Monetary Policy,Liquidity and Bank Risk-Taking

The great impact of monetary policy on bank risk-taking,facilitated by a liquidity mechanism,significantly complicates the macro-prudential supervision process.Surprisingly,limited scholarly research has delved into this particular issue.Hence,in this paper,the liquidity variable is introduced into the dynamic linear model to depict the liquidity mechanism by which monetary policy affects bank risk-taking.Based on micro-data from 133 commercial banks in China,this paper empirically tests using systematic Gaussian mixture models estimation and a panel smooth transition regression model.The findings reveal that while monetary policy does not exhibit a significant risk-shifting effect.A marked liquidity transmission effect,however,is observed,whereby easy monetary policy noticeably exacerbates bank risk-taking.This impact becomes more pronounced as liquidity levels improve.The most significant negative impact of monetary policy on bank risk-taking occurs when bank liquidity reaches approximately 43%.Moreover,when banks maintain high levels of liquidity,the statutory deposit reserve ratio exerts a greater regulatory effect than other monetary policy tools.Contractionary monetary policy imposes noticeably weaker restraints than expansionary monetary policy,particularly in banks with higher liquidity levels.Moreover,the interplay between monetary policy and bank risk-taking is contingent upon not just the liquidity level of banks,but also their asset size and capital adequacy.

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.

Funding Liquidity and Bank Risk-Taking:Empirical Evidence from China

Liquidity risk has a significant impact on the prudent operation of financial institutions and the stability of fi nancial system.Funding liquidity risk has played an important role in banking crises in history.This paper uses the data of 338 commercial banks in China from 2002 to 2016 to analyze the relationship between funding liquidity and bank risk-taking.The findings show that:(1)Banks with lower funding liquidity risk take more risks,which is evidenced by lower Z-score and capital adequacy ratio,as well as higher risk-weighted asset ratio and liquidity creation.(2)Funding liquidity risk has an impact on the factors of bank risks.Lower funding liquidity risk increases bank profitability and reduces capital level.(3)Funding liquidity risk can affect bank risk-taking behavior through the intermediary effect of bank loans.(4)With a lower funding liquidity risk,larger asset and higher leverage ratio can restrain banks from taking more risks,and the banks can take less risks during the international fi nancial crisis or higher economic risk periods.

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。

Risk-taking path choice behaviors under ATIS in transportation networks with demand uncertainty

A new travel time reliability-based traffic assignment model is proposed to investigate the effects of an advanced transportation information system (ATIS) on drivers' risk-taking path choice behaviours in transportation networks with demand uncertainty. In the model, drivers are divided into two classes. The first class is not equipped with ATIS, while the second class is equipped with ATIS. Different risk-taking path choice behaviours of the two classes are studied, respectively. A corresponding mixed equilibrium traffic assignment model is formulated as a variational inequality problem in terms of path flows, which is solved by a heuristic solution algorithm. Numerical results indicate that the ATIS can influence the drivers' risk-taking path choice behaviours and the total system travel time in transportation networks with demand uncertainty. It is also found that under higher demand levels, the benefits of ATIS for network performance enhancement may be more obvious.

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%。

Popularity, likeability, and risk-taking in middle adolescence

This study investigated the roles of adolescent popularity and likeability in eight domains of risk-taking in Australian grade 9 students (53% girls). The eight domains included previously examined areas of aggressive behaviours, alcohol use, and sexual intercourse, and areas where there is scarce information, including antisocial activities, unprotected intercourse, body image-related risk-taking, unsafe road practices, and stranger-related risk-taking. The results indicated a clear association between popularity and higher risk-taking in five of the eight domains. This is contrasted with likeability, which was not directly related to risk-taking aside from one two-way interaction with gender for sexual intercourse. The findings demonstrate the importance of including a broader range of risk-taking activities when considering popularity, particularly stranger-related risk-taking.

Development of a Self-Assessment Questionnaire for Nurses’ Risk-Taking Behavior in Medication

Purpose: The purpose of this study was to prepare a self-assessment questionnaire for nurses’ risk-taking behavior (RTB) in medication and to develop a reliable and valid questionnaire. Method: In the first study, a draft of the self-evaluation questionnaire for nurses’ RTB in medication was prepared based on the literature study and qualitative analysis of important case information included in the Project to Collect Medical Near-miss/Adverse Event Information Annual Report of the Ministry of Health, Labor and Welfare. Following the studies, face validity was confirmed, and a questionnaire survey was conducted for nurses who oversee medication nationwide to verify the reliability and validity. Result: The number of subjects was 586 (valid response rate: 94.1%). Item analysis and exploratory factor analysis showed that 4 factors and 12 items for the RTBs in daily life and 4 factors and 20 items for RTBs in medication could be extracted. Confirmatory factor analysis confirmed the fit of the hypothetical model obtained by exploratory factor analysis. In addition, Cronbach’s α coefficient was 0.888. Thus, high reliability and validity were obtained. A correlation was found by comparing the total scores of each RTB factor with the incident/accident group, and a standard for self-evaluation value could be established (p < 0.01). Conclusions: We were able to develop a self-assessment questionnaire for nurses’ risk-taking behavior in medication. This questionnaire will be used by nurses to find out their trends.

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.