Fuzzy Fibers: Uncertainty in dMRI Tractography

Fiber tracking based on diffusion weighted Magnetic Resonance Imaging (dMRI) allows for noninvasive reconstruction of fiber bundles in the human brain. In this chapter, we discuss sources of error and uncertainty in this technique, and review strategies that afford a more reliable interpretation of the results. This includes methods for computing and rendering probabilistic tractograms, which estimate precision in the face of measurement noise and artifacts. However, we also address aspects that have received less attention so far, such as model selection, partial voluming, and the impact of parameters, both in preprocessing and in fiber tracking itself. We conclude by giving impulses for future research

Cloud Material Handling System - Leveraging dynamic dispatching and reinforcement learning in a cloud-enabled shop floor material handling system

Effektiv håndtering av materialer og produkter på produksjonsgulv er viktig for å redusere produksjonskostnadene og forbedre produktiviteten. Selv om det vitenskapelige samfunnet har omfavnet automatisert materialhåndteringsutstyr i kjølvannet av Industry 4.0, er menneskedrevne kjøretøy som gaffeltrucker og palletrucker fortsatt det mest brukte utstyret for materialhåndtering. Denne masteroppgaven undersøker hvordan et skyaktivert produksjonsgulv kan utnytte dynamisk utsendelse ved å automatisere både menneskelige og autonomt betjente materialhåndteringsutstyr, kalt Cloud Material Handling System (CMHS). Hovedmålet med denne studien er å bestemme hvordan en CMHS kan forbedre materialhåndteringsaktivitetene i produksjonen. Spesielt evaluerer studien en CMHS i forskjellige scenarier for å undersøke når den er spesielt gunstig i materialhåndteringsoperasjoner. Flere utsendelsesmetoder som etablerte heuristikker og læringsmetoder med forsterkningslæring blir evaluert for å undersøke hvordan en CMHS kan implementeres. En litteraturstudie ble utført for å avsløre forskningshull adressert av en CMHS, mens en simuleringsmodell basert på et casestudie ble utviklet for å demonstrere bruken i praksis. Resultatene har vist CMHSs evne til å oppnå høyere produktivitet når det gjelder gjennomstrømning av produkter og utstyrsutnyttelse enn den konvensjonelle ikke-automatiserte referansen. Ytelsesøkninger ble observert i alle scenarier, mens antall nødvendige materialhåndteringsutstyr ble redusert med 40%. Simuleringsresultatene avslørte at CMHS med forsterkningslæring er spesielt gunstig for usikre produktankomster og arbeidsstasjonsfeil når produktbelastninger ble holdt på linje med arbeidsstasjonenes produksjonskapasitet. Mest fremtredende var under normale produktbelastninger, noe som resulterte i en 197% forbedring i total produktgjennomstrømning. De heuristiske metodene med lavere kompleksitet var på nivå eller bedre enn metodene med forsterkningslæring for forutsigbare materialstrømmer med høy ankomstrate. Videre evaluering av CMHS bør gjøres i samarbeid med en praktisk business case for å trekke ut viktige driftsparametere, redusere antall antagelser og utvikle en nøyaktig kostnadsmodell for CMHS.Efficient handling of materials and products on manufacturing shop floors is essential to reduce production costs and improve productivity. Although the scientific community has embraced automated material-handling equipment in the wake of Industry 4.0, human-operated vehicles like forklifts and pallet trucks are still the most commonly used equipment for material handling. This thesis investigates how a cloud-enabled shop floor can facilitate dynamic dispatching by automating human and autonomously operated material-handling equipment through a centralized system, coined as the Cloud Material Handling System (CMHS). The main objective of this study is to determine how a CMHS may improve material handling activities in manufacturing. Specifically, the study evaluates a CMHS in different scenarios to support when it is particularly beneficial in material handling operations. Multiple dispatching methods like heuristic dispatching rules and reinforcement learning policies are evaluated to support how a CMHS can be implemented. A literature study was conducted to disclose research gaps addressed by a CMHS, while a simulation model based on a case study was developed to demonstrate its use in practice. The results have shown the CMHS's ability to achieve higher productivity in product throughput and equipment utilization than the conventional non-automated benchmark. Performance increases were observed in all scenarios, while the number of required material-handling equipment was reduced by 40%. The simulation results revealed that the CMHS with reinforcement learning is particularly beneficial for uncertain product arrival rates and workstation failures when product loads were kept in line relative to production capacity. Most prominent were moderate product loads, resulting in a 197% gain in total product throughput. The lower-complexity heuristic methods were on a par, or superior, to the reinforcement learning policy for predictable material flows with high arrival rates. Further evaluation of the CMHS should be done in collaboration with a practical business case to extract key operation parameters, reducing the number of assumptions, and develop a rigorous economic model for the CMHS

Cloud Material Handling System - Leveraging dynamic dispatching andreinforcement learning in a cloud-enabled shopfloor material handling system

Effektiv håndtering av materialer og produkter på produksjonsgulv er viktig for å redusere produksjonskostnadene og forbedre produktiviteten. Selv om det vitenskapelige samfunnet har omfavnet automatisert materialhåndteringsutstyr i kjølvannet av Industry 4.0, er menneskedrevne kjøretøy som gaffeltrucker og palletrucker fortsatt det mest brukte utstyret for materialhåndtering. Denne masteroppgaven undersøker hvordan et skyaktivert produksjonsgulv kan utnytte dynamisk utsendelse ved å automatisere både menneskelige og autonomt betjente materialhåndteringsutstyr, kalt Cloud Material Handling System (CMHS). Hovedmålet med denne studien er å bestemme hvordan en CMHS kan forbedre materialhåndteringsaktivitetene i produksjonen. Spesielt evaluerer studien en CMHS i forskjellige scenarier for å undersøke når den er spesielt gunstig i materialhåndteringsoperasjoner. Flere utsendelsesmetoder som etablerte heuristikker og læringsmetoder med forsterkningslæring blir evaluert for å undersøke hvordan en CMHS kan implementeres. En litteraturstudie ble utført for å avsløre forskningshull adressert av en CMHS, mens en simuleringsmodell basert på et casestudie ble utviklet for å demonstrere bruken i praksis. Resultatene har vist CMHSs evne til å oppnå høyere produktivitet når det gjelder gjennomstrømning av produkter og utstyrsutnyttelse enn den konvensjonelle ikke-automatiserte referansen. Ytelsesøkninger ble observert i alle scenarier, mens antall nødvendige materialhåndteringsutstyr ble redusert med 40%. Simuleringsresultatene avslørte at CMHS med forsterkningslæring er spesielt gunstig for usikre produktankomster og arbeidsstasjonsfeil når produktbelastninger ble holdt på linje med arbeidsstasjonenes produksjonskapasitet. Mest fremtredende var under normale produktbelastninger, noe som resulterte i en 197% forbedring i total produktgjennomstrømning. De heuristiske metodene med lavere kompleksitet var på nivå eller bedre enn metodene med forsterkningslæring for forutsigbare materialstrømmer med høy ankomstrate. Videre evaluering av CMHS bør gjøres i samarbeid med en praktisk business case for å trekke ut viktige driftsparametere, redusere antall antagelser og utvikle en nøyaktig kostnadsmodell for CMHS.Efficient handling of materials and products on manufacturing shop floors is essential to reduce production costs and improve productivity. Although the scientific community has embraced automated material-handling equipment in the wake of Industry 4.0, human-operated vehicles like forklifts and pallet trucks are still the most commonly used equipment for material handling. This thesis investigates how a cloud-enabled shop floor can facilitate dynamic dispatching by automating human and autonomously operated material-handling equipment through a centralized system, coined as the Cloud Material Handling System (CMHS). The main objective of this study is to determine how a CMHS may improve material handling activities in manufacturing. Specifically, the study evaluates a CMHS in different scenarios to support when it is particularly beneficial in material handling operations. Multiple dispatching methods like heuristic dispatching rules and reinforcement learning policies are evaluated to support how a CMHS can be implemented. A literature study was conducted to disclose research gaps addressed by a CMHS, while a simulation model based on a case study was developed to demonstrate its use in practice. The results have shown the CMHS's ability to achieve higher productivity in product throughput and equipment utilization than the conventional non-automated benchmark. Performance increases were observed in all scenarios, while the number of required material-handling equipment was reduced by 40%. The simulation results revealed that the CMHS with reinforcement learning is particularly beneficial for uncertain product arrival rates and workstation failures when product loads were kept in line relative to production capacity. Most prominent were moderate product loads, resulting in a 197% gain in total product throughput. The lower-complexity heuristic methods were on a par, or superior, to the reinforcement learning policy for predictable material flows with high arrival rates. Further evaluation of the CMHS should be done in collaboration with a practical business case to extract key operation parameters, reducing the number of assumptions, and develop a rigorous economic model for the CMHS

The Nordic advantage in child mental health: separating health differences from reporting style in a cross-cultural comparison of psychopathology.

BACKGROUND: The use of similar standardised measures of psychopathology for population surveys permits cross-cultural comparisons. However, interpretation of findings can be challenging because rating thresholds may differ across cultures. By combining questionnaire and interview data, we explore whether lower questionnaire scores in Norway as compared to Britain reflect genuine differences in child mental health, or simply different reporting thresholds. METHODS: Information from the Strengths and Difficulties Questionnaire (SDQ) and the Development and Well-Being Assessment (DAWBA) interview were compared across recent population surveys in Norway and Britain. The Norwegian study (2002-03) had questionnaire data for 6,658 and interview data for 1,024 8-10-year-old children. The British dataset included questionnaire and interview data for 4,898 children of the same age range from two independent surveys (1999 and 2004). RESULTS: Norwegian children had lower SDQ scores on all problem scales (emotional, behavioural, hyperactive and peer relationship) according to parents as well as teachers. DAWBA information showed that the Norwegian prevalence of externalising disorders (behavioural and hyperactivity) was about half that found in Britain, whereas rates of emotional disorders were similar. Norwegian and British children with non-emotional disorders had similar questionnaire scores and rates of problem-recognition by parents and teachers. By contrast, questionnaire scores and problem-recognition were all lower in Norwegian children with emotional disorders. CONCLUSIONS: Lower Norwegian questionnaire scores for externalising problems appear to reflect real and substantial differences between the two countries. By contrast, lower questionnaire scores for emotional problems seem to reflect under-reporting/under-recognition by Norwegian adults, and not a genuinely lower prevalence of emotional disorders. This illustrates that cross-cultural differences in psychopathology based only on questionnaire data may be misleading. Nevertheless, careful use of questionnaire and interview data can focus mental health research on cross-cultural variations likely to reflect genuine health differences

A genome-wide test of the differential susceptibility hypothesis reveals a genetic predictor of differential response to psychological treatments for child anxiety Disorders

Background: The differential susceptibly hypothesis suggests that certain genetic variants moderate the effects of both negative and positive environments on mental health and may therefore be important predictors of response to psychological treatments. Nevertheless, the identification of such variants has so far been limited to preselected candidate genes. In this study we extended the differential susceptibility hypothesis from a candidate gene to a genome-wide approach to test whether a polygenic score of environmental sensitivity predicted response to cognitive behavioural therapy (CBT) in children with anxiety disorders. Methods: We identified variants associated with environmental sensitivity using a novel method in which within-pair variability in emotional problems in 1,026 monozygotic twin pairs was examined as a function of the pairs' genotype. We created a polygenic score of environmental sensitivity based on the whole-genome findings and tested the score as a moderator of parenting on emotional problems in 1,406 children and response to individual, group and brief parent-led CBT in 973 children with anxiety disorders. Results: The polygenic score significantly moderated the effects of parenting on emotional problems and the effects of treatment. Individuals with a high score responded significantly better to individual CBT than group CBT or brief parent-led CBT (remission rates: 70.9, 55.5 and 41.6%, respectively). Conclusions: Pending successful replication, our results should be considered exploratory. Nevertheless, if replicated, they suggest that individuals with the greatest environmental sensitivity may be more likely to develop emotional problems in adverse environments but also benefit more from the most intensive types of treatment

Goal-Based Portfolios - A mean-variance optimization approach with subportfolios -

Masteroppgave(MSc) in Master of Science in Business, Finance - Handelshøyskolen BI, 2018This thesis analysis the goal-based portfolio optimization approach and compares it to established theories of portfolio management. First, we review previous literature on the topic of portfolio optimization. Second, we identify the investor’s problem and define the methodology. Further, we perform a quantitative analysis of the goal-based portfolio optimization approach. We use historical asset returns to simulate future portfolio outcomes and analyse the performance of an investment according to goal-based portfolio theory. We find that by dividing an investment into multiple subportfolios, and optimizing each subportfolio separately, decreases the portfolios probability of failure. We conclude that an investor, with specific goals beyond attaining highest possible return, is better off investing in subportfolios as opposed to a single portfolio

Betydningen av idrett for personer med funksjonsnedsettelse

Bakgrunn: Grunnlaget for at jeg ønsker å fordype meg i dette temaet er at jeg har en stor interesse innenfor alt i paraidretten. Min personlige mening er at det å drive med paraidrett er en større prestasjon enn for de som bedriver funksjonsfrisk idrett. Jeg ble derfor veldig interessert i å høre mer fra de som er aktive og hvordan treningsmiljøet er. Metode: Det ble gjennomført en kvalitativ studie med fire intervju med fokusområde på betydning og tilhørighet. Her ble lydopptaker benyttet samt Word ved transkribering. Google Scholar og fagbøker ble også anvendt for innhenting av relevante referanse. Diskusjon: Gjennom diskusjonen har det blitt løftet frem bruken av selvbestemmelsesteorien satt opp mot tilhørighet, autonomi og kunnskap da dette har en ringvirkning på motivasjonen i idretten. Avslutning: En rød tråd gjennom hele oppgaven har vist seg å være betydningen av tilhørighet, da dette gjenspeiler seg i alle de utvalgte områdene. Tilhørighet har vist seg gjennom informantene å være en viktig faktor for motivasjon og samhold. Videre blir det belyst gjennom intervjuene at tilhørighet i idretten er en utmerket arena for utveksling av erfaringer

Genome-wide association study of response to cognitive-behavioural therapy in children with anxiety disorders

Background Anxiety disorders are common, and cognitive–behavioural therapy (CBT) is a first-line treatment. Candidate gene studies have suggested a genetic basis to treatment response, but findings have been inconsistent. Aims To perform the first genome-wide association study (GWAS) of psychological treatment response in children with anxiety disorders (n = 980). Method Presence and severity of anxiety was assessed using semi-structured interview at baseline, on completion of treatment (post-treatment), and 3 to 12 months after treatment completion (follow-up). DNA was genotyped using the Illumina Human Core Exome-12v1.0 array. Linear mixed models were used to test associations between genetic variants and response (change in symptom severity) immediately post-treatment and at 6-month follow-up. Results No variants passed a genome-wide significance threshold (P = 5×10−8) in either analysis. Four variants met criteria for suggestive significance (P<5×10−6) in association with response post-treatment, and three variants in the 6-month follow-up analysis. Conclusions This is the first genome-wide therapygenetic study. It suggests no common variants of very high effect underlie response to CBT. Future investigations should maximise power to detect single-variant and polygenic effects by using larger, more homogeneous cohorts

The utility of the SCAS-C/P to detect specific anxiety disorders among clinically anxious children

Questionnaire measures offer a time and cost-effective alternative to full diagnostic assessments for identifying and differentiating between potential anxiety disorders and are commonly used in clinical practice. Little is known, however, about the capacity of questionnaire measures to detect specific anxiety disorders in clinically anxious preadolescent children. This study aimed to establish the ability of the Spence Children’s Anxiety Scale (SCAS) subscales to identify children with specific anxiety disorders in a large clinic-referred sample (N = 1,438) of children aged 7 to 12 years. We examined the capacity of the Separation Anxiety, Social Phobia, Generalized Anxiety, and Physical Injury Fears (phobias) subscales to discriminate between children with and without the target disorder. We also identified optimal cutoff scores on subscales for accurate identification of children with the corresponding disorder, and examined the contribution of child, mother, and father reports. The Separation Anxiety subscale was able to accurately identify children with separation anxiety disorder, and this was replicated across all 3 reporters. Mother- and father-reported Social Phobia subscales also accurately identified children with social anxiety disorder, although child report was only able to accurately detect social anxiety disorder in girls. Using 2 or more reporters improved the sensitivity of the Separation Anxiety and Social Phobia subscales but reduced specificity. The Generalized Anxiety and Physical Injury Fears subscales failed to accurately identify children with the corresponding disorders. These findings have implications for the potential use of mother-, father-, and child-report SCAS subscales to detect specific disorders in preadolescent children in clinical settings

Clinicians’ perceptions of family involvement in the treatment of persons with psychotic disorders: a nested qualitative study

BackgroundFamily involvement in mental health care ranges from basic practices to complex interventions such as Family psychoeducation, the latter being a well-documented treatment for psychotic disorders. The aim of this study was to explore clinicians’ perceptions of the benefits and disadvantages of family involvement, including possible mediating factors and processes.MethodsNested in a randomised trial, which purpose was to implement Basic family involvement and support and Family psychoeducation in Norwegian community mental health centres during 2019–2020, this qualitative study is based on eight focus groups with implementation teams and five focus groups with ordinary clinicians. Using a purposive sampling strategy and semi-structured interview guides, focus groups were audio-recorded, transcribed verbatim, and analysed with reflexive thematic analysis.ResultsFour main themes were identified as perceived benefits: (1) Family psychoeducation—a concrete framework, (2) Reducing conflict and stress, (3) A triadic understanding, and (4) Being on the same team. Themes 2–4 formed an interconnected triad of mutually reinforcing elements and were further linked to three important clinician-facilitated sub-themes: a space for relatives’ experiences, emotions and needs; a space for patients and relatives to discuss sensitive topics and an open line of communication between clinician and relative. Although far less frequent, three main themes were identified as perceived disadvantages or challenges: (1) Family psychoeducation—occasional poor model fit or difficulties following the framework, (2) Getting more involved than usual, and (3) Relatives as a potentially negative influence—important nonethelessConclusionsThe findings contribute to the understanding of the beneficial processes and outcomes of family involvement, as well as the critical role of the clinician in achieving these and possible challenges. They could also be used to inform future quantitative research on mediating factors and implementation efforts