Learning Heterogeneous Similarity Measures for Hybrid-Recommendations in Meta-Mining

The notion of meta-mining has appeared recently and extends the traditional meta-learning in two ways. First it does not learn meta-models that provide support only for the learning algorithm selection task but ones that support the whole data-mining process. In addition it abandons the so called black-box approach to algorithm description followed in meta-learning. Now in addition to the datasets, algorithms also have descriptors, workflows as well. For the latter two these descriptions are semantic, describing properties of the algorithms. With the availability of descriptors both for datasets and data mining workflows the traditional modelling techniques followed in meta-learning, typically based on classification and regression algorithms, are no longer appropriate. Instead we are faced with a problem the nature of which is much more similar to the problems that appear in recommendation systems. The most important meta-mining requirements are that suggestions should use only datasets and workflows descriptors and the cold-start problem, e.g. providing workflow suggestions for new datasets. In this paper we take a different view on the meta-mining modelling problem and treat it as a recommender problem. In order to account for the meta-mining specificities we derive a novel metric-based-learning recommender approach. Our method learns two homogeneous metrics, one in the dataset and one in the workflow space, and a heterogeneous one in the dataset-workflow space. All learned metrics reflect similarities established from the dataset-workflow preference matrix. We demonstrate our method on meta-mining over biological (microarray datasets) problems. The application of our method is not limited to the meta-mining problem, its formulations is general enough so that it can be applied on problems with similar requirements

New Trends, Resources, and Applications | The Future of Nebraska\u27s Data

Many Nebraska organizations are doing excellent work in the field of data visualization and improving access to data. This session will highlight some of this work, including portals and dashboards that present data quickly and easily. See live demonstrations of various useful products from: Nebraska Department of Labor, Omaha Community Foundation, Nebraska Children and Families Foundation, Nebraska Coordinating Commission for Postsecondary Education, and our own Center for Public Affairs Research

Mechanistic insights into the metabolization of S-Sulfocysteine by CHO cells using a multi-omics approach

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Automated Fourier space region-recognition filtering for off-axis digital holographic microscopy

Automated label-free quantitative imaging of biological samples can greatly benefit high throughput diseases diagnosis. Digital holographic microscopy (DHM) is a powerful quantitative label-free imaging tool that retrieves structural details of cellular samples non-invasively. In off-axis DHM, a proper spatial filtering window in Fourier space is crucial to the quality of reconstructed phase image. Here we describe a region-recognition approach that combines shape recognition with an iterative thresholding to extracts the optimal shape of frequency components. The region recognition technique offers fully automated adaptive filtering that can operate with a variety of samples and imaging conditions. When imaging through optically scattering biological hydrogel matrix, the technique surpasses previous histogram thresholding techniques without requiring any manual intervention. Finally, we automate the extraction of the statistical difference of optical height between malaria parasite infected and uninfected red blood cells. The method described here pave way to greater autonomy in automated DHM imaging for imaging live cell in thick cell cultures

Entrepreneurship and Innovation Program Annual Report 2014

The Entrepreneurship and Innovation Program at the University of Sydney Business School focuses on identifying, nurturing and strengthening entrepreneurial communities of learning and practice. This 2014 Annual Report sets out our teaching and research activities and achievements, and shows how our programs such as Remote and Rural Enterprise (RARE), Genesis, and Entrepreneurship Development Network Asia (EDNA) act as catalysts for community and action

Using a constructive feedback approach to effectively reduce student plagiarism among first-year psychology students

Plagiarism challenges the efficacy of current teaching methods to encourage students’ independent learning and critical thinking. In addition, existing evidence within the School of Psychology at the University of Sydney suggests that a purely deterrent approach to reducing student plagiarism (i.e., detection software) is relatively ineffective. These findings and an emerging literature led the School to develop and implement a constructive feedback approach. In the first semester 2008 teaching staff provided first year psychology students with one of three extracts from a journal article. Over 1,300 participants were asked to read an extract and construct an appropriate paragraph in relation to a focused research question. Responses on this question focused writing module were submitted via WebCT upon which students subsequently received constructive feedback. Responses were analysed for serious breaches using plagiarism detection software and were also assessed according to writing style, referencing and (in)appropriate use of quotations. The best and worst paragraphs were then selected and posted on WebCT, fully annotated with comments. In addition to this module students were provided with examples of what constitutes plagiarism, a demonstration of the frequency of plagiarism, the ease of plagiarism detection and the penalties for plagiarism. A few weeks following this exercise, students submitted their essays for graded assessment. An analysis of these essays revealed a significant fall in the number of ‘severe’ plagiarism cases between 2007 and 2008. It is anticipated that this constructive feedback approach will have flow-on effects of enhancing student’s independent learning, improving student’s scientific writing and increasing academic honesty throughout the tertiary education community

In vivo and in vitro studies of Cry5B and nicotinic acetylcholine receptor agonist anthelmintics reveal a powerful and unique combination therapy against intestinal nematode parasites

BACKGROUND: The soil-transmitted nematodes (STNs) or helminths (hookworms, whipworms, large roundworms) infect the intestines of ~1.5 billion of the poorest peoples and are leading causes of morbidity worldwide. Only one class of anthelmintic or anti-nematode drugs, the benzimidazoles, is currently used in mass drug administrations, which is a dangerous situation. New anti-nematode drugs are urgently needed. Bacillus thuringiensis crystal protein Cry5B is a powerful, promising new candidate. Drug combinations, when properly made, are ideal for treating infectious diseases. Although there are some clinical trials using drug combinations against STNs, little quantitative and systemic work has been performed to define the characteristics of these combinations in vivo. METHODOLOGY/PRINCIPAL FINDINGS: Working with the hookworm Ancylostoma ceylanicum-hamster infection system, we establish a laboratory paradigm for studying anti-nematode combinations in vivo using Cry5B and the nicotinic acetylcholine receptor (nAChR) agonists tribendimidine and pyrantel pamoate. We demonstrate that Cry5B strongly synergizes in vivo with both tribendimidine and pyrantel at specific dose ratios against hookworm infections. For example, whereas 1 mg/kg Cry5B and 1 mg/kg tribendimidine individually resulted in only a 0%-6% reduction in hookworm burdens, the combination of the two resulted in a 41% reduction (P = 0.020). Furthermore, when mixed at synergistic ratios, these combinations eradicate hookworm infections at doses where the individual doses do not. Using cyathostomin nematode parasites of horses, we find based on inhibitory concentration 50% values that a strongylid parasite population doubly resistant to nAChR agonists and benzimidazoles is more susceptible or hypersusceptible to Cry5B than a cyathostomin population not resistant to nAChR agonists, consistent with previous Caenhorhabditis elegans results. CONCLUSIONS/SIGNIFICANCE: Our study provides a powerful means by which anthelmintic combination therapies can be examined in vivo in the laboratory. In addition, we demonstrate that Cry5B and nAChR agonists have excellent combinatorial properties-Cry5B combined with nAChR agonists gives rise to potent cures that are predicted to be recalcitrant to the development of parasite resistance. These drug combinations highlight bright spots in new anthelmintic development for human and veterinary animal intestinal nematode infections