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Nucleic acid biopolymers are essential to all living organisms. The chemical makeup of deoxyribonucleic acid (DNA) and ribonucleic acid (RNA) consist of sequences of only four monomers. However, they transmit and express genetic information for various biological functions based on stored blueprints. Along with communicating the flow of genetic information (DNA → RNA→ protein), nucleic acids have also become a preferred material for fabrication of objects and scaffolds at the nanoscale. Nucleic acid-based assemblies that interact with each other and communicate with the cellular machinery represent a new class of reconfigurable nanostructures that enable precise control over their formulation and physicochemical properties and activation of multiple biological functionalities. Therefore, the use of nucleic acids offers a unique platform for development of nanoparticles which consist of nanoscale-size oligonucleotides designed to fold into predicted three-dimentional structures. They can serve as scaffolds capable of carrying numerous functional moieties such as: RNA interference activators for gene silencing, aptamers for specific targeting of selected molecules, immunostimulatory sequences for modulating immune responses, and fluorescent entities for bioimaging. Programmable, controllable, biocompatible, rationally designed, and self-assembled nucleic acid nanoparticles have become attractive candidates for diverse therapeutic options. Despite profound advances in the field of therapeutic nucleic acids, their negative charges decrease membrane permeation capacity, thus hindering their translation from experimental research to clinical application. This dissertation focuses on the development of nucleic acid nanoparticles as therapeutics with defined immunostimulatory properties accompanied by rationally designed systems able to regulate the duration of therapeutic activity. Furthermore, a safe, efficient and stable intracellular delivery system for multi-functional nucleic acid nanoparticle platforms is investigated.
The proliferation of connected devices creates various use cases and heterogeneous services, e.g., augmented/virtual reality (AR/VR), vehicle-to-everything (V2X), and mobile artificial intelligence. These services and use cases have diverse networking and performance requirements such as throughput and delay, which challenge the "one-fit-all" service architecture in current networks. In this research, an intelligent network management framework in mobile edge computing is explored. The primary challenges lie in the unique characteristics of heterogeneous services and complicated correlations between network management on multiple technical domains and high-dimension performance requirements in the complex mobile networks. This research addresses these challenges with two different management approaches. From the perspective of service providers, multiple mobile systems are designed to allow service adaptation under complex network dynamics, e.g., channel variation and traffic workload, which dynamically and adaptively adjust resource allocations and system configurations by exploiting the unique characteristics of individual services. From the perspective of infrastructure providers, multiple network systems are proposed to enable orchestration intelligence without accurate performance modelings of services, which automatically learn to orchestrate multiple domain network resources for supporting various services by exploiting advanced machine learning techniques.
Climate change is one of the most pivotal issues for the world in which we live today.
The power grid transformation to become, smarter sustainable and carbon-free,
has been a primary emphasis in recent times. This includes the integration of Distributed
Energy Sources (DERs). In this work, innovative and novel techniques are
presented to facilitate and expedite the engineering, planning, and deployment of
high penetration levels of renewable and distributed energy resources to aggressively
attack climate change and move the industry to a new paradigm. Towards this end,
both traditional and non-traditional techniques and methodologies are leveraged to
enhance distribution planning methods such that more electric distribution feeders
can be analyzed more dynamically. Tried and true iterative mathematical techniques
and convergence algorithms are used to adhere to the Laws of Physics for the flow of
electricity.
Findings in the area of Control Theory and System Identification are used to develop
dynamic and predictive models of the electric distribution system that analyze
the impact of interconnecting high levels of renewable generation. These predictive
models are represented by parametric models or transfer functions developed from the
Laplace Transform technique, leveraging proven powerful tools of time-domain and
frequency domain analysis to evaluate system stability. Critical to this work is both
the validation of realized models wherein these models can accurately predict system
response at varying load levels, renewable energy penetration levels, all-around necessary
sensitivities. Such a dynamic model development process can be used and
applied to any electric distribution feeder to better optimize penetration levels and
provide the planning engineer with smart models to optimize system planning.
Freeform optics, or optics with no axis of rotational invariance, provide optical designers more degrees of freedom, flexibility, and opportunity for innovation increasing optical performance and system integration while decreasing the form factor. Advancements in optical fabrication have enabled freeform surface manufacture with greater precision. Metrology instruments and techniques are needed to verify the performance of freeform optical surfaces and systems to keep up with design and manufacture. Freeform optics often have high slopes, no axis of symmetry, and a large departure from spherical, making traditional metrology techniques inadequate. This research was conducted to enable form measurements of freeform mirrors in the 250 mm class for a next generation three mirror anastigmatic (TMA) telescope complete with a statement of the measurement uncertainty to fill the gap in metrology of freeform optics. A flexible metrology instrument that could measure relatively large optics with customizable probe paths and sampling strategies was needed while maintaining the required precision.
Ultra-precision manufacturing is a deterministic method of producing optical-grade components. Continuous and interruptive machine operations are the main focus of this research with the goal of improving the manufacturing communities knowledge. The original contributions of this research are: (a) a comprehensive analysis of the cutting mechanics of single-crystal germanium, specifically studying the effects of major crystal orientation in germanium and cutting speed; (b) methodology for producing
flat, damage-free test samples in single-crystal germanium; and (c) machine learning model for estimating surface finish parameters Sa, Sq, and Sz for SPDT of single-crystal germanium and oxygen-free high-conductivity copper. As a final product of this research, a pair of collimating lenses were produced. AFRL funded the research for development of these lenses.
Ultra-precision manufacturing is a deterministic method of producing optical-grade components. Continuous and interruptive machine operations are the focus of this research with the goal of improving the manufacturing community’s knowledge. The original contributions of this research are: (a) a comprehensive analysis of the cutting mechanics of single-crystal germanium, specifically studying the effects of major crystal orientation in germanium and cutting speed; (b) methodology for producing flat, damage-free test samples in single-crystal germanium; and (c) machine learning model for estimating surface finish parameters Sa, Sq, and Sz for SPDT of single-crystal germanium and oxygen-free high-conductivity copper. As a final product of this research, a pair of collimating lenses were produced. AFRL funded the research for development of these lenses.
Demand for clean and safe drinking water is a global challenge because of water scarcity, growth of human population, urbanization, and anthropogenic pollution. Purification of water involves removal of small molecules and ions from ground water addressed as “emerging contaminants” which are extremely mobile and toxic in nature, do not degrade or hydrolyze easily, and highly soluble in water resulting in bioaccumulation. Most of the current water treatment systems have complex deficiencies that affect their overall performance. We have synthesized carbon nanostructures assisted ion exchange resins in aqueous medium that help remove these emerging contaminants in a fast, easy, and high capacity manner while supporting less contact time and low transmembrane resistance primarily achieved using thin film assemblies. We have developed a novel sonochemistry assisted atom transfer radical polymerization (SONO-ATRP) process for synthesis of polyelectrolyte anion exchange resins in water without use of any external initiator or reducing agents while using only a few ppm of catalyst. We successfully performed high-density functionalization of polyelectrolyte anion exchange resin strands onto single walled carbon nanotubes sidewalls using the SONO-ATRP process while at low reaction temperatures thereby providing a less energy intensive alternative for green chemistry. We have developed green processes to defluorinate fluorographite in water and simultaneously perform covalent grafting of anionic short brushes of poly(vinyl benzyl trimethylammonium chloride) to its surface under mild reaction conditions without need of any external reactive reagents. Field Emission Scanning Electron microscopy of thin film of functionalized carbon nanotubes demonstrated pin-hole free mesoporous architecture illustrating scaffold robustness while thin films of functionalized fluorographite exhibited stacked arrangement of plate-like structures. Exfoliation and functionalization of fluorographite was revealed through Transmission Electron Microscopy. Both the resins demonstrated high water flux (>1500 L m^(-2) h^(-1) bar^(-1)) due to their intrinsic architecture and high percent removal (>90%) of contaminants due to the tortuous path length during molecular transport through the membrane. These properties enable adsorption of impurities at environmentally relevant concentrations. These materials exhibited facile regeneration and reusage of the thin films, thus supporting sustainability. In conclusion, these processes abide by the principles of green chemistry and their processability opens new avenues for smart point-of-use water purification systems.
Decades of discriminatory housing policies have resulted in geographic segregation, forcing low-income minorities into areas of concentrated poverty (Massey & Kanaiaupuni, 1993; Stoloff, 2004). Areas of concentrated poverty are typically marked by poor housing quality, under performing schools, high crime rates, and limited access to resources such as healthcare and grocery stores, lack of social cohesion, and poor health outcomes (Crump, 2002; Dutko, Ver Ploeg, & Farrigan, 2012; Kawachi & Berkman, 2000; Massey, 1990). To combat the challenges associated with concentrated poverty and build healthy communities, place-based interventions have become increasingly popular (Arias, Escobedo, Kennedy, Fu, & Cisewski, 2018; Diez-Roux, 2017; Jutte, Miller, & Erickson, 2015). Several place-based models (e.g., Harlem Children’s Zone, Purpose Built Communities) have shown positive outcomes (Bridgespan 2004; 2011), however evaluation to guide replication and best practices have lagged.
This study examined data from a nonprofit replicating the Purpose Built Communities model in the southeastern U.S. Renaissance West Community Initiative (RWCI) is a place-based nonprofit that coordinates activities and services for residents living in a newly redeveloped mixed-income community and an adjacent low-income community. Activities coordinated by RWCI include college and career readiness programs, health education programs, health resources, community engagement activities, and children’s programs. Data from program participation and community surveys were assessed to understand the characteristics of adult residents, such as their education level, employment status, income, health, social networks, perceptions of their neighbors, participation in the nonprofit’s activities, and the degree to which each of these variables are related. Additionally, longitudinal analyses examined changes in these variables over a twelve to eighteen-month period.
Findings show that residents’ socioeconomic status (SES) and social network size were the primary predictors of the types of RWCI activities in which they participated and the frequency of participation. Participation in RWCI’s activities was not related to changes in SES, health, or neighborhood perceptions, but participation in activities was related to increased social network size. Social networks also played a role in neighborhood perceptions, such that residents with stronger neighborhood social networks had more positive perceptions of their neighbors overall. Residents with a disability had the lowest perceptions of their neighbors and reported worse health status.
The present study provides an example of how even limited quantitative data can be used by place-based nonprofits to understand the characteristics and experiences of adults living in their service area, to monitor implementation and outcomes, and provide guidance for improvements in use of resources to improve the community. The findings have implications for RWCI and their ongoing efforts to revitalize this low-income neighborhood into a healthy mixed-income community. Recommendations for ongoing data collection and analyses, targeting of services, and community building strategies are provided.
The environment where a person lives impacts their health more than clinical care provided. (RWJF, 2013) This research posits that the determinants of health (DOH) are best understood as a combination of social, structural, spatial and temporal aspects, not just “social”. Literature to date acknowledges these dimensions, although researchers have yet to fully explore. Utilizing a mixed-method approach, this research explores various DOH and their interactions spatially, structurally and temporally at the neighborhood level and how changes to those determinants are impacted by restructuring forces adversely affecting a Hispanic immigrant population. Specifically, this research aims to answer the following questions (1) How are the DOH impacted by the social, spatial, structural and temporal elements individually and in concert; (2) How has urban restructuring been a factor in the DOH for the Hispanic immigrant population in Southwest (SW) Charlotte; and (3) How does the acknowledgement of the structural, spatial and temporal aspects of DOH inform action to address the social and health needs of Hispanic immigrants living in Charlotte, NC. The South Boulevard corridor in the SW area of the city is the ideal case study location as it is simultaneously experiencing several forms of urban restructuring and an on-going influx of Hispanic immigrants. Ultimately, urban restructuring is an overlooked DOH in its own right - especially as it impacts vulnerable communities such as Hispanic immigrants as well as the importance of viewing the DOH in a nuanced manner acknowledging the influence and interactions of the various aspects.
This dissertation presents a new class of power converter topologies that realize galvanic
isolation by utilizing active transistor devices instead of conventional transformers.
The power converters employ standard switch-mode topologies but isolate the
ground connections with the addition of active switches on the ground side of the
power path. Compared to transformer isolation, the Active Isolated (AI) converters
have reduced size and cost with increased efficiency. A generalized approach is given
that is used to create thrity-six new active isolated topologies based on the following
basic converters: buck, boost, buck-boost, Cuk, SEPIC, and Zeta. Of these, the
buck-boost and boost-buck are determined optimum topologies since they achieve
pulsating and non-pulsating galvanic isolated conversion with the fewest component
count, respectively. The two optium converters are modeled mathematically and various
protoypes are developed that confirms proper galvanic isolation. The concept of
unipolar and bipolar isolation is explored and it is found that in many applications,
including the application choosen for this work, that unipolar isolation is adequate
to provide proper operation and safety for the user. Commom-mode transient and
steady-state models of the converters are developed and correlated to experimental
results. The two optimum convertes are used in two appliations: PV microinverter
and offline AC-DC power supply with fault protection.
