663 resultados para Response prediction
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This paper examines the impact of allowing for stochastic volatility and jumps (SVJ) in a structural model on corporate credit risk prediction. The results from a simulation study verify the better performance of the SVJ model compared with the commonly used Merton model, and three sources are provided to explain the superiority. The empirical analysis on two real samples further ascertains the importance of recognizing the stochastic volatility and jumps by showing that the SVJ model decreases bias in spread prediction from the Merton model, and better explains the time variation in actual CDS spreads. The improvements are found particularly apparent in small firms or when the market is turbulent such as the recent financial crisis.
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Public acceptance is consistently listed as having an enormous impact on the implementation and success of a congestion charge scheme. This paper investigates public acceptance of such a scheme in Australia. Surveys were conducted in Brisbane and Melbourne, the two fastest growing Australian cities. Using an ordered logit modeling approach, the survey data including stated preferences were analyzed to pinpoint the important factors influencing people’s attitudes to a congestion charge and, in turn, to their transport mode choices. To accommodate the nature of, and to account for the resulting heterogeneity of the panel data, random effects were considered in the models. As expected, this study found that the amount of the congestion charge and the financial benefits of implementing it have a significant influence on respondents’ support for the charge and on the likelihood of their taking a bus to city areas. However, respondents’ current primary transport mode for travelling to the city areas has a more pronounced impact. Meanwhile, respondents’ perceptions of the congestion charge’s role in protecting the environment by reducing vehicle emissions, and of the extent to which the charge would mean that they travelled less frequently to the city for shopping or entertainment, also have a significant impact on their level of support for its implementation. We also found and explained notable differences across two cities. Finally, findings from this study have been fully discussed in relation to the literature.
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This work deals with estimators for predicting when parametric roll resonance is going to occur in surface vessels. The roll angle of the vessel is modeled as a second-order linear oscillatory system with unknown parameters. Several algorithms are used to estimate the parameters and eigenvalues of the system based on data gathered experimentally on a 1:45 scale model of a tanker. Based on the estimated eigenvalues, the system predicts whether or not parametric roll occurred. A prediction accuracy of 100% is achieved for regular waves, and up to 87.5% for irregular waves.
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Complex behaviour of air flow in the buildings makes it difficult to predict. Consequently, architects use common strategies for designing buildings with adequate natural ventilation. However, each climate needs specific strategies and there are not many heuristics for subtropical climate in literature. Furthermore, most of these common strategies are based on low-rise buildings and their performance for high-rise buildings might be different due to the increase of the wind speed with increase in the height. This study uses Computational Fluid Dynamics (CFD) to evaluate these rules of thumb for natural ventilation for multi-residential buildings in subtropical climate. Four design proposals for multi-residential towers with natural ventilation which were produced in intensive two days charrette were evaluated using CFD. The results show that all the buildings reach acceptable level of wind speed in living areas and poor amount of air flow in sleeping areas.
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This study developed an understanding of hydrological processes within the Cressbrook Creek catchment of the upper Brisbane River, in particular for the alluvial aquifers. Those aquifers within the lower catchment are used for intensive irrigation, and have been impacted by long-term drought followed by flooding. The study utilised water chemistry, isotopic characters and hydraulic measurements to determine factors such as recharge, links between creeks and groundwater, and variations in water quality. The catchment-wide study will enable improved management of the local water resources.
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CONTEXT AND OBJECTIVE: Suboptimal vitamin D status can be corrected by vitamin D supplementation, but individual responses to supplementation vary. We aimed to examine genetic and nongenetic determinants of change in serum 25-hydroxyvitamin D (25(OH)D) after supplementation. DESIGN AND PARTICIPANTS: We used data from a pilot randomized controlled trial in which 644 adults aged 60 to 84 years were randomly assigned to monthly doses of placebo, 30 000 IU, or 60 000 IU vitamin D3 for 12 months. Baseline characteristics were obtained from a self-administered questionnaire. Eighty-eight single-nucleotide polymorphisms (SNPs) in 41 candidate genes were genotyped using Sequenom MassArray technology. Serum 25(OH)D levels before and after the intervention were measured using the Diasorin Liaison platform immunoassay. We used linear regression models to examine associations between genetic and nongenetic factors and change in serum 25(OH)D levels. RESULTS: Supplement dose and baseline 25(OH)D level explained 24% of the variability in response to supplementation. Body mass index, self-reported health status, and ambient UV radiation made a small additional contribution. SNPs in CYP2R1, IRF4, MC1R, CYP27B1, VDR, TYRP1, MCM6, and HERC2 were associated with change in 25(OH)D level, although only CYP2R1 was significant after adjustment for multiple testing. Models including SNPs explained a similar proportion of variability in response to supplementation as models that included personal and environmental factors. CONCLUSION: Stepwise regression analyses suggest that genetic variability may be associated with response to supplementation, perhaps suggesting that some people might need higher doses to reach optimal 25(OH)D levels or that there is variability in the physiologically normal level of 25(OH)D.
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In recent years, research aimed at identifying and relating the antecedents and consequences of diffusing organizational practices/ideas has turned its attention to debating the international adoption and implementation of the Anglo-American model of corporate governance, i.e., a shareholder-value-orientation (SVO). While financial economists characterize the adoption of an SVO as necessary and performance-enhancing, behavioral scientists have disputed such claims, invoking institutional contingencies in the appropriateness of an SVO. Our study seeks to provide some resolution to the debate by developing an overarching socio-political perspective that links the antecedents and consequences of the adoption of the contested practice of SVO. We test our framework using extensive longitudinal data from 1992-2006 from the largest listed corporations in the Netherlands, and we find a negative relationship between SVO adoption and subsequent firm performance, although this effect is attenuated when accompanied by greater SVO-alignment among major owners and a firm’s visible commitment to an SVO. This study extends prior research on the diffusion of contested organizational practices that has taken a socio-political perspective by offering an original contingency perspective that addresses how and why the misaligned preferences of corporate owners will affect (i) a company’s inclination to espouse an SVO, and (ii) the performance consequences of such misalignment.This study suggests when board members are considering the adoption of new ideas/practices (e.g., SVO), they should consider the contextual fitness of the idea/practice with the firm’s owners and their interests.
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This thesis aimed at identifying cytokine markers associated with chlamydial infection and disease in koalas which is facing many threats to its survival, Chlamydia pecorum infections being a major one. To identify immunological markers associated with chlamydial infection and disease in koalas, key cytokines such as TNF alpha, IL10, IFN gamma and IL17A were cloned and sequenced and subsequently developed Quantitative Real Time PCR (qrtPCR) assays. The thesis provides preliminary data on the role of these cytokines in koala chlamydial disease and further longitudinal studies are required to confirm the role played by cytokines in pathology and protection against C. pecorum infection in the koala.
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This thesis explored how biophilic urbanism, or the integration of natural features into increasingly dense urban environments, has become mainstream in cities around the world. Fourteen factors uncovered through a case study investigation provide insight for decision makers and change agents in Australia to use biophilic urbanism to address impacts of population growth, climate change and resource shortages. The thesis uses an inductive research approach to explore how barriers to the integration of multi-functional vegetated and water design elements into the built environment, such that these become and standard inclusions in urban design and development processes.
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This research treated the response of underground transportation tunnels to surface blast loads using advanced computer simulation techniques. The influences of important parameters, such as tunnel material, geometrical configuration of segments and surrounding soil were investigated. The findings of this research offer significant new information on the blast performance of underground tunnels and will contribute towards future civil engineering applications.
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A framework supporting the systematic development of safety cases for Unmanned Aircraft System (UAS) operations in a broad range of civil and commercial applications is presented. The case study application is the use of UAS for disaster response. In those States where regulations do not preclude UAS operations altogether, approvals for UAS operations can be granted on a case-by-case basis contingent on the provision of a safety case acceptable to the relevant National Airworthiness Authority (NAA). A safety case for UAS operations must show how the risks associated with the hazards have been managed to an acceptable level. The foundational components necessary for structuring and assessing these safety cases have not yet been proposed. Barrier-bow-tie models are used in this paper to structure the safety case for the two primary hazards of 1) a ground impact, and 2) a Mid-Air Collision (MAC). The models establish the set of Risk Control Variables (RCVs) available to reduce the risk. For the ground-impact risk model, seven RCVs are identified which in combination govern the probability of an accident. Similarly, ten RCVs are identified within the MAC model. The effectiveness of the RCVs and how they can implemented in terms of processes, policies, devices, practices, or other actions for each of the case-study applications are discussed. The framework presented can provide for the more systematic and consistent regulation of UAS through a "safety target" approach.
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Enhancing quality of food products and reducing volume of waste during mechanical operations of food industry requires a comprehensive knowledge of material response under loadings. While research has focused on mechanical response of food material, the volume of waste after harvesting and during processing stages is still considerably high in both developing and developed countries. This research aims to develop and evaluate a constitutive model of mechanical response of tough skinned vegetables under postharvest and processing operations. The model focuses on both tensile and compressive properties of pumpkin flesh and peel tissues where the behaviours of these tissues vary depending on various factors such as rheological response and cellular structure. Both elastic and plastic response of tissue were considered in the modelling process and finite elasticity combined with pseudo elasticity theory was applied to generate the model. The outcomes were then validated using the published results of experimental work on pumpkin flesh and peel under uniaxial tensile and compression. The constitutive coefficients for peel under tensile test was α = 25.66 and β = −18.48 Mpa and for flesh α = −5.29 and β = 5.27 Mpa. under compression the constitutive coefficients were α = 4.74 and β = −1.71 Mpa for peel and α = 0.76 and β = −1.86 Mpa for flesh samples. Constitutive curves predicted the values of force precisely and close to the experimental values. The curves were fit for whole stress versus strain curve as well as a section of curve up to bio yield point. The modelling outputs had presented good agreement with the empirical values and the constructive curves exhibited a very similar pattern to the experimental curves. The presented constitutive model can be applied next to other agricultural materials under loading in future.
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Objectives Recent research has shown that machine learning techniques can accurately predict activity classes from accelerometer data in adolescents and adults. The purpose of this study is to develop and test machine learning models for predicting activity type in preschool-aged children. Design Participants completed 12 standardised activity trials (TV, reading, tablet game, quiet play, art, treasure hunt, cleaning up, active game, obstacle course, bicycle riding) over two laboratory visits. Methods Eleven children aged 3–6 years (mean age = 4.8 ± 0.87; 55% girls) completed the activity trials while wearing an ActiGraph GT3X+ accelerometer on the right hip. Activities were categorised into five activity classes: sedentary activities, light activities, moderate to vigorous activities, walking, and running. A standard feed-forward Artificial Neural Network and a Deep Learning Ensemble Network were trained on features in the accelerometer data used in previous investigations (10th, 25th, 50th, 75th and 90th percentiles and the lag-one autocorrelation). Results Overall recognition accuracy for the standard feed forward Artificial Neural Network was 69.7%. Recognition accuracy for sedentary activities, light activities and games, moderate-to-vigorous activities, walking, and running was 82%, 79%, 64%, 36% and 46%, respectively. In comparison, overall recognition accuracy for the Deep Learning Ensemble Network was 82.6%. For sedentary activities, light activities and games, moderate-to-vigorous activities, walking, and running recognition accuracy was 84%, 91%, 79%, 73% and 73%, respectively. Conclusions Ensemble machine learning approaches such as Deep Learning Ensemble Network can accurately predict activity type from accelerometer data in preschool children.
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Spatial variation of seismic ground motions is caused by incoherence effect, wave passage, and local site conditions. This study focuses on the effects of spatial variation of earthquake ground motion on the responses of adjacent reinforced concrete (RC) frame structures. The adjacent buildings are modeled considering soil-structure interaction (SSI) so that the buildings can be interacted with each other under uniform and non-uniform ground motions. Three different site classes are used to model the soil layers of SSI system. Based on fast Fourier transformation (FFT), spatially correlated non-uniform ground motions are generated compatible with known power spectrum density function (PSDF) at different locations. Numerical analyses are carried out to investigate the displacement responses and the absolute maximum base shear forces of adjacent structures subjected to spatially varying ground motions. The results are presented in terms of related parameters affecting the structural response using three different types of soil site classes. The responses of adjacent structures have changed remarkably due to spatial variation of ground motions. The effect can be significant on rock site rather than clay site.
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DNA double-strand breaks (DSBs), which are induced by either endogenous metabolic processes or by exogenous sources, are one of the most critical DNA lesions with respect to survival and preservation of genomic integrity. An early response to the induction of DSBs is phosphorylation of the H2A histone variant, H2AX, at the serine-139 residue, in the highly conserved C-terminal SQEY motif, forming gammaH2AX(1). Following induction of DSBs, H2AX is rapidly phosphorylated by the phosphatidyl-inosito 3-kinase (PIKK) family of proteins, ataxia telangiectasia mutated (ATM), DNA-protein kinase catalytic subunit and ATM and RAD3-related (ATR)(2). Typically, only a few base-pairs (bp) are implicated in a DSB, however, there is significant signal amplification, given the importance of chromatin modifications in DNA damage signalling and repair. Phosphorylation of H2AX mediated predominantly by ATM spreads to adjacent areas of chromatin, affecting approximately 0.03% of total cellular H2AX per DSB(2,3). This corresponds to phosphorylation of approximately 2000 H2AX molecules spanning approximately 2 Mbp regions of chromatin surrounding the site of the DSB and results in the formation of discrete gammaH2AX foci which can be easily visualized and quantitated by immunofluorescence microscopy(2). The loss of gammaH2AX at DSB reflects repair, however, there is some controversy as to what defines complete repair of DSBs; it has been proposed that rejoining of both strands of DNA is adequate however, it has also been suggested that re-instatement of the original chromatin state of compaction is necessary(4-8). The disappearence of gammaH2AX involves at least in part, dephosphorylation by phosphatases, phosphatase 2A and phosphatase 4C(5,6). Further, removal of gammaH2AX by redistribution involving histone exchange with H2A.Z has been implicated(7,8). Importantly, the quantitative analysis of gammaH2AX foci has led to a wide range of applications in medical and nuclear research. Here, we demonstrate the most commonly used immunofluorescence method for evaluation of initial DNA damage by detection and quantitation of gammaH2AX foci in gamma-irradiated adherent human keratinocytes(9)