Refine
Has Fulltext
- yes (70)
Year of publication
- 2015 (70) (remove)
Language
- English (70)
Keywords
- climate-change (4)
- New-Zealand (3)
- carbon (3)
- evolution (3)
- model (3)
- variability (3)
- Escherichia coli (2)
- Laptev Sea (2)
- Siberia (2)
- agriculture (2)
Institute
- Mathematisch-Naturwissenschaftliche Fakultät (70) (remove)
The Net Reclassification Improvement (NRI) has become a popular metric for evaluating improvement in disease prediction models through the past years. The concept is relatively straightforward but usage and interpretation has been different across studies. While no thresholds exist for evaluating the degree of improvement, many studies have relied solely on the significance of the NRI estimate. However, recent studies recommend that statistical testing with the NRI should be avoided. We propose using confidence ellipses around the estimated values of event and non-event NRIs which might provide the best measure of variability around the point estimates. Our developments are illustrated using practical examples from EPIC-Potsdam study.
A flexible approach to assess fluorescence decay functions in complex energy transfer systems
(2015)
Background: Time-correlated Forster resonance energy transfer (FRET) probes molecular distances with greater accuracy than intensity-based calculation of FRET efficiency and provides a powerful tool to study biomolecular structure and dynamics. Moreover, time-correlated photon count measurements bear additional information on the variety of donor surroundings allowing more detailed differentiation between distinct structural geometries which are typically inaccessible to general fitting solutions.
Results: Here we develop a new approach based on Monte Carlo simulations of time-correlated FRET events to estimate the time-correlated single photon counts (TCSPC) histograms in complex systems. This simulation solution assesses the full statistics of time-correlated photon counts and distance distributions of fluorescently labeled biomolecules. The simulations are consistent with the theoretical predictions of the dye behavior in FRET systems with defined dye distances and measurements of randomly distributed dye solutions. We validate the simulation results using a highly heterogeneous aggregation system and explore the conditions to use this tool in complex systems.
Conclusion: This approach is powerful in distinguishing distance distributions in a wide variety of experimental setups, thus providing a versatile tool to accurately distinguish between different structural assemblies in highly complex systems.
Climate change and its impacts already pose considerable challenges for societies that will further increase with global warming (IPCC, 2014a, b). Uncertainties of the climatic response to greenhouse gas emissions include the potential passing of large-scale tipping points (e.g. Lenton et al., 2008; Levermann et al., 2012; Schellnhuber, 2010) and changes in extreme meteorological events (Field et al., 2012) with complex impacts on societies (Hallegatte et al., 2013). Thus climate change mitigation is considered a necessary societal response for avoiding uncontrollable impacts (Conference of the Parties, 2010). On the other hand, large-scale climate change mitigation itself implies fundamental changes in, for example, the global energy system. The associated challenges come on top of others that derive from equally important ethical imperatives like the fulfilment of increasing food demand that may draw on the same resources. For example, ensuring food security for a growing population may require an expansion of cropland, thereby reducing natural carbon sinks or the area available for bio-energy production. So far, available studies addressing this problem have relied on individual impact models, ignoring uncertainty in crop model and biome model projections. Here, we propose a probabilistic decision framework that allows for an evaluation of agricultural management and mitigation options in a multi-impact-model setting. Based on simulations generated within the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), we outline how cross-sectorally consistent multi-model impact simulations could be used to generate the information required for robust decision making.
Using an illustrative future land use pattern, we discuss the trade-off between potential gains in crop production and associated losses in natural carbon sinks in the new multiple crop-and biome-model setting. In addition, crop and water model simulations are combined to explore irrigation increases as one possible measure of agricultural intensification that could limit the expansion of cropland required in response to climate change and growing food demand. This example shows that current impact model uncertainties pose an important challenge to long-term mitigation planning and must not be ignored in long-term strategic decision making.
Background: Medical training is very demanding and associated with a high prevalence of psychological distress. Compared to the general population, medical students are at a greater risk of developing a psychological disorder. Various attempts of stress management training in medical school have achieved positive results on minimizing psychological distress; however, there are often limitations. Therefore, the use of a rigorous scientific method is needed. The present study protocol describes a randomized controlled trial to examine the effectiveness of a specifically developed mindfulness-based stress prevention training for medical students that includes selected elements of cognitive behavioral strategies (MediMind).
Methods/Design: This study protocol presents a prospective randomized controlled trial, involving four assessment time points: baseline, post-intervention, one-year follow-up and five-year follow-up. The aims include evaluating the effect on stress, coping, psychological morbidity and personality traits with validated measures. Participants are allocated randomly to one of three conditions: MediMind, Autogenic Training or control group. Eligible participants are medical or dental students in the second or eighth semester of a German university. They form a population of approximately 420 students in each academic term. A final total sample size of 126 (at five-year follow-up) is targeted. The trainings (MediMind and Autogenic Training) comprise five weekly sessions lasting 90 minutes each. MediMind will be offered to participants of the control group once the five-year follow-up is completed. The allotment is randomized with a stratified allocation ratio by course of studies, semester, and gender. After descriptive statistics have been evaluated, inferential statistical analysis will be carried out with a repeated measures ANOVA-design with interactions between time and group. Effect sizes will be calculated using partial η-square values.
Discussion: Potential limitations of this study are voluntary participation and the risk of attrition, especially concerning participants that are allocated to the control group. Strengths are the study design, namely random allocation, follow-up assessment, the use of control groups and inclusion of participants at different stages of medical training with the possibility of differential analysis.
Abstract gringo
(2015)
This paper defines the syntax and semantics of the input language of the ASP grounder gringo. The definition covers several constructs that were not discussed in earlier work on the semantics of that language, including intervals, pools, division of integers, aggregates with non-numeric values, and lparse-style aggregate expressions. The definition is abstract in the sense that it disregards some details related to representing programs by strings of ASCII characters. It serves as a specification for gringo from Version 4.5 on.
Inventories of individually delineated landslides are a key to understanding landslide physics and mitigating their impact. They permit assessment of area–frequency distributions and landslide volumes, and testing of statistical correlations between landslides and physical parameters such as topographic gradient or seismic strong motion. Amalgamation, i.e. the mapping of several adjacent landslides as a single polygon, can lead to potentially severe distortion of the statistics of these inventories. This problem can be especially severe in data sets produced by automated mapping. We present five inventories of earthquake-induced landslides mapped with different materials and techniques and affected by varying degrees of amalgamation. Errors on the total landslide volume and power-law exponent of the area–frequency distribution, resulting from amalgamation, may be up to 200 and 50%, respectively. We present an algorithm based on image and digital elevation model (DEM) analysis, for automatic identification of amalgamated polygons. On a set of about 2000 polygons larger than 1000 m2, tracing landslides triggered by the 1994 Northridge earthquake, the algorithm performs well, with only 2.7–3.6% incorrectly amalgamated landslides missed and 3.9–4.8% correct polygons incorrectly identified as amalgams. This algorithm can be used broadly to check landslide inventories and allow faster correction by automating the identification of amalgamation.
aspeed
(2015)
Although Boolean Constraint Technology has made tremendous progress over the last decade, the efficacy of state-of-the-art solvers is known to vary considerably across different types of problem instances, and is known to depend strongly on algorithm parameters. This problem was addressed by means of a simple, yet effective approach using handmade, uniform, and unordered schedules of multiple solvers in ppfolio, which showed very impressive performance in the 2011 Satisfiability Testing (SAT) Competition. Inspired by this, we take advantage of the modeling and solving capacities of Answer Set Programming (ASP) to automatically determine more refined, that is, nonuniform and ordered solver schedules from the existing benchmarking data. We begin by formulating the determination of such schedules as multi-criteria optimization problems and provide corresponding ASP encodings. The resulting encodings are easily customizable for different settings, and the computation of optimum schedules can mostly be done in the blink of an eye, even when dealing with large runtime data sets stemming from many solvers on hundreds to thousands of instances. Also, the fact that our approach can be customized easily enabled us to swiftly adapt it to generate parallel schedules for multi-processor machines.
The transmission of wildlife zoonoses to humans depends, amongst others, on complex interactions of host population ecology and pathogen dynamics within host populations. In Europe, the Puumala virus (PUUV) causes nephropathia epidemica in humans. In this study we investigated complex interrelations within the epidemic system of PUUV and its rodent host, the bank vole (Myodes glareolus). We suggest that beech fructification and bank vole abundance are both decisive factors affecting human PUUV infections. While rodent host dynamics are expected to be directly linked to human PUUV infections, beech fructification is a rather indirect predictor by serving as food source for PUUV rodent hosts. Furthermore, we examined the dependence of bank vole abundance on beech fructification. We analysed a 12-year (2001-2012) time series of the parameters: beech fructification (as food resource for the PUUV host), bank vole abundance and human incidences from 7 Federal States of Germany. For the first time, we could show the direct interrelation between these three parameters involved in human PUUV epidemics and we were able to demonstrate on a large scale that human PUUV infections are highly correlated with bank vole abundance in the present year, as well as beech fructification in the previous year. By using beech fructification and bank vole abundance as predictors in one model we significantly improved the degree of explanation of human PUUV incidence. Federal State was included as random factor because human PUUV incidence varies considerably among states. Surprisingly, the effect of rodent abundance on human PUUV infections is less strong compared to the indirect effect of beech fructification. Our findings are useful to facilitate the development of predictive models for host population dynamics and the related PUUV infection risk for humans and can be used for plant protection and human health protection purposes.
Brief communication
(2015)
Accelerating climate change and increased economic and environmental interests in permafrost-affected regions have resulted in an acute need for more directed permafrost research. In June 2014, 88 early career researchers convened to identify future priorities for permafrost research. This multidisciplinary forum concluded that five research topics deserve greatest attention: permafrost landscape dynamics, permafrost thermal modeling, integration of traditional knowledge, spatial distribution of ground ice, and engineering issues. These topics underline the need for integrated research across a spectrum of permafrost-related domains and constitute a contribution to the Third International Conference on Arctic Research Planning (ICARP III).
The nitric oxide (NO)/soluble guanylate cyclase (sGC)/cyclic guanosine monophasphate (cGMP)-signalling pathway is impaired under oxidative stress conditions due to oxidation and subsequent loss of the prosthetic sGC heme group as observed in particular in chronic renal failure. Thus, the pool of heme free sGC is increased under pathological conditions. sGC activators such as cinaciguat selectively activate the heme free form of sGC and target the disease associated enzyme. In this study, a therapeutic effect of long-term activation of heme free sGC by the sGC activator cinaciguat was investigated in an experimental model of salt-sensitive hypertension, a condition that is associated with increased oxidative stress, heme loss from sGC and development of chronic renal failure. For that purpose Dahl/ss rats, which develop severe hypertension upon high salt intake, were fed a high salt diet (8% NaCl) containing either placebo or cinaciguat for 21 weeks. Cinaciguat markedly improved survival and ameliorated the salt-induced increase in blood pressure upon treatment with cinaciguat compared to placebo. Renal function was significantly improved in the cinaciguat group compared to the placebo group as indicated by a significantly improved glomerular filtration rate and reduced urinary protein excretion. This was due to anti-fibrotic and antiinflammatory effects of the cinaciguat treatment. Taken together, this is the first study showing that long-term activation of heme free sGC leads to renal protection in an experimental model of hypertension and chronic kidney disease. These results underline the promising potential of cinaciguat to treat renal diseases by targeting the disease associated heme free form of sGC.
Climate impacts on transocean dispersal and habitat in gray whales from the Pleistocene to 2100
(2015)
Arctic animals face dramatic habitat alteration due to ongoing climate change. Understanding how such species have responded to past glacial cycles can help us forecast their response to today's changing climate. Gray whales are among those marine species likely to be strongly affected by Arctic climate change, but a thorough analysis of past climate impacts on this species has been complicated by lack of information about an extinct population in the Atlantic. While little is known about the history of Atlantic gray whales or their relationship to the extant Pacific population, the extirpation of the Atlantic population during historical times has been attributed to whaling. We used a combination of ancient and modern DNA, radiocarbon dating and predictive habitat modelling to better understand the distribution of gray whales during the Pleistocene and Holocene. Our results reveal that dispersal between the Pacific and Atlantic was climate dependent and occurred both during the Pleistocene prior to the last glacial period and the early Holocene immediately following the opening of the Bering Strait. Genetic diversity in the Atlantic declined over an extended interval that predates the period of intensive commercial whaling, indicating this decline may have been precipitated by Holocene climate or other ecological causes. These first genetic data for Atlantic gray whales, particularly when combined with predictive habitat models for the year 2100, suggest that two recent sightings of gray whales in the Atlantic may represent the beginning of the expansion of this species' habitat beyond its currently realized range.
Closing yield gaps
(2015)
Global food production needs to be increased by 60-110% between 2005 and 2050 to meet growing food and feed demand. Intensification and/or expansion of agriculture are the two main options available to meet the growing crop demands. Land conversion to expand cultivated land increases GHG emissions and impacts biodiversity and ecosystem services. Closing yield gaps to attain potential yields may be a viable option to increase the global crop production. Traditional methods of agricultural intensification often have negative externalities. Therefore, there is a need to explore location-specific methods of sustainable agricultural intensification. We identified regions where the achievement of potential crop calorie production on currently cultivated land will meet the present and future food demand based on scenario analyses considering population growth and changes in dietary habits. By closing yield gaps in the current irrigated and rain-fed cultivated land, about 24% and 80% more crop calories can respectively be produced compared to 2000. Most countries will reach food self-sufficiency or improve their current food self-sufficiency levels if potential crop production levels are achieved. As a novel approach, we defined specific input and agricultural management strategies required to achieve the potential production by overcoming biophysical and socioeconomic constraints causing yield gaps. The management strategies include: fertilizers, pesticides, advanced soil management, land improvement, management strategies coping with weather induced yield variability, and improving market accessibility. Finally, we estimated the required fertilizers (N, P2O5, and K2O) to attain the potential yields. Globally, N-fertilizer application needs to increase by 45-73%, P2O5-fertilizer by 22-46%, and K2O-fertilizer by 2-3 times compared to the year 2010 to attain potential crop production. The sustainability of such agricultural intensification largely depends on the way management strategies for closing yield gaps are chosen and implemented.
Based on niche theory, closely related and morphologically similar species are not predicted to coexist due to overlap in resource and habitat use. Local assemblages of bats often contain cryptic taxa, which co-occur despite notable similarities in morphology and ecology. We measured in two different habitat types on Madagascar levels of stable carbon and nitrogen isotopes in hair (n = 103) and faeces (n = 57) of cryptic Vespertilionidae taxa to indirectly examine whether fine-grained trophic niche differentiation explains their coexistence. In the dry deciduous forest (Kirindy), six sympatric species ranged over 6.0% in delta N-15, i.e. two trophic levels, and 4.2% in delta C-13 with a community mean of 11.3% in delta N-15 and - 21.0% in delta C-13. In the mesic forest (Antsahabe), three sympatric species ranged over one trophic level (delta N-15: 2.4%, delta C-13: 1.0%) with a community mean of 8.0% delta N-15 and - 21.7% in delta C-13. Multivariate analyses and residual permutation of Euclidian distances in delta C-13- delta N-15 bi-plots revealed in both communities distinct stable isotope signatures and species separation for the hair samples among coexisting Vespertilionidae. Intraspecific variation in faecal and hair stable isotopes did not indicate that seasonal migration might relax competition and thereby facilitate the local co-occurrence of sympatric taxa.
Solving problems combining task and motion planning requires searching across a symbolic search space and a geometric search space. Because of the semantic gap between symbolic and geometric representations, symbolic sequences of actions are not guaranteed to be geometrically feasible. This compels us to search in the combined search space, in which frequent backtracks between symbolic and geometric levels make the search inefficient. We address this problem by guiding symbolic search with rich information extracted from the geometric level through culprit detection mechanisms.
Small scale distribution of insect root herbivores may promote plant species diversity by creating patches of different herbivore pressure. However, determinants of small scale distribution of insect root herbivores, and impact of land use intensity on their small scale distribution are largely unknown. We sampled insect root herbivores and measured vegetation parameters and soil water content along transects in grasslands of different management intensity in three regions in Germany. We calculated community-weighted mean plant traits to test whether the functional plant community composition determines the small scale distribution of insect root herbivores. To analyze spatial patterns in plant species and trait composition and insect root herbivore abundance we computed Mantel correlograms. Insect root herbivores mainly comprised click beetle (Coleoptera, Elateridae) larvae (43%) in the investigated grasslands. Total insect root herbivore numbers were positively related to community-weighted mean traits indicating high plant growth rates and biomass (specific leaf area, reproductive-and vegetative plant height), and negatively related to plant traits indicating poor tissue quality (leaf C/N ratio). Generalist Elaterid larvae, when analyzed independently, were also positively related to high plant growth rates and furthermore to root dry mass, but were not related to tissue quality. Insect root herbivore numbers were not related to plant cover, plant species richness and soil water content. Plant species composition and to a lesser extent plant trait composition displayed spatial autocorrelation, which was not influenced by land use intensity. Insect root herbivore abundance was not spatially autocorrelated. We conclude that in semi-natural grasslands with a high share of generalist insect root herbivores, insect root herbivores affiliate with large, fast growing plants, presumably because of availability of high quantities of food. Affiliation of insect root herbivores with large, fast growing plants may counteract dominance of those species, thus promoting plant diversity.
Winter storms are the most costly natural hazard for European residential property. We compare four distinct storm damage functions with respect to their forecast accuracy and variability, with particular regard to the most severe winter storms. The analysis focuses on daily loss estimates under differing spatial aggregation, ranging from district to country level. We discuss the broad and heavily skewed distribution of insured losses posing difficulties for both the calibration and the evaluation of damage functions. From theoretical considerations, we provide a synthesis between the frequently discussed cubic wind–damage relationship and recent studies that report much steeper damage functions for European winter storms. The performance of the storm loss models is evaluated for two sources of wind gust data, direct observations by the German Weather Service and ERA-Interim reanalysis data. While the choice of gust data has little impact on the evaluation of German storm loss, spatially resolved coefficients of variation reveal dependence between model and data choice. The comparison shows that the probabilistic models by Heneka et al. (2006) and Prahl et al. (2012) both provide accurate loss predictions for moderate to extreme losses, with generally small coefficients of variation. We favour the latter model in terms of model applicability. Application of the versatile deterministic model by Klawa and Ulbrich (2003) should be restricted to extreme loss, for which it shows the least bias and errors comparable to the probabilistic model by Prahl et al. (2012).
Efficacy, Safety & Modification of Albuminuria in Type 2 Diabetes Subjects with Renal Disease with LINAgliptin (MARLINA-T2D), a multicentre, multinational, randomized, double-blind, placebo-controlled, parallel-group, phase 3b clinical trial, aims to further define the potential renal effects of dipeptidyl peptidase-4 inhibition beyond glycaemic control. A total of 350 eligible individuals with inadequately controlled type 2 diabetes and evidence of renal disease are planned to be randomized in a 1:1 ratio to receive either linagliptin 5mg or placebo in addition to their stable glucose-lowering background therapy for 24weeks. Two predefined main endpoints will be tested in a hierarchical manner: (1) change from baseline in glycated haemoglobin and (2) time-weighted average of percentage change from baseline in urinary albumin-to-creatinine ratio. Both endpoints are sufficiently powered to test for superiority versus placebo after 24weeks with =0.05. MARLINA-T2D is the first of its class to prospectively explore both the glucose- and albuminuria-lowering potential of a dipeptidyl peptidase-4 inhibitor in patients with type 2 diabetes and evidence of renal disease.
In this paper we propose an algorithm to distinguish between light- and heavy-tailed probability laws underlying random datasets. The idea of the algorithm, which is visual and easy to implement, is to check whether the underlying law belongs to the domain of attraction of the Gaussian or non-Gaussian stable distribution by examining its rate of convergence. The method allows to discriminate between stable and various non-stable distributions. The test allows to differentiate between distributions, which appear the same according to standard Kolmogorov-Smirnov test. In particular, it helps to distinguish between stable and Student's t probability laws as well as between the stable and tempered stable, the cases which are considered in the literature as very cumbersome. Finally, we illustrate the procedure on plasma data to identify cases with so-called L-H transition.
Thermal permafrost degradation and coastal erosion in the Arctic remobilize substantial amounts of organic carbon (OC) and nutrients which have accumulated in late Pleistocene and Holocene unconsolidated deposits. Permafrost vulnerability to thaw subsidence, collapsing coastlines and irreversible landscape change are largely due to the presence of large amounts of massive ground ice such as ice wedges. However, ground ice has not, until now, been considered to be a source of dissolved organic carbon (DOC), dissolved inorganic carbon (DIC) and other elements which are important for ecosystems and carbon cycling. Here we show, using biogeochemical data from a large number of different ice bodies throughout the Arctic, that ice wedges have the greatest potential for DOC storage, with a maximum of 28.6 mg L-1 (mean: 9.6 mg L-1). Variation in DOC concentration is positively correlated with and explained by the concentrations and relative amounts of typically terrestrial cations such as Mg2+ and K+. DOC sequestration into ground ice was more effective during the late Pleistocene than during the Holocene, which can be explained by rapid sediment and OC accumulation, the prevalence of more easily degradable vegetation and immediate incorporation into permafrost. We assume that pristine snowmelt is able to leach considerable amounts of well-preserved and highly bioavailable DOC as well as other elements from surface sediments, which are rapidly frozen and stored in ground ice, especially in ice wedges, even before further degradation. We found that ice wedges in the Yedoma region represent a significant DOC (45.2 Tg) and DIC (33.6 Tg) pool in permafrost areas and a freshwater reservoir of 4200 km(2). This study underlines the need to discriminate between particulate OC and DOC to assess the availability and vulnerability of the permafrost car-bon pool for ecosystems and climate feedback upon mobilization.
Dual-normal logic programs
(2015)
Disjunctive Answer Set Programming is a powerful declarative programming paradigm with complexity beyond NP. Identifying classes of programs for which the consistency problem is in NP is of interest from the theoretical standpoint and can potentially lead to improvements in the design of answer set programming solvers. One of such classes consists of dual-normal programs, where the number of positive body atoms in proper rules is at most one. Unlike other classes of programs, dual-normal programs have received little attention so far. In this paper we study this class. We relate dual-normal programs to propositional theories and to normal programs by presenting several inter-translations. With the translation from dual-normal to normal programs at hand, we introduce the novel class of body-cycle free programs, which are in many respects dual to head-cycle free programs. We establish the expressive power of dual-normal programs in terms of SE- and UE-models, and compare them to normal programs. We also discuss the complexity of deciding whether dual-normal programs are strongly and uniformly equivalent.