An extended regression approach to estimating loads and their uncertainties in Great Barrier Reef catchments

There are numerous load estimation methods available, some of which are captured in various online tools. However, most estimators are subject to large biases statistically, and their associated uncertainties are often not reported. This makes interpretation difficult and the estimation of trends or determination of optimal sampling regimes impossible to assess. In this paper, we first propose two indices for measuring the extent of sampling bias, and then provide steps for obtaining reliable load estimates by minimizing the biases and making use of possible predictive variables. The load estimation procedure can be summarized by the following four steps: - (i) output the flow rates at regular time intervals (e.g. 10 minutes) using a time series model that captures all the peak flows; - (ii) output the predicted flow rates as in (i) at the concentration sampling times, if the corresponding flow rates are not collected; - (iii) establish a predictive model for the concentration data, which incorporates all possible predictor variables and output the predicted concentrations at the regular time intervals as in (i), and; - (iv) obtain the sum of all the products of the predicted flow and the predicted concentration over the regular time intervals to represent an estimate of the load. The key step to this approach is in the development of an appropriate predictive model for concentration. This is achieved using a generalized regression (rating-curve) approach with additional predictors that capture unique features in the flow data, namely the concept of the first flush, the location of the event on the hydrograph (e.g. rise or fall) and cumulative discounted flow. The latter may be thought of as a measure of constituent exhaustion occurring during flood events. The model also has the capacity to accommodate autocorrelation in model errors which are the result of intensive sampling during floods. Incorporating this additional information can significantly improve the predictability of concentration, and ultimately the precision with which the pollutant load is estimated. We also provide a measure of the standard error of the load estimate which incorporates model, spatial and/or temporal errors. This method also has the capacity to incorporate measurement error incurred through the sampling of flow. We illustrate this approach using the concentrations of total suspended sediment (TSS) and nitrogen oxide (NOx) and gauged flow data from the Burdekin River, a catchment delivering to the Great Barrier Reef. The sampling biases for NOx concentrations range from 2 to 10 times indicating severe biases. As we expect, the traditional average and extrapolation methods produce much higher estimates than those when bias in sampling is taken into account.

Assessment of quality defects in macadamia kernels using NIR spectroscopy

Spectral data were collected of intact and ground kernels using 3 instruments (using Si-PbS, Si, and InGaAs detectors), operating over different areas of the spectrum (between 400 and 2500 nm) and employing transmittance, interactance, and reflectance sample presentation strategies. Kernels were assessed on the basis of oil and water content, and with respect to the defect categories of insect damage, rancidity, discoloration, mould growth, germination, and decomposition. Predictive model performance statistics for oil content models were acceptable on all instruments (R2 > 0.98; RMSECV < 2.5%, which is similar to reference analysis error), although that for the instrument employing reflectance optics was inferior to models developed for the instruments employing transmission optics. The spectral positions for calibration coefficients were consistent with absorbance due to the third overtones of CH2 stretching. Calibration models for moisture content in ground samples were acceptable on all instruments (R2 > 0.97; RMSECV < 0.2%), whereas calibration models for intact kernels were relatively poor. Calibration coefficients were more highly weighted around 1360, 740 and 840 nm, consistent with absorbance due to overtones of O-H stretching and combination. Intact kernels with brown centres or rancidity could be discriminated from each other and from sound kernels using principal component analysis. Part kernels affected by insect damage, discoloration, mould growth, germination, and decomposition could be discriminated from sound kernels. However, discrimination among these defect categories was not distinct and could not be validated on an independent set. It is concluded that there is good potential for a low cost Si photodiode array instrument to be employed to identify some quality defects of intact macadamia kernels and to quantify oil and moisture content of kernels in the process laboratory and for oil content in-line. Further work is required to examine the robustness of predictive models across different populations, including growing districts, cultivars and times of harvest.

Non-destructive prediction of 'Hass' avocado dry matter via FT-NIR spectroscopy.

BACKGROUND: The inability to consistently guarantee internal quality of horticulture produce is of major importance to the primary producer, marketers and ultimately the consumer. Currently, commercial avocado maturity estimation is based on the destructive assessment of percentage dry matter (%DM), and sometimes percentage oil, both of which are highly correlated with maturity. In this study the utility of Fourier transform (FT) near-infrared spectroscopy (NIRS) was investigated for the first time as a non-invasive technique for estimating %DM of whole intact 'Hass' avocado fruit. Partial least squares regression models were developed from the diffuse reflectance spectra to predict %DM, taking into account effects of intra-seasonal variation and orchard conditions. RESULTS: It was found that combining three harvests (early, mid and late) from a single farm in the major production district of central Queensland yielded a predictive model for %DM with a coefficient of determination for the validation set of 0.76 and a root mean square error of prediction of 1.53% for DM in the range 19.4-34.2%. CONCLUSION: The results of the study indicate the potential of FT-NIRS in diffuse reflectance mode to non-invasively predict %DM of whole 'Hass' avocado fruit. When the FT-NIRS system was assessed on whole avocados, the results compared favourably against data from other NIRS systems identified in the literature that have been used in research applications on avocados.

Predicting the cost of eradication for 41 Class 1 declared weeds in Queensland

The feasibility of state-wide eradication of 41 invasive plant taxa currently listed as ‘Class 1 declared pests’ under the Queensland Land Protection (Pest and Stock Route Management) Act 2002 was assessed using the predictive model ‘WeedSearch’. Results indicated that all but one species (Alternanthera philoxeroides) could be eradicated, provided sufficient funding and labour were available. Slightly less than one quarter (24.4%) (n = 10) of Class 1 weed taxa could be eradicated for less than $100 000 per taxon. An additional 43.9% (n = 18) could be eradicated for between $100 000 and $1M per taxon. Hence, 68.3% of Class 1 weed taxa (n = 28) could be eradicated for less than $1M per taxon. Eradication of 29.3% (n = 12) is predicted to cost more than $1M per taxon. Comparison of these WeedSearch outputs with either empirical analysis or results from a previous application of the model suggests that these costs may, in fact, be underestimates. Considering the likelihood that each weed will cost the state many millions of dollars in long-term losses (e.g. losses to primary production, environmental impacts and control costs), eradication seems a wise investment. Even where predicted costs are over $1M, eradication can still offer highly favourable benefit:cost ratios. The total (cumulative) cost of eradication of all 41 weed taxa is substantial; for all taxa, the estimated cost of eradication in the first year alone is $8 618 000. This study provides important information for policy makers, who must decide where to invest public funding.

Better Macadamia Crop Forecasting - Part 2

The continually expanding macadamia industry needs an accurate crop forecasting system to allow it to develop effective crop handling and marketing strategies, particularly when the industry faces recurring cycles of unsustainably high and low commodity prices. This project aims to provide the AMS with a robust, reliable predictive model of national crop volume within 10% of the actual crop by 1 April each year by factoring known seasonal, environmental, cultural, climatic, management and biological constraints, together with the existing AMS database which includes data on tree numbers, tree age, variety, location and previous season's production.

Otolith morphology of four mackerel species (Scomberomorus spp.) in Australia: Species differentiation and prediction for fisheries monitoring and assessment

Four species of large mackerels (Scomberomorus spp.) co-occur in the waters off northern Australia and are important to fisheries in the region. State fisheries agencies monitor these species for fisheries assessment; however, data inaccuracies may exist due to difficulties with identification of these closely related species, particularly when specimens are incomplete from fish processing. This study examined the efficacy of using otolith morphometrics to differentiate and predict among the four mackerel species off northeastern Australia. Seven otolith measurements and five shape indices were recorded from 555 mackerel specimens. Multivariate modelling including linear discriminant analysis (LDA) and support vector machines, successfully differentiated among the four species based on otolith morphometrics. Cross validation determined a predictive accuracy of at least 96% for both models. An optimum predictive model for the four mackerel species was an LDA model that included fork length, feret length, feret width, perimeter, area, roundness, form factor and rectangularity as explanatory variables. This analysis may improve the accuracy of fisheries monitoring, the estimates based on this monitoring (i.e. mortality rate) and the overall management of mackerel species in Australia.

Prediction of breakout noise from an elliptical duct of finite length

This paper describes a predictive model for breakout noise from an elliptical duct or shell of finite length. The transmission mechanism is essentially that of ``mode coupling'', whereby higher structural modes in the duct walls get excited because of non-circularity of the wall. Effect of geometry has been taken care of by evaluating Fourier coefficients of the radius of curvature. The noise radiated from the duct walls is represented by that from a finite vibrating length of a semi infinite cylinder in a free field. Emphasis is on understanding the physics of the problem as well as analytical modeling. The analytical model is validated with 3-D FEM. Effects of the ovality, curvature, and axial terminations of the duct have been demonstrated. (C) 2010 Institute of Noise Control Engineering.

Rannansiirtyminen ja ihmisen toimintaympäristön muutos Mätäjokilaakson alueella esihistoriallisella ajalla

In this thesis, I study the changing ladscape and human environment of the Mätäjoki Valley, West-Helsinki, using reconstructions and predictive modelling. The study is a part of a larger project funded by the city of Helsinki aming to map the past of the Mätäjoki Valley. The changes in landscape from an archipelago in the Ancylus Lake to a river valley are studied from 10000 to 2000 years ago. Alongside shore displacement, we look at the changing environment from human perspective and predict the location of dwelling sitesat various times. As a result, two map series were produced that show how the landscape changed and where inhabitance is predicted. To back them up, we have also looked at what previous research says about the history of the waterways, climate, vegetation and archaeology. The changing landscape of the river valley is reconstructed using GIS methods. For this purpose, new laser point data set was used and at the same time tested in the context landscape modelling. Dwelling sites were modeled with logistic regression analysis. The spatial predictive model combines data on the locations of the known dwelling sites, environmental factors and shore displacement data. The predictions were visualised into raster maps that show the predictions for inhabitance 3000 and 5000 years ago. The aim of these maps was to help archaeologists map potential spots for human activity. The produced landscape reconstructions clarified previous shore displacement studies of the Mätäjoki region and provided new information on the location of shoreline. From the shore displacement history of the Mätäjoki Valley arise the following stages: 1. The northernmost hills of the Mätäjoki Valley rose from Ancylus Lake approximately 10000 years ago. Shore displacement was fast during the following thousand years. 2. The area was an archipelago with a relatively steady shoreline 9000 7000 years ago. 8000 years ago the shoreline drew back in the middle and southern parts of the river valley because of the transgression of the Litorina Sea. 3. Mätäjoki was a sheltered bay of the Litorina Sea 6000 5000 years ago. The Vantaanjoki River started to flow into the Mätäjoki Valley approximately 5000 years ago. 4. The sediment plains in the southern part of the river valley rose from the sea rather quickly 5000 3000 years ago. Salt water still pushed its way into the southermost part of the valley 4000 years ago. 5. The shoreline proceeded to Pitäjänmäki rapids where it stayed at least a thousand years 3000 2000 years ago. The predictive models managed to predict the locations of dwelling sites moderately well. The most accurate predictions were found on the eastern shore and Malminkartano area. Of the environment variables sand and aspect of slope were found to have the best predictive power. From the results of this study we can conclude that the Mätäjoki Valley has been a favorable location to live especially 6000 5000 years ago when the climate was mild and vegetation lush. The laser point data set used here works best in shore displacement studies located in rural areas or if further specific palaeogeographic or hydrologic analysis in the research area is not needed.

Avances analíticos en la datación forense de tintas y documentos

380 p. : il., gráf.

The logic of receptor-ligand interactions in the Notch signaling pathway

The Notch signaling pathway enables neighboring cells to coordinate developmental fates in diverse processes such as angiogenesis, neuronal differentiation, and immune system development. Although key components and interactions in the Notch pathway are known, it remains unclear how they work together to determine a cell's signaling state, defined as its quantitative ability to send and receive signals using particular Notch receptors and ligands. Recent work suggests that several aspects of the system can lead to complex signaling behaviors: First, receptors and ligands interact in two distinct ways, inhibiting each other in the same cell (in cis) while productively interacting between cells (in trans) to signal. The ability of a cell to send or receive signals depends strongly on both types of interactions. Second, mammals have multiple types of receptors and ligands, which interact with different strengths, and are frequently co-expressed in natural systems. Third, the three mammalian Fringe proteins can modify receptor-ligand interaction strengths in distinct and ligand-specific ways. Consequently, cells can exhibit non-intuitive signaling states even with relatively few components.

In order to understand what signaling states occur in natural processes, and what types of signaling behaviors they enable, this thesis puts forward a quantitative and predictive model of how the Notch signaling state is determined by the expression levels of receptors, ligands, and Fringe proteins. To specify the parameters of the model, we constructed a set of cell lines that allow control of ligand and Fringe expression level, and readout of the resulting Notch activity. We subjected these cell lines to an assay to quantitatively assess the levels of Notch ligands and receptors on the surface of individual cells. We further analyzed the dependence of these interactions on the level and type of Fringe expression. We developed a mathematical modeling framework that uses these data to predict the signaling states of individual cells from component expression levels. These methods allow us to reconstitute and analyze a diverse set of Notch signaling configurations from the bottom up, and provide a comprehensive view of the signaling repertoire of this major signaling pathway.

Desenvolvimento e validação de modelo preditivo e avaliação de testes de diagnóstico por classe latente para o parasitismo por L. chagasi em cães atendidos no Hospital Veterinário Universitário da UFPI, Teresina

A leishmaniose visceral americana (LVA) é uma doença em expansão no Brasil, para a qual se dispõem de poucas, e aparentemente ineficientes, estratégias de controle. Um dos grandes problemas para a contenção da leishmaniose visceral americana é a falta de um método acurado de identificação dos cães infectados, considerados os principais reservatórios da doença no meio urbano. Neste sentido, a caracterização de marcadores clínico-laboratoriais da infecção neste reservatório e a avaliação mais adequada do desempenho de testes para diagnóstico da infecção podem contribuir para aumentar a efetividade das estratégias de controle da LVA. Com isso, o presente estudo tem dois objetivos principais: (1) desenvolver e validar um modelo de predição para o parasitismo por Leishmania chagasi em cães, baseado em resultados de testes sorológicos e sinais clínicos e (2) avaliar a sensibilidade e especificidade de critérios clínicos, sorológicos e parasitológicos para detecção de infecção canina por L. chagasi mediante análise de classe latente. O primeiro objetivo foi desenvolvido a partir de estudo em que foram obtidos dados de exames clínico, sorológico e parasitológico de todos os cães, suspeitos ou não de LVA, atendidos no Hospital Veterinário Universitário da Universidade Federal do Piauí (HVU-UFPI), em Teresina, nos anos de 2003 e 2004, totalizando 1412 animais. Modelos de regressão logística foram construídos com os animais atendidos em 2003 com a finalidade de desenvolver um modelo preditivo para o parasitismo com base nos sinais clínicos e resultados de sorologia por Imunofluorescência Indireta (IFI). Este modelo foi validado nos cães atendidos no hospital em 2004. Para a avaliação da área abaixo da curva ROC (auROC), sensibilidade, especificidade, valores preditivos positivo (VPP), valores preditivos negativo (VPN) e acurácia global, foram criados três modelos: um somente baseado nas variáveis clínicas, outro considerando somente o resultado sorológico e um último considerando conjuntamente a clínica e a sorologia. Dentre os três, o último modelo apresentou o melhor desempenho (auROC=90,1%, sensibilidade=82,4%, especificidade=81,6%, VPP=73,4%, VPN=88,2% e acurácia global=81,9%). Conclui-se que o uso de modelos preditivos baseados em critérios clínicos e sorológicos para o diagnóstico da leishmaniose visceral canina pode ser de utilidade no processo de avaliação da infecção canina, promovendo maior agilidade na contenção destes animais com a finalidade de reduzir os níveis de transmissão. O segundo objetivo foi desenvolvido por meio de um estudo transversal com 715 cães de idade entre 1 mês e 13 anos, com raça variada avaliados por clínicos veterinários no HVU-UFPI, no período de janeiro a dezembro de 2003. As sensibilidades e especificidades de critérios clínicos, sorológicos e parasitológicos para detecção de infecção canina por Leishmania chagasi foram estimadas por meio de análise de classe latente, considerando quatro modelos de testes e diferentes pontos de corte. As melhores sensibilidades estimadas para os critérios clínico, sorológico e parasitológico foram de 60%, 95% e 66%, respectivamente. Já as melhores especificidades estimadas para os critérios clínico, sorológico e parasitológico foram de 77%, 90% e 100%, respectivamente. Conclui-se que o uso do exame parasitológico como padrão-ouro para validação de testes diagnósticos não é apropriado e que os indicadores de acurácia dos testes avaliados são insuficientes e não justificam que eles sejam usados isoladamente para diagnóstico da infecção com a finalidade de controle da doença.

Physiological Determinants of Invasive Success Linking Distribution Patterns to Metabolic Physiology in Native and Invasive Blue Mussels (genus Mytilus)

In the early 20th century, a blue mussel species from the Mediterranean invaded the California coast and subsequently out-competed the native species south of Monterey Bay. Like other invasive species, Mytilus galloprovincialis has physiological traits that make it successful in habitats formerly occupied by the native M. trossulus, namely its adaptation to warm sea surface temperatures. This study looks at the current genotype distributions and enzymatic activities of field-acclimatized mussels within the hybrid zone where the species co-occur as well as mussels that have been acclimated for four weeks to different temperature and salinity conditions. In the field-acclimatized and laboratory-acclimated mussels, the native species exhibited significantly higher enzyme rates, which may reflect an evolutionary adaptation to compensate to low habitat temperatures. Indeed, the results of the laboratory acclimation indicate that these differences are genetically based. Whether an acclimation capacity exists may require even longer-term acclimation to different temperatures. Current findings suggest that the further spread of the invasive species is likely to be governed in large measure by the potentially counteracting effects of rising temperatures, which would favor the northerly spread of M. galloprovincialis, and increased winter precipitation, which would favor the persistence of M. trossulus. However, the success of M. galloprovincialis during acclimation to ‘dilute’ salinity (25 ppt) suggests that the invasive species can tolerate a greater salinity range than previously thought. Thus, further investigation is needed to build a comprehensive predictive model of the movement of M. galloprovincialis and the hybrid zone along the California coast.

Medição experimental e previsão de velocidade do som de componentes de biocombustíveis

A velocidade do som é uma propriedade que vem sendo cada vez mais utilizada em diferentes áreas tecnológicas. Além disso, a velocidade do som é uma propriedade termodinâmica que está associada a outras propriedades do meio como a compressibilidade isentrópica e isotérmica, entre outras. Neste contexto, muitos estudos foram realizados a fim de obter modelos precisos que possam representar fielmente a velocidade do som, sendo observados desvios absolutos médios entre 0,13 e 24,8%. Neste trabalho, um banco de dados de velocidade do som e massa específica à pressão atmosférica de n-alcanos, alcanos ramificados, n-alcenos, aromáticos, alcoóis, éteres e ésteres, foram compilados da literatura aberta. Utilizando estes dados e baseando-se no modelo de Wada por contribuição de grupo recentemente proposto, foi desenvolvido um novo modelo por contribuição atômica para predizer a velocidade do som de todas as famílias dos compostos investigados neste trabalho. É mostrado que o modelo proposto é capaz de prever a velocidade do som para os compostos destas famílias com desvios próximos da incerteza experimental calculada a partir de diferentes dados da literatura. Este trabalho também discute o efeito da ramificação das cadeias na constante Wada, ressaltando a importância de novas medições para este tipo de compostos. Além disso, observou-se que a literatura necessita de mais dados experimentais de velocidade do som, à pressão atmosférica e diferentes temperaturas para substâncias puras presentes em biodiesel e bio-óleo de pirólise rápida. Neste contexto, o presente trabalho fornece novos dados experimentais de velocidade do som e massa específica de cinco ésteres metílicos de ácidos graxos, também conhecidos como FAMEs, (caprilato de metila, caprato de metila, palmitato de metila, estearato de metila e linoleato de metila), e sete componentes puros presentes em bio-óleo de pirólise à pressão atmosférica, de vários fenóis (fenol, o-, m- e p-cresol), dois éteres fenólicos (2-metoxifenol e eugenol) e um éster fenólico (salicilato de metila), a temperaturas de (288,15-343,15) K. O modelo preditivo de Wada atômico foi utilizado para calcular a velocidade do som dos FAMEs estudados neste trabalho, e os desvios foram comparados com o modelo de Wada por contribuição de grupo. O modelo atômico de Wada foi utilizado para prever a velocidade do som dos componentes puros presentes no bio-óleo de pirólise rápida experimentalmente estudados nesta dissertação. Além disso, os dados de massa específica e velocidade de som foram correlacionados com o modelo de Prigogine-Flory-Patterson (PFP). As propriedades foram bem representadas pelo modelo PFP, no entanto, para a velocidade do som o modelo apresenta desvios sistemáticos na dependência com a temperatura. O desempenho do modelo preditivo de Wada atômico foi considerado satisfatório, devido os desvios observados serem compatíveis ou até menores do que os desvios típicos obtidos na literatura com outros modelos correlativos para o cálculo da velocidade do som de outras substâncias

Proposal and validation of methodologies for the categorisation of continuous variables in the development of prediction models

158 p.

Modelagem da tensão superficial de misturas de hidrocarbonetos

Esta dissertação apresenta um novo modelo criado para a previsão do valor da tensão superficial de misturas de hidrocarbonetos. Pode ser utilizado na forma preditiva ou correlativa. Este modelo foi baseado no modelo preditivo para soluções ideais de HildebrandScott (1950) e no modelo correlativo de JouybanAcree (2004). Outras regras de mistura foram avaliadas e comparadas com o modelo proposto, incluindo abordagens clássicas como de Sprow e Prausnitz, parácoro e estados correspondentes. Foram avaliados os desempenhos dos modelos escolhidos na previsão e na correlação da tensão superficial de misturas de hidrocarbonetos em diferentes temperaturas que continham diferentes assimetrias na mistura, tanto em natureza química (e.g., parafínicos, naftênicos e aromáticos) quanto em tamanho de cadeia. No total foram empregados 773 dados experimentais. Dentre os modelos preditivos, o modelo proposto foi o de melhor desempenho. Para sistemas com comportamento próximo da idealidade, esse modelo apresentou desvios em relação aos dados experimentais compatíveis com o erro experimental. Todos os modelos correlativos estudados apresentaram desvios essencialmente da ordem do erro experimental. O modelo proposto é importante, pois é capaz de prever a tensão superficial de misturas binárias aproximadamente ideais de hidrocarbonetos com elevada acurácia, além de permitir a correlação eficiente dos dados de todas as misturas estudadas