An innovative classification system for ranking the biological effects of marine aromatic hydrocarbons based on fish embryotoxicity

Petroleum hydrocarbon pollution is a global concern,particularly in coastal environments.Polycyclic aromatic hydrocarbons(PAHs) are regarded as the most toxic components of petroleum hydrocarbons.In this study,the biomonitoring and ranking effects of petroleum hydrocarbons and PAHs on the marine fish model Oryzias melastigma embryos were determined in the Jiulong River Estuary(JRE) and its adjacent waters in China.The results showed that the levels of petroleum hydrocarbons from almost all sites met the primary standard for marine seawater quality,and the concentrations of the 16 priority PAHs in the surface seawater were lower compared with those in other coastal areas worldwide.A new fish expert system based on the embryotoxicity of O.melastigma(OME-FES) was developed and applied in the field to evaluate the biological effects of petroleum hydrocarbons and PAHs.The selected physiological index and molecular indicators in OME-FES were appropriate biomarkers for indicating the harmful effects of petroleum hydrocarbons and PAHs.The outcome of OME-FES revealed that the biological effect levels of the sampling sites ranged from level Ⅰ(no stress) to level Ⅲ(medium stress),which is further corroborated by the findings of nested analysis of variance(ANOVA) models.Our results suggest that the OME-FES is an effective tool for evaluating and ranking the biological effects of marine petroleum hydrocarbons and PAHs.This method may also be applied to evaluate other marine pollutants based on its framework.

The interactions between Chinese local corn and WTI crude oil prices:an empirical analysis

This paper investigates the relationship between China’s fuel ethanol promotion plan and food security based on the interactions between the crude oil market, the fuel ethanol market and the grain market. Based on the US West Texas Intermediate(WTI) crude oil spot price and Chinese corn prices from January 2008 to May 2018, this paper applies Granger causality testing and a generalized impulse response function to explore the relationship between world crude oil prices and Chinese corn prices. The results show that crude oil prices are not the Granger cause of China’s corn prices, but changes in world crude oil prices will have a long-term positive impact on Chinese corn prices. Therefore, the Chinese government should pay attention to changes in crude oil prices when promoting fuel ethanol. Considering the conduction e ect between fuel ethanol and the food market, the government should also take some measures to ensure food security.

Empirical Analysis on the Role Rural Urbanization in Promoting Economic Growth by Expanding Consumption

Urbanization construction is a historical mission of China's modernization construction,and is also the largest potential for expanding domestic demand. Actively promoting rural urbanization is favorable for expanding consumption and boosting economic growth. Through building VAR model using data of urbanization level and consumption in 1978- 2012,this paper made Granger causality test,impulse response analysis,and variance decomposition analysis on the relation between urbanization and economic growth. In addition,from comparing the effect of urbanization on expanding rural consumption and urban consumption,it is known that the effect of growth of urbanization rate on urban consumption is lower than rural consumption in short term,but urbanization level has a greater contribution to growth of urban consumption in the long run.

Analysis of the Dynamic Relationship among Financial Fund for Agriculture, Agricultural Output Value and Farmers' income

By using the methods of co-integration, impulse response function and variance decomposition, I conduct the empirical research on the dynamic relationship among China's financial fund for agriculture, agricultural output value, and farmers' income from the year 1978 to the year 2009. The results indicate that the government's financial fund for agriculture plays the significant role in promoting agricultural output value and farmers' income in the long run, but this role of promoting is not prominent in the short run; in the mean time, agricultural output value plays insignificant role in promoting farmers' income and the government's financial fund for agriculture; farmers' income plays the significant role in promoting agricultural output value and the government's financial fund for agriculture.

Optimization of the gas separation performance of polyurethane–zeolite 3A and ZSM-5 mixed matrix membranes using response surface methodology

In the present work, the response surface method software was used with five measurement levels with three factors.These were applied for the optimization of operating parameters that affected gas separation performance of polyurethane–zeolite 3A, ZSM-5 mixed matrix membranes.The basis of the experiments was a rotatable central composite design(CCD).The three independent variables studied were: zeolite content(0–24 wt%), operating temperature(25–45 ℃) and operating pressure(0.2–0.1 MPa).The effects of these three variables on the selectivity and permeability membranes were studied by the analysis of variance(ANOVA).Optimal conditions for the enhancement of gas separation performances of polyurethane–3A zeolite were found to be 18 wt%, 30 ℃ and 0.8 MPa respectively.Under these conditions, the permeabilities of carbon dioxide, methane, oxygen and nitrogen gases were measured at 138.4, 22.9, 15.7 and 6.4 Barrer respectively while the CO_2/CH_4, CO_2/N_2 and O_2/N_2 selectivities were 5.8, 22.5 and 2.5, respectively.Also, the optimal conditions for improvement of the gas separation performance of polyurethane–ZSM 5 were found to be 15.64 wt%, 30 ℃ and 4 bar.The permeabilities of these four gases(i.e.carbon dioxide, methane, oxygen and nitrogen) were 164.7, 21.2, 21.5 and 8.1 Barrer while the CO_2/CH_4, CO_2/N_2 and O_2/N_2 selectivities were 7.8, 20.6 and 2.7 respectively.

Interval analysis method and convex models for impulsive response of structures with uncertain-but-bounded external loads

Two non-probabilistic, set-theoretical methods for determining the maximum and minimum impulsive responses of structures to uncertain-but-bounded impulses are presented. They are, respectively, based on the theories of interval mathematics and convex models. The uncertain-but-bounded impulses are assumed to be a convex set, hyper-rectangle or ellipsoid. For the two non-probabilistic methods, less prior information is required about the uncertain nature of impulses than the probabilistic model. Comparisons between the interval analysis method and the convex model, which are developed as an anti-optimization problem of finding the least favorable impulsive response and the most favorable impulsive response, are made through mathematical analyses and numerical calculations. The results of this study indicate that under the condition of the interval vector being determined from an ellipsoid containing the uncertain impulses, the width of the impulsive responses predicted by the interval analysis method is larger than that by the convex model; under the condition of the ellipsoid being determined from an interval vector containing the uncertain impulses, the width of the interval impulsive responses obtained by the interval analysis method is smaller than that by the convex model.

Effect of frequency and pulse-on time of high power impulse magnetron sputtering on deposition rate and morphology of titanium nitride using response surface methodology

Titanium nitride thin films were deposited on silicon by high power impulse magnetron sputtering(HiPIMS)method at different frequencies(162-637 Hz)and pulse-on time(60-322μs).Response surface methodology(RSM)was employed to study the simultaneous effect of frequency and pulse-on time on the current waveforms and the crystallographic orientation,microstructure,and in particular,the deposition rate of titanium nitride at constant time and average power equal to 250 W.The crystallographic structure and morphology of deposited films were analyzed using XRD and FESEM,respectively.It is found that the deposition rate of HiPIMS samples is tremendously dependent on pulse-on time and frequency of pulses where the deposition rate changes from 4.5 to 14.5 nm/min.The regression equations and analyses of variance(ANOVA)reveal that the maximum deposition rate(equal to(17±0.8)nm/min)occurs when the frequency is 537 Hz and pulse-on time is 212μs.The experimental measurement of the deposition rate under this condition gives rise to the deposition rate of 16.7 nm/min that is in good agreement with the predicted value.

Optimization of the Ultrasonic-assisted Extraction Process for Protocatechuic Acid from Emilia sonchifolia DC by Response Surface Methodology

[Objectives] This study was conducted to optimize the extraction process of protocatechuic acid from Emilia sonchifolia DC. [Methods] The optimal extraction conditions were determined by single factor,response surface analysis and variance analysis,and the content of protocatechuic acid was determined by HPLC. [Results] The protocatechuic acid standard curve equation was: y = 1 435 x + 8 403,R^2= 0. 999 8,indicating a good linear relationship. The optimal extraction conditions were as follows: a temperature at 80 ℃,an extraction time of 1 h,a material-to-liquid ratio at 1:10 and an ultrasonic power of 600 W,and the content of protocatechuic acid extracted was 1. 93 mg/g. The method showed a RSD of 0. 41%,less than 2%,and the detection limit was 0. 0000047261 g/ml.The experimental sample X1 was the low-level 0. 1 mg/ml standard solution,which showed recovery of protocatechuic acid between 100.8% and 105.2%,with a RSD of 0. 013%;and the sample X2 was the high-level 1. 0 mg/ml standard solution,which exhibited recovery between 100. 6% and 102. 2%,with a RSD of 0.076%. Thus,the recovery was high,and the requirements of the performance index were met. [Conclusions] The detection method is stable and reliable and can produce satisfactory results.

The impact of foreign trade and FDI on environmental pollution

Over the past 30 years China＇s economy has made tremendous development and going on the road of opening-up is an important aspect of the successful experience, which should be unswervingly adhered to in the further. However, rationally looking at how different the impact of foreign economic activities on China＇s economy and society is economic workers＇ main task. From 1982 to 2006, based on six categories of China＇s environmental indicators, the paper improves the entropy method to calculate the environmental pollution index which can represent China＇s overall environmental situation, uses the VAR model of the impulse response function and variance decomposition method to study the impact of foreign trade, FDI on China＇s environmental pollution in the long-term. The results show that, FDI and import trade is conducive to the improvement of the quality of our environment and export trade is the deterioration of our environment, ＂pollution haven＂ hypothesis is proved in China. Export trade is an important variable that aggravates environmental pollution.

Third Order Adjoint Sensitivity and Uncertainty Analysis of an OECD/NEA Reactor Physics Benchmark: III. Response Moments

The (180)3 third-order mixed sensitivities of the leakage response of a polyethylene-reflected plutonium (PERP) experimental benchmark with respect to the benchmark’s 180 microscopic total cross sections have been computed in accompanying works [1] [2]. This work quantifies the contributions of these (180)3 third-order mixed sensitivities to the PERP benchmark’s leakage response distribution moments (expected value, variance and skewness) and compares these contributions to those stemming from the corresponding first- and second-order sensitivities of the PERP benchmark’s leakage response with respect to the total cross sections. The numerical results obtained in this work reveal that the importance of the 3rd-order sensitivities can surpass the importance of the 1st- and 2nd-order sensitivities when the parameters’ uncertainties increase. In particular, for a uniform standard deviation of 10% of the microscopic total cross sections, the 3rd-order sensitivities contribute 80% to the response variance, whereas the contribution stemming from the 1st- and 2nd-order sensitivities amount only to 2% and 18%, respectively. Consequently, neglecting the 3rd-order sensitivities could cause a very large non-conservative error by under-reporting the response variance by a factor of 506%. The results obtained in this work also indicate that the effects of the 3rd-order sensitivities are to reduce the response’s skewness in parameter space, rendering the distribution of the leakage response more symmetric about its expected value. The results obtained in this work are the first such results ever published in reactor physics. Since correlations among the group-averaged microscopic total cross sections are not available, only the effects of typical standard deviations for these cross sections could be considered. Due to this lack of correlations among the cross sections, the effects of the mixed 3rd-order sensitivities could not be quantified exactly at this time. These effects could be quantified only when correlations among the group-averaged microscopic total cross sections would be obtained experimentally by the nuclear physics community.

Third-Order Adjoint Sensitivity Analysis of an OECD/NEA Reactor Physics Benchmark: I. Mathematical Framework

This work extends to third-order previously published work on developing the adjoint sensitivity and uncertainty analysis of the numerical model of a polyethylene-reflected plutonium (acronym: PERP) OECD/NEA reactor physics benchmark. The PERP benchmark comprises 21,976 imprecisely known (uncertain) model parameters. Previous works have used the adjoint sensitivity analysis methodology to compute exactly and efficiently all of the 21,976 first-order and (21,976)2 second-order sensitivities of the PERP benchmark’s leakage response to all of the benchmark’s uncertain parameters, showing that the largest and most consequential 1st- and 2nd-order response sensitivities are with respect to the total microscopic cross sections. These results have motivated extending the previous adjoint-based derivations to third-order, leading to the derivation, in this work, of the exact mathematical expressions of the (180)3 third-order sensitivities of the PERP leakage response with respect to these total microscopic cross sections. The formulas derived in this work are valid not only for the PERP benchmark but can also be used for computing the 3rd-order sensitivities of the leakage response of any nuclear system involving fissionable material and internal or external neutron sources. Subsequent works will use the adjoint-based mathematical expressions obtained in this work to compute exactly and efficiently the numerical values of these (180)3 third-order sensitivities (which turned out to be very large and consequential) and use them for a third-order uncertainty analysis of the PERP benchmark’s leakage response.

The Effects of Oil Price Volatility on Some Macroeconomic Variables in Nigeria： Application of Garch and Var Models

The price of Nigeria＇s premium crude, the Bonny light has declined by about 51.8 percent between September 2014 and January 2015. Given that this resource is the major source of revenue for Nigeria, the possible effects on the economy of these continuing shocks in oil prices are definitely of prime interest in order to predict the effects of a drastic change in oil prices, on the Nigerian economy as a whole. This study investigates the impact of oil price shocks on the Nigerian economy using quarterly time series data from 1985Q2-2014Q3. The study employed GARCH model and a multivariate VAR analysis using impulse response functions and variance decompositions tests to examine the interrelationship among the variables. The impulse response functions show that oil price shocks have immediate and prolonged effect on all the macroeconomic variables considered. Thus, we conclude that oil price shocks have a direct impact on real GDP, total monetary assets and credit to private sector and as such urgent and serious efforts should be made to cut back on government expenditure, increase the tax base, diversify the economy and improve the overall efficiency and scope of other existing non-oil revenue sources, so as to ameliorate the impact of falling oil prices.

The Research of the Correlation between Stock Market and Macroeconomy--Based on Comparison of Chinese and American Stock Markets

Since 2008,the economic volume of the United States has gradually decreased from 30% of world GDP to 20%-25%,and China has risen from 7% to 15%.However,face at a fast-growing economy,China's stock market has been sluggish,contrast strongly to the US's thriving stock market.This paper studies the correlation between stock market and macroeconomy,based on the perspective of stock market and macroeconomy between China and the United States.This article takes China and the United States from 1999 to early 2017 as the time frame.Choosing the Shanghai Stock Exchange securities market,the S&P 500 index and the macroeconomy indicators and policies of China and the United States as research objects,using a comparative method to study the interactive relationship between the two major economies.In addition,this paper analyzes the parts of macroeconomy and microlisted companies in economic and financial theory,and innovatively applies the four different aspects of macroeconomy of total seven indicators to more fully represent the macroeconomy.This paper establishes the VAR model,impulsive response,and variance decomposition to explore the interaction between trends of the stock market and macroeconomic trends.The research results show that the stock market trend is positively related to the macroeconomic trend.China's stock market is greatly affected by capital,and the reason why the US stock market can develop better under the condition that the macroeconomic development is not as good as China's,because of the unique status of the US dollar.Finally,this paper combines descriptive analysis and empirical analysis results to propose policy recommendations for China's stock market and macroeconomic development.

Prediction and optimization of process parameter of friction stir welded AA5083-H111 aluminum alloy using response surface methodology

A systematic approach was presented to develop the empirical model for predicting the ultimate tensile strength of AA5083-H111 aluminum alloy which is widely used in ship building industry by incorporating friction stir welding(FSW) process parameters such as tool rotational speed,welding speed,and axial force.FSW was carried out considering three-factor five-level central composite rotatable design with full replications technique.Response surface methodology(RSM) was applied to developing linear regression model for establishing the relationship between the FSW process parameters and ultimate tensile strength.Analysis of variance(ANOVA) technique was used to check the adequacy of the developed model.The FSW process parameters were also optimized using response surface methodology(RSM) to maximize the ultimate tensile strength.The joint welded at a tool rotational speed of 1 000 r/min,a welding speed of 69 mm/min and an axial force of 1.33 t exhibits higher tensile strength compared with other joints.

Dynamic interaction numerical models in the time domain based on the high performance scaled boundary finite element method

Consideration of structure-foundation-soil dynamic interaction is a basic requirement in the evaluation of the seismic safety of nuclear power facilities. An efficient and accurate dynamic interaction numerical model in the time domain has become an important topic of current research. In this study, the scaled boundary finite element method （SBFEM） is improved for use as an effective numerical approach with good application prospects. This method has several advantages, including dimensionality reduction, accuracy of the radial analytical solution, and unlike other boundary element methods, it does not require a fundamental solution. This study focuses on establishing a high performance scaled boundary finite element interaction analysis model in the time domain based on the acceleration unit-impulse response matrix, in which several new solution techniques, such as a dimensionless method to solve the interaction force, are applied to improve the numerical stability of the actual soil parameters and reduce the amount of calculation. Finally, the feasibility of the time domain methods are illustrated by the response of the nuclear power structure and the accuracy of the algorithms are dynamically verified by comparison with the refinement of a large-scale viscoelastic soil model.

Optimizing process of laser transmission welding of thermoplastics through RSM

An experimental investigation on transmission welding of polycarbonate( PC) filled with and without black carbon has been carried out. Furthermore,correlations between the laser transmission welding parameters and output variables are developed by applying response surface methodology( RSM). The process parameters of the model include laser power,welding speed,clamping force and cooling time,the output parameters of the model include maximum tensile load. The design expert v8. 05 b establishes the design matrix and obtains the regression equation,in order to analyze the influence of the process parameters on the tensile load. The analysis-of-variance( ANOVA) method is used to check the models' adequacy.Results reveal that the measured and calculated results are in good agreement.

Modeling personalized head-related impulse response using support vector regression

A new customization approach based on support vector regression （SVR） is proposed to obtain individual headrelated impulse response （HRIR） without complex measurement and special equipment. Principal component analysis （PCA） is first applied to obtain a few principal components and corresponding weight vectors correlated with individual anthropometric parameters. Then the weight vectors act as output of the nonlinear regression model. Some measured anthropometric parameters are selected as input of the model according to the correlation coefficients between the parameters and the weight vectors. After the regression model is learned from the training data, the individual HRIR can be predicted based on the measured anthropometric parameters. Compared with a back-propagation neural network （BPNN） for nonlinear regression, better generalization and prediction performance for small training samples can be obtained using the proposed PCA-SVR algorithm.

A Dynamic Analysis on Determining of Housing Demand： A Comparison for Turkey, Hungary, and UK

Housing is both good and investment assets so that it plays an important role in the economy. Housing also can be characterized the most complex economic good because of its durability, heterogeneity, locational fixity, the possibility to raise loans against housing collateral, and the effect on well-developed secondary markets. On the other hand, income distribution, socio-economic justice, and regional disparities imply that housing market is an important concept for social and cultural transformation. In this study, the determinants of housing demand were compared for countries. These countries are selected according to economic situation： Turkey, Hungary, and United Kingdom. As a scope of this, the dynamic relationship between the housing demand and variables determining the housing demand in Turkey, Hungary, and UK has been analyzed. The model estimated uses quarterly data from January 2002 to January 2014. Building permits has been considered as housing demand. The other variables used for determining the housing demand are GDP, monetary aggregate, interest rate, and share prices. The long term relationship among variables has been analyzed with Vector Autoregressive Model （VAR） as impulse response and variance decomposition. The findings indicate that determining of housing demand changes according to economic and financial components such as government policies, mortgage system, consumer choice, tax, and subsidy in selected countries. All variables play an important role in housing demand, although the level of their impacts varies.

Impact of Inflation, Dollar Exchange Rate and Interest Rate on Red Meat Production in Turkey： Vector Autoregressive （VAR） Analysis

In this study, impact of inflation （WPI--Wholesale Price Index）, exchange rate, and interest rate on the production of red meat in Turkey was examined using the vector autoregressive （VAR） model. The model consisting of variables of dollar exchange rate, inflation rate, interest rate, beef, buffalo meat, mutton, and goat meat production amounts has been estimated for the period from 1981 to 2014. It has been detected that there is a tie among the dollar exchange rate, inflation rate, interest rate, and the amount of red meat production in Turkey. In order to determine the direction of this relation, Granger causality test was conducted. A one-way causal relation has been observed between： the goat meat production and dollar exchange rate; the buffalo meat production and the mutton production; and the beef production and the mutton production. To interpret VAR model, the impulse response function and variance decomposition analysis was used. As a result of variance decomposition, it has been detected that explanatory power of changes in the variance of dollar exchange rate, inflation rate, and interest rate in goat meat production amount is more than explanatory power of changes in the variances of mutton, beef, and buffalo meat variables.

Performance Analysis of an Inverse Notch Filter and Its Application to <i>F₀</i>Estimation

In this paper, we analyze an inverse notch filter and present its application to F0 (fundamental frequency) estimation. The inverse notch filter is a narrow band pass filter and it has an infinite impulse response. We derive the explicit forms for the impulse response and the sum of squared impulse response. Based on the analysis result, we derive a normalized inverse notch filter whose pass band area is identical to unit. As an application of the normalized inverse notch filter, we propose an F0 estimation method for a musical sound. The F0 estimation method is achieved by connecting the normalized inverse notch filters in parallel. Estimation results show that the proposed F0 estimation method effectively detects F0s for piano sounds in a mid-range.