4,846 research outputs found
Deep Multi-instance Networks with Sparse Label Assignment for Whole Mammogram Classification
Mammogram classification is directly related to computer-aided diagnosis of
breast cancer. Traditional methods rely on regions of interest (ROIs) which
require great efforts to annotate. Inspired by the success of using deep
convolutional features for natural image analysis and multi-instance learning
(MIL) for labeling a set of instances/patches, we propose end-to-end trained
deep multi-instance networks for mass classification based on whole mammogram
without the aforementioned ROIs. We explore three different schemes to
construct deep multi-instance networks for whole mammogram classification.
Experimental results on the INbreast dataset demonstrate the robustness of
proposed networks compared to previous work using segmentation and detection
annotations.Comment: MICCAI 2017 Camera Read
Spike Effects on Drag Reduction for Hypersonic Lifting Body
A high lift-to-drag ratio is considered crucial for high-altitude and long-endurance hypersonic vehicles. One of the simplest and most useful methods is to install an aerospike in front of the vehicle’s nose. In this paper, the flight aerodynamic characteristics are investigated by simulating and comparing the lifting body with or without the aerospikes at Ma=8. The flowfields around aerospikes using different spike lengths and a hemispherical disk along with the lifting body are analyzed. The results of aerodynamic characteristics indicate that L/D=2 is the best ratio of the spike length to the nose diameter. By comparing with the baseline model, the maximum drag reduction of the nose’s part is 49.3% at α=8 deg using a hemispherical disk. In addition, three shapes of aerospike disks are compared to search for the best disk for hypersonic drag reduction. The best drag reduction is found for the double flat-faced disk aerospike, which gives a pressure drag reduction of 60.5% of the nose’s part at α=8 deg. Furthermore, when the flight angle of attack increases, the drag increases significantly. Employing a certain installation angle is shown to effectively improve the drag reduction around the angle of attack and results in improving the lift-to-drag ratio. At the end, the lift-to-drag ratio of the final optimized design is 9.1% better than that of the baseline model. The pressure center is moved forward by 1.6%, barely influencing the vertical static stability of the vehicle
Complete genome sequence of a marine roseophage provides evidence into the evolution of gene transfer agents in alphaproteobacteria
Roseophage RDJLΦ1 is a siphovirus isolated from South China Sea on Roseobacter denitrificans OCh114. Its virion encapsulates 62.7 kb genome that encodes 87 gene products. RDJLΦ1 shares similar genome organization and gene content with the marine bacteriophage ΦJL001 and Pseudomonas phages YuA and M6, which are different from those of typical λ- or Mu-like phages. Four hallmark genes (ORFs 81 to 84) of RDJLΦ1 were highly homologous to RcGTA-like genes 12 to 15. The largest gene (ORF 84) was predicted to encode a tail fibre protein that could be involved in host recognition. Extended phylogenetic and comparative genomic analyses based on 77 RcGTA-like element-containing bacterial genomes revealed that RcGTA-like genes 12 to 15 together appear to be a conserved modular element that could also be found in some phage or prophage genomes. Our study suggests that RcGTA-like genes-containing phages and prophages and complete RcGTAs possibly descended from a same prophage ancestor that had diverged and then evolved vertically. The complete genome of RDJLΦ1 provides evidence into the hypothesis that extant RcGTA may be a prophage remnant
Method for quantification of aerobic anoxygenic phototrophic bacteria
Accurate quantification of aerobic anoxygenic phototrophic bacteria (AAPB) is of crucial importance for estimation of the role of AAPB in the carbon cycling in marine ecosystems. The normally used method "epifluorescence microscope-infrared photography (EFM-IRP)" is, however, subject to positive errors introduced by mistaking cyanobacteria as AAPB due to the visibility of cyanobacteria under infrared photographic conditions for AAPB. This error could be up to 30% in the coast of the East China Sea. Such bias should be avoided by either subtracting cyanobacteira from the total infrared counts or using a flowcytometer equipped with specific detectors for discrimination between cyanobacteria and AAPB
Emotion recognition and analysis of netizens based on micro-blog during covid-19 epidemic
The research is about emotion recognition and analysis based on Micro-blog short text. Emotion recognition is an important field of text classification in Natural Language Processing. The data of this research comes from Micro-blog 100K record related to COVID-19 theme collected by Data fountain platform, the data are manually labeled, and the emotional tendencies of the text are negative, positive and neutral. The empirical part adopts dictionary emotion recognition method and machine learning emotion recognition respectively. The algorithms used include support vector machine and naive Bayes based on TFIDF, support vector machine and LSTM based on wod2vec. The five results are compared. Combined with statistical analysis methods, the emotions of netizens in the early stage of the epidemic are analyzed for public opinion. This research uses machine learning algorithm combined with statistical analysis to analyze current events in real time. It will be of great significance for the introduction and implementation of national policies
Effects of Ru Substitution on Dimensionality and Electron Correlations in Ba(Fe_{1-x}Ru_x)_2As_2
We report a systematic angle-resolved photoemission spectroscopy study on
Ba(FeRu)As for a wide range of Ru concentrations (0.15
\emph{x} 0.74). We observed a crossover from two-dimension to
three-dimension for some of the hole-like Fermi surfaces with Ru substitution
and a large reduction in the mass renormalization close to optimal doping.
These results suggest that isovalent Ru substitution has remarkable effects on
the low-energy electron excitations, which are important for the evolution of
superconductivity and antiferromagnetism in this system.Comment: 4 pages, 4 figure
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