Displaying publications 61 - 68 of 68 in total

Abstract:
Sort:
  1. Ghani F, Rachele JN, Loh VH, Washington S, Turrell G
    PMID: 31167430 DOI: 10.3390/ijerph16111980
    Within a city, gender differences in walking for recreation (WfR) vary significantly across neighbourhoods, although the reasons remain unknown. This cross-sectional study investigated the contribution of the social environment (SE) to explaining such variation, using 2009 data from the How Areas in Brisbane Influence healTh and AcTivity (HABITAT) study, including 7866 residents aged 42-67 years within 200 neighbourhoods in Brisbane, Australia (72.6% response rate). The analytical sample comprised 200 neighbourhoods and 6643 participants (mean 33 per neighbourhood, range 8-99, 95% CI 30.6-35.8). Self-reported weekly minutes of WfR were categorised into 0 and 1-840 mins. The SE was conceptualised through neighbourhood-level perceptions of social cohesion, incivilities and safety from crime. Analyses included multilevel binomial logistic regression with gender as main predictor, adjusting for age, socioeconomic position, residential self-selection and neighbourhood disadvantage. On average, women walked more for recreation than men prior to adjustment for covariates. Gender differences in WfR varied significantly across neighbourhoods, and the magnitude of the variation for women was twice that of men. The SE did not explain neighbourhood differences in the gender-WfR relationship, nor the between-neighbourhood variation in WfR for men or women. Neighbourhood-level factors seem to influence the WfR of men and women differently, with women being more sensitive to their environment, although Brisbane's SE did not seem such a factor.
    Matched MeSH terms: Social Environment*
  2. Padilla-Iglesias C, Gjesfjeld E, Vinicius L
    PLoS One, 2020;15(12):e0243171.
    PMID: 33259529 DOI: 10.1371/journal.pone.0243171
    The origins of linguistic diversity remain controversial. Studies disagree on whether group features such as population size or social structure accelerate or decelerate linguistic differentiation. While some analyses of between-group factors highlight the role of geographical isolation and reduced linguistic exchange in differentiation, others suggest that linguistic divergence is driven primarily by warfare among neighbouring groups and the use of language as marker of group identity. Here we provide the first integrated test of the effects of five historical sociodemographic and geographic variables on three measures of linguistic diversification among 50 Austronesian languages: rates of word gain, loss and overall lexical turnover. We control for their shared evolutionary histories through a time-calibrated phylogenetic sister-pairs approach. Results show that languages spoken in larger communities create new words at a faster pace. Within-group conflict promotes linguistic differentiation by increasing word loss, while warfare hinders linguistic differentiation by decreasing both rates of word gain and loss. Finally, we show that geographical isolation is a strong driver of lexical evolution mainly due to a considerable drift-driven acceleration in rates of word loss. We conclude that the motor of extreme linguistic diversity in Austronesia may have been the dispersal of populations across relatively isolated islands, favouring strong cultural ties amongst societies instead of warfare and cultural group marking.
    Matched MeSH terms: Social Environment
  3. Waddy BB
    J Trop Med Hyg, 1974 Apr;77(4):s:19-21.
    PMID: 4841357
    Matched MeSH terms: Social Environment
  4. Oyedele DT, Sah SA, Kairuddinand L, Wan Ibrahim WM
    Trop Life Sci Res, 2015 Dec;26(2):27-44.
    PMID: 26868708 MyJurnal
    Studies of habitat suitability (HS) are essential when animals' habitats have been altered or when animals migrate to a habitat different from their natural habitat. This study assessed HS and used an integrated geographic information system in the assessment of Rattus norvegicus in a highly developed urban environment. Using data from the Campbell market and the police quarters of George Town, Malaysia, home range (through the use of 100% Minimum Convex Polygon [MCP], 95% MCP and 95% Harmonic Mean [HM]) was estimated. Home range for male rats at Campbell market reached an asymptote, with a slight increase, at 96 radio fixes (home range = 133.52 m(2); core area = 29.39 m(2)). Female rats reached an asymptote at 62 radio fixes (home range = 13.38 m(2); core area = 9.17 m(2)). At Campbell market, male rats emerged at 1900 hours every day, whereas females emerged at 2000 hours; at police quarters, the most common time of emergence for males was 2000 hours and for females was 2200. Raster charts of R. norvegicus showed that rat hot spots can be grouped into 4 zones (market, shop houses, settlement and general places). The standardised raster chart isolated the market as the major rallying points of the rats (hot spots) by producing the highest rats frequencies of 255. All of the habitat suitability thresholds, including the built-up points, skip bins, water source and nature of the site explored in this study, produced a structural pattern (monotonic increase or decrease) of habitat suitability.
    Matched MeSH terms: Social Environment
  5. Tackett S, Shochet R, Shilkofski NA, Colbert-Getz J, Rampal K, Abu Bakar H, et al.
    BMC Med Educ, 2015;15:105.
    PMID: 26081751 DOI: 10.1186/s12909-015-0388-0
    Perdana University Graduate School of Medicine (PUGSOM), the first graduate-entry medical school in Malaysia, was established in 2011 in collaboration with Johns Hopkins University School of Medicine (JHUSOM), an American medical school. This study compared learning environments (LE) at these two schools, which shared the same overarching curriculum, along with a comparator Malaysian medical school, Cyberjaya University College of Medical Sciences (CUCMS). As a secondary aim, we compared 2 LE assessment tools - the widely-used Dundee Ready Educational Environment Measure (DREEM) and the newer Johns Hopkins Learning Environment Scale (JHLES).
    Matched MeSH terms: Social Environment*
  6. Zheyuan C, Rahman MA, Tao H, Liu Y, Pengxuan D, Yaseen ZM
    Work, 2021;68(3):825-834.
    PMID: 33612525 DOI: 10.3233/WOR-203416
    BACKGROUND: The increasing use of robotics in the work of co-workers poses some new problems in terms of occupational safety and health. In the workplace, industrial robots are being used increasingly. During operations such as repairs, unmanageable, adjustment, and set-up, robots can cause serious and fatal injuries to workers. Collaborative robotics recently plays a rising role in the manufacturing filed, warehouses, mining agriculture, and much more in modern industrial environments. This development advances with many benefits, like higher efficiency, increased productivity, and new challenges like new hazards and risks from the elimination of human and robotic barriers.

    OBJECTIVES: In this paper, the Advanced Human-Robot Collaboration Model (AHRCM) approach is to enhance the risk assessment and to make the workplace involving security robots. The robots use perception cameras and generate scene diagrams for semantic depictions of their environment. Furthermore, Artificial Intelligence (AI) and Information and Communication Technology (ICT) have utilized to develop a highly protected security robot based risk management system in the workplace.

    RESULTS: The experimental results show that the proposed AHRCM method achieves high performance in human-robot mutual adaption and reduce the risk.

    CONCLUSION: Through an experiment in the field of human subjects, demonstrated that policies based on the proposed model improved the efficiency of the human-robot team significantly compared with policies assuming complete human-robot adaptation.

    Matched MeSH terms: Social Environment
  7. Thatcher A, Yeow PH
    Appl Ergon, 2016 May 24.
    PMID: 27234806 DOI: 10.1016/j.apergo.2016.05.007
    Current human activities are seriously eroding the ability of natural and social systems to cope. Clearly we cannot continue along our current path without seriously damaging our own ability to survive as a species. This problem is usually framed as one of sustainability. As concerned professionals, citizens, and humans there is a strong collective will to address what we see as a failure to protect the natural and social environments that supports us. While acknowledging that we cannot do this alone, human factors and ergonomics needs to apply its relevant skills and knowledge to assist where it can in addressing the commonly identified problem areas. These problems include pollution, climate change, renewable energy, land transformation, and social unrest amongst numerous other emerging global problems. The issue of sustainability raises two fundamental questions for human factors and ergonomics: which system requires sustaining and what length of time is considered sustainable? In this paper we apply Wilson (2014) parent-sibling-child model to understanding what is required of an HFE sustainability response. This model is used to frame the papers that appear in this Special Issue.
    Matched MeSH terms: Social Environment
  8. Aburas, Maher Milad, Sabrina Ho Abdullah, Mohammad Firuz Ramli, Zulfa Hanan Ash'aari
    MyJurnal
    Remote sensing and geographic information system techniques are significant and popular approaches that have been used in recent years to measure and map urban growth patterns. This paper primarily aims to provide a basis for a literature review of urban growth measurement and mapping by using different methods. For this purpose, the general characteristics of measuring and mapping urban growth patterns are described and classified. The strengths and weaknesses of the various methods have been identified from an analysis and discussion of the characteristics of the techniques. Results of reviews confirm that combining quantitative and qualitative techniques, such as Shannon approach and change detection, to measure and map urban growth patterns will improve understanding of the phenomenon of urban growth. Moreover, using social and economic data such as population and income data will improve understanding of the relationships between causes and effects. The integration of social and economic factors with quantitative and qualitative techniques will contribute to a perfect evaluation of urban growth patterns and land use changes, taking technical, social, economic, spatial, and temporal factors into account.
    Matched MeSH terms: Social Environment
Related Terms
Filters
Contact Us

Please provide feedback to Administrator (afdal@afpm.org.my)

External Links