Background: It remains unknown what the impacts of multiple dimensions of contact (e.g. level, quantity and quality) are on the stigma of mental illness. Aims: To explore the relationship between the multiple dimensions of contact and stigma of mental illness among family members (FM), mental health workers (MHW) and community residents (CR) in Hong Kong. Methods: The stigma, contact and knowledge were measured in FM, MHW and CR in Hong Kong. Multiple regression analyses were used. Results: MHW ( n = 141) had higher knowledge, more contact and lower stigma of mental illness than CR ( n = 95) or FM ( n = 62). Knowledge and contact quality were significantly associated with lower stigma of mental illness in the three groups. However, contact level and contact quantity were not significantly associated with most stigma components. The contact level was positively associated with stigma of mental illness among FM and CR. Conclusions: The results of this study highlight the differences in knowledge, contact and stigma of mental illness among different stakeholder groups. This study suggests that positive contact (e.g. equal, supportive, voluntary and pleasant contact) reduces stigma of mental illness, while negative contact (e.g. unfriendly, unsupportive, unpleasant contact) may increase stigma. The Enhancing Contact Model (ECM) should be tested in future anti-stigma interventions.

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. Nowadays, embedded system has been integrated into the various fields of people's life. The contradiction between energy efficiency and time efficiency is more and more seriously. A system with DVFS module can relieve this contradiction. But a lot of researches witch concern about it has kinds of defects. This paper designed a new energy consumption model for a DVFS system and a new simple multi-phase task module for the task generating and processing. Then a dynamic DVFS method was designed to run in our platform with kinds of different types of tasks. We introduced a mechanism with dynamic frequency update interval into our method, and proved that in most cases it can achieve better energy efficiency than other two algorithms which use a fixed frequency update interval. Meanwhile, it can hold the similar time efficiency to the algorithm which makes the best time efficiency in them.