Features Of Physical Environment Research Articles

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 probably evolved nearly 6000 years ago. Our analysis provides new supporting evidence for the recently advanced theory that the wheel was probably 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.

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

Understanding the response of vegetation to drought is significant for socio-economic development and biodiversity conservation. However, due to the complexity of drought, relying only on one approach, such as the surrounding physical environmental conditions or specific vegetation characteristics, does not yield precise results. To address this challenge, composite drought indices incorporating Normalized Difference Vegetation Index (NDVI) and other multiple variables, have been developed and shown promising effectiveness in drought detection. Compared to NDVI, solar-induced chlorophyll fluorescence (SIF) decreases due to the increased non-photochemical quenching and reduced photosynthesis during short-term drought stress. This indicates a direct association between SIF and vegetation photosynthesis, offering advantages over NDVI in capturing drought effects. Nevertheless, SIF has not yet been fully integrated into composite drought indices. Therefore, this study focused on assessing the advantages of SIF for short-term drought monitoring by constructing a new composite drought index (CPDI) using the Principal Component Analysis (PCA) method. Subsequently, CPDI was employed to forecast future drought conditions. Overall, CPDI performs exceptionally well as a composite drought index in drought trend analysis and drought event identification, indeed advancing the monitoring capability for short-term drought. Furthermore, the incorporation of SIF in CPDI, obtained from various data sources provides more timely monitoring of drought events, while the CPDI with NDVI reflects the cumulative effect of drought conditions over a longer period. In the future, it is potential to utilize the benefits of SIF in constructing drought indices or combine it with NDVI for comprehensive drought characterization.

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

Deprivation refers to the state of having unmet basic needs, defined by societal standards. We argue that the mono emphasis on material deprivation is insufficient, as the characteristics of physical and social environments play a crucial role in either accelerating deprivation or providing additional resources/support to compensate for lack of income or basic household demands. We extend the focal point of the multiple deprivation framework to Hong Kong, an ultra-dense metropolis experiencing rapid demographic aging. We construct a Hong Kong index of multiple deprivation with seven domains. Highly deprived neighborhoods are likely to be located in areas with ultra-high residential density, where living conditions are substandard (e.g., subdivided units). Urban areas that used to have a large proportion of resettlement and industrial lands are likely to become deprived owing to the uneven distribution of urban amenities and the fragmentation of residential areas by industrial land.

Epidemiological Risk Factors and Modelling Approaches for Risk Assessment of Lumpy Skin Disease Virus Introduction and Spread: Methodological Review and Implications for Risk-Based Surveillance in Australia

Lumpy skin disease (LSD) is a vector-borne infection caused by the poxvirus lumpy skin disease virus (LSDV) and is a serious disease of cattle, water buffalo, and banteng. While the disease has never occurred in Australia, it is regarded as a growing threat to the Australian cattle industry as there is on-going spread of the disease throughout Asia. The development of geospatial decision support tools, such as spatial epidemiological modelling, may assist in assessing areas at greater risk of this threat. To guide the design of disease modelling approaches to support future risk-based surveillance, existing LSDV epidemiological models need to be evaluated. In this study, we performed a literature review to evaluate existing LSDV epidemiological models, identify key risk factors for introduction and spread of LSDV, and consider previously adopted control strategies. The PRISMA guidelines were used to establish the processes for article selection and information extraction, and the PICO process was used to formulate search terms. From studies that met our inclusion criteria, we extracted information on LSDV epidemiological model structure and parameterisation, risk factors for LSDV transmission and spread, and biosecurity control strategies. The literature search retrieved a total of 402 articles from four databases, of which 68 were identified for inclusion in this review following screening. Of the 68 articles reviewed, 47 explored risk factors associated with LSDV transmission and spread, four explored risk factors of LSDV introduction, four explored existing surveillance strategies in LSD-free countries, and 14 presented epidemiological models. Our findings indicate that there are various risk factors for LSDV transmission in LSD endemic countries, including long-distance airborne movement of infected vectors such as stable flies and cattle movement between countries over land borders. Key risk factors for LSDV spread in LSD endemic countries include physical environmental characteristics, weather conditions, and population distributions of livestock and vectors. Our results indicate that while a variety of modelling studies have been conducted, the majority of studies experimentally explored LSD transmission mechanisms in vectors and cattle. Spatial and spatio-temporal models have primarily been developed for LSD endemic countries and focus on the spread of the disease in terms of environmental factors in relation to previous LSD events. There were very few studies on LSD-free countries, and these only focussed on risk of LSD introduction through specific entry pathways. This review did not identify any literature exploring the risk of spread of LSDV following introduction in LSD-free countries or geospatial modelling of the suitability of LSD-free countries for LSDV incursions. In conjunction with the risk parameters and models described in the identified literature, there is need to consider a wide range of risk factors specific to Australia to inform the design of risk-based surveillance for LSD in Australia.

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

Cities are challenged to provide older adults with high-quality neighborhoods that foster their mental health. Older adults with low socioeconomic position (SEP) are at risk for poor mental health, but research in this group is scarce. The neighborhood may have an impact on older adults' mental health through the elicitation of emotions. Qualitative on-site research can provide detailed and context-sensitive information on the experienced emotions. The aim of this walk-along study was to identify which emotions older adults with low SEP experience when they walk in their neighborhood and the physical and social neighborhood environmental characteristics that influence these emotions. Twenty-four older adults with low SEP were interviewed and content analysis was performed using NVivo 12 software. Participants experienced various positive emotions (e.g., calmness) in green and blue spaces, spaces with historical buildings, and open spaces. They experienced negative emotions (e.g., frustration) in spaces with heavy traffic and crime, paths with uneven surfaces, and areas with a lack of services, infrastructure and maintenance. The presence of public transport, renovations, graffiti, and cultural diversity evoked mixed emotions. Insights from this study could be used to develop specific hypotheses in quantitative studies and by urban planners and policy makers when (re-)designing neighborhoods.

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.

Physical Environment Characteristics With The Presebce Of Aedes Larvae At The Ummul Mukminin Islamic Boarding School Makassar, Indonesia

Objective: The research aimed to know characteristics of the physical environment with the presence of Aedes larvae at the Ummul Mukminin Islamic Boarding School in Makassar City. Methods: The type of research used is descriptive, the sample number is 33 containers with exhaustive sampling as a sampling technique. The research instrument used was an observation sheet with univariate analysis using SPSS and Excel program. The study was conducted in June 2022 at the Ummul Mukminin Islamic Boarding School. Results: A total of 33 containers were found at the study site, 31 (93.9%) containers were not found to have larvae (negative) and 2 (6.1%) containers were positive for Aedes larvae. Plastic container base material with 100% presentation. There are 24 (72.7%) containers were water reservoir (TPA) and 9 (27,3%) containers were non-water reservoir, 27 (81,8%) containers were located indoor and 6 (18,2%) containers were located outdoor. Conclusions: The larva-free dormitory program by the school health post (poskestren) should be continued and if possible the frequency of activities is increased, as well as toilets that are rarely used and in dark conditions are still considered because they have the potential to be Aedes larva breeding place. Research Implications: Such findings are expected to be a source of information for the community, especially the teachers and students of the Ummul Mukminin Islamic Boarding School regarding the importance of maintaining the cleanliness of the mosquito breeding environment, especially regarding the presence of Aedes larvae and efforts to prevent dengue incidents. And can be an information material for the Makassar City Health Office, especially in overcoming dengue problems and can be a source of reference and comparison for further research. Originality / value: This study discusses some characteristics of water reservoirs (containers) that have the potential to become breeding sites for Aedes larvae, as one of the references in efforts to eradicate Aedes mosquito nests as vectors for dengue fever transmission.

Investigating the diurnal effects of on-street population and streetscape physical environment on street theft crime: A machine learning and negative binomial regression approach using street view images

Street theft crime remains a significant public safety concern in China and a central focus of urban crime prevention initiatives. Recent studies have combined street view images and deep learning networks to detect on-street population and streetscape physical environment features, highlighting their significance in comprehending the occurrence of street crime. However, the question of whether on-street population better represents the ‘true risk population of street crime’ compared to previous static (residential) and dynamic (ambient) measures, and whether this advantage persists across different times of the day, remains unexplored. Additionally, the association between streetscape physical environment features and street theft crime, as established in the existing literature, has not been thoroughly examined with respect to temporal variations throughout the day. To address these gaps, this study employed a machine learning model and a simultaneous negative binomial regression model to explore the influence of on-street population and streetscape physical environment on street theft counts. Specifically, we assessed whether their effects exhibit noticeable variations between day and night. Furthermore, we controlled for potential effects of crime attractors, generators, and sociodemographic variables. Our findings demonstrate, firstly, that on-street population extracted from street view images outperforms other measures in assessing the risk population for street theft due to its superior ability to indicate outdoor activities. Moreover, this advantage of on-street population holds true during both daytime and nighttime hours. Secondly, differences in the impact of streetscape physical environment variables and control variables on street theft counts are observed across daytime and nighttime hours. On-street population proves to be a promising alternative for measuring the risk population of street crime victimization, and temporal variations should not be overlooked in future research endeavors.

Induced Formation of Plasma Membrane Protrusions with Porous Materials as Instructive Surfaces.

The plasma membrane is a vital component in cellular processes, and its structure has a significant impact on cellular behavior. The physical characteristics of the extracellular environment, along with the presence of surface pores, can influence the formation of membrane protrusions. Nanoporous surfaces have demonstrated their capacity to induce membrane protrusions in both adherent and non-adherent cells. This chapter presents a methodology that utilizes a nanoporous substrate with nanotopographical constraints to effectively stimulate the formation of membrane protrusions in cells.

Effectiveness of Heatwave Emergency Alert Messages through Analysis of Floating Population

Heatwave emergency alert messages (EAM) not only provide objective information on heatwave occurrences but also include behavioral guidelines, such as avoiding outdoor activities or going out to respond to heatwaves and minimize damage. To investigate the EAM's effectiveness, we analyzed the changes in the floating population during 2021 using Seoul dong-unit and hourly location-based mobile big data. We also examined what socioeconomic and physical environmental characteristics could cause differences in the effectiveness, focusing on the fact that EAM may have different effects depending on regional factors. The findings revealed a notable reduction in the overall floating population of Seoul, ranging from 0.1 to 3.4%. When examined by region, an average decrease of 2.4 to 5.6% was observed, indicating the different effects of EAM by region. Further analysis of regional characteristics highlighted that areas with low EAM effectiveness were characterized by a lower ratio of senior residents, higher employment concentration, and higher accessibility to public transportation. Additionally, the number of household members, gender distribution, average age, and presence of green spaces can contribute to the gap in the effectiveness of EAM between regions.