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Wearable devices and ambient sensors can monitor a growing number of aspects of daily life and work. We propose to use this context data as content for learning applications in workplace settings to enable employees to reflect on experiences from their work. Learning by reflection is essential for today's dynamic work environments, as employees have to adapt their behavior according to their experiences. Building on research on computer-supported reflective learning as well as persuasive technology, and inspired by the Quantified Self community, we present an approach to the design of tools supporting reflective learning at work by turning context information collected through sensors into learning content. The proposed approach has been implemented and evaluated with care staff in a care home and voluntary crisis workers. In both domains, tailored wearable sensors were designed and evaluated. The evaluations show that participants learned by reflecting on their work experiences based on their recorded context. The results highlight the potential of sensors to support learning from context data itself and outline lessons learned for the design of sensor-based capturing methods for reflective learning.

BACKGROUND: Approximately 20% of patients with stage II colorectal cancer will experience a relapse. Current clinical-pathologic stratification factors do not allow clear identification of these high-risk patients. ColoPrint (Agendia, Amsterdam, The Netherlands, http://www.agendia.com) is a gene expression classifier that distinguishes patients with low or high risk of disease relapse. METHODS: ColoPrint was developed using whole-genome expression data and validated in several independent validation cohorts. Stage II patients from these studies were pooled (n = 416), and ColoPrint was compared with clinical risk factors described in the National Comprehensive Cancer Network (NCCN) 2013 Guidelines for Colon Cancer. Median follow-up was 81 months. Most patients (70%) did not receive adjuvant chemotherapy. Risk of relapse (ROR) was defined as survival until first event of recurrence or death from cancer. RESULTS: In the pooled stage II data set, ColoPrint identified 63% of patients as low risk with a 5-year ROR of 10%, whereas high-risk patients (37%) had a 5-year ROR of 21%, with a hazard ratio (HR) of 2.16 (p = .004). This remained significant in a multivariate model that included number of lymph nodes retrieved and microsatellite instability. In the T3 microsatellite-stable subgroup (n = 301), ColoPrint classified 59% of patients as low risk with a 5-year ROR of 9.9%. High-risk patients (31%) had a 22.4% ROR (HR: 2.41; p = .005). In contrast, the NCCN clinical high-risk factors were unable to distinguish high- and low-risk patients (15% vs. 13% ROR; p = .55). CONCLUSION: ColoPrint significantly improved prognostic accuracy independent of microsatellite status or clinical variables, facilitating the identification of patients at higher risk who might be considered for additional treatment. [ABSTRACT FROM AUTHOR]

Sugarcane mosaic virus (SCMV) is one of the most important virus diseases of maize in Europe. In this study, the gene action at two major quantitative trait loci (QTL) affecting resistance to SCMV in maize was mapped and characterized. A total of 121 F[sub 3] lines from cross F7 (susceptible) x FAP1360A (resistant) were evaluated for SCMV resistance in replicated field trials across two environments under artificial inoculation at seven scoring dates. The genotypic variance was always highly significant and heritability increased up to 0.92 for later scoring dates. The method of composite interval mapping was employed for QTL mapping using four simple sequence repeat (SSR) markers flanking two regions identified in a previous study with cross D145 x D32. The presence of two QTL for SCMV resistance, one on chromosome 6 (Scm1 region) and one on chromosome 3 (Scm2 region), was confirmed. These two QTL together explained between 15% (first score) and 62% (final score) of the phenotypic variance at various stages of plant development. Gene action was additive for the Scm[sub 2] region but completely dominant for the Scm1 region. Comparison of results of this study with those obtained for cross D145 x D32 suggested that the resistance alleles in the two populations are identical for the Scm1 region but different for the Scm2 region. [ABSTRACT FROM AUTHOR]