804 resultados para ODOR DISCRIMINATION
Resumo:
This paper reports on a mixed-methods study of social exclusion experiences among 233 resettled refugees living in urban and regional Queensland, Australia. The findings reported here are drawn from the SettleMEN project, a longitudinal investigation of health and settlement experiences among recently arrived adult men from refugee backgrounds conducted between 2008 and 2010. Using questionnaire surveys and semi-structured interviews, we examine four key dimensions of social exclusion: production, consumption, social relations, and services. We show that, overall, participants experienced high levels of social exclusion across all four dimensions. Participants living in regional areas were significantly more likely to be excluded from production, social relations, and services. We argue that there is a pressing need to tackle barriers to economic participation and discrimination in order to promote the social inclusion of men from refugee backgrounds.
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Milk proteins are susceptible to chemical changes during processing and storage. We used proteomic tools to analyse bovine αS1-casein in UHT milk. 2-D gels of freshly processed milk αS1-casein was presented as five or more spots due to genetic polymorphism and variable phosphorylation. MS analysis after phosphopeptide enrichment allowed discrimination between phosphorylation states and genetic variants. We identified a new alternatively-spliced isoform with a deletion of exon 17, producing a new C-terminal sequence, K164SQVNSEGLHSYGL177, with a novel phosphorylation site at S174. Storage of UHT milk at elevated temperatures produced additional, more acidic αS1-casein spots on the gels and decreased the resolution of minor forms. MS analysis indicated that non-enzymatic deamidation and loss of the N-terminal dipeptide were the major contributors to the changing spot pattern. These results highlight the important role of storage temperature in the stability of milk proteins and the utility of proteomic techniques for analysis of proteins in food.
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Construction sites around the world employ large numbers of people from diverse cultural backgrounds. The effective management of this cultural diversity has important implications for the productivity, safety, health and welfare of construction workers and for the performance and reputation of firms which employ them. The findings of a three year, multi-staged study of cultural diversity management practices on construction sites are critiqued using social identity theory. This reveals that so called "best-practice" diversity management strategies may have an opposite effect to that intended. It is concluded that the management of diversity on construction projects would benefit from being informed by social identity research.
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Issues in Green Criminology: confronting harms against environments, humanity and other animals aims to provide, if not a manifesto, then at least a significant resource for thinking about green criminology, a rapidly developing field. It offers a set of specially written introductions and a variety of current and new directions, wide-ranging in scope and international in terms of coverage and contributors. It provides focused discussions of current and cutting edge issues that will influence the emergence of a coherent perspective on green issues. The contributors are drawn from the leading thinkers in the field. The twelve chapters of the book explore the myriad ways in which governments, transnational corporations, military apparatuses and ordinary people going about their everyday lives routinely harm environments, other animals and humanity. The book will be essential reading not only for students taking courses in colleges and universities but also for activists in the environmental and animal rights movements. Its concern is with an ever-expanding agenda - the whys, the hows and the whens of the generation and control of the many aspects of harm to environments, ecological systems and all species of animals, including humans. These harms include, but are not limited to, exploitation, modes of discrimination and disempowerment, degradation, abuse, exclusion, pain, injury, loss and suffering. Straddling and intersecting these many forms of harm are key concepts for a green criminology such as gender inequalities, racism, dominionism and speciesism, classism, the north/south divide, the accountability of science, and the ethics of global capitalist expansion. Green criminology has the potential to provide not only a different way of examining and making sense of various forms of crime and control responses (some well known, others less so) but can also make explicable much wider connections that are not generally well understood. As all societies face up to the need to confront harms against environments, other animals and humanity, criminology will have a major role to play. This book will be an essential part of this process.
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Stromatolites consist primarily of trapped and bound ambient sediment and/or authigenic mineral precipitates, but discrimination of the two constituents is difficult where stromatolites have a fine texture. We used laser ablation-inductively coupled plasma-mass spectrometry to measure trace element (rare earth element – REE, Y and Th) concentrations in both stromatolites (domical and branched) and closely associated particulate carbonate sediment in interspaces (spaces between columns or branches) from bioherms within the Neoproterozoic Bitter Springs Formation, central Australia. Our high resolution sampling allows discrimination of shale-normalised REE patterns between carbonate in stromatolites and immediately adjacent, fine-grained ambient particulate carbonate sediment from interspaces. Whereas all samples show similar negative La and Ce anomalies, positive Gd anomalies and chondritic Y/Ho ratios, the stromatolites and non-stromatolite sediment are distinguishable on the basis of consistently elevated light REEs (LREEs) in the stromatolitic laminae and relatively depleted LREEs in the particulate sediment samples. Additionally, concentrations of the lithophile element Th are higher in ambient sediment samples than in stromatolites, consistent with accumulation of some fine siliciclastic detrital material in the ambient sediment but a near absence in the stromatolites. These findings are consistent with the stromatolites consisting dominantly of in situ carbonate precipitates rather than trapped and bound ambient sediment. Hence, high resolution trace element (REE + Y, Th) geochemistry can discriminate fine-grained carbonates in these stromatolites from coeval non-stromatolitic carbonate sediment and demonstrates that the sampled stromatolites formed primarily from in situ precipitation, presumably within microbial mats/biofilms, rather than by trapping and binding of ambient sediment. Identification of the source of fine carbonate in stromatolites is significant, because if it is not too heavily contaminated by trapped ambient sediment, it may contain geochemical biosignatures and/or direct evidence of the local water chemistry in which the precipitates formed.
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This report presents an analysis of quantitative data collected from the Australian Human Rights Commission, the Anti-Discrimination Commission of Queensland, the Victorian Equal Opportunity and Human Rights Commission, the Anti-Discrimination Board of New South Wales, the Equal Opportunity Commission of South Australia, the Australian Capital Territory Human Rights Commission, the Equal Opportunity Commission Western Australia, the Northern Territory Anti-Discrimination Commission, and the Office of the Anti-Discrimination Commissioner (Tasmania) (hereafter referred to as the Commissions). The data comprise formal complaints lodged under the various federal, state and territory anti-discrimination laws in the period 1 July 2009 to 31 December 2009 where a complainant had alleged sexual harassment in the area of employment.
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Facial expression is an important channel of human social communication. Facial expression recognition (FER) aims to perceive and understand emotional states of humans based on information in the face. Building robust and high performance FER systems that can work in real-world video is still a challenging task, due to the various unpredictable facial variations and complicated exterior environmental conditions, as well as the difficulty of choosing a suitable type of feature descriptor for extracting discriminative facial information. Facial variations caused by factors such as pose, age, gender, race and occlusion, can exert profound influence on the robustness, while a suitable feature descriptor largely determines the performance. Most present attention on FER has been paid to addressing variations in pose and illumination. No approach has been reported on handling face localization errors and relatively few on overcoming facial occlusions, although the significant impact of these two variations on the performance has been proved and highlighted in many previous studies. Many texture and geometric features have been previously proposed for FER. However, few comparison studies have been conducted to explore the performance differences between different features and examine the performance improvement arisen from fusion of texture and geometry, especially on data with spontaneous emotions. The majority of existing approaches are evaluated on databases with posed or induced facial expressions collected in laboratory environments, whereas little attention has been paid on recognizing naturalistic facial expressions on real-world data. This thesis investigates techniques for building robust and high performance FER systems based on a number of established feature sets. It comprises of contributions towards three main objectives: (1) Robustness to face localization errors and facial occlusions. An approach is proposed to handle face localization errors and facial occlusions using Gabor based templates. Template extraction algorithms are designed to collect a pool of local template features and template matching is then performed to covert these templates into distances, which are robust to localization errors and occlusions. (2) Improvement of performance through feature comparison, selection and fusion. A comparative framework is presented to compare the performance between different features and different feature selection algorithms, and examine the performance improvement arising from fusion of texture and geometry. The framework is evaluated for both discrete and dimensional expression recognition on spontaneous data. (3) Evaluation of performance in the context of real-world applications. A system is selected and applied into discriminating posed versus spontaneous expressions and recognizing naturalistic facial expressions. A database is collected from real-world recordings and is used to explore feature differences between standard database images and real-world images, as well as between real-world images and real-world video frames. The performance evaluations are based on the JAFFE, CK, Feedtum, NVIE, Semaine and self-collected QUT databases. The results demonstrate high robustness of the proposed approach to the simulated localization errors and occlusions. Texture and geometry have different contributions to the performance of discrete and dimensional expression recognition, as well as posed versus spontaneous emotion discrimination. These investigations provide useful insights into enhancing robustness and achieving high performance of FER systems, and putting them into real-world applications.
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Structural health monitoring (SHM) refers to the procedure used to assess the condition of structures so that their performance can be monitored and any damage can be detected early. Early detection of damage and appropriate retrofitting will aid in preventing failure of the structure and save money spent on maintenance or replacement and ensure the structure operates safely and efficiently during its whole intended life. Though visual inspection and other techniques such as vibration based ones are available for SHM of structures such as bridges, the use of acoustic emission (AE) technique is an attractive option and is increasing in use. AE waves are high frequency stress waves generated by rapid release of energy from localised sources within a material, such as crack initiation and growth. AE technique involves recording these waves by means of sensors attached on the surface and then analysing the signals to extract information about the nature of the source. High sensitivity to crack growth, ability to locate source, passive nature (no need to supply energy from outside, but energy from damage source itself is utilised) and possibility to perform real time monitoring (detecting crack as it occurs or grows) are some of the attractive features of AE technique. In spite of these advantages, challenges still exist in using AE technique for monitoring applications, especially in the area of analysis of recorded AE data, as large volumes of data are usually generated during monitoring. The need for effective data analysis can be linked with three main aims of monitoring: (a) accurately locating the source of damage; (b) identifying and discriminating signals from different sources of acoustic emission and (c) quantifying the level of damage of AE source for severity assessment. In AE technique, the location of the emission source is usually calculated using the times of arrival and velocities of the AE signals recorded by a number of sensors. But complications arise as AE waves can travel in a structure in a number of different modes that have different velocities and frequencies. Hence, to accurately locate a source it is necessary to identify the modes recorded by the sensors. This study has proposed and tested the use of time-frequency analysis tools such as short time Fourier transform to identify the modes and the use of the velocities of these modes to achieve very accurate results. Further, this study has explored the possibility of reducing the number of sensors needed for data capture by using the velocities of modes captured by a single sensor for source localization. A major problem in practical use of AE technique is the presence of sources of AE other than crack related, such as rubbing and impacts between different components of a structure. These spurious AE signals often mask the signals from the crack activity; hence discrimination of signals to identify the sources is very important. This work developed a model that uses different signal processing tools such as cross-correlation, magnitude squared coherence and energy distribution in different frequency bands as well as modal analysis (comparing amplitudes of identified modes) for accurately differentiating signals from different simulated AE sources. Quantification tools to assess the severity of the damage sources are highly desirable in practical applications. Though different damage quantification methods have been proposed in AE technique, not all have achieved universal approval or have been approved as suitable for all situations. The b-value analysis, which involves the study of distribution of amplitudes of AE signals, and its modified form (known as improved b-value analysis), was investigated for suitability for damage quantification purposes in ductile materials such as steel. This was found to give encouraging results for analysis of data from laboratory, thereby extending the possibility of its use for real life structures. By addressing these primary issues, it is believed that this thesis has helped improve the effectiveness of AE technique for structural health monitoring of civil infrastructures such as bridges.
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In this work, a Langevin dynamics model of the diffusion of water in articular cartilage was developed. Numerical simulations of the translational dynamics of water molecules and their interaction with collagen fibers were used to study the quantitative relationship between the organization of the collagen fiber network and the diffusion tensor of water in model cartilage. Langevin dynamics was used to simulate water diffusion in both ordered and partially disordered cartilage models. In addition, an analytical approach was developed to estimate the diffusion tensor for a network comprising a given distribution of fiber orientations. The key findings are that (1) an approximately linear relationship was observed between collagen volume fraction and the fractional anisotropy of the diffusion tensor in fiber networks of a given degree of alignment, (2) for any given fiber volume fraction, fractional anisotropy follows a fiber alignment dependency similar to the square of the second Legendre polynomial of cos(θ), with the minimum anisotropy occurring at approximately the magic angle (θMA), and (3) a decrease in the principal eigenvalue and an increase in the transverse eigenvalues is observed as the fiber orientation angle θ progresses from 0◦ to 90◦. The corresponding diffusion ellipsoids are prolate for θ < θMA, spherical for θ ≈ θMA, and oblate for θ > θMA. Expansion of the model to include discrimination between the combined effects of alignment disorder and collagen fiber volume fraction on the diffusion tensor is discussed.
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Here we present a sequential Monte Carlo approach to Bayesian sequential design for the incorporation of model uncertainty. The methodology is demonstrated through the development and implementation of two model discrimination utilities; mutual information and total separation, but it can also be applied more generally if one has different experimental aims. A sequential Monte Carlo algorithm is run for each rival model (in parallel), and provides a convenient estimate of the marginal likelihood (of each model) given the data, which can be used for model comparison and in the evaluation of utility functions. A major benefit of this approach is that it requires very little problem specific tuning and is also computationally efficient when compared to full Markov chain Monte Carlo approaches. This research is motivated by applications in drug development and chemical engineering.
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The paper utilizes the 1989 Labour Market Activity Survey to examine the gender wage differential in Canada. The aim is to update previous studies and extend earlier analysis in two significant ways. First, occupation is treated as endogenously determined. Secondly,the Zabalza and Arrufat(1985) imputation method is utilized to estimate the level of female labour market experience. The results suggest that the level of estimated gender discrimination is sensitive to the measure of labour market experience. The paper also concludes that intra-occupation wage effects explain most of gender wage gap.
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The traditional decomposition of the gender wage gap distinguishes between a component attributable to gender differences in productivity-related characteristics and a residual component that is often taken as a measure of discrimination. This study of data from the 1989 Canadian Labour Market Activity Survey shows that when occupation is treated as a productivity-related characteristic, the proportion of the gender wage gap labeled explained increases with the number of occupational classifications distinguished. However, on the basis of evidence that occupational differences reflect the presence of barriers faced by women attempting to enter male-dominated occupations, the authors conclude that occupation should not be treated as a productivity-related characteristic; and in a decomposition of the gender wage gap that treats occupation as endogenously determined, they find that the level of occupational aggregation has little effect on the size of the "explained" component of the gap.
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This paper attempts, using data from the British Labour Force Survey 1996, to examine to what extent differences in labour market outcomes between able-bodied and disabled men may be attributed to differences in endowments of human capital and associated productivity differences. Both labour force participation and selectivity corrected human capital equations are estimated and decomposition techniques applied to them. Using the methodology of Baldwin and Johnson [Baldwin, M., Johnson, W.G., 1994. Labor market discrimination against men with disabilities. Journal of Human Resources, XXIX(1), Winter, 1–19], the employment effects of wage discrimination against the disabled are also estimated. Evidence of both substantial wage and participation rate differences between able-bodied and disabled men are found, which have implications for the operation of the 1995 Disability Discrimination Act.
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Article XX has been a valuable instrument to justify exceptions from the anti-discrimination provisions of the GATT 1994. In general, this Article is considered by experts to be the most likely defence for any climate change mitigation measure in breach GATT 1994 obligations. That assumption is not in dispute here; rather, this article considers the requirements of the Article XX exceptions, but also explores the conditions of the National Security exception contained in Article XXI. Although it is possible that this exception could be used for climate change mitigation measures, this paper argues that it is unlikely that the National Security exception could be legitimately applied in these circumstances without member agreement to the contrary.
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Making Sense of Mass Education provides a comprehensive analysis of the field of mass education. The book presents new assessment of traditional issues associated with education – class, race, gender, discrimination and equity –to dispel myths and assumptions about the classroom. It examines the complex relationship between the media, popular culture and schooling, and places the expectations surrounding the modern teacher within ethical, legal and historical contexts. The book blurs some of the disciplinary boundaries within the field of education, drawing upon sociology, cultural studies, history, philosophy, ethics and jurisprudence to provide stronger analyses. The book reframes the sociology of education as a complex mosaic of cultural practices, forces and innovations. Engaging and contemporary, it is an invaluable resource for teacher education students, and anyone interested in a better understanding of mass education.