Efficient regression analysis with ranked-set sampling

This article is motivated by a lung cancer study where a regression model is involved and the response variable is too expensive to measure but the predictor variable can be measured easily with relatively negligible cost. This situation occurs quite often in medical studies, quantitative genetics, and ecological and environmental studies. In this article, by using the idea of ranked-set sampling (RSS), we develop sampling strategies that can reduce cost and increase efficiency of the regression analysis for the above-mentioned situation. The developed method is applied retrospectively to a lung cancer study. In the lung cancer study, the interest is to investigate the association between smoking status and three biomarkers: polyphenol DNA adducts, micronuclei, and sister chromatic exchanges. Optimal sampling schemes with different optimality criteria such as A-, D-, and integrated mean square error (IMSE)-optimality are considered in the application. With set size 10 in RSS, the improvement of the optimal schemes over simple random sampling (SRS) is great. For instance, by using the optimal scheme with IMSE-optimality, the IMSEs of the estimated regression functions for the three biomarkers are reduced to about half of those incurred by using SRS.

Numerical simulation of conductive particle behaviour at the surface of a plate electrode affected by a DC corona field

The electric field in certain electrostatic devices can be modeled by a grounded plate electrode affected by a corona discharge generated by a series of parallel wires connected to a DC high-voltage supply. The system of differential equations that describe the behaviour (i.e., charging and motion) of the conductive particle in such an electric field has been numerically solved, using several simplifying assumptions. Thus, it was possible to investigate the effect of various electrical and mechanical factors on the trajectories of conductive particles. This model has been employed to study the behaviour of coalparticles in fly-ash corona separators.

Efficient algorithms for computing Reeb graphs

The Reeb graph tracks topology changes in level sets of a scalar function and finds applications in scientific visualization and geometric modeling. We describe an algorithm that constructs the Reeb graph of a Morse function defined on a 3-manifold. Our algorithm maintains connected components of the two dimensional levels sets as a dynamic graph and constructs the Reeb graph in O(nlogn+nlogg(loglogg)3) time, where n is the number of triangles in the tetrahedral mesh representing the 3-manifold and g is the maximum genus over all level sets of the function. We extend this algorithm to construct Reeb graphs of d-manifolds in O(nlogn(loglogn)3) time, where n is the number of triangles in the simplicial complex that represents the d-manifold. Our result is a significant improvement over the previously known O(n2) algorithm. Finally, we present experimental results of our implementation and demonstrate that our algorithm for 3-manifolds performs efficiently in practice.

Simulation of the supply capability of sheep on the Mitchell grass downs of north west Queensland

Sheep in western Queensland have been predominantly reared for wool. When wool prices became depressed interest in the sheep meat industry, increased. For north west Queensland producers, opportunities may exist to participate in live sheep and meat export to Asia. A simulation model was developed to determine whether this sheep producing area has the capability to provide sufficient numbers of sheep under variable climatic conditions while sustaining the land resources. Maximum capacity for sustainability of resources (as described by stock numbers) was derived from an in-depth study of the agricultural and pastoral potential of Queensland. Decades of sheep production and climatic data spanning differing seasonal conditions were collated for analysis. A ruminant biology model adapted from Grazplan was used to simulate pregnancy rate. Empirical equations predict mortalities, marking rates, and weight characteristics of sheep of various ages from simple climatic measures, stocking rate and reproductive status. The initial age structure of flocks was determined by running the model for several years with historical climatic conditions. Drought management strategies such as selling a proportion of wethers progressively down to two-tooth and oldest ewes were incorporated. Management decisions such as time of joining, age at which ewes were cast-for-age, wether turn-off age and turning-off rate of lambs vary with geographical area and can be specified at run time. The model is run for sequences of climatic conditions generated stochastically from distributions based on historical climatic data correlated in some instances. The model highlights the difficulties of sustaining a consistent supply of sheep under variable climatic conditions.

Using simulation techniques to investigate methods to determine resistance of helminths to anthelmintic treatment

The widespread and increasing resistance of internal parasites to anthelmintic control is a serious problem for the Australian sheep and wool industry. As part of control programmes, laboratories use the Faecal Egg Count Reduction Test (FECRT) to determine resistance to anthelmintics. It is important to have confidence in the measure of resistance, not only for the producer planning a drenching programme but also for companies investigating the efficacy of their products. The determination of resistance and corresponding confidence limits as given in anthelmintic efficacy guidelines of the Standing Committee on Agriculture (SCA) is based on a number of assumptions. This study evaluated the appropriateness of these assumptions for typical data and compared the effectiveness of the standard FECRT procedure with the effectiveness of alternative procedures. Several sets of historical experimental data from sheep and goats were analysed to determine that a negative binomial distribution was a more appropriate distribution to describe pre-treatment helminth egg counts in faeces than a normal distribution. Simulated egg counts for control animals were generated stochastically from negative binomial distributions and those for treated animals from negative binomial and binomial distributions. Three methods for determining resistance when percent reduction is based on arithmetic means were applied. The first was that advocated in the SCA guidelines, the second similar to the first but basing the variance estimates on negative binomial distributions, and the third using Wadley’s method with the distribution of the response variate assumed negative binomial and a logit link transformation. These were also compared with a fourth method recommended by the International Co-operation on Harmonisation of Technical Requirements for Registration of Veterinary Medicinal Products (VICH) programme, in which percent reduction is based on the geometric means. A wide selection of parameters was investigated and for each set 1000 simulations run. Percent reduction and confidence limits were then calculated for the methods, together with the number of times in each set of 1000 simulations the theoretical percent reduction fell within the estimated confidence limits and the number of times resistance would have been said to occur. These simulations provide the basis for setting conditions under which the methods could be recommended. The authors show that given the distribution of helminth egg counts found in Queensland flocks, the method based on arithmetic not geometric means should be used and suggest that resistance be redefined as occurring when the upper level of percent reduction is less than 95%. At least ten animals per group are required in most circumstances, though even 20 may be insufficient where effectiveness of the product is close to the cut off point for defining resistance.

Learning Temporal Alignment Uncertainty for Efficient Event Detection

In this paper we tackle the problem of efficient video event detection. We argue that linear detection functions should be preferred in this regard due to their scalability and efficiency during estimation and evaluation. A popular approach in this regard is to represent a sequence using a bag of words (BOW) representation due to its: (i) fixed dimensionality irrespective of the sequence length, and (ii) its ability to compactly model the statistics in the sequence. A drawback to the BOW representation, however, is the intrinsic destruction of the temporal ordering information. In this paper we propose a new representation that leverages the uncertainty in relative temporal alignments between pairs of sequences while not destroying temporal ordering. Our representation, like BOW, is of a fixed dimensionality making it easily integrated with a linear detection function. Extensive experiments on CK+, 6DMG, and UvA-NEMO databases show significant performance improvements across both isolated and continuous event detection tasks.

Rapid and efficient screening of a Representational Difference Analysis library using reverse Southern hybridisation: Identification of genetic differences between Haemophilus parasuis isolates

Representational Difference Analysis (RDA) is an established technique used for isolation of specific genetic differences between or within bacterial species. This method was used to investigate the genetic basis of serovar-specificity and the relationship between serovar and virulence in Haemophilus parasuis. An RDA clone library of 96 isolates was constructed using H. parasuis strains H425(P) (serovar 12) and HS1967 (serovar 4). To screen such a large clone library to determine which clones are strain-specific would typically involved separately labelling each clone for use in Southern hybridisation against genomic DNA from each of the strains. In this study, a novel application of reverse Southern hybridisation was used to screen the RDA library: genomic DNA from each strain was labelled and used to probe the library to identify strain-specific clones. This novel approach represents a significant improvement in methodology that is rapid and efficient.

Heterologous signals allow efficient targeting of a nuclear-encoded fusion protein to plastids and endoplasmic reticulum in diverse plant species

Approximately 30% of plant nuclear genes appear to encode proteins targeted to the plastids or endoplasmic reticulum (ER). The signals that direct proteins into these compartments are diverse in sequence, but, on the basis of a limited number of tests in heterologous systems, they appear to be functionally conserved across species. To further test the generality of this conclusion, we tested the ability of two plastid transit peptides and an ER signal peptide to target green fluorescent protein (GFP) in 12 crops, including three monocots (barley, sugarcane, wheat) and nine dicots (Arabidopsis, broccoli, cabbage, carrot, cauliflower, lettuce, radish, tobacco, turnip). In all species, transient assays following microprojectile bombardment or vacuum infiltration using Agrobacterium showed that the plastid transit peptides from tomato DCL (defective chloroplast and leaves) and tobacco RbcS [ribulose bisphosphate carboxylase (Rubisco) small subunit] genes were effective in targeting GFP to the leaf plastids. GFP engineered as a fusion to the N-terminal ER signal peptide from Arabidopsis basic chitinase and a C-terminal HDEL signal for protein retention in the ER was accumulated in the ER of all species. The results in tobacco were confirmed in stably transformed cells. These signal sequences should be useful to direct proteins to the plastid stroma or ER lumen in diverse plant species of biotechnological interest for the accumulation of particular recombinant proteins or for the modification of particular metabolic streams.

Sampling Methods for Exploring Between Subject Variability in Cardiac Electrophysiology Experiments

Between-subject and within-subject variability is ubiquitous in biology and physiology and understanding and dealing with this is one of the biggest challenges in medicine. At the same time it is difficult to investigate this variability by experiments alone. A recent modelling and simulation approach, known as population of models (POM), allows this exploration to take place by building a mathematical model consisting of multiple parameter sets calibrated against experimental data. However, finding such sets within a high-dimensional parameter space of complex electrophysiological models is computationally challenging. By placing the POM approach within a statistical framework, we develop a novel and efficient algorithm based on sequential Monte Carlo (SMC). We compare the SMC approach with Latin hypercube sampling (LHS), a method commonly adopted in the literature for obtaining the POM, in terms of efficiency and output variability in the presence of a drug block through an in-depth investigation via the Beeler-Reuter cardiac electrophysiological model. We show improved efficiency via SMC and that it produces similar responses to LHS when making out-of-sample predictions in the presence of a simulated drug block.

A comparison of plotless density estimators using Monte Carlo simulation on totally enumerated field data sets

Background: Plotless density estimators are those that are based on distance measures rather than counts per unit area (quadrats or plots) to estimate the density of some usually stationary event, e.g. burrow openings, damage to plant stems, etc. These estimators typically use distance measures between events and from random points to events to derive an estimate of density. The error and bias of these estimators for the various spatial patterns found in nature have been examined using simulated populations only. In this study we investigated eight plotless density estimators to determine which were robust across a wide range of data sets from fully mapped field sites. They covered a wide range of situations including animal damage to rice and corn, nest locations, active rodent burrows and distribution of plants. Monte Carlo simulations were applied to sample the data sets, and in all cases the error of the estimate (measured as relative root mean square error) was reduced with increasing sample size. The method of calculation and ease of use in the field were also used to judge the usefulness of the estimator. Estimators were evaluated in their original published forms, although the variable area transect (VAT) and ordered distance methods have been the subjects of optimization studies. Results: An estimator that was a compound of three basic distance estimators was found to be robust across all spatial patterns for sample sizes of 25 or greater. The same field methodology can be used either with the basic distance formula or the formula used with the Kendall-Moran estimator in which case a reduction in error may be gained for sample sizes less than 25, however, there is no improvement for larger sample sizes. The variable area transect (VAT) method performed moderately well, is easy to use in the field, and its calculations easy to undertake. Conclusion: Plotless density estimators can provide an estimate of density in situations where it would not be practical to layout a plot or quadrat and can in many cases reduce the workload in the field.

Development and Simulation of a Variable Rate Controller for an Air search and Air Sampling Unmanned Aerial System

This report describes the development and simulation of a variable rate controller for a 6-degree of freedom nonlinear model. The variable rate simulation model represents an off the shelf autopilot. Flight experiment involves risks and can be expensive. Therefore a dynamic model to understand the performance characteristics of the UAS in mission simulation before actual flight test or to obtain parameters needed for the flight is important. The control and guidance is implemented in Simulink. The report tests the use of the model for air search and air sampling path planning. A GUI in which a set of mission scenarios, in which two experts (mission expert, i.e. air sampling or air search and an UAV expert) interact, is presented showing the benefits of the method.

Testing the simulation capability of APSIM-ORYZA under different levels of nitrogen fertiliser and transplanting time regimes in Korea

APSIM-ORYZA is a new functionality developed in the APSIM framework to simulate rice production while addressing management issues such as fertilisation and transplanting, which are particularly important in Korean agriculture. To validate the model for Korean rice varieties and field conditions, the measured yields and flowering times from three field experiments conducted by the Gyeonggi Agricultural Research and Extension Services (GARES) in Korea were compared against the simulated outputs for different management practices and rice varieties. Simulated yields of early-, mid- and mid-to-late-maturing varieties of rice grown in a continuous rice cropping system from 1997 to 2004 showed close agreement with the measured data. Similar results were also found for yields simulated under seven levels of nitrogen application. When different transplanting times were modelled, simulated flowering times ranged from within 3 days of the measured values for the early-maturing varieties, to up to 9 days after the measured dates for the mid- and especially mid-to-late-maturing varieties. This was associated with highly variable simulated yields which correlated poorly with the measured data. This suggests the need to accurately calibrate the photoperiod sensitivity parameters of the model for the photoperiod-sensitive rice varieties in Korea.

Long-term trends in fertility of soils under continuous cultivation and cereal cropping in southern Queensland. IX. Simulation of soil carbon and nitrogen pools using CENTURY model

Cultivation and cropping of soils results in a decline in soil organic carbon and soil nitrogen, and can lead to reduced crop yields. The CENTURY model was used to simulate the effects of continuous cultivation and cereal cropping on total soil organic matter (C and N), carbon pools, nitrogen mineralisation, and crop yield from 6 locations in southern Queensland. The model was calibrated for each replicate from the original datasets, allowing comparisons for each replicate rather than site averages. The CENTURY model was able to satisfactorily predict the impact of long-term cultivation and cereal cropping on total organic carbon, but was less successful in simulating the different fractions and nitrogen mineralisation. The model firstly over-predicted the initial (pre-cropping) soil carbon and nitrogen concentration of the sites. To account for the unique shrinking and swelling characteristics of the Vertosol soils, the default annual decomposition rates of the slow and passive carbon pools were doubled, and then the model accurately predicted initial conditions. The ability of the model to predict carbon pool fractions varied, demonstrating the difficulty inherent in predicting the size of these conceptual pools. The strength of the model lies in the ability to closely predict the starting soil organic matter conditions, and the ability to predict the impact of clearing, cultivation, fertiliser application, and continuous cropping on total soil carbon and nitrogen.

In quest of a reliable and efficient computational test for detection of isomorphism in kinematic chains

The test based on comparison of the characteristic coefficients of the adjancency matrices of the corresponding graphs for detection of isomorphism in kinematic chains has been shown to fail in the case of two pairs of ten-link, simple-jointed chains, one pair corresponding to single-freedom chains and the other pair corresponding to three-freedom chains. An assessment of the merits and demerits of available methods for detection of isomorphism in graphs and kinematic chains is presented, keeping in view the suitability of the methods for use in computerized structural synthesis of kinematic chains. A new test based on the characteristic coefficients of the “degree” matrix of the corresponding graph is proposed for detection of isomorphism in kinematic chains. The new test is found to be successful in the case of a number of examples of graphs where the test based on characteristic coefficients of adjancency matrix fails. It has also been found to be successful in distinguishing the structures of all known simple-jointed kinematic chains in the categories of (a) single-freedom chains with up to 10 links, (b) two-freedom chains with up to 9 links and (c) three-freedom chains with up to 10 links.

Design and Simulation of a Solar Powered UAV for Remote Sensing Tasks Technical Report

This research deals with the development of a Solar-Powered UAV designed for remote sensing, in particular to the development of the autopilot sub-system and path planning. The design of the Solar-Powered UAS followed a systems engineering methodology, by first defining system architecture, and selecting each subsystem. Validation tests and integration of autopilot is performed, in order to evaluate the performances of each subsystem and to obtain a global operational system for data collection missions. The flight tests planning and simulation results are also explored in order to verify the mission capabilities using an autopilot on a UAS. The important aspect of this research is to develop a Solar-Powered UAS for the purpose of data collection and video monitoring, especially data and images from the ground; transmit to the GS (Ground Station), segment the collected data, and afterwards analyze it with a Matlab code.