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.     

Optimal allocation of assessment time in randomized pretest-posttest designs.

The widely used pretest–posttest design traditionally consists of a pretest and a posttest of equal lengths. However, greater statistical power can usually be achieved by using a posttest that is somewhat longer than the pretest. This article provides a method for calculating the optimal allocation of pretest and posttest assessment units so as to maximize power and presents the accompanying reduction in required sample size for a range of parameter values. When insufficient information is available to estimate the optimal location precisely, the effects of allocating 75% of the assessment units to the posttest are evaluated. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

BMP-2 and BMP-4, but not BMP-6, increase the number of adrenergic cells which develop in quail trunk neural crest cultures

Isolated rat liver mitochondria were incubated under various metabolic conditions to determine their membrane potential (MMP) as measured continuously by a tetraphenylphosphonium (TPP+)-selective electrode. By flow cytometry, a parallel analysis of fluorescence emissions observing single mitochondria stained with the lipophilic cation 5,5',6,6'-tetrachloro-1,1'3,3'-tetraethylbenzimidazolcarbocyanine iodide (JC-1) revealed linear correlation between the median orange fluorescence (FL2) due to J-aggregate formations and MMP values measured by TPP+. No correlation was detected with the green fluorescence (FL1) emission. A significantly higher correlation appeared between the FL2/FL1 ratio and MMP values. Within the same mitochondrial population, cytofluorimetric analysis revealed the presence of various classes of organelles with different MMP, whose distribution was dependent on metabolic condition. The highest functional heterogeneity was found in deenergized mitochondria, while the highest homogeneity was observed during the first phase of the phosphorylative process. Thus, these data suggest that the cytofluorimetric use of JC-1 provides direct experimental evidence for the hypothesis of functional mitochondrial heterogeneity, at least with respect to their membrane potential.     

Approximation algorithms for minimizing segments in radiation therapy

Intensity modulated radiation therapy (IMRT) is one of the most effective modalities for modern cancer treatment. The key to successful IMRT treatment hinges on the delivery of a two-dimensional discrete radiation intensity matrix using a device called a multileaf collimator (MLC). Mathematically, the delivery of an intensity matrix using an MLC can be viewed as the problem of representing a non-negative integral matrix (i.e., the intensity matrix) by a linear combination of certain special non-negative integral matrices called segments, where each such segment corresponds to one of the allowed states of the MLC. The problem of representing the intensity matrix with the minimum number of segments is known to be NP-complete. In this paper, we present two approximation algorithms for this matrix representation problem. To the best of our knowledge, these are the first algorithms to achieve non-trivial performance guarantees for multi-row intensity matrices.     

Incremental Evolution in ANNs: Neural Nets which Grow

This paper explains the optimisation of neuralnetwork topology using Incremental Evolution;that is, by allowing the network to expand byadding to its structure. This method allows anetwork to grow from a simple to a complexstructure until it is capable of fulfilling itsintended function. The approach is somewhatanalogous to the growth of an embryo or theevolution of a fossil line through time, it istherefore sometimes referred to as anembryology or embryological algorithm. Thepaper begins with a general introduction,comparing this method to other competingtechniques such as The Genetic Algorithm, otherEvolutionary Algorithms and SimulatedAnnealing. A literature survey of previous workis included, followed by an extensive newframework for application of the technique.Finally, examples of applications and a generaldiscussion are presented.     

Full Field Temperature Measurement of Specular Wafers During Rapid Thermal Processing

Many of the processes involved in the creation of semiconductor devices involve high-temperature processing of silicon wafers. The benefits of reduced thermal budget and faster cycle time make rapid thermal processing (RTP) a possible key technology for semiconductor manufacturing. However, the problem of nonuniform wafer temperature has prevented it from further spread among the industry. The first step in developing controls to maintain a uniform wafer temperature is accurate temperature measurement during processing. In this paper, a system was developed to exploit the specular reflectivity of silicon wafers and obtain a measurement of the wafer temperature profile. The spectral reflectivity is determined by measuring the intensity of an incident beam and the beam reflected from the wafer surface. With this measured reflectivity value the spectral-directional wafer emissivity was determined using Kirchhoff's law. The obtained emissivity then was used to calculate the wafer temperature profile from an image obtained with an infrared camera. An experimental study of the transmittance of an undoped silicon calibration wafer at an elevated temperature is also discussed     

Molybdenum Dioxide in Carbon Nanoreactors as a Catalytic Nanosponge for the Efficient Desulfurization of Liquid Fuels

The principle of a “catalytic nanosponge” that combines the catalysis of organosulfur oxidation and sequestration of the products from reaction mixtures is demonstrated. Group VI metal oxide nanoparticles (CrO_x, MoO_x, WO_x) are embedded within hollow graphitized carbon nanofibers (GNFs), which act as nanoscale reaction vessels for oxidation reactions used in the decontamination of fuel. When immersed in a model liquid alkane fuel contaminated with organosulfur compounds (benzothiophene, dibenzothiophene, dimethyldibenzothiophene), it is found that MoO₂@GNF nanoreactors, comprising 30 nm molybdenum dioxide nanoparticles grown within the channel of GNFs, show superior abilities toward oxidative desulfurization (ODS), affording over 98% sulfur removal at only 5.9 mol% catalyst loading. The role of the carbon nanoreactor in MoO₂@GNF is to enhance the activity and stability of catalytic centers over at least 5 cycles. Surprisingly, the nanotube cavity can selectively absorb and remove the ODS products (sulfoxides and sulfones) from several model fuel systems. This effect is related to an adsorptive desulfurization (ADS) mechanism, which in combination with ODS within the same material, yields a “catalytic nanosponge” MoO₂@GNF. This innovative ODS and ADS synergistic functionality negates the need for a solvent extraction step in fuel desulfurization and produces ultralow sulfur fuel.     

Optimizing the Optoelectronic Properties of Face-On Oriented Poly(3,4-Ethylenedioxythiophene) via Water-Assisted Oxidative Chemical Vapor Deposition

Engineering the texture and nanostructure to improve the electrical conductivity of semicrystalline conjugated polymers must address the rate-limiting step for charge carrier transport. In highly face-on orientation, the charge transport between chains within a crystallite becomes rate-limiting, which is highly sensitive to the π–π stacking distance and interchain charge transfer integral. Here, face-on oriented semicrystalline poly(3,4-ethylenedioxythiophene) (PEDOT) thin films are grown via water-assisted (W-A) oxidative chemical vapor deposition (oCVD). Combining W-A with the volatile oxidant, antimony pentachloride, yields an optimized electrical conductivity of 7520  ±  240 S cm⁻¹, a record for PEDOT thin films. Systematic control of π–π stacking distance from 3.50 Å down to 3.43 Å yields an electrical conductivity enhancement of ≈ 1140%. The highest electrical conductivity also corresponds to minimum in Urbach energy of 205 meV, indicating superior morphological order. The figure of merit for transparent conductors, σ_dc/σ_op, reaches a maximum value of 94, which is 1.9 × and 6.7 × higher than oCVD PEDOT grown without W-A and utilizing vanadium oxytrichloride and iron chloride oxidizing agents, respectively. The W-A oCVD is single-step all-dry process and provides conformal coverage, allowing direct growth on mechanical flexible, rough, and structured surfaces without the need for complex and costly transfer steps.     

Relationship between electrical and mechanical loss tangents of hollow glass powder reinforced epoxy composites: A pilot study

This study was focused on the synthesis of monodisperse poly(n‐butyl methacrylate‐co‐methyl methacrylate) submicrospheres via soap‐free emulsion polymerization and on their characterization. The glass‐transition temperatures of poly(n‐butyl methacrylate) and poly(methyl methacrylate) were approximately 25 and 110°C, respectively. Therefore, submicrospheres with different glass‐transition temperatures could be obtained through the variation of the copolymer composition. In addition, relationships between the monomer feed concentration (M₀) and the Mark–Houwink constant (α) for the copolymer submicrospheres were proposed. The molecular weights of the copolymer submicrospheres decreased sharply with an increase in the weight fraction of n‐butyl methacrylate. On the contrary, the particle diameter increased linearly from 277 to 335 nm with an increase in the weight fraction of n‐butyl methacrylate. The α values decreased with an increase in M₀, and this indicated that the branched structures of the copolymer submicrospheres were easily obtained when M₀ was higher than 0.11 g/mL of water. Consequently, the results of this study are expected to provide useful information for the synthesis of monodisperse copolymer submicrospheres by soap‐free emulsion polymerization. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2011     

Validation of a Method for Quantitation of Soybean Lectin in Commercial Varieties

Soybean agglutinin (SBA) protein, also known as soybean lectin, is regarded as an anti‐nutrient due to its negative effect on the ability of monogastric animals to gain weight following consumption of raw soybean seed. Historically, SBA has been measured using a time‐consuming and cumbersome hemagglutination procedure. The objective of our research was to obtain a validated methodology that is precise and accurate in the measurement of SBA while allowing minimally equipped laboratories to effectively conduct the analysis, thus our focus was on evaluating an existing commercially available ELISA, an enzyme‐linked‐lectin‐assay (ELLA), and a hybrid ELISA/ELLA. A new ELLA technique that can detect and quantify lectins was chosen and modified specifically for the quantitation of SBA in soybean seed. The proposed ELLA methodology is similar to a standard sandwich ELISA, and uses polyacrylamide‐linked N‐acetylgalactosamine (Gal–NAc–PAA) for a capture phase and the biotinylated version (Gal–NAc–PAA–Biotin) for detection. Based upon the validation data, the ELLA method can precisely and accurately determine soybean lectin levels in soybean seed. The validated ELLA method was used to quantify SBA in nine commercial soybean varieties introduced between 1972 and 2008 and demonstrated that the natural variability of SBA is subject to the effects of genotype and environment.