A principled experimental design approach to Big Data analysis

Big Datasets are endemic, but they are often notoriously difficult to analyse because of their size, heterogeneity, history and quality. The purpose of this paper is to open a discourse on the use of modern experimental design methods to analyse Big Data in order to answer particular questions of interest. By appealing to a range of examples, it is suggested that this perspective on Big Data modelling and analysis has wide generality and advantageous inferential and computational properties. In particular, the principled experimental design approach is shown to provide a flexible framework for analysis that, for certain classes of objectives and utility functions, delivers near equivalent answers compared with analyses of the full dataset under a controlled error rate. It can also provide a formalised method for iterative parameter estimation, model checking, identification of data gaps and evaluation of data quality. Finally, it has the potential to add value to other Big Data sampling algorithms, in particular divide-and-conquer strategies, by determining efficient sub-samples.

Dynamic, invivo, real-time detection of retinal oxidative status in a model of elevated intraocular pressure using a novel, reversibly responsive, profluorescent nitroxide probe

Changes to the redox status of biological systems have been implicated in the pathogenesis of a wide variety of disorders including cancer, Ischemia-reperfusion (I/R) injury and neurodegeneration. In times of metabolic stress e.g. ischaemia/reperfusion, reactive oxygen species (ROS) production overwhelms the intrinsic antioxidant capacity of the cell, damaging vital cellular components. The ability to quantify ROS changes in vivo, is therefore essential to understanding their biological role. Here we evaluate the suitability of a novel reversible profluorescent probe containing a redox-sensitive nitroxide moiety (methyl ester tetraethylrhodamine nitroxide, ME-TRN), as an in vivo, real-time reporter of retinal oxidative status. The reversible nature of the probe's response offers the unique advantage of being able to monitor redox changes in both oxidizing and reducing directions in real time. After intravitreal administration of the ME-TRN probe, we induced ROS production in rat retina using an established model of complete, acute retinal ischaemia followed by reperfusion. After restoration of blood flow, retinas were imaged using a Micron III rodent fundus fluorescence imaging system, to quantify the redox-response of the probe. Fluorescent intensity declined during the first 60 min of reperfusion. The ROS-induced change in probe fluorescence was ameliorated with the retinal antioxidant, lutein. Fluorescence intensity in non-Ischemia eyes did not change significantly. This new probe and imaging technology provide a reversible and real-time response to oxidative changes and may allow the in vivo testing of antioxidant therapies of potential benefit to a range of diseases linked to oxidative stress

Microscopic cooperative traffic flow: Calibration and simulation based on a next generation simulation dataset

The deployment of new emerging technologies, such as cooperative systems, allows the traffic community to foresee relevant improvements in terms of traffic safety and efficiency. Autonomous vehicles are able to share information about the local traffic state in real time, which could result in a better reaction to the mechanism of traffic jam formation. An upstream single-hop radio broadcast network can improve the perception of each cooperative driver within a specific radio range and hence the traffic stability. The impact of vehicle to vehicle cooperation on the onset of traffic congestion is investigated analytically and through simulation. A next generation simulation field dataset is used to calibrate the full velocity difference car-following model, and the MOBIL lane-changing model is implemented. The robustness of the calibration as well as the heterogeneity of the drivers is discussed. Assuming that congestion can be triggered either by the heterogeneity of drivers' behaviours or abnormal lane-changing behaviours, the calibrated car-following model is used to assess the impact of a microscopic cooperative law on egoistic lane-changing behaviours. The cooperative law can help reduce and delay traffic congestion and can have a positive effect on safety indicators.

5-year Chlamydia vaccination programme could reverse disease-related koala population decline: Predictions from a mathematical model using field data

BACKGROUND Many koala populations around Australia are in serious decline, with a substantial component of this decline in some Southeast Queensland populations attributed to the impact of Chlamydia. A Chlamydia vaccine for koalas is in development and has shown promise in early trials. This study contributes to implementation preparedness by simulating vaccination strategies designed to reverse population decline and by identifying which age and sex category it would be most effective to target. METHODS We used field data to inform the development and parameterisation of an individual-based stochastic simulation model of a koala population endemic with Chlamydia. The model took into account transmission, morbidity and mortality caused by Chlamydia infections. We calibrated the model to characteristics of typical Southeast Queensland koala populations. As there is uncertainty about the effectiveness of the vaccine in real-world settings, a variety of potential vaccine efficacies, half-lives and dosing schedules were simulated. RESULTS Assuming other threats remain constant, it is expected that current population declines could be reversed in around 5-6 years if female koalas aged 1-2 years are targeted, average vaccine protective efficacy is 75%, and vaccine coverage is around 10% per year. At lower vaccine efficacies the immunological effects of boosting become important: at 45% vaccine efficacy population decline is predicted to reverse in 6 years under optimistic boosting assumptions but in 9 years under pessimistic boosting assumptions. Terminating a successful vaccination programme at 5 years would lead to a rise in Chlamydia prevalence towards pre-vaccination levels. CONCLUSION For a range of vaccine efficacy levels it is projected that population decline due to endemic Chlamydia can be reversed under realistic dosing schedules, potentially in just 5 years. However, a vaccination programme might need to continue indefinitely in order to maintain Chlamydia prevalence at a sufficiently low level for population growth to continue.

A Model to Estimate the Population Contributing to the Wastewater Using Samples Collected on Census Day

An important uncertainty when estimating per capita consumption of, for example, illicit drugs by means of wastewater analysis (sometimes referred to as “sewage epidemiology”) relates to the size and variability of the de facto population in the catchment of interest. In the absence of a day-specific direct population count any indirect surrogate model to estimate population size lacks a standard to assess associated uncertainties. Therefore, the objective of this study was to collect wastewater samples at a unique opportunity, that is, on a census day, as a basis for a model to estimate the number of people contributing to a given wastewater sample. Mass loads for a wide range of pharmaceuticals and personal care products were quantified in influents of ten sewage treatment plants (STP) serving populations ranging from approximately 3500 to 500 000 people. Separate linear models for population size were estimated with the mass loads of the different chemical as the explanatory variable: 14 chemicals showed good, linear relationships, with highest correlations for acesulfame and gabapentin. De facto population was then estimated through Bayesian inference, by updating the population size provided by STP staff (prior knowledge) with measured chemical mass loads. Cross validation showed that large populations can be estimated fairly accurately with a few chemical mass loads quantified from 24-h composite samples. In contrast, the prior knowledge for small population sizes cannot be improved substantially despite the information of multiple chemical mass loads. In the future, observations other than chemical mass loads may improve this deficit, since Bayesian inference allows including any kind of information relating to population size.

A Synthetic Model for the Inhibition of Glutathione Peroxidase by Antiarthritic Gold Compounds

In this paper, inhibition of the glutathione peroxidase activity of two synthetic organoselenium compounds, bis[2-(N,N-dimethylamino)benzyl]diselenide (5) and bis[2-(N,N-dimethylamino)benzyl]selenide (9), by gold(I) thioglucose (1), chloro(triethylphosphine)gold(I), chloro(trimethylphosphine)gold(I), and chloro(triphenylphosphine)gold(I) is described. The inhibition is found to be competitive with respect to a peroxide (H2O2) substrate and noncompetitive with respect to a thiol (PhSH) cosubstrate. The diselenide 5 reacts with PhSH to produce the corresponding selenol (6), which upon treatment with 1 equiv of gold(I) chlorides produces the corresponding gold selenolate complexes 11−13. However, the addition of 1 equiv of selenol 6 to complexes 11−13 leads to the formation of bis-selenolate complex 14 by ligand displacement reactions involving the elimination of phosphine ligands. The phosphine ligands eliminated from these reactions are further converted to the corresponding phosphine oxides (R3PO) and selenides (R3PSe). In addition to the replacement of the phosphine ligand by selenol 6, an interchange between two different phosphine ligands is also observed. For example, the reaction of complex 11 having a trimethylphosphine ligand with triphenylphosphine produces complex 13 by phosphine interchange reactions via the formation of intermediates 15 and 16. The reactivity of selenol 6 toward gold(I) phosphines is found to be similar to that of selenocysteine.

Rapid assessment of genotype-by-environment interactions and heritability for growth rate in aquaculture species using in vitro fertilisation and DNA tagging

Commercial environments may receive only a fraction of expected genetic gains for growth rate as predicted from the selection environment This fraction is the result of undesirable genotype-by-environment interactions (G x E) and measured by the genetic correlation (r(g)) of growth between environments. Rapid estimates of genetic correlation achieved in one generation are notoriously difficult to estimate with precision. A new design is proposed where genetic correlations can be estimated by utilising artificial mating from cryopreserved semen and unfertilised eggs stripped from a single female. We compare a traditional phenotype analysis of growth to a threshold model where only the largest fish are genotyped for sire identification. The threshold model was robust to differences in family mortality differing up to 30%. The design is unique as it negates potential re-ranking of families caused by an interaction between common maternal environmental effects and growing environment. The design is suitable for rapid assessment of G x E over one generation with a true 0.70 genetic correlation yielding standard errors as low as 0.07. Different design scenarios were tested for bias and accuracy with a range of heritability values, number of half-sib families created, number of progeny within each full-sib family, number of fish genotyped, number of fish stocked, differing family survival rates and at various simulated genetic correlation levels

Accounting for individual variability in the von Bertalanffy growth model

Estimation of von Bertalanffy growth parameters has received considerable attention in fisheries research. Since Sainsbury (1980, Can. J. Fish. Aquat. Sci. 37: 241-247) much of this research effort has centered on accounting for individual variability in the growth parameters. In this paper we demonstrate that, in analysis of tagging data, Sainsbury's method and its derivatives do not, in general, satisfactorily account for individual variability in growth, leading to inconsistent parameter estimates (the bias does not tend to zero as sample size increases to infinity). The bias arises because these methods do not use appropriate conditional expectations as a basis for estimation. This bias is found to be similar to that of the Fabens method. Such methods would be appropriate only under the assumption that the individual growth parameters that generate the growth increment were independent of the growth parameters that generated the initial length. However, such an assumption would be unrealistic. The results are derived analytically, and illustrated with a simulation study. Until techniques that take full account of the appropriate conditioning have been developed, the effect of individual variability on growth has yet to be fully understood.

Validation of a 4DOF manoeuvring model of a high-speed vehicle-passenger trimaran

This paper presents the validation of a manoeuvring model for a novel 127m-vehicle-passenger trimaran via full scale trials. The adopted structure of the model is based on a model previously proposed in the literature with some simplifications. The structure of the model is discussed. Then initial parameter estimates are computed, and the final set of parameters are obtained via adjustments based on engineering judgement and application of a genetic algorithm so as to match the data of the trials. The validity of the model is also assessed with data from a trial different from the one use for the parameter adjustment. The model shows good agreement with the trial data.

Assessment of internal quality attributes of mandarin fruit. 2. NIR calibration model robustness

The robustness of multivariate calibration models, based on near infrared spectroscopy, for the assessment of total soluble solids (TSS) and dry matter (DM) of intact mandarin fruit (Citrus reticulata cv. Imperial) was assessed. TSS calibration model performance was validated in terms of prediction of populations of fruit not in the original population (different harvest days from a single tree, different harvest localities, different harvest seasons). Of these, calibration performance was most affected by validation across seasons (signal to noise statistic on root mean squared error of prediction of 3.8, compared with 20 and 13 for locality and harvest day, respectively). Procedures for sample selection from the validation population for addition to the calibration population (‘model updating’) were considered for both TSS and DM models. Random selection from the validation group worked as well as more sophisticated selection procedures, with approximately 20 samples required. Models that were developed using samples at a range of temperatures were robust in validation for TSS and DM.

Rationale of Length Scale-Down Model Span Testing of Transmission Lines

Length scale-down (LS) model tests have been traditionally employed for laboratory studies on aeolian vibration of transmission line conductors. The span adopted is normally 30 m and is recommended by the relevant Indian, as well as other, standards. The traditionally adopted length of the LS model is reexamined herein to establish the rationale behind the choice. Based on the theoretical studies discussed, certain guidelines for the choice of model span of conductor are emphasized. In addition, the adequacy of the LS span as a tool for predicting the performance of the full span is reestablished.

Evaluation of Australian Performing Arts Market 2014-2018 REPORT TWO APAM inter-year report 2015 DECEMBER

The report follows up on data and trends tabled in August 2015 that collected data from two key sources – six identified case study productions that have been tracked for eighteen months, and an online survey delivered to all APAM 2014 delegates. The comparative report has been constructed through an analysis of data reported from the August 2015 and the most recent online survey to all 2104 PM delegates conducted in late November 2015. The report highlights six key trends emerging from the data: The majority of survey respondents will return to APAM 2016; The central reason for attending is the networking opportunities the Market affords; Respondents are confident that a range of new relationships forged at the Market will afford long-term interest and buying opportunities and that as a result of the 2014 event, real touring outcomes were realised for some respondents; Respondents would like to see greater attention to a greater number of networking activities within the program to enable touring outcomes; The multi-venue model is still of concern, and is a recurrent issue from earlier surveys; The level of expense incurred by producers to present work at APAM. Throughout the report, extracted data from the online survey responses will be tabled to develop a narrative in response to the key research aims outlined in the Brisbane Powerhouse Tender document (2011). A full version of the collated responses to the survey questions can be found in the appendices of the report.

Development of a vaccine for Chlamydia trachomatis: Challenges and current progress

Chlamydia trachomatis remains an enigmatic bacterial pathogen with no vaccine yet available to treat human ocular and genital tract infections caused by tissue-tropic serovars of the organism. Globally, it is the leading cause of preventable blindness as well as the leading cause of bacterial sexually transmitted infections. The pathogen has a range of virulence factors that enable it to successfully evade both the innate and adaptive immune system of the host. The host immune system, although protective, paradoxically is also associated closely with the pathologies of trachoma and pelvic inflammatory disease – disease sequelae of some chlamydial infections and reinfections in some genetically susceptible hosts. In this review, we focus on what is known currently about the pathogenesis of ocular and genital infections caused by this mucosal pathogen. We also discuss novel insights into the pathogenesis of infections caused by the genital and ocular serovars of C. trachomatis, including a discussion of both pathogen and host factors, such as the human microbiota at these mucosal sites as well as the current immunological challenges facing vaccine development. Finally, we discuss the current progress toward development of a vaccine against C. trachomatis. A wide range of recombinant protein antigens are being identified and, hence, are available for vaccine trials. A plasmid-free live strain has recently been produced and evaluated in the mouse (Chlamydia muridarum) and monkey (C. trachomatis) models. The data for ocular infections in the monkey model was particularly encouraging, although the path to regulatory approval of a live vaccine is still uncertain. While still a major challenge, vaccines for ocular and genital C. trachomatis infections are looking more promising.

Developmental origins of psychological vulnerability factors for mental disorders

Premature birth and associated small body size are known to affect health over the life course. Moreover, compelling evidence suggests that birth size throughout its whole range of variation is inversely associated with risk for cardiovascular disease and type 2 diabetes in subsequent life. To explain these findings, the Developmental Origins of Health and Disease (DOHaD) model has been introduced. Within this framework, restricted physical growth is, to a large extent, considered either a product of harmful environmental influences, such as suboptimal nutrition and alterations in the foetal hormonal milieu, or an adaptive reaction to the environment. Whether inverse associations exist between body size at birth and psychological vulnerability factors for mental disorders is poorly known. Thus, the aim of this thesis was to study in three large prospective cohorts whether prenatal and postnatal physical growth, across the whole range of variation, is associated with subsequent temperament/personality traits and psychological symptoms that are considered vulnerability factors for mental disorders. Weight and length at birth in full term infants showed quadratic associations with the temperamental trait of harm avoidance (Study I). The highest scores were characteristic of the smallest individuals, followed by the heaviest/longest. Linear associations between birth size and psychological outcomes were found such that lower weight and thinness at birth predicted more pronounced trait anxiety in late adulthood (Study II); lower birth weight, placental size, and head circumference at 12 months predicted a more pronounced positive schitzotypal trait in women (Study III); and thinness and smaller head circumference at birth associated with symptoms of attention-deficit hyperactivity disorder (ADHD) in children who were born at term (Study IV). These associations occured across the whole variation in birth size and after adjusting for several confounders. With respect to growth after birth, individuals with high trait anxiety scores in late adulthood were lighter in weight and thinner in infancy, and gained weight more rapidly between 7 and 11 years of age, but weighed less and were shorter in late adulthood in relation to weight and height measured at 11 years of age (Study II). These results suggest that a suboptimal prenatal environment reflected in smaller birth size may affect a variety of psychological vulnerability factors for mental disorders, such as the temperamental trait of harm avoidance, trait anxiety, schizotypal traits, and symptoms of ADHD. The smaller the birth size across the whole range of variation, the more pronounced were these psychological vulnerability factors. Moreover, some of these outcomes, such as trait anxiety, were also predicted by patterns of growth after birth. The findings are concordant with the DOHaD model, and emphasise the importance of prenatal factors in the aetiology of not only mental disorders but also their psychological vulnerability factors.

Delineating environmental envelopes to improve mapping of species distributions, via a hurdle model with CART &/or MaxEnT

Species distribution modelling (SDM) typically analyses species’ presence together with some form of absence information. Ideally absences comprise observations or are inferred from comprehensive sampling. When such information is not available, then pseudo-absences are often generated from the background locations within the study region of interest containing the presences, or else absence is implied through the comparison of presences to the whole study region, e.g. as is the case in Maximum Entropy (MaxEnt) or Poisson point process modelling. However, the choice of which absence information to include can be both challenging and highly influential on SDM predictions (e.g. Oksanen and Minchin, 2002). In practice, the use of pseudo- or implied absences often leads to an imbalance where absences far outnumber presences. This leaves analysis highly susceptible to ‘naughty-noughts’: absences that occur beyond the envelope of the species, which can exert strong influence on the model and its predictions (Austin and Meyers, 1996). Also known as ‘excess zeros’, naughty noughts can be estimated via an overall proportion in simple hurdle or mixture models (Martin et al., 2005). However, absences, especially those that occur beyond the species envelope, can often be more diverse than presences. Here we consider an extension to excess zero models. The two-staged approach first exploits the compartmentalisation provided by classification trees (CTs) (as in O’Leary, 2008) to identify multiple sources of naughty noughts and simultaneously delineate several species envelopes. Then SDMs can be fit separately within each envelope, and for this stage, we examine both CTs (as in Falk et al., 2014) and the popular MaxEnt (Elith et al., 2006). We introduce a wider range of model performance measures to improve treatment of naughty noughts in SDM. We retain an overall measure of model performance, the area under the curve (AUC) of the Receiver-Operating Curve (ROC), but focus on its constituent measures of false negative rate (FNR) and false positive rate (FPR), and how these relate to the threshold in the predicted probability of presence that delimits predicted presence from absence. We also propose error rates more relevant to users of predictions: false omission rate (FOR), the chance that a predicted absence corresponds to (and hence wastes) an observed presence, and the false discovery rate (FDR), reflecting those predicted (or potential) presences that correspond to absence. A high FDR may be desirable since it could help target future search efforts, whereas zero or low FOR is desirable since it indicates none of the (often valuable) presences have been ignored in the SDM. For illustration, we chose Bradypus variegatus, a species that has previously been published as an exemplar species for MaxEnt, proposed by Phillips et al. (2006). We used CTs to increasingly refine the species envelope, starting with the whole study region (E0), eliminating more and more potential naughty noughts (E1–E3). When combined with an SDM fit within the species envelope, the best CT SDM had similar AUC and FPR to the best MaxEnt SDM, but otherwise performed better. The FNR and FOR were greatly reduced, suggesting that CTs handle absences better. Interestingly, MaxEnt predictions showed low discriminatory performance, with the most common predicted probability of presence being in the same range (0.00-0.20) for both true absences and presences. In summary, this example shows that SDMs can be improved by introducing an initial hurdle to identify naughty noughts and partition the envelope before applying SDMs. This improvement was barely detectable via AUC and FPR yet visible in FOR, FNR, and the comparison of predicted probability of presence distribution for pres/absence.