Particle tracking techniques for electrokinetic microchannel flows

We have applied particle tracking techniques to obtain spatially resolved velocity measurements in electrokinetic flow devices. Both micrometer-resolution particle image velocimetry (micro-PMV) and particle tracking velocimetry (PTV) techniques have been used to quantify and study flow phenomena in electrokinetic systems applicable to microfluidic bioanalytical devices. To make the flow measurements quantitative, we performed a series of seed particle calibration experiments. First, we measure the electroosmotic wall mobility of a borosilicate rectangular capillary (40 by 400 microm) using current monitoring. In addition to this wall mobility characterization, we apply PTV to determine the electrophoretic mobilities of more than 1,000 fluorescent microsphere particles in aqueous buffer solutions. Particles from this calibrated particle/ buffer mixture are then introduced into two electrokinetic flow systems for particle tracking flow experiments. In these experiments, we use micro-PIV, together with an electric field prediction, to obtain electroosmotic flow bulk fluid velocity measurements. The first example flow system is a microchannel intersection where we demonstrate a detailed documentation of the similitude between the electrical fields and the velocity fields in an electrokinetic system with uniform zeta potential, zeta. In the second system, we apply micro-PIV to a microchannel system with nonuniform zeta. The latter experiment provides a simultaneous measurement of two distinct wall mobilities within the microchannel.     

A middleware‐transparent approach to developing distributed applications

An innovative middleware‐transparent approach to developing distributed applications is presented. The approach uses an aspect‐oriented software development technique to separate an application's middleware‐independent functionality from its middleware‐specific functionality. Application elements that are specific to the middleware are localized in aspects that can be seamlessly integrated into middleware‐independent application designs. The middleware‐transparent approach is used to decouple business functionality from middleware‐specific functionality. The decoupling allows developers to change middleware application elements without significantly modifying business functionality. Middleware technologies such as Java Remote Method Invocation (RMI), Jini, Simple Object Access Protocol (SOAP) remote procedure call (RPC) and .Net are used as examples to illustrate the approach. Copyright © 2005 John Wiley & Sons, Ltd.     

Modeling resonance tests for electrostrictive ceramics

The electromechanical coupling coefficient represents a useful figure-of-merit for comparing the quality of different electroactive materials. However, the coupling coefficient for an electrostrictive ceramic is not a unique material parameter, because it depends strongly on the applied DC bias field, AC field amplitude and frequency, and stress. These dependencies make direct comparison between electrostrictors and piezoelectrics somewhat ambiguous. In this paper, we developed a pair of coupling parameters for electrostrictors that were strictly material constants and completely characterized the material's electromechanical quality. We proposed relatively simple, inexpensive resonance testing to measure these new parameters from the electrical admittance of a vibrating electrostrictive rod. The electromechanical coupling coefficient for a specific loading condition is computed from these parameters, allowing direct comparison between electrostrictive and piezoelectric materials.     

Noninvasive measurement of compliance of human leg arteries

Electrical impedance plethysmography has been evaluated for early detection of peripheral atherosclerosis. A pressure cuff was wrapped around the lower leg and the cuff pressure increased. Two circumferential electrodes glued in the middle of the cuff recorded the impedance pulse, from which the arterial pulse volume was calculated. The ratio of maximal arterial volume change to the pulse pressure was determined as a measure of maximal compliance Cp. Based on the data from 118 human subjects, Cp was found to correlate well with known cardiovascular risk factors. For example, Cp decreased on the average from 3.08 to 1.92 microL.mm Hg-1.cm-1 (1 microL.mm Hg-1.cm-1 = 7.5 x 10(-10) m4.N-1) in groups of subjects of increasing age from 22 to 70 years. Subjects on a regular exercise program had an average value of 3.86, while those with proven peripheral vascular disease had a value of 0.70. In a related pathologic validation study on 15 monkeys fed a cholesterol-control diet a good correlation was found between the limb peak compliance and morphometric data obtained from iliac and carotid arteries.     

Selective flocculation of iron oxide-kaolin mixtures using a modified polyacrylamide flocculant

High molecular weight polyacrylamides were synthesized and successfully modified to contain up to 8·3% hydroxamate functional groups. The selective flocculation tests carried out on 1:1 iron oxide/kaolin mixtures using parent polyacrylamide, polyacrylic acid and the modified polyacrylamide, confirm the possibility of enhancing selectivity through introduction of iron chelating functional groups in commercially available polymers. Starting with a feed grade of 35% iron, 92% recovery with acceptable grade of 60% iron has been achieved using the modified polyacrylamide. NCL communication No. 4415     

Pulse oximetry theory and calibration for low saturations

Pulse oximetry is a widely used technique in biomedical optics, but currently available pulse oximeters rely on empirical calibration approaches, which perform poorly at low saturations. We present an exact solution for pulse oximetry and show how this can be used as the basis for the development of a semiempirical calibration approach that may be useful, especially at low saturations and variable probe geometries. This new approach was experimentally tested against traditional empirical calibration techniques on transmission pulse oximetry for monitoring of fetal sheep using a minimally invasive spiral probe. The results open the way for the development of more accurate pulse oximetry.     

Variability of mesopause temperature derived from two independent methods using meteor radar and its comparison with SABER and EOS MLS and a collocated multi-wavelength dayglow photometer over an equatorial station,Thumba (8.5° N, 76.5° E)

Two independent methods for deriving mesopause temperature using meteor radar installed at an equatorial station, Thumba (8.5° N, 76.5° E), are discussed in this article. This meteor radar-derived mesopause temperature is then compared with two different types of spaceborne measurement, namely (i) Sounding the Atmosphere using Broadband Emission Radiometry (SABER) and (ii) the Earth Observing System Microwave Limb Sounder (EOS MLS), and a collocated multi-wavelength dayglow photometer (DGPM). The meteor radar-derived temperature is in fairly good agreement with all the three measurement techniques, with an uncertainty of ±10°. This study focuses on a detailed evaluation and inter-comparison of mesopause temperature derived from different measurement techniques. An attempt is also made to compare the suitability of these observations to study planetary waves and other oscillation activities in the mesospheric region.     

A quantitative analysis of the effectiveness of laparascopy and endoscopy virtual reality simulators

The increasing use of virtual reality (VR) simulators in surgical training makes it imperative that definitive studies be performed to assess their training effectiveness. Indeed in this paper we report the meta-analysis of the efficacy of virtual reality simulators in (1) the transference of skills from the simulator training environment to the operating room and (2) their ability to discriminate between the experience levels of its users. The task completion time and the error score were the two study outcomes collated and analyzed in this meta-analysis. Sixteen studies were identified from a computer-based literature search (1996-2004). The meta-analysis of the random-effects model (because of the heterogeneity of the data) revealed that training on virtual reality simulators did lessen the time taken to complete a given surgical task as also clearly differentiate between the experienced and the novice trainees. Meta-analytic studies such as the one reported here would be very helpful in the planning and setting up of surgical training programs and for the establishment of reference ‘learning curves’ for a specific simulator and surgical task. If any such programs already exist they can then indicate the improvements to be made in the simulator used such as providing for more variety in their case scenarios based on the state and/or rate of learning of the trainee.     

Bi-directional LSTM based channel estimation in 5G massive MIMO OFDM systems over TDL-C model with Rayleigh fading distribution

In this work, a deep learning (DL)-based massive multiple-input multiple-output (mMIMO) orthogonal frequency division multiplexing (OFDM) system is investigated over the tapped delay line type C (TDL-C) model with a Rayleigh fading distribution at frequencies ranging from 0.5 to 100 GHz. The proposed bi-directional long short-term memory (Bi-LSTM) channel state information (CSI) estimator uses online learning during training and offline learning during the practical implementation phase. The design of the estimator takes into account situations in which prior knowledge of channel statistics is limited and targets excellent performance, even with limited pilot symbols (PS). Three separate loss functions (mean square logarithmic error [MSLE], Huber, and Kullback–Leibler Distance [KLD]) are assessed in three classification layers. The symbol error rate (SER) and outage probability performance of the proposed estimator are evaluated using a number of optimization techniques, such as stochastic gradient descent (SGD), momentum, and the adaptive gradient (AdaGrad) algorithm. The Bi-LSTM-based CSI estimator is trained considering a specific number of PS. It can be readily seen that by incorporating a cyclic prefix (CP), the system becomes more resilient to channel impairments, resulting in a lower SER. Simulations show that the SGD optimization approach and Huber loss function-trained Bi-LSTM-based CSI estimator have the lowest SER and very high estimation accuracy. By using deep neural networks (DNNs), the Bi-LSTM method for CSI estimation achieves a superior channel capacity (in bps/Hz) at 10 dB than long short-term memory (LSTM) and other conventional CSI estimators, such as minimum mean square error (MMSE) and least squares (LS). The simulation results validate the analytical results in the study.