Ghost Module Based Residual Mixture of Self-Attention and Convolution for Online Signature Verification

Online Signature Verification (OSV), as a personal identification technology, is widely used in various industries.However, it faces challenges, such as incomplete feature extraction, low accuracy, and computational heaviness. Toaddress these issues, we propose a novel approach for online signature verification, using a one-dimensionalGhost-ACmix Residual Network (1D-ACGRNet), which is a Ghost-ACmix Residual Network that combines convolutionwith a self-attention mechanism and performs improvement by using Ghost method. The Ghost-ACmix Residualstructure is introduced to leverage both self-attention and convolution mechanisms for capturing global featureinformation and extracting local information, effectively complementing whole and local signature features andmitigating the problem of insufficient feature extraction. Then, the Ghost-based Convolution and Self-Attention(ACG) block is proposed to simplify the common parts between convolution and self-attention using the Ghostmodule and employ feature transformation to obtain intermediate features, thus reducing computational costs.Additionally, feature selection is performed using the random forestmethod, and the data is dimensionally reducedusing Principal Component Analysis (PCA). Finally, tests are implemented on the MCYT-100 datasets and theSVC-2004 Task2 datasets, and the equal error rates (EERs) for small-sample training using five genuine andforged signatures are 3.07% and 4.17%, respectively. The EERs for training with ten genuine and forged signaturesare 0.91% and 2.12% on the respective datasets. The experimental results illustrate that the proposed approacheffectively enhances the accuracy of online signature verification.

Probes and nano-delivery systems targeting NAD(P)H:quinone oxidoreductase 1:a mini-review

The two-electron cytoplasmic reductase NAD(P)H:quinone oxidoreductase 1 is expressed in many tissues.NAD(P)H:quinone oxidoreductase 1 is well-known for being highly expressed in most cancers.Therefore,it could be a target for cancer therapy.Because it is a quinone reductase,many bioimaging probes based on quinone structures target NAD(P)H:quinone oxidoreductase 1 to diagnose tumours.Its expression is higher in tumours than in normal tissues,and using target drugs such asβ-lapachone to reduce side effects in normal tissues can help.However,the physicochemical properties ofβlapachone limit its application.The problem can be solved by using nanosystems to deliverβ-lapachone.This minireview summarizes quinone-based fluorescent,nearinfrared and two-photon fluorescent probes,as well as nanosystems for delivering the NAD(P)H:quinone oxidoreductase 1-activating drugβ-lapachone.This review provides valuable information for the future development of probes and nano-delivery systems that target NAD(P)H:quinone oxidoreductase 1.