174 research outputs found

    Controlled Heterogeneous Nucleation and Growth of Germanium Quantum Dots on Nanopatterned Silicon Dioxide and Silicon Nitride Substrates

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    Controlled heterogeneous nucleation and growth of Ge quantum dots (QDs) are demonstrated on SiO_2/Si_3N_4 substrates by means of a novel fabrication process of thermally oxidizing nanopatterned SiGe layers. The otherwise random self-assembly process for QDs is shown to be strongly influenced by the nanopatterning in determining both the location and size of the QDs. Ostwald ripening processes are observed under further annealing at the oxidation temperature. Both nanopattern oxidation and Ostwald ripening offer additional mechanisms for lithography for controlling the size and placement of the QDs

    Alternative Ingredient Recommendation: A Co-occurrence and Ingredient Category Importance Based Approach

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    As many people will refer to a recipe when cooking, there are several recipe-sharing websites that include lots of recipes and make recipes easier to access than before. However, there is often the case that we could not get all the ingredients listed on the recipe. Prior research on alternative ingredient substitution has built a recommendation system considering the suitability of a recommended ingredient with the remained ingredients. In this paper, in addition to suitability, we also take the diversity of the ingredient categories and the novelty of new combination of ingredients into account. Besides, we combine suitability with novelty as an index, to see whether our method could help find out a new combination of ingredients that is possibly to be a new dish. Our evaluation results show that our proposed method attains a comparable or even better performance on each perspective

    Pulmonary sequestration at the posterior mediastinum in a neonate

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    The Division of Temporary and Permanent Employment and Business Cycle Fluctuations

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    This paper investigates the fluctuations in temporary relative to aggregate employment over the business cycle, as well as the underlying driving forces. We develop a dynamic general equilibrium model to investigate the following stylized facts: (i) temporary employment is more volatile than permanent employment, (ii) the share of temporary employment (the ratio of temporary to aggregate employment) exhibits strong pro-cyclicality, (iii) permanent employment lags by two quarters on average, and (iv) the correlation between temporary employment and output is stronger than that involving the permanent counterpart. The quantitative analysis suggests that the proposed channels explain the main facts very well and the model provides a possible prediction based on the counter-factual exercises

    The Division of Temporary and Permanent Employment and Business Cycle Fluctuations

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    This paper investigates the fluctuations in temporary relative to aggregate employment over the business cycle, as well as the underlying driving forces. We develop a dynamic general equilibrium model to investigate the following stylized facts: (i) temporary employment is more volatile than permanent employment, (ii) the share of temporary employment (the ratio of temporary to aggregate employment) exhibits strong pro-cyclicality, (iii) permanent employment lags by two quarters on average, and (iv) the correlation between temporary employment and output is stronger than that involving the permanent counterpart. The quantitative analysis suggests that the proposed channels explain the main facts very well and the model provides a possible prediction based on the counter-factual exercises

    The 2005 Ilan earthquake doublet and seismic crisis in northeastern Taiwan: evidence for dyke intrusion associated with on-land propagation of the Okinawa Trough

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    Northern Taiwan underwent mountain building in the early stage of the Taiwan orogeny but is currently subjected to post-collisional crustal extension. It may be related to gravitational collapse or to the rifting of the Okinawa Trough, which lies offshore northeastern Taiwan. The Ilan Plain, northeastern Taiwan, which is bounded by the normal fault systems and filled up with thick Pliocene–Pleistocene sedimentary sequences, formed under such an extension environment. Over there on 2005 March 5 two earthquakes with about the same magnitude (M_L = 5.9) occurred within 68 s and produced intense aftershocks activity according to the records of Central Weather Bureau Seismic Network of Taiwan. We relocated the earthquake sequence by the three-dimension earthquake location algorithm with the newly published 3-D Vp and Vp/Vs velocity model, and determined the first-polarity focal mechanisms of the earthquake doublet. One major cluster of aftershocks which trends E–W and dips steeply to the south can be identified and picked up as a potential fault plane. The focal mechanisms of the two main shocks are both classified as normal type by first-polarity but strike-slip by centroid moment tensor inversion; however two methods both yield consistent E–W strike. Static coseismic deformation was additionally determined from Global Positioning System (GPS) daily solutions at a set of continuous GPS stations and from strong-motion seismographs. These data show NW–SE extension at high angle to the fault plane, which cannot be explained from a simple strike-slip double-couple mechanism. On the other hand, the small vertical displacements and steep fault plane cannot be explained from a simple normal event as well. We present from elastic dislocation modelling that the geodetic data are best explained by significant component of tensile source with centimetre-scale of opening on a 15-km-long fault extending from 1 to 13 km depth. We therefore interpret the crisis as the result of dyke intrusion at the very tip of the Okinawa Trough, which is reasonably driven by backarc spreading

    Synthesis and Characterization of Iron Oxide Nanoparticles and Applications in the Removal of Heavy Metals from Industrial Wastewater

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    This study investigated the applicability of maghemite (γ-Fe 2 O 3 ) nanoparticles for the selective removal of toxic heavy metals from electroplating wastewater. The maghemite nanoparticles of 60 nm were synthesized using a coprecipitation method and characterized by X-ray diffraction (XRD) and scanning electron microscopy (SEM) equipped with energy dispersive X-ray spectroscopy (EDX). Batch experiments were carried out for the removal of Pb 2+ ions from aqueous solutions by maghemite nanoparticles. The effects of contact time, initial concentration of Pb 2+ ions, solution pH, and salinity on the amount of Pb 2+ removed were investigated. The adsorption process was found to be highly pH dependent, which made the nanoparticles selectively adsorb this metal from wastewater. The adsorption of Pb 2+ reached equilibrium rapidly within 15 min and the adsorption data were well fitted with the Langmuir isotherm

    Deep Learning for Brain Age Estimation: A Systematic Review

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    Over the years, Machine Learning models have been successfully employed on neuroimaging data for accurately predicting brain age. Deviations from the healthy brain aging pattern are associated to the accelerated brain aging and brain abnormalities. Hence, efficient and accurate diagnosis techniques are required for eliciting accurate brain age estimations. Several contributions have been reported in the past for this purpose, resorting to different data-driven modeling methods. Recently, deep neural networks (also referred to as deep learning) have become prevalent in manifold neuroimaging studies, including brain age estimation. In this review, we offer a comprehensive analysis of the literature related to the adoption of deep learning for brain age estimation with neuroimaging data. We detail and analyze different deep learning architectures used for this application, pausing at research works published to date quantitatively exploring their application. We also examine different brain age estimation frameworks, comparatively exposing their advantages and weaknesses. Finally, the review concludes with an outlook towards future directions that should be followed by prospective studies. The ultimate goal of this paper is to establish a common and informed reference for newcomers and experienced researchers willing to approach brain age estimation by using deep learning model
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