979 research outputs found

    Breakdown of anomalous channeling with ion energy for accurate strain determination in gan-based heterostructures

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    The influence of the beam energy on the determination of strain state with ion channeling in GaN-based heterostructures (HSs) is addressed. Experimental results show that anomalous channeling may hinder an accurate analysis due to the steering effects at the HS interface, which are more intense at lower ion energies. The experimental angular scans have been well reproduced by Monte Carlo simulations, correlating the steering effects with the close encounter probability at the interface. Consequently, limitations in the determination of the strain state by ion channeling can be overcome by selecting the adequate beam energy

    Induced innovation in energy technologies and systems: a review of evidence and potential implications for CO2 mitigation

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    We conduct a systematic, interdisciplinary review of empirical literature assessing evidence on induced innovation in energy and related technologies. We explore links between demand-drivers (both market-wide and targeted); indicators of innovation (principally, patents); and outcomes (cost reduction, efficiency, and multi-sector/macro consequences). We build on existing reviews in different fields and assess over 200 papers containing original data analysis. Papers linking drivers to patents, and indicators of cumulative capacity to cost reductions (experience curves), dominate the literature. The former does not directly link patents to outcomes; the latter does not directly test for the causal impact of on cost reductions). Diverse other literatures provide additional evidence concerning the links between deployment, innovation activities, and outcomes. We derive three main conclusions. (1) Demand-pull forces enhance patenting; econometric studies find positive impacts in industry, electricity and transport sectors in all but a few specific cases. This applies to all drivers - general energy prices, carbon prices, and targeted interventions that build markets. (2) Technology costs decline with cumulative investment for almost every technology studied across all time periods, when controlled for other factors. Numerous lines of evidence point to dominant causality from at-scale deployment (prior to self-sustaining diffusion) to cost reduction in this relationship. (3) Overall Innovation is cumulative, multi-faceted, and self-reinforcing in its direction (path-dependent). We conclude with brief observations on implications for modeling and policy. In interpreting these results, we suggest distinguishing the economics of active deployment, from more passive diffusion processes, and draw the following implications. There is a role for policy diversity and experimentation, with evaluation of potential gains from innovation in the broadest sense. Consequently, endogenising innovation in large-scale models is important for deriving policy-relevant conclusions. Finally, seeking to relate quantitative economic evaluation to the qualitative socio-technical transitions literatures could be a fruitful area for future research

    Effects of mixed versus blocked design on stimulus evaluation: combining underaddative effects.

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    (from the journal abstract) According to the asynchronous discrete coding model of Miller, two manipulations should display underadditive effects on reaction time if they slow down noncontingent stages associated with the processing of two separable dimensions of a stimulus. Underadditive effects are also predicted by a dual route model when a task variable is factorially varied with design type (mixed vs blocked). Interpretations of both underadditive effects and their combination were evaluated. Intact and degraded stimuli were presented to 18 young adults either in a single block (mixed) or in separate blocks (blocked). Spatial stimulus-response (S-R) compatibility was manipulated in all conditions. Stimulus degradation and S-R compatibility interacted underadditively, but only in blocked presentations. Both interpretations of underadditive effects were supported. Eye-movement registrations provided additional support for the alternative routes model

    Modeling and Simulation of Multi-Lane Traffic Flow

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    A most important aspect in the field of traffic modeling is the simulation of bottleneck situations. For their realistic description a macroscopic multi-lane model for uni-directional freeways including acceleration, deceleration, velocity fluctuations, overtaking and lane-changing maneuvers is systematically deduced from a gas-kinetic (Boltzmann-like) approach. The resulting equations contain corrections with respect to previous models. For efficient computer simulations, a reduced model delineating the coarse-grained temporal behavior is derived and applied to bottleneck situations.Comment: For related work see http://www.theo2.physik.uni-stuttgart.de/helbing.htm

    Congested Traffic States in Empirical Observations and Microscopic Simulations

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    We present data from several German freeways showing different kinds of congested traffic forming near road inhomogeneities, specifically lane closings, intersections, or uphill gradients. The states are localized or extended, homogeneous or oscillating. Combined states are observed as well, like the coexistence of moving localized clusters and clusters pinned at road inhomogeneities, or regions of oscillating congested traffic upstream of nearly homogeneous congested traffic. The experimental findings are consistent with a recently proposed theoretical phase diagram for traffic near on-ramps [D. Helbing, A. Hennecke, and M. Treiber, Phys. Rev. Lett. {\bf 82}, 4360 (1999)]. We simulate these situations with a novel continuous microscopic single-lane model, the ``intelligent driver model'' (IDM), using the empirical boundary conditions. All observations, including the coexistence of states, are qualitatively reproduced by describing inhomogeneities with local variations of one model parameter. We show that the results of the microscopic model can be understood by formulating the theoretical phase diagram for bottlenecks in a more general way. In particular, a local drop of the road capacity induced by parameter variations has practically the same effect as an on-ramp.Comment: Now published in Phys. Rev. E. Minor changes suggested by a referee are incorporated; full bibliographic info added. For related work see http://www.mtreiber.de/ and http://www.helbing.org

    Accounting for the increasing benefits from scarce ecosystems

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    Governments are catching up with economic theory and practice by increasingly integrating ecosystem service values into national planning processes, including benefitcost analyses of public policies. Such analyses require information not only about today’s benefits from ecosystem services but also on how benefits change over time. We address a key limitation of existing policy guidance, which assumes that benefits from ecosystem services remain unchanged. We provide a practical rule that is grounded in economic theory and evidence-based as a guideline for how benefits change over time: They rise as societies get richer and even more so when ecosystem services are declining. Our proposal will correct a substantial downward bias in currently used estimates of future ecosystem service values. This will help governments to reflect the importance of ecosystems more accurately in benefit-cost analyses and policy decisions they inform

    Multicentric validation of proteomic biomarkers in urine specific for diabetic nephropathy

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    Background: Urine proteome analysis is rapidly emerging as a tool for diagnosis and prognosis in disease states. For diagnosis of diabetic nephropathy (DN), urinary proteome analysis was successfully applied in a pilot study. The validity of the previously established proteomic biomarkers with respect to the diagnostic and prognostic potential was assessed on a separate set of patients recruited at three different European centers. In this case-control study of 148 Caucasian patients with diabetes mellitus type 2 and duration >= 5 years, cases of DN were defined as albuminuria >300 mg/d and diabetic retinopathy (n = 66). Controls were matched for gender and diabetes duration (n = 82). Methodology/Principal Findings: Proteome analysis was performed blinded using high-resolution capillary electrophoresis coupled with mass spectrometry (CE-MS). Data were evaluated employing the previously developed model for DN. Upon unblinding, the model for DN showed 93.8% sensitivity and 91.4% specificity, with an AUC of 0.948 (95% CI 0.898-0.978). Of 65 previously identified peptides, 60 were significantly different between cases and controls of this study. In <10% of cases and controls classification by proteome analysis not entirely resulted in the expected clinical outcome. Analysis of patient's subsequent clinical course revealed later progression to DN in some of the false positive classified DN control patients. Conclusions: These data provide the first independent confirmation that profiling of the urinary proteome by CE-MS can adequately identify subjects with DN, supporting the generalizability of this approach. The data further establish urinary collagen fragments as biomarkers for diabetes-induced renal damage that may serve as earlier and more specific biomarkers than the currently used urinary albumin
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