998 resultados para SIGMA-TERM


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Human skin fibroblasts were cultured long-term in the presence of ascorbic acid to allow formation of a three-dimensional collagen matrix, and the effects of this on activation of secreted matrix metalloproteinase-2 (MMP-2) were examined. Accumulation of collagen over time correlated with increased levels of both mature MMP-2 and cell-associated membrane type 1-MMP (MT1-MMP), and subsequently increased mRNA levels for MT1-MMP, providing temporal resolution of the "nontranscriptional" and "transcriptional" effects of collagen on MT-1MMP functionality. MMP-2 activation by these cultures was blocked by inhibitors of prolyl-4-hydroxylase, or when fibroblasts derived from the collagen α1(I) gene-deficient Mov-13 mouse were used. MMP-2 activation by the Mov-13 fibroblasts was rescued by transfection of a full-length α1(I) collagen cDNA, and to our surprise, also by transfection with an α1(I) collagen cDNA carrying a mutation at the C-proteinase cleavage, which almost abrogated fibrillogenesis. Although studies with ascorbate-cultured MT1-MMP-/- fibroblasts showed that MT1-MMP played a significant role in the collagen-induced MMP-2 activation, a residual MT1-MMP-independent activation of MMP-2 was seen which resembled the level of MMP-2 activation persisting when wild-type fibroblasts were cultured in the presence of both ascorbic acid and MMP inhibitors. We were also unable to block this residual activation with inhibitors specific for serinyl, aspartyl, or cysteinyl enzymes.

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OBJECTIVE Although the survival outcomes among women diagnosed with endometrial cancer are very favorable, little is known about the long-term impact of their cancer experience. This study identifies the extent of positive and negative impacts of cancer and factors associated with this, amongst long-term survivors of endometrial cancer. METHODS Australian women diagnosed with endometrial cancer (N=632) were sent questionnaires at the time of diagnosis and 3-5 years later. Hierarchical multiple regression models were used to examine whether a range of variables at diagnosis/treatment predicted subsequent scores on the Impact of Cancer Scale, which examines positive (e.g. health awareness) and negative (e.g. appearance concerns) impacts amongst cancer survivors. RESULTS Overall, women had a higher mean score for the positive than negative impact scales (M=3.5 versus M=2.5, respectively). An intermediate grade of endometrial cancer, a prior diagnosis of cancer and lower levels of education were significant, but weak, predictors of higher scores on the positive impact scale. Higher scores on the negative impact scale were predicted by a higher grade of cancer, poor physical and mental health, a younger age, being single or having lower levels of education. CONCLUSIONS The study demonstrates that factors that predict positive impact in cancer survivors differ to those that predict negative impact, suggesting that interventions to optimize cancer survivors' quality of life will need to be multi-dimensional, and this supports the need for tailored intervention.

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This paper describes and analyzes research on the dynamics of long-term care and the policy relevance of identifying the sources of persistence in caregiving arrangements (including the effect of dynamics on parameter estimates, implications for family welfare, parent welfare, child welfare, and cost of government programs). We discuss sources and causes of observed persistence in caregiving arrangements including inertia/state dependence (confounded by unobserved heterogeneity) and costs of changing caregivers. We comment on causes of dynamics including learning/human capital accumulation; burnout; and game-playing. We suggest how to deal with endogenous geography; dynamics in discrete and continuous choices; and equilibrium issues (multiple equilibria, dynamic equilibria). We also present an overview of commonly used longitudinal data sets and evaluate their relative advantages/disadvantages. We also discuss other data issues related to noisy measures of wealth and family structure. Finally, we suggest some methods to handle econometric problems such as endogeneous geography. © 2014 Springer Science+Business Media New York.

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This paper describes a strategic model of bargaining within a family to determine how to care for an elderly parent. We estimate the parameters of the model using data from the National Long-term Care Survey. We find that the parameter estimates generally make sense and that the model is consistent with the data. The results have strong implications for using less structural empirical models for policy analysis.

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We present a structural model of how families decide who should care for elderly parents. We use data from the National Long-Term Care Survey to estimate and test the parameters of the model. Then we use the parameter estimates to simulate the effects of the existing long-term trends in terms of the common but untested explanations for them. Finally, we simulate the effects of alternative family bargaining rules on individual utility to measure the sensitivity of our results to the family decision-making assumptions we make.

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This article estimates the effects of various parent and child characteristics on the choice of care arrangement of the parent, taking into account the potential endogeneity of some of the child characteristics. Three equations are estimated: a care choice equation, a child location equation, and a child work equation. Results suggest a hierarchy of family decision making; child locations affect the care decision, which affects child work decisions. The results also question previous research attempting to explain causes of secular trends in long-term care.

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Skeletal muscle is an attractive target tissue for delivery of therapeutic genes, since it is well vascularized, easily accessible, and has a high capacity for protein synthesis. For efficient transfection in skeletal muscle, several protocols have been described, including delivery of low voltage electric pulses and a combination of high and low voltage electric pulses. The aim of this study was to determine the influence of different parameters of electrotransfection on short-term and long-term transfection efficiency in murine skeletal muscle, and to evaluate histological changes in the treated tissue. Different parameters of electric pulses, different time lags between plasmid DNA injection and application of electric pulses, and different doses of plasmid DNA were tested for electrotransfection of tibialis cranialis muscle of C57BI/6 mice using DNA plasmid encoding green fluorescent protein (GFP). Transfection efficiency was assessed on frozen tissue sections one week after electrotransfection using a fluorescence microscope and also noninvasively, followed by an in vivo imaging system using a fluorescence stereo microscope over a period of several months. Histological changes in muscle were evaluated immediately or several months after electrotransfection by determining infiltration of inflammatory mononuclear cells and presence of necrotic muscle fibers. The most efficient electrotransfection into skeletal muscle of C57BI/6 mice in our experiments was achieved when one high voltage (HV) and four low voltage (LV) electric pulses were applied 5 seconds after the injection of 30 μg of plasmid DNA. This protocol resulted in the highest short-term as well as long-term transfection. The fluorescence intensity of the transfected area declined after 2-3 weeks, but GFP fluorescence was still detectable 18 months after electrotransfection. Extensive inflammatory mononuclear cell infiltration was observed immediately after the electrotransfection procedure using the described parameters, but no necrosis or late tissue damage was observed. This study showed that electric pulse parameters, time lag between the injection of DNA and application of electric pulses, and dose of plasmid DNA affected the duration of transgene expression in murine skeletal muscle. Therefore, transgene expression in muscle can be controlled by appropriate selection of electrotransfection protocol.

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This project recognized lack of data analysis and travel time prediction on arterials as the main gap in the current literature. For this purpose it first investigated reliability of data gathered by Bluetooth technology as a new cost effective method for data collection on arterial roads. Then by considering the similarity among varieties of daily travel time on different arterial routes, created a SARIMA model to predict future travel time values. Based on this research outcome, the created model can be applied for online short term travel time prediction in future.

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This paper is concerned with how a localised and energy-constrained robot can maximise its time in the field by taking paths and tours that minimise its energy expenditure. A significant component of a robot's energy is expended on mobility and is a function of terrain traversability. We estimate traversability online from data sensed by the robot as it moves, and use this to generate maps, explore and ultimately converge on minimum energy tours of the environment. We provide results of detailed simulations and parameter studies that show the efficacy of this approach for a robot moving over terrain with unknown traversability as well as a number of a priori unknown hard obstacles.

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In 2001, the red imported fire ant (Solenopsis invicta Buren) was identified in Brisbane, Australia. An eradication program involving broadcast bait treatment with two insect growth regulators and a metabolic inhibitor began in September of that year and is currently ongoing. To gauge the impacts of these treatments on local ant populations, we examined long-term monitoring data and quantified abundance patterns of S. invicta and common local ant genera using a linear mixed-effects model. For S. invicta, presence in pitfalls reduced over time to zero on every site. Significantly higher numbers of S. invicta workers were collected on high-density polygyne sites, which took longer to disinfest compared with monogyne and low-density polygyne sites. For local ants, nine genus groups of the 10 most common genera analyzed either increased in abundance or showed no significant trend. Five of these genus groups were significantly less abundant at the start of monitoring on high-density polygyne sites compared with monogyne and low-density polygyne sites. The genus Pheidole significantly reduced in abundance over time, suggesting that it was affected by treatment efforts. These results demonstrate that the treatment regime used at the time successfully removed S. invicta from these sites in Brisbane, and that most local ant genera were not seriously impacted by the treatment. These results have important implications for current and future prophylactic treatment efforts, and suggest that native ants remain in treated areas to provide some biological resistance to S. invicta.

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A hybrid energy storage system (HESS) consisting of battery and supercapacitor (SC) is proposed for use in a wind farm in order to achieve power dispatchability. In the designed scheme, the rate of charging/discharging powers of the battery is controlled while the faster wind power transients are diverted to the SC. This enhances the lifetime of the battery. Furthermore, by taking into consideration the random nature of the wind power, a statistical design method is developed to determine the capacities of the HESS needed to achieve specified confidence level in the power dispatch. The proposed approach is useful in the planning of the wind farm-HESS scheme and the coordination of the power flows between the battery and SC.

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"This work considers a mobile service robot which uses an appearance-based representation of its workplace as a map, where the current view and the map are used to estimate the current position in the environment. Due to the nature of real-world environments such as houses and offices, where the appearance keeps changing, the internal representation may become out of date after some time. To solve this problem the robot needs to be able to adapt its internal representation continually to the changes in the environment. This paper presents a method for creating an adaptive map for long-term appearance-based localization of a mobile robot using long-term and short-term memory concepts, with omni-directional vision as the external sensor."--publisher website

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Real-world environments such as houses and offices change over time, meaning that a mobile robot’s map will become out of date. In this work, we introduce a method to update the reference views in a hybrid metrictopological map so that a mobile robot can continue to localize itself in a changing environment. The updating mechanism, based on the multi-store model of human memory, incorporates a spherical metric representation of the observed visual features for each node in the map, which enables the robot to estimate its heading and navigate using multi-view geometry, as well as representing the local 3D geometry of the environment. A series of experiments demonstrate the persistence performance of the proposed system in real changing environments, including analysis of the long-term stability.

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Throughout a lifetime of operation, a mobile service robot needs to acquire, store and update its knowledge of a working environment. This includes the ability to identify and track objects in different places, as well as using this information for interaction with humans. This paper introduces a long-term updating mechanism, inspired by the modal model of human memory, to enable a mobile robot to maintain its knowledge of a changing environment. The memory model is integrated with a hybrid map that represents the global topology and local geometry of the environment, as well as the respective 3D location of objects. We aim to enable the robot to use this knowledge to help humans by suggesting the most likely locations of specific objects in its map. An experiment using omni-directional vision demonstrates the ability to track the movements of several objects in a dynamic environment over an extended period of time.

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This paper investigates the effect of topic dependent language models (TDLM) on phonetic spoken term detection (STD) using dynamic match lattice spotting (DMLS). Phonetic STD consists of two steps: indexing and search. The accuracy of indexing audio segments into phone sequences using phone recognition methods directly affects the accuracy of the final STD system. If the topic of a document in known, recognizing the spoken words and indexing them to an intermediate representation is an easier task and consequently, detecting a search word in it will be more accurate and robust. In this paper, we propose the use of TDLMs in the indexing stage to improve the accuracy of STD in situations where the topic of the audio document is known in advance. It is shown that using TDLMs instead of the traditional general language model (GLM) improves STD performance according to figure of merit (FOM) criteria.