493 resultados para Environmental Dependence


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Recent calls in Australia have addressed the need for better integration of planning processes. The consequent effort made by government has been, and still is, reshaping the way urban and regional planning and sustainability are managed. Focusing on planning practices at the local and regional levels, we investigate how environmental sustainability is pursued from an institutional perspective. Specifically, we analyse the way that planning in Australian cities aims to achieve sustainable strategies and reflect on the relationship with ‘Strategic Environmental Assessment’. This paper has four goals. First, sustainable planning practices at the local and regional levels are analysed considering the legislative and organizational frameworks of each state. The goal is to identify through an analysis of planning documents how much discretion is given to local councils to address sustainable strategies. Second, we focus on two regional and four cities in Queensland, to outline strengths and weaknesses of current legislative and practical frameworks. We use analytical criteria from the SEA literature to investigate these plans in more detail. Third, we examine the relationship between strategic and statutory plans, to see how sustainability is actually implemented. Finally we compare emerging issues about sustainable planning in Australia with countries overseas with different planning and SEA traditions. Considering that SEA is evolving and there are considerable international experiences, we offer recommendations on how Australia might achieve a more integrated and sustainable approach to planning.

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Bioacoustic data can be used for monitoring animal species diversity. The deployment of acoustic sensors enables acoustic monitoring at large temporal and spatial scales. We describe a content-based birdcall retrieval algorithm for the exploration of large data bases of acoustic recordings. In the algorithm, an event-based searching scheme and compact features are developed. In detail, ridge events are detected from audio files using event detection on spectral ridges. Then event alignment is used to search through audio files to locate candidate instances. A similarity measure is then applied to dimension-reduced spectral ridge feature vectors. The event-based searching method processes a smaller list of instances for faster retrieval. The experimental results demonstrate that our features achieve better success rate than existing methods and the feature dimension is greatly reduced.

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Identifying inequalities in air pollution levels across population groups can help address environmental justice concerns. We were interested in assessing these inequalities across major urban areas in Australia. We used a land-use regression model to predict ambient nitrogen dioxide (NO2) levels and sought the best socio-economic and population predictor variables. We used a generalised least squares model that accounted for spatial correlation in NO2 levels to examine the associations between the variables. We found that the best model included the index of economic resources (IER) score as a non-linear variable and the percentage of non-Indigenous persons as a linear variable. NO2 levels decreased with increasing IER scores (higher scores indicate less disadvantage) in almost all major urban areas, and NO2 also decreased slightly as the percentage of non-Indigenous persons increased. However, the magnitude of differences in NO2 levels was small and may not translate into substantive differences in health.

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Introduction: Ultrasmall superparamagnetic iron oxide (USPIO)-enhanced MRI has been shown to be a useful modality to image activated macrophages in vivo, which are principally responsible for plaque inflammation. This study determined the optimum imaging time-window to detect maximal signal change post-USPIO infusion using T1-weighted (T1w), T2*- weighted (T2*w) and quantitative T2*(qT 2*) imaging. Methods: Six patients with an asymptomatic carotid stenosis underwent high resolution T1w, T2*w and qT2*MR imaging of their carotid arteries at 1.5 T. Imaging was performed before and at 24, 36, 48, 72 and 96 h after USPIO (Sinerem™, Guerbet, France) infusion. Each slice showing atherosclerotic plaque was manually segmented into quadrants and signal changes in each quadrant were fitted to an exponential power function to model the optimum time for post-infusion imaging. Results: The power function determining the mean time to convergence for all patients was 46, 41 and 39 h for the T1w, T 2*w and qT2*sequences, respectively. When modelling each patient individually, 90% of the maximum signal intensity change was observed at 36 h for three, four and six patients on T1w, T 2*w and qT2*, respectively. The rates of signal change decrease after this period but signal change was still evident up to 96 h. Conclusion: This study showed that a suitable imaging window for T 1w, T2*w and qT2*signal changes post-USPIO infusion was between 36 and 48 h. Logistically, this would be convenient in bringing patients back for one post-contrast MRI, but validation is required in a larger cohort of patients.

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Power calculation and sample size determination are critical in designing environmental monitoring programs. The traditional approach based on comparing the mean values may become statistically inappropriate and even invalid when substantial proportions of the response values are below the detection limits or censored because strong distributional assumptions have to be made on the censored observations when implementing the traditional procedures. In this paper, we propose a quantile methodology that is robust to outliers and can also handle data with a substantial proportion of below-detection-limit observations without the need of imputing the censored values. As a demonstration, we applied the methods to a nutrient monitoring project, which is a part of the Perth Long-Term Ocean Outlet Monitoring Program. In this example, the sample size required by our quantile methodology is, in fact, smaller than that by the traditional t-test, illustrating the merit of our method.

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Purpose – The purpose of this study is to explore senior managers’ perception and motivations of corporate social and environmental responsibility (CSER) reporting in the context of a developing country, Bangladesh. Design/methodology/approach – In-depth semi-structured interviews were conducted with 25 senior managers of companies listed on the Dhaka Stock Exchange. Publicly available annual reports of these companies were also analysed. Findings – The results indicate that senior managers perceive CSER reporting as a social obligation. The study finds that the managers focus mostly on child labour, human resources/rights, responsible products/services, health education, sports and community engagement activities as part of the social obligations. Interviewees identify a lack of a regulatory framework along with socio-cultural and religious factors as contributing to the low level of disclosures. These findings suggest that CSER reporting is not merely stakeholder-driven, but rather country-specific social and environmental issues play an important role in relation to CSER reporting practices. Research limitations/implications – This paper contributes to engagement-based studies by focussing on CSER reporting practices in developing countries and are useful for academics, practitioners and policymakers in understanding the reasons behind CSER reporting in developing countries. Originality/value – This paper addresses a literature “gap” in the empirical study of CSER reporting in a developing country, such as Bangladesh. This study fills a gap in the existing literature to understand managers’ motivations for CSER reporting in a developing country context. Managerial perceptions on CSER issues are largely unexplored in developing countries.

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Species distribution modelling (SDM) typically analyses species’ presence together with some form of absence information. Ideally absences comprise observations or are inferred from comprehensive sampling. When such information is not available, then pseudo-absences are often generated from the background locations within the study region of interest containing the presences, or else absence is implied through the comparison of presences to the whole study region, e.g. as is the case in Maximum Entropy (MaxEnt) or Poisson point process modelling. However, the choice of which absence information to include can be both challenging and highly influential on SDM predictions (e.g. Oksanen and Minchin, 2002). In practice, the use of pseudo- or implied absences often leads to an imbalance where absences far outnumber presences. This leaves analysis highly susceptible to ‘naughty-noughts’: absences that occur beyond the envelope of the species, which can exert strong influence on the model and its predictions (Austin and Meyers, 1996). Also known as ‘excess zeros’, naughty noughts can be estimated via an overall proportion in simple hurdle or mixture models (Martin et al., 2005). However, absences, especially those that occur beyond the species envelope, can often be more diverse than presences. Here we consider an extension to excess zero models. The two-staged approach first exploits the compartmentalisation provided by classification trees (CTs) (as in O’Leary, 2008) to identify multiple sources of naughty noughts and simultaneously delineate several species envelopes. Then SDMs can be fit separately within each envelope, and for this stage, we examine both CTs (as in Falk et al., 2014) and the popular MaxEnt (Elith et al., 2006). We introduce a wider range of model performance measures to improve treatment of naughty noughts in SDM. We retain an overall measure of model performance, the area under the curve (AUC) of the Receiver-Operating Curve (ROC), but focus on its constituent measures of false negative rate (FNR) and false positive rate (FPR), and how these relate to the threshold in the predicted probability of presence that delimits predicted presence from absence. We also propose error rates more relevant to users of predictions: false omission rate (FOR), the chance that a predicted absence corresponds to (and hence wastes) an observed presence, and the false discovery rate (FDR), reflecting those predicted (or potential) presences that correspond to absence. A high FDR may be desirable since it could help target future search efforts, whereas zero or low FOR is desirable since it indicates none of the (often valuable) presences have been ignored in the SDM. For illustration, we chose Bradypus variegatus, a species that has previously been published as an exemplar species for MaxEnt, proposed by Phillips et al. (2006). We used CTs to increasingly refine the species envelope, starting with the whole study region (E0), eliminating more and more potential naughty noughts (E1–E3). When combined with an SDM fit within the species envelope, the best CT SDM had similar AUC and FPR to the best MaxEnt SDM, but otherwise performed better. The FNR and FOR were greatly reduced, suggesting that CTs handle absences better. Interestingly, MaxEnt predictions showed low discriminatory performance, with the most common predicted probability of presence being in the same range (0.00-0.20) for both true absences and presences. In summary, this example shows that SDMs can be improved by introducing an initial hurdle to identify naughty noughts and partition the envelope before applying SDMs. This improvement was barely detectable via AUC and FPR yet visible in FOR, FNR, and the comparison of predicted probability of presence distribution for pres/absence.

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Acoustic recordings play an increasingly important role in monitoring terrestrial and aquatic environments. However, rapid advances in technology make it possible to accumulate thousands of hours of recordings, more than ecologists can ever listen to. Our approach to this big-data challenge is to visualize the content of long-duration audio recordings on multiple scales, from minutes, hours, days to years. The visualization should facilitate navigation and yield ecologically meaningful information prior to listening to the audio. To construct images, we calculate acoustic indices, statistics that describe the distribution of acoustic energy and reflect content of ecological interest. We combine various indices to produce false-color spectrogram images that reveal acoustic content and facilitate navigation. The technical challenge we investigate in this work is how to navigate recordings that are days or even months in duration. We introduce a method of zooming through multiple temporal scales, analogous to Google Maps. However, the “landscape” to be navigated is not geographical and not therefore intrinsically visual, but rather a graphical representation of the underlying audio. We describe solutions to navigating spectrograms that range over three orders of magnitude of temporal scale. We make three sets of observations: 1. We determine that at least ten intermediate scale steps are required to zoom over three orders of magnitude of temporal scale; 2. We determine that three different visual representations are required to cover the range of temporal scales; 3. We present a solution to the problem of maintaining visual continuity when stepping between different visual representations. Finally, we demonstrate the utility of the approach with four case studies.

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Most information in linkage analysis for quantitative traits comes from pairs of relatives that are phenotypically most discordant or concordant. Confounding this, within-family outliers from non-genetic causes may create false positives and negatives. We investigated the influence of within-family outliers empirically, using one of the largest genome-wide linkage scans for height. The subjects were drawn from Australian twin cohorts consisting of 8447 individuals in 2861 families, providing a total of 5815 possible pairs of siblings in sibships. A variance component linkage analysis was performed, either including or excluding the within-family outliers. Using the entire dataset, the largest LOD scores were on chromosome 15q (LOD 2.3) and 11q (1.5). Excluding within-family outliers increased the LOD score for most regions, but the LOD score on chromosome 15 decreased from 2.3 to 1.2, suggesting that the outliers may create false negatives and false positives, although rare alleles of large effect may also be an explanation. Several regions suggestive of linkage to height were found after removing the outliers, including 1q23.1 (2.0), 3q22.1 (1.9) and 5q32 (2.3). We conclude that the investigation of the effect of within-family outliers, which is usually neglected, should be a standard quality control measure in linkage analysis for complex traits and may reduce the noise for the search of common variants of modest effect size as well as help identify rare variants of large effect and clinical significance. We suggest that the effect of within-family outliers deserves further investigation via theoretical and simulation studies.

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Migraine is a common neurovascular brain disorder that is manifested in recurrent episodes of disabling headache. The aim of the present study was to compare the prevalence and heritability of migraine across six of the countries that participate in GenomEUtwin project including a total number of 29,717 twin pairs. Migraine was assessed by questionnaires that differed between most countries. It was most prevalent in Danish and Dutch females (32% and 34%, respectively), whereas the lowest prevalence was found in the younger and older Finnish cohorts (13% and 10%, respectively). The estimated genetic variance (heritability) was significant and the same between sexes in all countries. Heritability ranged from 34% to 57%, with lowest estimates in Australia, and highest estimates in the older cohort of Finland, the Netherlands, and Denmark. There was some indication that part of the genetic variance was non-additive, but this was significant in Sweden only. In addition to genetic factors, environmental effects that are non-shared between members of a twin pair contributed to the liability of migraine. After migraine definitions are homogenized among the participating countries, the GenomEUtwin project will provide a powerful resource to identify the genes involved in migraine.

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Inorganic–organic clays (IOCs), clays intercalated with both organic cations such as cationic surfactants and inorganic cations such as metal hydroxy polycations have the properties of both organic and pillared clays, and thereby the ability to remove both inorganic and organic contaminants from water simultaneously. In this study, IOCs were synthesised using three different methods with different surfactant concentrations. Octadecyltrimethylammonium bromide (ODTMA) and hydroxy aluminium ([Al13O4 (OH)24(H2O)12]7+ or Al13) are used as the organic and inorganic modifiers (intercalation agents). According to the results, the interlayer distance, the surfactant loading amount and the Al/Si ratio of IOCs strictly depend on the intercalation method and the intercalation agent ratio. Interlayers of IOCs synthesised by intercalating ODTMA before Al13 and IOCs synthesised by simultaneous intercalation of ODTMA and Al13 were increased with increasing the ODTMA concentration used in the synthesis procedure and comparatively high loading amounts could be observed in them. In contrast, Al/Si decreased with increasing ODTMA concentration in these two types of IOCs. The results suggest that Al-pillars can be fixed within the interlayers by calcination and any increment in the amount of ODTMA used in the synthesis procedure did not affect the interlayer distance of the IOCs. Overall the study provides valuable insights into the structure and properties of the IOCs and their potential environmental applications.

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Research in organizational psychology has increasingly focused on understanding the determinants of "green" employee behavior. The present study used a daily diary design to investigate relationships between employees' daily affect, pro-environmental attitude, as well as daily task-related pro-environmental behavior (i.e., the extent to which employees complete required work tasks in environmentally friendly ways), and daily proactive pro-environmental behavior (i.e., the extent to which employees show personal initiative when acting in environmentally friendly ways at work). Fifty-six employees working in small businesses completed a baseline survey and two daily surveys over ten workdays. Daily unactivated positive affect and pro-environmental attitude positively predicted daily task-related pro-environmental behavior. In addition, daily activated positive affect positively predicted daily proactive pro-environmental behavior among employees with a less positive pro-environmental attitude but not among employees with a more positive pro-environmental attitude. These findings suggest that fostering pro-environmental attitudes and, to some extent, positive affect among employees could help organizations to promote pro-environmental behavior in the workplace.

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In their call to action, Ones and Dilchert(2012) discuss several possible individual and some contextual determinants of employee green behavior that await examination by industrial and organizational I–O) psychologists. Although these authors briefly mentioned organizational climate, specifically ethical climate, as a potentially relevant predictor of green behaviors, they mostly emphasized the role of individual difference characteristics and traditional job performance determinants such as knowledge, skills, abilities, and other person factors (KSAOs).