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

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.

Identification and lineage genotyping of South American trypanosomes using fluorescent fragment length barcoding

Trypanosoma cruzi and Trypanosoma rangeli are human-infective blood parasites, largely restricted to Central and South America. They also infect a wide range of wild and domestic mammals and are transmitted by a numerous species of triatomine bugs. There are significant overlaps in the host and geographical ranges of both species. The two species consist of a number of distinct phylogenetic lineages. A range of PCR-based techniques have been developed to differentiate between these species and to assign their isolates into lineages. However, the existence of at least six and five lineages within T. cruzi and T. rangeli, respectively, makes identification of the full range of isolates difficult and time consuming. Here we have applied fluorescent fragment length barcoding (FFLB) to the problem of identifying and genotyping T. cruzi, T. rangeli and other South American trypanosomes. This technique discriminates species on the basis of length polymorphism of regions of the rDNA locus. FFLB was able to differentiate many trypanosome species known from South American mammals: T. cruzi cruzi. T. cruzi marinkellei, T. dionisii-like, T. evansi, T. lewisi, T. rangeli, T. theileri and T. vivax. Furthermore, all five T. rangeli lineages and many T. cruzi lineages could be identified, except the hybrid lineages TcV and TcVI that could not be distinguished from lineages III and II respectively. This method also allowed identification of mixed infections of T. cruzi and T. rangeli lineages in naturally infected triatomine bugs. The ability of FFLB to genotype multiple lineages of T. cruzi and T. rangeli together with other trypanosome species, using the same primer sets is an advantage over other currently available techniques. Overall, these results demonstrate that FFLB is a useful method for species diagnosis, genotyping and understanding the epidemiology of American trypanosomes. (C) 2010 Elsevier B.V. All rights reserved.

Cysteine proteases of Trypanosoma (Megatrypanum) theileri: Cathepsin L-like gene sequences as targets for phylogenetic analysis, genotyping diagnosis

Although Trypanosoma theileri and allied trypanosomes are the most widespread trypanosomes in bovids little is known about proteolytic enzymes in these species. We have characterized genes encoding for cathepsin L-like (CATL) cysteine proteases from isolates of cattle, water buffalo and deer that largely diverged from homologues of other trypanosome species. Analysis of 78 CATL catalytic domain sequences from 22 T. theileri trypanosomes disclosed 6 genotypes tightly clustered together into the T. theileri clade. The CATL genes in these trypanosomes are organized in tandem arrays of similar to 1.7 kb located in 2 chromosomal bands of 600-720 kb. A diagnostic PCR assay targeting CATL sequences detected T. theileri of all genotypes from cattle, buffaloes and cervids and also from tabanid vectors. Expression of T. theileri cysteine proteases was demonstrated by proteolytic activity in gelatin gels and hydrolysis of Z-Phe-Arg-AMC substrate. Results from this work agree with previous data using ribosomal and spliced leader genes demonstrating that CATL gene sequences are useful for diagnosis, population genotyping and evolutionary studies of T. theileri trypanosomes. (c) 2010 Elsevier Ireland Ltd. All rights reserved.

Genes of cathepsin L-like proteases in Trypanosoma rangeli isolates: Markers for diagnosis, genotyping and phylogenetic relationships

We have sequenced genes encoding cathepsin L-like (CatL-like) cysteine proteases from isolates of Trypanosoma rangeli from humans, wild mammals and Rhodnius species of Central and South America. Phylogenetic trees of sequences encoding mature CatL-like enzymes of T rangeli and homologous genes from other trypanosomes, Leishmania spp. and bodonids positioned sequences of T rangeli (rangelipain) closest to T cruzi (cruzipain). Phylogenetic tree of kinetoplastids based on sequences of CatL-like was totally congruent with those derived from SSU rRNA and gGAPDH genes. Analysis of sequences from the CatL-like catalytic domains of 17 isolates representative of the overall phylogenetic diversity and geographical range of T rangeli supported all the lineages (A-D) previously defined using ribosomal and spliced leader genes. Comparison of the proteolytic activities of T rangeli isolates revealed heterogeneous banding profiles of cysteine proteases in gelatin gels, with differences even among isolates of the same lineage. CatL-like sequences proved to be excellent targets for diagnosis and genotyping of T rangeli by PCR. Data from CatL-like encoding genes agreed with results from previous studies of kDNA markers, and ribosomal and spliced leader genes, thereby corroborating clonal evolution, independent transmission cycles and the divergence of T rangeli lineages associated with sympatric species of Rhodnius. (c) 2009 Elsevier B.V. All rights reserved.

Genotyping, physiological features and proteolytic activities of a potentially pathogenic Acanthamoeba sp isolated from tap water in Brazil

Acanthamoeba spp., known to cause keratitis and granulomatous encephalitis in humans, are frequently isolated from a variety of water sources. Here we report for the first time the characterization of an Acanthamoeba sp. (ACC01) isolated from tap water in Brazil. This organism is currently being maintained in an axenic growth medium. Phylogenetic analysis based on SSU rRNA gene sequences positioned the new isolate in genotype T4, closest to the keratitis-causing isolate, A. polyphaga ATCC 30461 (similar to 99% similarity). Acanthamoeba ACC01 and A. polyphaga 30461 both grew at 37 degrees C and were osmotically resistant, multiplying in hyperosmolar medium. Both isolates secreted comparable amounts of proteolytic enzymes, including serine peptidases that were optimally active at a near neutral/alkaline pH and resolved identically in gelatin gels. Incubation of gels at pH 4.0 with 2 mM DTT also indicated the secretion of similar cysteine peptidases. Altogether, the results point to the pathogenic potential of Acanthamoeba ACC01. (C) 2009 Elsevier Inc. All rights reserved.

A new genotype of Trypanosoma cruzi associated with bats evidenced by phylogenetic analyses using SSU rDNA, cytochrome b and Histone H2B genes and genotyping based on ITS1 rDNA

We characterized 15 Trypanosoma cruzi isolates from bats captured in the Amazon, Central and Southeast Brazilian regions. Phylogenetic relationships among T. cruzi lineages using SSU rDNA, cytochrome b, and Histone H2B genes positioned all Amazonian isolates into T. cruzi I (TCI). However, bat isolates from the other regions, which had been genotyped as T. cruzi II (TC II) by the traditional genotyping method based on mini-exon gene employed in this study, Were not nested within any of the previously defined TCII sublineages, constituting a new genotype designated as TCbat. Phylogenetic analyses demonstrated that TCbat indeed belongs to T. cruzi and not to other closely related bat trypanosomes of the subgenus Schizotrypanum, and that although separated by large genetic distances TO-tat is closest to lineage TCI. A genotyping method targeting ITS1 rDNA distinguished TCbat from established T. cruzi lineages, and from other Schizotrypanum species. In experimentally infected mice, TCbat lacked virulence and yielded loss parasitaemias. Isolates of TCbat presented distinctive morphological features and behaviour in triatomines. To date, TCbat genotype wall found only in bats from anthropic environments of Central and Southeast Brazil. Our findings indicate that the complexity of T. cruzi is larger than currently known, and confirmed bats as important reservoirs and potential source of T. cruzi infections to humans.

Trypanosoma rangeli isolates of bats from Central Brazil: Genotyping and phylogenetic analysis enable description of a new lineage using spliced-leader gene sequences

Trypanosoma rangeli infects several mammalian orders but has never confidently been described in Chiroptera, which are commonly parasitized by many trypanosome species. Here, we described trypanosomes from bats captured in Central Brazil identified as T rangeli,.T. dionisii, T cruzimarinkellei and T cruzi. Two isolates, Tra643 from Platyrrhinus lineatus and Tra1719 from Artibeus plamirostris were identified as T rangeli by morphological, biological and molecular methods, and confirmed by phylogenetic analyses. Analysis using SSU rDNA sequences clustered these bat trypanosomes together with T rangeli from other hosts, and separated them from other trypanosomes from bats. Genotyping based on length and sequence polymorphism of PCR-amplified intergenic spliced-leader gene sequences assigned Tra1719 to the lineage A whereas Tra643 was shown to be a new genotype and was assigned to the new lineage E. To our knowledge, these two isolates are the earliest T rangeli from bats and the first isolates from Central Brazil molecularly characterized. Rhodnius stali captured for this study was found infected by T rangeli and T cruzi. (c) 2008 Elsevier B.V. All rights reserved.

Investigation of a new GRASP-based clustering algorithm applied to biological data

A large amount of biological data has been produced in the last years. Important knowledge can be extracted from these data by the use of data analysis techniques. Clustering plays an important role in data analysis, by organizing similar objects from a dataset into meaningful groups. Several clustering algorithms have been proposed in the literature. However, each algorithm has its bias, being more adequate for particular datasets. This paper presents a mathematical formulation to support the creation of consistent clusters for biological data. Moreover. it shows a clustering algorithm to solve this formulation that uses GRASP (Greedy Randomized Adaptive Search Procedure). We compared the proposed algorithm with three known other algorithms. The proposed algorithm presented the best clustering results confirmed statistically. (C) 2009 Elsevier Ltd. All rights reserved.

Infeasibility handling in genetic algorithm using nested domains for production planning

In this paper we present a genetic algorithm with new components to tackle capacitated lot sizing and scheduling problems with sequence dependent setups that appear in a wide range of industries, from soft drink bottling to food manufacturing. Finding a feasible solution to highly constrained problems is often a very difficult task. Various strategies have been applied to deal with infeasible solutions throughout the search. We propose a new scheme of classifying individuals based on nested domains to determine the solutions according to the level of infeasibility, which in our case represents bands of additional production hours (overtime). Within each band, individuals are just differentiated by their fitness function. As iterations are conducted, the widths of the bands are dynamically adjusted to improve the convergence of the individuals into the feasible domain. The numerical experiments on highly capacitated instances show the effectiveness of this computational tractable approach to guide the search toward the feasible domain. Our approach outperforms other state-of-the-art approaches and commercial solvers. (C) 2009 Elsevier Ltd. All rights reserved.