884 resultados para unified theories and models of strong and electroweak


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Starting from Kagitcibasi's (2007) conceptualization of family models, this study compared N = 2961 adolescents' values across eleven cultures and explored whether patterns of values were related to the three proposed family models through cluster analyses. Three clusters with value profiles corresponding to the family models of interdependence, emotional interdependence, and independence were identified on the cultural as well as on the individual level. Furthermore, individual-level clusters corresponded to culture-level clusters in terms of individual cluster membership. The results largely support Kagitcibasi's proposition of changing family models and demonstrate their representation as individual-level value profiles across cultures.

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Cultural models of the domains healing and health are important in how people understand health and their behavior regarding it. The biomedicine model has been predominant in Western society. Recent popularity of holistic health and alternative healing modalities contrasts with the biomedical model and the assumptions upon which that model has been practiced. The holistic health movement characterizes an effort by health care providers and others such as nurses to expand the biomedical model and has often incorporated alternative modalities. This research described and compared the cultural models of healing of professional nurses and alternative healers. A group of nursing faculty who promote a holistic model were compared to a group of healers using healing touch. Ethnographic methods of participant observation, free listing and pile sort were used. Theoretical sampling in the free listings reached saturation at 18 in the group of nurses and 21 in the group of healers. Categories consistent for both groups emerged from the data. These were: physical, mental, attitude, relationships, spiritual, self management, and health seeking including biomedical and alternative resources. The healers had little differentiation between the concepts health and healing. The nurses, however, had more elements in self management for health and in health seeking for healing. This reflects the nurse's role in facilitating the shift in locus of responsibility between health and healing. The healers provided more specific information regarding alternative resources. The healer's conceptualization of health was embedded in a spiritual belief system and contrasted dramatically with that of biomedicine. The healer's models also contrasted with holistic health in the areas of holism, locus of responsibility, and dealing with uncertainty. The similarity between the groups and their dissimilarity to biomedicine suggest a larger cultural shift in beliefs regarding health care. ^

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This paper reports a comparison of three modeling strategies for the analysis of hospital mortality in a sample of general medicine inpatients in a Department of Veterans Affairs medical center. Logistic regression, a Markov chain model, and longitudinal logistic regression were evaluated on predictive performance as measured by the c-index and on accuracy of expected numbers of deaths compared to observed. The logistic regression used patient information collected at admission; the Markov model was comprised of two absorbing states for discharge and death and three transient states reflecting increasing severity of illness as measured by laboratory data collected during the hospital stay; longitudinal regression employed Generalized Estimating Equations (GEE) to model covariance structure for the repeated binary outcome. Results showed that the logistic regression predicted hospital mortality as well as the alternative methods but was limited in scope of application. The Markov chain provides insights into how day to day changes of illness severity lead to discharge or death. The longitudinal logistic regression showed that increasing illness trajectory is associated with hospital mortality. The conclusion is reached that for standard applications in modeling hospital mortality, logistic regression is adequate, but for new challenges facing health services research today, alternative methods are equally predictive, practical, and can provide new insights. ^

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The North Atlantic spring bloom is one of the main events that lead to carbon export to the deep ocean and drive oceanic uptake of CO(2) from the atmosphere. Here we use a suite of physical, bio-optical and chemical measurements made during the 2008 spring bloom to optimize and compare three different models of biological carbon export. The observations are from a Lagrangian float that operated south of Iceland from early April to late June, and were calibrated with ship-based measurements. The simplest model is representative of typical NPZD models used for the North Atlantic, while the most complex model explicitly includes diatoms and the formation of fast sinking diatom aggregates and cysts under silicate limitation. We carried out a variational optimization and error analysis for the biological parameters of all three models, and compared their ability to replicate the observations. The observations were sufficient to constrain most phytoplankton-related model parameters to accuracies of better than 15 %. However, the lack of zooplankton observations leads to large uncertainties in model parameters for grazing. The simulated vertical carbon flux at 100 m depth is similar between models and agrees well with available observations, but at 600 m the simulated flux is larger by a factor of 2.5 to 4.5 for the model with diatom aggregation. While none of the models can be formally rejected based on their misfit with the available observations, the model that includes export by diatom aggregation has a statistically significant better fit to the observations and more accurately represents the mechanisms and timing of carbon export based on observations not included in the optimization. Thus models that accurately simulate the upper 100 m do not necessarily accurately simulate export to deeper depths.

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Methods for tracking an object have generally fallen into two groups: tracking by detection and tracking through local optimization. The advantage of detection-based tracking is its ability to deal with target appearance and disappearance, but it does not naturally take advantage of target motion continuity during detection. The advantage of local optimization is efficiency and accuracy, but it requires additional algorithms to initialize tracking when the target is lost. To bridge these two approaches, we propose a framework for unified detection and tracking as a time-series Bayesian estimation problem. The basis of our approach is to treat both detection and tracking as a sequential entropy minimization problem, where the goal is to determine the parameters describing a target in each frame. To do this we integrate the Active Testing (AT) paradigm with Bayesian filtering, and this results in a framework capable of both detecting and tracking robustly in situations where the target object enters and leaves the field of view regularly. We demonstrate our approach on a retinal tool tracking problem and show through extensive experiments that our method provides an efficient and robust tracking solution.

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Several lines of genetic, archeological and paleontological evidence suggest that anatomically modern humans (Homo sapiens) colonized the world in the last 60,000 years by a series of migrations originating from Africa (e.g. Liu et al., 2006; Handley et al., 2007; Prugnolle, Manica, and Balloux, 2005; Ramachandran et al. 2005; Li et al. 2008; Deshpande et al. 2009; Mellars, 2006a, b; Lahr and Foley, 1998; Gravel et al., 2011; Rasmussen et al., 2011). With the progress of ancient DNA analysis, it has been shown that archaic humans hybridized with modern humans outside Africa. Recent direct analyses of fossil nuclear DNA have revealed that 1–4 percent of the genome of Eurasian has been likely introgressed by Neanderthal genes (Green et al., 2010; Reich et al., 2010; Vernot and Akey, 2014; Sankararaman et al., 2014; Prufer et al., 2014; Wall et al., 2013), with Papua New Guineans and Australians showing even larger levels of admixture with Denisovans (Reich et al., 2010; Skoglund and Jakobsson, 2011; Reich et al., 2011; Rasmussen et al., 2011). It thus appears that the past history of our species has been more complex than previously anticipated (Alves et al., 2012), and that modern humans hybridized several times with local hominins during their expansion out of Africa, but the exact mode, time and location of these hybridizations remain to be clarifi ed (Ibid.; Wall et al., 2013). In this context, we review here a general model of admixture during range expansion, which lead to some predictions about expected patterns of introgression that are relevant to modern human evolution.

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Effects of conspecific neighbours on survival and growth of trees have been found to be related to species abundance. Both positive and negative relationships may explain observed abundance patterns. Surprisingly, it is rarely tested whether such relationships could be biased or even spurious due to transforming neighbourhood variables or influences of spatial aggregation, distance decay of neighbour effects and standardization of effect sizes. To investigate potential biases, communities of 20 identical species were simulated with log-series abundances but without species-specific interactions. No relationship of conspecific neighbour effects on survival or growth with species abundance was expected. Survival and growth of individuals was simulated in random and aggregated spatial patterns using no, linear, or squared distance decay of neighbour effects. Regression coefficients of statistical neighbourhood models were unbiased and unrelated to species abundance. However, variation in the number of conspecific neighbours was positively or negatively related to species abundance depending on transformations of neighbourhood variables, spatial pattern and distance decay. Consequently, effect sizes and standardized regression coefficients, often used in model fitting across large numbers of species, were also positively or negatively related to species abundance depending on transformation of neighbourhood variables, spatial pattern and distance decay. Tests using randomized tree positions and identities provide the best benchmarks by which to critically evaluate relationships of effect sizes or standardized regression coefficients with tree species abundance. This will better guard against potential misinterpretations.

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The MET receptor tyrosine kinase is often deregulated in human cancers and several MET inhibitors are evaluated in clinical trials. Similarly to EGFR, MET signals through the RAS-RAF-ERK/MAPK pathway which plays key roles in cell proliferation and survival. Mutations of genes encoding for RAS proteins, particularly in KRAS, are commonly found in various tumors and are associated with constitutive activation of the MAPK pathway. It was shown for EGFR, that KRAS mutations render upstream EGFR inhibition ineffective in EGFR-positive colorectal cancers. Currently, there are no clinical studies evaluating MET inhibition impairment due to RAS mutations. To test the impact of RAS mutations on MET targeting, we generated tumor cells responsive to the MET inhibitor EMD1214063 that express KRAS G12V, G12D, G13D and HRAS G12V variants. We demonstrate that these MAPK-activating RAS mutations differentially interfere with MET-mediated biological effects of MET inhibition. We report increased residual ERK1/2 phosphorylation indicating that the downstream pathway remains active in presence of MET inhibition. Consequently, RAS variants counteracted MET inhibition-induced morphological changes as well as anti-proliferative and anchorage-independent growth effects. The effect of RAS mutants was reversed when MET inhibition was combined with MEK inhibitors AZD6244 and UO126. In an in vivo mouse xenograft model, MET-driven tumors harboring mutated RAS displayed resistance to MET inhibition. Taken together, our results demonstrate for the first time in details the role of KRAS and HRAS mutations in resistance to MET inhibition and suggest targeting both MET and MEK as an effective strategy when both oncogenic drivers are expressed.

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Deregulated expression of the MET receptor tyrosine kinase has been reported in up to 50% of patients with hepatocellular carcinoma, the most abundant form of liver cancers, and is associated with decreased survival. Consequently, MET is considered as a molecular target in this malignancy, whose progression is highly dependent on extensive angiogenesis. Here we studied the impact of MET small molecule inhibitors on angiogenesis-associated parameters and growth of xenograft liver models consisting of cells expressing MET-mutated variants M1268T and Y1248H, which exhibit constitutive kinase activity. We demonstrate that MET mutations expression is associated with significantly increased production of vascular endothelial growth factor, which is blocked by MET targeting only in cells expressing the M1268T inhibitor-sensitive but not in the Y1248H inhibitor-resistant variant. Decrease in vascular endothelial growth factor production is also associated with reduction of tyrosine phopshorylation of the vascular endothelial growth factor receptor 2 expressed on primary liver sinusoidal endothelial cells and with inhibition of vessel formation. Furthermore, MET inhibition demonstrated an efficient anti-tumor activity and considerable reduction in microvessel density only against the M1268T-derived intrahepatic tumors. Collectively, our data support the role of targeting MET-associated angiogenesis as a major biological determinant for liver tumor growth control.

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The prognosis from thyroid cancer subtypes in humans covers a spectrum from "cured at almost 90%" to "100% lethal." Invasive and poorly differentiated forms of thyroid cancer are among the most aggressive human cancers, and there are few effective therapeutic options. Genetically engineered mice, based on mutations observed in patients, can accurately recapitulate the human disease and its progression, providing invaluable tools for the preclinical evaluation of novel therapeutic approaches. This overview details models developed to date as well as their uses for identifying novel anticancer agents. © 2015 by John Wiley & Sons, Inc.

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This study focuses on the present-day surface elevation of the Greenland and Antarctic ice sheets. Based on 3 years of CryoSat-2 data acquisition we derived new elevation models (DEMs) as well as elevation change maps and volume change estimates for both ice sheets. Here we present the new DEMs and their corresponding error maps. The accuracy of the derived DEMs for Greenland and Antarctica is similar to those of previous DEMs obtained by satellite-based laser and radar altimeters. Comparisons with ICESat data show that 80% of the CryoSat-2 DEMs have an uncertainty of less than 3 m ± 15 m. The surface elevation change rates between January 2011 and January 2014 are presented for both ice sheets. We compared our results to elevation change rates obtained from ICESat data covering the time period from 2003 to 2009. The comparison reveals that in West Antarctica the volume loss has increased by a factor of 3. It also shows an anomalous thickening in Dronning Maud Land, East Antarctica which represents a known large-scale accumulation event. This anomaly partly compensates for the observed increased volume loss of the Antarctic Peninsula and West Antarctica. For Greenland we find a volume loss increased by a factor of 2.5 compared to the ICESat period with large negative elevation changes concentrated at the west and southeast coasts. The combined volume change of Greenland and Antarctica for the observation period is estimated to be -503 ± 107 km**3/yr. Greenland contributes nearly 75% to the total volume change with -375 ± 24 km**3/yr.