Information from the TRMM-CSH and TRMM-2A12 datasets is used to examine the four-dimensional latent heating (LH) structures over the Asian monsoon region between 1998 and 2006. High sea surface temperatures, ocean-land contrasts and complex terrain produce large precipitation and atmospheric heating rates whose spatial and temporal characteristics are relatively undocumented. Analyses identify interannual and intraseasonal LH variations, with a large fraction of the interannual variability induced by internal intraseasonal variability. Also, the analyses identify a spatial dipole of LH anomalies between the equatorial Indian Ocean and the Bay of Bengal regions occurring during the summer active and suppressed phases of the monsoon intraseasonal oscillation. Comparisons made between the TRMM-CSH and TRMM-2A12 datasets indicate significant differences in the shape of the vertical profile of LH. Comparison of TRMM-LH retrievals with sounding budget observations made during the South China Sea Monsoon experiment shows a high correspondence in the timing of positive LH episodes during rainy periods. Negative values of LH, associated with radiative cooling and with higher troposphere cooling from non-precipitating clouds, are not captured by any of the TRMM datasets. In summary, LH algorithms based on satellite information are capable of representing the spatial and temporal characteristics of the vertically integrated heating in the Asian monsoon region. The TRMM-CSH presents better performance than TRMM-2A12. However, the vertical distribution of atmospheric heating is not captured accurately throughout all different convective phases. It is suggested that satellite derived radiative heating/cooling products are needed to supplement the LH products in order to give an overall better depiction of atmospheric heating.

With the vast amount of information available on the Internet today, helping users find relevant content has become a prioritized task in many software products that recommend news articles. One such product is Opera for Android, which has a news feed containing articles the user may be interested in. In order to easily determine what articles to recommend, they can be categorized by the topics they contain. One approach of categorizing articles is using Machine Learning and Natural Language Processing (NLP). A commonly used model is Latent Dirichlet Allocation (LDA), which finds latent topics within large datasets of for example text articles. An extension of LDA is hierarchical Latent Dirichlet Allocation (hLDA) which is an hierarchical variant of LDA. In hLDA, the latent topics found among a set of articles are structured hierarchically in a tree. Each node represents a topic, and the levels represent different levels of abstraction in the topics. A further extension of hLDA is constrained hLDA, where a set of predefined, constrained topics are added to the tree. The constrained topics are extracted from the dataset by grouping highly correlated words. The idea of constrained hLDA is to improve the topic structure derived by a hLDA model by making the process semi-supervised. The aim of this thesis is to create a hLDA and a constrained hLDA model from a dataset of articles provided by Opera. The models should then be evaluated using the novel metric word frequency similarity, which is a measure of the similarity between the words representing the parent and child topics in a hierarchical topic model. The results show that word frequency similarity can be used to evaluate whether the topics in a parent-child topic pair are too similar, so that the child does not specify a subtopic of the parent. It can also be used to evaluate if the topics are too dissimilar, so that the topics seem unrelated and perhaps should not be connected in the hierarchy. The results also show that the two topic models created had comparable word frequency similarity scores. None of the models seemed to significantly outperform the other with regard to the metric.

The present study draws on recent sociological literature that argues that the study of cognition and culture can benefit from theories of embodied cognition. The concept of semantic internalization is introduced, which is conceptualized as the ability to perceive and articulate the topics that are of most concern to a community as they are manifested in social discourse. Semantic internalization is partly an application of emotional intelligence in the context of community-level discourse. Semantic internalization is measured through the application of Latent Semantic Analysis. Furthermore, it is investigated whether this ability is related to an individual’s social capital and habitus. The analysis is based on data collected from the online review platform yelp.com.

Introduktion: Tuberkulos är en av världens mest spridda infektionssjukdomar. En tredjedel av jordens befolkning beräknas bära på bakterien utan att vara sjuka (latent tuberkulos, LTBI). Närmare tio procent av bärarna utvecklar aktiv tuberkulos någon gång under livet. Europa har jämförelsevis låg incidens av tuberkulos och i Sverige har antalet tuberkulosfall minskat sedan mitten av 40-talet. I Sverige ses de senaste årens ökade antal migranter som en förklaring till en tillfälligt ökad prevalens av tuberkulos. Tidig diagnostik och behandling av tuberkulos är avgörande faktorer för att förhindra smittspridning och ger den enskilde individen möjlighet att hantera sin hälsa, vilket är angeläget ur ett folkhälsoperspektiv. Landstingen/regionerna har valt olika strategier för vilka som ska inkluderas i screening för tuberkulos vid hälsoundersökningar av migranter. Syfte: Syftet med studien var att undersöka prevalens och uppföljning av latent tuberkulos bland migranter som genomgått hälsoundersökning vid vårdcentraler i Region Jönköpings län. Metod: Studien var en retrospektiv observationsstudie utifrån kvantitativ ansats. Data samlades in genom journalgranskning och 361 journaler inkluderades i analyserna. Förekomst av latent och aktiv tuberkulos korrelerades med kön, ålder och ursprungsland. Resultat: Resultaten från studien visade att prevalensen av LTBI i studiepopulationen var 9.4 %. Resultaten visade att LTBI var vanligare hos män och individer > 35 år. Däremot sågs inga skillnader utifrån ursprungsland. Slutsats: Studien är av begränsad storlek och därmed generaliserbarhet. LTBI är relativt vanligt bland migranter. Ytterligare studier behövs för att identifiera optimala rutiner för screening och förebyggande insatser i migrantgruppen. / Introduction: Tuberculosis is one of the world's most widespread infectious diseases. One third of the world’s population is expected to carry the bacterium without being ill (latent tuberculosis, LTBI). Nearly ten percent of the carriers develop active tuberculosis sometime during their lifetime. Europe has a comparatively low incidence of tuberculosis and in Sweden the number of cases of tuberculosis has decreased since the mid-40s. In Sweden, the increased number of immigrants in recent years is seen as an explanation for a temporarily increased prevalence of tuberculosis. Early diagnosis and treatment of tuberculosis are key factors in preventing the spread of infection and giving the individual the opportunity to manage their health, which is important from a public health perspective. The county councils/regions have chosen different strategies for whom to be included in screening for tuberculosis in health surveys of immigrants. Aim: The aim of the study was to investigate the prevalence and follow-up of latent tuberculosis among immigrants who have undergone a health examination at health centers in the County of Jönköping. Method: The study was a retrospective observation study based on quantitative approach. Data was collected through journal review and 361 records were included in the analysis. The presence of latent and active tuberculosis was correlated with gender, age and country of origin. Results: The results of the study showed that the prevalence of LTBI in the study population was 9.4%. The results showed that LTBI was more common in men and individuals > 35 years. However, no differences were seen by country of origin. Conclusion: The study is of limited size and thus generalisability. LTBI is relatively common among immigrants. Further studies are needed to identify optimal routines for screening and preventive measures in the immigrant group.

Regression testing is just as important for the quality assurance of a system, as it is time consuming. Several techniques exist with the purpose of lowering the execution times of test suites and provide faster feedback to the developers, examples are ones based on transition-models or string-distances. These techniques are called test case selection (TCS) techniques, and focuses on selecting subsets of the test suite deemed relevant for the modifications made to the system under test. This thesis project focused on evaluating the use of a topic model, latent dirichlet allocation, as a means to create a diverse selection of test cases for coverage of certain test characteristics. The model was tested on authentic data sets from two different companies, where the results were compared against prior work where TCS was performed using similarity-based techniques. Also, the model was tuned and evaluated, using an algorithm based on differential evolution, to increase the model’s stability in terms of inferred topics and topic diversity. The results indicate that the use of the model for test case selection purposes was not as efficient as the other similarity-based selection techniques studied in work prior to thist hesis. In fact, the results show that the selection generated using the model performs similar, in terms of coverage, to a randomly selected subset of the test suite. Tuning of the model does not improve these results, in fact the tuned model performs worse than the other methods in most cases. However, the tuning process results in the model being more stable in terms of inferred latent topics and topic diversity. The performance of the model is believed to be strongly dependent on the characteristics of the underlying data used to train the model, putting emphasis on word frequencies and the overall sizes of the training documents, and implying that this would affect the words’ relevance scoring to the better.

<p><strong>Bakgrund: </strong>Alzheimers sjukdom förändrar minnet hos den drabbade, detta innebär att de blir beroende av vårdande. Närstående vill oftast inte lämna dem, utan blir deras naturliga vårdare i hemmet. Detta upplevs vara en trygghet för den drabbade, då minnesstörning oftast förvärras av att flytta hemifrån. Oavsett om det handlar om naturlig vård eller professionell vård är den vårdande relationen viktigt då den lindrar lidandet. <strong>Problem: </strong>Människor drabbade av Alzheimers har svårt att uttrycka sig verbalt, något som kan förhindra att den vårdande relationen uppstår. Detta skulle kunna bidra till att deras lidande inte lindras. <strong>Syfte: </strong>Är att belysa hur den vårdande relationen gestaltas i drama, då anhörig är naturlig vårdare till en människa drabbad av Alzheimers sjukdom. <strong>Metod: </strong>En latent innehållsanalys användes för att analysera filmen ”En sång för Martin”. <strong>Resultat: </strong>I resultatet presenteras fyra teman, ”Som att spela ett spel”, ”Jag vill bara hjälpa dig”, ”Ensam fastän vi är två” och ”De heligaste löftena”, för att belysa syftet. <strong>Slutsats: </strong>Båda parter kan i den vårdande relationen växa tillsammans och finna en väg ut ur lidandet. Utan den vårdande relationens närvaro blev de ensamma i sin smärta, rädsla och oro. </p> / <p><strong>Background: </strong>Alzheimer´s disease changes the memory of the sufferer, this means that they become dependent of caring. Relatives do not often want to leave them, but rather become their natural caregivers in their home. This is experienced as security for the sufferer, because moving often disturbs a memory disorder. Regardless of whether it is natural care or professional care the caring relationship is important because it relieves suffering. <strong>Problem:</strong> Human beings affected by Alzheimer's, has difficulty expressing them verbally, which may prevent a caring relationship. This could contribute that their suffering will not alleviate. <strong>Aim: </strong>To illuminate how the caring relationship shapes in drama, when a relative becomes a natural caregiver to a person suffering from Alzheimer's disease. <strong>Method: </strong>A latent content analysis was used for analyzing the movie “En sång för Martin”. <strong>Results: </strong>The results are presented in four themes, “Like playing a game”, “I just want to help you”, “Solo though we are two” and “The most sacred promises”, to illuminate the aim. <strong>Conclusion: </strong>Both parts can in the caring relationships grow together and find a way out of suffering. Without the caring relationship presence they were left alone in their pain, fear and anxiety.</p>

Bakgrund: Alzheimers sjukdom förändrar minnet hos den drabbade, detta innebär att de blir beroende av vårdande. Närstående vill oftast inte lämna dem, utan blir deras naturliga vårdare i hemmet. Detta upplevs vara en trygghet för den drabbade, då minnesstörning oftast förvärras av att flytta hemifrån. Oavsett om det handlar om naturlig vård eller professionell vård är den vårdande relationen viktigt då den lindrar lidandet. Problem: Människor drabbade av Alzheimers har svårt att uttrycka sig verbalt, något som kan förhindra att den vårdande relationen uppstår. Detta skulle kunna bidra till att deras lidande inte lindras. Syfte: Är att belysa hur den vårdande relationen gestaltas i drama, då anhörig är naturlig vårdare till en människa drabbad av Alzheimers sjukdom. Metod: En latent innehållsanalys användes för att analysera filmen ”En sång för Martin”. Resultat: I resultatet presenteras fyra teman, ”Som att spela ett spel”, ”Jag vill bara hjälpa dig”, ”Ensam fastän vi är två” och ”De heligaste löftena”, för att belysa syftet. Slutsats: Båda parter kan i den vårdande relationen växa tillsammans och finna en väg ut ur lidandet. Utan den vårdande relationens närvaro blev de ensamma i sin smärta, rädsla och oro. / Background: Alzheimer´s disease changes the memory of the sufferer, this means that they become dependent of caring. Relatives do not often want to leave them, but rather become their natural caregivers in their home. This is experienced as security for the sufferer, because moving often disturbs a memory disorder. Regardless of whether it is natural care or professional care the caring relationship is important because it relieves suffering. Problem: Human beings affected by Alzheimer's, has difficulty expressing them verbally, which may prevent a caring relationship. This could contribute that their suffering will not alleviate. Aim: To illuminate how the caring relationship shapes in drama, when a relative becomes a natural caregiver to a person suffering from Alzheimer's disease. Method: A latent content analysis was used for analyzing the movie “En sång för Martin”. Results: The results are presented in four themes, “Like playing a game”, “I just want to help you”, “Solo though we are two” and “The most sacred promises”, to illuminate the aim. Conclusion: Both parts can in the caring relationships grow together and find a way out of suffering. Without the caring relationship presence they were left alone in their pain, fear and anxiety.

Social science researchers are increasingly using multi-group confirmatory factor analysis (MG-CFA) to compare different groups' latent variable means. To ensure that a MG-CFA model is identified, two approaches are commonly used to set the scale of the latent variable. The reference indicator (RI) strategy, which involves constraining one loading per factor to a value of one across groups, assumes that the RI has equal factor loadings across groups. The second approach involves constraining each factor's variance to a value of one across groups and, thus, assumes that the factor variances are equal across groups. Latent mean differences may be tested and described using Gonzalez and Griffin's (2001) likelihood ratio test (LRT[subscript k]) and Hancock's (2001) standardized latent mean difference effect size measure ([delta subscript k]), respectively. Applied researchers using the LRT[subscript k] and/or the [delta subscript k] when comparing groups' latent means may not explicitly test the assumptions underlying the two factor scaling methods. To date, no study has examined the impact of violating the assumptions associated with the two scaling methods on latent mean comparisons. The purpose of this study was to assess the performance of the LRT[subscript k] and the [delta subscript k] when violating the assumptions underlying the RI strategy and/or the factor variance scaling method. Type I error and power of the LRT[subscript k] as well as relative parameter bias and parameter bias of the [delta subscript k] were examined when varying loading difference magnitude, factor variance ratio, factor loading pattern and sample size ratio. Rejection rates of model fit indices, including the x² test, RMSEA, CFI, TLI and SRMR, under these varied conditions were also examined. The results indicated that violating the assumptions underlying the RI strategy did not affect the LRT[subscript k] or the [delta subscript k]. However, violating the assumption underlying the factorvariance scaling method influenced Type I error rates of the LRT[subscript k], particularly in unequal sample size conditions. Results also indicated that the four factors manipulated in this study had an impact on correct model rejection rates of the model fit indices. It is hoped that this study provides useful information to researchers concerning the use of the LRT[subscript k] and [delta subscript k] under factor scaling method assumption violations. / text

Contexte. Selon les directives de Mouvement 24 heures adoptées par le gouvernement du Canada, l’équilibre de trois habitudes de vie (activité physique, temps d’écran et sommeil) serait la clé pour une meilleure santé physique et psychologique. Plusieurs enfants ne respecteraient pas ces directives. L’adoption d’habitudes de vie problématiques à l’enfance serait liée prospectivement, entre autres, à l’apparition de problèmes intériorisés. Inversement, il semblerait que les problèmes intériorisés soient également associés prospectivement à l’adoption d’habitudes de vie problématiques à l’enfance. Bien que la tendance soit à considérer les habitudes de vie de façon conjointe, très peu d’études ont fait cet exercice. De plus, très peu d’études longitudinales ont vérifié les liens entre les problèmes intériorisés et les habitudes de vie à l’enfance. Objectifs. (1) Identifier les profils d’habitudes de vie à 10 ans en utilisant des indicateurs d’activité physique, de temps d’écran et de sommeil. (2) Examiner si les problèmes intériorisés à 8 ans prédisent l’appartenance aux profils d’habitudes de vie. (3) Examiner si les enfants qui composent chacun des profils d’habitudes de vie se distinguent en termes de problèmes intériorisés à 12 ans. Méthode. Les données utilisées sont celles de l’Étude longitudinale du développement des enfants du Québec. L’échantillon utilisé pour dériver les profils est composé de 1334 enfants. Les habitudes de vie à 10 ans ont été rapportées par les mères. Les problèmes intériorisés à 8 ans ont été rapportés par les mères et les enseignants, puis par les enfants à 12 ans. Ces données ont été collectées par questionnaires. Les profils ont été dérivés empiriquement par une analyse de profils latents. Des régressions logistiques multinomiales et des analyses de covariance ont été faites pour tester les associations entre les problèmes intériorisés et les profils. Résultats. Quatre profils ont été trouvés : (1) Habitudes de vie équilibrées (43 %), (2) Habitudes de vie moyennes (38 %), (3) Habitudes de vie inactives (15%) et Habitudes de vie très inactives (4 %). Les problèmes intériorisés à 8 ans ne prédisent pas l’appartenance aux profils d’habitudes de vie à 10 ans. Toutefois, l’appartenance au profil Habitudes de vie très inactives prédit un niveau élevé de sentiments dépressifs à 12 ans à comparer aux enfants du profil Habitudes de vie équilibrées. Implications. Les programmes gouvernementaux comme le Mouvement 24 heures visant à augmenter le niveau d'activité physique et à réduire le temps d'écran chez les jeunes seraient bénéfiques pour leur bien-être psychologique. Par ailleurs, l’ajout d’une composante d’activité physique aux programmes visant à diminuer les sentiments dépressifs chez les jeunes serait à encourager. / Context. According to the 24-Hour Movement guidelines adopted by the government of Canada, a balanced lifestyle regarding physical activity, screen time, and sleep is essential for a better physical and psychological health. Many children do not follow these guidelines. The adoption of an unhealthy lifestyle in childhood is prospectively linked, among other things, to internalizing problems such as depressive symptoms and anxiety. Conversely, internalizing problems are also prospectively associated with an unhealthy lifestyle in childhood. Very few studies have examined the specific effects of physical activity, screen time, and sleep when modelled jointly. In addition, very few longitudinal studies have examined the links between internalizing problems and lifestyle in childhood. Objectives. (1) To identify lifestyle profiles at 10 years old using indicators of physical activity, screen time, and sleep. (2) To examine the association between internalizing problems (depressive symptoms and anxiety) at 8 years old and lifestyle profiles membership at 10 years old. (3) To compare children according to profile membership in order to examine the differences in terms of internalizing problems at 12 years old. Method. Data are from the Québec Longitudinal Study of Child Development. The sample used to derive lifestyle profiles at age 10 included 1334 children. Physical activity, screen time and sleep were reported by mothers. Internalizing problems at age 8 were reported by mothers and teachers, then by children at age 12. All data were collected by questionnaires. The profiles have been derived empirically by a latent profile analysis. Multinomial logistic regressions and covariance analysis were conducted to test the associations between internalizing problems and profiles. Results. Four lifestyle profiles at age 10 were found among our sample: (1) Balanced lifestyle (43 %), (2) Average lifestyle (38 %), Inactive lifestyle (15 %), and Very inactive lifestyle (4 %). Internalizing problems at age 8 did not predict profile membership, whereas, children in the Very inactive lifestyle profile had significantly more depressive symptoms at age 12 compared to children in the Balanced lifestyle. Implications. In line with our hypothesis, children with an inactive lifestyle in childhood are at risk of elevated depressive symptoms in early adolescence. Therefore, governmental programs such as the 24-Hour Movement which aim to increase the levels of physical activity and decrease screen time in youth are beneficial for their psychological well-being. Furthermore, a physical activity component should be added to programs that aim to reduce depressive symptoms in youth.

In this thesis, the Twitter social media is data mined for information about the covid-19 outbreak during the month of March, starting from the 3’rd and ending on the 31’st. 100,000 tweets were collected from Harvard’s opensource data and recreated using Hydrate. This data is analyzed further using different Natural Language Processing (NLP) methodologies, such as termfrequency inverse document frequency (TF-IDF), lemmatizing, tokenizing, Latent Semantic Analysis (LSA) and Latent Dirichlet Allocation (LDA). Furthermore, the results of the LSA and LDA algorithms is reduced dimensional data that will be clustered using clustering algorithms HDBSCAN and K-Means for later comparison. Different methodologies are used to determine the optimal parameters for the algorithms. This is all done in the python programing language, as there are libraries for supporting this research, the most important being scikit-learn. The frequent words of each cluster will then be displayed and compared with factual data regarding the outbreak to discover if there are any correlations. The factual data is collected by World Health Organization (WHO) and is then visualized in graphs in ourworldindata.org. Correlations with the results are also looked for in news articles to find any significant moments to see if that affected the top words in the clustered data. The news articles with good timelines used for correlating incidents are that of NBC News and New York Times. The results show no direct correlations with the data reported by WHO, however looking into the timelines reported by news sources some correlation can be seen with the clustered data. Also, the combination of LDA and HDBSCAN yielded the most desireable results in comparison to the other combinations of the dimnension reductions and clustering. This was much due to the use of GridSearchCV on LDA to determine the ideal parameters for the LDA models on each dataset as well as how well HDBSCAN clusters its data in comparison to K-Means.