979 resultados para bio-optical


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In lake-rich regions, the gathering of information about water quality is challenging because only a small proportion of the lakes can be assessed each year by conventional methods. One of the techniques for improving the spatial and temporal representativeness of lake monitoring is remote sensing from satellites and aircrafts. The experimental material included detailed optical measurements in 11 lakes, air- and spaceborne remote sensing measurements with concurrent field sampling, automatic raft measurements and a national dataset of routine water quality measurements from over 1100 lakes. The analyses of the spatially high-resolution airborne remote sensing data from eutrophic and mesotrophic lakes showed that one or a few discrete water quality observations using conventional monitoring can yield a clear over- or underestimation of the overall water quality in a lake. The use of TM-type satellite instruments in addition to routine monitoring results substantially increases the number of lakes for which water quality information can be obtained. The preliminary results indicated that coloured dissolved organic matter (CDOM) can be estimated with TM-type satellite instruments, which could possibly be utilised as an aid in estimating the role of lakes in global carbon budgets. Based on the results of reflectance modelling and experimental data, MERIS satellite instrument has optimal or near-optimal channels for the estimation of turbidity, chlorophyll a and CDOM in Finnish lakes. MERIS images with a 300 m spatial resolution can provide water quality information in different parts of large and medium-sized lakes, and in filling in the gaps resulting from conventional monitoring. Algorithms that would not require simultaneous field data for algorithm training would increase the amount of remote sensing-based information available for lake monitoring. The MERIS Boreal Lakes processor, trained with the optical data and concentration ranges provided by this study, enabled turbidity estimations with good accuracy without the need for algorithm correction with field measurements, while chlorophyll a and CDOM estimations require further development of the processor. The accuracy of interpreting chlorophyll a via semi empirical algorithms can be improved by classifying lakes prior to interpretation according to their CDOM level and trophic status. Optical modelling indicated that the spectral diffuse attenuation coefficient can be estimated with reasonable accuracy from the measured water quality concentrations. This provides more detailed information on light attenuation from routine monitoring measurements than is available through the Secchi disk transparency. The results of this study improve the interpretation of lake water quality by remote sensing and encourage the use of remote sensing in lake monitoring.

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We report one-pot hydrothermal synthesis of nearly mono-disperse 3-mercaptopropionic acid capped water-soluble cadmium telluride (CdTe) quantum dots (QDs) using an air stable Te source. The optical and electrical characteristics were also studied here. It was shown that the hydrothermal synthesis could be tuned to synthesize nano structures of uniform size close to nanometers. The emissions of the CdTe QDs thus synthesized were in the range of 500-700 nm by varying the duration of synthesis. The full width at half maximum (FWHM) of the emission peaks is relatively narrow (40-90 nm), which indicates a nearly uniform distribution of QD size. The structural and optical properties of the QDs were characterized by transmission electron microscopy (TEM), photoluminescence (PL) and Ultraviolet-visible (UV-Vis) spectroscopy. The photoluminescence quenching of CdTe QDs in the presence of L-cysteine and DNA confirms its biocompatibility and its utility for biosensing applications. The room temperature current-voltage characteristics of QD film on ITO coated glass substrate show an electrically induced switching between states with high and low conductivities. The phenomenon is explained on the basis of charge confinement in quantum dots. (C) 2011 Elsevier B.V. All rights reserved.

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Recent advances in nanotechnology have paved ways to various techniques for designing and fabricating novel nanostructures incorporating noble metal nanoparticles, for a wide range of applications. The interaction of light with metal nanoparticles (NPs) can generate strongly localized electromagnetic fields (Localized Surface Plasmon Resonance, LSPR) at certain wavelengths of the incident beam. In assemblies or structures where the nanoparticles are placed in close proximity, the plasmons of individual metallic NPs can be strongly coupled to each other via Coulomb interactions. By arranging the metallic NPs in a chiral (e.g. helical) geometry, it is possible to induce collective excitations, which lead to differential optical response of the structures to right-and left circularly polarized light (e.g. Circular Dichroism - CD). Earlier reports in this field include novel techniques of synthesizing metallic nanoparticles on biological helical templates made from DNA, proteins etc. In the present work, we have developed new ways of fabricating chiral complexes made of metallic NPs, which demonstrate a very strong chiro-optical response in the visible region of the electromagnetic spectrum. Using DDA (Discrete Dipole Approximation) simulations, we theoretically studied the conditions responsible for large and broadband chiro-optical response. This system may be used for various applications, for example those related to polarization control of visible light, sensing of proteins and other chiral bio-molecules, and many more.

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Protein-Chip as micro-assays for the determination of protein interaction, the analysis, the identification and the purification of proteins has large potential applications. The Optical Protein-Chip is able to detect the multi-interaction of proteins and multi-bio-activities of molecules directly and simultaneously with no labeling. The chip is a small matrix on solid substrate containing multi-micro-area prepared by microfabrication with photolithography or soft lithography for surface patterning, and processed with surface modification which includes the physical, chemical, and bio-chemical modifications, etc. The ligand immobilization, such as protein immobilization, especially the oriented immobilization with low steric hindrance and high bio-specific binding activity between ligand and receptor is used to form a sensing surface. Each area of the pattern is corresponding to only one bioactivity. The interval between the areas is non-bioactive and optically extinctive. The affinity between proteins is used to realize non-labeling microassays for the determination of protein identification and protein interaction. The sampling of the chip is non-disturbing, performed with imaging ellipsometry and image processing on a database of proteins.

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Optical Coherence Tomography(OCT) is a popular, rapidly growing imaging technique with an increasing number of bio-medical applications due to its noninvasive nature. However, there are three major challenges in understanding and improving an OCT system: (1) Obtaining an OCT image is not easy. It either takes a real medical experiment or requires days of computer simulation. Without much data, it is difficult to study the physical processes underlying OCT imaging of different objects simply because there aren't many imaged objects. (2) Interpretation of an OCT image is also hard. This challenge is more profound than it appears. For instance, it would require a trained expert to tell from an OCT image of human skin whether there is a lesion or not. This is expensive in its own right, but even the expert cannot be sure about the exact size of the lesion or the width of the various skin layers. The take-away message is that analyzing an OCT image even from a high level would usually require a trained expert, and pixel-level interpretation is simply unrealistic. The reason is simple: we have OCT images but not their underlying ground-truth structure, so there is nothing to learn from. (3) The imaging depth of OCT is very limited (millimeter or sub-millimeter on human tissues). While OCT utilizes infrared light for illumination to stay noninvasive, the downside of this is that photons at such long wavelengths can only penetrate a limited depth into the tissue before getting back-scattered. To image a particular region of a tissue, photons first need to reach that region. As a result, OCT signals from deeper regions of the tissue are both weak (since few photons reached there) and distorted (due to multiple scatterings of the contributing photons). This fact alone makes OCT images very hard to interpret.

This thesis addresses the above challenges by successfully developing an advanced Monte Carlo simulation platform which is 10000 times faster than the state-of-the-art simulator in the literature, bringing down the simulation time from 360 hours to a single minute. This powerful simulation tool not only enables us to efficiently generate as many OCT images of objects with arbitrary structure and shape as we want on a common desktop computer, but it also provides us the underlying ground-truth of the simulated images at the same time because we dictate them at the beginning of the simulation. This is one of the key contributions of this thesis. What allows us to build such a powerful simulation tool includes a thorough understanding of the signal formation process, clever implementation of the importance sampling/photon splitting procedure, efficient use of a voxel-based mesh system in determining photon-mesh interception, and a parallel computation of different A-scans that consist a full OCT image, among other programming and mathematical tricks, which will be explained in detail later in the thesis.

Next we aim at the inverse problem: given an OCT image, predict/reconstruct its ground-truth structure on a pixel level. By solving this problem we would be able to interpret an OCT image completely and precisely without the help from a trained expert. It turns out that we can do much better. For simple structures we are able to reconstruct the ground-truth of an OCT image more than 98% correctly, and for more complicated structures (e.g., a multi-layered brain structure) we are looking at 93%. We achieved this through extensive uses of Machine Learning. The success of the Monte Carlo simulation already puts us in a great position by providing us with a great deal of data (effectively unlimited), in the form of (image, truth) pairs. Through a transformation of the high-dimensional response variable, we convert the learning task into a multi-output multi-class classification problem and a multi-output regression problem. We then build a hierarchy architecture of machine learning models (committee of experts) and train different parts of the architecture with specifically designed data sets. In prediction, an unseen OCT image first goes through a classification model to determine its structure (e.g., the number and the types of layers present in the image); then the image is handed to a regression model that is trained specifically for that particular structure to predict the length of the different layers and by doing so reconstruct the ground-truth of the image. We also demonstrate that ideas from Deep Learning can be useful to further improve the performance.

It is worth pointing out that solving the inverse problem automatically improves the imaging depth, since previously the lower half of an OCT image (i.e., greater depth) can be hardly seen but now becomes fully resolved. Interestingly, although OCT signals consisting the lower half of the image are weak, messy, and uninterpretable to human eyes, they still carry enough information which when fed into a well-trained machine learning model spits out precisely the true structure of the object being imaged. This is just another case where Artificial Intelligence (AI) outperforms human. To the best knowledge of the author, this thesis is not only a success but also the first attempt to reconstruct an OCT image at a pixel level. To even give a try on this kind of task, it would require fully annotated OCT images and a lot of them (hundreds or even thousands). This is clearly impossible without a powerful simulation tool like the one developed in this thesis.

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InN nanostructures with and without GaN capping layers were grown by using metal-organic chemical vapor deposition. Morphological, structural, and optical properties were systematically studied by using atomic force microscopy, X-ray diffraction (XRD) and temperature-dependent photoluminescence (PL). XRD results show that an InGaN structure is formed for the sample with a GaN capping layer, which will reduce the quality and the IR PL emission of the InN. The lower emission peak at similar to 0.7 eV was theoretically fitted and assigned as the band edge emission of InN. Temperature-dependent PL shows a good quantum efficiency for the sample without a GaN capping layers; this corresponds to a lower density of dislocations and a small activation energy.

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In this work we present core–shell nanowire arrays of gold coated with a nanometric layer of cobalt. Despite the extremely small Co volume, these core–shell nanowires display large magneto-optical activity and plasmonic resonance determined by the geometry of the structure. Therefore, we are able to tune both the plasmonic and magneto-optical response in the visible range. Through optical and ellipsometric measurements in transmission, and applying a magnetic field to the sample, it is possible to modulate the value of the phase angle (Del {Δ}) between the S and P polarised components. It was found that the core–shell sample produced an order of magnitude larger variation in Del with changing magnetic field direction, compared with hollow cobalt tubes. The enhancement of magneto optical properties through the plasmonic nature of the gold core is complemented with the ability to induce magnetic influence over optical properties via an externally applied field. Moreover, we demonstrate for the first time the ability to use the remanent magnetisation of the Co, in conjunction with the optical properties defined by the Au, to observe remanent optical states in this uniquely designed structure. This new class of magnetoplasmonic metamaterial has great potential in a wide range of applications, from bio-sensing to data storage due to the tuneable nature of multiple resonance modes and dual functionality.

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Esta tese descreve diversas estratégias preparativas assim como estudos de caracterização de nanocompósitos e outras nanoestruturas, para a análise em espectroscopia de Raman com intensificação por superfície (SERS). Em particular foi estudada a incorporação de nanopartículas (NPs) metálicas de Ag e Au em matrizes poliméricas visando avaliar o potencial destes materiais como novos substratos para SERS na deteção de moléculas. O primeiro capítulo consiste numa revisão bibliográfica, onde é destacado o desenvolvimento de novos substratos para SERS utilizando nomeadamente nanopartículas de Ag, Au e Cu. Numa primeira fase, esta secção apresenta uma breve descrição sobre as propriedades plasmónicas dos metais utilizados e alguns conceitos básicos de espectroscopia de difusão de Raman. Posteriormente, descreve-se em mais detalhe o efeito de SERS, revendo-se sobretudo a química de materiais descrita em trabalhos recentes tendo em conta a sua utilização como novas plataformas para análise química por SERS. O capítulo 2 descreve a síntese e caracterização de nanocompósitos de poli(acrilato de butilo) obtidos através de polimerização in situ por miniemulsão na presença de nanopartículas de Ag. Os nanocompósitos Ag/PtBA foram investigados como novos substratos de SERS visando o desenvolvimento de novas plataformas versáteis para deteção molecular. Estudos como o efeito da temperatura, pH e pressão foram investigados, visando a compreensão do efeito da matriz polimérica na difusão/adsorção do analito (ácido tiossalicílico) na superfície metálica. No capítulo 3, os nanocompósitos de Ag/PtBA descritos anteriormente foram investigados detalhadamente como substratos para bio-deteção em SERS, usando a adenina como analito modelo. Os nanocompósitos foram submetidos a vários tratamentos pré-analíticos para a bio-deteção da adenina. Foram realizadas experiências nos sistemas Ag/PtBA de modo a obter informação sobre o efeito do pH na deteção deste analito em soluções aquosas diluídas. Os nanocompósitos poliméricos obtidos apresentam a vantagem de poderem ser processados utilizando tecnologia disponível. Pelo que o estudo das suas propriedades térmicas é especialmente relevante. Assim, a influência da incorporação de NPs inorgânicas na temperatura de transição vítrea (Tg) do polímero PtBA foi investigada por meio de calorimetria diferencial de varrimento (DSC) e os resultados são apresentados no capítulo 4. Estes estudos descrevem efeitos na Tg do PtBA quando analisado em nanocompósitos obtidos por diferentes métodos (métodos ex situ e in situ), contendo nanopartículas metálicas com diferentes distribuições de tamanho e presentes em quantidade variável na matriz polimérica. Estes estudos possibilitaram relacionar a influência das NPs metálicas na mobilidade das cadeias poliméricas com as propriedades térmicas observadas. O capítulo 5 descreve a preparação e caracterização de materiais compósitos de base polimérica (PtBA) e NPs de Au com morfologia de bastonetes (NRs). Estes materiais foram investigados como substratos para SERS tendo originado um bom sinal de SERS na análise de 2-2’-ditiodipiridina. Investigouse igualmente o efeito da variação da morfologia das NPs metálicas (esferas e bastonetes), a razão de aspecto (R.A.) dos bastonetes e o tipo de matriz polimérica (PtBA e PnBA) no sinal de SERS. No capítulo 6 é descrita a utilização da técnica de SERS como método alternativo para a monitorização de alterações morfológicas de coloides de NRs de Au. Os NRs de Au foram recolhidos em diferentes fases de oxidação promovida pela presença de K2S2O8 e a sua sensibilidade como substratos de SERS foi avaliada utilizando o anião dietilditiocarbamato (DTC) como analito modelo. Os estudos foram realizados utilizando as linhas de excitação a 1064 nm e 633 nm. Este estudo demonstrou que a sensibilidade dos NRs de Au como substratos de SERS diminui à medida que a sua R.A. diminui devido à competitividade do CTAB (estabilizante) e o DTC pela superfície dos NRs. É de salientar que este processo é acompanhado por um diferente comportamento em termos de adsorção dos dois tautómeros do DTC à superfície do metal. O capítulo 7 introduz um novo tipo de compósitos para SERS, utilizando matrizes biopoliméricas. Assim, descreve-se a preparação e caracterização de nanocompósitos de carragenano e NPs de Ag. Nesta secção é avaliada a utilização destes materiais como novos substratos para a análise em SERS, utilizando a 2-2’-ditiodipiridina como molécula modelo. Descrevem-se estudos pioneiros que procuram relacionar a dependência do sinal de SERS com a força do gel. Para tal, realizou-se um estudo sistemático aos nanobiocompósitos usados como substratos de SERS em diferentes condições analíticas e investigaram-se as suas propriedades reológicas. No capitulo 8 é descrita a investigação de nanocompósitos de Ag/Gelatina como substratos para SERS, utilizando o anião dietilditiocarbamato como analito modelo. Realizaram-se várias experiências para correlacionar a variação da força do gel com o aumento do sinal de SERS bem como a diferente adsorção dos dois tautómeros do DTC à superfície do metal. Ao longo desta dissertação são apresentados metodologias distintas para a preparação e obtenção de nanocompósitos com base em polímeros (sintéticos ou naturais) e NPs metálicas (Ag e Au). Esta investigação não só permitiu a síntese e estudo de novos substratos para SERS mas também a compreensão do efeito matriz/NPs metálicas no sinal de SERS e na formação de “hot spots”. Este trabalho contribui para o enriquecimento na área da Nanociência e Nanotecnologia demonstrando a eficácia e reprodutibilidade de nanocompósitos com base em polímeros como novos substratos para SERS. Embora as propriedades óticas apresentadas por estes materiais serem aqui direcionadas para a deteção molecular pela técnica de SERS, estes materiais podem ser investigados em outras área tecnológicas.

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Fluorescence is a powerful tool in biological research, the relevance of which relies greatly on the availability of sensitive and selective fluorescent probes. Nanometer sized fluorescent semiconductor materials have attracted considerable attention in recent years due to the high luminescence intensity, low photobleaching, large Stokes’ shift and high photochemical stability. The optical and spectroscopic features of nanoparticles make them very convincing alternatives to traditional fluorophores in a range of applications. Efficient surface capping agents make these nanocrystals bio-compatible. They can provide a novel platform on which many biomolecules such as DNA, RNA and proteins can be covalently linked. In the second phase of the present work, bio-compatible, fluorescent, manganese doped ZnS (ZnS:Mn) nanocrystals suitable for bioimaging applications have been developed and their cytocompatibility has been assessed. Functionalization of ZnS:Mn nanocrystals by safe materials results in considerable reduction of toxicity and allows conjugation with specific biomolecules. The highly fluorescent, bio-compatible and water- dispersible ZnS:Mn nanocrystals are found to be ideal fluorescent probes for biological labeling

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We discuss the parametrisation of am-plitude and phase genes corre-sponding to space encoded femto-second transients in the wavelet domain. Differential evolution is used to improve the speed of con-vergence of the genetic algorithm. We discuss prospects of bio-molecular control using such methodology.

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Visual motion cues play an important role in animal and humans locomotion without the need to extract actual ego-motion information. This paper demonstrates a method for estimating the visual motion parameters, namely the Time-To-Contact (TTC), Focus of Expansion (FOE), and image angular velocities, from a sparse optical flow estimation registered from a downward looking camera. The presented method is capable of estimating the visual motion parameters in a complicated 6 degrees of freedom motion and in real time with suitable accuracy for mobile robots visual navigation.

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ZnO thin films were prepared by the polymeric precursor method. The films were deposited on silicon substrates using the spin-coating technique, and were annealed at 330°C for 32h under pressure-assisted thermal annealing and under ambient pressure. Their structural and optical properties were characterized, and the phases formed were identified by X-ray diffraction. No secondary phase was detected. The ZnO thin films were also characterized by field-emission scanning electron microscopy, Fourier transform infrared spectroscopy, photoluminescence and ultraviolet emission intensity measurements. The effect of pressure on these thin films modifies the active defects that cause the recombination of deep level states located inside the band gap that emit yellow-green (575nm) and orange (645nm) photoluminescence. © 2012 John Wiley & Sons, Ltd.

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The paper presents a process of cellulose thermal degradation with bio-hydrogen generation and zinc nanostructures synthesis. Production of zinc nanowires and zinc nanoflowers was performed by a novel processes based on cellulose pyrolysis, volatiles reforming and direct reduction of ZnO. The bio-hydrogen generated in situ promoted the ZnO reduction with Zn nanostructures formation by vapor–solid (VS) route. The cellulose and cellulose/ZnO samples were characterized by thermal analyses (TG/DTG/DTA) and the gases evolved were analyzed by FTIR spectroscopy (TG/FTIR). The hydrogen was detected by TPR (Temperature Programmed Reaction) tests. The results showed that in the presence of ZnO the cellulose thermal degradation produced larger amounts of H2 when compared to pure cellulose. The process was also carried out in a tubular furnace with N2 atmosphere, at temperatures up to 900 °C, and different heating rates. The nanostructures growth was catalyst-free, without pressure reduction, at temperatures lower than those required in the carbothermal reduction of ZnO with fossil carbon. The nanostructures were investigated by X-ray diffraction (XRD), scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS) and transmission electron microscopy (TEM). The optical properties were investigated by photoluminescence (PL). One mechanism was presented in an attempt to explain the synthesis of zinc nanostructures that are crystalline, were obtained without significant re-oxidation and whose morphologies are dependent on the heating rates of the process. This route presents a potential use as an industrial process taking into account the simple operational conditions, the low costs of cellulose and the importance of bio-hydrogen and nanostructured zinc.

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Physicochemical experimental techniques combined with the specificity of a biological recognition system have resulted in a variety of new analytical devices known as biosensors. Biosensors are under intensive development worldwide because they have many potential applications, e.g. in the fields of clinical diagnostics, food analysis, and environmental monitoring. Much effort is spent on the development of highly sensitive sensor platforms to study interactions on the molecular scale. In the first part, this thesis focuses on exploiting the biosensing application of nanoporous gold (NPG) membranes. NPG with randomly distributed nanopores (pore sizes less than 50 nm) will be discussed here. The NPG membrane shows unique plasmonic features, i.e. it supports both propagating and localized surface plasmon resonance modes (p SPR and l-SPR, respectively), both offering sensitive probing of the local refractive index variation on/in NPG. Surface refractive index sensors have an inherent advantage over fluorescence optical biosensors that require a chromophoric group or other luminescence label to transduce the binding event. In the second part, gold/silica composite inverse opals with macroporous structures were investigated with bio- or chemical sensing applications in mind. These samples combined the advantages of a larger available gold surface area with a regular and highly ordered grating structure. The signal of the plasmon was less noisy in these ordered substrate structures compared to the random pore structures of the NPG samples. In the third part of the thesis, surface plasmon resonance (SPR) spectroscopy was applied to probe the protein-protein interaction of the calcium binding protein centrin with the heterotrimeric G-protein transducin on a newly designed sensor platform. SPR spectroscopy was intended to elucidate how the binding of centrin to transducin is regulated towards understanding centrin functions in photoreceptor cells.