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.

Impacts of COVID-19 Lockdown on the Banking Activities in Conakry

Introduction: The COVID-19 pandemic has affected all professional sectors to varying degrees. It has forced companies to restructure, initiate and promote telework. The aim was to study the impacts of COVID-19 lockdown on banking activities in Conakry. Materials and Methods: This was a descriptive cross-sectional study over seven months (from November 25, 2020 to June 27, 2021) and multicentric. It included thirteen of the eighteen banks of the main city of the capital Conakry (Kaloum). We analysed socio-demographic data and occupational characteristics. We paid particular attention to banking activities and medical datas. Results: During our study period, 875 workers met to our criteria, one third of whom were men. The average age was 37.93 ± 9.39 years [22 - 71]. Financial accounters were the most represented and average seniority at the job was 5.35 years. The work schedule was reduced during lockdown but an telework increased (29.8%). On the medical datas, the prevalence of COVID-19 was 20.7%;the lethality rate was 0.6% and the absentee rate 15.6%. The COVID-19 lockdown has deeply impacted the banking activities in Conakry particularly the productivity by a significant decrease in net banking income. Conclusion: Despite the continuity of activities during this pandemic, banks have experienced a reduction in their productivity resulting in a significant decrease in net banking income. These impacts of COVID-19 on the banking sector reflect its impact on the national economy.

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.

GHG Emissions of Italian Unlisted Firms and Bank Debt

In this paper I investigate the effect of the greenhouse gas emissions of a sample of 478 Italian unlisted firms on their bank debt,in the context of the growing attention and awareness for climate change issue.My findings show that unlisted firms generating low levels of greenhouse gas emissions borrow less long-term,short term,and total bank debt than unlisted firms generating high levels of greenhouse gas emissions,to finance their growth opportunities.Being the first work analyzing this topic,to the best of my knowledge,further empirical research could also investigate the impact of greenhouse gas emissions on the bank financing of unlisted firms of different countries,representing specific cultural and political approaches towards climate change problems.

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.

Research on Career Development Paths and Incentive Model Design for Middle Managers in Banks

With the rapid development of financial technology,middle managers in banks face both new challenges and opportunities.This paper conducts an in-depth analysis of the current state and issues surrounding the career development of middle managers in banks and explores effective incentive model designs and implementation strategies.Employing both quantitative and qualitative evaluation methods,the study assesses the practical impact of various incentive models.Through case analysis,targeted improvement suggestions are proposed.The findings reveal that a well-designed incentive mechanism significantly enhances middle managers’job satisfaction and loyalty,which is essential for the sustained growth of banks.

Investigating customer churn in banking:a machine learning approach and visualization app for data science and management

Customer attrition in the banking industry occurs when consumers quit using the goods and services offered by the bank for some time and,after that,end their connection with the bank.Therefore,customer retention is essential in today’s extremely competitive banking market.Additionally,having a solid customer base helps attract new consumers by fostering confidence and a referral from a current clientele.These factors make reducing client attrition a crucial step that banks must pursue.In our research,we aim to examine bank data and forecast which users will most likely discontinue using the bank’s services and become paying customers.We use various machine learning algorithms to analyze the data and show comparative analysis on different evaluation metrics.In addition,we developed a Data Visualization RShiny app for data science and management regarding customer churn analysis.Analyzing this data will help the bank indicate the trend and then try to retain customers on the verge of attrition.

Study on the Countermeasures to Improve the Public Outdoor Leisure and Fitness Function on the Two Rivers and Four Banks in the Main Urban Area of Chongqing

The main urban area of Chongqing is surrounded by two rivers and set against each other.With its unique waterfront landscape,it has the resource conditions to become a leisure tourism destination.Intending to enhance people’s happiness,improve city quality,and promote Chongqing’s main urban area to become a tourist destination,this paper finds out the existing problems in the construction of public outdoor leisure and fitness facilities on the two rivers and four banks of Chongqing’s main urban area through investigation and analysis based on relevant experiences at home and abroad,takes the value chain theory as the guidance,and to find solutions to the problem.On this basis,combined with the law of economic operation,this paper puts forward the guiding ideology,principles,development goals,functional orientation,and development path for the improvement of public outdoor leisure and fitness on two rivers and four banks in the main city of Chongqing,and accordingly puts forward the policy system and guarantee measures for its improvement.

盐度和淹水频率对上海崇明东滩盐沼湿地近海区域土壤种子库动态的影响

以上海崇明东滩盐沼湿地近海区域不同群落(生境)土壤种子库为研究对象,通过在温室内模拟潮汐作用,探究土壤盐度、淹水频率及其交互作用对土壤种子库萌发动态的影响。结果表明:崇明东滩盐沼湿地近海区域海三棱藨草(×Bolboschoenoplectus mariqueter(Tang et F.T.Wang)Tatanov)群落、互花米草(Spartina alterniflora Loisel.)群落、芦苇(Phragmites australis(Cav.)Trin.ex Steud.)群落和光滩生境土壤种子库共萌发出13种植物,隶属于7科12属,其中海三棱藨草、马唐(Digitaria sanguinalis(Linn.)Scop.)和升马唐(Digitaria ciliaris(Retz.)Koeler)的总频度较高,分别为0.108、0.064和0.059。禾本科(Poaceae)和莎草科(Cyperaceae)是崇明东滩盐沼湿地近海区域土壤种子库萌发植物群落的典型科。本地植物(海三棱藨草和芦苇)群落土壤种子库主要萌发海三棱藨草、马唐和升马唐;而入侵植物(互花米草)群落土壤种子库主要萌发马唐、升马唐和碱菀(Tripolium pannonicum(Jacquin)Dobroczajeva),其中碱菀仅在互花米草群落土壤种子库中萌发。海三棱藨草群落土壤种子库对不同盐度和淹水频率的适应性较强。除光滩生境外,其他3种群落土壤种子库在盐度0.0%、0.5%、1.0%和1.5%以及淹水频率1、3、7、10 d处理条件下均有海三棱藨草萌发。与对照(淡水湿润)处理条件相比较,不同盐度和淹水频率处理显著(P<0.05)降低了该区域土壤种子库萌发植物群落的植株密度和物种多样性。综上所述,在恢复崇明东滩盐沼湿地的本地植物群落时,利用土壤种子库是一个可行的途径,其中特别推荐海三棱藨草群落的土壤种子库。

商业银行数字化与企业杠杆操纵

数字技术的发展和应用正在重塑金融行业的业务与服务模式,数字化已经成为商业银行新的发展战略。基于中国246家商业银行及2567家A股上市公司2013—2022年数据,探究了商业银行是否可以通过数字化来降低企业杠杆操纵行为,并深入分析其作用机制。研究发现,商业银行数字化能够显著抑制企业的杠杆操纵行为,其中管理数字化对企业杠杆操纵的抑制作用更强。提高企业长期贷款水平、降低融资成本、提高内部治理水平、减少银行对企业会计信息依赖是商业银行数字化影响企业杠杆操纵行为的主要机制。进一步分析表明,该抑制作用在资本市场融资能力强、成长性高及中小企业中更为明显。通过对商业银行数字化微观纠偏功能的研究,不仅从新视角揭示商业银行数字化对企业杠杆操纵行为的影响路径,也为进一步挖掘商业银行数字化意义提供新证据。

降雨及库水位变动对向阳水库岸坡稳定性的影响研究

在水的作用下,岸坡内地下水渗流场和岩土体力学性质发生变化,从而影响岸坡的整体稳定性。以重庆市向阳水库平进村岸坡工程为例,基于非饱和流固耦合理论、弹塑性理论和强度折减法,采用有限差分方法,分析在降雨工况、库水位升降等多种工况条件下平进村Ⅱ级缓坡的滑移破坏模式和安全系数变化规律,评价在岸坡前缘段采取压脚治理措施的防护效果。结果表明:①在不同工况下,岸坡均存在3种潜在滑移模式,即坡表覆盖层滑移、沿浅层软弱夹层滑移以及沿深层破碎夹层滑移。②岸坡天然地下水位埋深浅,当遭遇极端降雨时,大量雨水入渗将引起地下水位上抬,坡体有效应力降低,抗剪能力削弱,导致边坡稳定性明显降低。③采取前缘压脚防护措施可有效提高岸坡整体稳定性,压脚前后岸坡多滑移模式的安全系数提高约0.01~0.30。

库岸塔柱状危岩的压裂耦合损伤-突变失稳预测

位于三峡库区巫峡段消落带的塔柱状危岩,其底部多损伤因素的耦合作用下常呈压裂诱发座溃整体失稳模式,危岩底部耦合损伤至突变机制是研究该类库岸危岩体失稳预警的关键科学问题.以三峡库区库岸巫峡段箭穿洞塔柱状危岩体为例,将危岩体简化为中上部非劣化区和下部劣化区的二元地质力学模型,基于应变等价原理获得其危岩体下部劣化区的荷载效应、溶蚀效应、干湿循环弱化效应的耦合损伤本构模型和总损伤度演化方程,根据地质力学模型概化为等效弹簧模型转化为力-位移的耦合损伤本构方程;基于能量平衡原理和突变理论建立了塔柱状危岩的耦合损伤-折叠突变模型,获取了其失稳判据和临界位移的表达式.通过案例分析结果表明:该危岩体突变失稳时的系统控制变量为-0.0073,预测模型计算理论的突变起点垂向位移为42.2mm,终止点位移为60.5mm,当监测数据危岩体最大垂向累积位移为26.2mm时,小于突变起始位移时就采用及时治理措施,与危岩未失稳的状态吻合.其研究成果可为三峡库区灰岩地区库岸塔柱状压溃型危岩的监测预警与防治提供重要的理论支撑.

多核共享缓存bank冲突分析及其延迟最小化

在硬实时多核系统中,共享资源冲突的问题为硬实时任务的最差情况下执行时间(WCET)分析带来了新挑战.虽然现有的共享缓存冲突分析技术在storage冲突方面已取得研究进展,但对于bank冲突而言,现有研究仍局限于通过界定bank冲突延迟上限来分析和处理bank冲突.该文通过优化核-bank映射关系来使硬实时多核系统中的bank冲突延迟最小化,即在对bank冲突延迟进行分析的基础上,首先通过优化核-bank之间的映射关系来消除bank冲突;若无法消除,则需要寻找能使bank冲突延迟最小化的核-bank映射关系解,并为此设计了一种基于多核总线请求时间序列的bank冲突延迟求解算法.最后,文中设计了能够对总线访问延迟进行消重的多核硬实时任务WCET估算方法.实验结果表明:文中所提的优化方法可消除这类bank冲突或使其延迟最小化,文中所提的WCET估算方法与现有估算方法相比可获得更精确的最差情况下执行时间(WCET).

从信息不对称角度审视农村金融的困境与出路

农村金融市场的信息不对称问题突出,且有其自身特点,设计农村金融制度必须以此为基础和出发点。为此,针对中国农村金融的困境,除采取运用数字技术改进农村金融经营模式、健全治理结构、差异化经营、强化监管等措施外,更重要的是针对农村市场的信息不对称,构建以声誉机制为基础、以社区银行为载体的农村信贷体系,数字金融在其中起辅助作用。

Preparation of DNA from Silica Gel Dried Mini_amount of Leaves of Oryza rufipogon for RAPD Study and Total DNA Bank Construction

Gene resources of Oryza rufipogon Griff. play a crucial role in rice breeding, and hence to study their conservation is of utter importance. The authors describe a method for preparation of DNA from mini_amount of the silica_gel_dried leaves of Oryza rufipogon . The high molecular weight DNAs of 1?168 individuals representing 44 populations have been obtained with high yields, which could be used for RAPD PCR and construction of total DNA bank of this species. The template DNA from silica_gel_dried leaves stored for one year at room temperature gave the same RAPD results as that from the newly prepared silica_gel_dried leaves. The optional template DNA concentrations for amplification ranged from 3.1 ng to 50 ng. In addition, the quality and quantity of the template DNAs that affect RAPD results are also discussed.

Heterogeneity in Soil Seed Banks in a Mediterranean Coastal Sand Dune

Characteristics of total soil seed banks and permanent soil seed banks in three microhabitats in a Mediterranean coastal sand dune were investigated by using natural germination method combined with physically scanning separation method. The composition and structure of soil seed banks were analyzed between the microhabitats by using functional group method. The distribution patterns of soil seed bank were also analyzed between the microhabitats. We also analyzed the relationship between seed size and seed persistence in soil. The results show greatly spatial heterogeneity existed in soil seed bank of the Mediterranean coastal sand dune, even in the same microhabitats seed distribution was uneven. Sometimes a great difference occurred between them. Microhabitats significantly affected the distribution patterns of total soil seed banks and seed banks of the functional groups. The open area generally had the greater densities of seeds, but the seed densities under shrub and in trail were lower than that in the open area. Legumes seeds accounted for 76.0% total persistent seed banks. Annual and perennial grasses produced transient seed banks as no seeds were retrieved from the sieved soils. Seed persistence of legumes, umbeliferaes, perennial forbs, compositaes, annual forbs, crucifer decreased gradually. They were 50.1%, 45.6%, 40.6%, 6.3%, 5.6% and 0.6% respectively in the soil. There was a positive relationship between seed size and seed persistence. Bigger seeds had higher persistence, and vice versa.