conference paper
Archives: Research Products
published journal article
Individual truck speed estimation from advanced single inductive loops
Transportation Research Record
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Suggested Citation
Yiqiao Li, Andre Y.C. Tok and Stephen G. Ritchie (2019) “Individual truck speed estimation from advanced single inductive loops”, Transportation Research Record, 2673(5), pp. 272–284. Available at: 10.1177/0361198119841289.published journal article
An instantaneous kinematic wave theory of diverging traffic
Transportation Research Part B: Methodological
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Suggested Citation
Wen-Long Jin and H. Michael Zhang (2013) “An instantaneous kinematic wave theory of diverging traffic”, Transportation Research Part B: Methodological, 48(1), pp. 1–16. Available at: 10.1016/j.trb.2012.12.001.research report
Factors affecting speed of motor vehicles on urban arterials: Case of chennai, India
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Suggested Citation
Michael G McNally, R Jayakrishnan, Nesamani Subramanian Kalandiyur and KP Subramanian (2006) Factors affecting speed of motor vehicles on urban arterials: Case of chennai, India.published journal article
Child serum metabolome and traffic-related air pollution exposure in pregnancy
Environmental Research
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Abstract
Background Maternal exposure to traffic-related air pollution during pregnancy has been shown to increase the risk of adverse birth outcomes and childhood disorders. High-resolution metabolomics (HRM) has previously been employed to identify metabolic responses to traffic-related air pollution in adults, including pregnant women. Thus far, no studies have examined metabolic effects of air pollution exposure in utero on neonates. Methods We retrieved stored neonatal blood spots for 241 children born in California between 1998 and 2007. These children were randomly selected from all California birth rolls to serve as birth-year matched controls for children with retinoblastoma identified from the California cancer registry for a case control study of childhood cancer. We estimated prenatal traffic-related air pollution exposure (particulate matter less than 2.5 μm (PM2.5)) during the third-trimester using the California Line Source Dispersion Model, version 4 (CALINE4) based on residential addresses recorded at birth. We employed untargeted HRM to obtain metabolic profiles, and metabolites associated with air pollution exposure were identified using partial least squares (PLS) regression and linear regressions. Biological effects were characterized using pathway enrichment analyses adjusting for potential confounders including maternal age, race/ethnicity, and education. Results In total we extracted 4038 and 4957 metabolite features from neonatal blood spots in hydrophilic interaction (HILIC) chromatography (positive ion mode) and C18 reverse phase columns (negative ion mode), respectively. After controlling for confounding factors, partial least square regression (Variable Importance in Projection (VIP) ≥ 2) selected 402 HILIC positive and 182 C18 negative features as statistically significantly associated with increasing third trimester PM2.5 exposure. Using pathway enrichment analysis, we identified metabolites in oxidative stress and inflammation pathways as being altered, primarily involving lipid metabolism. Conclusion The metabolite features and pathways associated with air pollution exposure in neonates suggest that maternal exposure during late pregnancy contributes to oxidative stress and inflammation in newborn children.
Suggested Citation
Beate Ritz, Qi Yan, Di He, Jun Wu, Douglas I. Walker, Karan Uppal, Dean P. Jones and Julia E. Heck (2022) “Child serum metabolome and traffic-related air pollution exposure in pregnancy”, Environmental Research, 203, p. 111907. Available at: 10.1016/j.envres.2021.111907.research report
Zero-Emission Vehicle Transition in California’s Construction Industry
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Abstract
Although construction equipment generates 2% to 3% of total GHG emissions in California, the construction sector lags behind other industries for decarbonization, primarily due to the systemic challenges of delivering high-capacity electric power to temporary and remote jobsites. This study investigates the primary infrastructure, regulatory, and economic barriers to construction site electrification while exploring technological and policy solutions. Using a multi-faceted approach, the research conducted a literature review, interviewed California Electric Load-Serving Entities, and analyzed emerging mobile charging technologies. Findings indicate that utility support varies by institutional model; municipal utilities often manage requests more efficiently than larger investor-owned utilities, which face complex regulatory hurdles. Key obstacles include local grid capacity limitations, long lead times and high costs for distribution upgrades, and high capital costs for electric machinery. Since the immediate benefits of electrification—the elimination of tailpipe emissions and significant noise reduction—are most impactful in densely populated urban areas, electrification should be prioritized in these areas with quiet zones and low-emission construction zones coupled with subsidies to absorb the cost of bringing electric infrastructure to these sites. Alternative power solutions such as mobile battery energy storage systems (BESSs), hydrogen fuel cell generators, and solar-powered units could help other construction sites. A successful transition requires a coordinated framework involving streamlined permitting, technical guidance for emerging infrastructure, and targeted financial support to lower costs and improve local air quality.
published journal article
Estimating the value of urban green areas: A hedonic pricing analysis of the single family housing market in Los Angeles, CA
Landscape Urban Plann.
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Jean-Daniel Saphores and Wei Li (2012) “Estimating the value of urban green areas: A hedonic pricing analysis of the single family housing market in Los Angeles, CA”, Landscape Urban Plann., 104(3-4), pp. 373–387. Available at: 10.1016/j.landurbplan.2011.11.012.conference paper
Poster: Towards Large-Scale Measurement Study on LiDAR Spoofing Attacks against Object Detection
Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security
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Abstract
LiDAR (Light Detection And Ranging) is an indispensable sensor for precise long- and wide-range 3D sensing of the surrounding environment. The recent rapid deployment of autonomous driving (AD) has highly benefited from the advancement of LiDARs. At the same time, the safety-critical application strongly motivates its security research. Recent studies demonstrate that they can manipulate the LiDAR point cloud and fool object detection by shooting malicious lasers against LiDAR scanning. However, prior efforts focus on limited types of LiDARs and object detection models, and their threat models are not clearly validated in the real world. To fill the critical research gap, we plan to conduct the first large-scale measurement study on LiDAR spoofing attacks against a wide variety of LiDARs with major object detectors. To perform this measurement, we first significantly improved the LiDAR spoofing capability (30x more spoofing points than the prior attack) with more careful optics and functional electronics, which allows us to be the first to clearly demonstrate and quantify key attack capabilities assumed in prior works. In this poster, we present our preliminary results on VLP-16 and our research plan.
Suggested Citation
Takami Sato, Yuki Hayakawa, Ryo Suzuki, Yohsuke Shiiki, Kentaro Yoshioka and Qi Alfred Chen (2022) “Poster: Towards Large-Scale Measurement Study on LiDAR Spoofing Attacks against Object Detection”, in Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security. New York, NY, USA: Association for Computing Machinery (CCS '22), pp. 3459–3461. Available at: 10.1145/3548606.3563537.conference paper
Security trends and advances in manufacturing systems in the era of industry 4.0
2017 IEEE/ACM international conference on computer-aided design (ICCAD)
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Author(s)
Suggested Citation
Sujit Rokka Chhetri, Nafiul Rashid, Sina Faezi and Mohammad Abdullah Al Faruque (2017) “Security trends and advances in manufacturing systems in the era of industry 4.0”, in 2017 IEEE/ACM international conference on computer-aided design (ICCAD). IEEE, pp. 1039–1046. Available at: 10.1109/iccad.2017.8203896.published journal article
Socioeconomic disadvantage in pregnancy and postpartum risk of cardiovascular disease
American Journal of Obstetrics and Gynecology
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Areas of Expertise
Abstract
Background Pregnancy is an educable and actionable life stage to address social determinants of health (SDOH) and lifelong cardiovascular disease (CVD) prevention. However, the link between a risk score that combines multiple neighborhood-level social determinants in pregnancy and the risk of long-term CVD remains to be evaluated. Objective To examine whether neighborhood-level socioeconomic disadvantage measured by the Area Deprivation Index (ADI) in early pregnancy is associated with a higher 30-year predicted risk of CVD postpartum, as measured by the Framingham Risk Score. Study Design An analysis of data from the prospective Nulliparous Pregnancy Outcomes Study-Monitoring Mothers-to-Be Heart Health Study longitudinal cohort. Participant home addresses during early pregnancy were geocoded at the Census-block level. The exposure was neighborhood-level socioeconomic disadvantage using the 2015 ADI by tertile (least deprived [T1], reference; most deprived [T3]) measured in the first trimester. Outcomes were the predicted 30-year risks of atherosclerotic cardiovascular disease (ASCVD, composite of fatal and nonfatal coronary heart disease and stroke) and total CVD (composite of ASCVD plus coronary insufficiency, angina pectoris, transient ischemic attack, intermittent claudication, and heart failure) using the Framingham Risk Score measured 2 to 7 years after delivery. These outcomes were assessed as continuous measures of absolute estimated risk in increments of 1%, and, secondarily, as categorical measures with high-risk defined as an estimated probability of CVD ≥10%. Multivariable linear regression and modified Poisson regression models adjusted for baseline age and individual-level social determinants, including health insurance, educational attainment, and household poverty. Results Among 4309 nulliparous individuals at baseline, the median age was 27 years (interquartile range [IQR]: 23–31) and the median ADI was 43 (IQR: 22–74). At 2 to 7 years postpartum (median: 3.1 years, IQR: 2.5, 3.7), the median 30-year risk of ASCVD was 2.3% (IQR: 1.5, 3.5) and of total CVD was 5.5% (IQR: 3.7, 7.9); 2.2% and 14.3% of individuals had predicted 30-year risk ≥10%, respectively. Individuals living in the highest ADI tertile had a higher predicted risk of 30-year ASCVD % (adjusted ß: 0.41; 95% confidence interval [CI]: 0.19, 0.63) compared with those in the lowest tertile; and those living in the top 2 ADI tertiles had higher absolute risks of 30-year total CVD % (T2: adj. ß: 0.37; 95% CI: 0.03, 0.72; T3: adj. ß: 0.74; 95% CI: 0.36, 1.13). Similarly, individuals living in neighborhoods in the highest ADI tertile were more likely to have a high 30-year predicted risk of ASCVD (adjusted risk ratio [aRR]: 2.21; 95% CI: 1.21, 4.02) and total CVD ≥10% (aRR: 1.35; 95% CI: 1.08, 1.69). Conclusion Neighborhood-level socioeconomic disadvantage in early pregnancy was associated with a higher estimated long-term risk of CVD postpartum. Incorporating aggregated SDOH into existing clinical workflows and future research in pregnancy could reduce disparities in maternal cardiovascular health across the lifespan, and requires further study.