Path planning of robots in noisy workspaces using learning automata

The problem of a manipulator operating in a noisy workspace and required to move from an initial fixed position P0 to a final position Pf is considered. However, Pf is corrupted by noise, giving rise to Pˆf, which may be obtained by sensors. The use of learning automata is proposed to tackle this problem. An automaton is placed at each joint of the manipulator which moves according to the action chosen by the automaton (forward, backward, stationary) at each instant. The simultaneous reward or penalty of the automata enables avoiding any inverse kinematics computations that would be necessary if the distance of each joint from the final position had to be calculated. Three variable-structure learning algorithms are used, i.e., the discretized linear reward-penalty (DLR-P, the linear reward-penalty (LR-P ) and a nonlinear scheme. Each algorithm is separately tested with two (forward, backward) and three forward, backward, stationary) actions.

Evaluating the structure and magnitude of the ash plume during the initial phase of the 2010 Eyjafjallajökull eruption using lidar observations and NAME simulations

The Eyjafjallajökull volcano in Iceland erupted explosively on 14 April 2010, emitting a plume of ash into the atmosphere. The ash was transported from Iceland toward Europe where mostly cloud-free skies allowed ground-based lidars at Chilbolton in England and Leipzig in Germany to estimate the mass concentration in the ash cloud as it passed overhead. The UK Met Office's Numerical Atmospheric-dispersion Modeling Environment (NAME) has been used to simulate the evolution of the ash cloud from the Eyjafjallajökull volcano during the initial phase of the ash emissions, 14–16 April 2010. NAME captures the timing and sloped structure of the ash layer observed over Leipzig, close to the central axis of the ash cloud. Relatively small errors in the ash cloud position, probably caused by the cumulative effect of errors in the driving meteorology en route, result in a timing error at distances far from the central axis of the ash cloud. Taking the timing error into account, NAME is able to capture the sloped ash layer over the UK. Comparison of the lidar observations and NAME simulations has allowed an estimation of the plume height time series to be made. It is necessary to include in the model input the large variations in plume height in order to accurately predict the ash cloud structure at long range. Quantitative comparison with the mass concentrations at Leipzig and Chilbolton suggest that around 3% of the total emitted mass is transported as far as these sites by small (<100 μm diameter) ash particles.

Prediction of moisture, calorific value, ash and carbon content of two dedicated bioenergy crops using near-infrared spectroscopy

The potential of near infrared spectroscopy in conjunction with partial least squares regression to predict Miscanthus xgiganteus and short rotation coppice willow quality indices was examined. Moisture, calorific value, ash and carbon content were predicted with a root mean square error of cross validation of 0.90% (R2 = 0.99), 0.13 MJ/kg (R2 = 0.99), 0.42% (R2 = 0.58), and 0.57% (R2 = 0.88), respectively. The moisture and calorific value prediction models had excellent accuracy while the carbon and ash models were fair and poor, respectively. The results indicate that near infrared spectroscopy has the potential to predict quality indices of dedicated energy crops, however the models must be further validated on a wider range of samples prior to implementation. The utilization of such models would assist in the optimal use of the feedstock based on its biomass properties.

A study of the arrival over the United Kingdom in April 2010 of the Eyjafjallajökull ash cloud using ground-based lidar and numerical simulations

We make a qualitative and quantitative comparison of numericalsimulations of the ashcloud generated by the eruption of Eyjafjallajökull in April2010 with ground-basedlidar measurements at Exeter and Cardington in southern England. The numericalsimulations are performed using the Met Office’s dispersion model, NAME (Numerical Atmospheric-dispersion Modelling Environment). The results show that NAME captures many of the features of the observed ashcloud. The comparison enables us to estimate the fraction of material which survives the near-source fallout processes and enters into the distal plume. A number of simulations are performed which show that both the structure of the ashcloudover southern England and the concentration of ash within it are particularly sensitive to the height of the eruption column (and the consequent estimated mass emission rate), to the shape of the vertical source profile and the level of prescribed ‘turbulent diffusion’ (representing the mixing by the unresolved eddies) in the free troposphere with less sensitivity to the timing of the start of the eruption and the sedimentation of particulates in the distal plume.

Conformational analysis of oriented non-crystalline polymers using wide angle X-ray scattering

A procedure is presented for obtaining conformational parameters from oriented but non-crystalline polymers. This is achieved by comparison of the experimental wide angle X-ray scattering with that calculated from models but in such a way that foreknowledge of the orientation distribution function is not required. X-ray scattering intensity values for glassy isotactic poly(methylmethacrylate) are analysed by these techniques. The method could be usefully applied to other oriented molecular systems such as liquid crystalline materials.

Prediction of novel and analogous folds using fragment assembly and fold recognition

A number of new and newly improved methods for predicting protein structure developed by the Jones–University College London group were used to make predictions for the CASP6 experiment. Structures were predicted with a combination of fold recognition methods (mGenTHREADER, nFOLD, and THREADER) and a substantially enhanced version of FRAGFOLD, our fragment assembly method. Attempts at automatic domain parsing were made using DomPred and DomSSEA, which are based on a secondary structure parsing algorithm and additionally for DomPred, a simple local sequence alignment scoring function. Disorder prediction was carried out using a new SVM-based version of DISOPRED. Attempts were also made at domain docking and “microdomain” folding in order to build complete chain models for some targets.

Development of a dense SNP-based linkage map of an apple rootstock progeny using the Malus Infinium whole genome genotyping array

Background A whole-genome genotyping array has previously been developed for Malus using SNP data from 28 Malus genotypes. This array offers the prospect of high throughput genotyping and linkage map development for any given Malus progeny. To test the applicability of the array for mapping in diverse Malus genotypes, we applied the array to the construction of a SNPbased linkage map of an apple rootstock progeny. Results Of the 7,867 Malus SNP markers on the array, 1,823 (23.2 %) were heterozygous in one of the two parents of the progeny, 1,007 (12.8 %) were heterozygous in both parental genotypes, whilst just 2.8 % of the 921 Pyrus SNPs were heterozygous. A linkage map spanning 1,282.2 cM was produced comprising 2,272 SNP markers, 306 SSR markers and the S-locus. The length of the M432 linkage map was increased by 52.7 cM with the addition of the SNP markers, whilst marker density increased from 3.8 cM/marker to 0.5 cM/marker. Just three regions in excess of 10 cM remain where no markers were mapped. We compared the positions of the mapped SNP markers on the M432 map with their predicted positions on the ‘Golden Delicious’ genome sequence. A total of 311 markers (13.7 % of all mapped markers) mapped to positions that conflicted with their predicted positions on the ‘Golden Delicious’ pseudo-chromosomes, indicating the presence of paralogous genomic regions or misassignments of genome sequence contigs during the assembly and anchoring of the genome sequence. Conclusions We incorporated data for the 2,272 SNP markers onto the map of the M432 progeny and have presented the most complete and saturated map of the full 17 linkage groups of M. pumila to date. The data were generated rapidly in a high-throughput semi-automated pipeline, permitting significant savings in time and cost over linkage map construction using microsatellites. The application of the array will permit linkage maps to be developed for QTL analyses in a cost-effective manner, and the identification of SNPs that have been assigned erroneous positions on the ‘Golden Delicious’ reference sequence will assist in the continued improvement of the genome sequence assembly for that variety.

Multi-target out-of-sequence data association: tracking using graphical models

When performing data fusion, one often measures where targets were and then wishes to deduce where targets currently are. There has been recent research on the processing of such out-of-sequence data. This research has culminated in the development of a number of algorithms for solving the associated tracking problem. This paper reviews these different approaches in a common Bayesian framework and proposes an architecture that orthogonalises the data association and out-of-sequence problems such that any combination of solutions to these two problems can be used together. The emphasis is not on advocating one approach over another on the basis of computational expense, but rather on understanding the relationships among the algorithms so that any approximations made are explicit. Results for a multi-sensor scenario involving out-of-sequence data association are used to illustrate the utility of this approach in a specific context.

Effects of dietary selenium supplementation on tissue selenium distribution and glutathione peroxidase activity in Chinese Ring Necked Pheasants

The objective of this study was to determine the concentration of total selenium (Se) and the proportions of total Se comprised as selenomethionine (SeMet) and selenocysteine (SeCys) in the post mortem tissues of female pheasants (Phasianus Colchicus Torquator) offered diets containing graded additions of selenized enriched yeast (SY) or sodium selenite (SS). Thiobarbituric acid reactive substances (TBARS) and tissue glutathione peroxidase (GSH-Px) activity of breast (Pectoralis Major) were assessed at 0 and 5 d post-mortem. A total of 216 female pheasant chicks were enrolled onto the study. 24 birds were euthanased at the start of the study and samples of blood, breast muscle, leg muscle (Peroneus Longus and M. Gastrocnemius), heart, liver, kidney and gizzard collected for determination of total Se. Remaining birds were blocked by live weight and randomly allocated to one of four dietary treatments (n=48 birds/treatment) that either differed in Se source (SY vs. SS) or dose (Con [0.2 mg total Se/kg], SY-L and SS-L [0.3 mg/kg total Se as SY and SS, respectively], and SY-H [0.45 mg total Se/kg]). Following 42 and 91 days of treatment 24 birds/treatment were euthanased and samples of blood, breast muscle, leg muscle, heart, liver, kidney and gizzard retained for determination of total Se and the proportion of total Se comprised as SeMet or SeCys. Whole blood GSH-Px activity was determined at each time point. Tissue GSH-Px activity and TBARS were determined in breast tissue at the end of the study. There were positive responses (P<0.001) in both blood and tissues to the graded addition of SY to the diet but the same responses were not apparent in the blood and tissues of selenite supplemented birds receiving comparable doses. Although there were differences between tissue types in the distribution of SeMet and SeCys there were few differences between treatments. There were effects of treatment on erythrocyte GSH-Px activity (P = 0.012) with values being higher in treatments SY-H and SS-L when compared to the negative control and treatment SY-L. There were no effects of treatment on tissue GSH-Px activity which is reflected in the overall lack of any treatment effects on TBARS.

A comparison of the anticancer properties of isoxanthohumol and 8-prenylnaringenin using in vitro models of colon cancer

The hops plant (Humulus lupulus L.) is an essential ingredient in beer and contains a number of potentially bioactive prenylflavonoids, the predominant being the weakly estrogenic isoxanthohumol (Ix), which can be converted to the more strongly estrogenic 8-PN by the colonic microbiota. The aim of this study was to investigate the biological activity of 8-PN and Ix using in vitro models representing key stages of colorectal carcinogenesis, namely cell growth and viability (MTT assay), cell-cycle progression (DNA content assay), DNA damage (Comet assay), and invasion (Matrigel assay). A significant decrease in Caco-2 cell viability was noted after both 8-PN and Ix treatments at the higher doses (40 and 50 μM, respectively) although the impact on cell cycle differed between the two compounds. The decreased cell viability observed after Ix treatment was associated with a concentration-dependent increase in G2/M and an increased sub-G1 cell-cycle fraction, whereas treatment with 8-PN was associated with an elevated G0/G1 and an increased sub-G1 cell-cycle fraction. Significant antigenotoxic activity was noted at all 8-PN concentrations tested (5-40 μM). Although significant antigenotoxic activity was also noted with Ix treatment at ≤25 μM, at a higher dose, Ix itself exerted genotoxic activity. In a dose-dependent manner, both compounds inhibited HT115 cell invasion with reductions up to 52 and 46% for Ix and 8-PN, respectively, in comparison to untreated cells. This study demonstrated that both Ix and its gut microbial metabolite 8-PN exert anticancer effects on models of key stages of colon tumourigenesis.

Modelling QoS of a pervasive MVNO/M2M using semi-group theory

This paper aims to develop a mathematical model based on semi-group theory, which allows to improve quality of service (QoS), including the reduction of the carbon path, in a pervasive environment of a Mobile Virtual Network Operator (MVNO). This paper generalise an interrelationship Machine to Machine (M2M) mathematical model, based on semi-group theory. This paper demonstrates that using available technology and with a solid mathematical model, is possible to streamline relationships between building agents, to control pervasive spaces so as to reduce the impact in carbon footprint through the reduction of GHG.

Enhancement of aged and denatured fingerprints using the cyanoacrylate fuming technique following dusting with amino acid-containing powders

We have carried out experiments to investigate the ageing of latent fingerprints deposited on black PVC over a period of 4-15 weeks. A thumbprint was used in each case and before deposition of the print the donor rubbed their thumb around their nose to add sebaceous deposits. We have studied the effect of heat, light and moisture and we find that moisture is the most significant factor in the degradation of the latent print. We have attempted to enhance these latent prints by dusting with valine powder or powders composed of valine mixed with gold or red fluorescent commercial fingerprint powders. In order to make a direct comparison between “treated” and “untreated” prints, the prints were cut in half with one half being “treated” and one not. Our studies show the best results being obtained when powders of valine and red fluorescent powders are applied prior to cyanoacrylate fuming.