Magnetic multipole line-cusp plasma generator for neutral beam injectors

The magnetic multipole line-cusp device developed by MacKenzie and associates has been adapted for use as a neutral beam ion source. It has produced high-density, large volume, quiescent, uniform hydrogen plasmas, which makes it a potential candidate for use as a plasma generator for neutral beam injectors. The device is a water-cooled cylindrical copper discharge chamber (25 cm in diameter by 36 cm long) with one end enclosed by a set of extraction grids with a 15-cm-diam multi-aperture pattern. The chamber wall serves as an anode and is surrounded by an external system of rare-earth cobalt magnets arranged in a line-cusp geometry of 12 cusps; plasma is produced by electron emission from a hot cathode assembly. This source has achieved extracted beam currents of 12 A at 18.5 kV, radial plasma density uniformities of +/-5% over a 15-cm diameter, noise levels of less than +/-0.5%, and arc efficiencies (beam current/arc power) of 0.6 A/kW.     

Effect of Pseudomonas fluorescens on beef discoloration and oxymyoglobin oxidation in vitro

The relationship between bacterial growth and oxymyoglobin oxidation in vitro and in meat was studied. In the in vitro study, oxymyoglobin was combined with Pseudomonas fluorescens or sterile nutrient broth (control) in an airtight vessel. P. fluorescens samples showed greater metmyoglobin formation and oxygen consumption than controls. The P. fluorescens population in the reaction vessels was correlated with metmyoglobin formation (r = 0.85, P < 0.05) and oxygen consumption (r = 0.91, P < 0.05). When P. fluorescens and oxymyoglobin were combined in an airtight vessel, reducing the headspace from 13 ml and 9 ml to 3 ml resulted in greater metmyoglobin formation (P < 0.05). In the meat study, beef cores prepared from longissimus lumborum were inoculated with P. fluorescens (10(7) CFU/cm2) or sterile peptone water (control), packaged under 1% O2 (+99% N2), air, or 100% O2 and stored at 4 degrees C. Inoculated beef cores showed higher bacterial loads and metmyoglobin formation than their respective controls during 10 h storage in 1% O2, 3 days in air, and 7 days in 100% O2 (P < 0.05). This finding indicated that P. fluorescens could accelerate beef discoloration. Overall, studies demonstrated that oxygen consumption concomitant with P. fluorescens growth decreased partial oxygen pressure, which accelerated oxymyoglobin oxidation.     

Comparative analysis of 8-oxo-2' -deoxyguanosine in DNA by 32P- and 33P-postlabeling and electrochemical detection

8-Oxo-2'-deoxyguanosine (8-oxo-dG) is emerging as a useful marker for oxidative DNA damage. Reported basal levels determined by 32P-postlabeling (PPL) method were 10-fold or more higher than those obtained with HPLC/electrochemical detection (ECD). This discrepancy was investigated. In commercial calf thymus DNA, levels of 4 +/- 1 and 64 +/- 14 8-oxo-dG per 10(6) 2'-deoxynucleosides (dN) were measured by the standard HPLC/ECD and PPL methods, respectively. DNA digestion by micrococcal nuclease/spleen phosphodiesterase and nuclease P1 (as used in the standard PPL method), followed by ECD analysis resulted in a level of 8 +/- 3. In calf thymus DNA spiked with chemically synthesized 8-oxo-dGp to give an increment of 9 8-oxo-dG/10(6) dN, the added standard produced a significant increase with HPLC/ECD but not PPL. After spiking the DNA with 90 8-oxo-dG/10(6) dN, the added 8-oxo-dGp was detectable also with PPL, with a labeling efficiency of 65%. In order to investigate the role of ionizing radiation from 32P for the higher 8-oxo-dG levels in PPL, incubation times and amounts of radioactivity in the phosphorylation reaction with commercial dGp were increased, and external irradiation of commercial dG with 32P was investigated. All modifications resulted in higher values of 8-oxo-dG measured, but the effect was not large enough to fully explain the discrepancy between PPL and HPLC/ECD. Using [gamma-33P]ATP instead of [gamma-32P]ATP or adding [33P]phosphate to a 32P-PPL assay resulted in even higher levels of 8-oxo-dG measured. The increase in 8-oxo-dG levels during the PPL workup is attributed to the presence and oxidation of unmodified dGp in the reaction mixture. For a determination of true basal levels, the PPL method will have to be modified, including the removal of dGp prior to the phosphorylation reaction.     

Soft-Decoding SOM for VQ Over Wireless Channels

A self-organizing map (SOM) approach for vector quantization (VQ) over wireless channels is presented. We introduce a soft decoding SOM-based robust VQ (RVQ) approach with performance comparable to that of the conventional channel optimized VQ (COVQ) approach. In particular, our SOM approach avoids the time-consuming index assignment process in traditional RVQs and does not require a reliable feedback channel for COVQ-like training. Simulation results show that our approach can offer potential performance gain over the conventional COVQ approach. For data sources with Gaussian distribution, the gain of our approach is demonstrated to be in the range of 1–4 dB. For image data, our approach gives a performance comparable to a sufficiently trained COVQ, and is superior with a similar number of training epoches. To further improve the performance, a SOM–based COVQ approach is also discussed.     

Case-based reasoning and adaptation in hydraulic production machine design

Case-based reasoning (CBR) can support hydraulic circuit design. Existing expert systems for hydraulic system design use production rules as its source of knowledge. However, this leads to problems of knowledge acquisition and knowledge base maintenance. This paper describes the application of CBR to hydraulic circuit design for production machines, which helps solving problems using past experience. A technique Case-based adaptation (CBA) is implemented in the adaptation stage of CBR so that adaptation becomes much easier. A prototype system has been developed to verify the usefulness of CBR and CBA in hydraulic production machines.     

Optical temperature sensing based on the Goos-Hänchen effect

The possibility of constructing an optical sensor for temperature monitoring based on the Goos-H?nchen (GH) effect is explored using a theoretical model. This model considers the lateral shift of the incident beam upon reflection from a metal-dielectric interface, with the shift becoming a function of temperature due mainly to the temperature dependence of the optical properties of the metal. It is found that such a sensor can be most effective by using long wavelength p-polarized incident light at almost grazing incidence onto the metal, where significant variation of negative GH shifts can be observed as a function of the temperature.     

Green synthesis of silver nanoparticles using biopolymers,carboxymethylated-curdlan and fucoidan

There is a growing need in developing a reliable and eco-friendly methodology for the synthesis of metallic nanoparticles, which may be applied for many nanotechnological applications. Natural compounds such as biopolymers are one of the resources which could be used for this purpose. The present study involves the development of a simple, ecological and user-friendly method in synthesizing silver nanoparticles by using carboxymethylated-curdlan or fucoidan as reducing and stabilizing agents. Reduction of silver ions by these biopolymers occurred when heating at 100 °C, led to the formation of silver nanoparticles in the range of 40–80 nm in dimensions. The silver nanoparticles were formed readily within 10–15 min. Morphological observation and characterization of the silver nanoparticles were performed by using dynamic light scattering (DLS), high-resolution transmission electron microscopy (HRTEM), and UV–vis absorption spectrophotometer. The size of silver nanoparticles can be controlled by using different concentrations of carboxymethylated-curdlan, fucoidan or silver nitrate. This way of silver nanoparticles preparation is easy, fast, user-friendly and suitable for large-scale production.     

An efficient data mining method for learning Bayesian networks using an evolutionary algorithm-based hybrid approach

Given the explosive growth of data collected from current business environment, data mining can potentially discover new knowledge to improve managerial decision making. This paper proposes a novel data mining approach that employs an evolutionary algorithm to discover knowledge represented in Bayesian networks. The approach is applied successfully to handle the business problem of finding response models from direct marketing data. Learning Bayesian networks from data is a difficult problem. There are two different approaches to the network learning problem. The first one uses dependency analysis, while the second one searches good network structures according to a metric. Unfortunately, both approaches have their own drawbacks. Thus, we propose a novel hybrid algorithm of the two approaches, which consists of two phases, namely, the conditional independence (CI) test and the search phases. In the CI test phase, dependency analysis is conducted to reduce the size of the search space. In the search phase, good Bayesian network models are generated by using an evolutionary algorithm. A new operator is introduced to further enhance the search effectiveness and efficiency. In a number of experiments and comparisons, the hybrid algorithm outperforms MDLEP, our previous algorithm which uses evolutionary programming (EP) for network learning, and other network learning algorithms. We then apply the approach to two data sets of direct marketing and compare the performance of the evolved Bayesian networks obtained by the new algorithm with those by MDLEP, the logistic regression models, the na/spl inodot//spl uml/ve Bayesian classifiers, and the tree-augmented na/spl inodot//spl uml/ve Bayesian network classifiers (TAN). In the comparison, the new algorithm outperforms the others.     

Sparse and Truncated Nuclear Norm Based Tensor Completion

One of the main difficulties in tensor completion is the calculation of the tensor rank. Recently a tensor nuclear norm, which is equal to the weighted sum of matrix nuclear norms of all unfoldings of the tensor, was proposed to address this issue. However, in this approach, all the singular values are minimized simultaneously. Hence the tensor rank may not be well approximated. In addition, many existing algorithms ignore the structural information of the tensor. This paper presents a tensor completion algorithm based on the proposed tensor truncated nuclear norm, which is superior to the traditional tensor nuclear norm. Furthermore, to maintain the structural information, a sparse regularization term, defined in the transform domain, is added into the objective function. Experimental results showed that our proposed algorithm outperforms several state-of-the-art tensor completion schemes.     

Green cell association for multimedia transmission in cognitive heterogeneous networks

With the introduction of low‐powered pico/femto‐base stations and relay nodes into the macro‐cell, recent heterogeneous networks provide an attractive approach for future wireless communication. Although it may achieve better coverage and higher capacity, several problems remain unsolved before practical deployment. For example, how to select the proper cell from neighbor low‐powered cells and then occupy the radio resource without interference on macro‐users is both important and challenging, especially for rigorous multimedia applications. The traditional cell access algorithms and quality‐control parameters such as delay or throughput no longer suit well in this complex environment. An effective approach should be pursued. In this paper, we investigate this interesting cell association problem and propose a complete green resolution on the basis of thorough discussions about the multimedia transmission under these concerns. Cognitive radio is introduced to share spectrum between macro‐cell and low‐powered cells while securing the transmission of authorized macro‐users. We also bring forth the concept of ‘interference balance’ to better manage the overall interference and energy consumption in the network. Restless bandit model is formulated on the basis of channel state, data rate, interference control, and the carefully chosen intra‐refreshing rate for multimedia traffic. Then the cell association scheme is designed to be efficient and practical because of the simple index property of our model output. Simulation results have proven the performance of our proposed resolution compared with existing algorithms on interference constraint, multimedia distortion, and overall network energy consumption balance. Copyright © 2013 John Wiley & Sons, Ltd.