A novel fuzzy clustering algorithm for the analysis of axillary lymph node tissue sections

Recently Fourier Transform Infrared (FTIR) spectroscopic imaging has been used as a tool to detect the changes in cellular composition that may reflect the onset of a disease. This approach has been investigated as a mean of monitoring the change of the biochemical composition of cells and providing a diagnostic tool for various human cancers and other diseases. The discrimination between different types of tissue based upon spectroscopic data is often achieved using various multivariate clustering techniques. However, the number of clusters is a common unknown feature for the clustering methods, such as hierarchical cluster analysis, k-means and fuzzy c-means. In this study, we apply a FCM based clustering algorithm to obtain the best number of clusters as given by the minimum validity index value. This often results in an excessive number of clusters being created due to the complexity of this biochemical system. A novel method to automatically merge clusters was developed to try to address this problem. Three lymph node tissue sections were examined to evaluate our new method. These results showed that this approach can merge the clusters which have similar biochemistry. Consequently, the overall algorithm automatically identifies clusters that accurately match the main tissue types that are independently determined by the clinician.     

Visual insights into high-resolution earthquake Simulations.

This study focuses on the visualization of a series of large earthquake simulations collectively called TeraShake. The simulation series aims to assess the impact of San Andreas Fault earthquake scenarios in Southern California. We discuss the role of visualization in gaining scientific insight and aiding unexpected discoveries.     

Optical Splitting Trees for High-Precision Monocular Imaging

In this article, we consider the design of monocular multiview optical systems that form optical splitting trees, where the optical path topology takes the shape of a tree because of recursive beam splitting. Designing optical splitting trees is challenging when it requires many views with specific spectral properties. We introduce a manual design paradigm for optical splitting trees and a computer-assisted design tool to create efficient splitting-tree cameras. The tool accepts as input a specification for each view and a set of weights describing the user's relative affinity for efficiency, measurement accuracy, and economy. An optimizer then searches for a design that maximizes these weighted priorities. Our tool's output is a splitting-tree design that implements the input specification and an analysis of the efficiency of each root-to-leaf path. Automatically designed trees appear comparable to those designed by hand; we even show some cases where they are superior. With the help of the optimizer, the system demonstrates high dynamic range, focusing, matting, and hybrid imaging implemented on a single, reconfigurable camera containing eight sensors     

A microbubble-powered bioparticle actuator

We present the results of a device that uses controllable microbubble actuation to manipulate bioparticles. In order to create a useful device for controlling the position of bioparticles, predictable microfluidic actuation is crucial. The goal of this project was to develop fundamental technology that can be used to manipulate single bioparticles (e.g., cells). We use a thermal bubble actuation method to accomplish this goal. Microbubbles have the advantages of relatively simple electronics and fabrication but can be difficult to control. In this paper, we describe two specific accomplishments: the use of micromachined nucleation cavities to precisely localize thermal bubbles and to achieve controllable bubble formation temperatures and bubble dissipation and the demonstration of controllable microbubbles in a new device for particle sorting.     

Kinetics of chlorination of tantalum pentoxide in mixture with sucrose carbon by chlorine gas

The mechanism and kinetics of β-Ta₂O₅ chlorination, mixed with sucrose carbon, have been studied by a thermogravimetric technique. The investigated temperature range was 500 °C to 850 °C. The reactants and reaction residues were analyzed by scanning electronic microscopy (SEM), X-ray diffraction (XRD), and Brunauer-Emmett-Teller method for surface area (BET). The effect of various experimental parameters was studied, such as carbon percentage, temperature, chlorine partial pressure, and flow, use of the multiple sample method, and carbon previous oxidation. The carbon percentage and previous treatment have an effect on the system reactivity. The temperature has a marked effect on the reaction rate. In the 500 °C to 600 °C temperature interval, the apparent activation energy is 144 kJ/mol of oxide, while at higher temperatures, the activation energy decreases. With high chorine partial pressures, the order of reaction is near zero. The kinetic contractile plate model, X=kt, considering carbon oxidation as the controlling stage, is the one with the best fit to the experimental data. A probable mechanism for the carbochlorination of β-Ta₂O₅ is proposed: (1) activation of chlorine on the carbon surface, (2) chlorination of Ta₂O₅, (3) oxidation of carbon, and (4) recrystallization of β-Ta₂O₅.     

N-Type Field-Effect Transistors Using Multiple Mg-Doped ZnO Nanorods

Nanorod field-effect transistors (FETs) that use multiple Mg-doped ZnO nanorods and a SiO₂ gate insulator were fabricated and characterized. The use of multiple nanorods provides higher on-currents without significant degradation in threshold voltage shift and subthreshold slopes. It has been observed that the on-currents of the multiple ZnO nanorod FETs increase approximately linearly with the number of nanorods, with on-currents of ~1 muA per nanorod and little change in off-current (~4times10^-12). The subthreshold slopes and on-off ratios typically improve as the number of nanorods within the device channel is increased, reflecting good uniformity of properties from nanorod to nanorod. It is expected that Mg dopants contribute to high n-type semiconductor characteristics during ZnO nanorod growth. For comparison, nonintentionally doped ZnO nanorod FETs are fabricated, and show low conductivity to compare with Mg-doped ZnO nanorods. In addition, temperature-dependent current-voltage characteristics of single ZnO nanorod FETs indicate that the activation energy of the drain current is very low (0.05-0.16 eV) at gate voltages both above and below threshold     

Functions for relative maximization

We introduce functions for relative maximization in a general context: the beta and alpha applications. After a systematic study of different kinds of regularities, we investigate how to approximate certain values of these functions using periodic orbits. We also show that the differential of an alpha application determines the asymptotic behavior of the optimal trajectories.     

Compensation of the Piezo-Hall Effect in Integrated Hall Sensors on (100)-Si

Silicon Hall sensors are known to suffer from a long-term drift in the magnetic sensitivity between 1% and 4%, depending on the degree of moisture in the mold compound of the package. This drift is mainly caused by changes of mechanical stress exerted by the plastic package onto the die. We present a system, which continuously measures the relevant stress components, estimates the sensitivity drift, and corrects for it digitally. An individual precalibration versus temperature is necessary to achieve the required level of accuracy. Results from laboratory characterization with pressure cells and lifetime drift during qualification runs show that this system can keep the drift of magnetic sensitivity well below 1%.     

A Low-Complexity Circuit for On-Sensor Concurrent A/D Conversion and Compression

A low-complexity circuit for on-sensor compression is presented. The proposed circuit achieves complexity savings by combining a single-slope analog-to-digital converter with a Golomb-Rice entropy encoder and by implementing a low-complexity adaptation rule. The adaptation rule monitors the output codewords and minimizes their length by incrementing or decrementing the value of the Golomb-Rice coding parameter k. Its hardware implementation is one order of magnitude lower than existing adaptive algorithms. The compression circuit has been fabricated using a 0.35 muM CMOS technology and occupies an area of 0.0918 . Test measurements confirm the validity of the design.