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This purpose of this study was to explore the prevalence and recognition of depressive disorders in cardiology, gastroenterology, and neurology outpatient departments of general hospitals. Patients screened with a Hospital Anxiety and Depression Scale score of 8 or higher were interviewed by psychiatrists using Mini-International Neuropsychiatric Interview (MINI). Prevalence of depressive disorders within the cohort was determined, sociodemographic data were analyzed for correlations to a depression diagnosis, and comparisons between the surveys and the clinical diagnosis were done to assess recognition of depressive disorders by physicians. Of the patients screened for this study (1552 cases), 12.8% were diagnosed with depressive disorders by MINI, with major depressive disorder, depression due to general medical conditions, and dysthymia having prevalence values of 10.8%, 1.4%, and 0.6%, respectively. As compared with MINI, physicians only recognized 27.6% of any of the depressive disorders. Among the complaints examined, both mood problems and sleeping problems predicted the probability of recognition.

Abstract. How to manage the message passing among inter processor cores with lower overhead is a great challenge when the multi-core system is the contemporary solution to satisfy high performance and low energy demands in general and embedded computing domains. Generally speaking, the networks-on-chip connects the distributed multi-core system. It takes charge of message passing which including data and synchronization message among cores. The size of most data transmission is typically large enough that it remains strongly bandwidth-bound. The synchronization message is very small which is primarily latency bound. Thus the separated networks-on-chip are needed to transmit the above two types of message. In this paper we focus on the network for the transmission of synchronization messages. A hardware module -message passing unit (MPU) is proposed to manage the synchronization message passing for the heterogeneous multi-core system. Compared with the original single network approach, this solution reduces the run-time object scheduling and synchronization overhead effectively, thereby, improving the whole system performance.