A Haptic System for Depicting Mathematical Graphics for Students with Visual Impairments

When teaching students with visual impairments educators generally rely on tactile tools to depict visual mathematical topics. Tactile media, such as embossed paper and simple manipulable materials, are typically used to convey graphical information. Although these tools are easy to use and relatively inexpensive, they are solely tactile and are not modifiable. Dynamic and interactive technologies such as pin matrices and haptic pens are also commercially available, but tend to be more expensive and less intuitive. This study aims to bridge the gap between easy-to-use tactile tools and dynamic, interactive technologies in order to facilitate the haptic learning of mathematical concepts. We developed an haptic assistive device using a Tanvas electrostatic touchscreen that provides the user with multimodal (haptic, auditory, and visual) output. Three methodological steps comprise this research: 1) a systematic literature review of the state of the art in the design and testing of tactile and haptic assistive devices, 2) a user-centered system design, and 3) testing of the system’s effectiveness via a usability study. The electrostatic touchscreen exhibits promise as an assistive device for displaying visual mathematical elements via the haptic modality.

Time Reversed Electromagnetic Wave Propagation as a Novel Method of Wireless Power Transfer

We investigate the application of time-reversed electromagnetic wave propagation to transmit energy in a wireless power transmission system. “Time reversal” is a signal focusing method that exploits the time reversal invariance of the lossless wave equation to direct signals onto a single point inside a complex scattering environment. In this work, we explore the properties of time reversed microwave pulses in a low-loss ray-chaotic chamber. We measure the spatial profile of the collapsing wavefront around the target antenna, and demonstrate that time reversal can be used to transfer energy to a receiver in motion. We demonstrate how nonlinear elements can be controlled to selectively focus on one target out of a group. Finally, we discuss the design of a rectenna for use in a time reversal system. We explore the implication of these results, and how they may be applied in future technologies.

Quantitative and Qualitative Trade-Off Analysis of Drowsy Driver Detection Methods: Single Electrode Wearable EEG Device, Multi-Electrode Wearable EEG Device, and Head-Mounted Gyroscope

Drowsy driving impairs motorists’ ability to operate vehicles safely, endangering both the drivers and other people on the road. The purpose of the project is to find the most effective wearable device to detect drowsiness. Existing research has demonstrated several options for drowsiness detection, such as electroencephalogram (EEG) brain wave measurement, eye tracking, head motions, and lane deviations. However, there are no detailed trade-off analyses for the cost, accuracy, detection time, and ergonomics of these methods. We chose to use two different EEG headsets: NeuroSky Mindwave Mobile (single-electrode) and Emotiv EPOC (14- electrode). We also tested a camera and gyroscope-accelerometer device. We can successfully determine drowsiness after five minutes of training using both single and multi-electrode EEGs. Devices were evaluated using the following criteria: time needed to achieve accurate reading, accuracy of prediction, rate of false positives vs. false negatives, and ergonomics and portability. This research will help improve detection devices, and reduce the number of future accidents due to drowsy driving.

Angler Perception and Population Dynamics of the Northern Snakehead (Channa argus) in the Potomac River & Tributaries

Our research sought to address the extent to which the northern snakehead (Channa argus), an invasive fish species, represents a threat to the Potomac River ecosystem. The first goal of our research was to survey the perceptions and opinions of recreational anglers on the effects of the snakehead population in the Potomac River ecosystem. To determine angler perceptions, we created and administered 113 surveys from June – September 2014 at recreational boat ramps along the Potomac River. Our surveys were designed to expand information collected during previous surveys conducted by the U.S. Fish and Wildlife Service. Our results indicated recreational anglers perceive that abundances and catch rates of target species, specifically largemouth bass, have declined since snakehead became established in the river. The second goal of our research was to determine the genetic diversity and potential of the snakehead population to expand in the Potomac River. We hypothesized that the effective genetic population size would be much less than the census size of the snakehead population in the Potomac River. We collected tissue samples (fin clippings) from 79 snakehead collected in a recreational tournament held between Fort Washington and Wilson’s Landing, MD on the Potomac River and from electrofishing sampling conducted by the Maryland Department of Natural Resources in Pomonkey Creek, a tributary of the Potomac River. DNA was extracted from the tissue samples and scored for 12 microsatellite markers, which had previously been identified for Potomac River snakehead. Microsatellite allele frequency data were recorded and analyzed in the software programs GenAlEx and NeEstimator to estimate heterozygosity and effective genetic population size. Resampling simulations indicated that the number of microsatellites and the number of fish analyzed provided sufficient precision. Simulations indicated that the effective population size estimate would expect to stabilize for samples > 70 individual snakehead. Based on a sample of 79 fish scored for 12 microsatellites, we calculated an Ne of 15.3 individuals. This is substantially smaller than both the sample size and estimated population size. We conclude that genetic diversity in the snakehead population in the Potomac River is low because the population has yet to recover from a genetic bottleneck associated with a founder effect due to their recent introduction into the system.

Therapeutic Potential of RNAi Through Endocytotic Methods

The ability to manipulate gene expression promises to be an important tool for the management of infectious diseases and genetic disorders. However, a major limitation to effective delivery of therapeutic RNA to living cells is the cellular toxicity of conventional techniques. Team PANACEA’s research objective was to create new reagents based on a novel small-molecule delivery system that uses a modular recombinant protein vehicle consisting of a specific ligand coupled to a Hepatitis B Virus-derived RNA binding domain (HBV-RBD). Two such recombinant delivery proteins were developed: one composed of Interleukin-8, the other consisting of the Machupo Virus GP1 protein. The ability of these proteins to deliver RNA to cells were then tested. The non-toxic nature of this technology has the potential to overcome limitations of current methods and could provide a platform for the expansion of personalized medicine.

On the Incorporation of Psychologically-Driven 'Music' Preference Models for Music Recommendation

There are hundreds of millions of songs available to the public, necessitating the use of music recommendation systems to discover new music. Currently, such systems account for only the quantitative musical elements of songs, failing to consider aspects of human perception of music and alienating the listener’s individual preferences from recommendations. Our research investigated the relationships between perceptual elements of music, represented by the MUSIC model, with computational musical features generated through The Echo Nest, to determine how a psychological representation of music preference can be incorporated into recommendation systems to embody an individual’s music preferences. Our resultant model facilitates computation of MUSIC factors using The Echo Nest features, and can potentially be integrated into recommendation systems for improved performance.

The Effect of Psychological Distance on Willingness to Engage in Ideologically Based Violence

Research on the cognitive and decision-making processes of individuals who choose to engage in ideologically based violence is vital. Our research examines how abstract and concrete construal mindsets affect likelihood to engage in ideologically based violence. Construal Level Theory (CLT) states that an abstract mindset (high-level construal), as opposed to a concrete mindset (low-level construal), is associated with a greater likelihood of engaging in goal-oriented, value-motivated behaviors. Assuming that ideologically based violence is goal-oriented, we hypothesized that high-level construal should result in an increased likelihood of engaging in ideologically based violence. In the pilot study we developed and tested 24 vignettes covering controversial topics and assessed them on features such as relatability, emotional impact, and capacity to elicit a violent reaction. The ten most impactful vignettes were selected for use in the primary investigations. The two primary investigations examined the effect of high- and low-level construal manipulations on self-reported likelihood of engaging in ideologically based violence. Self-reported willingness was measured through an ideological violence assessment. Data trends implied that participants were engaged in the study, as they reported a higher willingness to engage in ideologically based violence when they had a higher passion for the vignette's social issue topic. Our results did not indicate a significant relationship between construal manipulations and level of passion for a topic.

Concussion: Examining the Effect of Neuronal Oxidative Stress on the Pathophysiology of Brain and Blood Brain Barrier Cells

Neuronal stretching during concussion alters glucose transport and reduces neuronal viability, also affecting other cells in the brain and the Blood Brain Barrier (BBB). Our hypothesis is that oxidative stress (OS) generated in neurons during concussions contributes to this outcome. To validate this, we investigated: (1) whether OS independently causes alterations in brain and BBB cells, namely human neuron-like, neuroblastoma cells (NCs), astrocyte cells (ACs) and brain microvascular endothelial cells (ECs), and (2) whether OS originated in NCs (as in concussion) is responsible for causing the subsequent alterations observed in ACs and ECs. We used H2O2 treatment to mimic OS, validated by examining the resulting reactive oxygen species, and evaluated alterations in cell morphology, expression and localization of the glucose transporter GLUT1, and the overall cell viability. Our results showed that OS, either directly affecting each cell type or originally affecting NCs, caused changes in several morphological parameters (surface area, Feret diameter, circularity, inter-cellular distance), slightly varied GLUT1 expression and lowered the overall cell viability of all NCs, ACs, and ECs. Therefore, we can conclude that oxidative stress, which is known to be generated during concussion, caused alterations in NCs, ACs, and ECs whether independently originated in each cell or when originated in the NCs and could further propagate the ACs and ECs.

Investigating the Diabetic Brain: The Effects of Pioglitazone and Insulin on the Cellular Processes and Pathology of Alzheimer's Disease

Alzheimer’s disease (AD) is the sixth leading cause of death in the US. Some researchers refer to AD as “Type III Diabetes” because of reported glucose metabolism dysfunction. Preclinical studies suggest increasing insulin decreases AD pathology, although the mechanism remains unclear. To sensitize insulin signaling, this study activated Peroxisome Proliferator-Activated Receptor Gamma using intranasal co-administration of pioglitazone (PGZ) and insulin. This method targeted the site of action to reduce peripheral effects and to maximize impact in transgenic mice expressing AD pathology. Data from GC-MS fluxomics analysis suggested that PGZ+Insulin increased glucose metabolism in the brain. Immunohistochemistry with relevant antibodies was used to identify AD pathological markers in the subiculum, indicating that PGZ+Insulin decreased pathology compared to Insulin and Saline. This suggests that increasing glucose uptake in the brain alleviated AD pathology, further clarifying the role of insulin signaling in AD pathology.Gemstone

A Stationless Bikeshare Proof of Concept for College Campuses

Bikeshares promote healthy lifestyles and sustainability among commuters, casual riders, and tourists. However, the central pillar of modern systems, the bike station, cannot be easily integrated into a compact college campus. Fixed stations lack the flexibility to meet the needs of college students who make quick, short-distance trips. Additionally, the necessary cost of implementing and maintaining each station prohibits increasing the number of stations for user convenience. Therefore, the team developed a stationless bikeshare based on a smartlock permanently attached to bicycles in the system. The smartlock system design incorporates several innovative approaches to provide usability, security, and reliability that overcome the limitations of a station centered design. A focus group discussion allowed the team to receive feedback on the early lock, system, and website designs, identify improvements and craft a pleasant user experience. The team designed a unique, two-step lock system that is intuitive to operate while mitigating user error. To ensure security, user access is limited through near field ii communications (NFC) technology connected to a mechatronic release system. The said system relied on a NFC module and a servo working through an Arduino microcontroller coded in the Arduino IDE. To track rentals and maintain the system, each bike is fitted with an XBee module to communicate with a scalable ZigBee mesh network. The network allows for bidirectional, real-time communication with a Meteor.js web application, which enables user and administrator functions through an intuitive user interface available on mobile and desktop. The development of an independent smartlock to replace bike stations is essential to meet the needs of the modern college student. With the goal of creating a bikeshare that better serves college students, Team BIKES has laid the framework for a system that is affordable, easily adaptable, and implementable on any university expressing an interest in bringing a bikeshare to its campus.

A Study of pH Manipulation on Tumor Proliferation and the CTL Response

Adoptive Cell Transfer (ACT) Therapy is a cancer treatment that enhances and utilizes the body’s own immune system. However, this treatment has had limited success in clinical trials. We hypothesized that this is due to the immunosuppressive, acidic microenvironment of cancer tumors. We tested the effects of acidic, neutral, and basic environments in vitro on cytotoxic T lymphocyte (CTL) survival, activation, migration and killing ability and on cancer cell survival. We found that CTLs have most optimum survival, activation, and migration in a neutral environment, while the optimal extracellular conditions for EG-7 lymphoma are slightly acidic and B16-OVA melanoma survives best in physiological conditions. Future research should further study the killing ability of T cells in the three different environments and look to move to in vivo experiments.

The Effect of Dietary Tartrazine on Brain Dopamine and the Behavioral Symptoms of Attention Deficit Hyperactivity Disorder

Attention Deficit Hyperactivity Disorder is a neurodevelopmental disorder correlated with a decrease in brain dopamine and an increase in behavioral symptoms of hyperactivity and impulsivity. This experiment explored how tartrazine (Yellow #5) impacts these symptoms. After tartrazine administration to Spontaneously Hypertensive Rats (SHR), dopamine concentrations in regions of brain tissue were measured using Enzyme-Linked Immunosorbent Assay analysis. Behavioral testing with a T-maze and open field test measured impulsivity and hyperactivity, respectively. Results indicate that dietary tartrazine increases hyperactive behaviors in the SHR. However, results do not indicate a relationship between dietary tartrazine and brain dopamine. No conclusions regarding the relationship between dietary tartrazine and impulsivity were drawn.

EXAMINING THE IMPACT OF TEACHER PRACTICE ON STUDENT LEARNING IN INTERACTIVE RADIO INSTRUCTION (IRI) CLASSROOMS: LESSONS FROM NEW DELHI AND RAJASTHAN (INDIA)

This quantitative study examines the impact of teacher practices on student achievement in classrooms where the English is Fun Interactive Radio Instruction (IRI) programs were being used. A contemporary IRI design using a dual-audience approach, the English is Fun IRI programs delivered daily English language instruction to students in grades 1 and 2 in Delhi and Rajasthan through 120 30-minute programs via broadcast radio (the first audience) while modeling pedagogical techniques and behaviors for their teachers (the second audience). Few studies have examined how the dual-audience approach influences student learning. Using existing data from 32 teachers and 696 students, this study utilizes a multivariate multilevel model to examine the role of the primary expectations for teachers (e.g., setting up the IRI classroom, following instructions from the radio characters and ensuring students are participating) and the role of secondary expectations for teachers (e.g., modeling pedagogies and facilitating learning beyond the instructions) in promoting students’ learning in English listening skills, knowledge of vocabulary and use of sentences. The study finds that teacher practice on both sets of expectations mattered, but that practice in the secondary expectations mattered more. As expected, students made the smallest gains in the most difficult linguistic task (sentence use). The extent to which teachers satisfied the primary and secondary expectations was associated with gains in all three skills – confirming the relationship between students’ English proficiency and teacher practice in a dual-audience program. When it came to gains in students’ scores in sentence use, a teacher whose focus was greater on primary expectations had a negative effect on student performance in both states. In all, teacher practice clearly mattered but not in the same way for all three skills. An optimal scenario for teacher practice is presented in which gains in all three skills are maximized. These findings have important implications for the way the classroom teacher is cast in IRI programs that utilize a dual-audience approach and in the way IRI programs are contracted insofar as the role of the teacher in instruction is minimized and access is limited to instructional support from the IRI lessons alone.

SEQUENTIAL DECISIONS AND PREDICTIONS IN NATURAL LANGUAGE PROCESSING

Natural language processing has achieved great success in a wide range of ap- plications, producing both commercial language services and open-source language tools. However, most methods take a static or batch approach, assuming that the model has all information it needs and makes a one-time prediction. In this disser- tation, we study dynamic problems where the input comes in a sequence instead of all at once, and the output must be produced while the input is arriving. In these problems, predictions are often made based only on partial information. We see this dynamic setting in many real-time, interactive applications. These problems usually involve a trade-off between the amount of input received (cost) and the quality of the output prediction (accuracy). Therefore, the evaluation considers both objectives (e.g., plotting a Pareto curve). Our goal is to develop a formal understanding of sequential prediction and decision-making problems in natural language processing and to propose efficient solutions. Toward this end, we present meta-algorithms that take an existent batch model and produce a dynamic model to handle sequential inputs and outputs. Webuild our framework upon theories of Markov Decision Process (MDP), which allows learning to trade off competing objectives in a principled way. The main machine learning techniques we use are from imitation learning and reinforcement learning, and we advance current techniques to tackle problems arising in our settings. We evaluate our algorithm on a variety of applications, including dependency parsing, machine translation, and question answering. We show that our approach achieves a better cost-accuracy trade-off than the batch approach and heuristic-based decision- making approaches. We first propose a general framework for cost-sensitive prediction, where dif- ferent parts of the input come at different costs. We formulate a decision-making process that selects pieces of the input sequentially, and the selection is adaptive to each instance. Our approach is evaluated on both standard classification tasks and a structured prediction task (dependency parsing). We show that it achieves similar prediction quality to methods that use all input, while inducing a much smaller cost. Next, we extend the framework to problems where the input is revealed incremen- tally in a fixed order. We study two applications: simultaneous machine translation and quiz bowl (incremental text classification). We discuss challenges in this set- ting and show that adding domain knowledge eases the decision-making problem. A central theme throughout the chapters is an MDP formulation of a challenging problem with sequential input/output and trade-off decisions, accompanied by a learning algorithm that solves the MDP.