CERVIXCHECK: A SPIRITUALLY-BASED SMS TEXT MESSAGING PILOT INTERVENTION TO INCREASE CERVICAL CANCER AWARENESS AND PAP TEST SCREENING INTENTION AMONG AFRICAN AMERICAN WOMEN

African American women account for a disproportionate burden of cervical cancer incidence and mortality rate when compared to non-Hispanic White women. Cervical cancer is one of the most preventable types of cancer, and women can be screened for it with a routine Pap test. Given that religion occupies an essential place in African American lives, framing health messages with important spiritual themes and delivering them through a popular communication delivery channel may allow for a more culturally-relevant and accessible technology-based approach to promoting cervical cancer educational content to African American women. Using community-engaged research as a framework, the purpose of this multiple methods study was to develop, pilot test, and evaluate the feasibility, acceptability, and initial efficacy of a spiritually-based SMS text messaging intervention to increase cervical cancer awareness and Pap test screening intention among African American women. The study recruited church-attending African American women ages 21-65 and was conducted in three phases. Phases 1 and 2 consisted of a series of focus group discussions (n=15), cognitive response interviews (n=8), and initial usability testing that were conducted to inform the intervention development and modifications. Phase 3 utilized a non-experimental one-group pretest-posttest design to pilot test the 16-day text messaging intervention (n=52). Of the individuals enrolled, forty-six completed the posttest (retention rate=88%). Findings provided evidence for the early feasibility, high acceptability, and some initial efficacy of the CervixCheck intervention. There were significant pre-post increases observed for knowledge about cervical cancer and the Pap test (p = .001) and subjective norms (p = .006). Additionally, results post-intervention revealed that 83% of participants reported being either “satisfied” or “very satisfied” with the program and 85% found the text messages either “useful” or “very useful”. 85% of the participants also indicated that they would “likely” or “very likely” share the information they learned from the intervention with the women around them, with 39% indicating that they had already shared some of the information they received with others they knew. A spiritually-based SMS text messaging intervention could be a culturally appropriate and cost-effective method of promoting cervical cancer early detection information to African American women.

Learning Binary Code Representations for Effective and Efficient Image Retrieval

The size of online image datasets is constantly increasing. Considering an image dataset with millions of images, image retrieval becomes a seemingly intractable problem for exhaustive similarity search algorithms. Hashing methods, which encodes high-dimensional descriptors into compact binary strings, have become very popular because of their high efficiency in search and storage capacity. In the first part, we propose a multimodal retrieval method based on latent feature models. The procedure consists of a nonparametric Bayesian framework for learning underlying semantically meaningful abstract features in a multimodal dataset, a probabilistic retrieval model that allows cross-modal queries and an extension model for relevance feedback. In the second part, we focus on supervised hashing with kernels. We describe a flexible hashing procedure that treats binary codes and pairwise semantic similarity as latent and observed variables, respectively, in a probabilistic model based on Gaussian processes for binary classification. We present a scalable inference algorithm with the sparse pseudo-input Gaussian process (SPGP) model and distributed computing. In the last part, we define an incremental hashing strategy for dynamic databases where new images are added to the databases frequently. The method is based on a two-stage classification framework using binary and multi-class SVMs. The proposed method also enforces balance in binary codes by an imbalance penalty to obtain higher quality binary codes. We learn hash functions by an efficient algorithm where the NP-hard problem of finding optimal binary codes is solved via cyclic coordinate descent and SVMs are trained in a parallelized incremental manner. For modifications like adding images from an unseen class, we propose an incremental procedure for effective and efficient updates to the previous hash functions. Experiments on three large-scale image datasets demonstrate that the incremental strategy is capable of efficiently updating hash functions to the same retrieval performance as hashing from scratch.

MULTI-BAND BOSE HUBBARD MODELS AND EFFECTIVE THREE-BODY INTERACTIONS

Experiments with ultracold atoms in optical lattice have become a versatile testing ground to study diverse quantum many-body Hamiltonians. A single-band Bose-Hubbard (BH) Hamiltonian was first proposed to describe these systems in 1998 and its associated quantum phase-transition was subsequently observed in 2002. Over the years, there has been a rapid progress in experimental realizations of more complex lattice geometries, leading to more exotic BH Hamiltonians with contributions from excited bands, and modified tunneling and interaction energies. There has also been interesting theoretical insights and experimental studies on “un- conventional” Bose-Einstein condensates in optical lattices and predictions of rich orbital physics in higher bands. In this thesis, I present our results on several multi- band BH models and emergent quantum phenomena. In particular, I study optical lattices with two local minima per unit cell and show that the low energy states of a multi-band BH Hamiltonian with only pairwise interactions is equivalent to an effec- tive single-band Hamiltonian with strong three-body interactions. I also propose a second method to create three-body interactions in ultracold gases of bosonic atoms in a optical lattice. In this case, this is achieved by a careful cancellation of two contributions in the pair-wise interaction between the atoms, one proportional to the zero-energy scattering length and a second proportional to the effective range. I subsequently study the physics of Bose-Einstein condensation in the second band of a double-well 2D lattice and show that the collision aided decay rate of the con- densate to the ground band is smaller than the tunneling rate between neighboring unit cells. Finally, I propose a numerical method using the discrete variable repre- sentation for constructing real-valued Wannier functions localized in a unit cell for optical lattices. The developed numerical method is general and can be applied to a wide array of optical lattice geometries in one, two or three dimensions.