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200 10$aChildren & libraries$b[electronic resource] $egetting it right /$fVirginia A. Walter
210   $aChicago $cAmerican Library Association$d2001
215   $a1 online resource (167 p.)
300   $aDescription based upon print version of record.
311   $a0-8389-0795-4 
320   $aIncludes bibliographical references and index.
327   $aIntroduction; Where We Came From; Where We Are Today; Warning Signs; The Changing Lives of Children; Emerging Trends in Library Services for Children; Future Libraries and Future Kids; Getting It Right; Afterword; Appendix; References; Index; 
330   $aWhile "getting it right" for kids in libraries can be a challenge?as rapid technology changes impact both library services and the needs and expectations of children?it is a goal that warrants serious attention. This visionary book by respected children's library specialist and advocate Virginia Walter is a call to action for libraries...to consider children as vital participants in the community, as well as serious readers and technology users. Children & Libraries: Getting it Right helps you to create a new vision statement, articulate heartfelt goals, and create glorious kid spaces in the l
606   $aChildren's librarians$zUnited States
606   $aChildren's libraries$zUnited States
606   $aPublic libraries$zUnited States
606   $aYoung adult services librarians$zUnited States
606   $aYoung adults' libraries$zUnited States
608   $aElectronic books.
615  0$aChildren's librarians
615  0$aChildren's libraries
615  0$aPublic libraries
615  0$aYoung adult services librarians
615  0$aYoung adults' libraries
676   $a027.62/5
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200 10$aPhysics-guided machine learning for prediction of cloud properties in satellite-derived solar data $epreprint /$fGrant Buster [and seven others]
210  1$aGolden, CO :$cNational Renewable Energy Laboratory,$dMay 2021.
215   $a1 online resource (4 pages) $ccolor illustrations
225 1 $aNREL/CP ;$v6A20-79705
300   $a"May 2021."
300   $a"Presented at the 48th IEEE Photovoltaic Specialists Conference (PVSC 48), June 20-25, 2020."
320   $aIncludes bibliographical references (page 4).
517   $aPhysics-guided machine learning for prediction of cloud properties in satellite-derived solar data 
606   $aMachine learning
606   $aCloud computing$zUnited States
606   $aSolar energy$zUnited States
615  0$aMachine learning.
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700   $aBuster$b Grant$01386949
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