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IEEE International Conference on Plasma Science (ICOPS) is an annual conference coordinated by the Plasma Science and Application Committee (PSAC) of the IEEE Nuclear & Plasma Sciences Society.
The world's premiere conference in MEMS sensors, actuators and integrated micro and nano systems welcomes you to attend this four-day event showcasing major technological, scientific and commercial breakthroughs in mechanical, optical, chemical and biological devices and systems using micro and nanotechnology.The major areas of activity in the development of Transducers solicited and expected at this conference include but are not limited to: Bio, Medical, Chemical, and Micro Total Analysis Systems Fabrication and Packaging Mechanical and Physical Sensors Materials and Characterization Design, Simulation and Theory Actuators Optical MEMS RF MEMS Nanotechnology Energy and Power
The conference program will consist of plenary lectures, symposia, workshops andinvitedsessions of the latest significant findings and developments in all the major fields ofbiomedical engineering.Submitted papers will be peer reviewed. Accepted high quality paperswill be presented in oral and postersessions, will appear in the Conference Proceedings and willbe indexed in PubMed/MEDLINE & IEEE Xplore
CLEO®/Europe will showcase the latest developments in a wide range of laser and photonics areas including laser source development, materials, ultrafast science, fibre optics, nonlinear optics, terahertz sources, high-field physics, optical telecommunications, nanophotonics, biophotonics.EQEC will feature the fundamentals of quantum optics, quantum information, atom optics, ultrafast optics, nonlinear phenomena and self-organization, plasmonics and metamaterials, fundamental nanooptics, theoretical and computational photonics.
DNA Nanotechnology Micro-to-nano-scale Bridging Nanobiology and Nanomedicine Nanoelectronics Nanomanufacturing and Nanofabrication Nano Robotics and Automation Nanomaterials Nano-optics, Nano-optoelectronics and Nanophotonics Nanofluidics Nanomagnetics Nano/Molecular Heat Transfer & Energy Conversion Nanoscale Communication and Networks Nano/Molecular Sensors, Actuators and Systems
Contains articles on the applications and other relevant technology. Electronic applications include analog and digital circuits employing thin films and active devices such as Josephson junctions. Power applications include magnet design as well asmotors, generators, and power transmission
Specific topics of interest include, but are not limited to, sequence analysis, comparison and alignment methods; motif, gene and signal recognition; molecular evolution; phylogenetics and phylogenomics; determination or prediction of the structure of RNA and Protein in two and three dimensions; DNA twisting and folding; gene expression and gene regulatory networks; deduction of metabolic pathways; micro-array design and analysis; proteomics; ...
Physics, medicine, astronomy—these and other hard sciences share a common need for efficient algorithms, system software, and computer architecture to address large computational problems. And yet, useful advances in computational techniques that could benefit many researchers are rarely shared. To meet that need, Computing in Science & Engineering (CiSE) presents scientific and computational contributions in a clear and accessible format. ...
Electrical insulation common to the design and construction of components and equipment for use in electric and electronic circuits and distribution systems at all frequencies.
Both general and technical articles on current technologies and methods used in biomedical and clinical engineering; societal implications of medical technologies; current news items; book reviews; patent descriptions; and correspondence. Special interest departments, students, law, clinical engineering, ethics, new products, society news, historical features and government.
Proceedings of 16th International Conference on Data Engineering (Cat. No.00CB37073), 2000
2006 IEEE International Conference on Systems, Man and Cybernetics, 2006
In the work, we try to construct the corresponding S-system and modified power-low model from a dataset. These two mathematical models are highly nonlinear. Though they can clearly describe reactions among genes in the biological system, the identification is a tough work, especially for huge genes. We adopt the evolution strategy to achieve 16-genes modeling with 544 or 288 parameters. ...
2009 International Conference on Intelligent Engineering Systems, 2009
The fed-batch fermentation process is nonlinear and often operated at unsteady state. In this work, a supervisory control system was added to a fed-batch fermentation plant. The objective was to preserve the final biomass concentration, as nearly as possible to its ideal final value, even if the process input was subjected to changes. The main process input is the initial ...
Proceedings. 2004 IEEE Computational Systems Bioinformatics Conference, 2004. CSB 2004., 2004
Hidden Markov models (HMMs) have demonstrated great successes in modeling noisy sequential data sets in the area of speech recognition and protein sequence profiling. Results from association test showed significant Markov dependency in time-series gene expression data, and therefore HMMs would be especially appropriate for modeling gene expressions. In this project, we developed a gene function prediction tool based on ...
2013 IEEE Nuclear Science Symposium and Medical Imaging Conference (2013 NSS/MIC), 2013
In plant ecophysiology research there is interest in studying the biology of the rhizosphere because of its importance in plant nutrient-interactions. The rhizosphere is the zone of soil surrounding a plant's root system where microbes (such as fungi) are influenced by the root and the roots by the microbes. We are investigating a methodology for imaging the distribution of molecular ...
In the work, we try to construct the corresponding S-system and modified power-low model from a dataset. These two mathematical models are highly nonlinear. Though they can clearly describe reactions among genes in the biological system, the identification is a tough work, especially for huge genes. We adopt the evolution strategy to achieve 16-genes modeling with 544 or 288 parameters. The time-course data of the yeast cell cycle is concerned. The proposed two different gene regulatory networks and their corresponding pathways can provide biological researchers for further experiments in yeast cell cycle control.
The fed-batch fermentation process is nonlinear and often operated at unsteady state. In this work, a supervisory control system was added to a fed-batch fermentation plant. The objective was to preserve the final biomass concentration, as nearly as possible to its ideal final value, even if the process input was subjected to changes. The main process input is the initial biomass concentration which has an ideal initial value that may change according to chemical laboratory quality assurance procedures. Simulated experiments on the proposed supervisory control were done using a Proportional controller only, then by a Composite controller. The results showed that the Composite controller has a superior effect than the Proportional.
Hidden Markov models (HMMs) have demonstrated great successes in modeling noisy sequential data sets in the area of speech recognition and protein sequence profiling. Results from association test showed significant Markov dependency in time-series gene expression data, and therefore HMMs would be especially appropriate for modeling gene expressions. In this project, we developed a gene function prediction tool based on profile HMMs. Each function class is associated with a distinct HMM whose parameters are trained using yeast time-series gene expression data. The function annotations of the HMM training set were obtained from Munich Information Centre for Protein Sequences (MIPS) data base. We designed several structural variants of HMMs (single, double-split) and tested each of them on forty function classes each of which includes more than one hundred instances. The highest prediction sensitivity we achieved is 51% by using double-split HMM with 3-fold cross- validation.
In plant ecophysiology research there is interest in studying the biology of the rhizosphere because of its importance in plant nutrient-interactions. The rhizosphere is the zone of soil surrounding a plant's root system where microbes (such as fungi) are influenced by the root and the roots by the microbes. We are investigating a methodology for imaging the distribution of molecular compounds of interest in the rhizosphere without disturbing the root or soil habitat. Our intention is to develop a single photon emission computed tomography (SPECT) system (PhytoSPECT) to image the bio-distribution of fungi in association with a host plant's roots. The technique we are exploring makes use of radioactive isotopes as tracers to label molecules that bind to fungal- specific compounds of interest and to image the fungi distribution in the plant and/or soil. We report on initial experiments designed to test the ability of fungal-specific compounds labeled with an iodine radioisotope that binds to chitin monomers (N-acetylglucosamine). Chitin is a compound not found in roots but in fungal cell walls. We will test the ability to label the compound with radioactive isotopes of iodine (<sup>125</sup>I, and <sup>123</sup>I).
The recent development of high-throughput experimental methods has generated a large amount of protein interaction data, which is becoming the foundation for new biological discoveries. There are several methods developed for motif discovery, but these methods focus on detecting individual motifs rather than interacting motif pairs. The primary focus of this study is to predict reliable interacting motif pairs from combinations of protein features using a stochastic method. This paper describes an improved boosting algorithm for predicting interacting motif pairs of proteins and a method for generating negative interaction data for the algorithm.
Summary form only given, as follows. In food processing, medical treatment, etc., safe and high speed dry type sterilizing method has been required. Using an ac silent discharge, hydrogen peroxide is dissociated to OH radicals. Recently, OH radicals have been used for the sterilization of medical instruments using a low pressure glow discharge. Since the lifetime of an OH radical is very short (less than 1 ms), safety in case of a leak is high. The main advantage of this method is that the final products are water and oxygen, and that there is no negative impact on the environment. In this study, we have developed surface sterilization equipment using an atmospheric pressure electric discharge. An effective sterilization performance has been achieved for a short treatment time by decomposing hydrogen peroxide by the discharge. The sterilization performance against Bacillus subtilus spore, E. Coli., and common germs on the surface of a plastic material has been studied. The six orders of decrease in the viability of the B. Subtilus spore, common germs and E. Coli was 300 sec, 120 sec, 90 sec, respectively, when a 1 kHz ac silent discharge was used. The proposed method can possibly be applied in food processing.
Summary form only given. Cells often use signal transduction networks to make decisions critical to proper cell functioning. However, the performance and efficiency of many cellular decision-making systems is relatively unclear. Here we use rate distortion theory as theoretical tool for studying performance-cost tradeoffs in cellular decision making. The rate distortion function provides a lower bound on the rate at which information must be transmitted through the cellular signal transduction network in order to achieve a given performance criterion. To study gradient sensing performance of D. discoideum cells, we developed a model of the cell's directional response to a chemoattractant gradient that arises from a random direction. The distribution of the gradient angle represents a priori knowledge of the chemoattractant source location from the perspective of the cell. Using a distortion function closely related to the chemotactic index - a widely used measure of chemotactic performance - we computed the rate distortion function that minimizes the mutual information between the gradient angle and the directional response of the cell. We found that the input-output maps that optimally achieve the rate distortion function closely match published models that capture key characteristics of the signaling network in D. discoideum, implying that these cells have evolved to respond to chemoattractant sources in an efficient manner.
Summary form only given, as follows. InnovaTek is developing a surface decontamination technology that utilizes active species generated in a nonequilibrium corona plasma. In tests conducted at InnovaTek, our prototype device destroyed more than 6 million spores per square inch of an anthrax simulant, Bacillus subtillis, var. niger in 60 seconds. Destruction efficiencies in 60 seconds were as high as 98% for plastic, 99.9% for aluminum and 99.4% for cotton surfaces. Five-minute treatments resulted in a login reduction greater than three. Treatment did not harm the surfaces of the materials being decontaminated. The plasma technology was also tested against DMMP, a simulant for the chemical agent Sarin. Greater than a four log/sub 10/ destruction of the DMMP on an aluminum surface was achieved in a 10 minute treatment. An ion-trap mass spectrometer was utilized to collect time-resolved data on the treatment off-gases. These data indicate that only non-toxic fragments of the broken down DMMP molecule were present in the gas phase.
A practical guide to utility engineers for specifying preservative treatments for wood structures used on distribution and transmission lines.