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Abstract
In recent years, feedforward neural networks (NNs) have been successfully applied to reconstruct global plasmasphere dynamics in the equatorial plane. These neural network‐based models capture the large‐scale dynamics of the plasmasphere, such as plume formation and erosion of the plasmasphere on the nightside. However, their performance depends strongly on the availability of training data. When the data coverage is limited or non‐existent, as occurs during geomagnetic storms, the performance of NNs significantly decreases, as networks inherently cannot learn from the limited number of examples. This limitation can be overcome by employing physics‐based modeling during strong geomagnetic storms. Physics‐based models show a stable performance during periods of disturbed geomagnetic activity if they are correctly initialized and configured. In this study, we illustrate how to combine the neural network‐ and physics‐based models of the plasmasphere in an optimal way by using data assimilation. The proposed approach utilizes advantages of both neural network‐ and physics‐based modeling and produces global plasma density reconstructions for both quiet and disturbed geomagnetic activity, including extreme geomagnetic storms. We validate the models quantitatively by comparing their output to the in‐situ density measurements from RBSP‐A for an 18‐month out‐of‐sample period from June 30, 2016 to January 01, 2018 and computing performance metrics. To validate the global density reconstructions qualitatively, we compare them to the IMAGE EUV images of the He+ particle distribution in the Earth's plasmasphere for a number of events in the past, including the Halloween storm in 2003.
The European Union is highly dependent on soybean imports from overseas to meet its protein demands. Individual Member States have been quick to declare self-sufficiency targets for plant-based proteins, but detailed strategies are still lacking. Rising global temperatures have painted an image of a bright future for soybean production in Europe, but emerging climatic risks such as drought have so far not been included in any of those outlooks.
Here, we present simulations of future soybean production and the most prominent risk factors across Europe using an ensemble of climate and soybean growth models. Projections suggest a substantial increase in potential soybean production area and productivity in Central Europe, while southern European production would become increasingly dependent on supplementary irrigation. Average productivity would rise by 8.3% (RCP 4.5) to 8.7% (RCP 8.5) as a result of improved growing conditions (plant physiology benefiting from rising temperature and CO2 levels) and farmers adapting to them by using cultivars with longer phenological cycles. Suitable production area would rise by 31.4% (RCP 4.5) to 37.7% (RCP 8.5) by the mid-century, contributing considerably more than productivity increase to the production potential for closing the protein gap in Europe.
While wet conditions at harvest and incidental cold spells are the current key challenges for extending soybean production, the models and climate data analysis anticipate that drought and heat will become the dominant limitations in the future. Breeding for heat-tolerant and water-efficient genotypes is needed to further improve soybean adaptation to changing climatic conditions.
Low-energy (5-20 eV) electron-induced single and double strand breaks in well-defined DNA sequences
(2022)
Ionizing radiation is used in cancer radiation therapy to effectively damage the DNA of tumors. The main damage is due to generation of highly reactive secondary species such as low-energy electrons (LEEs). The accurate quantification of DNA radiation damage of well-defined DNA target sequences in terms of absolute cross sections for LEE-induced DNA strand breaks is possible by the DNA origami technique; however, to date, it is possible only for DNA single strands. In the present work DNA double strand breaks in the DNA sequence 5 '-d(CAC)4/5 ' d(GTG)4 are compared with DNA single strand breaks in the oligonucleotides 5 '-d(CAC)4 and 5 '-d(GTG)4 upon irradiation with LEEs in the energy range from 5 to 20 eV. A maximum of strand break cross section was found around 7 and 10 eV independent of the DNA sequence, indicating that dissociative electron attachment is the underlying mechanism of strand breakage and confirming previous studies using plasmid DNA.
Dieser Beitrag vergleicht die kommunale Verwaltungsdigitalisierung in Deutschland, Österreich und der Schweiz (DACH-Länder) als Vertreter der kontinentaleuropäisch-föderalen Verwaltungstradition bei zugleich unterschiedlichen Digitalisierungsansätzen und -fortschritten. Basierend auf Interviews mit 22 Expert*innen und Beobachtungen in je einer Kommune pro Land sowie Dokumenten-, Literatur- und Sekundärdatenanalysen untersucht die Studie, wie Verwaltungsdigitalisierung im Mehrebenensystem organisiert ist und welche Rolle dabei das Verwaltungsprofil spielt sowie welche Innovationsschwerpunkte die Kommunen im Hinblick auf die Leistungserbringung und die internen Prozesse setzen. Die Ergebnisse zeigen, dass der hohe Grad lokaler Autonomie den Kommunen ermöglicht, eigene Akzente in der Verwaltungsdigitalisierung zu setzen. Zugleich wirken die stark verflochtenen komplexen Entscheidungsstrukturen und hohen Koordinationsbedarfe in verwaltungsföderalen Systemen, die in Deutschland am stärksten, in Österreich etwas schwächer und in der Schweiz am geringsten ausgeprägt sind, als Digitalisierungshemmnisse. Ferner weisen die Befunde auf eine unitarisierende Wirkung der Verwaltungsdigitalisierung als Reformbereich hin. Insgesamt trägt die Studie zu einem besseren Verständnis dafür bei, welche Problematik die Verwaltungsdigitalisierung für föderal-dezentrale Verwaltungsmodelle mit sich bringt.
‘Modern talking’
(2024)
Despite growing interest, we lack a clear understanding of how the arguably ambiguous phenomenon of agile is perceived in government practice. This study aims to alleviate this puzzle by investigating how managers and employees in German public sector organisations make sense of agile as a spreading management fashion in the form of narratives. This is important because narratives function as innovation carriers that ultimately influence the manifestations of the concept in organisations. Based on a multi-case study of 31 interviews and 24 responses to a qualitative online survey conducted in 2021 and 2022, we provide insights into what public sector managers, employees and consultants understand (and, more importantly, do not understand) as agile and how they weave it into their existing reality of bureaucratic organisations. We uncover three meta-narratives of agile government, which we label ‘renew’, ‘complement’ and ‘integrate’. In particular, the meta-narratives differ in their positioning of how agile interacts with the characteristics of bureaucratic organisations. Importantly, we also show that agile as a management fad serves as a projection surface for what actors want from a modern and digital organisation. Thus, the vocabulary of agile government within the narratives is inherently linked to other diffusing phenomena such as new work or digitalisation.
An accurate estimation of crop yield under climate change scenarios is essential to quantify our ability to feed a growing population and develop agronomic adaptations to meet future food demand. A coordinated evaluation of yield simulations from process-based eco-physiological models for climate change impact assessment is still missing for soybean, the most widely grown grain legume and the main source of protein in our food chain. In this first soybean multi-model study, we used ten prominent models capable of simulating soybean yield under varying temperature and atmospheric CO2 concentration [CO2] to quantify the uncertainty in soybean yield simulations in response to these factors. Models were first parametrized with high quality measured data from five contrasting environments. We found considerable variability among models in simulated yield responses to increasing temperature and [CO2]. For example, under a + 3 degrees C temperature rise in our coolest location in Argentina, some models simulated that yield would reduce as much as 24%, while others simulated yield increases up to 29%. In our warmest location in Brazil, the models simulated a yield reduction ranging from a 38% decrease under + 3 degrees C temperature rise to no effect on yield. Similarly, when increasing [CO2] from 360 to 540 ppm, the models simulated a yield increase that ranged from 6% to 31%. Model calibration did not reduce variability across models but had an unexpected effect on modifying yield responses to temperature for some of the models. The high uncertainty in model responses indicates the limited applicability of individual models for climate change food projections. However, the ensemble mean of simulations across models was an effective tool to reduce the high uncertainty in soybean yield simulations associated with individual models and their parametrization. Ensemble mean yield responses to temperature and [CO2] were similar to those reported from the literature. Our study is the first demonstration of the benefits achieved from using an ensemble of grain legume models for climate change food projections, and highlights that further soybean model development with experiments under elevated [CO2] and temperature is needed to reduce the uncertainty from the individual models.
This article analyses incremental institutional change and subsequent organizational and performance outcomes of the digital transformation from a comparative perspective. Through 31 expert interviews, the authors compare two digitalized public services in Germany. Two digitalization approaches are identified. The voluntary, decentralized bottom-up approach involves layering of new rules, limited organizational restructuring, and performance deficits. Conversely, the compulsory, top-down approach with centralized control facilitates displacement of existing rules and far-reaching organizational change; in this study, it is also associated with improved performance.
Purpose: The present work aimed to delineate (i) a revised protocol according to recent methodological developments in evidence generation, to (ii) describe its interpretation, the assessment of the overall certainty of evidence and to (iii) outline an Evidence to Decision framework for deriving an evidence-based guideline on quantitative and qualitative aspects of dietary protein intake. Methods A methodological protocol to systematically investigate the association between dietary protein intake and several health outcomes and for deriving dietary protein intake recommendations for the primary prevention of various non-communicable diseases in the general adult population was developed. Results The developed methodological protocol relies on umbrella reviews including systematic reviews with or without meta-analyses. Systematic literature searches in three databases will be performed for each health-related outcome. The methodological quality of all selected systematic reviews will be evaluated using a modified version of AMSTAR 2, and the outcome-specific certainty of evidence for systematic reviews with or without meta-analysis will be assessed with NutriGrade. The general outline of the Evidence to Decision framework foresees that recommendations in the derived guideline will be given based on the overall certainty of evidence as well as on additional criteria such as sustainability. Conclusion The methodological protocol permits a systematic evaluation of published systematic reviews on dietary protein intake and its association with selected health-related outcomes. An Evidence to Decision framework will be the basis for the overall conclusions and the resulting recommendations for dietary protein intake.
This study aimed to build on the relationship of well-established self-report and behavioral assessments to the latent constructs positive (PVS) and negative valence systems (NVS), cognitive systems (CS), and social processes (SP) of the Research Domain Criteria (RDoC) framework in a large transnosological population which cuts across DSM/ICD-10 disorder criteria categories. One thousand four hundred and thirty one participants (42.1% suffering from anxiety/fear-related, 18.2% from depressive, 7.9% from schizophrenia spectrum, 7.5% from bipolar, 3.4% from autism spectrum, 2.2% from other disorders, 18.4% healthy controls, and 0.2% with no diagnosis specified) recruited in studies within the German research network for mental disorders for the Phenotypic, Diagnostic and Clinical Domain Assessment Network Germany (PD-CAN) were examined with a Mini-RDoC-Assessment including behavioral and self-report measures. The respective data was analyzed with confirmatory factor analysis (CFA) to delineate the underlying latent RDoC-structure. A revised four-factor model reflecting the core domains positive and negative valence systems as well as cognitive systems and social processes showed a good fit across this sample and showed significantly better fit compared to a one factor solution. The connections between the domains PVS, NVS and SP could be substantiated, indicating a universal latent structure spanning across known nosological entities. This study is the first to give an impression on the latent structure and intercorrelations between four core Research Domain Criteria in a transnosological sample. We emphasize the possibility of using already existing and well validated self-report and behavioral measurements to capture aspects of the latent structure informed by the RDoC matrix.
Massive Open Online Courses (MOOCs) remarkably attracted global media attention, but the spotlight has been concentrated on a handful of English-language providers. While Coursera, edX, Udacity, and FutureLearn received most of the attention and scrutiny, an entirely new ecosystem of local MOOC providers was growing in parallel. This ecosystem is harder to study than the major players: they are spread around the world, have less staff devoted to maintaining research data, and operate in multiple languages with university and corporate regional partners. To better understand how online learning opportunities are expanding through this regional MOOC ecosystem, we created a research partnership among 15 different MOOC providers from nine countries. We gathered data from over eight million learners in six thousand MOOCs, and we conducted a large-scale survey with more than 10 thousand participants. From our analysis, we argue that these regional providers may be better positioned to meet the goals of expanding access to higher education in their regions than the better-known global providers. To make this claim we highlight three trends: first, regional providers attract a larger local population with more inclusive demographic profiles; second, students predominantly choose their courses based on topical interest, and regional providers do a better job at catering to those needs; and third, many students feel more at ease learning from institutions they already know and have references from. Our work raises the importance of local education in the global MOOC ecosystem, while calling for additional research and conversations across the diversity of MOOC providers.