Chitosanase may enhance anti-fungal defense responses in transgenic tobacco

Chitosanase is an enzyme, similar to chitinase, capable of hydrolyzing the β-1,4-linkages between N-acetyl-D-glucosamine and D-glucosamine residues in partially acetylated chitosan polymers found in fungal cell walls. When attacked by pathogenic fungi, many plants exploit this hydrolytic action as a component of a larger post-attack defense response, but these enzymes may also play a role in the initial plant-pathogen interaction via the generation of elicitors resulting from the hydrolysis of fungal cell walls. To gain insight into these mechanisms, a Paenbacillus chitosanase was cloned, sequenced, and modified for plant expression. The modified gene was delivered to tobacco (Nicotiana tabacum L. cv. Xanthine) leaf disks via Agrobacterium tumenfaciensmediated transformation. Whole plants were regenerated from the transformed cells. The putative transformants were tested for transgene integration, transcription, and translation. Confirmed transformants were then screened for enhanced responses to a Rhizoctonia solani cellwall preparation by measuring time-course production of hydrogen peroxide, phenylalanine ammonia lyase, and peroxidase. These compounds play roles at different points in a pathogenesis-related signal transduction pathway and thus allow for an initial assessment of the global defense response. Preliminary data suggest that transgenic tobacco constitutively expressing a Paenbacillus chitosanase may activate pathogenesis-related defense responses more quickly than wild type tobacco

Choosing the best forage species for a dairy farm: The Whole-farm approach

Although a handful of forage species such as perennial ryegrass are predominant, there are a wide range of forage species that can be grown in sub tropical and temperate regions in Australia as dairy pastures. These species have differing seasonal yields, nutrient quality and water use efficiency characteristics, as demonstrated in a large study evaluating 30 species University of Sydney in New South Wales, Australia. Some species can be grazed, while others require mechanical harvesting that incurs a further cost. Previous comparisons of species that relied on yields of dry matter per unit of some input (typically land or water) cannot simultaneously take into account the season in which forage is produced, or other factors related to the costs of production and delivery to the cows. To effectively compare the profitability of individual species, or combinations of species, requires the use of a whole-farm model. Linear programming was used to find the most profitable mix of forage species for an irrigated dairy farm in an irrigation region of New South Wales, Australia. It was concluded that a typical farmer facing the prevailing milk and purchased feed prices with average milk production per cow would find a mix of species including large proportions of perennial ryegrass (Lolium perenne) and prairie grass (Bromus willdenowii) was most profitable. The result was robust to changes in seasonal milk pricing and moving from year round to seasonal calving patterns.Dairy, Forage, Whole-farm, Linear programming

From Oil to Ingenuity, digitizing solar-powered mobility

No Abstract

Using distributional similarity to organise biomedical terminology

We investigate an application of distributional similarity techniques to the problem of structural organisation of biomedical terminology. Our application domain is the relatively small GENIA corpus. Using terms that have been accurately marked-up by hand within the corpus, we consider the problem of automatically determining semantic proximity. Terminological units are dened for our purposes as normalised classes of individual terms. Syntactic analysis of the corpus data is carried out using the Pro3Gres parser and provides the data required to calculate distributional similarity using a variety of dierent measures. Evaluation is performed against a hand-crafted gold standard for this domain in the form of the GENIA ontology. We show that distributional similarity can be used to predict semantic type with a good degree of accuracy

Where’s the value in engineering?

New theoretical perspectives on how engineers generate economic and social value have emerged from research on engineering practice, complementing the conventional entrepreneurship emphasis on innovation and start-up enterprises. This research demonstrated, apparently for the first time, how most engineers generate significant economic value with limited if any opportunities for innovation, research and development in their work. In the absence of appropriate theory, students acquire limited understanding on the contributions they will make to society as engineers. Observations from engineering practice provide a more compelling research-based narrative that could attract a more diverse student population, and help graduates secure well-paid employment. Many engineering faculty share uneasy feelings that their students will rarely use the advanced mathematical analysis techniques taught in classes. Research explains how practice solving traditional textbook problems builds tacit knowledge that enables rapid technical decision-making in engineering practice. The research also provides insights on how typical engineering science research supports engineering practice. We argue the benefits from widely disseminating the findings presented in this paper to help faculty staff and students better understand how they will contribute to our collective future. This can help overcome current significant engineering performance shortcomings in sustainability and productivity growth without major curriculum changes