Reinforcement learning algorithms to model learning and decision-making in individuals with depressive disorders

Mental illness causes enormous suffering for many people. Current treatments do not reliably alleviate that suffering. Unclear conceptualisations of mental disorders combined with little knowledge about their aetiology are roadblocks to developing better treatments. This dissertation reviews attempts to use reinforcement learning models to improve the way we conceptualise some of the processes happening in the brain in mental illness. The hope is that more clearly defining the problems we are dealing with will eventually have a positive impact on our ability to diagnose and treat them. I start by giving an overview of the reinforcement learning framework, and detail some of the reinforcement learning models that have been used to understand mental illness better. I explain the statistical techniques used to compare these models and to estimate parameters once a model has been chosen. This leads in to a survey of what researchers have learned about human behaviour using these techniques. I focus particularly on results related to depression. I argue that key parameters like learning rate and reward sensitivity are closely linked to depressive symptoms. Finally, I speculate about the impact that knowledge of this kind may have on the development of better diagnosis and treatment for mental illness in general and depression specifically

Duo - trumm ja kitarr

Antud loov-praktilise lõputöö teoreetiline osa keskendub peamiselt kitarri- ja trummiduo konseptsiooni lahkamisele ning sellest inspireeritud muusika kirjutamisele. Kuna töö eesmärgiks oli leida erinevaid kõlavärve ja võimalusi, kuidas saavad kitarrist ja trummar koos muusikas eksisteerida, oli ka edasine teoreetiline osa varasemate antud kooslust viljelevate konseptsioonide analüüs.http://tartu.ester.ee/record=b2609556~S1*es

Optimaalse aktsiaportfelli koostamine Balti aktsiaturu näitel

Käesoleva bakalaureusetöö eesmärk on anda ülevaade portfelliteooriast ning selle põhjal optimaalsete portfellide moodustamine Balti aktsiaturu näitel. Esmalt tutvustatakse lähemalt portfelliteooriat kahe väärtpaberi ja n-väärtpaberi korral. Praktilises osas koostatakse optimaalsed portfellid ja analüüsitakse saadud näitajaid

Juhtivpolümeeri dopeerimine funktsionaliseeritud süsiniknanotorudega

http://www.ester.ee/record=b4613174*es

Muusikaajaloo õpetajate arvamused muusikaajaloo õpetamisest huvihariduskoolides

http://www.ester.ee/record=b4578298*es

Kaskokindlustuse kahjude modelleerimine

Käesoleva magistritöö eesmärk on kaskokindlustuse kahjuandmete modelleerimine kasutades erinevaid tõenäosusjaotusi. Jaotuste sobivuse hindamiseks kasutatakse mitmeid meetodeid nagu Kolmogorov-Smirnovi test, hii-ruut-test, jääkkeskmise meetod ning kvantiil-kvantiil graafikuid. Töö esimeses osas antakse ülevaade kasutatud kahjujaotustest. Töö teises osas antakse ülevaade jääkkeskmise meetodist ning tuletatakse jääkkeskmise valemid log-normaalse ja nihutatud Pareto jaotuse korral. Kolmandas osas antakse ülevaade andmestikust, Kolmogorov-Smirnovi ja hii-ruut-testidest ning sobitatakse jaotusi kahjuandmetele

Resilience in the time of crisis: A review of the maternal, perinatal and reproductive health effects of COVID-19 in South Africa

Background. The COVID‐19 pandemic had a profound effect on the health sector globally and in South Africa (SA). Objective. To review the effects of COVID‐19 on maternal, perinatal and reproductive health outcomes and service utilisation in SA. Methods. Three routine national data collection systems were sourced: the District Health Information System, the Saving Mothers reports of the National Committee on Confidential Enquiry into Maternal Deaths and the Saving Babies reports from the National Perinatal Morbidity and Mortality Committee using data from the Perinatal Problem Identification Program. Results. There were 35% and 8% increases in maternal and stillbirth mortality rates, respectively, in 2020 and 2021, which correlated with the COVID‐19 waves. However, in 2022, rates returned to pre‐COVID levels. Antenatal visits and facility births showed little change, but there was a shift to more rural provinces. The use of oral and injectable contraceptives and termination of pregnancy services decreased markedly in 2020 and 2021, with a sustained shift to long‐acting reversible contraceptives. The increase in maternal deaths was predominantly due to COVID‐19 respiratory complications, but also an increase in obstetric haemorrhage. Stillbirths increased significantly (10%) for birthweights between 2 000 g and 2 499 g, categorised mostly as unexplained stillbirths or preterm labour, but no increase in neonatal deaths was observed. Administrative avoidable factors increased by 24% in the 2020 ‐ 2022 triennium, but there was no increase in patient/community level or healthcare provider‐related avoidable factors during the pandemic years. Conclusion. COVID‐19 caused a marked increase in maternal death and stillbirth rates in 2020 and 2021 due to both direct effects of the virus and indirect effects on functioning of the health system. The continued, although modified, health‐seeking behaviour of women and the rapid return to pre‐COVID‐19 mortality rates demonstrates enormous resilience in women and the health system