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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.
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.
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.
Manipulating spin waves is highly required for the development of innovative data transport and processing technologies. Recently, the possibility of triggering high-frequency standing spin waves in magnetic insulators using femtosecond laser pulses was discovered, raising the question about how one can manipulate their dynamics. Here we explore this question by investigating the ultrafast magnetiza-tion and spin-wave dynamics induced by double-pulse laser excitation. We demonstrate a suppression or enhancement of the amplitudes of the standing spin waves by precisely tuning the time delay between the two pulses. The results can be understood as the constructive or destructive interference of the spin waves induced by the first and second laser pulses. Our findings open exciting perspectives towards generating single-mode standing spin waves that combine high frequency with large amplitude and low magnetic damping.
Continuous verification of network security compliance is an accepted need. Especially, the analysis of stateful packet filters plays a central role for network security in practice. But the few existing tools which support the analysis of stateful packet filters are based on general applicable formal methods like Satifiability Modulo Theories (SMT) or theorem prover and show runtimes in the order of minutes to hours making them unsuitable for continuous compliance verification. In this work, we address these challenges and present the concept of state shell interweaving to transform a stateful firewall rule set into a stateless rule set. This allows us to reuse any fast domain specific engine from the field of data plane verification tools leveraging smart, very fast, and domain specialized data structures and algorithms including Header Space Analysis (HSA). First, we introduce the formal language FPL that enables a high-level human-understandable specification of the desired state of network security. Second, we demonstrate the instantiation of a compliance process using a verification framework that analyzes the configuration of complex networks and devices - including stateful firewalls - for compliance with FPL policies. Our evaluation results show the scalability of the presented approach for the well known Internet2 and Stanford benchmarks as well as for large firewall rule sets where it outscales state-of-the-art tools by a factor of over 41.
Bioconversion of waste animal fat (WAF) to polyhydroxyalkanoates (PHAs) is an approach to lower the production costs of these plastic alternatives. However, the solid nature of WAF requires a tailor-made process development. In this study, a double-jacket feeding system was built to thermally liquefy the WAF to employ a continuous feeding strategy. During laboratory-scale cultivations with Ralstonia eutropha Re2058/pCB113, 70% more PHA (45 g(PHA) L-1) and a 75% higher space-time yield (0.63 g(PHA) L-1 h(-1)) were achieved compared to previously reported fermentations with solid WAF. During the development process, growth and PHA formation were monitored in real-time by in-line photon density wave spectroscopy. The process robustness was further evaluated during scale-down fermentations employing an oscillating aeration, which did not alter the PHA yield although cells encountered periods of oxygen limitation. Flow cytometry with propidium iodide staining showed that more than two-thirds of the cells were viable at the end of the cultivation and viability was even little higher in the scale-down cultivations. Application of this feeding system at 150-L pilot-scale cultivation yielded in 31.5 g(PHA) L-1, which is a promising result for the further scale-up to industrial scale.
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.
In this study, 3-D models of P-wave velocity (Vp) and P-wave and S-wave ratio (Vp/Vs) of the crust and upper mantle in the Eastern and eastern Southern Alps (northern Italy and southern Austria) were calculated using local earthquake tomography (LET). The data set includes high-quality arrival times from well-constrained hypocenters observed by the dense, temporary seismic networks of the AlpArray AASN and SWATH-D. The resolution of the LET was checked by synthetic tests and analysis of the model resolution matrix. The small inter-station spacing (average of similar to 15 km within the SWATH-D network) allowed us to image crustal structure at unprecedented resolution across a key part of the Alps. The derived P velocity model revealed a highly heterogeneous crustal structure in the target area. One of the main findings is that the lower crust is thickened, forming a bulge at 30-50 km depth just south of and beneath the Periadriatic Fault and the Tauern Window. This indicates that the lower crust decoupled both from its mantle substratum as well as from its upper crust. The Moho, taken to be the iso-velocity contour of Vp = 7.25 km/s, agrees with the Moho depth from previous studies in the European and Adriatic forelands. It is shallower on the Adriatic side than on the European side. This is interpreted to indicate that the European Plate is subducted beneath the Adriatic Plate in the Eastern and eastern Southern Alps.
Interpreting high-energy, astrophysical phenomena, such as supernova explosions or neutron-star collisions, requires a robust understanding of matter at supranuclear densities. However, our knowledge about dense matter explored in the cores of neutron stars remains limited. Fortunately, dense matter is not probed only in astrophysical observations, but also in terrestrial heavy-ion collision experiments. Here we use Bayesian inference to combine data from astrophysical multi-messenger observations of neutron stars(1-9) and from heavy-ion collisions of gold nuclei at relativistic energies(10,11) with microscopic nuclear theory calculations(12-17) to improve our understanding of dense matter. We find that the inclusion of heavy-ion collision data indicates an increase in the pressure in dense matter relative to previous analyses, shifting neutron-star radii towards larger values, consistent with recent observations by the Neutron Star Interior Composition Explorer mission(5-8,18). Our findings show that constraints from heavy-ion collision experiments show a remarkable consistency with multi-messenger observations and provide complementary information on nuclear matter at intermediate densities. This work combines nuclear theory, nuclear experiment and astrophysical observations, and shows how joint analyses can shed light on the properties of neutron-rich supranuclear matter over the density range probed in neutron stars.
When new covalent organic frameworks (COFs) are designed, the main efforts are typically focused on selecting specific building blocks with certain geometries and properties to control the structure and function of the final COFs. The nature of the linkage (imine, boroxine, vinyl, etc.) between these building blocks naturally also defines their properties. However, besides the linkage type, the orientation, i.e., the constitutional isomerism of these linkages, has rarely been considered so far as an essential aspect. In this work, three pairs of constitutionally isomeric imine-linked donor-acceptor (D-A) COFs are synthesized, which are different in the orientation of the imine bonds (D-C=N-A (DCNA) and D-N=C-A (DNCA)). The constitutional isomers show substantial differences in their photophysical properties and consequently in their photocatalytic performance. Indeed, all DCNA COFs show enhanced photocatalytic H2 evolution performance than the corresponding DNCA COFs. Besides the imine COFs shown here, it can be concluded that the proposed concept of constitutional isomerism of linkages in COFs is quite universal and should be considered when designing and tuning the properties of COFs.
Studies on French adults using a written lexical decision task with masked priming, in which targets were more primed by consonant- (jalu-JOLI) than vowel-related (vobi-JOLI) primes, support the proposal that consonants have more weight than vowels in lexical processing.
This study examines the phonological and/or lexical nature of this consonant bias
(C-bias), using a sandwich priming task in which a brief presentation of the target
(pre-prime) precedes the prime-target sequence, a manipulation blocking lexical neighbourhood effects.
Results from three experiments (varying pre-prime/prime durations) show consistent
C-priming and no significant V-priming at earlier and later processing stages (50 or 66 ms primes).
Yet, a joint analysis reveals a small V-priming, while confirming a significant consonant advantage.
This demonstrates the contribution of the phonological level to the C-bias.
Second, differences in performance comparing the classic versus sandwich priming task also establish a contribution of lexical neighbourhood inhibition effects to the C-bias.
Active matter broadly covers the dynamics of self-propelled particles.
While the onset of collective behavior in homogenous active systems is relatively well understood, the effect of inhomogeneities such as obstacles and traps lacks overall clarity.
Here, we study how interacting, self-propelled particles become trapped and released from a trap.
We have found that captured particles aggregate into an orbiting condensate with a crystalline structure. As more particles are added, the trapped condensates escape as a whole.
Our results shed light on the effects of confinement and quenched disorder in active matter.
In this paper, we examine conditioning of the discretization of the Helmholtz problem. Although the discrete Helmholtz problem has been studied from different perspectives, to the best of our knowledge, there is no conditioning analysis for it. We aim to fill this gap in the literature. We propose a novel method in 1D to observe the near-zero eigenvalues of a symmetric indefinite matrix. Standard classification of ill-conditioning based on the matrix condition number is not true for the discrete Helmholtz problem. We relate the ill-conditioning of the discretization of the Helmholtz problem with the condition number of the matrix. We carry out analytical conditioning analysis in 1D and extend our observations to 2D with numerical observations. We examine several discretizations. We find different regions in which the condition number of the problem shows different characteristics. We also explain the general behavior of the solutions in these regions.
Quantum mechanical tunnelling describes transmission of matter waves through a barrier with height larger than the energy of the wave(1). Tunnelling becomes important when the de Broglie wavelength of the particle exceeds the barrier thickness; because wavelength increases with decreasing mass, lighter particles tunnel more efficiently than heavier ones. However, there exist examples in condensed-phase chemistry where increasing mass leads to increased tunnelling rates(2). In contrast to the textbook approach, which considers transitions between continuum states, condensed-phase reactions involve transitions between bound states of reactants and products. Here this conceptual distinction is highlighted by experimental measurements of isotopologue-specific tunnelling rates for CO rotational isomerization at an NaCl surface(3,4), showing nonmonotonic mass dependence. A quantum rate theory of isomerization is developed wherein transitions between sub-barrier reactant and product states occur through interaction with the environment. Tunnelling is fastest for specific pairs of states (gateways), the quantum mechanical details of which lead to enhanced cross-barrier coupling; the energies of these gateways arise nonsystematically, giving an erratic mass dependence. Gateways also accelerate ground-state isomerization, acting as leaky holes through the reaction barrier. This simple model provides a way to account for tunnelling in condensed-phase chemistry, and indicates that heavy-atom tunnelling may be more important than typically assumed.
The prevalence of obesity in the pediatric population has become a major public health issue. Indeed, the dramatic increase of this epidemic causes multiple and harmful consequences, Physical activity, particularly physical exercise, remains to be the cornerstone of interventions against childhood obesity. Given the conflicting findings with reference to the relevant literature addressing the effects of exercise on adiposity and physical fitness outcomes in obese children and adolescents, the effect of duration-matched concurrent training (CT) [50% resistance (RT) and 50% high-intensity-interval-training (HIIT)] on body composition and physical fitness in obese youth remains to be elucidated. Thus, the purpose of this study was to examine the effects of 9-weeks of CT compared to RT or HIIT alone, on body composition and selected physical fitness components in healthy sedentary obese youth. Out of 73 participants, only 37; [14 males and 23 females; age 13.4 ± 0.9 years; body-mass-index (BMI): 31.2 ± 4.8 kg·m-2] were eligible and randomized into three groups: HIIT (n = 12): 3-4 sets×12 runs at 80–110% peak velocity, with 10-s passive recovery between bouts; RT (n = 12): 6 exercises; 3–4 sets × 10 repetition maximum (RM) and CT (n = 13): 50% serial completion of RT and HIIT. CT promoted significant greater gains compared to HIIT and RT on body composition (p < 0.01, d = large), 6-min-walking test distance (6 MWT-distance) and on 6 MWT-VO2max (p < 0.03, d = large). In addition, CT showed substantially greater improvements than HIIT in the medicine ball throw test (20.2 vs. 13.6%, p < 0.04, d = large). On the other hand, RT exhibited significantly greater gains in relative hand grip strength (p < 0.03, d = large) and CMJ (p < 0.01, d = large) than HIIT and CT. CT promoted greater benefits for fat, body mass loss and cardiorespiratory fitness than HIIT or RT modalities. This study provides important information for practitioners and therapists on the application of effective exercise regimes with obese youth to induce significant and beneficial body composition changes. The applied CT program and the respective programming parameters in terms of exercise intensity and volume can be used by practitioners as an effective exercise treatment to fight the pandemic overweight and obesity in youth.
Compound inland flood events
(2022)
Several severe flood events hit Germany in recent years, with events in 2013 and 2016 being the most destructive ones, although dynamics and flood processes were very different. While the 2013 event was a slowly rising widespread fluvial flood accompanied by some severe dike breaches, the events in 2016 were fast-onset pluvial floods, which resulted in surface water flooding in some places due to limited capacities of the drainage systems and in destructive flash floods with high sediment loads and clogging in others, particularly in small steep catchments. Hence, different pathways, i.e. different routes that the water takes to reach (and potentially damage) receptors, in our case private households, can be identified in both events. They can thus be regarded as spatially compound flood events or compound inland floods. This paper analyses how differently affected residents coped with these different flood types (fluvial and pluvial) and their impacts while accounting for the different pathways (river flood, dike breach, surface water flooding and flash flood) within the compound events. The analyses are based on two data sets with 1652 (for the 2013 flood) and 601 (for the 2016 flood) affected residents who were surveyed around 9 months after each flood, revealing little socio-economic differences - except for income - between the two samples. The four pathways showed significant differences with regard to their hydraulic and financial impacts, recovery, warning processes, and coping and adaptive behaviour. There are just small differences with regard to perceived self-efficacy and responsibility, offering entry points for tailored risk communication and support to improve property-level adaptation.
Extreme habitats often harbor specific communities that differ substantially from non-extreme habitats. In many cases, these communities are characterized by archaea, bacteria and protists, whereas the number of species of metazoa and higher plants is relatively low. In extremely acidic habitats, mostly prokaryotes and protists thrive, and only very few metazoa thrive, for example, rotifers. Since many studies have investigated the physiology and ecology of individual species, there is still a gap in research on direct, trophic interactions among extremophiles. To fill this gap, we experimentally studied the trophic interactions between a predatory protist (Actinophrys sol, Heliozoa) and its prey, the rotifers Elosa woralli and Cephalodella sp., the ciliate Urosomoida sp. and the mixotrophic protist Chlamydomonas acidophila (a green phytoflagellate, Chlorophyta). We found substantial predation pressure on all animal prey. High densities of Chlamydomonas acidophila reduced the predation impact on the rotifers by interfering with the feeding behaviour of A. sol. These trophic relations represent a natural case of intraguild predation, with Chlamydomonas acidophila being the common prey and the rotifers/ciliate and A. sol being the intraguild prey and predator, respectively. We further studied this intraguild predation along a resource gradient using Cephalodella sp. as the intraguild prey. The interactions among the three species led to an increase in relative rotifer abundance with increasing resource (Chlamydomonas) densities. By applying a series of laboratory experiments, we revealed the complexity of trophic interactions within a natural extremophilic community.
Signaling trough p53is a major cellular stress response mechanism and increases upon nutrient stresses such as starvation. Here, we show in a human hepatoma cell line that starvation leads to robust nuclear p53 stabilization. Using BioID, we determine the cytoplasmic p53 interaction network within the immediate-early starvation response and show that p53 is dissociated from several metabolic enzymes and the kinase PAK2 for which direct binding with the p53 DNA-binding domain was confirmed with NMR studies. Furthermore, proteomics after p53 immunoprecipitation (RIME) uncovered the nuclear interactome under prolonged starvation, where we confirmed the novel p53 interactors SORBS1 (insulin receptor signaling) and UGP2 (glycogen synthesis). Finally, transcriptomics after p53 re-expression revealed a distinct starvation-specific transcriptome response and suggested previously unknown nutrient-dependent p53 target genes. Together, our complementary approaches delineate several nodes of the p53 signaling cascade upon starvation, shedding new light on the mechanisms of p53 as nutrient stress sensor. Given the central role of p53 in cancer biology and the beneficial effects of fasting in cancer treatment, the identified interaction partners and networks could pinpoint novel pharmacologic targets to fine-tune p53 activity.
Recently, glasses, a subset of amorphous solids, have gained attention in various fields, such as polymer chemistry, optical fibers, and pharmaceuticals. One of their characteristic features, the glass transition temperature (T-g) which is absent in 100% crystalline materials, influences several material properties, such as free volume, enthalpy, viscosity, thermodynamic transitions, molecular motions, physical stability, mechanical properties, etc. In addition to T-g, there may be several other temperaturedependent transitions known as sub-T-g transitions (or beta-, gamma-, and delta-relaxations) which are identified by specific analytical techniques. The study of T-g and sub-T-g transitions occurring in amorphous solids has gained much attention because of its importance in understanding molecular kinetics, and it requires the combination of conventional and novel characterization techniques. In the present study, three different analytical techniques [modulated differential scanning calorimetry (mDSC), dynamic mechanical analysis (DMA), and dielectric relaxation spectroscopy (DRS)] were used to perform comprehensive qualitative/quantitative characterization of molecular relaxations, miscibility, and molecular interactions present in an amorphous polymer (PVPVA), a model drug (indomethacin, IND), and IND/PVPVA-based amorphous solid dispersions (ASDs). This is the first ever reported DMA study on PVPVA in its powder form, which avoids the contribution of solvent to the mechanical properties when a selfstanding polymer film is used. A good correlation between the techniques in determining the T-g value of PVPVA, IND, and IND/ PVPVA-based ASDs is established, and the negligible difference (within 10 degrees C) is attributed to the different material properties assessed in each technique. However, the overall T-g behavior, the decrease in T-g with increase in drug loading in ASDs, is universally observed in all the above-mentioned techniques, which reveals their complementarity. DMA and DRS techniques are used to study the different sub-T-g transitions present in PVPVA, amorphous IND, and IND/PVPVA-based ASDs because these transitions are normally too weak or too broad for mDSC to detect. For IND/PVPVA-based ASDs, both techniques show a shift of sub-T-g transitions (or secondary relaxation peaks) toward the high-temperature region from -140 to -45 degrees C. Thus, this paper outlines the usage of different solid-state characterization techniques in understanding the different molecular dynamics present in the polymer, drug, and their interactions in ASDs with the integrated information obtained from individual techniques.
Sporadic E or Es is a transient phenomenon where thin layers of enhanced electron density appear in the ionospheric E region (90-120 km altitude). The neutral wind shear caused by atmospheric tides can lead ions to converge vertically at E-region heights and form the Es layer. This research aims to determine the role of atmospheric solar and lunar tides in Es occurrence. For this purpose, radio occultation data of FORMOSAT-3/COSMIC have been used, which provide complete global coverage of Es events. Moreover, GAIA model simulations have been employed to evaluate the vertical ion convergence induced by solar tides. The results show both migrating and non-migrating solar tidal signatures and the semidiurnal migrating lunar tidal signature mainly in low and mid-latitude Es occurrence. The seasonal variation of the migrating solar tidal components of Es is in good agreement with those in the vertical ion convergence derived from GAIA at higher altitudes. Furthermore, some non-migrating components of solar tides, including semidiurnal westward wavenumbers 1 and 3 and diurnal eastward wavenumbers 2 and 3, also significantly affect the Es occurrence rate.
Video is a widely used medium in teacher training for situating student teachers in classroom scenarios. Although the emerging technology of virtual reality (VR) provides similar, and arguably more powerful, capabilities for immersing teachers in lifelike situations, its benefits and risks relative to video formats have received little attention in the research to date. The current study used a randomized pretest-posttest experimental design to examine the influence of a video- versus VR-based task on changing situational interest and self-efficacy in classroom management. Results from 49 student teachers revealed that the VR simulation led to higher increments in self-reported triggered interest and self-efficacy in classroom management, but also invoked higher extraneous cognitive load than a video viewing task. We discussed the implications of these results for pre-service teacher education and the design of VR environments for professional training purposes. Practitioner notes What is already known about this topic Video is a popular teacher training medium given its ability to display classroom situations. Virtual reality (VR) also immerses users in lifelike situations and has gained popularity in recent years. Situational interest and self-efficacy in classroom management is vital for student teachers' professional development. What this paper adds VR outperforms video in promoting student teachers' triggered interest in classroom management. Student teachers felt more efficacious in classroom management after participating in VR. VR also invoked higher extraneous cognitive load than the video. Implications for practice and/or policy VR provides an authentic teacher training environment for classroom management. The design of the VR training environment needs to ensure a low extraneous cognitive load.
Here I present a comparison between two of the most widely used reduced-complexity models for the representation of sediment transport and deposition processes, namely the transport-limited (or TL) model and the under-capacity (or xi-q) model more recently developed by Davy and Lague (2009). Using both models, I investigate the behavior of a sedimentary continental system of length L fed by a fixed sedimentary flux from a catchment of size A(0) in a nearby active orogen through which sediments transit to a fixed base level representing a large river, a lake or an ocean. This comparison shows that the two models share the same steady-state solution, for which I derive a simple 1D analytical expression that reproduces the major features of such sedimentary systems: a steep fan that connects to a shallower alluvial plain. The resulting fan geometry obeys basic observational constraints on fan size and slope with respect to the upstream drainage area, A(0). The solution is strongly dependent on the size of the system, L, in comparison to a distance L-0, which is determined by the size of A(0), and gives rise to two fundamentally different types of sedimentary systems: a constrained system where L < L-0 and open systems where L > L-0. I derive simple expressions that show the dependence of the system response time on the system characteristics, such as its length, the size of the upstream catchment area, the amplitude of the incoming sedimentary flux and the respective rate parameters (diffusivity or erodibility) for each of the two models. I show that the xi-q model predicts longer response times. I demonstrate that although the manner in which signals propagates through the sedimentary system differs greatly between the two models, they both predict that perturbations that last longer than the response time of the system can be recorded in the stratigraphy of the sedimentary system and in particular of the fan. Interestingly, the xi-q model predicts that all perturbations in the incoming sedimentary flux will be transmitted through the system, whereas the TL model predicts that rapid perturbations cannot. I finally discuss why and under which conditions these differences are important and propose observational ways to determine which of the two models is most appropriate to represent natural systems.
Channel steepness index, k(s), is a metric derived from the stream power model that, under certain conditions, scales with relative rock uplift rate. Channel steepness index is a property of rivers, which can be relatively easily extracted from digital elevation models (DEMs). As DEM data sets are widely available for Earth and are becoming more readily available for other planetary bodies, channel steepness index represents a powerful tool for interpreting tectonic processes. However, multiple approaches to calculate channel steepness index exist. From this several important questions arise; does choice of approach change the values of channel steepness index, can values be so different that choice of approach can influence the findings of a study, and are certain approaches better than others? With the aid of a synthetic river profile and a case study from the Sierra Nevada, California, we show that values of channel steepness index vary over orders of magnitude according to the methodology used in the calculation. We explore the limitations, advantages and disadvantages of the key approaches to calculating channel steepness index, and find that choosing an appropriate approach relies on the context of a study. Given these observations, it is important that authors acknowledge the methodology used to calculate channel steepness index, to ensure that results can be contextualised and reproduced.
Supergenes are nonrecombining genomic regions ensuring the coinheritance of multiple, coadapted genes. Despite the importance of supergenes in adaptation, little is known on how they originate. A classic example of supergene is the S locus controlling heterostyly, a floral heteromorphism occurring in 28 angiosperm families. In Primula, heterostyly is characterized by the cooccurrence of two complementary, self-incompatible floral morphs and is controlled by five genes clustered in the hemizygous, ca. 300-kb S locus. Here, we present the first chromosome-scale genome assembly of any heterostylous species, that of Primula veris (cowslip). By leveraging the high contiguity of the P. veris assembly and comparative genomic analyses, we demonstrated that the S-locus evolved via multiple, asynchronous gene duplications and independent gene translocations. Furthermore, we discovered a new whole-genome duplication in Ericales that is specific to the Primula lineage. We also propose a mechanism for the origin of S-locus hemizygosity via nonhomologous recombination involving the newly discovered two pairs of CFB genes flanking the S locus. Finally, we detected only weak signatures of degeneration in the S locus, as predicted for hemizygous supergenes. The present study provides a useful resource for future research addressing key questions on the evolution of supergenes in general and the S locus in particular: How do supergenes arise? What is the role of genome architecture in the evolution of complex adaptations? Is the molecular architecture of heterostyly supergenes across angiosperms similar to that of Primula?
COMMIT
(2022)
Composition and functions of microbial communities affect important traits in diverse hosts, from crops to humans. Yet, mechanistic understanding of how metabolism of individual microbes is affected by the community composition and metabolite leakage is lacking. Here, we first show that the consensus of automatically generated metabolic reconstructions improves the quality of the draft reconstructions, measured by comparison to reference models. We then devise an approach for gap filling, termed COMMIT, that considers metabolites for secretion based on their permeability and the composition of the community. By applying COMMIT with two soil communities from the Arabidopsis thaliana culture collection, we could significantly reduce the gap-filling solution in comparison to filling gaps in individual reconstructions without affecting the genomic support. Inspection of the metabolic interactions in the soil communities allows us to identify microbes with community roles of helpers and beneficiaries. Therefore, COMMIT offers a versatile fully automated solution for large-scale modelling of microbial communities for diverse biotechnological applications. <br /> Author summaryMicrobial communities are important in ecology, human health, and crop productivity. However, detailed information on the interactions within natural microbial communities is hampered by the community size, lack of detailed information on the biochemistry of single organisms, and the complexity of interactions between community members. Metabolic models are comprised of biochemical reaction networks based on the genome annotation, and can provide mechanistic insights into community functions. Previous analyses of microbial community models have been performed with high-quality reference models or models generated using a single reconstruction pipeline. However, these models do not contain information on the composition of the community that determines the metabolites exchanged between the community members. In addition, the quality of metabolic models is affected by the reconstruction approach used, with direct consequences on the inferred interactions between community members. Here, we use fully automated consensus reconstructions from four approaches to arrive at functional models with improved genomic support while considering the community composition. We applied our pipeline to two soil communities from the Arabidopsis thaliana culture collection, providing only genome sequences. Finally, we show that the obtained models have 90% genomic support and demonstrate that the derived interactions are corroborated by independent computational predictions.
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.
Colloidal metal sulfide nanoparticles for high performance electrochemical energy storage systems
(2022)
Transition metal sulfides have emerged as excellent replacement candidates of traditional insertion electrode materials based on their conversion or alloying mechanisms, facilitating high specific capacity and rate ability. However, parasitic reactions such as massive volume change during the discharge/ charge processes, intermediate polysulfide dissolution, and passivating solid electrolyte interface formation have led to poor cyclability, hindering their feasibility and applicability in energy storage systems. Colloidal metal sulfide nanoparticles, a special class that integrates the intrinsic chemical properties of metal sulfides and their specified structural features, have fairly enlarged their contribution due to the synergistic effect. This review highlights the latest synthetic approaches based on colloidal process. Their corresponding electrochemical outcomes will also be discussed, which are thoroughly updated along with their insight scientific standpoints.
We consider a ring network of theta neurons with non-local homogeneous coupling. We analyse the corresponding continuum evolution equation, analytically describing all possible steady states and their stability. By considering a number of different parameter sets, we determine the typical bifurcation scenarios of the network, and put on a rigorous footing some previously observed numerical results.
We used structural topic modeling to analyze over 800,000 German tweets about COVID-19 to answer the questions: What patterns emerge in tweets as a response to a health crisis? And how do topics discussed change over time? The study leans on the goals associated with the health information seeking (GAINS) model, discerning whether a post aims at tackling and eliminating the problem (i.e., problem-focused) or managing the emotions (i.e., emotion-focused); whether it strives to maximize positive outcomes (promotion focus) or to minimize negative outcomes (prevention focus). The findings indicate four clusters salient in public reactions: 1) “Understanding” (problem-promotion); 2) “Action planning” (problem-prevention); 3) “Hope” (emotion-promotion) and 4) “Reassurance” (emotion-prevention). Public communication is volatile over time, and a shift is evidenced from self-centered to community-centered topics within 4.5 weeks. Our study illustrates social media text mining's potential to quickly and efficiently extract public opinions and reactions. Monitoring fears and trending topics enable policymakers to rapidly respond to deviant behavior, like resistive attitudes toward containment measures or deteriorating physical health. Healthcare workers can use the insights to provide mental health services for battling anxiety or extensive loneliness from staying home.
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.
Fram Strait in the northern North Atlantic is a key region for marine cold air outbreaks (MCAOs), southward discharges of polar air under northerly air flow, which have a strong impact on air-sea heat fluxes, boundary layer processes and severe weather. This study investigates climatologies and decadal trends of Fram Strait MCAOs of different intensity classes based on the ERA5 reanalysis product for 1979-2020. Among striking interannual variability, it is shown that the main MCAO season is December through March, when MCAOs occur around 2/3 of the time. We report on significant decadal MCAO decreases in December and January, and a significant increase in March. While the mid-winter decrease is mainly related to the different paces of warming between the surface and the lower atmosphere, the increase in March can be related to changes in synoptic circulation patterns. As an explanation for the latter, a possible feedback between retreating Barents Sea sea ice, enhanced cyclonic activity and Fram Strait MCAOs is postulated. Exemplifying the trend toward stronger MCAOs during March, the study details the recordbreaking MCAO season in early 2020, and an observational case study of an extreme MCAO event in March 2020 is conducted. Thereby, radiosonde observations are combined with kinematic air back-trajectories to provide rare observational evidence for the diabatic cooling and drying during the MCAO preconditioning phase.
Devolatilization of subducting lithologies liberates COH-fluids. These may become partially sequestered in peridotites in the slab and the overlying forearc mantle, affecting the cycling of volatiles and fluid mobile elements in subduction zones. Here we assess the magnitudes, timescales and mechanism of channelized injection of COH-fluids doped with Ca-aq(2+), Sr-aq(2+) and Ba-aq(2+) into the dry forearc mantle by performing piston cylinder experiments between 1-2.5 GPa and 600-700 degrees C. Cylindrical cores of natural spinel-bearing harzburgites were used as starting materials. Based on mineral assemblage and composition three reaction zones are distinguishable from the rim towards the core of primary olivine and orthopyroxene grains. Zone 1 contains carbonates + quartz +/- kyanite and zone 2 contains carbonates + talc +/- chlorite. Olivine is further replaced in zone 3 by either antigorite+ magnesite or magnesite +talc within or above antigorite stability, respectively. Orthopyroxene is replaced in zone 3 by talc + chlorite. Mineral assemblages and the compositions of secondary minerals depend on fluid composition and the replaced primary silicate. The extent of alteration depends on fluid CO2 content and fluid/rock-ratio, and is further promoted by fluid permeable reaction zones and reaction driven cracking. Our results show that COH-fluid induced metasomatism of the forearc mantle is self-perpetuating and efficient at sequestering Ca-aq(2+), Sr-aq(2+), Ba-aq(2+) and CO2aq into newly formed carbonates. This process is fast with 90% of the available C sequestered and nearly 50% of the initial minerals altered at 650 degrees C, 2 GPa within 55 h. The dissolution of primary silicates under high COH-fluid/rock-ratios, as in channelized fluid flow, enriches SiO2aq in the fluid, while CO2aq is sequestered into carbonates. In an open system, the remaining CO2-depleted, Si-enriched aqueous fluid may cause Si-metasomatism in the forearc further away from the injection of the COH-fluid into peridotite.
Maximizing the efficiency of nanocarrier-mediated co-delivery of genes for co-expression in the same cell is critical for many applications. Strategies to maximize co-delivery of nucleic acids (NA) focused largely on carrier systems, with little attention towards payload composition itself. Here, we investigated the effects of different payload designs: co-delivery of two individual "monocistronic" NAs versus a single bicistronic NA comprising two genes separated by a 2A self-cleavage site. Unexpectedly, co-delivery via the monocistronic design resulted in a higher percentage of co-expressing cells, while predictive co-expression via the bicistronic design remained elusive. Our results will aid the application-dependent selection of the optimal methodology for co-delivery of genes.
The highly structured nature of the educational sector demands effective policy mechanisms close to the needs of the field. That is why evidence-based policy making, endorsed by the European Commission under Erasmus+ Key Action 3, aims to make an alignment between the domains of policy and practice. Against this background, this article addresses two issues: First, that there is a vertical gap in the translation of higher-level policies to local strategies and regulations. Second, that there is a horizontal gap between educational domains regarding the policy awareness of individual players. This was analyzed in quantitative and qualitative studies with domain experts from the fields of virtual mobility and teacher training. From our findings, we argue that the combination of both gaps puts the academic bridge from secondary to tertiary education at risk, including the associated knowledge proficiency levels. We discuss the role of digitalization in the academic bridge by asking the question: which value does the involved stakeholders expect from educational policies? As a theoretical basis, we rely on the model of value co-creation for and by stakeholders. We describe the used instruments along with the obtained results and proposed benefits. Moreover, we reflect on the methodology applied, and we finally derive recommendations for future academic bridge policies.
Anomalous diffusion with a power-law time dependence vertical bar R vertical bar(2)(t) similar or equal to t(alpha i) of the mean squared displacement occurs quite ubiquitously in numerous complex systems. Often, this anomalous diffusion is characterised by crossovers between regimes with different anomalous diffusion exponents alpha(i). Here we consider the case when such a crossover occurs from a first regime with alpha(1) to a second regime with alpha(2) such that alpha(2) > alpha(1), i.e., accelerating anomalous diffusion. A widely used framework to describe such crossovers in a one-dimensional setting is the bi-fractional diffusion equation of the so-called modified type, involving two time-fractional derivatives defined in the Riemann-Liouville sense. We here generalise this bi-fractional diffusion equation to higher dimensions and derive its multidimensional propagator (Green's function) for the general case when also a space fractional derivative is present, taking into consideration long-ranged jumps (Levy flights). We derive the asymptotic behaviours for this propagator in both the short- and long-time as well the short- and long-distance regimes. Finally, we also calculate the mean squared displacement, skewness and kurtosis in all dimensions, demonstrating that in the general case the non-Gaussian shape of the probability density function changes.
Climatic and hydrological variability as a driver of the Lake Gościąż biota during the Younger Dryas
(2022)
The Younger Dryas (YD) is a roughly 1,100-year cold period marking the end of the last glaciation. Climate modelling for northern Europe indicates high summer temperatures and strong continentality. In eastern Europe, the scale of temperature variation and its influence on ecosystems is weakly recognised. Here, we present a multi-proxy reconstruction of YD conditions from Lake Gos ' ciaz (central Poland). The decadal-resolution analysis of its annually varved sediments indicates an initial decrease in Chironomidae-inferred mean July air temperature followed by steady warming. The pollen-inferred winter-to-summer temperature amplitude and annual precip-itation is highest at the Allerod/YD transition and the early YD (ca. 12.7-12.4 ky cal BP) and YD/Holocene (11.7-11.4 ka cal BP) transition. Temperature and precipitation were the main reasons for lake level fluctuations as reflected in the planktonic/littoral Cladocera ratio. The lake's diatom-inferred total phosphorus decreased with increasing summer temperature from about mid YD. Windy conditions in the early YD until ~12.3 ka cal BP caused water mixing and a short-lived/temporary increase in nutrient availability for phytoplankton. The Chironomidae-inferred summer temperature and pollen inferred summer temperature, winter temperature and annual precipitation herein are one of only a few in eastern Europe conducted with such high resolution.
Understanding the influence of climate change and population pressure on human conflict remains a critically important topic in the social sciences. Long-term records that evaluate these dynamics across multiple centuries and outside the range of modern climatic variation are especially capable of elucidating the relative effect of-and the interaction between-climate and demography. This is crucial given that climate change may structure population growth and carrying capacity, while both climate and population influence per capita resource availability. This study couples paleoclimatic and demographic data with osteological evaluations of lethal trauma from 149 directly accelerator mass spectrometry C-14-dated individuals from the Nasca highland region of Peru. Multiple local and supraregional precipitation proxies are combined with a summed probability distribution of 149 C-14 dates to estimate population dynamics during a 700-y study window. Counter to previous findings, our analysis reveals a precipitous increase in violent deaths associated with a period of productive and stable climate, but volatile population dynamics. We conclude that favorable local climate conditions fostered population growth that put pressure on the marginal and highly circumscribed resource base, resulting in violent resource competition that manifested in over 450 y of internecine warfare. These findings help support a general theory of intergroup violence, indicating that relative resource scarcity-whether driven by reduced resource abundance or increased competition-can lead to violence in subsistence societies when the outcome is lower per capita resource availability.
Climate Benefits of Cleaner Energy Transitions in East and South Asia Through Black Carbon Reduction
(2022)
The state of air pollution has historically been tightly linked to how we produce and use energy. Air pollutant emissions over Asia are now changing rapidly due to cleaner energy transitions; however, magnitudes of benefits for climate and air quality remain poorly quantified. The associated risks involve adverse health impacts, reduced agricultural yields, reduced freshwater availability, contributions to climate change, and economic costs. We focus particularly on climate benefits of energy transitions by making first-time use of two decades of high quality observations of atmospheric loading of light-absorbing black carbon (BC) over Kanpur (South Asia) and Beijing (East Asia) and relating these observations to changing energy, emissions, and economic trends in India and China. Our analysis reveals that absorption aerosol optical depth (AAOD) due to BC has decreased substantially, by 40% over Kanpur and 60% over Beijing between 2001 and 2017, and thus became decoupled from regional economic growth. Furthermore, the resultant decrease in BC emissions and BC AAOD over Asia is regionally coherent and occurs primarily due to transitions into cleaner energies (both renewables and fossil fuels) and not due to the decrease in primary energy supply or decrease in use of fossil use and biofuels and waste. Model simulations show that BC aerosols alone contribute about half of the surface temperature change (warming) of the total forcing due to greenhouse gases, natural and internal variability, and aerosols, thus clearly revealing the climate benefits due to a reduction in BC emissions, which would significantly reduce global warming. However, this modeling study excludes responses from natural variability, circulation, and sea ice responses, which cause relatively strong temperature fluctuations that may mask signals from BC aerosols. Our findings show additional benefits for climate (beyond benefits of CO2 reduction) and for several other issues of sustainability over South and East Asia, provide motivation for ongoing cleaner energy production, and consumption transitions, especially when they are associated with reduced emissions of air pollutants. Such an analysis connecting the trends in energy transitions and aerosol absorption loading, unavailable so far, is crucial for simulating the aerosol climate impacts over Asia which is quite uncertain.
The field of movement ecology has seen a rapid increase in high-resolution data in recent years, leading to the development of numerous statistical and numerical methods to analyse relocation trajectories. Data are often collected at the level of the individual and for long periods that may encompass a range of behaviours.
Here, we use the power spectral density (PSD) to characterise the random movement patterns of a black-winged kite (Elanus caeruleus) and a white stork (Ciconia ciconia). The tracks are first segmented and clustered into different behaviours (movement modes), and for each mode we measure the PSD and the ageing properties of the process.
For the foraging kite we find 1/f noise, previously reported in ecological systems mainly in the context of population dynamics, but not for movement data. We further suggest plausible models for each of the behavioural modes by comparing both the measured PSD exponents and the distribution of the single-trajectory PSD to known theoretical results and simulations.
Teachers frequently express stress associated with teaching in large classrooms. Despite the timehonored tradition in teacher stress research of treating class size as a job-related stressor, the underlying premise that class size directly impacts teachers' stress reactions remains untested. In this randomized controlled experiment targeted at preservice teachers, we utilized a standardized virtual reality (VR) classroom to examine whether class size (number of student avatars) directly affected physiological (heart rate) or psychological (subjective rating) stress reactions among 65 preservice teachers. Results from linear mixed-effects modeling (LMM) showed that class size significantly predicted both their physiological and psychological stress reactions in the simulated environment: Average heart rate and subjective stress ratings were both significantly higher in the large class size condition. Further investigations into the causes of this association has been proposed. These findings may contribute to a better understanding of the effects of classroom features on preservice teachers' emotional experiences and well-being.
Numerical magnitude information is assumed to be spatially represented in the form of a mental number line defined with respect to a body-centred, egocentric frame of reference. In this context, spatial language skills such as mastery of verbal descriptions of spatial position (e.g., in front of, behind, to the right/left) have been proposed to be relevant for grasping spatial relations between numerical magnitudes on the mental number line. We examined 4- to 5-year-old’s spatial language skills in tasks that allow responses in egocentric and allocentric frames of reference, as well as their relative understanding of numerical magnitude (assessed by a number word comparison task). In addition, we evaluated influences of children’s absolute understanding of numerical magnitude assessed by their number word comprehension (montring different numbers using their fingers) and of their knowledge on numerical sequences (determining predecessors and successors as well as identifying missing dice patterns of a series). Results indicated that when considering responses that corresponded to the egocentric perspective, children’s spatial language was associated significantly with their relative numerical magnitude understanding, even after controlling for covariates, such as children’s SES, mental rotation skills, and also absolute magnitude understanding or knowledge on numerical sequences. This suggests that the use of egocentric reference frames in spatial language may facilitate spatial representation of numbers along a mental number line and thus seem important for preschoolers’ relative understanding of numerical magnitude.
The process of number symbolization is assumed to be critically influenced by the acquisition of so-called verbal number skills (e.g., verbally reciting the number chain and naming Arabic numerals). For the acquisition of these verbal number skills, verbal and visuospatial skills are discussed as contributing factors. In this context, children’s verbal number skills have been found to be associated with their concurrent spatial language skills such as mastery of verbal descriptions of spatial position (e.g., in front of, behind). In a longitudinal study with three measurement times (T1, T2, T3) at an interval of about 6 months, we evaluated the predictive role of preschool children’s (mean age at T1: 3 years and 10 months) spatial language skills for the acquisition of verbal number skills. Children’s spatial language skills at T2 significantly predicted their verbal number skills at T3, when controlling for influences of important covariates such as vocabulary knowledge. In addition, further analyses replicated previous results indicating that children’s spatial language skills at T2 were associated with their verbal number skills at T2. Exploratory analyses further revealed that children’s verbal number skills at T1 predict their spatial language at T2. Results suggests that better spatial language skills at the age of 4 years facilitate the future acquisition of verbal number skills.
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.
High pressure and high temperature experiments performed with laser-heated diamond anvil cells (LH-DAC) are being extensively used in geosciences to study matter at conditions prevailing in planetary interiors. Due to the size of the apparatus itself, the samples that are produced are extremely small, on the order of few tens of micrometers. There are several ways to analyze the samples and extract physical, chemical or structural information, using either in situ or ex situ methods. In this paper, we compare two nanoprobe techniques, namely nano-XRF and NanoSIMS, that can be used to analyze recovered samples synthetized in a LH-DAC. With these techniques, it is possible to extract the spatial distribution of chemical elements in the samples. We show the results for several standards and discuss the importance of proper calibration for the acquisition of quantifiable results. We used these two nanoprobe techniques to retrieve elemental ratios of dilute species (few tens of ppm) in quenched experimental molten samples relevant for the formation of the iron-rich core of the Earth. We finally discuss the applications of such probes to constrain the partitioning of trace elements between metal and silicate phases, with a focus on moderately siderophile elements, tungsten and molybdenum.
Improving nitrogen (N) status in European water bodies is a pressing issue. N levels depend not only on current but also past N inputs to the landscape, that have accumulated through time in legacy stores (e.g., soil, groundwater).
Catchment-scale N models, that are commonly used to investigate in-stream N levels, rarely examine the magnitude and dynamics of legacy components.
This study aims to gain a better understanding of the long-term fate of the N inputs and its uncertainties, using a legacy-driven N model (ELEMeNT) in Germany's largest national river basin (Weser; 38,450 km(2)) over the period 1960-2015.
We estimate the nine model parameters based on a progressive constraining strategy, to assess the value of different observational data sets.
We demonstrate that beyond in-stream N loading, soil N content and in-stream N concentration allow to reduce the equifinality in model parameterizations.
We find that more than 50% of the N surplus denitrifies (1480-2210 kg ha(-1)) and the stream export amounts to around 18% (410-640 kg ha(-1)), leaving behind as much as around 230-780 kg ha(-1) of N in the (soil) source zone and 10-105 kg ha(-1) in the subsurface.
A sensitivity analysis reveals the importance of different factors affecting the residual uncertainties in simulated N legacies, namely hydrologic travel time, denitrification rates, a coefficient characterizing the protection of organic N in source zone and N surplus input.
Our study calls for proper consideration of uncertainties in N legacy characterization, and discusses possible avenues to further reduce the equifinality in water quality modeling.
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.
The strong chromospheric absorption lines Ca ii H & K are tightly connected to stellar surface magnetic fields. Only for the Sun, spectral activity indices can be related to evolving magnetic features on the solar disk. The Solar Disk-Integrated (SDI) telescope feeds the Potsdam Echelle Polarimetric and Spectroscopic Instrument (PEPSI) of the Large Binocular Telescope (LBT) at Mt. Graham International Observatory, Arizona, U.S.A. We present high-resolution, high-fidelity spectra that were recorded on 184 & 82 days in 2018 & 2019 and derive the Ca ii H & K emission ratio, that is, the S-index. In addition, we compile excess brightness and area indices based on full-disk Ca ii K-line-core filtergrams of the Chromospheric Telescope (ChroTel) at Observatorio del Teide, Tenerife, Spain and full-disk ultraviolet (UV) 1600 angstrom images of the Atmospheric Imaging Assembly (AIA) onboard the Solar Dynamics Observatory (SDO). Thus, Sun-as-a-star spectral indices are related to their counterparts derived from resolved images of the solar chromosphere. All indices display signatures of rotational modulation, even during the very low magnetic activity in the minimum of Solar Cycle 24. Bringing together different types of activity indices has the potential to join disparate chromospheric datasets yielding a comprehensive description of chromospheric activity across many solar cycles.
Characterization of binding interactions of SARS-CoV-2 spike protein and DNA-peptide nanostructures
(2022)
Binding interactions of the spike proteins of the severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) to a peptide fragment derived from the human angiotensin converting enzyme 2 (hACE2) receptor are investigated.
The peptide is employed as capture moiety in enzyme linked immunosorbent assays (ELISA) and quantitative binding interaction measurements that are based on fluorescence proximity sensing (switchSENSE).
In both techniques, the peptide is presented on an oligovalent DNA nanostructure, in order to assess the impact of mono- versus trivalent binding modes.
As the analyte, the spike protein and several of its subunits are tested as well as inactivated SARS-CoV-2 and pseudo viruses. While binding of the peptide to the full-length spike protein can be observed, the subunits RBD and S1 do not exhibit binding in the employed concentrations.
Variations of the amino acid sequence of the recombinant full-length spike proteins furthermore influence binding behavior. The peptide was coupled to DNA nanostructures that form a geometric complement to the trimeric structure of the spike protein binding sites.
An increase in binding strength for trimeric peptide presentation compared to single peptide presentation could be generally observed in ELISA and was quantified in switchSENSE measurements. Binding to inactivated wild type viruses could be shown as well as qualitatively different binding behavior of the Alpha and Beta variants compared to the wild type virus strain in pseudo virus models.
Nanostructured silicon and silicon-aluminum compounds are synthesized by a novel synthesis strategy based on spark plasma sintering (SPS) of silicon nanopowder, mesoporous silicon (pSi), and aluminum nanopowder. The interplay of metal-assisted crystallization and inherent porosity is exploited to largely suppress thermal conductivity. Morphology and temperature-dependent thermal conductivity studies allow us to elucidate the impact of porosity and nanostructure on the macroscopic heat transport. Analytic electron microscopy along with quantitative image analysis is applied to characterize the sample morphology in terms of domain size and interpore distance distributions. We demonstrate that nanostructured domains and high porosity can be maintained in densified mesoporous silicon samples. In contrast, strong grain growth is observed for sintered nanopowders under similar sintering conditions. We observe that aluminum agglomerations induce local grain growth, while aluminum diffusion is observed in porous silicon and dispersed nanoparticles. A detailed analysis of the measured thermal conductivity between 300 and 773 K allows us to distinguish the effect of reduced thermal conductivity caused by porosity from the reduction induced by phonon scattering at nanosized domains. With a modified Landauer/Lundstrom approach the relative thermal conductivity and the scattering length are extracted. The relative thermal conductivity confirms the applicability of Kirkpatrick's effective medium theory. The extracted scattering lengths are in excellent agreement with the harmonic mean of log-normal distributed domain sizes and the interpore distances combined by Matthiessen's rule.
Lithium-ion batteries have revolutionized battery technology. However, the scarcity of lithium in nature is driving the search for alternatives. For that reason, sodium-ion batteries have attracted increasing attention in recent years. The main obstacle to their development is the anode as, unlike for lithium-ion batteries, graphite cannot be used due to the inability to form stoichiometrically useful intercalation compounds with sodium. A promising candidate for sodium storage is hard carbon a form of nongraphitisable carbon, that can be synthesized from various precursor materials. Processing of hard carbons is often done by using mechanochemical treatments. Although it is generally accepted and often observed that they can influence the porosity of hard carbons, their effect on battery performance not well understood. Here, the changes in porosity occurring during ball milling are elucidated and related to the properties of hard carbons in sodium storage. Analysis by combined gas physisorption and small angle X-ray scattering shows that porosity changes during ball milling with a significant increase of the open porosity, unsuitable for reversible sodium storage, and decrease of the closed porosity, suitable for reversible sodium storage. While pristine hard carbon can store 58.5 mAh g(-1) in the closed pores, upon 5 h of mechanical treatment in a ball mill it can only store 35.5 mAh g(-1). The obtained results are furthermore pointing towards the disputed "intercalation-adsorption" mechanism.
INTRODUCTION:
We investigated the impact of changes in lifestyle habits on colorectal cancer (CRC) risk in a multicountry European cohort.
METHODS:
We used baseline and follow-up questionnaire data from the European Prospective Investigation into Cancer cohort to assess changes in lifestyle habits and their associations with CRC development. We calculated a healthy lifestyle index (HLI) score based on smoking status, alcohol consumption, body mass index, and physical activity collected at the 2 time points. HLI ranged from 0 (most unfavorable) to 16 (most favorable). We estimated the association between HLI changes and CRC risk using Cox regression models and reported hazard ratios (HR) with 95% confidence intervals (CI).
RESULTS:
Among 295,865 participants, 2,799 CRC cases were observed over a median of 7.8 years. The median time between questionnaires was 5.7 years. Each unit increase in HLI from the baseline to the follow-up assessment was associated with a statistically significant 3% lower CRC risk. Among participants in the top tertile at baseline (HLI > 11), those in the bottom tertile at follow-up (HLI <= 9) had a higher CRC risk (HR 1.34; 95% CI 1.02-1.75) than those remaining in the top tertile. Among individuals in the bottom tertile at baseline, those in the top tertile at follow-up had a lower risk (HR 0.77; 95% CI 0.59-1.00) than those remaining in the bottom tertile.
DISCUSSION:
Improving adherence to a healthy lifestyle was inversely associated with CRC risk, while worsening adherence was positively associated with CRC risk. These results justify and support recommendations for healthy lifestyle changes and healthy lifestyle maintenance for CRC prevention.
Mathematical modelling and statistical inference provide a framework to evaluate different non-pharmaceutical and pharmaceutical interventions for the control of epidemics that has been widely used during the COVID-19 pandemic. In this paper, lessons learned from this and previous epidemics are used to highlight the challenges for future pandemic control. We consider the availability and use of data, as well as the need for correct parameterisation and calibration for different model frameworks. We discuss challenges that arise in describing and distinguishing between different interventions, within different modelling structures, and allowing both within and between host dynamics. We also highlight challenges in modelling the health economic and political aspects of interventions. Given the diversity of these challenges, a broad variety of interdisciplinary expertise is needed to address them, combining mathematical knowledge with biological and social insights, and including health economics and communication skills. Addressing these challenges for the future requires strong cross disciplinary collaboration together with close communication between scientists and policy makers.
CH2 + O-2
(2022)
The singlet and triplet potential surfaces for the title reaction were investigated using the CBS-QB3 level of theory. The wave functions for some species exhibited multireference character and required the CASPT2/6-31+G(d,p) and CASPT2/aug-cc-pVTZ levels of theory to obtain accurate relative energies. A Natural Bond Orbital Analysis showed that triplet (CH2OO)-C-3 (the simplest Criegee intermediate) and (CH2O2)-C-3 (dioxirane) have mostly polar biradical character, while singlet (CH2OO)-C-1 has some zwitterionic character and a planar structure. Canonical variational transition state theory (CVTST) and master equation simulations were used to analyze the reaction system. CVTST predicts that the rate constant for reaction of (CH2)-C-1 + O-3(2) is more than ten times as fast as the reaction of (CH2)-C-3 ((XB1)-B-3) + O-3(2) and the ratio remains almost independent of temperature from 900 K to 3000 K. The master equation simulations predict that at low pressures the (CH2O)-C-1 + O-3 product set is dominant at all temperatures and the primary yield of OH radicals is negligible below 600 K, due to competition with other primary reactions in this complex system.
Cell-free protein synthesis (CFPS) represents a versatile key technology for the production of toxic proteins. As a cell lysate, rather than viable cells, is used, the toxic effects on the host organism can be circumvented. The open nature of cell-free systems allows for the addition of supplements affecting protein concentration and folding. Here, we present the cell-free synthesis and functional characterization of two AB(5) toxins, namely the cholera toxin (Ctx) and the heat-labile enterotoxin (LT), using two eukaryotic cell-free systems based on Chinese hamster ovary (CHO) and Spodoptera frugiperda (Sf21) cells. Through an iterative optimization procedure, the synthesis of the individual AB(5) toxins was established, and the formation of multimeric structures could be shown by autoradiography. A functional analysis was performed using cell-based assays, thereby demonstrating that the LT complex induced the characteristic cell elongation of target cells after 24 h. The LT complex induced cell death at higher concentrations, starting at an initial concentration of 5 nM. The initial toxic effects of the Ctx multimer could already be detected at 4 nM. The detection and characterization of such AB(5) toxins is of utmost importance, and the monitoring of intracellular trafficking facilitates the further identification of the mechanism of action of these toxins. We showed that the B-subunit of LT (LTB) could be fluorescently labeled using an LTB-Strep fusion protein, which is a proof-of-concept for future Trojan horse applications. Further, we performed a mutational analysis of the CtxA subunit as its template was modified, and an amber stop codon was inserted into CtxA's active site. Subsequently, a non-canonical amino acid was site-specifically incorporated using bio-orthogonal systems. Finally, a fluorescently labeled CtxA protein was produced using copper-catalyzed click reactions as well as a Staudinger ligation. As expected, the modified Ctx multimer no longer induced toxic effects. In our study, we showed that CFPS could be used to study the active centers of toxins by inserting mutations. Additionally, this methodology can be applied for the design of Trojan horses and targeted toxins, as well as enabling the intracellular trafficking of toxins as a prerequisite for the analysis of the toxin's mechanism of action.
The investigation of protein structures, functions and interactions often requires modifications to adapt protein properties to the specific application. Among many possible methods to equip proteins with new chemical groups, the utilization of orthogonal aminoacyl-tRNA synthetase/tRNA pairs enables the site-specific incorporation of non-canonical amino acids at defined positions in the protein. The open nature of cell-free protein synthesis reactions provides an optimal environment, as the orthogonal components do not need to be transported across the cell membrane and the impact on cell viability is negligible. In the present work, it was shown that the expression of orthogonal aminoacyl-tRNA synthetases in CHO cells prior to cell disruption enhanced the modification of the pharmaceutically relevant adenosine A2a receptor. For this purpose, in complement to transient transfection of CHO cells, an approach based on CRISPR/Cas9 technology was selected to generate a translationally active cell lysate harboring endogenous orthogonal aminoacyl-tRNA synthetase.
We study theoretically the quantum dynamics and spectroscopy of rovibrational polaritons formed in a model system composed of a single rovibrating diatomic molecule, which interacts with two degenerate, orthogonally polarized modes of an optical Fabry-Perot cavity. We employ an effective rovibrational Pauli-Fierz Hamiltonian in length gauge representation and identify three-state vibro-polaritonic conical intersections (VPCIs) between singly excited vibro-polaritonic states in a two-dimensional angular coordinate branching space. The lower and upper vibrational polaritons are of mixed light-matter hybrid character, whereas the intermediate state is purely photonic in nature. The VPCIs provide effective population transfer channels between singly excited vibrational polaritons, which manifest in rich interference patterns in rotational densities. Spectroscopically, three bright singly excited states are identified when an external infrared laser field couples to both a molecular and a cavity mode. The non-trivial VPCI topology manifests as pronounced multi-peak progression in the spectral region of the upper vibrational polariton, which is traced back to the emergence of rovibro-polaritonic light-matter hybrid states. Experimentally, ubiquitous spontaneous emission from cavity modes induces a dissipative reduction of intensity and peak broadening, which mainly influences the purely photonic intermediate state peak as well as the rovibro-polaritonic progression. Published under an exclusive license by AIP Publishing.
It has been experimentally demonstrated that reaction rates for molecules embedded in microfluidic optical cavities are altered when compared to rates observed under "ordinary" reaction conditions. However, precise mechanisms of how strong coupling of an optical cavity mode to molecular vibrations affects the reactivity and how resonance behavior emerges are still under dispute. In the present work, we approach these mechanistic issues from the perspective of a thermal model reaction, the inversion of ammonia along the umbrella mode, in the presence of a single-cavity mode of varying frequency and coupling strength. A topological analysis of the related cavity Born-Oppenheimer potential energy surface in combination with quantum mechanical and transition state theory rate calculations reveals two quantum effects, leading to decelerated reaction rates in qualitative agreement with experiments: the stiffening of quantized modes perpendicular to the reaction path at the transition state, which reduces the number of thermally accessible reaction channels, and the broadening of the barrier region, which attenuates tunneling. We find these two effects to be very robust in a fluctuating environment, causing statistical variations of potential parameters, such as the barrier height. Furthermore, by solving the time-dependent Schrodinger equation in the vibrational strong coupling regime, we identify a resonance behavior, in qualitative agreement with experimental and earlier theoretical work. The latter manifests as reduced reaction probability when the cavity frequency omega(c) is tuned resonant to a molecular reactant frequency. We find this effect to be based on the dynamical localization of the vibro-polaritonic wavepacket in the reactant well.
Previous research demonstrated a close bidirectional relationship between spatial attention and the manual motor system. However, it is unclear whether an explicit hand movement is necessary for this relationship to appear. A novel method with high temporal resolution–bimanual grip force registration–sheds light on this issue. Participants held two grip force sensors while being presented with lateralized stimuli (exogenous attentional shifts, Experiment 1), left- or right-pointing central arrows (endogenous attentional shifts, Experiment 2), or the words "left" or "right" (endogenous attentional shifts, Experiment 3). There was an early interaction between the presentation side or arrow direction and grip force: lateralized objects and central arrows led to a larger increase of the ipsilateral force and a smaller increase of the contralateral force. Surprisingly, words led to the opposite pattern: larger force increase in the contralateral hand and smaller force increase in the ipsilateral hand. The effect was stronger and appeared earlier for lateralized objects (60 ms after stimulus presentation) than for arrows (100 ms) or words (250 ms). Thus, processing visuospatial information automatically activates the manual motor system, but the timing and direction of this effect vary depending on the type of stimulus.
Inter-brain synchronization is primarily investigated during social interactions but had not been examined during coupled muscle action between two persons until now. It was previously shown that mechanical muscle oscillations can develop coherent behavior between two isometrically interacting persons. This case study investigated if inter-brain synchronization appears thereby, and if differences of inter- and intrapersonal muscle and brain coherence exist regarding two different types of isometric muscle action. Electroencephalography (EEG) and mechanomyography/mechanotendography (MMG/MTG) of right elbow extensors were recorded during six fatiguing trials of two coupled isometrically interacting participants (70% MVIC). One partner performed holding and one pushing isometric muscle action (HIMA/PIMA; tasks changed). The wavelet coherence of all signals (EEG, MMG/MTG, force, ACC) were analyzed intra- and interpersonally. The five longest coherence patches in 8–15 Hz and their weighted frequency were compared between real vs. random pairs and between HIMA vs. PIMA. Real vs. random pairs showed significantly higher coherence for intra-muscle, intra-brain, and inter-muscle-brain activity (p < 0.001 to 0.019). Inter-brain coherence was significantly higher for real vs. random pairs for EEG of right and central areas and for sub-regions of EEG left (p = 0.002 to 0.025). Interpersonal muscle-brain synchronization was significantly higher than intrapersonal one, whereby it was significantly higher for HIMA vs. PIMA. These preliminary findings indicate that inter-brain synchronization can arise during muscular interaction. It is hypothesized both partners merge into one oscillating neuromuscular system. The results reinforce the hypothesis that HIMA is characterized by more complex control strategies than PIMA. The pilot study suggests investigating the topic further to verify these results on a larger sample size. Findings could contribute to the basic understanding of motor control and is relevant for functional diagnostics such as the manual muscle test which is applied in several disciplines, e.g., neurology, physiotherapy.
Aging is one of the major non-reversible risk factors for several chronic diseases, including cancer, type 2 diabetes, dementia, and cardiovascular diseases (CVD), and it is a key cause of multimorbidity, disability, and frailty (decreased physical activity, fatigue, and weight loss). The underlying cellular mechanisms are complex and consist of multifactorial processes, such as telomere shortening, chronic low-grade inflammation, oxidative stress, mitochondrial dysfunction, accumulation of senescent cells, and reduced autophagy. In this review, we focused on the molecular mechanisms and translational aspects of cardiovascular aging-related inflammation, i.e., inflammaging.
The Arabidopsis knockout mutant lacking both the cytosolic disproportionating enzyme 2 (DPE2) and the plastidial phosphorylase (PHS1) had a dwarf-growth phenotype, a reduced and uneven distribution of starch within the plant rosettes, and a lower starch granule number per chloroplast under standard growth conditions. In contrast, a triple mutant impaired in starch degradation by its additional lack of the glucan, water dikinase (GWD) showed improved plant growth, a starch-excess phenotype, and a homogeneous starch distribution. Furthermore, the number of starch granules per chloroplast was increased and was similar to the wild type. We concluded that ongoing starch degradation is mainly responsible for the observed phenotype of dpe2/phs1. Next, we generated two further triple mutants lacking either the phosphoglucan, water dikinase (PWD), or the disproportionating enzyme 1 (DPE1) in the background of the double mutant. Analysis of the starch metabolism revealed that even minor ongoing starch degradation observed in dpe2/phs1/pwd maintained the double mutant phenotype. In contrast, an additional blockage in the glucose pathway of starch breakdown, as in dpe2/phs1/ dpe1, resulted in a nearly starch-free phenotype and massive chloroplast degradation. The characterized mutants were discussed in the context of starch granule formation.