Surface and Edge States in Topological Semi-metals

We study the topologically non-trivial semi-metals by means of the 6-band Kane model. Existence of surface states is explicitly demonstrated by calculating the LDOS on the material surface. In the strain free condition, surface states are divided into two parts in the energy spectrum, one part is in the direct gap, the other part including the crossing point of surface state Dirac cone is submerged in the valence band. We also show how uni-axial strain induces an insulating band gap and raises the crossing point from the valence band into the band gap, making the system a true topological insulator. We predict existence of helical edge states and spin Hall effect in the thin film topological semi-metals, which could be tested with future experiment. Disorder is found to significantly enhance the spin Hall effect in the valence band of the thin films

The Socialisation and Interaction in the Volunteer Experience

Volunteering experience is believed to provide the potential for the socialisation and interaction of the participants. By means of observations, focus group and interviews, the research attempts to analyse the volunteering process and attitude shifts in relation to volunteering. Findings of the research confirm that apart from helping the destinations, volunteers develop their personalities and attitudes towards life during their journey of helping children in rural China. A wide range of interactions and socialisation opportunities take place before, during, and after volunteering. Volunteers benefit in the confirmation of self-value, interaction, learning and socialisation. The research concludes that volunteering makes notable contribution to youth development and poverty alleviation

Family business, resilience, and ethnic tourism in Yunnan, China

The expansion in commodification through tourism and the transformation of communities and heritages into destination attributes have become the centre of tourism research facing the COVID-19 crisis. Since small family businesses comprise the majority of the tourism industry, theories and practices on surviving the crisis are urgently required. This research attempts to clarify the level of business resilience during the COVID-19 lock down when business can only be conducted at home with very few visitors. It provides insights on family businesses in Yunnan, China, moving ahead with ethnic tourism against the lockdown and shutdown of tourism industry. Data were collected through in-depth interviews. The researchers invited previous research respondents who agreed to continue for online interviews. Eight interviewees were selected by purposive sampling. Although the COVID-19 crisis was unexpected, external shocks need to be taken into account for business planning. Tourism will not necessarily grow massively in the total number of visitors as the destinations have become saturated. The diversification of a tourism business facilitates the resilience of the firm by venturing into other areas of practice, including taking advantage of online platforms in selling local food and herbs, live broadcasting the local flora and fauna, teaching school children in making the traditional pickles, and other business extensions from tourism. Businesses are working together with other stakeholders in the effort of overcoming the COVID-19 crisis. Previous visitors from not only China but also overseas, who have kept in touch with the hosts in Yunnan, are becoming part of the supporting team for the business. However, there appears to be a lack of coordination in the community when businesses are isolated. There is a call for skills in using technology for online business, complementarity in the community, and policy support in the ethnic family businesses. Small family businesses in ethnic Yunnan are actively adapting and progressing despite the odds. They are resilient in times of crisis, with a strong presence of entrepreneurship, diversification of activities, re-organising resources, and digital literacy. The research sheds light on how community-based small family businesses surviving the crisis through resilience, entrepreneurship, and celebrating their ethnic cultures in tourism. Small-scale tourism closely linked with the community, family, and people may provide more promising prospects for tourism

Enabling Large Language Models to Learn from Rules

Large language models (LLMs) have shown incredible performance in completing various real-world tasks. The current knowledge learning paradigm of LLMs is mainly based on learning from examples, in which LLMs learn the internal rule implicitly from a certain number of supervised examples. However, the learning paradigm may not well learn those complicated rules, especially when the training examples are limited. We are inspired that humans can learn the new tasks or knowledge in another way by learning from rules. That is, humans can grasp the new tasks or knowledge quickly and generalize well given only a detailed rule and a few optional examples. Therefore, in this paper, we aim to explore the feasibility of this new learning paradigm, which encodes the rule-based knowledge into LLMs. We propose rule distillation, which first uses the strong in-context abilities of LLMs to extract the knowledge from the textual rules and then explicitly encode the knowledge into LLMs' parameters by learning from the above in-context signals produced inside the model. Our experiments show that making LLMs learn from rules by our method is much more efficient than example-based learning in both the sample size and generalization ability.Comment: In progres