987 resultados para Modular matrix converter


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Tesis inédita presentada en la Universidad Europea de Madrid. Facultad de Arquitectura, Ingeniería y Diseño. Programa de Doctorado en Técnicas Avanzadas en Construcción

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We present results of calculations [1] that employ a new mixed quantum classical iterative density matrix propagation approach (ILDM , or so called Is‐Landmap) [2] to explore the survival of coherence in different photo synthetic models. Our model studies confirm the long lived quantum coherence , while conventional theoretical tools (such as Redfield equation) fail to describe these phenomenon [3,4]. Our ILDM method is a numerical exactly propagation scheme and can be served as a bench mark calculation tools[2]. Result get from ILDM and from other recent methods have been compared and show agreement with each other[4,5]. Long lived coherence plateau has been attribute to the shift of harmonic potential due to the system bath interaction, and the harvesting efficiency is a balance between the coherence and dissipation[1]. We use this approach to investigate the excitation energy transfer dynamics in various light harvesting complex include Fenna‐Matthews‐Olsen light harvesting complex[1] and Cryptophyte Phycocyanin 645 [6]. [1] P.Huo and D.F.Coker ,J. Chem. Phys. 133, 184108 (2010) . [2] E.R. Dunkel, S. Bonella, and D.F. Coker, J. Chem. Phys. 129, 114106 (2008). [3] A. Ishizaki and G.R. Fleming, J. Chem. Phys. 130, 234111 (2009). [4] A. Ishizaki and G.R. Fleming, Proc. Natl. Acad. Sci. 106, 17255 (2009). [5] G. Tao and W.H. Miller, J. Phys. Chem. Lett. 1, 891 (2010). [6] P.Huo and D.F.Coker in preparation

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Making use of very detailed neurophysiological, anatomical, and behavioral data to build biological-realistic computational models of animal behavior is often a difficult task. Until recently, many software packages have tried to resolve this mismatched granularity with different approaches. This paper presents KInNeSS, the KDE Integrated NeuroSimulation Software environment, as an alternative solution to bridge the gap between data and model behavior. This open source neural simulation software package provides an expandable framework incorporating features such as ease of use, scalabiltiy, an XML based schema, and multiple levels of granularity within a modern object oriented programming design. KInNeSS is best suited to simulate networks of hundreds to thousands of branched multu-compartmental neurons with biophysical properties such as membrane potential, voltage-gated and ligand-gated channels, the presence of gap junctions of ionic diffusion, neuromodulation channel gating, the mechanism for habituative or depressive synapses, axonal delays, and synaptic plasticity. KInNeSS outputs include compartment membrane voltage, spikes, local-field potentials, and current source densities, as well as visualization of the behavior of a simulated agent. An explanation of the modeling philosophy and plug-in development is also presented. Further developement of KInNeSS is ongoing with the ultimate goal of creating a modular framework that will help researchers across different disciplines to effecitively collaborate using a modern neural simulation platform.

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Making use of very detailed neurophysiological, anatomical, and behavioral data to build biologically-realistic computational models of animal behavior is often a difficult task. Until recently, many software packages have tried to resolve this mismatched granularity with different approaches. This paper presents KInNeSS, the KDE Integrated NeuroSimulation Software environment, as an alternative solution to bridge the gap between data and model behavior. This open source neural simulation software package provides an expandable framework incorporating features such as ease of use, scalability, an XML based schema, and multiple levels of granularity within a modern object oriented programming design. KInNeSS is best suited to simulate networks of hundreds to thousands of branched multi-compartmental neurons with biophysical properties such as membrane potential, voltage-gated and ligand-gated channels, the presence of gap junctions or ionic diffusion, neuromodulation channel gating, the mechanism for habituative or depressive synapses, axonal delays, and synaptic plasticity. KInNeSS outputs include compartment membrane voltage, spikes, local-field potentials, and current source densities, as well as visualization of the behavior of a simulated agent. An explanation of the modeling philosophy and plug-in development is also presented. Further development of KInNeSS is ongoing with the ultimate goal of creating a modular framework that will help researchers across different disciplines to effectively collaborate using a modern neural simulation platform.

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Advanced modulation formats have become increasingly important as telecoms engineers strive for improved tolerance to both linear and nonlinear fibre-based transmission impairments. Two important modulation schemes are Duobinary (DB) and Alternate-mark inversion (AMI) [1] where transmission enhancement results from auxiliary phase modulation. As advanced modulation formats displace Return-to-zero On-Off Keying (RZ-OOK), inter-modulation converters will become increasingly important. If the modulation conversion can be performed at high bitrates with a small number of operations per bit, then all-optical techniques may offer lower energy consumption compared to optical-electronic-optical approaches. In this paper we experimentally demonstrate an all-optical system incorporating a pair of hybrid-integrated semiconductor optical amplifier (SOA)-based Mach-Zehnder interferometer (MZI) gates which translate RZ-OOK to RZ-DB or RZ-AMI at 42.6 Gbps. This scheme includes a wavelength conversion to arbitrary output wavelength and has potential for high-level photonic integration, scalability to higher bitrates, and should exhibit regenerative properties [2].

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We numerically investigate a novel 40 Gbps OOK to AMI all-optical modulation format converter employing an SOA-based Mach-Zehnder interferometer.  We demonstrate operation with a 27-1 PRBS and explain the phase modulation's relationship with patterning.

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This paper reports on the design and the manufacturing of an integrated DCDC converter, which respects the specificity of sensor node network: compactness, high efficiency in acquisition and transmission modes, and compatibility with miniature Lithium batteries. A novel integrated circuit (ASIC) has been designed and manufactured to provide regulated Voltage to the sensor node from miniaturized, thin film Lithium batteries. Then, a 3D integration technique has been used to integrate this ASIC in a 3 layers stack with high efficiency passives components, mixing the wafer level technologies from two different research institutions. Electrical results have demonstrated the feasibility of this integrated system and experiments have shown significant improvements in the case of oscillations in regulated voltage. However, stability of this output voltage toward the input voltage has still to be improved.

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Emerging healthcare applications can benefit enormously from recent advances in pervasive technology and computing. This paper introduces the CLARITY Modular Ambient Health and Wellness Measurement Platform:, which is a heterogeneous and robust pervasive healthcare solution currently under development at the CLARITY Center for Sensor Web Technologies. This intelligent and context-aware platform comprises the Tyndall Wireless Sensor Network prototyping system, augmented with an agent-based middleware and frontend computing architecture. The key contribution of this work is to highlight how interoperability, expandability, reusability and robustness can be manifested in the modular design of the constituent nodes and the inherently distributed nature of the controlling software architecture.Emerging healthcare applications can benefit enormously from recent advances in pervasive technology and computing. This paper introduces the CLARITY Modular Ambient Health and Wellness Measurement Platform:, which is a heterogeneous and robust pervasive healthcare solution currently under development at the CLARITY Center for Sensor Web Technologies. This intelligent and context-aware platform comprises the Tyndall Wireless Sensor Network prototyping system, augmented with an agent-based middleware and frontend computing architecture. The key contribution of this work is to highlight how interoperability, expandability, reusability and robustness can be manifested in the modular design of the constituent nodes and the inherently distributed nature of the controlling software architecture.

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Motivated by accurate average-case analysis, MOdular Quantitative Analysis (MOQA) is developed at the Centre for Efficiency Oriented Languages (CEOL). In essence, MOQA allows the programmer to determine the average running time of a broad class of programmes directly from the code in a (semi-)automated way. The MOQA approach has the property of randomness preservation which means that applying any operation to a random structure, results in an output isomorphic to one or more random structures, which is key to systematic timing. Based on original MOQA research, we discuss the design and implementation of a new domain specific scripting language based on randomness preserving operations and random structures. It is designed to facilitate compositional timing by systematically tracking the distributions of inputs and outputs. The notion of a labelled partial order (LPO) is the basic data type in the language. The programmer uses built-in MOQA operations together with restricted control flow statements to design MOQA programs. This MOQA language is formally specified both syntactically and semantically in this thesis. A practical language interpreter implementation is provided and discussed. By analysing new algorithms and data restructuring operations, we demonstrate the wide applicability of the MOQA approach. Also we extend MOQA theory to a number of other domains besides average-case analysis. We show the strong connection between MOQA and parallel computing, reversible computing and data entropy analysis.

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This thesis is focused on the design and development of an integrated magnetic (IM) structure for use in high-power high-current power converters employed in renewable energy applications. These applications require low-cost, high efficiency and high-power density magnetic components and the use of IM structures can help achieve this goal. A novel CCTT-core split-winding integrated magnetic (CCTT IM) is presented in this thesis. This IM is optimized for use in high-power dc-dc converters. The CCTT IM design is an evolution of the traditional EE-core integrated magnetic (EE IM). The CCTT IM structure uses a split-winding configuration allowing for the reduction of external leakage inductance, which is a problem for many traditional IM designs, such as the EE IM. Magnetic poles are incorporated to help shape and contain the leakage flux within the core window. These magnetic poles have the added benefit of minimizing the winding power loss due to the airgap fringing flux as they shape the fringing flux away from the split-windings. A CCTT IM reluctance model is developed which uses fringing equations to accurately predict the most probable regions of fringing flux around the pole and winding sections of the device. This helps in the development of a more accurate model as it predicts the dc and ac inductance of the component. A CCTT IM design algorithm is developed which relies heavily on the reluctance model of the CCTT IM. The design algorithm is implemented using the mathematical software tool Mathematica. This algorithm is modular in structure and allows for the quick and easy design and prototyping of the CCTT IM. The algorithm allows for the investigation of the CCTT IM boxed volume with the variation of input current ripple, for different power ranges, magnetic materials and frequencies. A high-power 72 kW CCTT IM prototype is designed and developed for use in an automotive fuelcell-based drivetrain. The CCTT IM design algorithm is initially used to design the component while 3D and 2D finite element analysis (FEA) software is used to optimize the design. Low-cost and low-power loss ferrite 3C92 is used for its construction, and when combined with a low number of turns results in a very efficient design. A paper analysis is undertaken which compares the performance of the high-power CCTT IM design with that of two discrete inductors used in a two-phase (2L) interleaved converter. The 2L option consists of two discrete inductors constructed from high dc-bias material. Both topologies are designed for the same worst-case phase current ripple conditions and this ensures a like-for-like comparison. The comparison indicates that the total magnetic component boxed volume of both converters is similar while the CCTT IM has significantly lower power loss. Experimental results for the 72 kW, (155 V dc, 465 A dc input, 420 V dc output) prototype validate the CCTT IM concept where the component is shown to be 99.7 % efficient. The high-power experimental testing was conducted at General Motors advanced technology center in Torrence, Los Angeles. Calorific testing was used to determine the power loss in the CCTT IM component. Experimental 3.8 kW results and a 3.8 kW prototype compare and contrast the ferrite CCTT IM and high dc-bias 2L concepts over the typical operating range of a fuelcell under like-for-like conditions. The CCTT IM is shown to perform better than the 2L option over the entire power range. An 8 kW ferrite CCTT IM prototype is developed for use in photovoltaic (PV) applications. The CCTT IM is used in a boost pre-regulator as part of the PV power stage. The CCTT IM is compared with an industry standard 2L converter consisting of two discrete ferrite toroidal inductors. The magnetic components are compared for the same worst-case phase current ripple and the experimental testing is conducted over the operation of a PV panel. The prototype CCTT IM allows for a 50 % reduction in total boxed volume and mass in comparison to the baseline 2L option, while showing increased efficiency.

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In spectra of jet-cooled C2H2 recorded with an FTIR spectrometer, the ν5, ν4 + ν5, ν3 and ν2 + ν4 + ν5 bands all exhibit an intensity distribution corresponding to ∼6 K for rotation, with no evidence of nuclear spin conversion. Spectra of C2H2 isolated in solid p-H2 show no evidence of rotation of C2H2. The strong interaction between ν3 and ν2 + ν4 + ν5 in the gas phase is diminished in solid p-H2. Lines associated with dimer, trimer and tetramer of C2H2 are identified. Spectral features characteristic of solid state acetylene are observed under jet-cooled conditions. © 2007 Elsevier B.V. All rights reserved.

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OBJECTIVES: Adipose-derived stem cells (ASCs) and bone marrow-derived mesenchymal stem cells (MSCs) are multipotent adult stem cells with potential for use in cartilage tissue engineering. We hypothesized that these cells show distinct responses to different chondrogenic culture conditions and extracellular matrices, illustrating important differences between cell types. METHODS: Human ASCs and MSCs were chondrogenically differentiated in alginate beads or a novel scaffold of reconstituted native cartilage-derived matrix with a range of growth factors, including dexamethasone, transforming growth factor beta3, and bone morphogenetic protein 6. Constructs were analyzed for gene expression and matrix synthesis. RESULTS: Chondrogenic growth factors induced a chondrocytic phenotype in both ASCs and MSCs in alginate beads or cartilage-derived matrix. MSCs demonstrated enhanced type II collagen gene expression and matrix synthesis as well as a greater propensity for the hypertrophic chondrocyte phenotype. ASCs had higher upregulation of aggrecan gene expression in response to bone morphogenetic protein 6 (857-fold), while MSCs responded more favorably to transforming growth factor beta3 (573-fold increase). CONCLUSIONS: ASCs and MSCs are distinct cell types as illustrated by their unique responses to growth factor-based chondrogenic induction. This chondrogenic induction is affected by the composition of the scaffold and the presence of serum.

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Human adipose stem cells (hASCs) can differentiate into a variety of phenotypes. Native extracellular matrix (e.g., demineralized bone matrix or small intestinal submucosa) can influence the growth and differentiation of stem cells. The hypothesis of this study was that a novel ligament-derived matrix (LDM) would enhance expression of a ligamentous phenotype in hASCs compared to collagen gel alone. LDM prepared using phosphate-buffered saline or 0.1% peracetic acid was mixed with collagen gel (COL) and was evaluated for its ability to induce proliferation, differentiation, and extracellular matrix synthesis in hASCs over 28 days in culture at different seeding densities (0, 0.25 x 10(6), 1 x 10(6), or 2 x 10(6) hASC/mL). Biochemical and gene expression data were analyzed using analysis of variance. Fisher's least significant difference test was used to determine differences between treatments following analysis of variance. hASCs in either LDM or COL demonstrated changes in gene expression consistent with ligament development. hASCs cultured with LDM demonstrated more dsDNA content, sulfated-glycosaminoglycan accumulation, and type I and III collagen synthesis, and released more sulfated-glycosaminoglycan and collagen into the medium compared to hASCs in COL (p

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Complex diseases will have multiple functional sites, and it will be invaluable to understand the cross-locus interaction in terms of linkage disequilibrium (LD) between those sites (epistasis) in addition to the haplotype-LD effects. We investigated the statistical properties of a class of matrix-based statistics to assess this epistasis. These statistical methods include two LD contrast tests (Zaykin et al., 2006) and partial least squares regression (Wang et al., 2008). To estimate Type 1 error rates and power, we simulated multiple two-variant disease models using the SIMLA software package. SIMLA allows for the joint action of up to two disease genes in the simulated data with all possible multiplicative interaction effects between them. Our goal was to detect an interaction between multiple disease-causing variants by means of their linkage disequilibrium (LD) patterns with other markers. We measured the effects of marginal disease effect size, haplotype LD, disease prevalence and minor allele frequency have on cross-locus interaction (epistasis). In the setting of strong allele effects and strong interaction, the correlation between the two disease genes was weak (r=0.2). In a complex system with multiple correlations (both marginal and interaction), it was difficult to determine the source of a significant result. Despite these complications, the partial least squares and modified LD contrast methods maintained adequate power to detect the epistatic effects; however, for many of the analyses we often could not separate interaction from a strong marginal effect. While we did not exhaust the entire parameter space of possible models, we do provide guidance on the effects that population parameters have on cross-locus interaction.

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The extracellular matrix (ECM) of the human intervertebral disc is rich in molecules that interact with cells through integrin-mediated attachments. Porcine nucleus pulposus (NP) cells have been shown to interact with laminin (LM) isoforms LM-111 and LM-511 through select integrins that regulate biosynthesis and cell attachment. Since human NP cells lose many phenotypic characteristics with age, attachment and interaction with the ECM may be altered. Expression of LM-binding integrins was quantified for human NP cells using flow cytometry. The cell-ECM attachment mechanism was determined by quantifying cell attachment to LM-111, LM-511, or type II collagen after functionally blocking specific integrin subunits. Human NP cells express integrins β1, α3, and α5, with over 70% of cells positive for each subunit. Blocking subunit β1 inhibited NP cell attachment to all substrates. Blocking subunits α1, α2, α3, and α5 simultaneously, but not individually, inhibits NP cell attachment to laminins. While integrin α6β1 mediated porcine NP cell attachment to LM-111, we found integrins α3, α5, and β1 instead contributed to human NP cell attachment. These findings identify integrin subunits that may mediate interactions with the ECM for human NP cells and could be used to promote cell attachment, survival, and biosynthesis in cell-based therapeutics.