THE 2018 CGS/PROQUEST MATH, PHYSICAL SCIENCES, AND ENGINEERING AWARD WINNER:
Mohamed S. Ibrahim, Duke University
Optimization of Trustworthy Biomolecular Quantitative Analysis Using Cyber-Physical Microfluidic Platforms
Lab-on-a-chip systems (LoCs), often referred to as microfluidic biochips, are revolutionizing many biochemical analysis procedures such as clinical diagnostics and DNA sequencing. Biochips offer the advantages of miniaturization, simple instrumentation, dynamic reconfigurability, and ease of integration with other technologies. The rapid evolution of biochip technologies opens up opportunities for new biological or chemical science that can be directly facilitated by microfluidics control. For example, automated LoCs have been commercialized to enable automated syndromic testing that can be performed at the patient’s bedside.
Despite advances in research, the adoption of biochips in molecular biology has been slow. Recent studies suggest that state-of-the-art design techniques of microfluidics have two major drawbacks: (1) current LoCs were only optimized as auxiliary components and are only suitable for sample-limited analyses; therefore, they cannot cope with the requirements of contemporary molecular biology applications; (2) the integrity of these automated LoCs and their biochemical operations is still an open question, since no protection schemes were developed against adversarial contamination or result-manipulation attacks.
To address these challenges, this thesis presents a new design flow that is based on the realistic modeling of contemporary molecular biology protocols. It also presents a microfluidic security solution that provides a high level of confidence in the integrity of such protocols. The results presented in this thesis opens up new research directions by bridging the gap between microfluidic systems and molecular biology protocols, and enabling a new level of synergy between molecular biology, computing, and electrical engineering.
THE 2018 CGS/PROQUEST SOCIAL SCIENCES AWARD WINNER:
Eiko Strader, University of Massachusetts, Amherst
Immigration and Within-Group Wage Inequality: How Queuing, Competition, and Care Outsourcing Exacerbate and Erode Earnings Inequalities
The rhetoric against immigration in the United States focuses on the economic threat to low-educated native-born men using a singular labor market competition lens. In contrast to this trend, this dissertation builds on a large body of previous work on job queuing and ethnic competition, as well as insights gained from the studies on female labor force participation and the outsourcing of care work to migrant domestic workers. By exploring regional differences in the wage effects of immigration across 100 metropolitan areas between 1980 and 2007, I argue that immigration is a dynamic localized source of wage inequality and equality.
By taking an intersectional approach, I conclude that the wage effects of immigration are the result of gendered, raced and classed queuing processes, as well as changes in household production decisions. Findings presented in this dissertation advance empirical and theoretical debates about the linkage between immigration and within-country wage inequality. The policy implications of this dissertation are twofold. First, the binary treatment of native-born workers against immigrants is misguided because immigration intersects with other sources of inequality. Secondly, the continued reliance on the market-based care, as opposed to publicly provided care, increases the labor market vulnerability of some native-born workers.