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The coal reserves overlain by buildings, water bodies and railways are estimated to be about 14 billion tons in China. Based on the concept of green mining, in order to save the unit energy, Double pumps in parallel forms of pumping are adopted in 0the paste filling of the pumping system. The optimal solution of the objective function could be obtained by taking the unit flow power of the pumping system as the objective function, using the quadratic polynomial by the least square method curve fitting and by the application of MATLAB. Thereby it is possible to reduce power consumption and increase the efficiency of the operating economy in the paste filling station.

The purpose of this paper is to analyze the mechanism and filter efficacy of accumulation generation operator (AGO)/inverse accumulation generation operator (IAGO) in the frequency domain.

The AGO/IAGO in time domain will be transferred to the frequency domain by the Fourier transform. Based on the consistency of the mathematical expressions of the AGO/IAGO in the gray system and the digital filter in digital signal processing, the equivalent filter model of the AGO/IAGO is established. The unique methods in digital signal processing systems “spectrum analysis” of AGO/IAGO are carried out in the frequency domain.

Through the theoretical study and practical example, benefit of spectrum analysis is explained, and the mechanism and filter efficacy of AGO/IAGO are quantitatively analyzed. The study indicated that the AGO is particularly suitable to act on the system's behavior time series in which the long period parts is the main factor. The acted sequence has good effect of noise immunity.

The AGO/IAGO has a wonderful effect on the processing of some statistical data, e.g. most of the statistical data related to economic growth, crop production, climate and atmospheric changes are mainly affected by long period factors (i.e. low-frequency data), and most of the disturbances are short-period factors (high-frequency data). After processing by the 1-AGO, its high frequency content is suppressed, and its low frequency content is amplified. In terms of information theory, this two-way effect improves the signal-to-noise ratio greatly and reduces the proportion of noise/interference in the new sequence. Based on 1-AGO acting, the information mining and extrapolation prediction will have a good effect.

The authors find that 1-AGO has a wonderful effect on the processing of data sequence. When the 1-AGO acts on a data sequence X, its low-pass filtering effect will benefit the information fluctuations removing and high-frequency noise/interference reduction, so the data shows a clear exponential change trends. However, it is not suitable for excessive use because its equivalent filter has poles at the non-periodic content. But, because of pol effect at zero frequency, the 1-AGO will greatly amplify the low-frequency information parts and suppress the high-frequency parts in the information at the same time.

This paper aims to explore the relationships among local food consumption experience, cultural competence, eudaimonia, and behavioral intention. Building upon acculturation theory, need hierarchy theory and self-determination theory, the current study develops a conceptual model of local food consumption as international tourists’ acculturation process.

This study collects data from 305 Chinese outbound tourists and uses partial least squares-structural equation modeling to examine the developed model.

The findings reveal a significant effect of the local food consumption experience, consisting of novel, authentic, sensory and social dimensions, on cultural competence, which subsequently evokes eudaimonia and behavioral response toward local food. The mediating effect of cultural competence is also confirmed.

Destination marketers and restaurant managers should recognize local food consumption as a meaningful tool that contributes to tourists’ cultural competence and eudaimonic well-being during travel. They should strive to craft an indigenous consumption setting and provide employee training on the history and culture of local food, helping tourists understand local food customs and embrace different food cultures.

To the best of the authors’ knowledge, very few studies have attempted to examine the meaningful consequences of local food consumption through the theoretical lens of acculturation. This study dives into international tourists’ local food consumption and pioneers a conceptual model to capture how local food consumption experience provokes their eudaimonia and behavioral desires through the mechanism of cultural competence.

The purpose of this paper is to evaluate the technical efficiency and production risk in China's rice production and examine the effect of factor market reform on these two agricultural performance metrics.

Using an unbalanced farm-level panel data with 2,193 observations on 329 rice farms from 2004 to 2016, the authors estimate a translog stochastic production frontier model that accounts for both technical inefficiency and production risk. A one-step procedure through the maximum likelihood method that combines the stochastic production frontier, technical inefficiency and production risk functions is used to circumvent the bias problem often found in the conventional two-step model.

Estimation results show that both land and labor market reforms significantly improved the level of technical efficiency over the years, although the effect of land market deregulation is of a much higher magnitude compared to the latter. The land market reform, however, has also increased the risk of production. The authors further find that a higher proportion of hired labor in total labor cost helps lower production risk, while also acting to decrease technical efficiency. Additionally, agricultural subsidies not only increased the output variability but also lowered technical efficiency

First, the authors evaluate the effect of market deregulation on technical efficiency and production risk under a stochastic frontier framework that simultaneously accounts for both production performance metrics, which is important from a statistical point of view. Further, the authors exploit both cross-sectional and time-series variations in a panel setting to more accurately estimate the technical inefficiency scores and production risk for individual farmers, and investigate how the exogenous land and labor market reforms influence these two production performance measures in China's rice farming. This is the first study in the literature to analyze these questions under a panel framework.

The performance of the building envelope of a large-scale public building significantly influences the energy consumption of such a building. This study aims to determine the best strategy for the envelope by examining the engineering design of the building in Nanchang University. The building shape coefficient, sun-shading strategies, window–wall ratio, roof, and walls were studied through a method involving multilayer feed-forward neural network model simulations. Results show that the optimum shape coefficient value is 0.32. The combination of interior and exterior blinds and electrochromic glass is the ideal option to reduce the increase in the energy consumption of the architecture caused by solar radiation. Maintaining the window–wall ratio at 0.4 is ideal. A green roof exerts a minimal effect on building energy consumption decrease (only 0.4%). Applying the strategy of vertical greening to the external wall can reduce cooling energy consumption by as much as 5.4%. Adopting the best envelope strategy combination can further decrease energy consumption by 20.8%. This strategy is also applicable to the middle and lower reaches of Yangtze River in China, which flow through Nanchang and have a climate similar to that of the said area. Future research should be directed toward applying artificial neural networks to quantitatively evaluate the effects of a design strategy and produce the best design strategy combination.

Although primarily treated as two distinct research streams, strategic alliances and mergers and acquisitions together occupy much of the strategic management discourse. Alliances, in many cases, end in acquisitions as firms use alliances as intermediate strategic options to eventually acquire a partner. As the discipline of strategy matures and the frequency and the volume of inter-firm cooperation continue to rise, it is imperative to integrate these two research streams for a holistic understanding of the theory of the firm. The purpose of this conceptual piece is threefold. First, we review the extant studies that combine these two governance modes: alliance and acquisitions. Second, drawing on the dominant strategic management theories, we highlight how prior inter-firm alliances inform future acquisitions in terms of (a) pre-combination decisions, (b) post-deal integration processes, (c) alternatives and strategies, and (d) performance outcomes. Finally, in view of the emerging trends and evocative gaps, we offer a conceptual road map to encourage future theoretical development and empirical research.

The purpose of this paper is to examine the role of independent vs interdependent self-construal in non-smokers’ responses to an anti-smoking message that focuses on either personal or relational consequences of smoking.

Two web-based experimental studies were conducted among US college non-smokers. In the first study, participants’ self-construal was measured. Then participants were randomly assigned to view an anti-smoking message emphasizing either relational or personal consequences of smoking. Message evaluation, smoking attitudes, and behavioral intentions were assessed after message exposure. The second study followed the same procedure except that participants’ self-construal was manipulated by randomly assigning participants to an independent or interdependent self-construal priming task prior to message exposure.

Both studies showed a noticeable pattern of interaction between message focus and self-construal: non-smokers with a salient interdependent self-construal responded more favorably to an anti-smoking message emphasizing personal (vs relational) consequences of smoking whereas non-smokers with a salient independent self-construal responded more favorably to an anti-smoking message emphasizing relational (vs personal) consequences of smoking. However, the interaction effect was small in the first study.

Findings from this study are original in that they run counter to the general belief that messages matching people’s self-perceptions will be more persuasive. On the other hand, matching health risk messages with people’s dominant self-construal may reduce the messages effectiveness due to defensive processing. As a result, communication practitioners should take a great caution of tailoring threatening smoking prevention messages to target audiences’ self-perceptions.

The purpose of this paper is to gain an understanding of the current research on Internet-plus.

The authors collected scholarly publications from the scientific databases Web of Science, Core Collection, Inspec and Compendex (Ei Village 2) and performed statistical analysis of the retrieved data from five perspectives.

The research on Internet-plus has obtained increasing attention in China. The top three research fields were social science, education and management.

The study will help researchers understand the current trends on Internet-plus.

Challenges associated with ensuring the accuracy and reliability of cost estimation of highway construction bid items are of significant interest to state highway transportation agencies. Even with the existing research undertaken on the subject, the problem of inaccurate estimation of highway bid items still exists. This paper aims to assess the accuracy of the cost estimation methods employed in the selected studies to provide insights into how well they perform empirically. Additionally, this research seeks to identify, synthesize and assess the impact of the factors affecting highway unit prices because they affect the total cost of highway construction costs.

This paper systematically searched, selected and reviewed 105 papers from Scopus, Google Scholar, American Society of Civil Engineers (ASCE), Transportation Research Board (TRB) and Science Direct (SD) on conceptual cost estimation of highway bid items. This study used content and nonparametric statistical analyses to determine research trends, identify, categorize the factors influencing highway unit prices and assess the combined performance of conceptual cost prediction models.

Findings from the trend analysis showed that between 1983 and 2019 North America, Asia, Europe and the Middle East contributed the most to improving highway cost estimation research. Aggregating the quantitative results and weighting the findings using each study's sample size revealed that the average error between the actual and the estimated project costs of Monte-Carlo simulation models (5.49%) performed better compared to the Bayesian model (5.95%), support vector machines (6.03%), case-based reasoning (11.69%), artificial neural networks (12.62%) and regression models (13.96%). This paper identified 41 factors and was grouped into three categories, namely: (1) factors relating to project characteristics; (2) organizational factors and (3) estimate factors based on the common classification used in the selected papers. The mean ranking analysis showed that most of the selected papers used project-specific factors more when estimating highway construction bid items than the other factors.

This paper contributes to the body of knowledge by analyzing and comparing the performance of highway cost estimation models, identifying and categorizing a comprehensive list of cost drivers to stimulate future studies in improving highway construction cost estimates.

The purpose of this paper is to assess the impacts on production of five fruit crops from 1961 to 2018 of energy use, CO₂ emissions, farming areas and the labor force in China.

This analysis applied the autoregressive distributed lag-bound testing (ARDL) approach, Granger causality method and Johansen co-integration test to predict long-term co-integration and relation between variables. Four machine learning methods are used for prediction of the accuracy of climate effect on fruit production.

The Johansen test findings have shown that the fruit crop growth, energy use, CO₂ emissions, harvested land and labor force have a long-term co-integration relation. The outcome of the long-term use of CO₂ emission and rural population has a negative influence on fruit crops. The energy consumption, harvested area, total fruit yield and agriculture labor force have a positive influence on six fruit crops. The long-run relationships reveal that a 1% increase in rural population and CO₂ will decrease fruit crop production by −0.59 and −1.97. The energy consumption, fruit harvested area, total fruit yield and agriculture labor force will increase fruit crop production by 0.17%, 1.52%, 1.80% and 4.33%, respectively. Furthermore, uni-directional causality is correlated with the growth of fruit crops and energy consumption. Also, the results indicate that the bi-directional causality impact varies from CO₂ emissions to agricultural areas to fruit crops.

This study also fills the literature gap in implementing ARDL for agricultural fruits of China, used machine learning methods to examine the impact of climate change and to explore this important issue.