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Immigrants tend to display more favorable health outcomes than native-born co-ethnics. At the same time, they face considerable employment instability. It is unclear whether immigrants job conditions may compromise their health advantage. Using U.S. National Health Interview Survey data, this study shows that the experience of unemployment reduces immigrants health advantage, but unemployed foreign-born Blacks, White women, and Asian women still have lower mortality rates than their native-born employed counterparts. Overall, unemployment is less detrimental to immigrants than to natives, and immigrants survival advantage after unemployment persists as their duration of residence extends. We further find substantial heterogeneity in the unemployment effect within immigrants. Asian immigrants display a much sharper gender difference in the mortality consequence of unemployment than other immigrants. Asian mens worse general health and substantially higher smoking rate, especially among the unemployed, lead them to fare much worse than Asian women following unemployment.

Cover page: Do Immigrants Health Advantages Remain After Unemployment? Variations by Race-Ethnicity and Gender.

Article
Peer Reviewed

Stability and Relevance of Marriage Desires: Importance of Age Norms and Partnering Opportunities.

UCLA Previously Published Works (2023)

OBJECTIVE: This study investigates shifts in marriage desires during singlehood and the potential consequences associated with these shifts in Japan, a country epitomizing later and less marriage without substantial increases in nonmarital childbearing. BACKGROUND: Despite researchers long-standing interest in values potentially motivating demographic changes, few have systematically examined marriage desires among unmarried adults. Even fewer have considered how marriage desires may change during adulthood and how relevant such changes are to marriage and family behavior. METHOD: The analysis uses 11 waves of the Japan Life Course Panel Survey, which tracks singles marriage desires yearly. Fixed effects models are estimated to demonstrate factors associated with within-person changes and account for unobserved heterogeneity. RESULTS: Japanese singles marriage desires decline with age but are stronger when they perceive greater opportunities to form romantic relationships or marriage. Singles experiencing an increase in the desire to marry are more likely to take actions to seek partners and to enter a romantic relationship or marriage subsequently. The associations between marriage desires and the various behavioral changes strengthen with age and feasibility of marriage. Increases in marriage desires also correspond to increases in single mens parenthood desires and ideal numbers of children, and the link between marriage desires and fertility preferences is stronger as they age. CONCLUSION: Marriage desires are not always stable or equally relevant throughout singlehood. Our study suggests that age norms and partnering opportunities both contribute to the fluctuation of marriage desires and affect when such desires would have behavioral implications.

Cover page: Stability and Relevance of Marriage Desires: Importance of Age Norms and Partnering Opportunities.

Article
Peer Reviewed

Job characteristics, marital intentions, and partner-seeking actions: Longitudinal evidence from Japan

UCLA Previously Published Works (2020)

Article
Peer Reviewed

Diminished Advantage or Persistent Protection? A New Approach to Assess Immigrants Mortality Advantages Over Time.

UCLA Previously Published Works (2022)

Much research has debated whether immigrants health advantages over natives decline with their duration at destination. Most such research has relied on (pooled) cross-sectional data and used years since immigration as a proxy for the duration of residence, leading to the challenge of distilling the duration effect from the confounding cohort-of-arrival and age-of-arrival effects. Because longitudinal studies tend to use self-rated health as the outcome, the changes they observed may reflect shifts in immigrants awareness of health problems. We illuminate the debate by examining how immigrants mortality risk-a relatively unambiguous measure tied to poor health-changes over time compared to natives mortality risk. Our analysis uses the National Health Interview Survey (1992-2009) with linked mortality data through 2011 (n = 875,306). We find a survival advantage for U.S. immigrants over the native-born that persisted or amplified during the 20-year period. Moreover, this advantage persisted for all immigrants, regardless of their race/ethnicity and gender or when they began their U.S. residence. This study provides unequivocal evidence that immigrant status health protection as reflected in mortality is stable and long-lasting.

Cover page: Diminished Advantage or Persistent Protection? A New Approach to Assess Immigrants Mortality Advantages Over Time.

Article
Peer Reviewed

The Categorization Task is Insufficient to Distinguish between Strategies: A Case for Partial-XOR-like Tasks

Proceedings of the Annual Meeting of the Cognitive Science Society, Volume 45 (2023)

In categorization research, competing theories are typically compared by fitting their predictions to participant’s responses on a set of test items. The theory that best matches each participant's responses is identified as the strategy the participant is most likely employing. Researchers face considerable difficulty in selecting the best-fitting model due to several factors. In this study, we show the frailty of this approach. Due to pervasive model mimicry and across the similarity- and rule-based models, typical categorization task designs fail to reliably distinguish strategies. Some design modifications that might help are counter-indicated on practical grounds (e.g., carry-over effects); other possible means of improving strategy identification are also discussed.

Cover page: The Categorization Task is Insufficient to Distinguish between Strategies: A Case for Partial-XOR-like Tasks

Creative Commons 'BY' version 4.0 license

Thesis
Peer Reviewed

High biofuel production of Botryococcus braunii using optimized cultivation strategies

Yu, Wei
Advisor(s): Ho, Chih Ming

UCLA Electronic Theses and Dissertations (2014)

This thesis describes how using a heterotrophy-recovery-autotrophy route (called the green cycle) for the cultivation of Botryococcus braunii results in high biofuel production. Our experiments show that the addition of citrate to a culture can increase cell numbers by up to 20 times compared with the control in the first week. A metal solution was then added to help cells synthesize chlorophyll, enabling Botryococcus braunii to regenerate the chlorophyll content in the plastids and become autotrophic. In our experiments, high cell numbers were obtained after two weeks and biofuel production was enhanced.

We also developed an N-N-A source media which could achieve enhanced cell growth as opposed to using nitrate as the only nitrogen source. This N-N-A source media was able to balance pH variation due to nitrate uptake, so as to maintain the pH level in the media solution without the use of buffer.

By applying these techniques to the Botryococcus braunii culture, we found that cell growth could increase by up to 58 times in comparison with the control

Cover page: High biofuel production of Botryococcus braunii using optimized cultivation strategies

Thesis
Peer Reviewed

Electric Vehicle - Smart Grid Integration: Load Modeling, Scheduling, and Cyber Security

Chung, Yu-Wei
Advisor(s): Gadh, Rajit

UCLA Electronic Theses and Dissertations (2020)

The modern world has witnessed the surge of electric vehicles (EVs) driven by government policy worldwide to reduce transportation’s dependence on fossil fuels. According to (Slowik, 2019), the global EV market has grown sharply with the annual light-duty EV sales surpassing 2 million in 2018, which is about a 70% increase from 2017. The increase in EV population implies the rise in energy demand, and that introduces new challenges to the electricity sector. EV charging load demand in high penetration scenarios, which is foreseen, may lead to stability and quality issues in power grids. Generation capacity and the electricity infrastructure upgrade may be required to address those issues; however, it increases generation costs significantly. The most common EV chargers installed today deliver around 7 kW of power, which is over four times that of an average household power consumption in the US. EV charging load often shows two peaks in a day, one in the morning when people plug in the EV at the workplace and the other in the evening when people get home from work. Without proper energy management for EV charging, the vast power demand due to a large number of plugged-in EVs can stress the electric grid, degrade the electric power quality, and impact the wholesale electricity market. Although an EV battery may store energy up to 80 kWh, which requires more than 10 hours to charge at 7kW from empty, we found that most EVs need only 12 kWh per charge or 1.7 hours at 7 kW to meet daily commute requirement while they stay in the parking garage for a more extended period. This implies that EVs can have considerable time-flexibility for charging, and it is not necessary to start charging

right after plugging in, which is likely to result in the charging power add-up. A proper EV charging schedule can well allocate the charging load to prevent power peaks. Therefore, EV charging scheduling can play a significant role in mitigating the adverse effects of vast EV charging demand without upgrading the power grid capacity.

To optimize the EV charging schedule while satisfies EVs’ charging demand, each EV’s stay duration and energy need are essential parameters for the optimization. Those parameters are based on predictions to minimize human intervention. Nonetheless, the uncertainty of EV user behavior poses a challenge to the prediction accuracy. Therefore, this dissertation demonstrates an ensemble machine learning-based method to model and predict the EV loads accurately, thereby improving the performance of EV charging scheduling.

On the other hand, this smart EV-grid integration, which requires massive communication, including collecting, transmitting, and distributing real-time data within the network, makes it more susceptible to cyber-physical threats. Potential breaches could not only affect grid operation but also reduce consumers’ willingness to adopting EVs over conventional fuel-powered vehicles. This dissertation also presents the vulnerability analysis and risk assessment for a smart EV charging system to develop the countermeasures to secure the network. Also, while it is inevitable that the security has flaws, this dissertation provides a novel anomaly detection approach based on the invariant correlations of different measurements within the EV charging network.

Cover page: Electric Vehicle - Smart Grid Integration: Load Modeling, Scheduling, and Cyber Security