23 resultados para Automobiles by Make, Model, Year.

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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The performance of reanalysis-driven Canadian Regional Climate Model, version 5 (CRCM5) in reproducing the present climate over the North American COordinated Regional climate Downscaling EXperiment domain for the 1989–2008 period has been assessed in comparison with several observation-based datasets. The model reproduces satisfactorily the near-surface temperature and precipitation characteristics over most part of North America. Coastal and mountainous zones remain problematic: a cold bias (2–6 °C) prevails over Rocky Mountains in summertime and all year-round over Mexico; winter precipitation in mountainous coastal regions is overestimated. The precipitation patterns related to the North American Monsoon are well reproduced, except on its northern limit. The spatial and temporal structure of the Great Plains Low-Level Jet is well reproduced by the model; however, the night-time precipitation maximum in the jet area is underestimated. The performance of CRCM5 was assessed against earlier CRCM versions and other RCMs. CRCM5 is shown to have been substantially improved compared to CRCM3 and CRCM4 in terms of seasonal mean statistics, and to be comparable to other modern RCMs.

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When firms contribute to open source projects, they in fact invest into public goods which may be used by everyone, even by their competitors. This seemingly paradoxical behavior can be explained by the model of private-collective innovation where private investors participate in collective action. Previous literature has shown that companies benefit through the production process providing them with unique incentives such as learning and reputation effects. By contributing to open source projects firms are able to build a network of external individuals and organizations participating in the creation and development of the software. As will be shown in this doctoral dissertation firm-sponsored communities involve the formation of interorganizational relationships which eventually may lead to a source of sustained competitive advantage. However, managing a largely independent open source community is a challenging balancing act between exertion of control to appropriate value creation, and openness in order to gain and preserve credibility and motivate external contributions. Therefore, this dissertation consisting of an introductory chapter and three separate research papers analyzes characteristics of firm-driven open source communities, finds reasons why and mechanisms by which companies facilitate the creation of such networks, and shows how firms can benefit most from their communities.

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Despite numerous studies about nitrogen-cycling in forest ecosystems, many uncertainties remain, especially regarding the longer-term nitrogen accumulation. To contribute to filling this gap, the dynamic process-based model TRACE, with the ability to simulate 15N tracer redistribution in forest ecosystems was used to study N cycling processes in a mountain spruce forest of the northern edge of the Alps in Switzerland (Alptal, SZ). Most modeling analyses of N-cycling and C-N interactions have very limited ability to determine whether the process interactions are captured correctly. Because the interactions in such a system are complex, it is possible to get the whole-system C and N cycling right in a model without really knowing if the way the model combines fine-scale interactions to derive whole-system cycling is correct. With the possibility to simulate 15N tracer redistribution in ecosystem compartments, TRACE features a very powerful tool for the validation of fine-scale processes captured by the model. We first adapted the model to the new site (Alptal, Switzerland; long-term low-dose N-amendment experiment) by including a new algorithm for preferential water flow and by parameterizing of differences in drivers such as climate, N deposition and initial site conditions. After the calibration of key rates such as NPP and SOM turnover, we simulated patterns of 15N redistribution to compare against 15N field observations from a large-scale labeling experiment. The comparison of 15N field data with the modeled redistribution of the tracer in the soil horizons and vegetation compartments shows that the majority of fine-scale processes are captured satisfactorily. Particularly, the model is able to reproduce the fact that the largest part of the N deposition is immobilized in the soil. The discrepancies of 15N recovery in the LF and M soil horizon can be explained by the application method of the tracer and by the retention of the applied tracer by the well developed moss layer, which is not considered in the model. Discrepancies in the dynamics of foliage and litterfall 15N recovery were also observed and are related to the longevity of the needles in our mountain forest. As a next step, we will use the final Alptal version of the model to calculate the effects of climate change (temperature, CO2) and N deposition on ecosystem C sequestration in this regionally representative Norway spruce (Picea abies) stand.

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Ocean acidification might reduce the ability of calcifying plankton to produce and maintain their shells of calcite, or of aragonite, the more soluble form of CaCO3. In addition to possibly large biological impacts, reduced CaCO3 production corresponds to a negative feedback on atmospheric CO2. In order to explore the sensitivity of the ocean carbon cycle to increasing concentrations of atmospheric CO2, we use the new biogeochemical Bern3D/PISCES model. The model reproduces the large scale distributions of biogeochemical tracers. With a range of sensitivity studies, we explore the effect of (i) using different parameterizations of CaCO3 production fitted to available laboratory and field experiments, of (ii) letting calcite and aragonite be produced by auto- and heterotrophic plankton groups, and of (iii) using carbon emissions from the range of the most recent IPCC Representative Concentration Pathways (RCP). Under a high-emission scenario, the CaCO3 production of all the model versions decreases from ~1 Pg C yr−1 to between 0.36 and 0.82 Pg C yr−1 by the year 2100. The changes in CaCO3 production and dissolution resulting from ocean acidification provide only a small feedback on atmospheric CO2 of −1 to −11 ppm by the year 2100, despite the wide range of parameterizations, model versions and scenarios included in our study. A potential upper limit of the CO2-calcification/dissolution feedback of −30 ppm by the year 2100 is computed by setting calcification to zero after 2000 in a high 21st century emission scenario. The similarity of feedback estimates yielded by the model version with calcite produced by nanophytoplankton and the one with calcite, respectively aragonite produced by mesozooplankton suggests that expending biogeochemical models to calcifying zooplankton might not be needed to simulate biogeochemical impacts on the marine carbonate cycle. The changes in saturation state confirm previous studies indicating that future anthropogenic CO2 emissions may lead to irreversible changes in ΩA for several centuries. Furthermore, due to the long-term changes in the deep ocean, the ratio of open water CaCO3 dissolution to production stabilizes by the year 2500 at a value that is 30–50% higher than at pre-industrial times when carbon emissions are set to zero after 2100.

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Early stratification of degenerative processes is a prerequisite to warrant therapeutic options in prodromal Alzheimer disease. Our aim was to investigate differences in cerebral macromolecular tissue composition between patients with AD, mild cognitive impairment, and age- and sex-matched healthy controls by using model-based magnetization transfer with a binary spin-bath magnetization transfer model and magnetization transfer ratio at 1.5 T.

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OBJECTIVE: This study aimed to assess the potential cost-effectiveness of testing patients with nephropathies for the I/D polymorphism before starting angiotensin-converting enzyme (ACE) inhibitor therapy, using a 3-year time horizon and a healthcare perspective. METHODS: We used a combination of a decision analysis and Markov modeling technique to evaluate the potential economic value of this pharmacogenetic test by preventing unfavorable treatment in patients with nephropathies. The estimation of the predictive value of the I/D polymorphism is based on a systematic review showing that DD carriers tend to respond well to ACE inhibitors, while II carriers seem not to benefit adequately from this treatment. Data on the ACE inhibitor effectiveness in nephropathy were derived from the REIN (Ramipril Efficacy in Nephropathy) trial. We calculated the number of patients with end-stage renal disease (ESRD) prevented and the differences in the incremental costs and incremental effect expressed as life-years free of ESRD. A probabilistic sensitivity analysis was conducted to determine the robustness of the results. RESULTS: Compared with unselective treatment, testing patients for their ACE genotype could save 12 patients per 1000 from developing ESRD during the 3 years covered by the model. As the mean net cost savings was euro 356,000 per 1000 patient-years, and 9 life-years free of ESRD were gained, selective treatment seems to be dominant. CONCLUSION: The study suggests that genetic testing of the I/D polymorphism in patients with nephropathy before initiating ACE therapy will most likely be cost-effective, even if the risk for II carriers to develop ESRD when treated with ACE inhibitors is only 1.4% higher than for DD carriers. Further studies, however, are required to corroborate the difference in treatment response between ACE genotypes, before genetic testing can be justified in clinical practice.

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PURPOSE To explore whether population-related pharmacogenomics contribute to differences in patient outcomes between clinical trials performed in Japan and the United States, given similar study designs, eligibility criteria, staging, and treatment regimens. METHODS We prospectively designed and conducted three phase III trials (Four-Arm Cooperative Study, LC00-03, and S0003) in advanced-stage, non-small-cell lung cancer, each with a common arm of paclitaxel plus carboplatin. Genomic DNA was collected from patients in LC00-03 and S0003 who received paclitaxel (225 mg/m(2)) and carboplatin (area under the concentration-time curve, 6). Genotypic variants of CYP3A4, CYP3A5, CYP2C8, NR1I2-206, ABCB1, ERCC1, and ERCC2 were analyzed by pyrosequencing or by PCR restriction fragment length polymorphism. Results were assessed by Cox model for survival and by logistic regression for response and toxicity. Results Clinical results were similar in the two Japanese trials, and were significantly different from the US trial, for survival, neutropenia, febrile neutropenia, and anemia. There was a significant difference between Japanese and US patients in genotypic distribution for CYP3A4*1B (P = .01), CYP3A5*3C (P = .03), ERCC1 118 (P < .0001), ERCC2 K751Q (P < .001), and CYP2C8 R139K (P = .01). Genotypic associations were observed between CYP3A4*1B for progression-free survival (hazard ratio [HR], 0.36; 95% CI, 0.14 to 0.94; P = .04) and ERCC2 K751Q for response (HR, 0.33; 95% CI, 0.13 to 0.83; P = .02). For grade 4 neutropenia, the HR for ABCB1 3425C-->T was 1.84 (95% CI, 0.77 to 4.48; P = .19). CONCLUSION Differences in allelic distribution for genes involved in paclitaxel disposition or DNA repair were observed between Japanese and US patients. In an exploratory analysis, genotype-related associations with patient outcomes were observed for CYP3A4*1B and ERCC2 K751Q. This common-arm approach facilitates the prospective study of population-related pharmacogenomics in which ethnic differences in antineoplastic drug disposition are anticipated.

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We report a case involving a spring-gun device (muzzleloader) loaded solely with gunpowder, installed next to shoes to prevent the neighbors' puppy from removing them. The booby trap was triggered by the 15-year-old dog-owners son when he tried to put the shoes out of the reach of the puppy. The boy suffered second degree superficial burns located mainly at the dorsal side of the right hand and fingers. To estimate the danger of the used weapon, several tests were undertaken on soap blocks from different distances and with different loads of black powder. The particle density per mm and the depth of black powder tattooing in the soap was compared with the boy's injuries, and found conclusive with the gun-owners statement regarding the loading of the weapon. Furthermore, our experiments indicated that the gunpowder load involved was not able to inflict permanent damage, not even to the eyes, at the here estimated firing distance.

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Neurally adjusted ventilatory assist (NAVA) delivers airway pressure (P(aw)) in proportion to the electrical activity of the diaphragm (EAdi) using an adjustable proportionality constant (NAVA level, cm·H(2)O/μV). During systematic increases in the NAVA level, feedback-controlled down-regulation of the EAdi results in a characteristic two-phased response in P(aw) and tidal volume (Vt). The transition from the 1st to the 2nd response phase allows identification of adequate unloading of the respiratory muscles with NAVA (NAVA(AL)). We aimed to develop and validate a mathematical algorithm to identify NAVA(AL). P(aw), Vt, and EAdi were recorded while systematically increasing the NAVA level in 19 adult patients. In a multistep approach, inspiratory P(aw) peaks were first identified by dividing the EAdi into inspiratory portions using Gaussian mixture modeling. Two polynomials were then fitted onto the curves of both P(aw) peaks and Vt. The beginning of the P(aw) and Vt plateaus, and thus NAVA(AL), was identified at the minimum of squared polynomial derivative and polynomial fitting errors. A graphical user interface was developed in the Matlab computing environment. Median NAVA(AL) visually estimated by 18 independent physicians was 2.7 (range 0.4 to 5.8) cm·H(2)O/μV and identified by our model was 2.6 (range 0.6 to 5.0) cm·H(2)O/μV. NAVA(AL) identified by our model was below the range of visually estimated NAVA(AL) in two instances and was above in one instance. We conclude that our model identifies NAVA(AL) in most instances with acceptable accuracy for application in clinical routine and research.

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The application of scientific-based conservation measures requires that sampling methodologies in studies modelling similar ecological aspects produce comparable results making easier their interpretation. We aimed to show how the choice of different methodological and ecological approaches can affect conclusions in nest-site selection studies along different Palearctic meta-populations of an indicator species. First, a multivariate analysis of the variables affecting nest-site selection in a breeding colony of cinereous vulture (Aegypius monachus) in central Spain was performed. Then, a meta-analysis was applied to establish how methodological and habitat-type factors determine differences and similarities in the results obtained by previous studies that have modelled the forest breeding habitat of the species. Our results revealed patterns in nesting-habitat modelling by the cinereous vulture throughout its whole range: steep and south-facing slopes, great cover of large trees and distance to human activities were generally selected. The ratio and situation of the studied plots (nests/random), the use of plots vs. polygons as sampling units and the number of years of data set determined the variability explained by the model. Moreover, a greater size of the breeding colony implied that ecological and geomorphological variables at landscape level were more influential. Additionally, human activities affected in greater proportion to colonies situated in Mediterranean forests. For the first time, a meta-analysis regarding the factors determining nest-site selection heterogeneity for a single species at broad scale was achieved. It is essential to homogenize and coordinate experimental design in modelling the selection of species' ecological requirements in order to avoid that differences in results among studies would be due to methodological heterogeneity. This would optimize best conservation and management practices for habitats and species in a global context.

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The current therapeutic strategy in breast cancer is to identify a target, such as estrogen receptor (ER) status, for tailoring treatments. We investigated the patterns of recurrence with respect to ER status for patients treated in two randomized trials with 25 years' median follow-up. In the ER-negative subpopulations most breast cancer events occurred within the first 5-7 years after randomization, while in the ER-positive subpopulations breast cancer events were spread through 10 years. In the ER-positive subpopulation, 1 year endocrine treatment alone significantly prolonged disease-free survival (DFS) with no additional benefit observed by adding 1 year of chemotherapy. In the small ER-negative subpopulation chemo-endocrine therapy had a significantly better DFS than endocrine alone or no treatment. Despite small numbers of patients, "old-fashioned" treatments, and competing causes of treatment failure, the value of ER status as a target for response to adjuvant treatment is evident through prolonged follow-up.

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The marine aragonite cycle has been included in the global biogeochemical model PISCES to study the role of aragonite in shallow water CaCO3 dissolution. Aragonite production is parameterized as a function of mesozooplankton biomass and aragonite saturation state of ambient waters. Observation-based estimates of marine carbonate production and dissolution are well reproduced by the model and about 60% of the combined CaCO3 water column dissolution from aragonite and calcite is simulated above 2000 m. In contrast, a calcite-only version yields a much smaller fraction. This suggests that the aragonite cycle should be included in models for a realistic representation of CaCO3 dissolution and alkalinity. For the SRES A2 CO2 scenario, production rates of aragonite are projected to notably decrease after 2050. By the end of this century, global aragonite production is reduced by 29% and total CaCO3 production by 19% relative to pre-industrial. Geographically, the effect from increasing atmospheric CO2, and the subsequent reduction in saturation state, is largest in the subpolar and polar areas where the modeled aragonite production is projected to decrease by 65% until 2100.

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BACKGROUND Low-grade gliomas (LGGs) are rare brain neoplasms, with survival spanning up to a few decades. Thus, accurate evaluations on how biomarkers impact survival among patients with LGG require long-term studies on samples prospectively collected over a long period. METHODS The 210 adult LGGs collected in our databank were screened for IDH1 and IDH2 mutations (IDHmut), MGMT gene promoter methylation (MGMTmet), 1p/19q loss of heterozygosity (1p19qloh), and nuclear TP53 immunopositivity (TP53pos). Multivariate survival analyses with multiple imputation of missing data were performed using either histopathology or molecular markers. Both models were compared using Akaike's information criterion (AIC). The molecular model was reduced by stepwise model selection to filter out the most critical predictors. A third model was generated to assess for various marker combinations. RESULTS Molecular parameters were better survival predictors than histology (ΔAIC = 12.5, P< .001). Forty-five percent of studied patients died. MGMTmet was positively associated with IDHmut (P< .001). In the molecular model with marker combinations, IDHmut/MGMTmet combined status had a favorable impact on overall survival, compared with IDHwt (hazard ratio [HR] = 0.33, P< .01), and even more so the triple combination, IDHmut/MGMTmet/1p19qloh (HR = 0.18, P< .001). Furthermore, IDHmut/MGMTmet/TP53pos triple combination was a significant risk factor for malignant transformation (HR = 2.75, P< .05). CONCLUSION By integrating networks of activated molecular glioma pathways, the model based on genotype better predicts prognosis than histology and, therefore, provides a more reliable tool for standardizing future treatment strategies.

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Arguably, job satisfaction is one of the most important variables with regard to work. When explaining job satisfaction, research usually focuses on predictor variables in terms of levels but neglects growth rates. Therefore it remains unclear how potential predictors evolve over time and how their development affects job satisfaction. Using multivariate latent growth modeling in a study with 1145 young workers over five years, we analyzed how well job satisfaction is predicted a) by levels of situational (i.e., job control) and dispositional (i.e., Core Self-Evaluations (CSE)) factors and b) by growth per year of these predictors. Results showed both intercepts and slopes to be related to each other, suggesting a joint growth of job control and CSE during early careers. Job satisfaction after five years was best predicted by the slopes of job control (β = .31, p < .001) and CSE (β = .34, p < .01). These findings provide further longitudinal evidence for the role of situational as well as dispositional factors for predicting job satisfaction. In addition, growth rates per year were better predictors than initial levels. Furthermore, a lack of change in job control or CSE went along with a drop in job satisfaction, implying that young workers need to perceive things to be improving in order to increase, or at least maintain, their level of job satisfaction. In terms of theory, the relative importance of levels versus changes deserves more attention. In terms of practical implications, our results suggest a double emphasis on job design (i.e., granting sufficient, and increasing, control) and on personal development (e.g., through training) so that people experience a match between both. Finally, negative associations between initial levels and growth rates suggest that people are quite successful in achieving a reasonable fit between their job characteristics and their needs and goals.