526 resultados para Fertilizer application


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Study/Objective This research examines the types of emergency messages used in Australia during the response and early recovery phases of a natural disaster. The aim of the research is to develop theory-driven emergency messages that increase individual behavioural compliance during a disaster. Background There is growing evidence of non-compliant behaviour in Australia, such as refusing to evacuate and travelling through hazardous areas. This can result in personal injury, loss of life, and damage to (or loss of) property. Moreover, non-compliance can place emergency services personnel in life-threatening situations when trying to save non-compliant individuals. Drawing on message compliance research in psychology and sociology, a taxonomy of message types was developed to ascertain how emergency messaging can be improved to produce compliant behaviour. Method A review of message compliance literature was conducted to develop the taxonomy of message types previously found to achieve compliance. Seven categories were identified: direct-rational, manipulation, negative phrasing, positive phrasing, exchange appeals, normative appeals, and appeals to self. A content analysis was then conducted to assess the emergency messages evident in the Australian emergency management context. The existing messages were aligned with the literature to identify opportunities to improve emergency messaging. Results & Conclusion The results suggest there is an opportunity to improve the effectiveness of emergency messaging to increase compliance during the response and early recovery phases of a natural disaster. While some message types cannot legally or ethically be used in emergency communication (e.g. manipulative messaging), there is an opportunity to create more persuasive messages (e.g. appeals to self) that personalise the individual’s perception of risk, triggering them to comply with the message.

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Diabetic macular edema (DME) is one of the most common causes of visual loss among diabetes mellitus patients. Early detection and successive treatment may improve the visual acuity. DME is mainly graded into non-clinically significant macular edema (NCSME) and clinically significant macular edema according to the location of hard exudates in the macula region. DME can be identified by manual examination of fundus images. It is laborious and resource intensive. Hence, in this work, automated grading of DME is proposed using higher-order spectra (HOS) of Radon transform projections of the fundus images. We have used third-order cumulants and bispectrum magnitude, in this work, as features, and compared their performance. They can capture subtle changes in the fundus image. Spectral regression discriminant analysis (SRDA) reduces feature dimension, and minimum redundancy maximum relevance method is used to rank the significant SRDA components. Ranked features are fed to various supervised classifiers, viz. Naive Bayes, AdaBoost and support vector machine, to discriminate No DME, NCSME and clinically significant macular edema classes. The performance of our system is evaluated using the publicly available MESSIDOR dataset (300 images) and also verified with a local dataset (300 images). Our results show that HOS cumulants and bispectrum magnitude obtained an average accuracy of 95.56 and 94.39 % for MESSIDOR dataset and 95.93 and 93.33 % for local dataset, respectively.

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A new database called the World Resource Table is constructed in this study. Missing values are known to produce complications when constructing global databases. This study provides a solution for applying multiple imputation techniques and estimates the global environmental Kuznets curve (EKC) for CO2, SO2, PM10, and BOD. Policy implications for each type of emission are derived based on the results of the EKC using WRI. Finally, we predicted the future emissions trend and regional share of CO2 emissions. We found that East Asia and South Asia will be increasing their emissions share while other major CO2 emitters will still produce large shares of the total global emissions.

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The motivation for this analysis is the recently developed Excellence in Research for Australia (ERA) program developed to assess the quality of research in Australia. The objective is to develop an appropriate empirical model that better represents the underlying production of higher education research. In general, past studies on university research performance have used standard DEA models with some quantifiable research outputs. However, these suffer from the twin maladies of an inappropriate production specification and a lack of consideration of the quality of output. By including the qualitative attributes of peer-reviewed journals, we develop a procedure that captures both quality and quantity, and apply it using a network DEA model. Our main finding is that standard DEA models tend to overstate the research efficiency of most Australian universities.

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Despite the extent of works done on modelling port water collisions, not much research effort has been devoted to modelling collisions at port anchorages. This paper aims to fill this important gap in literature by applying the Navigation Traffic Conflict Technique (NTCT) for measuring the collision potentials in anchorages and for examining the factors contributing to collisions. Grounding on the principles of the NTCT, a collision potential measurement model and a collision potential prediction model were developed. These models were illustrated by using vessel movement data of the anchorages in Singapore port waters. Results showed that the measured collision potentials are in close agreement with those perceived by harbour pilots. Higher collision potentials were found in anchorages attached to shoreline and international fairways, but not at those attached to confined water. Higher operating speeds, larger numbers of isolated danger marks and day conditions were associated with reduction in the collision potentials.

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Background People with intellectual disabilities (ID) have lower levels of physical activity and quality of life and they have a lot of barriers to face when taking part in physical activity. Other problems are the poor adherence to physical activity such people have so this study is designed to improve adherence to physical activity for people with intellectual disabilities with the assistance of an application for smartphones. The aim of the study will be to improve physical activity and physical condition after multimodal intervention and to analyse the promotion of adherence to physical activity through a multimodal intervention and an app intervention (mHealth) in people with ID. Methods A two-stage study will be conducted. In stage 1 a multimodal intervention will take place will be done with physical activity and educational advice over eight weeks, two days a week. Data will be measured after and before the intervention. In stage 2 a randomized controlled trial will be conducted. In the intervention group we will install an application to a smartphone; this application will be a reminder to do a physical activity and they have to select whether they have or haven’t done a physical activity every day. This application will be installed for 18 weeks. Data will be measured after and before the application is installed in two groups. We will measure results 10 weeks later when the two groups don’t have the reminder. The principal outcome used to measure the adherence to physical activity will be the International Physical Activity Questionnaire; secondary outcomes will be a fun-fitness test and self-report survey about quality of life, self-efficacy and social support. Samples will be randomized by sealed envelope in two groups, with approximately 20 subjects in each group. It’s important to know that the therapist will be blinded and won’t know the subjects of each group. Discussion Offering people with ID a multimodal intervention and tool to increase the adherence to a physical activity may increase the levels of physical activity and quality of life. Such a scheme, if beneficial, could be implemented successfully within public health sense. Trial registration ClinicalTrials.gov Identifier: NCT01915381.

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In structural brain MRI, group differences or changes in brain structures can be detected using Tensor-Based Morphometry (TBM). This method consists of two steps: (1) a non-linear registration step, that aligns all of the images to a common template, and (2) a subsequent statistical analysis. The numerous registration methods that have recently been developed differ in their detection sensitivity when used for TBM, and detection power is paramount in epidemological studies or drug trials. We therefore developed a new fluid registration method that computes the mappings and performs statistics on them in a consistent way, providing a bridge between TBM registration and statistics. We used the Log-Euclidean framework to define a new regularizer that is a fluid extension of the Riemannian elasticity, which assures diffeomorphic transformations. This regularizer constrains the symmetrized Jacobian matrix, also called the deformation tensor. We applied our method to an MRI dataset from 40 fraternal and identical twins, to revealed voxelwise measures of average volumetric differences in brain structure for subjects with different degrees of genetic resemblance.

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To understand factors that affect brain connectivity and integrity, it is beneficial to automatically cluster white matter (WM) fibers into anatomically recognizable tracts. Whole brain tractography, based on diffusion-weighted MRI, generates vast sets of fibers throughout the brain; clustering them into consistent and recognizable bundles can be difficult as there are wide individual variations in the trajectory and shape of WM pathways. Here we introduce a novel automated tract clustering algorithm based on label fusion - a concept from traditional intensity-based segmentation. Streamline tractography generates many incorrect fibers, so our top-down approach extracts tracts consistent with known anatomy, by mapping multiple hand-labeled atlases into a new dataset. We fuse clustering results from different atlases, using a mean distance fusion scheme. We reliably extracted the major tracts from 105-gradient high angular resolution diffusion images (HARDI) of 198 young normal twins. To compute population statistics, we use a pointwise correspondence method to match, compare, and average WM tracts across subjects. We illustrate our method in a genetic study of white matter tract heritability in twins.

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We present global and regional rates of brain atrophy measured on serially acquired Tl-weighted brain MR images for a group of Alzheimer's disease (AD) patients and age-matched normal control (NC) subjects using the analysis procedure described in Part I. Three rates of brain atrophy: the rate of atrophy in the cerebrum, the rate of lateral ventricular enlargement and the rate of atrophy in the region of temporal lobes, were evaluated for 14 AD patients and 14 age-matched NC subjects. All three rates showed significant differences between the two groups. However, the greatest separation of the two groups was obtained when the regional rates were combined. This application has demonstrated that rates of brain atrophy, especially in specific regions of the brain, based on MR images can provide sensitive measures for evaluating the progression of AD. These measures will be useful for the evaluation of therapeutic effects of novel therapies for AD.

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The thiol-disulfide oxidoreductase enzyme DsbA catalyzes the formation of disulfide bonds in the periplasm of Gram-negative bacteria. DsbA substrates include proteins involved in bacterial virulence. In the absence of DsbA, many of these proteins do not fold correctly, which renders the bacteria avirulent. Thus DsbA is a critical mediator of virulence and inhibitors may act as antivirulence agents. Biophysical screening has been employed to identify fragments that bind to DsbA from Escherichia coli. Elaboration of one of these fragments produced compounds that inhibit DsbA activity in vitro. In cell-based assays, the compounds inhibit bacterial motility, but have no effect on growth in liquid culture, which is consistent with selective inhibition of DsbA. Crystal structures of inhibitors bound to DsbA indicate that they bind adjacent to the active site. Together, the data suggest that DsbA may be amenable to the development of novel antibacterial compounds that act by inhibiting bacterial virulence.

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Biophilic urbanism, or urban design which refl ects human’s innate need for nature in and around and on top of our buildings, stands to make signifi cant contributions to a range of national, state and local government policies related to climate change mitigation and adaptation. Potential benefi ts include reducing the heat island effect, reducing energy consumption for thermal control, enhancing urban biodiversity, improving well being and productivity, improving water cycle management, and assisting in the response to growing needs for densifi cation and revitalisation of cities. This discussion paper will give an overview of the concept of biophilia and consider enablers and disablers to its application to urban planning and design. The paper will present findings from stakeholder engagement related to a consideration of the economics of the use of biophilic elements (direct and indirect). The paper outlines eight strategic areas being considered in the project, including how a ‘daily minimum dose’ of nature can be received through biophilic elements, and how planning and policy can underpin effective biophilic urbanism.

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In this study, effects of concentrations of Cu(II), Zn(II) and Sn(II) ions in the electrolytic bath solution on the properties of electrochemically deposited CuZnSn (CZT) films were investigated. Study of the composition of a CZT film has shown that the metallic content (relative atomic ratio) in the film increased linearly with increase in the metal ion concentration. It is the first time that the relationship of the compositions of the alloy phases in the co-electrodeposited CZT film with the concentration of metal ions has been revealed. The results have confirmed that the formation and content of Cu6Sn5 and Cu5Zn8 alloy phases in the film were directly controlled by the concentration of Cu(II). SEM measurements have shown that Sn(II) has significant impact on film morphology, which became more porous as a result of the larger nucleation size of tin. The changes in the surface properties of the films was also confirmed by chronoamperometry characteristic (i–t) deposition curves. By optimization of metal ion concentrations in the electrolyte solution, a copper-poor and zinc-rich kesterite Cu2ZnSnS4 (CZTS) film was synthesized by the sulfurization of the deposited CZT film. The solar cell with the CZTS film showed an energy conversion efficiency of 2.15% under the illumination intensity of 100 mW cm 2.