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  1. There is growing concern about sensory pollutants affecting ecological communities. Anthropogenically enhanced oxidants [ozone (O3) and nitrate radicals (NO3)] rapidly degrade floral scents, potentially reducing pollinator attraction to flowers. However, the physiological and behavioral impacts on pollinators and plant fitness are unknown. Using a nocturnal flower-moth system, we found that atmospherically relevant concentrations of NO3eliminate flower visitation by moths, and the reaction of NO3with a subset of monoterpenes is what reduces the scent’s attractiveness. Global atmospheric models of floral scent oxidation reveal that pollinators in certain urban areas may have a reduced ability to perceive and navigate to flowers. These results illustrate the impact of anthropogenic pollutants on an animal’s olfactory ability and indicate that such pollutants may be critical regulators of global pollination.

     
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    Free, publicly-accessible full text available February 9, 2025
  2. Infrastructure networks, such as electrical power grids, transportation and water supply systems, support critical societal functions of society. Failures of such networks can have severe consequences, and quantification of the probability of failure of such systems is essential for understanding and managing their reliability. Analytical and simulation methods have been proposed to solve such kinds of problems, among which sampling methods feature prominently. Recently, the authors extended widely used structural reliability algorithms, subset simulation, cross-entropy-based importance sampling as well as uncertainty quantification methods built from particle integration methods and exact confidence, all for efficient reliability analysis in discrete spaces. This paper tests the performance of these algorithms for static network reliability assessment. In particular, we compare these methods for optimal power flow problems in various IEEE benchmark models. Overall, the cross-entropy-based method outperforms the other methods in all benchmark models except the largest IEEE 300, while the adaptive effort subset simulation and particle integration methods are more suitable for handling high-dimensional problems. By building up the benchmark models, we provide unified examples for comparing different emerging methods in static network reliability assessment and also to support improvement or combination of these methods. 
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  3. ABSTRACT

    Along their path from source to observer, gravitational waves may be gravitationally lensed by massive objects leading to distortion in the signals. Searches for these distortions amongst the observed signals from the current detector network have already been carried out, though there have as yet been no confident detections. However, predictions of the observation rate of lensing suggest detection in the future is a realistic possibility. Therefore, preparations need to be made to thoroughly investigate the candidate lensed signals. In this work, we present some follow-up analyses that could be applied to assess the significance of such events and ascertain what information may be extracted about the lens-source system by applying these analyses to a number of O3 candidate events, even if these signals did not yield a high significance for any of the lensing hypotheses. These analyses cover the strong lensing, millilensing, and microlensing regimes. Applying these additional analyses does not lead to any additional evidence for lensing in the candidates that have been examined. However, it does provide important insight into potential avenues to deal with high-significance candidates in future observations.

     
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  4. null (Ed.)
    We present six new time-delay measurements obtained from R c -band monitoring data acquired at the Max Planck Institute for Astrophysics (MPIA) 2.2 m telescope at La Silla observatory between October 2016 and February 2020. The lensed quasars HE 0047−1756, WG 0214−2105, DES 0407−5006, 2M 1134−2103, PSJ 1606−2333, and DES 2325−5229 were observed almost daily at high signal-to-noise ratio to obtain high-quality light curves where we can record fast and small-amplitude variations of the quasars. We measured time delays between all pairs of multiple images with only one or two seasons of monitoring with the exception of the time delays relative to image D of PSJ 1606−2333. The most precise estimate was obtained for the delay between image A and image B of DES 0407−5006, where τ AB = −128.4 −3.8 +3.5 d (2.8% precision) including systematics due to extrinsic variability in the light curves. For HE 0047−1756, we combined our high-cadence data with measurements from decade-long light curves from previous COSMOGRAIL campaigns, and reach a precision of 0.9 d on the final measurement. The present work demonstrates the feasibility of measuring time delays in lensed quasars in only one or two seasons, provided high signal-to-noise ratio data are obtained at a cadence close to daily. 
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  5. Time-delay cosmography of lensed quasars has achieved 2.4% precision on the measurement of the Hubble constant, H 0 . As part of an ongoing effort to uncover and control systematic uncertainties, we investigate three potential sources: 1- stellar kinematics, 2- line-of-sight effects, and 3- the deflector mass model. To meet this goal in a quantitative way, we reproduced the H0LiCOW/SHARP/STRIDES (hereafter TDCOSMO) procedures on a set of real and simulated data, and we find the following. First, stellar kinematics cannot be a dominant source of error or bias since we find that a systematic change of 10% of measured velocity dispersion leads to only a 0.7% shift on H 0 from the seven lenses analyzed by TDCOSMO. Second, we find no bias to arise from incorrect estimation of the line-of-sight effects. Third, we show that elliptical composite (stars + dark matter halo), power-law, and cored power-law mass profiles have the flexibility to yield a broad range in H 0 values. However, the TDCOSMO procedures that model the data with both composite and power-law mass profiles are informative. If the models agree, as we observe in real systems owing to the “bulge-halo” conspiracy, H 0 is recovered precisely and accurately by both models. If the two models disagree, as in the case of some pathological models illustrated here, the TDCOSMO procedure either discriminates between them through the goodness of fit, or it accounts for the discrepancy in the final error bars provided by the analysis. This conclusion is consistent with a reanalysis of six of the TDCOSMO (real) lenses: the composite model yields H 0 = 74.0 −1.8 +1.7 km s −1 Mpc −1 , while the power-law model yields 74.2 −1.6 +1.6 km s −1 Mpc −1 . In conclusion, we find no evidence of bias or errors larger than the current statistical uncertainties reported by TDCOSMO. 
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