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Projecting the population distribution in geographical regions is important for many applications such as launching marketing campaigns or enhancing the public safety in certain densely populated areas. Conventional studies require the collection of people’s trajectory data through offline means, which is limited in terms of cost and data availability. The wide use of online social network (OSN) apps over smartphones has provided the opportunities of devising a lightweight approach of conducting the study using the online data of smartphone apps. This paper aims to reveal the relationship between the online social networks and the offline communities, as well as to project the population distribution by modeling geo-homophily in the online social networks.

In this paper, the authors propose the concept of geo-homophily in OSNs to determine how much the data of an OSN can help project the population distribution in a given division of geographical regions. Specifically, the authors establish a three-layered theoretic framework that first maps the online message diffusion among friends in the OSN to the offline population distribution over a given division of regions via a Dirichlet process and then projects the floating population across the regions.

By experiments over large-scale OSN data sets, the authors show that the proposed prediction models have a high prediction accuracy in characterizing the process of how the population distribution forms and how the floating population changes over time.

This paper tries to project population distribution by modeling geo-homophily in OSNs.

Recent years have witnessed the rapid development of massive open online courses (MOOCs). With more and more courses being produced by instructors and being participated by learners all over the world, unprecedented massive educational resources are aggregated. The educational resources include videos, subtitles, lecture notes, quizzes, etc., on the teaching side, and forum contents, Wiki, log of learning behavior, log of homework, etc., on the learning side. However, the data are both unstructured and diverse. To facilitate knowledge management and mining on MOOCs, extracting keywords from the resources is important. This paper aims to adapt the state-of-the-art techniques to MOOC settings and evaluate the effectiveness on real data. In terms of practice, this paper also tries to answer the questions for the first time that to what extend can the MOOC resources support keyword extraction models, and how many human efforts are required to make the models work well.

Based on which side generates the data, i.e instructors or learners, the data are classified to teaching resources and learning resources, respectively. The approach used on teaching resources is based on machine learning models with labels, while the approach used on learning resources is based on graph model without labels.

From the teaching resources, the methods used by the authors can accurately extract keywords with only 10 per cent labeled data. The authors find a characteristic of the data that the resources of various forms, e.g. subtitles and PPTs, should be separately considered because they have the different model ability. From the learning resources, the keywords extracted from MOOC forums are not as domain-specific as those extracted from teaching resources, but they can reflect the topics which are lively discussed in forums. Then instructors can get feedback from the indication. The authors implement two applications with the extracted keywords: generating concept map and generating learning path. The visual demos show they have the potential to improve learning efficiency when they are integrated into a real MOOC platform.

Conducting keyword extraction on MOOC resources is quite difficult because teaching resources are hard to be obtained due to copyrights. Also, getting labeled data is tough because usually expertise of the corresponding domain is required.

The experiment results support that MOOC resources are good enough for building models of keyword extraction, and an acceptable balance between human efforts and model accuracy can be achieved.

This paper presents a pioneer study on keyword extraction on MOOC resources and obtains some new findings.

Human group behavior is the driving force behind many complex social and economic phenomena. Few studies have integrated multi-dimensional travel patterns and city interest points to construct urban security risk indicators. This paper combines traffic data and urban alarm data to analyze the safe travel characteristics of the urban population. The research results are helpful to explore the diversity of human group behavior, grasp the temporal and spatial laws and reveal regional security risks. It provides a reference for optimizing resource deployment and group intelligence analysis in emergency management.

Based on the dynamics index of group behavior, this paper mines the data of large shared bikes and ride-hailing in a big city of China. We integrate the urban interest points and travel dynamic characteristics, construct the urban traffic safety index based on alarm behavior and further calculate the urban safety index.

This study found significant differences in the travel power index among ride-sharing users. There is a positive correlation between user shared bike trips and the power-law bimodal phenomenon in the logarithmic coordinate system. It is closely related to the urban public security index.

Based on group-shared dynamic index integrated alarm, we innovatively constructed an urban public safety index and analyzed the correlation of travel alarm behavior. The research results fully reveal the internal mechanism of the group behavior safety index and provide a valuable supplement for the police intelligence analysis.

This paper aims to identify important factors in green public procurement (GPP) implementation and then to clarify how these factors affect GPP implementation.

The authors applied the Delphi method first and then conducted a focused and constrained multiple case study at 18 government procurement centers across China.

The authors identified four clusters of factors for successful GPP implementation: more clear, consistent and operational policy goals; a nation-wide green procurement campaign to enhance social capital and cultural resources; promoting staff’s ethics, professionalism, capacity and knowledge; and establishing checks and balances among organizations involved in the whole purchasing process.

GPP can significantly improve environmental protection and sustainable development.

Based on key insights from systems theory and agency theory, the authors emphasize that GPP implementation must take down its own functional silos and adopt a process approach across organizational tiers to synchronize human resource based and inter-organizational capabilities into a unified whole through information sharing, communications and collaboration.

This paper aims to evaluate the separation and purification characteristics of flavonoids from polygonum cuspidatum (PC) extracts by using macroporous adsorption resins (MAR) mixed bed to improve the utilization rate of flavonoids.

Taking the separation performance of flavonoids as an evaluation index, the best MAR were screened from 31 sorts of MAR and combined the best MAR to form a MAR mixed bed for adsorption and separation of flavonoids.

By studying the separation conditions that affect flavonoids, the results showed that resin LZ-72 has best separation and purification effect on flavonoids under the optimal adsorption and desorption conditions, the purity of the obtained flavonoid compound reaches 82.50%, 2.66 times of the initial extract, and the recovery rate reaches 89.70%. Theoretical research results have shown that the adsorption of flavonoids by MAR conforms to the pseudo-second-order kinetics and Freundlich models.

Because the flavonoids in PC have great medicinal value, the purpose of this work is to develop a method of separating and purifying flavonoids from PC, which will provide a certain foundation for the development of medicine.

This contribution provided a novel way to separate flavonoids from PC. Under the optimal conditions, the content of flavonoids in the product was increased 2.66-fold from 31.01% to 82.50%, and the recovery yield was 89.70%.

The purpose of this study is to investigate how the use of information technology (IT) and supply chain management initiatives (information sharing and collaboration) impact a company's performance in reverse logistics (RL).

A survey based on a previous exploratory research and literature review was sent out to 600 US companies having substantial activities in RL. Issues addressed in the survey, such as IT types deployed, IT operational attributes, information sharing, and collaboration, involve multiple parties in multi‐tier RL networks, extending beyond a simple buyer‐supplier dyad.

The results revealed that the type of IT used per se did not have a differential impact on a company's performance in RL. However, IT operational attributes positively affected RL performance and information sharing and collaboration are critical to RL performance.

Investment in IT alone cannot improve a company's performance; managers should take full account of IT attributes when deciding IT in RL. IT operational attributes tend to support one another – an improvement in one would lead to improvements in the others. With no exception in RL, companies need to share information and collaborate with their partners.

The paper reports an empirical survey of the IT use and collaboration practices in RL, and provides insights into the relationships and impacts of IT, RL operational attributes, information sharing, and collaboration on one another as well as on RL performance.

The purpose of this paper is to show that HIV/AIDS‐related stigma has persisted world‐wide for decades. However, studies on the linkage between stigmatizing attitudes towards people living with HIV/AIDS (PLWHA) and misconceptions about HIV transmission routes in the general population, especially among youth in China, are sparse – a gap this study is intended to fill.

Cross‐sectional data from 1,839 students from 19 colleges were collected by trained interviewers using a structured questionnaire in Jiangsu province of China.

This study reveals that there is a high proportion of college students having both stigmatizing attitudes toward PLWHA and misconceptions about HIV/AIDS transmission routes. Multilevel logistic regression analysis results show that having stigmatizing attitudes towards PLWHA is positively associated with having misconceptions about HIV transmission routes. Participants with high misconception scores were more likely to possess stigmatizing attitudes towards PLWHA.

To reduce stigmatizing attitudes towards PLWHA, HIV/AIDS education should be strengthened among the general population, especially among youth.

This paper seeks to report a case study that focuses on identifying what may be considered a typical or generic RL process flow as well as the key strategic issues that a firm may use for competitive advantage.

The research involves mainly interviews and plant visits to three companies, all of which manage some RL activities.

Highlighted are what type of RL process flow can be considered as generic, the type of technology innovation and IT a firm needs in order to operate an effective RL system and how these are integrated across the supply chain, the resource commitment (personnel, financial, upper‐level management) that a company needs to make to support successful RL efforts, and finally, the values firms derive from RL and the key performance indicators to measure these values for the RL operations.

A typical returns flow process is provided that can guide managers efficiently on their RL activities. Strategic activities are also presented that characterize successful practices in the RL industry.

Sex education in China has been promoted for many years, but limited data are available regarding the sources from which adolescents receive sex‐related knowledge. The present study was designed to examine the sources from which Chinese adolescents obtain their information on puberty, sexuality and STI/HIV/AIDS, and whether there are any differences in sources of sex knowledge according to adolescents' demographic characteristics and sexual status.

The data were collected in 2001 in Changchun City, China. Unmarried adolescents 15‐19 years of age (322 males and 360 females) were included in a cross‐sectional survey using self‐administered questionnaires.

Schoolteachers and mass media were identified as the two most important sources of sex knowledge. Sources of sex knowledge among adolescents on various topics (puberty, sexuality, and STI/HIV/AIDS) differed by the level of taboo associated with these topics in Chinese culture. The percentage of adolescents obtaining knowledge for puberty, sexuality, and STI/HIV/AIDS from teachers declined by topic (45.4, 30.7 and 18.4 percent, respectively), while the percentage of adolescents obtaining knowledge from television/movie increased by topic (6.7, 12.2 and 27.5 percent, respectively). Adolescents obtained knowledge on topics with less taboo (e.g. puberty) from teachers and obtained knowledge on topics with more taboo (e.g. sexuality, STI/HIV/AIDS) from mass media. However, this differs by having been sexually experienced or not. Parents were the primary source for sex knowledge on less taboo subjects. Doctors were the primary source for STI/HIV/AIDS knowledge. Sexually active adolescents obtained sex knowledge mainly from peers or mass media, while those adolescents who were not sexually experienced identified teachers and parents as the main sources of sex knowledge.

The current study illustrates that it is necessary to improve and enhance current sex education programs in China by recognizing and strengthening the role of parents, teachers, and health care professionals in adolescent sex education.