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Making decisions on production and maintenance separately, as is often done in practice and research literature, may not result in overall optimization. This paper aims to propose a joint method that better integrates production planning and maintenance at the tactical level. The potential of improving the performance of the classic planning method is also explored.

An integrated production planning and maintenance model is proposed. The production capacity losses resulted from both preventive and corrective maintenance activities are considered. Meanwhile, the reliability deterioration of the machine is considered to be operation dependent. An iterative approach is presented to find a solution for the nonlinear model through iteratively solving a sequence of mixed integer linear programming instances, accompanied by modification of some parameters prior to each iteration. Computational experiments are conducted to evaluate the performance of the proposed method compared with three other methods, including two methods based on separate planning and one integrated model.

The superiority of the proposed method compared with all the other three methods is demonstrated. Thus, the values of both integrated planning and considering operation-dependent failures are testified. The advantage of the proposed method is highlighted in the cases of high capacity utilization, long maintenance durations and low maintenance costs. The performance of the two methods based on separate planning is sensitive to the system utilization, and when utilization is high, the one with an availability-sensitive objective function defined for the maintenance problem performs better.

Few studies have been carried out to integrate decisions on production lot and maintenance. Their considerations are either incomplete or not realistic enough. A more comprehensive and realistic integrated model is proposed in this paper, along with an iterative solution algorithm for it. A potential way to improve the performance of the classic planning method with its simplicity preserved is also presented.

This study aims to investigate the corrosion inhibitor effect of migrating corrosion inhibitor (MCI) on Q235 steel in high alkaline environment under cathodic polarization.

This study investigated the electrochemical characteristics of Q235 steel with and without MCI by polarization curve and electrochemical impedance spectroscopy. Besides, the surface composition of Q235 steel under different environments was analyzed by X-ray photoelectron spectroscopy. In addition, the migration characteristic of MCI and the adsorption behavior of MCI under cathodic polarization were studied using Raman spectroscopy.

Diethanolamine (DEA) and N, N-dimethylethanolamine (DMEA) can inhibit the increase of Fe(II) in the oxide film of Q235 steel under cathodic polarization. The adsorption stability of DMEA film was higher under cathodic polarization potential, showing a higher corrosion inhibition ability. The corrosion inhibition mechanism of DEA and DMEA under cathodic polarization potential was proposed.

The MCI has a broad application prospect in the repair of damaged reinforced concrete due to its unique migratory characteristics. The interaction between MCIs, rebar and concrete with different compositions has been studied, but the passivation behavior of the steel interface in the presence of both the migrating electric field and corrosion inhibitors has been neglected. And it was investigated in this paper.

As an Internet fashion brand, HSTYLE has developed into an Internet enterprise with annual sales of 1.5 billion RMB within 10 years, establishing its position as the top industry performer in China. This case studies HSTYLES' innovation in business model and organizational management. HSTYLE's workgroups have achieved the balance of responsibilities and rights in a small team of three members at minimum, while mobilizing the enthusiasm and initiative of the line managers with the support of public service sector. At the same time, HSTYLE enriches its brand style, establishes a fashion cloud platform, and integrates individual and organizational consumers into its existing fashion design, manufacturing and sales system.

This paper aims to study the effect of temperature on the process and kinetic parameters of the hydrogen evolution reaction of X80 under cathodic protection (CP) in 3.5% NaCl solution.

Potentiodynamic polarization combined with the hydrogen permeation test is used to analyze the hydrogen evolution reaction (HER) process and the rate-determining step for which is diagnosed through the electrochemical impedance spectrum method. Then, the influence of temperature on kinetic parameters of HER can be known from the results obtained by using the Iver-Pickering-Zamenzadeh model for data analysis.

The results show that the HER proceeds through Volmer–Tafel route with the Volmer reaction acting as the rate-controlling step; Increasing temperature gives a higher activity of the HER on X80, it also accelerates the hydrogen desorption and diffusion of hydrogen into the metal.

There exist few studies on the topic of how temperature affects the HER process. It is imperative to conduct a relevant study to give some instruction in cathodic protection system design and this paper fulfills this need.

Delivering messages and information to potentially interested users is one of the distinguishing applications of online enterprise social network (ESN). The purpose of this paper is to provide insights to better understand the repost preferences of users and provide personalized information service in enterprise social media marketing.

It is accomplished by constructing a target audience identification framework. Repost preference latent Dirichlet allocation (RPLDA) topic model topic model is proposed to understand the mass user online repost preferences toward different contents. A topic-oriented preference metric is proposed to measure the preference degree of individual users. And the function of reposting forecasting is formulated to identify target audience.

The empirical research shows the following: a total of 20 percent of the repost users in ESN represent the key active users who are particularly interested in the latent topic of messages in ESN and fits Pareto distribution; and the target audience identification framework can successfully identify different target key users for messages with different latent topics.

The findings should motivate marketing managers to improve enterprise brand by identifying key target audience in ESN and marketing in a way that truthfully reflects personalized preferences.

This study runs counter to most current business practices, which tend to use simple popularity to seek important users. Adaptively and dynamically identifying target audience appears to have considerable potential, especially in the rapidly growing area of enterprise social media information service.

The purpose of this paper is to provide a solution for Reynolds equation with both throttling term and reverse throttling term and provides a reference for changing damping of hydrostatic bearing.

The reverse throttling term is introduced into the Reynolds equation, and the adaptive damping factor is used in the Newton iteration method to improve convergence of numerical calculations. The static and dynamic performances of this bearing are numerically investigated by the finite-element method.

The results indicate that the reflux orifices lead to a decrease in load capacity at a high eccentricity ratio. Additionally, the mass inflow rate is increased; however, the additional inflow increase can be controlled by enhanced backpressure of the reflux orifice. Nevertheless, the bearing with the reflux orifice shows superiority in resisting high-frequency disturbances and enhances direct damping by 20% under a high backpressure.

This work presents an adaptive Newton damping iterative method for solving Reynolds equation with both throttling term and reverse throttling term. This work also provides a new idea for bearing structure design in improving damping.

The purpose of this paper is to use Weibo as a window to examine the Chinese netizens’ online attitudes and responses to two sets of population policy: the Selective Two-Child Policy (Phase 2) and the Universal Two-Child Policy. The population policy change from the rigid One-Child Policy to the Selective Two-Child Policy then to the Universal Two-Child Policy aroused great attention of the Chinese people.

This research uses the crawler technique to extract data on the Sina Weibo platform. Through opinion mining of Weibo posts on two sets of population policy, the Weibo users’ online opinions on the Two-Child Policy are analyzed from two perspectives: their attention intensity and sentiment tendency. The research also use the State Bureau of Statistics of China’s national population data between 2011 and 2016 to examine the Chinese people’s actual birth behaviors after implementing the two different sets of the Two-Child Policy.

The research findings indicate that the Selective Two-Child Policy (Phase 2) and the Universal Two-Child Policy are good examples of thematic public sphere of Weibo. Weibo posts on the two sets of the Two-Child Policy have undergone different opinion cycles. People from economically developed regions and populous regions have paid more attention to both sets of Two-Child Policy than their counterparts in the less developed and less populated regions. Men pay more attention to the Two-Child Policy than women do. Despite people’s huge attention to the new population policy, the population growth after the policy is not sustainable.

The new population policy alone is difficult to boost China’s population within a short period of time. The Chinese Government must provide its people with enough incentives and supporting welfare to make the population growth happen.

These findings have important implications for understanding the dynamics of online opinion formation and changing population policy in China.

Currently, ubiquitous smartphones embedded with various sensors provide a convenient way to collect raw sequence data. These data bridges the gap between human activity and multiple sensors. Human activity recognition has been widely used in quite a lot of aspects in our daily life, such as medical security, personal safety, living assistance and so on.

To provide an overview, the authors survey and summarize some important technologies and involved key issues of human activity recognition, including activity categorization, feature engineering as well as typical algorithms presented in recent years. In this paper, the authors first introduce the character of embedded sensors and dsiscuss their features, as well as survey some data labeling strategies to get ground truth label. Then, following the process of human activity recognition, the authors discuss the methods and techniques of raw data preprocessing and feature extraction, and summarize some popular algorithms used in model training and activity recognizing. Third, they introduce some interesting application scenarios of human activity recognition and provide some available data sets as ground truth data to validate proposed algorithms.

The authors summarize their viewpoints on human activity recognition, discuss the main challenges and point out some potential research directions.

It is hoped that this work will serve as the steppingstone for those interested in advancing human activity recognition.