Features Of Physical Environment Research Articles

Social participation challenges and facilitators among Chinese stroke survivors: a qualitative descriptive study

BackgroundA significant proportion of stroke survivors have participation restrictions. Attaining an in-depth understanding of participation challenges and facilitators is necessary to identify rehabilitation priorities. However, current evidence in the Chinese context is insufficient as cultural norms, expectations, and behaviors may differ across countries. This study aimed to explore experiences of social participation among Chinese stroke survivors and their perceived challenges and facilitators, particularly the cultural issues that impact their social participation.MethodsThis study used a qualitative descriptive approach. Individual face-to-face semi-structured interviews were conducted with 30 first-time or recurrent stroke survivors recruited from a rehabilitation unit and a community health centre in China. Content analysis was used to analyse the data. Reporting complies with the COREQ checklist.ResultsThree investigator-derived categories and 14 subcategories based on data-derived responses were identified. The categories included changes in social participation after stroke, challenges of social participation, and facilitators of social participation. While common factors such as physical limitations, environmental features, and social support emerged as influences on social participation, cultural values were also found to exert a significant impact on survivors’ participation behaviors. These values included family-oriented beliefs regarding responsibility towards their children, struggles with societal expectations, and perceptions of social participation being a burden on others.ConclusionsStroke survivors perceived varying degrees of changes in their social participation. Specifically, this study identifies the influence of prevalent cultural values on survivors’ participation behaviors, indicating that cultural beliefs and the associated effects on health outcomes should be taken into consideration when developing interventions to enhance social participation after stroke. Potential interventions to empower survivors could aim to improve their stroke-related knowledge, provide psychological encouragement, incorporate skills training to improve communication with family members, and organise peer support groups to augment social support networks.

Effects of Underwater Lighting Time on the Growth of Vallisneria spinulosa Yan and Its Water Restoration Process

Submerged macrophytes play a crucial role in the ecological restoration of water bodies, and their restoration capacity is closely related to the underwater lighting conditions. This study explored the effects of underwater lighting time on the growth characteristics of Vallisneria spinulosa Yan (V. spinulosa) and its water restoration process. V. spinulosa achieved a higher Fv/Fm (0.64), ETRmax (10.43), chlorophyll content (0.85 mg/g), and removal efficiency of total phosphorus (0.37 × 10−3 g m−3 d−1) and a lower algal abundance with a longer lighting time (18 h every day). However, a higher removal efficiency of NH4+–N and TN was obtained with a shorter lighting time (6–12 h every day). The lighting time showed a significance influence on the microbial community of the V. spinulosa growth system, and the influence was significantly different in different regions. Temperature and electrical conductivity were the main environmental impact factors for the microbial community under different lighting times. The abundances of Proteobacteria, Bacteroidota, and Verrucomicrobia exhibited a great positive correlation with each other and a strong positive correlation with the two factors. In addition, the lighting time had a strongly significant correlation with the physical and chemical characteristics of the water environment (p < 0.001) and a significant correlation with the growth characteristics of V. spinulosa (p < 0.05).

Spatial Sense of Safety for Seniors in Living Streets Based on Street View Image Data

As the global population ages, the friendliness of urban spaces towards seniors becomes increasingly crucial. This research primarily investigates the environmental factors that influence the safety perception of elderly people in living street spaces. Taking Dingzigu Street in Tianjin, China, as an example, by employing deep learning fully convolutional network (FCN-8s) technology and the semantic segmentation method based on computer vision, the objective measurement data of street environmental elements are acquired. Meanwhile, the subjective safety perception evaluation data of elderly people are obtained through SD semantic analysis combined with the Likert scale. Utilizing Pearson correlation analysis and multiple linear regression analysis, the study comprehensively examines the impact of the physical environment characteristics of living street spaces on the spatial safety perception of seniors. The results indicate that, among the objective environmental indicators, ① the street greening rate is positively correlated with the spatial sense of security of seniors; ② there is a negative correlation between sky openness and interface enclosure; and ③ the overall safety perception of seniors regarding street space is significantly influenced by the spatial sense of security, the sense of security during walking behavior, and the security perception in visual recognition. This research not only uncovers the impact mechanism of the street environment on the safety perception of seniors, but also offers valuable references for the age-friendly design of urban spaces.

Developing nursing education in a low-income country

Nursing schools in low-income countries face challenges to effectively educate and retain future nurses in rural settings where healthcare needs are more prominent. It is important to understand the experiences of nursing students in rural settings to better prepare them to meet the complex needs of the community. Little is known about nursing students' experiences in rural Uganda. The purpose of this paper is to explore nursing students' experiences of attending school in a rural setting in Uganda. A qualitative descriptive design was used to conduct this study. Twelve nursing students from a nursing school in rural Uganda participated in semi-structured interviews. Data were analyzed using an inductive content analysis. Five themes were developed from the data to describe the participants' experiences attending nursing school in rural Uganda. The five themes consisted of: 1) External Factors Affect Nursing Students' Experiences, 2) Physical Environment Features Influence Nursing Students' Experiences, 3) Teaching and Mentoring Capabilities Shape Nursing Students' Experiences, 4) Technologies Impact Nursing Students' Experiences, and 5) Clinical Environment Considerations Structure Nursing Students' Experiences. Nursing students identified strengths and weaknesses of the learning environment which shaped their experiences of attending nursing school in rural Uganda. The findings of this study also highlight the need for more teaching resources, simulation technology, and on-site facilities to enhance the learning environment. Implications for improving nursing education in rural settings in Uganda and other low-income countries include recruiting and retaining more qualified faculty, offering professional development opportunities to faculty, and developing infrastructure to support quality education and training.

Incorporating functional traits with habitat maps: patterns of diversity in coastal benthic assemblages

Benthic species assemblages are groups of species that co-occur on the seafloor. Linking assemblages to physical environmental features allows for understanding and predicting their spatial distribution. Species identity and abundance are commonly quantified using a taxonomic approach to assess benthic diversity, yet functional traits that describe the behavior, life history, and morphology of a species may be equally or more important. Here, we investigate the biodiversity of five benthic species assemblages in relation to their habitat and environmental conditions in an Ecologically and Biologically Significant Area (EBSA) along Canada’s east coast, using both a taxonomic approach and biological traits analysis. Random Forest regression was applied to map spatial patterns of functional and taxonomic diversity metrics, including richness, Shannon index, and Rao’s quadratic entropy. We evaluate discrepancies between related taxonomic and trait measures, and the community-weighted mean of trait data was calculated to characterize each assemblage. Taxonomic and functional richness – representing the number of species and the species community volume in the trait space, respectively – showed similar spatial patterns. However, when considering diversity, which also accounts for the relative abundance and differences among species or traits, these patterns diverged. Taxonomically different assemblages exhibited similar trait compositions for two assemblages, indicating potential trait equivalencies, while one assemblage exhibited traits potentially indicating sensitivity to human activity. The taxonomic and functional metrics of richness and diversity were low close to the coast, which could be indicative of disturbance. Consideration of functional metrics can support spatial planning and prioritization for management and conservation efforts by assessing the sensitivity of traits to different stressors.

Reconstructing the invention of the wheel using computational structural analysis and design

The invention of the wheel is widely credited as a pivotal moment in human history, yet the details surrounding its discovery are shrouded in mystery. There remains no scholarly consensus on key questions such as where, how and by whom this technology was originally invented. In this study, we employ state-of-the-art techniques from computational structural mechanics to shed light on this long-standing puzzle. Based on this analysis, we propose a probable path along which the wheel evolved via a sequence of three major innovations. We also introduce an original computational design algorithm that autonomously generates a wheel-and-axle system using an evolutionary process that offers insight into the way in which the first wheels likely evolved nearly 6000 years ago. Our analysis provides new supporting evidence for the recently advanced theory that the wheel was invented by Neolithic miners harvesting copper ore from the Carpathian Mountains as early as 3900 BC. Moreover, we show how the discovery of the wheel was made possible by the unique physical features of the mine environment, whose impact was analogous to the selective environmental pressures that drive biological evolution.

Path loss prediction for air-to-ground communication links via scenario transfer technology

Path loss (PL) is a significant channel parameter for the link budget in unmanned aerial vehicle-aided communications. This study introduces an innovative neural network model to estimate PL for air-to-ground communication links. Utilizing the geometric characteristics of varied physical environments, the model accurately predicts PL in diverse communication scenarios. A back-propagation neural network technique is introduced for extrapolating PL under both line-of-sight and non-line-of-sight conditions. A dataset acquisition strategy, comprising scenario reconstruction and advanced ray-tracing techniques, is employed to foster the model’s training and evaluation. Finally, the proposed model is fully trained in diverse communication scenarios, and then used to predict the PLs in a new communication scenario generated by the International Telecommunication Union standard at 28 GHz. The results demonstrate that the extrapolated PLs of the proposed model are well consistent with the reference results. As existing PL models and standard PL models aim at several specifically defined scenarios, the proposed model can predict the PLs in some undefined and unknown scenarios.

The Impact of the Physical Environment on Staff in Healthcare Facilities: A Systematic Literature Review

This article investigates the staff outcomes that are influenced by physical environment features in a healthcare facility. Over the past few decades, research on the physical environment and its effects on hospital staff has advanced steadily. Focusing on the physical environment has become a research area with great potential because it is crucial to provide a favorable work environment for health professionals, which directly impacts the quality of care. A systematic literature review was conducted to identify research articles from two scientific databases and a healthcare journal. Articles that fulfilled the inclusion and exclusion criteria for relevant articles were included in this review. Relevant data were derived from the final shortlisted articles. The features identified in the articles were divided into three dimensions of the physical environment. The results demonstrate different outcomes for staff. This review shows the need to develop a comprehensive study involving the most important features of the three dimensions of the physical setting and its effects on staff. This study contributes invaluable insights for hospital administrators, architects, and designers by informing them about the critical factors shaping the healthcare workplace environment.

The relationship between the environment and physical activity-related motivational trajectories

The study explores motivational profiles for physical activity, using self-determination theory's full continuum of motivational regulations, and examines their stability over three months. Furthermore, it investigates whether physical environment and community characteristics are associated with transitioning between profiles, as well as the sociodemographic differences in these motivational transition pathways. Data were collected from 305 U.S. residents at three time points. The three profiles-'low in motivation' (23.5% of the sample in wave 1), 'self-determined motivation' (41.4%), and 'ambivalent motivation' (35.0%)-were relatively stable. Staying in the low-in-motivation profile was negatively associated with being active in social settings, community support, perceived environmental restorativeness, and availability of physical activity opportunities. Having a higher education and income, being male, employed, married or in a partnership, and identifying as White were associated with being in a motivationally positive profile in the last wave of the study. These profiles reported higher activity and life satisfaction.

A User-Centric CPTED-Based Approach to Investigate Physical Environmental Variables Influencing Perceived Security of Urban Park Users in Tiruchirappalli, India

The link between Fear of Crime (FC) and physical environment and crime levels is referred to as Crime Prevention Through Environmental Design (CPTED). However, FC, irrespective of the level of crime through physical environmental features, can hinder people's access to urban parks. This study is a novel attempt to evaluate the Perceived Security (PS) related to fear of (theft, robbery) crime under the CPTED classification by assessing actual users' perceptions of multiple physical environmental variables within and around fifteen Tiruchirappalli urban parks. The objectively measured CPTED variables were documented through observations and measurements by the authors, whereas subjectively measured ones were assessed using actual users’ (n=524) perceptions. The results majorly highlight the significance of park design and landscape-based surveillance and park facilities and landscape-based maintenance variables towards predicting PS. The findings from this study can aid policymakers, park designers, and managers in adopting strategies that can enhance the PS of users, prioritise interventions, and engage residents in addressing specific design considerations.

How Does Density Impact Carbon Emission Intensity: Insights from the Block Scale and an Optimal Parameters-Based Geographical Detector

Density is a crucial indicator for urban sustainable development and is considered a critical factor influencing the carbon emission intensity of construction land (CICL). The impact of density on carbon emissions has been extensively explored, mainly focusing on grid-scale and single-factor effects. However, how density and its interactions affect carbon emissions at the block scale is unclear. Therefore, based on multiple data sources such as energy consumption, remote sensing, and the point of interest (POI) in the urban block of Changxing County, this study constructed a density system that reflects the block’s physical environment and socioeconomic characteristics. An optimal-parameters-based geographical detector was employed to investigate the effects and interactions of density factors on the carbon emission intensity of residential blocks (CIRB), carbon emission intensity of commercial blocks (CICB), and carbon emission intensity of public blocks (CIPB). The results indicate the following: (1) The impact of density factors on different types of CICL varied significantly. Physical environmental factors (PEFs) had greater explanatory power than socioeconomic factors (SEFs) across the CIRB, CICB, and CIPB, with the floor area ratio (FAR) being the most influential. The spatial morphology of blocks also influenced the relationship between density factors and the CICL. (2) The interactions between the FAR and building density (BD), the FAR and commercial outlet density (COD), and the FAR and population density (PD) had the strongest explanatory power for the CIRB, CICB, and CIPB, respectively, and all exhibited nonlinear enhancements. Some factors exhibited more significant effects only when interacting with others. (3) An association chain encompassing the interactions of multiple density factors was extracted for the CIRB, CICB, and CIPB, respectively, as the basis for conducting collaborative management and control in spatial planning. The research findings can provide decision support for urban planners to consider the comprehensive effects of density factors and promote the development of low-carbon urban spaces.

Preschool children’s physical activity in the home, childcare and neighbourhood environment: A latent profile analysis using device-based measures

ABSTRACT Based on the socioecological conceptual model, the physical environment within the home, childcare and neighbourhood domains are key factors that influence preschool children’s physical activity; however, the relative importance of each of these domains for preschool children’s physical activity is unclear. We explored the physical environment characteristics within three latent profiles of 115 preschool children aged 2–5 years based on where they accumulated moderate-to-vigorous physical activity (MVPA) across five GPS-derived environmental domains. The three profiles were “Active at home” (n = 41), “Active except close to home” (n = 61), and “Active except in local neighbourhood” (n = 13). Compared to other profiles, “Active at home” had fewer parks and playgrounds within their 500–1600 m neighbourhood. Findings suggest preschool children’s MVPA profiles are reflections of their physical environmental opportunities.

Health-related quality of life and perceptions of neighborhood physical and social environment in Tehran, Iran

ABSTRACT In light of rapid global urbanization and development, planners have become more concerned with the quality of life in cities. However, the perceptual connections between the built environment and resident well-being deserve more systematic attention. This study investigates the relationship between the perceived physical and social features of the neighborhood environment and the health-related quality of life for 393 adult residents in Tehran, Iran. A questionnaire was developed to examine participants’ perceptions of neighborhood social and physical factors, along with the World Health Organization’s Quality of Life – Brief Form (WHOQOL – BREF) to measure their health-related quality of life. Using factor analysis, correlations, and multiple linear regressions, the findings suggest that all subcomponents of the physical environment (accessibility, amenity, and legibility) and social environment (participation, sense of community, and satisfaction) impact psychological, social relationships, and environmental health, but that amenities were most powerfully predictive of all three types of socio-environmental health.

The composite drought index incorporated solar-induced chlorophyll fluorescence enhances the monitoring capability of short-term drought

The composite drought index incorporated solar-induced chlorophyll fluorescence enhances the monitoring capability of short-term drought

Development of a contextualized index of multiple deprivation for age-friendly cities: Evidence from Hong Kong

Development of a contextualized index of multiple deprivation for age-friendly cities: Evidence from Hong Kong

Integrating street view imagery and taxi trajectory for identifying urban function of street space

ABSTRACT Street space is a crucial component of public space, serving as a site for a variety of human activities. However, prior studies have primarily focused on the traffic function of street space, neglecting other functional types, such as residential and commercial. To address this gap, this study proposes a classification method for street space by integrating taxi trajectory and street view imagery. The dynamic travel features of the residents are extracted from taxi trajectory data and the multi-level physical environment features of the streets are constructed based on street view imagery data. Then, the street space with same urban functions is assigned to the same cluster based on the dynamic travel features of the residents, the multi-level physical environment features of streets and K-means method. The proposed method is empirically applied to the Futian District of Shenzhen to demonstrate its validity, and the street space is successfully classified into five types, namely public, traffic, commercial, residential, and mixed commercial and residential. This work contributes to the evaluation of street space quality, facilitating scientific planning and efficient governance of street space.

The role of the local environment in selecting and determining architectural standards for buildings

The study aims to demonstrate the role of the local environment as a decisive factor in architecture design. It plays an important role in determining the form and function of buildings, from the presence of the landscape to its reflection in the architectural fabric. What constitutes the physical features of the local environment, such as terrain, climate, and availability of natural resources, by imposing environmental standards of measurement that are consistent with global environmental standards. Where the idea of sustainability in buildings was addressed. We decided to use the analytical approach in the study, as well as the inductive approach, to derive some standards in the research process. Four basic elements were identified that are relied upon in society through its social, cultural, and human environment, in addition to studying global and regional environmental standards, which are: LEED standards, which in turn also affect the integrated building strategy from an environmental standpoint, in terms of the functional performance of activities, environmental conditions, social needs, and the human aspect. The results of the environmental classification according to the research procedure showed that it gave results close to the LEED scale, which was between the normal and gold classification, and in the green cod classification, that matches the LED scale. Keywords: Local environment, design considerations, evaluation criteria, LED scale.

Physical working environments: how they affect our wellbeing and performance

The surroundings in which employees spend their working lives are an important source of job satisfaction, and have an impact on work motivation and patterns of interaction with others. On the other hand, they can be as much of a source of pressure as a heavy workload, poor work‐life balance or significant organisational change. This article provides an overview of the impact of elements of the physical working environment on staff wellbeing, including the building design, workspace, materials, furniture, lighting, temperature, noise and how much control the team have over their work environment. These factors need to be considered to ensure that the physical characteristics of the veterinary environment do not have a negative effect on engagement, productivity and wellbeing, but instead promote job satisfaction, improved performance and team cohesiveness.

Exploring emotions in relation to neighborhood environmental characteristics among older adults with low socioeconomic position: A qualitative study using walk-along interviews

Exploring emotions in relation to neighborhood environmental characteristics among older adults with low socioeconomic position: A qualitative study using walk-along interviews

ENHANCEMENT OF UNDERWATER IMAGES WITH ARTIFICIAL INTELLIGENCE

Abstract. Camera systems using optical sensors have made great progress in recent years in obtaining underwater images. Very high-resolution images can be obtained with underwater cameras. However, it becomes difficult to process the image obtained due to many distorting factors such as inhomogeneous underwater lighting, low contrast, blur, sea snow. For this purpose, image enhancement algorithms are used to minimise the problems in the captured images. The physical characteristics of the underwater environment cause degradation effects that are not found in normal images captured in air. Due to the effects such as colour distortion, low contrast and brightness, blurred details in images captured in this type of environment, the usage area of these images is very limited. This project aims to use artificial intelligence methods for colour enhancement of underwater images. In addition, one of the main objectives of the project is to examine the effect of colour enhancement applied to images on other areas of use. Within the scope of the project, An Underwater Image Enhancement Benchmark Dataset and Beyond Dataset and Large Scale Underwater Image Dataset datasets were used. In our study, U-Shape Transformer architecture and Pix2Pix architecture were tested for their usability for image enhancement. According to the results obtained, Pix2Pix architecture achieved the highest accuracy. Accuracy results were obtained as 22.5884 and 0.8764 for PSNR and SSIM, respectively using UIEB dataset. The accuracy values for LSUI dataset are 25.1010 and 0.8440 for PSNR and SSIM, respectively.