498 research outputs found

    An Umbrella-Shaped Topology for Broadband MEMS Piezoelectric Vibration Energy Harvesting

    Get PDF
    While cantilever topologies offer high power responsiveness for MEMS vibration energy harvesting (VEH), they are less robust than multiply clamped or membrane topologies. This paper attempts to address this topological optimisation dilemma by attempting to achieve both high power density and robustness. The proposed umbrella-shaped topology constituents of a single central anchor while the membrane area extends outwards and is further enclosed by a ring of proof mass. Implemented on a 0.5 μm AlN on 10 μm doped Si process, a fabricated device (121 mm2 die area) recorded a peak power of 173 μW (1798 Hz and 0.56 g). The normalised power density compares favourably against the state-of-the-art cantilever piezoelectric MEMS VEH, while not sacrificing robustness. Furthermore, this device offers a broadband response, and it has experimentally demonstrated over 3 times higher band-limited noise induced power density than a cantilevered harvester fabricated using the same process

    QSO 2237+0305 VR light curves from Gravitational Lenses International Time Project optical monitoring

    Get PDF
    We present VR observations of QSO 2237+0305 conducted by the GLITP collaboration from 1999 October 1 to 2000 February 3. The observations were made with the 2.56 m Nordic Optical Telescope at Roque de los Muchachos Observatory, La Palma (Spain). The PSF fitting method and an adapted version of the ISIS subtraction method have been used to derive the VR light curves of the four components (A-D) of the quasar. The mean errors range in the intervals 0.01-0.04 mag (PSF fitting) and 0.01-0.02 mag (ISIS subtraction), with the faintest component (D) having the largest uncertainties. We address the relatively good agreement between the A-D light curves derived using different filters, photometric techniques, and telescopes. The new VR light curves of component A extend the time coverage of a high magnification microlensing peak, which was discovered by the OGLE team.Comment: 15 pages, 3 figures, ApJ accepted (Feb 19

    The Importance of Ile716 toward the Mutagenicity of 8-Oxo-2’-deoxyguanosine with Bacillus Fragment DNA Polymerase

    Get PDF
    8-oxo-2’-deoxyguanosine (OdG) is a prominent DNA lesion that can direct the incorporation of dCTP or dATP during replication. As the latter reaction can lead to mutation, the ratio of dCTP/dATP incorporation can significantly affect the mutagenic potential of OdG. Previous work with the A-family polymerase BF and seven analogues of OdG identified a major groove amino acid, Ile716, which likely influences the dCTP/dATP incorporation ratio opposite OdG. To further probe the importance of this amino acid, dCTP and dATP incorporations opposite the same seven analogues were tested with two BF mutants, I716M and I716A. Results from these studies support the presence of clashing interactions between Ile716 and the C8-oxygen and C2-amine during dCTP and dATP incorporations, respectively. Crystallographic analysis suggests that residue 716 alters the conformation of the template base prior to insertion into the active site, thereby affecting enzymatic efficiency. These results are also consistent with previous work with A-family polymerases, which indicate they have tight, rigid active sites that are sensitive to template perturbations

    The INT Search for Metal-Poor Stars. Spectroscopic Observations and Classification via Artificial Neural Networks

    Full text link
    With the dual aims of enlarging the list of extremely metal-poor stars identified in the Galaxy, and boosting the numbers of moderately metal-deficient stars in directions that sample the rotational properties of the thick disk, we have used the 2.5m Isaac Newton Telescope and the Intermediate Dispersion Spectrograph to carry out a survey of brighter (primarily northern hemisphere) metal-poor candidates selected from the HK objective-prism/interference-filter survey of Beers and collaborators. Over the course of only three observing runs (15 nights) we have obtained medium-resolution (resolving power ~ 2000) spectra for 1203 objects (V ~ 11-15). Spectral absorption-line indices and radial velocities have been measured for all of the candidates. Metallicities, quantified by [Fe/H], and intrinsic (B-V)o colors have been estimated for 731 stars with effective temperatures cooler than roughly 6500 K, making use of artificial neural networks (ANNs), trained with spectral indices. We show that this method performs as well as a previously explored Ca II K calibration technique, yet it presents some practical advantages. Among the candidates in our sample, we identify 195 stars with [Fe/H] <= -1.0, 67 stars with [Fe/H] <= -2.0, and 12 new stars with [Fe/H] <= -3.0. Although the EFECTIVE YIELD of metal-poor stars in our sample is not as large as previous HK survey follow-up programs, the rate of discovery per unit of telescope time is quite high.Comment: 27 pages (including 13 figures) + 6 tables (20 pages); uses aastex, lscape and graphicx; to appear in A

    Data Mining and Machine Learning in Astronomy

    Full text link
    We review the current state of data mining and machine learning in astronomy. 'Data Mining' can have a somewhat mixed connotation from the point of view of a researcher in this field. If used correctly, it can be a powerful approach, holding the potential to fully exploit the exponentially increasing amount of available data, promising great scientific advance. However, if misused, it can be little more than the black-box application of complex computing algorithms that may give little physical insight, and provide questionable results. Here, we give an overview of the entire data mining process, from data collection through to the interpretation of results. We cover common machine learning algorithms, such as artificial neural networks and support vector machines, applications from a broad range of astronomy, emphasizing those where data mining techniques directly resulted in improved science, and important current and future directions, including probability density functions, parallel algorithms, petascale computing, and the time domain. We conclude that, so long as one carefully selects an appropriate algorithm, and is guided by the astronomical problem at hand, data mining can be very much the powerful tool, and not the questionable black box.Comment: Published in IJMPD. 61 pages, uses ws-ijmpd.cls. Several extra figures, some minor additions to the tex
    corecore