908 resultados para Spatially modulated
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Plants have been identified as promising expression systems for the commercial production of recombinant proteins. Plant-based protein production or “biofarming” offers a number of advantages over traditional expression systems in terms of scale of production, the capacity for post-translation processing, providing a product free of contaminants and cost effectiveness. A number of pharmaceutically important and commercially valuable proteins, such as antibodies, biopharmaceuticals and industrial enzymes are currently being produced in plant expression systems. However, several challenges still remain to improve recombinant protein yield with no ill effect on the host plant. The ability for transgenic plants to produce foreign proteins at commercially viable levels can be directly related to the level and cell specificity of the selected promoter driving the transgene. The accumulation of recombinant proteins may be controlled by a tissue-specific, developmentally-regulated or chemically-inducible promoter such that expression of recombinant proteins can be spatially- or temporally- controlled. The strict control of gene expression is particularly useful for proteins that are considered toxic and whose expression is likely to have a detrimental effect on plant growth. To date, the most commonly used promoter in plant biotechnology is the cauliflower mosaic virus (CaMV) 35S promoter which is used to drive strong, constitutive transgene expression in most organs of transgenic plants. Of particular interest to researchers in the Centre for Tropical Crops and Biocommodities at QUT are tissue-specific promoters for the accumulation of foreign proteins in the roots, seeds and fruit of various plant species, including tobacco, banana and sugarcane. Therefore this Masters project aimed to isolate and characterise root- and seed-specific promoters for the control of genes encoding recombinant proteins in plant-based expression systems. Additionally, the effects of matching cognate terminators with their respective gene promoters were assessed. The Arabidopsis root promoters ARSK1 and EIR1 were selected from the literature based on their reported limited root expression profiles. Both promoters were analysed using the PlantCARE database to identify putative motifs or cis-acting elements that may be associated with this activity. A number of motifs were identified in the ARSK1 promoter region including, WUN (wound-inducible), MBS (MYB binding site), Skn-1, and a RY core element (seed-specific) and in the EIR1 promoter region including, Skn-1 (seed-specific), Box-W1 (fungal elicitor), Aux-RR core (auxin response) and ABRE (ABA response). However, no previously reported root-specific cis-acting elements were observed in either promoter region. To confirm root specificity, both promoters, and truncated versions, were fused to the GUS reporter gene and the expression cassette introduced into Arabidopsis via Agrobacterium-mediated transformation. Despite the reported tissue-specific nature of these promoters, both upstream regulatory regions directed constitutive GUS expression in all transgenic plants. Further, similar levels of GUS expression from the ARSK1 promoter were directed by the control CaMV 35S promoter. The truncated version of the EIR1 promoter (1.2 Kb) showed some differences in the level of GUS expression compared to the 2.2 Kb promoter. Therefore, this suggests an enhancer element is contained in the 2.2 Kb upstream region that increases transgene expression. The Arabidopsis seed-specific genes ATS1 and ATS3 were selected from the literature based on their seed-specific expression profiles and gene expression confirmed in this study as seed-specific by RT-PCR analysis. The selected promoter regions were analysed using the PlantCARE database in order to identify any putative cis elements. The seed-specific motifs GCN4 and Skn-1 were identified in both promoter regions that are associated with elevated expression levels in the endosperm. Additionaly, the seed-specific RY element and the ABRE were located in the ATS1 promoter. Both promoters were fused to the GUS reporter gene and used to transform Arabidopsis plants. GUS expression from the putative promoters was consitutive in all transgenic Arabidopsis tissue tested. Importantly, the positive control FAE1 seed-specific promoter also directed constitutive GUS expression throughout transgenic Arabidopsis plants. The constitutive nature seen in all of the promoters used in this study was not anticipated. While variations in promoter activity can be caused by a number of influencing factors, the variation in promoter activity observed here would imply a major contributing factor common to all plant expression cassettes tested. All promoter constructs generated in this study were based on the binary vector pCAMBIA2300. This vector contains the plant selection gene (NPTII) under the transcriptional control of the duplicated CaMV 35S promoter. This CaMV 35S promoter contains two enhancer domains that confer strong, constitutive expression of the selection gene and is located immediately upstream of the promoter-GUS fusion. During the course of this project, Yoo et al. (2005) reported that transgene expression is significantly affected when the expression cassette is located on the same T-DNA as the 35S enhancer. It was concluded, the trans-acting effects of the enhancer activate and control transgene expression causing irregular expression patterns. This phenomenon seems the most plausible reason for the constitutive expression profiles observed with the root- and seed-specific promoters assessed in this study. The expression from some promoters can be influenced by their cognate terminator sequences. Therefore, the Arabidopsis ARSK1, EIR1, ATS1 and ATS3 terminator sequences were isolated and incorporated into expression cassettes containing the GUS reporter gene under the control of their cognate promoters. Again, unrestricted GUS activity was displayed throughout transgenic plants transformed with these reporter gene fusions. As previously discussed constitutive GUS expression was most likely due to the trans-acting effect of the upstream CaMV 35S promoter in the selection cassette located on the same T-DNA. The results obtained in this study make it impossible to assess the influence matching terminators with their cognate promoters have on transgene expression profiles. The obvious future direction of research continuing from this study would be to transform pBIN-based promoter-GUS fusions (ie. constructs containing no CaMV 35S promoter driving the plant selection gene) into Arabidopsis in order to determine the true tissue specificity of these promoters and evaluate the effects of their cognate 3’ terminator sequences. Further, promoter truncations based around the cis-elements identified here may assist in determining whether these motifs are in fact involved in the overall activity of the promoter.
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Purpose: The component modules in the standard BEAMnrc distribution may appear to be insufficient to model micro-multileaf collimators that have tri-faceted leaf ends and complex leaf profiles. This note indicates, however, that accurate Monte Carlo simulations of radiotherapy beams defined by a complex collimation device can be completed using BEAMnrc's standard VARMLC component module.---------- Methods: That this simple collimator model can produce spatially and dosimetrically accurate micro-collimated fields is illustrated using comparisons with ion chamber and film measurements of the dose deposited by square and irregular fields incident on planar, homogeneous water phantoms.---------- Results: Monte Carlo dose calculations for on- and off-axis fields are shown to produce good agreement with experimental values, even upon close examination of the penumbrae.--------- Conclusions: The use of a VARMLC model of the micro-multileaf collimator, along with a commissioned model of the associated linear accelerator, is therefore recommended as an alternative to the development or use of in-house or third-party component modules for simulating stereotactic radiotherapy and radiosurgery treatments. Simulation parameters for the VARMLC model are provided which should allow other researchers to adapt and use this model to study clinical stereotactic radiotherapy treatments.
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Cardiovascular diseases refer to the class of diseases that involve the heart or blood vessels (arteries and veins). Examples of medical devices for treating the cardiovascular diseases include ventricular assist devices (VADs), artificial heart valves and stents. Metallic biomaterials such as titanium and its alloy are commonly used for ventricular assist devices. However, titanium and its alloy show unacceptable thrombosis, which represents a major obstacle to be overcome. Polyurethane (PU) polymer has better blood compatibility and has been used widely in cardiovascular devices. Thus one aim of the project was to coat a PU polymer onto a titanium substrate by increasing the surface roughness, and surface functionality. Since the endothelium of a blood vessel has the most ideal non-thrombogenic properties, it was the target of this research project to grow an endothelial cell layer as a biological coating based on the tissue engineering strategy. However, seeding endothelial cells on the smooth PU coating surfaces is problematic due to the quick loss of seeded cells which do not adhere to the PU surface. Thus it was another aim of the project to create a porous PU top layer on the dense PU pre-layer-coated titanium substrate. The method of preparing the porous PU layer was based on the solvent casting/particulate leaching (SCPL) modified with centrifugation. Without the step of centrifugation, the distribution of the salt particles was not uniform within the polymer solution, and the degree of interconnection between the salt particles was not well controlled. Using the centrifugal treatment, the pore distribution became uniform and the pore interconnectivity was improved even at a high polymer solution concentration (20%) as the maximal salt weight was added in the polymer solution. The titanium surfaces were modified by alkli and heat treatment, followed by functionlisation using hydrogen peroxide. A silane coupling agent was coated before the application of the dense PU pre-layer and the porous PU top layer. The ability of the porous top layer to grow and retain the endothelial cells was also assessed through cell culture techniques. The bonding strengths of the PU coatings to the modified titanium substrates were measured and related to the surface morphologies. The outcome of the project is that it has laid a foundation to achieve the strategy of endothelialisation for the blood compatibility of medical devices. This thesis is divided into seven chapters. Chapter 2 describes the current state of the art in the field of surface modification in cardiovascular devices such as ventricular assist devices (VADs). It also analyses the pros and cons of the existing coatings, particularly in the context of this research. The surface coatings for VADs have evolved from early organic/ inorganic (passive) coatings, to bioactive coatings (e.g. biomolecules), and to cell-based coatings. Based on the commercial applications and the potential of the coatings, the relevant review is focused on the following six types of coatings: (1) titanium nitride (TiN) coatings, (2) diamond-like carbon (DLC) coatings, (3) 2-methacryloyloxyethyl phosphorylcholine (MPC) polymer coatings, (4) heparin coatings, (5) textured surfaces, and (6) endothelial cell lining. Chapter 3 reviews the polymer scaffolds and one relevant fabrication method. In tissue engineering, the function of a polymeric material is to provide a 3-dimensional architecture (scaffold) which is typically used to accommodate transplanted cells and to guide their growth and the regeneration of tissue. The success of these systems is dependent on the design of the tissue engineering scaffolds. Chapter 4 describes chemical surface treatments for titanium and titanium alloys to increase the bond strength to polymer by altering the substrate surface, for example, by increasing surface roughness or changing surface chemistry. The nature of the surface treatment prior to bonding is found to be a major factor controlling the bonding strength. By increasing surface roughness, an increase in surface area occurs, which allows the adhesive to flow in and around the irregularities on the surface to form a mechanical bond. Changing surface chemistry also results in the formation of a chemical bond. Chapter 5 shows that bond strengths between titanium and polyurethane could be significantly improved by surface treating the titanium prior to bonding. Alkaline heat treatment and H2O2 treatment were applied to change the surface roughness and the surface chemistry of titanium. Surface treatment increases the bond strength by altering the substrate surface in a number of ways, including increasing the surface roughness and changing the surface chemistry. Chapter 6 deals with the characterization of the polyurethane scaffolds, which were fabricated using an enhanced solvent casting/particulate (salt) leaching (SCPL) method developed for preparing three-dimensional porous scaffolds for cardiac tissue engineering. The enhanced method involves the combination of a conventional SCPL method and a step of centrifugation, with the centrifugation being employed to improve the pore uniformity and interconnectivity of the scaffolds. It is shown that the enhanced SCPL method and a collagen coating resulted in a spatially uniform distribution of cells throughout the collagen-coated PU scaffolds.In Chapter 7, the enhanced SCPL method is used to form porous features on the polyurethane-coated titanium substrate. The cavities anchored the endothelial cells to remain on the blood contacting surfaces. It is shown that the surface porosities created by the enhanced SCPL may be useful in forming a stable endothelial layer upon the blood contacting surface. Chapter 8 finally summarises the entire work performed on the fabrication and analysis of the polymer-Ti bonding, the enhanced SCPL method and the PU microporous surface on the metallic substrate. It then outlines the possibilities for future work and research in this area.
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Occidentalism, which treats the other as the same, can be detected in both the criminological and rural sociological treatment of violence in the sociospatial sites of rural countrysides. Criminology tends to mistakenly assume that violence in the modern world is primarily an urban phenomenon (Baldwin & Bottoms, 1976, p. 1; Braithwaite, 1989, p. 47). If violence in rural settings is encountered it tends to be treated as a smaller scale version of the urban problem, or the importation of an otherwise urban problem - as the corrupting influence of the gesellschaft within the gemeinschaft. Within much rural sociology violence is rendered invisible by the assumption that rural communities conform to the idealised conception of the typical gemeinschaft society, small-scale traditional societies based on strong cohesiveness, intimacy and organic forms of solidarity. What these bonds conceal, rather than reveal - violence within the family - remains invisible to the public gaze. The visibility of violence within Aboriginal families and communities presents a major exception to the spatially ordered social relations which render so much white family violence hidden. The need to take into account the complexity and diversity of these sociospatial relations is concretely highlighted in our research which has taken us out of the urban context and confronted us not only with the phenomenon of the violence of other rurals, but also with fundamentally competing claims on, and conceptions of, space and place in the context of a racially divided Australian interior. This article represents the second installment of conceptual reflections on this research, with the first having been published in this journal in 1998.
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Controlling free-ranging livestock requires low-stress cues to alter animal behaviour. Recently modulated sound and electric shock were demonstrated to be effective in controlling free-ranging cattle. In this study the behaviour of 60, 300 kg Belmont Red heifers were observed for behavioural changes when presented cues designed to impede their movement through an alley. The heifers were given an overnight drylot shrink off feed but not drinking water prior to being tested. Individual cattle were allowed to move down a 6.5 m wide alley towards a pen of peers and feed located 71 m from their point of release. Each animal was allowed to move through the alley unimpeded five times to establish a basal behavioural pattern. Animals were then randomly assigned to treatments consisting of sound plus shock, vibration plus shock, a visual cue plus shock, shock by itself and a control. The time each animal required to reach the pen of peers and feed was recorded. If the animal was prevented from reaching the pen of peers and feed by not penetrating through the cue barrier at set points along the alley for at least 60 sec the test was stopped and the animal was returned to peers located behind the release pen. Cues and shock were manually applied from a laptop while animals were observed from a 3.5 m tower located outside the alley. Electric shock, sound, vibration and Global Position System (GPS) hardware were housed in a neck collar. Results and implications will be discussed.
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Knowledge of the regulation of food intake is crucial to an understanding of body weight and obesity. Strictly speaking, we should refer to the control of food intake whose expression is modulated in the interests of the regulation of body weight. Food intake is controlled, body weight is regulated. However, this semantic distinction only serves to emphasize the importance of food intake. Traditionally food intake has been researched within the homeostatic approach to physiological systems pioneered by Claude Bernard, Walter Cannon and others; and because feeding is a form of behaviour, it forms part of what Curt Richter referred to as the behavioural regulation of body weight (or behavioural homeostasis). This approach views food intake as the vehicle for energy supply whose expression is modulated by a metabolic drive generated in response to a requirement for energy. The idea was that eating behaviour is stimulated and inhibited by internal signalling systems (for the drive and suppression of eating respectively) in order to regulate the internal environment (energy stores, tissue needs).
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The performance of an adaptive filter may be studied through the behaviour of the optimal and adaptive coefficients in a given environment. This thesis investigates the performance of finite impulse response adaptive lattice filters for two classes of input signals: (a) frequency modulated signals with polynomial phases of order p in complex Gaussian white noise (as nonstationary signals), and (b) the impulsive autoregressive processes with alpha-stable distributions (as non-Gaussian signals). Initially, an overview is given for linear prediction and adaptive filtering. The convergence and tracking properties of the stochastic gradient algorithms are discussed for stationary and nonstationary input signals. It is explained that the stochastic gradient lattice algorithm has many advantages over the least-mean square algorithm. Some of these advantages are having a modular structure, easy-guaranteed stability, less sensitivity to the eigenvalue spread of the input autocorrelation matrix, and easy quantization of filter coefficients (normally called reflection coefficients). We then characterize the performance of the stochastic gradient lattice algorithm for the frequency modulated signals through the optimal and adaptive lattice reflection coefficients. This is a difficult task due to the nonlinear dependence of the adaptive reflection coefficients on the preceding stages and the input signal. To ease the derivations, we assume that reflection coefficients of each stage are independent of the inputs to that stage. Then the optimal lattice filter is derived for the frequency modulated signals. This is performed by computing the optimal values of residual errors, reflection coefficients, and recovery errors. Next, we show the tracking behaviour of adaptive reflection coefficients for frequency modulated signals. This is carried out by computing the tracking model of these coefficients for the stochastic gradient lattice algorithm in average. The second-order convergence of the adaptive coefficients is investigated by modeling the theoretical asymptotic variance of the gradient noise at each stage. The accuracy of the analytical results is verified by computer simulations. Using the previous analytical results, we show a new property, the polynomial order reducing property of adaptive lattice filters. This property may be used to reduce the order of the polynomial phase of input frequency modulated signals. Considering two examples, we show how this property may be used in processing frequency modulated signals. In the first example, a detection procedure in carried out on a frequency modulated signal with a second-order polynomial phase in complex Gaussian white noise. We showed that using this technique a better probability of detection is obtained for the reduced-order phase signals compared to that of the traditional energy detector. Also, it is empirically shown that the distribution of the gradient noise in the first adaptive reflection coefficients approximates the Gaussian law. In the second example, the instantaneous frequency of the same observed signal is estimated. We show that by using this technique a lower mean square error is achieved for the estimated frequencies at high signal-to-noise ratios in comparison to that of the adaptive line enhancer. The performance of adaptive lattice filters is then investigated for the second type of input signals, i.e., impulsive autoregressive processes with alpha-stable distributions . The concept of alpha-stable distributions is first introduced. We discuss that the stochastic gradient algorithm which performs desirable results for finite variance input signals (like frequency modulated signals in noise) does not perform a fast convergence for infinite variance stable processes (due to using the minimum mean-square error criterion). To deal with such problems, the concept of minimum dispersion criterion, fractional lower order moments, and recently-developed algorithms for stable processes are introduced. We then study the possibility of using the lattice structure for impulsive stable processes. Accordingly, two new algorithms including the least-mean P-norm lattice algorithm and its normalized version are proposed for lattice filters based on the fractional lower order moments. Simulation results show that using the proposed algorithms, faster convergence speeds are achieved for parameters estimation of autoregressive stable processes with low to moderate degrees of impulsiveness in comparison to many other algorithms. Also, we discuss the effect of impulsiveness of stable processes on generating some misalignment between the estimated parameters and the true values. Due to the infinite variance of stable processes, the performance of the proposed algorithms is only investigated using extensive computer simulations.
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This thesis deals with the problem of the instantaneous frequency (IF) estimation of sinusoidal signals. This topic plays significant role in signal processing and communications. Depending on the type of the signal, two major approaches are considered. For IF estimation of single-tone or digitally-modulated sinusoidal signals (like frequency shift keying signals) the approach of digital phase-locked loops (DPLLs) is considered, and this is Part-I of this thesis. For FM signals the approach of time-frequency analysis is considered, and this is Part-II of the thesis. In part-I we have utilized sinusoidal DPLLs with non-uniform sampling scheme as this type is widely used in communication systems. The digital tanlock loop (DTL) has introduced significant advantages over other existing DPLLs. In the last 10 years many efforts have been made to improve DTL performance. However, this loop and all of its modifications utilizes Hilbert transformer (HT) to produce a signal-independent 90-degree phase-shifted version of the input signal. Hilbert transformer can be realized approximately using a finite impulse response (FIR) digital filter. This realization introduces further complexity in the loop in addition to approximations and frequency limitations on the input signal. We have tried to avoid practical difficulties associated with the conventional tanlock scheme while keeping its advantages. A time-delay is utilized in the tanlock scheme of DTL to produce a signal-dependent phase shift. This gave rise to the time-delay digital tanlock loop (TDTL). Fixed point theorems are used to analyze the behavior of the new loop. As such TDTL combines the two major approaches in DPLLs: the non-linear approach of sinusoidal DPLL based on fixed point analysis, and the linear tanlock approach based on the arctan phase detection. TDTL preserves the main advantages of the DTL despite its reduced structure. An application of TDTL in FSK demodulation is also considered. This idea of replacing HT by a time-delay may be of interest in other signal processing systems. Hence we have analyzed and compared the behaviors of the HT and the time-delay in the presence of additive Gaussian noise. Based on the above analysis, the behavior of the first and second-order TDTLs has been analyzed in additive Gaussian noise. Since DPLLs need time for locking, they are normally not efficient in tracking the continuously changing frequencies of non-stationary signals, i.e. signals with time-varying spectra. Nonstationary signals are of importance in synthetic and real life applications. An example is the frequency-modulated (FM) signals widely used in communication systems. Part-II of this thesis is dedicated for the IF estimation of non-stationary signals. For such signals the classical spectral techniques break down, due to the time-varying nature of their spectra, and more advanced techniques should be utilized. For the purpose of instantaneous frequency estimation of non-stationary signals there are two major approaches: parametric and non-parametric. We chose the non-parametric approach which is based on time-frequency analysis. This approach is computationally less expensive and more effective in dealing with multicomponent signals, which are the main aim of this part of the thesis. A time-frequency distribution (TFD) of a signal is a two-dimensional transformation of the signal to the time-frequency domain. Multicomponent signals can be identified by multiple energy peaks in the time-frequency domain. Many real life and synthetic signals are of multicomponent nature and there is little in the literature concerning IF estimation of such signals. This is why we have concentrated on multicomponent signals in Part-H. An adaptive algorithm for IF estimation using the quadratic time-frequency distributions has been analyzed. A class of time-frequency distributions that are more suitable for this purpose has been proposed. The kernels of this class are time-only or one-dimensional, rather than the time-lag (two-dimensional) kernels. Hence this class has been named as the T -class. If the parameters of these TFDs are properly chosen, they are more efficient than the existing fixed-kernel TFDs in terms of resolution (energy concentration around the IF) and artifacts reduction. The T-distributions has been used in the IF adaptive algorithm and proved to be efficient in tracking rapidly changing frequencies. They also enables direct amplitude estimation for the components of a multicomponent
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The concept of radar was developed for the estimation of the distance (range) and velocity of a target from a receiver. The distance measurement is obtained by measuring the time taken for the transmitted signal to propagate to the target and return to the receiver. The target's velocity is determined by measuring the Doppler induced frequency shift of the returned signal caused by the rate of change of the time- delay from the target. As researchers further developed conventional radar systems it become apparent that additional information was contained in the backscattered signal and that this information could in fact be used to describe the shape of the target itself. It is due to the fact that a target can be considered to be a collection of individual point scatterers, each of which has its own velocity and time- delay. DelayDoppler parameter estimation of each of these point scatterers thus corresponds to a mapping of the target's range and cross range, thus producing an image of the target. Much research has been done in this area since the early radar imaging work of the 1960s. At present there are two main categories into which radar imaging falls. The first of these is related to the case where the backscattered signal is considered to be deterministic. The second is related to the case where the backscattered signal is of a stochastic nature. In both cases the information which describes the target's scattering function is extracted by the use of the ambiguity function, a function which correlates the backscattered signal in time and frequency with the transmitted signal. In practical situations, it is often necessary to have the transmitter and the receiver of the radar system sited at different locations. The problem in these situations is 'that a reference signal must then be present in order to calculate the ambiguity function. This causes an additional problem in that detailed phase information about the transmitted signal is then required at the receiver. It is this latter problem which has led to the investigation of radar imaging using time- frequency distributions. As will be shown in this thesis, the phase information about the transmitted signal can be extracted from the backscattered signal using time- frequency distributions. The principle aim of this thesis was in the development, and subsequent discussion into the theory of radar imaging, using time- frequency distributions. Consideration is first given to the case where the target is diffuse, ie. where the backscattered signal has temporal stationarity and a spatially white power spectral density. The complementary situation is also investigated, ie. where the target is no longer diffuse, but some degree of correlation exists between the time- frequency points. Computer simulations are presented to demonstrate the concepts and theories developed in the thesis. For the proposed radar system to be practically realisable, both the time- frequency distributions and the associated algorithms developed must be able to be implemented in a timely manner. For this reason an optical architecture is proposed. This architecture is specifically designed to obtain the required time and frequency resolution when using laser radar imaging. The complex light amplitude distributions produced by this architecture have been computer simulated using an optical compiler.
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This dissertation is primarily an applied statistical modelling investigation, motivated by a case study comprising real data and real questions. Theoretical questions on modelling and computation of normalization constants arose from pursuit of these data analytic questions. The essence of the thesis can be described as follows. Consider binary data observed on a two-dimensional lattice. A common problem with such data is the ambiguity of zeroes recorded. These may represent zero response given some threshold (presence) or that the threshold has not been triggered (absence). Suppose that the researcher wishes to estimate the effects of covariates on the binary responses, whilst taking into account underlying spatial variation, which is itself of some interest. This situation arises in many contexts and the dingo, cypress and toad case studies described in the motivation chapter are examples of this. Two main approaches to modelling and inference are investigated in this thesis. The first is frequentist and based on generalized linear models, with spatial variation modelled by using a block structure or by smoothing the residuals spatially. The EM algorithm can be used to obtain point estimates, coupled with bootstrapping or asymptotic MLE estimates for standard errors. The second approach is Bayesian and based on a three- or four-tier hierarchical model, comprising a logistic regression with covariates for the data layer, a binary Markov Random field (MRF) for the underlying spatial process, and suitable priors for parameters in these main models. The three-parameter autologistic model is a particular MRF of interest. Markov chain Monte Carlo (MCMC) methods comprising hybrid Metropolis/Gibbs samplers is suitable for computation in this situation. Model performance can be gauged by MCMC diagnostics. Model choice can be assessed by incorporating another tier in the modelling hierarchy. This requires evaluation of a normalization constant, a notoriously difficult problem. Difficulty with estimating the normalization constant for the MRF can be overcome by using a path integral approach, although this is a highly computationally intensive method. Different methods of estimating ratios of normalization constants (N Cs) are investigated, including importance sampling Monte Carlo (ISMC), dependent Monte Carlo based on MCMC simulations (MCMC), and reverse logistic regression (RLR). I develop an idea present though not fully developed in the literature, and propose the Integrated mean canonical statistic (IMCS) method for estimating log NC ratios for binary MRFs. The IMCS method falls within the framework of the newly identified path sampling methods of Gelman & Meng (1998) and outperforms ISMC, MCMC and RLR. It also does not rely on simplifying assumptions, such as ignoring spatio-temporal dependence in the process. A thorough investigation is made of the application of IMCS to the three-parameter Autologistic model. This work introduces background computations required for the full implementation of the four-tier model in Chapter 7. Two different extensions of the three-tier model to a four-tier version are investigated. The first extension incorporates temporal dependence in the underlying spatio-temporal process. The second extensions allows the successes and failures in the data layer to depend on time. The MCMC computational method is extended to incorporate the extra layer. A major contribution of the thesis is the development of a fully Bayesian approach to inference for these hierarchical models for the first time. Note: The author of this thesis has agreed to make it open access but invites people downloading the thesis to send her an email via the 'Contact Author' function.
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Nitrous oxide (N2O) is primarily produced by the microbially-mediated nitrification and denitrification processes in soils. It is influenced by a suite of climate (i.e. temperature and rainfall) and soil (physical and chemical) variables, interacting soil and plant nitrogen (N) transformations (either competing or supplying substrates) as well as land management practices. It is not surprising that N2O emissions are highly variable both spatially and temporally. Computer simulation models, which can integrate all of these variables, are required for the complex task of providing quantitative determinations of N2O emissions. Numerous simulation models have been developed to predict N2O production. Each model has its own philosophy in constructing simulation components as well as performance strengths. The models range from those that attempt to comprehensively simulate all soil processes to more empirical approaches requiring minimal input data. These N2O simulation models can be classified into three categories: laboratory, field and regional/global levels. Process-based field-scale N2O simulation models, which simulate whole agroecosystems and can be used to develop N2O mitigation measures, are the most widely used. The current challenge is how to scale up the relatively more robust field-scale model to catchment, regional and national scales. This paper reviews the development history, main construction components, strengths, limitations and applications of N2O emissions models, which have been published in the literature. The three scale levels are considered and the current knowledge gaps and challenges in modelling N2O emissions from soils are discussed.
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Estimates of potential and actual C sequestration require areal information about various types of management activities. Forest surveys, land use data, and agricultural statistics contribute information enabling calculation of the impacts of current and historical land management on C sequestration in biomass (in forests) or in soil (in agricultural systems). Unfortunately little information exists on the distribution of various management activities that can impact soil C content in grassland systems. Limited information of this type restricts our ability to carry out bottom-up estimates of the current C balance of grasslands or to assess the potential for grasslands to act as C sinks with changes in management. Here we review currently available information about grassland management, how that information could be related to information about the impacts of management on soil C stocks, information that may be available in the future, and needs that remain to be filled before in-depth assessments may be carried out. We also evaluate constraints induced by variability in information sources within and between countries. It is readily apparent that activity data for grassland management is collected less frequently and on a coarser scale than data for forest or agricultural inventories and that grassland activity data cannot be directly translated into IPCC-type factors as is done for IPCC inventories of agricultural soils. However, those management data that are available can serve to delineate broad-scale differences in management activities within regions in which soil C is likely to change in response to changes in management. This, coupled with the distinct possibility of more intensive surveys planned in the future, may enable more accurate assessments of grassland C dynamics with higher resolution both spatially and in the number management activities.
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The potential to sequester atmospheric carbon in agricultural and forest soils to offset greenhouse gas emissions has generated interest in measuring changes in soil carbon resulting from changes in land management. However, inherent spatial variability of soil carbon limits the precision of measurement of changes in soil carbon and hence, the ability to detect changes. We analyzed variability of soil carbon by intensively sampling sites under different land management as a step toward developing efficient soil sampling designs. Sites were tilled crop-land and a mixed deciduous forest in Tennessee, and old-growth and second-growth coniferous forest in western Washington, USA. Six soil cores within each of three microplots were taken as an initial sample and an additional six cores were taken to simulate resampling. Soil C variability was greater in Washington than in Tennessee, and greater in less disturbed than in more disturbed sites. Using this protocol, our data suggest that differences on the order of 2.0 Mg C ha(-1) could be detected by collection and analysis of cores from at least five (tilled) or two (forest) microplots in Tennessee. More spatial variability in the forested sites in Washington increased the minimum detectable difference, but these systems, consisting of low C content sandy soil with irregularly distributed pockets of organic C in buried logs, are likely to rank among the most spatially heterogeneous of systems. Our results clearly indicate that consistent intramicroplot differences at all sites will enable detection of much more modest changes if the same microplots are resampled.