2,975 research outputs found
1.3 /spl mu/m GaAs/GaAsSb quantum well laser grown by solid source molecular beam epitaxy
No full text1.3 μm GaAs/GaAsSb quantum well laser grown by solid source molecular beam epitaxy
No full textA highly strained GaAs GaAs0.64 Sb0.36 single quantum well laser has
been grown on GaAs (100) substrate by using solid source molecular
beam epitaxy. The uncoated broad-area laser demonstrates 1.292 mm
pulsed operation with a low threshold current density of 300 A cm
2
.The
spontaneous emission of the laser was also studied. The result reveals
that the Auger recombination component dominates the threshold
current at high temperature
Author Correction:A cattle graph genome incorporating global breed diversity
Get PDFThe original version of this Article omitted from the author list the 12th and 13th authors Dennis Muhanguzi and Wilson Amanyire, who are from the ‘School of Biosecurity, Biotechnology and Laboratory Sciences (SBLS), College of Veterinary Medicine, Animal Resources and Biosecurity, Makerere University, P.O Box 7062, Kampala, Uganda’. Consequently, the final sentence of the Author Contributions incorrectly read ‘D.W., P.T., E.A.J.C., C.E., E.T.O., E.R.A., A. Tijjani, K.M., A.F., B.R.F., A.Q., U.C. and P.W. provided samples and expertise for the studies’. This has been replaced with ‘D.W., P.T., W.A., D.M., E.A.J.C., C.E., E.T.O., E.R.A., A. Tijjani, K.M., A.F., B.R.F., A.Q., U.C. and P.W. provided samples and expertise for the studies’. This has been corrected in both the PDF and HTML versions of the Article
Geomorphic evidence helps identifying the preexisting rupture: a lesson from 1999 Chichi earthquake in central Taiwan
No full textCharacterization of three-dimensional GaAs/Al/sub x/O/sub y/ near-infrared photonic crystals fabricated by using an auto-cloning technique
No full textTaxonomy and phylogeny of the genus Mycosphaerella and its anamorphs
No full textHistorically plant pathogenic species of Mycosphaerella have been regarded as host-specific, though this hypothesys has proven difficult to test largely due to the inavailability of fungal cultures. During the course of the past 20 years a concerted effort has been made to collect these fungi, and devise methods to cultivate them. Based on subsequent DNA sequence analyses the majority of these species were revealed to be host-specific, though some were not, suggesting that no general rule can be applied. Furthermore, analysis of recent molecular data revealed Mycosphaerella to be poly- and paraphyletic. Teleomorph morphology was shown to be too narrowly defined in some cases, and again too widely in others. Mycosphaerella and Teratosphaeria as presently circumscribed represent numerous different genera, many of which can be recognised based on the morphology of their 30 odd associated anamorph genera. Although Mycosphaerella is generally accepted to represent one of the largest genera of ascomycetous fungi, these data suggest that this is incorrect, and that Mycosphaerella should be restricted to taxa linked to Ramularia anamorphs. Furthermore, other anamorph form genera with Mycosphaerella-like teleomorphs appear to represent genera in their own right
High performance latent dirichlet allocation for text mining
Get PDFThis thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Latent Dirichlet Allocation (LDA), a total probability generative model, is a three-tier Bayesian model. LDA computes the latent topic structure of the data and obtains the significant information of documents. However, traditional LDA has several limitations in practical applications. LDA cannot be directly used in classification because it is a non-supervised learning model. It needs to be embedded into appropriate classification algorithms. LDA is a generative model as it normally generates the latent topics in the categories where the target documents do not belong to, producing the deviation in computation and reducing the classification accuracy. The number of topics in LDA influences the learning process of model parameters greatly. Noise samples in the training data also affect the final text classification result. And, the quality of LDA based classifiers depends on the quality of the training samples to a great extent. Although parallel LDA algorithms are proposed to deal with huge amounts of data, balancing computing loads in a computer cluster poses another challenge. This thesis presents a text classification method which combines the LDA model and Support Vector Machine (SVM) classification algorithm for an improved accuracy in classification when reducing the dimension of datasets. Based on Density-Based Spatial Clustering of Applications with Noise (DBSCAN), the algorithm automatically optimizes the number of topics to be selected which reduces the number of iterations in computation. Furthermore, this thesis presents a noise data reduction scheme to process noise data. When the noise ratio is large in the training data set, the noise reduction scheme can always produce a high level of accuracy in classification. Finally, the thesis parallelizes LDA using the MapReduce model which is the de facto computing standard in supporting data intensive applications. A genetic algorithm based load balancing algorithm is designed to balance the workloads among computers in a heterogeneous MapReduce cluster where the computers have a variety of computing resources in terms of CPU speed, memory space and hard disk space
Three years of Extreme Physiology & Medicine
Get PDF© 2015 Grocott and Montgomery. This article is distributed under the terms of the Creative Commons Attribution 4.0 Interna‑
tional License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in
any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Com‑
mons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecom‑
mons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated
An Extraordinary Flintlock Hunting Rifle
No full textOctagonal iron barrel mounted on beautifully carved walnut guard and stock, in which are incorporated very fine carved ivory panels depicting various mythological scenes. One of the panels also includes Coat-of-arms surmounted with coronet of Prince. The gun is further embellished by the patine of the wood and the ivory. Provenance: Purchased by William Randolph Hearst from P.W. French & Co., March 26, 1921 for 500; sold to Gimbel Bros., Inc., April 30, 1941 for $1078.https://digitalcommons.liu.edu/post_hearst/1215/thumbnail.jp
Peer-to-peer energy trading: A novel market mechanism incorporating cooperative behaviours and electricity-heat coupling
No full textWith the penetration of distributed energy resources, peer-to-peer (P2P) energy trading is becoming a promising way to harmonize the decarbonization and decentralization transformations in the energy sector. P2P markets give peers the autonomy to make individual decisions and cooperative behaviors between the peers may emerge. However, existing studies on cooperative behaviors in P2P markets focus mostly on the electricity sector, P2P multi-energy markets are rarely studied. In fact, other energy carriers not only constitute a large part of the total energy demand, but their coupling can potentially benefit the system as well as the end-users. In this paper, we propose a P2P multi-energy market mechanism that allows peers to trade both electricity and heat, where the peers can join two predefined trading coalitions. The proposed system model thus explores the integrated effects of the multi-energy coupling and the cooperative behaviors in the P2P market. In order to maximize the net benefits of the peers, price conditions are derived, based on which the peers will join either of the coalitions and determine their trading volumes. Then, the electricity and the heat markets are cleared separately by a market operator. Lastly, the market mechanism is illustrated by a case study on a neighborhood in the Netherlands using realistic data.Complex Systems Engineering and Management (CoSEM
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