Real-Time Gene-Expression Extraction with Fast Classification (FC) Networks

Fast Classification (FC) networks were inspired by a biologically plausible mechanism for short term memory where learning occurs instantaneously. Both weights and the topology for an FC network are mapped directly from the training samples by using a prescriptive training scheme. Only two presentations of the training data are required to train an FC network. Compared with iterative learning algorithms such as Back-propagation (which may require many hundreds of presentations of the training data), the training of FC networks is extremely fast and learning convergence is always guaranteed. Thus FC networks may be suitable for applications where real-time classification is needed. In this paper, the FC networks are applied for the real-time extraction of gene expressions for Chlamydia microarray data. Both the classification performance and learning time of the FC networks are compared with the Multi-Layer Proceptron (MLP) networks and support-vector-machines (SVM) in the same classification task. The FC networks are shown to have extremely fast learning time and comparable classification accuracy.

Estimating and evaluating the statistics of gapped local-alignment scores

We present a novel maximum-likelihood-based algorithm for estimating the distribution of alignment scores from the scores of unrelated sequences in a database search. Using a new method for measuring the accuracy of p-values, we show that our maximum-likelihood-based algorithm is more accurate than existing regression-based and lookup table methods. We explore a more sophisticated way of modeling and estimating the score distributions (using a two-component mixture model and expectation maximization), but conclude that this does not improve significantly over simply ignoring scores with small E-values during estimation. Finally, we measure the classification accuracy of p-values estimated in different ways and observe that inaccurate p-values can, somewhat paradoxically, lead to higher classification accuracy. We explain this paradox and argue that statistical accuracy, not classification accuracy, should be the primary criterion in comparisons of similarity search methods that return p-values that adjust for target sequence length.

Mapping and characterising subtropical estuarine landscapes using aerial photography and GIS for potential application in wildlife conservation and management

Coarse-resolution thematic maps derived from remotely sensed data and implemented in GIS play an important role in coastal and marine conservation, research and management. Here, we describe an approach for fine-resolution mapping of land-cover types using aerial photography and ancillary GIs and ground data in a large (100 x 35 km) subtropical estuarine system (Moreton Bay, Queensland, Australia). We have developed and implemented a classification scheme representing 24 coastal (subtidal, intertidal. mangrove, supratidal and terrestrial) cover types relevant to the ecology of estuarine animals, nekton and shorebirds. The accuracy of classifications of the intertidal and subtidal cover types, as indicated by the agreement between the mapped (predicted) and reference (ground) data, was 77-88%, depending on the zone and level of generalization required. The variability and spatial distribution of habitat mosaics (landscape types) across the mapped environment were assessed using K-means clustering and validated with Classification and Regression Tree models. Seven broad landscape types could be distinguished and ways of incorporating the information on landscape composition into site-specific conservation and field research are discussed. This research illustrates the importance and potential applications of fine-resolution mapping for conservation and management of estuarine habitats and their terrestrial and aquatic wildlife. (c) 2005 Elsevier Ltd. All rights reserved.

Prediction of protein continuum secondary structure with probabilistic models based on NMR solved structures

Background: The structure of proteins may change as a result of the inherent flexibility of some protein regions. We develop and explore probabilistic machine learning methods for predicting a continuum secondary structure, i.e. assigning probabilities to the conformational states of a residue. We train our methods using data derived from high-quality NMR models. Results: Several probabilistic models not only successfully estimate the continuum secondary structure, but also provide a categorical output on par with models directly trained on categorical data. Importantly, models trained on the continuum secondary structure are also better than their categorical counterparts at identifying the conformational state for structurally ambivalent residues. Conclusion: Cascaded probabilistic neural networks trained on the continuum secondary structure exhibit better accuracy in structurally ambivalent regions of proteins, while sustaining an overall classification accuracy on par with standard, categorical prediction methods.

Predictive validity of three ActiGraph energy expenditure equations for children

Purpose: This Study evaluated the predictive validity of three previously published ActiGraph energy expenditure (EE) prediction equations developed for children and adolescents. Methods: A total of 45 healthy children and adolescents (mean age: 13.7 +/- 2.6 yr) completed four 5-min activity trials (normal walking. brisk walking, easy running, and fast running) in ail indoor exercise facility. During each trial, participants were all ActiGraph accelerometer oil the right hip. EE was monitored breath by breath using the Cosmed K4b(2) portable indirect calorimetry system. Differences and associations between measured and predicted EE were assessed using dependent t-tests and Pearson correlations, respectively. Classification accuracy was assessed using percent agreement, sensitivity, specificity, and area under the receiver operating characteristic (ROC) curve, Results: None of the equations accurately predicted mean energy expenditure during each of the four activity trials. Each equation, however, accurately predicted mean EE in at least one activity trial. The Puyau equation accurately predicted EE during slow walking. The Trost equation accurately predicted EE during slow running. The Freedson equation accurately predicted EE during fast running. None of the three equations accurately predicted EE during brisk walking. The equations exhibited fair to excellent classification accuracy with respect to activity intensity. with the Trost equation exhibiting the highest classification accuracy and the Puyau equation exhibiting the lowest. Conclusions: These data suggest that the three accelerometer prediction equations do not accurately predict EE on a minute-by-minute basis in children and adolescents during overground walking and running. The equations maybe, however, for estimating participation in moderate and vigorous activity.

Classification and analysis of integrating frameworks in multiscale modelling

Chemical engineers are turning to multiscale modelling to extend traditional modelling approaches into new application areas and to achieve higher levels of detail and accuracy. There is, however, little advice available on the best strategy to use in constructing a multiscale model. This paper presents a starting point for the systematic analysis of multiscale models by defining several integrating frameworks for linking models at different scales. It briefly explores how the nature of the information flow between the models at the different scales is influenced by the choice of framework, and presents some restrictions on model-framework compatibility. The concepts are illustrated with reference to the modelling of a catalytic packed bed reactor. (C) 2004 Elsevier Ltd. All rights reserved.

Constraints on the spatiotemporal accuracy of interceptive action: effects of target size on hitting a moving object

Results of two experiments are reported that examined how people respond to rectangular targets of different sizes in simple hitting tasks. If a target moves in a straight line and a person is constrained to move along a linear track oriented perpendicular to the targetrsquos motion, then the length of the target along its direction of motion constrains the temporal accuracy and precision required to make the interception. The dimensions of the target perpendicular to its direction of motion place no constraints on performance in such a task. In contrast, if the person is not constrained to move along a straight track, the targetrsquos dimensions may constrain the spatial as well as the temporal accuracy and precision. The experiments reported here examined how people responded to targets of different vertical extent (height): the task was to strike targets that moved along a straight, horizontal path. In experiment 1 participants were constrained to move along a horizontal linear track to strike targets and so target height did not constrain performance. Target height, length and speed were co-varied. Movement time (MT) was unaffected by target height but was systematically affected by length (briefer movements to smaller targets) and speed (briefer movements to faster targets). Peak movement speed (Vmax) was influenced by all three independent variables: participants struck shorter, narrower and faster targets harder. In experiment 2, participants were constrained to move in a vertical plane normal to the targetrsquos direction of motion. In this task target height constrains the spatial accuracy required to contact the target. Three groups of eight participants struck targets of different height but of constant length and speed, hence constant temporal accuracy demand (different for each group, one group struck stationary targets = no temporal accuracy demand). On average, participants showed little or no systematic response to changes in spatial accuracy demand on any dependent measure (MT, Vmax, spatial variable error). The results are interpreted in relation to previous results on movements aimed at stationary targets in the absence of visual feedback.

Biomechanical consequences of impairment: A taxonomically valid basis for classification in a unified disability athletics system

Developing a unified classification system to replace four of the systems currently used in disability athletics (i.e., track and field) has been widely advocated. The diverse impairments to be included in a unified system require severed assessment methods, results of which cannot be meaningfully compared. Therefore, the taxonomic basis of current classification systems is invalid in a unified system. Biomechanical analysis establishes that force, a vector described in terms of magnitude and direction, is a key determinant of success in all athletic disciplines. It is posited that all impairments to be included in a unified system may be classified as either force magnitude impairments (FMI) or force control impairments (FCI). This framework would provide a valid taxonomic basis for a unified system, creating the opportunity to decrease the number of classes and enhance the viability of disability athletics.

Using FCD Mapper Software and Landsat Images to Assess Forest Canopy Density in Landscapes in Australia and the Philippines

Using Landsat imagery, forest canopy density (FCD) estimated with the FCD Mapper®, was correlated with predominant height (PDH, measured as the average height of the tallest 50 trees per hectare) for 20 field plots measured in native forest at Noosa Heads, south-east Queensland, Australia. A corresponding image was used to calculate FCD in Leyte Island, the Philippines and was validated on the ground for accuracy. The FCD Mapper was produced for the International Tropical Timber Organisation and estimates FCD as an index of canopy density using reflectance characteristics of Landsat Enhanced Thematic (ETM) Mapper images. The FCD Mapper is a ‘semi-expert’ computer program which uses interactive screens to allow the operator to make decisions concerning the classification of land into bare soil, grass and forest. At Noosa, a positive strong nonlinear relationship (r2 = 0.86) was found between FCD and PDH for 15 field plots with variable PDH but complete canopy closure. An additional five field plots were measured in forest with a broken canopy and the software assessed these plots as having a much lower FCD than forest with canopy closure. FCD estimates for forest and agricultural land in the island of Leyte and subsequent field validation showed that at appropriate settings, the FCD Mapper differentiated between tropical rainforest and banana or coconut plantation. These findings suggest that in forests with a closed canopy this remote sensing technique has promise for forest inventory and productivity assessment. The findings also suggest that the software has promise for discriminating between native forest with a complete canopy and forest which has a broken canopy, such as coconut or banana plantation.

Examination into the accuracy of exchangeable cation measurement in saline soils

Despite the increasing prevalence of salinity world-wide, the measurement of exchangeable cation concentrations in saline soils remains problematic. Two soil types (Mollisol and Vertisol) were equilibrated with a range of sodium adsorption ratio (SAR) solutions at various ionic strengths. The concentrations of exchangeable cations were then determined using several different types of methods, and the measured exchangeable cation concentrations compared to reference values. At low ionic strength (low salinity), the concentration of exchangeable cations can be accurately estimated from the total soil extractable cations. In saline soils, however, the presence of soluble salts in the soil solution precludes the use of this method. Leaching of the soil with a pre-wash solution (such as alcohol) was found to effectively remove the soluble salts from the soil, thus allowing the accurate measurement of the effective cation exchange capacity (ECEC). However, the dilution associated with this pre-washing increased the exchangeable Ca concentrations while simultaneously decreasing exchangeable Na. In contrast, when calculated as the difference between the total extractable cations and the soil solution cations, good correlations were found between the calculated exchangeable cation concentrations and the reference values for both Na (Mollisol: y=0.873x and Vertisol: y=0.960x) and Ca (Mollisol: y=0.901x and Vertisol: y=1.05x). Therefore, for soils with a soil solution ionic strength greater than 50 mM (electrical conductivity of 4 dS/m) (in which exchangeable cation concentrations are overestimated by the assumption they can be estimated as the total extractable cations), concentrations can be calculated as the difference between total extractable cations and soluble cations.

Bioimpedance spectrometry in the determination of body water compartments: Accuracy and clinical significance

Bioelectrical impedance analysis (BIA) offers the potential for a simple, portable and relatively inexpensive technique for the in vivo measurement of total body water (TBW). The potential of BIA as a technique of body composition analysis is even greater when one considers that body water can be used as a surrogate measure of lean body mass. However, BIA has not found universal acceptance even with the introduction of multi-frequency BIA (MFBIA) which, potentially, may improve the predictive accuracy of the measurement. There are a number of reasons for this lack of acceptance, although perhaps the major reason is that no single algorithm has been developed which can be applied to all subject groups. This may be due, in part, to the commonly used wrist-to-ankle protocol which is not indicated by the basic theory of bioimpedance, where the body is considered as five interconnecting cylinders. Several workers have suggested the use of segmental BIA measurements to provide a protocol more in keeping with basic theory. However, there are other difficulties associated with the application of BIA, such as effects of hydration and ion status, posture and fluid distribution. A further putative advantage of MFBIA is the independent assessment not only of TBW but also of the extracellular fluid volume (ECW), hence heralding the possibility of,being able to assess the fluid distribution between these compartments. Results of studies in this area have been, to date, mixed. Whereas strong relationships of impedance values at low frequencies with ECW, and at high frequencies with TBW, have been reported, changes in impedance are not always well correlated with changes in the size of the fluid compartments (assessed by alternative and more direct means) in pathological conditions. Furthermore, the theoretical advantages of Cole-Cole modelling over selected frequency prediction have not always been apparent. This review will consider the principles, methodology and applications of BIA. The principles and methodology will,be considered in relation to the basic theory of BIA and difficulties experienced in its application. The relative merits of single and multiple frequency BIA will be addressed, with particular attention to the latter's role in the assessment of compartmental fluid volumes. (C) 1998 Elsevier Science Ltd. All rights reserved.

Accuracy of predicting a child's response to potential threat: A comparison of children and their mothers

Considerable research has indicated that children and their parents often demonstrate marked discrepancies in their reporting of anxiety-related phenomena. In such cases, the question arises as to whether children are capable of accurately reporting on their anxiety. In the present study, 50 children (aged 5 to 14 years) were asked to approach a large, German Shepherd dog. Prior to the task, both the mother and child independently predicted the closest point likely to be reached by the child and the degree of anxiety likely to be experienced. These predictions were then compared with the actual phenomena displayed by the child during the task. On the behavioural measure (closest step reached), both the child and mother demonstrated equivalent predictive accuracy. On the subjective measure (fear ratings) children were considerably more accurate than their mothers. The data were not influenced by gender, age, or clinical status. The results indicate the ability of children to accurately predict their anxious responses, and support the value of incorporating children's self-reports in the assessment of emotional disorders.