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Prospective Students
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Faculty and Staff
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Current Students
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Alumni and Friends
Background: The most common cause of sentinel events is ineffective communication among the healthcare team. Nurses’ documentation of communication, including documenting the notification of critical laboratory results (CLR), is important to ensure that information is accessible. Growing evidence supports the potential of ongoing peer review with feedback as a quality improvement (QI) intervention for documentation.
Purpose: This project sought to implement and evaluate a peer audit and feedback intervention focused on CLR documentation.
Methods: The project occurred on two units of a tertiary medical center where compliance for documentation of CLR was below goal for several years. The intervention was timely peer audit and feedback of CLR events, with a post-project survey to gain nursing perspectives on the process. Data collected included overall compliance rate for CLR documentation, data from the peer audits, and post intervention survey responses.
Results: The improvement in CLR documentation compliance was not statistically significant; however, results were clinically significant as compliance improved on one unit from 6.10% to 9.6% (57.4% improvement). Survey results showed overall positive perceptions of peer audit and feedback as a QI tool, and the intervention was perceived as being non-punitive and helpful for improving practice.
Conclusion: Results support continued examination of the peer audit and feedback process, and its potential for QI in nursing documentation. Future projects should consider strategies to address limited time for nursing staff to engage in quality improvement projects.
In recent years, Wide Bandgap (WBG) semiconductor based power devices has matured rapidly and are playing a significant role in high switching frequency power electronic applications. WBG materials such as silicon carbide (SiC) and gallium nitride (GaN) possess a higher critical breakdown strength, an increased thermal conductivity, and a wider energy bandgap than silicon which make WBG semiconductors as a material of choice in low on-resistance, high blocking voltage, high switching frequency and high operating temperature power applications. In addition, using these devices result in the overall size reduction of the devices as higher doping levels can be achieved at similar voltage levels.
A gate driver acts as an interface between power devices and logic-level control signals and plays a significant role in the switching behaviour of WBG devices. To increase the overall efficiency and reduce the footprint of the system high switching frequency operation of the devices is desirable. However, power consumption in the gate driving circuit increases with frequency. A viable strategy to reduce the gate driving power consumption is to use resonant gate driving technique where part of the energy stored in the gate capacitance is recycled.
In this dissertation, a novel resonant gate driver (RGD) for WBG devices is proposed which drives the semiconductor device using quasi-square wave by utilizing higher order harmonics. Firstly, the operating principles of the proposed gate driver circuit is presented. Secondly, a detailed characteristic analysis and power loss analysis of the circuit are provided. Additionally, a comprehensive simulation study of the proposed circuit is introduced. Moreover, a prototype of the proposed RGD was built and tested. Experimental results demonstrate that the proposed gate driving technique can significantly reduce power consumption in the gate driver circuit in comparison to conventional gate driving techniques.
Over 80% of all malaria deaths occur in children under 5 years of age. Malaria control
strategies have been progressively shifted to specific populations and/or areas to max-
imize effectiveness. Malaria is a significant public health problem in Ghana. Seasonal
Malaria Chemoprevention (SMC) using a combination of sulfadoxine-pyrimethamine
and amodiaquine has been implemented since 2015 in northern Ghana where malaria
transmission is intense and seasonal. In this study, we estimated the prevalence of
asymptomatic P. falciparum carriers in three ecological zones of Ghana, and com-
pared the sensitivity and specificity of different molecular methods in identifying
asymptomatic infections. Moreover, we examined the frequency of mutations in pfcrt,
pfmdr1, pfdhfr, and pfdhps that relate to the ongoing SMC. A total of 535 asymp-
tomatic schoolchildren were screened by microscopy and PCR (18s rRNA and TARE-
2) methods. Among all samples, 28.6% were detected as positive by 18S nested PCR,
whereas 19.6% were detected by microscopy. A high PCR-based asymptomatic preva-
lence was observed in the north (51%) compared to in the central (27.8%) and south
(16.9%). The prevalence of pfdhfr-N51I/C59R/S108N/pfdhps-A437G quadruple mu-
tant associated with sulfadoxine-pyrimethamine resistance was significantly higher in
the north where SMC was implemented. Compared to 18S rRNA, TARE-2 serves as
a more sensitive molecular marker for detecting submicroscopic asymptomatic infec-
tions in high and low transmission settings. These findings establish a baseline for
monitoring P. falciparum prevalence and resistance in response to SMC over time.
Ghana is also one of the three African countries where the world’s first malaria
vaccine, RTS, S, was launched recently. The vaccine contains part of the central
repeat region and the complete C-terminal of the circumsporozoite protein (CSP)
gene of the 3D7 strain. Polymorphism in the PfCSP protein has been reported from
several parts of the world. However, whether RTS, S-induced immunity is PfCSP
allele-dependent and if selection favors non-3D7 strains are unclear. This study aims
to examine the genetic polymorphism of the PfCSP genes in clinical P. falciparum
cases and provide a baseline of parasite diversity prior to vaccine implementation in
Ghana. A total of 212 clinical samples were collected from Seikwa located in the
Brong Afrong region where the vaccine is currently being deployed. Preliminary data
indicated a high rate of polyclonal infections, with some samples harboring up to 3
clones based on the allele frequency among mapped reads. Parasite clones detected
within the same host were not genetically similar to one another. Instead, they were
distributed in various subclades and closely related to clones identified from other
hosts. It is yet to be investigated if the high PfCSP haplotype diversity and low
resemblance to the 3D7 strain have an impact on the anti-CSP immune response and
thereby the efficacy of RTS,S.
The focus of this dissertation is on the topic of chatter avoidance during machining and the prediction of specific cutting forces and maximum tool temperatures during machining using machine learning. Self-excited regenerative vibration or “chatter” is a significant obstacle in machining which results in poor surface quality. To avoid chatter, a 2D diagram of the depth cut limit vs. the spindle speed, called Stability Lobe Diagram (SLD), is used. The SLD depends on the cutting parameters and structural dynamics parameters. Theoretically, chatter can be avoided using the physic-based SLD. But in practice, there is a gap between the empirical results and what the theory supports due to the uncertainties associated with the in-process structural dynamics parameters. using a multivariate Newton method, given the empirical data sets. The first part of the dissertation focuses on the inverse problem in chatter avoidance where the in-process structural dynamics parameters are extracted using a multivariate Newton method, given the empirical data sets. The SLD and the cutting parameters are assumed to be known and given. Using this knowledge, the structural dynamics parameters are obtained using the inverse approach. In addition, the uncertainty in the value of each structural dynamics parameter derived through the inverse approach is also presented. The results derived from the algorithm are used to discover the sensitivity of the boundary with respect to each parameter. The last part of the dissertation covers the prediction of the specific cutting force and the maximum tool temperature during machining using machine learning models.
This study explored two aspects of K-12 core content area teachers' experiences with digital citizenship through the Connectivism lens (Siemens, 2005). First, it explored how teachers instruct students on digital citizenship topics, including how they define digital citizenship and integrate it into their core content area curriculum. Second, it looked at teachers’ experiences and needs regarding digital citizenship professional development. This study followed a basic qualitative approach and used interviews with a follow up questionnaire to gather data. Participants’ responses were analyzed using Fereday and Muir-Cochrane’s (2006) six-step, hybrid approach of inductive and deductive coding and theme development. Findings and discussion were presented through the learning theory of Connectivism. Information on how core content area teachers define digital citizenship was summarized using the S3 Guiding Principles from Ribble and Park (2019). Information on teachers’ experiences integrating digital citizenship into their core content curriculum revealed five major themes: Responsibility, Student Behavior, News & Media Literacy, Non-Cognitive Competencies, and Technology Use. Findings related to professional development experiences were presented through five broad themes: Personal Learning Networks, Parenting & Family, Self-Exploration, Technology Facilitators & Other Technology Champions, and Participating in the Digital World. Findings related to teachers' professional development needs regarding integrating digital citizenship into their core content curriculum were summarized through three themes: making this content relevant and authentic for their students, raising awareness among their peers to build a community around teaching digital citizenship, and identifying resources to integrate this subject matter into their curricula.
We are developing a real-time infrared image technique, Enhanced Thermal Imaging (ETI), that can detect blood vessels embedded in tissue and assess tissue perfusion. ETI is a combination of standard thermal imaging (8-10 µm) and selective heating of blood relative to surrounding water-rich tissue using LED sources at low power. Blood absorbs strongly at 530 nm. Illumination of water rich tissue and embedded blood vessels at this wavelength selectively increases the temperature of the blood vessels relative to the surrounding tissue causing the vessels to appear brighter in a thermal image. ETI does not require the use of injectable dyes and has a compact footprint allowing for use both during surgery and at the bedside. Previous studies using ETI were limited due to lengthy post-processing times required to delineate vessels. The first study presented in this dissertation shows the real-time capabilities of ETI in mapping vascular structures. Real time application of computational filters highlighting temporal and spatial changes reveal embedded blood vessels. ETI was obtained for a model with simulated blood vessels and a porcine heart tissue, and for both models, temporal and spatial filters outperformed standard thermal imaging. In the second study, ETI was simulated computationally to determine limitations and optimizations. The models were also analyzed to determine parameters that can delineate vessel depth and size and these results were compared with ex vivo tissue studies. The final study involved monitoring the reperfusion of skin flaps in a murine model. ETI appears to be more sensitive to the deeper healing while fluorescent imaging provides information about superficial healing. The use of intra-operative and post-operative optical guidance has beneficial impacts on patient costs and tissue viability.
Given the importance of understanding how gender bias impacts the advancement of women into upper leadership, this second-order meta-analysis attempts to explore and summarize previous developments in the gender and leadership literature in order to present the current state of the literature and identify a roadmap for future research.
This dissertation delivers three primary theoretical contributions. First, I conducted a systematic review of the leadership and gender literature to create a primer, with relevant definitions and theoretical frameworks, for gender and leadership theory. This review highlighted that little theoretical integration exists to synthesize the literature on gender and leadership.
Second, I present a second-order meta-analysis and subsequent relative weights analysis to demonstrate the relationship between personality, gender and follower evaluation of leadership constructs such as leader emergence and other leader behaviors (ex: transformational leadership, ethical leadership, etc.). The final meta-analytic correlation matrix included 89 meta-analytic estimates (total k=1,404; total n=366,329). Results indicate that variation in the evaluation of leaders can be explained by gender, however, the subsequent relative weights analysis indicates that for no construct is gender the dominant predictor.
Finally, this dissertation presents a research agenda based on the current findings that will advance the field, including research questions ranging from resolving methodological issues related to the measurement of evaluations of behaviors rather than actual behaviors, to further understanding further moderators of the relationship between gender and leader evaluations.
Energy efficiency and scalability continue to be key considerations for the development of low-cost wireless networks for meeting the needs of the emerging world of the Internet of Things (IoT). Recent developments in low-power wide area networks (LPWAN) promise to meet these requirements by achieving long communication ranges at low data rates without increasing the energy cost.
Consequently, LPWAN technologies are rapidly gaining prominence in the development of IoT networks in comparison to legacy WLANs. LPWANs address the challenges of legacy wireless technologies that use multi-hop mesh networking for increasing connectivity and coverage. Long Range (LoRa) technology is receiving increasing attention in recent years for addressing the challenges of providing wireless connections to a large number of end devices in the field of IoT. LoRa has become the most prominent LPWAN standard due to its long transmission range, low power consumption, and large network capacity. Despite these benefits, LoRa networks may not be able to achieve their full potential unless additional improvements are achieved in the network scalability domain. Specifically, the probability of success under heavy network traffic loads or a large number of end devices needs to be improved.
In this dissertation, we present the causes of performance degradation of LoRa networks and propose several approaches to enhance their performance. Next, we present a novel framework to employ AI tools to make IoT applications smarter. The effectiveness of all the proposed approaches is validated using mathematical analysis as well as via simulations thereby creating the basis for further research in this area.
In higher education institutions, as the number of online language courses continues to increase, it is paramount to provide training and support for faculty and equip them with the appropriate tools to improve students’ learning experiences, specifically those with visual impairments. This qualitative study aims to examine online language faculty’s experiences teaching students with vision impairments. The goal is to make a novel contribution by exploring accessibility issues for online accessibility in language courses in the United States. 10 in-depth, semi-structured interviews were conducted with 10 language faculty around the country. After analyzing each transcript, several themes were identified to answer each research question: 1) Faculty Experiences in Delivering Online Language Courses to Learners with Visual Impairments, 2) Training and Support in Delivering Accessible Online Language Courses, and 3) Strategies and Tools to Teach Students with Vision Impairments. These findings revealed that ADA compliance and online languages should be prioritized in higher education. Despite the increasing number of online courses to teach languages, it is salient that students with visual impairments require further support and attention in higher education language courses. Additionally, faculty require further training and support to help them implement accessibility strategies and tools to their courses.
The Triodopsis genus of Stylommatophoran land snails has been confusing to malacologists for decades. Twenty-eight species have been described in the eastern and southern US, but some original descriptions are insufficient to correctly identify specimens, and misidentifications are common. Phylogenetic approaches have not been applied for species in this genus as the usual mitochondrial markers are extremely variable and difficult to sequence. DNA extraction is complicated by the presence of mucopolysaccharides. A mollusk-specific DNA extraction protocol and custom primers are developed in this study to better facilitate genetic analysis of the family Polygyridae. Triodopsis genus phylogenies based on 16S, ITS2, and H3 genes are presented, with FST values suggesting a reduction in the number of named species. The phylogenetic clades are related to morphology and biogeography to attempt to better identify the recognized species and change the species status of some based on morphology measurements and overlapping distributions. An H3 molecular clock tree suggests a recent and rapid expansion in the family. New hypotheses are also presented that may explain the genetic variation in the Stylommatophoran mitochondrial genome, and a possible explanation of the morphological variation within a clade that could still be undergoing rapid speciation after repeated refugia isolation.
