Decomposition of the metastable beta phase in the all-beta alloy Ti-13V-11Cr-3Al

The phase transformations which occur in the all-β titanium alloy Ti-13V-llCr-3Al at temperatures below ∼ 500°C have been studied by transmission electron microscopy, X-ray diffraction, and electrical resistivity techniques. The decomposition of the metastable β phase has been found to proceed through a transition reaction leading to the formation of two bcc phases rather than through the precipitation of the ω phase as has been previously reported. An interpretation of the observed decomposition sequence, based on thermodynamic reasoning, is presented. The decomposition characteristics of the Ti-13V-llCr-3Al alloy have been compared with those of a Ti-13V-llCr alloy to determine the influence of aluminum on the transformation behavior.     

Fetal MEG redistribution by projection operators

The fetal magnetoencephalogram (fMEG) is measured in the presence of large interference from the maternal and fetal magnetocardiograms. This interference can be efficiently attenuated by orthogonal projection of the corresponding spatial vectors. However, the projection operators redistribute the fMEG signal among sensors. Although redistribution can be readily accounted for in the forward solution, visual interpretation of the fMEG signal topography is made difficult. We have devised a general, model-independent method for correction of the redistribution effect that utilizes the assumption that we know in which channels the fMEG should be negligible (such channels are distant from the known fetal head position). In a simplified case where the fMEG can be explained by equivalent current dipoles, the correction can also be obtained from fitting the dipoles to the fMEG signal. The corrected fMEG signal topography then corresponds to the dipole forward solution, but without orthogonal projection. We illustrate the redistribution correction on an example of experimentally measured flash evoked fMEG.     

Complexation of copper by zwitterionic aminosulfonic (good) buffers

Copper binding properties were investigated for several popular zwitterionic buffers. The two buffers 4-morpholinoethanesulfonic acid (MES) and 3-N-morpholinopropanesulfonic acid (MOPS) did not bind copper and would be good choices for metal speciation studies within their operational pH range. Conversely, 3-(N-morpholino)-2-hydroxypropanesulfonic acid (MOPSO) was observed to weakly bind copper directly (log Kc 2.02). Moreover, strong copper binding was observed for 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid (HEPES), 4-(2-hydroxyethyl)piperazine-1-propanesulfonic acid (HEPPS), and N-(2-hydroxyethyl)piperazine-N'-(2-hydroxypropanesulfonic acid) (HEPPSO). Log Kc values range from 7.04 to 7.68 and are indicative of strong copper binding ligands. The latter buffer also exhibited weak binding characteristics with a log Kc of 2.05. The strong Cu binding ligands were present in HEPES, HEPPS, and HEPPSO at much lower concentrations than the total buffer concentration. MES, HEPES, MOPSO, and HEPPSO were analyzed by electrospray-ionization quadrapole time-of-flight mass spectroscopy. The most prominent feature of the spectra for each buffer analyzed was the presence of multiple oligomers, indicating a propensity of interaction between buffer molecules. In addition, the presence of several contaminants was identified in the mass spectrum of the HEPES matrix, including a prominent contaminant (at m/z 131) present in levels similar to those obtained from the modeling of the copper titration data. Other contaminants were found in the other matrixes but were not identified as possible copper binding agents.     

Neural network approach to background modeling for video object segmentation.

This paper presents a novel background modeling and subtraction approach for video object segmentation. A neural network (NN) architecture is proposed to form an unsupervised Bayesian classifier for this application domain. The constructed classifier efficiently handles the segmentation in natural-scene sequences with complex background motion and changes in illumination. The weights of the proposed NN serve as a model of the background and are temporally updated to reflect the observed statistics of background. The segmentation performance of the proposed NN is qualitatively and quantitatively examined and compared to two extant probabilistic object segmentation algorithms, based on a previously published test pool containing diverse surveillance-related sequences. The proposed algorithm is parallelized on a subpixel level and designed to enable efficient hardware implementation.     

Efficient asynchronous executions of AMR computations and visualization on a GPU system

Adaptive Mesh Refinement is a method which dynamically varies the spatio-temporal resolution of localized mesh regions in numerical simulations, based on the strength of the solution features. In-situ visualization plays an important role for analyzing the time evolving characteristics of the domain structures. Continuous visualization of the output data for various timesteps results in a better study of the underlying domain and the model used for simulating the domain. In this paper, we develop strategies for continuous online visualization of time evolving data for AMR applications executed on GPUs. We reorder the meshes for computations on the GPU based on the users input related to the subdomain that he wants to visualize. This makes the data available for visualization at a faster rate. We then perform asynchronous executions of the visualization steps and fix-up operations on the CPUs while the GPU advances the solution. By performing experiments on Tesla S1070 and Fermi C2070 clusters, we found that our strategies result in 60% improvement in response time and 16% improvement in the rate of visualization of frames over the existing strategy of performing fix-ups and visualization at the end of the timesteps.     

Summary of current radiometric calibration coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI sensors

This paper provides a summary of the current equations and rescaling factors for converting calibrated Digital Numbers (DNs) to absolute units of at-sensor spectral radiance, Top-Of-Atmosphere (TOA) reflectance, and at-sensor brightness temperature. It tabulates the necessary constants for the Multispectral Scanner (MSS), Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+), and Advanced Land Imager (ALI) sensors. These conversions provide a basis for standardized comparison of data in a single scene or between images acquired on different dates or by different sensors. This paper forms a needed guide for Landsat data users who now have access to the entire Landsat archive at no cost.     

Installation of UPFC for enhancing overall performance of electrical power system

Stability of any power system is a major issue for secure operation of the system. The stability of power system is concerned with the behavior of synchronous generators following disturbances. Transmission system in competitive market refers to over loading of transmission lines or transformers due to market settlement. Thus there is a need of enhancing transmission capability of the network. FACTS controllers have the capability of controlling power flow by means of controlling line parameters, voltage injection at some of the angle. In the proposed work optimal location for installation of FACTS device is obtained using NN and the amount of voltage and angle to be injected in the system using UPFC is calculated using Bees algorithm. The method is tested on IEEE 26 bus system but it is general in nature and can be applied to any power system. The results exhibit the performance of the method in maintaining the system stability and АТС enhancement.     

Impact of Electron Beam on Storage Protein Subunits,In Vitro Protein Digestibility and Trypsin Inhibitor Content in Soybean Seeds

The present investigation was carried out to study the effect of 4.8, 9.2, 15.3 and 21.2 kGy of electron beam (EB)-irradiation on major storage proteins viz. glycinin (11S) and β-conglycinin (7S), in vitro protein digestibility (IVPD), and trypsin inhibitor (TI) content in seeds of three soybean genotypes. Densitometry of SDS-PAGE protein profile revealed significant (P < 0.05) reduction in α’, α and β subunits of 7S fraction at all doses. This reduction was higher (P < 0.05) than the decline observed in acidic and basic subunit of 11S fraction. Basic subunit registered significant (P < 0.05) increase at specific doses in two genotypes. All the doses induced significant (P < 0.05) increase in IVPD, and the increase due to 9.2, 15.3 and 21.2 kGy was higher (P < 0.05) compared to 4.8 kGy dose. The impact on TI content was genotype-dependent. The study showed a higher (P < 0.05) decline in the concentration of 7S fraction compared to 11S fraction and improvement in IVPD of soybean seeds due to exposure to EB-irradiation, which may influence the functional and nutritional value of soy products processed from them.     

Nucleic Acid Nanostructures for Chemical and Biological Sensing

The nanoscale features of DNA have made it a useful molecule for bottom‐up construction of nanomaterials, for example, two‐ and three‐dimensional lattices, nanomachines, and nanodevices. One of the emerging applications of such DNA‐based nanostructures is in chemical and biological sensing, where they have proven to be cost‐effective, sensitive and have shown promise as point‐of‐care diagnostic tools. DNA is an ideal molecule for sensing not only because of its specificity but also because it is robust and can function under a broad range of biologically relevant temperatures and conditions. DNA nanostructure‐based sensors provide biocompatibility and highly specific detection based on the molecular recognition properties of DNA. They can be used for the detection of single nucleotide polymorphism and to sense pH both in solution and in cells. They have also been used to detect clinically relevant tumor biomarkers. In this review, recent advances in DNA‐based biosensors for pH, nucleic acids, tumor biomarkers and cancer cell detection are introduced. Some challenges that lie ahead for such biosensors to effectively compete with established technologies are also discussed.