Experiments and simulations of short-pulse laser-pumped extreme ultraviolet lasers

Recent experimental work on the development of extreme ultraviolet lasers undertaken using as the pumping source the VULCAN laser at the Rutherford Appleton Laboratory is compared to detailed simulations. It is shown that short duration (/spl sim/picosecond) pumping can produce X-ray laser pulses of a few picosecond duration and that measurement of the emission from the plasma can give an estimate of the duration of the gain coefficient. The Ehybrid fluid and atomic physics code developed at the University of York is used to simulate X-ray laser gain and plasma emission. Two postprocessors to the Ehybrid code are utilized: 1) to raytrace the X-ray laser beam amplification and refraction and 2) to calculate the radiation emission in the kiloelectronvolt photon energy range. The raytracing and spectral simulations are compared, respectively, to measured X-ray laser output and the output of two diagnostics recording transverse X-ray emission. The pumping laser energy absorbed in the plasma is examined by comparing the simulations to experimental results. It is shown that at high pumping irradiance (>10/sup 15/ Wcm/sup -2/), fast electrons are produced by parametric processes in the preformed long scalelength plasmas. These fast electrons do not pump the population inversion and so pumping efficiency is reduced at high irradiance.     

高压自能式灭弧室和操动机构的技术进步(二)

高压SF_6断路器经多次改进在欧洲和日本已发展成第三代产品,第一代为热膨胀式断路器加助吹,将液压机构改为弹簧操动机构和变开距混合式灭弧室。第二代产品为改善开断容性电流特性发展“双容积”灭弧室和新型动态压缩灭弧室,以及双向运行触头系统等,更进一步减少分合闸操作功应用旋弧灭弧原理迫使电弧快速旋转冷却使电流零点时熄灭。第三代产品主要介绍加强操动机构的可靠性和稳定性,传输时无功消耗少,减少机构零件数量等。     

Wavelet-based feature extraction and selection for classification of power system disturbances using support vector machines

This paper presents a new approach for the classification of the power system disturbances using support vector machines (SVMs). The proposed approach is carried out at three serial stages. Firstly, the features to be form the SVM classifier are obtained by using the wavelet transform and a few different feature extraction techniques. Secondly, the features exposing the best classification accuracy of these features are selected by a feature selection technique called as sequential forward selection. Thirdly, the best appropriate input vector for SVM classifier is rummaged. The input vector is started with the first best feature and incrementally added the chosen features. After the addition of each feature, the performance of the SVM is evaluated. The kernel and penalty parameters of the SVM are determined by cross-validation. The parameter set that gives the smallest misclassification error is retained. Finally, both the noisy and noiseless signals are applied to the classifier given above stages. Experimental results indicate that the proposed classifier is robust and has more high classification accuracy with regard to the other approaches in the literature for this problem.     

Mannose based polymeric nanoparticles for lectin separation

The aim of this work is to synthesize the original, new polymeric nanoparticles for concanavalin A (Con A) purification. Nanoparticles were synthesized by surfactant free emulsion polymerization. In the polymerization prosedure, 1-O-(2′-hydroxy-3′-acryloyloxypropyl)-2,3:5,6-di-O-isopropylidene-α-D-mannofuranose (Man-OPA) was used as co-monomer and 2-hydroxyethylmethacrylate (HEMA) was used as a monomer. Man-OPA was characterized by Fourier Transform Infrared Spectroscopy (FTIR), nuclear magnetic resonance and elemental analysis techniques. Poly(HEMA-Man-OPA) nanoparticles were characterized by scanning electron microscopy, FTIR and Zeta Sizer. In adsorption?desorption experiments, maximum Con A adsorption capacity of poly(HEMA-Man-OPA) nanoparticles was found 630.6 mg/g nanoparticle (pH 7.5, 1.0 mg/mL). Adsorption?desorption experiments were repeated in four times. According to results, these nanoparticles could be used several times without significant decrease in Con A adsorption capacity.     

Utilization of Electrospun Polystyrene Membranes as a Preliminary Step for Rapid Diagnosis

Recent advances in clinical practice drive deoxyribonucleic acid (DNA) as an important class of biomarker. Monitoring the change in their concentration suggests the initiation and/or progression of various disorders. However, low quantity of DNA biomarkers in body fluids requires a delicate isolation methodology that provides efficient separation and easy handling. This study describes a newer‐generation separation technology relying on electrospun fibers of sub‐micrometer diameter of a commodity polymer for DNA biomarkers in simulative serum. Fibrous polystyrene membranes are prepared by electrospinning and they are subjected to post‐modification with Au. The composite membranes may provide a convenient environment for the removal of bovine serum albumin (BSA) from BSA and DNA mixtures. The eluent can be used as an efficient tool for detection of DNA biomarkers associated with diagnosis of numerous life‐threatening diseases.

     

An adaptive signal compression system with pre-specified reconstruction quality and compression rate

Two essential properties of a signal compression method are the compression rate and the distance between the original signal and the reconstruction from the compressed signal. These two properties are used to assess the performance and quality of the method. In a recent work [B. Tümer, B. Demir?z, Lecture Notes in Computer Science-Computer and Information Sciences, volume 2869, chapter Signal Compression Using Growing Cell Structures: A Transformational Approach, Springer Verlag, 2003, pp. 952-959], an adaptive signal compression system (ACS) is presented which defines the performance of the system as a function of the system complexity, system sensitivity and data size. For a compression method, it is desirable to formulate the performance of the system as a function of the system complexity and sensitivity to optimize the performance of the system. It would be further desirable to express the reconstruction quality in terms of the same system parameters so as to know up front what compression rate to end up with for a specific reconstruction quality. In this work, we modify ACS such that the modified ACS (MACS) estimates the reconstruction quality for a given system complexity and sensitivity. Once this relation is identified it is possible to optimize either compression rate or reconstruction quality with respect to system sensitivity and system complexity while limiting the other one.     

GPU-accelerated registration of hyperspectral images using KAZE features

The Journal of Supercomputing - Image registration is a common task in remote sensing, consisting in aligning different images of the same scene. In the particular case of hyperspectral images, the...     

Evaluating sociotechnical dynamics in a simulated remotely-piloted aircraft system: a layered dynamics approach

As coordination mechanisms change and technology failures occur, a sociotechnical system must reorganise itself across human and technological layers to maintain effectiveness. We present a study examining reorganisation across communication, controls and vehicle layers of a remotely-piloted aircraft system (RPAS) using a layered dynamics approach. Team members (pilot; navigator; photographer) performed 5 simulated RPAS missions using different operator configurations, including all-human and human-autonomy teams. Reorganization (operationally defined using entropy) time series measured the changing system reorganisation profiles under different operator configurations and following autonomy failures. Correlations between these reorganisation profiles and team effectiveness scores describe the manner in which the system had to be coordinated to maintain effectiveness under these changing conditions. Four unplanned autonomy failures were analysed to visualise system reorganisation following a technology failure. With its objective and real-time modelling and measurement capabilities, layered dynamics complements existing systems thinking tools for understanding sociotechnical complexity and enhancing system effectiveness.

Practitioner summary: A layered dynamics approach for understanding how a sociotechnical system dynamically reorganises itself is presented. The layered dynamics of RPAS were analysed under different operator configurations and following autonomy failures. Layered dynamics complements existing system-thinking tools for modelling sociotechnical system complexity and effectiveness.

Abbreviation: RPAS: remotely-piloted aircraft system; HIS: human-systems integration; EAST: event analysis of systemic teamwork; H1: hypothesis 1; H2: hypothesis 2; H3: hypothesis 3; CERTT-STE: cognitive engineering research on team tasks--synthetic task environment; AVO: air vehicle operator; PLO: payload operator; DEMPC: data exploitation, mission planning, and communications; ACT-R: adaptive control of thought-rational; sec: seconds; ANOVA: analysis of variance     

Multiobjective evolutionary clustering of Web user sessions: a case study in Web page recommendation

In this study, we experiment with several multiobjective evolutionary algorithms to determine a suitable approach for clustering Web user sessions, which consist of sequences of Web pages visited by the users. Our experimental results show that the multiobjective evolutionary algorithm-based approaches are successful for sequence clustering. We look at a commonly used cluster validity index to verify our findings. The results for this index indicate that the clustering solutions are of high quality. As a case study, the obtained clusters are then used in a Web recommender system for representing usage patterns. As a result of the experiments, we see that these approaches can successfully be applied for generating clustering solutions that lead to a high recommendation accuracy in the recommender model we used in this paper.     

Profiling hospitals based on emergency readmission: a multilevel transition modelling approach

Emergency readmission is seen as an important part of the United Kingdom government policy to improve the quality of care that patients receive. In this context, patients and the public have the right to know how well different health organizations are performing. Most methods for profiling estimate the expected numbers of adverse outcomes (e.g. readmission, mortality) for each organization. A number of statistical concerns have been raised, such as the differences in hospital sizes and the unavailability of relevant data for risk adjustment. Having recognized these statistical concerns, a new framework known as the multilevel transition model is developed. Hospital specific propensities of the first, second and further readmissions are considered to be measures of performance, where these measures are used to define a new performance index. During the period 1997 and 2004, the national (English) hospital episodes statistics dataset comprise more than 5 million patient readmissions. Implementing a multilevel model using the complete population dataset could possibly take weeks to estimate the parameters. To resolve the problem, we extract 1000 random samples from the original data, where each random sample is likely to lead to differing hospital performance measures. For computational efficiency a Grid implementation of the model is developed. Analysing the output from the full 1000 sample, we noticed that 4 out of the 5 worst performing hospitals treating cancer patients were in London. These hospitals are known to be the leading NHS Trusts in England, providing diverse range of services to complex patients, and therefore it is inevitable to expect higher numbers of emergency readmissions.