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An Advanced Statistical Approach to Data-Driven Earthquake Engineering

JOURNAL OF EARTHQUAKE ENGINEERING 2020年第8期24卷 1245-1269页

作者： Song, Ikkyun Cho, In Ho Wong, Raymond K. W. Iowa State Univ Dept Civil Construct & Environm Engn Ames IA 50011 USA Iowa State Univ Dept Stat Ames IA 50011 USA

Decades-long experimental databases become accessible in global earthquake engineering community. Yet, complex interactions of a multitude of variables pose formidable challenges to data-driven research. We embarked upon developing an advanced statistical learning and prediction framework with the generalized additive model (GAM). We showed promising performance of GAM with applications to existing RC shear wall databases. Without any prejudice, GAM can predict structural responses accurately using raw databases, and also can identify salient attributes. This study addresses computational implementation and parallel processing, and all codes are made publicly available to promote data-driven research of earthquake engineering community.

关键词： Statistical Learning and Prediction Data-driven Earthquake Engineering generalized additive model Reinforced Concrete Shear Wall

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Gradients of flow regulation shape community structures of stream fishes and insects within a catchment subject to typhoon events

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SCIENCE OF THE TOTAL ENVIRONMENT 2020年 748卷 141398-141398页

作者： Nukazawa, Kei Shirasaka, Kodai Kajiwara, Shinsuke Saito, Tsuyoshi Irie, Mitsuteru Suzuki, Yoshihiro Univ Miyazaki Fac Engn Dept Civil & Environm Engn Gakuen Kibanadai Nishi 1-1 Miyazaki 8892192 Japan Kyushu Elect Power Co Inc Chuo Ku Watanabe Dori 2-1-82 Fukuoka 8100004 Japan West Japan Engn Consultants Inc Chuo Ku Watanabe Dori 1-1-1 Fukuoka 8100004 Japan

Alterations in natural flow regimes caused by dams can significantly alter the aquatic habitats of stream organisms. However, few studies have characterized flow regulation to assess its impacts on stream fauna in the context of interannually variable extreme floods. This study aims to understand the variation in stream animals along flow regulation gradients due to hydropower dams in a catchment experiencing typhoons. We observed freshwater fishes and stream insects at fully regulated sites (receiving residual flow), moderately regulated sites (receiving hydropower outflow), and nonregulated site (tributary) in the Mimi River catchment in southern Japan, in summer and winter from 2010 to 2018. We computed indicators of hydrologic alteration (IHA) in each calendar/water (July to June) year from 2007 to 2017 and selected subsets of IHA based on principal component analysis (PCA) and variance inflation factor. The largest variance was mainly explained by minimum discharge levels (e.g., 30-day annual minimum) and flow variability among IHAs, distinguishing the moderately regulated and nonregulated sites from fully regulated sites because of residual flow and suppressed high pulses in the fully regulated sites. generalized additive models revealed that annual maxima of specific discharge were most significant predictors of fish and insectmetrics while its effects were generally inconsistent between summer and winter. Non-metric multidimensional scaling revealed that insect communities were clustered into the regulation extents in both seasons. The differences in winter fauna between the regulated and nonregulated sites, characterized by Ephemeroptera-Plecoptera-Trichoptera abundance, were associated with maximum discharge and high pulse numbers. Fish community variation did not correspond to flow regime gradients. Our findings on mechanistic ecohydrological consequences of various flow regulations, supported by long-term observations, will be useful for river managers a

关键词： Aquatic invertebrates generalized additive model Indicators of hydrologic alteration Non-metric multidimensional scaling Principal component analysis

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Association between ambient particulate matter and hospital outpatient visits for chronic obstructive pulmonary disease in Lanzhou, China

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ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH 2020年第18期27卷 22843-22854页

作者： Bao, Hairong Dong, Jiyuan Liu, Xiaoju Tan, Enli Shu, Juan Li, Sheng Lanzhou Univ Dept Gerontal Resp Med Hosp 1 Lanzhou 730000 Peoples R China Lanzhou Univ Sch Publ Hlth 199 Donggang West Rd Lanzhou 730000 Chengguan Distr Peoples R China First Peoples Hosp Lanzhou City Lanzhou 730050 Peoples R China

Until now, a number of epidemiological studies have focused on the association between ambient particulate matter pollution and chronic obstructive pulmonary disease (COPD), especially in developed countries. There are limited evidences on the association between short-term exposure to particulate matters (PM2.5, PMC, and PM10) and overall hospital outpatient visits for COPD at the same time in China. Thus, a time-series analysis on the short-term association between three subtypes of PM (PM2.5, PMC, and PM10) and daily hospital outpatients for COPD in Lanzhou, China was conducted, from 2014 to *** over dispersed, generalized additive model was used to analyze the associations after controlling for time trend, weather conditions, day of the week, and holidays. Stratified analyses were also performed by age and gender. The results disclosed that a 10-mu g/m(3) increase in PM2.5 concentration at a lag of 0-7 days was associated with 1.190% (95% CI 0.1762.215%). For PMc, therewere not statistically significant effects at any lag days, but we could find the greatest effect at lag07 that a 10-mu g/m(3) increase in concentration was associated with 0.014% (95% CI - 0.0650.093%). PM10 also exerted a high effect for COPD (0.185% increase;95% CI - 0.0460.417%) when 6 days of exposures (lag6), however, no significance relationship could be found. For COPD among males, positive results were observed for PM2.5 with lags of 0-7 days, a 10-mu g/m(3) increase was 1.184% (95% CI 0.0952.284%). The effect of PM2.5 on females was also most significant at lag07, a 10-mu g/m(3) increase was 1.254% (95% CI 0.0532.469%). For those aged < 65 years old, PM2.5 was not statistically significant at all lag days, but it reached the maximum at lag07, a 10-mu g/m(3) increase was 0.978% (95% CI - 0.1392.108%). For those aged 65 >= years old and older, PM2.5 had a statistically significant lag effect at lag1, lag2, lag3, lag02, lag03, lag04, lag05, lag06, and lag07, and it was most significant

关键词： Particulate matter Chronic obstructive pulmonary disease Daily outpatient visits generalized additive model

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Short-term effect of extreme air temperature on hospital emergency room visits for cardiovascular diseases from 2009 to 2012 in Beijing, China

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ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH 2020年第30期27卷 38029-38037页

作者： Ma, Yuxia Jiao, Haoran Zhang, Yifan Feng, Fengliu Cheng, Bowen Ma, Bingji Yu, Zhiang Lanzhou Univ Coll Atmospher Sci Key Lab Semiarid Climate Change Minist Educ Lanzhou 730000 Peoples R China

Extreme air temperature directly affected human health. However, the short-term effect of extreme air temperature on the incidence of cardiovascular diseases has rarely been reported in China. In this study, we focused on Beijing, China, and assessed the effects of cold/warm days and nights on the number of hospital emergency room (ER) visits for cardiovascular diseases from 2009 to 2012. We used a generalized additive model (GAM) to estimate the association between extreme air temperature and the number of hospital ER visits for cardiovascular diseases. We divided the entire study group into two gender subgroups and three age subgroups. The results showed that the short-term effect of extreme air temperature on hospital ER visits for cardiovascular diseases was more profound in females and the elderly (aged >= 75 years). Among all the study subgroups, the highest relative risk (RR) of cardiovascular diseases associated with extremely cold days, warm days, cold nights, and warm nights was 3.0% (95% CI, 1.6%-4.4%), 0.8% (95% CI, - 0.9%-2.6%), 2.8% (95% CI, 1.6%-4.2%), and 1.8% (95% CI, 0.6%-4.3%), respectively. Overall, the effect of extremely low air temperature (during both days and nights) on the incidence of cardiovascular diseases was stronger and more acute than that of extremely high air temperature.

关键词： Extreme air temperature Cardiovascular diseases generalized additive model

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Climate-informed models benefit hindcasting but present challenges when forecasting species-habitat associations

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ECOGRAPHY 2022年第10期2022卷 e06189-e06189页

作者： Barnes, Cheryl L. Essington, Timothy E. Pirtle, Jodi L. Rooper, Christopher N. Laman, Edward A. Holsman, Kirstin K. Aydin, Kerim Y. Thorson, James T. Univ Washington Sch Aquat & Fishery Sci Seattle WA 98195 USA NOAA Alaska Reg Off Natl Marine Fisheries Serv Juneau AK USA Fisheries & Oceans Canada Nanaimo BC Canada NOAA Alaska Fisheries Sci Ctr Natl Marine Fisheries Serv Seattle WA USA

Although species distribution models (SDMs) are commonly used to hindcast fine-scale population metrics, there remains a paucity of information about how well these models predict future responses to climate. Many conventional SDMs rely on spatially-explicit but time-invariant conditions to quantify species distributions and densities. We compared these status quo 'static' models with more climate-informed 'dynamic' SDMs to assess whether the addition of time-varying processes would improve hindcast performance and/or forecast skill. Here, we present two groundfish case studies from the Bering Sea - a high latitude system that has recently undergone considerable warming. We relied on conventional statistics (R-2, % deviance explained, UBRE or GCV) to evaluate hindcast performance for presence-absence, numerical abundance and biomass of arrowtooth flounder Atheresthes stomias and walleye pollock Gadus chalcogrammus. We then used retrospective skill testing to evaluate near-term forecast skill. Retrospective skill testing enables direct comparisons between forecasts and observations through a process of fitting and forecasting nested submodels within a given time series. We found that the inclusion of time-varying covariates improved hindcasts. However, dynamic models either did not improve or decreased forecast skill relative to static SDMs. This is likely a result of rapidly changing temperatures within the ecosystem, which required models to predict species responses to environmental conditions that were outside the range of observed values. Until additional model development allows for fully dynamic predictions, static model forecasts (or persistence forecasts from dynamic models) may serve as reliable placeholders, especially when anomalous conditions are anticipated. Nonetheless, our findings demonstrate support for the use of retrospective skill testing rather than selecting forecast models a priori based on their ability to quantify species-habitat association

关键词： climate change forecast skill generalized additive model hindcast performance retrospective skill testing species distribution model

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Predicting diversity changes in subalpine moorland ecosystems based on geometry of species distributions and realistic area loss

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JOURNAL OF VEGETATION SCIENCE 2022年第5期33卷 e13150-e13150页

作者： Makishima, Daichi Ishii, Naohiro Sutoh, Rui Goto, Akihito Kawai, Yutaka Taniguchi, Hayami Uchida, Kei Shimazaki, Masaya Nakashizuka, Tohru Suyama, Yoshihisa Hikosaka, Kouki Sasaki, Takehiro Yokohama Natl Univ Grad Sch Environm & Informat Sci 79-7 Tokiwadai Yokohama Kanagawa 2408501 Japan Tohoku Univ Field Sci Ctr Grad Sch Agr Sci Osaki Japan Tohoku Univ Grad Sch Life Sci Sendai Miyagi Japan Univ Tokyo Inst Sustainable Agroecosyst Serv Tokyo Japan Forestry & Forest Prod Res Inst Tsukuba Ibaraki Japan

Question How does plant species richness respond to simulated area loss based on the realistic geometry of area loss in subalpine moorland ecosystems? Location Hakkoda mountain range, Aomori, Japan. Methods We constructed species distribution models based on relationships between species distributions and environmental conditions in subalpine moorland ecosystems. We then simulated moorland area loss based on the realistic geometry of area loss from the past (1967) to the present (2019) to predict future changes in plant diversity. Here, we defined the realistic geometry of area loss as the plausible spatial pattern of future habitat loss. Finally, we analyzed how the rate of species loss in response to the realistic area loss can be explained by a range of factors including spatial patterns in species distributions, total number of species present, and environmental variables for the focal moorland. Results Within each moorland site, areas prone or those less prone to be lost were distributed non-randomly at a local scale. In general, the patterns of species loss caused by the realistic area loss differed from those caused by random area loss. At most sites, realistic area loss caused a relatively small decline in species richness up to a certain threshold of area loss, and accelerating decline thereafter. None of the factors can explain the rate of decrease in species richness caused by the realistic area loss. At the species level, however, species with lower occurrence rates at a given site can be lost earlier than those with higher occurrence rates by the realistic area loss. Conclusions Patterns of habitat loss and species distributions are not spatially random, and the classical approach based on the species-area relationship assuming random area loss can thus either under- or overestimate the risk of species loss.

关键词： climate change generalized additive model global warming historical landscape kriging random forest

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PM10 and Other Climatic Variables Are Important Predictors of Seasonal Variability of Coccidioidomycosis in Arizona

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MICROBIOLOGY SPECTRUM 2022年第2期10卷 e0148321页

作者： Kollath, Daniel R. Mihaljevic, Joseph R. Barker, Bridget M. No Arizona Univ Pathogen & Microbiome Inst Flagstaff AZ 86011 USA No Arizona Univ Sch Informat Comp & Cyber Syst Flagstaff AZ 86011 USA

Coccidioidomycosis (Valley fever) is a disease caused by the fungal pathogens Coccidioides immitis and Coccidioides posadasii that are endemic to the southwestern United States and parts of Mexico and South America. Throughout the range where the pathogens are endemic, there are seasonal patterns of infection rates that are associated with certain climatic variables. Previous studies that looked at annual and monthly relationships of coccidioidomycosis and climate suggest that infection numbers are linked with precipitation and temperature fluctuations;however, these analytic methods may miss important nonlinear, nonmonotonic seasonal relationships between the response (Valley fever cases) and explanatory variables (climate) influencing disease outbreaks. To improve our current knowledge and to retest relationships, we used case data from three counties of high endemicity in southern Arizona paired with climate data to construct a generalized additive statistical model that explores which meteorological parameters are most useful in predicting Valley fever incidence throughout the year. We then use our model to forecast the pattern of Valley fever cases by month. Our model shows that maximum monthly temperature, average PM10, and total precipitation 1 month prior to reported cases (lagged model) were all significant in predicting Valley fever cases. Our model fits Valley fever case data in the region of endemicity of southern Arizona and captures the seasonal relationships that predict when the public is at higher risk of being infected. This study builds on and retests relationships described by previous studies regarding climate variables that are important for predicting risk of infection and understanding this fungal pathogen. IMPORTANCE The inhalation of environmental infectious propagules from the fungal pathogens Coccidioides immitis and Coccidioides posadasii by susceptible mammals can result in coccidioidomycosis (Valley fever). Arizona is known to be a reg

关键词： Valley fever human fungal pathogen GAM climate coccidioidomycosis Coccidioides disease ecology generalized additive model mycology

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A More Efficient Causal Mediator model Without the No-Unmeasured-Confounder Assumption

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MULTIVARIATE BEHAVIORAL RESEARCH 2020年第4期55卷 531-552页

作者： Brandt, Holger Univ Zurich Dept Psychol Binzmuhlestr 14-28 CH-8050 Zurich Switzerland

Mediator models have been developed primarily under the assumption of no-unmeasured-confounding. In many situations, this assumption is violated and may lead to the identification of mediator variables that actually are statistical artifacts. The rank preserving model (RPM) is an alternative approach to estimate controlled direct and mediator effects. It is based on the structural mean models framework and a no-effect-modifier assumption. The RPM assumes that unobserved confounders do not interact with treatment or mediators. This assumption is often more plausible to hold than the no-unmeasured-confounder assumption. So far, models using the no-effect-modifier assumption have been rarely used, which might be due to its low power and inefficiency in many scenarios. Here, a semi-parametric nonlinear extension, the nRPM, is proposed that overcomes this inefficiency using thin plate regression splines that both increase the predictive power of the model and decrease the misspecification present in many situations. In a simulation study, it is shown that the nRPM provides estimates that are robust against the violation of the no-effect-modifier assumption and that are substantively more efficient than those of the RPM. The model is illustrated using a data set on CD4 cell counts in a context of the human immunodeficiency virus (HIV).

关键词： Mediator model structural mean models thin plate regression spline generalized additive model no-unmeasured-confounder rank preserving model no-effect-modifier

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The impact of autonomous vehicles on urban traffic network capacity: an experimental analysis by microscopic traffic simulation

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TRANSPORTATION LETTERS-THE INTERNATIONAL JOURNAL OF TRANSPORTATION RESEARCH 2020年第8期12卷 540-549页

作者： Lu, Qiong Tettamanti, Lamas Horcher, Daniel Varga, Istvan Budapest Univ Technol & Econ Dept Control Transportat & Vehicle Syst Budapest Hungary Imperial Coll Dept Civil & Environm Engn London England Budapest Univ Technol & Econ Fac Transportat Engn & Vehicle Engn Dept Transport Technol & Econ Budapest Hungary

Urban commuters have been suffering from traffic congestion for a long time. In order to avoid or mitigate the congestion effect, it is significant to know how the introduction of autonomous vehicles (AVs) influence the road capacity . The effects that AVs bring to the macroscopic fundamental diagram (MFD) were investigated through microscopic traffic simulations. This is a key issue as the MFD is a basic model to describe road capacity in practical traffic engineering. Accordingly, the paper investigates how the different percentage of AVs affects the urban MFD. A detailed simulation study was carried out by using SUMO both with an artificial grid road network and a real-world network in Budapest. On the one hand, simulations clearly show the capacity improvement along with AVs penetration growth. On the other hand, the paper introduces an efficient modeling for MFDs with different AVs rates by using the generalized additive model (GAM).

关键词： Autonomous vehicles macroscopic fundamental diagram urban road capacity SUMO generalized additive model

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Association between extreme heat and hospital admissions for cataract patients in Hefei, China

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ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH 2020年第36期27卷 45381-45389页

作者： Xie, Jingui Zhu, Yongjian Fan, Yiming Xie, Linbo Xie, Ruijin Huang, Fengming Cao, Liqing Tech Univ Munich Sch Management Bildungscampus 9 D-74076 Heilbronn Germany Univ Sci & Technol China Sch Management 96 Jin Zhai Rd Hefei 230026 Anhui Peoples R China Anhui Hlth Coll 9 Xue Yuan Rd Chizhou 247099 Anhui Peoples R China Univ Sci & Technol China Affiliated Hosp 1 17 Lu Jiang Rd Hefei 230001 Anhui Peoples R China

Cataract is the first cause of blindness and the major cause of visual impairment worldwide. Under conditions of global warming, researchers have begun to give attention to the influence of increasing temperature on cataract patients. Our paper aimed to investigate the association between extreme heat and hospital admissions for cataract in Hefei, China. Based on data from the New Rural Cooperative Medical System and National Meteorological Information Center, we used a generalized additive model and a distributed lag nonlinear model to examine the relationship between extreme heat and hospitalizations for cataract, with consideration of cumulative and lagged effects. When current mean temperature was above 28 degrees C, each 1 degrees C rise was associated with a 4% decrease in the number of cataract admissions (RR = 0.96, 95% CI = 0.94-0.98). The cumulative relative risk over 11 days of lag was the lowest, which indicated that every 1 degrees C increase in mean temperature above 28 degrees C was associated with a 19% decrease in the number of hospital admissions for cataract (RR = 0.81, 95% CI = 0.75-0.88). In subgroup analyses, the negative association between extreme heat and hospital admissions for cataract was stronger among patients who were not admitted to provincial-level hospitals. In conclusion, this paper found that extreme heat was negatively associated with cataract hospitalizations in Hefei, providing useful information for hospitals and policymakers.

关键词： Extreme heat Hospital admission Cataract generalized additive model Distributed lag nonlinear model

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