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.     

The use of aerosol formation, flammability, and explosion information for heat-transfer fluid selection

The devastating consequences of aerosol/mist explosions have been widely documented, and there are currently efforts to understand the mechanisms of formation and explosion of aerosols. Heat-transfer fluids (HTFs) are particularly susceptible to these hazards, because they are utilized under high pressures and below their flash points, making them more prone to leaking as aerosols. In fact, there is a critical need during design stages for a perception of explosion risks associated with the selection of HTFs. This paper discusses a novel scheme to integrate the knowledge of HTF aerosol formation from leaks in process equipment into the selection of HTFs during the design process. Hazards of aerosols formed from leaks are classified qualitatively using process pressure and droplet sizes.     

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.     

Fuzzy Reliability Assessment of Distribution System with Wind Farms and Plug-in Electric Vehicles

Abstract

The equipment failures are highly uncertain in nature and simple average failure rate will not reflect this uncertainty. The uncertainty level further increases in reliability evaluation due to the integration of wind farm (WF) because of the intermittent nature of wind speed and random charging patterns of plug-in electric vehicles (PEVs). In this work, the uncertain variables in the distribution system (failure rate, repair time, WF output, PEVs charging and system load factor) are represented as fuzzy numbers to handle the uncertainty. The available uncertain data are used to find the probability distribution function (PDF) of that parameter and is converted into fuzzy membership function using transformation techniques. Failure rate of equipment is converted into failure probability using Monte Carlo simulation (MCS) method. Sampling method is applied to create the PDF of a variable which has average value. Fuzzy severity index (FSI) is proposed to find the importance of an equipment on reliability and is evaluated by measuring the fuzzy distance between the fuzzy reliability indices. The proposed assessment method is validated on modified RBTS bus 2 by comparing with analytical and MCS methods. The proposed method has been tested with integration of WFs and PEVs.     

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.     

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.     

A simulation-based approach to study stochastic inventory-planning games

Non-cooperative decision-making problems in a decentralized supply chain can be characterized and studied using a stochastic game model. In an earlier paper, the authors developed a methodology that uses machine learning for finding (near) optimal policies for non-zero sum stochastic games, and applied their methodology on an N-retailer and W-warehouse inventory-planning problem. The focus of this paper is on making the methodology more amenable to practical applications by making it completely simulation-based. It is also demonstrated, through numerical example problems, how this methodology can be used to find (near) equilibrium policies, and evaluate short-term rewards of stochastic games. Short-term rewards of stochastic games could be, in many instances, more critical than equilibrium rewards. To our knowledge, no methodology exists in the open literature that can capture the short-term behaviour of non-zero sum stochastic games as examined in this paper.