Uncertainty quantification for severe-accident reactor modelling: Set-up and first results of the Horizon-2020 project MUSA

The current Horizon-2020 project on “Management and Uncertainties of Severe Accidents (MUSA)” aims at applying Uncertainty Quantification (UQ) in the modelling of Severe Accidents (SA), particularly in predicting the radiological source term of mitigated and unmitigated accident reactor scenarios. A selected number of severe accident sequences of different nuclear power plant designs (e.g. PWR, VVER, and BWR) are addressed. The application of the Best Estimate Plus Uncertainty (BEPU) methodology to reactor accident scenarios requires a number of key steps: (i) the selection of severe accident sequences for each reactor design; (ii) the development of a reference input model for the specific design and SA-code; (iii) the definition of the figures of merit for the UQ-analysis; (iv) the selection of a list of uncertain model parameters to be investigated; (v) the choice of a statistical tool to propagate input deck uncertainties; (vi) the selection of a feasible approach (i.e., Monte Carlo versus order statistics) to address UQ by using a statistical software (i.e., UQ-tools DAKOTA, SUSA, URANIE, etc.); (vii) the running phase to achieve a high number of successful realizations with the SA codes; and, (viii) the statistical evaluation of the results (i.e., sensitivity analysis). This paper describes each of these steps such as settled in the reactor applications work package of the EU MUSA project and pays particular attention to the choices made by partners. It presents preliminary results also with an emphasis on the major challenges posed by BEPU application in the field of SA analysis

Higher songs of city birds may not be an individual response to noise

It has been observed in many songbird species that populations in noisy urban areas sing with a higher minimum frequency than do matched populations in quieter, less developed areas. However, why and how this divergence occurs is not yet understood. We experimentally tested whether chronic noise exposure during vocal learning results in songs with higher minimum frequencies in great tits (Parus major), the first species for which a correlation between anthropogenic noise and song frequency was observed. We also tested vocal plasticity of adult great tits in response to changing background noise levels by measuring song frequency and amplitude as we changed noise conditions. We show that noise exposure during ontogeny did not result in songs with higher minimum frequencies. In addition, we found that adult birds did not make any frequency or song usage adjustments when their background noise conditions were changed after song crystallization. These results challenge the common view of vocal adjustments by city birds, as they suggest that either noise itself is not the causal force driving the divergence of song frequency between urban and forest populations, or that noise induces population-wide changes over a time scale of several generations rather than causing changes in individual behaviour

Effects of Pollination Method and Growing Location on Starch Thermal Properties of Corn Hybrids

Starch gelatinization and retrogradation properties of corn were studied to determine the effect of controlled (self) pollination versus noncontrolled pollination on analytical determinations, and the potential to eliminate the expensive and time-consuming step of self-pollinating before research screening of corn genotypes. Twenty-four hybrids were grown in two Iowa locations, Story City and Ames. At Story City, all hybrids received three pollination treatments: self-pollination; small-plot, openpollination (representing corn from small test plots); and large-plot, openpollination (representing corn from a farmer\u27s field). Self-pollinated and small-plot, open-pollinated corn were grown in replicated two-row plots, whereas large-plot, open-pollinated corn was grown in unreplicated plots of 12.8 m × 8 rows. At Ames, the small-plot, open pollination treatment was not done. Starch was extracted from samples of corn harvested from each plot, and gelatinization and retrogradation properties were determined using differential-scanning calorimetry (DSC). Hybrids exhibited different starch gelatinization and retrogradation properties. Significant differences (P ≤ 0.05) in starch gelatinization and retrogradation properties occurred among pollination methods and between locations. Pollination method did not influence gelatinization enthalpy values, but onset temperature values for gelatinization, and range values for retrogradation differed significantly among pollination methods. At Ames, treatments gave different values for retrogradation enthalpy and percentage of retrogradation. Because of differences in some starch characteristics associated with pollination methods, self-pollination is recommended when growing samples in small plots for research purposes

oPOSSUM: identification of over-represented transcription factor binding sites in co-expressed genes

Targeted transcript profiling studies can identify sets of co-expressed genes; however, identification of the underlying functional mechanism(s) is a significant challenge. Established methods for the analysis of gene annotations, particularly those based on the Gene Ontology, can identify functional linkages between genes. Similar methods for the identification of over-represented transcription factor binding sites (TFBSs) have been successful in yeast, but extension to human genomics has largely proved ineffective. Creation of a system for the efficient identification of common regulatory mechanisms in a subset of co-expressed human genes promises to break a roadblock in functional genomics research. We have developed an integrated system that searches for evidence of co-regulation by one or more transcription factors (TFs). oPOSSUM combines a pre-computed database of conserved TFBSs in human and mouse promoters with statistical methods for identification of sites over-represented in a set of co-expressed genes. The algorithm successfully identified mediating TFs in control sets of tissue-specific genes and in sets of co-expressed genes from three transcript profiling studies. Simulation studies indicate that oPOSSUM produces few false positives using empirically defined thresholds and can tolerate up to 50% noise in a set of co-expressed genes

Noise Pollution Filters Bird Communities Based on Vocal Frequency

BACKGROUND: Human-generated noise pollution now permeates natural habitats worldwide, presenting evolutionarily novel acoustic conditions unprecedented to most landscapes. These acoustics not only harm humans, but threaten wildlife, and especially birds, via changes to species densities, foraging behavior, reproductive success, and predator-prey interactions. Explanations for negative effects of noise on birds include disruption of acoustic communication through energetic masking, potentially forcing species that rely upon acoustic communication to abandon otherwise suitable areas. However, this hypothesis has not been adequately tested because confounding stimuli often co-vary with noise and are difficult to separate from noise exposure. METHODOLOGY/PRINCIPAL FINDINGS: Using a natural experiment that controls for confounding stimuli, we evaluate whether species vocal features or urban-tolerance classifications explain their responses to noise measured through habitat use. Two data sets representing nesting and abundance responses reveal that noise filters bird communities nonrandomly. Signal duration and urban tolerance failed to explain species-specific responses, but birds with low-frequency signals that are more susceptible to masking from noise avoided noisy areas and birds with higher frequency vocalizations remained. Signal frequency was also negatively correlated with body mass, suggesting that larger birds may be more sensitive to noise due to the link between body size and vocal frequency. CONCLUSIONS/SIGNIFICANCE: Our findings suggest that acoustic masking by noise may be a strong selective force shaping the ecology of birds worldwide. Larger birds with lower frequency signals may be excluded from noisy areas, whereas smaller species persist via transmission of higher frequency signals. We discuss our findings as they relate to interspecific relationships among body size, vocal amplitude and frequency and suggest that they are immediately relevant to the global problem of increases in noise by providing critical insight as to which species traits influence tolerance of these novel acoustics

Habitat-related birdsong divergence: a multi-level study on the influence of territory density and ambient noise in European blackbirds

Song plays an important role in avian communication and acoustic variation is important at both the individual and population level. Habitat-related variation between populations in particular can reflect adaptations to the environment accumulated over generations, but this may not always be the case. In this study, we test whether variation between individuals matches local conditions with respect to noise level and territory density to examine whether short-term flexibility could contribute to song divergence at the population level. We conducted a case study on an urban and forest population of the European blackbird and show divergence at the population level (i.e. across habitats) in blackbird song, anthropogenic noise level and territory density. Unlike in several other species, we found a lack of any correlation at the individual level (i.e. across individuals) between song features and ambient noise. This suggests species-specific causal explanations for noise-dependent song differentiation which are likely associated with variation in song-copying behaviour or feedback constraints related to variable singing styles. On the other hand, we found that at the level of individual territories, temporal features, but not spectral ones, are correlated to territory density and seasonality. This suggests that short-term individual variation can indeed contribute to habitat-dependent divergence at the population level. As this may undermine the potential role for song as a population marker, we conclude that more investigations on individual song flexibility are required for a better understanding of the impact of population-level song divergence on hybridisation and speciation

Diversity in sound pressure levels and estimated active space of resident killer whale vocalizations

Author Posting. © The Author, 2005. This is the author's version of the work. It is posted here by permission of Springer for personal use, not for redistribution. The definitive version was published in Journal of Comparative Physiology A: Sensory, Neural, and Behavioral Physiology 192 (2006): 449-459, doi:10.1007/s00359-005-0085-2.Signal source intensity and detection range, which integrates source intensity with propagation loss, background noise and receiver hearing abilities, are important characteristics of communication signals. Apparent source levels were calculated for 819 pulsed calls and 24 whistles produced by free-ranging resident killer whales by triangulating the angles-of-arrival of sounds on two beamforming arrays towed in series. Levels in the 1-20 kHz band ranged from 131-168 dB re 1μPa @1m, with differences in the means of different sound classes (whistles: 140.2 ± 4.1 dB; variable calls: 146.6 ± 6.6 dB; stereotyped calls: 152.6 ± 5.9 dB), and among stereotyped call types. Repertoire diversity carried through to estimates of active space, with “long-range” stereotyped calls all containing overlapping, independently-modulated high-frequency components (mean estimated active space of 10-16km in sea state zero) and “short-range” sounds (5-9 km) included all stereotyped calls without a high-frequency component, whistles, and variable calls. Short-range sounds are reported to be more common during social and resting behaviors, while long-range stereotyped calls predominate in dispersed travel and foraging behaviors. These results suggest that variability in sound pressure levels may reflect diverse social and ecological functions of the acoustic repertoire of killer whales.Funding was provided by WHOI’s Ocean Ventures Fund and Rinehart Coastal Research Center and a Royal Society fellowship