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DC currents that flow through the ground can be injected to the star windings of power transformers from their grounded neutral points and close their path with transmission lines. The geomagnetically induced currents (GICs) and AC/DC convertors of high voltage direct current (HVDC) systems are the sources of such DC currents. These currents may cause saturation of the core in power transformers that leads to destruction in the transformer performance. This phenomenon results in unwanted influences on power transformers and the power system. Very asymmetric magnetization current, increasing losses and creation of hot spots in the core, in the windings, and the metallic structural parts are adverse effects that occur in transformers. Also, increasing demand of reactive power and misoperation of protective relays menaces the power network. Damages in large power transformers and blackouts in networks have occurred due to this phenomenon Hence, studies regarding this subject have taken the attention of researchers during the last decades. However, a gap of a comprehensive analysis still remains. Thus, the main aim of this project is to reach to a deep understanding of the phenomena and to come up with a solution for a decrease of the undesired effects of GIC. Achieving this goal requires an improvement of the electromagnetic models of transformers which include a hysteresis model, numerical techniques, and transient analysis. In this project until now, a new algorithm for digital measurement of the core materials is developed and implemented. It enhances the abilities of accurate measurements and an improved hysteresis model has been worked out. Also, a novel differential scalar hysteresis model is suggested that easily can be implemented in numerical methods. Three dimensional finite element models of various core types of power transformers are created to study the effect on them due to DC magnetization. In order to enhance the numerical tools for analysis of low frequency transients related to power transformers and the network, a distributed reluctance network method has been outlined. In this thesis a method for solving such a network problem with coupling to an electrical circuit and taking hysteresis into account is suggested. / <p>QC 20121121</p>

A consensus exists in the body of academic literature that stocks with high BE/ME characteristics outperform stocks with low BE/ME characteristics. Researchers disagree, however, as to the cause of the phenomenon. Two competing theories have emerged. The value premium originates either from the relative riskiness of high BE/ME value and low BE/ME growth stocks or from the persistent irrational pricing of those stocks. Market participants question whether the long lineage of academic research showing the existence of the value premium can actually be applied to their portfolio decision-making. The lack of a pervasive value premium across stock size strata suggests the return phenomenon may result from information asymmetry or trading noise, and not from the pricing of greater risk. The value premium appears to be exclusively available to market participants who can effectively navigate the smallest, most illiquid segment of the stock market. In other words, the value premium does not appear to be available to large institutional investors.

Pour améliorer les performances des batteries au lithium, des ruptures technologiques sont nécessaires. Ceci impose que les aspects fondamentaux liés au fonctionnement de ces dispositifs électroniques soient reconsidérés. Dans cette optique, les méthodes de la chimie quantique peuvent apporter une aide précieuse, notamment pour comprendre les phénomènes électroniques microscopiques, à l'origine du stockage de l'énergie. Établir une relation directe entre la nature de la liaison chimique (microscopique) et les propriétés physico-chimiques (macroscopiques) des matériaux d'électrode pour batteries Li-Ion est donc l'objectif dans lequel s'inscrivent les travaux exposés dans cette thèse. Ce travail explore à la fois des aspects méthodologiques et des applications. Il vise à proposer des méthodologies d'analyse simples permettant de traiter les réactions électrochimiques d'un point de vue théorique et de déterminer les mécanismes microscopiques mis en jeu au cours des cycles de charge et de décharge des batteries. Les systèmes étudiés sont les composés d'insertion du graphite (Li-GICs) et un matériau hybride de type MOFs (« Metal Organic Framework ») basé sur l'ion ferrique (MIL-53(Fe)). Pour les Li-GICs, une nouvelle méthode couplant des calculs premiers principes DFT à un modèle statistique dérivé du modèle de Bethe-Peierls a été développée pour rendre compte des effets d'entropie (de configuration) dans leur diagramme de phase. Les résultats obtenus apportent un nouveau regard sur les processus électrochimiques induits par le lithium, ouvrant des perspectives technologiques intéressantes pour remédier aux problèmes de sécurité posés par ce type d'électrode. Pour le MIL-53(Fe), la méthode DFT+U a été utilisée pour rendre compte des effets de corrélation électronique et pour reproduire l'état fondamental complexe de ce système. Les résultats obtenus ont permis de comprendre l'origine de la faible capacité de ce matériau vis-`a-vis du lithium.

Geomagnetic disturbances that result from solar activities can affect technological systems such as power networks. They may cause DC currents in power networks and saturation of the core in power transformers that leads to destruction in the transformer performance. This phenomena result in unwanted influences on power transformers and the power system. Very asymmetric magnetization current, increasing losses and creation of hot spots in the core, in the windings, and the metallic structural parts are adverse effects that occur in transformers. Also, increasing demand of reactive power and malfunction of protective relays menaces the power network stability. Damages in large power transformers and blackouts in networks have occurred due to this phenomenon. Hence, studies regarding this subject have taken the attention of researchers during the last decades. However, a gap of a comprehensive analysis still remains. Thus, the main aim of this project is to reach to a deep understanding of the phenomena and to come up with a solution for a decrease of the undesired effects of GIC. Achieving this goal requires an improvement of the electromagnetic models of transformers which include a hysteresis model, numerical techniques, and transient analysis. In this project, a new algorithm for digital measurement of the magnetic materials is developed and implemented. It enhances the abilities of accurate measurements and an improved hysteresis model has been worked out. Also, a novel differential scalar hysteresis model is suggested that easily can be implemented in numerical methods. Two and three dimensional finite element models of various core types of power transformers are created to study the effect of DC magnetization on transformers. In order to enhance the numerical tools for analysis of low frequency transients related to power transformers and the network, a novel topological based time step transformer model has been outlined. The model can employ a detailed magnetic circuit and consider nonlinearity, hysteresis and eddy current effects of power transformers. Furthermore, the proposed model can be used in the design process of transformers and even extend other application such as analysis of electrical machines. The numerical and experimental studies in this project lead to understanding the mechanism that a geomantic disturbance affects power transformers and networks. The revealed results conclude with proposals for mitigation strategies against these phenomena. / <p>QC 20150210</p>

Insulin like Growth Factor Binding Proteins (IGFBPs) 1 to 6 have important physiological functions of regulating half life and bioavailability of Insulin like Growth Factors (IGFs). Consequently, these have been known to play important roles in embryonic development, postnatal growth and disease conditions like cancer. However, the physiological roles of IGFBPs are diverse and not restricted only to the IGF regulation. These molecules are found to be tumor suppressors or promoters depending on the physiological contexts. IGFBP-2 has been established as a tumor promoter and found to be unregulated in several cancers including breast, ovarian, prostate cancer and glioblastoma (GBM). Various in vitro and in vivo studies have convincingly demonstrated the role of IGFBP-2 in inducing tumor cell proliferation, migration, invasion and chemoresistance. Increased plasma and tissue levels of IGFBP-2 have been associated with poor clinical outcome with respect to patients’ response to the therapy, relapse and overall survival. Various studies so far have demonstrated the role of IGFBP-2 in promoting glioma cell proliferation, migration, invasion, chemoresistance and determining stamens of GICs (Glioma Initiating Cells). However, the exact mechanisms underlying these functions remain unknown. Apart from being a diagnostic and prognostic indicator, IGFBP-2 has also been proposed as a therapeutic target. Therefore it is essential to understand mechanistic insights into pro-tumorigenic functions of IGFBP-2. Apart from the conventional function of regulating IGFs, IGFBP-2 has been shown to have several IGF independent functions. In a previous study, we reported IGFBP-2 as an upstream regulator of β-catenin signaling pathway in breast cancer. Interestingly, this study linked the association of higher expression of IGFBP-2 and β-catenin with the lymph node metastasis status of breast cancer. β-catenin signaling has been considered as one of the most important pro-tumorigenic pathways in several cancers including glioblastoma. Considering the importance of IGFBP-2 and β-catenin signaling pathways in glioblastoma, it becomes important to evaluate regulation of β-catenin activity by IGFBP-2 in glioma and address its clinical relevance. With this aim, the objectives of this study are,  To study mechanism of IGFBP-2 mediated regulation of β-catenin signaling in glioma cells and prognostic significance of IGFBP-2 and β-catenin expression in GBM tissues.  Isolation of human single chain variable fragment (scFv) against IGFBP-2 and its characterization as an inhibitor for IGFBP-2 pro-tumorigenic functions. Towards this, we established stable IGFBP-2 knockdown U251 cell line and IGFBP-2 over expressing LN229 and U87 cell lines. IGFBP-2 modulation in these glioma cell lines did not alter the rate of proliferation but there was a significant effect on cellular migration and invasion. In case of U251 cell line, there was a significant decrease in the intracellular levels of β-catenin while in IGFBP-2 over expressing cell lines there was a marked increase in intracellular β-catenin suggesting that IGFBP-2 is involved in the regulation of β-catenin in these cells. It was observed that this regulation of β-catenin was not because of its transcriptional regulation or regulation of canonical Wnt ligands Wnt1, Wnt2 and Wnt3a. To further delineate the pathway and understand the mechanism behind regulation of β-catenin, upstream regulators of β-catenin were analyzed. GSK3β is an important negative regulator of β-catenin which primes it for ubiquitination and proteasomal degradation. Phosphorylation of GSK3β at Ser9 position renders this enzyme inactive. In our study, it was observed that there was a significant downregulation of p-GSK3β in U251 cells with IGFBP-2 knockdown and upregulation in IGFBP-2 over expressing cell lines. Overexpression of IGFBP-2 in LN229 and U87 cell lines resulted in considerable decrease in the GSK3β mediated phosphorylation of β-catenin. This study unequivocally established that regulation of β-catenin by IGFBP-2 is via inactivation of GSK3β. Furthermore, regulation of GSK3β was found to be due to action of FAK following binding of IGFBP-2 to integrins. The expression pattern of IGFBP-2 and β-catenin protein in the tumor tissues of 112 GBM patients was studied and its correlation with patient survival was analysed. In this analysis it was observed that co-expression of IGFBP-2 and β-catenin is a strong predictor of patient prognosis. These results further implied the importance of understanding IGFBP-2 and β-catenin association in GBM pathology. One of the interesting observations in our study is that, not only full length IGFBP-2 protein but also C-terminal domain of IGFBP-2 was sufficient to regulate β-catenin and other IGFBP-2 mediated functions. This strongly asserts the importance of C-terminal region of IGFBP-2 as a tumor promoter. Towards an attempt to develop an inhibitor for IGFBP-2 actions, we screened a human single chain variable fragment (scFv) library using phage display technique. From this screening, one scFv (B7J) was identified which was a binder of full length IGFBP-2 as well as C-terminal domain of IGFBP-2. This scFv showed inhibition of IGFBP-2-cell surface interaction and also efficiently inhibited IGFBP-2-induced signaling pathways like ERK, FAK and GSK3β/β-catenin. B7J treatment also neutralized regulation of IGFBP-2 transcriptional targets like MMP2 and CD24. Gelatin zymography indicated the ability of B7J to decrease matrix metalloprotease activity in the conditioned medium of glioma cells. These effects ultimately reflected on the IGFBP-2-induced cellular migratory and invasive behaviour which was largely abrogated by B7J scFv treatment. Considering the therapeutic importance of scFvs because of their small size, better tumor penetration and tumor retention capacity than full length antibody molecules, such kind of strategy could be of great importance in the management of GBM. Altogether, this study provides a mechanistic insight of IGFBP-2 mediated actions involving integrin/FAK/GSK3β/β-catenin pathways and the possible role of this crosstalk in the aggressiveness of glioblastoma. This study also provides a proof of principle that an inhibitor like anti IGFBP-2 scFv could be of importance for controlling invasive glioblastoma.

Sustainable business has become highly sought after today by stakeholders, which explains the importance of CSR for companies. Companies are required to work sustainably in order to legitimize themselves both in the market and society. This can be done by fulfilling and satisfying the economic, environmental and sustainable, as well as the social frameworks that exist in business society. Despite CSR's central role in companies, researchers have differentiated meanings on whether CSR initiatives really improve corporate profitability in terms of financial performance, and whether it has a positive relationship with corporate value. Regarding this, the report examines CSR's relationship to CFP and company value, through the profitability measures ROA and ROE, as well as the valuation measures market value and P/E ratio. A quantitative method has been applied to examine the companies published on Dagens Industri's sustainability index for the year 2021. Dagens Industri's list includes the largest listed companies in the GICS categories on the Swedish stock market exchange. The study uses regression analysis as a choice of statistical analysis method to examine the variables relationships. From the regressions, a small part of the result showed a weak negative relationship between CSR and ROA. The regressions otherwise mainly showed a non-significant relationship between CSR and a company's profitability and value. The variables do not have a significant relationship with each other, and a neutral relationship between them can thus be demonstrated. The existing research gap is therefore still ambiguous, hence the room for further future studies in the field.

Factor models attribute stock returns to a linear combination of factors. A model with great explanatory power (R2) can be used to estimate the systematic risk of an investment. One of the most important factors is the industry which the company of the stock operates in. In commercial risk models this factor is often determined with a manually constructed stock classification scheme such as GICS. We present Natural Language Industry Scheme (NLIS), an automatic and multivalued classification scheme based on topic modeling. The topic modeling is performed on transcripts of company earnings calls and identifies a number of topics analogous to industries. We use non-negative matrix factorization (NMF) on a term-document matrix of the transcripts to perform the topic modeling. When set to explain returns of the MSCI USA index we find that NLIS consistently outperforms GICS, often by several hundred basis points. We attribute this to NLIS’ ability to assign a stock to multiple industries. We also suggest that the proportions of industry assignments for a given stock could correspond to expected future revenue sources rather than current revenue sources. This property could explain some of NLIS’ success since it closely relates to theoretical stock pricing. / Faktormodeller förklarar aktieprisrörelser med en linjär kombination av faktorer. En modell med hög förklaringsgrad (R2) kan användas föratt skatta en investerings systematiska risk. En av de viktigaste faktorerna är aktiebolagets industritillhörighet. I kommersiella risksystem bestäms industri oftast med ett aktieklassifikationsschema som GICS, publicerat av ett finansiellt institut. Vi presenterar Natural Language Industry Scheme (NLIS), ett automatiskt klassifikationsschema baserat på topic modeling. Vi utför topic modeling på transkript av aktiebolags investerarsamtal. Detta identifierar ämnen, eller topics, som är jämförbara med industrier. Topic modeling sker genom icke-negativmatrisfaktorisering (NMF) på en ord-dokumentmatris av transkripten. När NLIS används för att förklara prisrörelser hos MSCI USA-indexet finner vi att NLIS överträffar GICS, ofta med 2-3 procent. Detta tillskriver vi NLIS förmåga att ge flera industritillhörigheter åt samma aktie. Vi föreslår också att proportionerna hos industritillhörigheterna för en aktie kan motsvara förväntade inkomstkällor snarare än nuvarande inkomstkällor. Denna egenskap kan också vara en anledning till NLIS framgång då den nära relaterar till teoretisk aktieprissättning.