914 resultados para High-dimensional index structure


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The branched vs. isoprenoid tetraether (BIT) index is based on the relative abundance of branched tetraether lipids (brGDGTs) and the isoprenoidal GDGT crenarchaeol. In Lake Challa sediments the BIT index has been applied as a proxy for local monsoon precipitation on the assumption that the primary source of brGDGTs is soil washed in from the lake's catchment. Since then, microbial production within the water column has been identified as the primary source of brGDGTs in Lake Challa sediments, meaning that either an alternative mechanism links BIT index variation with rainfall or that the proxy's application must be reconsidered. We investigated GDGT concentrations and BIT index variation in Lake Challa sediments at a decadal resolution over the past 2200 years, in combination with GDGT time-series data from 45 monthly sediment-trap samples and a chronosequence of profundal surface sediments.

Our 2200-year geochemical record reveals high-frequency variability in GDGT concentrations, and therefore in the BIT index, superimposed on distinct lower-frequency fluctuations at multi-decadal to century timescales. These changes in BIT index are correlated with changes in the concentration of crenarchaeol but not with those of the brGDGTs. A clue for understanding the indirect link between rainfall and crenarchaeol concentration (and thus thaumarchaeotal abundance) was provided by the observation that surface sediments collected in January 2010 show a distinct shift in GDGT composition relative to sediments collected in August 2007. This shift is associated with increased bulk flux of settling mineral particles with high Ti / Al ratios during March–April 2008, reflecting an event of unusually high detrital input to Lake Challa concurrent with intense precipitation at the onset of the principal rain season that year. Although brGDGT distributions in the settling material are initially unaffected, this soil-erosion event is succeeded by a massive dry-season diatom bloom in July–September 2008 and a concurrent increase in the flux of GDGT-0. Complete absence of crenarchaeol in settling particles during the austral summer following this bloom indicates that no Thaumarchaeota bloom developed at that time. We suggest that increased nutrient availability, derived from the eroded soil washed into the lake, caused the massive bloom of diatoms and that the higher concentrations of ammonium (formed from breakdown of this algal matter) resulted in a replacement of nitrifying Thaumarchaeota, which in typical years prosper during the austral summer, by nitrifying bacteria. The decomposing dead diatoms passing through the suboxic zone of the water column probably also formed a substrate for GDGT-0-producing archaea. Hence, through a cascade of events, intensive rainfall affects thaumarchaeotal abundance, resulting in high BIT index values.

Decade-scale BIT index fluctuations in Lake Challa sediments exactly match the timing of three known episodes of prolonged regional drought within the past 250 years. Additionally, the principal trends of inferred rainfall variability over the past two millennia are consistent with the hydroclimatic history of equatorial East Africa, as has been documented from other (but less well dated) regional lake records. We therefore propose that variation in GDGT production originating from the episodic recurrence of strong soil-erosion events, when integrated over (multi-)decadal and longer timescales, generates a stable positive relationship between the sedimentary BIT index and monsoon rainfall at Lake Challa. Application of this paleoprecipitation proxy at other sites requires ascertaining the local processes which affect the productivity of crenarchaeol by Thaumarchaeota and brGDGTs.

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Among various optical sensing schemes, infrared spectroscopy is a powerful tool for detecting and determining the composition of complex organic samples since vibrational finger prints of all biomolecules and organic species are located in this window. This spectroscopic technique is simple, reliable, fast, non-destructive, cost-effective while having low sensitivity. Use of metallic nanoparticles in association with a good IR transparent sensing substrate, is one of the promising solutions to enhance the sensitivity. Chalcogenide glasses are promising substrate material because of their extended optical transmission window starting from the visible to the far infrared range up to 20 μm, high refractive index usually between 2 and 3 and high optical nonlinearity, which make them good candidates as IR sensors and optical ultrafast nonlinear devices. These glasses are favorable sensor materials for the infrared spectral range because of their high IR transparency to allow for low optical loss at wavelengths corresponding to the characteristic optical absorption bands of organic molecules, high refractive index for tight confinement of optical energy within the resonator structure, processibility into thin film form, chemical compatibility for adhesion of silver nano particles and thin films and resistance to the chemical environment to be sensed. Molecules adsorbed to silver island structures shows enhanced IR absorption spectra and the extent of enhancement is determined by many factors such as the size, density and morphology of silver structures, optical and dielectric properties of the substrate material etc.

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The semiconductor industry's urge towards faster, smaller and cheaper integrated circuits has lead the industry to smaller node devices. The integrated circuits that are now under volume production belong to 22 nm and 14 nm technology nodes. In 2007 the 45 nm technology came with the revolutionary high- /metal gate structure. 22 nm technology utilizes fully depleted tri-gate transistor structure. The 14 nm technology is a continuation of the 22 nm technology. Intel is using second generation tri-gate technology in 14 nm devices. After 14 nm, the semiconductor industry is expected to continue the scaling with 10 nm devices followed by 7 nm. Recently, IBM has announced successful production of 7 nm node test chips. This is the fashion how nanoelectronics industry is proceeding with its scaling trend. For the present node of technologies selective deposition and selective removal of the materials are required. Atomic layer deposition and the atomic layer etching are the respective techniques used for selective deposition and selective removal. Atomic layer deposition still remains as a futuristic manufacturing approach that deposits materials and lms in exact places. In addition to the nano/microelectronics industry, ALD is also widening its application areas and acceptance. The usage of ALD equipments in industry exhibits a diversi cation trend. With this trend, large area, batch processing, particle ALD and plasma enhanced like ALD equipments are becoming prominent in industrial applications. In this work, the development of an atomic layer deposition tool with microwave plasma capability is described, which is a ordable even for lightly funded research labs.

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Thesis (Ph.D.)--University of Washington, 2016-08

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Internet users consume online targeted advertising based on information collected about them and voluntarily share personal information in social networks. Sensor information and data from smart-phones is collected and used by applications, sometimes in unclear ways. As it happens today with smartphones, in the near future sensors will be shipped in all types of connected devices, enabling ubiquitous information gathering from the physical environment, enabling the vision of Ambient Intelligence. The value of gathered data, if not obvious, can be harnessed through data mining techniques and put to use by enabling personalized and tailored services as well as business intelligence practices, fueling the digital economy. However, the ever-expanding information gathering and use undermines the privacy conceptions of the past. Natural social practices of managing privacy in daily relations are overridden by socially-awkward communication tools, service providers struggle with security issues resulting in harmful data leaks, governments use mass surveillance techniques, the incentives of the digital economy threaten consumer privacy, and the advancement of consumergrade data-gathering technology enables new inter-personal abuses. A wide range of fields attempts to address technology-related privacy problems, however they vary immensely in terms of assumptions, scope and approach. Privacy of future use cases is typically handled vertically, instead of building upon previous work that can be re-contextualized, while current privacy problems are typically addressed per type in a more focused way. Because significant effort was required to make sense of the relations and structure of privacy-related work, this thesis attempts to transmit a structured view of it. It is multi-disciplinary - from cryptography to economics, including distributed systems and information theory - and addresses privacy issues of different natures. As existing work is framed and discussed, the contributions to the state-of-theart done in the scope of this thesis are presented. The contributions add to five distinct areas: 1) identity in distributed systems; 2) future context-aware services; 3) event-based context management; 4) low-latency information flow control; 5) high-dimensional dataset anonymity. Finally, having laid out such landscape of the privacy-preserving work, the current and future privacy challenges are discussed, considering not only technical but also socio-economic perspectives.

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Nowadays, new computers generation provides a high performance that enables to build computationally expensive computer vision applications applied to mobile robotics. Building a map of the environment is a common task of a robot and is an essential part to allow the robots to move through these environments. Traditionally, mobile robots used a combination of several sensors from different technologies. Lasers, sonars and contact sensors have been typically used in any mobile robotic architecture, however color cameras are an important sensor due to we want the robots to use the same information that humans to sense and move through the different environments. Color cameras are cheap and flexible but a lot of work need to be done to give robots enough visual understanding of the scenes. Computer vision algorithms are computational complex problems but nowadays robots have access to different and powerful architectures that can be used for mobile robotics purposes. The advent of low-cost RGB-D sensors like Microsoft Kinect which provide 3D colored point clouds at high frame rates made the computer vision even more relevant in the mobile robotics field. The combination of visual and 3D data allows the systems to use both computer vision and 3D processing and therefore to be aware of more details of the surrounding environment. The research described in this thesis was motivated by the need of scene mapping. Being aware of the surrounding environment is a key feature in many mobile robotics applications from simple robotic navigation to complex surveillance applications. In addition, the acquisition of a 3D model of the scenes is useful in many areas as video games scene modeling where well-known places are reconstructed and added to game systems or advertising where once you get the 3D model of one room the system can add furniture pieces using augmented reality techniques. In this thesis we perform an experimental study of the state-of-the-art registration methods to find which one fits better to our scene mapping purposes. Different methods are tested and analyzed on different scene distributions of visual and geometry appearance. In addition, this thesis proposes two methods for 3d data compression and representation of 3D maps. Our 3D representation proposal is based on the use of Growing Neural Gas (GNG) method. This Self-Organizing Maps (SOMs) has been successfully used for clustering, pattern recognition and topology representation of various kind of data. Until now, Self-Organizing Maps have been primarily computed offline and their application in 3D data has mainly focused on free noise models without considering time constraints. Self-organising neural models have the ability to provide a good representation of the input space. In particular, the Growing Neural Gas (GNG) is a suitable model because of its flexibility, rapid adaptation and excellent quality of representation. However, this type of learning is time consuming, specially for high-dimensional input data. Since real applications often work under time constraints, it is necessary to adapt the learning process in order to complete it in a predefined time. This thesis proposes a hardware implementation leveraging the computing power of modern GPUs which takes advantage of a new paradigm coined as General-Purpose Computing on Graphics Processing Units (GPGPU). Our proposed geometrical 3D compression method seeks to reduce the 3D information using plane detection as basic structure to compress the data. This is due to our target environments are man-made and therefore there are a lot of points that belong to a plane surface. Our proposed method is able to get good compression results in those man-made scenarios. The detected and compressed planes can be also used in other applications as surface reconstruction or plane-based registration algorithms. Finally, we have also demonstrated the goodness of the GPU technologies getting a high performance implementation of a CAD/CAM common technique called Virtual Digitizing.

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Recent marine long-offset transient electromagnetic (LOTEM) measurements yielded the offshore delineation of a fresh groundwater body beneath the seafloor in the region of Bat Yam, Israel. The LOTEM application was effective in detecting this freshwater body underneath the Mediterranean Sea and allowed an estimation of its seaward extent. However, the measured data set was insufficient to understand the hydrogeological configuration and mechanism controlling the occurrence of this fresh groundwater discovery. Especially the lateral geometry of the freshwater boundary, important for the hydrogeological modelling, could not be resolved. Without such an understanding, a rational management of this unexploited groundwater reservoir is not possible. Two new high-resolution marine time-domain electromagnetic methods are theoretically developed to derive the hydrogeological structure of the western aquifer boundary. The first is called Circular Electric Dipole (CED). It is the land-based analogous of the Vertical Electric Dipole (VED), which is commonly applied to detect resistive structures in the subsurface. Although the CED shows exceptional detectability characteristics in the step-off signal towards the sub-seafloor freshwater body, an actual application was not carried out in the extent of this study. It was found that the method suffers from an insufficient signal strength to adequately delineate the resistive aquifer under realistic noise conditions. Moreover, modelling studies demonstrated that severe signal distortions are caused by the slightest geometrical inaccuracies. As a result, a successful application of CED in Israel proved to be rather doubtful. A second method called Differential Electric Dipole (DED) is developed as an alternative to the intended CED method. Compared to the conventional marine time-domain electromagnetic system that commonly applies a horizontal electric dipole transmitter, the DED is composed of two horizontal electric dipoles in an in-line configuration that share a common central electrode. Theoretically, DED has similar detectability/resolution characteristics compared to the conventional LOTEM system. However, the superior lateral resolution towards multi-dimensional resistivity structures make an application desirable. Furthermore, the method is less susceptible towards geometrical errors making an application in Israel feasible. In the extent of this thesis, the novel marine DED method is substantiated using several one-dimensional (1D) and multi-dimensional (2D/3D) modelling studies. The main emphasis lies on the application in Israel. Preliminary resistivity models are derived from the previous marine LOTEM measurement and tested for a DED application. The DED method is effective in locating the two-dimensional resistivity structure at the western aquifer boundary. Moreover, a prediction regarding the hydrogeological boundary conditions are feasible, provided a brackish water zone exists at the head of the interface. A seafloor-based DED transmitter/receiver system is designed and built at the Institute of Geophysics and Meteorology at the University of Cologne. The first DED measurements were carried out in Israel in April 2016. The acquired data set is the first of its kind. The measured data is processed and subsequently interpreted using 1D inversion. The intended aim of interpreting both step-on and step-off signals failed, due to the insufficient data quality of the latter. Yet, the 1D inversion models of the DED step-on signals clearly detect the freshwater body for receivers located close to the Israeli coast. Additionally, a lateral resistivity contrast is observable in the 1D inversion models that allow to constrain the seaward extent of this freshwater body. A large-scale 2D modelling study followed the 1D interpretation. In total, 425 600 forward calculations are conducted to find a sub-seafloor resistivity distribution that adequately explains the measured data. The results indicate that the western aquifer boundary is located at 3600 m - 3700 m before the coast. Moreover, a brackish water zone of 3 Omega*m to 5 Omega*m with a lateral extent of less than 300 m is likely located at the head of the freshwater aquifer. Based on these results, it is predicted that the sub-seafloor freshwater body is indeed open to the sea and may be vulnerable to seawater intrusion.

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In these last years a great effort has been put in the development of new techniques for automatic object classification, also due to the consequences in many applications such as medical imaging or driverless cars. To this end, several mathematical models have been developed from logistic regression to neural networks. A crucial aspect of these so called classification algorithms is the use of algebraic tools to represent and approximate the input data. In this thesis, we examine two different models for image classification based on a particular tensor decomposition named Tensor-Train (TT) decomposition. The use of tensor approaches preserves the multidimensional structure of the data and the neighboring relations among pixels. Furthermore the Tensor-Train, differently from other tensor decompositions, does not suffer from the curse of dimensionality making it an extremely powerful strategy when dealing with high-dimensional data. It also allows data compression when combined with truncation strategies that reduce memory requirements without spoiling classification performance. The first model we propose is based on a direct decomposition of the database by means of the TT decomposition to find basis vectors used to classify a new object. The second model is a tensor dictionary learning model, based on the TT decomposition where the terms of the decomposition are estimated using a proximal alternating linearized minimization algorithm with a spectral stepsize.

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Some recent results regarding the global dynamical behaviour of the wake of circular cylinders and airfoils with massive separation are reviewed in this paper. In order to investigate the effect of interference, the three-dimensional instability modes are analysed for the flow around two circular cylinders in tandem. In the same way, the flow around a stalled airfoil is investigated in order to provide a better understanding of the three-dimensional characteristics of wakes forming downstream of a lifting body with massive separation. These results are compared with those found for an isolated cylinder. Some fundamental differences among these flows are discussed. (C) 2011 Elsevier Ltd. All rights reserved.

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We assess the effect of the choice of spanwise periodic length on simulations of the flow around a fixed circular cylinder. The Reynolds number is set to 400 because, at this value, both lift coefficient and shedding frequency show significant drop due to three-dimensional flow structures. From the analysis of the three-dimensionalities of the wake and of the integral quantities such as Strouhal number, RMS of lift coefficient and energy contained in the three-dimensional portion of the flow we obtain an estimate of the minimum spanwise length to satisfactorily represent the flow. Furthermore, we observe a distinct wake behavior when the spanwise length is approximately the mode B instability wavelength. (C) 2011 Elsevier Ltd. All rights reserved.

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Over the last decades, anti-resonant reflecting optical waveguides (ARROW) have been used in different integrated optics applications. In this type of waveguide, light confinement is partially achieved through an anti-resonant reflection. In this work, the simulation, fabrication and characterization of ARROW waveguides using dielectric films deposited by a plasma-enhanced chemical vapor deposition (PECVD) technique, at low temperatures(similar to 300 degrees C), are presented. Silicon oxynitride (SiO(x)N(y)) films were used as core and second cladding layers and amorphous hydrogenated silicon carbide(a-SiC:H) films as first cladding layer. Furthermore, numerical simulations were performed using homemade routines based on two computational methods: the transfer matrix method (TMM) for the determination of the optimum thickness of the Fabry-Perot layers; and the non-uniform finite difference method (NU-FDM) for 2D design and determination of the maximum width that yields single-mode operation. The utilization of a silicon carbide anti-resonant layer resulted in low optical attenuations, which is due to the high refractive index difference between the core and this layer. Finally, for comparison purposes, optical waveguides using titanium oxide (TiO(2)) as the first ARROW layer were also fabricated and characterized.

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Stable carbon isotope analyses of wool staples provided insight into the vegetation consumed by sheep at a temporal resolution not previously studied. Contemporary Australian and historic South African samples dating back to 1916 were analyzed for their stable carbon isotope ratio, a proxy for the proportion of C-3 and C-4 plant species consumed by animals. Sheep sample vegetation continuously throughout a year, and as their wool grows it integrates and stores information about their diet. In subtropical and tropical rangelands the majority of grass species are C-4. Since sheep prefer to graze, and their wool is an isotopic record of their diet, we now have the potential to develop a high resolution index to the availability of grass from a sheep's perspective. Isotopic analyses of wool suggest a new direction for monitoring grazing and for the reconstruction of past vegetation changes, which will make a significant contribution to traditional rangeland ecology and management. It is recommended that isotopic and other analyses of wool be further developed for use in rangeland monitoring programs to provide valuable feedback for land managers.

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NMR is a powerful technique for determining structures of biologically active molecules in solution. In recent years. our laboratory has focussed on the structure determination of small disulfide-rich proteins from both plants and animals which are valuable targets in drug design applications. This article will review these structural studies and their implications in drug design.

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We have isolated a family of insect-selective neurotoxins from the venom of the Australian funnel-web spider that appear to be good candidates for biopesticide engineering. These peptides, which we have named the Janus-faced atracotoxins (J-ACTXs), each contain 36 or 37 residues, with four disulfide bridges, and they show no homology to any sequences in the protein/DNA databases. The three-dimensional structure of one of these toxins reveals an extremely rare vicinal disulfide bridge that we demonstrate to be critical for insecticidal activity. We propose that J-ACTX comprises an ancestral protein fold that we refer to as the disulfide-directed beta-hairpin.

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Many layered metals such as quasi-two-dimensional organic molecular crystals show properties consistent with a Fermi-liquid description at low temperatures. The effective masses extracted from the temperature dependence of the magnetic oscillations observed in these materials are in the range, m(c)*/m(e) similar to 1 - 7, suggesting that these systems are strongly correlated. However, the ratio m(c)*/m(e) contains both the renormalization due to the electron-electron interaction and the periodic potential of the lattice. We show that for any quasi-two-dimensional band structure, the cyclotron mass is proportional to the density-of-states at the Fermi energy. Due to Luttinger's theorem, this result is also valid in the presence of interactions. We then evaluate m(c) for several model band structures for the beta, kappa, and theta families of (BEDT-TTF)(2)X, where BEDT-TTF is bis-(ethylenedithia-tetrathiafulvalene) and X is an anion. We find that for kappa-(BEDT-TTF)(2)X, the cyclotron mass of the beta orbit, m(c)*(beta) is close to 2 m(c)*(alpha), where m(c)*(alpha) is the effective mass of the alpha orbit. This result is fairly insensitive to the band-structure details. For a wide range of materials we compare values of the cyclotron mass deduced from band-structure calculations to values deduced from measurements of magnetic oscillations and the specific-heat coefficient gamma.