Multidimensional Environments Research Articles

Associations among preschool classroom chaos, work climates, and child outcomes

This study examined the associations between two unique features of classroom chaos (chaotic structure and chaotic atmosphere) in preschool settings and teacher-perceived child functioning, and the roles of teacher- and director-perceived work climates. Multilevel modeling was used to analyze the nested data of 329 children within 53 classrooms. The study found distinct roles of chaotic structure and atmosphere. Moreover, the congruence/incongruence between teacher- and director-perceived work climates significantly moderated the associations between classroom chaos and teacher-perceived child outcomes. The findings highlight the importance of considering multidimensional preschool environments and promoting positive work climates perceived by both teachers and directors.

Psychological Stress Reduction and Their Impact on Workplace Productivity in Chinese Corporations

Objectives: The workplace is a complete living environment comprised of various supportive, constructive and nonsupportive, demotivating and negative components. In all these multi-dimensional working environments, the employees are the main components that endeavor everything. In such a deliberate matter, their well- being is highly crucial and any negative factor like stress, anxiety and burnout can deteriorate the workplace's effective working cycle. Methods: This study has examined the same narrated dilemma with the external supportive role of psychological in increasing the workplace productivity of the Chinese corporations. Results: The study adopted a quantitative strategy and used a purposive sampling technique under the nonprobability sampling to effectively assess the employees for data collection. The survey approach was utilized, and 312 responses were finalized as valid for data analysis. Conclusion: The structural equational modelling revealed significant influences of the job burnout and situational anxiety in decreasing the workplace productivity of the Chinese corporations and in this myriad, the constructive voice behavior is to some extent supportive for the employees' psychological components and the workplace productivity, however, the moderation of mindfulness hasn't provided no additional support to the constructive voice and productivity.

A general exposome factor explains individual differences in functional brain network topography and cognition in youth

Childhood environments are critical in shaping cognitive neurodevelopment. With the increasing availability of large-scale neuroimaging datasets with deep phenotyping of childhood environments, we can now build upon prior studies that have considered relationships between one or a handful of environmental and neuroimaging features at a time. Here, we characterize the combined effects of hundreds of inter-connected and co-occurring features of a child’s environment (“exposome”) and investigate associations with each child’s unique, multidimensional pattern of functional brain network organization (“functional topography”) and cognition. We apply data-driven computational models to measure the exposome and define personalized functional brain networks in pre-registered analyses. Across matched discovery (n=5139, 48.5% female) and replication (n=5137, 47.1% female) samples from the Adolescent Brain Cognitive Development study, the exposome was associated with current (ages 9–10) and future (ages 11–12) cognition. Changes in the exposome were also associated with changes in cognition after accounting for baseline scores. Cross-validated ridge regressions revealed that the exposome is reflected in functional topography and can predict performance across cognitive domains. Importantly, a single measure capturing a child’s exposome could more accurately and parsimoniously predict cognition than a wealth of personalized neuroimaging data, highlighting the importance of children’s complex, multidimensional environments in cognitive neurodevelopment.

Improved Double Deep Q-Network Algorithm Applied to Multi-Dimensional Environment Path Planning of Hexapod Robots.

Detecting transportation pipeline leakage points within chemical plants is difficult due to complex pathways, multi-dimensional survey points, and highly dynamic scenarios. However, hexapod robots' maneuverability and adaptability make it an ideal candidate for conducting surveys across different planes. The path-planning problem of hexapod robots in multi-dimensional environments is a significant challenge, especially when identifying suitable transition points and planning shorter paths to reach survey points while traversing multi-level environments. This study proposes a Particle Swarm Optimization (PSO)-guided Double Deep Q-Network (DDQN) approach, namely, the PSO-guided DDQN (PG-DDQN) algorithm, for solving this problem. The proposed algorithm incorporates the PSO algorithm to supplant the traditional random selection strategy, and the data obtained from this guided approach are subsequently employed to train the DDQN neural network. The multi-dimensional random environment is abstracted into localized maps comprising current and next level planes. Comparative experiments were performed with PG-DDQN, standard DQN, and standard DDQN to evaluate the algorithm's performance by using multiple randomly generated localized maps. After testing each iteration, each algorithm obtained the total reward values and completion times. The results demonstrate that PG-DDQN exhibited faster convergence under an equivalent iteration count. Compared with standard DQN and standard DDQN, reductions in path-planning time of at least 33.94% and 42.60%, respectively, were observed, significantly improving the robot's mobility. Finally, the PG-DDQN algorithm was integrated with sensors onto a hexapod robot, and validation was performed through Gazebo simulations and Experiment. The results show that controlling hexapod robots by applying PG-DDQN provides valuable insights for path planning to reach transportation pipeline leakage points within chemical plants.

What to Blame? Self-Serving Attribution Bias with Multi-Dimensional Uncertainty

Abstract People often receive feedback influenced by external factors, yet little is known about how this affects self-serving biases. Our theoretical model explores how multi-dimensional uncertainty allows additional degrees of freedom for self-serving bias. In our primary experiment, feedback combining an individual’s ability and a teammate’s ability leads to biased belief updating. However, in a follow-up experiment with a random fundamental replacing the teammate, unbiased updating occurs. A validation experiment shows that belief distortion is greater when outcomes originate from human actions. Overall, our experiments highlight how multi-dimensional environments can enable self-serving biases.

Hybrid actor-critic algorithm for quantum reinforcement learning at CERN beam lines

Free energy-based reinforcement learning (FERL) with clamped quantum Boltzmann machines (QBM) was shown to significantly improve the learning efficiency compared to classical Q-learning with the restriction, however, to discrete state-action space environments. In this paper, the FERL approach is extended to multi-dimensional continuous state-action space environments to open the doors for a broader range of real-world applications. First, free energy-based Q-learning is studied for discrete action spaces, but continuous state spaces and the impact of experience replay on sample efficiency is assessed. In a second step, a hybrid actor-critic (A-C) scheme for continuous state-action spaces is developed based on the deep deterministic policy gradient algorithm combining a classical actor network with a QBM-based critic. The results obtained with quantum annealing (QA), both simulated and with D-Wave QA hardware, are discussed, and the performance is compared to classical reinforcement learning methods. The environments used throughout represent existing particle accelerator beam lines at the European Organisation for Nuclear Research. Among others, the hybrid A-C agent is evaluated on the actual electron beam line of the Advanced Wakefield Experiment (AWAKE).

Scots pine - panmixia and the elusive signal of genetic adaptation.

Scots pine is the foundation species of diverse forested ecosystems across Eurasia and displays remarkable ecological breadth, occurring in environments ranging from temperate rainforests to arid tundra margins. Such expansive distributions can be favored by various demographic and adaptive processes and the interactions between them. To understand the impact of neutral and selective forces on genetic structure in Scots pine, we conducted range-wide population genetic analyses on 2321 trees from 202 populations using genotyping-by-sequencing, reconstructed the recent demography of the species and examined signals of genetic adaptation. We found a high and uniform genetic diversity across the entire range (global FST 0.048), no increased genetic load in expanding populations and minor impact of the last glacial maximum on historical population sizes. Genetic-environmental associations identified only a handful of single-nucleotide polymorphisms significantly linked to environmental gradients. The results suggest that extensive gene flow is predominantly responsible for the observed genetic patterns in Scots pine. The apparent missing signal of genetic adaptation is likely attributed to the intricate genetic architecture controlling adaptation to multi-dimensional environments. The panmixia metapopulation of Scots pine offers a good study system for further exploration into how genetic adaptation and plasticity evolve under gene flow and changing environment.

Intelligent Monitoring of Data Quality Based on Multiple Data Structures

In the current context of big data, data quality management has become a hot topic in data science research. This article focused on the intelligent monitoring needs of complex data structures and explored data quality evaluation indicators and monitoring methods for complex environments. Key technologies such as data fusion, cleaning, and quality evaluation were focused on research, and a data quality monitoring system for multi-dimensional data environments was constructed to verify its application effectiveness in multi-source data environments, as well as specific measures to improve data quality. On this basis, a data quality evaluation model based on data mining was utilized, and a real-time monitoring system was established for application research. When the number of consistency issues was 30, the response time was 300ms, and the success rate of processing was 95%. The lowest processing success rate was 88%, and the highest was 100%. The overall processing success rate of the system was very good. The research results of this article provided theoretical and methodological support for enterprises to effectively carry out data quality management, which has important theoretical significance and application value.

Social-spatial network structures among young urban and suburban persons who inject drugs in a large metropolitan area

BackgroundRecent studies underscore the significance of adopting a syndemics approach to study opioid misuse, overdose, hepatitis C (HCV) and HIV infections, within the broader context of social and environmental contexts in already marginalized communities. Social interactions and spatial contexts are crucial structural factors that remain relatively underexplored. This study examines the intersections of social interactions and spatial contexts around injection drug use. More specifically, we investigate the experiences of different residential groups among young (aged 18-30) people who inject drugs (PWID) regarding their social interactions, travel behaviors, and locations connected to their risk behaviors. By doing so, we aim to achieve a more comprehensive understanding of the multidimensional risk environment, thereby facilitating the development of informed policies. MethodsWe collected and examined data regarding young PWID's egocentric injection network and geographic activity spaces (i.e., where they reside, inject drugs, purchase drugs, and meet sex partners). Participants were stratified based on the location of all place(s) of residence in the past year i.e., urban, suburban, and transient (both urban and suburban) to i) elucidate geospatial concentration of risk activities within multidimensional risk environments based on kernel density estimates; and ii) examine spatialized social networks for each residential group. ResultsParticipants were mostly non-Hispanic white (59%); 42% were urban residents, 28% suburban, and 30% transient. We identified a spatial area with concentrated risky activities for each residential group on the West side of Chicago in Illinois where a large outdoor drug market area is located. The urban group (80%) reported a smaller concentrated area (14 census tracts) compared to the transient (93%) and suburban (91%) with 30 and 51 tracts, respectively. Compared to other areas in Chicago, the identified area had significantly higher neighborhood disadvantages. Significant differences were observed in social network structures and travel behaviors: suburban participants had the most homogenous network in terms of age and residence, transient participants had the largest network (degree) and more non-redundant connections, while the urban group had the shortest travel distance for all types of risk activities. ConclusionDistinct residential groups exhibit varying patterns of network interaction, travel behaviors, and geographical contexts related to their risk behaviors. Nonetheless, these groups share common concentrated risk activity spaces in a large outdoor urban drug market area, underscoring the significance of accounting for risk spaces and social networks in addressing syndemics within PWID populations.

Enhancing teaching and learning in STEM Labs: The development of an android-based virtual reality platform

Integrating information technology as an ancillary tool in education is indispensable, especially in an era witnessing a remarkable transition in teaching and learning. Globally, Higher Education Institutions (HEIs) are applying digital e-learning tools to complement teaching aids for educational purposes. The paradigm shift to the fourth industrial revolution is a significant problem educators face and requires a rapid response through STEM implementation. Practical concepts are presented visually to learners using digital media devices and computer-based interactive platforms, including Virtual Reality (VR), Augmented Reality (AR), Extended Reality (XR), and Mixed Reality (MR). The paper presents the development process and final output of a mobile VR application relevant to Science, Technology, Engineering, and Mathematics (STEM) labs, fit for purpose. Recently, HEIs have been utilizing VR technological platforms to communicate abstract ideas through this seamless approach, improving the learning process. A VR platform for education engineering students in induction motor technology was developed. Using VR, students interact in multiuser rooms within 3-Dimensional (3D) and multidimensional virtual environments. As a recommendation, the endless possibilities of VR may be explored by educators, as VR simulations enable the comprehension of imagined concepts.

Multidimensional specialization and generalization are pervasive in soil prokaryotes.

Habitat specialization underpins biological processes from species distributions to speciation. However, organisms are often described as specialists or generalists based on a single niche axis, despite facing complex, multidimensional environments. Here, we analysed 236 environmental soil microbiomes across the United States and demonstrate that 90% of >1,200 prokaryotes followed one of two trajectories: specialization on all niche axes (multidimensional specialization) or generalization on all axes (multidimensional generalization). We then documented that this pervasive multidimensional specialization/generalization had many ecological and evolutionary consequences. First, multidimensional specialization and generalization are highly conserved with very few transitions between these two trajectories. Second, multidimensional generalists dominated communities because they were 73 times more abundant than specialists. Lastly, multidimensional specialists played important roles in community structure with ~220% more connections in microbiome networks. These results indicate that multidimensional generalization and specialization are evolutionarily stable with multidimensional generalists supporting larger populations and multidimensional specialists playing important roles within communities, probably stemming from their overrepresentation among pollutant detoxifiers and nutrient cyclers. Taken together, we demonstrate that the vast majority of soil prokaryotes are restricted to one of two multidimensional niche trajectories, multidimensional specialization or multidimensional generalization, which then has far-reaching consequences for evolutionary transitions, microbial dominance and community roles.

Dimension-wise Sequential Update for Learning a Multidimensional Environment in Humans.

When confronted with multidimensional environment problems, humans may need to jointly update multiple state-action-outcome associations across various dimensions. Computational modeling of human behavior and neural activities suggests that such updates are implemented based upon Bayesian update principle. However, it is unclear whether humans perform these updates individually or sequentially. If the update occurs sequentially, the order in which the associations are updated matters and can influence the updated results. To address this question, we tested a few computational models with different update orders using both human behavior and EEG data. Our results indicated that a model undertaking dimension-wise sequential updates was the best fit to human behavior. In this model, ordering the dimensions was decided using entropy, which indexed the uncertainty of associations. Simultaneously collected EEG data revealed evoked potentials that were correlated to the proposed timing of this model. These findings provide new insights into the temporal processes underlying Bayesian update in multidimensional environments.

The effect of sensory experience on sport development: baseball simulation in Korea

ABSTRACT Rationale A baseball simulation provides its participants a sporting environment in which programmed game mechanics mediate sensory stimuli. The current study aims to discover how simulation users’ interests in baseball, athletic identity, and intentions to participate in baseball differ by degree of stimuli. The results would reveal the dynamics of how baseball simulation users’ sensory experiences relate to their baseball development. Design Data collection, taken at two Korean baseball simulation franchises, involved 136 simulation participants. On a self-administered survey, participants answered questions about their degree of perceiving visual, aural, and tactile stimuli as well as their baseball interest, athletic identity, and intentions to participate in baseball. The collected data were analyzed in MANOVA. Findings The simulation users’ interests in baseball differed according to the degree of visual and aural stimuli. Regarding the degree of tactile stimuli, the simulation users differed in the degree to which they identified as an athlete and intended to participate in baseball. Playing a crucial role in their baseball development was their tactile sense. Practical implications The study suggests managerial implications that sport practitioners implement toward developing a new participatory market. Research contribution The study reveals how sport simulation users interact with the simulation's multi-dimensional environments.

THE DYNAMIC RELATIONSHIP BETWEEN MULTIDIMENTIONAL ENVIRONMENT AND PHYSICAL ACTIVITY PARTICIPATION

Abstract Objectives Physical activity participation is a preventive factor in improving physical and cognitive functions. Both physical and social environments are essential in evaluating older adults’ opportunities to participate in physical activities. This study aims at assessing the multidimensional environment in physical activity participation and examining how the change in the multidimensional environments could affect their participation in physical activities. Methods This paper combined the nationally representative data, the China Longitudinal Aging Social Survey data 2014–2018, and the county-level administrative data extracted from various statistical yearbooks. It used the latent variable cross-lagged panel model to capture the dynamic relationship between environment and physical activities. Additionally, the dynamic analytical model considers a multidimensional environment, including indoor-, outdoor-, human-, social-environment, etc., by adding the latent variables. Results The descriptive statistics show that older adults who are in a better environment (.147 in the indoor environment, p < 0.001; .389 in the outdoor environment, p < 0.01; .571 in family support, p < 0.05; .346 in childhood activity experience, p < 0.001) are more likely to frequently participate in physical activities (three times or more per week). The results of the latent cross-lagged panel models indicate that every one percent increase in the multidimensional environmental index is expected to cause a 4.1% increase in the likelihood of participating in physical activities among Chinese older adults. Discussion: In addition to the continuous efforts to improve the physical environment, policymakers and researchers should pay more attention to the social environment to encourage more older adults to participate in physical activities.

A Hierarchical Bayesian Model for Inferring and Decision Making in Multi-Dimensional Volatile Binary Environments

The ability to track the changes of the surrounding environment is critical for humans and animals to adapt their behaviors. In high-dimensional environments, the interactions between each dimension need to be estimated for better perception and decision making, for example in volatile or social cognition tasks. We develop a hierarchical Bayesian model for inferring and decision making in multi-dimensional volatile environments. The hierarchical Bayesian model is composed of a hierarchical perceptual model and a response model. Using the variational Bayes method, we derived closed-form update rules. These update rules also constitute a complete predictive coding scheme. To validate the effectiveness of the model in multi-dimensional volatile environments, we defined a probabilistic gambling task modified from a two-armed bandit. Simulation results demonstrated that an agent endowed with the proposed hierarchical Bayesian model is able to infer and to update its internal belief on the tendency and volatility of the sensory inputs. Based on the internal belief of the sensory inputs, the agent yielded near-optimal behavior following its response model. Our results pointed this model a viable framework to explain the temporal dynamics of human decision behavior in complex and high dimensional environments.

Optimization Approaches of Multi-Dimensional Environments in Rural Space Reproduction Driven by Tourism

Rural tourism is an important driving force for the transformation of rural society in the process of urbanization. However, besides promoting rural economy, it also interrupts the development of the rural living, human, manage and economic multi-dimensional environments. Space reconstruction in rural settlements is an important means to optimize multi-dimensional environments and revitalize rural tourism. Focusing on two types of rural settlements, namely the “relocation village” and the “sightseeing and settlement symbiosis village”, this study has revealed the affecting mechanism of space reconstruction in rural tourist locations on the local multi-dimensional environment by establishing a multi-dimensional environment evaluation system through an analytic, hierarchical process. Subsequently, based on the theoretical perspective of the reproduction of the space and the paradigm of the three-fold model, a comprehensive optimization path of rural multi-dimensional environments has been proposed. The results show that in the space reconstruction process driven by tourism: (1) the multi-dimensional environments of the “sightseeing and settlement symbiosis village” generally develop better than the “relocation village”; (2) the ecological environment is the direct benefit while the management environment and economic environment are the bottlenecks; (3) the “sightseeing and settlement symbiosis village” is more appealing to tourists who are interested in rural tourism since it keeps more rustic characteristics than the “relocation village”; (4) in order to optimize the multi-dimensional environments, “relocation village” should pay more attention to the space needs of residents, improve space utilization rates, and increase the residents’ sense of belonging; (5) “sightseeing and settlement symbiosis village” needs to resolve the contradiction between the tourism and living demands, improve the reproduction process driven by diversified entities, and reconstruct the neighborhood network under rural tourism.

Multidimensional Environmental Factors and Sleep Health for Aging Adults: A Focused Narrative Review.

The timing, amount, and quality of sleep are critical for an individual's health and quality of life. This paper provides a focused narrative review of the existing literature around multidimensional environments and sleep health for aging adults. Five electronic databases, Scopus, Web of Science, PubMed/Medline; EBSCOhost, PsycINFO (ProQuest), and Google Scholar yielded 54,502 total records. After removing duplicates, non-peer reviewed academic articles, and nonrelevant articles, 70 were included for review. We were able to categorize environmental factors into housing security, home environment, and neighborhood environment, and, within each environmental category, specific elements/aspects are discussed. This paper provides a comprehensive map connecting identified levels of influence (individual, home/house, and neighborhood-level) in which subfactors are listed under each level of influence/category with the related literature list. Our review highlights that multidimensional environmental factors can affect aging adults' sleep health and eventually their physical, mental, and cognitive health and that sleep disparities exist in racial minorities in socioeconomically disadvantaged communities in which cumulative environmental stressors coexist. Based on this focused narrative review on the multidimensional sleep environments for aging adults, knowledge gaps are identified, and future research directions are suggested.

A review: Developing an ecological model approach to co-worker incivility experiences of new graduate nurses.

To explore how an ecological approach be used to explore relationships among workplace empowerment, authentic leadership, trust in management, areas of work life and co-worker incivility experiences of new graduate nurses. Key concepts related to new graduate nurses' incivility experience informed the research question building on the findings of our first author's integrative review. Second, relevant theories and concepts were identified by conducting a literature review. Third, the themes build on prior theories and factors to propose a hypothetical model. (2016-2019) CINAHL, OVID, PSYCINFO, PUBMED, EBSCO, ERIC, SCOPUS, Cochrane Library; PROQUEST and Google Scholar. (a) Constructs identified in an IR (Blackstock et al., 2018) guided a literature review on predictive variables linked to new graduate nurse's co-worker incivility experiences; (b) an ecological approach was explored; and (c) we demonstrate how multidimensional organizational factors related to incivility experiences of new graduate nurses can be situated in an ecological model. Structural and organizational factors, and nurse leaders influencing new graduate nurses' experiences are situated in an ecological model. Placing new graduate nurses' co-worker incivility experiences in the microsystem and close to the mesosystem (nurse supervisor) and exosystem (workplace empowerment) of our ecological model provides new insights into their incivility experiences and informs future research. The ecological approach and operational definition of incivility help to clarify incivility behaviours as not merely individual behaviours observed by others needing corrective cognitive behaviours, nor support in a graduate transition program, but rather a symptom of work environment factors contributing to multidimensional work environments of new graduate nurses' and influence incivility behaviours. New graduate nurse co-worker incivility research could measure change across time and across system domains informed by this ecological approach and can shape new ways of thinking about how to prevent and mitigate incivility.

Coastal Scenery Quality: A Management Tool for Sandy Beaches

Beaches are multidimensional environments, and their management must include the ecological, sociocultural and economic aspects. The continuous occupation of this ecosystem combined with the scarcity of adequate management plans has reduced the quality of coastal sceneries. Therefore, strategies are needed to ensure the perpetuity of resources and delivery of ecosystem services. The objective of this study was to assess the coastal scenery quality at three sandy beaches of Rio de Janeiro, Brazil. A quali-quantitative approach was applied using measurable aspects, considering eight categories as accessibility, water quality, scenic quality, infrastructure, safety and environmental education, based on 67 indicators. The beaches commonly presented higher values for water quality, while environmental education had the lowest ranks, indicating that this category should be prioritised in management strategies. In addition to the low cost of this effective tool for beach management, it is quick to apply, easy to analyse and represents an advancement in important issues about the use of integrative indicators to evaluate coastal sceneries, providing a scientific base that can offer evidence about the main management priorities in areas where coastal tourism has a significant role.

Adaptive Camouflage Textiles with Thermochromic Colorant and Liquid Crystal for Multidimensional Combat Background, a Technical Approach for Advancement in Defence Protection

Adaptive camouflage textiles with color changing and blending into the combat background (CB) and surrounding environments have been a great challenge for the color scientist. Defense professional urgently needs adaptive camouflage textiles for personal protection in extreme weather conditions and multidimensional CB environments. A technical approach of adaptive camouflage textiles can be formulated by using a novel combination of thermochromic colorant and liquid crystal. Absorption of heat can rapidly accelerate the thermal response of thermochromic liquid crystal (TLC) by changing molecular structure with thermo-color-light (TCL) mechanism of absorption and reflection of light at different wavelength. TLC shows chameleon performance of color tone which changes the light reflection of surface color; thus, target objects can be artificially confused by the replacement of chromatic appearance in multidimensional CB environments. TLC can be applied as deceiving mechanism and surface modification of textile substances with combination of dyes/pigment. TLC modified camouflage textiles have possibility of diverse applications in different weather of combat zone for defense actions and different CB environments. A single formulated camouflage textiles may be suited with different CB environments under TLC mechanism. Chameleon type of color tone in cooling and heating conditions of thermochromic changes automatically in both reversible and irreversible way. Therefore, the technical colorant combination has been preached for suitability of adaptation with surrounding CB. TLC treated textiles can be experimented with spectroscopic, microscopic, and photographic illumination. The applications of adaptive camouflage textiles are not only limited to military textiles, but also the principle of technologies have versatile applications for clothing of personal protection including fashionable garments production.