03883nam 22005895 450 991029987730332120200703010732.03-319-67825-610.1007/978-3-319-67825-2(CKB)4100000000881534(DE-He213)978-3-319-67825-2(MiAaPQ)EBC5103915(PPN)258872950(PPN)220128553(EXLCZ)99410000000088153420171013d2018 u| 0engurnn|008mamaatxtrdacontentcrdamediacrrdacarrierHandheld Total Chemical and Biological Analysis Systems Bridging NMR, Digital Microfluidics, and Semiconductors /by Ka-Meng Lei, Pui-In Mak, Man-Kay Law, Rui Paulo Martins1st ed. 2018.Cham :Springer International Publishing :Imprint: Springer,2018.1 online resource (XXI, 102 p. 63 illus., 61 illus. in color.) 3-319-67824-8 Includes bibliographical references at the end of each chapters and index.Introduction.- State-of-the-Art CMOS In Vitro Diagnostic Devices.- Electronic-Automated Micro-NMR Assay with DMF Device.- One-Chip Micro-NMR Platform with B0-field Stabilization -- Conclusion and Outlook -- Appendix -- Index.The book Handheld Total Chemical and Biological Analysis Systems: Bridging NMR, Digital Microfluidics, and Semiconductorscenters on the complete design of Nuclear Magnetic Resonance (NMR) microsystems for in vitro chemical and biological assays based on semiconductor chips and portable magnet. Different sensing mechanisms for CMOS in vitro assay are compared, key design criteria of the CMOS transceiver for NMR measurement are revealed, and system-level optimizations of the CMOS NMR platform utilizing digital microfluidic and diverse functions of the CMOS technology are discussed. Two CMOS NMR platforms are implemented, each of these focuses on different aspect of optimization. Shows literature review about state-of-the-art CMOS in vitro diagnosis systems and their sensing mechanisms; Shows brief physics background on biological sensing with NMR; Shows detailed design of the CMOS transceiver for NMR experiments; Describes the first CMOS NMR platform integrated with digital microfluidic devices for electronic-automated sample management; Demonstrates magnetic field stabilization for the portable magnet to enhance the robustness of the NMR platform with the aid of CMOS vertical Hall sensor.Electronic circuitsElectronicsMicroelectronicsBiomedical engineeringCircuits and Systemshttps://scigraph.springernature.com/ontologies/product-market-codes/T24068Electronics and Microelectronics, Instrumentationhttps://scigraph.springernature.com/ontologies/product-market-codes/T24027Biomedical Engineering and Bioengineeringhttps://scigraph.springernature.com/ontologies/product-market-codes/T2700XElectronic circuits.Electronics.Microelectronics.Biomedical engineering.Circuits and Systems.Electronics and Microelectronics, Instrumentation.Biomedical Engineering and Bioengineering.621.3815Lei Ka-Mengauthttp://id.loc.gov/vocabulary/relators/aut1065298Mak Pui-Inauthttp://id.loc.gov/vocabulary/relators/autLaw Man-Kayauthttp://id.loc.gov/vocabulary/relators/autMartins Rui Pauloauthttp://id.loc.gov/vocabulary/relators/autBOOK9910299877303321Handheld Total Chemical and Biological Analysis Systems2544409UNINA04107nam 2200637Ia 450 991096456510332120251117082137.00-309-14475-20-309-13959-7(CKB)2550000000004416(OCoLC)526717560(CaPaEBR)ebrary10333692(SSID)ssj0000344034(PQKBManifestationID)11252712(PQKBTitleCode)TC0000344034(PQKBWorkID)10310120(PQKB)10043843(Au-PeEL)EBL3378527(CaPaEBR)ebr10333692(OCoLC)923280709(MiAaPQ)EBC3378527(BIP)53856532(BIP)27725305(EXLCZ)99255000000000441620090917d2009 ua 0engurcn|||||||||txtccrUncertainty management in remote sensing of climate data summary of a workshop /Martha McConnell and Scott Weidman, rapporteurs1st ed.Washington, D.C. National Academies Press20091 online resource (63 p.) "Board on Atmospheric Sciences and Climate, Climate Research Committee, Board on Mathematical Sciences and Their Applications, Committee on Applied and Theoretical Statistics, Space Studies Board, Committee on Earth Studies, Division on Earth and Life Studies, Division on Engineering and Physical Sciences, National Research Council."0-309-13958-9 Includes bibliographical references.Intro -- Preface -- Acknowledgments -- Contents -- 1 Introduction -- 2 Cross-Cutting Issues -- 3 Concluding Thoughts -- References -- Appendix A: Workshop Agenda -- Appendix B: Summaries of Workshop Presentations -- Appendix C: Planning Committee andRapporteur Biographies.Great advances have been made in our understanding of the climate system over the past few decades, and remotely sensed data have played a key role in supporting many of these advances. Improvements in satellites and in computational and data-handling techniques have yielded high quality, readily accessible data. However, rapid increases in data volume have also led to large and complex datasets that pose significant challenges in data analysis. Uncertainty characterization is needed for every satellite mission and scientists continue to be challenged by the need to reduce the uncertainty in remotely sensed climate records and projections. The approaches currently used to quantify the uncertainty in remotely sensed data lack an overall mathematically based framework. An additional challenge is characterizing uncertainty in ways that are useful to a broad spectrum of end-users. In December 2008, the National Academies held a workshop, summarized in this volume, to survey how statisticians, climate scientists, and remote sensing experts might address the challenges of uncertainty management in remote sensing of climate data. The workshop emphasized raising and discussing issues that could be studied more intently by individual researchers or teams of researchers, and setting the stage for possible future collaborative activities.Satellite meteorologyUnited StatesData processingCongressesClimatic changesUnited StatesRemote sensingData processingCongressesClimatic changesUnited StatesData processingManagementCongressesSatellite meteorologyData processingClimatic changesRemote sensingData processingClimatic changesData processingManagement363.73874McConnell Martha Clarke1863010Weidman Scott1811384National Research Council (U.S.).Board on Atmospheric Sciences and Climate.MiAaPQMiAaPQMiAaPQBOOK9910964565103321Uncertainty management in remote sensing of climate data4469334UNINA