The main challenge in studying genetics has evolved from identifying variations and their impact on traits to comprehending the molecular mechanisms through which genetic variations affect human biology, including disease susceptibility. Despite having identified a vast number of variants associated with human traits through large scale genome wide association studies (GWAS) a significant portion of them still lack detailed insights into their underlying mechanisms [1]. Addressing this uncertainty requires the development of precise and scalable approaches to discover how genetic variation precisely influences phenotypes at a molecular level. In this study, we developed a pipeline to automate the annotation of structural variant feature effects. We applied this pipeline to a dataset of 33,942 variants from the ClinVar and GnomAD databases, which included both pathogenic and benign associations. To bridge the gap between genetic variation data and molecular phenotypes, I implemented Non-negative Matrix Factorization (NMF) on this large-scale dataset. This algorithm revealed 6 distinct clusters of variants with similar feature profiles. Among these groups, two exhibited a predominant presence of benign variants (accounting for 70% and 85% of the clusters), while one showed an almost equal distribution of pathogenic and benign variants. The remaining three groups were predominantly composed of pathogenic variants, comprising 68%, 83%, and 77% of the respective clusters. These findings revealed valuable insights into the underlying mechanisms contributing to pathogenicity. Further analysis of this dataset and the exploration of disease-related genes can enhance the accuracy of genetic diagnosis and therapeutic development through the direct inference of variants that are likely to affect the functioning of essential genes.

<p>Synthesis of terrains with complex features has been a challenging problem in computer graphics since most of the existing methods are based on the height field representation. Complex features in terrains adds to the overall realism of the terrain. Hence, there is a need to synthesize terrains in real-time with complex features that adhere to user input. The methodology described in this thesis describes a novel way to synthesize terrains with complex features based on user drawn sketches. Layered stack data structure is used to ensure that the resulting terrain has complex features. Since, Neural Networks are used to generate the terrains, the process is real-time.</p>

Face recognition research using automatic or semi-automatic techniques has emerged over the last two decades. One reason for growing interest in this topic is the wide range of possible applications for face recognition systems. Another reason is the emergence of affordable hardware, supporting digital photography and video, which have made the acquisition of high-quality and high resolution 2D images much more ubiquitous. However, 2D recognition systems are sensitive to subject pose and illumination variations and 3D face recognition which is not directly affected by such environmental changes, could be used alone, or in combination with 2D recognition. Recently with the development of more affordable 3D acquisition systems and the availability of 3D face databases, 3D face recognition has been attracting interest to tackle the limitations in performance of most existing 2D systems. In this research, we introduce a robust automated 3D Face recognition system that implements 3D data of faces with different facial expressions, hair, shoulders, clothing, etc., extracts features for discrimination and uses machine learning techniques to make the final decision. A novel system for automatic processing for 3D facial data has been implemented using multi stage architecture; in a pre-processing and registration stage the data was standardized, spikes were removed, holes were filled and the face area was extracted. Then the nose region, which is relatively more rigid than other facial regions in an anatomical sense, was automatically located and analysed by computing the precise location of the symmetry plane. Then useful facial features and a set of effective 3D curves were extracted. Finally, the recognition and matching stage was implemented by using cascade correlation neural networks and support vector machine for classification, and the nearest neighbour algorithms for matching. It is worth noting that the FRGC data set is the most challenging data set available supporting research on 3D face recognition and machine learning techniques are widely recognised as appropriate and efficient classification methods.

The dissertation is devoted to comparisons in the texts of modern printing. In the work given full structural analysis comparisons, identify the meanings of words in the object position, comparisons are set fixed and variable signs comparative constructions. Identified their stylistic features. / Диссертация посвящена исследованию сравнений в текстах современной печати. В работе дан полный структурный анализ сравнений, определены значения слов в позиции объекта сравнения, установлены постоянные и переменные признаки сравнительной конструкции. Выявлены их стилистические особенности.

The availability of industrial machinery is crucial to any business operating in the manufacturingsector. Mechanical failures halt production and unplanned downtime canbe disruptive and costly. Small failures can compound to serious failures which exponentiallyincreases downtime and repair costs. Therefore Identifying a degradationcondition before reaching failure is key to maintaining machine availability. On theother hand, it’s undesirable to spend resources performing maintenance that is notrequired. For these reasons a large field of academic work is dedicated to analyzingthe health of a machine, it’s remaining life and in turn preventing failures. This thesis analyses data from a tube straightening machine used in the steel industrywith the goal of implementing a condition monitoring strategy. The data comes froma real world application provided by a multinational manufacturer of steel products.It was obtained using the existing sensors and data acquisition system. The projectserves as a study of the existing infrastructure (available sensors) and it’s suitability forimplementing a condition monitoring strategy. The work is the first step in a largerstudy and does not attempt to perform any implementation or fault identification. Ina broad sense the aim of the project is to identify relationships and patterns in the datathat could be varying with time as the machine degrades. The data consists of twelve channels taken over a two week duration. It is prepossessedto isolate periods where the machine is operating and separated into cycles. Each ofthese is then further processed to extract time and frequency domain features. Thefeatures within each channel are compared with each other using the R2 coefficientof determination to find combinations that are correlated. A semi automated processis used to select the feature combinations. The same process is performed betweensignals for each feature. A number of linear regression models are created based on the results from the correlatedfeatures as well as some multivariate models. These are then compared usinga goodness of fit metric, Normalized Root Mean Square Error (NRMSE). Potentialclustering of machine states are highlighted based on observations in the feature combinations.The conclusions drawn from this study include identification of correlationsbetween signals, potential non-linear relationships and suggestions for future data collectionand analysis going forward. No one feature was identified as correlated betweenall signals.

Performance-based contracting (PBC) is an outcome-based product support strategy that provides efficient performance solutions for buyers. Suppliers under performance-based contracting are rewarded after achieving desired performance objectives. While current scholarship has deepened our knowledge of the benefits of PBC, the particular factors behind effective and efficient performance-based contracts (PBCs) are still vague. Thus, this dissertation will focus on essential dimensions for the successful PBC. There remains a great deal that is not understood about the success factors for effective PBCs. When looking at the critical criteria for the selection of suppliers in the context of PBC, even less is known. This dissertation contains three essays with the purpose of: (1) investigating the effect of supply chain collaboration and upfront investments on the benefits of the PBC; (2) exploring supplier selection criteria for successful PBC; and (3) examining the effect of contract length and fleet size on upfront investments for effective and efficient PBC. These three essays offer a solid foundation for theoretical and practitioner understanding for effective PBCs.

Finding if color has an effect on depth perception in virtual reality (VR) is important, as it could be important for e.g. surgeons to perceive the depth correctly if they were to be trained in VR environments as a preparation for surgeries on real patients. If color has an effect on perceived depth in VR then producers of these simulations have to take their color choices into account when creating simulations. Previous research has shown that luminosity and hue can have effects on depth perception. It is also perceived that depth underestimation is prevalent in VR. Discerning if either the color of the focal object or the background is affecting the depth perception is important. Therefore finding what effect different color attributes of a focal object and background has on the depth perception in a VR environment is important. This experimental study examined this through a case study performed in a VR environment built in Unity. The tests were set up to emulate the piercing of a catheter into a plane, where the user pressed a button the moment the plane was pierced. To test different colors of the focal object, in this case a plane, the background was assigned neutral colors (white or black) and while testing the background the plane had a neutral color (white). Results from the study show that colors have a small effect, namely up to 13.2 mm error (for the yellow hue with high luminosity and high saturation), on users’ depth perception in VR. No single attribute was better than another but on the object, blue hue gave the largest error while red hue gave the smallest error. For the background, there was more variation on the data but green and blue hue gave the smallest errors and red and yellow the largest. In sum, color has differing effects on depth perception in VR depending on if the color is applied to a background or an object. Red color gave the most accurate depth perception when applied to the object. For color applied to the background, green hue with high luminosity and blue hue with low luminosity resulted in the most accurate depth perception. / Att ta reda på om färg har en påverkan på djupseende i virtuell verklighet (VR) är viktigt, eftersom det skulle vara viktigt för t.ex. kirurger att uppfatta djupet korrekt om de skulle bli tränade i VR miljöer som en förberedelse inför operationer på riktiga patienter. Om färg har en effekt på upplevd djup i VR, då måste tillverkarna av dessa simulationer ha deras färgval i åtanke när de skapar simulatorerna. Tidigare forskning har visat att ljusintensitet och kulörton kan ha en effekt på djupseende. Det har också upptäckts att djupunderskattning är allmänt förekommande i VR. Att urskilja om antingen färgen på fokusobjektet eller på bakgrunden påverkar djupseendet är viktigt. Således att hitta vilken effekt olika färg attribut av ett fokusobjekt och bakgrund har på djupseendet i en VR miljö. Studien undersökte detta genom en fallstudie i en VR miljö byggd i Unity. Testen var uppbyggda för att efterlikna en kateter som genomtränger ett plan där användaren trycker på en knapp då den trängde igenom planet. För att testa olika färger på fokusobjektet, i detta fall ett plan, blev bakgrunden tilldelad neutrala färger (vit och svart) och när bakgrunden testades var planet tilldelad en neutral färg (vit). Resultaten från studien visar att färg har en liten effekt, upp till 13.2 mm i fel (för den gula kulörtonen med hög ljusintensitet och hög mättnad), på djupseende i VR. Inget enskilt attribut var bättre än ett annat, men på objektet gav blå kulörton det största felet medan röd kulörton gav det minsta felet. För bakgrunden var det mer variation på data men grön och blå kulörton gav de minsta felen och röd och gul gav de största felen. Färgen har olika påverkan på djupseende i VR beroende på om färgen är applicerad på en bakgrund eller ett objekt. Röd färg gav det mest korrekta djupseendet när den var applicerad på objektet. För färg applicerad på bakgrund, resulterade grön kulörton med hög ljusintensitet och blå kulörton med låg ljusintensitet i det mest korrekta djupseendet.

Concepts such as “women’s language” and “men’s language” suggest differences between how men and women speak, often concerning stereotypes. However, some research within the field of linguistics presents evidence showing little or no difference. This study aims to investigate linguistic differences between male and female characters, respectively, in The Office and analyze whether these findings correspond with, or challenge stereotypes associated with “men’s” and “women’s language”. Specifically, the analysis focuses on the lines assigned to the male and the female characters, respectively. The data was retrieved by closely watching eight episodes from two seasons and transcribing the lines spoken by male and female characters. The research methods employed are qualitative conversational analysis (CA) and quantitative content analysis. The results reveal several differences between how the male and the female characters speak in The Office. The female characters’ lines exhibit linguistic features associated with “women’s language” and lines borne out by the male characters are characterized by linguistic features typical of “men’s language”. Furthermore, these differences seem to correspond with stereotypes of gendered language features. In conclusion, the study suggests that the TV show adheres to stereotypes, potentially reinforcing stereotypical characterizations of how men and women speak. Additionally, this study suggests further research in the field of gender and language within TV shows to explore differences and the effects of these.

Det ställs allt större krav på hållbarhet inom fastighetsbranschen vilket leder till att det blir mer aktuellt att nyttja digitala och energieffektiva lösningar för att uppfylla dessa. Begreppet smart byggnad har funnits länge men i takt med en snabb teknisk utveckling ändras vad som anses vara smart och det skiljer sig även åt för vem det berör. Syftet med studien är att undersöka vad en smart byggnad är och hur privatpersoner ställer sig till att köpa en bostadsrätt i en smart byggnad. Därav kommer begreppet smart byggnad först att redas ut i rapporten, både av vad som går att hitta i litteratur och även vad privatpersoner anser att en smart byggnad är. Det kommer även studeras vilka smarta funktioner som finns i en byggnad med bostadsrätter och vilka som är viktiga för privatpersoner vid ett köp av en lägenhet. Till att börja med har en litteraturstudie genomförts för att sedan följas upp av en digital enkätundersökning som riktar sig till privatpersoner. Enkätundersökningen innehåller flervalsfrågor samt ja/nej-frågor som berör smarta bostadsrätter. Respondenterna har delats in i tre kategorier, bostadssökande, bostadssökande som vill köpa bostadsrätt och icke bostadssökande. Resultatet visar att ungefär hälften av respondenterna har hört begreppet smart byggnad, men det varierar vad de tror en smart byggnad är samt vilka funktioner som är viktiga. Majoriteten anser att ett smart säkerhetssystem är den viktigaste smarta funktionen, medan den främsta anledningen till att vilja bo smart är bekvämlighet. Resultatet tyder dock på en bristande kunskap bland privatpersoner om vad en smart byggnad är och många bryr sig inte om att bo smart. / There are increasing demands on sustainability in the real estate industry, which makes it more relevant to use digital and energy-efficient solutions to meet these demands. The concept of smart building has existed for a long time. What is considered smart is changing due to the rapid technological development and varies for whom it affects. The purpose of the study is to investigate what a smart building is and individuals' views on buying a condominium in a smart building. Hence, the concept of smart building will first be sorted out in the report, both what can be found in the literature and what individuals consider a smart building to be. It will also be studied what type of smart features are present in a building with condominiums and which features are important for individuals when buying an apartment. To begin with, a literature study has been done and then followed up by a digital survey aimed at individuals. The survey contains multiple-choice questions as well as yes / no questions that concern smart condominiums. The respondents have been divided into three categories, housing applicants, housing applicants who want to buy a condominium, and non-housing applicants. The study shows that about half of the respondents have heard the term smart building, but it differs from what they think it is and which features are important. The majority believe that a smart security system is the most important smart feature, while the main reason for wanting to live in a smart building is convenience. However, the results indicate a lack of knowledge among the individuals about what a smart building is and that many do not care about living smart.

This research focuses on examining the neurological similarities between schizophrenia and major depressive disorder with psychotic features in order to compare the manifestations of psychosis in each disorder. Both disorders often involve symptoms of psychosis, although the overall disorders are very different from each other. The hypothesis for this research is that the neurological similarities between schizophrenia and major depressive disorder with psychotic features will provide researchers with the strategies needed to develop a treatment for psychotic symptoms. In order to test this hypothesis, five related studies were gathered for each disorder, and three studies were gathered for psychosis. These studies were then analyzed to pinpoint any similarities among factors for psychosis, and this analysis allowed for the determination of whether or not the hypothesis would be rejected. The results indicated that a lot of the similarities between the two disorders cannot be verified because of the lack of substantial research.