A review of the unique features of HDL apoproteins

The human plasma high density lipoproteins (HDL) are a heterogeneous ensemble of five proteins associated with both neutral and polar lipids. The sequences of all five proteins are known. ApoA-I and apoA-II are the major protein components; apoC-I, apoC-II and apoC-III are the minor protein components. All these apoproteins spontaneously recombine with phospholipids to give stable lipid-protein complexes and freely exchange between the two major HDL subclasses, HDL₂ and HDL₃. In addition, ApoC-I, apoC-II, and apoC-III exchange between HDL and very low density lipoproteins. Furthermore, certain HDL apoproteins are activators for plasma enzymes that are important in lipid metabolism. ApoA-I and apoC-I activate lecithin/cholesterol acyltransferase; apoC-II is an activator of lipoprotein lipase. The regions of apoC-I and apoC-II that are involved in the activation of these enzymes have been localized with synthetic peptides. Studies of synthetic and native fragments of apoA-II, apoC-I, apoC-II, and apoC-III as well as model lipid-binding peptides have identified specific regions with structural features common to lipid-binding proteins. These special properties, which include helical potential, sequences with a critical amphipathic length, and high hydrophobicity of the nonpolar side of the amphipathic helix, are the determinants of HDL structure and metabolism.     

Approximate similarity search for online multimedia services on distributed CPU–GPU platforms

Similarity search in high-dimensional spaces is a pivotal operation for several database applications, including online content-based multimedia services. With the increasing popularity of multimedia applications, these services are facing new challenges regarding (1) the very large and growing volumes of data to be indexed/searched and (2) the necessity of reducing the response times as observed by end-users. In addition, the nature of the interactions between users and online services creates fluctuating query request rates throughout execution, which requires a similarity search engine to adapt to better use the computation platform and minimize response times. In this work, we address these challenges with Hypercurves, a flexible framework for answering approximate k-nearest neighbor (kNN) queries for very large multimedia databases. Hypercurves executes in hybrid CPU–GPU environments and is able to attain massive query-processing rates through the cooperative use of these devices. Hypercurves also changes its CPU–GPU task partitioning dynamically according to the observed load, aiming for optimal response times. In our empirical evaluation, dynamic task partitioning reduced query response times by approximately 50 % compared to the best static task partition. Due to a probabilistic proof of equivalence to the sequential kNN algorithm, the CPU–GPU execution of Hypercurves in distributed (multi-node) environments can be aggressively optimized, attaining superlinear scalability while still guaranteeing, with high probability, results at least as good as those from the sequential algorithm.     

A description of phase inversion behaviour in agitated liquid-liquid dispersions under the influence of the Marangoni effect

The influence of the Marangoni effect on phase inversion behaviour is examined by integrating a microscopic study of the drop coalescence process, in which thin film drainage in the presence of insoluble surfactant occurs, into a macroscopic phase inversion model which has been developed previously using a Monte Carlo technique. This is achieved via an immobility factor, obtained from a comparison of the film drainage times for surfactant-laden systems and surfactant-free systems as a function of the drop approach velocity, surface Péclet number, initial surfactant concentration and the Hamaker constant, which is then used to modify the coalescence probability in the phase inversion model. On the one hand, the results indicate that the Marangoni effect removes any influence that the viscosity ratio has on phase inversion due to immobilisation of the interface, thus shielding the flow in the film from the effects of the flow in the dispersed phase; the point at which phase inversion occurs therefore tends towards equivolume holdups with the addition of surfactant. On the other hand, when comparisons are made with pure systems in which surfactant is absent, the system is seen to be either stabilised or de-stabilised from inversion depending on the viscosity ratio of the system. This is attributed to the influence of surfactant on the dispersion morphologies on either side of the inversion (i.e. water-in-oil dispersions and oil-in-water dispersions) and depends on the dispersed phase holdup; the Marangoni effect is felt stronger when the dispersed phase holdup is low.     

Linear Chain Ferromagnetic Charge Transfer Compounds

Charge transfer complexes possessing a … DADA … structure with both the donor, D, and acceptor, A, being S = 1/2 radicals may exhibit cooperative magnetic phenomena. The complex [Fe(C₅Me₅)₂]⁺·[TCNQ]⁻· exhibits metamagnetic behavior. The similarly structured [TCNE]⁻· and [C₄(CN)₆]⁻· complexes are ferromagnets, whereas the [DDQ]⁻· salt is a paramagnet. The high temperature magnetic susceptibility obeys the Curie-Weiss expression with θ = + 30, + 30, and + 3 for the [TCNE]⁻·, [C₄(CN)₆]⁻·, and [TCNQ]⁻· salts, respectively. The ferromagnetic [TCNE]⁻· salt exhibits zero field Zeeman split ⁵⁷Fe Mossbauer spectra with an internal field of 425.6 kOe at 4.23 K. After reviewing the current papers discussing ferromagnetism in molecular (organic) compounds, a qualitative model consistent with the necessary bulk spin alignment required for a ferromagnet is presented.     

Design of simulator training: a comparative study of Swedish dynamic decision-making training facilities

Cognition, Technology & Work - Simulator training is becoming increasingly important for training of time-critical and dynamic situations. Hence, how simulator training in such domains is...     

Sulfidation properties of austenitic Fe-Mn and Fe-Mn-Al alloys under low sulfur vapor pressure (8 Pa) in the temperature range 873–1173 K

The sulfidation properties of austenitic Fe-Mn and Fe-Mn-Al alloys containing small amounts of carbon have been characterized with respect to the sulfidation kinetics, scale morphological development, structures, and composition of the sulfide phases. The alloys contained 21–40 wt. % Mn and 2.5–8 wt.% Al. The sulfide phase was monosulfide of manganese and iron containing the other metallic elements in solid solution. Two regimes of sulfidation categorized by slow and fast reaction rates were exhibited by all alloys when sulfidized in sulfur vapor at = 8 Pa and over the temperature range 873–1173 K. In the slow regime, a compact duplex -Mn(Fe)S/Fe(Mn)S scale evolved by a classical parabolic law associated with metal diffusion in scale. A porous microcrystalline mixed scale of the above sulfides evolved in the regime of rapid sulfidation by quasilinear kinetics associated with sulfur ingress through the porous scale.     

A functional approach for the formalization of the fixture design process

The design of machining fixtures is a highly complex process that relies on designer experience and his/her implicit knowledge to achieve a good design. In order to facilitate its automation by the development of a knowledge-based application, the explicit definition of the fixture design process and the knowledge involved is a prior and a fundamental task to undertake. Additionally, a fundamental and well-known engineering principle should be considered: the functional requirements and their associated constraints should be the first input to any design process. Considering these two main ideas, this paper presents the development undertaken to facilitate the automation of the fixture design process based on a functional approach.In this context, the MOKA methodology has been used to elicit fixtures knowledge. IDEF0 and UML have been used to represent the fixture design process. A methodology based on the function concept and aiming to formalize such design process is proposed. Fixture functional requirements have been defined and formalized. Functional fixtures elements have been used to create a functional design solution, the link of these elements with the functional requirements and with typical commercial fixture components has been defined via tables and rules mapping. And finally, a prototype knowledge-based application has been developed in order to make an initial validation of the proposed methodology.     

3D Surface Reconstruction of Noisy Point Clouds Using Growing Neural Gas: 3D Object/Scene Reconstruction

With the advent of low-cost 3D sensors and 3D printers, scene and object 3D surface reconstruction has become an important research topic in the last years. In this work, we propose an automatic (unsupervised) method for 3D surface reconstruction from raw unorganized point clouds acquired using low-cost 3D sensors. We have modified the growing neural gas network, which is a suitable model because of its flexibility, rapid adaptation and excellent quality of representation, to perform 3D surface reconstruction of different real-world objects and scenes. Some improvements have been made on the original algorithm considering colour and surface normal information of input data during the learning stage and creating complete triangular meshes instead of basic wire-frame representations. The proposed method is able to successfully create 3D faces online, whereas existing 3D reconstruction methods based on self-organizing maps required post-processing steps to close gaps and holes produced during the 3D reconstruction process. A set of quantitative and qualitative experiments were carried out to validate the proposed method. The method has been implemented and tested on real data, and has been found to be effective at reconstructing noisy point clouds obtained using low-cost 3D sensors.     

Mobile wireless network system simulation

This paper describes an advanced simulation environment which is used to examine, validate, and predict the performance of mobile wireless network systems. This simulation environment overcomes many of the limitations found with analytical models, experimentation, and other commercial network simulators available on the market today. We identify a set of components which make up mobile wireless systems and describe a set of flexible modules which can be used to model the various components and their integration. These models are developed using the Maisie simulation language. By modeling the various components and their integration, this simulation environment is able to accurately predict the performance bottlenecks of a multimedia wireless network system being developed at UCLA, determine the trade-off point between the various bottlenecks, and provide performance measurements and validation of algorithms which are not possible through experimentation and too complex for analysis.This work was supported in part by the Advanced Research Projects Agency, ARPA/CSTO, under Contract J-FBI-93-112 Computer Aided Design of High Performance Wireless Networked Systems, and by ARPA/CSTO under Contract DABT-63-94-C-0080 TransparentVirtual Mobile Environment.This paper was in part presented at the ACM Mobile Computing and Networking Conference (Mobicom '95), Berkeley, California, 14–15 November 1995.