A Distributed Approach of Big Data Mining for Financial Fraud Detection in a Supply Chain

Supply Chain Finance(SCF)is important for improving the effectiveness of supply chain capital operations and reducing the overall management cost of a supply chain.In recent years,with the deep integration of supply chain and Internet,Big Data,Artificial Intelligence,Internet of Things,Blockchain,etc.,the efficiency of supply chain financial services can be greatly promoted through building more customized risk pricing models and conducting more rigorous investment decision-making processes.However,with the rapid development of new technologies,the SCF data has been massively increased and new financial fraud behaviors or patterns are becoming more covertly scattered among normal ones.The lack of enough capability to handle the big data volumes and mitigate the financial frauds may lead to huge losses in supply chains.In this article,a distributed approach of big data mining is proposed for financial fraud detection in a supply chain,which implements the distributed deep learning model of Convolutional Neural Network(CNN)on big data infrastructure of Apache Spark and Hadoop to speed up the processing of the large dataset in parallel and reduce the processing time significantly.By training and testing on the continually updated SCF dataset,the approach can intelligently and automatically classify the massive data samples and discover the fraudulent financing behaviors,so as to enhance the financial fraud detection with high precision and recall rates,and reduce the losses of frauds in a supply chain.

Role of thioredoxin-interacting protein in mediating endothelial dysfunction in hypertension

Excessive oxidative stress is a major causative factor of endothelial dysfunction in hypertension.As an endogenous pro-oxidant,thioredoxin-interacting protein(TXNIP)contributes to oxidative damage in various tissues.The present study aimed to investigate the role of TXNIP in mediating endothelial dysfunction in hypertension.In vivo,an experimental model of acquired hypertension was established with two-kidney,one-clip(2K1C)surgery.The expression of TXNIP in the vascular endothelial cells of multiple vessels was significantly increased in hypertensive rats compared with sham-operated rats.Resveratrol,a TXNIP inhibitor,suppressed vascular oxidative damage and increased the expression and activity of eNOS in the aorta of hypertensive rats.Notably,impaired endothelium-dependent vasodilation was effectively improved by TXNIP inhibition in hypertensive rats.In vitro,we observed that Ang II increased the expression of TXNIP in primary human aortic endothelial cells(HAECs)and that TXNIP knockdown by RNA interference alleviated cellular oxidative stress damage and mitigated the impaired eNOS activation and intracellular nitric oxide(NO)production observed in Ang Il-treated HAECs.However,inhibiting thioredoxin(TRX)with PX-12 completely blunted the protective effect of silencing TXNIP.In addition,TXNIP knockdown facilitated TRX expression and promoted TRX nuclear translocation to further activate AP1 and REF1.TRX overexpressi on exhibited favorable effects on eNOS/NO homeostasis in Ang 11-treated HAECs.Thus,TXNIP contributes to oxidative stress and endothelial dysfunction in hypertension,and these effects are dependent on the antioxidant capacity of TRX,suggesting that targeting TXNIP may be a novel strategy for antihypertensive therapy.