239 resultados para processing platform


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A novel platform consisting of a multilayered substrate, activated graphite-like carbon film, and dense forest of long, vertically-aligned multiwall carbon nanotubes grown by the chemical vapor deposition is designed, fabricated, and tested for covalent immobilization of enzymatic biocatalysts with the aim of protecting them from shear forces and microbial attacks present in bioreactors. The covalent bonding ensures enzyme retention in a flow, while the dense nanotube forest may serve as a protection of the enzymes from microbial attack without impeding the flow of reactants and products. This platform was demonstrated for the two reference enzymes, horseradish peroxidase and catalase, which were immobilized without degrading their biological activity. This combination of an activated carbon layer for an efficient immobilization of biocatalysts with a protective layer of inert carbon nanotubes could dramatically improve the efficiency and longevity of enzymatic bio-catalysis employed in a large variety of advanced biotechnological processes.

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Low-temperature plasmas in direct contact with arbitrary, written linear features on a Si wafer enable catalyst-free integration of carbon nanotubes into a Si-based nanodevice platform and in situ resolution of individual nucleation events. The graded nanotube arrays show reliable, reproducible, and competitive performance in electron field emission and biosensing nanodevices.

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A three-dimensional surface enhanced Raman scattering (SERS)/plasmonic sensing platform based on plasma-enabled, catalyst-free, few-layer vertical graphenes decorated with self-organized Au nanoparticle arrays is demonstrated. This platform is viable for multiple species detection and overcomes several limitations of two-dimensional sensors.

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An effective technique to improve the precision and throughput of energetic ion condensation through dielectric nanoporous templates and reduce nanopore clogging by using finely tuned pulsed bias is proposed. Multiscale numerical simulations of ion deposition show the possibility of controlling the dynamic charge balance on the upper template's surface to minimize ion deposition on nanopore sidewalls and to deposit ions selectively on the substrate surface in contact with the pore opening. In this way, the shapes of nanodots in template-assisted nanoarray fabrication can be effectively controlled. The results are applicable to various processes involving porous dielectric nanomaterials and dense nanoarrays.

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Examples of successful fabrication of low-dimensional semiconducting nanomaterials in the Integrated Plasma-Aided Nanofabrication Facility are shown. Self-assembled size-uniform ZnO nanoparticles, ultra-high-aspect ratio Si nanowires, vertically aligned cadmium sulfide nanostructures, and quarternary semiconducting SiCAlN nanomaterial have been synthesized using inductively coupled plasma-assisted RF magnetron sputtering deposition. The observed increase in crystallinity and growth rates of the nanostructures are explained by using a model of plasma-enhanced adatom surface diffusion under conditions of local energy exchange between the ion flux and the growth surface. Issues related to plasma-based growth of low-dimensional semiconducting nanomaterials are discussed as well. © 2007 Elsevier B.V. All rights reserved.

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In this study we investigate previous claims that a region in the left posterior superior temporal sulcus (pSTS) is more activated by audiovisual than unimodal processing. First, we compare audiovisual to visual-visual and auditory-auditory conceptual matching using auditory or visual object names that are paired with pictures of objects or their environmental sounds. Second, we compare congruent and incongruent audiovisual trials when presentation is simultaneous or sequential. Third, we compare audiovisual stimuli that are either verbal (auditory and visual words) or nonverbal (pictures of objects and their associated sounds). The results demonstrate that, when task, attention, and stimuli are controlled, pSTS activation for audiovisual conceptual matching is 1) identical to that observed for intramodal conceptual matching, 2) greater for incongruent than congruent trials when auditory and visual stimuli are simultaneously presented, and 3) identical for verbal and nonverbal stimuli. These results are not consistent with previous claims that pSTS activation reflects the active formation of an integrated audiovisual representation. After a discussion of the stimulus and task factors that modulate activation, we conclude that, when stimulus input, task, and attention are controlled, pSTS is part of a distributed set of regions involved in conceptual matching, irrespective of whether the stimuli are audiovisual, auditory-auditory or visual-visual.

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This fMRI study investigates how audiovisual integration differs for verbal stimuli that can be matched at a phonological level and nonverbal stimuli that can be matched at a semantic level. Subjects were presented simultaneously with one visual and one auditory stimulus and were instructed to decide whether these stimuli referred to the same object or not. Verbal stimuli were simultaneously presented spoken and written object names, and nonverbal stimuli were photographs of objects simultaneously presented with naturally occurring object sounds. Stimulus differences were controlled by including two further conditions that paired photographs of objects with spoken words and object sounds with written words. Verbal matching, relative to all other conditions, increased activation in a region of the left superior temporal sulcus that has previously been associated with phonological processing. Nonverbal matching, relative to all other conditions, increased activation in a right fusiform region that has previously been associated with structural and conceptual object processing. Thus, we demonstrate how brain activation for audiovisual integration depends on the verbal content of the stimuli, even when stimulus and task processing differences are controlled.

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Monitoring gases for environmental, industrial and agricultural fields is a demanding task that requires long periods of observation, large quantity of sensors, data management, high temporal and spatial resolution, long term stability, recalibration procedures, computational resources, and energy availability. Wireless Sensor Networks (WSNs) and Unmanned Aerial Vehicles (UAVs) are currently representing the best alternative to monitor large, remote, and difficult access areas, as these technologies have the possibility of carrying specialised gas sensing systems, and offer the possibility of geo-located and time stamp samples. However, these technologies are not fully functional for scientific and commercial applications as their development and availability is limited by a number of factors: the cost of sensors required to cover large areas, their stability over long periods, their power consumption, and the weight of the system to be used on small UAVs. Energy availability is a serious challenge when WSN are deployed in remote areas with difficult access to the grid, while small UAVs are limited by the energy in their reservoir tank or batteries. Another important challenge is the management of data produced by the sensor nodes, requiring large amount of resources to be stored, analysed and displayed after long periods of operation. In response to these challenges, this research proposes the following solutions aiming to improve the availability and development of these technologies for gas sensing monitoring: first, the integration of WSNs and UAVs for environmental gas sensing in order to monitor large volumes at ground and aerial levels with a minimum of sensor nodes for an effective 3D monitoring; second, the use of solar energy as a main power source to allow continuous monitoring; and lastly, the creation of a data management platform to store, analyse and share the information with operators and external users. The principal outcomes of this research are the creation of a gas sensing system suitable for monitoring any kind of gas, which has been installed and tested on CH4 and CO2 in a sensor network (WSN) and on a UAV. The use of the same gas sensing system in a WSN and a UAV reduces significantly the complexity and cost of the application as it allows: a) the standardisation of the signal acquisition and data processing, thereby reducing the required computational resources; b) the standardisation of calibration and operational procedures, reducing systematic errors and complexity; c) the reduction of the weight and energy consumption, leading to an improved power management and weight balance in the case of UAVs; d) the simplification of the sensor node architecture, which is easily replicated in all the nodes. I evaluated two different sensor modules by laboratory, bench, and field tests: a non-dispersive infrared module (NDIR) and a metal-oxide resistive nano-sensor module (MOX nano-sensor). The tests revealed advantages and disadvantages of the two modules when used for static nodes at the ground level and mobile nodes on-board a UAV. Commercial NDIR modules for CO2 have been successfully tested and evaluated in the WSN and on board of the UAV. Their advantage is the precision and stability, but their application is limited to a few gases. The advantages of the MOX nano-sensors are the small size, low weight, low power consumption and their sensitivity to a broad range of gases. However, selectivity is still a concern that needs to be addressed with further studies. An electronic board to interface sensors in a large range of resistivity was successfully designed, created and adapted to operate on ground nodes and on-board UAV. The WSN and UAV created were powered with solar energy in order to facilitate outdoor deployment, data collection and continuous monitoring over large and remote volumes. The gas sensing, solar power, transmission and data management systems of the WSN and UAV were fully evaluated by laboratory, bench and field testing. The methodology created to design, developed, integrate and test these systems was extensively described and experimentally validated. The sampling and transmission capabilities of the WSN and UAV were successfully tested in an emulated mission involving the detection and measurement of CO2 concentrations in a field coming from a contaminant source; the data collected during the mission was transmitted in real time to a central node for data analysis and 3D mapping of the target gas. The major outcome of this research is the accomplishment of the first flight mission, never reported before in the literature, of a solar powered UAV equipped with a CO2 sensing system in conjunction with a network of ground sensor nodes for an effective 3D monitoring of the target gas. A data management platform was created using an external internet server, which manages, stores, and shares the data collected in two web pages, showing statistics and static graph images for internal and external users as requested. The system was bench tested with real data produced by the sensor nodes and the architecture of the platform was widely described and illustrated in order to provide guidance and support on how to replicate the system. In conclusion, the overall results of the project provide guidance on how to create a gas sensing system integrating WSNs and UAVs, how to power the system with solar energy and manage the data produced by the sensor nodes. This system can be used in a wide range of outdoor applications, especially in agriculture, bushfires, mining studies, zoology, and botanical studies opening the way to an ubiquitous low cost environmental monitoring, which may help to decrease our carbon footprint and to improve the health of the planet.

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Pcf11p, an essential subunit of the yeast cleavage factor IA, is required for pre‐mRNA 3′ end processing, binds to the C‐terminal domain (CTD) of the largest subunit of RNA polymerase II (RNAP II) and is involved in transcription termination. We show that the conserved CTD interaction domain (CID) of Pcf11p is essential for cell viability. Interestingly, the CTD binding and 3′ end processing activities of Pcf11p can be functionally uncoupled from each other and provided by distinct Pcf11p fragments in trans. Impaired CTD binding did not affect the 3′ end processing activity of Pcf11p and a deficiency of Pcf11p in 3′ end processing did not prevent CTD binding. Transcriptional run‐on analysis with the CYC1 gene revealed that loss of cleavage activity did not correlate with a defect in transcription termination, whereas loss of CTD binding did. We conclude that Pcf11p is a bifunctional protein and that transcript cleavage is not an obligatory step prior to RNAP II termination.

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As printed and flexible plastic electronic gadgets become increasingly viable today, there is a need to develop materials that suit the fabrication processes involved. Two desirable requirements are solution-processable active materials or precursors and low-temperature processability. In this article, we describe a straightforward method of depositing ZnO films by simple spin coating of an organometallic diethylzinc precursor solution and annealing the resulting film at low temperatures (≤200 °C) without involving any synthetic steps. By controlling the humidity in which annealing is conducted, we are able to adjust the intrinsic doping level and carrier concentration in diethylzinc-derived ZnO. Doped or conducting transport layers are greatly preferable to undoped layers as they enable low-resistance contacts and minimize the potential drops. This ability to controllably realize doped ZnO is a key feature of the fabrication process that we describe in this article. We employ field-effect measurements as a diagnostic tool to measure doping levels and mobilities in ZnO and demonstrate that doped ZnO with high charge carrier concentration is ideal for solar cell applications. Respectable power conversion efficiencies (up to 4.5%) are achieved in inverted solar cells that incorporate diethylzinc-derived ZnO films as the electron transport layer and organic blends as the active material. Extensions of this approach to grow ternary and quaternary films with organometallic precursor chemicals will enable solution based growth of a number of semiconductor films as well as a method to dope them.

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There is nothing new under the sun – so the saying goes, and in a digital age of recording oral histories, this holds true. Despite advances and innovations across the board in information and communication technology in the field of oral history it is essentially only the devices we record on that have changed. However, what has emerged is a plethora of ways that oral history interviews can be used to produce multimedia, or transmedia storytelling outputs- for exhibitions in public institutions, schools and by communities to engage interested groups, and in families and by individuals wanting to play with new ways of telling their family stories and histories. In 2010, QUT’s Creative Industries introduced a postgraduate unit called Transmedia Storytelling: From Interviewing to Multi-Platform, which was the first postgraduate course of its kind in Australia. Based in a Creative Writing discipline, but open to all coursework Masters, PhD, Research Masters and Doctorate of Creative Industries students, this unit introduces students to the theory and practice of semi-structured interviewing techniques, oral history conventions and applications, and the art of storytelling across various platforms.

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This chapter describes decentralized data fusion algorithms for a team of multiple autonomous platforms. Decentralized data fusion (DDF) provides a useful basis with which to build upon for cooperative information gathering tasks for robotic teams operating in outdoor environments. Through the DDF algorithms, each platform can maintain a consistent global solution from which decisions may then be made. Comparisons will be made between the implementation of DDF using two probabilistic representations. The first, Gaussian estimates and the second Gaussian mixtures are compared using a common data set. The overall system design is detailed, providing insight into the overall complexity of implementing a robust DDF system for use in information gathering tasks in outdoor UAV applications.

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Motion planning for planetary rovers must consider control uncertainty in order to maintain the safety of the platform during navigation. Modelling such control uncertainty is difficult due to the complex interaction between the platform and its environment. In this paper, we propose a motion planning approach whereby the outcome of control actions is learned from experience and represented statistically using a Gaussian process regression model. This mobility prediction model is trained using sample executions of motion primitives on representative terrain, and predicts the future outcome of control actions on similar terrain. Using Gaussian process regression allows us to exploit its inherent measure of prediction uncertainty in planning. We integrate mobility prediction into a Markov decision process framework and use dynamic programming to construct a control policy for navigation to a goal region in a terrain map built using an on-board depth sensor. We consider both rigid terrain, consisting of uneven ground, small rocks, and non-traversable rocks, and also deformable terrain. We introduce two methods for training the mobility prediction model from either proprioceptive or exteroceptive observations, and report results from nearly 300 experimental trials using a planetary rover platform in a Mars-analogue environment. Our results validate the approach and demonstrate the value of planning under uncertainty for safe and reliable navigation.