Tunable and switchable multiwavelength fiber lasers with broadband range based on nonlinear polarization rotation technique

Switchable multiwavelength fiber laser outputs with a wide tuning range are experimentally observed in an ultralong cavity. Because of the long spooled single-mode fiber and filter effect of the cavity, multiwavelength lasers with the spacing of similar to 14.5 nm are obtained. The proposed fiber laser has the capacity of simultaneously emitting the three wavelengths. By means of adjusting the polarization controllers, the arbitrary single- and dual-wavelength operations are achieved in our laser. (C) 2010 Society of Photo-Optical Instrumentation Engineers. [DOI: 10.1117/1.3485754]

The Dirichlet problem in convex bounded domains for operators with L^\infty-coefficients

M.Hieber, I.Wood: The Dirichlet problem in convex bounded domains for operators with L^\infty-coefficients, Diff. Int. Eq., 20, 7 (2007),721-734.

The Dirichlet problem in convex bounded domains for operators with L8-coefficients

Wood, Ian; Hieber, M., (2007) 'The Dirichlet problem in convex bounded domains for operators with L8-coefficients', Differential and Integral Equations 20 pp.721-734 RAE2008

The frequency of JAK2 exon 12 mutations in idiopathic erythrocytosis patients with low serum erythropoietin levels

Idiopathic erythrocytosis (IE) is characterized by erythrocytosis in the absence of megakaryocytic or granulocytic hyperplasia, and is associated with variable serum erythropoietin (Epo) levels. Most patients with IE lack the JAK2 V617F mutation that occurs in the majority of polycythemia vera patients. Four novel JAK2 mutant alleles have recently been described in patients with V617F-negative myeloproliferative disorders presenting with erythrocytosis. The aims of this study were to assess the prevalence of JAK2 exon 12 mutations in IE patients, and to determine the associated clinicopathological features.

Modelling gas storage with compressed air energy storage in a system with large wind penetrations

Installed wind capacity in the European Union is expected to continue to increase due to renewable energy targets and obligations to reduce greenhouse gas emissions. Renewable energy sources such as wind power are variable sources of power. Energy storage technologies are useful to manage the issues associated with variable renewable energy sources and align non-dispatchable renewable energy generation with load demands. Energy storage technologies can play different roles in electric power systems and can be used in each of the steps of the electric power supply chain. Moreover, large scale energy storage systems can act as renewable energy integrators by smoothening the variability of large penetrations of wind power. Compress Air Energy Storage is one such technology. The aim of this paper is to examine the technical and economic feasibility of a combined gas storage and compressed air energy storage facility in the all-island Single Electricity Market of Northern Ireland and the Republic of Ireland in order to optimise power generation and wind power integration. This analysis is undertaken using the electricity market software PLEXOS ® for power systems by developing a model of a combined facility in 2020.

Robust Multimodal Person Identification With Limited Training Data

This paper presents a novel method of audio-visual feature-level fusion for person identification where both the speech and facial modalities may be corrupted, and there is a lack of prior knowledge about the corruption. Furthermore, we assume there are limited amount of training data for each modality (e.g., a short training speech segment and a single training facial image for each person). A new multimodal feature representation and a modified cosine similarity are introduced to combine and compare bimodal features with limited training data, as well as vastly differing data rates and feature sizes. Optimal feature selection and multicondition training are used to reduce the mismatch between training and testing, thereby making the system robust to unknown bimodal corruption. Experiments have been carried out on a bimodal dataset created from the SPIDRE speaker recognition database and AR face recognition database with variable noise corruption of speech and occlusion in the face images. The system's speaker identification performance on the SPIDRE database, and facial identification performance on the AR database, is comparable with the literature. Combining both modalities using the new method of multimodal fusion leads to significantly improved accuracy over the unimodal systems, even when both modalities have been corrupted. The new method also shows improved identification accuracy compared with the bimodal systems based on multicondition model training or missing-feature decoding alone.

The C-Terminal Variable Region Specifies the Dynamic Properties of Arabidopsis Microtubule-Associated Protein MAP65 Isotypes

The microtubule-associated protein, MAP65, is a member of a family of divergent microtubule-associated proteins from different organisms generally involved in maintaining the integrity of the central spindle in mitosis. The dicotyledon Arabidopsis thaliana and the monocotyledon rice (Oryza sativa) genomes contain 9 and 11 MAP65 genes, respectively. In this work, we show that the majority of these proteins fall into five phylogenetic clades, with the greatest variation between clades being in the C-terminal random coil domain. At least one Arabidopsis and one rice isotype is within each clade, indicating a functional specification for the C terminus. In At MAP65-1, the C-terminal domain is a microtubule binding region (MTB2) harboring the phosphorylation sites that control its activity. The At MAP65 isotypes show differential localization to microtubule arrays and promote microtubule polymerization with variable efficiency in a MTB2-dependent manner. In vivo studies demonstrate that the dynamics of the association and dissociation of different MAP65 isotypes with microtubules can vary up to 10-fold and that this correlates with their ability to promote microtubule polymerization. Our data demonstrate that the C-terminal variable region, MTB2, determines the dynamic properties of individual isotypes and suggest that slower turnover is conditional for more efficient microtubule polymerization.

Impacts of compressed air energy storage plant on an electricity market with a large renewable energy portfolio

Renewable energy generation is expected to continue to increase globally due to renewable energy targets and obligations to reduce greenhouse gas emissions. Some renewable energy sources are variable power sources, for example wind, wave and solar. Energy storage technologies can manage the issues associated with variable renewable generation and align non-dispatchable renewable energy generation with load demands. Energy storage technologies can play different roles in each of the step of the electric power supply chain. Moreover, large scale energy storage systems can act as renewable energy integrators by smoothing the variability. Compressed air energy storage is one such technology. This paper examines the impacts of a compressed air energy storage facility in a pool based wholesale electricity market in a power system with a large renewable energy portfolio.

Type Synthesis of 3-DOF Multi-Mode Translational/Spherical Parallel Mechanisms with Lockable Joints

A 3-DOF (degrees-of-freedom) multi-mode translational/spherical PM (parallel mechanism) with lockable joints is a novel reconfigurable PM. It has both 3-DOF spatial translational operation mode and 3-DOF spherical operation mode. This paper presents an approach to the type synthesis of translational/spherical PMs with lockable joints. Using the proposed approach, several 3-DOF translational/spherical PMs are obtained. It is found that these translational/spherical PMs do not encounter constraint singular configurations and self-motion of sub-chain of a leg during reconfiguration. The approach can also be used for synthesizing other classes of multi-mode PMs with lockable joints, multi-mode PMs with variable kinematic joints, partially decoupled PMs, and reconfigurable PMs with a reconfigurable platform.

Nanoscale reinforced orthopaedic bone cement with graphene oxide - a possible solution to aseptic loosening of cemented hip implants? Preliminary results of an ongoing study

Hip replacement surgery is amongst the most common orthopaedic operations performed in the UK. Aseptic loosening is responsible for 40% of hip revision procedures. Aseptic loosening is a result of cement mantle fatigue. The aim of the current study is to analyse the effect of nanoscale Graphene Oxide (GO) on the mechanical properties of orthopaedic bone cement. Study Design A experimental thermal and mechanical analysis was conducted in a laboratory set up conforming to international standards for bone cement testing according to ISO 5583. Testing was performed on control cement samples of Colacryl bone cement, and additional samples reinforced with variable wt% of Graphene Oxide containing composites – 0.1%, 0.25%, 0.5% and 1.0% GO loading. Pilot Data Porosity demonstrated a linear relationship with increasing wt% loading compared to control (p<0.001). Thermal characterisation demonstrated maximal temperature during polymerization, and generated exotherm were inversely proportional to w%t loading (p<0.05) Fatigue strength performed on the control and 0.1 and 0.25%wt loadings of GO demonstrate increased average cycles to failure compared to control specimens. A right shift of the Weibull curve was demonstrated for both wt% available currently. Logistic regression analysis for failure demonstrated significant increases in number of cycles to failure for both specimens compared to a control (p<0.001). Forward Plan Early results convey positive benefits at low wt% loadings of GO containing bone cement. Study completion and further analysis is required in order to elude to the optimum w%t of GO which conveys the greatest mechanical advantage.

Robust bimodal person identification using face and speech with limited training data and corruption of both modalities

This paper presents a novel method of audio-visual fusion for person identification where both the speech and facial modalities may be corrupted, and there is a lack of prior knowledge about the corruption. Furthermore, we assume there is a limited amount of training data for each modality (e.g., a short training speech segment and a single training facial image for each person). A new representation and a modified cosine similarity are introduced for combining and comparing bimodal features with limited training data as well as vastly differing data rates and feature sizes. Optimal feature selection and multicondition training are used to reduce the mismatch between training and testing, thereby making the system robust to unknown bimodal corruption. Experiments have been carried out on a bimodal data set created from the SPIDRE and AR databases with variable noise corruption of speech and occlusion in the face images. The new method has demonstrated improved recognition accuracy.

Boundary value problems for analytic functions in the class of Cauchy-type integrals with density in

We study the Riemann boundary value problem , for analytic functions in the class of analytic functions represented by the Cauchy-type integrals with density in the spaces with variable exponent. We consider both the case when the coefficient is piecewise continuous and it may be of a more general nature, admitting its oscillation. The explicit formulas for solutions in the variable exponent setting are given. The related singular integral equations in the same setting are also investigated. As an application there is derived some extension of the Szegö-Helson theorem to the case of variable exponents.

Les impacts de la satisfaction envers les régimes de rémunération variable sur l’engagement organisationnel des travailleurs

Ce mémoire a pour objectif de comprendre l’impact de la satisfaction envers les régimes de rémunération variable sur l’engagement organisationnel des travailleurs. Pour étudier cette question, nous avons utilisé trois hypothèses basées sur la théorie des attentes ainsi que sur la théorie de l’agence. La première hypothèse stipule que la satisfaction envers les régimes de bonis fait augmenter le niveau d’engagement organisationnel des travailleurs. La deuxième hypothèse est que la satisfaction envers les régimes de partage des bénéfices fait augmenter le niveau d’engagement organisationnel des travailleurs. La troisième hypothèse stipule que la satisfaction envers les régimes d’actionnariat fait augmenter le niveau d’engagement organisationnel des travailleurs. Nous avons utilisé une base de données provenant d’une enquête plus large portant sur « les liens entre la rémunération, la formation et le développement des compétences et l’attraction et la rétention d’employés clés ». L’entreprise où les données ont été collectées œuvre dans le secteur des technologies de l’information et des communications (TIC). Les nouveaux employés embauchés dans cette entreprise établie à Montréal ont été interrogés. Nos résultats nous permettent de confirmer deux de nos hypothèses, soit celle qui concerne les régimes de bonis et celle qui concerne les régimes d’actionnariat. Nos résultats indiquent que les individus satisfaits à l’égard des régimes de rémunération variable, plus précisément envers les régimes de bonis et les régimes d’actionnariat, présentent de plus hauts niveaux d’engagement organisationnel. Le soutien organisationnel perçu est également un facteur important dans le développement de l’engagement organisationnel. Finalement, nous concluons ce mémoire avec l’implication de nos résultats pour les différents acteurs en relations industrielles.

Synapsing variable length crossover: An algorithm for crossing and comparing variable length genomes

The Synapsing Variable Length Crossover (SVLC) algorithm provides a biologically inspired method for performing meaningful crossover between variable length genomes. In addition to providing a rationale for variable length crossover it also provides a genotypic similarity metric for variable length genomes enabling standard niche formation techniques to be used with variable length genomes. Unlike other variable length crossover techniques which consider genomes to be rigid inflexible arrays and where some or all of the crossover points are randomly selected, the SVLC algorithm considers genomes to be flexible and chooses non-random crossover points based on the common parental sequence similarity. The SVLC Algorithm recurrently "glues" or synapses homogenous genetic sub-sequences together. This is done in such a way that common parental sequences are automatically preserved in the offspring with only the genetic differences being exchanged or removed, independent of the length of such differences. In a variable length test problem the SVLC algorithm is shown to outperform current variable length crossover techniques. The SVLC algorithm is also shown to work in a more realistic robot neural network controller evolution application.

Synapsing variable-length crossover: Meaningful crossover for variable-length genomes

The synapsing variable-length crossover (SVLC algorithm provides a biologically inspired method for performing meaningful crossover between variable-length genomes. In addition to providing a rationale for variable-length crossover, it also provides a genotypic similarity metric for variable-length genomes, enabling standard niche formation techniques to be used with variable-length genomes. Unlike other variable-length crossover techniques which consider genomes to be rigid inflexible arrays and where some or all of the crossover points are randomly selected, the SVLC algorithm considers genomes to be flexible and chooses non-random crossover points based on the common parental sequence similarity. The SVLC algorithm recurrently "glues" or synapses homogenous genetic subsequences together. This is done in such a way that common parental sequences are automatically preserved in the offspring with only the genetic differences being exchanged or removed, independent of the length of such differences. In a variable-length test problem, the SVLC algorithm compares favorably with current variable-length crossover techniques. The variable-length approach is further advocated by demonstrating how a variable-length genetic algorithm (GA) can obtain a high fitness solution in fewer iterations than a traditional fixed-length GA in a two-dimensional vector approximation task.