Measurement and management of genotype-environment interaction (GxE) for the improvement of rainfed lowland rice yield in Cambodia

The magnitude and nature of genotype-by-environment interactions (G×E) for grain yield (GY) and days to flower (DTF) in Cambodia were examined using a random population of 34 genotypes taken from the Cambodian rice improvement program. These genotypes were evaluated in multi-environment trials (MET) conducted across three years (2000 to 2002) and eight locations in the rainfed lowlands. The G×E interaction was partitioned into components attributed to genotype-by-location (G×L), genotype-by-year (G×Y) and genotype-by-location-by-year (G×L×Y) interactions. The G×L×Y interaction was the largest component of variance for GY. The G×L interaction was also significant and comparable in size to the genotypic component (G). The G×Y interaction was small and non significant. A major factor contributing to the large G×L×Y interactions for GY was the genotypic variation for DTF in combination with environmental variation for the timing and intensity of drought. Some of the interactions for GY associated with timing of plant development and exposure to drought were repeatable across the environments enabling the identification of three-target populations of environments (TPE) for consideration in the breeding program. Four genotypes were selected for wide adaptation in the rainfed lowlands in Cambodia.

Observations in a maternity ward: Usability considerations for EHRs in an interrupt driven environment

With the increasing demand on healthcare systems it is imperative that all care is provided as efficiently and effectively as possible. Technology within the medical domain offers an exciting opportunity to augment work practices in order to meet these needs. This research project explores the implications of the interrupt-driven nature of work in clinical situations on documentation within an environment that increasingly involves electronic health records (EHRs). Midwives in a busy maternity ward were observed and interviewed about the work practices they employed to document information associated with patient care. The results showed that the interrupt-driven nature of the workplace, a feature common to many healthcare settings, led to a tension between the work and the work to document the work. Further, the IT environment in which the information was collected was not designed to cater for frequent interruption of the data entry process. Several recommendations for improving the IT environment are proposed to support health professionals in documenting patient data whilst attending to the interruptions. The recommendations include timeout screens, push technology, use of handheld PDAs, and cues to augment documentation in an interrupted session. Copyright © 2008 RMIT Publishing

Moomba - A collaborative environment for supporting distributed extreme programming in global software development

Global Software Development (GSD) is an emerging distributive software engineering practice, in which a higher communication overhead due to temporal and geographical separation among developers is traded with gains in reduced development cost, improved flexibility and mobility for developers, increased access to skilled resource-pools and convenience of customer involvements. However, due to its distributive nature, GSD faces many fresh challenges in aspects relating to project coordination, awareness, collaborative coding and effective communication. New software engineering methodologies and processes are required to address these issues. Research has shown that, with adequate support tools, Distributed Extreme Programming (DXP) – a distributive variant of an agile methodology – Extreme Programming (XP) can be both efficient and beneficial to GDS projects. In this paper, we present the design and realization of a collaborative environment, called Moomba, which assists a distributed team in both instantiation and execution of a DXP process in GSD projects.