Hao Zhang

The increasing global effort to drive the energy transition has led to rising demand for lithium. This metal is crucial in manufacturing lithium-ion batteries, which are used for energy storage and electric vehicles (EVs). As governments worldwide push for renewable energy to achieve their clean energy targets, the role of lithium has become even more critical in making the energy transition process sustainable and affordable. Given its ambition to build the world’s largest EV market, China has prioritized lithium in its industrial policy agenda. Drawing lessons from China, this chapter examines the required regulatory and policy frameworks to bolster the lithium supply chain. Implementing these strategies has influenced the country’s domestic policy and regulation, focusing on driving the uptake of EVs, establishing dominance over the lithium supply chain, and securing supplies of raw materials. However, the sustainable development and greening of the supply chain face significant challenges.

ObjectiveThe information age has transformed technologies across disciplines. Generative artificial intelligence (GenAI), as an emerging technology, has integrated into scientific research. Recent studies identify GenAI-related scientific research integrity concerns. Using Complex Adaptive Systems (CAS) theory, this research examines risk factors and preventive measures for each agent within the scientific research integrity management system during GenAI adoption, providing new perspectives for integrity management.MethodThis study applies CAS theory to analyze the scientific research integrity management system, identifying four core micro-level agents: researchers, research subjects, scientific research administrators, and academic publishing institutions. It examines macro-system complexity, agent adaptability, and the impact of agent interactions on the overall system. This framework enables analysis of GenAI’s effects on the research integrity management system.ResultsThe scientific research integrity management system exhibits structural, hierarchical, and multidimensional complexities, with internal circulation of policy, funding, and information elements. In response to GenAI integration, four micro-level agents—researchers, research subjects, scientific research administrators, and academic publishing institutions—adapt their behaviors to systemic changes. Through these interactions, behavioral outcomes emerge at the macro level, driving evolution of the research integrity management system.ConclusionsRisks of scientific misconduct permeate the entire research process and require urgent governance. This study recommends that scientific research administrators promptly define applicable boundaries for GenAI in research to guide researchers. Concurrently, they should collaborate with relevant departments to establish regulatory frameworks addressing potential GenAI-related misconduct. Academic publishing institutions must assume quality assurance responsibilities by strengthening review and disclosure protocols. Furthermore, research integrity considerations should be systematically integrated into GenAI’s technological development and refinement.Highlights● Develops an analytical framework grounded in Complex Adaptive Systems (CAS) theory to map evolving interactions among researchers, research subjects, scientific research administrators, and academic publishing institutions within GenAI-integrated research ecosystems. ● Identifies self-reinforcing dynamics between GenAI adoption and integrity governance, wherein adaptive rule adjustments by agents reshape system-wide integrity thresholds. ● Proposes adaptive governance mechanisms that balance innovation safeguards with integrity guardrails, emphasizing context-sensitive policy calibration over universal solutions.

This research aims to investigate the potential implementation of robotic classes and robotics in modern music education. The research methodology is based on experimental approaches, the questionnaire method, static data analysis techniques, and the descriptive method of analysing the results obtained. A total of 245 students from Chinese music universities and conservatories participated in the survey. The research findings revealed that 88% of the students were willing to transition entirely to robotics-based education. Among them, 90% exhibited familiarity with contemporary technologies and their specific applications in music education. Over half of the students (80%) had grown accustomed to the robotic learning format and saw no need for attending classes with human instructors (85%). Furthermore, 81% of the participants in the study expressed confidence in the potential for complete automation of music education in the future. The majority of the students (94%) welcome the use of robotics in music education.

Polarized and unpolarized neutron scattering techniques along with x-ray diffraction have been used to study the magnetic and structural properties of a single crystal of Nd2CuO4. Long-range magnetic order of the Cu moments develops at TN=245 K, with a simple antiferromagnetic configuration of spins as found in La2NiO4, while the spin directions may be either collinear or noncollinear. Additional abrupt transitions are observed at 75 and 30 K, in which spin reorientations take place. Bragg peaks associated with the crystal structure are found at the same positions as the magnetic Bragg peaks, and indicate that a small distortion of the basic tetragonal structure has occurred above 300 K. At low temperatures the Nd moments also order antiferromagnetically, while an additional transition of a continuous nature is observed at 150 mK.

Aneuploidy with chromosome instability is a cancer hallmark. We studied chromosome 7 copy number variation in gliomas and in primary cultures derived from them. We found tumor heterogeneity with cells having Chr7-CNV commonly occurs in gliomas, with a higher percentage of cells in high-grade gliomas carrying more than 2 copies of Chr7, as compared to low-grade gliomas. Interestingly, all Chr7-aneuploid cell types in the parental culture of established glioma cell lines reappeared in single-cell-derived subcultures. We then characterized the biology of three syngeneic glioma cultures dominated by different Chr7-aneuploid cell types. We found phenotypic divergence for cells following Chr7 missegregation, which benefited overall tumor growth in vitro and in vivo. Mathematical modeling suggested the involvement of chromosome instability and interactions among cell subpopulations in restoring the optimal equilibrium of tumor cell types. Both our experimental data and mathematical modeling demonstrated that the complexity of tumor heterogeneity could be enhanced by the existence of chromosomes with structural abnormality, in addition to their mis-segregations. Overall, our findings show, for the first time, the involvement of chromosome instability in maintaining tumor heterogeneity, which underlies the enhanced growth, persistence and treatment resistance of cancers. © 2013 Hu et al.

In order to explore the correlation between students’ seat choice and interaction preference in the open gamification scenario, an experiment has been carried out on the platform of provincial virtual simulation experiment teaching center of a university, and tested the relationship between absolute distance, seat type, workstation type, and students’ interaction preference. The results show that in the virtual-reality fusion gamification scenario where students can move freely: The inner circle students can stimulate the outer circle students’ willingness to invest in learning. The task attribute and the seat distribution of the group may lead to the difference of students’ interaction preference. Students are more likely to learn knowledge and skills by interacting with “people” rather than “object.” Gender and major influence students’ experience of participating in gamified teaching. The results confirm that the interactive engagement effect of location does exist in immersive virtual-reality fusion gamification teaching scenario, and suggestions are put forward to adjust the effect of location through instructional design and teacher intervention.

This study aims to achieve the goal of cultivating and reserving emerging professional talents in social security law, improve the curriculum and mechanism of entrepreneurship education, and improve students’ entrepreneurial willingness and entrepreneurial ability. Deep learning technology is used to study the psychological effects of entrepreneurship education for college students majoring in social security law. Firstly, the concept of entrepreneurial psychology is elaborated and summarized. A related model is designed using the theory of proactive personality and planned behavior through questionnaire survey and regression analysis to explore the relationship between students’ entrepreneurial psychology and entrepreneurial intention. Secondly, an entrepreneurship education method based on deep learning is proposed, and a teaching model of multi-dimensional collaborative entrepreneurship education practice is constructed. On this basis, the deep learning algorithm combines the characteristics of the personalized recommendation algorithm to construct an efficient Problem-Based Learning learning resource recommendation algorithm. Finally, the proposed method is tested. The results show that the Significant value of students who have participated in PBL deep learning courses is less than 0.05, indicating that PBL significantly improves students’ learning ability and the ability to deal with entrepreneurial environments. The results verify the impact of entrepreneurial learning on entrepreneurial intentions. The research on PBL online learning recommendation system shows that the proposed recommendation algorithm is superior to the traditional recommendation algorithm in both roots mean square error value and mean absolute error value on both datasets. The proposed method provides a new idea of reform and innovation to cultivate social security law professionals and the cultivation of the reserve model.

As an emerging form of online display advertising, in-feed native advertising is increasingly employed in online news feed platforms. While many advertisers have largely embraced this new advertising format, the current research is full of controversy on whether the more native, the better the effect of in-feed native advertising. Based on recent studies on this emerging topic, the authors explore the effective in-feed native advertising persuasion strategies based on consumers’ dynamic online browsing modes. In study 1, the authors conducted an archived-data analysis. Results show that the match between in-feed native advertising persuasion style and consumers’ real-time news feed browsing modes can improve ad performance. In study 2, the authors further explained why consumers under different browsing modes respond differently to specific in-feed native advertising persuasion. Our work explores the boundaries of agency theory from a dynamic perspective and helps advertisers conduct real-time and effective targeting strategies.

Despite the vast academic interest in workplace helping, little is known about the impact of different types of helping behaviors on physiological and behavioral ramifications of helpers. By taking the actor-centric perspective, this study attempts to investigate the differential impacts of three kinds of helping behaviors on helpers themselves from the theory of resource conservation. To test our model, 512 Chinese employees were surveyed, utilizing a three-wave time-lagged design, and we found that caring and coaching helping were negatively associated with workplace deviance, whereas substituting helping was positively associated with subsequent workplace deviance. Emotional exhaustion mediated the effects of three helping behaviors on subsequent workplace deviance. Moreover, employees' extrinsic career goals influenced the strength of the relationship between three helping behaviors and emotional exhaustion and the indirect effects of three helping behaviors on subsequent workplace deviance via emotional exhaustion. We discuss the implications of our findings for both theories and practices.

Background High levels of moral distress in nursing professionals, of which oncology nurses are particularly prone, can negatively impact patient care, job satisfaction, and retention. Aim “Positive Attitudes Striving to Rejuvenate You: PASTRY” was developed at a tertiary cancer center to reduce the burden of moral distress among oncology nurses. Research Design A Quality Improvement (QI) initiative was conducted using a pre- and post-intervention design, to launch PASTRY and measure its impact on moral distress of the nursing unit, using Hamric’s Moral Distress Scale–Revised (MDS-R.) This program consisted of monthly 60-minute sessions allowing nurses to address morally distressing events and themes, such as clinicians giving “false hope” to patients or families. The PASTRY program sessions were led by certified clinicians utilizing strategies of discussion and mind-body practices. Participants Clinical nurses working on an adult leukemia/lymphoma unit. Ethical considerations This was a QI initiative, participation was voluntary, MDS-R responses were collected anonymously, and the institution’s Ethics Committee oversaw PASTRY’s implementation. Findings While improvement in moral distress findings were not statistically significant, the qualitative and quantitative findings demonstrated consistent themes. The PASTRY program received strong support from nurses and institutional leaders, lowered the nursing unit’s moral distress, led to enhanced camaraderie, and improved nurses’ coping skills. Discussion Measurement of moral distress is innately challenging due to its complexity. This study reinforces oncology nurses have measurable moral distress. Interventions should be implemented for a safe and healing environment to explore morally distressing clinical experiences. Poor communication among multidisciplinary team members is associated with moral distress among nurses. Programs like PASTRY may empower nurses to build support networks for change within themselves and institutions. Conclusion This QI initiative shows further research on moral distress reduction should be conducted to verify findings for statistical significance and so that institutional programs, like PASTRY, can be created.

A shortage or backlog of inventory can easily occur due to the backward forecasting method typically used, which will affect the normal flow of funds in pharmacies. This paper proposes a replenishment decision model with back propagation neural network multivariate regression analysis methods. With the regular pattern between sales and individual variables, supplemented with the safety stock empirical formula, an accurate replenishment quantity can be obtained. In the case analysis, this paper takes the sales situation of a pharmacy as an example and tests the accuracy and stability of the model. The results show that the model has good prediction accuracy which can be introduced into the intelligent pharmacy system and used in the replenishment of the intelligent pharmacy to prevent overstocking or a shortage of stock, thus improving the financial situation, reducing the manpower burden of typical retail pharmacy, and helping residents buy medicines.

Neutron and X-ray diffraction have been used to study the magnetic and structural properties of single crystal Nd2CuO4. Long range magnetic order of the Cu moments develops at TN=245 K, with a noncollinear antiferromagnetic arrangement of spins. Additional abrupt transitions are observed at 75 K and 30 K, in which a spin reorientation takes place. Bragg peaks associated with the crystal structure are found at the same positions as the magnetic Bragg peaks, and indicate that a distortion of the basic tetragonal structure has occurred above 300 K. © 1989.

This study examines whether community social capital in US counties, as captured by strength of civic norms and density of social networks in the counties, affects corporate social responsibility of resident corporations headquartered in the counties. Analyses of longitudinal data from 3688 unique US firms between 1997 and 2009 provide strong empirical support for the propositions that community social capital facilitates positive CSR activities that benefit non-shareholder stakeholders and constrains negative CSR activities that are detrimental to non-shareholder stakeholders. Additionally, we explore the effects of institutional logics arising from community isomorphism on positive and negative CSR activities, respectively. And, we explore the respective effects of corporate engagement in positive and negative CSR activities on corporate financial performance. Firms undertake more positive CSR activities when such activities are more prevalent among other local corporations headquartered in the same county. But, there is no systematic relationship between negative CSR activities and the community-level corporate engagement in negative CSR activities. Positive CSR activities enhance a firm’s future financial performance, and the positive effect is more prominent among firms headquartered in counties with high community social capital. However, negative CSR activities only reduce a firm’s future financial performance among firms headquartered in counties with high community social capital; negative CSR activities do not affect performance among firms headquartered in counties with lower levels of community social capital. Collectively, these results highlight the distinct effects of local social institutions, namely community social capital, on positive CSR activities and negative CSR activities, respectively.

Previous behavioral studies have identified the significant role of subliminal cues in creative problem solving. However, neural mechanisms of such unconscious processing remain poorly understood. Here we utilized an event-related potential approach and sandwich mask technique to investigate cerebral activities underlying the unconscious processing of cues in creative problem solving. College students were instructed to solve divergent problems under three different conditions . Our data showed that creative problem solving can benefit from unconscious cues, although not as much as from conscious cues. More importantly, we found that there are crucial ERP components associated with unconscious processing of cues in solving divergent problems. Similar to the processing of conscious cues, processing unconscious cues in problem solving involves the semantic activation of unconscious cues in the right inferior parietal lobule , new association formation in the right parahippocampal gyrus , and mental representation transformation in the right superior temporal gyrus . The present results suggest that creative problem solving can be modulated by unconscious processing of enlightening information that is weakly diffused in the semantic network beyond our conscious awareness