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Abstract: Nowadays, there is an increasing demand for incorporating unstructured narratives in decision support for knowledge-intensive industries such as healthcare and social service organizations. However, most of the current research on decision support systems (DSS) mainly focused on dealing with structured data and are inadequate to dealing with unstructured narratives such as clients’ records and stories. This paper presents a narrative-based reasoning (NBR) algorithm which incorporates the technologies of knowledge-based system (KBS), computational linguistics, and artificial intelligence (AI) for automatic processing unstructured narratives and inferring useful knowledge for decision support. A NBR enabled DSS has been built and was evaluated through a series of experiments conducted in early intervention of mental health of a social service company in Hong Kong. The performance of NBR was measured based on recall and precision and encouraging results were obtained. High recall and precision are achieved in the reasoning of unstructured data, and high recall is achieved for the association analysis. The results show that it is possible for inferring recommendations for problem solving from unstructured narratives automatically. Based on the approach, it helps to support knowledge workers with reliable suggestions on decision making so as to increase the quality of their solutions. [ABSTRACT FROM AUTHOR]

Blast, caused by Magnaporthe grisea is one of most serious diseases of rice worldwide. A Chinese local rice variety, Digu, with durable blast resistance, is one of the important resources for rice breeding for resistance to blast ( M. grisea) in China. The objectives of the current study were to assess the identity of the resistance genes in Digu and to determine the chromosomal location by molecular marker tagging. Two susceptible varieties to blast, Lijiangxintuanheigu (LTH) and Jiangnanxiangnuo (JNXN), a number of different varieties, each containing one blast resistance gene, Pik s, Pia, Pik, Pi- b, Pi- k p, Pi- ta2, Pi- ta, Pi- z, Pi- i, Pi- k m, Pi- z t, Pi- t and Pi-11, and the progeny populations from the crosses between Digu and each of these varieties were analysed with Chinese blast isolates. We found that the resistance of Digu to each of the two Chinese blast isolates, ZB13 and ZB15, were controlled by two single dominant genes, separately. The two genes are different from the known blast resistance genes and, therefore, designated as Pi-d(t)1 and Pi-d(t)2. By using bulked segregation method and molecular marker analysis in corresponding F2 populations, Pi-d(t)1 was located on chromosome 2 with a distance of 1.2 and 10.6 cM to restriction fragment length polymorphism (RFLP) markers G1314A and G45, respectively. And Pi-d(t)2 was located on chromosome 6 with a distance of 3.2 and 3.4 cM to simple sequence repeat markers RM527 and RM3, respectively. We also developed a novel strategy of resistance gene analogue (RGA) assay with uneven polymerase chain reaction (PCR) to further tag the two genes and successfully identified two RGA markers, SPO01 and SPO03, which were co-segregated to Pi-d(t)1 and Pi-d(t)2, respectively, in their corresponding F2 populations. These results provide essential information for further utilization of the Digu's blast resistance genes in rice disease resistance breeding and positional cloning of these genes. [ABSTRACT FROM AUTHOR]