293 resultados para Modified signed likelihood ratio statistic
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Water and ammonium retention by sandy soils may be low and result in leaching of applied fertiliser. To increase water and nutrient retention, zeolite is sometimes applied as a soil ameliorant for high value land uses including turf and horticulture. We have used a new modified kaolin material (MesoLite) as a soil amendment to test the efficiency of NH4+ retention and compared the results with natural zeolite. MesoLite is made by caustic reaction of kaolin at temperature between 80-95°C; although it has a moderate surface area, its cation exchange capacity is very high;(SA=13m2/g,CEC=500meq/100g). A 13cm tall sand column filled with ~450g of sandy soil homogeneously mixed with 1, 2, 4, and 8g of MesoLite or natural zeolite per 1kg of soil was prepared. After saturation with local bore water, concentrated ammonium sulfate solution was injected at the base. Then, bore water was passed from bottom to top through the column at amounts up to 6 pore volumes and at a constant flow rate of 10ml/min using a peristaltic pump. Concentrations of leached NH4+ were determined using an AutoAnalyser. The concentration of NH4+ leached from the column with 0.4% MesoLite was greatly (90%) reduced relative to unamended soil. Under these conditions NH4+ retention by the soil-MesoLite mixture was 11.5 times more efficient than the equivalent soil-natural zeolite mixture. Glasshouse experiments conducted in a separate study show that NH4+ adsorbed by MesoLite is available to plants.
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In this paper we present a new simulation methodology in order to obtain exact or approximate Bayesian inference for models for low-valued count time series data that have computationally demanding likelihood functions. The algorithm fits within the framework of particle Markov chain Monte Carlo (PMCMC) methods. The particle filter requires only model simulations and, in this regard, our approach has connections with approximate Bayesian computation (ABC). However, an advantage of using the PMCMC approach in this setting is that simulated data can be matched with data observed one-at-a-time, rather than attempting to match on the full dataset simultaneously or on a low-dimensional non-sufficient summary statistic, which is common practice in ABC. For low-valued count time series data we find that it is often computationally feasible to match simulated data with observed data exactly. Our particle filter maintains $N$ particles by repeating the simulation until $N+1$ exact matches are obtained. Our algorithm creates an unbiased estimate of the likelihood, resulting in exact posterior inferences when included in an MCMC algorithm. In cases where exact matching is computationally prohibitive, a tolerance is introduced as per ABC. A novel aspect of our approach is that we introduce auxiliary variables into our particle filter so that partially observed and/or non-Markovian models can be accommodated. We demonstrate that Bayesian model choice problems can be easily handled in this framework.
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Heteroatom doping on the edge of graphene may serve as an effective way to tune chemical activity of carbon-based electrodes with respect to charge carrier transfer in an aqueous environment. In a step towards developing mechanistic understanding of this phenomenon, we explore herein mechanisms of proton transfer from aqueous solution to pristine and doped graphene edges utilizing density functional theory. Atomic B-, N-, and O- doped edges as well as the native graphene are examined, displaying varying proton affinities and effective interaction ranges with the H3O+ charge carrier. Our study shows that the doped edges characterized by more dispersive orbitals, namely boron and nitrogen, demonstrate more energetically favourable charge carrier exchange compared with oxygen, which features more localized orbitals. Extended calculations are carried out to examine proton transfer from the hydronium ion in the presence of explicit water, with results indicating that the basic mechanistic features of the simpler model are unchanged.
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A quasi-maximum likelihood procedure for estimating the parameters of multi-dimensional diffusions is developed in which the transitional density is a multivariate Gaussian density with first and second moments approximating the true moments of the unknown density. For affine drift and diffusion functions, the moments are exactly those of the true transitional density and for nonlinear drift and diffusion functions the approximation is extremely good and is as effective as alternative methods based on likelihood approximations. The estimation procedure generalises to models with latent factors. A conditioning procedure is developed that allows parameter estimation in the absence of proxies.
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First-principles computational studies indicate that (B, N, or O)-doped graphene ribbon edges can substantially reduce the energy barrier for H2 dissociative adsorption. The low barrier is competitive with many widely used metal or metal oxide catalysts. This suggests that suitably functionalized graphene architectures are promising metal-free alternatives for low-cost catalytic processes.
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The giant freshwater prawn (Macrobrachium rosenbergii) or GFP is one of the most important freshwater crustacean species in the inland aquaculture sector of many tropical and subtropical countries. Since the 1990’s, there has been rapid global expansion of freshwater prawn farming, especially in Asian countries, with an average annual rate of increase of 48% between 1999 and 2001 (New, 2005). In Vietnam, GFP is cultured in a variety of culture systems, typically in integrated or rotational rice-prawn culture (Phuong et al., 2006) and has become one of the most common farmed aquatic species in the country, due to its ability to grow rapidly and to attract high market price and high demand. Despite potential for expanded production, sustainability of freshwater prawn farming in the region is currently threatened by low production efficiency and vulnerability of farmed stocks to disease. Commercial large scale and small scale GFP farms in Vietnam have experienced relatively low stock productivity, large size and weight variation, a low proportion of edible meat (large head to body ratio), scarcity of good quality seed stock. The current situation highlights the need for a systematic stock improvement program for GFP in Vietnam aimed at improving economically important traits in this species. This study reports on the breeding program for fast growth employing combined (between and within) family selection in giant freshwater prawn in Vietnam. The base population was synthesized using a complete diallel cross including 9 crosses from two local stocks (DN and MK strains) and a third exotic stock (Malaysian strain - MY). In the next three selection generations, matings were conducted between genetically unrelated brood stock to produce full-sib and (paternal) half-sib families. All families were produced and reared separately until juveniles in each family were tagged as a batch using visible implant elastomer (VIE) at a body size of approximately 2 g. After tags were verified, 60 to 120 juveniles chosen randomly from each family were released into two common earthen ponds of 3,500 m2 pond for a grow-out period of 16 to 18 weeks. Selection applied at harvest on body weight was a combined (between and within) family selection approach. 81, 89, 96 and 114 families were produced for the Selection line in the F0, F1, F2 and F3 generations, respectively. In addition to the Selection line, 17 to 42 families were produced for the Control group in each generation. Results reported here are based on a data set consisting of 18,387 body and 1,730 carcass records, as well as full pedigree information collected over four generations. Variance and covariance components were estimated by restricted maximum likelihood fitting a multi-trait animal model. Experiments assessed performance of VIE tags in juvenile GFP of different size classes and individuals tagged with different numbers of tags showed that juvenile GFP at 2 g were of suitable size for VIE tags with no negative effects evident on growth or survival. Tag retention rates were above 97.8% and tag readability rates were 100% with a correct assignment rate of 95% through to mature animal size of up to 170 g. Across generations, estimates of heritability for body traits (body weight, body length, cephalothorax length, abdominal length, cephalothorax width and abdominal width) and carcass weight traits (abdominal weight, skeleton-off weight and telson-off weight) were moderate and ranged from 0.14 to 0.19 and 0.17 to 0.21, respectively. Body trait heritabilities estimated for females were significantly higher than for males whereas carcass weight trait heritabilities estimated for females and males were not significantly different (P > 0.05). Maternal and common environmental effects for body traits accounted for 4 to 5% of the total variance and were greater in females (7 to 10%) than in males (4 to 5%). Genetic correlations among body traits were generally high in both sexes. Genetic correlations between body and carcass weight traits were also high in the mixed sexes. Average selection response (% per generation) for body weight (transformed to square root) estimated as the difference between the Selection and the Control group was 7.4% calculated from least squares means (LSMs), 7.0% from estimated breeding values (EBVs) and 4.4% calculated from EBVs between two consecutive generations. Favourable correlated selection responses (estimated from LSMs) were detected for other body traits (12.1%, 14.5%, 10.4%, 15.5% and 13.3% for body length, cephalothorax length, abdominal length, cephalothorax width and abdominal width, respectively) over three selection generations. Data in the second selection generation showed positive correlated responses for carcass weight traits (8.8%, 8.6% and 8.8% for abdominal weight, skeleton-off weight and telson-off weight, respectively). Data in the third selection generation showed that heritability for body traits were moderate and ranged from 0.06 to 0.11 and 0.11 to 0.22 at weeks 10 and 18, respectively. Body trait heritabilities estimated at week 10 were not significantly lower than at week 18. Genetic correlations between body traits within age and genetic correlations for body traits between ages were generally high. Overall our results suggest that growth rate responds well to the application of family selection and carcass weight traits can also be improved in parallel, using this approach. Moreover, selection for high growth rate in GFP can be undertaken successfully before full market size has been reached. The outcome of this study was production of an improved culture strain of GFP for the Vietnamese culture industry that will be trialed in real farm production environments to confirm the genetic gains identified in the experimental stock improvement program.
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Accuracy of dose delivery in external beam radiotherapy is usually verified with electronic portal imaging (EPI) in which the treatment beam is used to check the positioning of the patient. However the resulting megavoltage x-ray images suffer from poor quality. The image quality can be improved by developing a special operating mode in the linear accelerator. The existing treatment beam is modified such that it produces enough low-energy photons for imaging. In this work the problem of optimizing the beam/detector combination to achieve optimal electronic portal image quality is addressed. The linac used for this study was modified to produce two experimental photon beams. These beams, named Al6 and Al10, were non-flat and were produced by 4MeV electrons hitting aluminum targets, 6 and 10mm thick respectively. The images produced by a conventional EPI system (6MV treatment beam and camera-based EPID with a Cu plate & Gd2O2S screen ) were compared with the images produced by the experimental beams and various screens with the same camera). The contrast of 0.8cm bone equivalent material in 5 cm water increased from 1.5% for the conventional system to 11% for the combination of Al6 beam with a 200mg/cm2 Gd2O2S screen. The signal-to-noise ratio calculated for 1cGy flood field images increased by about a factor of two for the same EPI systems. The spatial resolution of the two imaging systems was comparable. This work demonstrates that significant improvements in portal image contrast can be obtained by simultaneous optimization of the linac spectrum and EPI detector.
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Classifier selection is a problem encountered by multi-biometric systems that aim to improve performance through fusion of decisions. A particular decision fusion architecture that combines multiple instances (n classifiers) and multiple samples (m attempts at each classifier) has been proposed in previous work to achieve controlled trade-off between false alarms and false rejects. Although analysis on text-dependent speaker verification has demonstrated better performance for fusion of decisions with favourable dependence compared to statistically independent decisions, the performance is not always optimal. Given a pool of instances, best performance with this architecture is obtained for certain combination of instances. Heuristic rules and diversity measures have been commonly used for classifier selection but it is shown that optimal performance is achieved for the `best combination performance' rule. As the search complexity for this rule increases exponentially with the addition of classifiers, a measure - the sequential error ratio (SER) - is proposed in this work that is specifically adapted to the characteristics of sequential fusion architecture. The proposed measure can be used to select a classifier that is most likely to produce a correct decision at each stage. Error rates for fusion of text-dependent HMM based speaker models using SER are compared with other classifier selection methodologies. SER is shown to achieve near optimal performance for sequential fusion of multiple instances with or without the use of multiple samples. The methodology applies to multiple speech utterances for telephone or internet based access control and to other systems such as multiple finger print and multiple handwriting sample based identity verification systems.
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The composition of a series of hydroxycarbonate precursors to copper/zinc oxide methanol synthesis catalysts prepared under conditions reported as optimum for catalytic activity has been studied. Techniques employed included thermogravimetry (TG), temperature-programmed decomposition (TPD), X-ray diffraction (XRD), high-resolution transmission electron microscopy (HRTEM), and Raman and FTIR spectroscopies. Evidence was obtained for various structural phases including hydrozincite, copper hydrozincite, aurichalcite, zincian malachite and malachite (the concentrations of which depended upon the exact Cu/Zn ratio used). Significantly, previously reported phases such as gerhardite and rosasite were not identified when catalysts were synthesized at optimum solution pH and temperature values, and after appropriate aging periods. Calcination of the hydroxycarbonate precursors resulted in the formation of catalysts containing an intimate mixture of copper and zinc oxides. Temperature-programmed reduction (TPR) revealed that a number of discrete copper oxide species were present in the catalyst, the precise concentrations of which were determined to be related to the structure of the catalyst precursor. Copper hydrozincite decomposed to give zinc oxide particles decorated by highly dispersed, small copper oxide species. Aurichalcite appeared to result ultimately in the most intimately mixed catalyst structure whereas zincian malachite decomposed to produce larger copper oxide and zinc oxide grains. The reason for the stabilization of small copper oxide and zinc oxide clusters by aurichalcite was investigated by using carefully selected calcination temperatures. It was concluded that the unique formation of an 'anion-modified' oxide resulting from the initial decomposition stage of aurichalcite was responsible for the 'binding' of copper species to zinc moieties.
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The positive relationship between speed and crash risk and severity is robust and well-established. While excessive speeding is typically regarded by the public as a common contributing factor in road crashes, speeding remains a common traffic infringement and an arguably socially acceptable behaviour, particularly at low levels over the speed limit. This suggests that other factors potentially contribute to this disparity between crash perceptions and actual behaviours. Previous work has described associations between perceptions of the legitimacy of speed enforcement, attitudes, and how they relate to the likelihood of speeding. This study sought to more closely examine the nature of the relationships between these variables. In total, 293 Queensland drivers participated in a study that examined how demographics, personality variables, attitudes, and perceptions of the legitimacy of enforcement contributed to drivers’ self-reported likelihood of speeding. Results suggested that positive attitudes towards speeding had the greatest impact on likelihood of speeding behaviours. Being younger and higher levels of the personality trait of extraversion were also associated with greater levels of self-reported likelihood of speeding. Attitudes were found to mediate the relationship between perceived legitimacy of speed enforcement and self-reported likelihood of speeding. A subgroup analysis of participants with positive and negative attitudes towards speeding revealed that a differential set of variables were predictive of self-reported likelihood of speeding for the two subgroups. This highlights the potential importance of attitudes in understanding the influence of perceptions of legitimacy of speed enforcement on speeding behaviour, and the need for targeted rather than a ‘one size fits all’ approach to changing attitudes and ultimately behaviour. The findings of the current study help to further understand why some drivers continue to speed.
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Three long chain cationic surfactants were intercalated into Ca-montmorillonite through ion exchangeand the obtained organoclays were characterized by X-ray diffraction (XRD), high resolution thermo-gravimetric analysis (TG) and Raman spectroscopy. The intercalation of surfactants not only changes thesurface properties of clay from hydrophilic to hydrophobic but also greatly increases the basal spacing ofthe interlayers based on XRD analysis. The thermal stability of organoclays intercalated with three sur-factants (TTAB, DTAB and CTAB) and the different arrangements of the surfactant molecules intercalatedinto Ca-montmorillonite were determined by TG-DTG analysis. A Raman spectroscopic study on the Ca-montmorillonite modified by three surfactants prepared at different concentrations provided the detailedconformational ordering of different intercalated long-chain surfactants under different conditions. Thewavenumber of the antisymmetric stretching mode is more sensitive than that of the symmetric stretch-ing mode to the mobility of the tail of the amine chain. At room temperature, the conformational orderingis more easily affected by the packing density in the lateral model. With the increase of the temperature,the positions of both the antisymmetric and symmetric stretching bands shift to higher wavenumbers,which indicates a decrease of conformational ordering. This study offers new insights into the struc-ture and properties of Ca-montmorillonite modified with different long chain surfactants. Moreover, theexperimental results confirm the potential applications of organic Ca-montmorillonites for the removalof organic impurities from aqueous media.
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Genomic DNA obtained from patient whole blood samples is a key element for genomic research. Advantages and disadvantages, in terms of time-efficiency, cost-effectiveness and laboratory requirements, of procedures available to isolate nucleic acids need to be considered before choosing any particular method. These characteristics have not been fully evaluated for some laboratory techniques, such as the salting out method for DNA extraction, which has been excluded from comparison in different studies published to date. We compared three different protocols (a traditional salting out method, a modified salting out method and a commercially available kit method) to determine the most cost-effective and time-efficient method to extract DNA. We extracted genomic DNA from whole blood samples obtained from breast cancer patient volunteers and compared the results of the product obtained in terms of quantity (concentration of DNA extracted and DNA obtained per ml of blood used) and quality (260/280 ratio and polymerase chain reaction product amplification) of the obtained yield. On average, all three methods showed no statistically significant differences between the final result, but when we accounted for time and cost derived for each method, they showed very significant differences. The modified salting out method resulted in a seven- and twofold reduction in cost compared to the commercial kit and traditional salting out method, respectively and reduced time from 3 days to 1 hour compared to the traditional salting out method. This highlights a modified salting out method as a suitable choice to be used in laboratories and research centres, particularly when dealing with a large number of samples.
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Reliability of the performance of biometric identity verification systems remains a significant challenge. Individual biometric samples of the same person (identity class) are not identical at each presentation and performance degradation arises from intra-class variability and inter-class similarity. These limitations lead to false accepts and false rejects that are dependent. It is therefore difficult to reduce the rate of one type of error without increasing the other. The focus of this dissertation is to investigate a method based on classifier fusion techniques to better control the trade-off between the verification errors using text-dependent speaker verification as the test platform. A sequential classifier fusion architecture that integrates multi-instance and multisample fusion schemes is proposed. This fusion method enables a controlled trade-off between false alarms and false rejects. For statistically independent classifier decisions, analytical expressions for each type of verification error are derived using base classifier performances. As this assumption may not be always valid, these expressions are modified to incorporate the correlation between statistically dependent decisions from clients and impostors. The architecture is empirically evaluated by applying the proposed architecture for text dependent speaker verification using the Hidden Markov Model based digit dependent speaker models in each stage with multiple attempts for each digit utterance. The trade-off between the verification errors is controlled using the parameters, number of decision stages (instances) and the number of attempts at each decision stage (samples), fine-tuned on evaluation/tune set. The statistical validation of the derived expressions for error estimates is evaluated on test data. The performance of the sequential method is further demonstrated to depend on the order of the combination of digits (instances) and the nature of repetitive attempts (samples). The false rejection and false acceptance rates for proposed fusion are estimated using the base classifier performances, the variance in correlation between classifier decisions and the sequence of classifiers with favourable dependence selected using the 'Sequential Error Ratio' criteria. The error rates are better estimated by incorporating user-dependent (such as speaker-dependent thresholds and speaker-specific digit combinations) and class-dependent (such as clientimpostor dependent favourable combinations and class-error based threshold estimation) information. The proposed architecture is desirable in most of the speaker verification applications such as remote authentication, telephone and internet shopping applications. The tuning of parameters - the number of instances and samples - serve both the security and user convenience requirements of speaker-specific verification. The architecture investigated here is applicable to verification using other biometric modalities such as handwriting, fingerprints and key strokes.
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Development and application of inorganic adsorbent materials have been continuously investigated due to their variability and versatility. This Master thesis has expanded the knowledge in the field of adsorption targeting radioactive iodine waste and proteins using modified inorganic materials. Industrial treatment of radioactive waste and safety disposal of nuclear waste is a constant concern around the world with the development of radioactive materials applications. To address the current problems, laminar titanate with large surface area (143 m2 g−1) was synthesized from inorganic titanium compounds by hydrothermal reactions at 433 K. Ag2O nanocrystals of particle size ranging from 5–30 nm were anchored on the titanate lamina surface which has crystallographic similarity to that of Ag2O nanocrystals. Therefore, the deposited Ag2O nanocrystals and titanate substrate could join together at these surfaces between which there forms a coherent interface. Such coherence between the two phases reduces the overall energy by minimizing surface energy and maintains the Ag2O nanocrystals firmly on the outer surface of the titanate structure. The combined adsorbent was then applied as efficient adsorbent to remove radioactive iodine from water (one gram adsorbent can capture up to 3.4 mmol of I- anions) and the composite adsorbent can be recovered easily for safe disposal. The structure changes of the titanate lamina and the composite adsorbent were characterized via various techniques. The isotherm and kinetics of iodine adsorption, competitive adsorption and column adsorption using the adsorbent were studied to determine the iodine removal abilities of the adsorbent. It is shown that the adsorbent exhibited excellent trapping ability towards iodine in the fix-bed column despite the presence of competitive ions. Hence, Ag2O deposited titanate lamina could serve as an effective adsorbent for removing iodine from radioactive waste. Surface hydroxyl group of the inorganic materials is widely applied for modification purposes and modification of inorganic materials for biomolecule adsorption can also be achieved. Specifically, γ-Al2O3 nanofibre material is converted via calcinations from boehmite precursor which is synthesised by hydrothermal chemical reactions under directing of surfactant. These γ-Al2O3 nanofibres possess large surface area (243 m2 g-1), good stability under extreme chemical conditions, good mechanical strength and rich surface hydroxyl groups making it an ideal candidate in industrialized separation column. The fibrous morphology of the adsorbent also guarantees facile recovery from aqueous solution under both centrifuge and sedimentation approaches. By chemically bonding the dyes molecules, the charge property of γ-Al2O3 is changed in the aim of selectively capturing of lysozyme from chicken egg white solution. The highest Lysozyme adsorption amount was obtained at around 600 mg/g and its proportion is elevated from around 5% to 69% in chicken egg white solution. It was found from the adsorption test under different solution pH that electrostatic force played the key role in the good selectivity and high adsorption rate of surface modified γ-Al2O3 nanofibre adsorbents. Overall, surface modified fibrous γ-Al2O3 could be applied potentially as an efficient adsorbent for capturing of various biomolecules.
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This thesis offered a step forward in the development of cheap and effective materials for water treatment. It described the modification of naturally abundant clay minerals with organic molecules, and used the modified clays as effective adsorbents for the removal of recalcitrant organic water pollutants. The outcome of the study greatly extended our understanding of the synthesis and characteristic properties of clay and modified clay minerals, provided optimistic evaluation of the modified clays for environmental remediation and offered potential utility for clay minerals in the industry and environment.