MR-RIEW: An MR Toolkit for Designing Remote Immersive Experiment Workflows

We present MR-RIEW, a toolkit for virtual and mixed reality that provides researchers with a dynamic way to design an immersive experiment workflow including instructions, environments, sessions, trials and questionnaires. It is implemented in Unity via scriptable objects, allowing simple customisation. The graphic elements, the scenes and the questionnaires can be selected and associated without code. MR-RIEW can save locally into the headset and remotely the questionnaire's answers. MR-RIEW is connected to Google Firebase service for the remote solution requiring a minimal configuration

Mitigation strategies for participant non-attendance in VR remote collaborative experiments

COVID-19 led to the temporary closure of many HCI research facilities disrupting many ongoing user studies. While some studies could easily move online, this has proven problematic for virtual reality (VR) studies. The main challenge of remote VR study is the recruitment of participants who have access to specialized hardware such as head-mounted displays. This challenge is exacerbated in collaborative VR studies, where multiple participants need to be available and remotely connect to the study simultaneously. We identify the latter as the worst-case scenario regarding resource wastage and frustration. Across two collaborative user studies, we identified the personal connection between the experimenter and the participant as a critical factor in reducing non-attendance. We compare three recruitment strategies that we have iteratively developed based on our recent experiences. We introduce a metric to quantify the cost for each recruitment strategy, and we show that our final strategy achieves the best metric score. Our work is valuable for HCI researchers recruiting participants for collaborative VR remote studies, but it can be easily extended to every remote experiment scenario

Shall I describe it or shall I move closer? Verbal references and locomotion in VR collaborative search tasks

Research in pointing-based communication within immersive collaborative virtual environments (ICVE) remains a compelling area of study. Previous studies explored techniques to improve accuracy and reduce errors when hand-pointing from a distance. In this study, we explore how users adapt their behaviour to cope with the lack of accuracy during pointing. In an ICVE where users can move (i.e., locomotion) when faced with a lack of laser pointers, pointing inaccuracy can be avoided by getting closer to the object of interest. Alternatively, collaborators can enrich the utterances with details to compensate for the lack of pointing precision. Inspired by previous CSCW remote desktop collaboration, we measure visual coordination, the implicitness of deixis’ utterances and the amount of locomotion. We design an experiment that compares the effects of the presence/absence of laser pointers across hard/easy-to-describe referents. Results show that when users face pointing inaccuracy, they prefer to move closer to the referent rather than enrich the verbal reference

Genomic diversity and signatures of selection in meat and fancy rabbit breeds based on high-density marker data

open6noThe study was funded by the PSRN (Programma di Sviluppo Rurale Nazionale) Cun-Fu and Cun-Fu 2 projects (co-funded by the European Agricultural Fund for Rural Development of the European Union and by the Italian Ministry of Agriculture, Food and Forestry—MiPAAF) and by the University of Bologna RFO 2019 programme.Background: Domestication of the rabbit (Oryctolagus cuniculus) has led to a multi-purpose species that includes many breeds and lines with a broad phenotypic diversity, mainly for external traits (e.g. coat colours and patterns, fur structure, and morphometric traits) that are valued by fancy rabbit breeders. As a consequence of this human-driven selection, distinct signatures are expected to be present in the rabbit genome, defined as signatures of selection or selective sweeps. Here, we investigated the genome of three Italian commercial meat rabbit breeds (Italian Silver, Italian Spotted and Italian White) and 12 fancy rabbit breeds (Belgian Hare, Burgundy Fawn, Champagne d’Argent, Checkered Giant, Coloured Dwarf, Dwarf Lop, Ermine, Giant Grey, Giant White, Rex, Rhinelander and Thuringian) by using high-density single nucleotide polymorphism data. Signatures of selection were identified based on the fixation index (FST) statistic with different approaches, including single-breed and group-based methods, the latter comparing breeds that are grouped based on external traits (different coat colours and body sizes) and types (i.e. meat vs. fancy breeds). Results: We identified 309 genomic regions that contained signatures of selection and that included genes that are known to affect coat colour (ASIP, MC1R and TYR), coat structure (LIPH), and body size (LCORL/NCAPG, COL11A1 and HOXD) in rabbits and that characterize the investigated breeds. Their identification proves the suitability of the applied methodologies for capturing recent selection events. Other regions included novel candidate genes that might contribute to the phenotypic variation among the analyzed breeds, including genes for pigmentation-related traits (EDNRA, EDNRB, MITF and OCA2) and body size, with a strong candidate for dwarfism in rabbit (COL2A1). Conclusions: We report a genome-wide view of genetic loci that underlie the main phenotypic differences in the analyzed rabbit breeds, which can be useful to understand the shift from the domestication process to the development of breeds in O. cuniculus. These results enhance our knowledge about the major genetic loci involved in rabbit external traits and add novel information to understand the complexity of the genetic architecture underlying body size in mammals.openBallan, Mohamad; Bovo, Samuele; Schiavo, Giuseppina; Schiavitto, Michele; Negrini, Riccardo; Fontanesi, LucaBallan, Mohamad; Bovo, Samuele; Schiavo, Giuseppina; Schiavitto, Michele; Negrini, Riccardo; Fontanesi, Luc

VR Toolkit for Identifying Group Characteristics

Visualising crowds is a key pedestrian dynamics topic, with significant research efforts aiming to improve the current state-of-the-art. Sophisticated visualisation methods are a standard for modern commercial models, and can improve crowd management techniques and sociological theory development. These models often define standard metrics, including density and speed. However, modern visualisation techniques typically use desktop screens. This can limit the capability of a user to investigate and identify key features, especially in real time scenarios such as control centres. Virtual reality (VR) provides the opportunity to represent scenarios in a fully immersive environment, granting the user the ability to quickly assess situations. Furthermore, these visualisations are often limited to the simulation model that has generated the dataset, rather than being source-agnostic. In this paper we implement an immersive, interactive toolkit for crowd behaviour analysis. This toolkit was built specifically for use within VR environments and was developed in conjunction with commercial users and researchers. It allows the user to identify locations of interest, as well as individual agents, showing characteristics such as group density, individual (Voronoi) density and speed. Furthermore, it was used as a data-extraction tool, building individual fundamental diagrams for all scenario agents, and predicting group status as a function of local agent geometry. Finally, this paper presents an evaluation of the toolkit made by crowd behaviour experts

OPTIMAL MANAGEMENT OF FLEXIBILITY SERVICES IN LV DISTRIBUTION GRIDS

With the increase of intermittent and not programmable generation from clean resources and of new demand tech-nologies characterized by high coincident peaks (like heat pumps, induction cookers, etc.) the management of avail-able flexibility in distribution grids to provide network ser-vices has become very important. The paper proposes an optimization model to manage the flexibility in the LV net-work to both solve local network problems and aggregate the available flexibility for use at higher levels while sat-isfying LV network constraints. The model is a tool for the LV DSOs to optimally manage the flexibilities and its fea-tures are illustrated on the IEEE 123 test feeder

Comparative analysis of genomic inbreeding parameters and runs of homozygosity islands in several fancy and meat rabbit breeds

Runs of homozygosity (ROH) are defined as long stretches of DNA homozygous at each polymorphic position. The proportion of genome covered by ROH and their length are indicators of the level and origin of inbreeding. In this study, we analysed SNP chip datasets (obtained using the Axiom OrcunSNP Array) of a total of 702 rabbits from 12 fancy breeds and four meat breeds to identify ROH with different approaches and calculate several genomic inbreeding parameters. The highest average number of ROH per animal was detected in Belgian Hare (~150) and the lowest in Italian Silver (~106). The average length of ROH ranged from 4.001 ± 0.556 Mb in Italian White to 6.268 ± 1.355 Mb in Ermine. The same two breeds had the lowest (427.9 ± 86.4 Mb, Italian White) and the highest (921.3 ± 179.8 Mb, Ermine) average values of the sum of all ROH segments. More fancy breeds had a higher level of genomic inbreeding (as defined by ROH) than meat breeds. Several ROH islands contain genes involved in body size, body length, pigmentation processes, carcass traits, growth, and reproduction traits (e.g.: AOX1, GPX5, IFRD1, ITGB8, NELL1, NR3C1, OCA2, TRIB1, TRIB2). Genomic inbreeding parameters can be useful to overcome the lack of information in the management of rabbit genetic resources. ROH provided information to understand, to some extent, the genetic history of rabbit breeds and to identify signatures of selection in the rabbit genome

Real-time head-based deep-learning model for gaze probability regions in collaborative VR

Eye behaviour has gained much interest in the VR research community as an interaction input and support for collaboration. Researchers implemented gaze inference models when eye-tracking is missing by using head behavior and saliency. However, these solutions are resource-demanding and thus unfit for untethered devices, and their angle accuracy is around 7°, which can be a problem in high-density informative areas. To address this issue, we propose a lightweight deep learning model that generates the probability density function of the gaze as a percentile contour. This solution allows us to introduce a visual attention representation based on a region rather than a point and manage a trade-off between the ambiguity of a region and the error of a point. We tested our model in untethered devices with real-time performances; we evaluated its accuracy which outperforms our identified baselines (average fixation map and head direction)

Genomic diversity, linkage disequilibrium and selection signatures in European local pig breeds assessed with a high density SNP chip

Genetic characterization of local breeds is essential to preserve their genomic variability, to advance conservation policies and to contribute to their promotion and sustainability. Genomic diversity of twenty European local pig breeds and a small sample of Spanish wild pigs was assessed using high density SNP chips. A total of 992 DNA samples were analyzed with the GeneSeek Genomic Profiler (GGP) 70 K HD porcine genotyping chip. Genotype data was employed to compute genetic diversity, population differentiation and structure, genetic distances, linkage disequilibrium and effective population size. Our results point out several breeds, such as Turopolje, Apulo Calabrese, Casertana, Mora Romagnola and Lithuanian indigenous wattle, having the lowest genetic diversity, supported by low heterozygosity and very small effective population size, demonstrating the need of enhanced conservation strategies. Principal components analysis showed the clustering of the individuals of the same breed, with few breeds being clearly isolated from the rest. Several breeds were partially overlapped, suggesting genetic closeness, which was particularly marked in the case of Iberian and Alentejana breeds. Spanish wild boar was also narrowly related to other western populations, in agreement with recurrent admixture between wild and domestic animals. We also searched across the genome for loci under diversifying selection based on F-S(T) outlier tests. Candidate genes that may underlie differences in adaptation to specific environments and productive systems and phenotypic traits were detected in potentially selected genomic regions