UC Irvine

The biological effects of ionizing radiation on female reproduction have relatively been understudied. Currently about 30 percent of astronauts are women, and 46% of the 2017 NASA astronaut class are women. Astronauts are exposed to galactic cosmic rays (GCR) during travel in deep space. Galactic cosmic radiation is the dominant source of radiation that originates outside the earth’s solar system. And must be dealt with aboard current spacecraft and future space missions within our solar system. It permeates interplanetary space and can pass practically unimpeded through a spacecraft or the skin of an astronaut. GCR consist of protons, alpha particles, high-energy and highly charged ions called HZE particles and electrons. When GCR interacts with the gases within interstellar space, gamma radiation is also emitted. In assessing the reproductive toxicity risks to female astronauts, the premise that HZE particles have greater relative biological effectiveness than gamma radiation for ovarian toxicity has not been directly tested. Recently published studies investigated the effects of high LET 56Fe and 16O particles in mice of the same strain and age (Mishra et al., 2016 and 2017). Both studies demonstrated profound sensitivity of the ovary to high-LET charged ion irradiation, with more than half of the irreplaceable ovarian follicle reserve destroyed 1week after low dose irradiation. Comparison of prior studies suggest that high LET radiation may be a more potent inducer of ovarian follicle depletion than photon radiation, but existing published data sets did not utilize low enough doses of photon radiation to model the dose-response for these endpoints. In the current study, we present a comparison study investigating gamma radiation-induced dose dependent follicular destruction and relative biological effectiveness using same mice strain and age. 3-month-old female C57BL/6J mice were gamma-irradiated (0, 5, 15, and 50 cGy) using a 137Cs source and euthanized 1week after irradiation. Ovaries were collected and fixed in Bouin’s fixative at necropsy and were embedded in paraffin. Ovaries were then serially and completely sectioned at 5 µm thickness. Sections were stained with hematoxylin and eosin. Ovarian follicles were counted using light microscopy, blinded to the treatment group. We hypothesized that 1) gamma radiation will cause dose dependent ovotoxicity and morphological reduction in ovarian size and 2) ovarian follicle destruction from gamma radiation will be less potent than high charged high LET particle radiation. Result: 137Cs gamma radiation induced statistically significant reduction in measured total body in irradiated mice. Preliminary histomorphometric counts of 15 out of 32 ovaries shows 50cGy resulted in a dramatic total destruction of primordial and primary ovarian follicles after 1 week of irradiation, while follicle counts after 5 and 15 cGy did not differ from unirradiated controls.

Although it is widely acknowledged that heart disease is the number one killer of Americans, what may not be so commonly known is that genetic mutations can cause heart diseases. According to numerous studies, many mutated genes cause heart diseases such as cardiomyopathies, and arrhythmias, yet the practical diagnosis and treatment for them are scarce. Lamin A/C gene (LMNA) is one of the genes that can cause dilated cardiomyopathy, arrhythmia, and heart failure. This gene codes for proteins, which create a mesh-like layer under the nucleus envelope known as the nuclear lamina. Even though nuclear lamina exists in almost every nucleated cell in the body, there are individuals with LMNA splice site mutation (c.357-2A>G) who mainly have heart problems. The mechanisms by which LMNA mutations cause heart dysfunctions remain a mystery. In this project, human-induced Pluripotent Stem Cells (hiPSCs) derived cardiomyocytes have been used to develop an in vitro model of the consequences of the mutation on heart function. We demonstrated that it is possible to recapitulate the pathological phenotype in vitro by using patient-specific derived cells and tissue engineering techniques, even though the patients do not exhibit symptoms until later in life. Moreover, this in vitro model of cardiomyocytes tissues can be utilized to correlate gene profiles, structure, and function of the hiPSC-derived cardiomyocytes; thus, elucidating the disease-causing mechanisms.

These poems are invested in measuring, or perhaps simply noticing, the distance between things— person A and person B, the external and internal, life and death, etc.

Time asynchrony inherently exists in many wireless communication systems, especially in

multiuser scenarios, where the users are located in various locations. Different locations

and paths impose different delays on the received signals, resulting in asynchronous reception

at the receiver. In most of the works in the literature, perfect synchronization among

received signals is a common presumption. However, it might be impossible to synchronize

signals at all the nodes in the network even if an ideal infrastructure using control

signals is considered. For example, assume that the receiver encompasses multiple receive

antennas or multiple distributed base stations. Then, although the synchronization can

be realized at one of them, realizing synchronization at all of the base stations/antennas

might be impossible. Thus, it is essential to investigate the effect of the time asynchrony

in the wireless systems, particularly multiuser systems.

Asynchrony naturally imposes some performance degradation in a system designed optimally

based on having synchronized incoming signals. One immediate solution is to

eliminate the time asynchrony and achieve almost perfect synchronization among the received

signals. This question is analyzed under the notion of time synchronization. There

are many methods proposed and analyzed in literature aiming for that goal, and one of the common ones is to use control signals to achieve synchronization among different users.

However, apart from this approach's feasibility, the questions which are atypical but of

importance to answer are: Can a system be designed such that it provides performance

improvement under an asynchronous condition? Can a system, which is designed based

on the asynchronous assumption, outperform its counterpart system, which is designed based

on the assumption of perfect synchronization?

We thoroughly investigate these questions in this thesis. First, we theoretically analyze

the performance bounds of multi-antenna, multiuser systems under the asynchrony assumptions.

We show that by exploiting inherent time delays between different users in

a multiuser/multi-antenna scenario, we can improve the performance. Besides, we propose

to intentionally add timing osets in the systems that are not inherently impaired

by time asynchrony. We introduce the optimal transceiver designs under asynchronous

assumptions and analyze the performance improvement provided. We consider various

multiuser networks, including broadcasting networks, multiple access networks, and cooperative

networks, and examine the advantages and disadvantages of having asynchrony

in such multiuser networks.

Drawing from Eccles’s Expectancy-Value Theory, the three studies in this dissertation adopted within-person cross-lagged panel models to examine youth’s bidirectional importance belief socialization by parents in math, sports and music. Using data from the Michigan Study of Adolescent and Adult Life Transitions as well as the Childhood and Beyond dataset, including youth and their parents from 1st to 7th grade, we had two sets of major findings. First, we found that parents influenced youth’s importance beliefs in all domains; however, youth only influenced their parents’ importance beliefs in leisure domains (i.e., sports and music). Second, in both math and sports, youth’s internalization of their parents’ values were interfered with or even hijacked by projection. We compared those results with prior research and discussed their theoretical relevance.

Over the last quarter century, the intensification of human activities in urbanized areas, coupled with an increase in frequency and length of extreme droughts, has resulted in the growing demand for safe, reliable, and sustainable water. Municipal and industrial water reclamation has been the subject of much interest since it provides a more balanced solution on metrics such as land-use footprint, energy and operational costs, and reliability when compared to other alternative water solutions. As water stressed cities are increasingly relying on recycled water, treated wastewater effluent standards are becoming progressively stricter due to concerns associated with human exposure. Therefore, significant efforts have been devoted towards the optimization of conventional and advanced wastewater treatment processes in order to improve the sustainability of their operations in terms of effluent quality, energy use, greenhouse gas emissions and costs.

Dynamic modeling continues to provide a powerful tool for the evaluation of novel optimization strategies in the field of municipal and industrial wastewater treatment. Therefore, in this dissertation, three different systems have been carefully analyzed due to their growing interest in the field of wastewater treatment and reclamation. Through the use of dynamic process models, the optimization of these systems was evaluated. The topics presented are: i) optimization of air supply system in municipal water resource recovery facilities (WRRFs); ii) optimization of produced water clarifiers in petrochemical wastewater treatment facilities (PWTFs); and iii) optimization of hybrid WRRFs systems.

In the first topic, in-situ off-gas testing coupled with dynamic simulations of a full-scale air supply system have highlighted the significant impact that an imbalance in airflow distribution can have on the overall performance of a municipal WRRFs. Along with a family of dynamic process models, a multi-criteria analysis of an air supply model was performed by parametrizing the manual valves used to distribute the airflow to the various reactor zones. A trade-offs analysis showed potential energy savings of up to 13.6% and improvement of effluent quality for NH4+ (up to 68.5%) and NOx (up to 81.6%).

In the second topic, a novel clarifier model is proposed for the dynamic description of clarification tanks used to concurrently separate solids and oils dispersion in petrochemical wastewaters. Batch settling tests of samples collected from a petrochemical wastewater treatment plant in China revealed that the gravity separation of oils and solids behaves according to discrete particle dynamics. Therefore, a Stokesian particle separation model was incorporated into the produced water clarifier model, which is based on measured particle settling velocity distribution (PSVD) curves. Furthermore, through an ensemble of Monte Carlo simulations it was possible to analyze the separation performance of various flow configurations of the underflow and water effluent streams. It was in general possible to observe a marked trade-off between the competing goals of solids thickening and oil recovery.

In the third topic, a new conceptual framework for the dynamic management of hybrid WRRFs systems comprised of both centralized and satellite WRRFs is introduced. The underlying concept of such strategy relies on exploiting the hydraulic delay of sewer trunk lines for the deferral of the treatment intensity between hydraulically connected facilities during specific hours of the day. This study provides a novel insight into the dynamic management of hybrid wastewater treatment systems and highlights its potential to reduce the greenhouse gases, power demand, energy use and costs associated with treating the wastewater. Results show the potential to reduce by 25% the total power demand exerted during grid ramping hours. Furthermore, total costs, energy and greenhouse gas emissions could be reduced by 8.5%, 4.1%, and 4.5% respectively.

Wireless mobile networks are expected to become progressively more prevalent in the future society, connecting billions of populations across the globe and an even higher number of intelligent devices scattered in the environment. Moreover, the supported data rate on mobile devices keeps increasing with the deployment of next generation network infrastructure, e.g. 5G network, and upgrades on existing infrastructures. Consequently, enormous amounts of data traffic will be generated on a daily basis and data exchange between base stations and the backbone network through conventional backhaul links will quickly become a bottleneck. On the other hand, mobile terminals, the elemental building blocks of all mobile networks continue to be hindered by ever-increasing interference blocking problems in a more and more congested environment, both spectrally and spatially. This dissertation aims to study potential solutions for the aforementioned two major issues in mobile networks from a transceiver circuit design perspective.

In the first part of this dissertation, a direct modulation high-order QAM transmitter architecture is proposed and analyzed for mm-wave high-speed wireless links, targeting for applications such as wireless backhaul. The daunting and costly task of designing integrated

high-speed-resolution digital-to-analog interface and complicated digital back-end in conventional architectures is completely avoided. Link performance, cost and level of integration are greatly improved as a result. Prototype transmitter has been designed, fabricated and

measured to verify the proposed concept. Operating at 115-GHz carrier frequency, the transmitter achieves a 20Gbps data rate in a short-range wireless link using 16QAM modulation. Error vector magnitude (EVM) was measured to be −15.8 dB at a modulated output power of +1 dBm. The transmitter consumes 520 mW of power and occupies 3.17 mm2 of active area in a 180-nm SiGe BiCMOS process.

In the second part, the mobile terminal blocking problem is addressed. While benefiting from superior linearity, blocker-tolerance and high-Q programmable selectivity brought forth by N-path filtering technique, the common problem of elevated local oscillator (LO) leakage in prior work is significantly mitigated in the proposed receiver design to comply with cellular standards. The design of the proposed receiver is analyzed in great details. The prototype receiver was measured to be highly linear with low noise figure and LO leakage. Out-of-band 2nd and 3rd order input-referred-intercept-point (IIP2 and IIP3) reaches +60 dBm and +14 dBm, respectively. Small-signal noise figure was measured to be below 2.5 dB and degrades by 4.5 dB in the presence of a 0 dBm blocker at 80 MHz offset. The LO leakage was kept under −80 dBm up to 2 GHz.

Obesity has reached epidemic status, threatening millions of lives and straining national economies and health-care systems. Obesity is a chronic disease with diverse etiologies, arising from complex interactions between genetic, physiologic, psychologic and environmental factors that can undermine one’s ability to maintain a healthy weight. The current standard of care, behavioral and lifestyle interventions, has proven to be inadequate for a majority of obese patients thus use of pharmacotherapies has been proposed as an adjunct to lifestyle changes to overcome barriers to weight loss.

However limited efficacy and poor safety prevent the widespread use of current pharmacotherapies, prompting the demand for new drug targets and novel therapeutics.

893 was previously characterized as a synthetic sphingolipid analog that simultaneously blocks multiple pathways of cellular nutrient uptake. Because chronic nutrient overload underlies much of obesity pathologies, we hypothesized that such a molecule would be an effective anti-obesity agent by putting cells on a diet, rather than a whole patient. To test this, we used 893 in an established mouse model of diet-induced obesity (DIO) that recapitulates the gradual weight gain and metabolic decline that occurs in humans from passive overconsumption of energy dense foods. 893 safely restored normal body weight, reversed hepatic steatosis, and improved glucose homeostasis in obese mice maintained on a high-fat diet (HFD). 893 suppressed food intake and promoted whole body lipid metabolism in vivo. Prolonged HFD feeding induces ceramide-dependent mitochondrial fission that was directly blocked by 893 both in vitro and in vivo. This work demonstrates that 893 and related molecules represent a potential new strategy to tackle the growing obesity epidemic and highlights mitochondrial fission as a potential therapeutic target.

This dissertation is an accumulation of my contribution to the fundamental understanding of ensemble Density Functional Theory and finite temperature Density Functional Theory, through the use of quantum model systems. Ensemble DFT is a time-independent method to extracting excitation energies, and provides a way to extract multiple excitations. Currently this is not possible with the common approximations used in time-dependent DFT. Chapter 3 of this thesis covers ensemble DFT and verifies an exact exchange approximation that can accurately capture multiple excitations using the Hubbard model. Finite temperature DFT is often incorrectly confused with ensemble DFT, and refers to DFT at non zero temperatures. Its value comes from its applications to warm dense matter simulations. The last three chapters of this dissertation contain several projects in the hopes of improving the understanding of finite temperature DFT. In particular it generalizes the PPLB derivative discontinuity model to finite temperatures, and discusses the construction of an exact finite temperature approximation. These contributions are done with the intention on enhancing warm dense simulations.

For self-driving vehicles, aerial drones, and autonomous robots to be successfully deployed in the real-world, they must be able to navigate complex environments and track objects. While Artificial Intelligence and Machine Vision have made significant progress in dynamic scene understanding, they are not yet as robust and computationally efficient as humans or other primates in these tasks. For example, the current state-of-the-art visual tracking methods become inaccurate when applied to random test videos. We suggest that ideas from cortical visual processing can inspire real world solutions for motion perception and tracking that are robust and efficient. In this context, the following contributions are made in this dissertation. First, a method for estimating 6DoF ego-motion and pixel-wise object motion is introduced, based on a learned overcomplete motion field basis set. The method uses motion field constraints for training and a novel differentiable sparsity regularizer to achieve state-of-the-art ego and object-motion performances on benchmark datasets. Second, a Convolutional Neural Network (CNN) that learns hidden neural representations analogous to the response characteristics of dorsal Medial Superior Temporal area (MSTd) neurons for optic flow and object motion is presented. The findings suggest that goal driven training of CNNs might automatically result in the MSTd-like response properties of model neurons. Third, a recurrent neural network model of predictive smooth pursuit eye movements is presented that generates similar pursuit initiation and predictive pursuit behaviors as observed in humans. The model provides the computational mechanisms of formation and rapid update of an internal model of target velocity, commonly attributed to zero lag tracking and smooth pursuit of occluded objects. Finally, a spike based stereo depth algorithm is presented that reconstructs dynamic visual scenes at 400 frames-per-second with one watt of power consumption when implemented using the IBM TrueNorth processor. Taken together, the presented models and implementations provide the computations for motion perception in the dorsal visual pathway in the brain and inform ideas for efficient computational vision systems.