Adversarial Attack Based on Prediction-Correction

Deep neural networks (DNNs) are vulnerable to adversarial examples obtained by adding small perturbations to original examples. The added perturbations in existing attacks are mainly determined by the gradient of the loss function with respect to the inputs. In this paper, the close relationship between gradient-based attacks and the numerical methods for solving ordinary differential equation (ODE) is studied for the first time. Inspired by the numerical solution of ODE, a new prediction-correction (PC) based adversarial attack is proposed. In our proposed PC-based attack, some existing attack can be selected to produce a predicted example first, and then the predicted example and the current example are combined together to determine the added perturbations. The proposed method possesses good extensibility and can be applied to all available gradient-based attacks easily. Extensive experiments demonstrate that compared with the state-of-the-art gradient-based adversarial attacks, our proposed PC-based attacks have higher attack success rates, and exhibit better transferability.Comment: This manuscript was submitted to CVPR 202

PID-Based Approach to Adversarial Attacks

Adversarial attack can misguide the deep neural networks (DNNs) with adding small-magnitude perturbations to normal examples, which is mainly determined by the gradient of the loss function with respect to inputs. Previously, various strategies have been proposed to enhance the performance of adversarial attacks. However, all these methods only utilize the gradients in the present and past to generate adversarial examples. Until now, the trend of gradient change in the future (i.e., the derivative of gradient) has not been considered yet. Inspired by the classic proportional-integral-derivative (PID) controller in the field of automatic control, we propose a new PID-based approach for generating adversarial examples. The gradients in the present and past, and the derivative of gradient are considered in our method, which correspond to the components of P, I and D in the PID controller, respectively. Extensive experiments consistently demonstrate that our method can achieve higher attack success rates and exhibit better transferability compared with the state-of-the-art gradient-based adversarial attacks. Furthermore, our method possesses good extensibility and can be applied to almost all available gradient-based adversarial attacks

Quasi Steady-State Modeling and Analysis of Diffusion-Controlled Dissolution from Monodisperse Spheroidal Particles

A quasi steady-model of the dissolution of a single prolate or oblate spheroidal particle has been developed based on the exact solution of the steady-state diffusion equation for mass transfer in an unconfined media. With appropriate treatment of bulk concentration, the model can predict the detailed dissolution process of a single particle in a container of finite size. The dimensionless governing equations suggest that the dissolution process is determined by three dimensionless control parameters, initial solid particle concentration, particle aspect ratio, and the product of specific volume of solid particles and saturation concentration of the dissolved species. Using this model, the dissolution process of felodipine particles in a broad range of space of the three control parameters are analyzed and some characteristics are identified. The effects of material properties indicated by the product of specific volume and saturation concentration are also analyzed.</jats:p

Magnetic nanoparticles coated with maltose-functionalized polyethyleneimine for highly efficient enrichment of N-glycopeptides

Hydrophilic interaction chromatography (HILIC) adsorbents have drawn increasing attention in recent years due to their high efficiency in N-glycopeptides enrichment. The hydrophilicity and binding capacity of HILIC adsorbents are crucial to the enrichment efficiency and mass spectrometry (MS) detection sensitivity of N-glycopeptides. Herein, magnetic nanoparticles coated with maltose-functionalized polyethyleneimine (Fe3O4-PEI-Maltose MNPs) were prepared by one-pot solvothermal reaction coupled with "click chemistry" and utilized for N-glycopeptides enrichment. Owing to the presence of hydrophilic and branched polyethyleneimine, the amount of immobilized disaccharide units was improved about four times. The N-glycopeptides capturing capacity was about 150 mg/g (IgG/MNPs) and the MS detection limitation as low as 115 fmol for IgG and 85% average enrichment recovery were feasibly achieved by using this hybrid magnetic adsorbent. Finally, 1237 unique N-glycosylation sites and 1567 unique N-glycopeptides from 684 N-glycoproteins were reliably characterized from 60 mu g protein sample extracted from mouse liver. Therefore, this maltose-functionalized polyethyleneimine coated adsorbent can play a promising role in highly efficient N-glycopeptides enrichment for glycoproteomic analyses of complex protein samples. (C) 2015 Elsevier B.V. All rights reserved

Effects of extracorporeal circulation with different time on platelet count after cardiac surgery: a retrospective study based on medical records

Abstract Our objective was to observe the effects of extracorporeal circulation (ECC) with different time on platelet count in patients undergoing cardiac surgery. A total of 427 patients who underwent elective cardiac surgery under ECC in affiliated hospital of north Sichuan medical college from January 1, 2018 to July 31, 2021 were divided into three groups according to ECC time. We concluded that thrombocytopenia was common after ECC, maximum drop of the platelet counts after ECC was usually seen on the second day after ECC, and platelet counts started to recover on the fifth day after ECC. With the extension of ECC time, the drop in platelet counts is more pronounced, the volume of perioperative blood loss and blood products transfusion are more, and the recovery level and speed of platelet counts is lower