prompting the exploration of alternatives. In response, Pseudo-Haptic feedback has emerged, utilizing visual and auditory cues to create illusions or modify perceived haptic feedback. Given that many pseudo-haptic techniques are yet to be tailored for VR, our proposal involves combining and adapting multiple techniques to enhance compliance perception in virtual environments. By modifying the Mass-Spring-Damper model and incorporating hand-tracking software along with an inverse kinematics algorithm, our aim is to deliver compliance feedback through visual stimuli, thereby elevating the realism of the overall experience. The outcomes were encouraging, with numerous participants expressing their ability to easily discern various compliance levels with high confidence, all within a realistic and immersive environment. Additionally, we observed an impact of object scale on the perception of compliance in specific scenarios, as participants noted a tendency to perceive smaller objects as more compliant. © 2023 IEEE.

Abstract
Tetun is one of Timor-Leste's official languages alongside Portuguese. It is a low-resource language with over 932,000 speakers that started developing when Timor-Leste restored its independence in 2002. Newspapers mainly use Tetun and more than ten national online news websites actively broadcast news in Tetun every day. However, since information retrieval-based solutions for Tetun do not exist, finding Tetun information on the internet and digital platforms is challenging. This work aims to investigate and develop solutions that can enable the application of information retrieval techniques to develop search solutions for Tetun using Tetun INL and focus on the ad-hoc text retrieval task. As a result, we expect to have effective search solutions for Tetun and contribute to the innovation in information retrieval for low-resource languages, including making Tetun datasets available for future researchers.

Abstract
Postoperative residual neuromuscular block (PRNB) is still a problem during the surgery procedures resulting in health problems, such as, airway obstruction, hypoxia and pulmonary aspiration. To perform more accurate monitoring of the patient during surgery quantitative neuromuscular blockade monitoring measuring TOF ratio has been recommended by medical institutions. There are some devices available using different techniques, however there are only a few number of clinicians using them, since those devices are costly and have difficult clinical set-up. This paper presents a systematic review of current devices for quantitative neuromuscular monitoring during the surgery procedure following the PRISMA methodology. This study was carried out to list the currently available devices and report the capabilities that are missing in these devices since 2017. The databases used to do the research were PubMed, Cochrane Library, PubMed Central (PMC), Web of Science, IEEE Xplore, ScienceDirect, Directory of Open Access Journals (DOAJ). 17 articles were selected, presenting comparisons between two devices using different techniques. Quantitative monitoring provides the most accurate TOF ratio measurement but still needs to be incentivized.

Abstract
Background: Schizophrenia is the most common psychotic illness in the world. The negative and cognitive symptoms of this mental disorder often prevent full reintegration of patients into society, and cannot be effectively addressed with drugs alone, relying on therapy and rehabilitation. Video games as a digital tool for rehabilitation and therapy can help promote accessibility, improve patient engagement and reduce costs to institutions. Methods: A systematic review was conducted from October to November 2022 to analyze the effects of video game based rehabilitation and therapy on negative and cognitive symptoms in schizophrenic patients. The databases used to perform the search were Scopus, PubMed and Web of Science, with the search query: Schizophrenia AND (Video Game OR Serious Game). Results: A total of 228 papers were found, of which 88 duplicates were removed. After reading the titles and abstracts of the remaining 140 papers, 116 were excluded for not meeting the defined eligibility criteria for the review. Of the 24 papers left, 20 were excluded for similar reasons, resulting in the inclusion of four studies in this systematic review Conclusion: The available data for this review was limited, highlighting a need for more research in the field as well as standardization of terms used to describe the digital tools developed and assessment methods used to gather results from these interventions. Nevertheless, statistical data from the four studies included in this review showed that serious games are a promising tool for the rehabilitation and therapy of negative and cognitive symptoms of schizophrenic patients, with significant effects on the patients' performance and motivation.

Abstract
Background-Classification, detection, and segmentation of minimally invasive instruments is an essential component for robotic-assisted surgeries and surgical skill assessments. Methods-Cochrane Library, PubMed, ScienceDirect, and IEEE Xplore databases were searched from January 2018 to May 2022. Selected studies evaluated deep learning (DL) models for image and video analysis of laparoscopic surgery. Comparisons were made of the studies' characteristics such as the dataset source, type of laparoscopic operation, number of images/videos, and types of neural networks (NN) used. Results-22 out of 152 studies identified met the selection criteria. The application with the greatest number of studies was instrument detection (59.1%) and the second was instrument segmentation (40.9%). The most tested procedure was cholecystectomy (72.73%). Conclusions-Although CNN-based algorithms outperform other methods in instrument detection and many have been proposed, there are still challenging conditions where numerous difficulties arise. U-Nets are the dominant force in the field for segmentation, but other models such as Mask R-CNN follow close behind with comparable results. Deep learning holds immense potential in laparoscopic surgery and many improvements are expected as soon as data quality improves.