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Complex Coacervate Emulsions as a Strategy to Stabilize Enzymes for Catalysis in Organic Solvents
No full textComplex coacervates have emerged as versatile platforms for protein encapsulation, enabling enzymatic catalysis in aqueous environments. Despite their potential, applications of coacervates are limited by the substrate solubility in water. In this study, we present a protocol to stabilize enzyme-loaded coacervate droplets in water-immiscible organic solvents via the formation of highly stable emulsions. These emulsions were formed using coacervates composed of poly(diallyldimethylammonium hydroxide) and poly(acrylic acid), stabilized by a polystyrene-based, amphiphilic, anionic copolymer in toluene, chlorobenzene, chloroform, and dichloromethane. The resulting microdroplets display exceptional resistance to coalescence, including after centrifugation, and remain stable for weeks. This stability facilitates their separation and redispersion for use in repeated catalytic applications. Using α-chymotrypsin as a model enzyme, we show that the aqueous microenvironment within the droplets maintains enzyme stability over time and enables biocatalysis in nonaqueous media
Polyelectrolyte–Carbon Dot Complex Coacervation
No full textThis Letter presents complex coacervation between the biopolymer diethylaminoethyl dextran hydrochloride (DEAE-Dex) and carbon dots. The formation of these coacervates was dependent on both DEAE-Dex concentration and solution ionic strength. Fluorescence spectroscopy revealed that the blue fluorescence of the carbon dots was unaffected by coacervation. Additionally, microrheological studies were conducted to determine the viscosity of these coacervates. These complex coacervates, formed through the interaction of nanoparticles and polyelectrolytes, hold a promising role for future applications where the combination of optical properties from the carbon dots and encapsulation via coacervation can be leveraged
Examining the Effects of a Tier 2 Check-in/Check-out Intervention on Middle School Aged Children: Check-ins and Logging Moods
No full textThis intervention study explored the effectiveness of a Tier 2 intervention, Check Ins and Logging Moods (CALM) (e.g., Check-in/Check-out with integrated components of Cognitive Behavioral Therapy and daily self-monitoring) on 7th grade students at risk for internalizing behavior problems. The study was conducted in two different school sites, CA and MA and used a combination of Multiple Baseline and simple AB single-case design with multiple outcome measures. The CALM intervention consisted of 6 lessons taught once a week for 6 weeks by the interventionist who held weekly meetings to review students’ self-reported mood, engagement and use of coping skills-- holding a space for students to reflect upon their week. Data collectors also conducted 20-minute observations to monitor the frequency of students internalizing behaviors. Visual analysis of direct observations, student self-reported mood, engagement and coping skill use data along with single-case effect size calculations indicated that there was a functional relation between the CALM intervention and an increase in students self-reported engagement at the school site in CA. However, many challenges occurred conducting school-based research. Findings from the current study provide evidence that through frequent check-ins and teaching coping skills, middle school students who are at-risk for internalizing behavior problems can increase perceived engagement in school and self-awareness.Doctor of Philosophy (Ph.D.
FAST, SCALABLE, WARM-START SEMIDEFINITE PROGRAMMING WITH APPLICATION TO KNOWLEDGE EDITING AND MIXED INTEGER SEMIDEFINITE OPTIMIZATION
No full textSemidefinite programming (SDP) has traditionally been limited to moderate-sized problems. Methods for scaling to larger problems have sacrificed the convexity of the original problem for scalalability. More recently, algorithms augmented with matrix sketching techniques have enabled solving larger SDPs. However, these methods achieve scalability at the cost of an increase in the number of necessary iterations, resulting in slower convergence as the problem size grows. Furthermore, they require iteration-dependent parameter schedules that prohibit effective utilization of warm-start initializations important in practical applications with incrementally-arriving data or constraints.
We present Unified Spectral Bundling with Sketching (USBS), a fast and scalable algorithm for solving massive SDPs that can leverage a warm-start initialization to further accelerate convergence. Our proposed algorithm is a spectral bundle method for solving general SDPs containing both equality and inequality constraints. Moreover, when augmented with an optional matrix sketching technique, our algorithm achieves the dramatically improved scalability of previous work while sustaining convergence speed. We empirically demonstrate the effectiveness of our method across multiple applications, with and without warm-starting. For example, USBS provides a 500x speed-up over the state-of-the-art scalable SDP solver on an instance with over 2 billion decision variables.
The speed and scalability of USBS enables the use of SDPs in novel applications. First, we present a new paradigm of interactive feedback, existential cluster constraints, for correcting entity resolution predictions and present a novel SDP relaxation at the core of the proposed inference algorithm. We demonstrate empirically that our proposed framework facilitates more accurate entity resolution with dramatically fewer user feedback inputs. We show USBS is not only faster than the previous state-of-the-art scalable SDP solver, but can also effectively leverage a warm-start initialization to improve empirical convergence.
Finally, we provide evidence that USBS could potentially be used as part of a mixed-integer semidefinite program solver. There are many applications where we want to optimize a semidefinite program where a subset of the decision variables are subject to additional integrality constraints. One of the barriers to applying standard branch-and-bound techniques to mixed-integer semidefinite programs is the lack of a fast semidefinite program solver that can warm-started. Given existing evidence that USBS can effectively utilize a warm-start initialization, we explore the possibility of using USBS as part of a branch-and-bound solver for mixed-integer semidefinite programs.NSF Graduate Research FellowshipDoctor of Philosophy (Ph.D.
EXAMINING THE RELATIONSHIP BETWEEN CANNABIS LIBERALIZATION POLICIES AND SCHOOL DISCIPLINE IN MASSACHUSETTS: A MIXED-METHODS STUDY
No full textSchool suspension and expulsion during adolescence are associated with multiple adverse outcomes such as an increased likelihood for mental health issues, a greater likelihood of alcohol and substance use, and involvement with the criminal justice system. Establishing school disciplinary policies that appropriately sanction unlawful drug use but that do not put youth on a trajectory toward involvement with the criminal justice system is complex. The “school to prison pipeline” has increased youth involvement in the criminal justice system, as schools have adopted “zero tolerance” for drug possession and use. These policies disproportionately affect youth of color, despite rates of drug use that are lower than white youth. In some states, the legalization of cannabis for persons aged 21+ is associated with a decrease in arrests among adults, but the evidence among youth is mixed. The relationship between these policies and risks of disciplinary action for youth remains unknown.
To fill this gap, this dissertation utilized a mixed-methods approach. Quantitative methods examined changes in counts of cannabis-related disciplinary incidents (CDIs) as cannabis policies became increasingly liberal in Massachusetts from 2005-2021. We identified associations between district-level sociodemographic characteristics and CDIs. Semi-structured interviews were conducted with youth under age 21 to explore their perceptions of and experiences with school-based discipline for cannabis incidents.
We found that counts of CDIs increased as cannabis policies became increasingly permissive. We also found that for every 1% increase in a district’s percentage of male students, English language learners, and students with a disability, the CDI incident rate increased. Qualitative findings demonstrated that cannabis use in schools is common, however schools respond to these situations in differing ways. Students called for open communication about the risks of cannabis use, without utilizing an abstinence-only approach.
These studies shed light on a potential unintended consequence of cannabis policies: as policies have become increasingly permissive, counts of CDIs have increased. These findings provide critical information for policymakers who seek to mitigate potential harm from cannabis policies upon youth. Cannabis policies should be updated to incorporate guidance for educators to explore disciplinary alternatives that do not result in suspension and expulsion.National Institute of JusticeDoctor of Philosophy (Ph.D.)2026-02-0
Three Essays Pertaining to Organizing for Value Creation in Professional Service Firms
No full textProfessional service firms (PSFs) including law firms, consulting firms, hospitals, and universities, have become an increasingly important fixture in the global economy. It is broadly accepted that due to their human capital intensity, knowledge intensity, and the professionalization of their workforce, such firms are imbued with several distinct management challenges that complicate organizing for value creation. In this dissertation, I develop three essays pertaining to organizing in PSFs. In essay one, I endeavor to make sense of the different ways in which client-based knowledge impacts PSF value creation and capture. Despite the consensus that client-based knowledge contributes to PSF performance and competitive advantage, the ubiquity of the concept has meant that there is little precision regarding what we are talking about in any given instance. Thus, I develop a taxonomy of different client-based knowledge types according to its explicitness and relative specificity. In essay two, I develop and test a model linking elements of a PSF’s structure to its ability to effectively create value via the acquisition and integration of strategically valuable knowledge. Specifically, I argue that as a PSF adopts a more generalist strategy, the cultivation and integration of client-based knowledge – relatively more idiosyncratic than problem-based knowledge – becomes more critical to PSF competitive advantage, necessitating the use of specific practices (lateral partner hiring, hiring for client overlap, a job rotation program, and a practice of mandating multiple client ties) to enhance firm growth. Finally, in essay three I develop an integrative review of what we know of how PSFs get the right resources to the right place at the right time to create value for clients. Specifically, I synthesize insights generated by coordination scholars, knowledge and human capital scholars, and strategic human capital scholars. The review reveals that each of these communities of practice follows a similar trajectory in their perspective, including elaborating the mechanisms that enable interdependent work and expounding on the relational dimension of organizing. It also reveals several shared assumptions and critical gaps that serve as the basis for a proposed agenda for future research on organizing for value creation in these firms.Doctor of Philosophy (Ph.D.
THE PARADOXICAL INFLUENCE OF SOCIAL IDENTITY THREAT ON SELF- GROUP DISTANCING IN THE CONTEXT OF GENDER DISCRIMINATION
No full textThe present study (N=347) investigates the effect of social identity threat and meritocratic beliefs on women’s willingness to align themselves with male leaders and distance themselves from female leaders. Employing a 2 between subjects design, I manipulated the social identity threat in an online study where participants applied for a leadership position and completed a measurement to assess their belief in meritocracy. Subsequently, participants were rejected from the leadership position, either because of gender discrimination (threat condition) or due to a schedule conflict (no-threat condition). Post rejection, participants were asked to respond to several questions on their motivation to interact with male vs. female leaders, motivation to interact with gender stereotypic vs. non-stereotypic leaders, inclusion (vs. exclusion) of male and female leaders within one’s self-concept, associating the self with stereotypically masculine vs. feminine attributes and perceived dissimilarity and detachment from the female leaders. Results showed that the participants showed a movement towards the male leaders, but they did not show any distancing from female leaders.Master of Science (M.S.
Data Generation for Weakly Supervised Neural Retrieval
No full textTo address data limitation in neural retrieval, weak supervision leverages existing ranking methods to automatically generate pseudo relevance judgments. However, there are still several limitations to consider. Firstly, the size and accessibility of the query collection pose challenges for existing methods in generating a sufficiently large and diverse set of weak signals. Secondly, while empirical and theoretical evidence demonstrates that a weakly supervised neural ranking model can outperform the original ranker, the quality of the information provided by the original ranking models highly correlates with and constrains the overall performance of weakly supervised models.
To overcome these limitations, the dissertation focuses on employing a neural generative approach for data generation in weak supervision settings, incorporating effective techniques.
To address the issue of query scarcity, a query augmentation framework is designed, which utilizes GAN-based methods to expand an insufficient query set. The evaluation results indicate that augmentation enhances ranking performance, particularly when the original query set is inadequate to support weakly supervised training. In the context of e-commerce applications, an ensemble approach is devised to generate pseudo queries from customer reviews. These generated queries exhibit similarity to real customer queries and effectively enhance ranking performance within the weak supervision framework. To tackle the challenge of weak labeler quality, we propose a framework called generalized weak supervision (GWS). This framework extends the definition of weak labeler to include the weakly supervised model itself. Through iterative re-labeling, the quality of pseudo relevance judgments is improved without the need for additional data. We present four implementations of the GWS framework, demonstrating significant improvements in ranking tasks compared to weak supervision methods. Finally, we extend weak signals generated from large language models (LLMs) to explanations in natural language. Through the extended form, the ranking ability of LLMs is transferred to smaller models more effectively.This work was supported in part by the Center for Intelligent Information Retrieval, in part by the Amazon Alexa Prize Competition, and in part by the Office of the Director of National Intelligence (ODNI), Intelligence Advanced Research Projects Activity (IARPA) via AFRL contract #FA8650-17-C-9116 under subcontract #94671240 from the University of Southern California. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of the ODNI, IARPA, or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright annotation thereon.Doctor of Philosophy (Ph.D.
STRUCTURE-PROPERTY RELATIONSHIPS OF POLYETHYLENE COPOLYMERS VIA POST-POLYMERIZATION MODIFICATION OF POLYCYCLOOCTENE FOR POLYMER UPCYCLING STRATEGIES
No full textAs plastics became a societal necessity, production skyrocketed with little consideration for disposal upon completion of their intended use0F0F . A take, make, waste mentality has since prevailed, leaving pollution in its wake. One major challenge is recycling polyolefins which make up the largest mass of plastic waste. Many strategies and efforts from government, industry, and academia are attempting to address this growing challenge. A large focus is on the breakdown of these polymers into small molecules or oligomers which can be used as building blocks for new polymers or other specialty chemicals. A newer idea to address the mass of plastic waste is polymer-to-polymer upcycling, a strategy that would maintain polymer molecular weight, thus transforming materials that would end up in the landfill to higher value products with extended lifetimes.
Efforts to address polyolefin upcycling were explored through a dehydrogenation and functionalization approach. The dehydrogenation step is non-trivial, and the chemistry was not directly addressed in this document as it was being studied at the University of Pennsylvania. In Chapter 2, using model dehydrogenated polyethylenes, calibration curves were established to estimate percent unsaturation independent of solubility, overcoming challenges typically associated with polyolefin characterization. The calibration curves illustrated relationships between percent unsaturation and melting temperature, crystallinity, and FTIR peak heights.
Chapters 3 through 5 described how model dehydrogenated polyethylenes were functionalized by hydroboration/oxidation to linear poly(ethylene-co-vinyl alcohol) (LEVOH) and epoxidation. Chapter 3 compared the saturated and unsaturated LEVOH and found that the level and presence of unsaturation impacted polymer properties. Chapters 4 and 5 further elaborated the epoxides by ring-opening to vicinal diols or halohydrins. The regioregular, stereoirregular diols were compared to those with opposite stereochemistry and determined that stereochemistry plays a role in determining melting temperature and crystal structure.
In Chapter 5, ring-opening of epoxides was successful to 100% conversion with hydrochloric and hydrobromic acid, whereas ring-opening with hydroiodic acid resulted in reformation of the alkene.
Chapter 6 summarized the findings throughout the dissertation and provided suggestions for future exploration. Additionally, it provided some perspective on the scalability and feasibility of applying the chemistries explored at a commercial level.DOE BES (DE-SC0022238)Doctor of Philosophy (Ph.D.