BackgroundLeft-behind children in China have aroused widespread concern in society and the academic field because they have a high risk of psychological problems. For left-behind children, depression is the most serious problem. Bullying victimization has been evidenced as one of the most common causes of children’s depression. However, less is known about its longitudinal association and the process for how bullying victimization influences depression among left-behind children. Thus, the presentation aims to explore the mechanisms underlying by considering the roles of (...) left-behind children’s negative thoughts and self-compassion.MethodsThe 3-wave longitudinal data were collected from a sample of 605 aged 8–11 from central China. We used the Olweus bully and victimization questionnaire, the children’s automatic thoughts scale, the depression scale, and the self-compassion scale.ResultsBullying victimization positively predicted the depression level of left-behind children. Negative thoughts and self-compassion mediate the relationship between bullying victimization and depression. In the mechanism of bullying victimization on depression exists gender differences among left-behind children.ConclusionThe present study suggested the association between bullying victimization and left-behind children’s depression and revealed the internal mechanism of negative thoughts and self-compassion. These findings provide a new perspective for left-behind children’s mental health education and intervention. (shrink)

On Tarkasaṅgraha, a treatise on logic as defined in the Nyāya and Vaiśeṣika systems of Hindu philosophy.

Network embedding aims to learn the low-dimensional representations of nodes in networks. It preserves the structure and internal attributes of the networks while representing nodes as low-dimensional dense real-valued vectors. These vectors are used as inputs of machine learning algorithms for network analysis tasks such as node clustering, classification, link prediction, and network visualization. The network embedding algorithms, which considered the community structure, impose a higher level of constraint on the similarity of nodes, and they make the learned node embedding (...) results more discriminative. However, the existing network representation learning algorithms are mostly unsupervised models; the pairwise constraint information, which represents community membership, is not effectively utilized to obtain node embedding results that are more consistent with prior knowledge. This paper proposes a semisupervised modularized nonnegative matrix factorization model, SMNMF, while preserving the community structure for network embedding; the pairwise constraints information are effectively fused with the adjacency matrix and node similarity matrix of the network so that the node representations learned by the model are more interpretable. Experimental results on eight real network datasets show that, comparing with the representative network embedding methods, the node representations learned after incorporating the pairwise constraints can obtain higher accuracy in node clustering task and the results of link prediction, and network visualization tasks indicate that the semisupervised model SMNMF is more discriminative than unsupervised ones. (shrink)

Treatises, with Arthadyotanikā auto commentary, of the Dvaita and Advaita school in Hindu philosophy.

During the COVID-19 pandemic, online education has become an important approach to learning in the information era and an important research topic in the field of educational technology as well as that of education in general. Teacher–student interaction in online education is an important factor affecting students’ learning performance. This study employed a questionnaire survey to explore the influence of teacher–student interaction on learning effects in online education as well as the mediating role of psychological atmosphere and learning engagement. The (...) study involved 398 college students studying at Chinese universities as the research object. Participants filled out a self-report questionnaire. The study found that the level of teacher–student interaction positively affected students’ learning effects. The psychological atmosphere mediated the positive effect of the level of teacher–student interaction on learning effects with mediating effect value of 0.1248. Learning engagement mediated the positive effect of teacher–student interaction on learning effects with a mediating effect value of 0.1539. The psychological atmosphere and learning engagement play a chain-mediating role in the mechanism of teacher–student interaction affecting students’ learning effects; that is, teacher–student interaction promotes students’ learning engagement by creating a good psychological atmosphere, which, in turn, influences learning effects. The mediating effect value was 0.0403. The results indicate that teacher–student interaction not only directly affects students’ learning effects but also influences students’ learning effects through the mediating effect of the psychological atmosphere and learning engagement. (shrink)

本书内容包括:儒学与全球化浪潮、儒学与知识经济、儒家精神与网络世界、儒学与环境伦理、儒学与当代生命伦理等。.

No Matter What the original meaning of "Ru" was, looking at it from the perspective of the history of philosophy, the image of "Ru" as portrayed by other schools in the Warring States period was infused with the characteristics of Confucianism of that time. The self-understanding of Warring States Confucians expressed by their employment of the character "Ru" clearly displayed Ru's character as well as the main points of the Ru school, namely Confucianism. In particular, the words and thoughts of (...) Xunzi, the great Confucian master, on "Ru", epitomize Pre-Qin Confucian's understanding and expectations of themselves, and also reflect the Confucian new pursuit in facing the age of the uniflcation of Qin. /// 不管"儒"字在宇源上的原始意义如何，从学术史的观点来看，战国时代的 其他学派对"儒"的思想刻画，己经鲜明地呈现出儒家的思想特质:而战国儒学在 运用"儒"字上所表达的自我理解，更突出显现了"何为儒之人格，何为儒家的学 说宗旨"在当时的通行理解。尤其是，战国末期的儒学大师苟子对"儒"的理解， 作为战国时代评论各家"儒"的总结性代表，集中体现了先秦儒家的自我理解和自 我期许，同时也反映了儒家因应秦的统4 的时代即将到来的新的追求。. (shrink)

王充哲学思想建立在广评诸子的基础之上，通过对先秦诸子思想的继承与发展，形成一个既不属于儒家又不属于道家的独特的思想体系，抑或说继承了儒、道又超越了儒、道。本书以王充对先秦儒、道思想的评介为切入点，有别 于学界常用的从史学、经学、文献学等维度研究王充思想，而是注重从哲学的角度考察、梳理王充对先秦儒、道思想的理解与评判、继承与发展。.

本书选收《中国儒学的起源》、《经学起源刍探》、《论儒家生死鬼神观的非宗教性特征》等研究儒学哲学思想的文章32篇。.

Ben cheng guo yi li lun jia gou er fei li shi xu shu de jiao du yan jiu zao qi ru jia de wang ba zhi bian, zong jie wang dao ba dao de zhu yao nei rong, shu li wang ba zhi bian suo guan zhu de si xiang zhu ti, fen xi qi si xiang luo ji jia gou, tan jiu wang ba zhi bian zai Zhongguo chuan tong zheng zhi zhe xue ji Zhongguo chuan tong she (...) hui zhong di ying xiang he yi yi, bing yi xian dai zheng zhi zhe xue de shi jiao fen xi qi li lun de shi wa jue wang ba zhi bian de ji ji yi yi. (shrink)

Juan yi. Quan qiu hua zhong de Zhongguo gu dai zhe li -- juan er. Ru jia zai lin de yun yi yu dao lu.