Style, experimentation and Jingju (Beijing Opera) as a decentered multiplicity

Jingju (Beijing Opera) is widely considered to be a fundamentally non-naturalistic practice that became known in the West after it caught the attention of western practitioners in 1935 following Mei Lanfang’s performance in Moscow. Given the implication that its importance is largely historical, some non-specialists have implied that Jingju has little relevance to contemporary modes of thinking, particularly the multiplicities of experience as outlined by philosophers such as Deleuze and Guattari. This article seeks to demonstrate the multiplicity of Jingju for a wider readership through both a historical analysis and a deconstruction of the form. It will show how, at the same time that Mei Lanfang was providing a ‘non-realistic’ model for western practitioners eager to displace the dominance of naturalism, realistic settings were becoming an integral part of Jingju performances in Shanghai. The article also engages with the various acting pai/styles that weave Jingju into a complex, multiple form. The article demonstrates how Deleuzian models actually facilitate a greater understanding of Jingju.

Temperature-tuned vector phase conjugation in azobenzene dye impregnated polymer films

Near-perfect vector phase conjugation was achieved at 488 nm in a methyl red dye impregnated polymethylmethacrylate film by employing a temperature tuning technique. Using a degenerate four-wave mixing geometry with vertically polarized counterpropagating pump beams, intensity and polarization gratings were written in the dye/polymer system using a vertically or horizontally polarized weak probe beam. Over a limited temperature range, as the sample was heated, the probe reflectivity from the polarization grating dropped but the reflectivity from the intensity grating rose sharply. At a sample temperature of approximately 50°C, the reflectivities of the gratings were measured to be equal and we confirmed that, at this temperature, the measured vector phase conjugate fidelity was very close to unity. We discuss a possible explanation of this effect.

Secondary structure prediction with support vector machines

Motivation: A new method that uses support vector machines (SVMs) to predict protein secondary structure is described and evaluated. The study is designed to develop a reliable prediction method using an alternative technique and to investigate the applicability of SVMs to this type of bioinformatics problem. Methods: Binary SVMs are trained to discriminate between two structural classes. The binary classifiers are combined in several ways to predict multi-class secondary structure. Results: The average three-state prediction accuracy per protein (Q3) is estimated by cross-validation to be 77.07 ± 0.26% with a segment overlap (Sov) score of 73.32 ± 0.39%. The SVM performs similarly to the 'state-of-the-art' PSIPRED prediction method on a non-homologous test set of 121 proteins despite being trained on substantially fewer examples. A simple consensus of the SVM, PSIPRED and PROFsec achieves significantly higher prediction accuracy than the individual methods. Availability: The SVM classifier is available from the authors. Work is in progress to make the method available on-line and to integrate the SVM predictions into the PSIPRED server.

Parkinson’s Disease tremor classification – a comparison between Support Vector Machines and neural networks

Deep Brain Stimulation has been used in the study of and for treating Parkinson’s Disease (PD) tremor symptoms since the 1980s. In the research reported here we have carried out a comparative analysis to classify tremor onset based on intraoperative microelectrode recordings of a PD patient’s brain Local Field Potential (LFP) signals. In particular, we compared the performance of a Support Vector Machine (SVM) with two well known artificial neural network classifiers, namely a Multiple Layer Perceptron (MLP) and a Radial Basis Function Network (RBN). The results show that in this study, using specifically PD data, the SVM provided an overall better classification rate achieving an accuracy of 81% recognition.

Nonlinear set-membership estimation: a support vector machine approach

In this paper a support vector machine (SVM) approach for characterizing the feasible parameter set (FPS) in non-linear set-membership estimation problems is presented. It iteratively solves a regression problem from which an approximation of the boundary of the FPS can be determined. To guarantee convergence to the boundary the procedure includes a no-derivative line search and for an appropriate coverage of points on the FPS boundary it is suggested to start with a sequential box pavement procedure. The SVM approach is illustrated on a simple sine and exponential model with two parameters and an agro-forestry simulation model.

Forecasting with vector autoregressive models of data vintages: US output growth and inflation

Vintage-based vector autoregressive models of a single macroeconomic variable are shown to be a useful vehicle for obtaining forecasts of different maturities of future and past observations, including estimates of post-revision values. The forecasting performance of models which include information on annual revisions is superior to that of models which only include the first two data releases. However, the empirical results indicate that a model which reflects the seasonal nature of data releases more closely does not offer much improvement over an unrestricted vintage-based model which includes three rounds of annual revisions.

Evidence that nematodes may vector the soft rot-causing enterobacterial phytopathogens

Bacterial soft rot is a globally significant plant disease that causes major losses in the production of many popular crops, such as potato. Little is known about the dispersal and ecology of soft-rot enterobacteria, and few animals have been identified as vectors for these pathogens. This study investigates whether soil-living and bacterial-feeding nematodes could act as vectors for the dispersal of soft-rot enterobacteria to plants. Soft-rot enterobacteria associated with nematodes were quantified and visualized through bacterial enumeration, GFP-tagging, and confocal and electron scanning microscopy. Soft-rot enterobacteria were able to withstand nematode grazing, colonize the gut of Caenorhabditis elegans and subsequently disperse to plant material while remaining virulent. Two nematode species were also isolated from a rotten potato sample obtained from a potato storage facility in Finland. Furthermore, one of these isolates (Pristionchus sp. FIN-1) was shown to be able to disperse soft-rot enterobacteria to plant material. The interaction of nematodes and soft-rot enterobacteria seems to be more mutualistic rather than pathogenic, but more research is needed to explain how soft-rot enterobacteria remain viable inside nematodes.

The role of the harmonic vector average in motion integration

The local speeds of object contours vary systematically with the cosine of the angle between the normal component of the local velocity and the global object motion direction. An array of Gabor elements whose speed changes with local spatial orientation in accordance with this pattern can appear to move as a single surface. The apparent direction of motion of plaids and Gabor arrays has variously been proposed to result from feature tracking, vector addition and vector averaging in addition to the geometrically correct global velocity as indicated by the intersection of constraints (IOC) solution. Here a new combination rule, the harmonic vector average (HVA), is introduced, as well as a new algorithm for computing the IOC solution. The vector sum can be discounted as an integration strategy as it increases with the number of elements. The vector average over local vectors that vary in direction always provides an underestimate of the true global speed. The HVA, however, provides the correct global speed and direction for an unbiased sample of local velocities with respect to the global motion direction, as is the case for a simple closed contour. The HVA over biased samples provides an aggregate velocity estimate that can still be combined through an IOC computation to give an accurate estimate of the global velocity, which is not true of the vector average. Psychophysical results for type II Gabor arrays show perceived direction and speed falls close to the IOC direction for Gabor arrays having a wide range of orientations but the IOC prediction fails as the mean orientation shifts away from the global motion direction and the orientation range narrows. In this case perceived velocity generally defaults to the HVA.

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.

Spatial expansion and population structure of the neotropical malaria vector, Anopheles darlingi (Diptera: Culicidae)

Extensive population structuring is known to occur in Anopheles darlingi, the primary malaria vector of the Neotropics. We analysed the phylogeographic structure of the species using the mitochondrial cytochrome oxidase I marker. Diversity is divided into six main population groups in South America: Colombia, central Amazonia, southern Brazil, south-eastern Brazil, and two groups in north-east Brazil. The ancestral distribution of the taxon is hypothesized to be central Amazonia, and there is evidence of expansion from this region during the late Pleistocene. The expansion was not a homogeneous front, however, with at least four subgroups being formed due to geographic barriers. As the species spread, populations became isolated from each other by the Amazon River and the coastal mountain ranges of south-eastern Brazil and the Andes. Analyses incorporating distances around these barriers suggest that the entire South American range of An. darlingi is at mutation-dispersal-drift equilibrium. Because the species is distributed throughout such a broad area, the limited dispersal across some landscape types promotes differentiation between otherwise proximate populations. Moreover, samples from the An. darlingi holotype location in Rio de Janeiro State are substantially derived from all other populations, implying that there may be additional genetic differences of epidemiological relevance. The results obtained contribute to our understanding of gene flow in this species and allow the formulation of human mosquito health protocols in light of the potential population differences in vector capacity or tolerance to control strategies. (C) 2009 The Linnean Society of London, Biological Journal of the Linnean Society, 2009, 97, 854-866.

Alboserpin, a Factor Xa Inhibitor from the Mosquito Vector of Yellow Fever, Binds Heparin and Membrane Phospholipids and Exhibits Antithrombotic Activity

The molecular mechanism of factor Xa (FXa) inhibition by Alboserpin, the major salivary gland anticoagulant from the mosquito and yellow fever vector Aedes albopictus, has been characterized. cDNA of Alboserpin predicts a 45-kDa protein that belongs to the serpin family of protease inhibitors. Recombinant Alboserpin displays stoichiometric, competitive, reversible and tight binding to FXa (picomolar range). Binding is highly specific and is not detectable for FX, catalytic site-blocked FXa, thrombin, and 12 other enzymes. Alboserpin displays high affinity binding to heparin (K(D) similar to 20 nM), but no change in FXa inhibition was observed in the presence of the cofactor, implying that bridging mechanisms did not take place. Notably, Alboserpin was also found to interact with phosphatidylcholine and phosphatidylethanolamine but not with phosphatidylserine. Further, annexin V (in the absence of Ca(2+)) or heparin outcompetes Alboserpin for binding to phospholipid vesicles, suggesting a common binding site. Consistent with its activity, Alboserpin blocks prothrombinase activity and increases both prothrombin time and activated partial thromboplastin time in vitro or ex vivo. Furthermore, Alboserpin prevents thrombus formation provoked by ferric chloride injury of the carotid artery and increases bleeding in a dose-dependent manner. Alboserpin emerges as an atypical serpin that targets FXa and displays unique phospholipid specificity. It conceivably uses heparin and phosphatidylcholine/phosphatidylethanolamine as anchors to increase protein localization and effective concentration at sites of injury, cell activation, or inflammation.

Development of an adenoviral vector with robust expression driven by p53

Here we introduce a new adenoviral vector where transgene expression is driven by p53. We first developed a synthetic promoter, referred to as PGTx beta containing a p53-responsive element, a minimal promoter and the first intron of the rabbit P-globin gene. Initial assays using plasmid-based vectors indicated that expression was tightly controlled by p53 and was 5-fold stronger than the constitutive CMV immediate early promoter/enhancer. The adenoviral vector, AdPG, was also shown to offer p53-responsive expression in prostate carcinoma cells LNCaP (wt p53), DU-145 (temperature sensitive mutant of p53) and PC3 (p53-null, but engineered to express temperature-sensitive p53 mutants). AdPG served as a sensor of p53 activity in LNCaP cells treated with chemotherapeutic agents. Since p53 can be induced by radiotherapy and chemotherapy, this new vector could be further developed for use in combination with conventional therapies to bring about cooperation between the genetic and pharmacologic treatment modalities. (c) 2007 Elsevier Inc. All rights reserved.