MeshAdv: Adversarial Meshes for Visual Recognition

Highly expressive models such as deep neural networks (DNNs) have been widely applied to various applications. However, recent studies show that DNNs are vulnerable to adversarial examples, which are carefully crafted inputs aiming to mislead the predictions. Currently, the majority of these studies have focused on perturbation added to image pixels, while such manipulation is not physically realistic. Some works have tried to overcome this limitation by attaching printable 2D patches or painting patterns onto surfaces, but can be potentially defended because 3D shape features are intact. In this paper, we propose meshAdv to generate "adversarial 3D meshes" from objects that have rich shape features but minimal textural variation. To manipulate the shape or texture of the objects, we make use of a differentiable renderer to compute accurate shading on the shape and propagate the gradient. Extensive experiments show that the generated 3D meshes are effective in attacking both classifiers and object detectors. We evaluate the attack under different viewpoints. In addition, we design a pipeline to perform black-box attack on a photorealistic renderer with unknown rendering parameters.Comment: Published in IEEE CVPR201

Three-dimensional Magnetic Restructuring in Two Homologous Solar Flares in the Seismically Active NOAA AR 11283

We carry out a comprehensive investigation comparing the three-dimensional magnetic field restructuring, flare energy release, and the helioseismic response, of two homologous flares, the 2011 September 6 X2.1 (FL1) and September 7 X1.8 (FL2) flares in NOAA AR 11283. In our analysis, (1) a twisted flux rope (FR) collapses onto the surface at a speed of 1.5 km/s after a partial eruption in FL1. The FR then gradually grows to reach a higher altitude and collapses again at 3 km/s after a fuller eruption in FL2. Also, FL2 shows a larger decrease of the flux-weighted centroid separation of opposite magnetic polarities and a greater change of the horizontal field on the surface. These imply a more violent coronal implosion with corresponding more intense surface signatures in FL2. (2) The FR is inclined northward, and together with the ambient fields, it undergoes a southward turning after both events. This agrees with the asymmetric decay of the penumbra observed in the peripheral regions. (3) The amounts of free magnetic energy and nonthermal electron energy released during FL1 are comparable to those of FL2 within the uncertainties of the measurements. (4) No sunquake was detected in FL1; in contrast, FL2 produced two seismic emission sources S1 and S2 both lying in the penumbral regions. Interestingly, S1 and S2 are connected by magnetic loops, and the stronger source S2 has weaker vertical magnetic field. We discuss these results in relation to the implosion process in the low corona and the sunquake generation.Comment: 12 pages, 9 figures, accepted to the Astrophysical Journa

Spatiotemporal Patterns of COVID-19 Impact on Human Activities and Environment in China Using Nighttime Light and Air Quality Data

In order to analyze the impact of COVID-19 on people's lives, activities and the natural environment, this paper investigates the spatial and temporal characteristics of Night Time Light (NTL) radiance and Air Quality Index (AQI) before and during the pandemic in mainland China. Our results show that the monthly average NTL brightness is much lower during the quarantine period than before. This study categorizes NTL into three classes: residential area, transportation and public facilities and commercial centers, with NTL radiance ranges of 5-20, 20-40 and greater than 40 nW/(cm*cm*sr), respectively. We found that the Number Of Pixels (NOP) with NTL detection increased in the residential area and decreased in the commercial centers for most of the provinces after the shutdown, while transportation and public facilities generally stayed the same. More specifically, we examined these factors in Wuhan, where the first confirmed cases were reported, and where the earliest quarantine measures were taken. Observations and analysis of pixels associated with commercial centers were observed to have lower NTL radiance values, indicating a dimming behavior, while residential area pixels recorded increased levels of brightness, after the beginning of the lockdown. The study also discovered a significant decreasing trend in the daily average AQI for the whole country, with cleaner air in most provinces during February and March, compared to January 2020. In conclusion, the outbreak and spread of COVID-19 has had a crucial impact on people's daily lives and activity ranges through the increased implementation of lockdown and quarantine policies. On the other hand, the air quality of China has improved with the reduction of non-essential industries and motor vehicle usage.Comment: 12 pages, 5 figure

Disruption of the Gene Encoding Endo-β-1, 4-Xylanase Affects the Growth and Virulence of Sclerotinia sclerotiorum

Sclerotinia sclerotiorum (Lib.) de Bary is a devastating fungal pathogen with worldwide distribution. S. sclerotiorum is a necrotrophic fungus that secretes many cell wall-degrading enzymes (CWDEs) that destroy plant’s cell-wall components. Functional analyses of the genes that encode CWEDs will help explain the mechanisms of growth and pathogenicity of S. sclerotiorum. Here, we isolated and characterized a gene SsXyl1 that encoded an endo-β-1, 4-xylanase in S. sclerotiorum. The SsXyl1 expression showed a slight increase during the development and germination stages of sclerotia and a dramatic increase during infection. The expression of SsXyl1 was induced by xylan. The SsXyl1 deletion strains produce aberrant sclerotia that could not germinate to form apothecia. The SsXyl1 deletion strains also lost virulence to the hosts. This study demonstrates the important roles of endo-β-1, 4-xylanase in the growth and virulence of S. sclerotiorum

Observation of a Large-scale Quasi-circular Secondary Ribbon associated with Successive Flares and a Halo CME

Solar flare ribbons provide an important clue to the magnetic reconnection process and associated magnetic field topology in the solar corona. We detected a large-scale secondary flare ribbon of a circular shape that developed in association with two successive M-class flares and one CME. The ribbon revealed interesting properties such as 1) a quasi-circular shape and enclosing the central active region; 2) the size as large as 500\arcsec\, by 650\arcsec\,, 3) successive brightenings in the clockwise direction at a speed of \kms{160} starting from the nearest position to the flaring sunspots, 4) radial contraction and expansion in the northern and the southern part, respectively at speeds of $\leq$ \kms{10}. Using multi-wavelength data from \textit{SDO}, \textit{RHESSI}, XRT, and Nobeyama, along with magnetic field extrapolations, we found that: 1) the secondary ribbon location is consistent with the field line footpoints of a fan-shaped magnetic structure that connects the flaring region and the ambient decaying field; 2) the second M2.6 flare occurred when the expanding coronal loops driven by the first M2.0 flare encountered the background decayed field. 3) Immediately after the second flare, the secondary ribbon developed along with dimming regions. Based on our findings, we suggest that interaction between the expanding sigmoid field and the overlying fan-shaped field triggered the secondary reconnection that resulted in the field opening and formation of the quasi-circular secondary ribbon. We thus conclude that interaction between the active region and the ambient large-scale fields should be taken into account to fully understand the entire eruption process.Comment: Accepted for publication in the ApJ, (20 pages, 13 figures

Benchmark Comparison of Cloud Analytics Methods Applied to Earth Observations

Earth Observation data are a vital resource for studying long term changes, but the large data volumes can be challenging to analyze. Time series analysis in particular is hampered by the typical thin-time-slice file organization. We examine several potential solutions inspired in large part by the data-parallel methods that have arisen with cloud computing. These solutions include various combinations of data re-organization, spatial indexing, distributed storage and pre-computation that we term "Analytics Optimized Data Stores" (AODS). We find that even simple solutions (such as a data cube) produce more than an order of magnitude improvement; the best provide two to three orders of magnitude improvement. The most performant solutions have tradeoffs in terms of generality or storage footprint, but may nonetheless be useful components in data analytics frameworks where performance is critical

Research on the emission reduction effects of carbon trading mechanism on power industry: plant-level evidence from China

Purpose Carbon trading mechanism has been adopted to foster the green transformation of the economy on a global scale, but its effectiveness for the power industry remains controversial. Given that energy-related greenhouse gas emissions account for most of all anthropogenic emissions, this paper aims to evaluate the effectiveness of this trading mechanism at the plant level to support relevant decision-making and mechanism design. Design/methodology/approach This paper constructs a novel spatiotemporal data set by matching satellite-based high-resolution (1 × 1 km) CO2 and PM2.5 emission data with accurate geolocation of power plants. It then applies a difference-in-differences model to analyse the impact of carbon trading mechanism on emission reduction for the power industry in China from 2007 to 2016. Findings Results suggest that the carbon trading mechanism induces 2.7% of CO2 emission reduction and 6.7% of PM2.5 emission reduction in power plants in pilot areas on average. However, the reduction effect is significant only in coal-fired power plants but not in gas-fired power plants. Besides, the reduction effect is significant for power plants operated with different technologies and is more pronounced for those with outdated production technology, indicating the strong potential for green development of backward power plants. The reduction effect is also more intense for power plants without affiliation relationships than those affiliated with particular manufacturers. Originality/value This paper identifies the causal relationship between the carbon trading mechanism and emission reduction in the power industry by providing an innovative methodology for identifying plant-level emissions based on high-resolution satellite data, which has been practically absent in previous studies. It serves as a reference for stakeholders involved in detailed policy formulation and execution, including policymakers, power plant managers and green investors