Time series prediction of reservoir bank landslide failure probability considering the spatial variability of soil properties

Historically,landslides have been the primary type of geological disaster worldwide.Generally,the stability of reservoir banks is primarily affected by rainfall and reservoir water level fluctuations.Moreover,the stability of reservoir banks changes with the long-term dynamics of external disastercausing factors.Thus,assessing the time-varying reliability of reservoir landslides remains a challenge.In this paper,a machine learning(ML)based approach is proposed to analyze the long-term reliability of reservoir bank landslides in spatially variable soils through time series prediction.This study systematically investigated the prediction performances of three ML algorithms,i.e.multilayer perceptron(MLP),convolutional neural network(CNN),and long short-term memory(LSTM).Additionally,the effects of the data quantity and data ratio on the predictive power of deep learning models are considered.The results show that all three ML models can accurately depict the changes in the time-varying failure probability of reservoir landslides.The CNN model outperforms both the MLP and LSTM models in predicting the failure probability.Furthermore,selecting the right data ratio can improve the prediction accuracy of the failure probability obtained by ML models.

Spatiotemporal characteristics of seed rain and soil seed bank of artificial Caragana korshinskii Kom. forest in the Tengger Desert, China

Vegetation restoration and reconstruction are effective approaches to desertification control and achieving social and economic sustainability in desert areas.However,the self-succession ability of native plants during the later periods of vegetation restoration remains unclear.Therefore,this study was conducted to bridge the knowledge gap by investigating the regeneration dynamics of artificial forest under natural conditions.The information of seed rain and soil seed bank was collected and quantified from an artificial Caragana korshinskii Kom.forest in the Tengger Desert,China.The germination tests were conducted in a laboratory setting.The analysis of species quantity and diversity in seed rain and soil seed bank was conducted to assess the impact of different durations of sand fixation(60,40,and 20 a)on the progress of vegetation restoration and ecological conditions in artificial C.korshinskii forest.The results showed that the top three dominant plant species in seed rain were Echinops gmelinii Turcz.,Eragrostis minor Host.,and Agropyron mongolicum Keng.,and the top three dominant plant species in soil seed bank were E.minor,Chloris virgata Sw.,and E.gmelinii.As restoration period increased,the density of seed rain and soil seed bank increased first and then decreased.While for species richness,as restoration period increased,it gradually increased in seed rain but decreased in soil seed bank.There was a positive correlation between seed rain density and soil seed bank density among all the three restoration periods.The species similarity between seed rain or soil seed bank and aboveground vegetation decreased with the extension of restoration period.The shape of the seeds,specifically those with external appendages such as spines and crown hair,clearly had an effect on their dispersal,then resulting in lower seed density in soil seed bank.In addition,precipitation was a crucial factor in promoting rapid germination,also resulting in lower seed density in soil seed bank.Our findings provide valuable insights for guiding future interventions during the later periods of artificial C.korshinskii forest,such as sowing and restoration efforts using unmanned aerial vehicles.

Research on Early Warning of Banking Crises from the Perspective of Credit Structures

The relationship between credit expansion and banking crises is complex and cannot be fully explained by total credit alone.A systematic analysis of the relationship between the amount and structure of total credit and banking crises is important for an objective prediction of the influence of potential financial risks.This paper,drawing on data from 15 selected countries,delves into the power of credit indicators in the early warning of banking crises from the perspectives of industrial structure,sector structure,and term structure of credit.Various machine learning methods were used,including Logistic Regression,Random Forest,Decision Tree,Support Vector Machine(SVM),Bagging,and Boosting models.The empirical findings indicate that credit expansion plays a crucial role in triggering banking crises.However,total credit is better suited for the early warning of short-term banking crises,whereas credit structure is more useful for the early warning of long-term banking crises.Moreover,in an early warning system,identifying key early warning indicators is more meaningful than merely increasing the number of indicators.Machine learning can somewhat enhance the early warning power,but it may not always be robust.Therefore,more attention should be paid to potential systemic banking crises resulting from an imbalance in credit structure while regulating the total credit threshold.

The Impact of the Monetary Policy During the COVID-19 in the Brazilian Banking Sector

The COVID-19 pandemic caused an outbreak on the global productive chains,transforming companies and society in general.Governments adopted anticyclical policies such as basic interest rates reduction as response.Brazil basic interest rate is denominated Selic.The application of these policies requires the protagonist of bank’s financial intermediation.This study aims to verify two events-under the perspective of the efficient markets’theory.The first is the communication of the first death by COVID-19-and the subsequent,Selic rate reduction to 2%p.a.-and its effects on bank’s shares prices.The hypotheses presented are:H1-The announcement of the first death by COVID-19 negatively impacts the banks’shares returns and H2-The announcement of the Selic interest rate-during the COVID-19-positively impacts the return of the banks’shares.We adopt event study methodology in a final sample of nine and 15 banks to Events 1 and 2 respectively.The results confirm H1 as well as the semi-strong informational efficiency market.H2 is not confirmed.Results confirm the non-effectiveness of the anticyclical policy of basic interest rate reduction.This contributes to the discussion about the impacts of COVID-19 and the efficacy of anticyclical policies.

Research on the Impact of the Digital Transformation of Commercial Banks

The development of the digital economy has presented both opportunities and challenges for the transformation of commercial banks.This article aims to conduct a literature review on the impact of digital transformation on commercial banks and to explore the multi-dimensional effects it brings.Through a review and analysis of relevant domestic and international literature,this paper first defines the connotation of digital transformation in commercial banks.It then conducts a literature analysis and research on the strategic governance,business performance,and risk management aspects of the digital transformation of commercial banks from multiple perspectives.Based on the analysis of the existing literature,the paper explores directions for future in-depth research and offers corresponding policy suggestions,providing a theoretical and practical foundation for the future digital development of commercial banks.

ISO Certification and Technical Efficiency in the Banking Sector:An Evidence from WAEMU’s Countries Using the DEA Method

In the view of the international organization of standardization,the introduction of ISO standards is typical of quality management systems oriented towards strengthening the efficiency of enterprises.Business banks are not excluded from this requirement.The current study aims to evaluate the effect of ISO certification on the technical performance of WAEMU banks.Using BCEAO data(2020),the DEA model and Tobit estimates show that ISO certification has no effect on the efficiency scores of the banks in the sample.It is therefore appropriate for these banks to work on improving their business climate.

Research on the Impact of Digital Transformation on the Business Performance of Commercial Banks

Nowadays,with the development of the digital economy,commercial banks are actively conducting digital transformation.Studying the impact of the digital transformation of commercial banks on their operating performance can help commercial banks form a stronger core competitiveness and promote high-quality financial development.Based on the above background,this article first describes the status and development of digital transformation and development of commercial banks,and secondly analyzes whether Chinese commercial banks’digital transformation is conducive to improving their operating performance.Thirdly,by selecting the data of the listed commercial banks in the ten years of 2012–2022,this article obtains the empirical testing of the digital transformation on different property rights.Finally,the higher the level of digitalization,the higher the digital level,the more significantly promotes the performance of commercial banks.Finally,based on the above analysis,this article puts forward feasibility opinions on commercial banks and related regulators.

基于Auto bank的某水库大坝渗流安全评价

以富水水库为例,依托达西定律和渗流理论基础,并结合Auto bank有限元软件分析了水库在正常高水位、设计洪水位、校核洪水位下坝体及坝基的渗流状况,计算结果表明水库日渗漏量远小于允许日渗漏量,水库渗漏量满足规范要求。大坝各工况最大渗透坡降均小于规范允许值,渗透变形满足规范要求。左坝肩存绕渗现象,建议加强监测。

ISMB:多核系统中利用Bank分区实现共享库隔离

动态随机存取存储器DRAM一直以来以其低功耗、高性价比和良好的扩展性等优点作为计算机内存的最佳选择。为了提高内存的访问速度,DRAM中的每个Bank都有一个行缓冲区,它可以有效地提升局部性良好的应用程序的性能。然而在多核系统中,DRAM被系统中的所有Core共享,因此对内存的并发访问会导致Bank行缓冲区冲突问题的产生,从而导致内存访问延迟的增大。共享库作为一种共享资源,使Bank行缓冲区冲突问题更加严重。虽然目前有一些基于DRAM Bank分区技术的解决方案可以有效缓解由进程访问私有内存导致的Bank行缓冲区冲突问题,但是这些解决方案无法解决访问共享库引起的Bank行缓冲区冲突问题。该文提出了一种在多核系统中利用Bank分区实现共享库隔离的方案(ISMB)。ISMB使运行在同一个Core上的进程只能访问属于该Core的共享库的副本,因此ISMB消除了共享库导致的Bank行缓冲区冲突问题。对比实验结果表明,ISMB能够有效地提升系统隔离性能,在使用ISMB的情况下,SPEC CPU2006基准测试程序的减速率最大可降低26.3%。

Soil seed bank is affected by transferred soil thickness and properties in the reclaimed coal mine in the Qilian Mountains, China

Reclamation of lands abandoned after mining in mountain areas is critical to erosion control,safety from landslides,and ecological protection of mountain ecosystems.However,little is known about alpine coal mine reclamation using the soil seed bank as a potential source for revegetation.We collected samples of persistent soil seed bank for germination experiments from nine reclaimed sites with different soil cover thicknesses and from six control sites in the Qilian Mountains of China.Soil properties of each site were determined(including soil water content,soil available potassium,soil available phosphorus,soil total nitrogen,pH,soil organic matter,soil total phosphorus,and soil total potassium,and soil alkali-hydrolyzable nitrogen),and the relationships of the characteristics of the soil seed bank with soil cover thickness and soil properties were examined.The results showed that the density,number of species,and diversity of the topsoil seed bank were significantly correlated with soil cover thickness,and all increased with the increment of soil cover thickness.Soil cover thickness controlled the soil seed bank by influencing soil properties.With the increase in soil cover thickness,soil properties(e.g.,soil organic matter,soil total nitrogen,etc.)content increased while soil pH decreased.The soil seed bank had the potential to restored the pre-mining habitat at reclaimed sites with approximately 20-cm soil cover thickness.Soil properties of reclaimed sites were lower than that of natural sites.The relationship between the soil seed bank and soil cover thickness determined in this study provides a foundation for improving reclamation measures used in coal mines,as well as for the management and monitoring of reclaimed areas.

Size matters:analyzing bank profitability and efficiency under the Basel III framework

The latest regulatory framework,which has been introduced globally in the form of Basel III,and its implementation in the legislation of the member states of the Euro-pean Union has generated much interest in the impact of regulation on the efficiency and profitability of banks.This study aims to examine the impact of the introduction of two major regulatory changes(Basel II and Basel III)on bank performance,in terms of bank size and bank-specific and macroeconomic variables.A two-stage empirical anal-ysis was conducted on a sample of 433 European commercial banks over the 2006–2015 period.In the first stage,relative efficiency was calculated using non-parametric data envelopment analysis.In the second stage,the generalized method of moments was used to examine the impact of bank-specific and macroeconomic variables as well as regulation on bank performance,that is,profitability and efficiency.Consider-ing bank size,the results show a diverse impact of regulation on bank performance.Regarding large-and medium-sized banks,regulation positively affects both efficiency and profitability,whereas,for small banks,it negatively affects performance.The results suggest that larger banks have skillfully adapted to the new regulatory environment.In contrast,small banks have problems with profitability and efficiency because the new regulatory framework has imposed additional administrative and regulatory burdens.This could result in future failure or mergers with larger banks,resulting in a higher concentration in the banking sector and increased systemic risk.Our results strongly suggest that regulation should not be implemented equally for all banks;that is,on a one size fits all terms.A distinction between small and large banks when introducing new regulatory frameworks should be made if a reasonable level of competition is to be preserved.

Private banking development in China under two organizational structures:Economic analysis from an organizational innovation perspective

This paper investigates optimal decisions for private banking development in China under two innovative organizational structures—the big retail mode(BRM)and the independent development mode(IDM).Under the BRM,the retail and private banking divisions form a cooperative relationship wherein the former transfers highnet-worth customers to the latter.In addition,retail banking receives a share of private banking revenues.We investigate the optimal revenue-sharing ratio between the two divisions and the optimal effort by private banking to serve transferred customers within the cooperative relationship.The analytical results show that as the private banking division becomes more developed,the optimal revenue-sharing ratio decreases,and the private banking division’s optimal effort to serve transferred customers decreases because it puts more effort into acquiring new customers.Under the IDM,the two divisions form a competitive relationship since they compete to acquire customers independently.We investigate customer acquisition efforts in this interdivisional competition.Optimal customer acquisition efforts by both divisions increase in potential assets and rates of return.This paper contributes to the literature by(1)analyzing financial innovation by private banks from an organizational perspective;(2)providing an economic analysis for private banking development in China.

Hydro-Geochemistry and Application of Water Quality Index (WQI) for Ground Water Quality Assessment, Wadi Al-Samen—Hebron—West Bank

Located south of the West Bank, Wadi Al-Samen is considered one of the most important sources of groundwater recharge for the eastern aquifer in Hebron. It is polluted by sewage originating from domestic and industrial consumption in the Hebron area. Water quality assessment is an important criterion for achieving sustainable development. To evaluate water quality, twenty samples were collected from groundwater sources for two seasons and were analyzed for Physical properties (Total dissolved solids (TDS), Electrical conductivity (EC), potential hydrogen (pH), Temperature (T)), Four major cations (Mg2+, Ca2+, Na+ and K+), and the Major anions (HCO-3, Cl-, and SO2-4);geochemical methods such as Piper scheme were used for the sample result analysis. To characterize wastewater components, six samples were collected from the Wadi discharge for two seasons and were analyzed (potential hydrogen (pH), Electrical Conductivity (EC), Total Dissolved Solid (TDS), Total Suspended Solids (TDS), Total Suspended Solids (TSS), Biological Oxygen Demand (BOD5), and Chemical Oxygen Demand (COD). The results of nitrate levels showed that 20% of the ground water samples exceeded the standard limit of the World Health Organization (WHO). The quality of drinking water was assessed using the Water Quality Index (WQI), which suggests that 10% of samples are classified from poor to very poor. The abundance of cations from highest to lowest was found to be: Ca;Mg;Na, and for the anions it is HCO3;Cl;SO4. The dominant hydrochemical facies of 35% of collected aquifer samples reveal that Ca-Mg-Na-Cl-HCO3 are in the domain. Evaluation of irrigation suitability was performed using parameters of Sodium adsorption ratio (SAR), electric conductivity (EC), and Salinity. The results in both rounds for EC showed that all water sources are suitable for irrigation according to Todd’s classification. SAR was not suitable in three water resources samples. Wilcox analysis for the two seasons revealed that 85% of samples are not appropriate for irrigation uses.

Filter Bank Networks for Few-Shot Class-Incremental Learning

Deep Convolution Neural Networks(DCNNs)can capture discriminative features from large datasets.However,how to incrementally learn new samples without forgetting old ones and recognize novel classes that arise in the dynamically changing world,e.g.,classifying newly discovered fish species,remains an open problem.We address an even more challenging and realistic setting of this problem where new class samples are insufficient,i.e.,Few-Shot Class-Incremental Learning(FSCIL).Current FSCIL methods augment the training data to alleviate the overfitting of novel classes.By contrast,we propose Filter Bank Networks(FBNs)that augment the learnable filters to capture fine-detailed features for adapting to future new classes.In the forward pass,FBNs augment each convolutional filter to a virtual filter bank containing the canonical one,i.e.,itself,and multiple transformed versions.During back-propagation,FBNs explicitly stimulate fine-detailed features to emerge and collectively align all gradients of each filter bank to learn the canonical one.FBNs capture pattern variants that do not yet exist in the pretraining session,thus making it easy to incorporate new classes in the incremental learning phase.Moreover,FBNs introduce model-level prior knowledge to efficiently utilize the limited few-shot data.Extensive experiments on MNIST,CIFAR100,CUB200,andMini-ImageNet datasets show that FBNs consistently outperformthe baseline by a significantmargin,reporting new state-of-the-art FSCIL results.In addition,we contribute a challenging FSCIL benchmark,Fishshot1K,which contains 8261 underwater images covering 1000 ocean fish species.The code is included in the supplementary materials.

An 80-GHz DCO utilizing improved SC ladder and promoted DCTL-based hybrid tuning banks

An 80-GHz DCO based on modified hybrid tuning banks is introduced in this paper.To achieve sub-MHz frequency res-olution with reduced circuit complexity,the improved circuit topology replaces the conventional circuit topology with two binary-weighted SC cells,enabling eight SC-cell-based improved SC ladders to achieve the same fine-tuning steps as twelve SC-cell-based conventional SC ladders.To achieve lower phase noise and smaller chip size,the promoted binary-weighted digi-tally controlled transmission lines(DCTLs)are used to implement the coarse and medium tuning banks of the DCO.Compared to the conventional thermometer-coded DCTLs,control bits of the proposed DCTLs are reduced from 30 to 8,and the total length is reduced by 34.3%(from 122.76 to 80.66μm).Fabricated in 40-nm CMOS,the DCO demonstrated in this work fea-tures a small fine-tuning step(483 kHz),a high oscillation frequency(79-85 GHz),and a smaller chip size(0.017 mm^(2)).Com-pared to previous work,the modified DCO exhibits an excellent figure of merit with an area(FoMA)of-198 dBc/Hz.

Dental pulp stem cells and banking of teeth as a lifesaving therapeutic vista

Exfoliated deciduous or an extracted healthy adult tooth can be used to harvest,process,and cryogenically preserve dental pulp stem cells.Future stem cell-based regenerative medicine methods could benefit significantly from these mesenchymal stem cells.Teeth serve as a substantial source of mesenchymal stem cells,otherwise disposed of as medical waste.Care should be taken to store this treasure trove of stem cells.Collective responsibility of patients,dentists,and physicians is necessary to ensure that this valuable resource is not wasted and that every possible dental pulp stem cell is available for use in the future.The dental pulp stem cells(DPSC)inside teeth represent a significant future source of stem cells for regenerative medicine procedures.This review describes the ontogeny,the laboratory processing and collection,and isolation methods of DPSC.This review also discusses currently available stem cell banking facilities and their potential use in regenerative medicine procedures in dental and general medical applications in the future.

Soil Seed Bank Characteristics of the Mbe and Nguela Shrub Savannas, and Implications for the Reforestation, Republic of Congo

The soil seed bank is an important source of restoration and resilience of disturbed ecosystems. This study evaluates the regeneration potential through the soil seed bank of the shrub savannas of Nguela and Mbe in order to predict the eventual dynamics. Three plots of 0.25 ha subdivided into four sub-plots of 0.015 ha have been installed in each savannah. In total, 48 samples of each savannah, i.e. 96 samples of both savannas, have been taken from the soil layers, 0 - 5 cm, 5 - 10 cm, 10 - 15 cm and 15 - 20 cm. Species diversity and abundance of the soil seed bank have been assessed after germination. The results reveal 167 seedlings belonging to 23 species in the Mbe savannah and 144 seedlings belonging to 14 species in the Nguela savannah. The total densities of the germinated seeds were respectively 463.63 seeds/m2 and 400 seeds/m2. Nevertheless, the 20 cm deep layers have illustrated themselves compared to the superficial layers with densities of 16.29 seeds/m2 and 21.66 seeds/m2, respectively, in the savannas of Mbe and Nguela. Herbaceous species largely dominated, with percentages of 91% and 100%, respectively, in the savannas of Mbe and Nguela. Alone, the Trema orientalis (L.) Blume species has been identified as woody species in the Mbe savannah. The greatest specific richness has been obtained in the first five centimeters of soil, with 21.73% and 28.57% of exclusive species, respectively, in the savannas of Mbe and Nguela. The results reveal that restoration through the soil seed bank would be limited to a single woody species found (T. orientalis). Consequently, the study suggests silvicultural interventions based on planting or enrichment techniques for sustainably managed savannas exposed to anthropogenic disturbances.

Does country risk impact the banking sectors’non‑performing loans?Evidence from BRICS emerging economies

This study aims to fill the gap in the literature by specifically investigating the impact of country risk on the credit risk of the banking sectors operating in Brazil,Russia,India,China,and South Africa(BRICS),emerging countries.More specifically,we explore whether the country-specific risks,namely financial,economic,and political risks significantly impact the BRICS banking sectors’non-performing loans and also probe which risk has the most outstanding effect on credit risk.To do so,we perform panel data analysis using the quantile estimation approach covering the period 2004–2020.The empirical results reveal that the country risk significantly leads to increasing the banking sector’s credit risk and this effect is prominent in the banking sector of countries with a higher degree of non-performing loans(Q.25=−0.105,Q.50=−0.131,Q.75=−0.153,Q.95=−0.175).Furthermore,the results underscore that an emerging country’s political,economic,and financial instabilities are strongly associated with increasing the banking sector’s credit risk and a rise in political risk in particular has the most positive prominent impact on the banking sector of countries with a higher degree of non-performing loans(Q.25=−0.122,Q.50=−0.141,Q.75=−0.163,Q.95=−0.172).Moreover,the results suggest that,in addition to the banking sectorspecific determinants,credit risk is significantly impacted by the financial market development,lending interest rate,and global risk.The results are robust and have significant policy suggestions for many policymakers,bank executives,researchers,and analysts.

How to Register a Wholly Foreign-Owned Enterprise in China?

In July 2017,China＇s Ministry of Commerce（MOFCOM）announced changes to the registration process for foreign-invested enterprises to speed up and ease market entry for foreign investors.While there are many types of legal entities that could be registered,

Open banking and inclusive finance in the European Union:perspectives from the Dutch stakeholder ecosystem

In the European Union(EU),the revised Payment Services Directive(PSD2)aims to provide more convenient and customized financial products through open banking(OB)platforms.However,little attention has been paid to the role of OB in improving the financial well-being of the growing number of the EU’s underserved groups,which currently constitute approximately a quarter of its population.This study examines how the PSD2 and OB impact inclusive finance in the EU based on the perspectives of the Netherlands’ecosystem,one of the leaders in the EU’s financial technology(FinTech)landscape.A fundamental distinction can be drawn between the OB users and the ecosystem’s players.Regarding the impact of financial services on the users’inclusivity,while the PSD2 strengthens the infrastructure necessary for financial inclusion,many challenges remain,mainly because it was not designed for this purpose.This study identifies several areas of improvement that include adjustments to the know your customer and anti-money laundering processes for underserved customers,innovative ways to communicate the PSD2’s potential,and the regulation of technology providers’activities to build trust.Meanwhile,from the ecosystem’s position,there is a need to strengthen and improve microfinance regulation according to the opportunities provided by the PSD2 to support microfinance institutions(MFIs)in scaling up and reaching underserved clients across borders with innovative services.OB improvements can also be achieved by organizations formed by MFIs and FinTechs in collaboration with banks.Such hybrid institutions will combine the best features of each of them:knowledge of the needs of local underserved clients from MFIs,technological innovations from FinTechs,and large and trusted customer bases,infrastructures,and access to institutional investments and governments from banks.Finally,an EU inclusive OB sector depends on the centrality of trusted regulators as coordination bodies.The PSD2 requires adjustments for underserved populations’specific needs.OB improvements can be achieved by organizations formed by MFIs and Fin-Techs in collaboration with banks.Regulated technical service providers(TSPs)are crucial to building trust and customer adoption in OB.The European Banking Authority(EBA)may function as coordination body to design inclusive rules by engaging with OB stakeholders.As inclusive finance moves into open-finance and data eras,an increasing regulatory complexity and scope will require networks of innovative and trusted regulators.