278 resultados para pesticide mixture
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Particulate matter (PM) emissions involve a complex mixture of solid and liquid particles suspended in a gas, where it is noted that PM emissions from diesel engines are a major contributor to the ambient air pollution problem. Whilst epidemiological studies have shown a link between increased ambient PM emissions and respiratory morbidity and mortality, studies of this design are not able to identify the PM constituents responsible for driving adverse respiratory health effects. This review explores in detail the physico-chemical properties of diesel particulate matter (DPM), and identifies the constituents of this pollution source that are responsible for the development of respiratory disease. In particular, this review shows that the DPM surface area and adsorbed organic compounds play a significant role in manifesting chemical and cellular processes that if sustained can lead to the development of adverse respiratory health effects. The mechanisms of injury involved included: inflammation, innate and acquired immunity, and oxidative stress. Understanding the mechanisms of lung injury from DPM will enhance efforts to protect at-risk individuals from the harmful respiratory effects of air pollutants.
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Recent research has described the restructuring of particles upon exposure to organic vapours; however, as yet hypotheses able to explain this phenomenon are limited. In this study, a range of experiments were performed to explore different hypotheses related to carbonaceous particle restructuring upon exposure to organic and water vapours, such as: the effect of surface tension, the role of organics in flocculating primary particles, as well as the ability of vapours to “wet” the particle surface. The change in mobility diameter (dm) was investigated for a range carbonaceous particle types (diesel exhaust, petrol exhaust, cigarette smoke, candle smoke, particles generated in a heptane/toluene flame, and wood smoke particles) exposed to different organic (heptane, ethanol, and dimethyl sulfoxide/water (1:1 vol%) mixture) and water vapours. Particles were first size-selected and then bubbled through an impinger (bubbler) containing either an organic solvent or water, where particles trapped inside rising bubbles were exposed to saturated vapours of the solvent in the impinger. The size distribution of particles was simultaneously measured upstream and downstream from the impinger. A size-dependent reduction in dm was observed when bubbling diesel exhaust, particles generated in a heptane/toluene flame, and candle smoke particles through heptane, ethanol and a dimethyl sulfoxide/water (1:1 vol %) mixture. In addition, the size distributions of particles bubbled through an impinger were broader. Moreover, an increase of the geometric standard deviation (σ) of the size distributions of particles bubbled through an impinger was also found to be size-dependent. Size-dependent reduction in dm and an increase of σ indicate that particles undergo restructuring to a more compact form, which was confirmed by TEM analysis. However, bubbling of these particles through water did not result in a size-dependent reduction in dm, nor in an increase of σ. Cigarette smoke, petrol exhaust, and wood smoke particles did not result in any substantial change in dm, or σ, when bubbled through organic solvents or water. Therefore, size-dependent reduction in the dm upon bubbling through organic solvents was observed only for particles that had a fractal-like structure, whilst particles that were liquid or were assumed to be spherical did not exhibit any reduction in dm. Compaction of fractal-like particles was attributed to the ability of condensing vapours to efficiently wet the particles. Our results also show that the presence of an organic layer on the surface of fractal-like particles, or the surface tension of the condensed liquid do not influence the extent of compaction.
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Background China has one of the highest suicide rates in the world; however, the recent trends in suicide have not been adequately studied. This study aimed to examine the potential changes in the rates and characteristics in a Chinese population. Methods Data on suicide deaths in 1991–2010 were extracted from the Shandong Disease Surveillance Point (DSP) mortality dataset based on ICD-10 codes. The temporal trend in age-adjusted suicide rates for each subpopulation was tested using log-linear Poisson regression analysis. Results From 1991 to 2010, there was a marked decrease in the overall suicide rate in Shandong, with an average reduction of 8% per year. The decrease trend was stronger in rural than in urban areas and more evident in females than in males. Similar decreases were observed for all age groups. Pesticide ingestion and hanging remained the top two methods for suicide. Limitations There are likely quality concerns in the morality data, such as underreporting and misclassification, as well as low accuracy in determining the underlying causes of deaths. The representativeness of the DSP system may also be problematic due to the rapid changes in economy and demography. Conclusions Completed suicides in Shandong have sharply declined over the past 20 years. Higher rates in females versus males and in rural versus urban areas, which were previously considered to be distinguishing features of suicide in China, are becoming less pronounced.
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Vehicle emissions are a significant source of fine particles (Dp < 2.5 µm) in an urban environment. These fine particles have been shown to have detrimental health effects, with children thought to be more susceptible. Vehicle emissions are mainly carbonaceous in nature, and carbonaceous aerosols can be defined as either elemental carbon (EC) or organic carbon (OC). EC is a soot-like material emitted from primary sources while OC fraction is a complex mixture of hundreds of organic compounds from either primary or secondary sources (Cao et al., 2006). Therefore the ratio of OC/EC can aid in the identification of source. The purpose of this paper is to use the concentration of OC and EC in fine particles to determine the levels of vehicle emissions in schools. It is expected that this will improve the understanding of the potential exposure of children in a school environment to vehicle emissions.
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Background. We have characterised a new highly divergent geminivirus species, Eragrostis curvula streak virus (ECSV), found infecting a hardy perennial South African wild grass. ECSV represents a new genus-level geminivirus lineage, and has a mixture of features normally associated with other specific geminivirus genera. Results. Whereas the ECSV genome is predicted to express a replication associated protein (Rep) from an unspliced complementary strand transcript that is most similar to those of begomoviruses, curtoviruses and topocuviruses, its Rep also contains what is apparently a canonical retinoblastoma related protein interaction motif such as that found in mastreviruses. Similarly, while ECSV has the same unusual TAAGATTCC virion strand replication origin nonanucleotide found in another recently described divergent geminivirus, Beet curly top Iran virus (BCTIV), the rest of the transcription and replication origin is structurally more similar to those found in begomoviruses and curtoviruses than it is to those found in BCTIV and mastreviruses. ECSV also has what might be a homologue of the begomovirus transcription activator protein gene found in begomoviruses, a mastrevirus-like coat protein gene and two intergenic regions. Conclusion. Although it superficially resembles a chimaera of geminiviruses from different genera, the ECSV genome is not obviously recombinant, implying that the features it shares with other geminiviruses are those that were probably present within the last common ancestor of these viruses. In addition to inferring how the ancestral geminivirus genome may have looked, we use the discovery of ECSV to refine various hypotheses regarding the recombinant origins of the major geminivirus lineages. © 2009 Varsani et al; licensee BioMed Central Ltd.
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Several approaches have been explored to eradicate HIV; however, a multigene vaccine appears to be the best option, given their proven potential to elicit broad, effective responses in animal models. The Pr55 Gagprotein is an excellent vaccine candidate in its own right, given that it can assemble into large, enveloped, virus-like particles (VLPs) which are highly immunogenic, and can moreover be used as a scaffold for the presentation of other large non-structural HIV antigens. In this study, we evaluated the potential of two novel chimaeric HIV-1 Pr55 Gag-based VLP constructs - C-terminal fusions with reverse transcriptase and a Tat::Nef fusion protein, designated GagRT and GagTN respectively - to enhance a cellular response in mice when used as boost components in two types of heterologous prime-boost vaccine strategies. A vaccine regimen consisting of a DNA prime and chimaeric HIV-1 VLP boosts in mice induced strong, broad cellular immune responses at an optimum dose of 100 ng VLPs. The enhanced cellular responses induced by the DNA prime-VLP boost were two- to three-fold greater than two DNA vaccinations. Moreover, a mixture of GagRT and GagTN VLPs also boosted antigen-specific CD8+ and CD4+ T-cell responses, while VLP vaccinations only induced predominantly robust Gag CD4+ T-cell responses. The results demonstrate the promising potential of these chimaeric VLPs as vaccine candidates against HIV-1. © 2010 Pillay et al; licensee BioMed Central Ltd.
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Airports and cities inevitably recognise the value that each brings the other; however, the separation in decision-making authority for what to build, where, when and how provides a conundrum for both parties. Airports often want a say in what is developed outside of the airport fence, and cities often want a say in what is developed inside the airport fence. Defining how much of a say airports and cities have in decisions beyond their jurisdictional control is likely to be a topic that continues so long as airports and cities maintain separate formal decision-making processes for what to build, where, when and how. However, the recent Green and White Papers for a new National Aviation Policy have made early inroads to formalising relationships between Australia’s major airports and their host cities. At present, no clear indication (within practice or literature) is evident to the appropriateness of different governance arrangements for decisions to develop in situations that bring together the opposing strategic interests of airports and cities; thus leaving decisions for infrastructure development as complex decision-making spaces that hold airport and city/regional interests at stake. The line of enquiry is motivated by a lack of empirical research on networked decision-making domains outside of the realm of institutional theorists (Agranoff & McGuire, 2001; Provan, Fish & Sydow, 2007). That is, governance literature has remained focused towards abstract conceptualisations of organisation, without focusing on the minutia of how organisation influences action in real-world applications. A recent study by Black (2008) has provided an initial foothold for governance researchers into networked decision-making domains. This study builds upon Black’s (2008) work by aiming to explore and understand the problem space of making decisions subjected to complex jurisdictional and relational interdependencies. That is, the research examines the formal and informal structures, relationships, and forums that operationalise debates and interactions between decision-making actors as they vie for influence over deciding what to build, where, when and how in airport-proximal development projects. The research mobilises a mixture of qualitative and quantitative methods to examine three embedded cases of airport-proximal development from a network governance perspective. Findings from the research provide a new understanding to the ways in which informal actor networks underpin and combine with formal decision-making networks to create new (or realigned) governance spaces that facilitate decision-making during complex phases of development planning. The research is timely, and responds well to Isett, Mergel, LeRoux, Mischen and Rethemeyer’s (2011) recent critique of limitations within current network governance literature, specifically to their noted absence of empirical studies that acknowledge and interrogate the simultaneity of formal and informal network structures within network governance arrangements (Isett et al., 2011, pp. 162-166). The combination of social network analysis (SNA) techniques and thematic enquiry has enabled findings to document and interpret the ways in which decision-making actors organise to overcome complex problems for planning infrastructure. An innovative approach to using association networks has been used to provide insights to the importance of the different ways actors interact with one another, thus providing a simple yet valuable addition to the increasingly popular discipline of SNA. The research also identifies when and how different types of networks (i.e. formal and informal) are able to overcome currently known limitations to network governance (see McGuire & Agranoff, 2011), thus adding depth to the emerging body of network governance literature surrounding limitations to network ways of working (i.e. Rhodes, 1997a; Keast & Brown, 2002; Rethemeyer & Hatmaker, 2008; McGuire & Agranoff, 2011). Contributions are made to practice via the provision of a timely understanding of how horizontal fora between airports and their regions are used, particularly in the context of how they reframe the governance of decision-making for airport-proximal infrastructure development. This new understanding will enable government and industry actors to better understand the structural impacts of governance arrangements before they design or adopt them, particularly for factors such as efficiency of information, oversight, and responsiveness to change.
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Pesticide spraying by farmers has an adverse impact on their health. However, in studies to date examining farmers’ exposure to pesticides, the costs of ill health and their determinants have been based on information provided by farmers themselves. Some doubt has therefore been cast on the reliability of these estimates. In this study, we address this by conducting surveys among two groups of farmers who use pesticides on a regular basis. The first group is made up of farmers who perceive that their ill health is due to exposure to pesticides and have obtained at least some form of treatment (described in this article as the ‘general farmer group’). The second group is composed of farmers whose ill health has been diagnosed by doctors and who have been treated in hospital for exposure to pesticides (described here as the ‘hospitalised farmer group’). Cost comparisons are made between the two groups of farmers. Regression analysis of the determinants of health costs show that the most important determinants of medical costs for both samples are the defensive expenditure, the quantity of pesticides used per acre per month, frequency of pesticide use and number of pesticides used per hour per day. The results have important policy implications.
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This paper proposes the use of Bayesian approaches with the cross likelihood ratio (CLR) as a criterion for speaker clustering within a speaker diarization system, using eigenvoice modeling techniques. The CLR has previously been shown to be an effective decision criterion for speaker clustering using Gaussian mixture models. Recently, eigenvoice modeling has become an increasingly popular technique, due to its ability to adequately represent a speaker based on sparse training data, as well as to provide an improved capture of differences in speaker characteristics. The integration of eigenvoice modeling into the CLR framework to capitalize on the advantage of both techniques has also been shown to be beneficial for the speaker clustering task. Building on that success, this paper proposes the use of Bayesian methods to compute the conditional probabilities in computing the CLR, thus effectively combining the eigenvoice-CLR framework with the advantages of a Bayesian approach to the diarization problem. Results obtained on the 2002 Rich Transcription (RT-02) Evaluation dataset show an improved clustering performance, resulting in a 33.5% relative improvement in the overall Diarization Error Rate (DER) compared to the baseline system.
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Readily accepted knowledge regarding crash causation is consistently omitted from efforts to model and subsequently understand motor vehicle crash occurrence and their contributing factors. For instance, distracted and impaired driving accounts for a significant proportion of crash occurrence, yet is rarely modeled explicitly. In addition, spatially allocated influences such as local law enforcement efforts, proximity to bars and schools, and roadside chronic distractions (advertising, pedestrians, etc.) play a role in contributing to crash occurrence and yet are routinely absent from crash models. By and large, these well-established omitted effects are simply assumed to contribute to model error, with predominant focus on modeling the engineering and operational effects of transportation facilities (e.g. AADT, number of lanes, speed limits, width of lanes, etc.) The typical analytical approach—with a variety of statistical enhancements—has been to model crashes that occur at system locations as negative binomial (NB) distributed events that arise from a singular, underlying crash generating process. These models and their statistical kin dominate the literature; however, it is argued in this paper that these models fail to capture the underlying complexity of motor vehicle crash causes, and thus thwart deeper insights regarding crash causation and prevention. This paper first describes hypothetical scenarios that collectively illustrate why current models mislead highway safety researchers and engineers. It is argued that current model shortcomings are significant, and will lead to poor decision-making. Exploiting our current state of knowledge of crash causation, crash counts are postulated to arise from three processes: observed network features, unobserved spatial effects, and ‘apparent’ random influences that reflect largely behavioral influences of drivers. It is argued; furthermore, that these three processes in theory can be modeled separately to gain deeper insight into crash causes, and that the model represents a more realistic depiction of reality than the state of practice NB regression. An admittedly imperfect empirical model that mixes three independent crash occurrence processes is shown to outperform the classical NB model. The questioning of current modeling assumptions and implications of the latent mixture model to current practice are the most important contributions of this paper, with an initial but rather vulnerable attempt to model the latent mixtures as a secondary contribution.
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YBCO wires which consist of well oriented plate-like fine grains are fabricated using a moving furnace to achieve higher mechanical strength. Melt-texturing experiments have been undertaken on YBCO wires with two different compositions: YBa1.5Cu2.9O7-x, and YBa1.8Cu3.0O7-x. Wires are extruded from a mixture of precursor powders (formed by a coprecipitation process) then textured by firing in a moving furnace. Size of secondary phases such as barium cuprate and copper oxide, and overall composition of the sample affect the orientation of the fine grains. At zero magnetic field, the YBa1.5Cu2.9O7-x wire shows the highest critical current density of 1,450 Acm-2 and 8,770 Acm-2 at 77K and 4.2K, respectively. At 1 T, critical current densities of 30 Acm-2 and 200 Acm-2, respectively, are obtained at 77K and 4.2K. Magnetisation curves are also obtained for one sample to evaluate critical current density using the Bean model. Analysis of the microstructure indicates that the starting composition of the green body significantly affects the achievement of grain alignment via melt-texturing processes.
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In the field of face recognition, Sparse Representation (SR) has received considerable attention during the past few years. Most of the relevant literature focuses on holistic descriptors in closed-set identification applications. The underlying assumption in SR-based methods is that each class in the gallery has sufficient samples and the query lies on the subspace spanned by the gallery of the same class. Unfortunately, such assumption is easily violated in the more challenging face verification scenario, where an algorithm is required to determine if two faces (where one or both have not been seen before) belong to the same person. In this paper, we first discuss why previous attempts with SR might not be applicable to verification problems. We then propose an alternative approach to face verification via SR. Specifically, we propose to use explicit SR encoding on local image patches rather than the entire face. The obtained sparse signals are pooled via averaging to form multiple region descriptors, which are then concatenated to form an overall face descriptor. Due to the deliberate loss spatial relations within each region (caused by averaging), the resulting descriptor is robust to misalignment & various image deformations. Within the proposed framework, we evaluate several SR encoding techniques: l1-minimisation, Sparse Autoencoder Neural Network (SANN), and an implicit probabilistic technique based on Gaussian Mixture Models. Thorough experiments on AR, FERET, exYaleB, BANCA and ChokePoint datasets show that the proposed local SR approach obtains considerably better and more robust performance than several previous state-of-the-art holistic SR methods, in both verification and closed-set identification problems. The experiments also show that l1-minimisation based encoding has a considerably higher computational than the other techniques, but leads to higher recognition rates.
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A process for making aluminosilicates of zeolite N structure comprising the steps of: (i) combining a water soluble monovalent cation, a solution of hydroxyl anions and an aluminosilicate to form a resultant mixture having a pH greater than 10 and a H.sub.2O/Al.sub.2O.sub.3 ratio in the range 30 to 220; (ii) heating the resultant mixture to a temperature of between 50.degree. C. and boiling point of the mixture for a time between 1 minute and 100 hours until a crystalline product of zeolite N structure is formed as determined by X-ray diffraction or other suitable characteristic; and (iii) separating the zeolite N product as a solid from the mixture.
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"Seventeen peer-reviewed papers cover the latest research on the ignition and combustion of metals and non-metals, oxygen compatibility of components and systems, analysis of ignition and combustion, failure analysis and safety. It includes aerospace, military, scuba diving, and industrial oxygen applications. Topics cover: • Development of safe oxygen systems • Ignition mechanisms within oxygen systems and how to avoid them • Specific hazards that exist with the oxygen mixture breathed by divers in the scuba industry • Issues related to oxygen system level safety • Issues related to oxygen safety in breathing systems • Detailed investigations and discussions related to the burn curves that have been generated for metals that are burning in a standard test fixture This new publication is a valuable resource for professionals in the air separation industries, oxygen manufacturers, manufacturers of materials intended for oxygen service, and users of oxygen and oxygen-enriched atmospheres, including aerospace, medical, industrial gases, chemical processing, steel and metals refining, as well as to military, commercial or recreational diving."--- publisher website