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MALDI-TOF-MS-based identification of monoclonal murine Anti-SARS-CoV-2 antibodies within one hour
(2022)
During the SARS-CoV-2 pandemic, many virus-binding monoclonal antibodies have been developed for clinical and diagnostic purposes. This underlines the importance of antibodies as universal bioanalytical reagents. However, little attention is given to the reproducibility crisis that scientific studies are still facing to date. In a recent study, not even half of all research antibodies mentioned in publications could be identified at all. This should spark more efforts in the search for practical solutions for the traceability of antibodies. For this purpose, we used 35 monoclonal antibodies against SARS-CoV-2 to demonstrate how sequence-independent antibody identification can be achieved by simple means applied to the protein. First, we examined the intact and light chain masses of the antibodies relative to the reference material NIST-mAb 8671. Already half of the antibodies could be identified based solely on these two parameters. In addition, we developed two complementary peptide mass fingerprinting methods with MALDI-TOF-MS that can be performed in 60 min and had a combined sequence coverage of over 80%. One method is based on the partial acidic hydrolysis of the protein by 5 mM of sulfuric acid at 99 degrees C. Furthermore, we established a fast way for a tryptic digest without an alkylation step. We were able to show that the distinction of clones is possible simply by a brief visual comparison of the mass spectra. In this work, two clones originating from the same immunization gave the same fingerprints. Later, a hybridoma sequencing confirmed the sequence identity of these sister clones. In order to automate the spectral comparison for larger libraries of antibodies, we developed the online software ABID 2.0. This open-source software determines the number of matching peptides in the fingerprint spectra. We propose that publications and other documents critically relying on monoclonal antibodies with unknown amino acid sequences should include at least one antibody fingerprint. By fingerprinting an antibody in question, its identity can be confirmed by comparison with a library spectrum at any time and context.
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?
N-of-1 trials are the gold standard study design to evaluate individual treatment effects and derive personalized treatment strategies. Digital tools have the potential to initiate a new era of N-of-1 trials in terms of scale and scope, but fully functional platforms are not yet available.
Here, we present the open source StudyU platform, which includes the StudyU Designer and StudyU app.
With the StudyU Designer, scientists are given a collaborative web application to digitally specify, publish, and conduct N-of-1 trials.
The StudyU app is a smartphone app with innovative user-centric elements for participants to partake in trials published through the StudyU Designer to assess the effects of different interventions on their health.
Thereby, the StudyU platform allows clinicians and researchers worldwide to easily design and conduct digital N-of-1 trials in a safe manner.
We envision that StudyU can change the landscape of personalized treatments both for patients and healthy individuals, democratize and personalize evidence generation for self-optimization and medicine, and can be integrated in clinical practice.
Complex networks are abundant in nature and many share an important structural property: they contain a few nodes that are abnormally highly connected (hubs). Some of these hubs are called influencers because they couple strongly to the network and play fundamental dynamical and structural roles. Strikingly, despite the abundance of networks with influencers, little is known about their response to stochastic forcing. Here, for oscillatory dynamics on influencer networks, we show that subjecting influencers to an optimal intensity of noise can result in enhanced network synchronization. This new network dynamical effect, which we call coherence resonance in influencer networks, emerges from a synergy between network structure and stochasticity and is highly nonlinear, vanishing when the noise is too weak or too strong. Our results reveal that the influencer backbone can sharply increase the dynamical response in complex systems of coupled oscillators. Influencer networks include a small set of highly-connected nodes and can reach synchrony only via strong node interaction. Tonjes et al. show that introducing an optimal amount of noise enhances synchronization of such networks, which may be relevant for neuroscience or opinion dynamics applications.
Ice-rich permafrost has been subject to abrupt thaw and thermokarst formation in the past and is vulnerable to current global warming. The ice-rich permafrost domain includes Yedoma sediments that have never thawed since deposition during the late Pleistocene and Alas sediments that were formed by previous thermokarst processes during the Lateglacial and Holocene warming. Permafrost thaw unlocks organic carbon (OC) and minerals from these deposits and exposes OC to mineralization. A portion of the OC can be associated with iron (Fe), a redox-sensitive element acting as a trap for OC. Post-depositional thaw processes may have induced changes in redox conditions in these deposits and thereby affected Fe distribution and interactions between OC and Fe, with knock-on effects on the role that Fe plays in mediating present day OC mineralization. To test this hypothesis, we measured Fe concentrations and proportion of Fe oxides and Fe complexed with OC in unthawed Yedoma and previously thawed Alas deposits. Total Fe concentrations were determined on 1,292 sediment samples from the Yedoma domain using portable X-ray fluorescence; these concentrations were corrected for trueness using a calibration based on a subset of 144 samples measured by inductively coupled plasma optical emission spectrometry after alkaline fusion (R (2) = 0.95). The total Fe concentration is stable with depth in Yedoma deposits, but we observe a depletion or accumulation of total Fe in Alas deposits, which experienced previous thaw and/or flooding events. Selective Fe extractions targeting reactive forms of Fe on unthawed and previously thawed deposits highlight that about 25% of the total Fe is present as reactive species, either as crystalline or amorphous oxides, or complexed with OC, with no significant difference in proportions of reactive Fe between Yedoma and Alas deposits. These results suggest that redox driven processes during past thermokarst formation impact the present-day distribution of total Fe, and thereby the total amount of reactive Fe in Alas versus Yedoma deposits. This study highlights that ongoing thermokarst lake formation and drainage dynamics in the Arctic influences reactive Fe distribution and thereby interactions between Fe and OC, OC mineralization rates, and greenhouse gas emissions.
How biased are our models?
(2021)
Geophysical process simulations play a crucial role in the understanding of the subsurface. This understanding is required to provide, for instance, clean energy sources such as geothermal energy. However, the calibration and validation of the physical models heavily rely on state measurements such as temperature. In this work, we demonstrate that focusing analyses purely on measurements introduces a high bias. This is illustrated through global sensitivity studies. The extensive exploration of the parameter space becomes feasible through the construction of suitable surrogate models via the reduced basis method, where the bias is found to result from very unequal data distribution. We propose schemes to compensate for parts of this bias. However, the bias cannot be entirely compensated. Therefore, we demonstrate the consequences of this bias with the example of a model calibration.
Urban air pollution is a substantial threat to human health. Traffic emissions remain a large contributor to air pollution in urban areas. The mobility restrictions put in place in response to the COVID-19 pandemic provided a large-scale real-world experiment that allows for the evaluation of changes in traffic emissions and the corresponding changes in air quality. Here we use observational data, as well as modelling, to analyse changes in nitrogen dioxide, ozone, and particulate matter resulting from the COVID-19 restrictions at the height of the lockdown period in Spring of 2020. Accounting for the influence of meteorology on air quality, we found that reduction of ca. 30-50 % in traffic counts, dominated by changes in passenger cars, corresponded to reductions in median observed nitrogen dioxide concentrations of ca. 40 % (traffic and urban background locations) and a ca. 22 % increase in ozone (urban background locations) during weekdays. Lesser reductions in nitrogen dioxide concentrations were observed at urban background stations at weekends, and no change in ozone was observed. The modelled reductions in median nitrogen dioxide at urban background locations were smaller than the observed reductions and the change was not significant. The model results showed no significant change in ozone on weekdays or weekends. The lack of a simulated weekday/weekend effect is consistent with previous work suggesting that NOx emissions from traffic could be significantly underestimated in European cities by models. These results indicate the potential for improvements in air quality due to policies for reducing traffic, along with the scale of reductions that would be needed to result in meaningful changes in air quality if a transition to sustainable mobility is to be seriously considered. They also confirm once more the highly relevant role of traffic for air quality in urban areas.
Design thinking is a well-established practical and educational approach to fostering high-level creativity and innovation, which has been refined since the 1950s with the participation of experts like Joy Paul Guilford and Abraham Maslow. Through real-world projects, trainees learn to optimize their creative outcomes by developing and practicing creative cognition and metacognition. This paper provides a holistic perspective on creativity, enabling the formulation of a comprehensive theoretical framework of creative metacognition. It focuses on the design thinking approach to creativity and explores the role of metacognition in four areas of creativity expertise: Products, Processes, People, and Places. The analysis includes task-outcome relationships (product metacognition), the monitoring of strategy effectiveness (process metacognition), an understanding of individual or group strengths and weaknesses (people metacognition), and an examination of the mutual impact between environments and creativity (place metacognition). It also reviews measures taken in design thinking education, including a distribution of cognition and metacognition, to support students in their development of creative mastery. On these grounds, we propose extended methods for measuring creative metacognition with the goal of enhancing comprehensive assessments of the phenomenon. Proposed methodological advancements include accuracy sub-scales, experimental tasks where examinees explore problem and solution spaces, combinations of naturalistic observations with capability testing, as well as physiological assessments as indirect measures of creative metacognition.
Case report
(2023)
The increasing prevalence of Long COVID is an imminent public health disaster, and established approaches have not provided adequate diagnostics or treatments. Recently, anesthetic blockade of the stellate ganglion was reported to improve Long COVID symptoms in a small case series, purportedly by "rebooting" the autonomic nervous system. Here, we present a novel diagnostic approach based on the Adaptive Force (AF), and report sustained positive outcome for one severely affected Long COVID patient using individualized pulsed electromagnetic field (PEMF) at the area C7/T1. AF reflects the capacity of the neuromuscular system to adapt adequately to external forces in an isometric holding manner. In case, maximal isometric AF (AFiso(max)) is exceeded, the muscle merges into eccentric muscle action. Thereby, the force usually increases further until maximal AF (AFmax) is reached. In case adaptation is optimal, AFiso(max) is similar to 99-100% of AFmax. This holding capacity (AFiso(max)) was found to be vulnerable to disruption by unpleasant stimulus and, hence, was regarded as functional parameter. AF was assessed by an objectified manual muscle test using a handheld device. Prior to treatment, AFiso(max) was considerably lower than AFmax for hip flexors (62 N = similar to 28% AFmax) and elbow flexors (71 N = similar to 44% AFmax); i.e., maximal holding capacity was significantly reduced, indicating dysfunctional motor control. We tested PEMF at C7/T1, identified a frequency that improved neuromuscular function, and applied it for similar to 15 min. Immediately post-treatment, AFiso(max) increased to similar to 210 N (similar to 100% AFmax) at hip and 184 N (similar to 100% AFmax) at elbow. Subjective Long COVID symptoms resolved the following day. At 4 weeks post-treatment, maximal holding capacity was still on a similarly high level as for immediately post-treatment (similar to 100% AFmax) and patient was symptom-free. At 6 months the patient's Long COVID symptoms have not returned. This case report suggests (1) AF could be a promising diagnostic for post-infectious illness, (2) AF can be used to test effective treatments for post-infectious illness, and (3) individualized PEMF may resolve post-infectious symptoms.
Gender stereotypes influence subjective beliefs about the world, and this is reflected in our use of language. But do gender biases in language transparently reflect subjective beliefs? Or is the process of translating thought to language itself biased? During the 2016 United States (N = 24,863) and 2017 United Kingdom (N = 2,609) electoral campaigns, we compared participants' beliefs about the gender of the next head of government with their use and interpretation of pronouns referring to the next head of government. In the United States, even when the female candidate was expected to win, she pronouns were rarely produced and induced substantial comprehension disruption. In the United Kingdom, where the incumbent female candidate was heavily favored, she pronouns were preferred in production but yielded no comprehension advantage. These and other findings suggest that the language system itself is a source of implicit biases above and beyond previously known biases, such as those measured by the Implicit Association Test.
Cyanobacteria are important primary producers in temperate freshwater ecosystems. However, studies on the seasonal and spatial distribution of cyanobacteria in deep lakes based on high-throughput DNA sequencing are still rare. In this study, we combined monthly water sampling and monitoring in 2019, amplicon sequence variants analysis (ASVs; a proxy for different species) and quantitative PCR targeting overall cyanobacteria abundance to describe the seasonal and spatial dynamics of cyanobacteria in the deep hard-water oligo-mesotrophic Lake Tiefer See, NE Germany. We observed significant seasonal variation in the cyanobacterial community composition (p < 0.05) in the epi- and metalimnion layers, but not in the hypolimnion. In winter-when the water column is mixed-picocyanobacteria (Synechococcus and Cyanobium) were dominant. With the onset of stratification in late spring, we observed potential niche specialization and coexistence among the cyanobacteria taxa driven mainly by light and nutrient dynamics. Specifically, ASVs assigned to picocyanobacteria and the genus Planktothrix were the main contributors to the formation of deep chlorophyll maxima along a light gradient. While Synechococcus and different Cyanobium ASVs were abundant in the epilimnion up to the base of the euphotic zone from spring to fall, Planktothrix mainly occurred in the metalimnetic layer below the euphotic zone where also overall cyanobacteria abundance was highest in summer. Our data revealed two potentially psychrotolerant (cold-adapted) Cyanobium species that appear to cope well under conditions of lower hypolimnetic water temperature and light as well as increasing sediment-released phosphate in the deeper waters in summer. The potential cold-adapted Cyanobium species were also dominant throughout the water column in fall and winter. Furthermore, Snowella and Microcystis-related ASVs were abundant in the water column during the onset of fall turnover. Altogether, these findings suggest previously unascertained and considerable spatiotemporal changes in the community of cyanobacteria on the species level especially within the genus Cyanobium in deep hard-water temperate lakes.
Many animals form aggregations with individuals of the same species (single-species aggregations, SSA). Less frequently, individuals may also aggregate with individuals of other species (mixed-species aggregations, MSA). Although the benefits and costs of SSA have been intensively studied, the same is not true for MSA. Here, we first review the cases of MSA in harvestmen, an arachnid order in which the records of MSA are more frequent than other arthropod orders. We then propose several benefits and costs of MSA in harvestmen, and contrast them with those of SSA. Second, using field-gathered data we describe gregariousness in seven species of Prionostemma harvestmen from Costa Rica. These species form MSA, but individuals are also found solitarily or in SSA. We tested one possible benefit and one possible cost of gregariousness in Prionostemma harvestmen. Regarding the benefit, we hypothesized that individuals missing legs would be more exposed to predation than eight-legged individuals and thus they should be found preferentially in aggregations, where they would be more protected from predators. Our data, however, do not support this hypothesis. Regarding the cost, we hypothesized that gregariousness increases the chances of parasitism. We found no support for this hypothesis either because both mite prevalence and infestation intensity did not differ between solitary or aggregated individuals. Additionally, the type of aggregation (SSA or MSA) was not associated with the benefit or the cost we explored. This lack of effect may be explained by the fluid membership of the aggregations, as we found high turnover over time in the number of individuals and species composition of the aggregations. In conclusion, we hope our review and empirical data stimulate further studies on MSA, which remains one of the most elusive forms of group living in animals.
Surface melting of the Greenland Ice Sheet contributes a large amount to current and future sea level rise. Increased surface melt may lower the reflectivity of the ice sheet surface and thereby increase melt rates: the so-called melt-albedo feedback describes this self-sustaining increase in surface melting. In order to test the effect of the melt-albedo feedback in a prognostic ice sheet model, we implement dEBM-simple, a simplified version of the diurnal Energy Balance Model dEBM, in the Parallel Ice Sheet Model (PISM). The implementation includes a simple representation of the melt-albedo feedback and can thereby replace the positive-degree-day melt scheme. Using PISM-dEBM-simple, we find that this feedback increases ice loss through surface warming by 60 % until 2300 for the high-emission scenario RCP8.5 when compared to a scenario in which the albedo remains constant at its present-day values. With an increase of 90 % compared to a fixed-albedo scenario, the effect is more pronounced for lower surface warming under RCP2.6. Furthermore, assuming an immediate darkening of the ice surface over all summer months, we estimate an upper bound for this effect to be 70 % in the RCP8.5 scenario and a more than 4-fold increase under RCP2.6. With dEBM-simple implemented in PISM, we find that the melt-albedo feedback is an essential contributor to mass loss in dynamic simulations of the Greenland Ice Sheet under future warming.
Knowing the source and runout of debris flows can help in planning strategies aimed at mitigating these hazards. Our research in this paper focuses on developing a novel approach for optimizing runout models for regional susceptibility modelling, with a case study in the upper Maipo River basin in the Andes of Santiago, Chile. We propose a two-stage optimization approach for automatically selecting parameters for estimating runout path and distance. This approach optimizes the random-walk and Perla et al.'s (PCM) two-parameter friction model components of the open-source Gravitational Process Path (GPP) modelling framework. To validate model performance, we assess the spatial transferability of the optimized runout model using spatial crossvalidation, including exploring the model's sensitivity to sample size. We also present diagnostic tools for visualizing uncertainties in parameter selection and model performance. Although there was considerable variation in optimal parameters for individual events, we found our runout modelling approach performed well at regional prediction of potential runout areas. We also found that although a relatively small sample size was sufficient to achieve generally good runout modelling performance, larger samples sizes (i.e. >= 80) had higher model performance and lower uncertainties for estimating runout distances at unknown locations. We anticipate that this automated approach using the open-source R software and the System for Automated Geoscientific Analyses geographic information system (SAGA-GIS) will make process-based debris-flow models more readily accessible and thus enable researchers and spatial planners to improve regional-scale hazard assessments.
In his essay, Mel Ainscow looks at inclusion and equity from an international perspective and makes suggestions on how to develop inclusive education in a ‘whole-system approach’. After discussing different conceptions of inclusion and equity, he describes international policies which address them. From this international macro-level, Ainscow zooms in to the meso-level of the school and its immediate environment, defining dimensions to be considered for an inclusive school development. One of these dimensions is the ‘use of evidence’. In my comment, I want to focus on this dimension and discuss its scope and the potential to apply it in inclusive education development. As a first and important precondition, Ainscow explains that different circumstances lead to different linguistic uses of the term ‘inclusive education’. Thus, the term ‘inclusive education’ does not refer to an identical set of objectives across countries, and neither does the term ‘equity’.
Rats are a reservoir of human- and livestock-associated methicillin-resistant Staphylococcus aureus (MRSA). However, the composition of the natural S. aureus population in wild and laboratory rats is largely unknown. Here, 144 nasal S. aureus isolates from free-living wild rats, captive wild rats and laboratory rats were genotyped and profiled for antibiotic resistances and human-specific virulence genes. The nasal S. aureus carriage rate was higher among wild rats (23.4%) than laboratory rats (12.3%). Free-living wild rats were primarily colonized with isolates of clonal complex (CC) 49 and CC130 and maintained these strains even in husbandry. Moreover, upon livestock contact, CC398 isolates were acquired. In contrast, laboratory rats were colonized with many different S. aureus lineages—many of which are commonly found in humans. Five captive wild rats were colonized with CC398-MRSA. Moreover, a single CC30-MRSA and two CC130-MRSA were detected in free-living or captive wild rats. Rat-derived S. aureus isolates rarely harbored the phage-carried immune evasion gene cluster or superantigen genes, suggesting long-term adaptation to their host. Taken together, our study revealed a natural S. aureus population in wild rats, as well as a colonization pressure on wild and laboratory rats by exposure to livestock- and human-associated S. aureus, respectively.
Strong hydroclimatic controls on vulnerability to subsurface nitrate contamination across Europe
(2020)
Subsurface contamination due to excessive nutrient surpluses is a persistent and widespread problem in agricultural areas across Europe. The vulnerability of a particular location to pollution from reactive solutes, such as nitrate, is determined by the interplay between hydrologic transport and biogeochemical transformations. Current studies on the controls of subsurface vulnerability do not consider the transient behaviour of transport dynamics in the root zone. Here, using state-of-the-art hydrologic simulations driven by observed hydroclimatic forcing, we demonstrate the strong spatiotemporal heterogeneity of hydrologic transport dynamics and reveal that these dynamics are primarily controlled by the hydroclimatic gradient of the aridity index across Europe. Contrasting the space-time dynamics of transport times with reactive timescales of denitrification in soil indicate that similar to 75% of the cultivated areas across Europe are potentially vulnerable to nitrate leaching for at least onethird of the year. We find that neglecting the transient nature of transport and reaction timescale results in a great underestimation of the extent of vulnerable regions by almost 50%. Therefore, future vulnerability and risk assessment studies must account for the transient behaviour of transport and biogeochemical transformation processes.
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.
We present a chronology framework named LegacyAge 1.0 containing harmonized chronologies for 2831 pollen records (downloaded from the Neotoma Paleoecology Database and the supplementary Asian datasets) together with their age control points and metadata in machine-readable data formats.
All chronologies use the Bayesian framework implemented in Bacon version 2.5.3. Optimal parameter settings of priors (accumulation.shape, memory.strength, memory.mean, accumulation.rate, and thickness) were identified based on information in the original publication or iteratively after preliminary model inspection.
The most common control points for the chronologies are radiocarbon dates (86.1 %), calibrated by the latest calibration curves (IntCal20 and SHCal20 for the terrestrial radiocarbon dates in the Northern Hemisphere and Southern Hemisphere and Marine20 for marine materials).
The original publications were consulted when dealing with outliers and inconsistencies. Several major challenges when setting up the chronologies included the waterline issue (18.8% of records), reservoir effect (4.9 %), and sediment deposition discontinuity (4.4 %).
Finally, we numerically compare the LegacyAge 1.0 chronologies to those published in the original publications and show that the reliability of the chronologies of 95.4% of records could be improved according to our assessment.
Our chronology framework and revised chronologies provide the opportunity to make use of the ages and age uncertainties in synthesis studies of, for example, pollen-based vegetation and climate change.
The LegacyAge 1.0 dataset, including metadata, datings, harmonized chronologies, and R code used, is openaccess and available at PANGAEA (https://doi.org/10.1594/PANGAEA.933132; Li et al., 2021) and Zenodo (https://doi.org/10.5281/zenodo.5815192; Li et al., 2022), respectively.
Predicting the electron population of Earth's ring current during geomagnetic storms still remains a challenging task.
In this work, we investigate the sensitivity of 10 keV ring current electrons to different driving processes, parameterised by the Kp index, during several moderate and intense storms.
Results are validated against measurements from the Van Allen Probes satellites. Perturbing the Kp index allows us to identify the most dominant processes for moderate and intense storms respectively.
We find that during moderate storms (Kp < 6) the drift velocities mostly control the behaviour of low energy electrons, while loss from wave-particle interactions is the most critical parameter for quantifying the evolution of intense storms (Kp > 6). Perturbations of the Kp index used to drive the boundary conditions at GEO and set the plasmapause location only show a minimal effect on simulation results over a limited L range.
It is further shown that the flux at L & SIM; 3 is more sensitive to changes in the Kp index compared to higher L shells, making it a good proxy for validating the source-loss balance of a ring current model.
Drought and the availability of mineable phosphorus minerals used for fertilization are two of the important issues agriculture is facing in the future. High phosphorus availability in soils is necessary to maintain high agricultural yields. Drought is one of the major threats for terrestrial ecosystem performance and crop production in future. Among the measures proposed to cope with the upcoming challenges of intensifying drought stress and to decrease the need for phosphorus fertilizer application is the fertilization with silica (Si). Here we tested the importance of soil Si fertilization on wheat phosphorus concentration as well as wheat performance during drought at the field scale. Our data clearly showed a higher soil moisture for the Si fertilized plots. This higher soil moisture contributes to a better plant performance in terms of higher photosynthetic activity and later senescence as well as faster stomata responses ensuring higher productivity during drought periods. The plant phosphorus concentration was also higher in Si fertilized compared to control plots. Overall, Si fertilization or management of the soil Si pools seem to be a promising tool to maintain crop production under predicted longer and more serve droughts in the future and reduces phosphorus fertilizer requirements.
Identification of protein complexes from protein-protein interaction (PPI) networks is a key problem in PPI mining, solved by parameter-dependent approaches that suffer from small recall rates. Here we introduce GCC-v, a family of efficient, parameter-free algorithms to accurately predict protein complexes using the (weighted) clustering coefficient of proteins in PPI networks. Through comparative analyses with gold standards and PPI networks from Escherichia coli, Saccharomyces cerevisiae, and Homo sapiens, we demonstrate that GCC-v outperforms twelve state-of-the-art approaches for identification of protein complexes with respect to twelve performance measures in at least 85.71% of scenarios. We also show that GCC-v results in the exact recovery of similar to 35% of protein complexes in a pan-plant PPI network and discover 144 new protein complexes in Arabidopsis thaliana, with high support from GO semantic similarity. Our results indicate that findings from GCC-v are robust to network perturbations, which has direct implications to assess the impact of the PPI network quality on the predicted protein complexes. (C) 2021 The Author(s). Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology.
Deliberative and paternalistic interaction styles for conversational agents in digital health
(2021)
Background:
Recent years have witnessed a constant increase in the number of people with chronic conditions requiring ongoing medical support in their everyday lives. However, global health systems are not adequately equipped for this extraordinarily time-consuming and cost-intensive development. Here, conversational agents (CAs) can offer easily scalable and ubiquitous support. Moreover, different aspects of CAs have not yet been sufficiently investigated to fully exploit their potential. One such trait is the interaction style between patients and CAs. In human-to-human settings, the interaction style is an imperative part of the interaction between patients and physicians. Patient-physician interaction is recognized as a critical success factor for patient satisfaction, treatment adherence, and subsequent treatment outcomes. However, so far, it remains effectively unknown how different interaction styles can be implemented into CA interactions and whether these styles are recognizable by users.
Objective:
The objective of this study was to develop an approach to reproducibly induce 2 specific interaction styles into CA-patient dialogs and subsequently test and validate them in a chronic health care context.
Methods:
On the basis of the Roter Interaction Analysis System and iterative evaluations by scientific experts and medical health care professionals, we identified 10 communication components that characterize the 2 developed interaction styles: deliberative and paternalistic interaction styles. These communication components were used to develop 2 CA variations, each representing one of the 2 interaction styles. We assessed them in a web-based between-subject experiment. The participants were asked to put themselves in the position of a patient with chronic obstructive pulmonary disease. These participants were randomly assigned to interact with one of the 2 CAs and subsequently asked to identify the respective interaction style. Chi-square test was used to assess the correct identification of the CA-patient interaction style.
Results:
A total of 88 individuals (42/88, 48% female; mean age 31.5 years, SD 10.1 years) fulfilled the inclusion criteria and participated in the web-based experiment. The participants in both the paternalistic and deliberative conditions correctly identified the underlying interaction styles of the CAs in more than 80% of the assessments (X-1(,8)8(2)=38.2; P<.001; phi coefficient r(phi)=0.68). The validation of the procedure was hence successful.
Conclusions:
We developed an approach that is tailored for a medical context to induce a paternalistic and deliberative interaction style into a written interaction between a patient and a CA. We successfully tested and validated the procedure in a web-based experiment involving 88 participants. Future research should implement and test this approach among actual patients with chronic diseases and compare the results in different medical conditions. This approach can further be used as a starting point to develop dynamic CAs that adapt their interaction styles to their users.
Pathogens and animal pests (P&A) are a major threat to global food security as they directly affect the quantity and quality of food. The Southern Amazon, Brazil's largest domestic region for soybean, maize and cotton production, is particularly vulnerable to the outbreak of P&A due to its (sub)tropical climate and intensive farming systems. However, little is known about the spatial distribution of P&A and the related yield losses. Machine learning approaches for the automated recognition of plant diseases can help to overcome this research gap. The main objectives of this study are to (1) evaluate the performance of Convolutional Neural Networks (ConvNets) in classifying P&A, (2) map the spatial distribution of P&A in the Southern Amazon, and (3) quantify perceived yield and economic losses for the main soybean and maize P&A. The objectives were addressed by making use of data collected with the smartphone application Plantix. The core of the app's functioning is the automated recognition of plant diseases via ConvNets. Data on expected yield losses were gathered through a short survey included in an "expert" version of the application, which was distributed among agronomists. Between 2016 and 2020, Plantix users collected approximately 78,000 georeferenced P&A images in the Southern Amazon. The study results indicate a high performance of the trained ConvNets in classifying 420 different crop-disease combinations. Spatial distribution maps and expert-based yield loss estimates indicate that maize rust, bacterial stalk rot and the fall armyworm are among the most severe maize P&A, whereas soybean is mainly affected by P&A like anthracnose, downy mildew, frogeye leaf spot, stink bugs and brown spot. Perceived soybean and maize yield losses amount to 12 and 16%, respectively, resulting in annual yield losses of approximately 3.75 million tonnes for each crop and economic losses of US$2 billion for both crops together. The high level of accuracy of the trained ConvNets, when paired with widespread use from following a citizen-science approach, results in a data source that will shed new light on yield loss estimates, e.g., for the analysis of yield gaps and the development of measures to minimise them.
Water bodies are a highly abundant feature of Arctic permafrost ecosystems and strongly influence their hydrology, ecology and biogeochemical cycling. While very high resolution satellite images enable detailed mapping of these water bodies, the increasing availability and abundance of this imagery calls for fast, reliable and automatized monitoring. This technical work presents a largely automated and scalable workflow that removes image noise, detects water bodies, removes potential misclassifications from infrastructural features, derives lake shoreline geometries and retrieves their movement rate and direction on the basis of ortho-ready very high resolution satellite imagery from Arctic permafrost lowlands. We applied this workflow to typical Arctic lake areas on the Alaska North Slope and achieved a successful and fast detection of water bodies. We derived representative values for shoreline movement rates ranging from 0.40-0.56 m yr(-1) for lake sizes of 0.10 ha-23.04 ha. The approach also gives an insight into seasonal water level changes. Based on an extensive quantification of error sources, we discuss how the results of the automated workflow can be further enhanced by incorporating additional information on weather conditions and image metadata and by improving the input database. The workflow is suitable for the seasonal to annual monitoring of lake changes on a sub-meter scale in the study areas in northern Alaska and can readily be scaled for application across larger regions within certain accuracy limitations.
The subsurface is a temporally dynamic and spatially heterogeneous compartment of the Earth's critical zone, and biogeochemical transformations taking place in this compartment are crucial for the cycling of nutrients.
The impact of spatial heterogeneity on such microbially mediated nutrient cycling is not well known, which imposes a severe challenge in the prediction of in situ biogeochemical transformation rates and further of nutrient loading contributed by the groundwater to the surface water bodies.
Therefore, we used a numerical modelling approach to evaluate the sensitivity of groundwater microbial biomass distribution and nutrient cycling to spatial heterogeneity in different scenarios accounting for various residence times.
The model results gave us an insight into domain characteristics with respect to the presence of oxic niches in predominantly anoxic zones and vice versa depending on the extent of spatial heterogeneity and the flow regime.
The obtained results show that microbial abundance, distribution, and activity are sensitive to the applied flow regime and that the mobile (i.e. observable by groundwater sampling) fraction of microbial biomass is a varying, yet only a small, fraction of the total biomass in a domain. Furthermore, spatial heterogeneity resulted in anaerobic niches in the domain and shifts in microbial biomass between active and inactive states. The lack of consideration of spatial heterogeneity, thus, can result in inaccurate estimation of microbial activity. In most cases this leads to an overestimation of nutrient removal (up to twice the actual amount) along a flow path.
We conclude that the governing factors for evaluating this are the residence time of solutes and the Damkohler number (Da) of the biogeochemical reactions in the domain. We propose a relationship to scale the impact of spatial heterogeneity on nutrient removal governed by the logioDa.
This relationship may be applied in upscaled descriptions of microbially mediated nutrient cycling dynamics in the subsurface thereby resulting in more accurate predictions of, for example, carbon and nitrogen cycling in groundwater over long periods at the catchment scale.
Changing climatic conditions and unsustainable land use are major threats to savannas worldwide. Historically, many African savannas were used intensively for livestock grazing, which contributed to widespread patterns of bush encroachment across savanna systems. To reverse bush encroachment, it has been proposed to change the cattle-dominated land use to one dominated by comparatively specialized browsers and usually native herbivores. However, the consequences for ecosystem properties and processes remain largely unclear. We used the ecohydrological, spatially explicit model EcoHyD to assess the impacts of two contrasting, herbivore land-use strategies on a Namibian savanna: grazer- versus browser-dominated herbivore communities. We varied the densities of grazers and browsers and determined the resulting composition and diversity of the plant community, total vegetation cover, soil moisture, and water use by plants. Our results showed that plant types that are less palatable to herbivores were best adapted to grazing or browsing animals in all simulated densities. Also, plant types that had a competitive advantage under limited water availability were among the dominant ones irrespective of land-use scenario. Overall, the results were in line with our expectations: under high grazer densities, we found heavy bush encroachment and the loss of the perennial grass matrix. Importantly, regardless of the density of browsers, grass cover and plant functional diversity were significantly higher in browsing scenarios. Browsing herbivores increased grass cover, and the higher total cover in turn improved water uptake by plants overall. We concluded that, in contrast to grazing-dominated land-use strategies, land-use strategies dominated by browsing herbivores, even at high herbivore densities, sustain diverse vegetation communities with high cover of perennial grasses, resulting in lower erosion risk and bolstering ecosystem services.
The investigation of metabolic fluxes and metabolite distributions within cells by means of tracer molecules is a valuable tool to unravel the complexity of biological systems. Technological advances in mass spectrometry (MS) technology such as atmospheric pressure chemical ionization (APCI) coupled with high resolution (HR), not only allows for highly sensitive analyses but also broadens the usefulness of tracer-based experiments, as interesting signals can be annotated de novo when not yet present in a compound library. However, several effects in the APCI ion source, i.e., fragmentation and rearrangement, lead to superimposed mass isotopologue distributions (MID) within the mass spectra, which need to be corrected during data evaluation as they will impair enrichment calculation otherwise. Here, we present and evaluate a novel software tool to automatically perform such corrections. We discuss the different effects, explain the implemented algorithm, and show its application on several experimental datasets. This adjustable tool is available as an R package from CRAN.
Studies have evaluated the effectiveness of dual career (DC) support services among student-athletes by examining scholastic performances.
These studies investigated self-reported grades student-athletes or focused on career choices student-athletes made after leaving school. Most of these studies examined scholastic performances cross-sectionally among lower secondary school student-athletes or student-athletes in higher education.
The present longitudinal field study in a quasi-experimental design aims to evaluate the development of scholastic performances among upper secondary school students aged 16-19 by using standardized scholastic assessments and grade points in the subject English over a course of 3-4 years.
A sample of 159 students (54.4% females) at three German Elite Sport Schools (ESS) and three comprehensive schools participated in the study. The sample was split into six groups according to three criteria: (1) students' athletic engagement, (2) school type attendance, and (3) usage of DC support services in secondary school.
Repeated-measurement analyses of variance were conducted in order to evaluate the impact of the three previously mentioned criteria as well as their interaction on the development of scholastic performances.
Findings indicated that the development of English performance levels differ among the six groups.
Current attempts to prevent and manage type 2 diabetes have been moderately effective, and a better understanding of the molecular roots of this complex disease is important to develop more successful and precise treatment options.
Recently, we initiated the collective diabetes cross, where four mouse inbred strains differing in their diabetes susceptibility were crossed with the obese and diabetes-prone NZO strain and identified the quantitative trait loci (QTL) Nidd13/NZO, a genomic region on chromosome 13 that correlates with hyperglycemia in NZO allele carriers compared to B6 controls.
Subsequent analysis of the critical region, harboring 644 genes, included expression studies in pancreatic islets of congenic Nidd13/NZO mice, integration of single-cell data from parental NZO and B6 islets as well as haplotype analysis.
Finally, of the five genes (Acot12, S100z, Ankrd55, Rnf180, and Iqgap2) within the polymorphic haplotype block that are differently expressed in islets of B6 compared to NZO mice, we identified the calcium-binding protein S100z gene to affect islet cell proliferation as well as apoptosis when overexpressed in MINE cells. In summary, we define S100z as the most striking gene to be causal for the diabetes QTL Nidd13/NZO by affecting beta-cell proliferation and apoptosis. Thus, S100z is an entirely novel diabetes gene regulating islet cell function.
Model uncertainty quantification is an essential component of effective data assimilation. Model errors associated with sub-grid scale processes are often represented through stochastic parameterizations of the unresolved process. Many existing Stochastic Parameterization schemes are only applicable when knowledge of the true sub-grid scale process or full observations of the coarse scale process are available, which is typically not the case in real applications. We present a methodology for estimating the statistics of sub-grid scale processes for the more realistic case that only partial observations of the coarse scale process are available. Model error realizations are estimated over a training period by minimizing their conditional sum of squared deviations given some informative covariates (e.g., state of the system), constrained by available observations and assuming that the observation errors are smaller than the model errors. From these realizations a conditional probability distribution of additive model errors given these covariates is obtained, allowing for complex non-Gaussian error structures. Random draws from this density are then used in actual ensemble data assimilation experiments. We demonstrate the efficacy of the approach through numerical experiments with the multi-scale Lorenz 96 system using both small and large time scale separations between slow (coarse scale) and fast (fine scale) variables. The resulting error estimates and forecasts obtained with this new method are superior to those from two existing methods.
El artículo analiza la corrupción como un fenómeno complejo y con frecuencia ambiguo, relacionado con comportamientos y mentalidades individuales y colectivas, que son percibidos como ilegítimos o inmorales y, por lo tanto, desviados de normas establecidas. Más allá de un acercamiento reduccionista u objetivista a lugares comunes de la corrupción política, o a delitos tipificados por la ley, esta contribución pretende destacar la relevancia del análisis histórico del discurso en el estudio del tema. Este enfoque nos permite reconstruir contextos en los que se identifica la corrupción, así como analizar relatos, no siempre unánimes, sobre estas prácticas. El trabajo se adentra en una época lejana, pero a la vez cercana a nuestro tiempo, el último siglo la República romana. La evidencia nos permite evaluar críticamente aspectos fundamentales de la construcción retórica de la corrupción y de sus zonas grises, como la distinción, a menudo borrosa, entre regalo y soborno.
Who has the future in mind?
(2022)
An individual's relation to time may be an important driver of pro-environmental behaviour. We studied whether young individual's gender and time-orientation are associated with pro-environmental behaviour. In a controlled laboratory environment with students in Germany, participants earned money by performing a real-effort task and were then offered the opportunity to invest their money into an environmental project that supports climate protection. Afterwards, we controlled for their time-orientation. In this consequential behavioural setting, we find that males who scored higher on future-negative orientation showed significantly more pro-environmental behaviour compared to females who scored higher on future-negative orientation and males who scored lower on future-negative orientation. Interestingly, our results are completely reversed when it comes to past-positive orientation. These findings have practical implications regarding the most appropriate way to address individuals in order to achieve more pro-environmental behaviour.
Shape-memory hydrogels (SMH) are multifunctional, actively-moving polymers of interest in biomedicine. In loosely crosslinked polymer networks, gelatin chains may form triple helices, which can act as temporary net points in SMH, depending on the presence of salts. Here, we show programming and initiation of the shape-memory effect of such networks based on a thermomechanical process compatible with the physiological environment. The SMH were synthesized by reaction of glycidylmethacrylated gelatin with oligo(ethylene glycol) (OEG) alpha,omega-dithiols of varying crosslinker length and amount. Triple helicalization of gelatin chains is shown directly by wide-angle X-ray scattering and indirectly via the mechanical behavior at different temperatures. The ability to form triple helices increased with the molar mass of the crosslinker. Hydrogels had storage moduli of 0.27-23 kPa and Young's moduli of 215-360 kPa at 4 degrees C. The hydrogels were hydrolytically degradable, with full degradation to water-soluble products within one week at 37 degrees C and pH = 7.4. A thermally-induced shape-memory effect is demonstrated in bending as well as in compression tests, in which shape recovery with excellent shape-recovery rates R-r close to 100% were observed. In the future, the material presented here could be applied, e.g., as self-anchoring devices mechanically resembling the extracellular matrix.
Starting from the observation that the reduced state of a system strongly coupled to a bath is, in general, an athermal state, we introduce and study a cyclic battery-charger quantum device that is in thermal equilibrium, or in a ground state, during the charge storing stage. The cycle has four stages: the equilibrium storage stage is interrupted by disconnecting the battery from the charger, then work is extracted from the battery, and then the battery is reconnected with the charger; finally, the system is brought back to equilibrium. At no point during the cycle are the battery-charger correlations artificially erased. We study the case where the battery and charger together comprise a spin-1/2 Ising chain, and show that the main characteristics-the extracted energy and the thermodynamic efficiency-can be enhanced by operating the cycle close to the quantum phase transition point. When the battery is just a single spin, we find that the output work and efficiency show a scaling behavior at criticality and derive the corresponding critical exponents. Due to always present correlations between the battery and the charger, operations that are equivalent from the perspective of the battery can entail different energetic costs for switching the battery-charger coupling. This happens only when the coupling term does not commute with the battery's bare Hamiltonian, and we use this purely quantum leverage to further optimize the performance of the device.
Charitable giving
(2023)
We investigate how different levels of information influence the allocation decisions of donors who are entitled to freely distribute a fixed monetary endowment between themselves and a charitable organization in both giving and taking frames. Participants donate significantly higher amounts, when the decision is described as taking rather than giving. This framing effect becomes smaller if more information about the charity is provided.
Scaling agriculture to the globally rising population demands new approaches for future crop production such as multilayer and multitrophic indoor farming. Moreover, there is a current trend towards sustainable local solutions for aquaculture and saline agriculture. In this context, halophytes are becoming increasingly important for research and the food industry. As Salicornia europaea is a highly salt-tolerant obligate halophyte that can be used as a food crop, indoor cultivation with saline water is of particular interest. Therefore, finding a sustainable alternative to the use of seawater in non-coastal regions is crucial. Our goal was to determine whether natural brines, which are widely distributed and often available in inland areas, provide an alternative water source for the cultivation of saline organisms. This case study investigated the potential use of natural brines for the production of S. europaea. In the control group, which reflects the optimal growth conditions, fresh weight was increased, but there was no significant difference between the treatment groups comparing natural brines with artificial sea water. A similar pattern was observed for carotenoids and chlorophylls. Individual components showed significant differences. However, within treatments, there were mostly no changes. In summary, we showed that the influence of the different chloride concentrations was higher than the salt composition. Moreover, nutrient-enriched natural brine was demonstrated to be a suitable alternative for cultivation of S. europaea in terms of yield and nutritional quality. Thus, the present study provides the first evidence for the future potential of natural brine waters for the further development of aquaculture systems and saline agriculture in inland regions.
Sarcopenic obesity is increasingly found in youth, but its health consequences remain unclear.
Therefore, we studied the prevalence of sarcopenia and its association with cardiometabolic risk factors as well as muscular and cardiorespiratory fitness using data from the German Children's Health InterventionaL Trial (CHILT III) programme.
In addition to anthropometric data and blood pressure, muscle and fat mass were determined with bioelectrical impedance analysis.
Sarcopenia was classified via muscle-to-fat ratio. A fasting blood sample was taken, muscular fitness was determined using the standing long jump, and cardiorespiratory fitness was determined using bicycle ergometry. Of the 119 obese participants included in the analysis (47.1% female, mean age 12.2 years), 83 (69.7%) had sarcopenia. Affected individuals had higher gamma-glutamyl transferase, higher glutamate pyruvate transaminase, higher high-sensitivity C-reactive protein, higher diastolic blood pressure, and lower muscular and cardiorespiratory fitness (each p < 0.05) compared to participants who were 'only' obese.
No differences were found in other parameters. In our study, sarcopenic obesity was associated with various disorders in children and adolescents.
However, the clinical value must be tested with larger samples and reference populations to develop a unique definition and appropriate methods in terms of identification but also related preventive or therapeutic approaches.
As the complexity of learning task requirements, computer infrastruc- tures and knowledge acquisition for artificial neuronal networks (ANN) is in- creasing, it is challenging to talk about ANN without creating misunderstandings. An efficient, transparent and failure-free design of learning tasks by models is not supported by any tool at all. For this purpose, particular the consideration of data, information and knowledge on the base of an integration with knowledge- intensive business process models and a process-oriented knowledge manage- ment are attractive. With the aim of making the design of learning tasks express- ible by models, this paper proposes a graphical modeling language called Neu- ronal Training Modeling Language (NTML), which allows the repetitive use of learning designs. An example ANN project of AI-based dynamic GUI adaptation exemplifies its use as a first demonstration.
In the present paper we empirically investigate the psychometric properties of some of the most famous statistical and logical cognitive illusions from the "heuristics and biases" research program by Daniel Kahneman and Amos Tversky, who nearly 50 years ago introduced fascinating brain teasers such as the famous Linda problem, the Wason card selection task, and so-called Bayesian reasoning problems (e.g., the mammography task). In the meantime, a great number of articles has been published that empirically examine single cognitive illusions, theoretically explaining people's faulty thinking, or proposing and experimentally implementing measures to foster insight and to make these problems accessible to the human mind. Yet these problems have thus far usually been empirically analyzed on an individual-item level only (e.g., by experimentally comparing participants' performance on various versions of one of these problems). In this paper, by contrast, we examine these illusions as a group and look at the ability to solve them as a psychological construct. Based on an sample of N = 2,643 Luxembourgian school students of age 16-18 we investigate the internal psychometric structure of these illusions (i.e., Are they substantially correlated? Do they form a reflexive or a formative construct?), their connection to related constructs (e.g., Are they distinguishable from intelligence or mathematical competence in a confirmatory factor analysis?), and the question of which of a person's abilities can predict the correct solution of these brain teasers (by means of a regression analysis).
Many phenomena of high relevance for economic development such as human capital, geography and climate vary considerably within countries as well as between them. Yet, global data sets of economic output are typically available at the national level only, thereby limiting the accuracy and precision of insights gained through empirical analyses. Recent work has used interpolation and downscaling to yield estimates of sub-national economic output at a global scale, but respective data sets based on official, reported values only are lacking. We here present DOSE — the MCC-PIK Database Of Sub-national Economic Output. DOSE contains harmonised data on reported economic output from 1,661 sub-national regions across 83 countries from 1960 to 2020. To avoid interpolation, values are assembled from numerous statistical agencies, yearbooks and the literature and harmonised for both aggregate and sectoral output. Moreover, we provide temporally- and spatially-consistent data for regional boundaries, enabling matching with geo-spatial data such as climate observations. DOSE provides the opportunity for detailed analyses of economic development at the subnational level, consistent with reported values.
Atwood analyzes the effects of the 1963 U.S. measles vaccination on long-run labor market outcomes, using a generalized difference-in-differences approach. We reproduce the results of this paper and perform a battery of robustness checks. Overall, we confirm that the measles vaccination had positive labor market effects. While the negative effect on the likelihood of living in poverty and the positive effect on the probability of being employed are very robust across the different specifications, the headline estimate—the effect on earnings—is more sensitive to the exclusion of certain regions and survey years.
The fluxes of water and solutes in the subsurface compartment of the Critical Zone are temporally dynamic and it is unclear how this impacts microbial mediated nutrient cycling in the spatially heterogeneous subsurface. To investigate this, we undertook numerical modeling, simulating the transport in a wide range of spatially heterogeneous domains, and the biogeochemical transformation of organic carbon and nitrogen compounds using a complex microbial community with four (4) distinct functional groups, in water saturated subsurface compartments. We performed a comprehensive uncertainty analysis accounting for varying residence times and spatial heterogeneity. While the aggregated removal of chemical species in the domains over the entire simulation period was approximately the same as that in steady state conditions, the sub-scale temporal variation of microbial biomass and chemical discharge from a domain depended strongly on the interplay of spatial heterogeneity and temporal dynamics of the forcing. We showed that the travel time and the Damkohler number (Da) can be used to predict the temporally varying chemical discharge from a spatially heterogeneous domain. In homogeneous domains, chemical discharge in temporally dynamic conditions could be double of that in the steady state conditions while microbial biomass varied up to 75% of that in steady state conditions. In heterogeneous domains, the interquartile range of uncertainty in chemical discharge in reaction dominated systems (log(10)Da > 0) was double of that in steady state conditions. However, high heterogeneous domains resulted in outliers where chemical discharge could be as high as 10-20 times of that in steady state conditions in high flow periods. And in transport dominated systems (log(10)Da < 0), the chemical discharge could be half of that in steady state conditions in unusually low flow conditions. In conclusion, ignoring spatio-temporal heterogeneities in a numerical modeling approach may exacerbate inaccurate estimation of nutrient export and microbial biomass. The results are relevant to long-term field monitoring studies, and for homogeneous soil column-scale experiments investigating the role of temporal dynamics on microbial redox dynamics.
The Influence of acute sprint interval training on cognitive performance of healthy younger adults
(2022)
There is considerable evidence showing that an acute bout of physical exercises can improve cognitive performance, but the optimal exercise characteristics (e.g., exercise type and exercise intensity) remain elusive. In this regard, there is a gap in the literature to which extent sprint interval training (SIT) can enhance cognitive performance. Thus, this study aimed to investigate the effect of a time-efficient SIT, termed as "shortened-sprint reduced-exertion high-intensity interval training" (SSREHIT), on cognitive performance. Nineteen healthy adults aged 20-28 years were enrolled and assessed for attentional performance (via the d2 test), working memory performance (via Digit Span Forward/Backward), and peripheral blood lactate concentration immediately before and 10 min after an SSREHIT and a cognitive engagement control condition (i.e., reading). We observed that SSREHIT can enhance specific aspects of attentional performance, as it improved the percent error rate (F%) in the d-2 test (t (18) = -2.249, p = 0.037, d = -0.516), which constitutes a qualitative measure of precision and thoroughness. However, SSREHIT did not change other measures of attentional or working memory performance. In addition, we observed that the exercise-induced increase in the peripheral blood lactate levels correlated with changes in attentional performance, i.e., the total number of responses (GZ) (r(m) = 0.70, p < 0.001), objective measures of concentration (SKL) (r(m) = 0.73, p < 0.001), and F% (r(m) = -0.54, p = 0.015). The present study provides initial evidence that a single bout of SSREHIT can improve specific aspects of attentional performance and conforming evidence for a positive link between cognitive improvements and changes in peripheral blood lactate levels.
Understanding the key factors influencing the water quality of large river systems forms an important basis for the assessment and protection of cross-regional ecosystems and the implementation of adapted water management concepts. However, identifying these factors requires in-depth comprehension of the unique environmental systems, which can only be achieved by detailed water quality monitoring.
Within the scope of the joint science and sports event "Elbschwimmstaffel" (swimming relay on the river Elbe) in June/July 2017 organized by the German Ministry of Education and Research, water quality data were acquired along a 550 km long stretch of the Elbe River in Germany. During the survey, eight physiochemical water quality parameters were recorded in high spatial and temporal resolution with the BIOFISH multisensor system. Multivariate statistical methods were applied to identify and delineate processes influencing the water quality.
The BIOFISH dataset revealed that phytoplankton activity has a major impact on the water quality of the Elbe River in the summer months. The results suggest that phytoplankton biomass constitutes a substantial proportion of the suspended particles and that photosynthetic activity of phytoplankton is closely related to significant temporal changes in pH and oxygen saturation.
An evaluation of the BIOFISH data based on the combination of statistical analysis with weather and discharge data shows that the hydrological and meteorological history of the sampled water body was the main driver of phytoplankton dynamics. This study demonstrates the capacity of longitudinal river surveys with the BIOFISH or similar systems for water quality assessment, the identification of pollution sources and their utilization for online in situ monitoring of rivers.
Damit die EU ihre ambitionierten Klimaschutzziele erreichen kann, werden die Preise für Treibhausgasemissionen in den nächsten Jahren spürbar steigen. Das hat ökonomische Auswirkungen für die EU-Mitgliedsländer, aber auch den Rest der Welt. Einzelne Sektoren und auch Volkswirtschaften werden davon unterschiedlich stark getroffen.
Basal ice-shelf melting is the key driver of Antarctica's increasing sea-level contribution. In diminishing the buttressing force of the ice shelves that fringe the ice sheet, the melting increases the ice discharge into the ocean.
Here we contrast the influence of basal melting in two different ice-shelf regions on the time-dependent response of an isothermal, inherently buttressed ice-sheet-shelf system. In the idealized numerical simulations, the basal-melt perturbations are applied close to the grounding line in the ice-shelf's (1) ice-stream region, where the ice shelf is fed by the fastest ice masses that stream through the upstream bed trough and (2) shear margins, where the ice flow is slower.
The results show that melting below one or both of the shear margins can cause a decadal to centennial increase in ice discharge that is more than twice as large compared to a similar perturbation in the ice-stream region. We attribute this to the fact that melt-induced ice-shelf thinning in the central grounding-line region is attenuated very effectively by the fast flow of the central ice stream. In contrast, the much slower ice dynamics in the lateral shear margins of the ice shelf facilitate sustained ice-shelf thinning and thereby foster buttressing reduction.
Regardless of the melt location, a higher melt concentration toward the grounding line generally goes along with a stronger response. Our results highlight the vulnerability of outlet glaciers to basal melting in stagnant, buttressing-relevant ice-shelf regions, a mechanism that may gain importance under future global warming.
Schulpraktische Phasen stellen eine bedeutende praxisnahe Lerngelegenheit im Lehramtsstudium dar, da sie Raum für umfangreiche Reflexionen der eigenen Lernerfahrung bieten. Das im Studium erworbene theoretisch-formale Wissen steht hierbei dem praktischen Wissen und Können gegenüber. Mit der professionellen Entwicklung im Referendariat, besonders im Kompetenzbereich des Unterrichtens, kann geschlussfolgert werden, dass sich eine Reflexion über eher fachliche Aspekte unter den Studierenden im Referendariat auf eine Reflexion über eher überfachliche und pädagogische Aspekte weitet. Infolge der Analyse von N = 55 schriftlichen Fremdreflexionen von angehenden Physiklehrkräften aus Studium und Referendariat konnte diese Hypothese für den Bereich der Unterrichtsanalyse und -reflexion unterstützt werden. Weiter wurde aus der Videovignette ein Workshopangebot für Lehrkräfte der zweiten und dritten Phase der Lehrkräftebildung entwickelt, erprobt und evaluiert.
Dieser Beitrag beschäftigt sich mit den Herausforderungen der Professionalisierung angehender Lehrkräfte im Rahmen der universitären Lehrkräftebildung und nimmt dabei kasuistische Lehrformate als wichtige Elemente hochschuldidaktischer Konzeptionen in den Blick. In diesem Zusammenhang wird das Modul „Außerunterrichtliches Pädagogisches Praktikum“ (AuPP) als ein zentrales Element der Praxisphasen des Lehramtsstudiums an der Martin-Luther-Universität Halle-Wittenberg (MLU) vorgestellt. Im Rahmen dieses Moduls wird versucht, durch die Arbeit an konkreten Fällen aus der pädagogischen Praxis – gemeint sind vor allem Beobachtungsprotokolle und Transkripte von Interviewauszügen aus unterschiedlichen (sozial-)pädagogischen Handlungsfeldern – einen reflexiven Zugang zu Spannungsmomenten, Problem- und Krisendynamiken, Orientierungsmustern der Akteur:innen sowie Gelingensbedingungen pädagogischer Praxis für angehende Lehrpersonen zu eröffnen und darüber einen reflexiven Habitus anzubahnen, der für die weitere Berufsbiografie und Professionalisierung essenziell erscheint.