Short-term temporal changes of soil carbon losses after tillage described by a first-order decay model

Tillage stimulates soil carbon (C) losses by increasing aeration, changing temperature and moisture conditions, and thus favoring microbial decomposition. In addition, soil aggregate disruption by tillage exposes once protected organic matter to decomposition. We propose a model to explain carbon dioxide (CO2) emission after tillage as a function of the no-till emission plus a correction due to the tillage disturbance. The model assumes that C in the readily decomposable organic matter follows a first-order reaction kinetics equation as: dC(sail)(t)/dt = -kC(soil)(t) and that soil C-CO2 emission is proportional to the C decay rate in soil, where C-soil(t) is the available labile soil C (g m(-2)) at any time (t). Emissions are modeled in terms soil C available to decomposition in the tilled and non-tilled plots, and a relationship is derived between no-till (F-NT) and tilled (F-Gamma) fluxes, which is: F-T = a1F(NT)e(-a2t), where t is time after tillage. Predicted and observed fluxes showed good agreement based on determination coefficient (R-2), index of agreement and model efficiency, with R-2 as high as 0.97. The two parameters included in the model are related to the difference between the decay constant (k factor) of tilled and no-till plots (a(2)) and also to the amount of labile carbon added to the readily decomposable soil organic matter due to tillage (a,). These two parameters were estimated in the model ranging from 1.27 and 2.60 (a(1)) and - 1.52 x 10(-2) and 2.2 x 10(-2) day(-1) (a(2)). The advantage is that temporal variability of tillage-induced emissions can be described by only one analytical function that includes the no-till emission plus an exponential term modulated by tillage and environmentally dependent parameters. (C) 2008 Elsevier B.V. All rights reserved.

The primary sources of carbon loss during the crop-establishment period in a subtropical Oxisol under contrasting tillage systems

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

The user-led disruption : self-(re)broadcasting at Justin.tv and elsewhere

The rise of videosharing and self-(re)broadcasting Web services is posing new threats to a television industry already struggling with the impact of filesharing networks. This paper outlines these threats, focussing especially on the DIY re-broadcasting of live sports using Websites such as Justin.tv and a range of streaming media networks built on peer-to-peer filesharing technology.

Identifying aggregate demand and supply shocks in a small open economy

The standard Blanchard-Quah (BQ) decomposition forces aggregate demand and supply shocks to be orthogonal. However, this assumption is problematic for a nation with an inflation target. The very notion of inflation targeting means that monetary policy reacts to changes in aggregate supply. This paper employs a modification of the BQ procedure that allows for correlated shifts in aggregate supply and demand. It is found that shocks to Australian aggregate demand and supply are highly correlated. The estimated shifts in the aggregate demand and supply curves are then used to measure the effects of inflation targeting on the Australian inflation rate and level of GDP.

Disruption of androgen regulation in the prostate by the environmental contaminant hexachlorobenzene

Hexachlorobenzene (HCB) is a persistent environmental contaminant that has the potential to interfere with steroid hormone regulation. The prostate requires precise control by androgens to regulate its growth and function. To determine if HCB impacts androgen action in the prostate, we used a number of methods. Our in vitro cell-culture-based assay used a firefly luciferase reporter gene driven by an androgen-responsive promoter. In the presence of dihydrotestosterone, low concentrations (0.5-5 nM) of HCB increased the androgen-responsive production of firefly luciferase and high concentrations of HCB (> 10 microM) suppressed this transcriptional activity. Results from a binding assay showed no evidence of affinity between HCB and the androgen receptor. We also tested HCB for in vivo effects using transgenic mice in which the transgene was a prostate-specific, androgen-responsive promoter upstream of a chloramphenicol acetyl transferase (CAT) reporter gene. In 4-week-old mice, the proportion of dilated prostate acini, a marker of sexual maturity, increased in the low HCB dose group and decreased in the high HCB dose mice. In the 8-week-old mice, there was a significant decrease in both CAT activity and prostate weight upon exposure to 20 mg/kg/day HCB. Therefore, in vitro and in vivo data suggest that HCB weakly agonizes androgen action, and consequently, low levels of HCB enhanced androgen action but high levels of HCB interfered. Environmental contaminants have been implicated in the rising incidence of prostate cancer, and insight into the mechanisms of endocrine disruption will help to clarify their role.

Participatory design for technological disruption within the agricultural sector

Agricultural adoption of innovation has traditionally been described as slow to diffuse. This paper therefore describes a case study grounded in PD to address a disruptive technology/system within the livestock industry. Results of the process were positive, as active engagement of stakeholders returned rich data. The contribution of the work is also presented as grounds for further design research in the livestock industry.

Social Impact of Mining Survey : Aggregate Results Queensland Communities

This is the final report from a study into the social impact of mining in Queensland.

Designing disruption : linking participatory design and design thinking in technology orientated industries

A vast proportion of companies nowadays are looking to design and are focusing on the end users as a means of driving new projects. However still many companies are drawn to technological improvements which drive innovation within their industry context. The Australian livestock industry is no different. To date the adoption of new products and services within the livestock industry has been documented as being quite slow. This paper investigates how disruptive innovation should be a priority for these technologically focused companies and demonstrates how the use of design led innovation can bring about a higher quality engagement between end user and company alike. A case study linking participatory design and design thinking is presented. Within this, a conceptual model of presenting future scenarios to internal and external stakeholders is applied to the livestock industry; assisting companies to apply strategy, culture and advancement in meaningful product offerings to consumers.

‘Moments of disruption’ and the development of expatriate TESOL teachers

TESOL teachers, like mainstream teachers, often experience key incidents in their professional development. In expatriate TESOL however, unfamiliar cultural and linguistic contexts may disrupt teachers’ sense of both professional and personal identity. In this paper, narratives constructed from interviews of teacher experiences document a selection of critical events and discuss their implications for professional development in TESOL. Teachers reported that deep reflection on their experiences led to a re-conceptualisation of their professional and cultural identities. The analysis of their reflections may have significant implications for TESOL work in the context of the global and the local.

Aggregate distance based clustering using Fibonacci Series -FIBCLUS

This paper proposes an innovative instance similarity based evaluation metric that reduces the search map for clustering to be performed. An aggregate global score is calculated for each instance using the novel idea of Fibonacci series. The use of Fibonacci numbers is able to separate the instances effectively and, in hence, the intra-cluster similarity is increased and the inter-cluster similarity is decreased during clustering. The proposed FIBCLUS algorithm is able to handle datasets with numerical, categorical and a mix of both types of attributes. Results obtained with FIBCLUS are compared with the results of existing algorithms such as k-means, x-means expected maximization and hierarchical algorithms that are widely used to cluster numeric, categorical and mix data types. Empirical analysis shows that FIBCLUS is able to produce better clustering solutions in terms of entropy, purity and F-score in comparison to the above described existing algorithms.