Prasun Mahanti

Dielectrophoretic mobility determination in DC insulator-based dielectrophoresis

Insulator‐based dielectrophoresis (iDEP) is a powerful tool for separating and characterizing particles, yet it is limited by a lack of quantitative characterizations. Here, this limitation is addressed by employing a method capable of quantifying the DEP mobility of particles. Using streak‐based velocimetry the particle properties are deduced from their motion in a microfluidic channel with a constant electric field gradient. From this approach, the DEP mobility of 1 μm polystyrene particles was found to be −2±0.4 10−8 cm4/(V2 s). In the future, such quantitative treatment will allow for the elucidation of unique insights and rational design of devices.

Efficient Deterministic Compressed Sensing for Images with Chirps and Reed-Muller Codes

A recent approach to compressed sensing using deterministic sensing matrices formed from discrete frequency-modulated chirps or from Reed-Muller codes is extended to support efficient deterministic reconstruction of signals that are much less sparse than envisioned in the original work. In particular, this allows the application of this approach in imaging. The reconstruction algorithm developed for images incorporates several new elements to improve computational complexity and reconstruction fidelity in this application regime.

Quantitative assessment of flow and electric fields for electrophoretic focusing at a converging channel entrance with interfacial electrode

The electric field and flow field gradients near an electrified converging channel are amenable to separating and focusing specific classes of electrokinetic material, but the detailed local electric field and flow dynamics in this region have not been thoroughly investigated. Finite elemental analysis was used to develop a model of a buffer reservoir connected to a smaller channel to simulate the electrophoretic and flow velocities (which correspond directly to the respective electric and flow fields) at a converging entrance. A detailed PTV (Particle Tracking Velocimetry) study using charged fluorescent microspheres was performed to assess the model validity both in the absence and presence of an applied electric field. The predicted flow velocity gradient from the model agreed with the PTV data when no electric field was present. Once the additional forces that act on the large particles required for tracing (dielectrophoresis) were included, the model accurately described the velocity of the charged particles in electric fields.

Improved signal extraction from fluorescence immunoassay image sequences

A recently developed dynamic fluorescence immunoassay for the biomarker Myoglobin promises to provide detection of myocardial infarction within minutes. Signal extraction for this method is based on epifluorescence video microscopy, but is confounded by inhomogeneous spatial gain, intensity inhomogeneity or IIH. We present here a novel adaptive correction method which estimates the IIH from a video image sequence. This estimated IIH may be used to correct the image signal extraction process. The enhancement to detection limits and consistency of estimated concentrations are quantified, based on an improvement to SNR of approximately 9 dB.

In-orbit multi-spectral image sharpness assessment for the Lunar Reconnaissance Orbiter Wide Angle Camera

The Lunar Reconnaissance Orbiter Camera (LROC) Wide Angle Camera (WAC) began systematic lunar imaging in January of 2010. WAC image maps and derived data products are allowing scientists to improve our knowledge of the Moon with science and engineering applications for future mission planning. The sharpness of the WAC images is an important measure of the camera performance over the duration of the mission time. Accordingly, a measure of the in orbit sharpness was achieved by computing the modulation transfer function (MTF) of the WAC multi-spectral optics from in-orbit lunar limb images. Historically, lunar limb images were used for MTF evaluation for imaging devices on Earth based satellites (e.g. NASA Earth Observer) as a supplement to other imaging targets, but were never used successfully for MTF computation for a lunar orbiter prior to this work (to the best of our knowledge). The proposed method is similar to the ISO 12233:2000 standard slanted edge gradient based method, but uses edge-fitting to obtain high resolution edge spread functions with the lunar limb (that is not perfectly straight). Adaptive noise suppressed derivative computation and the Monte Carlo method for obtaining robust statistics, two other enhancements to standard MTF techniques, are also used in this work. Both cross-track and down-track MTFs were obtained and the results show that the LROC WAC meets and exceeds the MTF requirement of greater than 0.2 at the Nyquist frequency.

Enhancement of spatial resolution of the LROC wide angle camera images

Image fusion, a popular method for resolution enhancement in Earth-based remote sensing studies involves the integration of geometric (sharpness) detail of a high-resolution panchromatic (Pan) image and the spectral information of a lower resolution multi-spectral (MS) image. Image fusion with planetary images is not as widespread as with terrestrial studies, although successful application of image fusion can lead to the generation of higher resolution MS image data. A comprehensive comparison of six image fusion algorithms in the context of lunar images is presented in this work. Performance of these algorithms is compared by visual inspection of the high-resolution multi-spectral products, derived products such as band-to-band ratio and composite images, and performance metrics with an emphasis on spectral content preservation. Enhanced MS images of the lunar surface can enable new science and maximize the science return for current and future missions.

Visualization of probabilistic relationships in shape-maturity data for lunar craters

Probabilistic modeling and visualization of crater shape-maturity relationships is explored in context of remote sensing data acquired by Apollo, Clementine and Lunar Reconnaissance Orbiter spacecraft. Unlike any earlier attempt of understanding relationships between lunar crater features (depth and diameter), relative age of crater formation (Pre-Nectarian to Copernican) and optical maturity of the lunar surface (OMAT values), the joint probability of these variables is modeled. The proposed model is strongly dependent on data density and is not based on deterministic equations as in earlier works. Once developed, a joint probability model can accommodate additional factors through conditional probability weights in a Bayesian network architecture. It is expected that probabilistic modeling will facilitate visualization of relationships between experimental variables and eventually help gain additional insight into lunar cratering mechanisms and linkages between crater morphology, spectral properties and crater degradation mechanisms. The described simple Bayesian network in this work is by no means complete, but illustrates the potential of the proposed novel method with the advent of high resolution images and topographic measurements for the Moon.

Simulation and visualization of velocity fields in simple electrokinetic devices

Capillary electrophoresis and similar techniques which use an electrified contracting-flow interface (gradient elution moving boundary electrophoresis, electrophoretic exclusion, for examples) are widely used, but the detailed flow dynamics and local electric field effects within this zone have only recently been quantitatively investigated. The motivating force behind this work is establishing particle flow based visualization tools enabling advances for arbitrary interfacial designs beyond this traditional flow/electric field interface. These tools work with pre-computed 2-dimensional fundamental interacting fields which govern particle and(or) fluid flow and can now be obtained from various computational fluid dynamics (CFD) software packages. The particle-flow visualization calculations implemented in the tool and are built upon a solid foundation in fluid dynamics. The module developed in here provides a simulated video particle observation tool which generates a fast check for legitimacy. Further, estimating the accuracy and precision of full 2-D and 3-D simulation is notoriously difficult and a centerline estimation is used to quickly and easily quantitate behaviors in support of decision points. This tool and the recent quantitative assessment of particle behavior within the interfacial area have set the stage for new designs which can emphasize advantageous behaviors not offered by the traditional configuration.

Spatio-temporal image analysis of particle streaks in micro-channels for low-cost electro-hydrodynamic flow characterization

Flow characterization is a primary analytical method for performance evaluation of microfluidic devices. With the increasing prevalence of microfluidic devices in recent years, there is a growing need for simple methods of automated flow estimation. In this work, a novel flow diagnostic technique based on image analysis of particle streaks is introduced, to characterize local flow velocities. While 1D velocimetry using particle tracks has occasionally been discussed for macro-scale environments, the use of particle streaks for 2-D flow characterization in micro-channels has not been explored. The proposed technique is qualitatively validated against electroki-netic experiment and numerically validated with simulated flows.

Using reed-muller sequences as deterministic compressed sensing matrices for image reconstruction

An image reconstruction algorithm using compressed sensing (CS) with deterministic matrices of second-order Reed-Muller (RM) sequences is introduced. The 1D algorithm of Howard et al. using CS with RM sequences suffers significant loss in speed and accuracy when the degree of sparsity is not high, making it inviable for 2D signals. This paper describes an efficient 2D CS algorithm using RM sequences, provides medical image reconstruction examples, and compares it with the original 2DCS using noiselets. This algorithm entails several innovations that enhance its suitability for images: initial best approximation, a greedy algorithm for the nonzero locations, and a new approach in the least-squares step. These enhancements improve fidelity, execution time, and stability in the context of image reconstruction.