Maryland Farm Internships and Labor Laws

Many farms across Maryland use interns to lighten the overall farm workload and help young people gain practical farming knowledge. Although interns can be a welcome addition to a farm’s workforce, farm employers need to be aware of how to properly compensate interns and the legal consequences of adding them to the payroll.

DATA DRIVEN APPROACHES TO IDENTIFY DETERMINANTS OF HEART DISEASES AND CANCER RESISTANCE

Cancer and cardio-vascular diseases are the leading causes of death world-wide. Caused by systemic genetic and molecular disruptions in cells, these disorders are the manifestation of profound disturbance of normal cellular homeostasis. People suffering or at high risk for these disorders need early diagnosis and personalized therapeutic intervention. Successful implementation of such clinical measures can significantly improve global health. However, development of effective therapies is hindered by the challenges in identifying genetic and molecular determinants of the onset of diseases; and in cases where therapies already exist, the main challenge is to identify molecular determinants that drive resistance to the therapies. Due to the progress in sequencing technologies, the access to a large genome-wide biological data is now extended far beyond few experimental labs to the global research community. The unprecedented availability of the data has revolutionized the capabilities of computational researchers, enabling them to collaboratively address the long standing problems from many different perspectives. Likewise, this thesis tackles the two main public health related challenges using data driven approaches. Numerous association studies have been proposed to identify genomic variants that determine disease. However, their clinical utility remains limited due to their inability to distinguish causal variants from associated variants. In the presented thesis, we first propose a simple scheme that improves association studies in supervised fashion and has shown its applicability in identifying genomic regulatory variants associated with hypertension. Next, we propose a coupled Bayesian regression approach -- eQTeL, which leverages epigenetic data to estimate regulatory and gene interaction potential, and identifies combinations of regulatory genomic variants that explain the gene expression variance. On human heart data, eQTeL not only explains a significantly greater proportion of expression variance in samples, but also predicts gene expression more accurately than other methods. We demonstrate that eQTeL accurately detects causal regulatory SNPs by simulation, particularly those with small effect sizes. Using various functional data, we show that SNPs detected by eQTeL are enriched for allele-specific protein binding and histone modifications, which potentially disrupt binding of core cardiac transcription factors and are spatially proximal to their target. eQTeL SNPs capture a substantial proportion of genetic determinants of expression variance and we estimate that 58% of these SNPs are putatively causal. The challenge of identifying molecular determinants of cancer resistance so far could only be dealt with labor intensive and costly experimental studies, and in case of experimental drugs such studies are infeasible. Here we take a fundamentally different data driven approach to understand the evolving landscape of emerging resistance. We introduce a novel class of genetic interactions termed synthetic rescues (SR) in cancer, which denotes a functional interaction between two genes where a change in the activity of one vulnerable gene (which may be a target of a cancer drug) is lethal, but subsequently altered activity of its partner rescuer gene restores cell viability. Next we describe a comprehensive computational framework --termed INCISOR-- for identifying SR underlying cancer resistance. Applying INCISOR to mine The Cancer Genome Atlas (TCGA), a large collection of cancer patient data, we identified the first pan-cancer SR networks, composed of interactions common to many cancer types. We experimentally test and validate a subset of these interactions involving the master regulator gene mTOR. We find that rescuer genes become increasingly activated as breast cancer progresses, testifying to pervasive ongoing rescue processes. We show that SRs can be utilized to successfully predict patients' survival and response to the majority of current cancer drugs, and importantly, for predicting the emergence of drug resistance from the initial tumor biopsy. Our analysis suggests a potential new strategy for enhancing the effectiveness of existing cancer therapies by targeting their rescuer genes to counteract resistance. The thesis provides statistical frameworks that can harness ever increasing high throughput genomic data to address challenges in determining the molecular underpinnings of hypertension, cardiovascular disease and cancer resistance. We discover novel molecular mechanistic insights that will advance the progress in early disease prevention and personalized therapeutics. Our analyses sheds light on the fundamental biological understanding of gene regulation and interaction, and opens up exciting avenues of translational applications in risk prediction and therapeutics.

“FOR THE UNION MAKES US STRONG”: PROTEST MUSIC IN THE 1989−90 PITTSTON STRIKE

Music making was a common practice during the 1989−90 strike against the Pittston Coal Company, an action led by the United Mine Workers of America. The types of music made varied greatly based on the contexts in which musicians and protesters were participating. In this thesis, I discuss how performers and audiences engaged with the music of the Pittston strike, with a focus on how different participatory and presentational contexts included music with similar or the same lyrics to achieve different goals. I argue that the musicians’ understanding of the people around them as potential participants, audiences, or inherent audiences shifted their use of music as they worked to use music strategically and effectively for the strike. The musical methods and considerations of the Pittston strike protesters have had a lasting impact on more recent protest movements.

Essays on Macroeconomic Trends and Cycles

This dissertation describes two studies on macroeconomic trends and cycles. The first chapter studies the impact of Information Technology (IT) on the U.S. labor market. Over the past 30 years, employment and income shares of routine-intensive occupations have declined significantly relative to nonroutine occupations, and the overall U.S. labor income share has declined relative to capital. Furthermore, the decline of routine employment has been largely concentrated during recessions and ensuing recoveries. I build a model of unbalanced growth to assess the role of computerization and IT in driving these labor market trends and cycles. I augment a neoclassical growth model with exogenous IT progress as a form of Routine-Biased Technological Change (RBTC). I show analytically that RBTC causes the overall labor income share to follow a U-shaped time path, as the monotonic decline of routine labor share is increasingly offset by the monotonic rise of nonroutine labor share and the elasticity of substitution between the overall labor and capital declines under IT progress. Quantitatively, the model explains nearly all the divergence between routine and nonroutine labor in the period 1986-2014, as well as the mild decline of the overall labor share between 1986 and the early 2000s. However, the model with IT progress alone cannot explain the accelerated decline of labor income share after the early 2000s, suggesting that other factors, such as globalization, may have played a larger role in this period. Lastly, when nonconvex labor adjustment costs are present, the model generates a stepwise decline in routine labor hours, qualitatively consistent with the data. The timing of these trend adjustments can be significantly affected by aggregate productivity shocks and concentrated in recessions. The second chapter studies the implications of loss aversion on the business cycle dynamics of aggregate consumption and labor hours. Loss aversion refers to the fact that people are distinctively more sensitive to losses than to gains. Loss averse agents are very risk averse around the reference point and exhibit asymmetric responses to positive and negative income shocks. In an otherwise standard Real Business Cycle (RBC) model, I study loss aversion in both consumption alone and consumption-and-leisure together. My results indicate that how loss aversion affects business cycle dynamics depends critically on the nature of the reference point. If, for example, the reference point is status quo, loss aversion dramatically lowers the effective inter-temporal rate of substitution and induces excessive consumption smoothing. In contrast, if the reference point is fixed at a constant level, loss aversion generates a flat region in the decision rules and asymmetric impulse responses to technology shocks. Under a reasonable parametrization, loss aversion has the potential to generate asymmetric business cycles with deeper and more prolonged recessions.

Bodies on the Line: Violence, Disposable Subjects, and the US-Mexico Border Industrial Complex

Bodies On the Line: Violence, Disposable Subjects, and the Border Industrial Complex explores the construction of identity and notions of belonging within an increasingly privatized and militarized Border Industrial Complex. Specifically, the project interrogates how discourses of Mexican migrants as racialized, gendered, and hypersexualized “deviants” normalize violence against border crossers. Starting at Juárez/El Paso border, I follow the expanding border, interrogating the ways that Mexican migrants, regardless of sexual orientation, have been constructed and disciplined according to racialized notions of “sexual deviance." I engage a queer of color critique to argue that sexual deviance becomes a justification for targeting and containing migrant subjects. By focusing on the economic and racially motivated violence that the Border Industrial Complex does to Mexican migrant communities, I expand the critiques that feminists of color have long leveraged against systemic violence done to communities of color through the prison industrial system. Importantly, this project contributes to transnational feminist scholarship by contextualizing border violence within the global circuits of labor, capital, and ideology that shape perceptions of border insecurity. The project contributes an interdisciplinary perspective that uses a multi-method approach to understand how border violence is exercised against Mexicans at the Mexico-US border. I use archival methods to ask how historical records housed at the National Border Patrol Museum and Memorial Library serve as political instruments that reinforce the contemporary use of violence against Mexican migrants. I also use semi-structured interviews with nine frequent border crossers to consider the various ways crossers defined and aligned themselves at the border. Finally, I analyze the master narratives that come to surround specific cases of border violence. To that end, I consider the mainstream media’s coverage, legal proceedings, and policy to better understand the racialized, gendered, and sexualized logics of the violence.

Design and Pilot Study for an Efficient High-Throughput Automated Computer-Vision Guided Intelligent De-Calyxing Machine for Post-Harvest Strawberry Processing

Strawberries harvested for processing as frozen fruits are currently de-calyxed manually in the field. This process requires the removal of the stem cap with green leaves (i.e. the calyx) and incurs many disadvantages when performed by hand. Not only does it necessitate the need to maintain cutting tool sanitation, but it also increases labor time and exposure of the de-capped strawberries before in-plant processing. This leads to labor inefficiency and decreased harvest yield. By moving the calyx removal process from the fields to the processing plants, this new practice would reduce field labor and improve management and logistics, while increasing annual yield. As labor prices continue to increase, the strawberry industry has shown great interest in the development and implementation of an automated calyx removal system. In response, this dissertation describes the design, operation, and performance of a full-scale automatic vision-guided intelligent de-calyxing (AVID) prototype machine. The AVID machine utilizes commercially available equipment to produce a relatively low cost automated de-calyxing system that can be retrofitted into existing food processing facilities. This dissertation is broken up into five sections. The first two sections include a machine overview and a 12-week processing plant pilot study. Results of the pilot study indicate the AVID machine is able to de-calyx grade-1-with-cap conical strawberries at roughly 66 percent output weight yield at a throughput of 10,000 pounds per hour. The remaining three sections describe in detail the three main components of the machine: a strawberry loading and orientation conveyor, a machine vision system for calyx identification, and a synchronized multi-waterjet knife calyx removal system. In short, the loading system utilizes rotational energy to orient conical strawberries. The machine vision system determines cut locations through RGB real-time feature extraction. The high-speed multi-waterjet knife system uses direct drive actuation to locate 30,000 psi cutting streams to precise coordinates for calyx removal. Based on the observations and studies performed within this dissertation, the AVID machine is seen to be a viable option for automated high-throughput strawberry calyx removal. A summary of future tasks and further improvements is discussed at the end.