Measure of Watershed Ecological Compensation Standard Based on WTP and WTA

In this paper,Liao River Basin was taken as the research object and field surveys were conducted in Fudedian,the source of Liao river mainstream and Panjin,the estuary of Liao River. Through the questionnaires,the willingness to pay ( WTP) and willingness to accept ( WTA) of the residents in Liao River Basin were analyzed. Then based on analysis of the existing ecological compensation standard measuring methods,the WTP and WTA using contingent valuation method ( CVM) were measured and analyzed. Without considering other factors,and based on using the nonparametric estimation method,it was concluded the ecological compensation standard of Liao River Basin was 160. 72 yuan/person·years. When considering other factors,using the parametric estimation we obtain that the ecological compensation standard of Liao River Basin was 255. 97 yuan/person·years. Measuring the respondents' WTP and WTA at the same time and processing the average can actually reflect the respondents' real WTP,thus to a certain extent solving the problems of high compensation caused by formulating ecological compensation standards according to measuring WTP of respondents separately. In addition,the policy suggestions have been proposed from three aspects including financial transfer payment,ecological compensation forms and public participation system. This will not only protect residents' right to know and strengthen public participation and supervision,but also benefit the comprehensive implementation of ecological environment of Liao River Basin and establishment of a long-term mechanism of water resources protection.

Determinants of corporate cash holdings in tranquil and turbulent period:evidence from an emerging economy

Using a sample of 280 firms listed on the Pakistan Stock Exchange,we empirically investigate factors that determine corporate cash holdings in different periods from 2005 to 2014.We divide the sample into three sub-periods—pre-crisis,crisis,and post-crisis—and apply a panel data model to estimate the results.The results suggest that financial crises affect firms’cash holdings policies.Further,findings show that financial crisis has influenced the relationship of size and leverage with cash holdings.In particular,cash flow,liquidity,and tangibility are major determinants of cash holdings in the sub-periods.We present important implications for corporate managers,academicians,and policymakers.

The Relationship between Corporate Social Responsibility and Financial Performance of Iraqi Corporations: A Literature Review

This paper aims to explore past researches that examine the relationship between corporate social responsibility (CSR) and financial performance. The researcher intends to conduct researches that examine the relationship between CSR and financial performance in Iraq corporations. This paper highlights review of literatures from various countries that examine relationships between CSR with financial performance. This paper is based on secondary sources which are accumulated from many researches in Malaysia, Australia, UK, Indonesia, Sri Lanka, Nigerian, and Jordan. The study uses information generated from literature reviewed from different researchers relating to the topic. This method was applied by collecting information from journals and online sources relating to the issue under consideration. Regression analysis documents significant evidence to support a positive relationship between CSR and financial performance. Evidence suggests that CSR leads to good financial performance in Iraq corporations. Findings based on the review revealed that researchers also showed that there was a significant positive relationship between CSR practice and financial performance in Iraq corporations. This study focuses on disclosures made in the corporate annual reports. This is because the annual report is the common document produced by companies on a regular basis and is widely used in prior studies related to CSR. The study provides some important insights for our understanding of CSR in developing economies and its effects on financial performance in the context of Iraq companies.

Harmonization of financial reporting of small and medium-sized enterprises in the Czech Republic

A current problem of the present-day accounting and financial reporting consists in aligning the accounting in small and medium enterprises. In July 2009 the International Financial Reporting Standard for small and medium-sized enterprises was issued, which extended the aligning possibilities also to small and medium enterprises considerably. If the standard is adopted by the national legislation, problems connected with the standard implementation in the national legislation will have to be solved as well as practical issues connected with making financial statements. At present the yields and the problems which can arise in connection with the standard application have to be focused on. A contribution of the standard application will be a better informative ability of financial statements on the international level. At small and medium enterprises this can contribute to better comanunication with banks, with investors, rating application are： parallel reporting according to national agencies etc. The problems connected with the standard regulations, differences between the national legislation and the standard, wide practice at keeping accounts and making financial statements and limited approach of small and medium enterprises to obtaining information and to training of their employees. Another problem can be a tight link between the trading income and the tax base, when small companies prefer rather the tax point of view.

LDNet: A Robust Hybrid Approach for Lie Detection Using Deep Learning Techniques

Deception detection is regarded as a concern for everyone in their daily lives and affects social interactions.The human face is a rich source of data that offers trustworthy markers of deception.The deception or lie detection systems are non-intrusive,cost-effective,and mobile by identifying facial expressions.Over the last decade,numerous studies have been conducted on deception detection using several advanced techniques.Researchers have focused their attention on inventing more effective and efficient solutions for the detection of deception.So,it could be challenging to spot trends,practical approaches,gaps,and chances for contribution.However,there are still a lot of opportunities for innovative deception detection methods.Therefore,we used a variety of machine learning(ML)and deep learning(DL)approaches to experiment with this work.This research aims to do the following:(i)review and analyze the current lie detection(LD)systems;(ii)create a dataset;(iii)use several ML and DL techniques to identify lying;and(iv)create a hybrid model known as LDNet.By combining layers from Vgg16 and DeneseNet121,LDNet was developed and offered the best accuracy(99.50%)of all the models.Our developed hybrid model is a great addition that significantly advances the study of LD.The findings from this research endeavor are expected to advance our understanding of the effectiveness of ML and DL techniques in LD.Furthermore,it has significant practical applications in diverse domains such as security,law enforcement,border control,organizations,and investigation cases where accurate lie detection is paramount.

Technical Components of Total Factor Productivity Growth in Malaysian Manufacturing Industry

This article attempts to disaggregate and explore the components of TFP growth that contribute to changes in output, scale of production, and allocative efficiency and technical efficiency of the Malaysian manufacturing sector. The total factor productivity (TFP) concept defined as total output per unit of all inputs used in the production of an industry has gained a prominent place in academia. The investigation on TFP growth is obviously useful for identifying sources of output growth in the development of an industry. The TFP growth is often interchangeably understood as the technical progress or changes in technology as the sole contributor to economic development. Nonetheless there are other factors contributing to its substance. Knowledge on these technical changes would help decision makers to realize the strengths and weaknesses that contribute to the growth and development of an industry. Alternatively this research would be more beneficial in the case of cross-industry or cross-country comparative studies in order to plan for developmental goal. In such a case a model industry or country can be chosen that exhibits special growth features.

From Importation to Innovation: The Perspective of Organizational Inertia's Effects

Based on an explorative embedded single-case study, this paper analyzes its import-based innovation process, identifies characteristics of manifestation of organizational inertia＇s effects, and reveals organizational learning＇s effects on firms＂ organizational inertia. The case selected is the successful practice about typical technology import of internal combustion locomotive, electric locomotive, and diesel engine, owned by Dalian Locomotive and Rolling Stock Ltd Company of CRRC. Based on analysis, it can be found that firms＇organizational inertia exhibits primarily negative effects, positive effects and a combination of positive and negative effects in different stages of imitative, improved and indigenous innovation respectively. Further analysis of typical events shows that explorative learning mitigates organizational inertia＇s negative effects, while exploitative learning enhances its positive effects. From the angle of organizational inertia＇s effects, this paper deepens understanding on the mechanism of transition from technology importation to indigenous innovation, and provides inspirations for late-coming firms to break the vieious cycle where technology importation leads to more backwardness..

Causalities between Price, Pond Area and Employment in Aquaculture Production

The role of aquaculture industry is becoming more prominent in order to supplement marine capture in meeting the food need for the growing Malaysian population. In an attempt to minimize depletion of marine fisheries, only traditional vessels are allowed to fish along the coastal area while bigger vessels are relegated to deep-sea fishing. During the 9th Malaysian Plan (2006-2010) aquaculture has been recognized as the engine of growth in the national food sector’s development strategy. Future fisheries policy is expected to focus more on aquaculture production, marketing and technological improvement as an alternative to marine capture. This paper investigates the causalities between the selected freshwater fish prices, aquaculture area and production. The study aspires to establish whether or not market price is a key contributor to a rise in the aquaculture area and production. Aquaculture firms comprising the individual culturists are generally motivated by the economic potential of the industry which is reflected in excess of price over cost of production. Our hypothesis is that government policy and initiation rather than prices had give rise to greater participation of culturists and hence augmented the level of employment. However, production increase has a negative implication on environment degradation. Thus there is a conflicting view as regards to the employment opportunity generated by aquaculture undertakings and the need for sustainable development arising from this growing industry. Multivariate time series analysis was used in this investigation.

Inequality of Realization of a Stochastic Dynamics Based on the Erdos Discrepancy Problem

This paper proposes a stochastic dynamics model in which people who are endowed with different discount factors chose to buy the capital stock periodically with different periodicities and are exposed to randomness at arithmetic progression times. We prove that the realization of a stochastic equilibrium may render to the people quite unequal benefits. Its proof is based on Erdös Discrepancy Problem that an arithmetic progression sum of any sign sequence goes to infinity, which is recently solved by Terence Tao [1]. The result in this paper implies that in some cases, the sources of inequality come from pure luck.

应急状态下新冠流行曲线预测的方法学研究——基于北京市百度搜索和传统流感样病例监测

Surveillance is an essential work on infectious diseases prevention and control.When the pandemic occurred,the inadequacy of traditional surveillance was exposed,but it also provided a valuable opportunity to explore new surveillance methods.This study aimed to estimate the transmission dynamics and epidemic curve of severe acute respiratory syndrome coronavirus 2(SARS-Co V-2)Omicron BF.7 in Beijing under the emergent situation using Baidu index and influenza-like illness(ILI)surveillance.A novel hybrid model(multiattention bidirectional gated recurrent unit(MABG)-susceptible-exposed-infected-removed(SEIR))was developed,which leveraged a deep learning algorithm(MABG)to scrutinize the past records of ILI occurrences and the Baidu index of diverse symptoms such as fever,pyrexia,cough,sore throat,anti-fever medicine,and runny nose.By considering the current Baidu index and the correlation between ILI cases and coronavirus disease 2019(COVID-19)cases,a transmission dynamics model(SEIR)was formulated to estimate the transmission dynamics and epidemic curve of SARS-Co V-2.During the COVID-19 pandemic,when conventional surveillance measures have been suspended temporarily,cases of ILI can serve as a useful indicator for estimating the epidemiological trends of COVID-19.In the specific case of Beijing,it has been ascertained that cumulative infection attack rate surpass 80.25%(95%confidence interval(95%CI):77.51%-82.99%)since December 17,2022,with the apex of the outbreak projected to transpire on December 12.The culmination of existing patients is expected to occur three days subsequent to this peak.Effective reproduction number(Rt)represents the average number of secondary infections generated from a single infected individual at a specific point in time during an epidemic,remained below 1 since December 17,2022.The traditional disease surveillance systems should be complemented with information from modern surveillance data such as online data sources with advanced technical support.Modern surveillance channels should be used primarily in emerging infectious and disease outbreaks.Syndrome surveillance on COVID-19 should be established to following on the epidemic,clinical severity,and medical resource demand.

An assessment of China's joint prevention and control policy on sulfur dioxide emissions reduction:A spatial econometric analysis

Sulfur dioxide(SO_(2))is a typical pollutant that affects human health,climate,and environmental and ecological conditions.China has been experiencing high concentrations of SO_(2),particularly in urban areas,since the 1990s.In 2010,a"joint prevention and control"(JPC)policy was issued to address air pollution problems and strengthen the regulation of SO_(2)emissions.This study aimed to describe the mitigation effects of this policy on SO_(2)emissions in 116 Chinese cities from 2003 to 2017.We applied global and local Moran's I indices to confirm the presence of significant spatial autocorrelation in SO_(2)emissions and constructed four spatial models to assess the effect of the JPC policy in reducing SO_(2)emissions and its transmission mechanism.We found that the policy decreased SO_(2)emissions by 1.89×10^(4)tons,S0_(2)intensity by 1.70 tons per km^(2),and S0_(2)per capita of 158.49 tons per 10,000 people in each city,on average,all of which are significant changes.The empirical results also show that population growth,economic structure,and environmental protection significantly decrease SO_(2)emissions.Finally,we recommended policies to encourage regional cooperation under the JPC policy,with the aim of promoting furtherreductions in SO_(2)emissions.

Exploring the Lagged Correlation Between Baidu Index and Influenza-Like Illness-China,2014-2019

Introduction:This study investigated the lagged correlation between Baidu Index for influenza-related keywords and influenza-like illness percentage(ILI%)across regions in China.The aim is to establish a scientific foundation for utilizing Baidu Index as an early warning tool for influenza-like illness epidemics.Methods:In this study,data on ILI%and Baidu Index were collected from 30 provincial-level administrative divisions(PLADs)spanning April 2014 to March 2019.The Baidu Index was categorized into Overall Index,Ordinary Index,Prevention Index,Symptom Index,and Treatment Index based on search query themes.The lagged correlation between the Baidu Index and ILI%was examined through the cross-correlation function(CCF)method.Results:Correlating the Baidu Overall Index of 30 PLADs with ILI%revealed CCF values ranging from 0.46 to 0.86,with a median lag of 0.5 days.Subcategory analysis indicated that the Prevention Index and Symptom Index exhibited quicker responses to ILI%,with median lags of−9 and−0.5 days,respectively,compared to 0 and 3 days for the Ordinary and Treatment Indexes.The median lag days between the Baidu Index and the ILI%were earlier in the northern PLADs compared to the southern PLADs.Discussion:The Prevention and Symptom Indexes show promising predictive capabilities for influenzalike illness epidemics.

Predicting influenza-like illness trends based on sentinel surveillance data in China from 2011 to 2019:A modelling and comparative study

Background Influenza is an acute respiratory infectious disease with a significant global disease burden.Additionally,the coronavirus disease 2019 pandemic and its related non-pharmaceutical interventions(NPIs)have introduced uncertainty to the spread of influenza.However,comparative studies on the performance of innovative models and approaches used for influenza prediction are limited.Therefore,this study aimed to predict the trend of influenza-like illness(ILI)in settings with diverse climate characteristics in China based on sentinel surveillance data using three approaches and evaluate and compare their predictive performance.Methods The generalized additive model(GAM),deep learning hybrid model based on Gate Recurrent Unit(GRU),and autoregressive moving average-generalized autoregressive conditional heteroscedasticity(ARMA—GARCH)model were established to predict the trends of ILI 1-,2-,3-,and 4-week-ahead in Beijing,Tianjin,Shanxi,Hubei,Chongqing,Guangdong,Hainan,and the Hong Kong Special Administrative Region in China,based on sentinel surveillance data from 2011 to 2019.Three relevant metrics,namely,Mean Absolute Percentage Error(MAPE),Root Mean Squared Error(RMSE),and R squared,were calculated to evaluate and compare the goodness of fit and robustness of the three models.Results Considering the MAPE,RMSE,and R squared values,the ARMA—GARCH model performed best,while the GRU-based deep learning hybrid model exhibited moderate performance and GAM made predictions with the least accuracy in the eight settings in China.Additionally,the models’predictive performance declined as the weeks ahead increased.Furthermore,blocked cross-validation indicated that all models were robust to changes in data and had low risks of overfitting.Conclusions Our study suggested that the ARMA—GARCH model exhibited the best accuracy in predicting ILI trends in China compared to the GAM and GRU-based deep learning hybrid model.Therefore,in the future,the ARMA—GARCH model may be used to predict ILI trends in public health practice across diverse climatic zones,thereby contributing to influenza control and prevention efforts.

Duopoly Competition Between Chauffeured Car and Taxi:An Analysis of Pricing and Market Segmentation

Chauffeured car service(CCS) has developed rapidly in recent years. Although CCS brings convenience and effectiveness, it also triggers some new problems like vicious competition. This work studies the duopoly competition between CCS company and taxi company, in terms of different average cost and number of vehicles of two companies. To find the solutions like the pricing scheme to ease the vicious competition, Hotelling model is introduced. The Hotelling-type model is used to present passengers’ preferences to the companies. Besides, failing situation is taken into account in the Hotelling model to describe the situation where passenger’s demand is not satisfied in reality. This work theoretically analyzes the price scheme and equilibrium market segmentation based on the average cost and number of vehicles of each company. Furthermore, companies’ profits, passengers’ utility and social welfare in equilibrium are revealed based on the game theory. The study shows that both of companies can get optimal profits by setting effective price scheme. The company which has higher price, definitely gets less market share. In addition, moderate competition can lead to positive influence on social welfare.

A hybrid approach for evaluating CPT-based seismic soil liquefaction potential using Bayesian belief networks

Discernment of seismic soil liquefaction is a complex and non-linear procedure that is affected by diversified factors of uncertainties and complexity.The Bayesian belief network(BBN)is an effective tool to present a suitable framework to handle insights into such uncertainties and cause–effect relationships.The intention of this study is to use a hybrid approach methodology for the development of BBN model based on cone penetration test(CPT)case history records to evaluate seismic soil liquefaction potential.In this hybrid approach,naive model is developed initially only by an interpretive structural modeling(ISM)technique using domain knowledge(DK).Subsequently,some useful information about the naive model are embedded as DK in the K2 algorithm to develop a BBN-K2 and DK model.The results of the BBN models are compared and validated with the available artificial neural network(ANN)and C4.5 decision tree(DT)models and found that the BBN model developed by hybrid approach showed compatible and promising results for liquefaction potential assessment.The BBN model developed by hybrid approach provides a viable tool for geotechnical engineers to assess sites conditions susceptible to seismic soil liquefaction.This study also presents sensitivity analysis of the BBN model based on hybrid approach and the most probable explanation of liquefied sites,owing to know the most likely scenario of the liquefaction phenomenon.

Conditional dependence between oil price and stock prices of renewable energy: a vine copula approach

The current paper focusses on the co-movement between oil prices and renewable energy stock markets in a multivariate framework.The vine copula approach that offers a great flexibility in conditional dependence modelling is used.More specifically,we investigate the issue of the average dependence and co-movement between oil prices(West Texas Intermediate[WTI])and renewable energy stock prices(Wilder Hill New Energy Global Innovation Index[NEX],Wilder Hill Clean Energy Index[ECO]and S and P Global Clean Energy Index[SPGCE])by applying the vine copula based threshold generalised autoregressive conditional heteroskedasticity(TGARCH)model.Over the period 2003–2016,empirical findings reveal significant and symmetric dependence between the considered markets.Therefore,there is symmetric tail dependence,indicating the evidence of upper and lower tail dependence.This means that movements in oil prices and renewable energy indices are coupled to the same direction.These empirical insights are of particular interest to policymakers,risk managers and investors in renewable energy sector.

Ecological Risk Management of Drinking Water Project: The Case Study of Kunming City

Following rapid infrastructure development and industrialization, the problems of water pollution and water shortage have become more severe. Whether there is safe drinking water in cities has attracted wide attention.The ecological risk management of drinking water project is an important means of ensuring the safety of a drinking water source. Based on ecological risk assessment and management theories, this paper establishes an ecological risk management model and assessment system with the aim of providing theoretical guidance and scientific basis for formulating a policy on the safety and protection of drinking water sources in a city. Kunming is one of the cities plagued by severe water shortage in China. Its ecological risk management of drinking water has attracted the attention of both the local government and the public.Using Kunming as the case study, this paper conducts a comparative analysis and assessment on three major reservoirs that face ecological risks. It highlights the existing problems and gives helpful suggestions.

A Nonlinear Interval Portfolio Selection Model and Its Application in Banks

In classical Markowitz＇s Mean-Variance model, parameters such as the mean and covari- ance of the underlying assets＇ future return are assumed to be known exactly. However, this is not always the case. The parameters often correspond to quantities that fall within a range, or can be known ambiguously at the time when investment decision must be made. In such situations, investors determine returns on investment and risks etc. and make portfolio decisions based on experience and economic wisdom. This paper tries to use the concept of interval numbers in the fuzzy set theory to extend the classical mean-variance portfolio selection model to a mean-downside semi-variance model with consideration of liquidity requirements of a bank. The semi-variance constraint is employed to control the downside risk, filling in the existing interval portfolio optimization model based on the linear semi-absolute deviation to depict the downside risk. Simulation results show that the model behaves robustly for risky assets with highest or lowest mean historical rate of return and the optimal investment proportions have good stability. This suggests that for these kinds of assets the model can reduce the risk of high deviation caused by the deviation in the decision maker＇s experience and economic wisdom.

The Influence of Third-party E-Commerce Platform Price Limits on the Dual-Channel Strategy of Manufacturers

Powerful platform operators always set price limits for sellers on the platform. This paper establishes Stackelberg game models according to two pricing models when the manufacturer enters the third-party e-commerce platform and sells products online. The first is a seller-pricing model in which the manufacturer decides the online price. The second is a platform-pricing model in which the platform decides the online price. We obtain the equilibrium results for these two models and the condition that allows the manufacturer to adopt the dual-channel strategy by comparing the operation decisions and performance of supply-chain members in the two models. Results show that the dual-channel strategy of the manufacturer always decreases the profit of the traditional retailer. In comparison with the sellerpricing model, the platform-pricing model always erodes parts of the manufacturers profit obtained by the dual-channel strategy. The manufacturer will pass on the partial loss to the retailer using relative leadership in the platform-pricing model, which renders the profit of the retailer lower than that in the seller-pricing model. Also, price limits do not always bring the platform more profits;sometimes the platform is forced to set a low price.

MEAN-VARIANCE MODEL BASED ON FILTERS OF MINIMUM SPANNING TREE

This study aims to reduce the statistical uncertainty of the correlation coefficient matrix in the mean-variance model of Markowitz. A filtering algorithm based on minimum spanning tree （MST） is proposed. Daily data of the 30 stocks of the Hang Seng Index （HSI） and Dow Jones Index （DJI） from 2004 to 2009 are selected as the base dataset. The proposed algorithm is compared with the Markowitz method in terms of risk, reliability, and effective size of the portfolio. Results show that （1） although the predicted risk of portfolio built with the MST is slightly higher than that of Markowitz, the realized risk of MST filtering algorithm is much smaller; and （2） the reliability and the effective size of filtering algorithm based on MST is apparently better than that of the Markowitz portfolio. Therefore, conclusion is that filtering algorithm based on MST improves the mean-variance model of Markowitz.