Analysis of diffusion tensor magnetic resonance imaging data using principal component analysis

An analysis method for diffusion tensor (DT) magnetic resonance imaging data is described, which, contrary to the standard method (multivariate fitting), does not require a specific functional model for diffusion-weighted (DW) signals. The method uses principal component analysis (PCA) under the assumption of a single fibre per pixel. PCA and the standard method were compared using simulations and human brain data. The two methods were equivalent in determining fibre orientation. PCA-derived fractional anisotropy and DT relative anisotropy had similar signal-to-noise ratio (SNR) and dependence on fibre shape. PCA-derived mean diffusivity had similar SNR to the respective DT scalar, and it depended on fibre anisotropy. Appropriate scaling of the PCA measures resulted in very good agreement between PCA and DT maps. In conclusion, the assumption of a specific functional model for DW signals is not necessary for characterization of anisotropic diffusion in a single fibre.

Survival analysis statistics applied to threshold data obtained from the ascending forced-choice method of limits

Sensory thresholds are often collected through ascending forced-choice methods. Group thresholds are important for comparing stimuli or populations; yet, the method has two problems. An individual may correctly guess the correct answer at any concentration step and might detect correctly at low concentrations but become adapted or fatigued at higher concentrations. The survival analysis method deals with both issues. Individual sequences of incorrect and correct answers are adjusted, taking into account the group performance at each concentration. The technique reduces the chance probability where there are consecutive correct answers. Adjusted sequences are submitted to survival analysis to determine group thresholds. The technique was applied to an aroma threshold and a taste threshold study. It resulted in group thresholds similar to ASTM or logarithmic regression procedures. Significant differences in taste thresholds between younger and older adults were determined. The approach provides a more robust technique over previous estimation methods.

Kinematical analysis of redundant drive wire mechanisms with velocity constraint

In this paper, we propose a new velocity constraint type for Redundant Drive Wire Mechanisms. The purpose of this paper is to demonstrate that the proposed velocity constraint module can fix the orientation of the movable part and to use the kinematical analysis method to obtain the moving direction of the movable part. First, we discuss the necessity of using this velocity constraint type and the possible applications of the proposed mechanism. Second, we derive the basic equations of a wire mechanism with this constraint type. Next, we present a method of motion analysis on active and passive constraint spaces, which is used to find the moving direction of a movable part. Finally, we apply the above analysis method on a wire mechanism with a velocity constraint module and on a wire mechanism with four double actuator modules. By evaluating the results, we prove the validity of the proposed constraint type.

Convectively coupled equatorial waves: A new methodology for identifying wave structures in observational data

Convectively coupled equatorial waves are fundamental components of the interaction between the physics and dynamics of the tropical atmosphere. A new methodology, which isolates individual equatorial wave modes, has been developed and applied to observational data. The methodology assumes that the horizontal structures given by equatorial wave theory can be used to project upper- and lower-tropospheric data onto equatorial wave modes. The dynamical fields are first separated into eastward- and westward-moving components with a specified domain of frequency–zonal wavenumber. Each of the components for each field is then projected onto the different equatorial modes using the y structures of these modes given by the theory. The latitudinal scale yo of the modes is predetermined by data to fit the equatorial trapping in a suitable latitude belt y = ±Y. The extent to which the different dynamical fields are consistent with one another in their depiction of each equatorial wave structure determines the confidence in the reality of that structure. Comparison of the analyzed modes with the eastward- and westward-moving components in the convection field enables the identification of the dynamical structure and nature of convectively coupled equatorial waves. In a case study, the methodology is applied to two independent data sources, ECMWF Reanalysis and satellite-observed window brightness temperature (Tb) data for the summer of 1992. Various convectively coupled equatorial Kelvin, mixed Rossby–gravity, and Rossby waves have been detected. The results indicate a robust consistency between the two independent data sources. Different vertical structures for different wave modes and a significant Doppler shifting effect of the background zonal winds on wave structures are found and discussed. It is found that in addition to low-level convergence, anomalous fluxes induced by strong equatorial zonal winds associated with equatorial waves are important for inducing equatorial convection. There is evidence that equatorial convection associated with Rossby waves leads to a change in structure involving a horizontal structure similar to that of a Kelvin wave moving westward with it. The vertical structure may also be radically changed. The analysis method should make a very powerful diagnostic tool for investigating convectively coupled equatorial waves and the interaction of equatorial dynamics and physics in the real atmosphere. The results from application of the analysis method for a reanalysis dataset should provide a benchmark against which model studies can be compared.

Storm prediction research and its application to the oil/gas industry

The accurate prediction of storms is vital to the oil and gas sector for the management of their operations. An overview of research exploring the prediction of storms by ensemble prediction systems is presented and its application to the oil and gas sector is discussed. The analysis method used requires larger amounts of data storage and computer processing time than other more conventional analysis methods. To overcome these difficulties eScience techniques have been utilised. These techniques potentially have applications to the oil and gas sector to help incorporate environmental data into their information systems

Are Cape floral clades the same age? Contemporaneous origins of two lineages in the genistoids s.l. (Fabaceae)

The hypothesis that the elements of the modern species-rich flora of the Cape Floristic Region (CFR), South Africa, originated more or less simultaneously at the Miocene/Pliocene boundary, in response to the development of a mediterranean climate, has been challenged by numerous molecular dating estimates of Cape floral clades. These studies reveal a more gradual emergence, with the oldest clades originating in the Eocene, but others appearing later, some as recently as the Pliocene. That there are factors which might affect the dates recovered, such as choice of calibration point, analysis method, sampling density and the delimitation of Cape floral clades, suggests a need for further critical evaluation of the age estimates presented to date. In this study, the dates of origin of two Cape floral clades (the legume Crotalarieae p.p. and Podalyrieae) are estimated, constrained by a shared calibration point in a single analysis using an rDNA ITS phylogeny in which 633 taxa are sampled. The results indicate that these two clades arose contemporaneously 44-46 mya, not at the Miocene/Pliocene boundary as had been previously supposed. The contemporaneous origin of these Cape floral clades suggests that additional more inclusive analyses are needed before rejecting the hypothesis that a. single environmental trigger explains the establishment of Cape floral clades. (c) 2007 Elsevier Inc. All rights reserved.

A phylogenetic reappraisal of the Peltophorum group (Caesalpinieae: Leguminosae) based on the chloroplast trnL-F, rbcL and rps16 sequence data

The monophyly of the Peltophorum group, one of nine informal groups recognized by Polhill in the Caesalpinieae, was tested using sequence data from the trnL-F, rbcL, and rps16 regions of the chloroplast genome. Exemplars were included from all 16 genera of the Peltophorum group, and from 15 genera representing seven of the other eight informal groups in the tribe. The data were analyzed separately and in combined analyses using parsimony and Bayesian methods. The analysis method had little effect on the topology of well-supported relationships. The molecular data recovered a generally well-supported phylogeny with many intergeneric relationships resolved. Results show that the Peltophorum group as currently delimited is polyphyletic, but that eight genera plus one undescribed genus form a core Peltophorum group, which is referred to here as the Peltophorum group sensu stricto. These genera are Bussea, Conzattia, Colvillea, Delonix, Heteroflorum (inedit.), Lemuropisum, Parkinsonia, Peltophorum, and Schizolobium. The remaining eight genera of the Peltophorum group s.l. are distributed across the Caesalpinieae. Morphological support for the redelimited Peltophorum group and the other recovered clades was assessed, and no unique synapomorphy was found for the Peltophorum group s.s. A proposal for the reclassification of the Peltophorum group s.l. is presented.

The impact of an intelligent classroom on pupils' interactive behaviour

Purpose – The purpose of this research is to determine whether new intelligent classrooms will affect the behaviour of children in their new learning environments. Design/methodology/approach – A multi-method study approach was used to carry out the research. Behavioural mapping was used to observe and monitor the classroom environment and analyse usage. Two new classrooms designed by INTEGER (Intelligent and Green) in two different UK schools provided the case studies to determine whether intelligent buildings (learning environments) can enhance learning experiences. Findings – Several factors were observed in the learning environments: mobility, flexibility, use of technology, interactions. Relationships among them were found indicating that the new environments have positive impact on pupils' behaviour. Practical implications – A very useful feedback for the Classrooms of the Future initiative will be provided, which can be used as basis for the School of the Future initiative. Originality/value – The behavioural analysis method described in this study will enable an evaluation of the “Schools of the Future” concept, under children's perspective. Using a real life laboratory gives contribution to the education field by rethinking the classroom environment and the way of teaching.

Neurofuzzy state identification using prefiltering

A new state estimator algorithm is based on a neurofuzzy network and the Kalman filter algorithm. The major contribution of the paper is recognition of a bias problem in the parameter estimation of the state-space model and the introduction of a simple, effective prefiltering method to achieve unbiased parameter estimates in the state-space model, which will then be applied for state estimation using the Kalman filtering algorithm. Fundamental to this method is a simple prefiltering procedure using a nonlinear principal component analysis method based on the neurofuzzy basis set. This prefiltering can be performed without prior system structure knowledge. Numerical examples demonstrate the effectiveness of the new approach.

Epoch-specific functional networks involved in working memory

Working memory (WM) is not a unitary construct. There are distinct processes involved in encoding information, maintaining it on-line, and using it to guide responses. The anatomical configurations of these processes are more accurately analyzed as functionally connected networks than collections of individual regions. In the current study we analyzed event-related functional magnetic resonance imaging (fMRI) data from a Sternberg Item Recognition Paradigm WM task using a multivariate analysis method that allowed the linking of functional networks to temporally-separated WM epochs. The length of the delay epochs was varied to optimize isolation of the hemodynamic response (HDR) for each task epoch. All extracted functional networks displayed statistically significant sensitivity to delay length. Novel information extracted from these networks that was not apparent in the univariate analysis of these data included involvement of the hippocampus in encoding/probe, and decreases in BOLD signal in the superior temporal gyrus (STG), along with default-mode regions, during encoding/delay. The bilateral hippocampal activity during encoding/delay fits with theoretical models of WM in which memoranda held across the short term are activated long-term memory representations. The BOLD signal decreases in the STG were unexpected, and may reflect repetition suppression effects invoked by internal repetition of letter stimuli. Thus, analysis methods focusing on how network dynamics relate to experimental conditions allowed extraction of novel information not apparent in univariate analyses, and are particularly recommended for WM experiments for which task epochs cannot be randomized.

Ontology modeling for generation of clinical pathways

Purpose: Increasing costs of health care, fuelled by demand for high quality, cost-effective healthcare has drove hospitals to streamline their patient care delivery systems. One such systematic approach is the adaptation of Clinical Pathways (CP) as a tool to increase the quality of healthcare delivery. However, most organizations still rely on are paper-based pathway guidelines or specifications, which have limitations in process management and as a result can influence patient safety outcomes. In this paper, we present a method for generating clinical pathways based on organizational semiotics by capturing knowledge from syntactic, semantic and pragmatic to social level. Design/methodology/approach: The proposed modeling approach to generation of CPs adopts organizational semiotics and enables the generation of semantically rich representation of CP knowledge. Semantic Analysis Method (SAM) is applied to explicitly represent the semantics of the concepts, their relationships and patterns of behavior in terms of an ontology chart. Norm Analysis Method (NAM) is adopted to identify and formally specify patterns of behavior and rules that govern the actions identified on the ontology chart. Information collected during semantic and norm analysis is integrated to guide the generation of CPs using best practice represented in BPMN thus enabling the automation of CP. Findings: This research confirms the necessity of taking into consideration social aspects in designing information systems and automating CP. The complexity of healthcare processes can be best tackled by analyzing stakeholders, which we treat as social agents, their goals and patterns of action within the agent network. Originality/value: The current modeling methods describe CPs from a structural aspect comprising activities, properties and interrelationships. However, these methods lack a mechanism to describe possible patterns of human behavior and the conditions under which the behavior will occur. To overcome this weakness, a semiotic approach to generation of clinical pathway is introduced. The CP generated from SAM together with norms will enrich the knowledge representation of the domain through ontology modeling, which allows the recognition of human responsibilities and obligations and more importantly, the ultimate power of decision making in exceptional circumstances.

Wave activity in the tropical tropopause layer in seven reanalysis and four chemistry climate model data sets

Sub-seasonal variability including equatorial waves significantly influence the dehydration and transport processes in the tropical tropopause layer (TTL). This study investigates the wave activity in the TTL in 7 reanalysis data sets (RAs; NCEP1, NCEP2, ERA40, ERA-Interim, JRA25, MERRA, and CFSR) and 4 chemistry climate models (CCMs; CCSRNIES, CMAM, MRI, and WACCM) using the zonal wave number-frequency spectral analysis method with equatorially symmetric-antisymmetric decomposition. Analyses are made for temperature and horizontal winds at 100 hPa in the RAs and CCMs and for outgoing longwave radiation (OLR), which is a proxy for convective activity that generates tropopause-level disturbances, in satellite data and the CCMs. Particular focus is placed on equatorial Kelvin waves, mixed Rossby-gravity (MRG) waves, and the Madden-Julian Oscillation (MJO). The wave activity is defined as the variance, i.e., the power spectral density integrated in a particular zonal wave number-frequency region. It is found that the TTL wave activities show significant difference among the RAs, ranging from ∼0.7 (for NCEP1 and NCEP2) to ∼1.4 (for ERA-Interim, MERRA, and CFSR) with respect to the averages from the RAs. The TTL activities in the CCMs lie generally within the range of those in the RAs, with a few exceptions. However, the spectral features in OLR for all the CCMs are very different from those in the observations, and the OLR wave activities are too low for CCSRNIES, CMAM, and MRI. It is concluded that the broad range of wave activity found in the different RAs decreases our confidence in their validity and in particular their value for validation of CCM performance in the TTL, thereby limiting our quantitative understanding of the dehydration and transport processes in the TTL.

On the detection and attribution of gravity waves generated by the 20 March 2015 solar eclipse

Internal gravity waves are generated as adjustment radiation whenever a sudden change in forcing causes the atmosphere to depart from its large-scale balanced state. Such a forcing anomaly occurs during a solar eclipse, when the Moon’s shadow cools part of the Earth’s surface. The resulting atmospheric gravity waves are associated with pressure and temperature perturbations, which in principle are detectable both at the surface and aloft. In this study, surface pressure and temperature data from two UK sites at Reading and Lerwick are analysed for eclipse-driven gravity-wave perturbations during the 20 March 2015 solar eclipse over north-west Europe. Radiosonde wind data from the same two sites are also analysed using a moving parcel analysis method, to determine the periodicities of the waves aloft. On this occasion, the perturbations both at the surface and aloft are found not to be confidently attributable to eclipse-driven gravity waves. We conclude that the complex synoptic weather conditions over the UK at the time of this particular eclipse helped to mask any eclipse-driven gravity waves.

A general-method for tracking analysis and its application to meteorological data

Recent interest in the validation of general circulation models (GCMs) has been devoted to objective methods. A small number of authors have used the direct synoptic identification of phenomena together with a statistical analysis to perform the objective comparison between various datasets. This paper describes a general method for performing the synoptic identification of phenomena that can be used for an objective analysis of atmospheric, or oceanographic, datasets obtained from numerical models and remote sensing. Methods usually associated with image processing have been used to segment the scene and to identify suitable feature points to represent the phenomena of interest. This is performed for each time level. A technique from dynamic scene analysis is then used to link the feature points to form trajectories. The method is fully automatic and should be applicable to a wide range of geophysical fields. An example will be shown of results obtained from this method using data obtained from a run of the Universities Global Atmospheric Modelling Project GCM.