941 resultados para Synchronous machinery


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The states of cytochrome C molecules in aquous solution were studied with synchronous fluorescence spectroscopy, It was found that the synchronous fluorescent spectra of cytochrome C were contributed by tyrosine and tryptophan residues separately at Delta lambda = 20 nm and Delta lambda = 80 nm, The peak position in synchronous fluorescent spectra of tyrosine residues in cytochrome C molecule does not change with its concentration, but that of tryptophan residue changes with its concentration, Only one peak at 340.0 nm was observed in the dilute solution of cytochrome C, With increasing the concentration of cytochrome C, a new peak at 304. 0 nm appeared. The peak at 340.0 nm disappeared and only one peak at 304.0 nm was observed at a higher concentration of cytochrome C, It may originate from the change of aggregation states of cytochrome C molecules and it was considered that the peak at 340.0 nm was attributed to the monomer and peak at 304.0 nm was due to the dimmer or oligomers. When urea was added into cytochrome C solution in which both monomer and dimmer or oligomers exist, cytochrome C molecules do not denature in the range of the specific concentrations of urea. The concentration of monomer of cytochrome C molecules increased and that of aggregation slates decreased by adding urea, Therefore, the synchronous fluorescence spectroscopy can be used to identify monomer and aggregation states of cytochrome C molecules.

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The performance of Kalman filtering, synchronous excitation and numerical derivative techniques for the resolution of overlapping emission spectra in spectrofluorimetry was studied. The extent of spectrum overlap was quantitatively described by the separation degree D(s), defined as the ratio of the peak separation to the full width at half-maximum of the emission spectrum of the interferent. For the system of Rhodamine B and Rhodamine 6G with a large D(s) of about 0.4, both Kalman filtering and synchronous techniques are able to resolve the overlapping spectra well and to give satisfactory results while the derivative spectra are still overlapped with each other. Moreover, the sensitivities are greatly decreased in derivative techniques. For more closely spaced spectra emitted by the complexes of Al and Zn with 7-iodo-8-hydroxyquinoline-5-sulphonic acid (Ferron)-hexadecyltrimethylammonium bromide, the synchronous excitation technique cannot completely separate the overlapping peaks, although it increases the separation degree from 0.25 in the conventional spectra to 0.37 in the synchronous spectra. On the other hand, Kalman filtering is capable of resolving this system. When the Al/Zn intensity ratio at the central wavelength of Al was > 1, however, the accuracy and precision of the estimates for Zn concentration produced by the Kalman filter became worse. In this event, the combination of synchronous excitation and Kalman filtering can much improve the analytical results.

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Predictability -- the ability to foretell that an implementation will not violate a set of specified reliability and timeliness requirements -- is a crucial, highly desirable property of responsive embedded systems. This paper overviews a development methodology for responsive systems, which enhances predictability by eliminating potential hazards resulting from physically-unsound specifications. The backbone of our methodology is the Time-constrained Reactive Automaton (TRA) formalism, which adopts a fundamental notion of space and time that restricts expressiveness in a way that allows the specification of only reactive, spontaneous, and causal computation. Using the TRA model, unrealistic systems – possessing properties such as clairvoyance, caprice, infinite capacity, or perfect timing -- cannot even be specified. We argue that this "ounce of prevention" at the specification level is likely to spare a lot of time and energy in the development cycle of responsive systems -- not to mention the elimination of potential hazards that would have gone, otherwise, unnoticed. The TRA model is presented to system developers through the Cleopatra programming language. Cleopatra features a C-like imperative syntax for the description of computation, which makes it easier to incorporate in applications already using C. It is event-driven, and thus appropriate for embedded process control applications. It is object-oriented and compositional, thus advocating modularity and reusability. Cleopatra is semantically sound; its objects can be transformed, mechanically and unambiguously, into formal TRA automata for verification purposes, which can be pursued using model-checking or theorem proving techniques. Since 1989, an ancestor of Cleopatra has been in use as a specification and simulation language for embedded time-critical robotic processes.

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Communication and synchronization stand as the dual bottlenecks in the performance of parallel systems, and especially those that attempt to alleviate the programming burden by incurring overhead in these two domains. We formulate the notions of communicable memory and lazy barriers to help achieve efficient communication and synchronization. These concepts are developed in the context of BSPk, a toolkit library for programming networks of workstations|and other distributed memory architectures in general|based on the Bulk Synchronous Parallel (BSP) model. BSPk emphasizes efficiency in communication by minimizing local memory-to-memory copying, and in barrier synchronization by not forcing a process to wait unless it needs remote data. Both the message passing (MP) and distributed shared memory (DSM) programming styles are supported in BSPk. MP helps processes efficiently exchange short-lived unnamed data values, when the identity of either the sender or receiver is known to the other party. By contrast, DSM supports communication between processes that may be mutually anonymous, so long as they can agree on variable names in which to store shared temporary or long-lived data.

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This article presents our most recent advances in synchronous fluorescence (SF) methodology for biomedical diagnostics. The SF method is characterized by simultaneously scanning both the excitation and emission wavelengths while keeping a constant wavelength interval between them. Compared to conventional fluorescence spectroscopy, the SF method simplifies the emission spectrum while enabling greater selectivity, and has been successfully used to detect subtle differences in the fluorescence emission signatures of biochemical species in cells and tissues. The SF method can be used in imaging to analyze dysplastic cells in vitro and tissue in vivo. Based on the SF method, here we demonstrate the feasibility of a time-resolved synchronous fluorescence (TRSF) method, which incorporates the intrinsic fluorescent decay characteristics of the fluorophores. Our prototype TRSF system has clearly shown its advantage in spectro-temporal separation of the fluorophores that were otherwise difficult to spectrally separate in SF spectroscopy. We envision that our previously-tested SF imaging and the newly-developed TRSF methods will combine their proven diagnostic potentials in cancer diagnosis to further improve the efficacy of SF-based biomedical diagnostics.

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The parallelization of existing/industrial electromagnetic software using the bulk synchronous parallel (BSP) computation model is presented. The software employs the finite element method with a preconditioned conjugate gradient-type solution for the resulting linear systems of equations. A geometric mesh-partitioning approach is applied within the BSP framework for the assembly and solution phases of the finite element computation. This is combined with a nongeometric, data-driven parallel quadrature procedure for the evaluation of right-hand-side terms in applications involving coil fields. A similar parallel decomposition is applied to the parallel calculation of electron beam trajectories required for the design of tube devices. The BSP parallelization approach adopted is fully portable, conceptually simple, and cost-effective, and it can be applied to a wide range of finite element applications not necessarily related to electromagnetics.

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Over the last few decades, global warming has accelerated both the rate and magnitude of changes observed in many functional units of the Earth System. In this context, plankton are sentinel organisms because they are sensitive to subtle levels of changes in temperature and might help in identifying the current effects of climate change on pelagic ecosystems. In this paper, we performed a comparative approach in two regions of the North Atlantic (i.e. the Northeast Atlantic and the North Sea) to explore the relationships between changes in marine plankton, the regional physico-chemical environment and large-scale hydro-climatic forcing using four key indices: the North Atlantic Oscillation (NAO), the Atlantic Multidecadal Oscillation (AMO), the East Atlantic (EA) pattern and Northern Hemisphere Temperature (NHT) anomalies. Our analyses suggest that long-term changes in the states of the two ecosystems were synchronous and correlated to the same large-scale hydro-climatic variables: NHT anomalies, the AMO and to a lesser extent the EA pattern. No significant correlation was found between long-term ecosystem modifications and the state of the NAO. Our results suggest that the effect of climate on these ecosystems has mainly occurred in both regions through the modulation of the thermal regime.

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The amount of distributed generation connected to the distribution network is increasing. To use this resource more effectively, splitting of the distribution network, or islanding the system, for prevention of power outages is being considered by some utilities. In this paper an islanding method that avoids out-ofsynchronism re-closure is proposed. The island is kept in synchronism with the rest of the utility while it is not electrically connected. This is referred to as synchronous islanded operation. A phase difference control algorithm, developed by the authors, was tested in a single set scenario on a 50-kVA diesel generator using two different governors. These are the “standard product” variable gain governor of the diesel generator and a governor developed by the authors, which utilizes supplementary inputs in addition to engine speed. The results show that phase difference can be controlled within acceptable limits, both in steady state and after load disturbances are applied. The advantages of employing supplementary governor inputs are fully evaluated.

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In this paper, a Radial Basis Function neural network based AVR is proposed. A control strategy which generates local linear models from a global neural model on-line is used to derive controller feedback gains based on the Generalised Minimum Variance technique. Testing is carried out on a micromachine system which enables evaluation of practical implementation of the scheme. Constraints imposed by gathering training data, computational load, and memory requirements for the training algorithm are addressed.