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The purpose of this paper is to achieve effective governance of online rumors through the proposed rumor propagation model and immunization strategy.

The paper leverages the agent-based modeling (ABM) method to model individuals from two aspects, behavior and attitude. Based on the analysis and research of online data, we propose a rumor propagation model, namely the Untouched view transmit removed-Susceptible hesitate agree disagree (Unite-Shad), and devise an immunization strategy, namely the Gravity Immunization Strategy (GIS). A graph-based framework, namely Pregel, is used to carry out the rumor propagation simulation experiments. Through the experiments, the rationality of the Unite-Shad and the effectiveness of the GIS are verified.

The study discovers that the inconsistency between human behaviors and attitudes in rumor propagation can be explained by the Unite-shad model. Besides, the GIS, which shows better performance in small-world networks than in scale-free networks, can effectively suppress rumor propagation in the early stage.

This paper provides an effective immunization strategy for rumor governance. Specifically, the Unite-Shad model reveals the mechanism of rumor propagation, and the GIS provides an effective governance method for selecting immune nodes.

The inconsistency of human behaviors and attitudes in real scenes is modeled in the Unite-Shad model. Combined with the model, the definition of diffusion domain is proposed and a novel immunization strategy, namely GIS, is designed, which is significant for the social governance of rumor propagation.

The purpose of the study is to examine the impact of behavioural biases (i.e. overconfidence, risk-aversion, herding and disposition) on investment decisions amongst gender. The authors further examine the moderation effect of financial literacy in the relationship between behaviour biases and investment decisions amongst gender.

The study considered a cross-sectional research design. For this survey, the data have been collected through a structured questionnaire from 253 individual investors of the Delhi-NCR region. To analyse the validity and reliability, the Pearson correlation and Cronbach's alpha test have been taken into account respectively. For testing the hypothesis, hierarchical regression analysis has been used in the study.

The results of the study reveal that amongst male investors, the influence of risk-aversion and herding on investment decision was negative and statistically significant, while the influence of overconfidence on investment decision was positive and significant. However, the influence of disposition was found statistically insignificant. The results stated that amongst female investors the effect of risk-aversion and herding on investment decision was negative and statistically significant. However, the effect of overconfidence and disposition was statistically insignificant influence the investment decision. It has been observed that financial literacy has significantly influenced investment decisions amongst male and female investors. The results of the interaction effect amongst male investors stated that the interaction between overconfidence and investment decision was significantly influenced by financial literacy. However, the interaction of financial literacy with the remaining three biases, i.e. risk-aversion, herding and disposition was found insignificant. The results for the interaction effect of financial literacy with overconfidence, risk-aversion, disposition and herding were found statistically significant amongst female investors.

Based on this present research finding, the study is more productive for the portfolio manager and policymakers at the time of making an investment portfolio for the investors based on their behavioural biases. The study recommends that investors need training programmes, workshops and seminars that enhance financial literacy and financial knowledge of investors which helps them to overcome the behavioural biases while making an investment decision.

The current study aims to explore whether several behavioural biases can affect investment decisions amongst gender. Moreover, the authors would like to examine whether these associations are moderated by financial literacy. In this sense, financial literacy might also show a substantial part in the prediction of investments. The current study might be of the first study that examines the moderation effect financial literacy amongst male and female investors.

We make use of the Volunteered Geographic Information (VGI) data to extract the total extent of the roads using remote sensing images. VGI data is often provided only as vector data represented by lines and not as full extent. Also, high geolocation accuracy is not guaranteed and it is common to observe misalignment with the target road segments by several pixels on the images. In this work, we use the prior information provided by the VGI and extract the full road extent even if there is significant mis-registration between the VGI and the image. The method consists of image segmentation and traversal of multiple agents along available VGI information. First, we perform image segmentation, and then we traverse through the fragmented road segments using autonomous agents to obtain a complete road map in a semi-automatic way once the seed-points are defined. The road center-line in the VGI guides the process and allows us to discover and extract the full extent of the road network based on the image data. The results demonstrate the validity and good performance of the proposed method for road extraction that reflects the actual road width despite the presence of disturbances such as shadows, cars and trees which shows the efficiency of the fusion of the VGI and satellite images.

This study aims to investigate whether temperature affects the product quality of exporters and whether the effect is non-linear. More specifically, whether the impact of high temperatures differs from the impact of low temperatures, and whether different types of companies or industries are affected differently.

The paper uses detailed data covering all Chinese exporters from 2000 to 2016 to estimate the effects of temperature on the product quality of export firms. To clarify the relationship between them, the authors use a semi-parametric regression method, trying to test whether there is a non-linear relationship between temperature and the export quality of firms.

The increase in the number of high temperature days significantly reduces the quality of exported products, and this negative effect increases as the temperature rises. High temperature has the most significant negative impact on export quality for firms with low technical complexity, private firms and firms with no intermediate imports and located in historical hot cities. Product quality of both labor-intensive and capital-intensive firms will be affected by heat. High temperatures have the greatest negative impact on the export quality of newly entering products, followed by exiting products, with the least negative impact on persisting product.

To the best of the authors’ knowledge, this paper is the first to examine the impact of temperature on the quality of economic development. The findings of this paper again show that the potential economic impacts of global warming are huge. In addition to some potentially devastating impacts in the future, global warming is already causing imperceptible impacts in the present. Public and economic agents need to fully understand the possible adverse impacts of climate change and take corresponding adaptation measures to cope with global warming.