975 resultados para multiple data


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Ongoing changes in disturbance regimes are predicted to cause acute changes in ecosystem structure and function in the coming decades, but many aspects of these predictions are uncertain. A key challenge is to improve the predictability of postdisturbance biogeochemical trajectories at the ecosystem level. Ecosystem ecologists and paleoecologists have generated complementary data sets about disturbance (type, severity, frequency) and ecosystem response (net primary productivity, nutrient cycling) spanning decadal to millennial timescales. Here, we take the first steps toward a full integration of these data sets by reviewing how disturbances are reconstructed using dendrochronological and sedimentary archives and by summarizing the conceptual frameworks for carbon, nitrogen, and hydrologic responses to disturbances. Key research priorities include further development of paleoecological techniques that reconstruct both disturbances and terrestrial ecosystem dynamics. In addition, mechanistic detail from disturbance experiments, long-term observations, and chronosequences can help increase the understanding of ecosystem resilience.

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Application of biogeochemical models to the study of marine ecosystems is pervasive, yet objective quantification of these models' performance is rare. Here, 12 lower trophic level models of varying complexity are objectively assessed in two distinct regions (equatorial Pacific and Arabian Sea). Each model was run within an identical one-dimensional physical framework. A consistent variational adjoint implementation assimilating chlorophyll-a, nitrate, export, and primary productivity was applied and the same metrics were used to assess model skill. Experiments were performed in which data were assimilated from each site individually and from both sites simultaneously. A cross-validation experiment was also conducted whereby data were assimilated from one site and the resulting optimal parameters were used to generate a simulation for the second site. When a single pelagic regime is considered, the simplest models fit the data as well as those with multiple phytoplankton functional groups. However, those with multiple phytoplankton functional groups produced lower misfits when the models are required to simulate both regimes using identical parameter values. The cross-validation experiments revealed that as long as only a few key biogeochemical parameters were optimized, the models with greater phytoplankton complexity were generally more portable. Furthermore, models with multiple zooplankton compartments did not necessarily outperform models with single zooplankton compartments, even when zooplankton biomass data are assimilated. Finally, even when different models produced similar least squares model-data misfits, they often did so via very different element flow pathways, highlighting the need for more comprehensive data sets that uniquely constrain these pathways.

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Multiple sclerosis (MS) is a chronic disease with an inflammatory and neurodegenerative pathology. Axonal loss and neurodegeneration occurs early in the disease course and may lead to irreversible neurological impairment. Changes in brain volume, observed from the earliest stage of MS and proceeding throughout the disease course, may be an accurate measure of neurodegeneration and tissue damage. There are a number of magnetic resonance imaging-based methods for determining global or regional brain volume, including cross-sectional (e.g. brain parenchymal fraction) and longitudinal techniques (e.g. SIENA [Structural Image Evaluation using Normalization of Atrophy]). Although these methods are sensitive and reproducible, caution must be exercised when interpreting brain volume data, as numerous factors (e.g. pseudoatrophy) may have a confounding effect on measurements, especially in a disease with complex pathological substrates such as MS. Brain volume loss has been correlated with disability progression and cognitive impairment in MS, with the loss of grey matter volume more closely correlated with clinical measures than loss of white matter volume. Preventing brain volume loss may therefore have important clinical implications affecting treatment decisions, with several clinical trials now demonstrating an effect of disease-modifying treatments (DMTs) on reducing brain volume loss. In clinical practice, it may therefore be important to consider the potential impact of a therapy on reducing the rate of brain volume loss. This article reviews the measurement of brain volume in clinical trials and practice, the effect of DMTs on brain volume change across trials and the clinical relevance of brain volume loss in MS.

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It is contested that the mineral dust found in Greenlandic ice cores during the Holocene stems from multiple source areas. Particles entrained above a more productive, primary source dominate the signal’s multi-seasonal average. Data in sub-annual resolution, however, reveal at least one further source. Whereas distinct inputs from the primary source are visible in elevated concentration levels, various inputs of the secondary source(s) are reflected by multiple maxima in the coarse particle percentage. As long as the dust sources’ respective seasonal cycles are preserved, primary and secondary source can be distinguished. Since the two source’s ejecta eventually detected differ in size, which can be attributed to a change in atmospheric residence times, it is suggested that the secondary source is located in closer proximity to the drilling site than the primary one.

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Purpose The purpose of this study was to investigate multiple indirect Big Five personality influences on professionals’ annual salary while considering relevant mediators. These are the motivational variables of occupational self-efficacy and career-advancement goals, and the work status variable of contractual work hours. The motivational and work status variables were conceptualized as serial mediators (Big Five → occupational self-efficacy/career-advancement goals → contractual work hours → annual salary). Design/Methodology/Approach We realized a 4 year longitudinal survey study with 432 participants and three points of measurement. We assessed personality prior to the mediators and the mediators prior to annual salary. Findings Results showed that except for openness the other Big Five personality traits exerted indirect influences on annual salary. Career-advancement goals mediated influences of conscientiousness (+), extraversion (+), and agreeableness (−). Occupational self-efficacy mediated influences of neuroticism (–) and conscientiousness (+). Because the influence of occupational self-efficacy on annual salary was fully mediated by contractual work hours, indirect personality influences via occupational self-efficacy always included contractual work hours in a serial mediation. Implications These findings underline the importance of distal personality traits for career success. They give further insights into direct and indirect relationships between personality, goal content, self-efficacy beliefs, and an individual’s career progress. Originality/Value Previous research predominantly investigated direct Big Five influences on salary, and it analyzed cross-sectional data. This study is one of the first to investigate multiple indirect Big Five influences on salary in a longitudinal design. The findings support process-oriented theories of personality influences on career outcomes.

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BACKGROUND Complex pelvic traumas, i.e., pelvic fractures accompanied by pelvic soft tissue injuries, still have an unacceptably high mortality rate of about 18 %. PATIENTS AND METHODS We retrospectively evaluated an intersection set of data from the TraumaRegister DGU® and the German Pelvic Injury Register from 2004-2009. Patients with complex and noncomplex pelvic traumas were compared regarding their vital parameters, emergency management, stay in the ICU, and outcome. RESULTS From a total of 344 patients with pelvic injuries, 21 % of patients had a complex and 79 % a noncomplex trauma. Complex traumas were significantly less likely to survive (16.7 % vs. 5.9 %). Whereas vital parameters and emergency treatment in the preclinical setting did not differ substantially, patients with complex traumas were more often in shock and showed acute traumatic coagulopathy on hospital arrival, which resulted in more fluid volumes and transfusions when compared to patients with noncomplex traumas. Furthermore, patients with complex traumas had more complications and longer ICU stays. CONCLUSION Prevention of exsanguination and complications like multiple organ dysfunction syndrome still pose a major challenge in the management of complex pelvic traumas.

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Inflammation is one possible mechanism underlying the associations between mental disorders and cardiovascular diseases (CVD). However, studies on mental disorders and inflammation have yielded inconsistent results and the majority did not adjust for potential confounding factors. We examined the associations of several pro-inflammatory cytokines (IL-1β, IL-6 and TNF-α) and high sensitive C-reactive protein (hsCRP) with lifetime and current mood, anxiety and substance use disorders (SUD), while adjusting for multiple covariates. The sample included 3719 subjects, randomly selected from the general population, who underwent thorough somatic and psychiatric evaluations. Psychiatric diagnoses were made with a semi-structured interview. Major depressive disorder was subtyped into "atypical", "melancholic", "combined atypical-melancholic" and "unspecified". Associations between inflammatory markers and psychiatric diagnoses were assessed using multiple linear and logistic regression models. Lifetime bipolar disorders and atypical depression were associated with increased levels of hsCRP, but not after multivariate adjustment. After multivariate adjustment, SUD remained associated with increased hsCRP levels in men (β = 0.13 (95% CI: 0.03,0.23)) but not in women. After multivariate adjustment, lifetime combined and unspecified depression were associated with decreased levels of IL-6 (β = -0.27 (-0.51,-0.02); β = -0.19 (-0.34,-0.05), respectively) and TNF-α (β = -0.16 (-0.30,-0.01); β = -0.10 (-0.19,-0.02), respectively), whereas current combined and unspecified depression were associated with decreased levels of hsCRP (β = -0.20 (-0.39,-0.02); β = -0.12 (-0.24,-0.01), respectively). Our data suggest that the significant associations between increased hsCRP levels and mood disorders are mainly attributable to the effects of comorbid disorders, medication as well as behavioral and physical CVRFs.

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BACKGROUND The lung clearance index (LCI) measured by multiple-breath washout (MBW) has been proposed as an outcome for clinical trials; however, MBW is time consuming and LCI can be affected by breathing pattern. We aimed to evaluate moment ratios and abbreviated LCI in school-aged children with mild-to-moderate CF lung disease. METHODS Using existing data from three studies we assessed the sensitivity of moment ratios and abbreviated LCIs to (i) detect mild-to-moderate CF lung disease and (ii) detect treatment effects after 4weeks of hypertonic saline or dornase alfa inhalation. MBW was measured by respiratory mass spectrometry using 4% "sulphur hexafluoride as a tracer gas. RESULTS Compared to the traditional LCI, moment ratios and abbreviated LCIs were similarly sensitive to detect CF lung disease. Moment ratios consistently demonstrated treatment effects, whereas abbreviated LCIs were less sensitive. CONCLUSIONS Both moment ratios and abbreviated LCI are suitable to differentiate health from disease. Sensitivity is decreased for abbreviated LCIs in interventional studies in mild CF lung disease.

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Sequence analysis and optimal matching are useful heuristic tools for the descriptive analysis of heterogeneous individual pathways such as educational careers, job sequences or patterns of family formation. However, to date it remains unclear how to handle the inevitable problems caused by missing values with regard to such analysis. Multiple Imputation (MI) offers a possible solution for this problem but it has not been tested in the context of sequence analysis. Against this background, we contribute to the literature by assessing the potential of MI in the context of sequence analyses using an empirical example. Methodologically, we draw upon the work of Brendan Halpin and extend it to additional types of missing value patterns. Our empirical case is a sequence analysis of panel data with substantial attrition that examines the typical patterns and the persistence of sex segregation in school-to-work transitions in Switzerland. The preliminary results indicate that MI is a valuable methodology for handling missing values due to panel mortality in the context of sequence analysis. MI is especially useful in facilitating a sound interpretation of the resulting sequence types.

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Although multiple-response questions are quite common in survey research, Stata’s official release does not provide much capability for an effective analysis of multiple-response variables. For example, in a study on drug addiction an interview question might be, “Which substances did you consume during the last four weeks?” The respondents just list all the drugs they took, if any; e.g., an answer could be “cannabis, cocaine, heroin” or “ecstasy, cannabis” or “none”, etc. Usually, the responses to such questions are stored as a set of variables and, therefore, cannot be easily tabulated. I will address this issue here and present a new module to compute one- and two-way tables of multiple responses. The module supports several types of data structure, provides significance tests, and offers various options to control the computation and display of the results. In addition, tools to create graphs of multiple-response distributions are presented.

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Correct predictions of future blood glucose levels in individuals with Type 1 Diabetes (T1D) can be used to provide early warning of upcoming hypo-/hyperglycemic events and thus to improve the patient's safety. To increase prediction accuracy and efficiency, various approaches have been proposed which combine multiple predictors to produce superior results compared to single predictors. Three methods for model fusion are presented and comparatively assessed. Data from 23 T1D subjects under sensor-augmented pump (SAP) therapy were used in two adaptive data-driven models (an autoregressive model with output correction - cARX, and a recurrent neural network - RNN). Data fusion techniques based on i) Dempster-Shafer Evidential Theory (DST), ii) Genetic Algorithms (GA), and iii) Genetic Programming (GP) were used to merge the complimentary performances of the prediction models. The fused output is used in a warning algorithm to issue alarms of upcoming hypo-/hyperglycemic events. The fusion schemes showed improved performance with lower root mean square errors, lower time lags, and higher correlation. In the warning algorithm, median daily false alarms (DFA) of 0.25%, and 100% correct alarms (CA) were obtained for both event types. The detection times (DT) before occurrence of events were 13.0 and 12.1 min respectively for hypo-/hyperglycemic events. Compared to the cARX and RNN models, and a linear fusion of the two, the proposed fusion schemes represents a significant improvement.

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The OPERA detector, designed to search for νμ → ντ oscillations in the CNGS beam, is located in the underground Gran Sasso laboratory, a privileged location to study TeV-scale cosmic rays. For the analysis here presented, the detector was used to measure the atmospheric muon charge ratio in the TeV region. OPERA collected chargeseparated cosmic ray data between 2008 and 2012. More than 3 million atmospheric muon events were detected and reconstructed, among which about 110000 multiple muon bundles. The charge ratio Rμ ≡ Nμ+/Nμ− was measured separately for single and for multiple muon events. The analysis exploited the inversion of the magnet polarity which was performed on purpose during the 2012 Run. The combination of the two data sets with opposite magnet polarities allowedminimizing systematic uncertainties and reaching an accurate determination of the muon charge ratio. Data were fitted to obtain relevant parameters on the composition of primary cosmic rays and the associated kaon production in the forward fragmentation region. In the surface energy range 1–20 TeV investigated by OPERA, Rμ is well described by a parametric model including only pion and kaon contributions to themuon flux, showing no significant contribution of the prompt component. The energy independence supports the validity of Feynman scaling in the fragmentation region up to 200 TeV/nucleon primary energy.

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Land-use intensification is a key driver of biodiversity change. However, little is known about how it alters relationships between the diversities of different taxonomic groups, which are often correlated due to shared environmental drivers and trophic interactions. Using data from 150 grassland sites, we examined how land-use intensification (increased fertilization, higher livestock densities, and increased mowing frequency) altered correlations between the species richness of 15 plant, invertebrate, and vertebrate taxa. We found that 54% of pairwise correlations between taxonomic groups were significant and positive among all grasslands, while only one was negative. Higher land-use intensity substantially weakened these correlations (35% decrease in r and 43% fewer significant pairwise correlations at high intensity), a pattern which may emerge as a result of biodiversity declines and the breakdown of specialized relationships in these conditions. Nevertheless, some groups (Coleoptera, Heteroptera, Hymenoptera and Orthoptera) were consistently correlated with multidiversity, an aggregate measure of total biodiversity comprised of the standardized diversities of multiple taxa, at both high and low land-use intensity. The form of intensification was also important; increased fertilization and mowing frequency typically weakened plant–plant and plant–primary consumer correlations, whereas grazing intensification did not. This may reflect decreased habitat heterogeneity under mowing and fertilization and increased habitat heterogeneity under grazing. While these results urge caution in using certain taxonomic groups to monitor impacts of agricultural management on biodiversity, they also suggest that the diversities of some groups are reasonably robust indicators of total biodiversity across a range of conditions. Read More: http://www.esajournals.org/doi/10.1890/14-1307.1

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PURPOSE: To identify programmed cell death (PCD) pathways involved in N-methyl-N-nitrosourea (MNU)-induced photoreceptor (PR) degeneration. METHODS: Adult C57BL/6 mice received a single MNU i.p. injection (60 mg/kg bodyweight), and were observed over a period of 7 days. Degeneration was visualized by H&E overview staining and electron microscopy. PR cell death was measured by quantifying TUNEL-positive cells in the outer nuclear layer (ONL). Activity measurements of key PCD enzymes (calpain, caspases) were used to identify the involved cell death pathways. Furthermore, the expression level of C/EBP homologous protein (CHOP) and glucose-regulated protein 78 (GRP78), key players in endoplasmic reticulum (ER) stress-induced apoptosis, was analyzed using quantitative real-time PCR. RESULTS: A decrease in ONL thickness and the appearance of apoptotic PR nuclei could be detected beginning 3 days post-injection (PI). This was accompanied by an increase of TUNEL-positive cells. Significant upregulation of activated caspases (3, 9, 12) was found at different time periods after MNU injection. Additionally, several other players of nonconventional PCD pathways were also upregulated. Consequently, calpain activity increased in the ONL, with a maximum on day 7 PI and an upregulation of CHOP and GRP78 expression beginning on day 1 PI was found. CONCLUSIONS: The data indicate that regular apoptosis is the major cause of MNU-induced PR cell death. However, alternative PCD pathways, including ER stress and calpain activation, are also involved. Knowledge about the mechanisms involved in this mouse model of PR degeneration could facilitate the design of putative combinatory therapeutic approaches.

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Convergent plate margins typically experience a transition from subduction to collision dynamics as massive continental blocks enter the subduction channel. Studies of high-pressure rocks indicate that tectonic fragments are rapidly exhumed from eclogite facies to midcrustal levels, but the details of such dynamics are controversial.To understand the dynamics of a subduction channel we report the results of a petrochronological study from the central Sesia Zone, a key element of the internalWestern Alps.This comprises two polymetamorphic basement complexes (Eclogitic Micaschist Complex and Gneiss Minuti Complex) and a thin, dismembered cover sequence (Scalaro Unit) associated with pre-Alpine metagabbros and metasediments (Bonze Unit). Structurally controlled samples from three of these units (Eclogitic Micaschist Complex and Scalaro-Bonze Units) yield unequivocal petrological and geochronological evidence of two distinct high-pressure stages. Ages (U-Th-Pb) of growth zones in accessory allanite and zircon, combined with inclusion and textural relationships, can be tied to the multi-stage evolution of single samples.Two independent tectono-metamorphic ‘slices’ showing a coherent metamorphic evolution during a given time interval have been recognized: the Fondo slice (which includes Scalaro and Bonze rocks) and the Druer slice (belonging to the Eclogitic Micaschist Complex).The new data indicate separate stages of deformation at eclogite-facies conditions for each recognized independent kilometer-sized tectono-metamorphic slice, between ~85 and 60 Ma, with evidence of intermittent decompression (∆P~0.5 GPa) within only the Fondo slice. The evolution path of the Druer slice indicates a different P-T-time evolution with prolonged eclogite-facies metamorphism between ~85 and 75Ma. Our approach, combining structural, petrological and geochronological techniques, yields field-based constraints on the duration and rates of dynamics within a subduction channel.