Shared Environment Research Articles

Multi-users interaction anomalous subgraph detection for event mining

Event detection on networks is an important research task in data mining. Most previous approaches usually detect a particular type of event that satisfies the predefined rules in the model, i.e., data-driven methods. However, few methods consider the diverse interests of multiple experts during the detection process to discover unexplored events. In this paper, we regard interactive event detection on attributed networks as Multi-users Interaction Anomalous Subgraph Detection (MIASD), where events are represented as connected subgraphs on networks. The core of our method is automatically maximizing a non-parametric scan statistic over connected subgraphs to identify the most anomalous subgraph as the event and integrating the interactions from multiple experts simultaneously, i.e., under both data-driven and user-driven paradigm. In our approach, we first define individual and shared environments of experts on attributed networks to model the interests of experts, including the interactive operations and Recommended Interaction Domain. Afterwards, we propose an efficient anomalous subgraph detection algorithm in which each expert gives feedback separately on the vertices in the Recommended Interaction Domain; then, the non-parametric scan statistic over the connected subgraph is approximately maximized by integrating various feedback from experts into the iterative subgraph expansion process. In this way, our method retrieves the most anomalous subgraph on the network as the final event, which contains the potential unexplored information. We have conducted extensive experiments on three real-world datasets and proved that our algorithm could achieve better performance compared with several competitive baselines. Furthermore, the case study shows that our method could detect global abnormal events effectively.

Thriving While Working Remotely: An fsQCA Application in Coworking Spaces

The present study investigates what drives thriving at work for remote workers in coworking spaces. Coworking spaces are flexible workspaces involving individuals from various occupational backgrounds that work in shared work environments that are usually deemed as vibrant and supportive. Coworking spaces reflect significant changes in economic activity due to the increase in digital and location-independent knowledge work. These changes have been further accelerated by the COVID-19 pandemic, with many companies relying on coworking alternatives for their employees who work remotely. Within this scenario, acknowledging the complexity and importance of coworking spaces, recent literature calls for a more fine-grained understanding of how coworking spaces help achieve positive psychological outcomes such as thriving at work (e.g., represented by a joint sense of vitality and learning at work). A greater understanding of what drives remote workers’ thriving in coworking spaces can help coworking providers and employing companies define work arrangements and environments that suit the different – and sometimes conflicting – needs, motives, and psychological experiences of remote workers. Acknowledging the complex set of interrelationships underlying thriving at work, this study leverages complexity theory and qualitative comparative analysis to uncover six different, yet equifinal, configurations of antecedents driving remote workers’ thriving in coworking spaces.

Mean Field Behavior of Collaborative Multiagent Foragers

Collaborative multi-agent robotic systems where agents coordinate by modifying a shared environment often result in undesired dynamical couplings that complicate the analysis and experiments when solving a specific problem or task. Simultaneously, biologically-inspired robotics rely on simplifying agents and increasing their number to obtain more efficient solutions to such problems, drawing similarities with natural processes. In this work we focus on the problem of a biologically-inspired multi-agent system solving collaborative foraging. We show how mean field techniques can be used to re-formulate such a stochastic multi-agent problem into a deterministic autonomous system. This de-couples agent dynamics, enabling the computation of limit behaviours and the analysis of optimality guarantees. Furthermore, we analyse how having finite number of agents affects the performance when compared to the mean field limit and we discuss the implications of such limit approximations in this multi-agent system, which have impact on more general collaborative stochastic problems.

Depicting Fecal Microbiota Characteristic in Yak, Cattle, Yak-Cattle Hybrid and Tibetan Sheep in Different Eco-Regions of Qinghai-Tibetan Plateau.

ABSTRACTThe gut microbiota is closely associated with the health and production performance of livestock. Partial studies on ruminant microbiota are already in progress in the Qinghai-Tibetan Plateau Area (QTPA) in China, but large-scale and representative profiles for the QTPA are still lacking. Here, 16S rRNA sequencing was used to analyze 340 samples from yak, cattle, yak-cattle hybrids, and Tibetan sheep, which lived in a shared environment from 4 eco-regions of the QTPA during the same season, and aimed to investigate the fecal microbiota community composition, diversity, and potential function. All samples were clustered into 2 enterotypes, which were derived from the genera Ruminococcaceae UCG-005 and Acinetobacter, respectively. Environment, human activity, species, and parasitization all affected the fecal microbiota. By assessing the relationship between the fecal microbiota and the above variables, we identified a scattered pattern of fecal microbiota dissimilarity based more significantly on diet over other factors. Additionally, gastrointestinal nematode infection could reduce the capacity of the bacterial community for biosynthesis of other secondary metabolites, carbohydrate metabolism, and nucleotide metabolism. Ultimately, this study provided a fecal microbiota profile for ruminants living in 4 eco-regions of the QTPA and its potential future applications in developing animal husbandry regimes.IMPORTANCE Cattle, yak, and sheep reside as the main ruminants distributed throughout most regions of Qinghai-Tibetan Plateau Area (QTPA) in China. However, there is a lack of large-scale research in the QTPA on their fecal microbiota, which can regulate and reflect host health as an internalized “microbial organ.” Our study depicted the fecal microbiota community composition and diversity of yak, cattle, yak-cattle hybrids, and Tibetan sheep from 4 eco-regions of the QTPA. Additionally, our results demonstrated here that the ruminant samples could be clustered into 2 enterotypes and that diet outweighed other factors in shaping fecal microbiota in the QTPA. This study provided a basis for understanding the microbiota characteristic of ruminants and its possible applications for livestock production in the QTPA.

Taste Metaphors Ground Emotion Concepts Through the Shared Attribute of Valence.

“Parting is such sweet sorrow.” Taste metaphors provide a rich vocabulary for describing emotional experience, potentially serving as an adaptive mechanism for conveying abstract emotional concepts using concrete verbal references to our shared experience. We theorized that the popularity of these expressions results from the close association with hedonic valence shared by these two domains of experience. To explore the possibility that this affective quality underlies the semantic similarity of these domains, we used a behavioral “odd-one-out” task in an online sample of 1059 participants in order to examine the semantic similarity of concepts related to emotion, taste, and color, another rich source of sensory metaphors. We found that the semantic similarity of emotion and taste concepts was greater than that of emotion and color concepts. Importantly, the similarity of taste and emotion concepts was strongly related to their similarity in hedonic valence, a relationship which was also significantly greater than that present between color and emotion. These results suggest that the common core of valence between taste and emotion concepts allows us to bridge the conceptual divide between our shared sensory environment and our internal emotional experience.

Reflections on Co-production, Lived Experience and the Shared Learning Environment within the Development and Early Delivery of a Recovery College.

Objective: This study sought to explore and value the experiences of the service users, staff, carers and volunteers who were involved in the development and early establishment of a recovery college in a large mental health Trust in the United Kingdom.
 Research Design and Methods: This qualitative study used Interpretative Phenomenological Analysis (IPA) to explore the experiences of 25 participants who were involved in the design, development and early delivery phases of the recovery college. Data was collected using face-to-face semi-structured interviews.
 Results: The findings discuss a number of key features relating to participants’ experiences of the development of the recovery college, with the central themes being: 1) co-production; 2) lived experience; and 3) the shared learning environment.
 Conclusions: Key recommendations for those seeking to develop their own recovery college include: i) co-production is essential, but there are both philosophical and practical considerations; ii) lived experience is valuable, but it needs to be valued and supported within both the recovery college and the host organisation; and iii) the shared learning environment and educational approach of the college is vital and needs equity of opportunity between the service users, staff, carers and volunteers involved.

Sky-high concerns: examining the influence of drones on destination experience

ABSTRACT Drones are recognized as one of the technological advances that drive tourism development. Whereas prior research has provided initial insights into drone usage in the tourism industry, little attention has been paid to the influence of drone usage on non-users at a tourism destination. It is worth noting that although a small group of drone enthusiasts would fly drones to record their travel activities, most tourists at a destination are non-users of drones. As the tourism destination is a shared environment, understanding the non-users’ reactions would shed light on the role of drones in shaping the destination experience. The current study takes the perspective of the tourist who observes drone usage at a tourism destination to examine how the use of drones affects the non-user’s destination experience, drawing on the dark side of technology. Based on data collected from 255 respondents, we found that privacy concern and safety risk each have a positive influence on drone irritation, which in turn, negatively affects the tourist’s intention to recommend the destination. This study advances research on drones in tourism by generating new insights into the impact of drone usage on tourists’ experience at tourism destinations.

Rethinking haute couture: Julien Fournié in the virtual worlds of the metaverse

This article deals with the concept and practice of haute couture, of the designing and making of high-quality fashion clothes, and haute couture's contemporary engagement with the virtual worlds of the ‘metaverse’, a shared virtual environment that features online gaming and augmented reality. The article is an encounter with these virtual worlds, particularly as they are manifested in the haute couture of the French haute couturier Julian Fournié. To understand Fournié's haute couture, and thus to build a foundation for an interpretation of his most important fashion ideas, it is argued that researchers need to explore Fournié's engagement with virtual worlds and augmented reality from the perspective of German philosopher Martin Heidegger's phenomenological explanation of thinking and rethinking, and then at how Fournié develops and revises the meaning of haute couture.

MAPF-LNS2: Fast Repairing for Multi-Agent Path Finding via Large Neighborhood Search

Multi-Agent Path Finding (MAPF) is the problem of planning collision-free paths for multiple agents in a shared environment. In this paper, we propose a novel algorithm MAPF-LNS2 based on large neighborhood search for solving MAPF efficiently. Starting from a set of paths that contain collisions, MAPF-LNS2 repeatedly selects a subset of colliding agents and replans their paths to reduce the number of collisions until the paths become collision-free. We compare MAPF-LNS2 against a variety of state-of-the-art MAPF algorithms, including Prioritized Planning with random restarts, EECBS, and PPS, and show that MAPF-LNS2 runs significantly faster than them while still providing near-optimal solutions in most cases. MAPF-LNS2 solves 80% of the random-scenario instances with the largest number of agents from the MAPF benchmark suite with a runtime limit of just 5 minutes, which, to our knowledge, has not been achieved by any existing algorithms.

A Separate Reality: An Update on Place Illusion and Plausibility in Virtual Reality

We review the concept of presence in virtual reality, normally thought of as the sense of “being there” in the virtual world. We argued in a 2009 paper that presence consists of two orthogonal illusions that we refer to as Place Illusion (PI, the illusion of being in the place depicted by the VR) and Plausibility (Psi, the illusion that the virtual situations and events are really happening). Both are with the proviso that the participant in the virtual reality knows for sure that these are illusions. Presence (PI and Psi) together with the illusion of ownership over the virtual body that self-represents the participant, are the three key illusions of virtual reality. Copresence, togetherness with others in the virtual world, can be a consequence in the context of interaction between remotely located participants in the same shared virtual environments, or between participants and virtual humans. We then review several different methods of measuring presence: questionnaires, physiological and behavioural measures, breaks in presence, and a psychophysics method based on transitions between different system configurations. Presence is not the only way to assess the responses of people to virtual reality experiences, and we present methods that rely solely on participant preferences, including the use of sentiment analysis that allows participants to express their experience in their own words rather than be required to adopt the terminology and concepts of researchers. We discuss several open questions and controversies that exist in this field, providing an update to the 2009 paper, in particular with respect to models of Plausibility. We argue that Plausibility is the most interesting and complex illusion to understand and is worthy of significant more research. Regarding measurement we conclude that the ideal method would be a combination of a psychophysical method and qualitative methods including sentiment analysis.

Shared environment and colorectal cancer: A Nordic pedigree registry-based cohort study.

Risk of colorectal cancer (CRC) increases in relatives of patients with CRC. The extent to which this is attributable to genetic predisposition or shared environment is unclear. We explored this question using nationwide cohorts from Denmark, Finland and Sweden. From 1977 to 2013, we identified 359 879 individuals with a CRC diagnosis and 2 258 870 of their relatives who we followed for CRC incidence. We calculated standardized incidence ratios (SIR) and 95% confidence intervals (CI) for CRC in individuals with an affected relative. We used nationwide household and pedigree data along with national SIR estimates to calculate risk ratios (RR) for the contribution of shared household environment, childhood environment and genetic relationship to CRC risk in those with an affected relative. SIR of CRC was increased for individuals with an affected relative, across all countries and ages. For those with an affected parent, the SIR was 1.65 (95% CI: 1.61‐1.69), 1.98 (95% CI: 1.87‐2.09), for those with an affected sibling and 2.14 (95% CI: 1.84‐2.49) for those with an affected halfsibling. In those <65 years old, shared childhood (RR: 1.41, 95% CI: 1.26‐1.57) and household (RR: 2.08, 95% CI: 1.25‐3.46) environments were significantly greater contributors to familial risk of CRC than genetics (RR: 0.88, 95% CI: 0.53‐1.46). This large‐scale Nordic population‐based study of excess risk of CRC among relatives of those with CRC addresses the difficult disentangling of shared environment from genetic predisposition in the heritability of CRC. We found shared environment to be the most important contributor to CRC risk.

Simulation: An active learning pedagogy for an undergraduate nursing leadership course.

Interpretive pedagogy with simulation encourages students to consider multiple perspectives contextually leading students to think deeper in a shared learning environment. Clinical sites were lacking in a senior nursing leadership and management course and necessitated the adaptation of traditional clinical teaching methodologies. Low-fidelity simulation was used as an active learning strategy to fulfill clinical hours. Comparing student groups' pretest mean scores were not significant (p = .610; 95% confidence interval [CI][-0.95, 0.12]). Comparatively, the student groups' posttest scores ranging between 87% and 90%, respectively, were also not statistical significance (p = .136, 95% CI [-0.95, 0.12]). Students were positive about their experience. They appreciated the opportunity to practice what they learned in the classroom in a safe environment. As a result, simulation in a senior nursing leadership course can be successfully used as an alternative to traditional clinical experiences and fulfill clinical hour requirements.

One health the future of rural health?

One health the future of rural health?

TripletCough: Cougher Identification and Verification From Contact-Free Smartphone-Based Audio Recordings Using Metric Learning.

Cough, a symptom associated with many prevalent respiratory diseases, can serve as a potential biomarker for diagnosis and disease progression. Consequently, the development of cough monitoring systems and, in particular, automatic cough detection algorithms have been studied since the early 2000s. Recently, there has been an increased focus on the efficiency of such algorithms, as implementation on consumer-centric devices such as smartphones would provide a scalable and affordable solution for monitoring cough with contact-free sensors. Current algorithms, however, are incapable of discerning between coughs of different individuals and, thus, cannot function reliably in situations where potentially multiple individuals have to be monitored in shared environments. Therefore, we propose a weakly supervised metric learning approach for cougher recognition based on smartphone audio recordings of coughs. Our approach involves a triplet network architecture, which employs convolutional neural networks (CNNs). The CNNs of the triplet network learn an embedding function, which maps Mel spectrograms of cough recordings to an embedding space where they are more easily distinguishable. Using audio recordings of nocturnal coughs from asthmatic patients captured with a smartphone, our approach achieved a mean accuracyof 88 % ( ± 10 % SD) on two-way identification tests with 12 enrollment samples and accuracy of 80 % and an equal error rate (EER) of 20 % on verification tests. Furthermore, our approach outperformed human raters with regard to verification tests on average by 8% in accuracy, 4% in false acceptance rate (FAR), and 12% in false rejection rate (FRR). Our code and models are publicly available.

The relationships between IBS and perceptions of physical and mental health—a Norwegian twin study

Background and aimsPoor quality of life is a main complaint among individuals with irritable bowel syndrome (IBS). Self-rated health (SRH) is a powerful predictor of clinical outcomes, and also reflects psychological and social aspects of life and an overall sense of well-being. This population-based twin study evaluates how IBS affects ratings of physical and mental health, and influences perceptions of hindrance of daily activity by physical or mental health. Further, we examine how IBS is related to these SRH measures.MethodsThe sample included 5288 Norwegian twins aged 40–80, of whom 575 (10.9%) suffer from IBS. Hierarchical regressions were used to estimate the impact of IBS on perceptions of health, before and after accounting for other chronic physical and mental health conditions. Two dimensions of SRH, physical and mental, and two aspects of functional limitations, the extent to which physical or mental health interferes with daily activities, were included as outcomes in separate models. Co-twin control analyses were used to explore whether the relationships between IBS and the four measures of SRH are causal, or due to shared genetic or shared environment effects.ResultsIBS was an independent predictor of poor self-rated physical health (OR = 1.82 [1.41; 2.33]), the size of this effect was comparable to that predicted by chronic somatic conditions. However, in contrast to somatic diseases, IBS was associated with the perception that poorer ratings of mental health (OR = 1.45 [1.02; 2.06]), but not physical health (OR = 1.23 [0.96; 1.58]), interfered with daily activity. The co‐twin control analyses suggest that causal mechanisms best explain the relationships between IBS with self-rated physical health and with hindrance of daily activities. In contrast, the relationship between IBS and self-rated mental health was consistent with shared genetic effects.ConclusionIBS is predictive of poor self-rated physical health. The relationship between IBS and self-rated mental health is best explained by shared genetic effects which might partially explain why mental health interferes with daily activity to a larger degree among those with IBS.

Young children’s learning about lighting and turn-off behaviour in preschool environments

In the promotion of energy efficiency in educational facilities, preschool children play an important role since simple energy-saving behaviour can be developed in early childhood. This study aimed to investigate the effects of behaviour interventions, with a particular focus on preschool children’s turn-off behaviour in shared environments. The intervention tools i.e. digital game, paper-board game and visual prompt were developed for 3–6 years old children. The study took place in a preschool in which energy-efficient lighting and combined automatic and manual controls were installed. The data were collected by means of participatory observations of the children’s light-off behaviour (N = 42), measurements of lighting use using data loggers, and interviews with the teachers (N = 11). The overall results point to associations between the interventions and the behaviour specifically, the visual prompts were found to have a significantly positive effect. No significant effect of the games on the behaviour could be identified however, the games were found to have the potential to promote learning about lighting and lighting use. Effects of the interventions on the long-term behaviour and energy saving remain unclear. Design improvements of the interventions are thus, needed considering other related factors (e.g. social norms, habits) together with lighting quality for young children and activities in preschool environments.

I can't get no Sleep: The Role of Leaders' Health and Leadership Behavior on Employees' Sleep Quality

ABSTRACT A leader’s role is often associated with increased psychosocial demands, which could lead to rumination during nonwork time. Leader rumination might trigger a cascade of mechanisms causing employee rumination and eventually persistent employee sleep problems. In a three-wave study, we examined whether leader rumination predicts changes in employee sleep quality linked by employee rumination. As a possible serial mechanism underlying the trickle-down effect of leader rumination on employee rumination, we investigated leaders’ general health and resource-oriented leadership behaviour. Based on self-report data from 94 leaders and their 332 employees, we found support for a multilevel mediation model in which leader rumination negatively affected employee sleep quality via employee rumination while controlling for baseline measures and a shared work environment (workload). Finally, leader rumination was negatively related to employee sleep quality via the serial mediation of leader health, resource-oriented leadership, and rumination perceived by the team members. The results demonstrate the importance of leader rumination for employees’ sleep quality nearly 2 years later and provide knowledge that can be used to expand and optimize interventions.

Increased genetic contribution to wellbeing during the COVID-19 pandemic.

Physical and mental health are determined by an interplay between nature, for example genetics, and nurture, which encompasses experiences and exposures that can be short or long-lasting. The COVID-19 pandemic represents a unique situation in which whole communities were suddenly and simultaneously exposed to both the virus and the societal changes required to combat the virus. We studied 27,537 population-based biobank participants for whom we have genetic data and extensive longitudinal data collected via 19 questionnaires over 10 months, starting in March 2020. This allowed us to explore the interaction between genetics and the impact of the COVID-19 pandemic on individuals' wellbeing over time. We observe that genetics affected many aspects of wellbeing, but also that its impact on several phenotypes changed over time. Over the course of the pandemic, we observed that the genetic predisposition to life satisfaction had an increasing influence on perceived quality of life. We also estimated heritability and the proportion of variance explained by shared environment using variance components methods based on pedigree information and household composition. The results suggest that people's genetic constitution manifested more prominently over time, potentially due to social isolation driven by strict COVID-19 containment measures. Overall, our findings demonstrate that the relative contribution of genetic variation to complex phenotypes is dynamic rather than static.

Resource Profiling and Performance Modeling for Distributed Scientific Computing Environments

Scientific applications often require substantial amount of computing resources for running challenging jobs potentially consisting of many tasks from hundreds of thousands to even millions. As a result, many institutions collaborate to solve large-scale problems by creating virtual organizations (VOs), and integrate hundreds of thousands of geographically distributed heterogeneous computing resources. Over the past decade, VOs have been proven to be a powerful research testbed for accessing massive amount of computing resources shared by several organizations at almost no cost. However, VOs often suffer from providing exact dynamic resource information due to their scale and autonomous resource management policies. Furthermore, shared resources are inconsistent, making it difficult to accurately forecast resource capacity. An effective VO’s resource profiling and modeling system can address these problems by forecasting resource characteristics and availability. This paper presents effective resource profiling and performance prediction models including Adaptive Filter-based Online Linear Regression (AFOLR) and Adaptive Filter-based Moving Average (AFMV) based on the linear difference equation combining past predicted values and recent profiled information, which aim to support large-scale applications in distributed scientific computing environments. We performed quantitative analysis and conducted microbenchmark experiments on a real multinational shared computing platform. Our evaluation results demonstrate that the proposed prediction schemes outperform well-known common approaches in terms of accuracy, and actually can help users in a shared resource environment to run their large-scale applications by effectively forecasting various computing resource capacity and performance.

Gut microbial similarity in twins is driven by shared environment and aging.

SummaryBackgroundHuman gut microbiome composition is influenced by genetics, diet and environmental factors. We investigated the microbial composition in several gastrointestinal (GI) compartments to evaluate the impact of genetics, delivery mode, diet, household sharing and aging on microbial similarity in monozygotic and dizygotic twins.MethodsFecal, biopsy and saliva samples were obtained from total 108 twins. DNA and/or RNA was extracted and the region V1-V2 of the 16S rRNA gene was amplified and sequenced. Bray-Curtis similarity was used for further microbiome comparisons, Mann-Whitney test was applied to evaluate the significant differences between groups and Spearman test was applied to reveal potential correlations between data.FindingsThe global bacterial profiles were grouped into two clusters separating the upper and lower GI. The upper GI microbiome composition was strictly dependent on the Helicobacter pylori status. With a positivity rate of 55%, H. pylori completely colonized the stomach and separated infected twins from non-infected twins irrespective of zygosity status. Lower GI microbiome similarity between the twins was defined mainly by household-sharing and aging; whereas delivery mode and host genetics had no influence. There was a progredient decrease in the bacterial similarity with aging. Shared vs. non-shared phylotypes analysis showed that in both siblings the shared phylotypes progressively diminished with aging, while the non-shared phylotypes increased.InterpretationOur findings strongly highlight the aging and shared household as they key determinants in gut microbial similarity and drift in twins irrespective of their zygotic state.FundingThis work was supported by the grant of the Research Council of Lithuania (Project no. APP-2/2016) and also partially supported by the funds of European Commission through the “European funds for regional development” (EFRE) as well as by the regional Ministry of Economy, Science and Digitalization as part of the “LiLife” Project as part of the “Autonomy in old Age” research group (Project ID: ZS/2018/11/95324).