2,638 research outputs found
Model Predictive Direct Current Control (MPDCC) for Grid Connected Application
This paper deals with the design and simulation of Dual Active Bridge Multilevel Inverter (DABMI) based Model Predictive Direct Current Control (MPDCC) for grid connected application. To achieve multilevel output voltage waveforms, the second inverter will be supply with half of the dc-link voltage. Model predictive direct current control used to control the grid current component in order to achieve minimum grid current error. Modulation is unnecessary in this system because the switching pattern is produce by the possible switching that determined by the proposed MPDCC. The voltage vector which minimizes the cost function will be selected and applied to track the reference current. The performance of the proposed MPDCC is observe and implement by MATLAB/Simulink Software
Suppression of Superconducting Critical Current Density by Small Flux Jumps in Thin Films
By doing magnetization measurements during magnetic field sweeps on thin
films of the new superconductor , it is found that in a low temperature
and low field region small flux jumps are taking place. This effect strongly
suppresses the central magnetization peak leading to reduced nominal
superconducting critical current density at low temperatures. A borderline for
this effect to occur is determined on the field-temperature (H-T) phase
diagram. It is suggested that the small size of the flux jumps in films is due
to the higher density of small defects and the relatively easy thermal
diffusion in thin films in comparison with bulk samples.Comment: 7 figures Phys. Rev. B accepted scheduled issue: 01 Feb 200
Rejoinder on "Conjectures on exact solution of three-dimensional (3D) simple orthorhombic Ising lattices"
It is shown that the arguments in the reply of Z.-D. Zhang (arXiv:0812.0194)
to the comment arXiv:0811.1802 defending his conjectures in arXiv:0705.1045 are
invalid. His conjectures have been thoroughly disproved.Comment: LaTeX2e, 2 pages, added responses to arXiv:0812.0194v3 and
arXiv:0812.0194v
Interaction of desulfovibrio desulfuricans biofilms with stainless steel surface and its impact on bacterial metabolism
Aims: To study the influence of some metallic elements of stainless steel 304 (SS 304) on the development and activity of a sulfate-reducing bacterial biofilm, using as comparison a reference nonmetallic material polymethylmethacrylate (PMMA).
Methods and Results: Desulfovibrio desulfuricans biofilms were developed on SS
304 and on a reference nonmetallic material, PMMA, in a flow cell system.
Steady-state biofilms were metabolically more active on SS 304 than on PMMA. Activity tests with bacteria from both biofilms at steady state also showed that the doubling time was lower for bacteria from SS 304 biofilms.
The influence of chromium and nickel, elements of SS 304 composition, was
also tested on a cellular suspension of Des. desulfuricans. Nickel decreased the bacterial doubling time, while chromium had no significant effect.
Conclusions: The following mechanism is hypothesized: a Des. desulfuricans
biofilm grown on a SS 304 surface in anaerobic conditions leads to the weakening
of the metal passive layer and to the dissolution in the bulk phase of nickel ions that have a positive influence on the sulfate-reducing bacteria metabolism.
This phenomenon may enhance the biocorrosion process.
Significance and Impact of the Study: A better understanding of the interactions between metallic surfaces such as stainless steel and bacteria commonly implied in the corrosion phenomena which is primordial to fight biocorrosion.Programme Praxis XXI; University of Santiago de
Compostela
The Neural Network Pushdown Automaton: Model, Stack and Learning Simulations
In order for neural networks to learn complex languages or grammars, they
must have sufficient computational power or resources to recognize or generate
such languages. Though many approaches have been discussed, one obvious
approach to enhancing the processing power of a recurrent neural network is to
couple it with an external stack memory - in effect creating a neural network
pushdown automata (NNPDA). This paper discusses in detail this NNPDA - its
construction, how it can be trained and how useful symbolic information can be
extracted from the trained network.
In order to couple the external stack to the neural network, an optimization
method is developed which uses an error function that connects the learning of
the state automaton of the neural network to the learning of the operation of
the external stack. To minimize the error function using gradient descent
learning, an analog stack is designed such that the action and storage of
information in the stack are continuous. One interpretation of a continuous
stack is the probabilistic storage of and action on data. After training on
sample strings of an unknown source grammar, a quantization procedure extracts
from the analog stack and neural network a discrete pushdown automata (PDA).
Simulations show that in learning deterministic context-free grammars - the
balanced parenthesis language, 1n0n, and the deterministic Palindrome - the
extracted PDA is correct in the sense that it can correctly recognize unseen
strings of arbitrary length. In addition, the extracted PDAs can be shown to
be identical or equivalent to the PDAs of the source grammars which were used
to generate the training strings.
(Also cross-referenced as UMIACS-TR-93-77.
Photoresponsive and Ultraviolet to Visible-Light Range Photocatalytic Properties of ZnO:Sb Nanowires
100學年度研究獎補助論文[[abstract]]Zinc oxide (ZnO) doped antimony (Sb) nanowires have been synthesized for improving ultraviolet sensing and photocatalytic properties. Upon illumination by UV light (365nm , 2.33mWcm−2 ), the photoelectric current of the ZnO:Sb nanowires exhibited a rapid photoresponse as compared to that of the ZnO nanowires. A highest ratio of photocurrent to dark current of around 48.8-fold was achieved in the as-synthesized ZnO:Sb nanowires. A UV-visible spectrophotometer was used to investigate the absorbance spectrum of the ZnO:Sb nanowires, which exhibited a high absorbance ratio with redshift effect in contrast to that of the ZnO nanowires. Visible-light photocatalysis and UV photoresponsive properties of the ZnO:Sb nanowires are superior to those of the ZnO nanowires.[[notice]]補正完畢[[incitationindex]]SCI[[booktype]]電子
Spin-triplet superconductivity in repulsive Hubbard models with disconnected Fermi surfaces: a case study on triangular and honeycomb lattices
We propose that spin-fluctuation-mediated spin-triplet superconductivity may
be realized in repulsive Hubbard models with disconnected Fermi surfaces. The
idea is confirmed for Hubbard models on triangular (dilute band filling) and
honeycomb (near half-filling) lattices using fluctuation exchange
approximation, where triplet pairing order parameter with f-wave symmetry is
obtained. Possible relevance to real superconductors is suggested.Comment: 5 pages, 6 figures, RevTeX, uses epsf.sty and multicol.st
Stopping and Isospin Equilibration in Heavy Ion Collisions
We investigate the density behaviour of the symmetry energy with respect to
isospin equilibration in the combined systems at relativistic
energies of 0.4 and . The study is performed within a relativistic
framework and the contribution of the iso-vector, scalar field to the
symmetry energy and the isospin dynamics is particularly explored. We find that
the isospin mixing depends on the symmetry energy and a stiff behaviour leads
to more transparency. The results are also nicely sensitive to the "fine
structure" of the symmetry energy, i.e. to the covariant properties of the
isovector meson fields. The isospin tracing appears much less dependent on the
in-medium neutron-proton cross-sections () and this makes such
observable very peculiar for the study of the isovector part of the nuclear
equation of state. Within such a framework, comparisons with experiments
support the introduction of the meson in the description of the
iso-vector equation of state.Comment: 11 pages, 5 figures. Accepted for publication in Phys.Lett.
Branchial FXYD protein expression in response to salinity change and its interaction with Na+/K+-ATPase of the euryhaline teleost Tetraodon nigroviridis
Na+/K+-ATPase (NKA) is a ubiquitous membrane-bound protein crucial for teleost osmoregulation. The enzyme is composed of two essential subunits, a catalytic alpha subunit and a glycosylated beta subunit which is responsible for membrane targeting of the enzyme. In mammals, seven FXYD members have been found. FXYD proteins have been identified as the regulatory protein of NKA in mammals and elasmobranchs, it is thus interesting to examine the expression and functions of FXYD protein in the euryhaline teleosts with salinity-dependent changes of gill NKA activity. The present study investigated the expression and distribution of the FXYD protein in gills of seawater (SW)- or freshwater (FW)-acclimated euryhaline pufferfish (Tetraodon nigroviridis). The full-length pufferfish FXYD gene (pFXYD) was confirmed by RT-PCR. pFXYD was found to be expressed in many organs including gills of both SW and FW pufferfish. pFXYD mRNA abundance in gills, determined by real-time PCR, was significantly higher in FW fish than in SW fish. An antiserum raised against a partial amino acid sequence of pFXYD was used for the immunoblots of gill homogenates and a major band at 13 kDa was detected. The relative amounts of pFXYD protein and mRNA in gills of SW and FW pufferfish were identical, but opposite to the expression levels of NKA. Immunofluorescent staining of frozen sections demonstrated that pFXYD was colocalized to NKA-immunoreactive cells in the gill filaments. In addition, interaction between pFXYD and NKA was demonstrated by co-immunoprecipitation. Taken together, salinity-dependent expression of pFXYD protein and NKA, as well as the evidence for their colocalization and interaction in pufferfish gills suggested that pFXYD regulates NKA activity in gills of euryhaline teleosts upon salinity challenge
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