24 resultados para LINEAR ALPHA-OLEFINS


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Actin stress fibers are dynamic structures in the cytoskeleton, which respond to mechanical stimuli and affect cell motility, adhesion and invasion of cancer cells. In nonmuscle cells, stress fibers have been subcategorized to three distinct stress fiber types: dorsal and ventral stress fibers and transverse arcs. These stress fibers are dissimilar in their subcellular localization, connection to substratum as well as in their dynamics and assembly mechanisms. Still uncharacterized is how they differ in their function and molecular composition. Here, I have studied involvement of nonmuscle alpha-actinin-1 and -4 in regulating distinct stress fibers as well as their localization and function in human U2OS osteosarcoma cells. Except for the correlation of upregulation of alpha-actinin-4 in invasive cancer types very little is known about whether these two actinins are redundant or have specific roles. The availability of highly specific alpha-actinin-1 antibody generated in the lab, revealed localization of alpha-actinin-1 along all three categories of stress fibers while alphaactinin-4 was detected at cell edge, distal ends of stress fibers as well as perinuclear regions. Strikingly, by utilizing RNAi-mediated gene silencing of alpha-actinin-1 resulted in specific loss of dorsal stress fibers and relocalization of alpha-actinin-4 to remaining transverse arcs and ventral stress fibers. Unexpectedly, aberrant migration was not detected in cells lacking alpha-actinin-1 even though focal adhesions were significantly smaller and fewer. Whereas, silencing of alpha-actinin-4 noticeably affected overall cell migration. In summary, as part of my master thesis study I have been able to demonstrate distinct localization and functional patterns for both alpha-actinin-1 and -4. I have identified alpha-actinin-1 to be a selective dorsal stress fiber crosslinking protein as well as to be required for focal adhesion maturation, while alpha-actinin-4 was demonstrated to be fundamental for cell migration.

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This paper examines how volatility in financial markets can preferable be modeled. The examination investigates how good the models for the volatility, both linear and nonlinear, are in absorbing skewness and kurtosis. The examination is done on the Nordic stock markets, including Finland, Sweden, Norway and Denmark. Different linear and nonlinear models are applied, and the results indicates that a linear model can almost always be used for modeling the series under investigation, even though nonlinear models performs slightly better in some cases. These results indicate that the markets under study are exposed to asymmetric patterns only to a certain degree. Negative shocks generally have a more prominent effect on the markets, but these effects are not really strong. However, in terms of absorbing skewness and kurtosis, nonlinear models outperform linear ones.

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In a max-min LP, the objective is to maximise ω subject to Ax ≤ 1, Cx ≥ ω1, and x ≥ 0 for nonnegative matrices A and C. We present a local algorithm (constant-time distributed algorithm) for approximating max-min LPs. The approximation ratio of our algorithm is the best possible for any local algorithm; there is a matching unconditional lower bound.

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In a max-min LP, the objective is to maximise ω subject to Ax ≤ 1, Cx ≥ ω1, and x ≥ 0. In a min-max LP, the objective is to minimise ρ subject to Ax ≤ ρ1, Cx ≥ 1, and x ≥ 0. The matrices A and C are nonnegative and sparse: each row ai of A has at most ΔI positive elements, and each row ck of C has at most ΔK positive elements. We study the approximability of max-min LPs and min-max LPs in a distributed setting; in particular, we focus on local algorithms (constant-time distributed algorithms). We show that for any ΔI ≥ 2, ΔK ≥ 2, and ε > 0 there exists a local algorithm that achieves the approximation ratio ΔI (1 − 1/ΔK) + ε. We also show that this result is the best possible: no local algorithm can achieve the approximation ratio ΔI (1 − 1/ΔK) for any ΔI ≥ 2 and ΔK ≥ 2.

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A new classification and linear sequence of the gymnosperms based on previous molecular and morphological phylogenetic and other studies is presented. Currently accepted genera are listed for each family and arranged according to their (probable) phylogenetic position. A full synonymy is provided, and types are listed for accepted genera. An index to genera assists in easy access to synonymy and family placement of genera.

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Throughout the history of the classification of extant ferns (monilophytes) and lycophytes, familial and generic concepts have been in great flux. For the organisation of lycophytes and ferns in herbaria, books, checklists, indices and spore banks and on the internet, this poses a problem, and a standardized linear sequence of these plants is therefore in great need. We provide here a linear classification to the extant lycophytes and ferns based on current phylogenetic knowledge; this provides a standardized guide for organisation of fern collections into a more natural sequence. Two new families, Diplaziopsidaceae and Rhachidosoraceae, are here introduced.

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This study addresses the challenge of analyzing interruption in spoken interaction. It begins with my observation of eight hours of academic group work among speakers of English as a lingua franca (ELF) in a university course. Unlike the common findings of ELF research which underscore the cooperative orientation of ELF users, this particular group gave strong impressions of interruption and uncooperativeness as they prepared a scientific group presentation. In the effort to investigate these impressions, I found that no satisfactory method exists for systematically identifying and analyzing interruptions. A useful tool was found in Linear Unit Grammar or LUG (Sinclair & Mauranen 2006), which analyzes spoken interaction prospectively as linear text. In the course of transcribing one of the early group work meetings, I developed a model of LUG-based criteria for identifying individual instances of interruption. With this system in place, I was then able to evaluate the aggregate occurrences of interruption in the group work and identify co-occurring interactive features which further influenced the perception of uncooperativeness. Finally, these aggregate statistics directed a return to the data and a contextually sensitive, qualitative analysis. This research cycle illuminates the interactive features which contributed to my own impressions of uncooperativeness, as well as the group members orientations to their own interruptive practice.