Parameter sensitivity and predictive uncertainty in a new water quality model, Q(2)

A new dynamic model of water quality, Q(2), has recently been developed, capable of simulating large branched river systems. This paper describes the application of a generalized sensitivity analysis (GSA) to Q(2) for single reaches of the River Thames in southern England. Focusing on the simulation of dissolved oxygen (DO) (since this may be regarded as a proxy for the overall health of a river); the GSA is used to identify key parameters controlling model behavior and provide a probabilistic procedure for model calibration. It is shown that, in the River Thames at least, it is more important to obtain high quality forcing functions than to obtain improved parameter estimates once approximate values have been estimated. Furthermore, there is a need to ensure reasonable simulation of a range of water quality determinands, since a focus only on DO increases predictive uncertainty in the DO simulations. The Q(2) model has been applied here to the River Thames, but it has a broad utility for evaluating other systems in Europe and around the world.

Predictive vegetation mapping in the Mediterranean context: Considerations and methodological issues

The need to map vegetation communities over large areas for nature conservation and to predict the impact of environmental change on vegetation distributions, has stimulated the development of techniques for predictive vegetation mapping. Predictive vegetation studies start with the development of a model relating vegetation units and mapped physical data, followed by the application of that model to a geographic database and over a wide range of spatial scales. This field is particularly important for identifying sites for rare and endangered species and locations of high biodiversity such as many areas of the Mediterranean Basin. The potential of the approach is illustrated with a mapping exercise in the alti-meditterranean zone of Lefka Ori in Crete. The study established the nature of the relationship between vegetation communities and physical data including altitude, slope and geomorphology. In this way the knowledge of community distribution was improved enabling a GIS-based model capable of predicting community distribution to be constructed. The paper describes the development of the spatial model and the methodological problems of predictive mapping for monitoring Mediterranean ecosystems. The paper concludes with a discussion of the role of predictive vegetation mapping and other spatial techniques, such as fuzzy mapping and geostatistics, for improving our understanding of the dynamics of Mediterranean ecosystems and for practical management in a region that is under increasing pressure from human impact.

Non-commutative symbolic coding

We give a non-commutative generalization of classical symbolic coding in the presence of a synchronizing word. This is done by a scattering theoretical approach. Classically, the existence of a synchronizing word turns out to be equivalent to asymptotic completeness of the corresponding Markov process. A criterion for asymptotic completeness in general is provided by the regularity of an associated extended transition operator. Commutative and non-commutative examples are analysed.

Selection of candidate coding DNA barcoding regions for use on land plants

An in silico screen of 41 of the 81 coding regions of the Nicotiana plastid genome generated a shortlist of 12 candidates as DNA barcoding loci for land plants. These loci were evaluated for amplification and sequence variation against a reference set of 98 land plant taxa. The deployment of multiple primers and a modified multiplexed tandem polymerase chain reaction yielded 85–94% amplification across taxa, and mean sequence differences between sister taxa of 6.1 from 156 bases of accD to 22 from 493 bases of matK. We conclude that loci should be combined for effective diagnosis, and recommend further investigation of the following six loci: matK, rpoB, rpoC1, ndhJ, ycf5 and accD.

Predictive empirical modelling of Orobanche life cycle and seed ecology

Abstract 1.7.4

A hierarchical Bayesian model for predicting the functional consequences of amino-acid polymorphisms

Genetic polymorphisms in deoxyribonucleic acid coding regions may have a phenotypic effect on the carrier, e.g. by influencing susceptibility to disease. Detection of deleterious mutations via association studies is hampered by the large number of candidate sites; therefore methods are needed to narrow down the search to the most promising sites. For this, a possible approach is to use structural and sequence-based information of the encoded protein to predict whether a mutation at a particular site is likely to disrupt the functionality of the protein itself. We propose a hierarchical Bayesian multivariate adaptive regression spline (BMARS) model for supervised learning in this context and assess its predictive performance by using data from mutagenesis experiments on lac repressor and lysozyme proteins. In these experiments, about 12 amino-acid substitutions were performed at each native amino-acid position and the effect on protein functionality was assessed. The training data thus consist of repeated observations at each position, which the hierarchical framework is needed to account for. The model is trained on the lac repressor data and tested on the lysozyme mutations and vice versa. In particular, we show that the hierarchical BMARS model, by allowing for the clustered nature of the data, yields lower out-of-sample misclassification rates compared with both a BMARS and a frequen-tist MARS model, a support vector machine classifier and an optimally pruned classification tree.

Evaluation of a predictive model for Mycosphaerella graminicola for economic and environmental benefits

A method was developed to evaluate crop disease predictive models for their economic and environmental benefits. Benefits were quantified as the value of a prediction measured by costs saved and fungicide dose saved. The value of prediction was defined as the net gain made by using predictions, measured as the difference between a scenario where predictions are available and used and a scenario without prediction. Comparable 'with' and 'without' scenarios were created with the use of risk levels. These risk levels were derived from a probability distribution fitted to observed disease severities. These distributions were used to calculate the probability that a certain disease induced economic loss was incurred. The method was exemplified by using it to evaluate a model developed for Mycosphaerella graminicola risk prediction. Based on the value of prediction, the tested model may have economic and environmental benefits to growers if used to guide treatment decisions on resistant cultivars. It is shown that the value of prediction measured by fungicide dose saved and costs saved is constant with the risk level. The model could also be used to evaluate similar crop disease predictive models.

A predictive model for early-warning of Septoria leaf blotch on winter wheat

Disease-weather relationships influencing Septoria leaf blotch (SLB) preceding growth stage (GS) 31 were identified using data from 12 sites in the UK covering 8 years. Based on these relationships, an early-warning predictive model for SLB on winter wheat was formulated to predict the occurrence of a damaging epidemic (defined as disease severity of 5% or > 5% on the top three leaf layers). The final model was based on accumulated rain > 3 mm in the 80-day period preceding GS 31 (roughly from early-February to the end of April) and accumulated minimum temperature with a 0A degrees C base in the 50-day period starting from 120 days preceding GS 31 (approximately January and February). The model was validated on an independent data set on which the prediction accuracy was influenced by cultivar resistance. Over all observations, the model had a true positive proportion of 0.61, a true negative proportion of 0.73, a sensitivity of 0.83, and a specificity of 0.18. True negative proportion increased to 0.85 for resistant cultivars and decreased to 0.50 for susceptible cultivars. Potential fungicide savings are most likely to be made with resistant cultivars, but such benefits would need to be identified with an in-depth evaluation.

Coding of visual space during motor preparation: approaching objects rapidly modulate corticospinal excitability in hand-centered coordinates

Defensive behaviors, such as withdrawing your hand to avoid potentially harmful approaching objects, rely on rapid sensorimotor transformations between visual and motor coordinates. We examined the reference frame for coding visual information about objects approaching the hand during motor preparation. Subjects performed a simple visuomanual task while a task-irrelevant distractor ball rapidly approached a location either near to or far from their hand. After the distractor ball appearance, single pulses of transcranial magnetic stimulation were delivered over the subject's primary motor cortex, eliciting motor evoked potentials (MEPs) in their responding hand. MEP amplitude was reduced when the ball approached near the responding hand, both when the hand was on the left and the right of the midline. Strikingly, this suppression occurred very early, at 70-80ms after ball appearance, and was not modified by visual fixation location. Furthermore, it was selective for approaching balls, since static visual distractors did not modulate MEP amplitude. Together with additional behavioral measurements, we provide converging evidence for automatic hand-centered coding of visual space in the human brain.

Evidence for unusual spatial location coding in Williams syndrome: an explanation for the local bias in visuo-spatial construction tasks?

Individuals with Williams syndrome (WS) display poor visuo-spatial cognition relative to verbal abilities. Furthermore, whilst perceptual abilities are delayed, visuo-spatial construction abilities are comparatively even weaker, and are characterised by a local bias. We investigated whether his differentiation in visuo-spatial abilities can be explained by a deficit in coding spatial location in WS. This can be measured by assessing participants' understanding of the spatial relations between objects within a visual scene. Coordinate and categorical spatial relations were investigated independently in four participant groups: 21 individuals with WS; 21 typically developing (TD) children matched for non-verbal ability; 20 typically developing controls of a lower non-verbal ability; and 21 adults. A third task measured understanding of visual colour relations. Results indicated first, that the comprehension of categorical and coordinate spatial relations is equally poor in WS. Second, that the comprehension of visual relations is also at an equivalent level to spatial relational understanding in this population. These results can explain the difference in performance on visuo-spatial perception and construction tasks in WS. In addition, both the WS and control groups displayed response biases in the spatial tasks. However, the direction of bias differed across the groups. This finding is explored in relation to current theories of spatial location coding. (c) 2005 Elsevier Inc. All rights reserved.

Orientation coding: a specific deficit in Williams syndrome?

Williams syndrome (WS) is a rare genetic disorder with a unique cognitive profile in which verbal abilities are markedly stronger than visuospatial abilities. This study investigated the claim that orientation coding is a specific deficit within the visuospatial domain in WS. Experiment I employed a simplified version of the Benton Judgement of Line Orientation task and a control, length-matching task. Results demonstrated comparable levels of orientation matching performance in the group with WS and a group of typically developing (TD) controls matched by nonverbal ability, although it is possible that floor effects masked group differences. A group difference was observed in the length-matching task due to stronger performance from the control group. Experiment 2 employed an orientation-discrimination task and a length-discrimination task. Contrary to previous reports, the results showed that individuals with WS were able to code by orientation to a comparable level as that of their matched controls. This demonstrates that, although some impairment is apparent, orientation coding does not represent a specific deficit in WS. Comparison between Experiments I and 2 suggests that orientation coding is vulnerable to task complexity. However, once again, this vulnerability does not appear to be specific to the population with WS, as it was also apparent in the TD controls.

Application of constrained predictive control on a 3D crane system

This paper describes the SIMULINK implementation of a constrained predictive control algorithm based on quadratic programming and linear state space models, and its application to a laboratory-scale 3D crane system. The algorithm is compatible with Real Time. Windows Target and, in the case of the crane system, it can be executed with a sampling period of 0.01 s and a prediction horizon of up to 300 samples, using a linear state space model with 3 inputs, 5 outputs and 13 states.

Performance of GPRS coding scheme detection under severe multipath and co-channel interference as a function of soft-bit width

The General Packet Radio Service (GPRS) has been developed for the mobile radio environment to allow the migration from the traditional circuit switched connection to a more efficient packet based communication link particularly for data transfer. GPRS requires the addition of not only the GPRS software protocol stack, but also more baseband functionality for the mobile as new coding schemes have be en defined, uplink status flag detection, multislot operation and dynamic coding scheme detect. This paper concentrates on evaluating the performance of the GPRS coding scheme detection methods in the presence of a multipath fading channel with a single co-channel interferer as a function of various soft-bit data widths. It has been found that compressing the soft-bit data widths from the output of the equalizer to save memory can influence the likelihood decision of the coding scheme detect function and hence contribute to the overall performance loss of the system. Coding scheme detection errors can therefore force the channel decoder to either select the incorrect decoding scheme or have no clear decision which coding scheme to use resulting in the decoded radio block failing the block check sequence and contribute to the block error rate. For correct performance simulation, the performance of the full coding scheme detection must be taken into account.

Two-pass hexagonal algorithm with parallel implementation for video coding

This paper presents a paralleled Two-Pass Hexagonal (TPA) algorithm constituted by Linear Hashtable Motion Estimation Algorithm (LHMEA) and Hexagonal Search (HEXBS) for motion estimation. In the TPA, Motion Vectors (MV) are generated from the first-pass LHMEA and are used as predictors for second-pass HEXBS motion estimation, which only searches a small number of Macroblocks (MBs). We introduced hashtable into video processing and completed parallel implementation. We propose and evaluate parallel implementations of the LHMEA of TPA on clusters of workstations for real time video compression. It discusses how parallel video coding on load balanced multiprocessor systems can help, especially on motion estimation. The effect of load balancing for improved performance is discussed. The performance of the algorithm is evaluated by using standard video sequences and the results are compared to current algorithms.