Chang Liu

A positive attitude toward later life is crucial for wellbeing among older adults. Maintaining a healthy relationship with adult children can help reduce older parents’ sense of loneliness and nurture a positive life attitude. This study aimed to investigate the associations between multidimensional intergenerational relationship quality and attitudes toward later life among aging Chinese adults in Hong Kong and examine the mediating effects of a sense of loneliness. Representative survey data were collected from 801 participants with at least one adult child. Multiple linear regression was employed to investigate the associations between overall intergenerational relationship quality with a sense of loneliness as well as the attitude toward later life. To examine the mediating effects of a sense of loneliness, causal mediational analyses were performed. Results demonstrated that overall intergenerational relationship quality was positively associated with aging parents’ attitude toward later life, and this relationship could be partially mediated by a sense of loneliness. Among the four subdomains of intergenerational relationship quality, the influences of structural-associational solidarity and intergenerational conflict on attitude toward later life were almost fully mediated by a sense of loneliness, whereas the influences of consensual-normative solidarity and affectual closeness were partially mediated. These findings contributed to an improved understanding of the relationship between intergenerational relationship quality, sense of loneliness, and attitude toward later life, and could inform future policies and service programs that promote aging adults’ social integration and positive aging.

Most mass incidents are created by economic or social concerns brought on by fast socioeconomic change and poor local government. The number of mass occurrences in China has significantly increased in recent years, putting the country’s steady growth and public behavior decision-making in harm. We examine the factors that influence public behavior decision-making in the following significant factors, contributing to the development of effective prevention and response strategies. The structural equation approach is used to analyze the main determinants influencing public behavioral decisions in the aftermath of mass incidents using surveys of a large population. The finding shows that media plays a mediating role in the relationship between mass occurrences and influencing factors impacting public emotion. The direct and indirect effects of public behavior decision-making and its role increasingly social changes as things happen, government credibility, media plays mediating role in public emotional factors. All directly impact public behavior decision-making, while emotional factors have an indirect impact via media intermediaries. The escalation of public behavior decisions is seen as a result of structural transmission and the increase of dynamic as well as other factors.

Double 11 shopping carnival, celebrated by the most successful electronic-commerce Chinese company, Alibaba, has always been the online shopping festival with the highest turnover and involves the largest number of consumers and enterprises in China. This study integrates the elaboration likelihood model and stimulus-organism-response theory to study the dual-processing path of information, which drives customers’ behavioral intention on Double 11. There are 454 valid samples of data are collected, and the research model is tested using the partial least squares method. Results show that in the Double 11 context, two different processing mechanisms affect consumers’ behavioral intention. Thereinto, consumers’ behavioral intention is more affected by the peripheral path than the central path. The affective experience affected by the information stimulus has a greater impact on the behavioral intention than cognitive experience. Furthermore, we find situational involvement have different moderating effects on the relationship between two experiences and behavioral intention.

As the world’s most populous country, China is experiencing unprecedented magnitude and speed of population ageing since it entered the ageing society two decades ago. The rapid population ageing- driven by decreasing fertility rate and prolonged life expectancy- has profound impacts on economic development and poses significant challenges for formal and informal care provision. Although the Chinese government has implemented a series of progressive policy reforms on pension, healthcare, and long-term care systems, the capacity gaps regarding the coverage, adequacy, affordability, and sustainability remain large. At the same time, social and economic changes have eroded the supportive role of family, especially for rural-dwelling, childless, and empty-nest older adults. This chapter documents the statistical and social reality of ageing in China, introduces a series of policy reforms implemented by the Chinese government in response to population ageing, and describes the family dynamics and intergenerational support patterns under the changing socioeconomic background. Besides pressing challenges of ageing for family and society, this chapter also looks at the emerging lifestyle and proactivity for active ageing in China.

Service process optimization is conducive to the innovation of enterprise services, but the poor logic design of multiple touchpoints can easily lead to problems in the service process, such as scattered layouts and repeated paths. Aiming at the promotion of service innovation and user experience, this paper takes the optimization of a single service touchpoint as the prerequisite and proposes a service process optimization method based on service touchpoint association and the design structure matrix. The association of service touchpoints is categorized into two types, namely, noncoupled and coupled association. The DSM is used to describe the two types of association between service touchpoints, and the matrix operation is used for modular identification and layering of the two kinds of association. Finally, through the above steps, the problematic service process was replanned. By using the service process optimization of a new retail convenience store as an example, the service process is divided into 6 relatively independent modules, and the order of module execution is arranged. Moreover, the optimal service process of the convenience store system is determined, and the method is verified to be feasible. Through optimization both from single service touchpoint and service process modularization, the study provides a reference for process optimization of the complex service system.

This study concentrates on an investigation on how the variable of collaboration moderates the relationship between cultural typology of variety and work outcome in the cross-cultural work settings. The author predicts that collaboration will have impact on the relationship between variety of cultural character of gender egalitarian and task satisfactory. The empirical study conducted in the multinational companies located in China supported the assumptions. The result shows that by using the moderator of collaboration, gender variable is no longer the cultural character of separation reflecting conflict in cultural diversity team, instead, under the circumstance of collaboration, the attribute of cultural variety – coexistence of symmetry and asymmetry (e.g. Gender egalitarian) demonstrates more inclusive solution that benefit work outcomes in cultural diversity team.

While the genre-based approach has assumed increasing prominence in discussions of writing pedagogy for diverse classrooms, little is known about how secondary school student-teachers understand and adopt genre pedagogies in the English as a foreign language writing class. Based on the data from semi-structured interviews and teaching materials, this study examined Chinese EFL student-teachers’ knowledge and use of genre-based writing instruction during the teaching practicum and explored the challenges they encountered in enacting it. The findings demonstrated that teacher informants showed some familiarity with genre pedagogies, especially in terms of scaffolding the linguistic features and semantic patterns in the focused genres. However, they were generally confused over the connection between language, content, and context, and their GBWI practice scarcely involved the explicit teaching of the linguistic and semantic choices for a specific audience and context, which gave rise to some perceived tensions in the teaching reality. Further probing has revealed the complex interplay between Chinese EFL student-teachers’ professional knowledge, perceived difficulties, and genre instructional practice in the secondary school writing class. The study concludes with practical implications for the student-teachers’ professional development of effective GBA.

Short video addiction (SVA) has emerged as a growing behavioral and social issue, driven by the widespread use of digital platforms that provide highly engaging, personalized, and brief video content. We investigated the neuroanatomical and functional substrates of SVA symptoms, alongside brain transcriptomic and cellular characteristics, using Inter-Subject Representational Similarity Analysis (IS-RSA) and transcriptomic approaches. Behaviorally, we found that dispositional envy was associated with SVA. Structurally, SVA was positively correlated with increased morphological volumes in the orbitofrontal cortex (OFC) and bilateral cerebellum. Functionally, the dorsolateral prefrontal cortex (DLPFC), posterior cingulate cortex (PCC), cerebellum, and temporal pole (TP) exhibited heightened spontaneous activity, which was positively correlated with SVA severity. Transcriptomic and cellular analyses also showed specific genes linked to gray matter volume (GMV) associated with SVA, with predominant expression in excitatory and inhibitory neurons. These genes showed distinct spatiotemporal expression patterns in the cerebellum during adolescence. This study offers a comprehensive framework integrating structural, functional, and neurochemical evidence to highlight the neural-transcriptomic underpinnings of SVA symptoms in a non-clinical population.

Daoist meditation has been less widely adopted than Buddhist meditation as a daily method for psychological regulation, partly due to the complexity of its underlying philosophical system. This study aims to explore how key Daoist meditation practices can be psychologized and adapted into a usable method for modern psychological training. A comparative analysis was conducted on classical Daoist meditation methods, including Sitting in Oblivion, Mind Fasting, Ingestion of Qi, Visualization and Imagination, Inner Observation, and Internal Alchemy. Based on this analysis, a novel psychological training method called “Merging Oblivion Meditation” was developed by integrating elements of Inner Observation and Sitting in Oblivion. Among the practices analyzed, Inner Observation—which involves merging with the cosmic landscape—was found to be more adaptable for psychological application. The proposed “Merging Oblivion Meditation” employs guided imagination to reduce the sense of self by fostering an experiential merging with cosmic landscapes, thus facilitating nondual awareness without requiring apophatic operations. This method simplifies the difficulty of traditional Sitting in Oblivion and increases its feasibility as a psychological technique. Rooted in the Daoist vision of the body as an immortal cosmos, Merging Oblivion Meditation differs from Buddhist-derived practices in both process and psychological effects. By dissolving bodily boundaries and encouraging experiential unity with the Dao, it may engage distinct mechanisms conducive to nondual experiences, offering a unique contribution to contemplative science and meditation-based interventions.

In this paper, we study the radial neural network algorithm for low-carbon circular economy in forest area, design a coupled development evaluation model, study its algorithmic ideas operation mode and the update formula obtained by standard algorithm, and finally optimize the RBF neural network by particle swarm algorithm. After an in-depth analysis of the particle swarm algorithm, an improved particle swarm algorithm is proposed to improve the search accuracy and capability of the algorithm by nonlinearly adjusting the inertia weights and introducing the average extreme value factor, in response to the problems of premature convergence and poor search capability that appear in the particle swarm algorithm. Through the analysis and evaluation of the interaction between industrial ecosystem and carbon emission, the main influencing factors of carbon emission are identified, and the size and magnitude of the influence of economic growth, industrial structure, energy intensity, and energy structure on carbon emission are determined; the current situation of the industrial ecological structure is evaluated, and the direction of optimization and adjustment of industrial economic structure, energy structure, and ecological structure is clarified. We construct a multidimensional multiconstraint multimodel industrial ecological structure optimization prediction model, set the development scenarios of economy and society, and optimize the prediction of low-carbon industrial ecological structure in forest areas; based on the simulation analysis of the prediction results, we propose the direction of industrial ecological structure adjustment and the path of industrial ecological system construction.

Although emerging evidence has implicated structural/functional abnormalities of patients with Autism Spectrum Disorder, definitive neuroimaging markers remain obscured due to inconsistent or incompatible findings, especially for structural imaging. Furthermore, brain differences defined by statistical analysis are difficult to implement individual prediction. The present study has employed the machine learning techniques under the unified framework in neuroimaging to identify the neuroimaging markers of patients with ASD and distinguish them from typically developing controls. To enhance the interpretability of the machine learning model, the study has processed three levels of assessments including model-level assessment, feature-level assessment, and biology-level assessment. According to these three levels assessment, the study has identified neuroimaging markers of ASD including the opercular part of bilateral inferior frontal gyrus, the orbital part of right inferior frontal gyrus, right rolandic operculum, right olfactory cortex, right gyrus rectus, right insula, left inferior parietal gyrus, bilateral supramarginal gyrus, bilateral angular gyrus, bilateral superior temporal gyrus, bilateral middle temporal gyrus, and left inferior temporal gyrus. In addition, negative correlations between the communication skill score in the Autism Diagnostic Observation Schedule and regional gray matter volume in the gyrus rectus, left middle temporal gyrus, and inferior temporal gyrus have been detected. A significant negative correlation has been found between the communication skill score in ADOS_G and the orbital part of the left inferior frontal gyrus. A negative correlation between verbal skill score and right angular gyrus and a significant negative correlation between non-verbal communication skill and right angular gyrus have been found. These findings in the study have suggested the GM alteration of ASD and correlated with the clinical severity of ASD disease symptoms. The interpretable machine learning framework gives sight to the pathophysiological mechanism of ASD but can also be extended to other diseases.

Traditional theories construe approximate truth or truthlikeness as a measure of closeness to facts, singular facts, and idealization as an act of either assuming zero of otherwise very small differences from facts or imagining ideal conditions under which scientific laws are either approximately true or will be so when the conditions are relaxed. I first explain the serious but not insurmountable difficulties for the theories of approximation, and then argue that more serious and perhaps insurmountable difficulties for the theory of idealization force us to sever its close tie to approximation. This leads to an appreciation of lawlikeness as a measure of closeness to laws, which I argue is the real measure of idealization whose main purpose is to carve nature at its joints.

Non-native listeners deal with adverse listening conditions in their daily life much harder than native listeners. However, previous work in our laboratories found that native Chinese listeners with native English exposure may improve the use of temporal fluctuations of noise for English vowel identification. The purpose of this study was to investigate whether Chinese listeners can generalize the use of temporal cues for the English sentence recognition in noise. Institute of Electrical and Electronics Engineers sentence recognition in quiet condition, stationary noise, and temporally-modulated noise were measured for native American English listeners, native Chinese listeners in the United States, and native Chinese listeners in China. Results showed that in general, EN listeners outperformed the two groups of CN listeners in quiet and noise, while CNU listeners had better scores of sentence recognition than CNC listeners. Moreover, the native English exposure helped CNU listeners use high-level linguistic cues more effectively and take more advantage of temporal fluctuations of noise to process English sentence in severely degraded listening conditions [i.e., the signal-to-noise ratio of −12 dB] than CNC listeners. These results suggest a significant effect of language experience on the auditory processing of both speech and noise.