Leveraging Local Patch Differences in Multi-Object Scenes for Generative Adversarial Attacks

State-of-the-art generative model-based attacks against image classifiers overwhelmingly focus on single-object (i.e., single dominant object) images. Different from such settings, we tackle a more practical problem of generating adversarial perturbations using multi-object (i.e., multiple dominant objects) images as they are representative of most real-world scenes. Our goal is to design an attack strategy that can learn from such natural scenes by leveraging the local patch differences that occur inherently in such images (e.g. difference between the local patch on the object `person' and the object `bike' in a traffic scene). Our key idea is to misclassify an adversarial multi-object image by confusing the victim classifier for each local patch in the image. Based on this, we propose a novel generative attack (called Local Patch Difference or LPD-Attack) where a novel contrastive loss function uses the aforesaid local differences in feature space of multi-object scenes to optimize the perturbation generator. Through various experiments across diverse victim convolutional neural networks, we show that our approach outperforms baseline generative attacks with highly transferable perturbations when evaluated under different white-box and black-box settings.Comment: Accepted at WACV 2023 (Round 1), camera-ready versio

Comparing impacts of climate change on streamflow in four large African river basins

This study aims to compare impacts of climate change on streamflow in four large representative African river basins: the Niger, the Upper Blue Nile, the Oubangui and the Limpopo. We set up the eco-hydrological model SWIM (Soil and Water Integrated Model) for all four basins individually. The validation of the models for four basins shows results from adequate to very good, depending on the quality and availability of input and calibration data. For the climate impact assessment, we drive the model with outputs of five bias corrected Earth system models of Coupled Model Intercomparison Project Phase 5 (CMIP5) for the representative concentration pathways (RCPs) 2.6 and 8.5. This climate input is put into the context of climate trends of the whole African continent and compared to a CMIP5 ensemble of 19 models in order to test their representativeness. Subsequently, we compare the trends in mean discharges, seasonality and hydrological extremes in the 21st century. The uncertainty of results for all basins is high. Still, climate change impact is clearly visible for mean discharges but also for extremes in high and low flows. The uncertainty of the projections is the lowest in the Upper Blue Nile, where an increase in streamflow is most likely. In the Niger and the Limpopo basins, the magnitude of trends in both directions is high and has a wide range of uncertainty. In the Oubangui, impacts are the least significant. Our results confirm partly the findings of previous continental impact analyses for Africa. However, contradictory to these studies we find a tendency for increased streamflows in three of the four basins (not for the Oubangui). Guided by these results, we argue for attention to the possible risks of increasing high flows in the face of the dominant water scarcity in Africa. In conclusion, the study shows that impact intercomparisons have added value to the adaptation discussion and may be used for setting up adaptation plans in the context of a holistic approach

Multi-model climate impact assessment and intercomparison for three large-scale river basins on three continents

Climate change impacts on hydrological processes should be simulated for river basins using validated models and multiple climate scenarios in order to provide reliable results for stakeholders. In the last 10–15 years, climate impact assessment has been performed for many river basins worldwide using different climate scenarios and models. However, their results are hardly comparable, and do not allow one to create a full picture of impacts and uncertainties. Therefore, a systematic intercomparison of impacts is suggested, which should be done for representative regions using state-of-the-art models. Only a few such studies have been available until now with the global-scale hydrological models, and our study is intended as a step in this direction by applying the regional-scale models. The impact assessment presented here was performed for three river basins on three continents: the Rhine in Europe, the Upper Niger in Africa and the Upper Yellow in Asia. For that, climate scenarios from five general circulation models (GCMs) and three hydrological models, HBV, SWIM and VIC, were used. Four representative concentration pathways (RCPs) covering a range of emissions and land-use change projections were included. The objectives were to analyze and compare climate impacts on future river discharge and to evaluate uncertainties from different sources. The results allow one to draw some robust conclusions, but uncertainties are large and shared differently between sources in the studied basins. Robust results in terms of trend direction and slope and changes in seasonal dynamics could be found for the Rhine basin regardless of which hydrological model or forcing GCM is used. For the Niger River, scenarios from climate models are the largest uncertainty source, providing large discrepancies in precipitation, and therefore clear projections are difficult to do. For the Upper Yellow basin, both the hydrological models and climate models contribute to uncertainty in the impacts, though an increase in high flows in the future is a robust outcome ensured by all three hydrological models

Change in chirality of semiconducting single-walled carbon nanotubes can overcome anionic surfactant stabilisation: a systematic study of aggregation kinetics

Single-walled carbon nanotubes’ (SWNT) effectiveness in applications is enhanced by debundling or stabilisation. Anionic surfactants are known to effectively stabilise SWNTs. However, the role of specific chirality on surfactant-stabilised SWNT aggregation has not been studied to date. The aggregation behaviour of chirally enriched (6,5) and (7,6) semiconducting SWNTs, functionalised with three anionic surfactants – sodium dodecyl sulfate, sodium dodecyl benzene sulfonate and sodium deoxycholate – was evaluated with time-resolved dynamic light scattering. A wide range of mono- (NaCl) and divalent (CaCl2) electrolytes as well as a 2.5 mg total organic carbon (TOC) L–1 Suwannee River humic acid were used as background chemistry. Overall, sodium dodecyl benzene sulfonate showed the most effectiveness in stabilising SWNTs, followed by sodium deoxycholate and sodium dodecyl sulfate. However, the larger diameter (7,6) chirality tubes (compared to (6,5) diameter), compromised the surfactant stability due to enhanced van der Waals interaction. The presence of divalent electrolytes overshadowed the chirality effects and resulted in similar aggregation behaviour for both the SWNT samples. Molecular modelling results elucidated key differences in surfactant conformation on SWNT surfaces and identified interaction energy changes between the two chiralities to delineate aggregation mechanisms. The stability of SWNTs increased in the presence of Suwannee River humic acid under 10 mM monovalent and mixed-electrolyte conditions. The results suggest that change in chirality can overcome surfactant stabilisation of semiconducting SWNTs. SWNT stability can also be strongly influenced by the anionic surfactant structure

One simulation, different conclusions—the baseline period makes the difference!

The choice of the baseline period, intentionally chosen or not, as a reference for assessing future changes of any projected variable can play an important role for the resulting statement. In regional climate impact studies, well-established or arbitrarily chosen baselines are often used without being questioned. Here we investigated the effects of different baseline periods on the interpretation of discharge simulations from eight river basins in the period 1960–2099. The simulations were forced by four bias-adjusted and downscaled Global Climate Modelsunder two radiative forcing scenarios (RCP 2.6 and RCP 8.5). To systematically evaluate how far the choice of different baselines impacts the simulation results, we developed a similarity index that compares two time series of projected changes. The results show that 25% of the analyzed simulations are sensitive to the choice of the baseline period under RCP 2.6 and 32% under RCP 8.5. In extreme cases, change signals of two time series show opposite trends. This has serious consequences for key messages drawn from a basin-scale climate impact study. To address this problem, an algorithm was developed to identify flexible baseline periods for each simulation individually, which better represent the statistical properties of a given historical period

GW190521: A Binary Black Hole Merger with a Total Mass of 150 M

© 2020 authors. Published by the American Physical Society. On May 21, 2019 at 03:02:29 UTC Advanced LIGO and Advanced Virgo observed a short duration gravitational-wave signal, GW190521, with a three-detector network signal-to-noise ratio of 14.7, and an estimated false-alarm rate of 1 in 4900 yr using a search sensitive to generic transients. If GW190521 is from a quasicircular binary inspiral, then the detected signal is consistent with the merger of two black holes with masses of 85-14+21 Mm and 66-18+17 Mm (90% credible intervals). We infer that the primary black hole mass lies within the gap produced by (pulsational) pair-instability supernova processes, with only a 0.32% probability of being below 65 Mm. We calculate the mass of the remnant to be 142-16+28 Mm, which can be considered an intermediate mass black hole (IMBH). The luminosity distance of the source is 5.3-2.6+2.4 Gpc, corresponding to a redshift of 0.82-0.34+0.28. The inferred rate of mergers similar to GW190521 is 0.13-0.11+0.30 Gpc-3 yr-1