Is Robustness the Cost of Accuracy? -- A Comprehensive Study on the Robustness of 18 Deep Image Classification Models

The prediction accuracy has been the long-lasting and sole standard for comparing the performance of different image classification models, including the ImageNet competition. However, recent studies have highlighted the lack of robustness in well-trained deep neural networks to adversarial examples. Visually imperceptible perturbations to natural images can easily be crafted and mislead the image classifiers towards misclassification. To demystify the trade-offs between robustness and accuracy, in this paper we thoroughly benchmark 18 ImageNet models using multiple robustness metrics, including the distortion, success rate and transferability of adversarial examples between 306 pairs of models. Our extensive experimental results reveal several new insights: (1) linear scaling law - the empirical $\ell_2$ and $\ell_\infty$ distortion metrics scale linearly with the logarithm of classification error; (2) model architecture is a more critical factor to robustness than model size, and the disclosed accuracy-robustness Pareto frontier can be used as an evaluation criterion for ImageNet model designers; (3) for a similar network architecture, increasing network depth slightly improves robustness in $\ell_\infty$ distortion; (4) there exist models (in VGG family) that exhibit high adversarial transferability, while most adversarial examples crafted from one model can only be transferred within the same family. Experiment code is publicly available at \url{https://github.com/huanzhang12/Adversarial_Survey}.Comment: Accepted by the European Conference on Computer Vision (ECCV) 201

A review of shale pore structure evolution characteristics with increasing thermal maturities

   Pore structure has a significant effect on the occurrence state of shale hydrocarbons and the hydrocarbon storage capability of shale reservoirs. Consequently, it is quite meaningful to clarify the shale pore structure evolution characteristics for understanding the migration and enrichment mechanisms of hydrocarbons within shale reservoirs during different geological stages. The abundant existence of organic matter within shales complicates the shale pore structure evolution process by hydrocarbon generation, migration and cracking. Many studies have been conducted to reveal the shale pore structure evolution characteristics and the controlling factors. Basically, these studies could be divided into two categories based on the sample source: comparing the pore structure of natural shale samples with different thermal maturities; obtaining shale samples with different thermal maturities by conducting thermal simulation experiments on low-mature shale samples and comparing the pore structure of these simulated shale samples. However, no consistent viewpoint on shale pore structure evolution has been reached. This review presents the state of the art of shale pore structure evolution studies. It is widely recognized in the literature that both the inorganic and organic diagenesis control the shale pore structure evolution process. However, it is found that the shale pore structure evolution models proposed in the literature were largely dependent on the samples used. And it is recommended to conduct the two categories of studies simultaneously in order to obtain more reliable shale pore structure evolution characteristics in future investigations.Cited as: Gao, Z., Fan, Y., Xuan, Q., Zheng, G. A review of shale pore structure evolution characteristics with increasing thermal maturities. Advances in Geo-Energy Research, 2020, 4(3): 247-259, doi: 10.46690/ager.2020.03.0

Smart solar concentrators for building integrated photovoltaic façades

In this study a novel static concentrating photovoltaic (PV) system, suitable for use in windows or glazing façades, has been designed. The developed smart Concentrating PV (CPV) system is lightweight, low cost and able to generate electricity. Additionally, this system automatically responds to climate by varying the balance of electricity generated from the PV with the amount of solar light and heat permitted through it into the building. It therefore offers the potential to contribute to, and control, energy consumption within buildings. A comprehensive optical analysis of the smart CPV is undertaken via 3-D ray tracing technique. To obtain optimal overall optical performance of the novel smart CPV analysis has been based upon all necessary design parameters including the average reflectivity of the thermotropic reflective layer, the glazing cover dimension, the glazing cover materials as well as the dimensions of the solar cells. In addition, a hydroxypropyl cellulose (HPC) hydrogel polymer, suitable for use as the reflective thermotropic layer for the smart CPV system, was synthesized and experimentally studied

POM@ZIF Derived Mixed Metal Oxide Catalysts for Sustained Electrocatalytic Oxygen Evolution

The design of efficient and stable oxygen evolution reaction (OER) catalysts based on noble-metal-free materials is crucial for energy conversion and storage. In this work, it was demonstrated how polyoxometalate (POM)-doped ZIF-67 can be converted into a stable oxygen evolution electrocatalyst by chemical etching, cation exchange, and thermal annealing steps. Characterization by X-ray photoelectron spectroscopy, transmission electron microscopy, energy-dispersive X-ray spectroscopy and Raman spectroscopy indicate that POM-doped ZIF-67 derived carbon-supported metal oxides were synthesized. The resulting composite shows structural and compositional advantages which lead to low overpotential (306 mV at j=10 mA ⋅ cm−2) and long-term stability under harsh OER conditions (1.0 M aqueous KOH)

Seek Homogeneous Critical Ice Nucleus at Moderate Supercooling

The quantitative investigation and dynamical understanding of homogeneous nucleation remain a topic of intense research in the interdisciplinary subject. From supercooled water, homogeneous ice nucleation will not happen spontaneously until a critical crystallite nucleus (Nc) pre-exists. In this work, we investigate homogeneous ice nucleation with our molecular dynamics software SPONGE. Using metadynamics and two structural-based collective variables, we successfully improve the sampling technic to grow spherical nuclei with various cubicity and sizes in a 23040-water box. First, we perform the first long-term freezing in all-atom simulation, various nuclei freeze out into Isd. Instead of a certain cluster size based on classical nucleation theory, the dynamic behaviors of ice nuclei experience a wide range of intermediate states. We provide a novel critical nucleus diagram to seek the critical nucleus: the main external factor, surface area, contributes to the freezing speed of the ice nucleus; while the key internal factor, the mean tetrahedral order, controls the melting speed instead. The ice nucleation rates of our work are in good agreement with the former simulation data. We provide a brief frame to discuss the structural details of the nucleation decision

Full-Length Transcriptome Analysis Reveals Candidate Genes Involved in Terpenoid Biosynthesis in Artemisia argyi

Artemisia argyi is an important medicinal plant widely utilized for moxibustion heat therapy in China. The terpenoid biosynthesis process in A. argyi is speculated to play a key role in conferring its medicinal value. However, the molecular mechanism underlying terpenoid biosynthesis remains unclear, in part because the reference genome of A. argyi is unavailable. Moreover, the full-length transcriptome of A. argyi has not yet been sequenced. Therefore, in this study, de novo transcriptome sequencing of A. argyi's root, stem, and leaf tissues was performed to obtain those candidate genes related to terpenoid biosynthesis, by combining the PacBio single-molecule real-time (SMRT) and Illumina sequencing NGS platforms. And more than 55.4 Gb of sequencing data and 108,846 full-length reads (non-chimeric) were generated by the Illumina and PacBio platform, respectively. Then, 53,043 consensus isoforms were clustered and used to represent 36,820 non-redundant transcripts, of which 34,839 (94.62%) were annotated in public databases. In the comparison sets of leaves vs roots, and leaves vs stems, 13,850 (7,566 up-regulated, 6,284 down-regulated) and 9,502 (5,284 up-regulated, 4,218 down-regulated) differentially expressed transcripts (DETs) were obtained, respectively. Specifically, the expression profile and KEGG functional enrichment analysis of these DETs indicated that they were significantly enriched in the biosynthesis of amino acids, carotenoids, diterpenoids and flavonoids, as well as the metabolism processes of glycine, serine and threonine. Moreover, multiple genes encoding significant enzymes or transcription factors related to diterpenoid biosynthesis were highly expressed in the A. argyi leaves. Additionally, several transcription factor families, such as RLK-Pelle_LRR-L-1 and RLK-Pelle_DLSV, were also identified. In conclusion, this study offers a valuable resource for transcriptome information, and provides a functional genomic foundation for further research on molecular mechanisms underlying the medicinal use of A. argyi leaves