Jetstream will be the first production cloud resource supporting general science and engineering research within the XD ecosystem. In this report we describe the motivation for proposing Jetstream, the configuration of the Jetstream system as funded by the NSF, the team that is implementing Jetstream, and the communities we expect to use this new system. Our hope and plan is that Jetstream, which will become available for production use in 2016, will aid thousands of researchers who need modest amounts of computing power interactively. The implementation of Jetstream should increase the size and disciplinary diversity of the US research community that makes use of the resources of the XD ecosystem.
Cyberinfrastructure is a word commonly used but lacking a single, precise definition. One recognizes intuitively the analogy with infrastructure, and the use of cyber to refer to thinking or computing -but what exactly is cyberinfrastructure as opposed to information technology infrastructure? Indiana University has developed one of the more widely cited definitions of cyberinfrastructure:Cyberinfrastructure consists of computing systems, data storage systems, advanced instruments and data repositories, visualization environments, and people, all linked together by software and high performance networks to improve research productivity and enable breakthroughs not otherwise possible.A second definition, more inclusive of scholarship generally and educational activities, has also been published and is useful in describing cyberinfrastructure:Cyberinfrastructure consists of computational systems, data and information management, advanced instruments, visualization environments, and people, all linked together by software and advanced networks to improve scholarly productivity and enable knowledge breakthroughs and discoveries not otherwise possible.In this paper, we describe the origin of the term cyberinfrastructure based on the history of the root word infrastructure, discuss several terms related to cyberinfrastructure, and provide several examples of cyberinfrastructure.
This is the sixth annual summary of the International Liaison Committee on Resuscitation International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations. This summary addresses the most recently published resuscitation evidence reviewed by International Liaison Committee on Resuscitation Task Force science experts. Topics covered by systematic reviews include cardiopulmonary resuscitation during transport; approach to resuscitation after drowning; passive ventilation; minimizing pauses during cardiopulmonary resuscitation; temperature management after cardiac arrest; use of diagnostic point-of-care ultrasound during cardiac arrest; use of vasopressin and corticosteroids during cardiac arrest; coronary angiography after cardiac arrest; public-access defibrillation devices for children; pediatric early warning systems; maintaining normal temperature immediately after birth; suctioning of amniotic fluid at birth; tactile stimulation for resuscitation immediately after birth; use of continuous positive airway pressure for respiratory distress at term birth; respiratory and heart rate monitoring in the delivery room; supraglottic airway use in neonates; prearrest prediction of in-hospital cardiac arrest mortality; basic life support training for likely rescuers of high-risk populations; effect of resuscitation team training; blended learning for life support training; training and recertification for resuscitation instructors; and recovery position for maintenance of breathing and prevention of cardiac arrest. Members from 6 task forces have assessed, discussed, and debated the quality of the evidence using Grading of Recommendations Assessment, Development, and Evaluation criteria and generated consensus treatment recommendations. Insights into the deliberations of the task forces are provided in the Justification and Evidence-to-Decision Framework Highlights sections, and priority knowledge gaps for future research are listed.
Many previous attempts by fetal alcohol spectrum disorders researchers to compare data across multiple prospective and retrospective human studies have failed due to both structural differences in the collected data as well as difficulty in coming to agreement on the precise meaning of the terminology used to describe the collected data. Although some groups of researchers have an established track record of successfully integrating data, attempts to integrate data more broadly amongst different groups of researchers have generally faltered. Lack of tools to help researchers share and integrate data has also hampered data analysis. This situation has delayed improving diagnosis, intervention, and treatment before and after birth. We worked with various researchers and research programs in the Collaborative Initiative on Fetal Alcohol Spectrum Disorders (CI-FASD) to develop a set of common data dictionaries to describe the data to be collected, including definitions of terms and specification of allowable values. The resulting data dictionaries were the Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. NIH Public Access Author ManuscriptAlcohol. Author manuscript; available in PMC 2011 November 1. NIH-PA Author ManuscriptNIH-PA Author Manuscript NIH-PA Author Manuscript basis for creating a central data repository (CI-FASD Central Repository) and software tools to input and query data. Data entry restrictions ensure that only data which conform to the data dictionaries reach the CI-FASD Central Repository. The result is an effective system for centralized and unified management of the data collected and analyzed by the initiative, including a secure, long-term data repository. CI-FASD researchers are able to integrate and analyze data of different types, collected using multiple methods, and collected from multiple populations, and data are retained for future reuse in a secure, robust repository.
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