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A combinatorial study of the effect of in-mixing of various guests on the thermoelectric properties of the host workhorse polymer poly[2,5-bis(3-tetradecylthiophen-2-yl)thieno[3,2-b]thiophene] (PBTTT) is presented. Specifically, the composition and thickness for doped films of PBTTT blended with different polymers are varied. Some blends at guest weight fractions around 10-15% exhibit up to a fivefold increase in power factor compared to the reference material, leading to zT values around 0.1. Spectroscopic analysis of the charge-transfer species, structural characterization using grazing-incidence wide-angle X-ray scattering, differential scanning calorimetry, Raman, and atomic force microscopy, and Monte Carlo simulations are employed to determine that the key to improved performance is for the guest to promote long-range electrical connectivity and low disorder, together with similar highest occupied molecular orbital levels for both materials in order to ensure electronic connectivity are combined.
Wheat alpha-amylase/trypsin inhibitors remain a subject of interest considering the latest findings showing their implication in wheat-related non-celiac sensitivity (NCWS). Understanding their functions in such a disorder is still unclear and for further study, the need for pure ATI molecules is one of the limiting problems. In this work, a simplified approach based on the successive fractionation of ATI extracts by reverse phase and ion exchange chromatography was developed. ATIs were first extracted from wheat flour using a combination of Tris buffer and chloroform/methanol methods. The separation of the extracts on a C18 column generated two main fractions of interest F1 and F2. The response surface methodology with the Doehlert design allowed optimizing the operating parameters of the strong anion exchange chromatography. Finally, the seven major wheat ATIs namely P01083, P17314, P16850, P01085, P16851, P16159, and P83207 were recovered with purity levels (according to the targeted LC-MS/MS analysis) of 98.2 ± 0.7; 98.1 ± 0.8; 97.9 ± 0.5; 95.1 ± 0.8; 98.3 ± 0.4; 96.9 ± 0.5, and 96.2 ± 0.4%, respectively. MALDI-TOF-MS analysis revealed single peaks in each of the pure fractions and the mass analysis yielded deviations of 0.4, 1.9, 0.1, 0.2, 0.2, 0.9, and 0.1% between the theoretical and the determined masses of P01083, P17314, P16850, P01085, P16851, P16159, and P83207, respectively. Overall, the study allowed establishing an efficient purification process of the most important wheat ATIs. This paves the way for further in-depth investigation of the ATIs to gain more knowledge related to their involvement in NCWS disease and to allow the absolute quantification in wheat samples.
Soft actuator performance can be tuned by chemistry or mechanical manipulation, but this adjustability is limited especially in view of their growing technological relevance. Inspired from textile engineering, we designed and fabricated fiber mesh actuators and introduced new features like anisotropic behavior and soft-tissue like elastic deformability. Design criteria for the meshes are the formation of fiber bundles, the angle between fiber bundles in different stacked layers and covalent crosslinks forming within and between fibers at their interfacial contact areas. Through crosslinking the interfiber bond strength increased from a bond transmitting neither axial nor rotational loads (pin joint) to a bond strength capable of both (welded joint). For non-linear elastic stiffening, stacked fiber bundles with four embracing fibers were created forming microstructural rhombus shapes. Loading the rhombus diagonally allowed generation of “soft tissue”-like mechanics. By adjustment of stacking angles, the point of strong increase in stress is tuned. While the highest stresses are observed in aligned and crosslinked fiber mats along the direction of the fiber, the strongest shape-memory actuation behavior is found in randomly oriented fiber mats. Fiber mesh actuators controlled by temperature are of high significance as soft robot skins and as for active patches supporting tissue regeneration.
In this paper, we present a study comparing the depth to diameter (d/D) ratio of small simple craters (200-1000 m) of an area between -88.5 degrees to -90 degrees latitude at the lunar south pole containing Permanent Shadowed Regions (PSRs) versus craters without PSRs. As PSRs can reach temperatures of 110 K and are capable of harboring volatiles, especially water ice, we analyzed the relationship of depth versus diameter ratios and its possible implications for harboring water ice. Variations in the d/D ratios can also be caused by other processes such as degradation, isostatic adjustment, or differences in surface properties. The conducted d/D ratio analysis suggests that a differentiation between craters containing PSRs versus craters without PSRs occurs. Thus, a possible direct relation between d/D ratio, PSRs, and water ice harboring might exist. Our results suggest that differences in the target's surface properties may explain the obtained results. The resulting d/D ratios of craters with PSRs can help to select target areas for future In-Situ Resource Utilization (ISRU) missions.
Fast-localized electron loss, resulting from interactions with electromagnetic ion cyclotron (EMIC) waves, can produce deepening minima in phase space density (PSD) radial profiles. Here, we perform a statistical analysis of local PSD minima to quantify how readily these are associated with radiation belt depletions. The statistics of PSD minima observed over a year are compared to the Versatile Electron Radiation Belts (VERB) simulations, both including and excluding EMIC waves. The observed minima distribution can only be achieved in the simulation including EMIC waves, indicating their importance in the dynamics of the radiation belts. By analyzing electron flux depletions in conjunction with the observed PSD minima, we show that, in the heart of the outer radiation belt (L* < 5), on average, 53% of multi-MeV electron depletions are associated with PSD minima, demonstrating that fast localized loss by interactions with EMIC waves are a common and crucial process for ultra-relativistic electron populations.
Background: Biological age markers are a crucial indicator whether children are decelerated in growth tempo. Skeletal maturation is the standard measure. Yet, it relies on exposing children to x-radiation. Dental eruption is a potential, but highly debated, radiation free alternative.
Objectives: We assess the interrelationship between dental eruption and other maturational markers. We hypothesize that dental age correlates with body height and skeletal age. We further evaluate how the three different variables behave in cohorts from differing social backgrounds.
Sample and Method: Dental, skeletal and height data from the 1970s to 1990s from Guatemalan boys were converted into standard deviation scores, using external references for each measurement. The boys, aged between 7 and 12, derived from different social backgrounds (middle SES (N = 6529), low-middle SES (N = 736), low SES Ladino (N = 3653) and low SES Maya (N = 4587).
Results: Dental age shows only a weak correlation with skeletal age (0.18) and height (0.2). The distinction between cohorts differs according to each of the three measurements. All cohorts differ significantly in height. In skeletal maturation, the middle SES cohort is significantly advanced compared to all other cohorts. The periodically malnourished cohorts of low SES Mayas and Ladinos are significantly delayed in dental maturation compared to the well-nourished low-middle and middle class Ladino children.
Conclusion: Dental development is an independent system, that is regulated by different mechanisms than skeletal development and growth. Tooth eruption is sensitive to nutritional status, whereas skeletal age is more sensitive to socioeconomic background.
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.
In recent years, gravitational-wave astronomy has motivated increasingly accurate perturbative studies of gravitational dynamics in compact binaries. This in turn has enabled more detailed analyses of the dynamical black holes in these systems. For example, Pound et al. [Phys. Rev. Lett. 124, 021101 (2020)] recently computed the surface area of a Schwarzschild black hole's apparent horizon, perturbed by an orbiting body, to second order in the binary's mass ratio. In this paper, we take that as the starting point for a comprehensive study of a perturbed Schwarzschild black hole's apparent and event horizon at second perturbative order, deriving generic formulas for the first- and second-order corrections to the horizons' radial profiles, surface areas, Hawking masses, and intrinsic curvatures. We find that the two horizons are remarkably similar, and that any teleological behavior of the event horizon is suppressed in several ways. Critically, we establish that at all orders, the perturbed event horizon in a small-mass-ratio binary is effectively localized in time. Even more pointedly, the event horizon is identical to the apparent horizon at linear order regardless of the source of perturbation, implying that the seemingly teleological "tidal lead," previously observed in linearly perturbed event horizons, is not genuinely teleological in origin. The two horizons do generically differ at second order, but their Hawking masses remain identical, implying that the event horizon obeys the same energy-flux balance law as the apparent horizon. At least in the case of a binary system, the difference between their surface areas remains extremely small even in the late stages of inspiral. In the course of our analysis, we also numerically illustrate puzzling behavior in the black hole's motion around the binary's center of mass.
Hydrogeological information about an aquifer is difficult and costly to obtain, yet essential for the efficient management of groundwater resources. Transferring information from sampled sites to a specific site of interest can provide information when site-specific data is lacking. Central to this approach is the notion of site similarity, which is necessary for determining relevant sites to include in the data transfer process. In this paper, we present a data-driven method for defining site similarity. We apply this method to selecting groups of similar sites from which to derive prior distributions for the Bayesian estimation of hydraulic conductivity measurements at sites of interest. We conclude that there is now a unique opportunity to combine hydrogeological expertise with data-driven methods to improve the predictive ability of stochastic hydrogeological models.
Privacy regulations and the physical distribution of heterogeneous data are often primary concerns for the development of deep learning models in a medical context. This paper evaluates the feasibility of differentially private federated learning for chest X-ray classification as a defense against data privacy attacks. To the best of our knowledge, we are the first to directly compare the impact of differentially private training on two different neural network architectures, DenseNet121 and ResNet50. Extending the federated learning environments previously analyzed in terms of privacy, we simulated a heterogeneous and imbalanced federated setting by distributing images from the public CheXpert and Mendeley chest X-ray datasets unevenly among 36 clients. Both non-private baseline models achieved an area under the receiver operating characteristic curve (AUC) of 0.940.94 on the binary classification task of detecting the presence of a medical finding. We demonstrate that both model architectures are vulnerable to privacy violation by applying image reconstruction attacks to local model updates from individual clients. The attack was particularly successful during later training stages. To mitigate the risk of a privacy breach, we integrated Rényi differential privacy with a Gaussian noise mechanism into local model training. We evaluate model performance and attack vulnerability for privacy budgets ε∈{1,3,6,10}�∈{1,3,6,10}. The DenseNet121 achieved the best utility-privacy trade-off with an AUC of 0.940.94 for ε=6�=6. Model performance deteriorated slightly for individual clients compared to the non-private baseline. The ResNet50 only reached an AUC of 0.760.76 in the same privacy setting. Its performance was inferior to that of the DenseNet121 for all considered privacy constraints, suggesting that the DenseNet121 architecture is more robust to differentially private training.
Cutting-edge hyperscanning methods led to a paradigm shift in social neuroscience. It allowed researchers to measure dynamic mutual alignment of neural processes between two or more individuals in naturalistic contexts. The ever-growing interest in hyperscanning research calls for the development of transparent and validated data analysis methods to further advance the field. We have developed and tested a dual electroencephalography (EEG) analysis pipeline, namely DEEP. Following the preprocessing of the data, DEEP allows users to calculate Phase Locking Values (PLVs) and cross-frequency PLVs as indices of inter-brain phase alignment of dyads as well as time-frequency responses and EEG power for each participant. The pipeline also includes scripts to control for spurious correlations. Our goal is to contribute to open and reproducible science practices by making DEEP publicly available together with an example mother-infant EEG hyperscanning dataset.
We use a dense seismic network on the Reykjanes Peninsula, Iceland, to image a group of earthquakes at 10-12 km depth, 2 km north-east of 2021 Fagradalsfjall eruption site. These deep earthquakes have a lower frequency content compared to earthquakes located in the upper, brittle crust and are similar to deep long period (DLP) seismicity observed at other volcanoes in Iceland and around the world. We observed several swarms of DLP earthquakes between the start of the study period (June 2020) and the initiation of the 3-week-long dyke intrusion that preceded the eruption in March 2021. During the eruption, DLP earthquake swarms returned 1 km SW of their original location during periods when the discharge rate or fountaining style of the eruption changed. The DLP seismicity is therefore likely to be linked to the magma plumbing system beneath Fagradalsfjall. However, the DLP seismicity occurred similar to 5 km shallower than where petrological modelling places the near-Moho magma storage region in which the Fagradalsfjall lava was stored. We suggest that the DLP seismicity was triggered by the exsolution of CO2-rich fluids or the movement of magma at a barrier to the transport of melt in the lower crust. Increased flux through the magma plumbing system during the eruption likely adds to the complexity of the melt migration process, thus causing further DLP seismicity, despite a contemporaneous magma channel to the surface.
Deep lipidomics in human plasma: cardiometabolic disease risk and effect of dietary fat modulation
(2022)
Background: In blood and tissues, dietary and endogenously generated fatty acids (FAs) occur in free form or as part of complex lipid molecules that collectively represent the lipidome of the respective tissue. We assessed associations of plasma lipids derived from high-resolution lipidomics with incident cardiometabolic diseases and subsequently tested if the identified risk-associated lipids were sensitive to dietary fat modification. Methods: The EPIC Potsdam cohort study (European Prospective Investigation into Cancer and Nutrition) comprises 27 548 participants recruited within an age range of 35 to 65 years from the general population around Potsdam, Germany. We generated 2 disease-specific case cohorts on the basis of a fixed random subsample (n=1262) and all respective cohort-wide identified incident primary cardiovascular disease (composite of fatal and nonfatal myocardial infarction and stroke; n=551) and type 2 diabetes (n=775) cases. We estimated the associations of baseline plasma concentrations of 282 class-specific FA abundances (calculated from 940 distinct molecular species across 15 lipid classes) with the outcomes in multivariable-adjusted Cox models. We tested the effect of an isoenergetic dietary fat modification on risk-associated lipids in the DIVAS randomized controlled trial (Dietary Intervention and Vascular Function; n=113). Participants consumed either a diet rich in saturated FAs (control), monounsaturated FAs, or a mixture of monounsaturated and n-6 polyunsaturated FAs for 16 weeks. Results: Sixty-nine lipids associated (false discovery rate<0.05) with at least 1 outcome (both, 8; only cardiovascular disease, 49; only type 2 diabetes, 12). In brief, several monoacylglycerols and FA16:0 and FA18:0 in diacylglycerols were associated with both outcomes; cholesteryl esters, free fatty acids, and sphingolipids were largely cardiovascular disease specific; and several (glycero)phospholipids were type 2 diabetes specific. In addition, 19 risk-associated lipids were affected (false discovery rate<0.05) by the diets rich in unsaturated dietary FAs compared with the saturated fat diet (17 in a direction consistent with a potential beneficial effect on long-term cardiometabolic risk). For example, the monounsaturated FA-rich diet decreased diacylglycerol(FA16:0) by 0.4 (95% CI, 0.5-0.3) SD units and increased triacylglycerol(FA22:1) by 0.5 (95% CI, 0.4-0.7) SD units. Conclusions: We identified several lipids associated with cardiometabolic disease risk. A subset was beneficially altered by a dietary fat intervention that supports the substitution of dietary saturated FAs with unsaturated FAs as a potential tool for primary disease prevention.
Hundreds of basaltic plateau margins east of the Patagonian Cordillera are undermined by numerous giant slope failures. However, the overall extent of this widespread type of plateau collapse remains unknown and incompletely captured in local maps. To detect giant slope failures consistently throughout the region, we train two convolutional neural networks (CNNs), AlexNet and U-Net, with Sentinel-2 optical data and TanDEM-X topographic data on elevation, surface roughness, and curvature. We validated the performance of these CNNs with independent testing data and found that AlexNet performed better when learned on topographic data, and UNet when learned on optical data. AlexNet predicts a total landslide area of 12,000 km2 in a study area of 450,000 km2, and thus one of Earth's largest clusters of giant landslides. These are mostly lateral spreads and rotational failures in effusive rocks, particularly eroding the margins of basaltic plateaus; some giant landslides occurred along shores of former glacial lakes, but are least prevalent in Quaternary sedimentary rocks. Given the roughly comparable topographic, climatic, and seismic conditions in our study area, we infer that basalts topping weak sedimentary rocks may have elevated potential for large-scale slope failure. Judging from the many newly detected and previously unknown landslides, we conclude that CNNs can be a valuable tool to detect large-scale slope instability at the regional scale. However, visual inspection is still necessary to validate results and correctly outline individual landslide source and deposit areas.
Objectives To compare image quality of deep learning reconstruction (AiCE) for radiomics feature extraction with filtered back projection (FBP), hybrid iterative reconstruction (AIDR 3D), and model-based iterative reconstruction (FIRST). Methods Effects of image reconstruction on radiomics features were investigated using a phantom that realistically mimicked a 65-year-old patient's abdomen with hepatic metastases. The phantom was scanned at 18 doses from 0.2 to 4 mGy, with 20 repeated scans per dose. Images were reconstructed with FBP, AIDR 3D, FIRST, and AiCE. Ninety-three radiomics features were extracted from 24 regions of interest, which were evenly distributed across three tissue classes: normal liver, metastatic core, and metastatic rim. Features were analyzed in terms of their consistent characterization of tissues within the same image (intraclass correlation coefficient >= 0.75), discriminative power (Kruskal-Wallis test p value < 0.05), and repeatability (overall concordance correlation coefficient >= 0.75). Results The median fraction of consistent features across all doses was 6%, 8%, 6%, and 22% with FBP, AIDR 3D, FIRST, and AiCE, respectively. Adequate discriminative power was achieved by 48%, 82%, 84%, and 92% of features, and 52%, 20%, 17%, and 39% of features were repeatable, respectively. Only 5% of features combined consistency, discriminative power, and repeatability with FBP, AIDR 3D, and FIRST versus 13% with AiCE at doses above 1 mGy and 17% at doses >= 3 mGy. AiCE was the only reconstruction technique that enabled extraction of higher-order features. Conclusions AiCE more than doubled the yield of radiomics features at doses typically used clinically. Inconsistent tissue characterization within CT images contributes significantly to the poor stability of radiomics features.
Deep metric learning employs deep neural networks to embed instances into a metric space such that distances between instances of the same class are small and distances between instances from different classes are large. In most existing deep metric learning techniques, the embedding of an instance is given by a feature vector produced by a deep neural network and Euclidean distance or cosine similarity defines distances between these vectors. This paper studies deep distributional embeddings of sequences, where the embedding of a sequence is given by the distribution of learned deep features across the sequence. The motivation for this is to better capture statistical information about the distribution of patterns within the sequence in the embedding. When embeddings are distributions rather than vectors, measuring distances between embeddings involves comparing their respective distributions. The paper therefore proposes a distance metric based on Wasserstein distances between the distributions and a corresponding loss function for metric learning, which leads to a novel end-to-end trainable embedding model. We empirically observe that distributional embeddings outperform standard vector embeddings and that training with the proposed Wasserstein metric outperforms training with other distance functions.
Concentrating Solar Power (CSP) offers flexible and decarbonized power generation and is one of the few dispatchable renewable technologies able to generate renewable electricity on demand. Today (2018) CSP contributes only 5TWh to the European power generation, but it has the potential to become one of the key pillars for European decarbonization pathways. In this paper we investigate how factors and pivotal policy decisions leading to different futures and associated CSP deployment in Europe in the years up to 2050. In a second step we characterize the scenarios with their associated system cost and the costs of support policies. We show that the role of CSP in Europe critically depends on political developments and the success or failure of policies outside renewable power. In particular, the uptake of CSP depends on the overall decarbonization ambition, the degree of cross border trade of renewable electricity and is enabled by the presence of strong grid interconnection between Southern and Norther European Member States as well as by future electricity demand growth. The presence of other baseload technologies, prominently nuclear power in France, reduce the role and need for CSP. Assuming favorable technological development, we find a strong role for CSP in Europe in all modeled scenarios: contributing between 100TWh to 300TWh of electricity to a future European power system. This would require increasing the current European CSP fleet by a factor of 20 to 60 in the next 30 years. To achieve this financial support between € 0.4-2 billion per year into CSP would be needed, representing only a small share of overall support needs for power-system transformation. Cooperation of Member States could further help to reduce this cost.
Recently, a large number of research teams from around the world collaborated in the so-called 'anomalous diffusion challenge'. Its aim: to develop and compare new techniques for inferring stochastic models from given unknown time series, and estimate the anomalous diffusion exponent in data. We use various numerical methods to directly obtain this exponent using the path increments, and develop a questionnaire for model selection based on feature analysis of a set of known stochastic processes given as candidates. Here, we present the theoretical background of the automated algorithm which we put for these tasks in the diffusion challenge, as a counter to other pure data-driven approaches.
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.
Deciphering chemical mediators regulating specialized metabolism in a symbiotic cyanobacterium
(2022)
Genomes of cyanobacteria feature a variety of cryptic biosynthetic pathways for complex natural products, but the peculiarities limiting the discovery and exploitation of the metabolic dark matter are not well understood. Here we describe the discovery of two cell density-dependent chemical mediators, nostoclide and nostovalerolactone, in the symbiotic model strain Nostoc punctiforme, and demonstrate their pronounced impact on the regulation of specialized metabolism. Through transcriptional, bioinformatic and labeling studies we assigned two adjacent biosynthetic gene clusters to the biosynthesis of the two polyketide mediators. Our findings provide insight into the orchestration of specialized metabolite production and give lessons for the genomic mining and high-titer production of cyanobacterial bioactive compounds.
Introduction Physical activity among children and adolescents remains insufficient, despite the substantial efforts made by researchers and policymakers. Identifying and furthering our understanding of potential modifiable determinants of physical activity behaviour (PAB) and sedentary behaviour (SB) is crucial for the development of interventions that promote a shift from SB to PAB. The current protocol details the process through which a series of systematic literature reviews and meta-analyses (MAs) will be conducted to produce a best-evidence statement (BESt) and inform policymakers. The overall aim is to identify modifiable determinants that are associated with changes in PAB and SB in children and adolescents (aged 5-19 years) and to quantify their effect on, or association with, PAB/SB. Methods and analysis A search will be performed in MEDLINE, SportDiscus, Web of Science, PsychINFO and Cochrane Central Register of Controlled Trials. Randomised controlled trials (RCTs) and controlled trials (CTs) that investigate the effect of interventions on PAB/SB and longitudinal studies that investigate the associations between modifiable determinants and PAB/SB at multiple time points will be sought. Risk of bias assessments will be performed using adapted versions of Cochrane's RoB V.2.0 and ROBINS-I tools for RCTs and CTs, respectively, and an adapted version of the National Institute of Health's tool for longitudinal studies. Data will be synthesised narratively and, where possible, MAs will be performed using frequentist and Bayesian statistics. Modifiable determinants will be discussed considering the settings in which they were investigated and the PAB/SB measurement methods used. Ethics and dissemination No ethical approval is needed as no primary data will be collected. The findings will be disseminated in peer-reviewed publications and academic conferences where possible. The BESt will also be shared with policy makers within the DE-PASS consortium in the first instance. Systematic review registration CRD42021282874.
Data recorded by distributed acoustic sensing (DAS) along an optical fibre sample the spatial and temporal properties of seismic wavefields at high spatial density. Often leading to massive amount of data when collected for seismic monitoring along many kilometre long cables. The spatially coherent signals from weak seismic arrivals within the data are often obscured by incoherent noise. We present a flexible and computationally efficient filtering technique, which makes use of the dense spatial and temporal sampling of the data and that can handle the large amount of data. The presented adaptive frequency-wavenumber filter suppresses the incoherent seismic noise while amplifying the coherent wavefield. We analyse the response of the filter in time and spectral domain, and we demonstrate its performance on a noisy data set that was recorded in a vertical borehole observatory showing active and passive seismic phase arrivals. Lastly, we present a performant open-source software implementation enabling real-time filtering of large DAS data sets.
This study aims to compare online vs. offline flirting and dating behavior using the example of the location-based real-time dating (LBRTD) app Tinder, a popular dating platform. We focus on persons' self-descriptions like self-esteem, social desirability, state social anxiety, and adjustment behavior on Tinder and the perceived data privacy of the app. Data was gathered using a survey approach with Tinder users reporting their behavior in offline and online settings. The comparison between offline and online behavior was made using Response Surface Analysis. The results suggest that the different conditions of the natural and digital worlds do not influence the individual's behavior and emotional perception. The results are analyzed and discuss gender, age, motivation to use the app, and the user's relationship status.
This dataset comprises tree inventories and damage assessments performed in Namibia's semi-arid Zambezi Region. Data were sampled in savannas and savanna woodlands along steep gradients of elephant population densities to capture the effects of those (and other) disturbances on individual-level and stand-level aboveground woody biomass (AGB). The dataset contains raw data on dendrometric measures and processed data on specific wood density (SWD), woody aboveground biomass, and biomass losses through disturbance impacts. Allometric proxies (height, canopy diameters, and in adult trees also stem circumferences) were recorded for n = 6,179 tree and shrub individuals. Wood samples were taken for each encountered species to measure specific wood density.
These measurements have been used to estimate woody aboveground biomass via established allometric models, advanced through our improved methodologies and workflows that accounted for tree and shrub architecture shaped by disturbance impacts. To this end, we performed a detailed damage assessment on each woody individual in the field. In addition to estimations of standing biomass, our new method also delivered data on biomass losses to different disturbance agents (elephants, fire, and others) on the level of plant individuals and stands.
The data presented here have been used within a study published with Ecological Indicators (Kindermann et al., 2022) to evaluate the benefits of our improved methodology in comparison to a standard reference method of aboveground biomass estimations. Additionally, it has been employed in a study on carbon storage and sequestration in vegetation and soils (Sandhage-Hofmann et al., 2021).
The raw data of dendrometric measurements can be subjected to other available allometric models for biomass estimation. The processed data can be used to analyze disturbance impacts on woody aboveground biomass, or for regional carbon storage estimates. The data on species-specific wood density can be used for application to other dendrometric datasets to (re-) estimate biomass through allometric models requiring wood density. It can further be used for plant functional trait analyses.
Data-driven expectations for electromagnetic counterpart searches based on LIGO/Virgo public alerts
(2022)
Searches for electromagnetic counterparts of gravitational-wave signals have redoubled since the first detection in 2017 of a binary neutron star merger with a gamma-ray burst, optical/infrared kilonova, and panchromatic afterglow. Yet, one LIGO/Virgo observing run later, there has not yet been a second, secure identification of an electromagnetic counterpart. This is not surprising given that the localization uncertainties of events in LIGO and Virgo's third observing run, O3, were much larger than predicted.
We explain this by showing that improvements in data analysis that now allow LIGO/Virgo to detect weaker and hence more poorly localized events have increased the overall number of detections, of which well-localized, gold-plated events make up a smaller proportion overall.
We present simulations of the next two LIGO/Virgo/KAGRA observing runs, O4 and O5, that are grounded in the statistics of O3 public alerts. To illustrate the significant impact that the updated predictions can have, we study the follow-up strategy for the Zwicky Transient Facility. Realistic and timely forecasting of gravitational-wave localization accuracy is paramount given the large commitments of telescope time and the need to prioritize which events are followed up.
We include a data release of our simulated localizations as a public proposal planning resource for astronomers.
Teaching and learning as well as administrative processes are still experiencing intensive changes with the rise of artificial intelligence (AI) technologies and its diverse application opportunities in the context of higher education. Therewith, the scientific interest in the topic in general, but also specific focal points rose as well. However, there is no structured overview on AI in teaching and administration processes in higher education institutions that allows to identify major research topics and trends, and concretizing peculiarities and develops recommendations for further action. To overcome this gap, this study seeks to systematize the current scientific discourse on AI in teaching and administration in higher education institutions. This study identified an (1) imbalance in research on AI in educational and administrative contexts, (2) an imbalance in disciplines and lack of interdisciplinary research, (3) inequalities in cross-national research activities, as well as (4) neglected research topics and paths. In this way, a comparative analysis between AI usage in administration and teaching and learning processes, a systematization of the state of research, an identification of research gaps as well as further research path on AI in higher education institutions are contributed to research.
Dynamical models make specific assumptions about cognitive processes that generate human behavior. In data assimilation, these models are tested against timeordered data. Recent progress on Bayesian data assimilation demonstrates that this approach combines the strengths of statistical modeling of individual differences with the those of dynamical cognitive models.
The random nature of self-amplified spontaneous emission (SASE) is a well-known challenge for x-ray core level spectroscopy at SASE free-electron lasers (FELs). Especially in time-resolved experiments that require a combination of good temporal and spectral resolution the jitter and drifts in the spectral characteristics, relative arrival time as well as power fluctuations can smear out spectral-temporal features. We present a combination of methods for the analysis of time-resolved photoelectron spectra based on power and time corrections as well as self-referencing of a strong photoelectron line. Based on sulfur 2p photoelectron spectra of 2-thiouracil taken at the SASE FEL FLASH2, we show that it is possible to correct for some of the photon energy drift and jitter even when reliable shot-to-shot photon energy data is not available. The quality of pump-probe difference spectra improves as random jumps in energy between delay points reduce significantly. The data analysis allows to identify coherent oscillations of 1 eV shift on the mean photoelectron line of 4 eV width with an error of less than 0.1 eV.
Understanding and constraining the source of geodetic deformation in volcanic areas is an important component of hazard assessment. Here, we analyse deformation and seismicity for one year before the March 2021 Fagradalsfjall eruption in Iceland. We generate a high-resolution catalogue of 39,500 earthquakes using optical cable recordings and develop a poroelastic model to describe three pre-eruptional uplift and subsidence cycles at the Svartsengi geothermal field, 8 km west of the eruption site. We find the observed deformation is best explained by cyclic intrusions into a permeable aquifer by a fluid injected at 4 km depth below the geothermal field, with a total volume of 0.11 ± 0.05 km3 and a density of 850 ± 350 kg m–3. We therefore suggest that ingression of magmatic CO2 can explain the geodetic, gravity and seismic data, although some contribution of magma cannot be excluded.
Structure and spatial magnetic properties, through-space NMR shieldings (TSNMRSs), of all ten cycl[2.2.2]azine to cycl[4.4.4]azine, hetero-analogues and the corresponding hydrocarbons have been calculated at the B3LYP/6-311G(d,p) theory level using the GIAO perturbation method and employing the nucleus independent chemical shift (NICS) concept. The TSNMRS values (actually, the ring current effect as measurable in H-1 NMR spectroscopy) are visualized as iso-chemical-shielding surfaces (ICSS) of various size and direction, and employed to readily qualify and quantify the degree of (anti)aromaticity. Results are confirmed by NMR [delta(H-1)/ppm, delta(N-15)/ppm] and geometry (planar, twisted, bow-shaped) data. The cyclazines N[2.2.2](-) up to N[2.4.4](-) are planar or at most slightly bowl-shaped and, due to coherent peripheral ring currents (except in N[2.3.3](-), N[2.3.4], N[3.3.4](+) and N[2.4.4](+)), develop aromaticity or anti-aromaticity of the whole molecules dependent on the number of peripheral conjugated pi electrons. The cyclazines N[2.3.3](-), N[2.3.4], N[3.3.4](+) and N[2.4.4](+) develop two ring currents of different direction within the same molecule, in which the dominating ring current proves to be paratropic (in N[3.3.4](+) diatropic) including the nodal N p(z) lone pair into the conjugation. The residual cyclazines N[3.4.4], N[4.4.4](-) and N[4.4.4](+) are heavily twisted and, therefore, are not developing peripheral or diverse ring currents. The TSNMRS information about cyclazines and the parent tricyclic annulene analogues is congruent subject to structure and number of peripheral or internal conjugated pi electrons, the corresponding (anti)aromaticity is in unequivocal accordance with Huckel's rule.
The fluctuating hydrogen bridge bonded network of liquid water at ambient conditions entails a varied ensemble of the underlying constituting H2O molecular moieties. This is mirrored in a manifold of the H2O molecular potentials. Subnatural line width resonant inelastic X-ray scattering allowed us to quantify the manifold of molecular potential energy surfaces along the H2O symmetric normal mode and the local asymmetric O-H bond coordinate up to 1 and 1.5 angstrom, respectively. The comparison of the single H2O molecular potentials and spectroscopic signatures with the ambient conditions liquid phase H2O molecular potentials is done on various levels. In the gas phase, first principles, Morse potentials, and stepwise harmonic potential reconstruction have been employed and benchmarked. In the liquid phase the determination of the potential energy manifold along the local asymmetric O-H bond coordinate from resonant inelastic X-ray scattering via the bound state oxygen ls to 4a(1) resonance is treated within these frameworks. The potential energy surface manifold along the symmetric stretch from resonant inelastic X-ray scattering via the oxygen 1 s to 2b(2) resonance is based on stepwise harmonic reconstruction. We find in liquid water at ambient conditions H2O molecular potentials ranging from the weak interaction limit to strongly distorted potentials which are put into perspective to established parameters, i.e., intermolecular O-H, H-H, and O-O correlation lengths from neutron scattering.
Ionic liquid crystals (ILCs), that is, ionic liquids exhibiting mesomorphism, liquid crystalline phases, and anisotropic properties, have received intense attention in the past years. Among others, this is due to their special properties arising from the combination of properties stemming from ionic liquids and from liquid crystalline arrangements. Besides interesting fundamental aspects, ILCs have been claimed to have tremendous application potential that again arises from the combination of properties and architectures that are not accessible otherwise, or at least not accessible easily by other strategies. The current review highlights recent developments in ILC research, starting with some key fundamental aspects. Further subjects covered include the synthesis and variations of modern ILCs, including the specific tuning of their mesomorphic behavior. The review concludes with reflections on some applications that may be within reach for ILCs and finally highlights a few key challenges that must be overcome prior and during true commercialization of ILCs.
In his article, 'Social constructionism and climate science denial', Hansson claims to present empirical evidence that the cultural theory developed by Dame Mary Douglas, Aaron Wildavsky and ourselves (among others) leads to (climate) science denial. In this reply, we show that there is no validity to these claims. First, we show that Hansson's empirical evidence that cultural theory has led to climate science denial falls apart under closer inspection. Contrary to Hansson's claims, cultural theory has made significant contributions to understanding and addressing climate change. Second, we discuss various features of Douglas' cultural theory that differentiate it from other constructivist approaches and make it compatible with the scientific method. Thus, we also demonstrate that cultural theory cannot be accused of epistemic relativism.
Cultural diversity approaches in schools and adolescents’ willingness to support refugee youth
(2022)
Background Culturally diverse schools contribute to adolescents' intergroup relations. Complex and inclusive social identities are mechanisms that can explain the link between structural school cultural diversity (i.e., proportion of students of immigrant descent and the number of different ethnic groups) and positive intergroup relations. We expected that similar mechanisms might be at play linking cultural diversity approaches in schools with adolescents' intergroup relations. Aim We examined the link between two sub-dimensions of cultural diversity approaches (i.e., equal treatment; heritage and intercultural learning) and adolescents' prosocial intentions and behaviour towards refugee youth. Then, we explored the mediating role of identity inclusiveness (i.e., perceived similarity of the self with others). Sample and methods We sampled culturally diverse eighth grade adolescents from 54 classrooms in Berlin (N = 503, M-age = 13.76 years, 50.6% female). Surveys measured perceived cultural diversity norms, adolescents' perceived identity inclusiveness with refugee youth, prosocial intentions to support refugee youth, and willingness to donate to a project for refugee youth. Results Multilevel models revealed that adolescents' perception of heritage and intercultural learning predicted adolescents' prosocial intentions towards refugee youth, but not their willingness to donate. Equal treatment was not a significant predictor of adolescents' prosocial intentions towards refugee youth, or their willingness to donate. Identity inclusiveness did not mediate the relation between cultural diversity approaches and prosocial intentions. However, identity inclusiveness did positively relate adolescents' prosocial intentions and willingness to donate. Conclusions We conclude that culturally diverse schools that engage in heritage and intercultural learning might help to promote positive relations between local and refugee youth in schools and society. Fostering inclusive identities may enhance local adolescent's prosocial intention and behaviour.
High-throughput proteomics approaches have resulted in large-scale protein–protein interaction (PPI) networks that have been employed for the prediction of protein complexes. However, PPI networks contain false-positive as well as false-negative PPIs that affect the protein complex prediction algorithms. To address this issue, here we propose an algorithm called CUBCO+ that: (1) employs GO semantic similarity to retain only biologically relevant interactions with a high similarity score, (2) based on link prediction approaches, scores the false-negative edges, and (3) incorporates the resulting scores to predict protein complexes. Through comprehensive analyses with PPIs from Escherichia coli, Saccharomyces cerevisiae, and Homo sapiens, we show that CUBCO+ performs as well as the approaches that predict protein complexes based on recently introduced graph partitions into biclique spanned subgraphs and outperforms the other state-of-the-art approaches. Moreover, we illustrate that in combination with GO semantic similarity, CUBCO+ enables us to predict more accurate protein complexes in 36% of the cases in comparison to CUBCO as its predecessor.
Numerous phosphorus-rich metal phosphides containing both P-P bonds and metal-P bonds are known from the solid-state chemistry literature. A method to grow these materials in thin-film form would be desirable, as thin films are required in many applications and they are an ideal platform for high-throughput studies. In addition, the high density and smooth surfaces achievable in thin films are a significant advantage for characterization of transport and optical properties. Despite these benefits, there is hardly any published work on even the simplest binary phosphorus-rich phosphide films. Here, we demonstrate growth of single-phase CuP2 films by a two-step process involving reactive sputtering of amorphous CuP2+x and rapid annealing in an inert atmosphere. At the crystallization temperature, CuP2 is thermodynamically unstable with respect to Cu3P and P-4. However, CuP2 can be stabilized if the amorphous precursors are mixed on the atomic scale and are sufficiently close to the desired composition (neither too P poor nor too P rich). Fast formation of polycrystalline CuP2, combined with a short annealing time, makes it possible to bypass the diffusion processes responsible for decomposition. We find that thin-film CuP2 is a 1.5 eV band gap semiconductor with interesting properties, such as a high optical absorption coefficient (above 10(5) cm(-1)), low thermal conductivity (1.1 W/(K m)), and composition-insensitive electrical conductivity (around 1 S/cm). We anticipate that our processing route can be extended to other phosphorus-rich phosphides that are still awaiting thin-film synthesis and will lead to a more complete understanding of these materials and of their potential applications.
Cross-national variation in the relationship between welfare generosity and single mother employment
(2022)
Reform of the U.S. welfare system in 1996 spurred claims that cuts to welfare programs effectively incentivized single mothers to find employment. It is difficult to assess the veracity of those claims, however, absent evidence of how the relationship between welfare benefits and single mother employment generalizes across countries. This study combines data from the European Union Labour Force Survey and the U.S. Current Population Survey (1992-2015) into one of the largest samples of single mothers ever, testing the relationships between welfare generosity and single mothers’ employment and work hours. We find no consistent evidence of a negative relationship between welfare generosity and single mother employment outcomes. Rather, we find tremendous cross-national heterogeneity, which does not clearly correspond to well-known institutional variations. Our findings demonstrate the limitations of single country studies and the pervasive, salient interactions between institutional contexts and social policies.
Schools are key contexts for the development of adolescents' critical consciousness. We explored how three dimensions of the classroom cultural diversity climate (critical consciousness, color-evasion, and multiculturalism) related to adolescents' critical reflection (i.e., perceived societal Islamophobia) and intended critical action (i.e., political activism). Our sample included adolescents experiencing high (second generation, Muslim, N = 237) versus low (non-immigrant descent, non-Muslim, N = 478) stigmatization in Germany. Multilevel analyses revealed that for both groups a critical consciousness climate, but not a color-evasive or a multicultural climate, was positively associated with perceived societal Islamophobia and intended critical action. Thus, to promote adolescents' critical consciousness, schools should go beyond emphasizing a common humanity and celebrating cultural diversity and include explicit discussions of social inequity.
Critical anthropology? On the relation between philosophical anthropology and critical theory
(2022)
This article compares Max Horkheimer's and Theodor W. Adorno's foundation of the Frankfurt Critical Theory with Helmuth Plessner's foundation of Philosophical Anthropology.
While Horkheimer's and Plessner's paradigms are mutually incompatible, Adorno's << negative dialectics >> and Plessner's << negative anthropology >> (G. Gamm) can be seen as complementing one another.
Jurgen Habermas at one point sketched a complementary relationship between his own publicly communicative theory of modern society and Plessner's philosophy of nature and human expressivity, and though he then came to doubt this, he later reaffirmed it. Faced with the << life power >> in << high capitalism >> (Plessner), the ambitions for a public democracy in a pluralistic society have to be broadened from an argumentative focus (Habermas) to include the human condition and the expressive modes of our experience as essentially embodied persons. The article discusses some possible aspects of this complementarity under the title of a << critical anthropology >> (H. Schnädelbach).
CovRadar
(2022)
The ongoing pandemic caused by SARS-CoV-2 emphasizes the importance of genomic surveillance to understand the evolution of the virus, to monitor the viral population, and plan epidemiological responses. Detailed analysis, easy visualization and intuitive filtering of the latest viral sequences are powerful for this purpose. We present CovRadar, a tool for genomic surveillance of the SARS-CoV-2 Spike protein. CovRadar consists of an analytical pipeline and a web application that enable the analysis and visualization of hundreds of thousand sequences. First, CovRadar extracts the regions of interest using local alignment, then builds a multiple sequence alignment, infers variants and consensus and finally presents the results in an interactive app, making accessing and reporting simple, flexible and fast.
This paper addresses terrorism trials as sites of research and proposes an approach for the analysis of ethnographic data collected during these trials. The suggested approach offers multi-level analytical access, it centers around interactionist conceptions and knowledge discourses. The conceptual framework we suggest is spelled out in terms of how to observe and being sensitive of (re-)production of power structures inside the courtroom as well as in regard to relations imported into the courtroom. For this purpose, we integrate (i) the micro-level of courtroom interactions and (ii) (self-)presentation, (iii) the meso-level of knowledge (re)production and the establishment of knowledge orders and (iv) an intersectional perspective on gender, race, and class in knowledge discourses. By applying a multi-level approach, we open up new explanatory avenues to understand the constitution of terrorism as a socio-legal object. The methodical framework connects hitherto unconnected elements, that is, participants' interactions and negotiation, their (self-)representations, ascriptions and narrative performances, and knowledge (re-)production in order to establish or maintain political and social orders.
Modelling of an open quantum system requires knowledge of parameters that specify how it couples to its environment. However, beyond relaxation rates, realistic parameters for specific environments and materials are rarely known. Here we present a method of inferring the coupling between a generic system and its bosonic (e.g., phononic) environment from the experimentally measurable density of states (DOS). With it we confirm that the DOS of the well-known Debye model for three-dimensional solids is physically equivalent to choosing an Ohmic bath. We further match a real phonon DOS to a series of Lorentzian coupling functions, allowing us to determine coupling parameters for gold, yttrium iron garnet (YIG) and iron as examples. The results illustrate how to obtain material-specific dynamical properties, such as memory kernels. The proposed method opens the door to more accurate modelling of relaxation dynamics, for example for phonon-dominated spin damping in magnetic materials.
As presidents approach the end of their constitutionally defined term in office, they face a number of difficulties, most importantly the deprivation of sources of power, personal enrichment, and protection from prosecution. This leads many of them to attempt to circumvent their term limits. Recent studies explain both the reasons for the extension or full abolition of term limits, and failed attempts to do so. Key explanations include electoral competition and the post-term fate of previous post holders. What we do not know yet is how compliance with term limits may be tied to the current president's expectations for their post-term fate. In particular, we do not know whether leaders who attempt to remove term limits and fail to do so jeopardize their post-term career as a result, and conversely, whether leaders who comply will have better outcomes in terms of security, prestige, and economic gain. Hence, we ask how the decision of a leader to comply or not comply with term limits is conditioned by the expectation of their post-term fate. To address this question, this article introduces new data on the career trajectories of term-limited presidents and its systematic effect on term limit compliance.
This paper studies cosmic-ray (CR) transport in magnetohydrodynamic (MHD) turbulence. CR transport is strongly dependent on the properties of the magnetic turbulence.
We perform test particle simulations to study the interactions of CR with both total MHD turbulence and decomposed MHD modes.
The spatial diffusion coefficients and the pitch angle scattering diffusion coefficients are calculated from the test particle trajectories in turbulence.
Our results confirm that the fast modes dominate the CR propagation, whereas Alfven and slow modes are much less efficient and have shown similar pitch-angle scattering rates.
We investigate the cross field transport on large and small scales. On large/global scales, normal diffusion is observed and the diffusion coefficient is suppressed by M-A(zeta) compared to the parallel diffusion coefficients, with zeta closer to 4 in Alfven modes than that in total turbulence, as theoretically expected.
For the CR transport on scales smaller than the turbulence injection scale, both the local and global magnetic reference frames are adopted. Superdiffusion is observed on such small scales in all the cases. Particularly, CR transport in Alfven modes show clear Richardson diffusion in the local reference frame. The diffusion transitions smoothly from the Richardson's one with index 1.5 to normal diffusion as the particle mean free path decreases from lambda(parallel to) >> L to lambda(parallel to) << L, where L is the injection/coherence length of turbulence.
Our results have broad applications to CRs in various astrophysical environments.
This study investigated the role of medium (face-to-face, cyber) and publicity (public, private) in adolescents' perceptions of severity and coping strategies (i.e., avoidant, ignoring, helplessness, social support seeking, retaliation) for victimization, while accounting for gender and cultural values. There were 3432 adolescents (ages 11-15, 49% girls) in this study; they were from China, Cyprus, the Czech Republic, India, Japan, and the United States. Adolescents completed questionnaires on individualism and collectivism, and ratings of coping strategies and severity for public face-to-face victimization, private face-to-face victimization, public cyber victimization, and private cyber victimization. Findings revealed similarities in adolescents' coping strategies based on perceptions of severity, publicity, and medium for some coping strategies (i.e., social support seeking, retaliation) but differential associations for other coping strategies (i.e., avoidance, helplessness, ignoring). The results of this study are important for prevention and intervention efforts because they underscore the importance of teaching effective coping strategies to adolescents, and to consider how perceptions of severity, publicity, and medium might influence the implementation of these coping strategies.
In an ocean-continent subduction zone, the assessment of the lithospheric thermal state is essential to determine the controls of the deformation within the upper plate and the dip angle of the subducting lithosphere. In this study, we evaluate the degree of influence of both the configuration of the upper plate (i.e., thickness and composition of the rock units) and variations of the subduction angle on the lithospheric thermal field of the southern Central Andes (29 degrees-39 degrees S). Here, the subduction angle increases from subhorizontal (5 degrees) north of 33 degrees S to steep (similar to 30 degrees) in the south. We derived the 3D temperature and heat flow distribution of the lithosphere in the southern Central Andes considering conversion of S wave tomography to temperatures together with steady-state conductive thermal modeling. We found that the orogen is overall warmer than the forearc and the foreland and that the lithosphere of the northern part of the foreland appears colder than its southern counterpart. Sedimentary blanketing and the thickness of the radiogenic crust exert the main control on the shallow thermal field (<50km depth). Specific conditions are present where the oceanic slab is relatively shallow (<85 km depth) and the radiogenic crust is thin. This configuration results in relatively colder temperatures compared to regions where the radiogenic crust is thick and the slab is steep. At depths >50km, the temperatures of the overriding plate are mainly controlled by the mantle heat input and the subduction angle. The thermal field of the upper plate likely preserves the flat subduction angle and influences the spatial distribution of shortening.
Controls on the deformation pattern (shortening mode and tectonic style) of orogenic forelands during lithospheric shortening remain poorly understood. Here, we use high-resolution 2D thermomechanical models to demonstrate that orogenic crustal thickness and foreland lithospheric thickness significantly control the shortening mode in the foreland. Pure-shear shortening occurs when the orogenic crust is not thicker than the foreland crust or thick, but the foreland lithosphere is thin (<70-80 km, as in the Puna foreland case). Conversely, simple-shear shortening, characterized by foreland underthrusting beneath the orogen, arises when the orogenic crust is much thicker. This thickened crust results in high gravitational potential energy in the orogen, which triggers the migration of deformation to the foreland under further shortening. Our models present fully thick-skinned, fully thin-skinned, and intermediate tectonic styles in the foreland. The first tectonics forms in a pure-shear shortening mode whereas the others require a simple-shear mode and the presence of thick (>similar to 4 km) sediments that are mechanically weak (friction coefficient <similar to 0.05) or weakened rapidly during deformation. The formation of fully thin-skinned tectonics in thick and weak foreland sediments, as in the Subandean Ranges, requires the strength of the orogenic upper lithosphere to be less than one-third as strong as that of the foreland upper lithosphere. Our models successfully reproduce foreland deformation patterns in the Central and Southern Andes and the Laramide province.
Fast style transfer methods have recently gained popularity in art-related applications as they make a generalized real-time stylization of images practicable. However, they are mostly limited to one-shot stylizations concerning the interactive adjustment of style elements. In particular, the expressive control over stroke sizes or stroke orientations remains an open challenge. To this end, we propose a novel stroke-adjustable fast style transfer network that enables simultaneous control over the stroke size and intensity, and allows a wider range of expressive editing than current approaches by utilizing the scale-variance of convolutional neural networks. Furthermore, we introduce a network-agnostic approach for style-element editing by applying reversible input transformations that can adjust strokes in the stylized output. At this, stroke orientations can be adjusted, and warping-based effects can be applied to stylistic elements, such as swirls or waves. To demonstrate the real-world applicability of our approach, we present StyleTune, a mobile app for interactive editing of neural style transfers at multiple levels of control. Our app allows stroke adjustments on a global and local level. It furthermore implements an on-device patch-based upsampling step that enables users to achieve results with high output fidelity and resolutions of more than 20 megapixels. Our approach allows users to art-direct their creations and achieve results that are not possible with current style transfer applications.