published journal article

Association Between Outdoor Air Pollution and Risk of Malignant and Benign Brain Tumors: The Multiethnic Cohort Study

JNCI Cancer Spectrum

Publication Date

April 1, 2020

Author(s)

Anna H Wu, Jun Wu, Chiuchen Tseng, Johnny Yang, Salma Shariff-Marco, Scott Fruin, Timothy Larson, Veronica W Setiawan, Shahir Masri, Jacqueline Porcel, Jennifer Jain, Thomas C Chen, Daniel O Stram, Loïc Le Marchand, Beate Ritz, Iona Cheng

Abstract

There are increasing concerns about the potential impact of air pollution on chronic brain inflammation and microglia cell activation, but evidence of its carcinogenic effects is limited.We used kriging interpolation and land use regression models to estimate long-term air pollutant exposures of oxides of nitrogen (NOx, NO2), kriging interpolation for ozone (O3), carbon monoxide, and particulate matter (PM2.5, PM10), and nearest monitoring station measurements for benzene for 103 308 men and women from the Multiethnic Cohort, residing largely in Los Angeles County from recruitment (1993–1996) through 2013. We used Cox proportional hazards models to examine the associations between time-varying pollutants and risk of malignant brain cancer (94 men, 116 women) and meningioma (130 men, 425 women) with adjustment for sex, race and ethnicity, neighborhood socioeconomic status, smoking, occupation, and other covariates. Stratified analyses were conducted by sex and race and ethnicity.Brain cancer risk in men increased in association with exposure to benzene (hazard ratio [HR] = 3.52, 95% confidence interval [CI] = 1.55 to 7.55) and PM10 (HR = 1.80, 95% CI = 1.00 to 3.23). Stronger associations with PM10 (HR = 3.02, 95% CI = 1.26 to 7.23), O3 (HR = 2.93, 95% CI = 1.09 to 7.88), and benzene (HR = 4.06, 95% CI = 1.17 to 18.2) were observed among Latino men. Air pollution was unrelated to risk of meningioma except that O3 exposure was associated with risk in men (HR = 1.77, 95% CI = 1.02 to 3.06). Brain cancer risk in women was unrelated to air pollution exposures.Confirmation of these sex differences in air pollution–brain cancer associations and the stronger findings in Latino men in additional diverse populations is warranted.

Suggested Citation
Anna H Wu, Jun Wu, Chiuchen Tseng, Juan Yang, Salma Shariff-Marco, Scott Fruin, Timothy Larson, Veronica W Setiawan, Shahir Masri, Jacqueline Porcel, Jennifer Jain, Thomas C Chen, Daniel O Stram, Loïc Le Marchand, Beate Ritz and Iona Cheng (2020) “Association Between Outdoor Air Pollution and Risk of Malignant and Benign Brain Tumors: The Multiethnic Cohort Study”, JNCI Cancer Spectrum, 4(2), p. pkz107. Available at: 10.1093/jncics/pkz107.

conference paper

Doppelgänger Test Generation for Revealing Bugs in Autonomous Driving Software

2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE)

Publication Date

May 1, 2023

Author(s)

Yuqi Huai, Yuntianyi Chen, Sumaya Almanee, Tuan Ngo, Xiang Liao, Ziwen Wan, Qi Alfred Chen, Joshua Garcia

Abstract

Vehicles controlled by autonomous driving software (ADS) are expected to bring many social and economic benefits, but at the current stage not being broadly used due to concerns with regard to their safety. Virtual tests, where autonomous vehicles are tested in software simulation, are common practices because they are more efficient and safer compared to field operational tests. Specifically, search-based approaches are used to find particularly critical situations. These approaches provide an opportunity to automatically generate tests; however, system-atically producing bug-revealing tests for ADS remains a major challenge. To address this challenge, we introduce DoppelTest, a test generation approach for ADSes that utilizes a genetic algorithm to discover bug-revealing violations by generating scenarios with multiple autonomous vehicles that account for traffic control (e.g., traffic signals and stop signs). Our extensive evaluation shows that DoppelTest can efficiently discover 123 bug-revealing violations for a production-grade ADS (Baidu Apollo) which we then classify into 8 unique bug categories.

Suggested Citation
Yuqi Huai, Yuntianyi Chen, Sumaya Almanee, Tuan Ngo, Xiang Liao, Ziwen Wan, Qi Alfred Chen and Joshua Garcia (2023) “Doppelgänger Test Generation for Revealing Bugs in Autonomous Driving Software”, in 2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE). 2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE), pp. 2591–2603. Available at: 10.1109/ICSE48619.2023.00216.

published journal article

A model of complex travel behavior: Part I—Theoretical development

Transportation Research Part A: General

Publication Date

July 1, 1986

Abstract

This paper presents a policy sensitive approach to modeling travel behavior based on activity pattern analysis. A theoretical model of complex travel behavior is formulated on a recognition of a wide range of interdependencies associated with an individual’s travel decisions in a constrained environment. Travel is viewed as input to a more basic process involving activity decisions. A fundamental tenet of this approach is that travel decisions are driven by the collection of activities that form an agenda for participation; the utility of any specific travel decision can be determined only within the context of the entire agenda. Based on the theoretical model of complex travel behavior, an operational system of models, STARCHILD (Simulation of Travel/Activity Responses to Complex Household Interactive Logistic Decisions), has been developed to examine the formation of household travel/activity patterns, and is presented in a companion paper (Recker et al., 1986).

Suggested Citation
W. W. Recker, M. G. McNally and G. S. Root (1986) “A model of complex travel behavior: Part I—Theoretical development”, Transportation Research Part A: General, 20(4), pp. 307–318. Available at: 10.1016/0191-2607(86)90089-0.

published journal article

Sustainable neighbourhood development: Missed opportunities in southern California

Environment and planning. B, Planning & design

Publication Date

June 1, 2010
Suggested Citation
Ajay Garde, Jean-Daniel Saphores, Richard Matthew and Kristen Day (2010) “Sustainable neighbourhood development: Missed opportunities in southern California”, Environment and planning. B, Planning & design, 37(3), pp. 387–407. Available at: 10.1068/b35098.

Phd Dissertation

A mall in a former life : how converting failing malls into mixed-use neighborhoods impacts sense of community

Publication Date

June 30, 2007

Author(s)

Suggested Citation
MARIELA ALFONZO (2007) A mall in a former life : how converting failing malls into mixed-use neighborhoods impacts sense of community. PhD Dissertation. UC Irvine. Available at: https://uci.primo.exlibrisgroup.com/permalink/01CDL_IRV_INST/17uq3m8/alma991002896829704701.

policy brief

Evaluating Mixed Electric Vehicle and Conventional Fueled Vehicle Fleets for Last-mile Package Delivery

Suggested Citation
Michael Hyland and Dingtong Yang (2023) Evaluating Mixed Electric Vehicle and Conventional Fueled Vehicle Fleets for Last-mile Package Delivery. Policy Brief. ITS-Irvine. Available at: https://metrans.org/assets/research/21-35%20hyland%20psr%20research%20brief%20template.pdf.

conference paper

Applications of path flow estimator for estimating origin-destination trip tables

Proceedings, 7th Hong Kong Society of Transportation Studies Conference

Publication Date

December 1, 2002

Author(s)

Suggested Citation
P. Chootin, A. Chen and W. W. Recker (2002) “Applications of path flow estimator for estimating origin-destination trip tables”, in Proceedings, 7th Hong Kong Society of Transportation Studies Conference.

published journal article

A transactions choice model for forecasting demand for alternative-fuel vehicles

Research in Transportation Economics

Publication Date

January 1, 1996

Author(s)

Suggested Citation
David Brownstone, David S. Bunch, Thomas F. Golob and Weiping Ren (1996) “A transactions choice model for forecasting demand for alternative-fuel vehicles”, Research in Transportation Economics, 4, pp. 87–129. Available at: 10.1016/S0739-8859(96)80007-2.