DOAJ gelistet
Refine
Year of publication
Is part of the Bibliography
- yes (1226)
Keywords
- climate change (17)
- machine learning (15)
- COVID-19 (7)
- permafrost (7)
- children (6)
- embodied cognition (6)
- inflammation (6)
- metabarcoding (6)
- precipitation (6)
- Dictyostelium (5)
Institute
- Institut für Biochemie und Biologie (275)
- Institut für Geowissenschaften (196)
- Institut für Physik und Astronomie (157)
- Institut für Umweltwissenschaften und Geographie (104)
- Institut für Chemie (78)
- Department Psychologie (64)
- Department Sport- und Gesundheitswissenschaften (63)
- Institut für Ernährungswissenschaft (62)
- Institut für Mathematik (32)
- Department Linguistik (31)
A circulatory loop
(2023)
In the digitalization debate, gender biases in digital technologies play a significant role because of their potential for social exclusion and inequality. It is therefore remarkable that organizations as drivers of digitalization and as places for social integration have been widely overlooked so far. Simultaneously, gender biases and digitalization have structurally immanent connections to organizations. Therefore, a look at the reciprocal relationship between organizations, digitalization, and gender is needed. The article provides answers to the question of whether and how organizations (re)produce, reinforce, or diminish gender‐specific inequalities during their digital transformations. On the one hand, gender inequalities emerge when organizations use post‐bureaucratic concepts through digitalization. On the other hand, gender inequalities are reproduced when organizations either program or implement digital technologies and fail to establish control structures that prevent gender biases. This article shows that digitalization can act as a catalyst for inequality‐producing mechanisms, but also has the potential to mitigate inequalities. We argue that organizations must be considered when discussing the potential of exclusion through digitalization.
Genomic prediction has revolutionized crop breeding despite remaining issues of transferability of models to unseen environmental conditions and environments. Usage of endophenotypes rather than genomic markers leads to the possibility of building phenomic prediction models that can account, in part, for this challenge. Here, we compare and contrast genomic prediction and phenomic prediction models for 3 growth-related traits, namely, leaf count, tree height, and trunk diameter, from 2 coffee 3-way hybrid populations exposed to a series of treatment-inducing environmental conditions. The models are based on 7 different statistical methods built with genomic markers and ChlF data used as predictors. This comparative analysis demonstrates that the best-performing phenomic prediction models show higher predictability than the best genomic prediction models for the considered traits and environments in the vast majority of comparisons within 3-way hybrid populations. In addition, we show that phenomic prediction models are transferrable between conditions but to a lower extent between populations and we conclude that chlorophyll a fluorescence data can serve as alternative predictors in statistical models of coffee hybrid performance. Future directions will explore their combination with other endophenotypes to further improve the prediction of growth-related traits for crops.
A comparative whole-genome approach identifies bacterial traits for marine microbial interactions
(2022)
Luca Zoccarato, Daniel Sher et al. leverage publicly available bacterial genomes from marine and other environments to examine traits underlying microbial interactions.
Their results provide a valuable resource to investigate clusters of functional and linked traits to better understand marine bacteria community assembly and dynamics.
Microbial interactions shape the structure and function of microbial communities with profound consequences for biogeochemical cycles and ecosystem health. Yet, most interaction mechanisms are studied only in model systems and their prevalence is unknown. To systematically explore the functional and interaction potential of sequenced marine bacteria, we developed a trait-based approach, and applied it to 473 complete genomes (248 genera), representing a substantial fraction of marine microbial communities.
We identified genome functional clusters (GFCs) which group bacterial taxa with common ecology and life history. Most GFCs revealed unique combinations of interaction traits, including the production of siderophores (10% of genomes), phytohormones (3-8%) and different B vitamins (57-70%). Specific GFCs, comprising Alpha- and Gammaproteobacteria, displayed more interaction traits than expected by chance, and are thus predicted to preferentially interact synergistically and/or antagonistically with bacteria and phytoplankton. Linked trait clusters (LTCs) identify traits that may have evolved to act together (e.g., secretion systems, nitrogen metabolism regulation and B vitamin transporters), providing testable hypotheses for complex mechanisms of microbial interactions.
Our approach translates multidimensional genomic information into an atlas of marine bacteria and their putative functions, relevant for understanding the fundamental rules that govern community assembly and dynamics.
Air pollution is a pressing issue that is associated with adverse effects on human health, ecosystems, and climate. Despite many years of effort to improve air quality, nitrogen dioxide (NO2) limit values are still regularly exceeded in Europe, particularly in cities and along streets. This study explores how concentrations of nitrogen oxides (NOx = NO + NO2) in European urban areas have changed over the last decades and how this relates to changes in emissions. To do so, the incremental approach was used, comparing urban increments (i.e. urban background minus rural concentrations) to total emissions, and roadside increments (i.e. urban roadside concentrations minus urban background concentrations) to traffic emissions. In total, nine European cities were assessed. The study revealed that potentially confounding factors like the impact of urban pollution at rural monitoring sites through atmospheric transport are generally negligible for NOx. The approach proves therefore particularly useful for this pollutant. The estimated urban increments all showed downward trends, and for the majority of the cities the trends aligned well with the total emissions. However, it was found that factors like a very densely populated surrounding or local emission sources in the rural area such as shipping traffic on inland waterways restrict the application of the approach for some cities. The roadside increments showed an overall very diverse picture in their absolute values and trends and also in their relation to traffic emissions. This variability and the discrepancies between roadside increments and emissions could be attributed to a combination of local influencing factors at the street level and different aspects introducing inaccuracies to the trends of the emis-sion inventories used, including deficient emission factors. Applying the incremental approach was evaluated as useful for long-term pan-European studies, but at the same time it was found to be restricted to certain regions and cities due to data availability issues. The results also highlight that using emission inventories for the prediction of future health impacts and compliance with limit values needs to consider the distinct variability in the concentrations not only across but also within cities.
Narcissists are assumed to lack the motivation and ability to share and understand the mental states of others. Prior empirical research, however, has yielded inconclusive findings and has differed with respect to the specific aspects of narcissism and socioemotional cognition that have been examined. Here, we propose a differentiated facet approach that can be applied across research traditions and that distinguishes between facets of narcissism (agentic vs. antagonistic) on the one hand, and facets of socioemotional cognition ability (SECA; self-perceived vs. actual) on the other. Using five nonclinical samples in two studies (total N = 602), we investigated the effect of facets of grandiose narcissism on aspects of socioemotional cognition across measures of affective and cognitive empathy, Theory of Mind, and emotional intelligence, while also controlling for general reasoning ability. Across both studies, agentic facets of narcissism were found to be positively related to perceived SECA, whereas antagonistic facets of narcissism were found to be negatively related to perceived SECA. However, both narcissism facets were negatively related to actual SECA. Exploratory condition-based regression analyses further showed that agentic narcissists had a higher directed discrepancy between perceived and actual SECA: They self-enhanced their socio-emotional capacities. Implications of these results for the multifaceted theoretical understanding of the narcissism-SECA link are discussed.
The past three decades of policy process studies have seen the emergence of a clear intellectual lineage with regard to complexity. Implicitly or explicitly, scholars have employed complexity theory to examine the intricate dynamics of collective action in political contexts. However, the methodological counterparts to complexity theory, such as computational methods, are rarely used and, even if they are, they are often detached from established policy process theory. Building on a critical review of the application of complexity theory to policy process studies, we present and implement a baseline model of policy processes using the logic of coevolving networks. Our model suggests that an actor's influence depends on their environment and on exogenous events facilitating dialogue and consensus-building. Our results validate previous opinion dynamics models and generate novel patterns. Our discussion provides ground for further research and outlines the path for the field to achieve a computational turn.
Apoptotic death of cells damaged by genotoxic stress requires regulatory input from surrounding tissues. The C. elegans scaffold protein KRI-1, ortholog of mammalian KRIT1/CCM1, permits DNA damage-induced apoptosis of cells in the germline by an unknown cell non-autonomous mechanism. We reveal that KRI-1 exists in a complex with CCM-2 in the intestine to negatively regulate the ERK-5/MAPK pathway. This allows the KLF-3 transcription factor to facilitate expression of the SLC39 zinc transporter gene zipt-2.3, which functions to sequester zinc in the intestine. Ablation of KRI-1 results in reduced zinc sequestration in the intestine, inhibition of IR-induced MPK-1/ERK1 activation, and apoptosis in the germline. Zinc localization is also perturbed in the vasculature of krit1(-/-) zebrafish, and SLC39 zinc transporters are mis-expressed in Cerebral Cavernous Malformations (CCM) patient tissues. This study provides new insights into the regulation of apoptosis by cross-tissue communication, and suggests a link between zinc localization and CCM disease.
Compound natural hazards likeEl Ninoevents cause high damage to society, which to manage requires reliable risk assessments. Damage modelling is a prerequisite for quantitative risk estimations, yet many procedures still rely on expert knowledge, and empirical studies investigating damage from compound natural hazards hardly exist. A nationwide building survey in Peru after theEl Ninoevent 2017 - which caused intense rainfall, ponding water, flash floods and landslides - enables us to apply data-mining methods for statistical groundwork, using explanatory features generated from remote sensing products and open data. We separate regions of different dominant characteristics through unsupervised clustering, and investigate feature importance rankings for classifying damage via supervised machine learning. Besides the expected effect of precipitation, the classification algorithms select the topographic wetness index as most important feature, especially in low elevation areas. The slope length and steepness factor ranks high for mountains and canyons. Partial dependence plots further hint at amplified vulnerability in rural areas. An example of an empirical damage probability map, developed with a random forest model, is provided to demonstrate the technical feasibility.
A familial congenital heart disease with a possible multigenic origin involving a mutation in BMPR1A
(2019)
The genetics of many congenital heart diseases (CHDs) can only unsatisfactorily be explained by known chromosomal or Mendelian syndromes. Here, we present sequencing data of a family with a potentially multigenic origin of CHD. Twelve of nineteen family members carry a familial mutation [NM_004329.2:c.1328 G > A (p.R443H)] which encodes a predicted deleterious variant of BMPR1A. This mutation co-segregates with a linkage region on chromosome 1 that associates with the emergence of severe CHDs including Ebstein’s anomaly, atrioventricular septal defect, and others. We show that the continuous overexpression of the zebrafish homologous mutation bmpr1aap.R438H within endocardium causes a reduced AV valve area, a downregulation of Wnt/ß-catenin signalling at the AV canal, and growth of additional tissue mass in adult zebrafish hearts. This finding opens the possibility of testing genetic interactions between BMPR1A and other candidate genes within linkage region 1 which may provide a first step towards unravelling more complex genetic patterns in cardiovascular disease aetiology.
Biogenic greenhouse gas emissions, e.g., of methane (CH4) and carbon dioxide (CO2) from inland waters, contribute substantially to global warming. In aquatic systems, dissolved greenhouse gases are highly heterogeneous in both space and time. To better understand the biological and physical processes that affect sources and sinks of both CH4 and CO2, their dissolved concentrations need to be measured with high spatial and temporal resolution. To achieve this goal, we developed the Fast-Response Automated Gas Equilibrator (FaRAGE) for real-time in situ measurement of dissolved CH4 and CO2 concentrations at the water surface and in the water column. FaRAGE can achieve an exceptionally short response time (t(95%) = 12 s when including the response time of the gas analyzer) while retaining an equilibration ratio of 62.6% and a measurement accuracy of 0.5% for CH4. A similar performance was observed for dissolved CO2 (t(95%) = 10 s, equilibration ratio 67.1 %). An equilibration ratio as high as 91.8% can be reached at the cost of a slightly increased response time (16 s). The FaRAGE is capable of continuously measuring dissolved CO2 and CH4 concentrations in the nM-to-submM (10(-9)-10(-3) mol L-1) range with a detection limit of subnM (10(-10) mol L-1), when coupling with a cavity ring-down greenhouse gas analyzer (Picarro GasScouter). FaRAGE allows for the possibility of mapping dissolved concentration in a "quasi" three-dimensional manner in lakes and provides an inexpensive alternative to other commercial gas equilibrators. It is simple to operate and suitable for continuous monitoring with a strong tolerance for suspended particles. While the FaRAGE is developed for inland waters, it can be also applied to ocean waters by tuning the gas-water mixing ratio. The FaRAGE is easily adapted to suit other gas analyzers expanding the range of potential applications, including nitrous oxide and isotopic composition of the gases.
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.
This work reviews the literature on an alleged global warming 'pause' in global mean surface temperature (GMST) to determine how it has been defined, what time intervals are used to characterise it, what data are used to measure it, and what methods used to assess it. We test for 'pauses', both in the normally understood meaning of the term to mean no warming trend, as well as for a 'pause' defined as a substantially slower trend in GMST. The tests are carried out with the historical versions of GMST that existed for each pause-interval tested, and with current versions of each of the GMST datasets. The tests are conducted following the common (but questionable) practice of breaking the linear fit at the start of the trend interval ('broken' trends), and also with trends that are continuous with the data bordering the trend interval. We also compare results when appropriate allowance is made for the selection bias problem. The results show that there is little or no statistical evidence for a lack of trend or slower trend in GMST using either the historical data or the current data. The perception that there was a 'pause' in GMST was bolstered by earlier biases in the data in combination with incomplete statistical testing.
Aging in speech production is a multidimensional process. Biological, cognitive, social, and communicative factors can change over time, stay relatively stable, or may even compensate for each other. In this longitudinal work, we focus on stability and change at the laryngeal and supralaryngeal levels in the discourse particle euh produced by 10 older French-speaking females at two times, 10 years apart. Recognizing the multiple discourse roles of euh, we divided out occurrences according to utterance position. We quantified the frequency of euh, and evaluated acoustic changes in formants, fundamental frequency, and voice quality across time and utterance position. Results showed that euh frequency was stable with age. The only acoustic measure that revealed an age effect was harmonics-to-noise ratio, showing less noise at older ages. Other measures mostly varied with utterance position, sometimes in interaction with age. Some voice quality changes could reflect laryngeal adjustments that provide for airflow conservation utterance-finally. The data suggest that aging effects may be evident in some prosodic positions (e.g., utterance-final position), but not others (utterance-initial position). Thus, it is essential to consider the interactions among these factors in future work and not assume that vocal aging is evident throughout the signal.
A Metabarcoding Analysis of the Mycobiome of Wheat Ears Across a Topographically Heterogeneous Field
(2019)
In this study, we model a sequence of a confined and a full eruption, employing the relaxed end state of the confined eruption of a kink-unstable flux rope as the initial condition for the ejective one. The full eruption, a model of a coronal mass ejection, develops as a result of converging motions imposed at the photospheric boundary, which drive flux cancellation. In this process, parts of the positive and negative external flux converge toward the polarity inversion line, reconnect, and cancel each other. Flux of the same amount as the canceled flux transfers to a flux rope, increasing the free magnetic energy of the coronal field. With sustained flux cancellation and the associated progressive weakening of the magnetic tension of the overlying flux, we find that a flux reduction of approximate to 11% initiates the torus instability of the flux rope, which leads to a full eruption. These results demonstrate that a homologous full eruption, following a confined one, can be driven by flux cancellation.
A new evidence-based diet score to capture associations of food consumption and chronic disease risk
(2022)
Previously, the attempt to compile German dietary guidelines into a diet score was predominantly not successful with regards to preventing chronic diseases in the EPIC-Potsdam study. Current guidelines were supplemented by the latest evidence from systematic reviews and expert papers published between 2010 and 2020 on the prevention potential of food groups on chronic diseases such as type 2 diabetes, cardiovascular diseases and cancer. A diet score was developed by scoring the food groups according to a recommended low, moderate or high intake. The relative validity and reliability of the diet score, assessed by a food frequency questionnaire, was investigated. The consideration of current evidence resulted in 10 key food groups being preventive of the chronic diseases of interest. They served as components in the diet score and were scored from 0 to 1 point, depending on their recommended intake, resulting in a maximum of 10 points. Both the reliability (r = 0.53) and relative validity (r = 0.43) were deemed sufficient to consider the diet score as a stable construct in future investigations. This new diet score can be a promising tool to investigate dietary intake in etiological research by concentrating on 10 key dietary determinants with evidence-based prevention potential for chronic diseases.
Background
Teleost fishes comprise more than half of the vertebrate species. Within teleosts, most phylogenies consider the split between Osteoglossomorpha and Euteleosteomorpha/Otomorpha as basal, preceded only by the derivation of the most primitive group of teleosts, the Elopomorpha. While Osteoglossomorpha are generally species poor, the taxon contains the African weakly electric fish (Mormyroidei), which have radiated into numerous species. Within the mormyrids, the genus Campylomormyrus is mostly endemic to the Congo Basin. Campylomormyrus serves as a model to understand mechanisms of adaptive radiation and ecological speciation, especially with regard to its highly diverse species-specific electric organ discharges (EOD). Currently, there are few well-annotated genomes available for electric fish in general and mormyrids in particular. Our study aims at producing a high-quality genome assembly and to use this to examine genome evolution in relation to other teleosts. This will facilitate further understanding of the evolution of the osteoglossomorpha fish in general and of electric fish in particular.
Results
A high-quality weakly electric fish (C. compressirostris) genome was produced from a single individual with a genome size of 862 Mb, consisting of 1,497 contigs with an N50 of 1,399 kb and a GC-content of 43.69%. Gene predictions identified 34,492 protein-coding genes, which is a higher number than in the two other available Osteoglossomorpha genomes of Paramormyrops kingsleyae and Scleropages formosus. A Computational Analysis of gene Family Evolution (CAFE5) comparing 33 teleost fish genomes suggests an overall faster gene family turnover rate in Osteoglossomorpha than in Otomorpha and Euteleosteomorpha. Moreover, the ratios of expanded/contracted gene family numbers in Osteoglossomorpha are significantly higher than in the other two taxa, except for species that had undergone an additional genome duplication (Cyprinus carpio and Oncorhynchus mykiss). As potassium channel proteins are hypothesized to play a key role in EOD diversity among species, we put a special focus on them, and manually curated 16 Kv1 genes. We identified a tandem duplication in the KCNA7a gene in the genome of C. compressirostris.
Conclusions
We present the fourth genome of an electric fish and the third well-annotated genome for Osteoglossomorpha, enabling us to compare gene family evolution among major teleost lineages. Osteoglossomorpha appear to exhibit rapid gene family evolution, with more gene family expansions than contractions. The curated Kv1 gene family showed seven gene clusters, which is more than in other analyzed fish genomes outside Osteoglossomorpha. The KCNA7a, encoding for a potassium channel central for EOD production and modulation, is tandemly duplicated which may related to the diverse EOD observed among Campylomormyrus species.
Almost one third of global drylands are open forests and savannas, which are typically shaped by frequent natural disturbances such as wildfire and herbivory. Studies on ecosystem functions and services of woody vegetation require robust estimates of aboveground biomass (AGB). However, most methods have been developed for comparatively undisturbed forest ecosystems. As they are not tailored to accurately quantify AGB of small and irregular growth forms, their application on these growth forms may lead to unreliable or even biased AGB estimates in disturbance-prone dryland ecosystems. Moreover, these methods cannot quantify AGB losses caused by disturbance agents. Here we propose a methodology to estimate individual-and stand-level woody AGB in disturbance-prone ecosystems. It consists of flexible field sampling routines and estimation workflows for six growth classes, delineated by size and damage criteria. It also comprises a detailed damage assessment, harnessing the ecological archive of woody growth for past disturbances.
Based on large inventories collected along steep gradients of elephant disturbances in African dryland ecosystems, we compared the AGB estimates generated with our proposed method against estimates from a less adapted forest inventory method. We evaluated the necessary stepwise procedures of method adaptation and analyzed each step's effect on stand-level AGB estimation. We further explored additional advantages of our proposed method with regard to disturbance impact quantification. Results indicate that a majority of growth forms and individuals in savanna vegetation could only be assessed if methods of AGB estimation were adapted to the conditions of a disturbance-prone ecosystem. Furthermore, our damage assessment demonstrated that one third to half of all woody AGB was lost to disturbances. Consequently, less adapted methods may be insufficient and are likely to render inaccurate AGB estimations.
Our proposed method has the potential to accurately quantify woody AGB in disturbance-prone ecosystems, as well as AGB losses. Our method is more time consuming than conventional allometric approaches, yet it can cover sufficient areas within reasonable timespans, and can also be easily adapted to alternative sampling schemes.
By using an integrative approach, we describe a new species of mayfly, Bungona (Chopralla) pontica sp. n., from Turkey. The discovery of a representative of the tropical mayfly genus Bungona in the Middle East is rather unexpected. The new species shows all the main morphological characters of the subgenus Chopralla, which has its closest related species occurring in southeastern Asia. Barcoding clearly indicated that the new species represents an independent lineage isolated for a very long time from other members of the complex. The claw is equipped with two rows of three or four flattened denticles. This condition is a unique feature of Bungona (Chopralla) pontica sp. n. among West Palaearctic mayfly species. Within the subgenus Chopralla, the species can be identified by the presence of a simple, not bifid right prostheca (also present only in Bungona (Chopralla) liebenauae (Soldan, Braasch & Muu, 1987)), the shape of the labial palp, and the absence of protuberances on pronotum.
Nitraria is a halophytic taxon (i.e., adapted to saline environments) that belongs to the plant family Nitrariaceae and is distributed from the Mediterranean, across Asia into the south-eastern tip of Australia. This taxon is thought to have originated in Asia during the Paleogene (66-23 Ma), alongside the proto-Paratethys epicontinental sea. The evolutionary history of Nitraria might hold important clues on the links between climatic and biotic evolution but limited taxonomic documentation of this taxon has thus far hindered this line of research. Here we investigate if the pollen morphology and the chemical composition of the pollen wall are informative of the evolutionary history of Nitraria and could explain if origination along the proto-Paratethys and dispersal to the Tibetan Plateau was simultaneous or a secondary process. To answer these questions, we applied a novel approach consisting of a combination of Fourier Transform Infrared spectroscopy (FTIR), to determine the chemical composition of the pollen wall, and pollen morphological analyses using Light Microscopy (LM) and Scanning Electron Microscopy (SEM). We analysed our data using ordinations (principal components analysis and non-metric multidimensional scaling), and directly mapped it on the Nitrariaceae phylogeny to produce a phylomorphospace and a phylochemospace. Our LM, SEM and FTIR analyses show clear morphological and chemical differences between the sister groups Peganum and Nitraria. Differences in the morphological and chemical characteristics of highland species (Nitraria schoberi, N. sphaerocarpa, N. sibirica and N. tangutorum) and lowland species (Nitraria billardierei and N. retusa) are very subtle, with phylogenetic history appearing to be a more important control on Nitraria pollen than local environmental conditions. Our approach shows a compelling consistency between the chemical and morphological characteristics of the eight studied Nitrariaceae species, and these traits are in agreement with the phylogenetic tree. Taken together, this demonstrates how novel methods for studying fossil pollen can facilitate the evolutionary investigation of living and extinct taxa, and the environments they represent.
Most biochemical reactions depend on the pH value of the aqueous environment and some are strongly favoured to occur in an acidic environment. A non-invasive control of pH to tightly regulate such reactions with defined start and end points is a highly desirable feature in certain applications, but has proven difficult to achieve so far. We report a novel optical approach to reversibly control a typical biochemical reaction by changing the pH and using acid phosphatase as a model enzyme. The reversible photoacid G-acid functions as a proton donor, changing the pH rapidly and reversibly by using high power UV LEDs as an illumination source in our experimental setup. The reaction can be tightly controlled by simply switching the light on and off and should be applicable to a wide range of other enzymatic reactions, thus enabling miniaturization and parallelization through non-invasive optical means.
Remote sensing plays an increasingly key role in the determination of soil organic carbon (SOC) stored in agriculturally managed topsoils at the regional and field scales. Contemporary Unmanned Aerial Systems (UAS) carrying low-cost and lightweight multispectral sensors provide high spatial resolution imagery (<10 cm). These capabilities allow integrate of UAS-derived soil data and maps into digitalized workflows for sustainable agriculture. However, the common situation of scarce soil data at field scale might be an obstacle for accurate digital soil mapping. In our case study we tested a fixed-wing UAS equipped with visible and near infrared (VIS-NIR) sensors to estimate topsoil SOC distribution at two fields under the constraint of limited sampling points, which were selected by pedological knowledge. They represent all releva nt soil types along an erosion-deposition gradient; hence, the full feature space in terms of topsoils' SOC status. We included the Topographic Position Index (TPI) as a co-variate for SOC prediction. Our study was performed in a soil landscape of hummocky ground moraines, which represent a significant of global arable land. Herein, small scale soil variability is mainly driven by tillage erosion which, in turn, is strongly dependent on topography. Relationships between SOC, TPI and spectral information were tested by Multiple Linear Regression (MLR) using: (i) single field data (local approach) and (ii) data from both fields (pooled approach). The highest prediction performance determined by a leave-one-out-cross-validation (LOOCV) was obtained for the models using the reflectance at 570 nm in conjunction with the TPI as explanatory variables for the local approach (coefficient of determination (R-2) = 0.91; root mean square error (RMSE) = 0.11% and R-2 = 0.48; RMSE = 0.33, respectively). The local MLR models developed with both reflectance and TPI using values from all points showed high correlations and low prediction errors for SOC content (R-2 = 0.88, RMSE = 0.07%; R-2 = 0.79, RMSE = 0.06%, respectively). The comparison with an enlarged dataset consisting of all points from both fields (pooled approach) showed no improvement of the prediction accuracy but yielded decreased prediction errors. Lastly, the local MLR models were applied to the data of the respective other field to evaluate the cross-field prediction ability. The spatial SOC pattern generally remains unaffected on both fields; differences, however, occur concerning the predicted SOC level. Our results indicate a high potential of the combination of UAS-based remote sensing and environmental covariates, such as terrain attributes, for the prediction of topsoil SOC content at the field scale. The temporal flexibility of UAS offer the opportunity to optimize flight conditions including weather and soil surface status (plant cover or residuals, moisture and roughness) which, otherwise, might obscure the relationship between spectral data and SOC content. Pedologically targeted selection of soil samples for model development appears to be the key for an efficient and effective prediction even with a small dataset.
Bacteria swim in sequences of straight runs that are interrupted by turning events. They drive their swimming locomotion with the help of rotating helical flagella. Depending on the number of flagella and their arrangement across the cell body, different run-and-turn patterns can be observed. Here, we present fluorescence microscopy recordings showing that cells of the soil bacterium Pseudomonas putida that are decorated with a polar tuft of helical flagella, can alternate between two distinct swimming patterns. On the one hand, they can undergo a classical push-pull-push cycle that is well known from monopolarly flagellated bacteria but has not been reported for species with a polar bundle of multiple flagella. Alternatively, upon leaving the pulling mode, they can enter a third slow swimming phase, where they propel themselves with their helical bundle wrapped around the cell body. A theoretical estimate based on a random-walk model shows that the spreading of a population of swimmers is strongly enhanced when cycling through a sequence of pushing, pulling, and wrapped flagellar configurations as compared to the simple push-pull-push pattern.
Background
There is consistent evidence that the COVID-19 pandemic is associated with an increased psychosocial burden on children and adolescents and their parents. Relatively little is known about its particular impact on high-risk groups with chronic physical health conditions (CCs). Therefore, the primary aim of the study is to analyze the multiple impacts on health care and psychosocial well-being on these children and adolescents and their parents.
Methods
We will implement a two-stage approach. In the first step, parents and their underage children from three German patient registries for diabetes, obesity, and rheumatic diseases, are invited to fill out short questionnaires including questions about corona-specific stressors, the health care situation, and psychosocial well-being. In the next step, a more comprehensive, in-depth online survey is carried out in a smaller subsample.
Discussion
The study will provide insights into the multiple longer-term stressors during the COVID-19 pandemic in families with a child with a CC. The simultaneous consideration of medical and psycho-social endpoints will help to gain a deeper understanding of the complex interactions affecting family functioning, psychological well-being, and health care delivery.
The computation of such synthetic GFs is computationally and operationally demanding. As a consequence, the onthe-fly recalculation of synthetic GFs in each iteration of an optimisation is time-consuming and impractical. Therefore, the pre-calculation and efficient storage of synthetic GFs on a dense grid of source to receiver combinations enables the efficient lookup and utilisation of GFs in time-critical scenarios. We present a Python-based framework and toolkit - Pyrocko-GF - that enables the pre-calculation of synthetic GF stores, which are independent of their numerical calculation method and GF transfer function. The framework aids in the creation of such GF stores by interfacing a suite of established numerical forward modelling codes in seismology (computational back ends). So far, interfaces to back ends for layered Earth model cases have been provided; however, the architecture of Pyrocko-GF is designed to cover back ends for other geometries (e.g. full 3-D heterogeneous media) and other physical quantities (e.g. gravity, pressure, tilt). Therefore, Pyrocko-GF defines an extensible GF storage format suitable for a wide range of GF types, especially handling elasticity and wave propagation problems. The framework assists with visualisations, quality control, and the exchange of GF stores, which is supported through an online platform that provides many pre-calculated GF stores for local, regional, and global studies. The Pyrocko-GF toolkit comes with a well-documented application programming interface (API) for the Python programming language to efficiently facilitate forward modelling of geophysical processes, e.g. synthetic waveforms or static displacements for a wide range of source models.
A review of source models to further the understanding of the seismicity of the Groningen field
(2022)
The occurrence of felt earthquakes due to gas production in Groningen has initiated numerous studies and model attempts to understand and quantify induced seismicity in this region. The whole bandwidth of available models spans the range from fully deterministic models to purely empirical and stochastic models. In this article, we summarise the most important model approaches, describing their main achievements and limitations. In addition, we discuss remaining open questions and potential future directions of development.
Obligate human pathogenic Neisseria gonorrhoeae are the second most frequent bacterial cause of sexually transmitted diseases. These bacteria invade different mucosal tissues and occasionally disseminate into the bloodstream. Invasion into epithelial cells requires the activation of host cell receptors by the formation of ceramide-rich platforms. Here, we investigated the role of sphingosine in the invasion and intracellular survival of gonococci. Sphingosine exhibited an anti-gonococcal activity in vitro. We used specific sphingosine analogs and click chemistry to visualize sphingosine in infected cells. Sphingosine localized to the membrane of intracellular gonococci. Inhibitor studies and the application of a sphingosine derivative indicated that increased sphingosine levels reduced the intracellular survival of gonococci. We demonstrate here, that sphingosine can target intracellular bacteria and may therefore exert a direct bactericidal effect inside cells.
Changes in the steepness of river profiles or abrupt vertical steps (i.e. waterfalls) are thought to be indicative of changes in erosion rates, lithology or other factors that affect landscape evolution. These changes are referred to as knickpoints or knickzones and are pervasive in bedrock river systems. Such features are thought to reveal information about landscape evolution and patterns of erosion, and therefore their locations are often reported in the geomorphic literature. It is imperative that studies reporting knickpoints and knickzones use a reproducible method of quantifying their locations, as their number and spatial distribution play an important role in interpreting tectonically active landscapes. In this contribution we introduce a reproducible knickpoint and knickzone extraction algorithm that uses river profiles transformed by integrating drainage area along channel length (the so-called integral or chi method). The profile is then statistically segmented and the differing slopes and step changes in the elevations of these segments are used to identify knickpoints, knickzones and their relative magnitudes. The output locations of identified knickpoints and knickzones compare favourably with human mapping: we test the method on Santa Cruz Island, CA, using previously reported knickzones and also test the method against a new dataset from the Quadrilatero Ferrifero in Brazil. The algorithm allows for the extraction of varying knickpoint morphologies, including stepped, positive slope-break (concave upward) and negative slope-break knickpoints. We identify parameters that most affect the resulting knickpoint and knickzone locations and provide guidance for both usage and outputs of the method to produce reproducible knickpoint datasets.
Both ice sheets in Greenland and Antarctica are discharging ice into the ocean. In many regions along the coast of the ice sheets, the icebergs calve into a bay. If the addition of icebergs through calving is faster than their transport out of the embayment, the icebergs will be frozen into a melange with surrounding sea ice in winter. In this case, the buttressing effect of the ice melange can be considerably stronger than any buttressing by mere sea ice would be. This in turn stabilizes the glacier terminus and leads to a reduction in calving rates. Here we propose a simple parametrization of ice melange buttressing which leads to an upper bound on calving rates and can be used in numerical and analytical modelling.
Over large coastal regions in Greenland and Antarctica the ice sheet calves directly into the ocean. In contrast to ice-shelf calving, an increase in calving from grounded glaciers contributes directly to sea-level rise. Ice cliffs with a glacier freeboard larger than approximate to 100 m are currently not observed, but it has been shown that such ice cliffs are increasingly unstable with increasing ice thickness. This cliff calving can constitute a self-amplifying ice loss mechanism that may significantly alter sea-level projections both of Greenland and Antarctica. Here we seek to derive a minimalist stress-based parametrization for cliff calving from grounded glaciers whose freeboards exceed the 100m stability limit derived in previous studies. This will be an extension of existing calving laws for tidewater glaciers to higher ice cliffs. To this end we compute the stress field for a glacier with a simplified two-dimensional geometry from the two-dimensional Stokes equation. First we assume a constant yield stress to derive the failure region at the glacier front from the stress field within the glacier. Secondly, we assume a constant response time of ice failure due to exceedance of the yield stress. With this strongly constraining but very simple set of assumptions we propose a cliff-calving law where the calving rate follows a power-law dependence on the freeboard of the ice with exponents between 2 and 3, depending on the relative water depth at the calving front. The critical freeboard below which the ice front is stable decreases with increasing relative water depth of the calving front. For a dry water front it is, for example, 75 m. The purpose of this study is not to provide a comprehensive calving law but to derive a particularly simple equation with a transparent and minimalist set of assumptions.
Higher eco-efficiency will not be enough to slow global warming caused by climate change. To keep global warming to 2 degrees, people also need to reduce their consumption. At present, however, many who would be able to do so seem unwilling to comply. Given the threats of a runaway climate change, urgent measures are needed to promote less personal consumption. This study, therefore, examines whether social marketing consume-less appeals can be used to encourage consumers to voluntarily abstain from consumption. As part of an online experiment with nearly 2000 randomly sampled users of an online platform for sustainable consumption, we tested the effectiveness of five different “consume-less” appeals based on traditional advertising formats (including emotional, informational, and social claims). The study shows that consume-less appeals are capable of limiting personal desire to buy. However, significant differences in the effectiveness of the appeal formats used in this study were observed. In addition, we found evidence of rebound effects, which leads us to critically evaluate the overall potential of social marketing to promote more resource-conserving lifestyles. While commercial consumer-free appeals have previously been studied (e.g., Patagonia’s “Don’t Buy This Jacked”), this study on the effectiveness of non-commercial consume-free appeals is novel and provides new insights.
Mineral resource exploration and mining is an essential part of today's high-tech industry. Elements such as rare-earth elements (REEs) and copper are, therefore, in high demand. Modern exploration techniques from multiple platforms (e.g., spaceborne and airborne), to detect and map the spectral characteristics of the materials of interest, require spectral libraries as an essential reference. They include field and laboratory spectral information in combination with geochemical analyses for validation. Here, we present a collection of REE- and copper-related hyperspectral spectra with associated geochemical information. The libraries contain reflectance spectra from rare-earth element oxides, REE-bearing minerals, copper-bearing minerals and mine surface samples from the Apliki copper-gold-pyrite mine in the Republic of Cyprus. The samples were measured with the HySpex imaging spectrometers in the visible and near infrared (VNIR) and shortwave infrared (SWIR) range (400-2500 nm). The geochemical validation of each sample is provided with the reflectance spectra. The spectral libraries are openly available to assist future mineral mapping campaigns and laboratory spectroscopic analyses. The spectral libraries and corresponding geochemistry are published via GFZ Data Services with the following DOIs: https://doi.org/10.5880/GFZ.1.4.2019.004 (13 REE-bearing minerals and 16 oxide powders, Koerting et al., 2019a), https://doi.org/10.5880/GFZ.1.4.2019.003 (20 copper-bearing minerals, Koellner et al., 2019), and https://doi.org/10.5880/GFZ.1.4.2019.005 (37 copper-bearing surface material samples from the Apliki coppergold-pyrite mine in Cyprus, Koerting et al., 2019b). All spectral libraries are united and comparable by the internally consistent method of hyperspectral data acquisition in the laboratory.
Both ground- and satellite-based airglow imaging have significantly contributed to understanding the low-latitude ionosphere, especially the morphology and dynamics of the equatorial ionization anomaly (EIA). The NASA Global-scale Observations of the Limb and Disk (GOLD) mission focuses on far-ultraviolet airglow images from a geostationary orbit at 47.5 degrees W. This region is of particular interest at low magnetic latitudes because of the high magnetic declination (i.e., about -20 degrees) and proximity of the South Atlantic magnetic anomaly. In this study, we characterize an exciting feature of the nighttime EIA using GOLD observations from October 5, 2018 to June 30, 2020. It consists of a wavelike structure of a few thousand kilometers seen as poleward and equatorward displacements of the EIA-crests. Initial analyses show that the synoptic-scale structure is symmetric about the dip equator and appears nearly stationary with time over the night. In quasi-dipole coordinates, maxima poleward displacements of the EIA-crests are seen at about +/- 12 degrees latitude and around 20 and 60 degrees longitude (i.e., in geographic longitude at the dip equator, about 53 degrees W and 14 degrees W). The wavelike structure presents typical zonal wavelengths of about 6.7 x 10(3) km and 3.3 x 10(3) km. The structure's occurrence and wavelength are highly variable on a day-to-day basis with no apparent dependence on geomagnetic activity. In addition, a cluster or quasi-periodic wave train of equatorial plasma depletions (EPDs) is often detected within the synoptic-scale structure. We further outline the difference in observing these EPDs from FUV images and in situ measurements during a GOLD and Swarm mission conjunction.
In clinical practice, only a few reliable measurement instruments are available for monitoring knee joint rehabilitation. Advances to replace motion capturing with sensor data measurement have been made in the last years. Thus, a systematic review of the literature was performed, focusing on the implementation, diagnostic accuracy, and facilitators and barriers of integrating wearable sensor technology in clinical practices based on a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. For critical appraisal, the COSMIN Risk of Bias tool for reliability and measurement of error was used. PUBMED, Prospero, Cochrane database, and EMBASE were searched for eligible studies. Six studies reporting reliability aspects in using wearable sensor technology at any point after knee surgery in humans were included. All studies reported excellent results with high reliability coefficients, high limits of agreement, or a few detectable errors. They used different or partly inappropriate methods for estimating reliability or missed reporting essential information. Therefore, a moderate risk of bias must be considered. Further quality criterion studies in clinical settings are needed to synthesize the evidence for providing transparent recommendations for the clinical use of wearable movement sensors in knee joint rehabilitation.
Sustainable development goals (SDGs) have set the 2030 agenda to transform our world by tackling multiple challenges humankind is facing to ensure well-being, economic prosperity, and environmental protection. In contrast to conventional development agendas focusing on a restricted set of dimensions, the SDGs provide a holistic and multidimensional view on development. Hence, interactions among the SDGs may cause diverging results. To analyze the SDG interactions we systematize the identification of synergies and trade-offs using official SDG indicator data for 227 countries. A significant positive correlation between a pair of SDG indicators is classified as a synergy while a significant negative correlation is classified as a trade-off. We rank synergies and trade-offs between SDGs pairs on global and country scales in order to identify the most frequent SDG interactions. For a given SDG, positive correlations between indicator pairs were found to outweigh the negative ones in most countries. Among SDGs the positive and negative correlations between indicator pairs allowed for the identification of particular global patterns. SDG 1 (No poverty) has synergetic relationship with most of the other goals, whereas SDG 12 (Responsible consumption and production) is the goal most commonly associated with trade-offs. The attainment of the SDG agenda will greatly depend on whether the identified synergies among the goals can be leveraged. In addition, the highlighted trade-offs, which constitute obstacles in achieving the SDGs, need to be negotiated and made structurally nonobstructive by deeper changes in the current strategies.
We present a prototype of an integrated reasoning environment for educational purposes. The presented tool is a fragment of a proof assistant and automated theorem prover. We describe the existing and planned functionality of the theorem prover and especially the functionality of the educational fragment. This currently supports working with terms of the untyped lambda calculus and addresses both undergraduate students and researchers. We show how the tool can be used to support the students' understanding of functional programming and discuss general problems related to the process of building theorem proving software that aims at supporting both research and education.
We present a new algorithm for solving the common problem of flow trapped in closed depressions within digital elevation models, as encountered in many applications relying on flow routing. Unlike other approaches (e.g., the Priority-Flood depression filling algorithm), this solution is based on the explicit computation of the flow paths both within and across the depressions through the construction of a graph connecting together all adjacent drainage basins. Although this represents many operations, a linear time complexity can be reached for the whole computation, making it very efficient. Compared to the most optimized solutions proposed so far, we show that this algorithm of flow path enforcement yields the best performance when used in landscape evolution models. In addition to its efficiency, our proposed method also has the advantage of letting the user choose among different strategies of flow path enforcement within the depressions (i.e., filling vs. carving). Furthermore, the computed graph of basins is a generic structure that has the potential to be reused for solving other problems as well, such as the simulation of erosion. This sequential algorithm may be helpful for those who need to, e.g., process digital elevation models of moderate size on single computers or run batches of simulations as part of an inference study.
Continental rift systems form by propagation of isolated rift segments that interact, and eventually evolve into continuous zones of deformation. This process impacts many aspects of rifting including rift morphology at breakup, and eventual ocean-ridge segmentation. Yet, rift segment growth and interaction remain enigmatic. Here we present geological data from the poorly documented Ririba rift (South Ethiopia) that reveals how two major sectors of the East African rift, the Kenyan and Ethiopian rifts, interact. We show that the Ririba rift formed from the southward propagation of the Ethiopian rift during the Pliocene but this propagation was short-lived and aborted close to the Pliocene-Pleistocene boundary. Seismicity data support the abandonment of laterally offset, overlapping tips of the Ethiopian and Kenyan rifts. Integration with new numerical models indicates that rift abandonment resulted from progressive focusing of the tectonic and magmatic activity into an oblique, throughgoing rift zone of near pure extension directly connecting the rift sectors.
In this paper, we propose a consistent mechanism of protein microcapsule formation upon ultrasound treatment. Aqueous suspensions of bovine serum albumin (BSA) microcapsules filled with toluene are prepared by use of high-intensity ultrasound following a reported method. Stabilization of the oil-in-water emulsion by the adsorption of the protein molecules at the interface of the emulsion droplets is accompanied by the creation of the cross-linked capsule shell due to formation of intermolecular disulfide bonds caused by highly reactive species like superoxide radicals generated sonochemically. The evidence for this mechanism, which until now remained elusive and was not proven properly, is presented based on experimental data from SDS-PAGE, Raman spectroscopy and dynamic light scattering.
Identifying abrupt transitions is a key question in various disciplines. Existing transition detection methods, however, do not rigorously account for time series uncertainties, often neglecting them altogether or assuming them to be independent and qualitatively similar. Here, we introduce a novel approach suited to handle uncertainties by representing the time series as a time-ordered sequence of probability density functions. We show how to detect abrupt transitions in such a sequence using the community structure of networks representing probabilities of recurrence. Using our approach, we detect transitions in global stock indices related to well-known periods of politico-economic volatility. We further uncover transitions in the El Niño-Southern Oscillation which coincide with periods of phase locking with the Pacific Decadal Oscillation. Finally, we provide for the first time an ‘uncertainty-aware’ framework which validates the hypothesis that ice-rafting events in the North Atlantic during the Holocene were synchronous with a weakened Asian summer monsoon.
We study the diffusive motion of a particle in a subharmonic potential of the form U(x) = |x|( c ) (0 < c < 2) driven by long-range correlated, stationary fractional Gaussian noise xi ( alpha )(t) with 0 < alpha <= 2. In the absence of the potential the particle exhibits free fractional Brownian motion with anomalous diffusion exponent alpha. While for an harmonic external potential the dynamics converges to a Gaussian stationary state, from extensive numerical analysis we here demonstrate that stationary states for shallower than harmonic potentials exist only as long as the relation c > 2(1 - 1/alpha) holds. We analyse the motion in terms of the mean squared displacement and (when it exists) the stationary probability density function. Moreover we discuss analogies of non-stationarity of Levy flights in shallow external potentials.
Classroom noise impairs students' cognition and learning. At a first glance, it seems useful to prevent the negative effects of noise on academic learning by wearing noise-cancelling (NC) headphones during class. The literature and guidelines emphasize the academic benefits of wearing NC headphones (decreased auditory distraction, increased concentration, learning improvement, and decreased distress). These benefits are particularly expected for students with special needs. None of the recommendations to wear NC headphones during class refer to any empirical studies, indicating a potential research gap and lack of evidence. Therefore, the question arises: Is there any empirical evidence supporting academic benefits of wearing NC headphones during class for typically developing students or students with special needs? A total of 13 empirical studies (quantitative and qualitative) were identified through a systematic scoping review of the existing literature. A wide range of outcomes (cognition, learning, academic performance, behaviour, and emotions) were reported related to the use of NC headphones. Most of the studies refer to specific groups of students with special needs (learning disabilities, autism, ADHD, etc.). In view of the limited number of studies, small sample sizes, and lack of replication studies, all studies give the impression of being pilot studies on the academic benefits of wearing NC headphones. The practice of wearing NC headphones during class is an understudied topic. The current body of evidence does not meet the standards for evidence-based practices in both general and special education. Implications for educational practice and future research are discussed.
Digital terrain models (DTMs) are a fundamental source of information in Earth sciences. DTM-based studies, however, can contain remarkable biases if limitations and inaccuracies in these models are disregarded. In this work, four freely available datasets, including Shuttle Radar Topography Mission C-Band Synthetic Aperture Radar (SRTM C-SAR V3 DEM), Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Map (ASTER GDEM V2), and two nationwide airborne light detection and ranging (LiDAR)-derived DTMs (at 5-m and 1-m spatial resolution, respectively) were analysed in three geomorphologically contrasting, small (3–5 km2) catchments located in Mediterranean landscapes under intensive human influence (Mallorca Island, Spain). Vertical accuracy as well as the influence of each dataset’s characteristics on hydrological and geomorphological modelling applicability were assessed by using ground-truth data, classic geometric and morphometric parameters, and a recently proposed index of sediment connectivity. Overall vertical accuracy—expressed as the root mean squared error (RMSE) and normalised median deviation (NMAD)—revealed the highest accuracy for the 1-m (RMSE = 1.55 m; NMAD = 0.44 m) and 5-m LiDAR DTMs (RMSE = 1.73 m; NMAD = 0.84 m). Vertical accuracy of the SRTM data was lower (RMSE = 6.98 m; NMAD = 5.27 m), but considerably higher than for the ASTER data (RMSE = 16.10 m; NMAD = 11.23 m). All datasets were affected by systematic distortions. Propagation of these errors and coarse horizontal resolution caused negative impacts on flow routing, stream network, and catchment delineation, and to a lower extent, on the distribution of slope values. These limitations should be carefully considered when applying DTMs for catchment hydrogeomorphological modelling.
Farber disease is a rare lysosomal storage disorder resulting from acid ceramidase deficiency and subsequent ceramide accumulation. No treatments for Farber disease are clinically available, and affected patients have a severely shortened lifespan. We have recently reported a novel acid ceramidase deficiency model that mirrors the human disease closely. Acid sphingomyelinase is the enzyme that generates ceramide upstream of acid ceramidase in the lysosomes. Using our acid ceramidase deficiency model, we tested if acid sphingomyelinase could be a potential novel therapeutic target for the treatment of Farber disease. A number of functional acid sphingomyelinase inhibitors are clinically available and have been used for decades to treat major depression. Using these as a therapeutic for Farber disease, thus, has the potential to improve central nervous symptoms of the disease as well, something all other treatment options for Farber disease can’t achieve so far. As a proof-of-concept study, we first cross-bred acid ceramidase deficient mice with acid sphingomyelinase deficient mice in order to prevent ceramide accumulation. Double-deficient mice had reduced ceramide accumulation, fewer disease manifestations, and prolonged survival. We next targeted acid sphingomyelinase pharmacologically, to test if these findings would translate to a setting with clinical applicability. Surprisingly, the treatment of acid ceramidase deficient mice with the acid sphingomyelinase inhibitor amitriptyline was toxic to acid ceramidase deficient mice and killed them within a few days of treatment. In conclusion, our study provides the first proof-of-concept that acid sphingomyelinase could be a potential new therapeutic target for Farber disease to reduce disease manifestations and prolong survival. However, we also identified previously unknown toxicity of the functional acid sphingomyelinase inhibitor amitriptyline in the context of Farber disease, strongly cautioning against the use of this substance class for Farber disease patients.
The purpose of this study was to examine the acute effects of short-term Achilles tendon vibration on plantar flexor torque, twitch contractile properties as well as muscle and cortical activity in young athletes. Eleven female elite soccer players aged 15.6 +/- 0.5 years participated in this study. Three different conditions were applied in randomized order: Achilles tendon vibration (80 Hz) for 30 and 300 s, and a passive control condition (300 s). Tests at baseline and following conditions included the assessment of peak plantar flexor torque during maximum voluntary contraction, electrically evoked muscle twitches (e.g., potentiated twitch peak torque [PT]), and electromyographic (EMG) activity of the plantar flexors. Additionally, electroencephalographic (EEG) activity of the primary motor and somatosensory cortex were assessed during a submaximal dynamic concentric-eccentric plantar flexion exercise using an elastic rubber band. Large-sized main effects of condition were found for EEG absolute alpha-1 and beta-1 band power (p <= 0.011; 1.5 <= d <= 2.6). Post-hoc tests indicated that alpha-1 power was significantly lower at 30 and 300 s (p = 0.009; d = 0.8) and beta-1 power significantly lower at 300 s (p < 0.001; d = 0.2) compared to control condition. No significant effect of condition was found for peak plantar flexor torque, electrical evoked muscle twitches, and EMG activity. In conclusion, short-term local Achilles tendon vibration induced lower brain activity (i.e., alpha-1 and beta-1 band power) but did not affect lower limb peak torque, twitch contractile properties, and muscle activity. Lower brain activity following short-term local Achilles tendon vibration may indicate improved cortical function during a submaximal dynamic exercise in female young soccer players.
Earth’s surface temperature will continue to rise for another 20 to 30 years even with the strongest carbon emission reduction currently considered. The associated changes in rainfall patterns can result in an increased flood risk worldwide. We compute the required increase in flood protection to keep high-end fluvial flood risk at present levels. The analysis is carried out worldwide for subnational administrative units. Most of the United States, Central Europe, and Northeast and West Africa, as well as large parts of India and Indonesia, require the strongest adaptation effort. More than half of the United States needs to at least double their protection within the next two decades. Thus, the need for adaptation to increased river flood is a global problem affecting industrialized regions as much as developing countries.
Flood risk management in Germany follows an integrative approach in which both private households and businesses can make an important contribution to reducing flood damage by implementing property-level adaptation measures. While the flood adaptation behavior of private households has already been widely researched, comparatively less attention has been paid to the adaptation strategies of businesses. However, their ability to cope with flood risk plays an important role in the social and economic development of a flood-prone region. Therefore, using quantitative survey data, this study aims to identify different strategies and adaptation drivers of 557 businesses damaged by a riverine flood in 2013 and 104 businesses damaged by pluvial or flash floods between 2014 and 2017. Our results indicate that a low perceived self-efficacy may be an important factor that can reduce the motivation of businesses to adapt to flood risk. Furthermore, property-owners tended to act more proactively than tenants. In addition, high experience with previous flood events and low perceived response costs could strengthen proactive adaptation behavior. These findings should be considered in business-tailored risk communication.
Adaptation to flood risk
(2017)
As flood impacts are increasing in large parts of the world, understanding the primary drivers of changes in risk is essential for effective adaptation. To gain more knowledge on the basis of empirical case studies, we analyze eight paired floods, that is, consecutive flood events that occurred in the same region, with the second flood causing significantly lower damage. These success stories of risk reduction were selected across different socioeconomic and hydro-climatic contexts. The potential of societies to adapt is uncovered by describing triggered societal changes, as well as formal measures and spontaneous processes that reduced flood risk. This novel approach has the potential to build the basis for an international data collection and analysis effort to better understand and attribute changes in risk due to hydrological extremes in the framework of the IAHSs Panta Rhei initiative. Across all case studies, we find that lower damage caused by the second event was mainly due to significant reductions in vulnerability, for example, via raised risk awareness, preparedness, and improvements of organizational emergency management. Thus, vulnerability reduction plays an essential role for successful adaptation. Our work shows that there is a high potential to adapt, but there remains the challenge to stimulate measures that reduce vulnerability and risk in periods in which extreme events do not occur.