LOUIS University of Alabama in Huntsville
Not a member yet
8547 research outputs found
Sort by
Royal Society\u27s Impact on Battery Technology Today
Get PDFhttps://louis.uah.edu/honors-399/1016/thumbnail.jp
Implementing a donor human milk protocol to improve exclusive breastfeeding rates
No full textExclusive breastfeeding is a metric that hospitals nationwide work to improve. It is recommended that newborns breastfeed exclusively for at least the first six months to one year. There are several long-term health benefits and impacts for the new mother-baby couplet. Although touted as the most natural way to feed your baby, it is not always easy. Prenatal breastfeeding intention and education are associated with increased rates of exclusivity and duration. The breastfeeding journey is a process unique to the couplet experiencing it. Worldwide, the rates of newborns who exclusively breastfeed are below the World Health Assembly’s 2030 target of 70%. Connecticut’s statewide average is 48%, and only 36% at Bridgeport Hospital. The Newborn Intensive Care Unit offers pasteurized donor human milk (PDHM) for supplementation if the mother’s milk is insufficient. This option is not available for well-newborns. After an extensive literature review, PDHM for supplementation was found to be an intervention that improved exclusive breastfeeding. Implementation of a PDHM protocol will promote a clinical practice change that improves consistency for the agency’s Care Signature. Staff education was a key component of a stepwise approach aimed at ensuring success. Ramona Mercer’s Maternal Role Attainment and Becoming a Mother Theory was used as a foundational guide for this project. Exclusive breastfeeding data was collected and analyzed. Sixty staff participated in implementing this protocol, which was available to every patient regardless of race, ethnicity, primary language or insurance status, in an effort to promote health equity, safety and advocacy. The three-month average exclusive breastfeeding rate was 35%. During the three-month implementation period, the average exclusivity rate increased to 40%. In addition, among PDHM users, 89% remained exclusive during the birth hospitalization, which would not have been possible before this project. This protocol was useful in enhancing the overall exclusive breastfeeding average and is sustainable by making the protocol a standard operating procedure, incorporating the education into all new hires’ competency-based orientation, and merging the exclusivity and PDHM reports into one seamless report. Bridgeport Hospital is almost at the Healthy People 2030 goal of 42.4% in three months
The effects of low-temperature pre-cycling on high-temperature degradation of lithium-ion cells
No full textDegradation is a big challenge for lithium-ion (Li-ion) batteries in various applications, especially at extreme temperatures. Low and high temperature cycling can cause lithium plating and increased solid-electrolyte interphase (SEI) growth, respectively. However, a previous work in our lab showed that pre-cycling Li-ion cells at low temperature reduced degradation during high temperature cycling. The previous work was based on small single-layer cells. This thesis intends to confirm this phenomenon for larger multi-layer cells and to further understanding of the mechanisms behind the reduced degradation for the low-temperature pre-cycled cells. Multi-layer commercial pouch cells were pre-cycled at 1C at low temperature before cycling at high temperature. Improved capacity retention was observed for these pre-cycled cells, confirming the previous observation. However, compression of the cells was necessary for the observation. Without compression, the pre-cycled cells would swell after shifting to high temperature cycling and degraded quicker than baseline cells cycled only at high temperature. Pre-cycling with a lower C-rate (C/5) at low temperature, which has lower risk of lithium plating than the 1C pre-cycled cells, showed similar degradation to the baseline cells. This implied that lithium plating from 1C pre-cycling at low temperature was responsible for the reduced high temperature degradation. Further cycling of baseline cells and 1C pre-cycled cells with a low discharge rate (C/20) showed that the significant capacity loss of the baseline cells was primarily due to power fade. A baseline cell, a 1C pre-cycled cell, and a C/5 pre-cycled cell were disassembled and examined using optical microscopy and SEM (scanning electron microscopy). It was observed that the baseline cell and the C/5 pre-cycled cell had areas of uneven deposition on the anode. The 1C pre-cycled cell, however, had a more even deposition layer across the entire surface of the anode. It is suspected that this layer offers protection against degradation at high temperatures. Additional investigation is needed for further understanding of this deposition layer
Characterizing a web server deployed in a lightweight Kubernetes cluster in an IoT computing environment
Get PDFAs the world’s reliance on the internet continues to grow, so does the need for cloud-based computing solutions. These solutions offer a degree of flexibility, scalability, and reliability that traditional computing methods cannot provide. This thesis focuses on characterizing a web server deployed in a lightweight Kubernetes cluster hosted across three Raspberry Pi 4 minicomputers. Characterization metrics include the transfer rate of data from the web server as well as the CPU utilization and power consumption of the Raspberry Pi devices when under load. The background on cloud-based technology is introduced and the tools used in the thesis research are discussed. Experimental methods are then detailed and the results for several cluster-based deployments of the web server are presented. Finally, these results are compared to those obtained for an identical web server hosted locally on a Raspberry Pi device external to the Kubernetes cluster
ClearScan : a machine learning system for customized, site-specific radar image filters
Get PDFIn the field of radar meteorology, a perpetual problem is removal of so-called anomalous propagation (AP), i.e. non-precipitation echoes, from the produced images. Much work has been done in this area already, including conventional heuristic algorithms as well as machine-learning systems such as neural networks. Often the focus is on certain familiar radar architectures such as WSR-88D, also known as NEXRAD. However, a large number of radars exist which are not identical to NEXRAD; and there are also environmental differences such as RF interference which can affect the success rate of existing AP removal strategies. The focus of this paper is to present a flexible machine-learning system for this task which provides a convenient training interface, so it can be adapted to the specific conditions present at any given radar site to create a customized filter. We have named this system ClearScan
Retribution or Reform? A Qualitative Analysis of Racial and Gendered Opinions towards Rehabilitative Justice
Get PDFhttps://louis.uah.edu/rceu-hcr/1455/thumbnail.jp
Finite Element Investigation of Piezoelectric Energy Harvesting: The Effect of Harvester Shape on Output Voltage
Get PDFhttps://louis.uah.edu/rceu-hcr/1469/thumbnail.jp
Synthesis and Characterization of Novel Cerium Crystals
Get PDFhttps://louis.uah.edu/rceu-hcr/1479/thumbnail.jp