LEADER 01242cam0-2200349---450- 001 990004225040403321 005 20120326151015.0 010 $a84-313-1750-7 035 $a000422504 035 $aFED01000422504 035 $a(Aleph)000422504FED01 035 $a000422504 100 $a19990604d2000----km-y0itay50------ba 101 1 $aspa$cger 102 $aES 105 $a--------001yy 200 1 $a<>ideales de Don Quijote en el cambio de valores desde la Edad Media hasta el Barroco$ela utopia restaurativa de la Edad de Oro$fHeinz-Peter Endress$gtraducción y adaptación de Mercedes Figueras 210 $aPamplona$cEUNSA$d2000 215 $a182 p.$d24 cm 225 1 $aAnejos de Rilce$v32 454 0$12001$aDon Quijotes Ideale im Umbruch der Werte vom Mittelalter bis zum Barock$919123 610 0 $aCervantes Saavedra, Miguel de$aDon Chisciotte 676 $a863.3 700 1$aEndress,$bHeinz-Peter$0166503 702 1$aFigueras,$bMercedes 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990004225040403321 952 $a863.3 CERV/S 52$bDip.f.m.10641$fFLFBC 959 $aFLFBC 996 $aDon Quijotes Ideale im Umbruch der Werte vom Mittelalter bis zum Barock$919123 997 $aUNINA LEADER 00884nam2-2200325---450 001 990001974410203316 005 20200903070622.0 035 $a000197441 035 $aUSA01000197441 035 $a(ALEPH)000197441USA01 035 $a000197441 100 $a20040901d1980----km-y0itay0103----ba 101 $arus 102 $aRU 105 $a||||||||001yy 200 1 $a4 : Povesti$fVladimir Tendrjakov 210 $aMoskva$cHudo?estvennaja literatura$d1980 215 $a701 p.$d20 cm 410 0$12001 454 1$12001 461 1$1001000197434$12001$aSobranie socinenij v cetyreh tomah 676 $a891.7 700 1$aTENDRJAKOV,$bVladimir Fedorovic$0565846 801 0$aIT$bsalbc$gISBD 912 $a990001974410203316 951 $aVIII.1.B. 154/4(II r A 197/4)$b92800 L.M.$cII r A 959 $aBK 969 $aUMA 996 $aPovesti$91046739 997 $aUNISA LEADER 05326oam 2200445 450 001 9910483177103321 005 20210419131852.0 010 $a3030573583 010 $z3030573575 035 $a(CKB)4100000011558768 035 $a(MiAaPQ)EBC6386164 035 $a(DE-He213)978-3-030-57358-4 035 $a(PPN)252507177 035 $a(EXLCZ)994100000011558768 100 $a20210419d2021 uy 0 101 0 $aeng 135 $aurcn#---||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aQuantitative risk analysis of air pollution health effects /$fLouis Anthony Cox Jr 210 1$aCham, Switzerland :$cSpringer,$d[2021] 210 4$d©2021 215 $a1 online resource 225 1 $aInternational series in operations research & management science ;$vVolume 299 327 $aPart I: Estimating and Simulating Dynamic Health Risks -- Chapter 1: Scientific Method for Health Risk Analysis: The Example of Fine Particulate Matter Air Pollution and COVID-19 Mortality Risk -- Chapter 2: Modeling Nonlinear Dose-Response Functions: Regression, Simulation, and Causal Bayesian Networks -- Chapter 3: Simulating Exposure-Related Health Effects: Basic Ideas -- Chapter 4: Case Study: Occupational Health Risks from Crystalline Silica -- Chapter 5: Case Study: Health Risks from Asbestos Exposures -- Chapter 6: Nonlinear Dose-Time-Response Risk Models for Protecting Worker Health -- Part 2: Statistics, Causality, and Machine Learning for Health Risk Assessment -- Chapter 7: Why Not Replace Quantitative Risk Assessment Models with Regression Models -- Chapter 8: Causal vs. Spurious Spatial Exposure-Response Associations in Health Risk Analysis -- Chapter 9: Methods of Causal Analysis for Health Risk Assessment -- Chapter 10: Clarifying Exposure-Response Regression Coefficients with Bayesian Networks: Blood Lead-Mortality Associations an Example -- Chapter 11: Case Study: Does Molybdenum Decrease Testosterone -- Chapter 12: Case Study: Are Low Concentrations of Benzene Disproportionately Dangerous -- Part III: Public Health Effects Of Fine Particulate Matter Air Pollution -- Chapter 13: Socioeconomic Correlates of Air Pollution and Heart Disease -- Chapter 14: How Realistic are Estimates of Health Benefits from Air Pollution Control -- Chapter 15: Do Causal Exposure Concentration-Response Relations -- Chapter 16: How Do Exposure Estimation Errors Affect Estimated Exposure-Response Relations -- Chapter 17: Have Decreases in Air Pollution Reduced Mortality Risks in the United States -- Chapter 18: Improving Causal Determination -- Chapter 19: Communicating More Clearly about Deaths Caused by Air Pollution. 330 $aThis book highlights quantitative risk assessment and modeling methods for assessing health risks caused by air pollution, as well as characterizing and communicating remaining uncertainties. It shows how to apply modern data science, artificial intelligence and machine learning, causal analytics, mathematical modeling, and risk analysis to better quantify human health risks caused by environmental and occupational exposures to air pollutants. The adverse health effects that are caused by air pollution, and preventable by reducing it, instead of merely being statistically associated with exposure to air pollution (and with other many conditions, from cold weather to low income) have proved to be difficult to quantify with high precision and confidence, largely because correlation is not causation. This book shows how to use recent advances in causal analytics and risk analysis to determine more accurately how reducing exposures affects human health risks. Quantitative Risk Analysis of Air Pollution Health Effects is divided into three parts. Part I focuses mainly on quantitative simulation modelling of biological responses to exposures and resulting health risks. It considers occupational risks from asbestos and crystalline silica as examples, showing how dynamic simulation models can provide insights into more effective policies for protecting worker health. Part II examines limitations of regression models and the potential to instead apply machine learning, causal analysis, and Bayesian network learning methods for more accurate quantitative risk assessment, with applications to occupational risks from inhalation exposures. Finally, Part III examines applications to public health risks from air pollution, especially fine particulate matter (PM2.5) air pollution. The book applies freely available browser analytics software and data sets that allow readers to download data and carry out many of the analyses described, in addition to applying the techniques discussed to their own data. 410 0$aInternational series in operations research & management science ;$vVolume 299. 606 $aAir$xPollution$xRisk assessment 606 $aHealth risk assessment$xStatistical methods 615 0$aAir$xPollution$xRisk assessment. 615 0$aHealth risk assessment$xStatistical methods. 676 $a363.7392 700 $aCox$b Louis Anthony$cJr.,$01229718 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bUtOrBLW 912 $a9910483177103321 996 $aQuantitative risk analysis of air pollution health effects$92854512 997 $aUNINA