Architectural structures open new dimensions in magnetism: magnetic buckyballs

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Countrywide mapping of shrub forest using multi-sensor data and bias correction techniques

The continual increase of shrub forest in the Swiss Alps over the past few decades impacts biodiversity, forest succession and the protective function of forests. Therefore, up-to-date and area-wide information on its distribution is of great interest. To detect the shrub forest areas for the whole of Switzerland (41,285 km2), we developed an approach that uses Random Forest (RF), bias correction techniques and data from multiple remote sensing sources. Manual aerial orthoimage interpretation of shrub forest areas was conducted in a non-probabilistic way to derive initial training data. The multi-sensor and open access predictor data included digital terrain and vegetation height models obtained from Airborne Laser Scanning (ALS) and stereo-imagery, as well as Synthetic Aperture Radar (SAR) backscatter from Sentinel-1 and multispectral imagery from Sentinel-2. To mitigate the expected bias due to the training data sampling strategy, two techniques using RF probability estimates were tested to improve mapping accuracy. 1) an iterative and semi-automated active learning technique was used to generate further training data and 2) threshold-moving related object growing was applied. Both techniques facilitated the production of a shrub forest map for the whole of Switzerland at a spatial resolution of 10 m. An accuracy assessment was performed using independent data covering 7640 regularly distributed National Forest Inventory (NFI) plots. We observed the influence of the bias correction techniques and found higher accuracies after each performed iteration. The Mean Absolute Error (MAE) for the predicted shrub forest proportion was reduced from 6.04% to 2.68% while achieving a Mean Bias Error (MBE) of close to 0. The present study underscores the potential of combining multi-sensor data with bias correction techniques to provide cost-effective and accurate countrywide detection of shrub forest. Moreover, the map complements currently available NFI plot sample point data

The food additive vanillic acid controls transgene expression in mammalian cells and mice

Trigger-inducible transcription-control devices that reversibly fine-tune transgene expression in response to molecular cues have significantly advanced the rational reprogramming of mammalian cells. When designed for use in future gene- and cell-based therapies the trigger molecules have to be carefully chosen in order to provide maximum specificity, minimal side-effects and optimal pharmacokinetics in a mammalian organism. Capitalizing on control components that enable Caulobacter crescentus to metabolize vanillic acid originating from lignin degradation that occurs in its oligotrophic freshwater habitat, we have designed synthetic devices that specifically adjust transgene expression in mammalian cells when exposed to vanillic acid. Even in mice transgene expression was robust, precise and tunable in response to vanillic acid. As a licensed food additive that is regularly consumed by humans via flavoured convenience food and specific fresh vegetable and fruits, vanillic acid can be considered as a safe trigger molecule that could be used for diet-controlled transgene expression in future gene- and cell-based therapie

A prolonged outbreak of KPC-3-producing Enterobacter cloacae and Klebsiella pneumoniae driven by multiple mechanisms of resistance transmission at a large academic burn center

Klebsiella pneumoniae carbapenemase (KPC)-producing Enterobacter cloacae have been recently recognized in the United States. Whole-genome sequencing (WGS) has become a useful tool for analysis of outbreaks and for determining transmission networks of multidrug-resistant organisms in healthcare settings, including carbapenem-resistant Enterobacteriaceae (CRE). We experienced a prolonged outbreak of CRE of E. cloacae and K. pneumoniae over a three-year period at a large academic burn center despite rigorous infection control measures. To understand the molecular mechanisms that sustained this outbreak, we investigated the CRE outbreak isolates using WGS. Twenty-two clinical isolates of CRE, including E. cloacae (N=15) and K. pneumoniae (N=7), were sequenced and analyzed genetically. WGS revealed that this outbreak, which seemed epidemiologically unlinked, was in fact genetically linked over a prolonged period. Multiple mechanisms were found to account for the ongoing outbreak of KPC-3-producing E. cloacae and K. pneumoniae . This outbreak was primarily maintained by a clonal expansion of E. cloacae ST114 with distribution of multiple resistance determinants. Plasmid and transposon analysis suggested that the majority of bla KPC-3 was transmitted via an identical Tn 4401 b element on part of a common plasmid. WGS analysis demonstrated complex transmission dynamics within the burn center at levels of strain and/or plasmid in association with transposon, highlighting the versatility of KPC-producing Enterobacteriaceae in their ability to utilize multiple modes to resistance-gene propagation

Next-Generation Sequencing and Comparative Analysis of Sequential Outbreaks Caused by Multidrug-Resistant Acinetobacter baumannii at a Large Academic Burn Center

Next-generation sequencing (NGS) analysis has emerged as a promising molecular epidemiological method for investigating health care-associated outbreaks. Here, we used NGS to investigate a 3-year outbreak of multidrug-resistant Acinetobacter baumannii (MDRAB) at a large academic burn center. A reference genome from the index case was generated using de novo assembly of PacBio reads. Forty-six MDRAB isolates were analyzed by pulsed-field gel electrophoresis (PFGE) and sequenced using an Illumina platform. After mapping to the index case reference genome, four samples were excluded due to low coverage, leaving 42 samples for further analysis. Multilocus sequence types (MLST) and the presence of acquired resistance genes were also determined from the sequencing data. A transmission network was inferred from genomic and epidemiological data using a Bayesian framework. Based on single-nucleotide variant (SNV) differences, this MDRAB outbreak represented three sequential outbreaks caused by distinct clones. The first and second outbreaks were caused by sequence type 2 (ST2), while the third outbreak was caused by ST79. For the second outbreak, the MLST and PFGE results were discordant. However, NGS-based SNV typing detected a recombination event and consequently enabled a more accurate phylogenetic analysis. The distribution of resistance genes varied among the three outbreaks. The first- and second-outbreak strains possessed a bla OXA-23-like group, while the third-outbreak strains harbored a bla OXA-40-like group. NGS-based analysis demonstrated the superior resolution of outbreak transmission networks for MDRAB and provided insight into the mechanisms of strain diversification between sequential outbreaks through recombination

Efficacy and safety of argatroban in patients with acute respiratory distress syndrome and extracorporeal lung support

Background Extracorporeal membrane oxygenation (ECMO) or pumpless extracorporeal lung assist (pECLA) requires effective anticoagulation. Knowledge on the use of argatroban in patients with acute respiratory distress syndrome (ARDS) undergoing ECMO or pECLA is limited. Therefore, this study assessed the feasibility, efficacy and safety of argatroban in critically ill ARDS patients undergoing extracorporeal lung support. Methods This retrospective analysis included ARDS patients on extracorporeal lung support who received argatroban between 2007 and 2014 in a single ARDS referral center. As controls, patients who received heparin were matched for age, sex, body mass index and severity of illness scores. Major and minor bleeding complications, thromboembolic events, administered number of erythrocyte concentrates, thrombocytes and fresh-frozen plasmas were assessed. The number of extracorporeal circuit systems and extracorporeal lung support cannulas needed due to clotting was recorded. Also assessed was the efficacy to reach the targeted activated partial thromboplastin time (aPTT) in the first consecutive 14 days of therapy, and the controllability of aPTT values is within a therapeutic range of 50–75 s. Fisher’s exact test, Mann–Whitney U tests, Friedman tests and multivariate nonparametric analyses for longitudinal data (MANOVA; Brunner’s analysis) were applied where appropriate. Results Of the 535 patients who met the inclusion criteria, 39 receiving argatroban and 39 matched patients receiving heparin (controls) were included. Baseline characteristics were similar between the two groups, including severity of illness and organ failure scores. There were no significant differences in major and minor bleeding complications. Rates of thromboembolic events were generally low and were similar between the two groups, as were the rates of transfusions required and device-associated complications. The controllability of both argatroban and heparin improved over time, with a significantly increasing probability to reach the targeted aPTT corridor over the first days (p < 0.001). Over time, there were significantly fewer aPTT values below the targeted aPTT goal in the argatroban group than in the heparin group (p < 0.05). Both argatroban and heparin reached therapeutic aPTT values for adequate application of extracorporeal lung support. Conclusions Argatroban appears to be a feasible, effective and safe anticoagulant for critically ill ARDS patients undergoing extracorporeal lung support

A pore-size classification for peat bogs derived from unsaturated hydraulic properties

In ombrotrophic peatlands, the moisture content of the acrotelm (vadoze zone) controls oxygen diffusion rates, redox state, and the turnover of organic matter. Thus, variably saturated flow processes determine whether peatlands act as sinks or sources of atmospheric carbon, and modelling these processes is crucial to assess effects of changed environmental conditions on the future development of these ecosystems. We show that the Richards equation can be used to accurately describe the moisture dynamics under evaporative conditions in variably saturated peat soil, encompassing the transition from the topmost living moss layer to the decomposed peat as part of the vadose zone. Soil hydraulic properties (SHP) were identified by inverse simulation of evaporation experiments on samples from the entire acrotelm. To obtain consistent descriptions of the observations, the traditional van Genuchten–Mualem model was extended to account for non-capillary water storage and flow. We found that the SHP of the uppermost moss layer reflect a pore-size distribution (PSD) that combines three distinct pore systems of the Sphagnum moss. For deeper samples, acrotelm pedogenesis changes the shape of the SHP due to the collapse of inter-plant pores and an infill with smaller particles. This leads to gradually more homogeneous and bi-modal PSDs with increasing depth, which in turn can serve as a proxy for increasing state of pedogenesis in peatlands. From this, we derive a nomenclature and size classification for the pore spaces of Sphagnum mosses and define inter-, intra-, and inner-plant pore spaces, with effective pore diameters of >  300, 300–30, and 30–10 µm, respectively

DLR Forschungsinfrastruktur NGT-Fahrwerk (NGT-FuN)

Das Deutsche Zentrum für Luft- und Raumfahrt baut im Rahmen des Projektes Next Generation Train einen ersten Prototyp des für den Hochgeschwindigkeitsverkehr entwickelten, mechatronischen Einzelradfahrwerkes. Bis Ende 2022 wird das Fahrwerk mit einem Integrationsprüfstand in Betrieb genommen und anschließend auf Rollprüfständen und in Versuchsfahrzeugen weiter getestet

Application of artificial neural networks for editing measured acoustical data for simulations in virtual environments

Acoustic simulation tools are used and demanded by various groups of people. Architects and urban planners as well as product designers and engineers are interested in simulating the acoustical properties of buildings, machines or other products. Acoustic simulation techniques are continually evolving. The current trend is towards integrating forward-looking technologies like virtual reality (VR) into the simulation process. Common acoustical simulation tools, such as numerical methods, are computationally expensive and cannot be applied in real time. This, however, is a mandatory requirement for VR-applications. For that reason, techniques based on measured acoustical data are often used for acoustic simulations in VR. However, various disturbance variables, such as interfering noise, can distort measurement results immensely. In this paper an Artificial Neural Network (ANN) is described which can be used for the post-processing of measured data. A concept specifically for the noise cancellation in acoustic measurement data is outlined