Genom en närläsning av filmerna Girl, Interrupted (James Mangold, 1999) och Min lilla syster (Sanna Lenken, 2015) söker denna uppsats att undersöka porträtteringen av kvinnliga karaktärer med psykisk ohälsa inom den kommersiella filmen. Huvudfokuset i uppsatsens undersökning är framförallt hur karaktärernas psykiska ohälsa framställs i enlighet med deras konformerande eller avvikande från acceptabel femininitet. Karaktärerna som är föremål för undersökningen är Susanna Kaysen (Winona Ryder), Lisa Rowe (Angelina Jolie) och Daisy Randone (Brittany Murphy) i Girl, Interrupted samt Katja (Amy Deasismont) i Min lilla syster. Med hjälp av feministisk filmteori söker uppsatsen att undersöka hur gestaltningen av karaktärernas psykiska ohälsa sammanflätas med dominerande föreställningar kring den kvinnliga könsrollen. Genom att använda termerna psykets estetik, delikat skärande, patientkarriär, fogliga kroppar och anorektiskt suicid blottlägger uppsatsen hur karaktärernas diagnoser genomsyras av kulturella föreställningar kring att vara kvinna och lida av psykisk ohälsa.

Over recent years, military research has focused on ways of being able to predict operational success and readiness through the development of simulated operational tasks measuring the physical limits of the soldier. Therefore, to properly prepare the tactical athlete for the demands and rigor of combat, accurate assessment of baseline physical abilities and limitations are necessary. Currently, western armies use a basic physical fitness test, which has been heavily argued to have no bearing on operational readiness, thus they are in the process of transitioning to a more specific combat readiness test. However, specific assessments to predict operational success/readiness are inefficient or lacking. A single test that requires minimal time, but provides simultaneous assessment of the necessary physical characteristics (i.e. aerobic and anaerobic capacities) may provide a unique opportunity to enhance soldier performance assessment. The 3-min all-out run, is a relatively new test that has been recently validated. It provides two performance estimates, critical velocity (CV) and anaerobic distance capacity (ADC). CV provides a measure of the individual's aerobic capacity, while the ADC is an indicator of anaerobic capacity. The purpose of this study, therefore, is to examine the relationship between CV and ADC from the 3-min all-out run and combat specific tasks (2.5-km run, 50-m casualty carry, and repeated sprints with rush shooting) in an elite special force unit. Eighteen male soldiers (age: 19.9 ± 0.8 years; height: 177.6 ± 6.6 cm; body mass: 74.1 ± 5.8 kg; BMI: 23.52 ± 1.63) from an elite combat special force unit of the Israel Defense Forces (IDF) volunteered to complete a 3-min all-out run, while wearing a global positioning system (GPS) unit, and a battery of operational CST (2.5-km run, 50-m casualty carry and 30-m repeated sprints with "rush" shooting (RPTDS)). Estimates of CV and ADC from the 3-min all-out run were determined from the downloaded GPS data with CV calculated as the average velocity of the final 30 s of the run and ADC as the velocity-time integral above CV. CV exhibited significant negative correlations with the 2.5-km run time (r = - 0.62, p < 0.01), and RPTDS time (r = - 0.71p < 0.01). However, CV (r = - 0.31) or ADC (r = 0.16) did not show any correlation with the 50-m casualty carry run. In addition, CV was positively correlated with the average velocity during the 2.5- km run (r = 0.64, p < 0.01). Stepwise regression identified CV as the most significant performance measure associated with the 2.5-km run time, and BMI and CV measures as significant predictors of RPTDS time (R2= 0.67, p < 0.05). Our main findings indicate that CV was highly related to performance during CST, including the 2.5-km run and RPTDS, but not the 50-m casualty carry. Using the 3-min all-out run as a testing measurement offers a more efficient and simpler way in assessing both aerobic and anaerobic capabilities (CV and ADC) with-in a relatively large sample. In this regard, this method of testing may be conducive to a military type environment whether for selection purposes, to predict combat readiness, to prescribe a training program or just a need analysis for the company commander.

This essay examines various aspects of alienation in Karl Ove Knausgaard's autobiographical novel My Struggle and its cultural contexts. The overall purpose of the essay is twofold. The aim is to analyze both the depiction and the causes of alienation in My struggle, and to examine how the cultural contexts contribute to the author Knausgaard's experience of alienation. To accomplish this the analysis is divided into two sections. The first part focuses on the literary character Karl Ove and aims to analyze the experience of alienation in the novel. The aim of the second part is, on the other hand, to look at how the cultural context affects the author Knausgaard in an alienating way, mainly how the media landscape and the digitalization of society increases Knausgaard's self-exploitation and the reification of his name. The second part, thereby, reads the novel as a work of autofiction where the author (Knausgaard) and the protagonist (Karl Ove) are treated as one and the same. The theoretical framework of the essay is based upon Rahel Jaeggi's and Hartmut Rosa's definitions of alienation. Altogether, the analysis indicates multiple examples of alienation in My Struggle. The protagonist, Karl Ove, is indifferent to the people and the world around him, and he feels as if he has lost control over his own life. Karl Ove is also unable to combine his two most important social roles in life – as a father and as a writer. Consequently, this leads to an internal division between his conflicting ideals and gender notions. Furthermore, Karl Ove is described as a rootless and formless subject, who is alienated from time and space. Another form of alienation occurs when Knausgaard becomes famous, and his authorship is reified. The reification of Knausgaard's name and face implies that he, as a commodified subject, is linked to the trademark Knausgaard™ over which he has limited control. Also, the results of the analysis suggest that it matters whether you choose to read the book as a novel or as autofiction. As a novel, My Struggle’s ending seems to indicate that the protagonist, Karl Ove, manages to replace his alienation with a meaningful seeing, and that he is able to shift his attention to what really matters in life. If you read My Struggle as autofiction, however, this progress is not that obvious. Rather, it looks as if the uncontrollable autobiographical feedback structure of My Struggle continues in media even after the novel is completed.

This thesis addresses an inventory management problem of what, when and how many products should be ordered from the supplier applying order line fees. Order line fee is a fixed fee which the company pays to the supplier per every ordered product not depending on the ordered quantity. Even though there are various inventory management methods and variety of research done in the field, there was no research found related to inventory management when supplier order line fees are applied. The described problem is real and currently exists at the company ASWO Baltic. The problem is solved by using experimental research method and CRISP-DM process. The historical company’s data of customer and supplier orders is used for the project. Data is analyzed and prepared for model creation by using feature engineering, data transformation and data normalization methods. Min/Max inventory management method is used as a base for model creation. The improvement proposed by the thesis is to use machine learning algorithms to predict Min and Max stock levels. Support Vector Regression, k-nearest neighbors, Random Forest, Artificial Neural Network, ARIMA, and Prophet machine learning algorithms are tested both for Min and Max level prediction. It was found out that the best results for Min stock level prediction were achieved by k-nearest neighbors algorithm with the average sMAPE measure of 7.0079%. The best predictions for Max stock level were done by Random Forest algorithm with the average sMAPE of 15.0303%. After the hyperparameter optimization sMAPE was improved to 6.8730% and 14.6813% accordingly. The simulation was run to evaluate if the proposed algorithm outperforms the current system. It showed that for the items which have more than 200 orders the algorithm decreased the number of supplier orders by 35,83% and the number of backorders by 49,29% while keeping almost the same inventory turnover. If the same results are achieved with the all products, it is expected that the company would save around 60K euros per annum on supplier order line fees and the lower number of backorders would increase sales by 24%. / Detta examensarbete tar upp ett lagerhanteringsproblem om vad, när och hur många produkter som ska beställas från leverantören som tillämpar orderradsavgifter. Orderradsavgift är en fast avgift som företaget betalar till leverantören för varje beställd produkt, inte beroende på beställd kvantitet. Även om det finns olika lagerhanteringsmetoder och olika undersökningar som gjorts inom området, hittades ingen forskning relaterad till lagerhantering när orderradsavgifter tillämpas. Det beskrivna problemet existerar idag på företaget ASWO Baltic. Problemet löstes genom att använda experimentell forskningsmetod och CRISPDM- process. Företagets historiska data om kund- och leverantörsbeställningar har används för projektet. Data har analyseras och förbereds och modellerats med hjälp av funktionsteknik, datatransformation och datanormaliseringsmetoder. Min/Max lagerhanteringsmetoden används som bas för att skapa en modell. Förbättringen som föreslås i avhandlingen är att använda maskininlärningsalgoritmer för att förutsäga Min och Max lagernivåer. Stöd för vektorregression, k-närmaste grannar, Random Forest, Artificiellt neuralt nätverk, ARIMA och Prophet maskininlärningsalgoritmer testas både för förutsägelse av min- och maxnivå. Det visade sig att de bästa resultaten för förutsägelse av Min lagernivå uppnåddes med algoritmen "k-nearest neighbors" med det genomsnittliga sMAPE-måttet på 7,0079%. De bästa förutsägelserna för Max lagernivå gjordes av Random Forest-algoritmen med den genomsnittliga sMAPE på 15,0303%. Efter hyperparameteroptimeringen förbättrades sMAPE till 6,8730 % och 14,6813 % i enlighet därmed. Simuleringen kördes för att utvärdera om den föreslagna algoritmen överträffar det nuvarande systemet. Den visade att för de artiklar som har mer än 200 beställningar minskade algoritmen antalet leverantörsbeställningar med 35,83 % och antalet restorder med 49,29 % samtidigt som det bibehöll nästan samma lageromsättning. Om samma resultat uppnås med alla produkter, förväntas företaget spara cirka 60 000 euro per år på leverantörsorderavgifter och det lägre antalet restorder skulle öka försäljningen med 24 %.

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Bacterial taxonomy is the science of classifying, naming, and identifying bacteria. The scope and practice of taxonomy has evolved through history with our understanding of life and our growing and changing needs in research, medicine, and industry. As in animal and plant taxonomy, the species is the fundamental unit of taxonomy, but the genetic and phenotypic diversity that exists within a single bacterial species is substantially higher compared to animal or plant species. Therefore, the current "type"-centered classification scheme that describes a species based on a single type strain is not sufficient to classify bacterial diversity, in particular in regard to human, animal, and plant pathogens, for which it is necessary to trace disease outbreaks back to their source. Here we discuss the current needs and limitations of classic bacterial taxonomy and introduce LINbase, a Web service that not only implements current species-based bacterial taxonomy but complements its limitations by providing a new framework for genome sequence-based classification and identification independently of the type-centric species. LINbase uses a sequence similarity-based framework to cluster bacteria into hierarchical taxa, which we call LINgroups, at multiple levels of relatedness and crowdsources users' expertise by encouraging them to circumscribe these groups as taxa from the genus-level to the intraspecies-level. Circumscribing a group of bacteria as a LINgroup, adding a phenotypic description, and giving the LINgroup a name using the LINbase Web interface allows users to instantly share new taxa and complements the lengthy and laborious process of publishing a named species. Furthermore, unknown isolates can be identified immediately as members of a newly described LINgroup with fast and precise algorithms based on their genome sequences, allowing species- and intraspecies-level identification. The employed algorithms are based on a combination of the alignment-based algorithm BLASTN and the alignment-free method Sourmash, which is based on k-mers, and the MinHash algorithm. The potential of LINbase is shown by using examples of plant pathogenic bacteria. / Doctor of Philosophy / Life is always easier when people talk to each other in the same language. Taxonomy is the language that biologists use to communicate about life by 1. classifying organisms into groups, 2. giving names to these groups, and 3. identifying individuals as members of these named groups. When most scientists and the general public think of taxonomy, they think of the hierarchical structure of “Life”, “Domain”, “Kingdom”, “Phylum”, “Class”, “Order”, “Family”, “Genus” and “Species”. However, the basic goal of taxonomy is to allow the identification of an organism as a member of a group that is predictive of its characteristics and to provide a name to communicate about that group with other scientists and the public. In the world of micro-organism, taxonomy is extremely important since there are an estimated 10,000,000 to 1,000,000,000 different bacteria species. Moreover, microbiologists and pathologists need to consider differences among bacterial isolates even within the same species, a level, that the current taxonomic system does not even cover. Therefore, we developed a Web service, LINbase, which uses genome sequences to classify individual microbial isolates. The database at the backend of LINbase assigns Life Identification Numbers (LINs) that express how individual microbial isolates are related to each other above, at, and below the species level. The LINbase Web service is designed to be an interactive web-based encyclopedia of microorganisms where users can share everything they know about micro-organisms, be it individual isolates or groups of isolates, for professional and scientific purposes. To develop LINbase, efficient computer programs were developed and implemented. To show how LINbase can be used, several groups of bacteria that cause plant diseases were classified and described.

Muitas relações min-max em otimização combinatória podem ser demonstradas através de total dual integralidade de sistemas lineares. O conceito algébrico de bases de Hilbert foi originalmente introduzido com o objetivo de melhor compreender a estrutura geral dos sistemas totalmente dual integrais. Resultados apresentados posteriormente mostraram que bases de Hilbert também são relevantes para a otimização combinatória em geral e para a caracterização de certas classes de objetos discretos. Entre tais resultados, foram provadas, a partir dessas bases, versões do teorema de Carathéodory para programação inteira. Nesta dissertação, estudamos aspectos estruturais e computacionais de bases de Hilbert e relações destas com programação inteira e otimização combinatória. Em particular, consideramos versões inteiras do teorema de Carathéodory e conjecturas relacionadas. / There are several min-max relations in combinatorial optimization that can be proved through total dual integrality of linear systems. The algebraic concept of Hilbert basis was originally introduced with the objective of better understanding the general structure of totally dual integral systems. Some results that were proved later have shown that Hilbert basis are also relevant to combinatorial optimization in a general manner and to characterize certain classes of discrete objects. Among such results, there are versions of Carathéodory\'s theorem for integer programming that were proved through those basis. In this dissertation, we study structural and computational aspects of Hilbert basis and their relations to integer programming and combinatorial optimization. In particular, we consider integer versions of Carathéodory\'s theorem and related conjectures.

Dans cette thèse, les réseaux coopératifs sont étudiés sous cette hypothèse que la source est incertain par rapport le canal en opération. Dans le premier chapitre, des stratégies coopératives sont développées pour les canaux à relais simultanés (SRC) lesquelles se composent d'un ensemble de deux canaux à relais parmi lesquels le canal en opération est choisi. Cela est équivalent au canal de diffusion à relais (BRC). Les bornes sur la région de capacité de BRC général sont dérivées. Les résultats de capacité sont obtenus pour les cas particuliers du canal à relais simultané semi-dégradé et dégradé Gaussien. Dans le deuxième chapitre, le canal à relais composite est considéré où le canal est tiré aléatoirement d'un ensemble de la distribution conditionnelle. Le débit est fixé en dépit du canal actuel et la probabilité d'erreur (EP) asymptotique est caractérisée. Une nouvelle stratégie de codage sélectif (SCS) est introduit permettant aux relais de choisir -selon leur mesurage du canal – la meilleur schéma de codage entre Décoder-et-Transmettre (DF) et Comprimer-et-Transmettre (CF). Les théorèmes de codage de réseau bruit généralisées sont démontrés pour le cas de réseau unicast général où les relais utilisent soit DF soit CF. Dans le troisième chapitre, le spectre asymptotique de EP est introduit en tant que nouvelle mesure de performance pour réseaux composites. Il est démontré que chaque code avec le débit hors de la borne cut-set, abouti à EP égal à un et le spectre asymptotique de EP coïncide avec la probabilité d'outage pour les réseaux satisfaisant la converse forte. / In this thesis, cooperative networks are studied under the assumption that the source is uncertain about the channel in operation. In the first chapter, cooperative strategies are developed for simultaneous relay channels (SRC) which consist of a set of two single relay channels out of which the channel in operation is chosen. This is equivalent to the broadcast relay channel (BRC). Bounds on the capacity region of the general BRC with two helper relays are derived. Capacity results are obtained for specific cases of semi-degraded and degraded Gaussian simultaneous relay channels. In the second chapter, the composite relay channel is considered where the channel is randomly drawn from a set of conditional distributions according to a given distribution. The transmission rate is fixed regardless of the current channel and the asymptotic error probability (EP) is characterized. A novel selective coding strategy (SCS) is introduced which enables relays to select –based on their channel measurement– the best coding scheme between Compress-and-Forward (CF) and Decode-and-Forward (DF). Generalized Noisy Network Coding theorems are shown for the case of unicast general networks where the relays use either DF or CF scheme. In the third chapter, the asymptotic behavior of EP is studied for composite multiterminal networks. The asymptotic spectrum of EP is introduced as a novel performance measure for composite networks. It is shown that every code with rate outside cut-set bound, yields EP equal to one and for the networks satisfying strong converse condition, the asymptotic spectrum of EP coincides with the outage probability.