912 resultados para Blending and morphing joining techniques
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Ultrasonic P wavc transmission seismograms recorded on sediment cores have been analyzed to study the acoustic and estimate the clastic properties of marine sediments from different provinces dominated by terrigenous, calcareous, amI diatomaceous sedimentation. Instantaneous frequencies computed from the transmission seismograms are displayed as gray-shaded images to give an acoustic overview of the lithology of each core. Ccntirneter-scale variations in the ultrasonic waveforms associated with lithological changes are illustrated by wiggle traces in detail. Cross-correlation, multiple-filter, and spectral ratio techniques are applied to derive P wave velocities and attenuation coefficients. S wave velocities and attenuation coefficients, elastic moduli, and permeabilities are calculated by an inversion scheme based on the Biot-Stoll viscoelastic model. Together wilh porosity measurements, P and S wave scatter diagrams are constructed to characterize different sediment types by their velocity- and attenuation-porosity relationships. They demonstrate that terrigenous, calcareous, and diatomaceous sediments cover different velocity- and attenuation-porosity ranges. In terrigcnous sediments, P wave vclocities and attenuation coefficients decrease rapidly with increasing porosity, whereas S wave velocities and shear moduli are very low. Calcareous sediments behave similarly at relatively higher porosities. Foraminifera skeletons in compositions of terrigenous mud and calcareous ooze cause a stiffening of the frame accompanied by higher shear moduli, P wave velocities, and attenuation coefficients. In diatomaceous ooze the contribution of the shear modulus becomes increasingly important and is controlled by the opal content, whereas attenuation is very low. This leads to the opportunity to predict the opal content from nondestructive P wave velocity measurements at centimeter-scale resolution.
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This report is a review of additive and subtractive manufacturing techniques. This approach (additive manufacturing) has resided largely in the prototyping realm, where the methods of producing complex freeform solid objects directly from a computer model without part-specific tooling or knowledge. But these technologies are evolving steadily and are beginning to encompass related systems of material addition, subtraction, assembly, and insertion of components made by other processes. Furthermore, these various additive processes are starting to evolve into rapid manufacturing techniques for mass-customized products, away from narrowly defined rapid prototyping. Taking this idea far enough down the line, and several years hence, a radical restructuring of manufacturing could take place. Manufacturing itself would move from a resource base to a knowledge base and from mass production of single use products to mass customized, high value, life cycle products, majority of research and development was focused on advanced development of existing technologies by improving processing performance, materials, modelling and simulation tools, and design tools to enable the transition from prototyping to manufacturing of end use parts.
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This paper details methodologies that have been explored for the fast proofing of on-chip architectures for Circular Dichroism techniques. Flow-cell devices fabricated from UV transparent Quartz are used for these experiments. The complexity of flow-cell production typically results in lead times of six months from order to delivery. Only at that point can the on-chip architecture be tested empirically and any required modifications determined ready for the next six month iteration phase. By using the proposed 3D printing and PDMS moulding techniques for fast proofing on-chip architectures the optimum design can be determined within a matter of hours prior to commitment to quartz chip production.
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Various techniques and devices have been developed for the purpose of detecting wildlife but many only provide optimum results in particular habitats, for certain species or under ideal weather conditions. It is therefore advantageous to understand the efficiency and suitability of techniques under different scenarios. The effectiveness of methods for detecting rural Irish hedgehogs was investigated as part of a larger study in April 2008. Road kill sightings and questionnaires were employed to locate possible hedgehog sites. Six sites were subsequently selected, and in these areas trapping, spotlighting and foot print tunnels were employed to investigate whether hedgehogs were indeed in the surrounding landscape. Infrared thermal imagery was examined as a detection device. Trapping and infrared imagery failed to detect hedgehogs in areas where they had previously been recorded. Footprint tunnels proved to be unsuccessful in providing absolute proof of hedgehogs in an area. No single method of detection technique could be relied upon to conclude the presence of hedgehogs in an area. A combination of methods is therefore recommended. However, spotlighting was the most effective method, taking a mean of 4 nights to detect a hedgehog, in comparison to 48 nights if footprint tunnels were used as a sole method of detection. This was also suggested by rarefaction curves of these two detection techniques, where over a 48 night period hedgehogs were expected to be recorded 27 times through spotlighting and just 5 times in an equivalent period of footprint tunnel nights.
Memory-Based Attentional Guidance: A Window to the Relationship between Working Memory and Attention
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Attention, the cognitive means by which we prioritize the processing of a subset of information, is necessary for operating efficiently and effectively in the world. Thus, a critical theoretical question is how information is selected. In the visual domain, working memory (WM)—which refers to the short-term maintenance and manipulation of information that is no longer accessible by the senses—has been highlighted as an important determinant of what is selected by visual attention. Furthermore, although WM and attention have traditionally been conceived as separate cognitive constructs, an abundance of behavioral and neural evidence indicates that these two domains are in fact intertwined and overlapping. The aim of this dissertation is to better understand the nature of WM and attention, primarily through the phenomenon of memory-based attentional guidance, whereby the active maintenance of items in visual WM reliably biases the deployment of attention to memory-matching items in the visual environment. The research presented here employs a combination of behavioral, functional imaging, and computational modeling techniques that address: (1) WM guidance effects with respect to the traditional dichotomy of top-down versus bottom-up attentional control; (2) under what circumstances the contents of WM impact visual attention; and (3) the broader hypothesis of a predictive and competitive interaction between WM and attention. Collectively, these empirical findings reveal the importance of WM as a distinct factor in attentional control and support current models of multiple-state WM, which may have broader implications for how we select and maintain information.
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This dissertation studies the coding strategies of computational imaging to overcome the limitation of conventional sensing techniques. The information capacity of conventional sensing is limited by the physical properties of optics, such as aperture size, detector pixels, quantum efficiency, and sampling rate. These parameters determine the spatial, depth, spectral, temporal, and polarization sensitivity of each imager. To increase sensitivity in any dimension can significantly compromise the others.
This research implements various coding strategies subject to optical multidimensional imaging and acoustic sensing in order to extend their sensing abilities. The proposed coding strategies combine hardware modification and signal processing to exploiting bandwidth and sensitivity from conventional sensors. We discuss the hardware architecture, compression strategies, sensing process modeling, and reconstruction algorithm of each sensing system.
Optical multidimensional imaging measures three or more dimensional information of the optical signal. Traditional multidimensional imagers acquire extra dimensional information at the cost of degrading temporal or spatial resolution. Compressive multidimensional imaging multiplexes the transverse spatial, spectral, temporal, and polarization information on a two-dimensional (2D) detector. The corresponding spectral, temporal and polarization coding strategies adapt optics, electronic devices, and designed modulation techniques for multiplex measurement. This computational imaging technique provides multispectral, temporal super-resolution, and polarization imaging abilities with minimal loss in spatial resolution and noise level while maintaining or gaining higher temporal resolution. The experimental results prove that the appropriate coding strategies may improve hundreds times more sensing capacity.
Human auditory system has the astonishing ability in localizing, tracking, and filtering the selected sound sources or information from a noisy environment. Using engineering efforts to accomplish the same task usually requires multiple detectors, advanced computational algorithms, or artificial intelligence systems. Compressive acoustic sensing incorporates acoustic metamaterials in compressive sensing theory to emulate the abilities of sound localization and selective attention. This research investigates and optimizes the sensing capacity and the spatial sensitivity of the acoustic sensor. The well-modeled acoustic sensor allows localizing multiple speakers in both stationary and dynamic auditory scene; and distinguishing mixed conversations from independent sources with high audio recognition rate.
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Humanity is shaped by its relationships with microbes. From bacterial infections to the production of biofuels, industry and health often hinge on our control of microbial populations. Understanding the physiological and genetic basis of their behaviors is therefore of the highest importance. To this end I have investigated the genetic basis of plastic adhesion in Saccharomyces cerevisiae, the mechanistic and evolutionary dynamics of mixed species biofilms with Escherichia coli and S. cerevisiae, and the induction of filamentation in E. coli. Using a bulk segregant analysis on experimentally evolved populations, I detected 28 genes that are likely to mediate plastic adhesion in S. cerevisiae. With a variety of imaging and culture manipulation techniques, I found that particular strains of E. coli are capable of inducing flocculation and macroscopic biofilm formation via coaggregation with yeast. I also employed experimental evolution and microbial demography techniques to find that selection for mixed species biofilm association leads to lower fecundity in S. cerevisiae. Using culture manipulation and imaging techniques, I also found that E. coli are capable of inducing a filamentous phenotype with a secreted signal that has many of the qualities of a quorum sensing molecule.
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This thesis involved the development of two Biosensors and their associated assays for the detection of diseases, namely IBR and BVD for veterinary use and C1q protein as a biomarker to pancreatic cancer for medical application, using Surface Plasmon Resonance (SPR) and nanoplasmonics. SPR techniques have been used by a number of groups, both in research [1-3] and commercially [4, 5] , as a diagnostic tool for the detection of various biomolecules, especially antibodies [6-8]. The biosensor market is an ever expanding field, with new technology and new companies rapidly emerging on the market, for both human [8] and veterinary applications [9, 10]. In Chapter 2, we discuss the development of a simultaneous IBR and BVD virus assay for the detection of antibodies in bovine serum on an SPR-2 platform. Pancreatic cancer is the most lethal cancer by organ site, partially due to the lack of a reliable molecular signature for diagnostic testing. C1q protein has been recently proposed as a biomarker within a panel for the detection of pancreatic cancer. The third chapter discusses the fabrication, assays and characterisation of nanoplasmonic arrays. We will talk about developing C1q scFv antibody assays, clone screening of the antibodies and subsequently moving the assays onto the nanoplasmonic array platform for static assays, as well as a custom hybrid benchtop system as a diagnostic method for the detection of pancreatic cancer. Finally, in chapter 4, we move on to Guided Mode Resonance (GMR) sensors, as a low-cost option for potential use in Point-of Care diagnostics. C1q and BVD assays used in the prior formats are transferred to this platform, to ascertain its usability as a cost effective, reliable sensor for diagnostic testing. We discuss the fabrication, characterisation and assay development, as well as their use in the benchtop hybrid system.
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Online Social Network (OSN) services provided by Internet companies bring people together to chat, share the information, and enjoy the information. Meanwhile, huge amounts of data are generated by those services (they can be regarded as the social media ) every day, every hour, even every minute, and every second. Currently, researchers are interested in analyzing the OSN data, extracting interesting patterns from it, and applying those patterns to real-world applications. However, due to the large-scale property of the OSN data, it is difficult to effectively analyze it. This dissertation focuses on applying data mining and information retrieval techniques to mine two key components in the social media data — users and user-generated contents. Specifically, it aims at addressing three problems related to the social media users and contents: (1) how does one organize the users and the contents? (2) how does one summarize the textual contents so that users do not have to go over every post to capture the general idea? (3) how does one identify the influential users in the social media to benefit other applications, e.g., Marketing Campaign? The contribution of this dissertation is briefly summarized as follows. (1) It provides a comprehensive and versatile data mining framework to analyze the users and user-generated contents from the social media. (2) It designs a hierarchical co-clustering algorithm to organize the users and contents. (3) It proposes multi-document summarization methods to extract core information from the social network contents. (4) It introduces three important dimensions of social influence, and a dynamic influence model for identifying influential users.
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The Caribbean genus Pseudophoenix (Arecaceae) has its center of taxonomic diversity in Hispaniola (Haiti and the Dominican Republic). Three species (P. ekmanii, P. lediniana, and P. vinifera) are restricted to this island. In this thesis I investigated the population genetic diversity and structure of Pseudophoenix using ten microsatellite loci. Results showed homozygote excess and high inbreeding coefficients in all populations across all polymorphic loci. Overall, there was high differentiation among populations. Results from the Bayesian and Neighbor Joining cluster analyses identified groups that were consistence with currently accepted species delimitation. We included the only known population of an undescribed morph from the Dominican Republic that has been suggested to represent a new species. Results from the cluster analyses suggested that this putative species is closely related to P. sargentii from Turk and Caicos. Our study provided insights pertinent to the conservation genetics and management of this genus in Hispaniola.
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The presence of harmful algal blooms (HAB) is a growing concern in aquatic environments. Among HAB organisms, cyanobacteria are of special concern because they have been reported worldwide to cause environmental and human health problem through contamination of drinking water. Although several analytical approaches have been applied to monitoring cyanobacteria toxins, conventional methods are costly and time-consuming so that analyses take weeks for field sampling and subsequent lab analysis. Capillary electrophoresis (CE) becomes a particularly suitable analytical separation method that can couple very small samples and rapid separations to a wide range of selective and sensitive detection techniques. This paper demonstrates a method for rapid separation and identification of four microcystin variants commonly found in aquatic environments. CE coupled to UV and electrospray ionization time-of-flight mass spectrometry (ESI-TOF) procedures were developed. All four analytes were separated within 6 minutes. The ESI-TOF experiment provides accurate molecular information, which further identifies analytes.
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This thesis consists of a large composition for violoncello and orchestra, together with an analytical paper in which I discuss my compositional techniques and some of their historical antecedents. The composition draws on the genres of imaginary musical theater, the symphonic poem, and the concerto. It was also inspired by the story of Hermes, the messenger god from Greek mythology. While the myth partially informs the compositional structure, the work is ultimately meant to showcase the versatility of the cello, the coloristic range of the orchestra (in some cases emulating the orchestral styles of previous composers), the balance of cello and orchestra together, and the eclectic invocation of many compositional techniques separately and simultaneously. These techniques encompass set theory (the use of unordered pitch collections), polytonality, and serialism. It is composed in a post-romantic style.
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A molecular organic geochemical proxy (TEX86) for sea surface temperature (SST) is compared with a foraminifera-based SST proxy (Mg/Ca) in a decadal-resolution marine sedimentary record spanning the last 1000 years from the Gulf of Mexico. We assess the relative strengths of the organic and inorganic paleoceanographic techniques for reconstructing high-resolution SST variability during recent climate events, including the Little Ice Age (LIA) and the Medieval Warm Period (MWP). SST estimates based on the molecular organic proxy TEX86 show a similar magnitude and pattern of SST variability to foraminiferal Mg/Ca-SST estimates but with some important differences. For instance, both proxies show a cooling (1°C-2°C) of Gulf of Mexico SSTs during the LIA. During the MWP, however, Mg/Ca-SSTs are similar to near-modern SSTs, while TEX86 indicates SSTs that were cooler than modern. Using the respective SST calibrations for each proxy results in TEX86-SST estimates that are 2°C-4°C warmer than Mg/Ca-SST throughout the 1000 year record. We interpret the TEX86-SST as a summer-weighted SST signal from the upper mixed layer, whereas the Mg/Ca-SST better reflects the mean annual SST. Downcore differences in the SST estimates between the two proxies (DeltaT = TEX86 - Mg/Ca) are interpreted in the context of varying seasonality and/or changing water column temperature gradients.
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Iron (Fe) can limit phytoplankton productivity in approximately 40% of the global ocean, including in high-nutrient, low-chlorophyll (HNLC) waters. However, there is little information available on the impact of CO2-induced seawater acidification on natural phytoplankton assemblages in HNLC regions. We therefore conducted an on-deck experiment manipulating CO2 and Fe using Fe-deficient Bering Sea water during the summer of 2009. The concentrations of CO2 in the incubation bottles were set at 380 and 600 ppm in the non-Fe-added (control) bottles and 180, 380, 600, and 1000 ppm in the Fe-added bottles. The phytoplankton assemblages were primarily composed of diatoms followed by haptophytes in all incubation bottles as estimated by pigment signatures throughout the 5-day (control) or 6-day (Fe-added treatment) incubation period. At the end of incubation, the relative contribution of diatoms to chlorophyll a biomass was significantly higher in the 380 ppm CO2 treatment than in the 600 ppm treatment in the controls, whereas minimal changes were found in the Fe-added treatments. These results indicate that, under Fe-deficient conditions, the growth of diatoms could be negatively affected by the increase in CO2 availability. To further support this finding, we estimated the expression and phylogeny of rbcL (which encodes the large subunit of RuBisCO) mRNA in diatoms by quantitative reverse transcription polymerase chain reaction (PCR) and clone library techniques, respectively. Interestingly, regardless of Fe availability, the transcript abundance of rbcL decreased in the high CO2 treatments (600 and 1000 ppm). The present study suggests that the projected future increase in seawater pCO2 could reduce the RuBisCO transcription of diatoms, resulting in a decrease in primary productivity and a shift in the food web structure of the Bering Sea.
(Table 1, page 376), Composition of manganese deposits from the Gulf of Aden and the Carlsberg Ridge
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Iron-manganese nodules from the ocean floor have been extensively studied. But, because of the fine grain size of the particles of the nodules, structural identification by X-ray and electron diffraction techniques is difficult and the mineralogy of the iron oxide phase has not been well characterized. The observation of the Mössbauer spectrum-in which each nucleus absorbs gamma-rays independently-is not limited by particle size in the same way as is the observation of Bragg peaks in diffraction measurements, in which radiation must be scattered coherently from a large number of atoms. The magnetic hyperfine splitting in the Mössbauer spectrum of magnetic materials is affected, however, when the particles are so small that they become superparamagnetic. We describe here an investigation using the 57Fe Mössbauer effect of two iron-manganese nodules in which the iron oxide phase could not be detected by X-ray or electron diffraction.