bluuebunny/crossref_metadata_2025_split huggingface dataset:
Simple analytical solutions of one-equation modelling for steady/decaying homogeneous turbulence sensitized to small strain
Authors: Suzuki Hiroki , Mochizuki Shinsuke , Hasegawa Yutaka 
Published: October 2019

Abstract
This study presents a simple mathematical solution describing the turbulent kinetic energy in steady or decaying homogeneous turbulence sensitized to small strain. Small strain is found to have little effect on the anisotropy of decaying homogeneous turbulence, which is consistent with a previous experiment. The effect of small strain on dissipation in the governing equations of turbulent kinetic energy is examined using the standard k-ε model. Two temporal profiles, namely a constant profile and a linear profile, with small strain are used. The steady homogeneous turbulence is maintained by linear forcing, as previously reported. This study mainly focuses on the effects of small strain on the turbulence time scale. When the magnitude of the small strain is small, the effects on the turbulence time scale can be negligibly small, especially for a constant profile. Based on this result, the governing equations for steady or decaying homogeneous turbulence sensitized to small strain can be reduced to simple linear equations. The analytical solution of these equations, a simple exponential function, is the same for the two types of homogeneous turbulence.
Orthogonal experiment analysis of coal gangue and corn straw mixed burning under considering multiple factors
Authors: Song Changzhong , Gong Zhen , Wen Jianghui , Liu Kun , Liu Yan 
Published: October 2019

Abstract
Combustion test of multi-mass blending ratio of corn straw and coal gangue by using thermogravimetric analyzer with different heating rates and different oxygen concentrations. Comprehensive consideration of the synergy between factors and factors, combustion performance analysis of ignition performance, flammability, volatiles precipitation performance and comprehensive combustion performance. The results show that the optimum combination of ignition and combustibility in order of priority is: oxygen concentration 30%, mass blending ratio of corn straw and coal gangue 2:3, heating rate v=10 K/min. The optimum combination of flammability and elease of the volatile matter in order of priority is: oxygen concentration 30%, mass mixing ratio of corn straw and coal gangue 4:1, heating rate v=20 K/min. The optimum combination test of combustible combustion is: oxygen concentration 30%, heating rate v=10 K/min, mass mixing ratio of corn straw and coal gangue 2:3, and the combustible performance obtained by multi-factor orthogonal analysis has been significantly improved.
Quasi-approximation for Stefan problem of nearly spherical phase change materials
Authors: Li Jiayan , Chan Yue 
Published: October 2019

Abstract
Phase change occurs when a phase change material exchanges its energy with the external environment. In this paper, we investigate the solidification of nearly spherical materials, which is famously known as Stefan problem and is of practically important. When the material solidifies, the inner moving boundary (see Figure 1) can be determined by solving the elliptic-typed partial differential equation, equipped with the outer fixed and the inner moving boundary conditions, derived from the Newton cooling law and the latent heat, respectively. Since the shape of materials induces a huge impact on the retreating speed of the moving boundary. To demonstrate this idea, we consider the perfect spherical object and certain irregular objects, such as an ellipse. We derive the analytical solutions for both cases and find that the shape of the moving boundary changes from the ellipse into the sphere during the solidification process.
A theoretical study on nonnative contacts in protein folding by a modified HP model
Authors: Chen Chong , Huang Ran 
Published: October 2019

Abstract
We have investigated the nonnative contacts for proteins in a modified HP model by generating all possible conformations (enumeration) to carry out exact calculation for the nonnative contact density nc(e) as a function of the energy e, as well as the thermodynamically average nonnative contacts

n
¯

c

(
T
)

as a function of temperature of T. A series of abstract coarse-grained chains on standard, weekly and strongly interacting models were studied to estimate the properties of nc(e) and

n
¯

c

(
T
)

to understand the role for nonnative contacts playing in the protein folding process.-->
Investigation of a compact model for squeeze-film air damping in the free molecular regime
Authors: Li Pu , Lu Cunhao 
Published: October 2019

Abstract
Due to the huge computational cost, the Monte Carlo (MC) model is difficult to use to predict squeeze-film air damping in the free molecular regime. Sumali (2007) proposed an empirical compact formula relating MC model and the analytical energy transfer model (ETM) by fitting two curves. By using the efficient numerical model, this paper discusses the application of the compact formula for squeeze-film air damping of different microplate sizes in the free molecular regime. The results show that, for plates of various sizes, the quality factors predicted by the compact model match well with those predicted by the numerical model. The work of this paper has validated that the compact model for squeeze-film air damping proposed by Sumali (2007) can be used for plates of various sizes.
Study on reflection characteristics of plasma and metallic periodic structure composite frequency selective device
Authors: Zhu Xuefeng , Hou Zhongyu 
Published: October 2019

Abstract
Plasma technology is widely used in the electromagnetic field. In this work, a novel composite frequency selection (CFS) device composed of plasma and metallic periodic structure is proposed. This paper demonstrates the reflection coefficient of the proposed CFS at 12-18 GHz. The dispersion of absorption effect in the frequency domain is also mentioned. A simulation result of the electric field distribution of CFS device is presented to give a tentative explanation.
Numerical modelling of fluid transportation based on digital core model
Authors: Liu Jianjun , Wang Rui , Zhang Bohu , Zu Lin , He Xiang 
Published: October 2019

Abstract
Rock pore is the storage space and migration channel of geo-fluid resource like petroleum, coalbed methane and shale gas etc. In this paper, the rock core microscopic pore structure based on CT image is studied through image processing. Then the parameters are analyzed statistically by numerical modelling. The reconstructed software Mimics is used to reconstruct the core structural model. Finally, the relationship between the pore structure parameters and penetrability is studied by numerical simulation. The equivalent permeability of the reconstructed core is calculated by using FEM software Abaqus. The results shown that fluid percolation is directly related with porosity, pore shape, pore conectivity. The permeability of core can be obtained by substituting flow numerical simulation for seepage laboratory experiment.
Adaptive iterative learning control for a class of fractional-order nonlinear systems
Authors: Hao Xiuqing , Liu Xiaoli 
Published: October 2019

Abstract
Based on the discussions on the properties of fractional integral and Caputo fractional derivative, an adaptive iterative learning control approach is proposed for a class of fractional-order nonlinear system (FONS) with unknown time-varying parameter. With the design of learning controller and adaptive learning law for unknown parameter, the tracking error sequence converges to zero in the iteration domain while all the closed-loop signals remain bounded. Finally, a numerical example is given to verify the validity of the designed method.
A prediction model for population change using ARIMA model based on feature extraction
Authors: Li Wei , Su Zhongyu , Guo Pengcheng 
Published: October 2019

Abstract
Population is a social entity with complex contents and a variety of social relations. It includes gender, age and natural composition, as well as a variety of social composition, social relations, economic composition and economic relations. It is difficult to analyze the population change in large number and high dimension over the years in China. A prediction model for population change using ARIMA model based on feature extraction is proposed. It provides the reduction of population change indicators and predicts the population change in the future. Principal component analysis is firstly used to transform this problem in high-dimensional space into low-dimensional space, making the problem simple and intuitive. These less comprehensive indexes obtained are not related to each other and provide most information of the original indexes. The data of the national population change from 1979 to 2015 is effectively reduced to one principal component. On the basis of the analysis results, a prediction model using ARIMA model is established to predict the population change in the next few years.
Alternative prediction methods in the stock exchanges of Thailand
Authors: Chokethaworn Kanchana , Chaiboonsri Chukiat , Wannapan Satawat 
Published: October 2019

Abstract
This paper is conducted to substantially do the two alternatives between the traditional statistical methods such as ARMA and HW models, and artificial intelligence (AI) contains KNN and ELM, respectively. To scope the main object of the paper, SET indexes are collected as the main financial variable, which are 5,472 daily observed days during 9 September 1997 to 11 June 2018. Technically, the cross-entropy (CE) analysis, MSE and RMSE calculations are computationally employed to clarify the resolution of the two computations. The empirical results state that the AI prediction can be a substitution replacing the traditional estimations, and this can strongly confirm that machine learning (ML) algorithms are continuously interested, and they are recently becoming a powerful tool for modern econometric forecasting.
The optimization of kink regression with differential evolution (DE)
Authors: Pastpipatkul Pathairat , Boonyakunakorn Petchaluck , Sriboonchitta Songsak 
Published: October 2019

Abstract
This paper aims to estimate the kink model with respect to Thailand’s exports to Thai GDP. Another main contribution of this study is to compare the performance of optimization the kink regression model with DE and MLE. The traditional optimization is maximum likelihood estimator (MLE) which has problems in the case where the function is nondifferentiable, or the likelihood is difficult to find. Furthermore, it is difficult to obtain the global maximum in the non-linear model. One of the optimization techniques is DE which is a successful method for searching for the global maximum. To evaluate the estimated performance of DE and MLE, we apply the Monte Carlo simulation. The simulation result indicates that DE has the both lower MSE and bias. We apply the regression model with respect to Thai exports to Thai GDP. For the estimated parameter results show that the kink point is -0.016%. The estimated coefficients in the first part and second part are 1.144% and 0.341%, respectively.
Sensitivity analysis of the policy of minimum grain purchase prices
Authors: Wang Yu , Wang Dongjie , Zhang Yongen , Wang Shengwei , Zhou Han , Yu Wen , Li Ganqiong 
Published: October 2019

Abstract
The grain price, the base of all other prices, is relatively sensitive to policy adjustments. The too high minimum purchase prices will lead to the imbalance of the grain market, while the decline of the minimum purchase prices will exert a direct influence on business entities’ expectation of the market prices in the following year. With the early long-grain nonglutinous rice, the middle-late long-grain nonglutinous rice, the round-grain nonglutinous rice and wheat as instances, this article applies the stepwise regression model and the data between 2004 and 2014 to simulate the effect of the minimum grain purchase prices of 2018 on the cultivated area and the yield of the early long-grain nonglutinous rice, the middle long-grain nonglutinous rice, the round-grain nonglutinous rice and wheat as well as farmers’ corresponding revenues. As suggested by the research, the minimum purchase prices play a significantly positive role in the fluctuation of the rice and wheat prices. In case of the same decline rate of minimum purchase prices, the round-grain nonglutinous rice sees the greatest decline rate of the cultivated area and the yield, followed by the middle-late long-grain nonglutinous rice, while the cultivated area and the yield of the early long-grain nonglutinous rice show the smallest decline. However, when deciding to plant rice and wheat, farmers not only consider about the changes of the minimum purchase prices of rice and wheat, but also are subject to the technical input, the revenue and the cost etc. The government may appropriately adjust the minimum purchase prices of rice and wheat to adjust the cultivated area of rice and wheat, thus to stabilize the cultivated area of rice and wheat in China and realize a win-win situation between society and farmers.
Bayesian analysis of population agglomeration and ecological efficiency in Beijing-Tianjin-Hebei region
Authors: Chen Jianming , Wei Na , Zhou Yanli , Ge Xiangyu 
Published: October 2019

Abstract
By using 35 cities data directly under the jurisdiction of Beijing-Tianjin-Hebei region, this paper improved Bayesian spatial quantile regression method to explore the relationship between population aggregation and eco-efficiency and its mutual influence under the background of Beijing, Tianjin and Hebei urban agglomeration construction theme. The study found that population aggregation has a significant negative impact on the urban eco-efficiency. In addition, the number of primary schools, the scale of urban economic development and investment in real estate development also have a significant negative impact on urban eco-efficiency. While the number of secondary schools and the number of beds in medical and health institutions has a significant positive impact on urban eco-efficiency.
Spatially correlated binary data modelling using generalized estimating equations with alternative hypersphere decomposition
Authors: Li Junjie , Pan Jianxin 
Published: October 2019

Abstract
For correlated binary data, generalized estimating Equation (GEE) approach is commonly used for inference of the mean parameters. When the associated correlation is of interest, e.g., in spatial data analysis, some traditional correlation structures such as compound symmetry and AR(1) were employed in the literature, which is not appropriate for the inherent correlation for correlated binary data. In this paper, we proposed another set of GEE implemented with alternative hypersphere decomposition (AHPC) to model the correlation parameters. An iterative algorithm is provided to estimate the mean and correlation parameters simultaneously. By utilizing the AHPC, we developed a parametrization for the correlation matrix that automatically ensures the order independence and non-negative definiteness. We also addressed the issue of asymptotic properties. For illustration, the proposed methods were used to fit a spatial bovine tuberculosis infection data in Ireland, aiming to analyse the influential factors which affect the infection of cattle and/or badgers.
Risk measurement of global stock markets: a factor copula-based GJR-GARCH approach
Authors: Song Quanrui , Liu Jianxu , Sriboonchitta Songsak 
Published: October 2019

AbstractFinancial crisis in 2008 caused huge loss and one of the accusations is the misprediction of risk measurement. Considering the important role the stock markets play, and the trend of globalization in economy, we propose forecasting Value at Risk of G20’s (except European Union) stock indexes in three periods, pre-crisis, during crisis and post-crisis, via factor copula model. Unlike those models based on multivariate normality, factor copula is based on the assumption that there exists a or several common factors which lead to the change of stock prices. In this paper, different levels of dependence among 19 countries are presented and the results indicate that, during crisis countries with higher values of coefficients tend to have larger loss than others. Also, the large numbers of violations to VaR may be an indicator of the upcoming financial crisis.
The role of Fintech e-payment on APEC economic development
Authors: Khiewngamdee Chatchai , Yan Ho-don 
Published: October 2019

Abstract
The goal of this study is to investigate whether Fintech e-payment affects economic development in APEC countries, in particular, income growth, productivity, price volatility, and income inequality. We use e-payment index introduced by RMIT University and TRPC and apply quantile regression with GME approach. We consider the quantile level at 0.25, 0.50, and 0.75. At the low level of economic development variables, the Fintech have the highest effects on these variables compared with the medium and high level of economic development. In other words, Fintech supports not only low level of growth and productivity but also reduce the low level of price volatility and income inequity. Further investigation provides that e-payment usage and technology empowerment are helpful to economic development, particularly, increasing in growth and productivity.
The application of ARIMA model in forecasting population data
Authors: Dai Jie , Chen Shuping 
Published: October 2019

Abstract
The prediction of population data plays a positive role in adjusting population policy and promoting the development of social, economic and cultural undertakings. In this paper, the population data of Zhejiang Province from 1978 to 2016 are processed and analyzed by using the principle of time series analysis. In order to test the validity of the parameters selected by this model, the population data of Zhejiang Province in 2017 are verified in this paper. The experimental results show that the actual fitting effect of the model is good. Finally, with the help of SAS software, the population data of Zhejiang Province from 2018 to 2022 are analyzed and forecasted.
Grouped variables selection via alternating direction method of multipliers in longitudinal analysis
Authors: Zhang Chengyu , Yang Yihe , Pan Jianxin 
Published: October 2019

Abstract
This work focuses on automatically and simultaneously selecting and estimating the coefficients of grouped variables in longitudinal data. It is motivated by a large cohort study, the UK North Staffordshire Osteoarthritis Project (NorStOP), which contains highly associated continuous, binary and ordinal variables. To select grouped variables associated with the target response efficiently, we propose a newly-developed generalized estimating equation (GEE) estimation. The innovation of this method is to study and implement GEE with group-lasso rather than traditional lasso which lacks consideration of group effects. We applied the proposed approach to the NorStOP data, and the results turned out to be reasonable.
Suckling lamb meat: A smart and sustainable food combining tradition and innovation
Authors: Battacone G , Nudda A , Atzori A S , Pulina G 
Published: October 2019

Abstract
Meat from milk-fed lambs is one of the most relevant products in the traditional dairy sheep industry. This product is the meat from suckling lambs fed maternal milk in flocks raised almost only on pasture. The aim of this paper is to briefly summarise current knowledge of the qualitative traits of suckling lamb meat, with special attention paid to the lipid fraction. We report the main scientific data for suckling lamb meat that contributes to its alleged properties as a functional and environmentally sustainable food. Furthermore, reference is made to how innovative chill/freeze technologies can be profitable, enlarging consumption of this meat in the dynamic global markets.
Pros and cons of using a computer vision system for color evaluation of meat and meat products
Authors: Milovanovic B , Djekic I , Djordjevic V , Tomovic V , Barba F , Tomasevic I , Lorenzo J M 
Published: October 2019

AbstractThe ability of a computer vision system to evaluate the color of meat and meat products was investigated by a comparison study with color measurements from a traditional colorimeter. Pros and cons of using a computer vision system for color evaluation of meat and meat products were evaluated. Statistical analysis revealed significant differences between the instrumental values in all three dimensions (L*,a*,b*) between the computer vision system and the colorimeter. The computer vision system-generated colors were perceived as being more similar to the sample of the meat products visualized on the monitor, compared to colorimeter-generated colors in all (100%) individual trials performed. The use of the computer vision system is, therefore, considered a superior and less expensive alternative to the traditional method for measuring color of meat and meat products. The disadvantages of the computer vision system are its size, which makes it stationary, and the lack of official manufacturers that can provide ready-to-use systems. This type of computerized system still demands experts for its assembly and utilization.
From white coat and gumboots to virtual reality and digitalisation: where is veterinary medicine now?
Authors: Fejzic N , Seric-Haracic S , Mehmedbasic Z 
Published: October 2019

Abstract
The paper reviews the current role of information and communication technologies in veterinary medicine, management of animal health, animal production and food safety worldwide and discusses the shift from recognising the digital revolution as a novelty to accepting it as a norm. Due to the diversity in veterinary medicine, it is unlikely that information and communication technologies will fully substitute the need for field veterinarians in direct contact with animals, farms, diseases, food production and food products. However, information and communication technology has a growing role in our work and provides opportunities to exploit new technologies for professional and societal affirmation. Consumers, trade and regulations drive demands on veterinary medicine, reflected in our increased focus on prevention and early recognition of animal diseases and food safety issues through output-based and integrated monitoring systems and shared responsibility between public and private sectors. Simultaneously, information and communication technology has been incorporated within these demands and so now has roles in: veterinary clinical practice, heard health management, animal health databases, traceability of animals and their products, trade and veterinary certification, animal disease data analysis, tools for veterinary education and animal health diagnostics. The symbiosis of bio- and information technologies has opened a new era in health and food production, providing a novel chance for veterinarians to make a significant leap in their professional development, achievable only through strategic and active participation as leaders and collaborators.