On the use of electrochemical techniques to monitor free oxide content in molten fluoride media

The electrochemical behaviour of oxide ions has been studied in fluoride melts(LiF/NaF eutectic) by cyclic voltammetry, square wave voltammetry and chronopotentiometry. The purpose is to determine whether these techniques can be used for titration of free oxide ions (O2-) in molten fluorides released by lithium oxide additions. Cyclic voltammetry is shown to be unsuitable for this purpose due to oxygen bubbling disturbing the oxidation peak, while square wave voltammetry is far more appropriate because the observed signal is a well defined oxidation peak with a height proportional to the oxide content. Thus, the present work is focused on a strategy of oxide ions titration by square wave voltammetry. In addition, this work allows assessing that the electrochemical reduction of oxide ions proceeds by diffusion of these species, and the O2- diffusion coefficient is estimated by chronopotentiometry

A Dynamic Graph, Context, and Content Analysis Approach to Detect Cybergrooming

Internett, og spesielt sosiale medier, har blitt en fundamental del av livene våre, uansett alder. Mange sosiale medieplattformer er rettet mot barn og gir dem mu- lighet til å kontakte nye venner uten å behøve og møtes fysisk. Til tross for de tydelige fordelene ved sosiale medier åpner det også for bekymringer knyttet til truslene som møter barna på nett. Disse plattformene gir ikke bare barn enkel tilgang, men også personer med fiendtlige intensjoner, slik som overgripere. Over- gripere kan opprette falske nettprofiler, utgi seg som barn og kontakte sårbare barn, med minimal risiko for å bli avslørt. Nettovergrep kan resultere i psykolo- giske, fysiske, emosjonelle, adferdsmessige og psykososiale problemer som kan påvirke barnet livet ut. For å unngå slike livsendrende konsekvenser er det av- gjørende å detektere og forhindre seksuelle nettovergrep. I løpet av denne masteravhandlingen har vi undersøkt hvorvidt en kombin- ert tilnærming av graf-, kontekst- og innholdsanalyse kan benyttes for å dynam- isk detektere overgripere på nett. Dette oppnådd vi ved å studere oppførselen til individuelle brukere i spill chatter. Vi implementerte en veiledet maskinlæring- salgoritme som klassifiserte meldingene sendt av brukere basert på flere atferds- egenskaper. Videre ble det implementert en deteksjonsmekanisme for å detektere overgripere så tidlig som mulig samtidig som høy dekning og presisjon kunne oppnås. Basert på de oppnådde resultatene konkluderte vi med at dynamisk deteksjon av overgripere i chatter er mulig. I tillegg konkluderte vi med at tidlig deteksjon av overgripere var mulig ved å overvåke brukernes atferd i pågående chatter. For å fortsette forskning for å forbedre deteksjon, bør bruken av andre klassifiseringsal- goritmer, inkludering av andre adferds-egenskaper og tilnærminger for å beregne dem, samt andre deteksjonsmekanismer studeres.The internet, and especially social media, has become a fundamental part of our life, no matter the age. Many social media platforms are targeted towards children enabling them to contact new friends without the need for physical meetings. Despite the clear benefits of social media, it also raises concerns about threats facing children online. These platforms do not only give access to children, but also to people with bad intentions, such as predators. Predators can create fake online profiles, pose as a child, and contact vulnerable children with a minimal risk of disclosure. Online assaults can result in psychological, physical, emotional, behavioral, and psycho-social issues affecting the child for the rest of its life. To avoid such life altering consequences it is crucial to detect and prevent sexual abuse online. During this thesis we have investigated whether a combined graph, context and content analysis approach could be used to dynamically detect predators on- line. This was accomplished by studying the behavior of individual users in game chats. We implemented a supervised machine learning algorithm which classified the messages sent by the users based on several behavioral features. Further, a detection mechanism was created to detect predators as early as possible whilst achieving high recall and precision. Based on the results achieved we concluded that dynamic detection of predat- ors in chats is possible. In addition, we concluded that early detection of predators was possible when monitoring the user’s behavior in ongoing chats. To continue the research into improving detection, the use of other classification algorithms, inclusion of other features and approaches to calculate them, and other detection mechanisms should be studied

A Dynamic Graph, Context, and Content Analysis Approach to Detect Cybergrooming

Internett, og spesielt sosiale medier, har blitt en fundamental del av livene våre, uansett alder. Mange sosiale medieplattformer er rettet mot barn og gir dem mu- lighet til å kontakte nye venner uten å behøve og møtes fysisk. Til tross for de tydelige fordelene ved sosiale medier åpner det også for bekymringer knyttet til truslene som møter barna på nett. Disse plattformene gir ikke bare barn enkel tilgang, men også personer med fiendtlige intensjoner, slik som overgripere. Over- gripere kan opprette falske nettprofiler, utgi seg som barn og kontakte sårbare barn, med minimal risiko for å bli avslørt. Nettovergrep kan resultere i psykolo- giske, fysiske, emosjonelle, adferdsmessige og psykososiale problemer som kan påvirke barnet livet ut. For å unngå slike livsendrende konsekvenser er det av- gjørende å detektere og forhindre seksuelle nettovergrep. I løpet av denne masteravhandlingen har vi undersøkt hvorvidt en kombin- ert tilnærming av graf-, kontekst- og innholdsanalyse kan benyttes for å dynam- isk detektere overgripere på nett. Dette oppnådd vi ved å studere oppførselen til individuelle brukere i spill chatter. Vi implementerte en veiledet maskinlæring- salgoritme som klassifiserte meldingene sendt av brukere basert på flere atferds- egenskaper. Videre ble det implementert en deteksjonsmekanisme for å detektere overgripere så tidlig som mulig samtidig som høy dekning og presisjon kunne oppnås. Basert på de oppnådde resultatene konkluderte vi med at dynamisk deteksjon av overgripere i chatter er mulig. I tillegg konkluderte vi med at tidlig deteksjon av overgripere var mulig ved å overvåke brukernes atferd i pågående chatter. For å fortsette forskning for å forbedre deteksjon, bør bruken av andre klassifiseringsal- goritmer, inkludering av andre adferds-egenskaper og tilnærminger for å beregne dem, samt andre deteksjonsmekanismer studeres.The internet, and especially social media, has become a fundamental part of our life, no matter the age. Many social media platforms are targeted towards children enabling them to contact new friends without the need for physical meetings. Despite the clear benefits of social media, it also raises concerns about threats facing children online. These platforms do not only give access to children, but also to people with bad intentions, such as predators. Predators can create fake online profiles, pose as a child, and contact vulnerable children with a minimal risk of disclosure. Online assaults can result in psychological, physical, emotional, behavioral, and psycho-social issues affecting the child for the rest of its life. To avoid such life altering consequences it is crucial to detect and prevent sexual abuse online. During this thesis we have investigated whether a combined graph, context and content analysis approach could be used to dynamically detect predators on- line. This was accomplished by studying the behavior of individual users in game chats. We implemented a supervised machine learning algorithm which classified the messages sent by the users based on several behavioral features. Further, a detection mechanism was created to detect predators as early as possible whilst achieving high recall and precision. Based on the results achieved we concluded that dynamic detection of predat- ors in chats is possible. In addition, we concluded that early detection of predators was possible when monitoring the user’s behavior in ongoing chats. To continue the research into improving detection, the use of other classification algorithms, inclusion of other features and approaches to calculate them, and other detection mechanisms should be studied

A DNA Vaccine Encoding Multiple HIV CD4 Epitopes Elicits Vigorous Polyfunctional, Long-Lived CD4+ and CD8+ T Cell Responses

T-cell based vaccines against HIV have the goal of limiting both transmission and disease progression by inducing broad and functionally relevant T cell responses. Moreover, polyfunctional and long-lived specific memory T cells have been associated to vaccine-induced protection. CD4+ T cells are important for the generation and maintenance of functional CD8+ cytotoxic T cells. We have recently developed a DNA vaccine encoding 18 conserved multiple HLA-DR-binding HIV-1 CD4 epitopes (HIVBr18), capable of eliciting broad CD4+ T cell responses in multiple HLA class II transgenic mice. Here, we evaluated the breadth and functional profile of HIVBr18-induced immune responses in BALB/c mice. Immunized mice displayed high-magnitude, broad CD4+/CD8+ T cell responses, and 8/18 vaccine-encoded peptides were recognized. In addition, HIVBr18 immunization was able to induce polyfunctional CD4+ and CD8+ T cells that proliferate and produce any two cytokines (IFNγ/TNFα, IFNγ/IL-2 or TNFα/IL-2) simultaneously in response to HIV-1 peptides. For CD4+ T cells exclusively, we also detected cells that proliferate and produce all three tested cytokines simultaneously (IFNγ/TNFα/IL-2). The vaccine also generated long-lived central and effector memory CD4+ T cells, a desirable feature for T-cell based vaccines. By virtue of inducing broad, polyfunctional and long-lived T cell responses against conserved CD4+ T cell epitopes, combined administration of this vaccine concept may provide sustained help for CD8+ T cells and antibody responses- elicited by other HIV immunogens

Kreativitet i en målstyrt skole

Eksamensoppgave PPU teaterAvsluttende eksamensoppgave. Årsenhet, praktisk-pedagogisk utdanning i teater ved Avdeling Dans, 202

COVID-19 response measures the effect of national non-pharmaceutical intervention on hospitalizations : an empirical study of governments response to the COVID-19 pandemic

Throughout this thesis we will analyze the reaction in the growth rate of COVID-19 related hospitalizations following the implementation of Non-Pharmaceutical Interventions (NPIs), in order to estimate their effectiveness. Additionally, our thesis will investigate the effect of specific NPIs, and the difference in NPI performance throughout the pandemic. Although previous studies have focused on the reproduction number R, case growth, and cumulative deaths as their dependent variable, our thesis focuses on the number of daily COVID-19 related hospitalizations. We believe this to be a more reliable indicator of the spread of infection within the population. In doing so, we use a moving average of daily COVID-19 related hospitalizations as our dependent variable in our analysis. In order to carry out our analysis, we conduct our first regression on 64 events of NPI implementation. We undertake this regression in order to compute the difference in the growth rate of COVID-19 related hospitalizations, before and after NPI implementation. Furthermore, to conduct our second regression, we use the effect of each NPI in place as our dependent variable, which utilizes dummy variables for each active group of NPIs in order to find the effect of each NPI group. Lastly, our concluding regression introduces a final variable to determine if NPIs are getting increasingly more effective throughout the pandemic. For our conclusion, we determine from the results of our event studies that not all NPI implementations were successful, and that the outcome of our second regression indicates that there are extensive differences in the effectiveness of NPIs. We understood from our regression that school closures and lockdown measures are the most effective NPI in order to reduce the growth rate in COVID-19 related hospitalizations. Furthemore, we conclude that the implementation of these NPIs was more effective in reducing the growth rate of COVID-19 related hospitalizations during the first wave of infection.nhhma