Ancient Greece

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    The Elegance of a Hedgehog
    (Europa editions, 2006) Barbery, Muriel
    First paragraph: This is an abstract with hard coded line breaks (not HTML). Start of second paragraph: People with COVID-19 have had a wide range of symptoms reported – ranging from mild symptoms to severe illness. Symptoms may appear 2-14 days after exposure to the virus. Anyone can have mild to severe symptoms. People with these symptoms may have COVID-19: Start of third paragraph: This list does not include all possible symptoms. CDC will continue to update this list as we learn more about COVID-19. Older adults and people who have severe underlying medical conditions like heart or lung disease or diabetes seem to be at higher risk for developing more serious complications from COVID-19 illness.

    Start of 4th paragraph with HTML p tag. This list does not include all possible symptoms. CDC will continue to update this list as we learn more about COVID-19. Older adults and people who have severe underlying medical conditions like heart or lung disease or diabetes seem to be at higher risk for developing more serious complications from COVID-19 illness.

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    Simmons, Cameron
    Director of the Institute of Vector-Borne Disease
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    A comparison of some vibration parameters for the condition monitoring of rolling element bearings
    (1994) Tandon, N
    In the present study some of the vibration parameters used for the detection of defects in rolling element bearings have been compared. Overall RMS, peak, crest factor, power and cepstrum of the vibration acceleration signal of the bearings with defects of different sizes have been measured and compared with those of good bearings. SPM measurements were also performed. The results of the measurements indicate that except for crest factor and SPM, all other parameters have detected defects in the bearings. The defect detectability of overall power is the best followed by peak and RMS measurements.
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    A feature selection technique for classificatory analysis
    (2005) Ahmad, Amir; Dey, Lipika
    Patterns summarizing mutual associations between class decisions and attribute values in a pre-classified database, provide insight into the significance of attributes and also useful classificatory knowledge. In this paper we have proposed a conditional probability based, efficient method to extract the significant attributes from a database. Reducing the feature set during pre-processing enhances the quality of knowledge extracted and also increases the speed of computation. Our method supports easy visualization of classificatory knowledge. A likelihood-based classification algorithm that uses this classificatory knowledge is also proposed. We have also shown how the classification methodology can be used for cost-sensitive learning where both accuracy and precision of prediction are important.