Komponentmetoden berör den bokföringsmässiga hanteringen av materiella anläggningstillgångar. I många avseenden kan dessa bestå av olika delar förknippade med olika förbrukningstakt och nyttjandeperioder. Fastigheter är en typisk sådan anläggningstillgång där exempelvis stomme, tak och fasad då utgör sådana komponenter vilka enligt komponentmetoden ska redovisas separat. Företag som tillämpar K3-regelverket behöver förhålla sig till detta. Följande studie fokuserar på redovisning av komponenter utifrån fastighetsförvaltande företag. Studien ämnar undersöka skillnader samt likheter i företagens tillämpning såväl som hur detta förhåller sig mot publicerade vägledningar kring hur metoden kan tillämpas. Likaså söker studien förståelse för vilka implikationer komponentmetoden medför för företagen. Studien utgår från en kvalitativ metod där intervjuer av fyra företag utgör grunden för det empiriska materialet. Vidare har en komparativ multipel fallstudiedesign använts för att uppnå studiens syfte. Resultatet påvisar att komponentmetodens tillämpning är företagsunik och består i många fall av uppskattningar hos respektive företag. Även likheter mellan företag och vägledningar har såväl identifierats. De implikationer som följer beror delvis på hur metoden tillämpas. Ökade avskrivningskostnader, jämnare resultat, en ökning av fastigheternas bokförda värden samt dess påverkan på redovisningens jämförbarhet är dock att betrakta som några av de huvudsakliga konsekvenserna. / Component accounting concerns the accounting management of tangible fixed assets. In many cases, these assets consist of different parts with varying economical and technical lifespans. Real estates are regarded as such assets whereby the building frame, roof and facade could be examples of distinguished components that should be accounted for separately. Swedish companies applying the K3-framework need to manage their accounting accordingly. This study´s focus relates to real estate companies’ application of component accounting. The aim of the study is to investigate differences and similarities between different companies, also in comparison to published guidelines on this topic. Furthermore, the study seeks to understand the implications of component accounting. A qualitative method has been applied where interviews have been conducted with four companies that form the basis of the empirical data. To achieve the purpose of the study a comparative multiple case design has been used.  The results show that component accounting is uniquely applied between companies and is often characterized by estimations. However, similarities between the companies as well as the guidelines do also exist. The implications that follow depend in part on how it´s applied, although increased depreciations, profit smoothing, increased book values and the componentization´s impact on comparability have been found to be some of the main consequences.

Rotylenchulus reniformis is a nematode species affecting the cotton crop and quickly spreading throughout the southeastern United States. Effective use of nematicides at a variable rate is the only economic counter measure. It requires the intraield variable nematode population, which in turn depends on the collection of soil samples from the field and analyzing them in the laboratory. This process is economically prohibitive. Hence estimating the nematode infestation on the cotton crop using remote sensing and machine learning techniques which are cost and time effective is the motivation for this study. In the current research, the concept of multi-temporal remote sensing has been implemented in order to design a robust and generalized Nematode detection regression model. Finally, a user friendly web-service is created which is gives trustworthy results for the given input data and thereby reducing the nematode infestation in the crop and their expenses on nematicides.

Polymicrobial communities of bacterial and fungal species are present on the skin and mucosal surfaces of the body. Invasive infections caused by Candida species are commonly seen in immunocompromised individuals (HIV, transplants, cancer) and ranks as the third leading cause of infection in hospitalized patients. C. albicans is a polymorphic opportunistic fungus that infects critically ill patients and has the ability to change its morphology from yeast to hyphal form.The morphogenesis of C. albicans is a major aspect of its virulence and is regulated by quorum sensing (QS) molecules they produce, as well as the presence of neighboring microbes.In this study, we examined two transporter mutants, cdr4 and ssu1, for their ability to form biofilms in the presence of cyclic-di-GMP and 3-oxo-12-homoserine lactone. To quantify biomass, wild type and mutant cells were grown overnight at 30˚C in YPD. The cells were washed, counted and diluted to a desired density of 106 cells/ml in medium 199, pH7.5. Cells were added to 96-well plates pre-incubated with 5% fetal bovine serum at densities of 105, 104, and 103 cells/well and allowed to adhere at 37˚C for one hour. The wells were then covered with fresh M199 media containing the QS molecule and monitored for 48 hours at 37˚C. After this time, the media and planktonic cells were removed. The biofilms were fixed with methanol, dried, then stained with 0.05% crystal violet. Bulk biomass was assessed by spectrophotometry. We did observe a difference in biofilm density when incubated in the presence of cyclic-diGMP. We noted that for the wild type and ssu1 strain their biofilms biomass increased by as much as 10% at 104 and 103 cell densities when compared with the control. While the cdr4 strain had a slight reduction in biofilm density when cyclic-diGMP was present. This result also indicates a potentially positive role in which cyclic-diGMP can help C. albicans develop denser biofilms, potentially in the presence of bacteria like P. aeruginsa, which secrete cyclic di-GMP, but kill hyphal forms of C. albicans. Additionally, it has been shown that C. albicans mutants lacking the hybrid histidine kinase, Chk1p, are refractory to the effects of farnesol, a QS molecule that inhibits morphogenesis.Given that mutations in CDR4 and SSU1 impact the QS response in C. albicans, we investigated whether these genes were regulated through two-component signaling by Chk1. To assess CDR4 and SSU1 expression, wild type and mutant strains were grown overnight in YPD media at 30˚C. Cells were then harvested and RNA was obtained by acid phenol extraction. Using RT-PCR, we determined both CDR4 and SSU1 expression is reduced or highly repressed in the chk1, ypd1, and skn7 null strains. These results suggest the two genes are downstream targets in a pathway regulated by Chk1p. The finding that QS proceeds through a two-component pathway can be exploited in antifungal drug development. Given that two-component signaling is absent in mammalian cells, development of novel compounds that interfere with this pathway may be a useful alternative for treating patients with candidiasis.

In order to model check a software component which is not a standalone program, we need a model of the software which completes the program. This problem is important for software engineers who need to deploy an existing component into a new environment. The model is typically generated by abstracting the surrounding software environment in which the component will be executed. However, abstracting the surrounding software is a difficult and error-prone task, particularly when the surrounding software is a complex software artifact which can not be easily abstracted. In this dissertation, we present a new approach to the problem by abstracting the software component under test and leaving the surrounding software concrete. We derive this abstract-concrete mixed model automatically for both sequential and concurrent C programs and verify them using the SPIN model checker. We give verification results for several components under test contained within complex software environments to demonstrate the strengths and weaknesses of our approach. We are able to find errors in components which were too complex for analysis by existing model checking techniques. We prove that this mixed abstract-concrete model can be bisimilar to the original complete software system using an abstraction refinement scheme. We then show how to generate test cases for the component under test using this abstraction refinement process.

The PstSCAB2 complex serves the dual function of being a phosphate transporter as well as the primary sensor of phosphate for the Pho regulon. PhoU is an integral protein required for the signal from PstSCAB2 to be transmitted to PhoR. Our hypothesis is that conformational changes of PstSCAB2 during the phosphate transport process are the mechanism by which information about environmental phosphate levels are transduced to the cell. Additionally, we propose that direct protein-protein interactions between PhoU and the alternating conformations of PstSCAB2 mediate PhoU interactions with PhoR. By means of genetic and biochemical approaches, we have found substantial evidence supporting both these hypotheses.

Background: Movement screens are frequently used to identify abnormal movement patterns that may increase risk of injury and/or hinder performance. However, abnormal patterns are often detected visually based on the observations of a coach or clinician leading to poor inter- and intrarater reliability. In addition, they have been criticized for having poor validity and sensitivity. Quantitative, or data-driven methods can increase objectivity, remove issues related to inter-rater reliability and offer the potential to detect new and important features that may not be observable by the human eye. The combination of motion capture data, pattern recognition and machine learning could provide a quantitative method to better assess movement competency. Purpose: The purpose of this doctoral thesis was to create the foundation for the development of an objective movement screening tool that combines motion capture data, pattern recognition and machine learning. This doctoral thesis is part of a larger project to bring an objective movement screening tool for use in the field to market. Methods: This thesis is comprised of four studies based on a single data collection and a common series of pre-processing steps. Data from 542 athletes were collected by Motus Global, a for-profit biomechanics company, with athletes ranging in competition level from youth to professional and competing in a wide-range of sports. For the first study of this thesis, an online software program was developed to examine the inter- and intra-reliability of a movement screen, with intrareliability being further examined to compare reliability when body-shape was and was not modified. The second study developed the objective movement screen framework that utilized motion capture, pattern recognition and machine learning. Study 3 and 4 assessed different types of input data, classification goals (e.g., skill level and sport played), feature reduction and selection methods, and increasingly complex machine learning algorithms. Results: For Study 1, when looking at inter- and intra-rater reliability of expert assessors during subjective scoring of movements, intra-rater reliability was better than inter-rater reliability. When assessing the effects of body-shape, on average, reliability worsened when body-shape was manipulated. Study 2 provided proof-of-principle that athletes were able to be classified based on skill level using marker-based optical motion capture data, principal component analysis (PCA) and linear discriminant analysis. For Study 3, PCA in combination with linear classifiers outperformed non-linear classifiers when classifying athletes based on skill level; feature selection increased classification rates, and classification rates when using simulated inertial measurement unit data as the input data were on average better than when using marker-based optical motion capture data. In Study 4, athletes were able to be differentiated based on sport played and recurrent neural nets (RNNs) and PCA in combination with traditional linear classifiers were the optimal machine learning algorithms when classifying athletes based on skill level and sport played. Conclusion: This thesis demonstrates that objective methods can differentiate athletes based on desired demographics using motion capture, pattern recognition and machine learning. This thesis is part of a larger project to bring an objective movement screening tool for field-use to market and provides a solid foundation to use in the continued development of an objective movement screening tool.

Forensic fiber evidence plays an important role in many criminal investigations. Nondestructive techniques that preserve the physical integrity of the fibers for further court examination are highly valuable in forensic science. Non-destructive techniques that can either discriminate between similar fibers or match a known to a questioned fiber - and still preserve the physical integrity of the fibers for further court examination - are highly valuable in forensic science. When fibers cannot be discriminated by non-destructive tests, the next reasonable step is to extract the questioned and known fibers for dye analysis with a more selective technique such as high-performance liquid chromatography (HPLC) and/or gas chromatography-mass spectrometry (GC-MS). The common denominator among chromatographic techniques is to primarily focus on the dyes used to color the fibers and do not investigate other potential discriminating components present on the fiber. Differentiating among commercial dyes with very similar chromatographic behaviors and almost identical absorption spectra and/or fragmentation patterns is a challenging task. This dissertation explores a different aspect of fiber analysis as it focuses on the total fluorescence emission of fibers. In addition to the contribution of the textile dye (or dyes) to the fluorescence spectrum of the fiber, we investigate the contribution of intrinsic fluorescence impurities – i.e. impurities imbedded into the fibers during fabrication of garments - as a reproducible source of fiber comparison. Differentiation of visually indistinguishable fibers is achieved by comparing excitation-emission matrices (EEMs) recorded from single textile fibers with the aid of a commercial spectrofluorimeter coupled to an epi-fluorescence microscope. Statistical data comparison was carried out via principal component analysis. An application of iv this statistical approach is demonstrated using challenging dyes with similarities both in twodimensional absorbance spectra and in three dimensional EEM data. High accuracy of fiber identification was observed in all the cases and no false positive identifications were observed at 99% confidence levels.

This bachelor thesis examines design implementation and differences between game entity systems, with a focus on a component-based structure. How each will affect the other will be discussed from both a technical and design point of view, including possible drawbacks or advantages regarding game design iteration and performance. Since the focus is on component-based entity systems, a clarification on traditional entity systems are required, thus this thesis focuses on entity systems that are traditional, property-based, container-based, and aggravated component-based. The design and implementation of each system was founded from different generations of programming paradigms which resulted in specific compositional structure based on each specific era of hardware configuration. This thesis analyses the progress of hardware alongside game entity system design to further understand its progression and evolution into today’s standards and implementation. Details on each system is provided from a design perspective for the traditional entity system and with an in-depth view for the component-based entity systems.

Yes / The usage of AI-empowered Industrial Robots (InRos) is booming in the Auto Component Manufacturing Companies (ACMCs) across the globe. Based on a model leveraging the Technology, Organisation, and Environment (TOE) framework, this work examines the adoption of InRos in ACMCs in the context of an emerging economy. This research scrutinizes the adoption intention and potential use of InRos in ACMCs through a survey of 460 senior managers and owners of ACMCs in India. The findings indicate that perceived compatibility, external pressure, perceived benefits and support from vendors are critical predictors of InRos adoption intention. Interestingly, the study also reveals that IT infrastructure and government support do not influence InRos adoption intention. Furthermore, the analysis suggests that perceived cost issues negatively moderate the relationship between the adoption intention and potential use of InRos in ACMCs. This study offers a theoretical contribution as it deploys the traditional TOE framework and discovers counter-intuitively that IT resources are not a major driver of technology adoption: as such, it suggests that a more comprehensive framework than the traditional RBV should be adopted. The work provides managerial recommendations for managers, shedding light on the antecedents of adoption intention and potential use of InRos at ACMCs in a country where the adoption of InRos is in a nascent stage.

No / Advances in micromoulding technology are leading to complex,net-shape products having sub-milligramme masses with micro-scale surface features in a range of polymer and nano-composite materials.For such small components subjected to the extreme stress,strain-rate and temperature gradients encountered in the micromoulding process,detailed process monitoring is desirable to highlight variations in moulding conditions and assist in creating a viable manufacturing process with acceptable quality products.This paper covers the implementation of a suite of sensors on a commercial micromoulding machine and detailed computer monitoring during processing of a polyacetal component over a range of processing conditions.The results determined that cavity pressure curve integral data provides the most sensitive factor for characterisation of a moulding process of a 0.34 mm~3(0.49 mg)product.The repeatability of the process is directly compared with that of a 15.6mm~3(22.2 mg)product and shown to beinferior.DSC measurements of the whole products indicated little variation in average crystallinity of the products manufactured over a mould temperature range of 30 to 130deg C.