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„Zur rechten Zeit“ ist ein flüssig geschriebenes, gut lesbares und an ein breites Publikum gerichtetes Sachbuch. Es will die Geschichte der Bundesrepublik „unter dem Eindruck der gegenwärtigen rechten Konjunktur anders denn als gängige Erfolgsgeschichte“ (S. 10) erzählen. Die Autorinnen und Autoren sind nicht bestrebt, das Erfolgsnarrativ radikal zu dekonstruieren und damit den Forschungsertrag der Zeitgeschichtsschreibung zu ignorieren, wohl aber rekonstruieren sie Abschattungen und Brüche, die zeigen, dass der Prozess weniger geradlinig war als häufig angenommen – und dass seine Ergebnisse nicht irreversibel sind.
Quantification of reaction fluxes of metabolic networks can help us understand how the integration of different metabolic pathways determines cellular functions. Yet, intracellular fluxes cannot be measured directly but are estimated with metabolic flux analysis (MFA), which relies on the patterns of isotope labeling of metabolites in the network. The application of MFA also requires a stoichiometric model with atom mappings that are currently not available for the majority of large-scale metabolic network models, particularly of plants. While automated approaches such as the Reaction Decoder Toolkit (RDT) can produce atom mappings for individual reactions, tracing the flow of individual atoms of the entire reactions across a metabolic model remains challenging. Here we establish an automated workflow to obtain reliable atom mappings for large-scale metabolic models by refining the outcome of RDT, and apply the workflow to metabolic models of Arabidopsis thaliana. We demonstrate the accuracy of RDT through a comparative analysis with atom mappings from a large database of biochemical reactions, MetaCyc. We further show the utility of our automated workflow by simulating N-15 isotope enrichment and identifying nitrogen (N)-containing metabolites which show enrichment patterns that are informative for flux estimation in future N-15-MFA studies of A. thaliana. The automated workflow established in this study can be readily expanded to other species for which metabolic models have been established and the resulting atom mappings will facilitate MFA and graph-theoretic structural analyses with large-scale metabolic networks.
Tacitus' Wonders
(2022)
This volume approaches the broad topic of wonder in the works of Tacitus, encompassing paradox, the marvellous and the admirable. Recent scholarship on these themes in Roman literature has tended to focus on poetic genres, with comparatively little attention paid to historiography: Tacitus, whose own judgments on what is worthy of note have often differed in interesting ways from the preoccupations of his readers, is a fascinating focal point for this complementary perspective.
Scholarship on Tacitus has to date remained largely marked by a divide between the search for veracity – as validated by modern historiographical standards – and literary approaches, and as a result wonders have either been ignored as unfit for an account of history or have been deprived of their force by being interpreted as valid only within the text. While the modern ideal of historiographical objectivity tends to result in striving for consistent heuristic and methodological frameworks, works as varied as Tacitus' Histories, Annals and opera minora can hardly be prefaced with a statement of methodology broad enough to escape misrepresenting their diversity. In our age of specialization a streamlined methodological framework is a virtue, but it should not be assumed that Tacitus had similar priorities, and indeed the Histories and Annals deserve to be approached with openness towards the variety of perspectives that a tradition as rich as Latin historiographical prose can include within its scope. This collection proposes ways to reconcile the divide between history and historiography by exploring contestable moments in the text that challenge readers to judge and interpret for themselves, with individual chapters drawing on a range of interpretive approaches that mirror the wealth of authorial and reader-specific responses in play.
Long- and short-term monitoring of a dam in response to seasonal changes and ground motion loading
(2021)
An experimental multi-parameter structural monitoring system has been installed on the Kurpsai dam, western Kyrgyz Republic. This system consists of equipment for seismic and strain measurements for making longer- (days, weeks, months) and shorter- (minutes, hours) term observations, dealing with, for example seasonal (longer) effects or the response of the dam to ground motion from noise or seismic events. Fibre-optic strain sensors allow the seasonal and daily opening and closing of the spaces between the dam's segments to be tracked. For the seismic data, both amplitude (in terms of using differences in amplitudes in the Fourier spectra for mapping the modes of vibration of the dam) and their time-frequency distribution for a set of small to moderate seismic events are investigated and the corresponding phase variabilities (in terms of lagged coherency) are evaluated. Even for moderate levels of seismic-induced ground motion, some influence on the structural response can be detected, which then sees the dam quickly return to its original state. A seasonal component was identified in the strain measurements, while levels of noise arising from the operation of the dam's generators and associated water flow have been provisionally identified.
Lost in Germania
(2021)
Tacitus’ Germania is notable for its absences: lacking a preface and programmatic statements, and being the only ethnographic monograph to have survived from Greco-Roman antiquity, readers have often leapt to fill in its perceived blanks. This chapter aims at redressing the effects of overdetermined readings by interpreting the text’s absences as significant in their own right.
Centroid moment tensor (CMT) parameters can be estimated from seismic waveforms. Since these data indirectly observe the deformation process, CMTs are inferred as solutions to inverse problems which are generally underdetermined and require significant assumptions, including assumptions about data noise. Broadly speaking, we consider noise to include both theory and measurement errors, where theory errors are due to assumptions in the inverse problem and measurement errors are caused by the measurement process. While data errors are routinely included in parameter estimation for full CMTs, less attention has been paid to theory errors related to velocity-model uncertainties and how these affect the resulting moment-tensor (MT) uncertainties. Therefore, rigorous uncertainty quantification for CMTs may require theory-error estimation which becomes a problem of specifying noise models. Various noise models have been proposed, and these rely on several assumptions. All approaches quantify theory errors by estimating the covariance matrix of data residuals. However, this estimation can be based on explicit modelling, empirical estimation and/or ignore or include covariances. We quantitatively compare several approaches by presenting parameter and uncertainty estimates in nonlinear full CMT estimation for several simulated data sets and regional field data of the M-1 4.4, 2015 June 13 Fox Creek, Canada, event. While our main focus is at regional distances, the tested approaches are general and implemented for arbitrary source model choice. These include known or unknown centroid locations, full MTs, deviatoric MTs and double-couple MTs. We demonstrate that velocity-model uncertainties can profoundly affect parameter estimation and that their inclusion leads to more realistic parameter uncertainty quantification. However, not all approaches perform equally well. Including theory errors by estimating non-stationary (non-Toeplitz) error covariance matrices via iterative schemes during Monte Carlo sampling performs best and is computationally most efficient. In general, including velocity-model uncertainties is most important in cases where velocity structure is poorly known.
Successful conservation efforts have led to recent increases of large mammals such as European bison Bison bonasus, moose Alces alces and grey wolf Canis lupus and their return to former habitats in central Europe.
While embraced by some, the recovery of these species is a controversial topic and holds potential for human-wildlife conflicts.
Involving the public has been suggested to be an effective method for monitoring wildlife and mitigating associated conflicts.
To assess two interrelated prerequisites for engaging people in Citizen Science (CS)-knowledge of returning species and respondents' readiness to participate in CS activities for monitoring and managing these species-we conducted a survey (questionnaire) in two wildlife parks located in different states of Germany.
Based on 472 complete questionnaires, we developed generalized linear models to understand how sociodemographic variables and exposure to the species affected visitors' knowledge of each species, and to investigate if sociodemographic variables and knowledge influenced the likelihood of visitors to participate in CS activities.
Almost all visitors were aware of the returning wolf population, while knowledge and awareness about bison and moose were significantly lower.
Knowledge of the two herbivores differed geographically (higher knowledge of moose in the north-eastern state), possibly indicating a positive association between exposure to the species and knowledge.
However, models generally performed poorly in predicting knowledge about wildlife, suggesting that such specific knowledge is insufficiently explained by sociodemographic variables. Our model, which explained stated willingness in CS indicated that younger participants and those with higher knowledge scores in the survey were more willing to engage in CS activities.
Overall, our analyses highlight how exposure to large mammals, knowledge about wildlife and human demographics are interrelated-insights that are helpful for effectively recruiting citizen scientists for wildlife conservation.
Read the free Plain Language Summary for this article on the Journal blog.
This study investigates the use of pulse stretching (skew-sized) inverters for monitoring the variation of count rate and linear energy transfer (LET) of energetic particles. The basic particle detector is a cascade of two pulse stretching inverters, and the required sensing area is obtained by connecting up to 12 two-inverter cells in parallel and employing the required number of parallel arrays. The incident particles are detected as single-event transients (SETs), whereby the SET count rate denotes the particle count rate, while the SET pulsewidth distribution depicts the LET variations. The advantage of the proposed solution is the possibility to sense the LET variations using fully digital processing logic. SPICE simulations conducted on IHP's 130-nm CMOS technology have shown that the SET pulsewidth varies by approximately 550 ps over the LET range from 1 to 100 MeV center dot cm(2) center dot mg(-1). The proposed detector is intended for triggering the fault-tolerant mechanisms within a self-adaptive multiprocessing system employed in space. It can be implemented as a standalone detector or integrated in the same chip with the target system.
Fatty acids are widely used to study trophic interactions in food web assemblages. Generally, it is assumed that there is a very small modification of fatty acids from one trophic step to another, making them suitable as trophic biomarkers. However, recent literature provides evidence that many fishes possess genes encoding enzymes with a role in bioconversion, thus the capability for bioconversion might be more widespread than previously assumed. Nonetheless, empirical evidence for biosynthesis occurring in natural populations remains scarce. In this study, we investigated different feeding types of perch (Perca fluviatilis) that are specialized on specific resources with different levels of highly unsaturated fatty acids (HUFAs), and analyzed the change between HUFA proportions in perch muscle tissue compared to their resources. Perch showed matching levels to their resources for EPA, but ARA and especially DHA were accumulated. Compound-specific stable isotope analyses helped us to identify the origin of HUFA carbon. Our results suggest that perch obtain a substantial amount of DHA via bioconversion when feeding on DHA-poor benthic resources. Thus, our data indicate the capability of bioconversion of HUFAs in a natural freshwater fish population.
Circular economy
(2021)
In a circular economy, the use of recycled resources in production is a key performance indicator for management. Yet, academic studies are still unable to inform managers on appropriate recycling and pricing policies. We develop an optimal control model integrating a firm's recycling rate, which can use both virgin and recycled resources in the production process. Our model accounts for recycling influence both at the supply- and demandsides. The positive effect of a firm's use of recycled resources diminishes over time but may increase through investments. Using general formulations for demand and cost, we analytically examine joint dynamic pricing and recycling investment policies in order to determine their optimal interplay over time. We provide numerical experiments to assess the existence of a steady-state and to calculate sensitivity analyses with respect to various model parameters. The analysis shows how to dynamically adapt jointly optimized controls to reach sustainability in the production process. Our results pave the way to sounder sustainable practices for firms operating within a circular economy.
Cirrus is the only cloud type capable of inducing daytime cooling or heating at the top of the atmosphere (TOA) and the sign of its radiative effect highly depends on its optical depth. However, the investigation of its geometrical and optical properties over the Arctic is limited. In this work the long-term properties of cirrus clouds are explored for the first time over an Arctic site (Ny-Alesund, Svalbard) using lidar and radiosonde measurements from 2011 to 2020. The optical properties were quality assured, taking into account the effects of specular reflections and multiple-scattering. Cirrus clouds were generally associated with colder and calmer wind conditions compared to the 2011-2020 climatology. However, the dependence of cirrus properties on temperature and wind speed was not strong. Even though the seasonal cycle was not pronounced, the winter-time cirrus appeared under lower temperatures and stronger wind conditions. Moreover, in winter, geometrically- and optically-thicker cirrus were found and their ice particles tended to be more spherical. The majority of cirrus was associated with westerly flow and westerly cirrus tended to be geometrically-thicker. Overall, optically-thinner layers tended to comprise smaller and less spherical ice crystals, most likely due to reduced water vapor deposition on the particle surface. Compared to lower latitudes, the cirrus layers over Ny-Alesund were more absorbing in the visible spectral region and they consisted of more spherical ice particles.
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.
Both climate change and land use regimes affect the viability of populations, but they are often studied separately. Moreover, population viability analyses (PVAs) often ignore the effects of large environmental gradients and use temporal resolutions that are too coarse to take into account that different stages of a population's life cycle may be affected differently by climate change. Here, we present the High-resolution Large Environmental Gradient (HiLEG) model and apply it in a PVA with daily resolution based on daily climate projections for Northwest Germany. We used the large marsh grasshopper (LMG) as the target species and investigated (1) the effects of climate change on the viability and spatial distribution of the species, (2) the influence of the timing of grassland mowing on the species and (3) the interaction between the effects of climate change and grassland mowing. The stageand cohort-based model was run for the spatially differentiated environmental conditions temperature and soil moisture across the whole study region. We implemented three climate change scenarios and analyzed the population dynamics for four consecutive 20-year periods. Climate change alone would lead to an expansion of the regions suitable for the LMG, as warming accelerates development and due to reduced drought stress. However, in combination with land use, the timing of mowing was crucial, as this disturbance causes a high mortality rate in the aboveground life stages. Assuming the same date of mowing throughout the region, the impact on viability varied greatly between regions due to the different climate conditions. The regional negative effects of the mowing date can be divided into five phases: (1) In early spring, the populations were largely unaffected in all the regions; (2) between late spring and early summer, they were severely affected only in warm regions; (3) in summer, all the populations were severely affected so that they could hardly survive; (4) between late summer and early autumn, they were severely affected in cold regions; and (5) in autumn, the populations were equally affected across all regions. The duration and start of each phase differed slightly depending on the climate change scenario and simulation period, but overall, they showed the same pattern. Our model can be used to identify regions of concern and devise management recommendations. The model can be adapted to the life cycle of different target species, climate projections and disturbance regimes. We show with our adaption of the HiLEG model that high-resolution PVAs and applications on large environmental gradients can be reconciled to develop conservation strategies capable of dealing with multiple stressors.
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.
Ancient genome provides insights into the history of Eurasian lynx in Iberia and Western Europe
(2022)
The Eurasian lynx (Lynx lynx) is one of the most widely distributed felids in the world. However, most of its populations started to decline a few millennia ago. Historical declines have been especially severe in Europe, and particularly in Western Europe, from where the species disappeared in the last few centuries. Here, we analyze the genome of an Eurasian lynx inhabiting the Iberian Peninsula 2500 ya, to gain insights into the phylogeographic position and genetic status of this extinct population. Also, we contextualize previous ancient data in the light of new phylogeographic studies of the species. Our results suggest that the Iberian population is part of an extinct European lineage closely related to the current Carpathian-Baltic lineages. Also, this sample holds the lowest diversity reported for the species so far, and similar to that of the highly endangered Iberian lynx. A combination of historical factors, such as a founder effect while colonizing the peninsula, together with intensified human impacts during the Holocene in the Cantabrian strip, could have led to a genetic impoverishment of the population and precipitated its extinction. Mitogenomic lineages distribution in space and time support the long-term coexistence of several lineages of Eurasian lynx in Western Europe with fluctuating ranges. While mitochondrial sequences related to the lineages currently found in Balkans and Caucasus were predominant during the Pleistocene, those more closely related to the lineage currently distributed in Central Europe prevailed during the Holocene. The use of ancient genomics has proven to be a useful tool to understand the biogeographic pattern of the Eurasian lynx in the past.
The water vapor-induced swelling, as well as subsequent phase-transition kinetics, of thin films of a diblock copolymer (DBC) loaded with different amounts of the salt NaBr, is investigated in situ. In dilute aqueous solution, the DBC features an orthogonally thermoresponsive behavior. It consists of a zwitterionic poly(sulfobetaine) block, namely, poly(4-(N-(3'-methacrylamidopropyl)-N, N-dimethylammonio) butane-1-sulfonate) (PSBP), showing an upper critical solution temperature, and a nonionic block, namely, poly(N-isopropylmethacrylamide) (PNIPMAM), exhibiting a lower critical solution temperature. The swelling kinetics in D2O vapor at 15 degrees C and the phase transition kinetics upon heating the swollen film to 60 degrees C and cooling back to 15 degrees C are followed with simultaneous time-of-flight neutron reflectometry and spectral reflectance measurements. These are complemented by Fourier transform infrared spectroscopy. The collapse temperature of PNIPMAM and the swelling temperature of PSBP are found at lower temperatures than in aqueous solution, which is attributed to the high polymer concentration in the thin-film geometry. Upon inclusion of sub-stoichiometric amounts (relative to the monomer units) of NaBr in the films, the water incorporation is significantly increased. This increase is mainly attributed to a salting-in effect on the zwitterionic PSBP block. Whereas the addition of NaBr notably shifts the swelling temperature of PSBP to lower temperatures, the collapse temperature of PNIPMAM remains unaffected by the presence of salt in the films.
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.
The mean free path of ionizing photons, lambda(mfp), is a key factor in the photoionization of the intergalactic medium (IGM). At z greater than or similar to 5, however, lambda(mfp) may be short enough that measurements towards QSOs are biased by the QSO proximity effect. We present new direct measurements of lambda(mfp) that address this bias and extend up to z similar to 6 for the first time. Our measurements at z similar to 5 are based on data from the Giant Gemini GMOS survey and new Keck LRIS observations of low-luminosity QSOs. At z similar to 6 we use QSO spectra from Keck ESI and VLT X-Shooter. We measure lambda(mfp) = 9.09(-1.28)(+1.62) proper Mpc and 0.75(-0.45)(+0.65) proper Mpc (68 percent confidence) at z = 5.1 and 6.0, respectively. The results at z = 5.1 are consistent with existing measurements, suggesting that bias from the proximity effect is minor at this redshift. At z = 6.0, however, we find that neglecting the proximity effect biases the result high by a factor of two or more. Our measurement at z = 6.0 falls well below extrapolations from lower redshifts, indicating rapid evolution in lambda(mfp) over 5 < z < 6. This evolution disfavours models in which reionization ended early enough that the IGM had time to fully relax hydrodynamically by z = 6, but is qualitatively consistent with models wherein reionization completed at z = 6 or even significantly later. Our mean free path results are most consistent with late reionization models wherein the IGM is still 20 percent neutral at z = 6, although our measurement at z = 6.0 is even lower than these models prefer.