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The decision to exercise is not only bound to rational considerations but also automatic affective processes. The affective–reflective theory of physical inactivity and exercise (ART) proposes a theoretical framework for explaining how the automatic affective process (type‑1 process) will influence exercise behavior, i.e., through the automatic activation of exercise-related associations and a subsequent affective valuation of exercise. This study aimed to empirically test this assumption of the ART with data from 69 study participants. A single-measurement study, including within-subject experimental variation, was conducted. Automatic associations with exercise were first measured with a single-target implicit association test. The somato-affective core of the participants’ automatic valuation of exercise-related pictures was then assessed via heart rate variability (HRV) analysis, and the affective valence of the valuation was tested with a facial expression (FE; smile and frown) task. Exercise behavior was assessed via self-report. Multiple regression (path) analysis revealed that automatic associations predicted HRV reactivity (β = −0.24, p = .044); the signs of the correlation between automatic associations and the smile FE score was in the expected direction but remained nonsignificant (β = −0.21, p = .078). HRV reactivity predicted self-reported exercise behavior (β = −0.28, p = .013) (the same pattern of results was achieved for the frown FE score). The HRV-related results illustrate the potential role of automatic negative affective reactions to the thought of exercise as a restraining force in exercise motivation. For better empirical distinction between the two ART type‑1 process components, automatic associations and the affective valuation should perhaps be measured separately in the future. The results support the notion that automatic and affective processes should be regarded as essential aspects of the motivation to exercise.
The Ornstein–Uhlenbeck process is a stationary and ergodic Gaussian process, that is fully determined by its covariance function and mean. We show here that the generic definitions of the ensemble- and time-averaged mean squared displacements fail to capture these properties consistently, leading to a spurious ergodicity breaking. We propose to remedy this failure by redefining the mean squared displacements such that they reflect unambiguously the statistical properties of any stochastic process. In particular we study the effect of the initial condition in the Ornstein–Uhlenbeck process and its fractional extension. For the fractional Ornstein–Uhlenbeck process representing typical experimental situations in crowded environments such as living biological cells, we show that the stationarity of the process delicately depends on the initial condition.
A surface modification of ultraflat gold nanotriangles (AuNTs) with different shaped nanoparticles is of special relevance for surface-enhanced Raman scattering (SERS) and the photo-catalytic activity of plasmonic substrates. Therefore, different approaches are used to verify the flat platelet morphology of the AuNTs by oriented overgrowth with metal nanoparticles. The most important part for the morphological transformation of the AuNTs is the coating layer, containing surfactants or polymers. By using well established AuNTs stabilized by a dioctyl sodium sulfosuccinate (AOT) bilayer, different strategies of surface modification with noble metal nanoparticles are possible. On the one hand undulated superstructures were synthesized by in situ growth of hemispherical gold nanoparticles in the polyethyleneimine (PEI)-coated AOT bilayer of the AuNTs. On the other hand spiked AuNTs were obtained by a direct reduction of Au³⁺ ions in the AOT double layer in presence of silver ions and ascorbic acid as reducing agent. Additionally, crumble topping of the smooth AuNTs can be realized after an exchange of the AOT bilayer by hyaluronic acid, followed by a silver-ion mediated reduction with ascorbic acid. Furthermore, a decoration with silver nanoparticles after coating the AOT bilayer with the cationic surfactant benzylhexadecyldimethylammonium chloride (BDAC) can be realized. In that case the ultraviolet (UV)-absorption of the undulated Au@Ag nanoplatelets can be tuned depending on the degree of decoration with silver nanoparticles. Comparing the Raman scattering data for the plasmon driven dimerization of 4-nitrothiophenol (4-NTP) to 4,4′-dimercaptoazobenzene (DMAB) one can conclude that the most important effect of surface modification with a 75 times higher enhancement factor in SERS experiments becomes available by decoration with gold spikes.
Wind influences the development, architecture and morphology of plant roots and may modify subsequent interactions between plants and soil (plant–soil feedbacks—PSFs). However, information on wind effects on fine root morphology is scarce and the extent to which wind changes plant–soil interactions remains unclear. Therefore, we investigated the effects of two wind intensity levels by manipulating surrounding vegetation height in a grassland PSF field experiment. We grew four common plant species (two grasses and two non-leguminous forbs) with soil biota either previously conditioned by these or other species and tested the effect of wind on root:shoot ratio, fine root morphological traits as well as the outcome for PSFs. Wind intensity did not affect biomass allocation (i.e. root:shoot ratio) in any species. However, fine-root morphology of all species changed under high wind intensity. High wind intensity increased specific root length and surface area and decreased root tissue density, especially in the two grasses. Similarly, the direction of PSFs changed under high wind intensity in all four species, but differences in biomass production on the different soils between high and low wind intensity were marginal and most pronounced when comparing grasses with forbs. Because soils did not differ in plant-available nor total nutrient content, the results suggest that wind-induced changes in root morphology have the potential to influence plant–soil interactions. Linking wind-induced changes in fine-root morphology to effects on PSF improves our understanding of plant–soil interactions under changing environmental conditions.
Permafrost is warming in the northern high latitudes, inducing highly dynamic thaw-related permafrost disturbances across the terrestrial Arctic. Monitoring and tracking of permafrost disturbances is important as they impact surrounding landscapes, ecosystems and infrastructure. Remote sensing provides the means to detect, map, and quantify these changes homogeneously across large regions and time scales. Existing Landsat-based algorithms assess different types of disturbances with similar spatiotemporal requirements. However, Landsat-based analyses are restricted in northern high latitudes due to the long repeat interval and frequent clouds, in particular at Arctic coastal sites. We therefore propose to combine Landsat and Sentinel-2 data for enhanced data coverage and present a combined annual mosaic workflow, expanding currently available algorithms, such as LandTrendr, to achieve more reliable time series analysis. We exemplary test the workflow for twelve sites across the northern high latitudes in Siberia. We assessed the number of images and cloud-free pixels, the spatial mosaic coverage and the mosaic quality with spectral comparisons. The number of available images increased steadily from 1999 to 2019 but especially from 2016 onward with the addition of Sentinel-2 images. Consequently, we have an increased number of cloud-free pixels even under challenging environmental conditions, which then serve as the input to the mosaicking process. In a comparison of annual mosaics, the Landsat+Sentinel-2 mosaics always fully covered the study areas (99.9–100 %), while Landsat-only mosaics contained data-gaps in the same years, only reaching coverage percentages of 27.2 %, 58.1 %, and 69.7 % for Sobo Sise, East Taymyr, and Kurungnakh in 2017, respectively. The spectral comparison of Landsat image, Sentinel-2 image, and Landsat+Sentinel-2 mosaic showed high correlation between the input images and mosaic bands (e.g., for Kurungnakh 0.91–0.97 between Landsat and Landsat+Sentinel-2 mosaic and 0.92–0.98 between Sentinel-2 and Landsat+Sentinel-2 mosaic) across all twelve study sites, testifying good quality mosaic results. Our results show that especially the results for northern, coastal areas was substantially improved with the Landsat+Sentinel-2 mosaics. By combining Landsat and Sentinel-2 data we accomplished to create reliably high spatial resolution input mosaics for time series analyses. Our approach allows to apply a high temporal continuous time series analysis to northern high latitude permafrost regions for the first time, overcoming substantial data gaps, and assess permafrost disturbance dynamics on an annual scale across large regions with algorithms such as LandTrendr by deriving the location, timing and progression of permafrost thaw disturbances
Engineering biotechnological microorganisms to use methanol as a feedstock for bioproduction is a major goal for the synthetic metabolism community. Here, we aim to redesign the natural serine cycle for implementation in E. coli. We propose the homoserine cycle, relying on two promiscuous formaldehyde aldolase reactions, as a superior pathway design. The homoserine cycle is expected to outperform the serine cycle and its variants with respect to biomass yield, thermodynamic favorability, and integration with host endogenous metabolism. Even as compared to the RuMP cycle, the most efficient naturally occurring methanol assimilation route, the homoserine cycle is expected to support higher yields of a wide array of products. We test the in vivo feasibility of the homoserine cycle by constructing several E. coli gene deletion strains whose growth is coupled to the activity of different pathway segments. Using this approach, we demonstrate that all required promiscuous enzymes are active enough to enable growth of the auxotrophic strains. Our findings thus identify a novel metabolic solution that opens the way to an optimized methylotrophic platform.
Formaldehyde is a highly reactive compound that participates in multiple spontaneous reactions, but these are mostly deleterious and damage cellular components. In contrast, the spontaneous condensation of formaldehyde with tetrahydrofolate (THF) has been proposed to contribute to the assimilation of this intermediate during growth on C1 carbon sources such as methanol. However, the in vivo rate of this condensation reaction is unknown and its possible contribution to growth remains elusive. Here, we used microbial platforms to assess the rate of this condensation in the cellular environment. We constructed Escherichia coli strains lacking the enzymes that naturally produce 5,10-methylene-THF. These strains were able to grow on minimal medium only when equipped with a sarcosine (N-methyl-glycine) oxidation pathway that sustained a high cellular concentration of formaldehyde, which spontaneously reacts with THF to produce 5,10-methylene-THF. We used flux balance analysis to derive the rate of the spontaneous condensation from the observed growth rate. According to this, we calculated that a microorganism obtaining its entire biomass via the spontaneous condensation of formaldehyde with THF would have a doubling time of more than three weeks. Hence, this spontaneous reaction is unlikely to serve as an effective route for formaldehyde assimilation.
Many technical challenges still need to be overcome to improve the quality of the green coffee beans. In this work, the wet Arabica coffee processing in batch and continuous modus were investigated. Coffee beans samples as well as by-products and wastewaters collected at different production steps were analyzed in terms of their content in total phenols, antioxidant capacity, caffeine content, organic acids, reducing sugars, free amino group and protein content. The results showed that 40% of caffeine was removed with pulp. Green coffee beans showed highest concentration of organic acids and sucrose (4.96 ± 0.25 and 5.07 ± 0.39 g/100 g DW for the batch and continuous processing). Batch green coffee beans contained higher amount of phenols. 5-caffeoylquinic Acid (5-CQA) was the main constituent (67.1 and 66.0% for the batch and continuous processing, respectively). Protein content was 15 and 13% in the green coffee bean in batch and continuous processing, respectively. A decrease of 50 to 64% for free amino groups during processing was observed resulting in final amounts of 0.8 to 1.4% in the processed beans. Finally, the batch processing still revealed by-products and wastewater with high nutrient content encouraging a better concept for valorization.
Starch and Glycogen Analyses
(2020)
For complex carbohydrates, such as glycogen and starch, various analytical methods and techniques exist allowing the detailed characterization of these storage carbohydrates. In this article, we give a brief overview of the most frequently used methods, techniques, and results. Furthermore, we give insights in the isolation, purification, and fragmentation of both starch and glycogen. An overview of the different structural levels of the glucans is given and the corresponding analytical techniques are discussed. Moreover, future perspectives of the analytical needs and the challenges of the currently developing scientific questions are included
Electric currents flowing in the terrestrial ionosphere have conventionally been diagnosed by low-earth-orbit (LEO) satellites equipped with science-grade magnetometers and long booms on magnetically clean satellites. In recent years, there are a variety of endeavors to incorporate platform magnetometers, which are initially designed for navigation purposes, to study ionospheric currents. Because of the suboptimal resolution and significant noise of the platform magnetometers, however, most of the studies were confined to high-latitude auroral regions, where magnetic field deflections from ionospheric currents easily exceed 100 nT. This study aims to demonstrate the possibility of diagnosing weak low-/mid-latitude ionospheric currents based on platform magnetometers. We use navigation magnetometer data from two satellites, CryoSat-2 and the Gravity Recovery and Climate Experiment Follow-On (GRACE-FO), both of which have been intensively calibrated based on housekeeping data and a high-precision geomagnetic field model. Analyses based on 8 years of CryoSat-2 data as well as similar to 1.5 years of GRACE-FO data reproduce well-known climatology of inter-hemispheric field-aligned currents (IHFACs), as reported by previous satellite missions dedicated to precise magnetic observations. Also, our results show that C-shaped structures appearing in noontime IHFAC distributions conform to the shape of the South Atlantic Anomaly. The F-region dynamo currents are only partially identified in the platform magnetometer data, possibly because the currents are weaker than IHFACs in general and depend significantly on altitude and solar activity. Still, this study evidences noontime F-region dynamo currents at the highest altitude (717 km) ever reported. We expect that further data accumulation from continuously operating missions may reveal the dynamo currents more clearly during the next solar maximum.