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Objective:
This study aimed to systematically review and meta-analyze the effect of flywheel resistance training (FRT) versus traditional resistance training (TRT) on change of direction (CoD) performance in male athletes.
Methods:
Five databases were screened up to December 2021.
Results:
Seven studies were included. The results indicated a significantly larger effect of FRT compared with TRT (standardized mean difference [SMD] = 0.64). A within-group comparison indicated a significant large effect of FRT on CoD performance (SMD = 1.63). For TRT, a significant moderate effect was observed (SMD = 0.62). FRT of <= 2 sessions/week resulted in a significant large effect (SMD = 1.33), whereas no significant effect was noted for >2 sessions/week. Additionally, a significant large effect of <= 12 FRT sessions (SMD = 1.83) was observed, with no effect of >12 sessions. Regarding TRT, no significant effects of any of the training factors were detected (p > 0.05).
Conclusions:
FRT appears to be more effective than TRT in improving CoD performance in male athletes. Independently computed single training factor analyses for FRT indicated that <= 2 sessions/week resulted in a larger effect on CoD performance than >2 sessions/week. Additionally, a total of <= 12 FRT sessions induced a larger effect than >12 training sessions. Practitioners in sports, in which accelerative and decelerative actions occur in quick succession to change direction, should regularly implement FRT.
The objectives of this study were the identification in (morbidly) obese and nonobese patients of (i) the most appropriate body size descriptor for fosfomycin dose adjustments and (ii) adequacy of the currently employed dosing regimens. Plasma and target site (interstitial fluid of subcutaneous adipose tissue) concentrations after fosfomycin administration (8 g) to 30 surgery patients (15 obese/15 nonobese) were obtained from a prospective clinical trial. After characterization of plasma and microdialysis-derived target site pharmacokinetics via population analysis, short-term infusions of fosfomycin 3 to 4 times daily were simulated. The adequacy of therapy was assessed by probability of pharmacokinetic/pharmacodynamic target attainment (PTA) analysis based on the unbound drug-related targets of an %fT(>= MIC) (the fraction of time that unbound fosfomycin concentrations exceed the MIC during 24 h) of 70 and an fAUC(0-24h)/MIC (the area under the concentration-time curve from 0 to 24 h for the unbound fraction of fosfomycin relative to the MIC) of 40.8 to 83.3. Lean body weight, fat mass, and creatinine clearance calculated via adjusted body weight (ABW) (CLCRCG_ABW) of all patients (body mass index [BMI] = 20.1 to 52.0 kg/m(2)) explained a considerable proportion of between-patient pharmacokinetic variability (up to 31.0% relative reduction). The steady-state unbound target site/plasma concentration ratio was 26.3% lower in (morbidly) obese than nonobese patients. For infections with fosfomycin-susceptible pathogens (MIC <= 16 mg/L), intermittent "high-dosage" intravenous (i.v.) fosfomycin (8 g, three times daily) was sufficient to treat patients with a CLCRCG_ABW of,130 mL/min, irrespective of the pharmacokinetic/pharmacodynamic indices considered. For infections by Pseudomonas aeruginosa with a MIC of 32 mg/L, when the index fAUC0-24h/MIC is applied, fosfomycin might represent a promising treatment option in obese and nonobese patients, especially in combination therapy to complement beta-lactams, in which carbapenem-resistant P. aeruginosa is critical. In conclusion, fosfomycin showed excellent target site penetration in obese and nonobese patients. Dosing should be guided by renal function rather than obesity status.
The terrestrial ecosystem in the Yellow River Source Area (YRSA) is sensitive to climate change and human impacts, although past vegetation change and the degree of human disturbance are still largely unknown. A 170-cm-long sediment core covering the last 7,400 years was collected from Lake Xingxinghai (XXH) in the YRSA. Pollen, together with a series of other environmental proxies (including grain size, total organic carbon (TOC) and carbonate content), were analysed to explore past vegetation and environmental changes for the YRSA. Dominant and common pollen components-Cyperaceae, Poaceae, Artemisia, Chenopodiaceae and Asteraceae-are stable throughout the last 7,400 years. Slight vegetation change is inferred from an increasing trend of Cyperaceae and decreasing trend of Poaceae, suggesting that alpine steppe was replaced by alpine meadow at ca. 3.5 ka cal bp. The vegetation transformation indicates a generally wetter climate during the middle and late Holocene, which is supported by increased amounts of TOC and Pediastrum (representing high water-level) and is consistent with previous past climate records from the north-eastern Tibetan Plateau. Our results find no evidence of human impact on the regional vegetation surrounding XXH, hence we conclude the vegetation change likely reflects the regional climate signal.
Wildfires play an essential role in the ecology of boreal forests.
In eastern Siberia, fire activity has been increasing in recent years, challenging the livelihoods of local communities. Intensifying fire regimes also increase disturbance pressure on the boreal forests, which currently protect the permafrost beneath from accelerated degradation.
However, long-term relationships between changes in fire regime and forest structure remain largely unknown.
We assess past fire-vegetation feedbacks using sedimentary proxy records from Lake Satagay, Central Yakutia, Siberia, covering the past c. 10,800 years.
Results from macroscopic and microscopic charcoal analyses indicate high amounts of burnt biomass during the Early Holocene, and that the present-day, low-severity surface fire regime has been in place since c. 4,500 years before present.
A pollen-based quantitative reconstruction of vegetation cover and a terrestrial plant record based on sedimentary ancient DNA metabarcoding suggest a pronounced shift in forest structure toward the Late Holocene.
Whereas the Early Holocene was characterized by postglacial open larch-birch woodlands, forest structure changed toward the modern, mixed larch-dominated closed-canopy forest during the Mid-Holocene.
We propose a potential relationship between open woodlands and high amounts of burnt biomass, as well as a mediating effect of dense larch forest on the climate-driven intensification of fire regimes.
Considering the anticipated increase in forest disturbances (droughts, insect invasions, and wildfires), higher tree mortality may force the modern state of the forest to shift toward an open woodland state comparable to the Early Holocene.
Such a shift in forest structure may result in a positive feedback on currently intensifying wildfires.
These new long-term data improve our understanding of millennial-scale fire regime changes and their relationships to changes of vegetation in Central Yakutia, where the local population is already being confronted with intensifying wildfire seasons.
Drawing on the social-ecological perspective, this longitudinal study investigated the potential moderating effect of gender in the relationships among Machiavellianism, popularity goals, and cyberbullying involvement (i.e. victimization, perpetration) among adolescents from China, Cyprus, India, and the United States.
There were 2,452 adolescents (M-age = 14.85; SD = .53; 13-16 years old; 49.1% girls) from China, Cyprus, India, and the United States included in this study.
They completed surveys on Machiavellianism, popularity goals, and cyberbullying victimization and perpetration during the fall of 2014 (Time 1). One year later, during the fall of 2015, adolescents completed surveys on cyberbullying victimization and perpetration.
Findings revealed that Machiavellianism and popularity goals were both associated positively with Time 2 cyberbullying victimization and perpetration for all adolescents. The associations between Machiavellianism and Time 2 cyberbullying perpetration and between popularity goals and Time 2 cyberbullying perpetration were stronger for Chinese and Indian boys than girls.
Opposite patterns were found for popularity goals and Time 2 cyberbullying perpetration for adolescents from the United States.
Gender did not moderate any of the associations for Cypriot adolescents or for Time 2 cyberbullying victimization.
The social-ecological perspective provides a useful understanding of how various contexts influence bullying.
Modern stationary X-ray spectroscopy is unable to resolve rotational structure.
In the present paper, we propose to use time-resolved two color X-ray pump-probe spectroscopy with picosecond resolution for real-time monitoring of the rotational dynamics induced by the recoil effect.
The proposed technique consists of two steps.
The first short pump X-ray pulse ionizes the valence electron, which transfers angular momentum to the molecule.
The second time-delayed short probe X-ray pulse resonantly excites a 1s electron to the created valence hole.
Due to the recoil-induced angular momentum the molecule rotates and changes the orientation of transition dipole moment of core-excitation with respect to the transition dipole moment of the valence ionization, which results in a temporal modulation of the probe X-ray absorption as a function of the delay time between the pulses.
We developed an accurate theory of the X-ray pump-probe spectroscopy of the recoil-induced rotation and study how the energy of the photoelectron and thermal dephasing affect the structure of the time-dependent X-ray absorption using the CO molecule as a case-study.
We also discuss the feasibility of experimental observation of our theoretical findings, opening new perspectives in studies of molecular rotational dynamics.
We characterize finite-time thermodynamic processes of multidimensional quadratic overdamped systems.
Analytic expressions are provided for heat, work, and dissipation for any evolution of the system covariance matrix.
The Bures-Wasserstein metric between covariance matrices naturally emerges as the local quantifier of dissipation.
General principles of how to apply these geometric tools to identify optimal protocols are discussed.
Focusing on the relevant slow-driving limit, we show how these results can be used to analyze cases in which the experimental control over the system is partial.
Hantaviruses are enveloped viruses that possess a tri-segmented, negative-sense RNA genome.
The viral S-segment encodes the multifunctional nucleocapsid protein (N), which is involved in genome packaging, intracellular protein transport, immunoregulation, and several other crucial processes during hantavirus infection.
In this study, we generated fluorescently tagged N protein constructs derived from Puumalavirus (PUUV), the dominant hantavirus species in Central, Northern, and Eastern Europe.
We comprehensively characterized this protein in the rodent cell line CHO-K1, monitoring the dynamics of N protein complex formation and investigating co-localization with host proteins as well as the viral glycoproteins Gc and Gn.
We observed formation of large, fibrillar PUUV N protein aggregates, rapidly coalescing from early punctate and spike-like assemblies.
Moreover, we found significant spatial correlation of N with vimentin, actin, and P-bodies but not with microtubules. N constructs also co-localized with Gn and Gc albeit not as strongly as the glycoproteins associated with each other.
Finally, we assessed oligomerization of N constructs, observing efficient and concentration-dependent multimerization, with complexes comprising more than 10 individual proteins.
Through its magnetic activity, the Sun governs the conditions in Earth's vicinity, creating space weather events, which have drastic effects on our space- and ground-based technology.
One of the most important solar magnetic features creating the space weather is the solar wind that originates from the coronal holes (CHs).
The identification of the CHs on the Sun as one of the source regions of the solar wind is therefore crucial to achieve predictive capabilities.
In this study, we used an unsupervised machine-learning method, k-means, to pixel-wise cluster the passband images of the Sun taken by the Atmospheric Imaging Assembly on the Solar Dynamics Observatory in 171, 193, and 211 angstrom in different combinations.
Our results show that the pixel-wise k-means clustering together with systematic pre- and postprocessing steps provides compatible results with those from complex methods, such as convolutional neural networks.
More importantly, our study shows that there is a need for a CH database where a consensus about the CH boundaries is reached by observers independently.
This database then can be used as the "ground truth," when using a supervised method or just to evaluate the goodness of the models.
Brain activation during active balancing and its behavioral relevance in younger and older adults
(2022)
Age-related deterioration of balance control is widely regarded as an important phenomenon influencing quality of life and longevity, such that a more comprehensive understanding of the neural mechanisms underlying this process is warranted.
Specifically, previous studies have reported that older adults typically show higher neural activity during balancing as compared to younger counterparts, but the implications of this finding on balance performance remain largely unclear.
Using functional near-infrared spectroscopy (fNIRS), differences in the cortical control of balance between healthy younger (n = 27) and older (n = 35) adults were explored.
More specifically, the association between cortical functional activity and balance performance across and within age groups was investigated. To this end, we measured hemodynamic responses (i.e., changes in oxygenated and deoxygenated hemoglobin) while participants balanced on an unstable device.
As criterion variables for brain-behavior-correlations, we also assessed postural sway while standing on a free-swinging platform and while balancing on wobble boards with different levels of difficulty.
We found that older compared to younger participants had higher activity in prefrontal and lower activity in postcentral regions.
Subsequent robust regression analyses revealed that lower prefrontal brain activity was related to improved balance performance across age groups, indicating that higher activity of the prefrontal cortex during balancing reflects neural inefficiency.
We also present evidence supporting that age serves as a moderator in the relationship between brain activity and balance, i.e., cortical hemodynamics generally appears to be a more important predictor of balance performance in the older than in the younger. Strikingly, we found that age differences in balance performance are mediated by balancing-induced activation of the superior frontal gyrus, thus suggesting that differential activation of this region reflects a mechanism involved in the aging process of the neural control of balance.
Our study suggests that differences in functional brain activity between age groups are not a mere by-product of aging, but instead of direct behavioral relevance for balance performance.
Potential implications of these findings in terms of early detection of fall-prone individuals and intervention strategies targeting balance and healthy aging are discussed.
A magnetic field modifies optical properties and provides valley splitting in a molybdenum disulfide (MoS2) monolayer.
Here we demonstrate a scalable approach to the epitaxial synthesis of MoS2 monolayer on a magnetic graphene/Co system.
Using spin- and angle-resolved photoemission spectroscopy we observe a magnetic proximity effect that causes a 20 meV spin-splitting at the (Gamma) over bar point and canting of spins at the (K) over bar point in the valence band toward the in-plane direction of cobalt magnetization.
Our density functional theory calculations reveal that the in-plane spin component at (K) over bar is localized on Co atoms in the valence band, while in the conduction band it is localized on the MoS2 layer.
The calculations also predict a 16 meV spin-splitting at the (Gamma) over bar point and 8 meV (K) over bar-(K) over bar' valley asymmetry for an out-of-plane magnetization. These findings suggest control over optical transitions in MoS2 via Co magnetization. Our estimations show that the magnetic proximity effect is equivalent to the action of the magnetic field as large as 100 T.
We perform a statistical clustering analysis of upper main-sequence stars in the Large Magellanic Cloud (LMC) using data from the Visible and Infrared Survey Telescope for Astronomy survey of the Magellanic Clouds. We map over 2500 young stellar structures at 15 significance levels across similar to 120 square degrees centred on the LMC. The structures have sizes ranging from a few parsecs to over 1 kpc. We find that the young structures follow power-law size and mass distributions. From the perimeter-area relation, we derive a perimeter-area dimension of 1.44 +/- 0.20. From the mass-size relation and the size distribution, we derive two-dimensional fractal dimensions of 1.50 +/- 0.10 and 1.61 +/- 0.20, respectively. We find that the surface density distribution is well represented by a lognormal distribution. We apply the Larson relation to estimate the velocity dispersions and crossing times of these structures. Our results indicate that the fractal nature of the young stellar structures has been inherited from the gas clouds from which they form and that this architecture is generated by supersonic turbulence. Our results also suggest that star formation in the LMC is scale-free from 10 to 700 pc.
We present an astrometric and photometric wide-field study of the Galactic open star cluster M37 (NGC 2099). The studied field was observed with ground-based images covering a region of about four square degrees in the Sloan-like filters ugi. We exploited the Gaia catalogue to calibrate the geometric distortion of the large field mosaics, developing software routines that can be also applied to other wide-field instruments. The data are used to identify the hottest white dwarf (WD) member candidates of M37. Thanks to the Gaia EDR3 exquisite astrometry we identified seven such WD candidates, one of which, besides being a high-probability astrometric member, is the putative central star of a planetary nebula. To our knowledge, this is a unique object in an open cluster, and we have obtained follow-up low-resolution spectra that are used for a qualitative characterization of this young WD. Finally, we publicly release a three-colour atlas and a catalogue of the sources in the field of view, which represents a complement of existing material.
Assessing the risk of yield loss in African drought-affected regions is key to identify feasible solutions for stable crop production. Recent studies have demonstrated that Copula-based probabilistic methods are well suited for such assessment owing to reasonably inferring important properties in terms of exceedance probability and joint dependence of different characterization. However, insufficient attention has been given to quantifying the probability of yield loss and determining the contribution of climatic factors. This study applies the Copula theory to describe the dependence between drought and crop yield anomalies for rainfed maize, millet, and sorghum crops in sub-Saharan Africa (SSA). The environmental policy integrated climate model, calibrated with Food and Agriculture Organization country-level yield data, was used to simulate yields across SSA (1980-2012). The results showed that the severity of yield loss due to drought had a higher magnitude than the severity of drought itself. Sensitivity analysis to identify factors contributing to drought and high-temperature stresses for all crops showed that the amount of precipitation during vegetation and grain filling was the main driver of crop yield loss, and the effect of temperature was stronger for sorghum than for maize and millet. The results demonstrate the added value of probabilistic methods for drought-impact assessment. For future studies, we recommend looking into factors influencing drought and high-temperature stresses as individual/concurrent climatic extremes.
Magnetic fields can play an important role in stellar evolution. Among white dwarfs, the most common stellar remnant, the fraction of magnetic systems is more than 20 per cent. The origin of magnetic fields in white dwarfs, which show strengths ranging from 40 kG to hundreds of MG, is still a topic of debate. In contrast, only one magnetic hot subdwarf star has been identified out of thousands of known systems. Hot subdwarfs are formed from binary interaction, a process often associated with the generation of magnetic fields, and will evolve to become white dwarfs, which makes the lack of detected magnetic hot subdwarfs a puzzling phenomenon. Here we report the discovery of three new magnetic hot subdwarfs with field strengths in the range 300-500 kG. Like the only previously known system, they are all helium-rich O-type stars (He-sdOs). We analysed multiple archival spectra of the three systems and derived their stellar properties. We find that they all lack radial velocity variability, suggesting formation via a merger channel. However, we derive higher than typical hydrogen abundances for their spectral type, which are in disagreement with current model predictions. Our findings suggest a lower limit to the magnetic fraction of hot subdwarfs of 0.147(+0.143)(-0.047) per cent, and provide evidence for merger-induced magnetic fields which could explain white dwarfs with field strengths of 50-150 MG, assuming magnetic flux conservation.
Modern pollen-vegetation-climate relationships underpin palaeovegetation and palaeoclimate reconstructions from fossil pollen records. East Siberia is an ideal area for investigating the relationships between modern pollen assemblages and near natural vegetation under cold continental climate conditions. Reliable pollen-based quantitative vegetation and climate reconstructions are still scarce due to the limited number of modern pollen datasets. Furthermore, differences in pollen representation of samples from lake sediments and soils are not well understood. Here, we present a new pollen dataset of 48 moss/soil and 24 lake surface-sediment samples collected in Chukotka and central Yakutia in East Siberia. The pollen-vegetation-climate relationships were investigated by ordination analyses. Generally, tundra and taiga vegetation types can be well distinguished in the surface pollen assemblages. Moss/soil and lake samples contain generally similar pollen assemblages as revealed by a Procrustes comparison with some exceptions. Overall, modern pollen assemblages reflect the temperature and precipitation gradients in the study areas as revealed by constrained ordination analysis. We estimate the relative pollen productivity (RPP) of major taxa and the relevant source area of pollen (RSAP) for moss/soil samples from Chukotka and central Yakutia using Extended R-Value (ERV) analysis. The RSAP of the tundra-forest transition area in Chukotka and taiga area in central Yakutia are ca. 1300 and 360 m, respectively. For Chukotka, RPPs relative to both Poaceae and Ericaceae were estimated while RPPs for central Yakutia were relative only to Ericaceae. Relative to Ericaceae (reference taxon, RPP = 1), Larix, Betula, Picea, and Pinus are overrepresented while Alnus, Cyperaceae, Poaceae, and Salix are underrepresented in the pollen spectra. Our estimates are in general agreement with previously published values and provide the basis for reliable quantitative reconstructions of East Siberian vegetation.
Uncertainty in climate change impact studies for irrigated maize cropping systems in southern Spain
(2022)
This study investigates the main drivers of uncertainties in simulated irrigated maize yield under historical conditions as well as scenarios of increased temperatures and altered irrigation water availability.
Using APSIM, MONICA, and SIMPLACE crop models, we quantified the relative contributions of three irrigation water allocation strategies, three sowing dates, and three maize cultivars to the uncertainty in simulated yields.
The water allocation strategies were derived from historical records of farmer's allocation patterns in drip-irrigation scheme of the Genil-Cabra region, Spain (2014-2017).
By considering combinations of allocation strategies, the adjusted R-2 values (showing the degree of agreement between simulated and observed yields) increased by 29% compared to unrealistic assumptions of considering only near optimal or deficit irrigation scheduling. The factor decomposition analysis based on historic climate showed that irrigation strategies was the main driver of uncertainty in simulated yields (66%).
However, under temperature increase scenarios, the contribution of crop model and cultivar choice to uncertainty in simulated yields were as important as irrigation strategy. This was partially due to different model structure in processes related to the temperature responses.
Our study calls for including information on irrigation strategies conducted by farmers to reduce the uncertainty in simulated yields at field scale.
The contribution of dead zooplankton biomass to carbon cycle in aquatic ecosystems is practically unknown. Using abundance data of zooplankton in water column and dead zooplankton in sediment traps in Lake Stechlin, an ecological-mathematical model was developed to simulate the abundance and sinking of zooplankton carcasses and predict the related release of labile organic matter (LOM) into the water column. We found species-specific differences in mortality rate of the dominant zooplankton: Daphnia cucullata, Bosmina coregoni and Diaphanosoma brachyurum (0.008, 0.129 and 0.020 day(-1), respectively) and differences in their carcass sinking velocities in metalimnion (and hypolimnion): 2.1 (7.64), 14.0 (19.5) and 1.1 (5.9) m day(-1), respectively. Our model simulating formation and degradation processes of dead zooplankton predicted a bimodal distribution of the released LOM: epilimnic and metalimnic peaks of comparable intensity, ca. 1 mg DW m(-3) day(-1). Maximum degradation of carcasses up to ca. 1.7 mg DW m(-3) day(-1) occurred in the density gradient zone of metalimnion. LOM released from zooplankton carcasses into the surrounding water may stimulate microbial activity and facilitate microbial degradation of more refractory organic matter; therefore, dead zooplankton are expected to be an integral part of water column carbon source/sink dynamics in stratified lakes.
A bacterial effector counteracts host autophagy by promoting degradation of an autophagy component
(2022)
Beyond its role in cellular homeostasis, autophagy plays anti- and promicrobial roles in host-microbe interactions, both in animals and plants.
One prominent role of antimicrobial autophagy is to degrade intracellular pathogens or microbial molecules, in a process termed xenophagy.
Consequently, microbes evolved mechanisms to hijack or modulate autophagy to escape elimination.
Although well-described in animals, the extent to which xenophagy contributes to plant-bacteria interactions remains unknown.
Here, we provide evidence that Xanthomonas campestris pv. vesicatoria (Xcv) suppresses host autophagy by utilizing type-III effector XopL. XopL interacts with and degrades the autophagy component SH3P2 via its E3 ligase activity to promote infection.
Intriguingly, XopL is targeted for degradation by defense-related selective autophagy mediated by NBR1/Joka2, revealing a complex antagonistic interplay between XopL and the host autophagy machinery.
Our results implicate plant antimicrobial autophagy in the depletion of a bacterial virulence factor and unravel an unprecedented pathogen strategy to counteract defense-related autophagy in plant-bacteria interactions.
Etmopteridae (lantern sharks) is the most species-rich family of sharks, comprising more than 50 species.
Many species are described from few individuals, and re-collection of specimens is often hindered by the remoteness of their sampling sites.
For taxonomic studies, comparative morphological analysis of type specimens housed in natural history collections has been the main source of evidence.
In contrast, DNA sequence information has rarely been used.
Most lantern shark collection specimens, including the types, were formalin fixed before long-term storage in ethanol solutions.
The DNA damage caused by both fixation and preservation of specimens has excluded these specimens from DNA sequence-based phylogenetic analyses so far.
However, recent advances in the field of ancient DNA have allowed recovery of wet-collection specimen DNA sequence data.
Here we analyse archival mitochondrial DNA sequences, obtained using ancient DNA approaches, of two wet-collection lantern shark paratype specimens, namely Etmopterus litvinovi and E. pycnolepis, for which the type series represent the only known individuals.
Target capture of mitochondrial markers from single-stranded DNA libraries allows for phylogenetic placement of both species.
Our results suggest synonymy of E. benchleyi with E. litvinovi but support the species status of E. pycnolepis. This revised taxonomy is helpful for future conservation and management efforts, as our results indicate a larger distribution range of E. litvinovi. This study further demonstrates the importance of wet-collection type specimens as genetic resource for taxonomic research.
Auger-photoelectron coincidence spectroscopy (APECS) has been used to examine the electron correlation and itinerance effects in transition metals Cu, Ni and Co.
It is shown that the LVV Auger, in coincidence with 2p photoelectrons, spectra can be represented using atomic multiplet positions if the 3d-shell is localized (atomic-like) and with a self-convoluted valence band for band-like (itinerant) materials as explained using the Cini-Sawatzky model.
For transition metals, the 3d band changes from band-like to localized with increasing atomic number, with the possibility of a mixed behavior.
Our result shows that the LVV spectra of Cu can be represented by atomic multiplet calculations, those of Co resemble the self-convolution of the valence band and those of Ni are a mixture of both, consistent with the Cini-Sawatzky model.
Air chemistry is affected by the emission of biogenic volatile organic compounds (BVOCs), which originate from almost all plants in varying qualities and quantities. They also vary widely among different crops, an aspect that has been largely neglected in emission inventories. In particular, bioenergy-related species can emit mixtures of highly reactive compounds that have received little attention so far. For such species, long-term field observations of BVOC exchange from relevant crops covering different phenological phases are scarcely available. Therefore, we measured and modeled the emission of three prominent European bioenergy crops (maize, ryegrass, and oil-seed rape) for full rotations in north-eastern Germany. Using a proton transfer reaction-mass spectrometer combined with automatically moving large canopy chambers, we were able to quantify the characteristic seasonal BVOC flux dynamics of each crop species. The measured BVOC fluxes were used to parameterize and evaluate the BVOC emission module (JJv) of the physiology-oriented LandscapeDNDC model, which was enhanced to cover de novo emissions as well as those from plant storage pools. Parameters are defined for each compound individually. The model is used for simulating total compound-specific reactivity over several years and also to evaluate the importance of these emissions for air chemistry. We can demonstrate substantial differences between the investigated crops with oil-seed rape having 37-fold higher total annual emissions than maize. However, due to a higher chemical reactivity of the emitted blend in maize, potential impacts on atmospheric OH-chemistry are only 6-fold higher.
Detection of changes in dynamic balance could help identify older adults at fall risk. Walking on a narrow beam with its width, cognitive load, and arm position manipulated could be an alternative to current tests. Therefore, we examined additive and interactive effects of beam width, cognitive task (CT), and arm position on dynamic balance during beam walking in older adults. Twenty older adults (69 +/- 4y) walked on 6, 8, and 10-cm wide beams (2-cm high, 4-m-long), with and without CT, with three arm positions (free, crossed, akimbo). We determined cognitive errors, distance walked, step speed, root mean square (RMS) of center of mass (COM) displacement and trunk acceleration in the frontal plane. Beam width decrease progressively reduced distance walked and increased trunk acceleration RMS. Step speed decreased on the narrowest beam and with CT. Arm crossing decreased distance walked and step speed. COM displacement RMS and cognitive errors were not affected by any manipulation. In conclusion, distance walked indicated that beam width and arm position, but less so CT, affected dynamic balance, implying that beam walking has the potential to become a test of fall risk. Stability measurements suggested effective trunk adjustments to control COM position and keep dynamic balance during the task.
As the recent permafrost thawing of northern Asia proceeds due to anthropogenic climate change, precise and detailed palaeoecological records from past warm periods are essential to anticipate the extent of future permafrost variations. Here, based on the modern relationship between permafrost and vegetation (represented by pollen assemblages), we trained a Random Forest model using pollen and permafrost data and verified its reliability to reconstruct the history of permafrost in northern Asia during the Holocene. An early Holocene (12-8 cal ka BP) strong thawing trend, a middle-to-late Holocene (8-2 cal ka BP) relatively slow thawing trend, and a late Holocene freezing trend of permafrost in northern Asia are consistent with climatic proxies such as summer solar radiation and Northern Hemisphere temperature. The extensive distribution of permafrost in northern Asia inhibited the spread of evergreen coniferous trees during the early Holocene warming and might have decelerated the enhancement of the East Asian summer monsoon (EASM) by altering hydrological processes and albedo. Based on these findings, we suggest that studies of the EASM should consider more the state of permafrost and vegetation in northern Asia, which are often overlooked and may have a profound impact on climate change in this region.
Arctic coasts, which feature land-ocean transport of freshwater, sediments, and other terrestrial material, are impacted by climate change, including increased temperatures, melting glaciers, changes in precipitation and runoff.
These trends are assumed to affect productivity in fjordic estuaries.
However, the spatial extent and temporal variation of the freshwater-driven darkening of fjords remain unresolved.
The present study illustrates the spatio-temporal variability of suspended particulate matter (SPM) in the Adventfjorden estuary, Svalbard, using in-situ field campaigns and ocean colour remote sensing (OCRS) via high-resolution Sentinel-2 imagery.
To compute SPM concentration (C-SPMsat), a semi-analytical algorithm was regionally calibrated using local in-situ data, which improved the accuracy of satellite-derived SPM concentration by similar to 20% (MRD). Analysis of SPM concentration for two consecutive years (2019, 2020) revealed strong seasonality of SPM in Adventfjorden.
Highest estimated SPM concentrations and river plume extent (% of fjord with C-SPMsat > 30 mg L-1) occurred during June, July, and August.
Concurrently, we observed a strong relationship between river plume extent and average air temperature over the 24 h prior to the observation (R-2 = 0.69).
Considering predicted changes to environmental conditions in the Arctic region, this study highlights the importance of the rapidly changing environmental parameters and the significance of remote sensing in analysing fluxes in light attenuating particles, especially in the coastal Arctic Ocean.
Context.
Thermonuclear supernovae (SNe), a subset of which are the highly important SNe of Type Ia and Iax, are relatively poorly understood phenomena. One of the more promising scenarios leading up to the creation of a thermonuclear SN involves accretion of helium-rich material from a binary companion. Following the SN, the binary companion is then ejected from the location of the progenitor binary at velocities possibly large enough to unbind it from the gravitational potential of the Galaxy. Ejected companion stars should form a detectable population, if their production mechanism is not exceedingly rare.
Aims.
This study builds on previous works, producing the most extensive prediction of the properties of such a hypothetical population to date, taking both Chandrasekhar and non-Chandrasekhar mass events into account. These results are then used to define criteria for membership of this population and characterise putative subpopulations.
Methods.
This study contains 6 x 10(6) individual ejection trajectories out of the Galactic plane calculated with the stellar kinematics framework SHyRT, which are analysed with regard to their bulk observational properties. These are then put into context with the only previously identified population member US 708 and applied to a number of other possible candidate objects.
Results.
We find that two additional previously observed objects possess properties to warrant a designation as candidate objects. Characterisation of these object with respect to the predicted population finds all of them to be extreme in at least one astrometric observable. Higher mass ( >0 :7 M-circle dot) objects should be over-represented in the observationally accessible volume, with the ratio of bound to unbound objects being an accessible observable for the determination of the dominant terminal accretor mass. We find that current observations of runaway candidates within 10 kpc support a Galactic SN rate of the order of similar to 3 x 10(-7) yr(-1) to similar to 2 x 10(-6) yr(-1), three orders of magnitude below the inferred Galactic SN Ia rate and two orders of magnitude below the formation rate of predicted He-donor progenitors.
Conclusions.
The number of currently observed population members suggests that the He-donor scenario, as suspected before, is not a dominant contributor to the number of observed SNe Ia. However, even at the low event rate suggested, we find that the majority of possibly detectable population members is still undetected. The extreme nature of current population members suggests that a still larger number of objects has simply evaded detection up to this point, hinting at a higher contribution than is currently supported by observation.
Leaf area index (LAI) is a key variable in understanding and modeling crop-environment interactions.
With the advent of increasingly higher spatial resolution satellites and sensors mounted on remotely piloted aircrafts (RPAs), the use of remote sensing in precision agriculture is becoming more common.
Since also the availability of methods to retrieve LAI from image data have also drastically expanded, it is necessary to test simultaneously as many methods as possible to understand the advantages and disadvantages of each approach.
Ground-based LAI data from three years of barley experiments were related to remote sensing information using vegetation indices (VI), machine learning (ML) and radiative transfer models (RTM), to assess the relative accuracy and efficacy of these methods.
The optimized soil adjusted vegetation index and a modified version of the Weighted Difference Vegetation Index performed slightly better than any other retrieval method. However, all methods yielded coefficients of determination of around 0.7 to 0.9.
The best performing machine learning algorithms achieved higher accuracies when four Sentinel-2 bands instead of 12 were used.
Also, the good performance of VIs and the satisfactory performance of the 4-band RTM, strongly support the synergistic use of satellites and RPAs in precision agriculture. One of the methods used, Sen2-Agri, an open source ML-RTM-based operational system, was also able to accurately retrieve LAI, although it is restricted to Sentinel-2 and Landsat data.
This study shows the benefits of testing simultaneously a broad range of retrieval methods to monitor crops for precision agriculture.
Diffusion with stochastic resetting is a paradigm of resetting processes. Standard renewal or master equation approach are typically used to study steady state and other transport properties such as average, mean squared displacement etc.
What remains less explored is the two time point correlation functions whose evaluation is often daunting since it requires the implementation of the exact time dependent probability density functions of the resetting processes which are unknown for most of the problems.
We adopt a different approach that allows us to write a stochastic solution for a single trajectory undergoing resetting.
Moments and the autocorrelation functions between any two times along the trajectory can then be computed directly using the laws of total expectation. Estimation of autocorrelation functions turns out to be pivotal for investigating the ergodic properties of various observables for this canonical model.
In particular, we investigate two observables (i) sample mean which is widely used in economics and (ii) time-averaged-mean-squared-displacement (TAMSD) which is of acute interest in physics.
We find that both diffusion and drift-diffusion processes with resetting are ergodic at the mean level unlike their reset-free counterparts. In contrast, resetting renders ergodicity breaking in the TAMSD while both the stochastic processes are ergodic when resetting is absent. We quantify these behaviors with detailed analytical study and corroborate with extensive numerical simulations.
Our results can be verified in experimental set-ups that can track single particle trajectories and thus have strong implications in understanding the physics of resetting.
Although phytoliths are recognized as an important proxy for paleoenvironmental reconstruction, the quantitative relationship between phytoliths and climate is still debated. In order to provide an improved basis for phytolith-based paleoclimate reconstructions, a representative modern phytolith dataset is essential. Here, we synthesize a modern topsoil phytolith dataset for Northeast China, analyze its climatic significance, and apply it to a fossil phytolith series from the Hani peat core in Northeast China. The dataset comprises 660 topsoil phytolith assemblages from 289 sample sites. We compiled modern meteorological data to assess the quantitative relationship between the phytolith assemblages and climatic variables. Detrended correspondence analysis (DCA) and Redundancy analysis (RDA) were used to determine the dominant climatic variable influencing the phytolith distributions. The results showed that mean annual temperature (MAT) is the dominant variable controlling the spatial distribution of phytoliths, accounting for 8.91% of the total variance. Transfer function based on inverse deshrinking locally-weighted weighted averaging (LWWA_Inv) was developed for MAT (R-_boot(2) = 0.86, RMSEP = 1.02 degrees C). Applying the LWWA_Inv transfer function to fossil phytolith records from the Hani peat core enables quantitative inferences to be made about Holocene climate changes in Northeast China. Overall, combined with the LWWA_Inv method, the topsoil phytolith dataset of Northeast China can be used for reliable quantitative MAT reconstruction.
We investigate whether the distribution of maximum seasonal streamflow is significantly affected by catchment or climate state of the season/month ahead. We fit the Generalized Extreme Value (GEV) distribution to extreme seasonal streamflow for around 600 stations across Europe by conditioning the GEV location and scale parameters on 14 indices, which represent the season-ahead climate or catchment state. The comparison of these climate-informed models with the classical GEV distribution, with time-constant parameters, suggests that there is a substantial potential for seasonal forecasting of flood probabilities. The potential varies between seasons and regions. Overall, the season-ahead catchment wetness shows the highest potential, although climate indices based on large-scale atmospheric circulation, sea surface temperature or sea ice concentration also show some skill for certain regions and seasons. Spatially coherent patterns and a substantial fraction of climate-informed models are promising signs towards early alerts to increase flood preparedness already a season ahead.
Losses of radiation belt energetic particles by encounters with four of the inner Moons of Jupiter
(2022)
Based on an improved model of the moon absorption of Jovian radiation belt particles, we investigate quantitatively and comprehensively the absorption probabilities and particle lifetimes due to encounters with four of the inner moons of Jupiter (Amalthea, Thebe, Io, and Europa) inside L < 10. Our results demonstrate that the resultant average lifetimes of energetic protons and electrons vary dramatically between similar to 0.1 days and well above 1,000 days, showing a strong dependence on the particle equatorial pitch angle, kinetic energy and moon orbit. The average lifetimes of energetic protons and electrons against moon absorption are shortest for Io (i.e., similar to 0.1-10 days) and longest for Thebe (i.e., up to thousands of days), with the lifetimes in between for Europa and Amalthea. Due to the diploe tilt angle absorption effect, the average lifetimes of energetic protons and electrons vary markedly below and above alpha eq ${\alpha }_{\mathrm{e}\mathrm{q}}$ = 67 degrees. Overall, the average electron lifetimes exhibit weak pitch angle dependence, but the average proton lifetimes are strongly dependent on equatorial pitch angle. The average lifetimes of energetic protons decrease monotonically and substantially with the kinetic energy, but the average lifetimes of energetic electrons are roughly constant at energies <similar to 10 MeV, increase substantially around the Kepler velocities of the moons (similar to 10-50 MeV), and decrease quickly at even higher energies. Compared with the averaged electron lifetimes, the average proton lifetimes are longer at energies below a few MeV and shorter at energies above tens of MeV.
transferGWAS
(2022)
Motivation:
Medical images can provide rich information about diseases and their biology. However, investigating their association with genetic variation requires non-standard methods. We propose transferGWAS, a novel approach to perform genome-wide association studies directly on full medical images. First, we learn semantically meaningful representations of the images based on a transfer learning task, during which a deep neural network is trained on independent but similar data. Then, we perform genetic association tests with these representations.
Results:
We validate the type I error rates and power of transferGWAS in simulation studies of synthetic images. Then we apply transferGWAS in a genome-wide association study of retinal fundus images from the UK Biobank. This first-of-a-kind GWAS of full imaging data yielded 60 genomic regions associated with retinal fundus images, of which 7 are novel candidate loci for eye-related traits and diseases.
Context. The Large Magellanic Cloud (LMC) is the most luminous satellite galaxy of the Milky Way and, owing to its companion, the Small Magellanic Cloud (SMC), represents an excellent laboratory to study the interaction of dwarf galaxies. Aims. The aim of this study is to investigate the kinematics of the outer regions of the LMC by using stellar proper motions to understand the impact of interactions, for example with the SMC about 250 Myr ago. Methods. We calculate proper motions using multi-epoch K s -band images from the VISTA survey of the Magellanic Cloud system (VMC). Observations span a time baseline of 2-5 yr. We combine the VMC data with data from the Gaia Early Data Release 3 and introduce a new method to distinguish between Magellanic and Milky Way stars based on a machine learning algorithm. This new technique enables a larger and cleaner sample selection of fainter sources as it reaches below the red clump of the LMC. Results. We investigate the impact of the SMC on the rotational field of the LMC and find hints of stripped SMC debris. The southeastern region of the LMC shows a slow rotational speed compared to the overall rotation. N-body simulations suggest that this could be caused by a fraction of stripped SMC stars located in that particular region that move opposite to the expected rotation.
Aims/hypothesis It was shown that maternal endothelial nitric oxide synthase (eNOS) deficiency causes fatty liver disease and numerically lower fasting glucose in female wild-type offspring, suggesting that parental genetic variants may influence the offspring's phenotype via epigenetic modifications in the offspring despite the absence of a primary genetic defect. The aim of the current study was to analyse whether paternal eNOS deficiency may cause the same phenotype as seen with maternal eNOS deficiency. Methods Heterozygous (+/-) male eNOS (Nos3) knockout mice or wild-type male mice were bred with female wild-type mice. The phenotype of wild-type offspring of heterozygous male eNOS knockout mice was compared with offspring from wild-type parents. Results Global sperm DNA methylation decreased and sperm microRNA pattern altered substantially. Fasting glucose and liver glycogen storage were increased when analysing wild-type male and female offspring of +/- eNOS fathers. Wild-type male but not female offspring of +/- eNOS fathers had increased fasting insulin and increased insulin after glucose load. Analysing candidate genes for liver fat and carbohydrate metabolism revealed that the expression of genes encoding glucocorticoid receptor (Gr; also known as Nr3c1) and peroxisome proliferator-activated receptor gamma coactivator 1-alpha (Pgc1a; also known as Ppargc1a) was increased while DNA methylation of Gr exon 1A and Pgc1a promoter was decreased in the liver of male wild-type offspring of +/- eNOS fathers. The endocrine pancreas in wild-type offspring was not affected. <br /> Conclusions/interpretation Our study suggests that paternal genetic defects such as eNOS deficiency may alter the epigenome of the sperm without transmission of the paternal genetic defect itself. In later life wild-type male offspring of +/- eNOS fathers developed increased fasting insulin and increased insulin after glucose load. These effects are associated with increased Gr and Pgc1a gene expression due to altered methylation of these genes.
Herein, the concept of constructing binder- and carbon additive-free organosulfur cathode was proved based on thiol-containing conducting polymer poly(4-(thiophene-3-yl) benzenethiol) (PTBT). The PTBT featured the polythiophene-structure main chain as a highly conducting framework and the benzenethiol side chain to copolymerize with sulfur and form a crosslinked organosulfur polymer (namely S/PTBT). Meanwhile, it could be in-situ deposited on the current collector by electro-polymerization, making it a binder-free and free-standing cathode for Li-S batteries. The S/PTBT cathode exhibited a reversible capacity of around 870 mAh g(-1) at 0.1 C and improved cycling performance compared to the physically mixed cathode (namely S&PTBT). This multifunction cathode eliminated the influence of the additives (carbon/binder), making it suitable to be applied as a model electrode for operando analysis. Operando X-ray imaging revealed the remarkable effect in the suppression of polysulfides shuttle via introducing covalent bonds, paving the way for the study of the intrinsic mechanisms in Li-S batteries.
With the increasing sensitivity of gravitational-wave detectors, we expect to observe multiple binary neutron-star systems through gravitational waves in the near future. The combined analysis of these gravitational-wave signals offers the possibility to constrain the neutron-star radius and the equation of state of dense nuclear matter with unprecedented accuracy. However, it is crucial to ensure that uncertainties inherent in the gravitational-wave models will not lead to systematic biases when information from multiple detections is combined. To quantify waveform systematics, we perform an extensive simulation campaign of binary neutron-star sources and analyze them with a set of four different waveform models. For our analysis with 38 simulations, we find that statistical uncertainties in the neutron-star radius decrease to 1250 m (2% at 90% credible interval) but that systematic differences between currently employed waveform models can be twice as large. Hence, it will be essential to ensure that systematic biases will not become dominant in inferences of the neutron-star equation of state when capitalizing on future developments.
Numerical studies of the dynamics of gravitational systems, e.g., black hole-neutron star systems, require physical and constraint-satisfying initial data. In this article, we present the newly developed pseudospectral code ELLIPTICA, an infrastructure for construction of initial data for various binary and single gravitational systems of all kinds. The elliptic equations under consideration are solved on a single spatial hypersurface of the spacetime manifold. Using coordinate maps, the hypersurface is covered by patches whose boundaries can adapt to the surface of the compact objects. To solve elliptic equations with arbitrary boundary condition, ELLIPTICA deploys a Schur complement domain decomposition method with a direct solver. In this version, we use cubed sphere coordinate maps and the fields are expanded using Chebyshev polynomials of the first kind. Here, we explain the building blocks of ELLIPTICA and the initial data construction algorithm for a black hole-neutron star binary system. We perform convergence tests and evolve the data to validate our results. Within our framework, the neutron star can reach spin values close to breakup with arbitrary direction, while the black hole can have arbitrary spin with dimensionless spin magnitude ∼0.8.
The nature of the interaction between prehistoric humans and their environment, especially the vegetation, has long been of interest. The Qinghai Lake Basin in North China is well-suited to exploring the interactions between prehistoric humans and vegetation in the Tibetan Plateau, because of the comparatively dense distribution of archaeological sites and the ecologically fragile environment. Previous pollen studies of Qinghai Lake have enabled a detailed reconstruction of the regional vegetation, but they have provided relatively little information on vegetation change within the Qinghai Lake watershed. To address the issue we conducted a pollen-based vegetation reconstruction for an archaeological site (YWY), located on the southern shore of Qinghai Lake. We used high temporal-resolution pollen records from the YWY site and from Qinghai Lake, spanning the interval since the last deglaciation (15.3 kyr BP to the present) to quantitatively reconstruct changes in the local and regional vegetation using Landscape Reconstruction Algorithm models. The results show that, since the late glacial, spruce forest grew at high altitudes in the surrounding mountains, while the lakeshore environment was occupied mainly by shrub-steppe. From the lateglacial to the middle Holocene, coniferous woodland began to expand downslope and reached the YWY site at 7.1 kyr BP. The living environment of the local small groups of Paleolithic-Epipaleolithic humans (during 15.3-13.1 kyr BP and 9-6.4 kyr BP) changed from shrub-steppe to coniferous forest-steppe. The pollen record shows no evidence of pronounced changes in the vegetation community corresponding to human activity. However, based on a comparison of the local and regional vegetation reconstructions, low values of biodiversity and a significant increase in two indicators of vegetation degradation, Chenopodiaceae and Rosaceae, suggest that prehistoric hunters-gatherers likely disturbed the local vegetation during 9.0-6.4 kyr BP. Our findings are a preliminary attempt to study human-environment interactions at Paleolithic-Epipaleolithic sites in the region, and they contribute to ongoing environmental archaeology research in the Tibetan Plateau.
Biodiversity maintains soil multifunctionality and soil organic carbon in novel urban ecosystems
(2022)
Biodiversity in urban ecosystems has the potential to increase ecosystem functions and support a suite of services valued by society, including services provided by soils. Specifically, the sequestration of carbon in soils has often been advocated as a solution to mitigate the steady increase in CO2 concentration in the atmosphere as a key driver of climate change. However, urban ecosystems are also characterized by an often high level of ecological novelty due to profound human-mediated changes, such as the presence of high numbers of non-native species, impervious surfaces or other disturbances. Yet it is poorly understood whether and how biodiversity affects ecosystem functioning and services of urban soils under these novel conditions. In this study, we assessed the influence of above- and below-ground diversity, as well as urbanization and plant invasions, on multifunctionality and organic carbon stocks of soils in non-manipulated grasslands along an urbanization gradient in Berlin, Germany. We focused on plant diversity (measured as species richness and functional trait diversity) and, in addition, on soil organism diversity as a potential mediator for the relationship of plant species diversity and ecosystem functioning. Our results showed positive effects of plant diversity on soil multifunctionality and soil organic carbon stocks along the entire gradient. Structural equation models revealed that plant diversity enhanced soil multifunctionality and soil organic carbon by increasing the diversity of below-ground organisms. These positive effects of plant diversity on soil multifunctionality and soil fauna were not restricted to native plant species only, but were also exerted by non-native species, although to a lesser degree. Synthesis. We conclude that enhancing diversity in plants and soil fauna of urban grasslands can increase the multifunctionality of urban soils and also add to their often underestimated but very valuable role in mitigating effects of climate change.
The geomagnetic activity index Kp is widely used but is restricted by low time resolution (3-hourly) and an upper limit. To address this, new geomagnetic activity indices, Hpo, are introduced. Similar to Kp, Hpo expresses the level of planetary geomagnetic activity in units of thirds (0o, 0+, 1-, 1o, 1+, 2-, horizontal ellipsis ) based on the magnitude of geomagnetic disturbances observed at subauroral observatories. Hpo has a higher time resolution than Kp. 30-min (Hp30) and 60-min (Hp60) indices are produced. The frequency distribution of Hpo is designed to be similar to that of Kp so that Hpo may be used as a higher time-resolution alternative to Kp. Unlike Kp, which is capped at 9o, Hpo is an open-ended index and thus can characterize severe geomagnetic storms more accurately. Hp30, Hp60 and corresponding linearly scaled ap30 and ap60 are available, in near real time, at the GFZ website (https://www.gfz-potsdam.de/en/hpo-index).
Rapidly evolving floods are rare but powerful drivers of landscape reorganisation that have severe and long-lasting impacts on both the functions of a landscape's subsystems and the affected society. The July 2021 flood that particularly hit several river catchments of the Eifel region in western Germany and Belgium was a drastic example. While media and scientists highlighted the meteorological and hydrological aspects of this flood, it was not just the rising water levels in the main valleys that posed a hazard, caused damage, and drove environmental reorganisation. Instead, the concurrent coupling of landscape elements and the wood, sediment, and debris carried by the fast-flowing water made this flood so devastating and difficult to predict. Because more intense floods are able to interact with more landscape components, they at times reveal rare non-linear feedbacks, which may be hidden during smaller events due to their high thresholds of initiation. Here, we briefly review the boundary conditions of the 14-15 July 2021 flood and discuss the emerging features that made this event different from previous floods. We identify hillslope processes, aspects of debris mobilisation, the legacy of sustained human land use, and emerging process connections and feedbacks as critical non-hydrological dimensions of the flood. With this landscape scale perspective, we develop requirements for improved future event anticipation, mitigation, and fundamental system understanding.
We perform numerical studies of a thermally driven, overdamped particle in a random quenched force field, known as the Sinai model. We compare the unbounded motion on an infinite 1-dimensional domain to the motion in bounded domains with reflecting boundaries and show that the unbounded motion is at every time close to the equilibrium state of a finite system of growing size. This is due to time scale separation: inside wells of the random potential, there is relatively fast equilibration, while the motion across major potential barriers is ultraslow. Quantities studied by us are the time dependent mean squared displacement, the time dependent mean energy of an ensemble of particles, and the time dependent entropy of the probability distribution. Using a very fast numerical algorithm, we can explore times up top 10(17) steps and thereby also study finite-time crossover phenomena.
Both children and adults have been shown to benefit from the integration of multisensory and sensorimotor enrichment into pedagogy. For example, integrating pictures or gestures into foreign language (L2) vocabulary learning can improve learning outcomes relative to unisensory learning. However, whereas adults seem to benefit to a greater extent from sensorimotor enrichment such as the performance of gestures in contrast to multisensory enrichment with pictures, this is not the case in elementary school children. Here, we compared multisensory- and sensorimotor-enriched learning in an intermediate age group that falls between the age groups tested in previous studies (elementary school children and young adults), in an attempt to determine the developmental time point at which children's responses to enrichment mature from a child-like pattern into an adult-like pattern. Twelve-year-old and fourteen-year-old German children were trained over 5 consecutive days on auditorily presented, concrete and abstract, Spanish vocabulary. The vocabulary was learned under picture-enriched, gesture-enriched, and non-enriched (auditory-only) conditions. The children performed vocabulary recall and translation tests at 3 days, 2 months, and 6 months post-learning. Both picture and gesture enrichment interventions were found to benefit children's L2 learning relative to non-enriched learning up to 6 months post-training. Interestingly, gesture-enriched learning was even more beneficial than picture-enriched learning for the 14-year-olds, while the 12-year-olds benefitted equivalently from learning enriched with pictures and gestures. These findings provide evidence for opting to integrate gestures rather than pictures into L2 pedagogy starting at 14 years of age.
Introduction: Remote telemonitoring (RTM) for patients with chronic heart failure (HF) holds promise to improve prognosis and well-being beyond the standard of care (SoC). The CardioBBEAT trial assessed the health economic and clinical impact of an interactive bidirectional RTM system (Motiva(R)) versus SoC for patients with HF and a reduced ejection fraction (HFrEF), in Germany.Methods: This multicenter, randomized controlled trial enrolled 621 patients with HFrEF (mean age 63.0 +/- 11.5 years, 88% men). The primary endpoint was the integrated effect of the intervention on total costs and nonhospitalized days alive after 12 months, reported as incremental cost-effectiveness ratio (ICER). Costs (in keuro) were based on actual charges of patients' statutory health insurance. Among secondary outcome measures were mortality and disease-specific quality of life.Results: We found a neutral effect on nonhospitalized days alive (RTM mean 341 +/- 59 days, SoC 346 +/- 45 days; p = 0.298) associated with increased total costs (RTM 18.5 +/- 39.5 keuro, SoC 12.8 +/- 22.0 keuro; p = 0.046). This yielded an ICER of -1.15 keuro/day. RTM did not impact mortality risk. All quality of life scales were consistently and meaningfully improved in the RTM group at 12 months compared to SoC (all p < 0.01).Conclusions: The first 12 months of RTM were not cost-effective compared to SoC in patients with HFrEF, but associated with a relevant improvement in disease-specific quality of life. The balanced assessment of the potential benefit of RTM requires integration of both the societal and patient perspective.ClinTrials.gov (NCT02293252).
Local biodiversity patterns are expected to strongly reflect variation in topography, land use, dispersal boundaries, nutrient supplies, contaminant spread, management practices, and other anthropogenic influences. Contrary to this expectation, studies focusing on specific taxa revealed a biodiversity homogenization effect in areas subjected to long-term intensive industrial agriculture. We investigated whether land use affects biodiversity levels and community composition (alpha- and beta-diversity) in 67 kettle holes (KH) representing small aquatic islands embedded in the patchwork matrix of a largely agricultural landscape comprising grassland, forest, and arable fields. These KH, similar to millions of standing water bodies of glacial origin, spread across northern Europe, Asia, and North America, are physico-chemically diverse and differ in the degree of coupling with their surroundings. We assessed aquatic and sediment biodiversity patterns of eukaryotes, Bacteria, and Archaea in relation to environmental features of the KH, using deep-amplicon-sequencing of environmental DNA (eDNA). First, we asked whether deep sequencing of eDNA provides a representative picture of KH aquatic biodiversity across the Bacteria, Archaea, and eukaryotes. Second, we investigated if and to what extent KH biodiversity is influenced by the surrounding land use. We hypothesized that richness and community composition will greatly differ in KH from agricultural land use compared with KH in grasslands and forests. Our data show that deep eDNA amplicon sequencing is useful for in-depth assessments of cross-domain biodiversity comprising both micro- and macro-organisms, but has limitations with respect to single-taxa conservation studies. Using this broad method, we show that sediment eDNA, integrating several years to decades, depicts the history of agricultural land-use intensification. Aquatic biodiversity was best explained by seasonality, whereas land-use type explained little of the variation. We concluded that, counter to our hypothesis, land use intensification coupled with landscape wide nutrient enrichment (including atmospheric deposition), groundwater connectivity between KH and organismal (active and passive) dispersal in the tight network of ponds, resulted in a biodiversity homogenization in the KH water, leveling off today's detectable differences in KH biodiversity between land-use types. These findings have profound implications for measures and management strategies to combat current biodiversity loss in agricultural landscapes worldwide.
Background: Adolescents and young adults (AYA) with a chronic medical condition show an increased risk for developing mental comorbidities compared to their healthy peers. Internet- and mobile-based cognitive behavioral therapy (iCBT) might be a low-threshold treatment to support affected AYA. In this randomized controlled pilot trial, the feasibility and potential efficacy of youthCOACH(CD), an iCBT targeting symptoms of anxiety and depression in AYA with chronic medical conditions, was evaluated. Methods: A total of 30 AYA (M-age 16.13; SD= 2.34; 73% female), aged 12-21 years either suffering from cystic fibrosis, juvenile idiopathic arthritis or type 1 diabetes, were randomly assigned to either a guided version of the iCBT youthCOACH(CD) (IC, n=15) or to a waitlist control group (CG, n=15), receiving an unguided version of the iCBT six months post-randomization. Participants of the IG and the CG were assessed before (t0), twelve weeks after (t1) and six months after (t2) randomization. Primary outcome was the feasibility of the iCBT. Different parameters of feasibility e.g. acceptance, client satisfaction or potential side effects were evaluated. First indications of the possible efficacy with regard to the primary efficacy outcome, the Patient Health Questionnaire Anxiety and Depression Scale, and further outcome variables were evaluated using linear regression models, adjusting for baseline values. Results: Regarding feasibility, intervention completion was 60%; intervention satisfaction (M = 25.42, SD = 5.85) and perceived therapeutic alliance (M = 2.83, SD = 1.25) were moderate and comparable to other iCBTs. No patterns emerged regarding subjective and objective negative side effects due to participation in youthCOACH(CD). Estimates of potential efficacy showed between group differences, with a potential medium-term benefit of youthCOACH(CD) (beta = -0.55, 95%Cl: -1.17; 0.07), but probably not short-term (beta = 0.20, 95%Cl: -0.47; 0.88). Conclusions: Our results point to the feasibility of youthCOACH(CD) and the implementation of a future definitive randomized controlled trial addressing its effectiveness and cost-effectiveness. Due to the small sample size, conclusions are premature, however, further strategies to foster treatment adherence should be considered.
Recent observations have revealed remarkable insights into the gas reservoir in the circumgalactic medium (CGM) of galaxy haloes. In this paper, we characterise the gas in the vicinity of Milky Way and Andromeda analogues in the hestia (High resolution Environmental Simulations of The Immediate Area) suite of constrained Local Group (LG) simulations. The hestia suite comprise of a set of three high-resolution arepo-based simulations of the LG, run using the Auriga galaxy formation model.
For this paper, we focus only on the 𝑧 = 0 simulation datasets and generate mock skymaps along with a power spectrum analysis to show that the distributions of ions tracing low-temperature gas (H i and Si iii) are more clumpy in comparison to warmer gas tracers (O vi, O vii and O viii). We compare to the spectroscopic CGM observations of M31 and low-redshift galaxies.
hestia under-produces the column densities of the M31 observations, but the simulations are consistent with the observations of low-redshift galaxies. A possible explanation for these findings is that the spectroscopic observations of M31 are contaminated by gas residing in the CGM of the Milky Way.
The present study estimated diet-related greenhouse gas emissions (GHGE) and land use (LU) in a sample of adults, examined main dietary contributors of GHGE, and evaluated socio demographic, lifestyle, and wellbeing factors as potential determinants of high environmental impact. A cross-sectional design based on data collected from the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam cohort (2010-2012) was used. Usual diet was assessed using food frequency questionnaires. Diet-related GHGE and LU were calculated using a European-average lifecycle analyses-food-item database (SHARP-ID). Information on potential determinants were collected using self-administered questionnaires. Men (n = 404) and women (n = 401) at an average age of 66.0 +/- 8.4 years were included. Dietary-related energy-adjusted GHGE in men was 6.6 +/- 0.9 and in women was 7.0 +/- 1.1 kg CO2 eq per 2000 kcal. LU in men was 7.8 +/- 1.2 and in women was 7.7 +/- 1.2 m(2)/year per 2000 kcal. Food groups contributing to most GHGE included dairy, meat and non-alcoholic beverages. Among women, being single, having a job, being a smoker and having higher BMI were characteristics associated with higher GHGE, whereas for men these included being married, longer sleeping duration and higher BMI. Further studies are warranted to provide insights into population-specific determinants of sustainable dietary choices.
The drug concentrations targeted in meropenem and piperacillin/tazobactam therapy also depend on the susceptibility of the pathogen. Yet, the pathogen is often unknown, and antibiotic therapy is guided by empirical targets. To reliably achieve the targeted concentrations, dosing needs to be adjusted for renal function. We aimed to evaluate a meropenem and piperacillin/tazobactam monitoring program in intensive care unit (ICU) patients by assessing (i) the adequacy of locally selected empirical targets, (ii) if dosing is adequately adjusted for renal function and individual target, and (iii) if dosing is adjusted in target attainment (TA) failure. In a prospective, observational clinical trial of drug concentrations, relevant patient characteristics and microbiological data (pathogen, minimum inhibitory concentration (MIC)) for patients receiving meropenem or piperacillin/tazobactam treatment were collected. If the MIC value was available, a target range of 1-5 x MIC was selected for minimum drug concentrations of both drugs. If the MIC value was not available, 8-40 mg/L and 16-80 mg/L were selected as empirical target ranges for meropenem and piperacillin, respectively. A total of 356 meropenem and 216 piperacillin samples were collected from 108 and 96 ICU patients, respectively. The vast majority of observed MIC values was lower than the empirical target (meropenem: 90.0%, piperacillin: 93.9%), suggesting empirical target value reductions. TA was found to be low (meropenem: 35.7%, piperacillin 50.5%) with the lowest TA for severely impaired renal function (meropenem: 13.9%, piperacillin: 29.2%), and observed drug concentrations did not significantly differ between patients with different targets, indicating dosing was not adequately adjusted for renal function or target. Dosing adjustments were rare for both drugs (meropenem: 6.13%, piperacillin: 4.78%) and for meropenem irrespective of TA, revealing that concentration monitoring alone was insufficient to guide dosing adjustment. Empirical targets should regularly be assessed and adjusted based on local susceptibility data. To improve TA, scientific knowledge should be translated into easy-to-use dosing strategies guiding antibiotic dosing.
Biochemical markers and wellness status during a congested match play period in elite soccer players
(2022)
Objectives:
To analyze biochemical markers, wellness status, and physical fitness in elite soccer players in relation to changes in training and match exposure during a congested period of match play.
Methods:
Fourteen elite soccer players were evaluated 3 times (T1, T2, and T3) over 12 weeks (T1-T2: 6-wk regular period of match play and T2-T3: 6-wk congested period of match play). Players performed vertical jump tests, repeated shuttle sprint ability test, and the Yo-Yo Intermittent Recovery Test at T1, T2, and T3. Plasma C-reactive protein, creatinine, and creatine kinase were analyzed at T1, T2, and T3. Wellness status was measured daily using the Hopper questionnaire (delayed onset of muscle soreness, stress, fatigue, and sleep quality). Training session rating of perceived exertion was also recorded on a daily basis.
Results:
A significant increase was found in stress, fatigue, delayed onset of muscle soreness scores, and Hopper index during the congested period (between T2 and T3) compared with the regular period (between T1 and T2) (.001 < P < .008, 0.8 < ES < 2.3). Between T2 and T3, significant relationships were found between the percentage variations (Delta%) of C-reactive protein, and Delta% of creatine kinase with the Hopper Index, and the Delta% of fatigue score. In addition, the Delta% of fatigue score and Delta% of delayed onset of muscle soreness score correlated with Delta% Yo-Yo Intermittent Recovery Test and Delta% best of repeated shuttle sprint ability test (.49 < r < P < .01).
Conclusions:
An intensive period of congested match play significantly compromised elite soccer players' physical fitness and wellness status. Elite soccer players' wellness status reflects declines in physical fitness during this period while biochemical changes do not.
Trophic transfer efficiency (TTE) is usually calculated as the ratio of production rates between two consecutive trophic levels. Although seemingly simple, TTE estimates from lakes are rare. In our review, we explore the processes and structures that must be understood for a proper lake TTE estimate.
We briefly discuss measurements of production rates and trophic positions and mention how ecological efficiencies, nutrients (N, P) and other compounds (fatty acids) affect energy transfer between trophic levels and hence TTE.
Furthermore, we elucidate how TTE estimates are linked with size-based approaches according to the Metabolic Theory of Ecology, and how food-web models can be applied to study TTE in lakes.
Subsequently, we explore temporal and spatial heterogeneity of production and TTE in lakes, with a particular focus on the links between benthic and pelagic habitats and between the lake and the terrestrial environment.
We provide an overview of TTE estimates from lakes found in the published literature. Finally, we present two alternative approaches to estimating TTE. First, TTE can be seen as a mechanistic quantity informing about the energy and matter flow between producer and consumer groups.
This approach is informative with respect to food-web structure, but requires enormous amounts of data. The greatest uncertainty comes from the proper consideration of basal production to estimate TTE of omnivorous organisms.
An alternative approach is estimating food-chain and food-web efficiencies, by comparing the heterotrophic production of single consumer levels or the total sum of all heterotrophic production including that of heterotrophic bacteria to the total sum of primary production.
We close the review by pointing to a few research questions that would benefit from more frequent and standardized estimates of TTE in lakes.
Lithium and boron are trace components of magmas, released during exsolution of a gas phase during volcanic activity.
In this study, we determine the diffusivity and isotopic fractionation of Li and B in hydrous silicate melts.
Two glasses were synthesized with the same rhyolitic composition (4.2 wt% water), having different Li and B contents; these were studied in diffusion-couple experiments that were performed using an internally heated pressure vessel, operated at 300 MPa in the temperature range 700-1250 degrees C for durations from 0 s to 24 h. From this we determined activation energies for Li and B diffusion of 57 +/- 4 kJ/mol and 152 +/- 15 kJ/mol with pre-exponential factors of 1.53 x 10(-7) m(2)/s and 3.80 x 10(-8) m(2)/s, respectively.
Lithium isotopic fractionation during diffusion gave beta values between 0.15 and 0.20, whereas B showed no clear isotopic fractionation.
Our Li diffusivities and isotopic fractionation results differ somewhat from earlier published values, but overall confirm that Li diffusivity increases with water content. Our results on B diffusion show that similarly to Li, B mobility increases in the presence of water.
By applying the Eyring relation, we confirm that B diffusivity is limited by viscous flow in silicate melts.
Our results on Li and B diffusion present a new tool for understanding degassing-related processes, offering a potential geospeedometer to measure volcanic ascent rates.
How accurately can we retrieve irrigation timing and water amounts from (satellite) soil moisture?
(2022)
While ensuring food security worldwide, irrigation is altering the water cycle and generating numerous environmental side effects. As detailed knowledge about the timing and the amounts of water used for irrigation over large areas is still lacking, remotely sensed soil moisture has proved potential to fill this gap.
However, the spatial resolution and revisit time of current satellite products represent a major limitation to accurately estimating irrigation. This work aims to systematically quantify their impact on the retrieved irrigation information, hence assessing the value of satellite soil moisture for estimating irrigation timing and water amounts.
In a real-world experiment, we modeled soil moisture using actual irrigation and meteorological data, obtained from farmers and weather stations, respectively. Modeled soil moisture was compared against various remotely sensed products differing in terms of spatio-temporal resolution to test the hypothesis that high-resolution observations can disclose the irrigation signal from individual fields while coarse-scale satellite products cannot.
Then, in a synthetic experiment, we systematically investigated the effect of soil moisture spatial and temporal resolution on the accuracy of irrigation estimates. The analysis was further elaborated by considering different irrigation scenarios and by adding realistic amounts of random errors in the soil moisture time series.
We show that coarse-scale remotely sensed soil moisture products achieve higher correlations with rainfed simulations, while high-resolution satellite observations agree significantly better with irrigated simulations, suggesting that high-resolution satellite soil moisture can inform on field-scale (similar to 40 ha) irrigation. A thorough analysis of the synthetic dataset showed that satisfactory results, both in terms of detection (F-score > 0.8) and quantification (Pearson's correlation > 0.8), are found for noise-free soil moisture observations either with a temporal sampling up to 3 days or if at least one-third of the pixel covers the irrigated field(s).
However, irrigation water amounts are systematically underestimated for temporal samplings of more than one day, and decrease proportionally to the spatial resolution, i.e., coarsening the pixel size leads to larger irrigation underestimations.
Although lower spatial and temporal resolutions decrease the detection and quantification accuracies (e.g., R between 0.6 and 1 depending on the irrigation rate and spatio-temporal resolution), random errors in the soil moisture time series have a stronger negative impact (Pearson R always smaller than 0.85).
As expected, better performances are found for higher irrigation rates, i.e. when more water is supplied during an irrigation event. Despite the potentially large underestimations, our results suggest that high-resolution satellite soil moisture has the potential to track and quantify irrigation, especially over regions where large volumes of irrigation water are applied to the fields, and given that low errors affect the soil moisture observations.
The process of species formation is characterized by the accumulation of multiple reproductive barriers. The evolution of hybrid male sterility, or Haldane's rule, typically characterizes later stages of species formation, when reproductive isolation is strongest.
Yet, understanding how quickly reproductive barriers evolve and their consequences for maintaining genetic boundaries between emerging species remains a challenging task because it requires studying taxa that hybridize in nature.
Here, we address these questions using the meadow grasshopper Pseudochorthippus parallelus, where populations that show multiple reproductive barriers, including hybrid male sterility, hybridize in two natural hybrid zones. Using mitochondrial data, we infer that such populations diverged some 100,000 years ago, at the beginning of the last glacial cycle in Europe.
Nuclear data show that contractions at multiple glacial refugia, and post-glacial expansions have facilitated genetic differentiation between lineages that today interact in hybrid zones.
We find extensive introgression throughout the sampled species range, irrespective of the current strength of reproductive isolation. Populations exhibiting hybrid male sterility in two hybrid zones show repeatable patterns of genomic differentiation, consistent with shared genomic constraints affecting ancestral divergence or with the role of those regions in reproductive isolation.
Together, our results suggest that reproductive barriers that characterize late stages of species formation can evolve relatively quickly, particularly when associated with strong demographic changes. Moreover, we show that such barriers persist in the face of extensive gene flow, allowing future studies to identify associated genomic regions.
In vitro transcribed (IVT)-mRNA has been accepted as a promising therapeutic modality. Advances in facile and rapid production technologies make IVT-mRNA an appealing alternative to protein- or virus-based medicines.
Robust expression levels, lack of genotoxicity, and their manageable immunogenicity benefit its clinical applicability.
We postulated that innate immune responses of therapeutically relevant human cells can be tailored or abrogated by combinations of 5'-end and internal IVT-mRNA modifications.
Using primary human macrophages as targets, our data show the particular importance of uridine modifications for IVT-mRNA performance.
Among five nucleotide modification schemes tested, 5-methoxy-uridine outperformed other modifications up to 4-fold increased transgene expression, triggering moderate proinflammatory and non-detectable antiviral responses.
Macrophage responses against IVT-mRNAs exhibiting high immunogenicity (e.g., pseudouridine) could be minimized upon HPLC purification. Conversely, 5'-end modifications had only modest effects on mRNA expression and immune responses.
Our results revealed how the uptake of chemically modified IVT-mRNA impacts human macrophages, responding with distinct patterns of innate immune responses concomitant with increased transient transgene expression.
We anticipate our findings are instrumental to predictively address specific cell responses required for a wide range of therapeutic applications from eliciting controlled immunogenicity in mRNA vaccines to, e.g., completely abrogating cell activation in protein replacement therapies.
Non-fullerene acceptors (NFAs) as used in state-of-the-art organic solar cells feature highly crystalline layers that go along with low energetic disorder.
Here, the crucial role of energetic disorder in blends of the donor polymer PM6 with two Y-series NFAs, Y6, and N4 is studied.
By performing temperature-dependent charge transport and recombination studies, a consistent picture of the shape of the density of state distributions for free charges in the two blends is developed, allowing an analytical description of the dependence of the open-circuit voltage V-OC on temperature and illumination intensity.
Disorder is found to influence the value of the V-OC at room temperature, but also its progression with temperature. Here, the PM6:Y6 blend benefits substantially from its narrower state distributions.
The analysis also shows that the energy of the equilibrated free charge population is well below the energy of the NFA singlet excitons for both blends and possibly below the energy of the populated charge transfer manifold, indicating a down-hill driving force for free charge formation.
It is concluded that energetic disorder of charge-separated states has to be considered in the analysis of the photovoltaic properties, even for the more ordered PM6:Y6 blend.
The dynamics of grassland ecosystems are highly complex due to multifaceted interactions among their soil, water, and vegetation components.
Precise simulations of grassland productivity therefore rely on accurately estimating a variety of parameters that characterize different processes of these systems.
This study applied three calibration schemes - a Single-Objective (SO-SUFI2), a Multi-Objective Pareto (MO-Pareto), and, a novel Uncertainty-Based Multi-Objective (MO-SUFI2) - to estimate the parameters of MONICA (Model for Nitrogen and Carbon Simulation) agro-ecosystem model in grassland ecosystems across Germany.
The MO-Pareto model is based on a traditional Pareto optimality concept, while the MO-SUFI2 optimizes multiple target variables considering their level of prediction uncertainty.
We used measurements of leaf area index, aboveground biomass, and soil moisture from experimental data at five sites with different intensities of cutting regimes (from two to five cutting events per season) to evaluate model performance.
Both MO-Pareto and MO-SUFI2 outperformed SO-SUFI2 during calibration and validation.
The comparison of the two MO approaches shows that they do not necessarily conflict with each other, but MO-SUFI2 provides complementary information for better estimations of model parameter uncertainty.
We used the obtained parameter ranges to simulate grassland productivity across Germany under different cutting regimes and quantified the uncertainty associated with estimated productivity across regions.
The results showed higher uncertainty in intensively managed grasslands compared to extensively managed grasslands, partially due to a lack of high-resolution input information concerning cutting dates. Furthermore, the additional information on the quantified uncertainty provided by our proposed MO-SUFI2 method adds deeper insights on confidence levels of estimated productivity.
Benefiting from additional management data collected at high resolution and ground measurements on the composition of grassland species mixtures appear to be promising solutions to reduce uncertainty and increase model reliability.
Objective:
The open expression of hatred, hostility, and violence against minorities has become a common online phenomenon. Adolescents are at particular risk of being involved in different hate speech roles (e.g., witness, perpetrator).
However, the correlates of their involvement as perpetrators and the mechanisms that might explain their involvement in hate speech across different roles have not yet been thoroughly investigated.
To this end, this study investigates moral disengagement and empathy as correlates of online hate speech perpetration and the moderation effects of empathy and moral disengagement in the relationship between witnessing and perpetrating online hate speech.
Method:
The sample consists of 3,560 7th to 9th graders from 40 schools in Germany and Switzerland. Self-report questionnaires were utilized to assess online hate speech involvement, moral disengagement, and empathy.
Results:
Multilevel regression analyses revealed that moral disengagement and witnessing online hate speech were positively associated with online hate speech perpetration, while empathy was negatively associated with it.
The findings also showed that the positive relationship between witnessing and perpetrating online hate speech was stronger at higher levels of moral disengagement and weaker when moral disengagement was low.
The association between witnessing and perpetrating online hate speech was weaker when adolescents had higher rather than lower levels of empathy.
Conclusions:
The findings underscore the need for prevention efforts to accelerate moral engagement and empathy as critical future directions in hate speech prevention. This study also contributes to our understanding of underlying mechanisms that explain adolescents' involvement across different roles in hate speech.
Adolescents around the globe are increasingly exposed to online hate speech (OHS). And yet little is known about the varying roles of involvement and the determinants of adolescents' hate speech perpetration.
Building on previous research, this study aims to test the cycle of violence hypothesis for OHS and to analyze whether moral disengagement (MD) and empathy moderate the victim-to-perpetrator relationship.
The sample consists of 3,560 seventh to ninth graders (52.1 percent girls), recruited from 40 schools across Germany and Switzerland. Self-report questionnaires were administered to assess OHS involvement, MD, and empathy.
Multilevel analyses revealed that victims of OHS were more likely to report OHS perpetration.
In addition, victims of OHS were more likely to report OHS perpetration when they reported higher levels of MD than those with lower levels of MD.
Finally, victims of OHS were less likely to report OHS perpetration when they reported higher levels of empathy than those with lower levels of empathy.
The findings extend the cycle of violence hypothesis to OHS and highlight the need to address MD and empathy in hate speech prevention. Implications for future research will be discussed.
Job satisfaction is a major driver of an individual’s subjective well-being and thus affects public health, societal prosperity, and organisations, as dissatisfied employees are less productive and more likely to change jobs. However, changing jobs does not necessarily lead to higher job satisfaction in the long run. Previous studies have shown, instead, that changing jobs only increases job satisfaction for a short period of time before it gradually falls back to similar levels as before. This phenomenon is known as the ’honeymoon–hangover’ pattern. In our study, we identify an important new moderator of the relation between job change and job satisfaction: the job–education match of job changes. Based on relative deprivation theory, we argue that job changes from being overeducated in a job lowers the likelihood of negative comparisons and thus increases the honeymoon period, lessens the hangover period, and increases long-term job satisfaction. We use data from the Socio-Economic Panel ranging from 1994–2018 and focus specifically on individual periods of employees before and after job changes (n = 134,404). Our results confirm that a change to a job that requires a matched education has a stronger and longer-lasting effect on job satisfaction, and that this effect is slightly lower for respondents born abroad.
Ground-motion models (GMMs) are often used to predict the random distribution of Spectral accelerations (SAs) at a site due to a nearby earthquake. In probabilistic seismic hazard and risk assessment, large earthquakes occurring close to a site are considered as critical scenarios. GMMs are expected to predict realistic SAs with low within-model uncertainty (sigma(mu)) for such rare scenarios. However, the datasets used to regress GMMs are usually deficient of data from critical scenarios. The (Kotha et al., A Regionally Adaptable Ground-Motion Model for Shallow Crustal Earthquakes in Europe Bulletin of Earthquake Engineering 18:4091-4125, 2020) GMM developed from the Engineering strong motion (ESM) dataset was found to predict decreasing short-period SAs with increasing M-W >= M-h = 6.2, and with large sigma(mu) at near-source distances <= 30km. In this study, we updated the parametrisation of the GMM based on analyses of ESM and the Near source strong motion (NESS) datasets. With M-h = 5.7, we could rectify the M-W scaling issue, while also reducing sigma(mu). at M-W >= M-h. We then evaluated the GMM against NESS data, and found that the SAs from a few large, thrust-faulting events in California, New Zealand, Japan, and Mexico are significantly higher than GMM median predictions. However, recordings from these events were mostly made on soft-soil geology, and contain anisotropic pulse-like effects. A more thorough non-ergodic treatment of NESS was not possible because most sites sampled unique events in very diverse tectonic environments. We provide an updated set of GMM coefficients,sigma(mu), and heteroscedastic variance models; while also cautioning against its application for M-W <= 4 in low-moderate seismicity regions without evaluating the homogeneity of M-W estimates between pan-European ESM and regional datasets.
Recent advances in organic solar cell performance have been mainly driven forward by combining high-performance p-type donor-acceptor copolymers (e.g.PM6) and non-fullerene small molecule acceptors (e.g.Y6) as bulk-heterojunction layers. A general observation in such devices is that the device performance, e.g., the open-circuit voltage, is strongly dependent on the processing solvent. While the morphology is a typically named key parameter, the energetics of donor-acceptor blends are equally important, but less straightforward to access in the active multicomponent layer. Here, we propose to use spectral onsets during electrochemical cycling in a systematic spectroelectrochemical study of blend films to access the redox behavior and the frontier orbital energy levels of the individual compounds. Our study reveals that the highest occupied molecular orbital offset (Delta E-HOMO) in PM6:Y6 blends is similar to 0.3 eV, which is comparable to the binding energy of Y6 excitons and therefore implies a nearly zero driving force for the dissociation of Y6 excitons. Switching the PM6 orientation in the blend films from face-on to edge-on in bulk has only a minor influence on the positions of the energy levels, but shows significant differences in the open circuit voltage of the device. We explain this phenomenon by the different interfacial molecular orientations, which are known to affect the non-radiative decay rate of the charge-transfer state. We compare our results to ultraviolet photoelectron spectroscopy data, which shows distinct differences in the HOMO offsets in the PM6:Y6 blend compared to neat films. This highlights the necessity to measure the energy levels of the individual compounds in device-relevant blend films.
Instrumental data show that the groundwater and lake levels in Northeast Germany have decreased over the past decades, and this process has accelerated over the past few years. In addition to global warming, the direct influence of humans on the local water balance is suspected to be the cause. Since the instrumental data usually go back only a few decades, little is known about the multidecadal to centennial-scale trend, which also takes long-term climate variation and the long-term influence by humans on the water balance into account. This study aims to quantitatively reconstruct the surface water areas in the Lower Havel Inner Delta and of adjacent Lake Gulpe in Brandenburg. The analysis includes the calculation of surface water areas from historical and modern maps from 1797 to 2020. The major finding is that surface water areas have decreased by approximately 30% since the pre-industrial period, with the decline being continuous. Our data show that the comprehensive measures in Lower Havel hydro-engineering correspond with groundwater lowering that started before recent global warming. Further, large-scale melioration measures with increasing water demands in the upstream wetlands beginning from the 1960s to the 1980s may have amplified the decline in downstream surface water areas.
Insights into the geographical origin and phylogeographical patterns of Paradisaea birds-of-paradise
(2022)
Birds-of-paradise represent a textbook example for geographical speciation and sexual selection. Perhaps the most iconic genus is Paradisaea, which is restricted to New Guinea and a few surrounding islands. Although several species concepts have been applied in the past to disentangle the different entities within this genus, no attempt has been made so far to uncover phylogeographical patterns based on a genetic dataset that includes multiple individuals per species. Here, we applied amplicon sequencing for the mitochondrial fragment Cytb for a total of 69 museum specimens representing all seven Paradisaea species described and inferred both phylogenetic relationships and colonization pathways across the island. Our analyses show that the most recent common ancestor of the diverging lineages within Paradisaea probably originated in the Late Miocene in the eastern part of the Central Range and suggest that tectonic processes played a key role in shaping the diversification and distribution of species. All species were recovered as monophyletic, except for those within the apoda-minor-raggiana clade, which comprises the allopatric and parapatric species P. apoda, P. minor and P. raggiana. The comparatively young divergence times, together with possible instances of mitochondrial introgression and incomplete lineage sorting, suggest recent speciation in this clade.
A dataset of 2184 field measurements reported in the literature was used to evaluate the predictive capability of eight conventional flow resistance equations to predict the mean flow velocity in gravel-bed rivers. The results reveal considerable disagreement with the observed flow velocities for relative submergence less than 4 and for the non-uniformity of the bed material greater than 7.5 for all the equations. However, the predictions made using the Smart and Jaggi (1983), Ferguson (2007), and Rickenmann and Recking (2011) equations were closer to the observed values. Furthermore, bedload sediment transport also reduces the predictive capability of the equations considered in this study except for the Recking et al. (2008) equation, which was developed consid- ering active bedload transport. The performance of flow resistance equations improves when corrected by considering the geometric standard deviation of the bed material. Here we present an empirical approach using the whole dataset and its subsets for accounting for the additional energy losses occurring due to the wake vortices, spill losses, and free surface instabilities occurring due to the protrusions from the bed. The results obtained using the validation dataset shows the importance and usefulness of this approach to account for the additional energy losses, especially for the Strickler (1923) and Keulegan (1938) equations.
Statistical distributions of flood peak discharge often show heavy tail behavior, that is, extreme floods are more likely to occur than would be predicted by commonly used distributions that have exponential asymptotic behavior.
This heavy tail behavior may surprise flood managers and citizens, as human intuition tends to expect light tail behavior, and the heaviness of the tails is very difficult to predict, which may lead to unnecessarily high flood damage.
Despite its high importance, the literature on the heavy tail behavior of flood distributions is rather fragmented.
In this review, we provide a coherent overview of the processes causing heavy flood tails and the implications for science and practice.
Specifically, we propose nine hypotheses on the mechanisms causing heavy tails in flood peak distributions related to processes in the atmosphere, the catchment, and the river system.
We then discuss to which extent the current knowledge supports or contradicts these hypotheses.
We also discuss the statistical conditions for the emergence of heavy tail behavior based on derived distribution theory and relate them to the hypotheses and flood generation mechanisms.
We review the degree to which the heaviness of the tails can be predicted from process knowledge and data. Finally, we recommend further research toward testing the hypotheses and improving the prediction of heavy tails.
Continuous pollen and chironomid records from Lake Emanda (65 degrees 17'N, 135 degrees 45'E) provide new insights into the Late Quaternary environmental history of the Yana Highlands (Yakutia). Larch forest with shrubs (alders, pines, birches) dominated during the deposition of the lowermost sediments suggesting its Early Weichselian [Marine Isotope Stage (MIS) 5] age. Pollen- and chironomid-based climate reconstructions suggest July temperatures (T-July) slightly lower than modern. Gradually increasing amounts of herb pollen and cold stenotherm chironomid head capsules reflect cooler and drier environments, probably during the termination of MIS 5. T-July dropped to 8 degrees C. Mostly treeless vegetation is reconstructed during MIS 3. Tundra and steppe communities dominated during MIS 2. Shrubs became common after similar to 14.5 ka BP but herb-dominated habitats remained until the onset of the Holocene. Larch forests with shrub alder and dwarf birch dominated after the Holocene onset, ca. 11.7 ka BP. Decreasing amounts of shrub pollen during the Lateglacial are assigned to the Older Dryas and Younger Dryas with T-July similar to 7.5 degrees C. T-July increased up to 13 degrees C. Shrub stone pine was present after similar to 7.5 ka BP. The vegetation has been similar to modern since ca. 5.8 ka BP. Chironomid diversity and concentration in the sediments increased towards the present day, indicating the development of richer hydrobiological communities in response to the Holocene thermal maximum.
Effect of temperature on the densification of silicate melts to lower earth's mantle conditions
(2022)
Physical properties of silicate melts play a key role for global planetary dynamics, controlling for example volcanic eruption styles, mantle convection and elemental cycling in the deep Earth. They are significantly modified by structural changes at the atomic scale due to external parameters such as pressure and temperature or due to chemistry. Structural rearrangements such as 4- to 6-fold coordination change of Si with increasing depth may profoundly influence melt properties, but have so far mostly been studied at ambient temperature due to experimental difficulties. In order to investigate the structural properties of silicate melts and their densification mechanisms at conditions relevant to the deep Earth's interior, we studied haplo basaltic glasses and melts (albite-diopside composition) at high pressure and temperature conditions in resistively and laser-heated diamond anvil cells using X-ray absorption near edge structure spectroscopy. Samples were doped with 10 wt% of Ge, which is accessible with this experimental technique and which commonly serves as a structural analogue for the network forming cation Si. We acquired spectra on the Ge K edge up to 48 GPa and 5000 K and derived the average Ge-O coordination number NGe-O, and bond distance RGe-O as functions of pressure. Our results demonstrate a continuous transformation from tetrahedral to octahedral coordination between ca. 5 and 30 GPa at ambient temperature. Above 1600 K the data reveal a reduction of the pressure needed to complete conversion to octahedral coordination by ca. 30 %. The results allow us to determine the influence of temperature on the Si coordination number changes in natural melts in the Earth's interior. We propose that the complete transition to octahedral coordination in basaltic melts is reached at about 40 GPa, corresponding to a depth of ca. 1200 km in the uppermost lower mantle. At the core-mantle boundary (2900 km, 130 GPa, 3000 K) the existence of non-buoyant melts has been proposed to explain observed low seismic wave velocity features. Our results highlight that the melt composition can affect the melt density at such extreme conditions and may strongly influence the structural response.
Climate change projections predict that Mediterranean-type ecosystems (MTEs) are becoming hotter and drier and that fires will become more frequent and severe.
While most plant species in these important biodiversity hotspots are adapted to hot, dry summers and recurrent fire, the Interval Squeeze framework suggests that reduced seed production (demographic shift), reduced seedling establishment after fire (post fire recruitment shift), and reduction in the time between successive fires (fire interval shift) will threaten fire killed species under climate change.
One additional potential driver of accelerated species decline, however, has not been considered so far: the decrease in pollination success observed in many ecosystems worldwide has the potential to further reduce seed accumulation and thus population persistence also in these already threatened systems.
Using the well-studied fire-killed and serotinous shrub species Banksia hookeriana as an example, we apply a new spatially implicit population simulation model to explore population dynamics under past (1988-2002) and current (2003-2017) climate conditions, deterministic and stochastic fire regimes, and alternative scenarios of pollination decline.
Overall, model results suggest that while B. hookeriana populations were stable under past climate conditions, they will not continue to persist under current (and prospective future) climate.
Negative effects of climatic changes and more frequent fires are reinforced by the measured decline in seed set leading to further reduction in the mean persistence time by 12-17%.
These findings clearly indicate that declining pollination rates can be a critical factor that increases further the pressure on the persistence of fire-killed plants.
Future research needs to investigate whether other fire-killed species are similarly threatened, and if local population extinction may be compensated by recolonization events, facilitating persistence in spatially structured meta-communities.
The radiation-sensitive field-effect transistors (RADFETs) with an oxide thickness of 400 nm are irradiated with gate voltages of 2, 4 and 6 V, and without gate voltage.
A detailed analysis of the mechanisms responsible for the creation of traps during irradiation is performed.
The creation of the traps in the oxide, near and at the silicon/silicon-dioxide (Si/SiO2) interface during irradiation is modelled very well. This modelling can also be used for other MOS transistors containing SiO2.
The behaviour of radiation traps during postirradiation annealing is analysed, and the corresponding functions for their modelling are obtained. The switching traps (STs) do not have significant influence on threshold voltage shift, and two radiation-induced trap types fit the fixed traps (FTs) very well. The fading does not depend on the positive gate voltage applied during irradiation, but it is twice lower in case there is no gate voltage.
A new dosimetric parameter, called the Golden Ratio (GR), is proposed, which represents the ratio between the threshold voltage shift after irradiation and fading after spontaneous annealing. This parameter can be useful for comparing MOS dosimeters.
The formation of large polarons has been proposed as reason for the high defect tolerance, low mobility, low charge carrier trapping, and low nonradiative recombination rates of lead halide perovskites. Recently, direct evidence for large-polaron formation has been reported from a 50% effective mass enhancement in angle-resolved photoemission of CsPbBr3 over theory for the orthorhombic structure. We present in-depth band dispersion measurements of CsPbBr3 and GW calculations, which lead to similar effective masses at the valence band maximum of 0.203 1 0.016 m0 in experiment and 0.226 m0 in orthorhombic theory. We argue that the effective mass can be explained solely on the basis of electron-electron correlation and largepolaron formation cannot be concluded from photoemission data.
Monitoring agricultural systems becomes increasingly important in the context of global challenges like climate change, biodiversity loss, population growth, and the rising demand for agricultural products. High-resolution, national-scale maps of agricultural land are needed to develop strategies for future sustainable agriculture.
However, the characterization of agricultural land cover over large areas and for multiple years remains challenging due to the locally diverse and temporally variable characteristics of cultivated land.
We here propose a workflow for generating national agricultural land cover maps on a yearly basis that accounts for varying environmental conditions. We tested the approach by mapping 24 agricultural land cover classes in Germany for the three years 2017, 2018, and 2019, in which the meteorological conditions strongly differed.
We used a random forest classifier and dense time series data from Sentinel-2 and Landsat 8 in combination with monthly Sentinel-1 composites and environmental data and evaluated the relative importance of optical, radar, and environmental data.
Our results show high overall accuracy and plausible class accuracies for the most dominant crop types across different years despite the strong inter-annual meteorological variability and the presence of drought and nondrought years. The maps show high spatial consistency and good delineation of field parcels.
Combining optical, SAR, and environmental data increased overall accuracies by 6% to 10% compared to single sensor approaches, in which optical data outperformed SAR. Overall accuracy ranged between 78% and 80%, and the mapped areas aligned well with agricultural statistics at the regional and national level.
Based on the multi-year dataset we mapped major crop sequences of cereals and leaf crops. Most crop sequences were dominated by winter cereals followed by summer cereals.
Monocultures of summer cereals were mainly revealed in the Northwest of Germany. We showcased that high spatial and thematic detail in combination with annual mapping will stimulate research on crop cycles and studies to assess the impact of environmental policies on management decisions.
Our results demonstrate the capabilities of integrated optical time series and SAR data in combination with variables describing local and seasonal environmental conditions for annual large-area crop type mapping.
The past three decades of policy process studies have seen the emergence of a clear intellectual lineage with regard to complexity. Implicitly or explicitly, scholars have employed complexity theory to examine the intricate dynamics of collective action in political contexts. However, the methodological counterparts to complexity theory, such as computational methods, are rarely used and, even if they are, they are often detached from established policy process theory. Building on a critical review of the application of complexity theory to policy process studies, we present and implement a baseline model of policy processes using the logic of coevolving networks. Our model suggests that an actor's influence depends on their environment and on exogenous events facilitating dialogue and consensus-building. Our results validate previous opinion dynamics models and generate novel patterns. Our discussion provides ground for further research and outlines the path for the field to achieve a computational turn.
Social theory has long predicted that social mobility, in particular downward social mobility, is detrimental to the well-being of individuals. Dissociative and “falling from grace” theories suggest that mobility is stressful due to the weakening of social ties, feelings of alienation, and loss of status. In light of these theories, it is a puzzle that the majority of quantitative studies in this area have shown null results. Our approach to resolve the puzzle is two-fold. First, we argue for a broader conception of the mobility process than is often used and thus focus on intragenerational occupational class mobility rather than restricting ourselves to the more commonly studied intergenerational mobility. Second, we argue that self-reported measures may be biased by habituation (or “entrenched deprivation”). Using nurse-collected health and biomarker data from the UK Household Longitudinal Study (2010–2012, N = 4,123), we derive a measure of allostatic load as an objective gauge of physiological “wear and tear” and compare patterns of mobility effects with self-reports of health using diagonal reference models. Our findings indicate a strong class gradient in both allostatic load and self-rated health, and that both first and current job matter for current well-being outcomes. However, in terms of the effects of mobility itself, we find that intragenerational social mobility is consequential for allostatic load, but not for self-rated health. Downward mobility is detrimental and upward mobility beneficial for well-being as assessed by allostatic load. Thus, these findings do not support the idea of generalized stress from dissociation, but they do support the “falling from grace” hypothesis of negative downward mobility effects. Our findings have a further implication, namely that the differences in mobility effects between the objective and subjective outcome infer the presence of entrenched deprivation. Null results in studies of self-rated outcomes may therefore be a methodological artifact, rather than an outright rejection of decades-old social theory.
Reconstructing thermal histories in thrust belts is commonly used to infer the age and rates of thrusting and hence the driving mechanisms of orogenesis.
In areas where ancient basins have been incorporated into the orogenic wedge, a quantitative reconstruction of the thermal history helps distinguish among potential mechanisms responsible for heating events.
We present such a reconstruction for the Ischigualasto-Villa Union basin in the western Pampean Ranges of Argentina, where Triassic rifting and late Cretaceous-Cenozoic retroarc foreland basin development has been widely documented, including Miocene flat-slab subduction.
We report results of organic and inorganic thermal indicators acquired along three stratigraphic sections, including vitrinite reflectance and X-ray diffractometry in claystones and new thermochronological [(apatite fission-track and apatite and zircon [U-Th]/He)] analyses.
Despite up to 5 km-thick Cenozoic overburden and unlike previously thought, the thermal peak in the basin is not due to Cenozoic burial but occurred in the Triassic, associated with a high heat flow of up to 90 mWm(-2) and <2 km of burial, which heated the base of the Triassic strata to similar to 160 degrees C. Following exhumation, attested by the development of an unconformity between the Triassic and Late-Cretaceous-Cenozoic sequences, Cenozoic re-burial increased the temperature to similar to 110 degrees C at the base of the Triassic section and only similar to 50 degrees C 7 km upsection, suggesting a dramatic decrease in the thermal gradient.
The onset of Cenozoic cooling occurred at similar to 10(-8) Ma, concomitant with sediment accumulation and thus preceding the latest Miocene onset of thrusting that has been independently documented by stratigraphic-cross-cutting relationships.
We argue that the onset of cooling is associated with lithospheric refrigeration following establishment of flat-slab subduction, leading to the eastward displacement of the asthenospheric wedge beneath the South American plate.
Our study places time and temperature constraints on flat-slab cooling that calls for a careful interpretation of exhumation signals in thrustbelts inferred from thermochronology only.
Only a fast and global transformation towards decarbonization and sustainability can keep the Earth in a civilization-friendly state. As hotspots for (green) innovation and experimentation, cities could play an important role in this transition. They are also known to profit from each other's ideas, with policy and technology innovations spreading to other cities. In this way, cities can be conceptualized as nodes in a globe-spanning learning network. The dynamics of this process are important for society's response to climate change and other challenges, but remain poorly understood on a macroscopic level. In this contribution, we develop an approach to identify whether network-based complex contagion effects are a feature of sustainability policy adoption by cities, based on dose-response contagion and surrogate data models. We apply this methodology to an exemplary data set, comprising empirical data on the spreading of a public transport innovation (Bus Rapid Transit Systems) and a global inter-city connection network based on scheduled flight routes. Although our approach is not able to identify detailed mechanisms, our results point towards a contagious spreading process, and cannot be explained by either the network structure or the increase in global adoption rate alone. Further research on the role of a city's abstract "global neighborhood" regarding its policy and innovation decisions is thus both needed and promising, and may connect with research on social tipping processes. The methodology is generic, and can be used to compare the predictive power for innovation spreading of different kinds of inter-city network connections, e.g. via transport links, trade, or co-membership in political networks.
For many years scholars and politicians discuss the economic importance of the middle income class. Our article contributes to broaden the present state of research by not only examining the structure of the middle class whilst focusing on individual attributes, but by especially taking the role of gender-specific occupational characteristics and country-specific conditions into account. Based on the EU-SILC data 2020 for 17 countries, we analyze which factors affect the structure of the middle income class on the individual, on the occupational and country level. Our findings show that occupational attributes (e.g. part-time rate) prove to be highly relevant in this realm. Moreover, significant gender differences can be observed: women who work in an occupation which is mainly performed by women bear a higher risk of belonging to the lower income class as compared to men.
Leptonic nonthermal emission from supernova remnants evolving in the circumstellar magnetic field
(2022)
The very-high-energy (VHE; E > 100 GeV) gamma-ray emission observed from a number of supernova remnants (SNRs) indicates particle acceleration to high energies at the shock of the remnants and a potentially significant contribution to Galactic cosmic rays. It is extremely difficult to determine whether protons (through hadronic interactions and subsequent pion decay) or electrons (through inverse Compton scattering on ambient photon fields) are responsible for this emission. For a successful diagnostic, a good understanding of the spatial and energy distribution of the underlying particle population is crucial. Most SNRs are created in core-collapse explosions and expand into the wind bubble of their progenitor stars. This circumstellar medium features a complex spatial distribution of gas and magnetic field which naturally strongly affects the resulting particle population. In this work, we conduct a detailed study of the spectro-spatial evolution of the electrons accelerated at the forward shock of core-collapse SNRs and their nonthermal radiation, using the RATPaC code that is designed for the time- and spatially dependent treatment of particle acceleration at SNR shocks. We focus on the impact of the spatially inhomogeneous magnetic field through the efficiency of diffusion and synchrotron cooling. It is demonstrated that the structure of the circumstellar magnetic field can leave strong signatures in the spectrum and morphology of the resulting nonthermal emission.
Context
For a given body mass index (BMI), both impaired metabolic health (MH) and reduced cardiorespiratory fitness (CRF) associate with increased risk of cardiovascular disease (CVD).
Objective
It remains unknown whether both risk phenotypes relate to CVD independently of each other, and whether these relationships differ in normal weight, overweight, and obese subjects.
Methods
Data from 421 participants from the Tubingen Diabetes Family Study, who had measurements of anthropometrics, metabolic parameters, CRF (maximal aerobic capacity [VO2max]) and carotid intima-media thickness (cIMT), an early marker of atherosclerosis, were analyzed. Subjects were divided by BMI and MH status into 6 phenotypes.
Results
In univariate analyses, older age, increased BMI, and a metabolic risk profile correlated positively, while insulin sensitivity and VO2max negatively with cIMT. In multivariable analyses in obese subjects, older age, male sex, lower VO2max (std. ss -0.21, P = 0.002) and impaired MH (std. ss 0.13, P = 0.02) were independent determinants of increased cIMT. After adjustment for age and sex, subjects with metabolically healthy obesity (MHO) had higher cIMT than subjects with metabolically healthy normal weight (MHNW; 0.59 +/- 0.009 vs 0.52 +/- 0.01 mm; P < 0.05). When VO2max was additionally included in this model, the difference in cIMT between MHO and MHNW groups became statistically nonsignificant (0.58 +/- 0.009 vs 0.56 +/- 0.02 mm; P > 0.05).
Conclusion
These data suggest that impaired MH and low CRF independently determine increased cIMT in obese subjects and that low CRF may explain part of the increased CVD risk observed in MHO compared with MHNW.
Ultrafast X-ray diffraction is used to quantify the transport of energy in laser-excited nanoscale gold-nickel (Au-Ni) bilayers.
Electron transport and efficient electron-phonon coupling in Ni convert the laser-deposited energy in the conduction electrons within a few picoseconds into a strong non-equilibrium between hot Ni and cold Au phonons at the bilayer interface.
Modeling of the subsequent equilibration dynamics within various two-temperature models confirms that for ultrathin Au films, the thermal transport is dominated by phonons instead of conduction electrons because of the weak electron-phonon coupling in Au.
A novel approach for estimating precipitation patterns is developed here and applied to generate a new hydrologically corrected daily precipitation dataset, called RAIN4PE (Rain for Peru and Ecuador), at 0.1 degrees spatial resolution for the period 1981-2015 covering Peru and Ecuador. It is based on the application of 1) the random forest method to merge multisource precipitation estimates (gauge, satellite, and reanalysis) with terrain elevation, and 2) observed and modeled streamflow data to first detect biases and second further adjust gridded precipitation by inversely applying the simulated results of the ecohydrological model SWAT (Soil and Water Assessment Tool). Hydrological results using RAIN4PE as input for the Peruvian and Ecuadorian catchments were compared against the ones when feeding other uncorrected (CHIRP and ERA5) and gauge-corrected (CHIRPS, MSWEP, and PISCO) precipitation datasets into the model. For that, SWAT was calibrated and validated at 72 river sections for each dataset using a range of performance metrics, including hydrograph goodness of fit and flow duration curve signatures. Results showed that gauge-corrected precipitation datasets outperformed uncorrected ones for streamflow simulation. However, CHIRPS, MSWEP, and PISCO showed limitations for streamflow simulation in several catchments draining into the Pacific Ocean and the Amazon River. RAIN4PE provided the best overall performance for streamflow simulation, including flow variability (low, high, and peak flows) and water budget closure. The overall good performance of RAIN4PE as input for hydrological modeling provides a valuable criterion of its applicability for robust countrywide hydrometeorological applications, including hydroclimatic extremes such as droughts and floods. Significance StatementWe developed a novel precipitation dataset RAIN4PE for Peru and Ecuador by merging multisource precipitation data (satellite, reanalysis, and ground-based precipitation) with terrain elevation using the random forest method. Furthermore, RAIN4PE was hydrologically corrected using streamflow data in watersheds with precipitation underestimation through reverse hydrology. The results of a comprehensive hydrological evaluation showed that RAIN4PE outperformed state-of-the-art precipitation datasets such as CHIRP, ERA5, CHIRPS, MSWEP, and PISCO in terms of daily and monthly streamflow simulations, including extremely low and high flows in almost all Peruvian and Ecuadorian catchments. This underlines the suitability of RAIN4PE for hydrometeorological applications in this region. Furthermore, our approach for the generation of RAIN4PE can be used in other data-scarce regions.
Magnetic reconnection is a multi-faceted process of energy conversion in astrophysical, space and laboratory plasmas that operates at microscopic scales but has macroscopic drivers and consequences.
Solar flares present a key laboratory for its study, leaving imprints of the microscopic physics in radiation spectra and allowing the macroscopic evolution to be imaged, yet a full observational characterization remains elusive.
Here we combine high resolution imaging and spectral observations of a confined solar flare at multiple wavelengths with data-constrained magnetohydrodynamic modeling to study the dynamics of the flare plasma from the current sheet to the plasmoid scale. The analysis suggests that the flare resulted from the interaction of a twisted magnetic flux rope surrounding a filament with nearby magnetic loops whose feet are anchored in chromospheric fibrils. Bright cusp-shaped structures represent the region around a reconnecting separator or quasi-separator (hyperbolic flux tube).
The fast reconnection, which is relevant for other astrophysical environments, revealed plasmoids in the current sheet and separatrices and associated unresolved turbulent motions.
Solar flares provide wide range of observational details about fundamental processes involved. Here, the authors show evidence for magnetic reconnection in a strong confined solar flare displaying all four reconnection flows with plasmoids in the current sheet and the separatrices.
With the advent of Nanotechnology, the use of nanomaterials in consumer products is increasing on a daily basis, due to which a deep understanding and proper investigation regarding their safety and risk assessment should be a major priority. To date, there is no investigation regarding the microrheological properties of nanomaterials (NMs) in biological media.
In our study, we utilized in silico models to select the suitable NMs based on their physicochemical properties such as solubility and lipophilicity. Then, we established a new method based on dynamic light scattering (DLS) microrheology to get the mean square displacement (MSD) and viscoelastic property of two model NMs that are dendrimers and cerium dioxide nanoparticles in Dulbecco's Modified Eagle Medium (DMEM) complete media at three different concentrations for both NMs. Subsequently, we established the cytotoxicological profiling using water-soluble tetrazolium salt-1 (WST-1) and a reactive oxygen species (ROS) assay.
To take one step forward, we further looked into the tight junction properties of the cells using immunostaining with Zonula occluden-1 (ZO-1) antibodies and found that the tight junction function or transepithelial resistance (TEER) was affected in response to the microrheology and cytotoxicity. The quantitative polymerase chain reaction (q-PCR) results in the gene expression of ZO-1 after the 24 h treatment with NPs further validates the findings of immunostaining results.
This new method that we established will be a reference point for other NM studies which are used in our day-to-day consumer products.
Obesity has been linked to lower concentrations of fat-soluble micronutrients and higher concentrations of oxidative stress markers as well as an altered metabolism of branched chain amino acids and phospholipids. In the context of morbid obesity, the aim of this study was to investigate whether and to which extent plasma status of micronutrients, amino acids, phospholipids and oxidative stress differs between morbidly obese (n = 23) and non-obese patients (n = 13). In addition to plasma, malondialdehyde, retinol, cholesterol and triglycerides were assessed in visceral and subcutaneous adipose tissue in both groups. Plasma gamma-tocopherol was significantly lower (p < 0.011) in the obese group while other fat-soluble micronutrients showed no statistically significant differences between both groups. Branched-chain amino acids (all p < 0.008) and lysine (p < 0.006) were significantly higher in morbidly obese patients compared to the control group. Malondialdehyde concentrations in both visceral (p < 0.016) and subcutaneous (p < 0.002) adipose tissue were significantly higher in the morbidly obese group while plasma markers of oxidative stress showed no significant differences between both groups. Significantly lower plasma concentrations of phosphatidylcholine, phosphatidylethanolamine, lyso-phosphatidylethanolamine (all p < 0.05) and their corresponding ether-linked analogs were observed, which were all reduced in obese participants compared to the control group. Pre-operative assessment of micronutrients in patients undergoing bariatric surgery is recommended for early identification of patients who might be at higher risk to develop a severe micronutrient deficiency post-surgery. Assessment of plasma BCAAs and phospholipids in obese patients might help to differentiate between metabolic healthy patients and those with metabolic disorders.
Instruments for measuring the absorbed dose and dose rate under radiation exposure, known as radiation dosimeters, are indispensable in space missions. They are composed of radiation sensors that generate current or voltage response when exposed to ionizing radiation, and processing electronics for computing the absorbed dose and dose rate. Among a wide range of existing radiation sensors, the Radiation Sensitive Field Effect Transistors (RADFETs) have unique advantages for absorbed dose measurement, and a proven record of successful exploitation in space missions. It has been shown that the RADFETs may be also used for the dose rate monitoring. In that regard, we propose a unique design concept that supports the simultaneous operation of a single RADFET as absorbed dose and dose rate monitor. This enables to reduce the cost of implementation, since the need for other types of radiation sensors can be minimized or eliminated. For processing the RADFET's response we propose a readout system composed of analog signal conditioner (ASC) and a self-adaptive multiprocessing system-on-chip (MPSoC). The soft error rate of MPSoC is monitored in real time with embedded sensors, allowing the autonomous switching between three operating modes (high-performance, de-stress and fault-tolerant), according to the application requirements and radiation conditions.
In the last years, electron density profile functions characterized by a linear dependence on the scale height showed good results when approximating the topside ionosphere. The performance above 800 km, however, is not yet well investigated.
This study investigates the capability of the semi-Epstein functions to represent electron density profiles from the peak height up to 20,000 km. Electron density observations recorded by the Van Allen Probes were used to resolve the scale height dependence in the plasmasphere.
It was found that the linear dependence of the scale height in the topside ionosphere cannot be directly used to extrapolate profiles above 800 km.
We find that the dependence of scale heights on altitude is quadratic in the plasmasphere. A statistical model of the scale heights is therefore proposed. After combining the topside ionosphere and plasmasphere by a unified model, we have obtained good estimations not only in the profile shapes, but also in the Total Electron Content magnitude and distributions when compared to actual measurements from 2013, 2014, 2016 and 2017.
Our investigation shows that Van Allen Probes can be merged to radio-occultation data to properly represent the upper ionosphere and plasmasphere by means of a semi-Epstein function.
Groundwater is critical in supporting current and future reliable water supply throughout Africa. Although continental maps of groundwater storage and recharge have been developed, we currently lack a clear understanding on how the controls on groundwater recharge vary across the entire continent. Reviewing the existing literature, we synthesize information on reported groundwater recharge controls in Africa. We find that 15 out of 22 of these controls can be characterised using global datasets. We develop 11 descriptors of climatic, topographic, vegetation, soil and geologic properties using global datasets, to characterise groundwater recharge controls in Africa. These descriptors cluster Africa into 15 Recharge Landscape Units for which we expect recharge controls to be similar. Over 80% of the continents land area is organized by just nine of these units. We also find that aggregating the Units by similarity into four broader Recharge Landscapes (Desert, Dryland, Wet tropical and Wet tropical forest) provides a suitable level of landscape organisation to explain differences in ground-based long-term mean annual recharge and recharge ratio (annual recharge / annual precipitation) estimates. Furthermore, wetter Recharge Landscapes are more efficient in converting rainfall to recharge than drier Recharge Landscapes as well as having higher annual recharge rates. In Dryland Recharge Landscapes, we found that annual recharge rates largely varied according to mean annual precipitation, whereas recharge ratio estimates increase with increasing monthly variability in P-PET. However, we were unable to explain why ground based estimates of recharge signatures vary across other Recharge Landscapes, in which there are fewer ground based recharge estimates, using global datasets alone. Even in dryland regions, there is still considerable unexplained variability in the estimates of annual recharge and recharge ratio, stressing the limitations of global datasets for investigating ground-based information.
Microbiome science is revolutionizing many concepts of plant biology, ecology, and evolution.
Understanding plant microbiomes is key to developing solutions that protect crop health without impacting the environment.
In this perspective article, we highlight the importance of both the structure and functions of plant-associated microbial communities in protecting their host from pathogens.
These new findings have a high potential to aid biocontrol programs and to replace traditional chemical products, guiding the transition towards a sustainable production.
Plasmon-driven dehalogenation of brominated purines has been recently explored as a model system to understand fundamental aspects of plasmon-assisted chemical reactions. Here, it is shown that divalent Ca2+ ions strongly bridge the adsorption of bromoadenine (Br-Ade) to Ag surfaces.
Such ion-mediated binding increases the molecule's adsorption energy leading to an overlap of the metal energy states and the molecular states, enabling the chemical interface damping (CID) of the plasmon modes of the Ag nanostructures (i.e., direct electron transfer from the metal to Br-Ade).
Consequently, the conversion of Br-Ade to adenine almost doubles following the addition of Ca2+.
These experimental results, supported by theoretical calculations of the local density of states of the Ag/Br-Ade complex, indicate a change of the charge transfer pathway driving the dehalogenation reaction, from Landau damping (in the lack of Ca2+ ions) to CID (after the addition of Ca2+).
The results show that the surface dynamics of chemical species (including water molecules) play an essential role in charge transfer at plasmonic interfaces and cannot be ignored. It is envisioned that these results will help in designing more efficient nanoreactors, harnessing the full potential of plasmon-assisted chemistry.
A large Rashba effect is essential for future applications in spintronics. Particularly attractive is understanding and controlling nonequilibrium properties of ferroelectric Rashba semiconductors. Here, time- and angle-resolved photoemission is utilized to access the ultrafast dynamics of bulk and surface transient Rashba states after femtosecond optical excitation of GeTe. A complex thermalization pathway is observed, wherein three different timescales can be clearly distinguished: intraband thermalization, interband equilibration, and electronic cooling. These dynamics exhibit an unconventional temperature dependence: while the cooling phase speeds up with increasing sample temperature, the opposite happens for interband thermalization. It is demonstrated how, due to the Rashba effect, an interdependence of these timescales on the relative strength of both electron-electron and electron-phonon interactions is responsible for the counterintuitive temperature dependence, with spin-selection constrained interband electron-electron scatterings found both to dominate dynamics away from the Fermi level, and to weaken with increasing temperature. These findings are supported by theoretical calculations within the Boltzmann approach explicitly showing the opposite behavior of all relevant electron-electron and electron-phonon scattering channels with temperature, thus confirming the microscopic mechanism of the experimental findings. The present results are important for future applications of ferroelectric Rashba semiconductors and their excitations in ultrafast spintronics.
Using over-5-year EMFISIS wave measurements from Van Allen Probes, we present a detailed survey to identify the controlling factors among the geomagnetic indices and solar wind parameters for the 1-min root mean square amplitudes of lower band chorus (LBC) and upper band chorus (UBC).
A set of important features are automatically determined by feature selection techniques, namely, Random Forest and Maximum Relevancy Minimum Redundancy. Our analysis results indicate the AE index with zero-time-delay dominates the intensity evolution of LBC and UBC, consistent with the evidence that chorus waves prefer to occur and amplify during enhanced substorm periods. Regarding solar wind parameters, solar wind speed and IMF B-z are identified as the controlling factors for chorus wave intensity. Using the combination of all these important features, a predictive neural network model of chorus wave intensity is established to reconstruct the temporal variations of chorus wave intensity, for which application of Random Forest produces the overall best performance.
Plain Language Summary
Whistler mode chorus waves are electromagnetic waves observed in the low-density region near the geomagnetic equator outside the plasmapause. The dynamics of Earth's radiation belts are largely influenced by chorus waves owing to their dual contributions to both radiation belt electron acceleration and loss. In this study, we use feature selection techniques to identify the controlling geomagnetic and solar wind factors for magnetospheric chorus waves. Feature selection techniques implement the processes which can select the features most influential to the output.
In this study, the inputs are geomagnetic indices and solar wind parameters and the output is the chorus wave intensity. The results indicate that AE index with zerotime delay dominates the chorus wave intensity. Furthermore, solar wind speed and IMF B-z are identified as the most important solar wind drivers for chorus wave intensity.
On basis of the combination of all these important geomagnetic and solar wind controlling factors, we develop a neural network model of chorus wave intensity, and find that the model with the inputs identified using the Random Forest method produces the overall best performance.
Solar H alpha excess during Solar Cycle 24 from full-disk filtergrams of the Chromospheric Telescope
(2022)
Context
The chromospheric H alpha spectral line is a strong line in the spectrum of the Sun and other stars. In the stellar regime, this spectral line is already used as a powerful tracer of stellar activity. For the Sun, other tracers, such as Ca II K, are typically used to monitor solar activity. Nonetheless, the Sun is observed constantly in H alpha with globally distributed ground-based full-disk imagers.
Aims
The aim of this study is to introduce the imaging H alpha excess and deficit as tracers of solar activity and compare them to other established indicators. Furthermore, we investigate whether the active region coverage fraction or the changing H alpha excess in the active regions dominates temporal variability in solar H alpha observations.
Methods
We used observations of full-disk H alpha filtergrams of the Chromospheric Telescope and morphological image processing techniques to extract the imaging H alpha excess and deficit, which were derived from the intensities above or below 10% of the median intensity in the filtergrams, respectively. These thresholds allowed us to filter for bright features (plage regions) and dark absorption features (filaments and sunspots). In addition, the thresholds were used to calculate the mean intensity I-mean(E/D) for H alpha excess and deficit regions. We describe the evolution of the H alpha excess and deficit during Solar Cycle 24 and compare it to the mean intensity and other well established tracers: the relative sunspot number, the F10.7 cm radio flux, and the Mg II index. In particular, we tried to determine how constant the H alpha excess and number density of H alpha excess regions are between solar maximum and minimum. The number of pixels above or below the intensity thresholds were used to calculate the area coverage fraction of H alpha excess and deficit regions on the Sun, which was compared to the imaging H alpha excess and deficit and the respective mean intensities averaged for the length of one Carrington rotation. In addition, we present the H alpha excess and mean intensity variation of selected active regions during their disk passage in comparison to the number of pixels of H alpha excess regions.
Results.
The H alpha excess and deficit follow the behavior of the solar activity over the course of the cycle. They both peak around solar maximum, whereby the peak of the H alpha deficit is shortly after the solar maximum. Nonetheless, the correlation of the monthly averages of the H alpha excess and deficit is high with a Spearman correlation of rho = 0.91. The H alpha excess is closely correlated to the chromospheric Mg II index with a correlation of 0.95. The highest correlation of the H alpha deficit is found with the F10.7 cm radio flux, with a correlation of 0.89, due to their peaks after the solar activity maximum. Furthermore, the H alpha deficit reflects the cyclic behavior of polar crown filaments and their disappearance shortly before the solar maximum. We investigated the mean intensity distribution for H alpha excess regions for solar minimum and maximum. The shape of the distributions for solar minimum and maximum is very similar, but with different amplitudes. Furthermore, we found that the area coverage fraction of H alpha excess regions and the H alpha excess are strongly correlated with an overall Spearman correlation of 0.92. The correlation between the H alpha excess and the mean intensity of H alpha excess regions is 0.75. The correlation of the area coverage fraction and the mean intensity of H alpha excess regions is in general relatively low (rho = 0.45) and only for few active regions is this correlation above 0.7. The weak correlation between the area coverage fraction and mean intensity leaves us pessimistic that the degeneracy between these two quantities can be broken for the modeling of unresolved stellar surfaces.
Simple Summary Asian elephants (Elephas maximus) are considered endangered and their population is in continuous decline. Understanding their social interactions, health, and welfare status has been a topic of intense research in recent decades. Coagulation assessments have been underutilized in wildlife but can give valuable information on individual health. This study aims to increase the knowledge of the coagulation status in healthy Asian elephants from different backgrounds and age groups, using a fast point-of-care analyzer. This tool can be further used in either routine health check-ups performed by caretakers or in a clinical emergency, such as in cases of elephant endotheliotropic herpesvirus hemorrhagic disease outbreaks. We have also investigated the presence of genomic mutations in one coagulation factor-factor VII-where a disorder was previously reported in an Asian elephant. Hereby, we report new reference values for coagulation parameters, such as coagulation times and fibrinogen concentration of Asian elephants assessed in Thailand and in Europe, as well as several single point mutations found in the exons of Elephas maximus coagulation F7 gene. We found the point-of-care analyzer used in this study to be very practical and user friendly for a zoo and field environment and hope that this project will incentivize further coagulation studies in Asian elephants and in other wildlife species. The Asian elephant population is continuously declining due to several extrinsic reasons in their range countries, but also due to diseases in captive populations worldwide. One of these diseases, the elephant endotheliotropic herpesvirus (EEHV) hemorrhagic disease, is very impactful because it particularly affects Asian elephant calves. It is commonly fatal and presents as an acute and generalized hemorrhagic syndrome. Therefore, having reference values of coagulation parameters, and obtaining such values for diseased animals in a very short time, is of great importance. We analyzed prothrombin time (PT), activated partial thromboplastin time (aPTT), and fibrinogen concentrations using a portable and fast point-of-care analyzer (VetScan Pro) in 127 Asian elephants from Thai camps and European captive herds. We found significantly different PT and aPTT coagulation times between elephants from the two regions, as well as clear differences in fibrinogen concentration. Nevertheless, these alterations were not expected to have biological or clinical implications. We have also sequenced the coagulation factor VII gene of 141 animals to assess the presence of a previously reported hereditary coagulation disorder in Asian elephants and to investigate the presence of other mutations. We did not find the previously reported mutation in our study population. Instead, we discovered the presence of several new single nucleotide polymorphisms, two of them being considered as deleterious by effect prediction software.
Several morphological and mitochondrial lineages of the alpine ringlet butterfly species Erebia pronoe have been described, indicating a complex phylogenetic structure. However, the existing data were insufficient and allow neither a reconstruction of the biogeographic history, nor an assessment of the genetic lineages. Therefore, we analysed mitochondrial (COI, NDI) and nuclear (EF1 alpha, RPS5) gene sequences and compared them with sequences from the sister species Erebia melas. Additionally, we combined this information with morphometric data of the male genitalia and the infection patterns with Wolbachia strains, based on a WSP analysis. We obtained a distinct phylogeographic structure within the E. pronoe-melas complex with eight well-distinguishable geographic groups, but also a remarkable mito-nuclear discordance. The mito-nuclear discordance in E. melas and E. pronoe glottis can be explained by different ages of Wolbachia infections with different Wolbachia strains, associated selective sweeps, and hybridisation inhibition. Additionally, we found indications for incipient speciation of E. pronoe glottis in the Pyrenees and a pronounced range dynamic within and among the other high mountain systems of Europe. Our results emphasize the importance of combined approaches in reconstructing biogeographic patterns and evaluating phylogeographic splits.
Over the last few years, the vegan diet has become increasingly popular in Germany. It has been proposed that this diet is generally lower in fat, but less is known about the impact on fatty acid (FA) profiles. Therefore, the cross-sectional "Risks and Benefits of a Vegan Diet" (RBVD) study (n = 72) was used to investigate dietary FA intake as well as plasma phospholipid FA in vegans (n = 36) compared to omnivores (n = 36). Vegans had a significantly lower dietary intake of total fat (median 86 g/day, IQR 64-111) in comparison to omnivores (median 104 g/day, IQR 88-143, p = 0.004). Further, vegans had a lower intake of saturated fatty acids (SFA) (p < 0.0001) and monounsaturated fatty acids (MUFA) (p = 0.001) compared to omnivores. Vegans had a higher intake in total polyunsaturated fatty acids (PUFA), omega-3 and omega-6 PUFA compared to omnivores, but without statistical significance after Bonferroni correction. According to plasma phospholipid profiles, relatively lower proportions of SFA (p < 0.0001), total trans fatty acids (TFA) (p = 0.0004) and omega-3-FA (p < 0.0001), but higher proportions of omega-6-FA (p < 0.0001) were observed in vegans. With the exception of omega-3 PUFA, a vegan diet is associated with a more favorable dietary fat intake and more favorable plasma FA profiles and therefore may reduce cardiovascular risk.
Coronary artery disease (CAD) is the leading cause of death worldwide.
Statins reduce morbidity and mortality of CAD. Intake of n-3 polyunsaturated fatty acid (n-3 PUFAs), particularly eicosapentaenoic acid (EPA), is associated with reduced morbidity and mortality in patients with CAD. Previous data indicate that a higher conversion of precursor fatty acids (FAs) to arachidonic acid (AA) is associated with increased CAD prevalence.
Our study explored the FA composition in blood to assess n-3 PUFA levels from patients with and without CAD. We analyzed blood samples from 273 patients undergoing cardiac catheterization. Patients were stratified according to clinically relevant CAD (n = 192) and those without (n = 81). FA analysis in full blood was performed by gas chromatography. Indicating increased formation of AA from precursors, the ratio of dihomo-gamma-linolenic acid (DGLA) to AA, the delta-5 desaturase index (D5D index) was higher in CAD patients. CAD patients had significantly lower levels of omega-6 polyunsaturated FAs (n-6 PUFA) and n-3 PUFA, particularly EPA, in the blood.
Thus, our study supports a role of increased EPA levels for cardioprotection.