Cancer is one of the most common causes of mortality in homeless adults. When a homeless person is hospitalized, they typically return to the streets, making recovery difficult. Conducting a needs assessment survey of homeless patients who are newly diagnosed with cancer was the first step towards evaluating how they can receive safe and cost-effective healthcare. Collection of information was from three perspectives: the patient, the oncology provider, and costs. Nine qualitative interviews with homeless individuals focused on concerns and barriers to care. Ten qualitative interviews with Medical Oncologists as well as a 20 question Survey Monkey was sent to all providers and focused on current treatment of their homeless patients. Lastly, a retrospective cost analysis examined costs of inpatient and outpatient care during chemotherapy. Two themes emerged from the patient interviews: Barriers to care and Someone to help. Three themes emerged from the oncology interviews: I worry about everything, Making decisions, and Care after chemotherapy. Half of the 19 providers who responded to the Survey Monkey questions indicated that they would revise treatment plans because of homelessness. All providers stated they would utilize a housing first option if available for their homeless patients. The retrospective cost analysis of 53 homeless patients with cancer over a 5-year period showed cost savings from inpatient vs outpatient treatment which totaled $9.0 million dollars. Drawing up a proposal to share with stakeholders is needed to develop a plan to help this population which may include a housing first/respite home as a solution.
In this paper, we have applied case cohort study design to semiparametric additive hazard models to study the effect of covariates on failure times. We have considered the phase one covariates to have both time varying and constant effect on failure time while phase two covariates have constant effect. We have applied Augmented Inverse Probability Weighted (AIPW) method to estimate the model
parameters and compared the result with widely adopted Inverse Probability Weighted (IPW) method. Our simulation study shows that AIPW estimation is more consistent than IPW estimation method. The method is applied to analyze the RV144 vaccine trial data to assess whether immune response and behavioral risk level has effect on HIV-1 infection.
The correct folding of proteins after synthesis and stress-promoted denaturation is critical for cell viability in all organisms. The Hsp70 molecular chaperone is a key player in proteostasis, deciding which proteins are foldable and which are too badly damaged and need to be targeted for degradation. Hsp70 plays an important role as a drive of cancer, stabilizing key mutated oncoproteins such as HER2, p53, RNR, SHR and MUC1. This importance of Hsp70 in basic cell functions as well as human illness prompted us to examine novel ways to characterize Hsp70 genetic and physical interactors. In this thesis, we decided to tackle three main roadblocks in studying chaperone interactions; 1) purification of chaperone complexes at native stoichiometry in mammalian cells, 2) understanding the roles of co-chaperones in cancer 3) teasing apart bridged vs direct chaperone interactions. To solve the issue of native stoichiometry purification, we have utilized CRISPR-Cas9 genome engineering to insert epitope tags into the N-terminus of Hsp70 in mammalian cells. This tagged chaperone is present as the only Hsp70 in cells, is stable without the use of any selectable marker and allows expression of Hsp70 at native levels. To understand co-chaperone function in cancer, we used a novel chemogenomic screening technology on WT and DNAJA1 knockout HAP1 cells. In doing so, we have uncovered a dependence of a large proportion of approved oncology drugs on DNAJA1 status. Finally, we have used cross-linking mass spectrometry to define for the first time the direct interactors of Hsp70 in yeast. Our data reveals a wealth of information of fundamental Hsp70 function including discovery of active Hsp70 dimers, client binding throughout Hsp70 and a huge number of novel PTM-associated Hsp70 interactions. Overall, aside from gaining fundamental insight into the workings of Hsp70, this thesis provides a roadmap and tools for the chaperone community to explore novel biologically relevant Hsp70 interactions.
This multiple case study explored the characteristics of clinical experiences that support preservice teachers' understandings of culturally responsive literacy in elementary classrooms. In particular, this study focused on capturing the voices and perspectives of three preservice teachers through semi-structured interviews, observations, and the collection of artifacts such as literacy lesson plans, journal entries, and photographs. Findings suggest that preservice teachers generally understand culturally responsive teaching as: (a) using a variety of diverse texts; (b) building a learning community that honors students’ cultures, (c) maintaining high expectations for all students; and (d) teachers knowing their students in order to connect the course content to their lives, cultures, and interests based on their coursework and experiences in the clinical setting. Data also showed that clinical educators are the most influential characteristic of preservice teachers’ understandings of culturally responsive literacy and being in the classroom setting is more influential than only learning about culturally responsive teaching through university coursework. Findings also indicate that preservice teachers are developing superficial understandings of culturally responsive teaching, suggesting implications for teacher education and preparation.
Federal legislation has mandated students with and without disabilities be prepared for college and careers (ESSA, 2015; IDEA, 2004). Students with high-incidence disabilities experience less success than their peers without disabilities (Newman et al., 2011). Initially, college and career readiness efforts lacked a focus on students with disabilities (e.g., Conley 2007, 2008), but recent efforts have increased the focus on students with disabilities (e.g., Morningstar et al., 2017). The predictors of post-school success appear to be a viable option to bridge both efforts. Students with high-incidence disabilities spend at least part of their day in general education classes (NCES, 2017), but general education teachers report wanting additional information to prepare students with high-incidence disabilities for college and careers (Kwiatek, 2017). General educators identified the predictors of post-school success as relevant, important, and feasible for implementation (Kwiatek et al., 2021). Coupling the alignment between secondary transition and college and career readiness, the predictors of post-school success appear to be an ideal option to provide general educators with professional development to prepare students with high-incidence disabilities for college and careers. The purpose of this dissertation was to examine the effects of an asynchronous online intervention (i.e., General Educators Now Embedding Research [for] Adult Life in Educational Design [GENERAL ED]) on general education teachers’ knowledge of research-based, in-school predictors of post-school success. Results indicated a functional relation between the asynchronous online intervention and increased knowledge of three predictors of post-school success. Effect sizes were large for increased knowledge of the predictors of post-school success. Additional measures included application; confidence; generalization; and social validity (i.e., feasibility evaluation, intervention rating scale). Finally, limitations, suggestions for future research, and implications for practice will be discussed.
This quantitative study explores the potential school-level and school district-level factors associated with North Carolina school performance grades in K-5 elementary schools. The desire was to examine if any of the school- or school district-level factors were associated with the outcome variable of North Carolina school performance grades. This study used the data from the North Carolina school report cards and Civil Rights Data Collection from the 2015 – 2016 school year. The sample had 1096 schools and 92 school districts. A hierarchical linear model was created with the overall school performance grade as the outcome variable and the sixteen school level predictors and thirteen school district predictors. Results indicated that twelve out of sixteen school-level variables were statistically significant. One out of thirteen school district-level variables were statistically significant and two additional variables approached significance. Recommendations for improving student achievement were provided for United States policymakers, university education programs, North Carolina policymakers, local governments, school districts, and schools. These recommendations are presented as opportunities to ensure equitable educational practices and outcomes for all students.
Veteran business owners are essential contributors to American society and the U. S. economy. Statistics showed a looming drawdown of military personnel and comparatively higher unemployment rates than the civilian population, which led to a growing interest in assisting veterans with entrepreneurship. Studies show that military service has a strong association with entrepreneurship. Few studies have identified key factors of veteran business ownership and action-oriented questions on how or why veteran entrepreneurs find their way to business ownership. There are calls in the literature to answer the question of whether entrepreneurial competencies can influence entrepreneurial intentions. Veterans are often faced with the challenge of building a second career following separation from the military. There is limited research about what factors may motivate and support their transition to self-employment or how they fare compared to nonveteran employees. Furthermore, there are no studies that examine the role of resilience in the entrepreneurial process related to American Veteran Entrepreneurs. The purpose of the study is to determine if resilience and entrepreneurial competencies influence veteran entrepreneurial intention to start a business. This study examines the relationship between entrepreneurial competencies and entrepreneurial intentions among Veterans.
The availability of OpenCL for FPGAs along with High-Level Synthesis tools have made FPGAs an attractive platform for realizing massively parallel compute-intensive applications. FPGAs with their customizable data-path, deep pipelining abilities and enhanced power efficiency features are the most viable solutions for programming and integrating them with heterogeneous platforms. Furthermore, OpenCL for FPGAs raises many challenges which require in-depth understanding to better utilize their enormous capabilities. In this work we identify, analyze and categorize the semantic differences between the OpenCL parallelism and the execution model on FPGAs. As an end result we propose a generic taxonomy for classifying FPGA parallelism potential.
At the same time, new design challenges continue to emerge for massive thread-level parallelism on FPGAs. One major execution bottleneck is the high number of memory stalls exposed to data-path which overshadows the benefits of data-path customization. We introduce a unique approach for hiding the memory stalls on FPGAs when running massively parallel applications and present a novel LLVM-based tool for decoupling memory access from computations. To enable systematic decoupling, we use the idea of kernel parallelism and implement a new parallelism granularity that breaks down kernels to separate data-path and memory-path (memory read/write) which work concurrently to overlap the computation of current threads with the memory access of future threads (memory pre-fetching at large scale).
We next move to the Xilinx based AWS cloud platform and conduct an exhaustive study on the scalability of OpenCL coarse-grain parallelism, Compute Unit(CU) replication on cloud FPGAs. In addition we present a generic template and a front-end design exploration tool to explore and identify the optimum CU number for a given application, while hiding the programming and exploration difficulties from programmers.