Adversarial Training with Fast Gradient Projection Method against Synonym Substitution based Text Attacks

Adversarial training is the most empirically successful approach in improving the robustness of deep neural networks for image classification.For text classification, however, existing synonym substitution based adversarial attacks are effective but not efficient to be incorporated into practical text adversarial training. Gradient-based attacks, which are very efficient for images, are hard to be implemented for synonym substitution based text attacks due to the lexical, grammatical and semantic constraints and the discrete text input space. Thereby, we propose a fast text adversarial attack method called Fast Gradient Projection Method (FGPM) based on synonym substitution, which is about 20 times faster than existing text attack methods and could achieve similar attack performance. We then incorporate FGPM with adversarial training and propose a text defense method called Adversarial Training with FGPM enhanced by Logit pairing (ATFL). Experiments show that ATFL could significantly improve the model robustness and block the transferability of adversarial examples.Comment: Accepted by AAAI 2021, code is available at https://github.com/JHL-HUST/FGP

The Yellow Sea Surface Cold Patches in Warm Seasons

An important hydrographic phenomenon in the Yellow Sea is the surface cold patches (SCP) in warm seasons, among which the most conspicuous are the Shandong SCP, Subei SCP, and Mokpo SCP. Previous studies based on monthly mean fields propose that these patches result from the collaboration of tidal mixing and tidal induced upwelling. While this is true for patches like the Shandong SCP, the monthly mean tidal mixing and upwelling alone cannot explain all their formations. In this study, through a detailed analysis of their patterns over a spring-neap tidal cycle, it is found that the Subei and Mokpo SCPs show distinct spring-neap variations. During the neap tide phase, strong stratification is established, and hence the cold patches in these two areas may be greatly weakened or even suppressed, while during the spring tide phase, the surface temperature reaches its minimum. That is to say, for these two SCPs, besides the well-accepted mechanisms, the effect of spring-neap tidal variation must be taken into account

Koopman Neural Forecaster for Time Series with Temporal Distribution Shifts

Temporal distributional shifts, with underlying dynamics changing over time, frequently occur in real-world time series, and pose a fundamental challenge for deep neural networks (DNNs). In this paper, we propose a novel deep sequence model based on the Koopman theory for time series forecasting: Koopman Neural Forecaster (KNF) that leverages DNNs to learn the linear Koopman space and the coefficients of chosen measurement functions. KNF imposes appropriate inductive biases for improved robustness against distributional shifts, employing both a global operator to learn shared characteristics, and a local operator to capture changing dynamics, as well as a specially-designed feedback loop to continuously update the learnt operators over time for rapidly varying behaviors. To the best of our knowledge, this is the first time that Koopman theory is applied to real-world chaotic time series without known governing laws. We demonstrate that KNF achieves the superior performance compared to the alternatives, on multiple time series datasets that are shown to suffer from distribution shifts

Clustering and Differentiation of glr-3 Gene Function and Its Homologous Proteins

In order to adapt to the low temperature environment, organisms transmitexcitement to the central system through the thermal sensing system, whichis a classic reflex reaction. The cold receptor GLR-3 perceives cold and produces cold avoidance behavior through peripheral sensory neurons ASER.In order to further understand the gene encoding of the cold sensing glr-3gene and the evolution of its homologous gene group function and proteinfunction, the nucleotide sequence and amino acid sequence of the glr-3gene and its homologous gene in 24 species were obtained and compared.By clustering with the GRIK2 gene sequence of Rana chensinensis, the bioinformatics method was used to predict and sequence analyze the change ofgene, evolution rate, physical and chemical properties of protein, glycosylation sites, phosphorylation sites, secondary structure and tertiary structureof protein. The analysis results show that the glr-3 gene and its homologousgene have obvious positive selection effect. The protein prediction analysisshowed that the glr-3 gene and its homologous genes encoded proteinsin these 25 species were hydrophilic proteins, and the proportion of sidechains of aliphatic amino acids was high. The transmembrane helix waswidespread and there were more N-glycosylation sites and O-glycosylationsites. The protein phosphorylation sites encoded were serine, threonine andtyrosine phosphorylation sites. Secondary structure prediction showed thatthe secondary structure units of the encoded protein were α-helix, β-turn,random coil and extended chain, and the proportion of α-helix was the largest. This study provides useful information on the evolution and function ofthe cold sensing gene glr-3 and its homologous genes

Study on Oil Pressure Characteristics and Trajectory Tracking Control in Shift Process of Wet-Clutch for Electric Vehicles

Accurate control of oil pressure of wet-clutch is of great importance for improving shift quality. Based on dynamic models of two-gear planetary transmission and hydraulic control system, a trajectory tracking model of oil pressure was built by sliding mode control method. An experiment was designed to verify the validity of hydraulic control system, through which the relationship between duty cycle of on-off valve and oil pressure of clutch was determined. The tracking effect was analyzed by simulation. Results showed that oil pressure could follow well the optimal trajectory and the shift quality was effectively improved

Macrophage inhibits the osteogenesis of fibroblasts in ultrahigh molecular weight polyethylene (UHMWPE) wear particle-induced osteolysis

Background In the ultrahigh molecular weight polyethylene (UHMWPE) prosthetic environment, fibroblasts affected by wear particles have the capacity of osteogenesis to reduce osteolysis. We aimed to assess the effects of macrophages on the osteogenic capability of fibroblasts treated with UHMWPE wear particles. Methods The effect of different concentrations of UHMWPE (0, 0.01, 0.1, and 1 mg/ml, respectively) on macrophage proliferation were validated by MTT assay to determine the optimum one. The fibroblasts viability was further determined in the co-culture system of UHMWPE particles and macrophage supernatants. The experiment was designed as seven groups: (A) fibroblasts only; (B) fibroblasts + 1 mg/ml UHMWPE particles; and (C1–C5) fibroblasts + 1/16, 1/8, 1/4, 1/2, and 1/1 supernatants of macrophage cultures stimulated by 1 mg/ml UHMWPE particles vs. fibroblast complete media, respectively. Alizarin red staining was used to detect calcium accumulation. The expression levels of osteogenic proteins were detected by Western blot and ELISA, including alkaline phosphatase (ALP) and osteocalcin (OCN). Results The concentration of 0.1 mg/ml was considered as the optimum concentration for macrophage proliferation due to the survival rate and was highest among the four concentrations. Fibroblast viability was better in the group of fibroblasts + 1/16 ratio of macrophage supernatants stimulated by 1 mg/ml of UHMWPE particles than the other groups (1:8, 1:4, 1:2, 1:1). ALP and OCN expressions were significantly decreased in the group of fibroblasts + 1/4, 1/2, and 1/1 supernatants stimulated by 1 mg/ml of UHMWPE particles compared with other groups (1/8, 1/16) and the group of fibroblasts + 1 mg/ml UHMWPE (p < 0.5). Conclusions Macrophages are potentially involved in the periprosthetic osteolysis by reducing the osteogenic capability of fibroblasts treated with wear particles generated from UHMWPE materials in total hip arthroplasty.China Sholarship Council (Grant 201506370173)China. National Natural Science Foundation (Grant 31200739)China. National Natural Science Foundation (Grant 31470948

The Effects of Storage Conditions on Lycopene Content and Color of Tomato Hot Pot Sauce

Tomato hot pot sauce (THPS) at different storage temperatures (0, 25, and 37°C) and with two kinds of packaging for 120 days was investigated in this study. High performance liquid chromatography was employed for detecting lycopene and 5-hydroxymethylfurfural (HMF). The changes of lycopene and HMF during storage were regressed with kinetic equation of both zero-order and first-order models, and the latter fitted better. The kinetic equation constant (k value) of lycopene or HMF at 37°C was higher than that at 25°C. The k value of lycopene of PET/PE (P1) packaged THPS was 1.60 times of that of PET/Al/EAA/PE (P2) packaged at 37°C, while it was 2.12 times at 25°C. The k value of HMF of P1 packaged THPS was 1.69 times of that of P2 packaged at 37°C, while it was 1.01 times at 25°C. Significant correlations between color index of L⁎, a⁎, and a⁎/b⁎ and lycopene or HMF were found at storage temperature. Browning color was attributed to both Maillard reaction and degradation of lycopene. In conclusion, lower storage temperature and stronger oxygen barrier property of package could maintain color stability and extend shelf life