928 resultados para practical applications


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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Functionalization with surfactants and with active molecules of deoxyribonucleic acid (DNA), thin film processing as well as their nonlinear optical and electrical properties are reviewed and discussed. On the basis of a quantum three level model, we show that the anomalous concentration variation of cubic susceptibility chi((3))(-3 omega; omega, omega, omega) in thin films of DNA-CTMA complexes doped with Disperse Red 1 chromophore can be explained by the concentration variation of two-photon resonance contribution. We show also that the DNA complexes, plasticized with glycerol and adequately doped can be processed into self standing conducting membranes with a high electrical conductivity. The measured ionic conductivity at room temperature, depending on dopant used and its concentration, is in the range of 3.5 x 10(-4)-10(-5) S/cm and increases linearly as a function of temperature, reaching 10(-3) S/cm at 358 K for the most conducting sample, obeying predominantly the Arrhenius law. Practical applications of DNA complexes are also described and discussed. (C) 2012 Academie des sciences. Published by Elsevier Masson SAS. All rights reserved.

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The research has included the efforts in designing, assembling and structurally and functionally characterizing supramolecular biofunctional architectures for optical biosensing applications. In the first part of the study, a class of interfaces based on the biotin-NeutrAvidin binding matrix for the quantitative control of enzyme surface coverage and activity was developed. Genetically modified ß-lactamase was chosen as a model enzyme and attached to five different types of NeutrAvidin-functionalized chip surfaces through a biotinylated spacer. All matrices are suitable for achieving a controlled enzyme surface density. Data obtained by SPR are in excellent agreement with those derived from optical waveguide measurements. Among the various protein-binding strategies investigated in this study, it was found that stiffness and order between alkanethiol-based SAMs and PEGylated surfaces are very important. Matrix D based on a Nb2O5 coating showed a satisfactory regeneration possibility. The surface-immobilized enzymes were found to be stable and sufficiently active enough for a catalytic activity assay. Many factors, such as the steric crowding effect of surface-attached enzymes, the electrostatic interaction between the negatively charged substrate (Nitrocefin) and the polycationic PLL-g-PEG/PEG-Biotin polymer, mass transport effect, and enzyme orientation, are shown to influence the kinetic parameters of catalytic analysis. Furthermore, a home-built Surface Plasmon Resonance Spectrometer of SPR and a commercial miniature Fiber Optic Absorbance Spectrometer (FOAS), served as a combination set-up for affinity and catalytic biosensor, respectively. The parallel measurements offer the opportunity of on-line activity detection of surface attached enzymes. The immobilized enzyme does not have to be in contact with the catalytic biosensor. The SPR chip can easily be cleaned and used for recycling. Additionally, with regard to the application of FOAS, the integrated SPR technique allows for the quantitative control of the surface density of the enzyme, which is highly relevant for the enzymatic activity. Finally, the miniaturized portable FOAS devices can easily be combined as an add-on device with many other in situ interfacial detection techniques, such as optical waveguide lightmode spectroscopy (OWLS), the quartz crystal microbalance (QCM) measurements, or impedance spectroscopy (IS). Surface plasmon field-enhanced fluorescence spectroscopy (SPFS) allows for an absolute determination of intrinsic rate constants describing the true parameters that control interfacial hybridization. Thus it also allows for a study of the difference of the surface coupling influences between OMCVD gold particles and planar metal films presented in the second part. The multilayer growth process was found to proceed similarly to the way it occurs on planar metal substrates. In contrast to planar bulk metal surfaces, metal colloids exhibit a narrow UV-vis absorption band. This absorption band is observed if the incident photon frequency is resonant with the collective oscillation of the conduction electrons and is known as the localized surface plasmon resonance (LSPR). LSPR excitation results in extremely large molar extinction coefficients, which are due to a combination of both absorption and scattering. When considering metal-enhanced fluorescence we expect the absorption to cause quenching and the scattering to cause enhancement. Our further study will focus on the developing of a detection platform with larger gold particles, which will display a dominant scattering component and enhance the fluorescence signal. Furthermore, the results of sequence-specific detection of DNA hybridization based on OMCVD gold particles provide an excellent application potential for this kind of cheap, simple, and mild preparation protocol applied in this gold fabrication method. In the final chapter, SPFS was used for the in-depth characterizations of the conformational changes of commercial carboxymethyl dextran (CMD) substrate induced by pH and ionic strength variations were studied using surface plasmon resonance spectroscopy. The pH response of CMD is due to the changes in the electrostatics of the system between its protonated and deprotonated forms, while the ionic strength response is attributed from the charge screening effect of the cations that shield the charge of the carboxyl groups and prevent an efficient electrostatic repulsion. Additional studies were performed using SPFS with the aim of fluorophore labeling the carboxymethyl groups. CMD matrices showed typical pH and ionic strength responses, such as high pH and low ionic strength swelling. Furthermore, the effects of the surface charge and the crosslink density of the CMD matrix on the extent of stimuli responses were investigated. The swelling/collapse ratio decreased with decreasing surface concentration of the carboxyl groups and increasing crosslink density. The study of the CMD responses to external and internal variables will provide valuable background information for practical applications.

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An extensive sample (2%) of private vehicles in Italy are equipped with a GPS device that periodically measures their position and dynamical state for insurance purposes. Having access to this type of data allows to develop theoretical and practical applications of great interest: the real-time reconstruction of traffic state in a certain region, the development of accurate models of vehicle dynamics, the study of the cognitive dynamics of drivers. In order for these applications to be possible, we first need to develop the ability to reconstruct the paths taken by vehicles on the road network from the raw GPS data. In fact, these data are affected by positioning errors and they are often very distanced from each other (~2 Km). For these reasons, the task of path identification is not straightforward. This thesis describes the approach we followed to reliably identify vehicle paths from this kind of low-sampling data. The problem of matching data with roads is solved with a bayesian approach of maximum likelihood. While the identification of the path taken between two consecutive GPS measures is performed with a specifically developed optimal routing algorithm, based on A* algorithm. The procedure was applied on an off-line urban data sample and proved to be robust and accurate. Future developments will extend the procedure to real-time execution and nation-wide coverage.

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The complementary Watson-Crick base-pairs, A:T and G:C, have long been recognized as pivotal to both the stability of the DNA double helix and replication/transcription. Recently, the replacement of the Watson-Crick base-pairs with other molecular entities has received considerable attention. In this tutorial review we highlight different approaches used to replace natural base-pairs and equip them with novel function. We also discuss the advantages that non-natural base-pairs convey with respect to practical applications.

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Graphene, which is a two-dimensional carbon material, exhibits unique properties that promise its potential applications in photovoltaic devices. Dye-sensitized solar cell (DSSC) is a representative of the third generation photovoltaic devices. Therefore, it is important to synthesize graphene with special structures, which possess excellent properties for dye-sensitized solar cells. This dissertation research was focused on (1) the effect of oxygen content on the structure of graphite oxide, (2) the stability of graphene oxide solution, (3) the application of graphene precipitate from graphene oxide solution as counter electrode for DSSCs, (4) the development of a novel synthesis method for the three-dimensional graphene with honeycomb-like structure, and (5) the exploration of honeycomb structured graphene (HSG) as counter electrodes for DSSCs. Graphite oxide is a crucial precursor to synthesize graphene sheets via chemical exfoliation method. The relationship between the oxygen content and the structures of graphite oxides was still not explored. In this research, the oxygen content of graphite oxide is tuned by changing the oxidation time and the effect of oxygen content on the structure of graphite oxide was evaluated. It has been found that the saturated ratio of oxygen to carbon is 0.47. The types of functional groups in graphite oxides, which are epoxy, hydroxyl, and carboxylgroups, are independent of oxygen content. However, the interplanar space and BET surface area of graphite oxide linearly increases with increasing O/C ratio. Graphene oxide (GO) can easily dissolve in water to form a stable homogeneous solution, which can be used to fabricate graphene films and graphene based composites. This work is the first research to evaluate the stability of graphene oxide solution. It has been found that the introduction of strong electrolytes (HCl, LiOH, LiCl) into GO solution can cause GO precipitation. This indicates that the electrostatic repulsion plays a critical role in stabilizing aqueous GO solution. Furthermore, the HCl-induced GO precipitation is a feasible approach to deposit GO sheets on a substrate as a Pt-free counter electrode for a dye-sensitized solar cell (DSSC), which exhibited 1.65% of power conversion efficiency. To explore broad and practical applications, large-scale synthesis with controllable integration of individual graphene sheets is essential. A novel strategy for the synthesis of graphene sheets with three-dimensional (3D) Honeycomb-like structure has been invented in this project based on a simple and novel chemical reaction (Li2O and CO to graphene and Li2CO3). The simultaneous formation of Li2CO3 with graphene not only can isolate graphene sheets from each other to prevent graphite formation during the process, but also determine the locally curved shape of graphene sheets. After removing Li2CO3, 3D graphene sheets with a honeycomb-like structure were obtained. This would be the first approach to synthesize 3D graphene sheets with a controllable shape. Furthermore, it has been demonstrated that the 3D Honeycomb-Structured Graphene (HSG) possesses excellent electrical conductivity and high catalytic activity. As a result, DSSCs with HSG counter electrodes exhibit energy conversion efficiency as high as 7.8%, which is comparable to that of an expensive noble Pt electrode.

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We present a new thermodynamic activity-composition model for di-trioctahedral chlorite in the system FeO–MgO–Al2O3–SiO2–H2O that is based on the Holland–Powell internally consistent thermodynamic data set. The model is formulated in terms of four linearly independent end-members, which are amesite, clinochlore, daphnite and sudoite. These account for the most important crystal-chemical substitutions in chlorite, the Fe–Mg, Tschermak and di-trioctahedral substitution. The ideal part of end-member activities is modeled with a mixing-on-site formalism, and non-ideality is described by a macroscopic symmetric (regular) formalism. The symmetric interaction parameters were calibrated using a set of 271 published chlorite analyses for which robust independent temperature estimates are available. In addition, adjustment of the standard state thermodynamic properties of sudoite was required to accurately reproduce experimental brackets involving sudoite. This new model was tested by calculating representative P–T sections for metasediments at low temperatures (<400 °C), in particular sudoite and chlorite bearing metapelites from Crete. Comparison between the calculated mineral assemblages and field data shows that the new model is able to predict the coexistence of chlorite and sudoite at low metamorphic temperatures. The predicted lower limit of the chloritoid stability field is also in better agreement with petrological observations. For practical applications to metamorphic and hydrothermal environments, two new semi-empirical chlorite geothermometers named Chl(1) and Chl(2) were calibrated based on the chlorite + quartz + water equilibrium (2 clinochlore + 3 sudoite = 4 amesite + 4 H2O + 7 quartz). The Chl(1) thermometer requires knowledge of the (Fe3+/ΣFe) ratio in chlorite and predicts correct temperatures for a range of redox conditions. The Chl(2) geothermometer which assumes that all iron in chlorite is ferrous has been applied to partially recrystallized detrital chlorite from the Zone houillère in the French Western Alps.

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After a brief review of some old concepts getting application when new technologies have been developed, this paper offers a short review to some optical bistability concepts. It is shown how different concepts can be employed today in many fields, after being considered as inconvenient when they were found. Some practical applications and some proposals will be reported.

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Esta tesis establece los fundamentos teóricos y diseña una colección abierta de clases C++ denominada VBF (Vector Boolean Functions) para analizar funciones booleanas vectoriales (funciones que asocian un vector booleano a otro vector booleano) desde una perspectiva criptográfica. Esta nueva implementación emplea la librería NTL de Victor Shoup, incorporando nuevos módulos que complementan a las funciones de NTL, adecuándolas para el análisis criptográfico. La clase fundamental que representa una función booleana vectorial se puede inicializar de manera muy flexible mediante diferentes estructuras de datas tales como la Tabla de verdad, la Representación de traza y la Forma algebraica normal entre otras. De esta manera VBF permite evaluar los criterios criptográficos más relevantes de los algoritmos de cifra en bloque y de stream, así como funciones hash: por ejemplo, proporciona la no-linealidad, la distancia lineal, el grado algebraico, las estructuras lineales, la distribución de frecuencias de los valores absolutos del espectro Walsh o del espectro de autocorrelación, entre otros criterios. Adicionalmente, VBF puede llevar a cabo operaciones entre funciones booleanas vectoriales tales como la comprobación de igualdad, la composición, la inversión, la suma, la suma directa, el bricklayering (aplicación paralela de funciones booleanas vectoriales como la empleada en el algoritmo de cifra Rijndael), y la adición de funciones coordenada. La tesis también muestra el empleo de la librería VBF en dos aplicaciones prácticas. Por un lado, se han analizado las características más relevantes de los sistemas de cifra en bloque. Por otro lado, combinando VBF con algoritmos de optimización, se han diseñado funciones booleanas cuyas propiedades criptográficas son las mejores conocidas hasta la fecha. ABSTRACT This thesis develops the theoretical foundations and designs an open collection of C++ classes, called VBF, designed for analyzing vector Boolean functions (functions that map a Boolean vector to another Boolean vector) from a cryptographic perspective. This new implementation uses the NTL library from Victor Shoup, adding new modules which complement the existing ones making VBF better suited for cryptography. The fundamental class representing a vector Boolean function can be initialized in a flexible way via several alternative types of data structures such as Truth Table, Trace Representation, Algebraic Normal Form (ANF) among others. This way, VBF allows the evaluation of the most relevant cryptographic criteria for block and stream ciphers as well as for hash functions: for instance, it provides the nonlinearity, the linearity distance, the algebraic degree, the linear structures, the frequency distribution of the absolute values of the Walsh Spectrum or the Autocorrelation Spectrum, among others. In addition, VBF can perform operations such as equality testing, composition, inversion, sum, direct sum, bricklayering (parallel application of vector Boolean functions as employed in Rijndael cipher), and adding coordinate functions of two vector Boolean functions. This thesis also illustrates the use of VBF in two practical applications. On the one hand, the most relevant properties of the existing block ciphers have been analysed. On the other hand, by combining VBF with optimization algorithms, new Boolean functions have been designed which have the best known cryptographic properties up-to-date.

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Thesis (Ph.D.)--University of Washington, 2016-06

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This paper reviews the recent developments in the mechanics of superplasticity and its applications in industrial practice. After introducing the phenomena of superplasticity, the basic experiments for determining material deformation behavior and related parameters, and constructing superplastic constitutive equations, are reviewed. Finite element related formulations and techniques for simulating superplastic forming are discussed, together with some practical applications. (C) 2004 Elsevier B.V. All rights reserved.

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While molecular and cellular processes are often modeled as stochastic processes, such as Brownian motion, chemical reaction networks and gene regulatory networks, there are few attempts to program a molecular-scale process to physically implement stochastic processes. DNA has been used as a substrate for programming molecular interactions, but its applications are restricted to deterministic functions and unfavorable properties such as slow processing, thermal annealing, aqueous solvents and difficult readout limit them to proof-of-concept purposes. To date, whether there exists a molecular process that can be programmed to implement stochastic processes for practical applications remains unknown.

In this dissertation, a fully specified Resonance Energy Transfer (RET) network between chromophores is accurately fabricated via DNA self-assembly, and the exciton dynamics in the RET network physically implement a stochastic process, specifically a continuous-time Markov chain (CTMC), which has a direct mapping to the physical geometry of the chromophore network. Excited by a light source, a RET network generates random samples in the temporal domain in the form of fluorescence photons which can be detected by a photon detector. The intrinsic sampling distribution of a RET network is derived as a phase-type distribution configured by its CTMC model. The conclusion is that the exciton dynamics in a RET network implement a general and important class of stochastic processes that can be directly and accurately programmed and used for practical applications of photonics and optoelectronics. Different approaches to using RET networks exist with vast potential applications. As an entropy source that can directly generate samples from virtually arbitrary distributions, RET networks can benefit applications that rely on generating random samples such as 1) fluorescent taggants and 2) stochastic computing.

By using RET networks between chromophores to implement fluorescent taggants with temporally coded signatures, the taggant design is not constrained by resolvable dyes and has a significantly larger coding capacity than spectrally or lifetime coded fluorescent taggants. Meanwhile, the taggant detection process becomes highly efficient, and the Maximum Likelihood Estimation (MLE) based taggant identification guarantees high accuracy even with only a few hundred detected photons.

Meanwhile, RET-based sampling units (RSU) can be constructed to accelerate probabilistic algorithms for wide applications in machine learning and data analytics. Because probabilistic algorithms often rely on iteratively sampling from parameterized distributions, they can be inefficient in practice on the deterministic hardware traditional computers use, especially for high-dimensional and complex problems. As an efficient universal sampling unit, the proposed RSU can be integrated into a processor / GPU as specialized functional units or organized as a discrete accelerator to bring substantial speedups and power savings.

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Ill-conditioned inverse problems frequently arise in life sciences, particularly in the context of image deblurring and medical image reconstruction. These problems have been addressed through iterative variational algorithms, which regularize the reconstruction by adding prior knowledge about the problem's solution. Despite the theoretical reliability of these methods, their practical utility is constrained by the time required to converge. Recently, the advent of neural networks allowed the development of reconstruction algorithms that can compute highly accurate solutions with minimal time demands. Regrettably, it is well-known that neural networks are sensitive to unexpected noise, and the quality of their reconstructions quickly deteriorates when the input is slightly perturbed. Modern efforts to address this challenge have led to the creation of massive neural network architectures, but this approach is unsustainable from both ecological and economic standpoints. The recently introduced GreenAI paradigm argues that developing sustainable neural network models is essential for practical applications. In this thesis, we aim to bridge the gap between theory and practice by introducing a novel framework that combines the reliability of model-based iterative algorithms with the speed and accuracy of end-to-end neural networks. Additionally, we demonstrate that our framework yields results comparable to state-of-the-art methods while using relatively small, sustainable models. In the first part of this thesis, we discuss the proposed framework from a theoretical perspective. We provide an extension of classical regularization theory, applicable in scenarios where neural networks are employed to solve inverse problems, and we show there exists a trade-off between accuracy and stability. Furthermore, we demonstrate the effectiveness of our methods in common life science-related scenarios. In the second part of the thesis, we initiate an exploration extending the proposed method into the probabilistic domain. We analyze some properties of deep generative models, revealing their potential applicability in addressing ill-posed inverse problems.

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O estudo teve como objetivo buscar evidências na literatura acerca da inclusão de crianças com Síndrome de Down na rede regular de ensino. Elaboraram-se revisão da literatura e busca dos artigos nas bases de dados PubMed e PsycINFO, utilizando as palavras-chave Down syndrome, schools, mainstreaming (education), education, infant, newborn, adolescent, child e preschool, no período de 1994 a 2007. Selecionaram-se oito artigos e sua análise permitiu a identificação do tema: experiências e recomendações para a inclusão. Os dados desta revisão, em sua maioria provenientes de relatos de experiências, indicaram que os fatores que colaboraram ou dificultaram o processo de inclusão da criança com síndrome de Down na rede regular de ensino relacionaram-se à escola, aos pais e ao professor. Os resultados deste estudo oferecem possibilidades para melhorar o processo de inclusão, apresentam os desafios e ainda apontam a necessidade do desenvolvimento de novas pesquisas, cujos resultados possam ser aplicados na prática.

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Bounds on the exchange-correlation energy of many-electron systems are derived and tested. By using universal scaling properties of the electron-electron interaction, we obtain the exponent of the bounds in three, two, one, and quasione dimensions. From the properties of the electron gas in the dilute regime, the tightest estimate to date is given for the numerical prefactor of the bound, which is crucial in practical applications. Numerical tests on various low-dimensional systems are in line with the bounds obtained and give evidence of an interesting dimensional crossover between two and one dimensions.