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Copyright and reuse:The Warwick Research Archive Portal (WRAP) makes this work by researchers of the University of Warwick available open access under the following conditions. Copyright © and all moral rights to the version of the paper presented here belong to the individual author(s) and/or other copyright owners. To the extent reasonable and practicable the material made available in WRAP has been checked for eligibility before being made available.Copies of full items can be used for personal research or study, educational, or not-for profit purposes without prior permission or charge. Provided that the authors, title and full bibliographic details are credited, a hyperlink and/or URL is given for the original metadata page and the content is not changed in any way.Publisher's statement: © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. A note on versions:The version presented here may differ from the published version or, version of record, if you wish to cite this item you are advised to consult the publisher's version. Please see the 'permanent WRAP url' above for details on accessing the published version and note that access may require a subscription. Abstract-Failure diagnosis for large compute clusters using only message logs is known to be incomplete. Recent availability of resource use data provides another potentially useful source of data for failure detection and diagnosis. Early work combining message logs and resource use data for failure diagnosis has shown promising results. This paper describes the CRUMEL framework which implements a new approach to combining rationalized message logs and resource use data for failure diagnosis. CRUMEL identifies patterns of errors and resource use and correlates these patterns by time with system failures. Application of CRUMEL to data from the Ranger supercomputer has yielded improved diagnoses over previous research. CRUMEL has: (i) showed that more events correlated with system failures can only be identified by applying different correlation algorithms, (ii) confirmed six groups of errors, (iii) identified Lustre I/O resource use counters which are correlated with occurrence of Lustre faults which are potential flags for online detection of failures, (iv) matched the dates of correlated error events and correlated resource use with the dates of compute node hangups and (v) identified two more error groups associated with compute node hang-ups. The pre-processed data will be put on the public domain in September, 2016.

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Background and Objectives Measuring head circumference (HC) of newborns is an important tool for evaluating intra-uterine brain development. HC reference charts currently in use in Nigeria are not representative of the local population. We thus present locally derived HC reference data for Nigerian infants at birth. Subjects and Methods We reviewed birth records of all infants at the Jos University Teaching Hospital (JUTH) over a 10 year period from January 2006. JUTH is a tertiary care center offering obstetric services to a large population of women in Jos and its environs. All births with gestational age between 28 and 42 weeks were included in the study. STATA version 14 was used to calculate gestational age associated HC percentile measurements. Results We included 18 282 babies to generate the reference values. The mean HC value was 34.4 ± 2.1 cm (M = 34.6 ± 2.16 cm, F = 34.1 ± 2.02 cm, p < 0.001). Our HC reference values significantly differ from the USA and INTERGROWTH-21 charts currently in use in our country. Mean HC was higher in male infants compared with female infants. This difference was uniformly so across all gestational age groups. Conclusions The use of our locally derived HC reference values could be more appropriate in defining normal head growth in Nigerian infant populations thereby improving newborn care.