Role of the hemobiologist in the detection and prevention of post-transfusional hepatitis

To prevent post-transfusional hepatitis B and C, two epidemiologic studies were performed. The first, based on the frequencies distribution of hepatitis B virus serological markers versus sex and classes of age, has permitted the assessment of the profile of the infection in a population composed of 573 north vietnamese blood donors. There is no significant difference between men and women frequencies of HBs antigen (11.5%), anti-HBs antibody (70.2%) and anti-HBc antibody alone (3.8%), but a significant difference of no-marker frequencies: 7.8% and 17.9% in men and women respectively (X2 = 9.11; p = 0.010). The percentage of no-marker decreases when the mean age of each class increases. The second, using the increase of the serum alanine aminotransferase (ALAT) activity as an indirect marker of non-A, non-B hepatitis for determining in a population of more than 25,000 parisian blood donors, the percentage of donors eliminated. They are between 0.70 and 0.76 in women and 2.26 and 2.46 in men. These investigations can be applied to prevent the hepatitis B transmission in a population of 102 south vietnamese women in age to procreate or to determine the percentage of blood donors eliminated (3.12%) in a population of 2,950 Parisians composed in majority (50.9%) of new donors. The hemobiologist will have an important role to elaborate strategies for orientation of blood gifts with hepatitis B and C virus markers.     

Satellite SAR Remote Sensing of Great Lakes Ice Cover,Part 2. Ice Classification and Mapping

During the 1997 winter season, shipborne polarimetric backscatter measurements of Great Lakes (freshwater) ice types using the Jet Propulsion Laboratory C-band scatterometer, together with surface-based ice physical characterization measurements and environmental parameters, were acquired concurrently with Earth Resource Satellite 2 (ERS-2) and RADARSAT Synthetic Aperture Radar (SAR) data. This polarimetric data set, composed of over 20 variations of different ice types measured at incident angles from 0° to 60° for all polarizations, was processed to radar cross-section to establish a library of signatures (look-up table) for different ice types. The library is used in the computer classification of calibrated satellite SAR data. Computer analysis of ERS-2 and RADARSAT ScanSAR images of Great Lakes ice cover using a supervised classification technique indicates that different ice types in the ice cover can be identified and mapped, and that wind speed and direction can have an influence on the classification of water as ice based on single frequency, single polarization data. Once satellite SAR data are classified into ice types, the ice map provides important and necessary input for environmental protection and management, ice control and ice breaking operations, and ice forecasting and modeling efforts.     

Bandwidth and region division for broadband multi-cell networks

A cell planning technique termed BRD (bandwidth and region division) is presented for overcoming interference, maintaining QoS (quality of service) and improving channel capacity over OFDM (orthogonal frequency division multiplexing)-based broadband cellular networks. Through an optimal combination of sectorization and zero padding, bandwidth and region division is achieved that minimizes the outage probability for forward-link cell planning. In order to verify the effectiveness of the proposed algorithm, a Monte Carlo simulation is performed over multi-cell environments.     

Generation of adaptive gait patterns for quadruped robot with CPG network including motor dynamic model

This paper describes the generation of adaptive gait patterns using new Central Pattern Generators (CPGs) including motor dynamic models for a quadruped robot under various environments. The CPGs act as the flexible oscillators of the joints and adjust joint angles to required values. The CPGs are interconnected with each other and sets of their coupling parameters are adjusted by a genetic algorithm so that the quadruped robot can realize stable and adequate gait patterns. Generation of gait patterns results in the formation of the CPG networks suitable for the formation of not only a straight walking pattern but also of rotating gait patterns. Experimental results demonstrate that the proposed CPG networks are effective for the automatic adjustment of the adaptive gait patterns for the tested quadruped robot under various environments. Furthermore, the target tracking control based on image processing is achieved by combining the general gait patterns. © 2006 Wiley Periodicals, Inc. Electr Eng Jpn, 155(1): 35–43, 2006; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20225     

A study of solid circulation rate in a circulating fluidized bed

An experimental investigation under cold condition was made to study the effects of some operating/design parameters and non-mechanical L valve configuration on the solid circulation rate in a 4.5 m tall, 0.15 m diameter circulating fluidized bed with riser flow rate varying from 1400 litres/min to 2000 litres/min and bed inventory from 15 kg to 25 kg of sand of average sizes 200 μm, 400 μm and 500 μm. Solid circulation rate was estimated by measuring velocity of sand particle travelling through a vertical Perspex tube section at the bottom of the return leg. It was found to be in the range of 2.8 to 12.3kg/m²s, 0.07 to 9.1kg/m²s and 0.12 to 2.23kg/m²s for sand sizes of 200 μm, 400 μm and 500 μm, respectively for a horizontal L valve. Two mathematical correlations have been developed from the experimental results to predict solid circulation rate as a function of riser flow rate, aeration flow rate, total bed inventory and particle size used.     

Integrating security and real-time requirements using covertchannel capacity

Database systems for real-time applications must satisfy timing constraints associated with transactions in addition to maintaining data consistency. In addition to real-time requirements, security is usually required in many applications. Multi-level security requirements introduce a new dimension to transaction processing in real-time database systems. In this paper, we argue that, due to the conflicting goals of each requirement, tradeoffs need to be made between security and timeliness. We first define mutual information, a measure of the degree to which security is being satisfied by a system. A secure two-phase locking protocol is then described and a scheme is proposed to allow partial violations of security for improved timeliness. Analytical expressions for the mutual information of the resultant covert channel are derived, and a feedback control scheme is proposed that does not allow the mutual information to exceed a specified upper bound. Results showing the efficacy of the scheme obtained through simulation experiments are also discussed     

Efficient screen-space approach to high-quality multiscale ambient occlusion

We present a new screen-space ambient occlusion (SSAO) algorithm that improves on the state-of-the-art SSAO methods in both performance and quality. Our method computes ambient occlusion (AO) values at multiple image resolutions and combines them to obtain the final, high-resolution AO value for each image pixel. It produces high-quality AO that includes both high-frequency shadows due to nearby, occluding geometry and low-frequency shadows due to distant geometry. Our approach only needs to use very small sampling kernels at every resolution, thereby achieving high performance without resorting to random sampling. As a consequence, our results do not suffer from noise and excessive blur, which are common of other SSAO methods. Therefore, our method also avoids the expensive, final blur pass commonly used in other SSAO methods. The use of multiple resolutions also helps reduce errors that are caused by SSAO’s inherent lack of visibility checking. Temporal incoherence caused by using coarse resolutions is solved with an optional temporal filtering pass. Our method produces results that are closer to ray-traced solutions than those of any existing SSAO methods, while running at similar or higher frame rates than the fastest ones.     

Forecasting trends of high-frequency KOSPI200 index data using learning classifiers

Recently many statistical learning techniques have been applied to the prediction of financial variables. The aim of this paper is to conduct a comprehensive study of the applications of statistical learning techniques to predict the trend of the return of high-frequency Korea composite stock price index (KOSPI) 200 index data using the information from the one-minute time series of spot index, futures index, and foreign exchange rate. Through experiments, it is observed that the spot index change is better predictable with high-frequency time series data and the futures index information significantly improves the prediction accuracy of the return trends of the spot index for high-frequency index data, while the information of exchange rate does not. Also, dimension reduction process before training helps to increase the accuracy and dramatically for some classifiers. In addition, the trained classifiers with which a virtual trading strategy is applied to, noticeable better profits can be achieved than just a buy-and-hold-like strategy.