Segmentation-level fusion for iris recognition

This paper investigates the potential of fusion at normalisation/segmentation level prior to feature extraction. While there are several biometric fusion methods at data/feature level, score level and rank/decision level combining raw biometric signals, scores, or ranks/decisions, this type of fusion is still in its infancy. However, the increasing demand to allow for more relaxed and less invasive recording conditions, especially for on-the-move iris recognition, suggests to further investigate fusion at this very low level. This paper focuses on the approach of multi-segmentation fusion for iris biometric systems investigating the benefit of combining the segmentation result of multiple normalisation algorithms, using four methods from two different public iris toolkits (USIT, OSIRIS) on the public CASIA and IITD iris datasets. Evaluations based on recognition accuracy and ground truth segmentation data indicate high sensitivity with regards to the type of errors made by segmentation algorithms.

A Genetic Algorithm for the selection of structural MRI features for classification of Mild Cognitive Impairment and Alzheimer's Disease

This work investigates the problem of feature selection in neuroimaging features from structural MRI brain images for the classification of subjects as healthy controls, suffering from Mild Cognitive Impairment or Alzheimer’s Disease. A Genetic Algorithm wrapper method for feature selection is adopted in conjunction with a Support Vector Machine classifier. In very large feature sets, feature selection is found to be redundant as the accuracy is often worsened when compared to an Support Vector Machine with no feature selection. However, when just the hippocampal subfields are used, feature selection shows a significant improvement of the classification accuracy. Three-class Support Vector Machines and two-class Support Vector Machines combined with weighted voting are also compared with the former and found more useful. The highest accuracy achieved at classifying the test data was 65.5% using a genetic algorithm for feature selection with a three-class Support Vector Machine classifier.

Modelling personal thermal sensations using C-Support Vector Classification (C-SVC) algorithm

The personalised conditioning system (PCS) is widely studied. Potentially, it is able to reduce energy consumption while securing occupants’ thermal comfort requirements. It has been suggested that automatic optimised operation schemes for PCS should be introduced to avoid energy wastage and discomfort caused by inappropriate operation. In certain automatic operation schemes, personalised thermal sensation models are applied as key components to help in setting targets for PCS operation. In this research, a novel personal thermal sensation modelling method based on the C-Support Vector Classification (C-SVC) algorithm has been developed for PCS control. The personal thermal sensation modelling has been regarded as a classification problem. During the modelling process, the method ‘learns’ an occupant’s thermal preferences from his/her feedback, environmental parameters and personal physiological and behavioural factors. The modelling method has been verified by comparing the actual thermal sensation vote (TSV) with the modelled one based on 20 individual cases. Furthermore, the accuracy of each individual thermal sensation model has been compared with the outcomes of the PMV model. The results indicate that the modelling method presented in this paper is an effective tool to model personal thermal sensations and could be integrated within the PCS for optimised system operation and control.

Bio-inspired ant colony optimization based clustering algorithm with mobile sinks for applications in consumer home automation networks

With the fast development of wireless communications, ZigBee and semiconductor devices, home automation networks have recently become very popular. Since typical consumer products deployed in home automation networks are often powered by tiny and limited batteries, one of the most challenging research issues is concerning energy reduction and the balancing of energy consumption across the network in order to prolong the home network lifetime for consumer devices. The introduction of clustering and sink mobility techniques into home automation networks have been shown to be an efficient way to improve the network performance and have received significant research attention. Taking inspiration from nature, this paper proposes an Ant Colony Optimization (ACO) based clustering algorithm specifically with mobile sink support for home automation networks. In this work, the network is divided into several clusters and cluster heads are selected within each cluster. Then, a mobile sink communicates with each cluster head to collect data directly through short range communications. The ACO algorithm has been utilized in this work in order to find the optimal mobility trajectory for the mobile sink. Extensive simulation results from this research show that the proposed algorithm significantly improves home network performance when using mobile sinks in terms of energy consumption and network lifetime as compared to other routing algorithms currently deployed for home automation networks.

A constrained recursive least squares algorithm for adaptive combination of multiple models

In this paper, we develop a novel constrained recursive least squares algorithm for adaptively combining a set of given multiple models. With data available in an online fashion, the linear combination coefficients of submodels are adapted via the proposed algorithm.We propose to minimize the mean square error with a forgetting factor, and apply the sum to one constraint to the combination parameters. Moreover an l1-norm constraint to the combination parameters is also applied with the aim to achieve sparsity of multiple models so that only a subset of models may be selected into the final model. Then a weighted l2-norm is applied as an approximation to the l1-norm term. As such at each time step, a closed solution of the model combination parameters is available. The contribution of this paper is to derive the proposed constrained recursive least squares algorithm that is computational efficient by exploiting matrix theory. The effectiveness of the approach has been demonstrated using both simulated and real time series examples.

A generalised background correction algorithm for a Halo Doppler lidar and its application to data from Finland

Current commercially available Doppler lidars provide an economical and robust solution for measuring vertical and horizontal wind velocities, together with the ability to provide co- and cross-polarised backscatter profiles. The high temporal resolution of these instruments allows turbulent properties to be obtained from studying the variation in radial velocities. However, the instrument specifications mean that certain characteristics, especially the background noise behaviour, become a limiting factor for the instrument sensitivity in regions where the aerosol load is low. Turbulent calculations require an accurate estimate of the contribution from velocity uncertainty estimates, which are directly related to the signal-to-noise ratio. Any bias in the signal-to-noise ratio will propagate through as a bias in turbulent properties. In this paper we present a method to correct for artefacts in the background noise behaviour of commercially available Doppler lidars and reduce the signal-to-noise ratio threshold used to discriminate between noise, and cloud or aerosol signals. We show that, for Doppler lidars operating continuously at a number of locations in Finland, the data availability can be increased by as much as 50 % after performing this background correction and subsequent reduction in the threshold. The reduction in bias also greatly improves subsequent calculations of turbulent properties in weak signal regimes.

Gaze stabilization testing: The efficiency and test-retest reliability of user operated control versus the parameter estimation (PEST) algorithm

The primary objective of this research study is to determine which form of testing, the PEST algorithm or an operator-controlled condition is most accurate and time efficient for administration of the gaze stabilization test

Evaluation of the contribution of the placentomal fusion during gestation in cattle

The placenta of mammals is a structure formed by the juxtaposition of the fetal membranes and the maternal tissues. The main function of the placenta is to regulate the physiological interchange between the fetus and the mother as well as to operate as an important endocrine organ during the gestation. The placentomal fusions were characterized throughout gestation of cattle using macroscopic, histological and flow cytometry analyses. Analyzing the cell cycle phases with a flow cytometry, a balance between the G2M phase and apoptosis was observed, suggesting that the placentomal fusions do not interfere in the placentary maturation process, which is a pre-requirement for the fetal-maternal disconnection and the release of fetal membrane. (C) 2011 Elsevier B.V. All rights reserved.

The SARS algorithm: detrending CoRoT light curves with Sysrem using simultaneous external parameters

Surveys for exoplanetary transits are usually limited not by photon noise but rather by the amount of red noise in their data. In particular, although the CoRoT space-based survey data are being carefully scrutinized, significant new sources of systematic noises are still being discovered. Recently, a magnitude-dependant systematic effect was discovered in the CoRoT data by Mazeh et al. and a phenomenological correction was proposed. Here we tie the observed effect to a particular type of effect, and in the process generalize the popular Sysrem algorithm to include external parameters in a simultaneous solution with the unknown effects. We show that a post-processing scheme based on this algorithm performs well and indeed allows for the detection of new transit-like signals that were not previously detected.

Genetic algorithm inversion of the average 1D crustal structure using local and regional earthquakes

Knowing the best 1D model of the crustal and upper mantle structure is useful not only for routine hypocenter determination, but also for linearized joint inversions of hypocenters and 3D crustal structure, where a good choice of the initial model can be very important. Here, we tested the combination of a simple GA inversion with the widely used HYPO71 program to find the best three-layer model (upper crust, lower crust, and upper mantle) by minimizing the overall P- and S-arrival residuals, using local and regional earthquakes in two areas of the Brazilian shield. Results from the Tocantins Province (Central Brazil) and the southern border of the Sao Francisco craton (SE Brazil) indicated an average crustal thickness of 38 and 43 km, respectively, consistent with previous estimates from receiver functions and seismic refraction lines. The GA + HYPO71 inversion produced correct Vp/Vs ratios (1.73 and 1.71, respectively), as expected from Wadati diagrams. Tests with synthetic data showed that the method is robust for the crustal thickness, Pn velocity, and Vp/Vs ratio when using events with distance up to about 400 km, despite the small number of events available (7 and 22, respectively). The velocities of the upper and lower crusts, however, are less well constrained. Interestingly, in the Tocantins Province, the GA + HYPO71 inversion showed a secondary solution (local minimum) for the average crustal thickness, besides the global minimum solution, which was caused by the existence of two distinct domains in the Central Brazil with very different crustal thicknesses. (C) 2010 Elsevier Ltd. All rights reserved.

Evidence of chromosome fusion in Gymnotus sylvius Albert & Fernandes-Matoli, 1999 (Teleostei: Gymnotiformes) detected by telomeric probes and R-banding

Gymnotus cf. carapo and Gynznotus sylvius are two fish species inhabiting the Upper Parana River Basin, presenting respectively 2n =54 and 2n = 40 chromosomes. In the present cytogenetic analysis, R-banding and telomere-sequence hybridization were carried out in order to determine the possible relationship between the karyotipes of these two species. Incorporation bands (R-bands) obtained for the two species allowed the identification of chromosome similarities, showing to be an usefull alternative to the G-banding methods, which fail in producing satisfying results in most of analyzed fish species. This approach, associated with the hybridization of telomeric sequences, permited to identify chromosomal rearrangements that could be used as indicators of karyotypic evolution within the group. In the present case, telomeric sequences were detected in the centromeric region of two metacentric chromosome pairs of Gymnotus sylvius. The results obtained after hybridization with the telomere sequences, coupled with the chromosome homeologies detected by R-banding, showed that G. cf carapo and G. sylvius should present a common ancestor, and this may also be corroborated by the similarities found in three chromosome pairs, that seem to have been conserved during the evolution of the two species. Based on the data here presented we propose that G. sylvius may have undergone a recent process of chromosome fusion that resulted in the diminution of its chromosome number.

Chromosomal Evolution in the Brazilian Geckos of the Genus Gymnodactylus (Squamata, Phyllodactylidae) from the Biomes of Cerrado, Caatinga and Atlantic Rain Forest: Evidence of Robertsonian Fusion Events and Supernumerary Chromosomes

Chromosomes of the South American geckos Gymnodactylus amarali and G. geckoides from open and dry areas of the Cerrado and Caatinga biomes in Brazil, respectively, were studied for the first time, after conventional and AgNOR staining, CBG- and RBG-banding, and FISH with telomeric sequences. Comparative analyses between the karyotypes of open areas and the previously studied Atlantic forest species G. darwinii were also performed. The chromosomal polymorphisms detected in populations of G. amarali from the states of Goias and Tocantins is the result of centric fusions (2n = 38, 39 and 40), suggesting a differentiation from a 2n = 40 ancestral karyotype and the presence of supernumerary chromosomes. The CBG- and RBG-banding patterns of the Bs are described. G. geckoides has 40 chromosomes with gradually decreasing sizes, but it is distinct from the 2n = 40 karyotypes of G. amarali and G. darwinii due to occurrence of pericentric inversions or centromere repositioning. NOR location seems to be a marker for Gymnodactylus, as G. amarali and G. geckoides share a medium-sized subtelocentric NOR-bearing pair, while G. darwinii has NORs at the secondary constriction of the long arm of pair 1. The comparative analyses indicate a non-random nature of the Robertsonian rearrangements in the genus Gymnodactylus. Copyright (C) 2010 S. Karger AG, Basel

TAF15 and the leukemia-associated fusion protein TAF15-CIZ/NMP4 are cleaved by caspases-3 and-7

Caspases are central players in proteolytic pathways that regulate cellular processes Such as apoptosis and differentiation. To accelerate the discovery of novel caspase substrates we developed a method combining in silico screening and in vitro validation. With this approach, we identified TAH15 as a novel caspase Substrate in a trial Study. We find that TAF15 was specifically cleaved by caspases-3 and -7. Site-directed mutagenesis revealed the consensus sequence (106)DQPD/Y(110) as the only site recognized by these caspases. Surprisingly, TAF15 was cleaved at more than one site in staurosporine-treated Jurkat cells. In addition, we generated two oncogenic TAF15-CIZ/NMP4-fused proteins which have been found in acute myeloid leukemia and demonstrate that caspases-3 and -7 cleave the fusion proteins at one single site. Broad application of this combination approach should expedite identification of novel caspase-interacting proteins and provide new insights into the regulation of caspase pathways leading to cell death in normal and cancer cells. (C) 2009 Elsevier Inc. All rights reserved.

Expression and purification of human respiratory syncytial virus recombinant fusion protein

The Human Respiratory Syncytial Virus (HRSV) fusion protein (F) was expressed in Escherichia call BL21A using the pET28a vector at 37 degrees C. The protein was purified from the soluble fraction using affinity resin. The structural quality of the recombinant fusion protein and the estimation of its secondary structure were obtained by circular dichroism. Structural models of the fusion protein presented 46% of the helices in agreement with the spectra by circular dichroism analysis. There are only few studies that succeeded in expressing the HRSV fusion protein in bacteria. This is a report on human fusion protein expression in E. call and structure analysis, representing a step forward in the development of fusion protein F inhibitors and the production of antibodies. (c) 2008 Elsevier Inc. All rights reserved.