Neuromorphic model for sound source segregation

While humans can easily segregate and track a speaker's voice in a loud noisy environment, most modern speech recognition systems still perform poorly in loud background noise. The computational principles behind auditory source segregation in humans is not yet fully understood. In this dissertation, we develop a computational model for source segregation inspired by auditory processing in the brain. To support the key principles behind the computational model, we conduct a series of electro-encephalography experiments using both simple tone-based stimuli and more natural speech stimulus. Most source segregation algorithms utilize some form of prior information about the target speaker or use more than one simultaneous recording of the noisy speech mixtures. Other methods develop models on the noise characteristics. Source segregation of simultaneous speech mixtures with a single microphone recording and no knowledge of the target speaker is still a challenge. Using the principle of temporal coherence, we develop a novel computational model that exploits the difference in the temporal evolution of features that belong to different sources to perform unsupervised monaural source segregation. While using no prior information about the target speaker, this method can gracefully incorporate knowledge about the target speaker to further enhance the segregation.Through a series of EEG experiments we collect neurological evidence to support the principle behind the model. Aside from its unusual structure and computational innovations, the proposed model provides testable hypotheses of the physiological mechanisms of the remarkable perceptual ability of humans to segregate acoustic sources, and of its psychophysical manifestations in navigating complex sensory environments. Results from EEG experiments provide further insights into the assumptions behind the model and provide motivation for future single unit studies that can provide more direct evidence for the principle of temporal coherence.

A comprehensive study of multiplicative attribute graph model

Graphs are powerful tools to describe social, technological and biological networks, with nodes representing agents (people, websites, gene, etc.) and edges (or links) representing relations (or interactions) between agents. Examples of real-world networks include social networks, the World Wide Web, collaboration networks, protein networks, etc. Researchers often model these networks as random graphs. In this dissertation, we study a recently introduced social network model, named the Multiplicative Attribute Graph model (MAG), which takes into account the randomness of nodal attributes in the process of link formation (i.e., the probability of a link existing between two nodes depends on their attributes). Kim and Lesckovec, who defined the model, have claimed that this model exhibit some of the properties a real world social network is expected to have. Focusing on a homogeneous version of this model, we investigate the existence of zero-one laws for graph properties, e.g., the absence of isolated nodes, graph connectivity and the emergence of triangles. We obtain conditions on the parameters of the model, so that these properties occur with high or vanishingly probability as the number of nodes becomes unboundedly large. In that regime, we also investigate the property of triadic closure and the nodal degree distribution.

THERMAL VACUUM TEST CORRELATION OF A ZERO PROPELLANT LOAD CASE THERMAL CAPACITANCE PROPELLANT GAUGING ANALYTICAL MODEL

This thesis describes the development and correlation of a thermal model that forms the foundation of a thermal capacitance spacecraft propellant load estimator. Specific details of creating the thermal model for the diaphragm propellant tank used on NASA’s Magnetospheric Multiscale spacecraft using ANSYS and the correlation process implemented are presented. The thermal model was correlated to within +/- 3 Celsius of the thermal vacuum test data, and was determined sufficient to make future propellant predictions on MMS. The model was also found to be relatively sensitive to uncertainties in applied heat flux and mass knowledge of the tank. More work is needed to improve temperature predictions in the upper hemisphere of the propellant tank where predictions were found to be 2-2.5 Celsius lower than the test data. A road map for applying the model to predict propellant loads on the actual MMS spacecraft in 2017-2018 is also presented.

TAXONOMY, MORPHOLOGY, AND RNA-SEQ TRANSCRIPTOMICS OF THE CUBOZOAN ALATINA ALATA, AN EMERGING MODEL CNIDARIAN

Cnidarians are often considered simple animals, but the more than 13,000 estimated species (e.g., corals, hydroids and jellyfish) of the early diverging phylum exhibit a broad diversity of forms, functions and behaviors, some of which are demonstrably complex. In particular, cubozoans (box jellyfish) are cnidarians that have evolved a number of distinguishing features. Some cubozoan species possess complex mating behaviors or particularly potent stings, and all possess well-developed light sensation involving image-forming eyes. Like all cnidarians, cubozoans have specialized subcellular structures called nematocysts that are used in prey capture and defense. The objective of this study is to contribute to the development of the box jellyfish Alatina alata as a model cnidarian. This cubozoan species offers numerous advantages for investigating morphological and molecular traits underlying complex processes and coordinated behavior in free-living medusozoans (i.e., jellyfish), and more broadly throughout Metazoa. First, I provide an overview of Cnidaria with an emphasis on the current understanding of genes and proteins implicated in complex biological processes in a few select cnidarians. Second, to further develop resources for A. alata, I provide a formal redescription of this cubozoan and establish a neotype specimen voucher, which serve to stabilize the taxonomy of the species. Third, I generate the first functionally annotated transcriptome of adult and larval A. alata tissue and apply preliminary differential expression analyses to identify candidate genes implicated broadly in biological processes related to prey capture and defense, vision and the phototransduction pathway and sexual reproduction and gametogenesis. Fourth, to better understand venom diversity and mechanisms controlling venom synthesis in A. alata, I use bioinformatics to investigate gene candidates with dual roles in venom and digestion, and review the biology of prey capture and digestion in cubozoans. The morphological and molecular resources presented herein contribute to understanding the evolution of cubozoan characteristics and serve to facilitate further research on this emerging cubozoan model.

The Role of Attachment in a Social Cognitive Model of Social Domain Satisfaction in College Students

The study examined a modified social cognitive model of domain satisfaction (Lent, 2004). In addition to social cognitive variables and trait positive affect, the model included two aspects of adult attachment, attachment anxiety and avoidance. The study extended recent research on well-being and satisfaction in academic, work, and social domains. The adjusted model was tested in a sample of 454 college students, in order to determine the role of adult attachment variables in explaining social satisfaction, above and beyond the direct and indirect effects of trait positive affect. Confirmatory factor analysis found support for 8 correlated factors in the modified model: social domain satisfaction, positive affect, attachment avoidance, attachment anxiety, social support, social self-efficacy, social outcome expectations, and social goal progress. Three alternative structural models were tested to account for the ways in which attachment anxiety and attachment avoidance might relate to social satisfaction. Results of model testing provided support for a model in which attachment avoidance produced only an indirect path to social satisfaction via self-efficacy and social support. Positive affect, avoidance, social support, social self-efficacy, and goal progress each produced significant direct or indirect paths to social domain satisfaction, though attachment anxiety and social outcome expectations did not contribute to the predictive model. Implications of the findings regarding the modified social cognitive model of social domain satisfaction were discussed.

SOVLENT REACTIVITY AND INTERFACE EVOLUTION AT MODEL ELECTRODES FOR ENERGY APPLICATIONS

The Li-ion rechargeable battery (LIB) is widely used as an energy storage device, but has significant limitations in battery cycle life and safety. During initial charging, decomposition of the ethylene carbonate (EC)-based electrolytes of the LIB leads to the formation of a passivating layer on the anode known as the solid electrolyte interphase (SEI). The formation of an SEI has great impact on the cycle life and safety of LIB, yet mechanistic aspects of SEI formation are not fully understood. In this dissertation, two surface science model systems have been created under ultra-high vacuum (UHV) to probe the very initial stage of SEI formation at the model carbon anode surfaces of LIB. The first model system, Model System I, is an lithium-carbonate electrolyte/graphite C(0001) system. I have developed a temperature programmed desorption/temperature programmed reaction spectroscopy (TPD/TPRS) instrument as part of my dissertation to study Model System I in quantitative detail. The binding strengths and film growth mechanisms of key electrolyte molecules on model carbon anode surfaces with varying extents of lithiation were measured by TPD. TPRS was further used to track the gases evolved from different reduction products in the early-stage SEI formation. The branching ratio of multiple reaction pathways was quantified for the first time and determined to be 70.% organolithium products vs. 30% inorganic lithium product. The obtained branching ratio provides important information on the distribution of lithium salts that form at the very onset of SEI formation. One of the key reduction products formed from EC in early-stage SEI formation is lithium ethylene dicarbonate (LEDC). Despite intensive studies, the LEDC structure in either the bulk or thin-film (SEI) form is unknown. To enable structural study, pure LEDC was synthesized and subject to synchrotron X-ray diffraction measurements (bulk material) and STM measurements (deposited films). To enable studies of LEDC thin films, Model System II, a lithium ethylene dicarbonate (LEDC)-dimethylformamide (DMF)/Ag(111) system was created by a solution microaerosol deposition technique. Produced films were then imaged by ultra-high vacuum scanning tunneling microscopy (UHV-STM). As a control, the dimethylformamide (DMF)-Ag(111) system was first prepared and its complex 2D phase behavior was mapped out as a function of coverage. The evolution of three distinct monolayer phases of DMF was observed with increasing surface pressure — a 2D gas phase, an ordered DMF phase, and an ordered Ag(DMF)2 complex phase. The addition of LEDC to this mixture, seeded the nucleation of the ordered DMF islands at lower surface pressures (DMF coverages), and was interpreted through nucleation theory. A structural model of the nucleation seed was proposed, and the implication of ionic SEI products, such as LEDC, in early-stage SEI formation was discussed.

Counseling Self-Efficacy and the Relational Efficacy Model

Relation-inferred self-efficacy (RISE), a relatively new concept, is defined as a target individual’s beliefs about how an observer, often a relationship partner, perceives the target’s ability to perform certain actions successfully. Along with self-efficacy (i.e., one’s beliefs about his or her own ability) and other-efficacy (i.e., one’s beliefs about his or her partner’s ability), RISE makes up a three part system of interrelated efficacy beliefs known as the relational efficacy model (Lent & Lopez, 2002). Previous research has shown this model to be helpful in understanding how relational dyads, including coach-athlete, advisor-advisee, and romantic partners, contribute to the development of self-efficacy beliefs. The clinical supervision dyad (i.e., supervisor-supervisee), is another context in which relational efficacy beliefs may play an important role. This study investigated the relationship between counseling self-efficacy, RISE, and other-efficacy within the context of clinical supervision. Specifically, it examined whether supervisee perceptions about how their supervisor sees their counseling ability (RISE) related to how supervisees see their own counseling ability (counseling self-efficacy), and what moderates this relationship. The study also sought to discover the degree to which RISE mediated the relationship between supervisor working alliance and counseling self-efficacy. Data were collected from 240 graduate students who were currently enrolled in counseling related fields, working with at least one client, and receiving regular supervision. Results demonstrated that years of experience and RISE predicted counseling self-efficacy and that the relationship between RISE and counseling self-efficacy was, as expected, moderated by other-efficacy. Contrary to expectations, however, counseling experience and level of client difficulty did not moderate the relationship between RISE and counseling self-efficacy. These findings suggest that the relationship between RISE and counseling self-efficacy was stronger when supervisees saw their supervisors as capable therapists. Furthermore, RISE was found to fully mediate the relationship between supervisor working alliance and counseling self-efficacy. Future research directions and implications for training and supervision are discussed.

THE INFLUENCE OF MOTIVATION ON EMOTION REGULATION AND MOTOR PERFORMANCE: EXAMINATION OF A NEURO-AFFECTIVE MODEL

Mental stress is known to disrupt the execution of motor performance and can lead to decrements in the quality of performance, however, individuals have shown significant differences regarding how fast and well they can perform a skilled task according to how well they can manage stress and emotion. The purpose of this study was to advance our understanding of how the brain modulates emotional reactivity under different motivational states to achieve differential performance in a target shooting task that requires precision visuomotor coordination. In order to study the interactions in emotion regulatory brain areas (i.e. the ventral striatum, amygdala, prefrontal cortex) and the autonomic nervous system, reward and punishment interventions were employed and the resulting behavioral and physiological responses contrasted to observe the changes in shooting performance (i.e. shooting accuracy and stability of aim) and neuro-cognitive processes (i.e. cognitive load and reserve) during the shooting task. Thirty-five participants, aged 18 to 38 years, from the Reserve Officers’ Training Corp (ROTC) at the University of Maryland were recruited to take 30 shots at a bullseye target in three different experimental conditions. In the reward condition, $1 was added to their total balance for every 10-point shot. In the punishment condition, $1 was deducted from their total balance if they did not hit the 10-point area. In the neutral condition, no money was added or deducted from their total balance. When in the reward condition, which was reportedly most enjoyable and least stressful of the conditions, heart rate variability was found to be positively related to shooting scores, inversely related to variability in shooting performance and positively related to alpha power (i.e. less activation) in the left temporal region. In the punishment (and most stressful) condition, an increase in sympathetic response (i.e. increased LF/HF ratio) was positively related to jerking movements as well as variability of placement (on the target) in the shots taken. This, coupled with error monitoring activity in the anterior cingulate cortex, suggests evaluation of self-efficacy might be driving arousal regulation, thus affecting shooting performance. Better performers showed variable, increasing high-alpha power in the temporal region during the aiming period towards taking the shot which could indicate an adaptive strategy of engagement. They also showed lower coherence during hit shots than missed shots which was coupled with reduced jerking movements and better precision and accuracy. Frontal asymmetry measures revealed possible influence of the prefrontal lobe in driving this effect in reward and neutral conditions. The possible interactions, reasons behind these findings and implications are discussed.

DEVELOPMENT OF A NUCLEIC ACID-BASED SPECIFIC GROWTH MODEL FOR JUVENILE BLUE CRAB, CALLINECTES SAPIDUS

The evaluation and identification of habitats that function as nurseries for marine species has the potential to improve conservation and management. A key assessment of nursery habitat is estimating individual growth. However, the discrete growth of crustaceans presents a challenge for many traditional in situ techniques to accurately estimate growth over a short temporal scale. To evaluate the use of nucleic acid ratios (R:D) for juvenile blue crab (Callinectes sapidus), I developed and validated an R:D-based index of growth in the laboratory. R:D based growth estimates of crabs collected in the Patuxent River, MD indicated growth ranged from 0.8-25.9 (mg·g-1·d-1). Overall, there was no effect of size on growth, whereas there was a weak, but significant effect of date. These data provide insight into patterns of habitat-specific growth. These results highlight the complexity of the biological and physical factors which regulate growth of juvenile blue crabs in the field.

TRAFFIC IMPACT ANALYSIS OF SEVERAL DYNAMIC LANE MANAGEMENT STRATEGIES FOR CONGESTION MITIGATION BASED ON DTA MODEL

Persistent daily congestion has been increasing in recent years, particularly along major corridors during selected periods in the mornings and evenings. On certain segments, these roadways are often at or near capacity. However, a conventional Predefined control strategy did not fit the demands that changed over time, making it necessary to implement the various dynamical lane management strategies discussed in this thesis. Those strategies include hard shoulder running, reversible HOV lanes, dynamic tolls and variable speed limit. A mesoscopic agent-based DTA model is used to simulate different strategies and scenarios. From the analyses, all strategies aim to mitigate congestion in terms of the average speed and average density. The largest improvement can be found in hard shoulder running and reversible HOV lanes while the other two provide more stable traffic. In terms of average speed and travel time, hard shoulder running is the most congested strategy for I-270 to help relieve the traffic pressure.

Curated Commons: The Maryland Model

The curated commons is a model in which a flexible library building shell and its infrastructure can respond to the specific time-sensitive needs of differing clients. It applies to faculty research, in particular small science activities (as opposed to big science activities that have major support which includes proprietary laboratories and facilities). It provides for sustained transformation of library facilities as well as its utilitarian and cyber-infrastructures to become a flexible reconfigurable space with cutting edge technology and sustained funding streams.