Ensemble learning framework for landslide susceptibility mapping:Different basic classifier and ensemble strategy

The application of ensemble learning models has been continuously improved in recent landslide susceptibility research,but most studies have no unified ensemble framework.Moreover,few papers have discussed the applicability of the ensemble learning model in landslide susceptibility mapping at the township level.This study aims at defining a robust ensemble framework that can become the benchmark method for future research dealing with the comparison of different ensemble models.For this purpose,the present work focuses on three different basic classifiers:decision tree(DT),support vector machine(SVM),and multi-layer perceptron neural network model(MLPNN)and two homogeneous ensemble models such as random forest(RF)and extreme gradient boosting(XGBoost).The hierarchical construction of deep ensemble relied on two leading ensemble technologies(i.e.,homogeneous/heterogeneous model ensemble and bagging,boosting,stacking ensemble strategy)to provide a more accurate and effective spatial probability of landslide occurrence.The selected study area is Dazhou town,located in the Jurassic red-strata area in the Three Gorges Reservoir Area of China,which is a strategic economic area currently characterized by widespread landslide risk.Based on a long-term field investigation,the inventory counting thirty-three slow-moving landslide polygons was drawn.The results show that the ensemble models do not necessarily perform better;for instance,the Bagging based DT-SVM-MLPNNXGBoost model performed worse than the single XGBoost model.Amongst the eleven tested models,the Stacking based RF-XGBoost model,which is a homogeneous model based on bagging,boosting,and stacking ensemble,showed the highest capability of predicting the landslide-affected areas.Besides,the factor behaviors of DT,SVM,MLPNN,RF and XGBoost models reflected the characteristics of slow-moving landslides in the Three Gorges reservoir area,wherein unfavorable lithological conditions and intense human engineering activities(i.e.,reservoir water level fluctuation,residential area construction,and farmland development)are proven to be the key triggers.The presented approach could be used for landslide spatial occurrence prediction in similar regions and other fields.

Potential Impact for Issuing Libra in Financial Systems and Policy Implications

Cryptocurrency,which is a type of digital currency that uses cryptography for security and anti-counterfeiting measures,has become a hot topic in the financial market.Since cryptocurrency is new,and in the financial sector,new is stimulating.The features of cryptocurrency such as high process speed,strictly digital nature and low transaction costs that are not present in traditional financial systems.Considerably,cryptocurrency will inevitably lead to exciting new business models,financial opportunities,and online business strategies.In this paper we will analysis the characteristics of Libra,and put forward corresponding Libra’s impact on sovereign currency,financial regulation and commercial banks.

Screening bifunctional flavonoids of anti-cholinesterase and anti-glucosidase by in vitro and in silico studies:Quercetin,kaempferol and myricetin

Type 2 diabetes mellitus(T2DM)and Alzheimer disease(AD)are two independent non-infectious diseases,however,evidences demonstrate that insulin resistance(IR)directly affects the glucose metabolism of the central nervous system(CNS),ultimately leading to neurodegenerative disorders,such as AD.Therefore,developing anti-AD/-diabetes inhibitors with fewer side effects have become a focus of the public and pharmacologist.In this study,the inhibitory activities of 16 flavonoids and 3 standards(galantamine,donepezil hydrochloride and acarbose)on acetylcholinesterase(AChE),butyrylcholinesterase(BChE),α-glucosidase(αG)andα-amylase(αA)and their corresponding structure-activity relationships were studied by multiple methods.The results showed that,unlike the positive effect of hydroxyl group,methoxy group of flavonoids had a negative effect on the inhibitory activity of enzyme.Besides,the glycosylation of C3 and C7 significantly reduced the inhibitory effect of flavonoids,and the hydrogenation of C2=C3 double bond also had a similar inhibitory effect.Hence,flavonols,especially quercetin,kaempferol and myricetin showed high anti-AChE/-BChE/-αG/-αA activities,and their activities had a highest correlation with their antioxidant activities,while catechin,epicatechin,and artemetin had low inhibitory activities.Furthermore,molecular docking further confirmed the C4′-OH,C5′-OH and C3-OH of flavonoids skeleton played an important role in the binding and interaction between flavonoids and enzymes.In conclusion,flavonoids with specific structures may be used as inhibitors of cholinesterase,αG andαA in the treatment and prevention of AD and T2DM.