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This opinion article describes recent approaches to use the "biorefinery" concept to lower the carbon footprint of typical mass polymers, by replacing parts of the fossil monomers with similar or even the same monomer made from regrowing dendritic biomass. Herein, the new and green catalytic synthetic routes are for lactic acid (LA), isosorbide (IS), 2,5-furandicarboxylic acid (FDCA), and p-xylene (pXL). Furthermore, the synthesis of two unconventional lignocellulosic biomass derivable monomers, i.e., alpha-methylene-gamma-valerolactone (MeGVL) and levoglucosenol (LG), are presented. All those have the potential to enter in a cost-effective way, also the mass market and thereby recover lost areas for polymer materials. The differences of catalytic unit operations of the biorefinery are also discussed and the challenges that must be addressed along the synthesis path of each monomers.
We study those nonlinear partial differential equations which appear as Euler-Lagrange equations of variational problems. On defining weak boundary values of solutions to such equations we initiate the theory of Lagrangian boundary value problems in spaces of appropriate smoothness. We also analyse if the concept of mapping degree of current importance applies to Lagrangian problems.
Gait analysis is an important tool for the early detection of neurological diseases and for the assessment of risk of falling in elderly people. The availability of low-cost camera hardware on the market today and recent advances in Machine Learning enable a wide range of clinical and health-related applications, such as patient monitoring or exercise recognition at home. In this study, we evaluated the motion tracking performance of the latest generation of the Microsoft Kinect camera, Azure Kinect, compared to its predecessor Kinect v2 in terms of treadmill walking using a gold standard Vicon multi-camera motion capturing system and the 39 marker Plug-in Gait model. Five young and healthy subjects walked on a treadmill at three different velocities while data were recorded simultaneously with all three camera systems. An easy-to-administer camera calibration method developed here was used to spatially align the 3D skeleton data from both Kinect cameras and the Vicon system. With this calibration, the spatial agreement of joint positions between the two Kinect cameras and the reference system was evaluated. In addition, we compared the accuracy of certain spatio-temporal gait parameters, i.e., step length, step time, step width, and stride time calculated from the Kinect data, with the gold standard system. Our results showed that the improved hardware and the motion tracking algorithm of the Azure Kinect camera led to a significantly higher accuracy of the spatial gait parameters than the predecessor Kinect v2, while no significant differences were found between the temporal parameters. Furthermore, we explain in detail how this experimental setup could be used to continuously monitor the progress during gait rehabilitation in older people.
Glacial-cycle simulations of the Antarctic Ice Sheet with the Parallel Ice Sheet Model (PISM)
(2020)
The Parallel Ice Sheet Model (PISM) is applied to the Antarctic Ice Sheet over the last two glacial cycles (approximate to 210 000 years) with a resolution of 16 km. An ensemble of 256 model runs is analyzed in which four relevant model parameters have been systematically varied using full-factorial parameter sampling. Parameters and plausible parameter ranges have been identified in a companion paper (Albrecht et al., 2020) and are associated with ice dynamics, climatic forcing, basal sliding and bed deformation and represent distinct classes of model uncertainties. The model is scored against both modern and geologic data, including reconstructed grounding-line locations, elevation-age data, ice thickness, surface velocities and uplift rates. An aggregated score is computed for each ensemble member that measures the overall model-data misfit, including measurement uncertainty in terms of a Gaussian error model (Briggs and Tarasov, 2013). The statistical method used to analyze the ensemble simulation results follows closely the simple averaging method described in Pollard et al. (2016).
This analysis reveals clusters of best-fit parameter combinations, and hence a likely range of relevant model and boundary parameters, rather than individual best-fit parameters. The ensemble of reconstructed histories of Antarctic Ice Sheet volumes provides a score-weighted likely range of sea-level contributions since the Last Glacial Maximum (LGM) of 9.4 +/- 4.1m (or 6.5 +/- 2.0 x 10(6) km(3)), which is at the upper range of most previous studies. The last deglaciation occurs in all ensemble simulations after around 12 000 years before present and hence after the meltwater pulse 1A (MWP1a). Our ensemble analysis also provides an estimate of parametric uncertainty bounds for the present-day state that can be used for PISM projections of future sea-level contributions from the Antarctic Ice Sheet.
Glacial-cycle simulations of the Antarctic Ice Sheet with the Parallel Ice Sheet Model (PISM)
(2020)
Simulations of the glacial-interglacial history of the Antarctic Ice Sheet provide insights into dynamic threshold behavior and estimates of the ice sheet's contributions to global sea-level changes for the past, present and future. However, boundary conditions are weakly constrained, in particular at the interface of the ice sheet and the bedrock. Also climatic forcing covering the last glacial cycles is uncertain, as it is based on sparse proxy data. <br /> We use the Parallel Ice Sheet Model (PISM) to investigate the dynamic effects of different choices of input data, e.g., for modern basal heat flux or reconstructions of past changes of sea level and surface temperature. As computational resources are limited, glacial-cycle simulations are performed using a comparably coarse model grid of 16 km and various parameterizations, e.g., for basal sliding, iceberg calving, or for past variations in precipitation and ocean temperatures. In this study we evaluate the model's transient sensitivity to corresponding parameter choices and to different boundary conditions over the last two glacial cycles and provide estimates of involved uncertainties. We also discuss isolated and combined effects of climate and sea-level forcing. Hence, this study serves as a "cookbook" for the growing community of PISM users and paleo-ice sheet modelers in general. <br /> For each of the different model uncertainties with regard to climatic forcing, ice and Earth dynamics, and basal processes, we select one representative model parameter that captures relevant uncertainties and motivates corresponding parameter ranges that bound the observed ice volume at present. The four selected parameters are systematically varied in a parameter ensemble analysis, which is described in a companion paper.
Whereas stable homogenous states of aqueous hydrocarbon solutions are typically observed at high temperatures and pressures far beyond the critical values corresponding to individual components, the stability of such system may be preserved upon transition into the region of metastable states at low temperatures and low pressures. This work is dedicated to the study of the thermal stability of a water-methane mixture formed by cryogenic vapor phase deposition. The obtained thin films were studied using vibrational spectroscopy in the temperature range of 16-180 K. During thermal annealing of the samples, characteristic vibrational C-H modes of methane were monitored alongside the chamber pressure to register both structural changes and desorption of the film material. The obtained results reveal that upon the co-deposition of methane and water, methane molecules appear both in non-bound and trapped states. The observed broadening of the characteristic C-H stretching mode at 3010 cm(-1) upon an increase in temperature of the sample from 16 to 90 K, followed by narrowing of the peak as the temperature is reduced back to 16 K, indicates localization of methane molecules within the water matrix at lower temperatures.
Context
Transmission spectroscopy is a promising tool for the atmospheric characterization of transiting exoplanets. Because the planetary signal is faint, discrepancies have been reported regarding individual targets.
Aims
We investigate the dependence of the estimated transmission spectrum on deviations of the orbital parameters of the star-planet system that are due to the limb-darkening effects of the host star. We describe how the uncertainty on the orbital parameters translates into an uncertainty on the planetary spectral slope.
Methods
We created synthetic transit light curves in seven different wavelength bands, from the near-ultraviolet to the near-infrared, and fit them with transit models parameterized by fixed deviating values of the impact parameter b. First, we performed a qualitative study to illustrate the effect by presenting the changes in the transmission spectrum slope with different deviations of b. Then, we quantified these variations by creating an error envelope (for centrally transiting, off-center, and grazing systems) based on a derived typical uncertainty on b from the literature. Finally, we compared the variations in the transmission spectra for different spectral types of host stars.
Results
Our simulations show a wavelength-dependent offset that is more pronounced at the blue wavelengths where the limb-darkening effect is stronger. This offset introduces a slope in the planetary transmission spectrum that becomes steeper with increasing b values. Variations of b by positive or negative values within its uncertainty interval introduce positive or negative slopes, thus the formation of an error envelope. The amplitude from blue optical to near-infrared wavelength for a typical uncertainty on b corresponds to one atmospheric pressure scale height and more. This impact parameter degeneracy is confirmed for different host types; K stars present prominently steeper slopes, while M stars indicate features at the blue wavelengths.
Conclusions
We demonstrate that transmission spectra can be hard to interpret, basically because of the limitations in defining a precise impact parameter value for a transiting exoplanet. This consequently limits a characterization of its atmosphere.
Bacterial chemotaxis-a fundamental example of directional navigation in the living world-is key to many biological processes, including the spreading of bacterial infections. Many bacterial species were recently reported to exhibit several distinct swimming modes-the flagella may, for example, push the cell body or wrap around it. How do the different run modes shape the chemotaxis strategy of a multimode swimmer? Here, we investigate chemotactic motion of the soil bacterium Pseudomonas putida as a model organism. By simultaneously tracking the position of the cell body and the configuration of its flagella, we demonstrate that individual run modes show different chemotactic responses in nutrition gradients and, thus, constitute distinct behavioral states. On the basis of an active particle model, we demonstrate that switching between multiple run states that differ in their speed and responsiveness provides the basis for robust and efficient chemotaxis in complex natural habitats.