Search Results (4)

Cyberspace has evolved into a hub for the dissemination of large amounts of tendentious information, posing significant challenges to the role of mainstream value information. As netizens’ are the main recipients of tendentious information, their personal cognition, attitude, and behavioral ability affect their willingness to re-disseminate information, making them an inalienable force in the promotion of information dissemination. Exploring the dissemination mechanism of tendentious information in cyberspace can help to understand the law of information dissemination and predict the trend of information diffusion, which is of great significance to maintaining information security and social stability. However, the existing research has overlooked the potential influence of the attribute characteristics of information in terms of content, and has failed to overcome the methodological constraints of traditional statistical analysis to accurately describe the variables and mechanisms influencing the dissemination of tendentious information at the cognitive level. Therefore, using structural equation modeling, we propose a research index system based on the Theory of Planned Behavior and the characteristics of tendentious information. To this end, confirmatory factor and model fitting analyses were conducted to develop a tendentious information dissemination mechanism model, which we validated through testing and comparative experiments. Path analysis revealed that Attitude Toward Dissemination, Information Dissemination Intention, and Information Dissemination Behavior are the main links in the information dissemination process. Moreover, Information Sentiment Orientation was found to strongly promote the dissemination of tendentious information, while Subject Norm of Dissemination had a minor inhibiting effect. Full article

In recent years, 3D imaging became an increasingly popular screening modality for high-throughput plant phenotyping. The 3D scans provide a rich source of information about architectural plant organization which cannot always be derived from multi-view projection 2D images. On the other hand, 3D scanning is associated with a principle inaccuracy by assessment of geometrically complex plant structures, for example, due the loss of geometrical information on reflective, shadowed, inclined and/or curved leaf surfaces. Here, we aim to quantitatively assess the impact of geometrical inaccuracies in 3D plant data on phenotypic descriptors of four different shoot architectures, including tomato, maize, cucumber, and arabidopsis. For this purpose, virtual laser scanning of synthetic models of these four plant species was used. This approach was applied to simulate different scenarios of 3D model perturbation, as well as the principle loss of geometrical information in shadowed plant regions. Our experimental results show that different plant traits exhibit different and, in general, plant type specific dependency on the level of geometrical perturbations. However, some phenotypic traits are tendentially more or less correlated with the degree of geometrical inaccuracies in assessing 3D plant architecture. In particular, integrative traits, such as plant area, volume, and physiologically important light absorption show stronger correlation with the effectively visible plant area than linear shoot traits, such as total plant height and width crossover different scenarios of geometrical perturbation. Our study addresses an important question of reliability and accuracy of 3D plant measurements and provides solution suggestions for consistent quantitative analysis and interpretation of imperfect data by combining measurement results with computational simulation of synthetic plant models. Full article

Performance prediction is of significant importance. Previous mining of behaviour data was limited to machine learning models. Corresponding research has not made good use of the information of spatial location changes over time, in addition to discriminative students’ behavioural patterns and tendentious behaviour. Thus, we establish students’ behaviour networks, combine temporal and spatial information to mine behavioural patterns of academic performance discrimination, and predict student’s performance. Firstly, we put forward some principles to build graphs with a topological structure based on consumption data; secondly, we propose an improved self-attention mechanism model; thirdly, we perform classification tasks related to academic performance, and determine discriminative learning and life behaviour sequence patterns. Results showed that the accuracy of the two-category classification reached 84.86% and that of the three-category classification reached 79.43%. In addition, students with good academic performance were observed to study in the classroom or library after dinner and lunch. Apart from returning to the dormitory in the evening, they tended to stay focused in the library and other learning venues during the day. Lastly, different nodes have different contributions to the prediction, thereby providing an approach for feature selection. Our research findings provide a method to grasp students’ campus traces. Full article

This paper focuses on the evaluation of local institutional capacities for advancing climate-environmental governance in the Mexico Valley Metropolitan Area (MVMA). It starts with a brief contextualization of the MVMA, followed by an estimation of current and tendential urban inflows and outflows by 2050 with the objective of delineating the challenges and potential implications ahead. Next, an assessment of local climate-environmental institutional capacities is offered. For that, the methodology and main outcomes of the so-called ICI-CLIMA index is presented for 2019. A qualitative discussion continues in order to assert the challenges and opportunities for advancing a coordinated urban agenda for sustainability and resilience. Such discussion has been enriched with documental and other type of information gathered through field research in all of the 76 municipalities that comprise the MVMA. The paper concludes that, in addition to the limited current climate-environmental local capacities, there is a mismatch between them and both the level of climate vulnerability officially identified and the environmental challenges currently facing. Therefore, for coping with a tendential scenario of increasing urban inflows and outflows and their associated climate-environmental implications, MVMA governments will have to improve their capacities while advancing, at all levels of government, the coordination of climate-environmental agendas, and of the later with urban planning and development agendas. Full article