878 resultados para Aggregation phenomena


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2002 Mathematics Subject Classification: 65C05

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2000 Mathematics Subject Classification: 35Q55,42B10.

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For a fibre Raman amplifier with randomly varying birefringence, we provide insight on the validity of previously explored multi-scale techniques leading to polarisation pulling of the signal state of polarisation to the pump state of polarisation. Unlike previous study, we demonstrate that in addition to polarisation pulling a new random birefringence-mediated phenomenon that goes beyond existing multi-scale techniques can boost resonance-like gain fluctuations similar to the Stochastic Anti-Resonance. For mode locked fibre lasers we report on fast and slow polarisation dynamics of fundamental, bound state, and multipulsing vector solitons along with stretched pulses. We demonstrate that tuning cavity anisotropy and birefringence along with parameters of an injected signal with randomly varying state of polarisation provides access to the variety of vector waveforms previously unexplored.

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The interaction of the wound dressing as a biomaterial with the wound bed is the central issue of this chapter. The interfacial phenomenon that encompasses the biological and biochemical consequences that arise when a biomaterial is introduced to a host biological environment is discussed. A great deal can be learned from observations arising from the behaviour of biomaterials at other body sites; one particularly relevant body site in the context of wound healing is the anterior eye. The cornea, tear film and posterior surface of the contact lens provide an informative model of the parallel interface that exists between the chronic wound bed, wound fluid and the dressing biomaterial. © 2011 Woodhead Publishing Limited All rights reserved.

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In wireless sensor networks where nodes are powered by batteries, it is critical to prolong the network lifetime by minimizing the energy consumption of each node. In this paper, the cooperative multiple-input-multiple-output (MIMO) and data-aggregation techniques are jointly adopted to reduce the energy consumption per bit in wireless sensor networks by reducing the amount of data for transmission and better using network resources through cooperative communication. For this purpose, we derive a new energy model that considers the correlation between data generated by nodes and the distance between them for a cluster-based sensor network by employing the combined techniques. Using this model, the effect of the cluster size on the average energy consumption per node can be analyzed. It is shown that the energy efficiency of the network can significantly be enhanced in cooperative MIMO systems with data aggregation, compared with either cooperative MIMO systems without data aggregation or data-aggregation systems without cooperative MIMO, if sensor nodes are properly clusterized. Both centralized and distributed data-aggregation schemes for the cooperating nodes to exchange and compress their data are also proposed and appraised, which lead to diverse impacts of data correlation on the energy performance of the integrated cooperative MIMO and data-aggregation systems.

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Climate change is one of the biggest environmental problems of the 21st century. The most sensitive indicators of the effects of the climatic changes are phenological processes of the biota. The effects of climate change which were observed the earliest are the remarkable changes in the phenology (i.e. the timing of the phenophases) of the plants and animals, which have been systematically monitored later. In our research we searched for the answer: which meteorological factors show the strongest statistical relationships with phenological phenomena based on some chosen plant and insect species (in case of which large phenological databases are available). Our study was based on two large databases: one of them is the Lepidoptera database of the Hungarian Plant Protection and Forestry Light Trap Network, the other one is the Geophytes Phenology Database of the Botanical Garden of Eötvös Loránd University. In the case of butterflies, statistically defined phenological dates were determined based on the daily collection data, while in the case of plants, observation data on blooming were available. The same meteorological indicators were applied for both groups in our study. On the basis of the data series, analyses of correlation were carried out and a new indicator, the so-called G index was introduced, summing up the number of correlations which were found to be significant on the different levels of significance. In our present study we compare the significant meteorological factors and analyse the differences based on the correlation data on plants and butterflies. Data on butterflies are much more varied regarding the effectiveness of the meteorological factors.

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The paper reviews some additive and multiplicative properties of ranking procedures used for generalized tournaments with missing values and multiple comparisons. The methods analysed are the score, generalised row sum and least squares as well as fair bets and its variants. It is argued that generalised row sum should be applied not with a fixed parameter, but a variable one proportional to the number of known comparisons. It is shown that a natural additive property has strong links to independence of irrelevant matches, an axiom judged unfavourable when players have different opponents.

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The paper reviews some axioms of additivity concerning ranking methods used for generalized tournaments with possible missing values and multiple comparisons. It is shown that one of the most natural properties, called consistency, has strong links to independence of irrelevant comparisons, an axiom judged unfavourable when players have different opponents. Therefore some directions of weakening consistency are suggested, and several ranking methods, the score, generalized row sum and least squares as well as fair bets and its two variants (one of them entirely new) are analysed whether they satisfy the properties discussed. It turns out that least squares and generalized row sum with an appropriate parameter choice preserve the relative ranking of two objects if the ranking problems added have the same comparison structure.

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An iterative travel time forecasting scheme, named the Advanced Multilane Prediction based Real-time Fastest Path (AMPRFP) algorithm, is presented in this dissertation. This scheme is derived from the conventional kernel estimator based prediction model by the association of real-time nonlinear impacts that caused by neighboring arcs’ traffic patterns with the historical traffic behaviors. The AMPRFP algorithm is evaluated by prediction of the travel time of congested arcs in the urban area of Jacksonville City. Experiment results illustrate that the proposed scheme is able to significantly reduce both the relative mean error (RME) and the root-mean-squared error (RMSE) of the predicted travel time. To obtain high quality real-time traffic information, which is essential to the performance of the AMPRFP algorithm, a data clean scheme enhanced empirical learning (DCSEEL) algorithm is also introduced. This novel method investigates the correlation between distance and direction in the geometrical map, which is not considered in existing fingerprint localization methods. Specifically, empirical learning methods are applied to minimize the error that exists in the estimated distance. A direction filter is developed to clean joints that have negative influence to the localization accuracy. Synthetic experiments in urban, suburban and rural environments are designed to evaluate the performance of DCSEEL algorithm in determining the cellular probe’s position. The results show that the cellular probe’s localization accuracy can be notably improved by the DCSEEL algorithm. Additionally, a new fast correlation technique for overcoming the time efficiency problem of the existing correlation algorithm based floating car data (FCD) technique is developed. The matching process is transformed into a 1-dimensional (1-D) curve matching problem and the Fast Normalized Cross-Correlation (FNCC) algorithm is introduced to supersede the Pearson product Moment Correlation Co-efficient (PMCC) algorithm in order to achieve the real-time requirement of the FCD method. The fast correlation technique shows a significant improvement in reducing the computational cost without affecting the accuracy of the matching process.

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Sociolinguists have documented the substrate influence of various languages on the formation of dialects in numerous ethnic-regional setting throughout the United States. This literature shows that while phonological and grammatical influences from other languages may be instantiated as durable dialect features, lexical phenomena often fade over time as ethnolinguistic communities assimilate with contiguous dialect groups. In preliminary investigations of emerging Miami Latino English, we have observed that lexical forms based on Spanish lexical forms are not only ubiquitous among the speech of the first generation Cuban Americans but also of the second. Examples, observed in field work, casual observation, and studied formally in an experimental context include the following: “get down from the car,” which derives from the Spanish equivalent, bajar del carro instead of “get out of the car”. The translation task administered to thirty-one participants showed a variety lexical phenomena are still maintained at equal or higher frequencies.

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The present study measured a chemotherapy drug, etoposide, in pig cerebrospinal fluid after intraventricular administrations were made directly into the fourth ventricle of the brain; cytotoxic concentrations for a twenty-four hour period after infusions. The analytical method developed validates the potential treatment of malignant brain tumors. The increase in serum carotenoid concentration in 30 healthy individuals was measured after supplementation with lutein. HPLC analysis of serum levels of carotenoids showed an increase in the concentration of lutein and a constant concentration of other major serum carotenoids. An initial attempt to measure the enthalpy of aggregation of xanthophylls was conducted by using ultraviolet-visible spectroscopy. The enthalpy of lutein aggregation and AH range of zeaxanthin disordering of aggregation are reported. Monomethyl ether of lutein did not aggregate in any of the aqueous solutions.

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This project was supported by the National Natural Science Foundation of China (No. 41572116), the Fundamental Research Funds for the Central Universities, China University of Geosciences, Wuhan) (No. CUG160602).

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Self-organization of organic molecules with carbon nanomaterials leads to formation of functionalized molecular nano-complexes with advanced features. We present a study of physical and chemical properties of carbon nanotube-surfactant-indocarbocyanine dye (astraphloxin) in water focusing on aggregation of the dye and resonant energy transfer from the dye to the nanotubes. Self-assembly of astraphloxin is evidenced in absorbance and photoluminescence depending dramatically on the concentrations of both the dye and surfactant in the mixtures. We observed an appearance of new photoluminescence peaks in visible range from the dye aggregates. The aggregates characterized with red shifted photoluminescence peaks at 595, 635 and 675 nm are formed mainly due to the presence of surfactant at the premicellar concentration. The energy transfer from the dye to the nanotubes amplifying near-infrared photoluminescence from the nanotubes is not affected by the aggregation of astraphloxin molecules providing important knowledge for further development of advanced molecular nano-complexes. The aggregation with the turned-on peaks and the energy transfer with amplified photoluminescence create powerful tools of visualization and/or detection of the nanotubes in visible and near-infrared spectral range, respectively, boosting its possible applications in sensors, energy generation/storage, and healthcare.

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Sensitive detection of pathogens is critical to ensure the safety of food supplies and to prevent bacterial disease infection and outbreak at the first onset. While conventional techniques such as cell culture, ELISA, PCR, etc. have been used as the predominant detection workhorses, they are however limited by either time-consuming procedure, complicated sample pre-treatment, expensive analysis and operation, or inability to be implemented at point-of-care testing. Here, we present our recently developed assay exploiting enzyme-induced aggregation of plasmonic gold nanoparticles (AuNPs) for label-free and ultrasensitive detection of bacterial DNA. In the experiments, AuNPs are first functionalized with specific, single-stranded RNA probes so that they exhibit high stability in solution even under high electrolytic condition thus exhibiting red color. When bacterial DNA is present in a sample, a DNA-RNA heteroduplex will be formed and subsequently prone to the RNase H cleavage on the RNA probe, allowing the DNA to liberate and hybridize with another RNA strand. This continuously happens until all of the RNA strands are cleaved, leaving the nanoparticles ‘unprotected’. The addition of NaCl will cause the ‘unprotected’ nanoparticles to aggregate, initiating a colour change from red to blue. The reaction is performed in a multi-well plate format, and the distinct colour signal can be discriminated by naked eye or simple optical spectroscopy. As a result, bacterial DNA as low as pM could be unambiguously detected, suggesting that the enzyme-induced aggregation of AuNPs assay is very easy to perform and sensitive, it will significantly benefit to development of fast and ultrasensitive methods that can be used for disease detection and diagnosis.