The electrokinetic behavior of calcium oxalate monohydrate in macromolecular solutions

Electrophoretic mobilities were measured for calcium oxalate monohydrate (COM) in solutions containing macromolecules. Two mucopolysaccharides (sodium heparin and chrondroitin sulfate) and two proteins (positively charged lysozyme and negatively charged bovine serum albumin) were studied as adsorbates. The effects of pH, calcium oxalate surface charge (varied by calcium or oxalate ion activity), and citrate concentration were investigated. All four macromolecules showed evidence for chemical adsorption. The macromolecule concentrations needed for reversing the surface charge indicated that the mucopopolysacchrides have greater affinity for the COM surface than the proteins. The amount of proteins that can chemically adsorb appears to be limited to approximately one monomolecular layer. When the surface charge is high, an insufficient number of proteins can chemically adsorb to neutralize or reverse the surface charge. The remaining surface charge is balanced by proteins held near the surface by longer range electrostatic forces only. Citrate ions at high concentrations appear to compete effectively with the negative protein for surface sites but show no evidence for competing with the positively charged protein

Bio-economic evaluation of pasture-cropping, a novel system of integrating perennial pastures and crops on crop-livestock farms

Pasture-cropping is a novel approach to increase the area of perennial crops in mixed sheep and cropping systems. It involves planting annual cereals directly into a living perennial pasture. There is interest in subtropical grasses as they are winter dormant and their growth profile is potentially well suited to pasture-cropping. However, a wide range of factors can affect the uptake of such systems. This paper assesses the relative importance of factors that can influence decisions to introduce pasture-cropping. In this paper the research question is: what factors predispose a farm to take up a new technology such as (1) subtropical grass and (2) subtropical grass that is pasture-cropped. The analysis uses the MIDAS model of a central wheatbelt farm in Western Australia. The results suggest the adoption of subtropical grasses is likely to be strongly influenced by soil mix; feed quality; and whether the farm is predominantly grazing or cropping and by the presence of meat versus wool producing animals. The same factors are relevant for subtropical grass that is pasture-cropped but in addition yield penalties due to competition between the host perennial and the companion cereal become important. The results suggest the level of forage production by subtropical grass is less important but this factor is likely to become more important if feed quality can be improved.Environmental Economics and Policy,

A new method for mapping perceptual biases across visual space

How we perceive the environment is not stable and seamless. Recent studies found that how a person qualitatively experiences even simple visual stimuli varies dramatically across different locations in the visual field. Here we use a method we developed recently that we call multiple alternatives perceptual search (MAPS) for efficiently mapping such perceptual biases across several locations. This procedure reliably quantifies the spatial pattern of perceptual biases and also of uncertainty and choice. We show that these measurements are strongly correlated with those from traditional psychophysical methods and that exogenous attention can skew biases without affecting overall task performance. Taken together, MAPS is an efficient method to measure how an individual's perceptual experience varies across space

Cost analysis of the CTLB Study, a multitherapy antenatal education programme to reduce routine interventions in labour

Objective: To assess whether the multitherapy antenatal education ‘CTLB’ (Complementary Therapies for Labour and Birth) Study programme leads to net cost savings. Design: Cost analysis of the CTLB Study, using analysis of outcomes and hospital funding data. Methods: We take a payer perspective and use Australian Refined Diagnosis-Related Group (AR-DRG) cost data to estimate the potential savings per woman to the payer (government or private insurer). We consider scenarios in which the intervention cost is either borne by the woman or by the payer. Savings are computed as the difference in total cost between the control group and the study group. Results: If the cost of the intervention is not borne by the payer, the average saving to the payer was calculated to be $A808 per woman. If the payer covers the cost of the programme, this figure reduces to$A659 since the average cost of delivering the programme was $A149 per woman. All these findings are significant at the 95Conclusion: The CTLB antenatal education programme leads to significant savings to payers that come from reduced use of hospital resources. Depending on which perspective is considered, and who is responsible for covering the cost of the programme, the net savings vary from$A659 to $A808 per woman. Compared with the average cost of birth in the control group, we conclude that the programme could lead to a reduction in birth-related healthcare costs of approximately 9%. Trial registration number: ACTRN12611001126909

ProppML: A Complete Annotation Scheme for Proppian Morphologies

We give a preliminary description of ProppML, an annotation scheme designed to capture all the components of a Proppian-style morphological analysis of narratives. This work represents the first fully complete annotation scheme for Proppian morphologies, going beyond previous annotation schemes such as PftML, ProppOnto, Bod et al., and our own prior work. Using ProppML we have annotated Propp\u27s morphology on fifteen tales (18,862 words) drawn from his original corpus of Russian folktales. This is a significantly larger set of data than annotated in previous studies. This pilot corpus was constructed via double annotation by two highly trained annotators, whose annotations were then combined after discussion with a third highly trained adjudicator, resulting in gold standard data which is appropriate for training machine learning algorithms. Agreement measures calculated between both annotators show very good agreement (F_1>0.75, kappa>0.9 for functions; F_1>0.6 for moves; and F_1>0.8, kappa>0.6 for dramatis personae). This is the first robust demonstration of reliable annotation of Propp\u27s system

Learning a Better Motif Index: Toward Automated Motif Extraction

Motifs are distinctive recurring elements found in folklore, and are used by folklorists to categorize and find tales across cultures and track the genetic relationships of tales over time. Motifs have significance beyond folklore as communicative devices found in news, literature, press releases, and propaganda that concisely imply a large constellation of culturally-relevant information. Until now, folklorists have only extracted motifs from narratives manually, and the conceptual structure of motifs has not been formally laid out. In this short paper we propose that it is possible to automate the extraction of both existing and new motifs from narratives using supervised learning techniques and thereby possible to learn a computational model of how folklorists determine motifs. Automatic extraction would enable the construction of a truly comprehensive motif index, which does not yet exist, as well as the automatic detection of motifs in cultural materials, opening up a new world of narrative information for analysis by anyone interested in narrative and culture. We outline an experimental design, and report on our efforts to produce a structured form of Thompson\u27s motif index, as well as a development annotation of motifs in a small collection of Russian folklore. We propose several initial computational, supervised approaches, and describe several possible metrics of success. We describe lessons learned and difficulties encountered so far, and outline our plan going forward

Achieving best for project success outcomes through optimal employee engagement – a proposal for organisations operating engineering alliances

Employee engagement has continued to develop as an area of both academic and business interest but there remains paucity in literature that links employee engagement to engineering alliances and concomitant achievement of project success. This research examines current theoretical concepts and praxis contributions of institutions that represent industry. This research is contextualised within the engineering sector and does not specifically address other sectors such as, for example, healthcare, and public sectors. The research outlines key components of an employee engagement model within an engineering alliance and does not critically focus attention on conceptual notions of employee engagement not their utility. The research has novelty in that, to our knowledge, it is original in defining employee engagement in an engineering alliance. It addresses the knowledge gap in this area and makes a contribution to academic discourse pertaining to employee engagement as a developing approach to managing projects

Computational Models of Narrative: Review of a Workshop

On October 8-10, 2009 an interdisciplinary group met at the Wylie Center in Beverley, Massachusetts to evaluate the state of the art in the computational modeling of narrative. Three important findings emerged: (1) current work in computational modeling is described by three different levels of representation; (2) there is a paucity of studies at the highest, most abstract level aimed at inferring the meaning or message of the narrative; and (3) there is a need to establish a standard data bank of annotated narratives, analogous to the Penn Treebank