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Under different ground motion excitation modes, the spatial coupling effect of seismic response for the arch bridge with thrust, seismic weak parts and the internal force components of the control section of main arch ribs are analyzed.

Taking a 490 m deck type railway steel truss arch bridge as the background, the dynamic calculation model of the whole bridge was established by SAP2000 software. The seismic response analyses under one-, two- and three-dimension (1D, 2D and 3D) uniform ground motion excitations were carried out.

For the steel truss arch bridge composed of multiple arch ribs, any single direction ground motion excitation will cause large axial force in the chord of arch rib. The axial force caused by transverse and vertical ground motion excitation in the chord of arch crown area is 1.4–3.6 times of the corresponding axial force under longitudinal seismic excitation. The in-plane bending moment caused by the lower chord at the vault is 4.2–5.5 times of the corresponding bending moment under the longitudinal seismic excitation. For the bottom chord of arch rib, the arch foot is the weak part of earthquake resistance, but for the upper chord of arch rib, the arch foot, arch crown and the intersection of column and upper chord can all be the potential earthquake-resistant weak parts. The normal stress of the bottom chord of the arch rib under multidimensional excitation is mainly caused by the axial force, but the normal stress of the upper chord of the arch rib is caused by the axial force, in-plane and out of plane bending moment.

The research provides specific suggestions for ground motion excitation mode and also provides reference information for the earthquake-resistant weak part and seismic design of long-span deck type railway steel truss arch bridges.

The purpose of this paper is to develop a statistical-based model to forecast future domestic water demand in the context of climate change, population growth and technological development in Yellow River.

The model is developed through the analysis of the effects of climate variables and population on domestic water use in eight sub-basins of the Yellow River. The model is then used to forecast water demand under different environment change scenarios.

The model projected an increase in domestic water demand in the Yellow River basin in the range of 67.85 × 10⁸ to 62.20 × 10⁸ m³ in year 2020 and between 73.32 × 10⁸ and 89.27 × 10⁸ m³ in year 2030. The general circulation model Beijing Normal University-Earth System Model (BNU-ESM) predicted the highest increase in water demand in both 2020 and 2030, while Centre National de Recherches Meteorologiques Climate Model v.5 (CNRM-CM5) and Model for Interdisciplinary Research on Climate- Earth System (MIROC-ESM) projected the lowest increase in demand in 2020 and 2030, respectively. The fastest growth in water demand is found in the region where water demand is already very high, which may cause serious water shortage and conflicts among water users.

The simple regression-based domestic water demand model proposed in the study can be used for rapid evaluation of possible changes in domestic water demand due to environmental changes to aid in adaptation and mitigation planning.

Research on grey systems is becoming more sophisticated, and grey relational and prediction analyses are receiving close review worldwide. Particularly, the application of grey systems in marine economics is gaining importance. The purpose of this paper is to summarize and review literature on grey models, providing new directions in their application in the marine economy.

This paper organized seminal studies on grey systems published by Chinese core journal database – CNKI, Web of Science and Elsevier from 1982 to 2018. After searching the aforementioned database for the said duration, the authors used the CiteSpace visualization tools to analyze them.

The authors sorted the studies according to their countries/regions, institutions, keywords and categories using the CiteSpace tool; analyzed current research characteristics on grey models; and discussed their possible applications in marine businesses, economy, scientific research and education, marine environment and disasters. Finally, the authors pointed out the development trend of grey models.

Although researches are combining grey theory with fractals, neural networks, fuzzy theory and other methods, the applications, in terms of scope, have still not met the demand. With the increasingly in-depth research in marine economics and management, international marine economic research has entered a new period of development. Grey theory will certainly attract scholars’ attention, and its role in marine economy and management will gain considerable significance.

Traditional Chinese medicine (TCM) prescriptions have always relied on the experience of TCM doctors, and machine learning(ML) provides a technical means for learning these experiences and intelligently assists in prescribing. However, in TCM prescription, there are the main (Jun) herb and the auxiliary (Chen, Zuo and Shi) herb collocations. In a prescription, the types of auxiliary herbs are often more than the main herb and the auxiliary herbs often appear in other prescriptions. This leads to different frequencies of different herbs in prescriptions, namely, imbalanced labels (herbs). As a result, the existing ML algorithms are biased, and it is difficult to predict the main herb with less frequency in the actual prediction and poor performance. In order to solve the impact of this problem, this paper proposes a framework for multi-label traditional Chinese medicine (ML-TCM) based on multi-label resampling.

In this work, a multi-label learning framework is proposed that adopts and compares the multi-label random resampling (MLROS), multi-label synthesized resampling (MLSMOTE) and multi-label synthesized resampling based on local label imbalance (MLSOL), three multi-label oversampling techniques to rebalance the TCM data.

The experimental results show that after resampling, the less frequent but important herbs can be predicted more accurately. The MLSOL method is shown to be the best with over 10% improvements on average because it balances the data by considering both features and labels when resampling.

The authors first systematically analyzed the label imbalance problem of different sampling methods in the field of TCM and provide a solution. And through the experimental results analysis, the authors proved the feasibility of this method, which can improve the performance by 10%−30% compared with the state-of-the-art methods.

In 2002, variable annuities were introduced in South Korea and have shown enormous success since then. They are life-insurance products with investment guarantees. Variable annuities allow policyholders to allocate premiums into a wide range of investment vehicles such as stocks, bonds, money market instruments, or some combinations of them. Due to the investment guarantee which is called guaranteed living benefits (GLBs), the benefit is always the greater of (1) the account value of the policyholder investment and (2) the guaranteed amount. Life insurance companies set aside reserves for the guarantees in the general account. Just as the account value depends on the performance of investments, VA lapses also rely on the performance of investments. For example, policyholders will not terminate the contracts when account value is way lower than the guaranteed amount. Considering that lapses determine the total benefit of VAs that a insurance company should pay, calculating risk margin for lapse is a key issue in the VA business. In this study, risk margin for VA lapses is estimated with Wang transform suggested by Wang (2000, 2002).

Coastal zone ecological restoration project is of great significance to alleviate marine ecological degradation. Evaluating the effect of coastal ecological restoration projects and identifying the obstacle factors affecting their restoration level can provide an empirical basis for future Marine ecological restoration projects.

However, due to the initial stage of coastal zone ecological restoration projects, the actual monitoring data of coastal zone ecological restoration is relatively lacking. Based on the CRITIC-TOPSIS (combination of CRITIC method and TOPSIS method) method, combined with the subjective perception of the public and the actual data of the restoration project, this paper proposes an evaluation method of the coastal zone ecological restoration effect to obtain the specific implementation effect of the coastal zone ecological restoration project. The main obstacle factors affecting the evaluation of coastal ecological restoration effect are identified by using the obstacle degree model.

This paper conducted an empirical study on the restoration of sandy shoreline and coastal wetland in Qinhuangdao city. Based on the data of restoration projects and the subjective perception of ecological restoration by the public in Qinhuangdao city, the research results showed that the coastal zone ecological restoration effect of Qinhuangdao city was general. The quality of the restoration project and the public perception have an important influence on the evaluation of the restoration effect. Improving the quality of the restoration project, strengthening the public's participation in ecological restoration and allowing the public to better participate in the ecological restoration of the coastal zone can improve the effect of ecological restoration of the coastal zone in an all-round way.

The research results of this paper have a guiding role in the ecological restoration of coastal cities in the future, and also have a demonstration and reference role for the assessment of the effect of ecological restoration of coastal zones.

Forecasts of commodity prices are vital issues to market participants and policy makers. Those of corn are of no exception, considering its strategic importance. In the present study, the authors assess the forecast problem for the weekly wholesale price index of yellow corn in China during January 1, 2010–January 10, 2020 period.

The authors employ the nonlinear auto-regressive neural network as the forecast tool and evaluate forecast performance of different model settings over algorithms, delays, hidden neurons and data splitting ratios in arriving at the final model.

The final model is relatively simple and leads to accurate and stable results. Particularly, it generates relative root mean square errors of 1.05%, 1.08% and 1.03% for training, validation and testing, respectively.

Through the analysis, the study shows usefulness of the neural network technique for commodity price forecasts. The results might serve as technical forecasts on a standalone basis or be combined with other fundamental forecasts for perspectives of price trends and corresponding policy analysis.

The purpose of the study is to examine how utilizing volunteered data influences the response and unsubscribe rates of e-mail marketing to consumers.

In three longitudinal field experiments conducted among 1,864 applicants of a higher education institution, the study compares customized marketing e-mails based on volunteered consumer data to e-mails that are personalized based on observed consumer data and to control e-mails that are not tailored by the marketer at all.

The results indicate that marketers should make consumers active participants in the communication process, as response rates are higher in those e-mails where volunteered data are utilized. However, the unsubscribe rate is the highest in customized e-mails.

The authors demonstrate that e-mails displaying empowering aspects influence consumers' behaviors and lead to outcomes that mostly outperform non-empowered e-mails.

Compared to other forms of interactive marketing, e-mail has lagged behind in both popularity and customer-friendly implementation. However, it has the potential to succeed if marketers pay more attention to consumer empowerment. As over 306 billion e-mails are sent worldwide daily and 75% of marketers use e-mail when contacting customers, the increase in response rates can have a significant influence on their returns.

Unlike prior research the focus was on the process of tailoring, this perspective supports customer advocacy and emphasizes consumers' important role in creating engaging, empowering e-mail marketing communication.

This paper aims to probe into the implementation of internship courses under the five-year cosmetology program in Taiwan from the perspective of Dewey's philosophies in hopes that the analysis can serve as reference for schools in planning their internship courses in the future.

This paper probes into the off-campus internship courses under Taiwan's five-year junior college education program by applying Dewey's empirical philosophy.

The study aims to understand the learning experience acquired by students from learning by doing internship courses as reference for future internship design. The current internship courses comprise the follows: summer, during the semester and for a full academic year. The experience of summer internship is career exploration, the experience for semester internship is career experience and the experience from academic-year internship is career choice. The internship strategies are designed according to the three different internship approaches, so that the internship courses can implement the educational effect of “learning from experience”.

To minimize the discrepancy between the cosmetology program under the five-year junior college education and the employment market, credit-based off-campus internship courses are arranged for students' final years at school.

Through on-site trainings, students accumulate work experience and explore into a related career field. The accumulation of experience and gaining of insights mirror the philosophy of learning by doing, which involves students' reflective thinking.

It is hoped that the analysis can serve as reference for internship courses planning in the future.

China's marine economy occupies an important position within the national economy, and its contribution thereto is constantly improving. The overall operation of the marine economy shows positive developmental trends with potential for further growth. The purpose of this research is to analyse the prosperity of China's marine economy, reveal trends therein and forecast the likely turning point in its operation.

Based on the periodicity and fluctuation of China's marine economy development, China's marine economic prosperity indicator system is established from five perspectives. On this basis, China's marine economic operation prosperity index can be synthesised and calculated, then a dynamic factor model is constructed. Using the filtering method to calculate China's marine economic operational Stock–Watson index, Markov switching has been used to determine the trend to transition. Furthermore, China's current marine economic prosperity is evaluated through analysis of influencing factors and correlation analysis.

The analysis shows that, from 2017 to 2019, the operation of the marine economy is relatively stable, and the prosperity index supports this finding; meanwhile it also exposes problems in China's marine economy, such as an unbalanced industrial structure, low marine economic benefits and insufficient capacity for sustainable development.

Through the analysis of the prosperity of China's marine economy, the authors reveal the trends in China's marine economy and forecast its likely future turning point.