The antibody Immunoglobulin G (IgG) main function is to protect and prevent the body from infections, and it is normally found in human serum. This study is about IgG glycosylation, which is associated with different types of diseases such as neurological diseases, cancers and immunodeficiency etc. This study attempts to optimize IgG glycopeptide enrichment in a 100 μL micropipette tip set up, and to separate the enriched glycopeptides using capillary electrophoresis (CE). Matrix-assisted laser desorption/ionization – mass spectrometry (MALDI-MS) was used for data acquisition and glycopeptide profiling.  In this study, loading solutions with different combinations of acetonitrile (ACN) and trifluoroacetic acid (TFA), together with various precondition and sample preparation procedures were evaluated on IgG digest samples. Best enrichment performance, particularly regarding the selectivity, was achieved using the parameters as follows: loading solution of 83% ACN/16% H2O/1% TFA, sample solution in H2O containing 83% ACN, using a 100 μL micropipette tip packed with 1 mg cotton wool. A re-enrichment step was carried out on enriched glycopeptide samples, and improved selectivity of glycopeptides could be observed. Enriched glycopeptides could be separated into three major groups by CE using an acidic background electrolyte of 50 mM formic acid and 50 mM acetic acid, pH 2.5. / Huvudfunktionen för antikroppen Immunoglobulin G (IgG) är att skydda kroppen och förhindra infektioner och det finns normalt i mänskligt serum. Denna studie handlar om glykosylering, som är kopplad till olika typer av sjukdomar såsom neurologiska sjukdomar, cancer och immunbrist etc, och är en potentiell biomarkör för sjukdomar. Denna studie försöker optimera en IgG glycopeptidanrikningsmetod i en 100 μL mikropipettspets och separera de anrikade och intakta glycopeptiderna med hjälp av kapillärelektrofores (CE). Matrisassisterad laserdesorption/jonisering – masspektrometri (MALDI-MS) användes för datainsamling och glykopeptidprofilering  I denna studie utvärderades lösningar med olika kombinationer av acetonitril (ACN) och trifluororättiksyra (TFA) tillsammans med olika föberedelseförfaranden och provberedningsprocedurer på IgG prover. Anrikningsprestanda, särskilt selektiviteten, uppnåddes bäst med användning av följande parametrar: lösningen av 83% ACN / 16% H2O / 1% TFA, provlösning i H2O innehållande 83% ACN, med användning av en 100 mikroliter mikropipettspets fylld med 1 mg bomull. Återreningssteget genomfördes på anrikade glykopeptidprover och förbättrad selektivitet för glykopeptider kunde observeras. Anrikade glykopeptider kunde separeras i tre huvudgrupper med CE med användning av sur bakgrundselektrolyt med 50 mM myrsyra och 50 mM ättiksyra, pH 2,5.

<p>Mammoths (<em>Mammuthus</em>) have been studied extensively at the genetic level. However due to both taphonomic and technological limitations, only one of several late Pleistocene mammoth species, the woolly mammoth (<em>M. primigenius</em>), has been investigated. This limits our impression of mammoth population history to the the northern latitudes, just one of several environments in which mammoths lived and went extinct. It also obscures their evolutionary chronology, which prevents proper climatic and biogeographic contextualization of their history. Fortunately recent technological advances in high-throughput sequencing and targeted enrichment promise to expand Pleistocene faunal population phylogeography to non-permafrost, non-cave burial contexts. However the capacity and behavior of these combined technologies for characterizing ancient DNA is largely unexplored, preventing efficient and routine use for population-level studies. In this thesis I test and apply these technologies to remains of mammoth species from throughout North America. I first demonstrate their potential for poorly-preserved DNA, and then I evaluate their efficient application to large sample sets, as well as for capturing complete nuclear genomes. I then use these technologies to sequence dozens of mitochondrial genomes from Columbian (<em>M. columbi</em>)<em> </em>and other non-woolly mammoths, reconstructing their matrilineal phylogeography south of the ice. The revealed patterns not only imply a deep chronology for mammoth matrilineal diversity, but also that North American mammoth evolution was occurred via separate episodes of interbreeding between resident and invading populations, and between ecotypes. Overall the biological and methodological discoveries afforded by this body of work outline future research avenues on mammoth evolution, behavior, and extinction.</p> / Doctor of Philosophy (PhD)

Bangladesh is one of the most vulnerable countries to climate change, with coastal areas being especially vulnerable. Along the Bangladeshi coast lies mangrove forests that protect against storm surges, tropical cyclones, SLR, coastal erosion, and salt-water intrusion. On Char Kukri Mukri, a remote island in the Bay of Bengal, Keora-species (Sonneratia apetala) mangroves are planted. The forest is virtually a monoculture in degradation and thus needs restoration through enrichment. Therefore, this study aimed to explore the opportunities and limitations of mangrove enrichment as climate adaptation on Char Kukri Mukri. We conducted semi-structured interviews with local communities and other key stakeholders and analysed soil and water samples along the island's south coast to assess this. Our results indicate that the soil is highly saline, which, combined with projected climate impact, limits the abilities of more sensitive mangroves to survive there. Climate impacts severely affect the lives and livelihoods of the people living on Char Kukri Mukri. Successful adaptation requires further involvement of local communities, site-specific solutions, and a holistic approach to adaptation. However, a hindrance to adaptation measures is the lack of resources to fund large-scale projects, which leads to beneficiaries being required to provide money and land themselves to be considered for projects. This risks systematically excluding the landless poor, and there is therefore a need to reform adaptation financing systems so that measures benefit the most vulnerable. / Bangladesh är ett av de länder i världen som är mest sårbara för klimatförändringarna. Kustområdena är mest känsliga. Längs Bangladeshs kust finns mangroveskogar, som skyddar mot klimateffekter som stormar, cykloner, havsnivåhöjning, kusterosion, och saltvattenintrång. På Char Kukri Mukri, en avlägsen ö utanför Bangladeshs centralkust i Bengaliska viken, har mangrover av arten Keora (Sonneratia apetala) planterats. Skogen är praktiskt taget en monokultur som håller på att förstöras, och det finns därför ett behov av att restaurera skogen. Denna studie syftade till att undersöka möjligheterna och hindrena för restaurering av mangroveskogarna som klimatanpassning på Char Kukri Mukri. För att uppnå detta genomförde vi semistrukturerade intervjuer med lokalbefolkningen och andra nyckelintressenter, och analyserade jord- och vattenprover tagna vid öns sydkust. Våra resultat indikerar att jorden har hög salthalt, vilket i kombination med ökade klimateffekter minskar mer känsliga mangrovearters möjligheter att överleva i dessa områden. Klimateffekter påverkar människorna och deras försörjning på Char Kukri Mukri i hög grad. Lyckad klimatanpassning kräver mer inkludering av lokalbefolkningen i initativ, platsspecifika lösningar, samt ett holistiskt tillvägagångssätt. Resursbrist hindrar dock investeringar i storskaliga och långsiktiga projekt, vilket gör att förmånstagare behöver bidra med pengar och mark till projekten. Detta gör att fattiga människor som inte äger mark systematiskt exkluderas ur anpassningsprojekten. De nuvarande finansieringssystemen behöver därför reformeras för att projekten ska ge fördelar till de människor som är mest sårbara för klimatförändringarna.

No / Many datasets are available in the form of conventional databases, or simplified comma separated values. The machines do not adequately handle these types of unstructured data. There are compatibility issues as well, which are not addressed well to manage the transformation. The literature describes several rigid techniques that do the transformation from unstructured or conventional data sources to Resource Description Framework (RDF) with data loss and limited customization. These techniques do not present any remote way that helps to avoid compatibility issues among these data forms simultaneous utilization. In this article, a new approach has been introduced that allows data mapping. This mapping can be used to understand their differences at the level of data representations. The mapping is done using Extensible Markup Language (XML) based data structures as intermediate data presenter. This approach also allows bi-directional data transformation from conventional data format and RDF without data loss and with improved remote availability of data. This is a solution to the issue concerning update when dealing with any change in the remote environment for the data. Thus, traditional systems can easily be transformed into Semantic Web-based system. The same is true when transforming data back to conventional data format, i.e. Database (DB). This bidirectional transformation results in no data loss, which creates compatibility between both traditional and semantic form of data. It will allow applying inference and reasoning on conventional systems. The census un-employment dataset is used which is being collected from US different states. Remote bi-directional transformation is mapped on the dataset and developed linkage using relationships between data elements. This approach will help to handle both types of data formats to co-exist at the same time, which will create opportunities for data compatibility, statistical powers and inference on linked data found in remote areas.

The purpose of this study is to gain a better understanding of the practices and attitudes of EFL teachers concerning the challenges and methods involved in teaching gifted students, specifically in regard to the two most prevalent approaches, enrichment and acceleration. Data for this qualitative study was collected through semi-structured interviews with five EFL teachers and the data was analyzed using thematic analysis. Results showed that teachers perceived lacking resources, difficulties identifying gifted students in their classes and poor attitudes from gifted students as their main challenges when teaching this group of students. The results also showed that the teachers were inclined to favor enrichment over acceleration, stating a fear for negative social effects and acceleration being messy as their reasons. The teachers in this study problematize and criticize the Swedish approach of inclusion while at the same time struggling to find an alternative. The results also showed that the teachers saw acceleration as a natural next step for when enrichment has failed. Given the limited research on linguistically gifted students, it was concluded that further investigation is needed to assess the current effectiveness of enrichment as a strategy in the EFL classroom.

This thesis explores the transformative potential of eco-cultural tourism in revitalizing post-industrial cities, with a focus on the network of towns along the Ohio River in West Virginia. The research seeks to understand the multifaceted impacts of tourism on urban development, social infrastructure, and economic growth in small towns. The core concept is to create a tapestry of connectivity along the river, celebrating the region's natural beauty and promoting shared experiences and community cohesion. The proposed initiative envisions a Master Plan featuring a well-integrated network that connects cities along the Ohio River. This network includes walking and biking trails, ATV routes, camping areas, water activities like kayaking and motorboating, accommodations, restaurants, local shops, and a dedicated rail corridor for travel. The proposed development primarily targets Parkersburg, a small city in Wood County, West Virginia, located at the confluence of the Ohio and Little Kanawha Rivers. The second phase of the project focuses on two critical sites within Parkersburg, essential for implementing the revitalization plan. Parkersburg is envisioned as the catalyst and starting point for the entire network, positioning it as the epicenter of urban regeneration and community development. Overall, the thesis investigates the potential benefits and challenges of implementing a comprehensive tourism-driven urban revitalization strategy. Through an interdisciplinary approach to planning and design, it examines the ecological, cultural, tourism, and environmental impacts on development, envisioning a sustainable future where West Virginia's post-industrial cities prosper as interconnected nodes. / Master of Science / Discover the transformative power of eco-cultural tourism in breathing new life into West Virginia's post-industrial cities. This research delves into the intricate impacts of tourism on urban development, social fabric, and economic resurgence in suburban areas, focusing on the picturesque towns lining the Ohio River. Imagine a meticulously planned network seamlessly connecting these towns through a myriad of experiences: tranquil water trails, adventurous ATV paths, historic rail lines, and scenic biking routes. This master plan not only celebrates the region's natural splendor but also cultivates a sense of community and shared heritage. At its heart lies Parkersburg, strategically positioned to spearhead this revitalization effort. As a nexus for urban renewal and communal growth, Parkersburg is poised to serve as the gateway to a vibrant tourism destination, breathing vitality into once-dwindling local economies. Through interdisciplinary analysis, this thesis explores the numerous benefits and challenges of implementing such a comprehensive tourism-driven strategy. By envisioning a future where West Virginia's post-industrial cities thrive as interconnected hubs along culturally enriched eco-trails, it paves the way for sustainable growth and shared prosperity.

This thesis consists of two projects in which various machine learning approaches and statistical analysis for the integration of biomedical data analysis were explored, developed and tested. Integration of different biomedical data sources allows us to get a better understating of human body from a bigger picture. If we can get a more complete view of the data, we not only get a more complete view of the molecule basis of phenotype, but also possibly can identify abnormality in diseases which were not found when using only one type of biomedical data. The objective of the first project is to find biological pathways which are related to Duechenne Muscular Dystrophy(DMD) and Lamin A/C(LMNA) using the integration of multi-omics data. We proposed a novel method which allows us to integrate proteins, mRNAs and miRNAs to find disease related pathways. The goal of the second project is to develop a personalized recommendation system which recommend cancer treatments to patients. Compared to the traditional way of using only users' rating to impute missing values, we proposed a method to incorporate users' profile to help enhance the accuracy of the prediction. / Master of Science

Pathway analysis is an important task for gaining novel insights into the molecular architecture of many complex diseases. With the advancement of new sequencing technologies, a large amount of quantitative gene expression data have been continuously acquired. The springing up omics data sets such as proteomics has facilitated the investigation on disease relevant pathways. Although much work has previously been done to explore the single omics data, little work has been reported using multi-omics data integration, mainly due to methodological and technological limitations. While a single omic data can provide useful information about the underlying biological processes, multi-omics data integration would be much more comprehensive about the cause-effect processes responsible for diseases and their subtypes. This project investigates the combination of miRNAseq, proteomics, and RNAseq data on seven types of muscular dystrophies and control group. These unique multi-omics data sets provide us with the opportunity to identify disease-specific and most relevant biological pathways. We first perform t-test and OVEPUG test separately to define the differential expressed genes in protein and mRNA data sets. In multi-omics data sets, miRNA also plays a significant role in muscle development by regulating their target genes in mRNA dataset. To exploit the relationship between miRNA and gene expression, we consult with the commonly used gene library - Targetscan to collect all paired miRNA-mRNA and miRNA-protein co-expression pairs. Next, by conducting statistical analysis such as Pearson's correlation coefficient or t-test, we measured the biologically expected correlation of each gene with its upstream miRNAs and identify those showing negative correlation between the aforementioned miRNA-mRNA and miRNA-protein pairs. Furthermore, we identify and assess the most relevant disease-specific pathways by inputting the differential expressed genes and negative correlated genes into the gene-set libraries respectively, and further characterize these prioritized marker subsets using IPA (Ingenuity Pathway Analysis) or KEGG. We will then use Fisher method to combine all these p-values derived from separate gene sets into a joint significance test assessing common pathway relevance. In conclusion, we will find all negative correlated paired miRNA-mRNA and miRNA-protein, and identifying several pathophysiological pathways related to muscular dystrophies by gene set enrichment analysis. This novel multi-omics data integration study and subsequent pathway identification will shed new light on pathophysiological processes in muscular dystrophies and improve our understanding on the molecular pathophysiology of muscle disorders, preventing and treating disease, and make people become healthier in the long term. / Master of Science

<p dir="ltr">Anomaly detection systems identify abnormal behaviors, and can increase the uptime, safety, and profitability of an industrial system. This research investigates the development of an AI model for detecting anomalies in nuclear reactors. An LSTM network was used to predict the value of a key reactor signal, and then the predictions are compared to the measured values in order to determine if the data is abnormal. The predictive AI model was trained using regular operation data from the nuclear reactor at Purdue University, PUR-1. It is shown in the experiment that the model can accurately track reactor neutron counts during normal operation, with an average error of less than 5% when predicting five seconds into the future. It is also shown that the model reacts to abnormal inputs, with average errors above 50% when fed data which simulates a false data injection cyberattack. The framework of using prediction error to identify anomalies is investigated and a false positive rate of 0.2% is achieved on the normal evaluation dataset while still identifying the abnormal data as anomalous.</p>

<p dir="ltr">Nuclear mobile microreactors will serve as a unique, transportable power source, especially for remote communities. Because mobile microreactors are meant to remain operable after initial startup, keeping the microreactor cool during transport is a safety concern that must be taken into consideration. Due to the compact nature of shipping containers, there is no significant room for the installation of active cooling mechanisms. The thermal limitations imposed by current regulatory guidelines lead to a reactor shipment external maximum temperature of 85◦C. Transporting heat from the microreactor's exterior walls to its surrounding air within the shipping container under natural convection will serve as the greatest source of resistance to the decay heat removal. In the event of mechanical failure or local regulations restricting forced cooling systems within the shipping container, natural convection will be the primary method for transferring heat. Before mobile microreactors can reach commercial status, research must be conducted on ensuring continued passive safety. </p><p><br></p><p dir="ltr">During the unavailability of helium circulation, the internal reactor core is designed to cool by block-to-block conduction and radiation, and the reactor vessel surface is cooled by the ambient air. This scenario is anticipated during the transport of the micro-high temperature gas-cooled reactor (HTGR) in a shipping container. The conduction and radiation between the prismatic micro-HTGR blocks in the core can be influenced by variances in the thermal contacts. This work investigated the conduction within a simulated horizontal micro-HTGR core. An experimental setup was used to validate a numerical model for conduction radiation cooldown with postulated thermal contact conductances (TCC). The experimental setup consisted of a hexagonal assembly with scaled prismatic blocks placed within a high-temperature vacuum environment. The gaps between the blocks were well controlled and monitored. The experimental setup was designed in such a way that the temperature variation in the axial direction was minimal, such that the experiment could be observed as a 2D (r,θ) heat transfer problem. The experimental scenario was computationally modelled with a finite element analysis (FEA) program. Once validated, the computational model was used to investigate the impact of gap conductance on overall decay heat removal. Using a conservative estimate for gap conductance value (100 W/m2 − K) between the prismatic blocks, there is a negligible increase in temperature observed during decay heat generation with constant natural convection coefficients. </p><p><br></p><p dir="ltr">However, the internal temperature profile may change drastically depending on the exterior conditions of the microreactor. A second model for the worst case scenario of exterior cooling being limited to natural convection flows was validated against existing benchmark experimental data on natural convection in closed cavities. The investigations have been performed for several configurations, including different reactor sizes, power levels, and scenarios with or without shielding around the reactor pressure vessel (RPV). This conservative safety analysis restricts the power level of the reactor to be equal to 1 MWe. A more realistic analysis with intermittent shutdown of shipping container air circulation demonstrates that a 4 MWe reactor will reach 85◦C Code of Federal Regulations (CFR) limitations after one hour while a 5 MWe reactor reaches the limit after 34 minutes. </p><p><br></p><p dir="ltr">Finally, both models were combined into a conjugate heat transfer model to examine whether thermal contact conductance (TCC) values would affect the external temperature profile as well as the maximum temperature reached by the core to ensure material limitations would be maintained. Studies have been conducted on a micro-HTGR design that originates from the fuel block design of the MHTGR-350 with changes to the overall power level, TCC values, and outer shipping container wall temperatures. Changes to TCC values do not significantly change microreactor exterior temperatures. In addition, the internal temperatures under all examined conditions remained under 875◦C. </p>