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Nowadays, structural health monitoring of critical infrastructures is considered as of primal importance especially for managing transport infrastructure however most current SHM methodologies are based on point-sensors that show various limitations relating to their spatial positioning capabilities, cost of development and measurement range. This publication describes the progress in the SENSKIN EC co-funded research project that is developing a dielectric-elastomer sensor, formed from a large highly extensible capacitance sensing membrane and is supported by an advanced micro-electronic circuitry, for monitoring transport infrastructure bridges. The sensor under development provides spatial measurements of strain in excess of 10%, while the sensing system is being designed to be easy to install, require low power in operation concepts, require simple signal processing, and have the ability to self-monitor and report. An appropriate wireless sensor network is also being designed and developed supported by local gateways for the required data collection and exploitation. SENSKIN also develops a Decision-Support-System (DSS) for proactive condition-based structural interventions under normal operating conditions and reactive emergency intervention following an extreme event. The latter is supported by a life-cycle-costing (LCC) and life-cycle-assessment (LCA) module responsible for the total internal and external costs for the identified bridge rehabilitation, analysis of options, yielding figures for the assessment of the economic implications of the bridge rehabilitation work and the environmental impacts of the bridge rehabilitation options and of the associated secondary effects respectively. The overall monitoring system will be evaluated and benchmarked on actual bridges of Egnatia Highway (Greece) and Bosporus Bridge (Turkey).
Background: The pathophysiology behind the subacute but persistent hypercoagulable state after traumatic brain injury (TBI) is poorly understood but contributes to morbidity induced by venous thromboembolism. Because platelets and their microvesicles have been hypothesized to play a role in post-traumatic hypercoagulability, administration of commonly used agents may ameliorate this coagulability. We hypothesized that utilization of aspirin, ketorolac, amitriptyline, unfractionated heparin, or enoxaparin would modulate the platelet aggregation response after TBI. Methods: Concussive TBI was induced by weight drop. Mice were then randomized to receive aspirin, ketorolac, amitriptyline, heparin, enoxaparin, or saline control at 2 and 8 h after TBI. Mice were sacrificed at 6 or 24 h after injury to determine coagulability by rotational thromboelastometry (ROTEM), platelet function testing with impedance aggregometry, and microvesicle enumeration. Platelet sphingolipid metabolites were analyzed by mass spectrometry. Results: ROTEM demonstrated increased platelet contribution to maximum clot firmness at 6 h after TBI in mice that received aspirin or amitriptyline, but this did not persist at 24 h. By contrast, adenosine diphosphate- and arachidonic acid-induced platelet aggregation at 6 h was significantly lower in mice receiving ketorolac, aspirin, and amitriptyline compared with mice receiving saline at 6 h after injury and only arachidonic acid-initiated platelet aggregation was decreased by aspirin at 24 h. There were no differences in microvesicle production at either time point. Platelet sphingosine-1-phosphate levels were decreased at 6 h in the group receiving amitriptyline and increased at 24 h along with platelet ceramide levels at 24 h in the amitriptyline group. Conclusion: After TBI, amitriptyline decreased platelet aggregability and increased contribution to clot in a manner similar to aspirin. The amitriptyline effects on platelet function and sphingolipid metabolites may represent a possible role of the acid sphingomyelinase in the hypercoagulability observed after injury. In addition, inhibition of platelet reactivity may be an underappreciated benefit of low molecular weight heparins, such as enoxaparin. (C) 2019 Elsevier Inc. All rights reserved.
Ventilator-associated pneumonia (VAP) is a major cause of morbidity and mortality in critically ill patients. Here, we employed the broad antibacterial effects of sphingosine to prevent VAP by developing a novel method of coating surfaces of endotracheal tubes with sphingosine and sphingosine analogs. Sphingosine and phytosphingosine coatings of endotracheal tubes prevent adherence and mediate killing of Pseudomonas aeruginosa, Acinetobacter baumannii, and Staphylococcus aureus, even in biofilms. Most importantly, sphingosine-coating of endotracheal tubes also prevented P. aeruginosa and S. aureus pneumonia in vivo. Coating of the tubes with sphingosine was stable, without obvious side effects on tracheal epithelial cells and did not induce inflammation. In summary, we describe a novel method to coat plastic surfaces and provide evidence for the application of sphingosine and phytosphingosine as novel antimicrobial coatings to prevent bacterial adherence and induce killing of pathogens on the surface of endotracheal tubes with potential to prevent biofilm formation and VAP.Key messagesNovel dip-coating method to coat plastic surfaces with lipids.Sphingosine and phytosphingosine as novel antimicrobial coatings on plastic surface.Sphingosine coatings of endotracheal tubes prevent bacterial adherence and biofilms.Sphingosine coatings of endotracheal tubes induce killing of pathogens.Sphingosine coatings of endotracheal tubes ventilator-associated pneumonia.
Local probes of the electronic ground state are essential for understanding hydrogen bonding in aqueous environments. When tuned to the dissociative core-excited state at the O1s pre-edge of water, resonant inelastic X-ray scattering back to the electronic ground state exhibits a long vibrational progression due to ultrafast nuclear dynamics. We show how the coherent evolution of the OH bonds around the core-excited oxygen provides access to high vibrational levels in liquid water. The OH bonds stretch into the long-range part of the potential energy curve, which makes the X-ray probe more sensitive than infra-red spectroscopy to the local environment. We exploit this property to effectively probe hydrogen bond strength via the distribution of intramolecular OH potentials derived from measurements. In contrast, the dynamical splitting in the spectral feature of the lowest valence-excited state arises from the short-range part of the OH potential curve and is rather insensitive to hydrogen bonding.
The progress of science is tied to the standardization of measurements, instruments, and data. This is especially true in the Big Data age, where analyzing large data volumes critically hinges on the data being standardized. Accordingly, the lack of community-sanctioned data standards in paleoclimatology has largely precluded the benefits of Big Data advances in the field. Building upon recent efforts to standardize the format and terminology of paleoclimate data, this article describes the Paleoclimate Community reporTing Standard (PaCTS), a crowdsourced reporting standard for such data. PaCTS captures which information should be included when reporting paleoclimate data, with the goal of maximizing the reuse value of paleoclimate data sets, particularly for synthesis work and comparison to climate model simulations. Initiated by the LinkedEarth project, the process to elicit a reporting standard involved an international workshop in 2016, various forms of digital community engagement over the next few years, and grassroots working groups. Participants in this process identified important properties across paleoclimate archives, in addition to the reporting of uncertainties and chronologies; they also identified archive-specific properties and distinguished reporting standards for new versus legacy data sets. This work shows that at least 135 respondents overwhelmingly support a drastic increase in the amount of metadata accompanying paleoclimate data sets. Since such goals are at odds with present practices, we discuss a transparent path toward implementing or revising these recommendations in the near future, using both bottom-up and top-down approaches.
Biological responses to climate change have been widely documented across taxa and regions, but it remains unclear whether species are maintaining a good match between phenotype and environment, i.e. whether observed trait changes are adaptive. Here we reviewed 10,090 abstracts and extracted data from 71 studies reported in 58 relevant publications, to assess quantitatively whether phenotypic trait changes associated with climate change are adaptive in animals. A meta-analysis focussing on birds, the taxon best represented in our dataset, suggests that global warming has not systematically affected morphological traits, but has advanced phenological traits. We demonstrate that these advances are adaptive for some species, but imperfect as evidenced by the observed consistent selection for earlier timing. Application of a theoretical model indicates that the evolutionary load imposed by incomplete adaptive responses to ongoing climate change may already be threatening the persistence of species.
Background: Population-specificity of exploratory dietary patterns limits their generalizability in investigations with type 2 diabetes incidence.
Objective: The aim of this study was to derive country-specific exploratory dietary patterns, investigate their association with type 2 diabetes incidence, and replicate diabetes-associated dietary patterns in other countries.
Methods: Dietary intake data were used, assessed by country-specific questionnaires at baseline of 11,183 incident diabetes cases and 14,694 subcohort members (mean age 52.9 y) from 8 countries, nested within the European Prospective Investigation into Cancer and Nutrition study (mean follow-up time 6.9 y). Exploratory dietary patterns were derived by principal component analysis. HRs for incident type 2 diabetes were calculated by Prentice-weighted Cox proportional hazard regression models. Diabetes-associated dietary patterns were simplified or replicated to be applicable in other countries. A meta-analysis across all countries evaluated the generalizability of the diabetes-association.
Results: Two dietary patterns per country/UK-center, of which overall 3 dietary patterns were diabetes-associated, were identified. A risk-lowering French dietary pattern was not confirmed across other countries: pooled HRFrance per 1 SD: 1.00; 95% CI: 0.90, 1.10. Risk-increasing dietary patterns, derived in Spain and UK-Norfolk, were confirmed, but only the latter statistically significantly: HRSpain: 1.09; 95% CI: 0.97, 1.22 and HRUK-Norfolk: 1.12; 95% CI: 1.04, 1.20. Respectively, this dietary pattern was characterized by relatively high intakes of potatoes, processed meat, vegetable oils, sugar, cake and cookies, and tea. Conclusions: Only few country/center-specific dietary patterns (3 of 18) were statistically significantly associated with diabetes incidence in this multicountry European study population. One pattern, whose association with diabetes was confirmed across other countries, showed overlaps in the food groups potatoes and processed meat with identified diabetes-associated dietary patterns from other studies. The study demonstrates that replication of associations of exploratory patterns with health outcomes is feasible and a necessary step to overcome population-specificity in associations from such analyses.
The extragalactic background light (EBL), a diffuse photon field in the optical and infrared range, is a record of radiative processes over the universe?s history. Spectral measurements of blazars at very high energies (>100 GeV) enable the reconstruction of the spectral energy distribution (SED) of the EBL, as the blazar spectra are modified by redshift- and energy-dependent interactions of the gamma-ray photons with the EBL. The spectra of 14 VERITAS-detected blazars are included in a new measurement of the EBL SED that is independent of EBL SED models. The resulting SED covers an EBL wavelength range of 0.56?56 ?m, and is in good agreement with lower limits obtained by assuming that the EBL is entirely due to radiation from cataloged galaxies.
The angular size of a star is a critical factor in determining its basic properties1. Direct measurement of stellar angular diameters is difficult: at interstellar distances stars are generally too small to resolve by any individual imaging telescope. This fundamental limitation can be overcome by studying the diffraction pattern in the shadow cast when an asteroid occults a star2, but only when the photometric uncertainty is smaller than the noise added by atmospheric scintillation3. Atmospheric Cherenkov telescopes used for particle astrophysics observations have not generally been exploited for optical astronomy due to the modest optical quality of the mirror surface. However, their large mirror area makes them well suited for such high-time-resolution precision photometry measurements4. Here we report two occultations of stars observed by the Very Energetic Radiation Imaging Telescope Array System (VERITAS)5 Cherenkov telescopes with millisecond sampling, from which we are able to provide a direct measurement of the occulted stars’ angular diameter at the ≤0.1 mas scale. This is a resolution never achieved before with optical measurements and represents an order of magnitude improvement over the equivalent lunar occultation method6. We compare the resulting stellar radius with empirically derived estimates from temperature and brightness measurements, confirming the latter can be biased for stars with ambiguous stellar classifications.
Permafrost thaw subjects previously frozen organic carbon (OC) to microbial decomposition, generating the greenhouse gases (GHG) carbon dioxide (CO2) and methane (CH4) and fueling a positive climate feedback. Over one quarter of permafrost OC is stored in deep, ice-rich Pleistocene-aged yedoma permafrost deposits. We used a combination of anaerobic incubations, microbial sequencing, and ultrahigh-resolution mass spectrometry to show yedoma OC biolability increases with depth along a 12-m yedoma profile. In incubations at 3 degrees C and 13 degrees C, GHG production per unit OC at 12-versus 1.3-m depth was 4.6 and 20.5 times greater, respectively. Bacterial diversity decreased with depth and we detected methanogens at all our sampled depths, suggesting that in situ microbial communities are equipped to metabolize thawed OC into CH4. We concurrently observed an increase in the relative abundance of reduced, saturated OC compounds, which corresponded to high proportions of C mineralization and positively correlated with anaerobic GHG production potentials and higher proportions of OC being mineralized as CH4. Taking into account the higher global warming potential (GWP) of CH4 compared to CO2, thawed yedoma sediments in our study had 2 times higher GWP at 12-versus 9.0-m depth at 3 degrees C and 15 times higher GWP at 13 degrees C. Considering that yedoma is vulnerable to processes that thaw deep OC, our findings imply that it is important to account for this increasing GHG production and GWP with depth to better understand the disproportionate impact of yedoma on the magnitude of the permafrost carbon feedback.