Taking Stock: Seventeen Years after the Murray-Darling Basin Agreement

There has now been almost two decades of natural resource management by signatory states under the Murray-Darling Basin Agreement Despite significant public expense, the success of initiatives to improve the Basin’s environmental remains ambiguous. This confusion is partly due to poorly distinguished investment outcomes, a blurring of the transparency of public spending and a lack of accountability of decision makers. The aim of this study is to demonstrate that significant environmental improvements could have been achieved at a much lower cost if decisive action been taken early. The research report outlines the myriad of Murray-Darling Basin related policies and its funding. It also notes the achievements and impediments to program success.water reform, water policy, cost efficiency, Murray-Darling Basin, Community/Rural/Urban Development, Environmental Economics and Policy, Land Economics/Use,

Study of RNA Secondary Structure Prediction Algorithms

Dynamic programming algorithms such as Nussinov algorithm and Zuker algorithm define criteria to search the most stable RNA secondary structures. Stochastic Context-Free Grammar (SCFG) predicts the most possible RNA secondary structure using context-free grammar and a defined set of probabilities for each grammar rule. These algorithms form the base of using computer programs to predict RNA secondary structures without pseudoknots. In this report, we review these RNA secondary structure prediction algorithms and present our own software implementations of these algorithms. The Nussinov algorithm is easy to understand. But our results show that the Nussinov algorithm is overly simplified and can not produce the most accurate result. The SCFG algorithm may be powerful. But its result is also inaccurate because there are no accurate probabilities for each corresponding grammar rule. The Zuker’s minimum free energy method incorporated far more biological knowledge in its energy definitions. Thus, its predictions are much better than the other two algorithms. Our implementations use both recursive and non-recursive function calls. Recursion is easy to understand, but recursion introduces significant overhead. We are able to rearrange the function calls to effectively stop the recursion. The non-recursion feature allows us to parallelize the most computing intensive part of the calculation. By abstracting a secondary structure to a tree representation and a string representation, we compared our prediction results with the results from experiment measurement or non-conventional general purpose computational methods, and results from popular package such as MFOLD. Our results also illustrate the limitation of these algorithms. The limitations clearly demonstrate that more biological and chemical knowledge of RNA need to be incorporated into the RNA secondary structure prediction algorithms

An empirical study of multidimensional fidelity of COMPASS consultation

Consultation is essential to the daily practice of school psychologists (National Association of School Psychologist, 2010). Successful consultation requires fidelity at both the consultant (implementation) and consultee (intervention) levels. We applied a multidimensional, multilevel conception of fidelity (Dunst, Trivette, & Raab, 2013) to a consultative intervention called the Collaborative Model for Promoting Competence and Success (COMPASS) for students with autism. The study provided 3 main findings. First, multidimensional, multilevel fidelity is a stable construct and increases over time with consultation support. Second, mediation analyses revealed that implementation-level fidelity components had distant, indirect effects on student Individualized Education Program (IEP) outcomes. Third, 3 fidelity components correlated with IEP outcomes: teacher coaching responsiveness at the implementation level, and teacher quality of delivery and student responsiveness at the intervention levels. Implications and future directions are discussed. (PsycINFO Database Record

Online Matrix Completion with Side Information

This thesis considers the problem of binary matrix completion with side information in the online setting and the applications thereof. The side information provides additional information on the rows and columns and can yield improved results compared to when such information is not available. We present efficient and general algorithms in transductive and inductive models. The performance guarantees that we prove are with respect to the matrix complexity measures of the max-norm and the margin complexity. We apply our bounds to the hypothesis class of biclustered matrices. Such matrices can be permuted through the rows and columns into homogeneous latent blocks. This class is a natural choice for our problem since the margin complexity and max-norm of these matrices have an upper bound that is easy to interpret in terms of the latent dimensions. We also apply our algorithms to a novel online multitask setting with RKHS hypothesis classes. In this setting, each task is partitioned in a sequence of segments, where a hypothesis is associated with each segment. Our algorithms are designed to exploit the scenario where the number of associated hypotheses is much smaller than the number of segments. We prove performance guarantees that hold for any segmentation of the tasks and any association of hypotheses to the segments. In the single-task setting, this is analogous to switching with long-term memory in the sense of [Bousquet and Warmuth; 2003]

EFFICIENT WATER ALLOCATION IN A HETEROGENEOUS CATCHMENT SETTING

The problem of water scarcity has become one of the most controversial topics in Australia over the past decades, with particular focus being the ‘sustainable’ allocation of water between extractive and environmental purposes. Geographical factors are defining the extreme variability in climate and water supply in Australia and, in the past, this was used as a rationale for the construction of large irrigation projects to deliver water to rural, urban, and industrial users. During this ‘expansionary’ phase of Australia’s water use sector, the cost of augmenting supply was relatively low and environmental considerations were secondary to the development imperative. As a result, water resources became over-allocated for extractive uses spurred on by consistent underpricing of water, which indicated a failure to reflect the true cost of water supply. As Australia’s water economy entered a ‘mature’ phase, it was no longer possible to increase supply cheaply as the most easily accessible water resources had already been captured. This was followed by widespread environmental degradation manifested in the Murray- Darling Basin, the nation’s largest river basin which hosts much of Australia’s agricultural production. Consequently, the focus shifted towards demand management, leading to a myriad of regulation aimed at increasing the allocative efficiency of scarce water resources. Towards this end, substantial government funding was injected into the various initiatives throughout the water reform process. Despite the on-going government activities in the area of water reform, the understanding of the actual economic impact and environmental outcomes of various water policies in practice remains limited. In the absence of such understanding, the effectiveness of various government water initiatives is ambiguous and inevitably compromised. The present study addresses this knowledge gap by establishing a method for evaluating the economic and environmental outcomes of environmentally-oriented polices that affect irrigated industries in a catchment. The method is based on an integrated biophysical and economic modelling approach, which enables spatial relationships to be captured accurately allowing a more realistic analysis. Information generated from a computer based biophysical simulation model form the basis of an economic optimisation model with constraints pertaining to environmental targets and water supply limits. The economic model consists of a linear programming and dynamic programming component, and involves the optimisation of resource use from a catchment manager’s perspective, seeking to achieve efficient resource use but at the same time conform to given environmental objectives. This embedded linear and dynamic programming approach was required to determine the optimal intra-seasonal and inter-seasonal water allocation, given various catchment environmental targets. The interdisciplinary approach enables the economic and ecological outcomes of the catchment management policies to be simulated and assessed at a spatially explicit scale, due to the link to Geographical Information Systems (GIS) in the biophysical model. The overall objective was to create a decision-making framework that could be used to determine the least-cost means of meeting environmental targets and resource constraints. The solutions to the analysis are directly applicable to the case study, the Mooki catchment in northern New South Wales (NSW), but with an adaptable framework that can be applied to other catchments. Specific objectives include an evaluation of the possibility of using alternative irrigation systems, as well as an evaluation of the benefits that can be realised by establishing water market, in the light of environmentally-oriented catchment policies for the case study. The economic cost of achieving environmental targets pertaining to environmental flow requirements and salinity reduction, in the form of end-of-valley salinity targets, was explicitly calculated through the economic model. While salinity targets have been set for NSW catchments, the practicality of such targets is in question, given the substantial reductions in water allocation to irrigation activities, which is one of the key contributors to deep-drainage. An additional objective in this study was therefore to investigate the value of having deep drainage targets. A further consideration is the effect of “external agents” in the form of government plans to buyback entitlements from irrigation districts, or the possibility of significant water rights purchases from mining industries. The implications of external water market entrants on the regional agricultural industry were examined

Empowering Educators with Google\u27s Android App Inventor: An Online Workshop in Mobile App Design

In this report, the authors describe an introductory-level mobile app design workshop developed and offered over six weeks in Summer 2011. We also discuss the challenges and instructional implications derived from our experiences with this workshop

How does this make you feel? A comparison of four affect induction procedures

Affect is a fundamental aspect of the human mind. An increasing number of experiments attempt to examine the influence of affect on other psychological phenomena. To accomplish this research, it is necessary to experimentally modify participants' affective states. In the present experiment, we compared the efficacy of four commonly used affect induction procedures. Participants (38 healthy undergraduate students: 18 males) were randomly assigned to either a pleasant or an unpleasant affect induction group, and then underwent four different affect induction procedures: (1) recall of an affectively salient event accompanied by affectively congruent music, (2) script-driven guided imagery, (3) viewing images while listening to affectively congruent music, and (4) posing affective facial actions, body postures, and vocal expressions. All four affect induction methods were successful in inducing both pleasant and unpleasant affective states. The viewing image with music and recall with music procedures were most effective in enhancing positive affect, whereas the viewing image with music procedure was most effective in enhancing negative affect. Implications for the scientific study of affect are discussed