高职生自主学习能力与网络依赖程度关系的研究

在问卷调查法的基础上,本研究对高职生自主学习能力与网络依赖程度进行多种维度的相关分析,并通过多重线性回归分别对突出影响网络依赖及其四种维度的自主学习因子进行考察.结果表明:高职生自主学习能力和网络依赖程度之间存在十分密切的关系,其中学习策略分量表中的学习求助因子和学习管理因子对高职生的网络依赖有最大的影响.     

Trust,risk, and the social contract

The problem of trust is discussed in terms of David Hume’s meadow-draining example. This is analyzed in terms of rational choice, evolutionary game theory and a dynamic model of social network formation. The kind of explanation that postulates an innate predisposition to trust is seen to be unnecessary when social network dynamics is taken into account.     

Rationality,Reasonableness, and Critical Rationalism: Problems with the Pragma-dialectical View

A major virtue of the Pragma-Dialectical theory of argumentation is its commitment to reasonableness and rationality as central criteria of argumentative quality. However, the account of these key notions offered by the originators of this theory, Frans van Eemeren and Rob Grootendorst, seems to us problematic in several respects. In what follows we criticize that account and suggest an alternative, offered elsewhere, that seems to us to be both independently preferable and more in keeping with the epistemic approach to arguments and argumentation we favor.

Causal relationship between Internet use and social capital in Japan

Based on longitudinal data collected from a random sample panel survey, the present study found that different types of Internet usage are differentially related to social networks. The more social ties people have, the more likely they are to use personal computer (PC) email, and the use of PC email increases social ties. The results also show that the more supportive ties people have, the more they tend to use mobile phone email; however, it does not prove the use of mobile phone email increases supportive ties. However, participation in an online community is not related social networks. These findings suggest that PC email may increase the size of personal social networks, whereas mobile phone email is useful in maintaining existing strong ties which provide social support.     

How do shy people expand their social networks? Using social surrogates as a strategy to expand one's network

The authors examined the use of social surrogates by shy people to expand their social network when entering a new environment, following Bradshaw's social surrogate hypothesis. The authors conducted a panel survey of 70 friendship pairs of students 7 months after they entered university. The results revealed that when a friend acted as a surrogate, the shy students extended their joint networks more. In contrast, not-shy students extended their networks regardless of whether a friend acted as a surrogate. These results indicate that even shy people can adjust indirectly to new social circumstances because they can expand their social networks by using a close friend as a surrogate.     

失用性失写的脑机制

失用性失写是指人们知道该如何书写, 但实际上却不会书写或错误书写的一种现象。失用性失写涉及的神经网络包括皮层与皮层连接、皮层与皮质下连接。其中前者包括额-顶叶相关脑区的连接、顶-枕叶相关脑区的连接以及额-顶-枕相关脑区的连接, 这些神经网络分别负责操作空间表征图像、回忆以及检索字母的形状等; 后者包括小脑与额-顶叶的连接、左丘脑-大脑皮质的连接以及纹状体-内囊-左额顶叶的连接等, 它们分别与图像输出程序、书写运动过程、操作指令的执行过程以及字素形成过程等有关。今后的研究应该集中在完善失用性失写的研究范式、深入探讨失用性失写的心理机制以及推动其康复工作的开展等方面。     

Developing networks in disempowered communities: Experiencing hardships while focusing on opportunities

This study aims to present an evaluation and the process steps of a community‐based initiative (CBI) consisting of a group of organizations that work to enhance the lives of boys and men of colour. Using a participatory research model, the researchers collaborated with 14 community stakeholders to develop the questions during two data collection periods and reviewed the reports for accuracy. The findings were separated into two broad categories. The perceived challenges included a lack of clear goals and measurements of success, an absence of leadership and direction, and a shortage of resources. The successes included passion of partners, increased collaboration, and increasing and maintaining social capital within the community. The lessons learned from both data collection periods helped this CBI broaden its reach and collaboration efforts. Overall, this study provides suggestions to other CBIs as they embark on making changes in their own communities.     

Narrative congruence between populist President Duterte and the Filipino public: Shifting global alliances from the United States to China

This research examines what happened when the populist Philippine President Rodrigo Duterte reversed his country's global alliance, switching loyalties away from the United States towards China. We use the lens of narrative congruence, to see if political storylines of a populist president are accompanied by similar shifts in storylines among his followers. Our data corpus consists of text from Duterte's speeches and from comments on partisan Facebook pages, representing supporters and opponents of the president. We time‐bound our data corpus to text produced around the time President Duterte announced his realignment towards China. We use text mining and network analysis to identify overlaps among words used by the different social actors. Our findings show that when Duterte switched alliances, Facebookers—regardless of partisanship—accepted this alliance shift. However, our results likewise reveal an imperfect congruence. Duterte's followers move on to a story criticizing Duterte's domestic political enemies, whereas anti‐Duterte Facebookers talk about monetary deals and drug issues in the Philippines' newfound friendship with China. We discuss our findings in the light of a psychology of populism, the use of a discursive social networks approach to study macropsychological phenomena, and discursive resistance in a populist state.     

An accurate and efficient multi-category edge detection method

Edge detection plays an important role in image processing. With the development of deep learning, the accuracy of edge detection has been greatly improved, and people have more requirements for edge detection tasks. Most edge detection algorithms are binary edge detection methods, but there are usually multiple categories of edges in an image. In this paper, we present an accurate multi-category edge detection network, the richer category-aware semantic edge detection network (R-CASENet). In order to make full use of convolutional neural network’s powerful feature expression capabilities, we attempt to use more information from feature maps for edge feature extraction and classification. Using the ResNet101 network as the backbone, firstly we merge the building blocks in different composite blocks and down-sample to obtain the feature maps. Then we fuse the feature maps in different composite blocks to obtain the final fused classifier. Experimental results show that R-CASENet can achieve state-of-the-art performance on the large SBD dataset. Furthermore, to get precise one-pixel width edges, we also propose an edge refinement network (ERN) structure. The proposed scheme is an end-to-end method and the proposed ERN can reduce redundant points and improve computational efficiency, especially for further image processing.