37 research outputs found

    Transportation is a Barrier to Healthcare in Central Vermont

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    Transportation is a significant barrier to healthcare access in Central Vermont due to a variety of reasons that include low income households, poor access to public transportation, elderly populations, and populations with disabilities. Improving access to transportation is a goal for both the local public transportation authority and the UVMHN-Central Vermont Medical Center in Berlin, VT. The purpose of this project was twofold. The first goal was to find an underutilized transportation resource in the community by heavily researching the area's transportation system and coordinating the distribution of informational sheets regarding this resource with my family medicine clerkship site members. The second goal was to survey current patients and discover what the particular status quo and challenges are for the local community with regards to transportation in 2016

    Adsorption of free floating DNA and antimicrobial resistance genes out of wastewater effluents by sewage-based biochar and iron-oxide-coated sands

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    The presence of extracellular DNA (eDNA) containing antibiotic resistance genes in the treated wastewater effluents can contribute to the spread of antimicrobial resistance (AMR) among receiving waters. The removal of cell associated antibiotic resistance genes (ARGs) has been widely studied using advance treatments. However, these treatments were not evaluated for cell free or extracellular ARGs resulting from the cell lysis or secretion during metabolic activities. eDNA is known to well adsorb onto clay, suspended particles and other soil components. Thus, in this research the potential and the main mechanisms involved in the removal of eDNA by adsorption onto sewage-based biochar and iron-oxide-coated sands has been studied.Master of Science in Civil Engineering and in Environmental EngineeringCivil Engineering | Environmental Engineerin

    Arsenic Removal by Adsorption and Multilayer Sand Filtration

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    The presence of Arsenic in the groundwater, and eventually in the drinking water is a serious problem in many of the Asian countries. Due to it high toxicity to its removal is very essential. There are many removal technologies for the removal of arsenic such as adsorption, coagulation-filtration, membrane filtration, ion exchange and precipitation. Adsorption is one such technology which is mainly used as it’s a very simple technique. the extent of adsorption is affected by pH, nature of the adsorbent, surface area of the adsorbents. Iron is widely used for the removal of Arsenic from groundwater. The iron which is present in dissolved form in groundwater needs to first get oxidised to hydrous ferric oxides as flocs which provide adsorption sites for arsenic. In this study the effect of pH and Iron dosage on the arsenic removal by adsorption with the available dissolved Iron in the groundwater. The effect of pH on arsenic removal by floc formation of iron with a series of Jar tests were done for Arsenite and Arsenate. Also, the removal of arsenic in a multilayer sand bed (3 layers with Anthracite, Sand and Garnet) was evaluated at three different pH. It was found that pH plays a very important role on Arsenic removal. Arsenite removal was increased with pH whereas Arsenate removal decreased with increase in pH. At pH 5 and at high Fe concentrations, the removal decreases but the effective iron or the iron that flocculated to greater than 0.45µm was quite similar. This was also seen in the particle counter analysis. Iron concentration of 5mg/l was enough to remove Arsenate upto 90% whereas Arsenite needed higher doses of upto 20mg/l to reach 90%. Clear increase in the flocculation was observed in particle counts with the increase of iron concentration. Before the dosing of Iron Arsenic oxidation was seen in the filter bed maybe due to the presence of Arsenic Oxidising Bacteria (AOB). High oxidation efficiency was seen Sand and Garnet layer. The oxidation of Arsenite to Arsenate before dosing iron in the filter was less at pH 8. High resistance was observed in the filter bed within 3 days after backwashing although the removal was quite stable in the three days. After dosing of Iron, high removal of arsenic was seen in Anthracite layer due to the high adsorption of Iron in the Anthracite layer.CIE 5050-0

    Synaptic mechanisms of OPRM1 A118G single nucleotide polymorphism in human neurons

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    Association of the non-synonymous single nucleotide polymorphism (SNP) rs1799971 in OPRM1 to drug dependence and alcohol abuse suggests it may have a functional consequence in altering receptor signaling in the brain. The A118G SNP causes a switch of asparagine (N) at position 40 of the mu-opioid receptor (MOR) to aspartate (D). To dissect the underlying neural and synaptic basis of the N40D MOR variant, we generated human GABAergic induced neuronal (iN) cells from induced pluripotent stem (iPS) cells of donors homozygous for either the major (N40) or minor (D40) alleles of the MOR. We found that the subject-derived iN cells exhibit mature neuronal properties such as action potential firing and neuronal excitability and express functional MORs. Interestingly, upon MOR activation by the agonist DAMGO, D40 MOR iN cells exhibit consistently stronger suppression of spontaneous inhibitory postsynaptic currents (sIPSCs) than N40 MOR iN cells across multiple subjects. To mitigate the complexity of diverse genetic backgrounds of the subject iN cells derived from multiple human subjects, we employed CRISPR/Cas9 genome-editing to generate two pairs of isogenic human pluripotent stem cell lines. Remarkably, the synaptic regulation of MOR activation in the isogenic lines recapitulate those of neurons generated from different individuals, i.e. stronger suppression in D40 MOR carrying human neuronal cells by MOR activation. We further determined that the increased sensitivity of D40 iN cells to DAMGO was caused by a more robust inhibition of excitability and synaptic release by DAMGO in D40 MOR expressing neurons. Additionally, we found that the N40D SNP influences the development of long-term tolerance at the MOR. Specifically, D40 iN cells are unable to develop adaptive changes in synaptic function unlike N40 iN cells following long-term mu opioid receptor activation by DAMGO. This study utilizes patient-specific iPS cells as well as a gene edited isogenic neurons to advance our understanding of the fundamental synaptic alterations associated with OPRM1 A118G in a human neuronal context.Ph.D.Includes bibliographical referencesby Apoorva Haliker

    The Evolution of Human Skin Color

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    LoRaWAN Class B Multicast Scalability

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    LoRaWAN has emerged as a popular IoT commu- nications technology. It comes with three classes of operation: A, B, and C. Although many IoT use-cases, like Firmware-over- the-Air updates, require multicast, Class A cannot be used for that purpose. Class C can, but consumes a lot of energy. This leaves Class B. In this paper, we investigate Class B multicast and its scalability properties. Issues like multicast member capacity, beacon blocking, and beacon collisions are highlighted, and several approaches to mitigate them are proposed: (1) “Ping-Slot Relaying,” to allow for more multicast members, (2) a scheduling approach indicating when to best send multicast packets, and (3) “Dynamic Region Formation” to coordinate the sending of beacons over multiple gateways. The proposed solutions do not require any modifications to the LoRaWAN protocol.Virtual/online event due to COVID-19 accepted author manuscriptEmbedded System

    Performance of the Pareto Envelope-Based Search Algorithm - II in Automated Test Case Generation

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    Software testing is an important yet time consuming task in the software development life cycle. Artificial Intelligence (AI) algorithms have been used to automate this task and have proven to be proficient at it. This research focuses on the automated testing of JavaScript programs, and builds upon the existing SynTest framework that is the current state of the art, with the Dynamic Many Objective Sorting Algorithm (DynaMOSA) being the best performing AI algorithm for test case generation. DynaMOSA uses the Non-Dominated Sorting Algorithm - II (NSGA-II) as its base algorithm, and adds modifications to it. This paper investigates whether the use of the Pareto Envelope Based Search Algorithm - II (PESA-II) as the base algorithm results in improved performance. The contributions of this research includes a modified PESA-II integrated into the SynTest framework, using inspiration from DynaMOSA. Moreover, we answer the question "How does the modified PESA- II perform compared to DynaMOSA in generating test cases for JavaScript programs?" The performance of the algorithms is measured based on the (branch and method) coverage of the test cases generated for a suite of JavaScript classes. The results show that the modified version of PESA-II outperforms the base version. However, neither manage to outperform DynaMOSA.CSE3000 Research ProjectComputer Science and Engineerin
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