Distance learning, OER, and MOOCs: some UK experiences

This paper discusses learning at scale from the perspective of two UK Universities engaging in technology enhanced learning. Three case studies are used to illustrate ways in which scale has been achieved. There is diversity in how scale is supported but also common factors. Openness and choice appear as enablers in all cases

Beyond the Standard Model Higgs Boson Searches at the Tevatron

Results are presented for beyond the Standard Model Higgs boson searches using up to 4.2 fb-1 of data from Run II at the Tevatron. No significant excess is observed in any of the channels so 95% confidence level limits are presented.Comment: Proceedings for Hadron Collider Physics 2010 conference (7 pages, 8 figures

Boosted Higgs →bbˉ\rightarrow b\bar{b} in vector-boson associated production at 14 TeV

The production of the Standard Model Higgs boson in association with a vector boson, followed by the dominant decay to $H \rightarrow b\bar{b}$, is a strong prospect for confirming and measuring the coupling to $b$-quarks in $pp$ collisions at $\sqrt{s}=14$ TeV. We present an updated study of the prospects for this analysis, focussing on the most sensitive highly Lorentz-boosted region. The evolution of the efficiency and composition of the signal and main background processes as a function of the transverse momentum of the vector boson are studied covering the region $200-1000$ GeV, comparing both a conventional dijet and jet substructure selection. The lower transverse momentum region ($200-400$ GeV) is identified as the most sensitive region for the Standard Model search, with higher transverse momentum regions not improving the statistical sensitivity. For much of the studied region ($200-600$ GeV), a conventional dijet selection performs as well as the substructure approach, while for the highest transverse momentum regions ($> 600$ GeV), which are particularly interesting for Beyond the Standard Model and high luminosity measurements, the jet substructure techniques are essential.Comment: 13 pages.(Fixed figure layout error

Rain, rain, gone away. Decreased growing season rainfall for the dryland cropping region of south-western Australia

The shift in Indian Ocean sea surface temperatures in 1976 led to a change in rainfall for the broad-scale winter annual grain cropping and pasture region in the south-west of Western Australia (the WA wheatbelt). Agriculture in the eastern part the WA Wheatbelt was particularly sensitive to the change in rainfall because it is a marginal area for agronomic production, with low rainfall before changes in sea surface temperature. A second shift in sea surface temperature occurred in 2000, but there has been no analysis of the resulting impact on rainfall in the eastern WA wheatbelt. An analysis of rainfall pre- and post-2000 was performed for sites in the eastern WA wheatbelt in three groups: 19 sites in the west, 56 central, and 10 east. The analysis found a decline in growing-season rainfall (i.e. April–October), especially during May–July, post- 2000. Rainfall declines of 49.9mm(west group), 39.1mm(central group) and 28.0mm(east group) represented respective losses of 20.1%, 17.4% and 14.2% of growing-season rainfall. Increases in out-of-season rainfall in the respective groups of 31.0, 33.6, and 50.7 mm (57.8%, 60.8% and 87.6%) meant that annual rainfall changes were smaller than growing-season losses. The west and central groups lost 17.5 and 6.16 mm annual rainfall, whereas the east group gained 15.6 mm. Analysis of wheat yield indicated reductions of 13.5% (west) and 9.90% (central) in the eastern WA wheatbelt; the small group of east sites had a potential yield gain of 8.9% arising from the increased out-of-season rainfall. Further, increased out of- season rainfall will exacerbate weed and disease growth over the summer fallow

B-tagging and the search for neutral supersymmetric Higgs bosons at D0

A search for neutral supersymmetric Higgs bosons and work relating to the improvement of the b-tagging and trigger capabilities at the D0 detector during Run II of the Fermilab Tevatron collider is presented. The search for evidence of the Higgs sector in the Standard Model (SM) and supersymmetric extensions of the SM are a high priority for the D0 collaboration, and b-tagging and good triggers are a vital component of these searches. The development and commissioning of the first triggers at D0 which use b-tagging is outlined, along with the development of a new secondary vertex b-tagging tool for use in the Level 3 trigger. Upgrades to the Level 3 trigger hit finding code, which have led to significant improvements in the quality and efficiency of the tracking code, and by extension the b-tagging tools, are also presented. An offline Neural Network (NN) b-tagging tool was developed, trained on Monte Carlo and extensively tested and measured on data. The new b-tagging tool significantly improves the b-tagging performance at D0, for a fixed fake rate relative improvements in signal efficiency range from {approx} 40% to {approx} 15%. Fake rates, for a fixed signal efficiency, are typically reduced to between a quarter and a third of their value. Finally, three versions of the search for neutral supersymmetric Higgs bosons are presented. The latest version of the analysis makes use of almost 1 fb{sup -1} of data, the new NN b-tagger and the new b-tagging triggers, and has set one of the world's best limits on the supersymmetric parameter tan{beta} in the mass range 90 to 150 GeV

Primary Industries Development Research Highlights 2021

The Primary Industries Development Research Highlights 2021 showcases the breadth and depth of the Department of Primary Industries and Regional Development’s research and development activities over the past several years. Stories featured in Research Highlights 2021 stem from about 60 (of 140) current and recently-completed projects undertaken by the Department of Primary Industries and Regional Development’s (DPIRD) 1100 scientists, technical experts and economists throughout the State. Explore our Research Highlights 2021. The publication demonstrates the innovative and applicable research that DPIRD and its collaborators and investment partners deliver to Western Australia. Download the Research Highlights 2021 here. Alternatively, a copy is available from DPIRD offices on request.https://researchlibrary.agric.wa.gov.au/books/1021/thumbnail.jp

Accessible Inclusive Learning: Futures

The last chapter outlined some key approaches and challenges that we have seen when conducting research that seeks to make learning accessible to all. Here, we explore newer trends that are directing our current research and practice in this area. These promising directions include devising models for global networks, the potential to collect and use data to understand learning experiences in new ways, and new opportunities arising through artificial intelligence. By exploring current and recent projects around these areas, we also highlight some emerging tensions. Finally, we return to thinking about how we conduct research, considering how concepts of bricolage and guerrilla research can be an important part of our palette of approaches

Accessible Inclusive Learning: Foundations

One of the most persistent themes in discussions around technology in education is the idea that technology can affect access to learning. This can be seen as positive or negative, and it is often more complex than it seems. If computers can convert the text in a web page into spoken word, or the spoken words on a video into captions, have we made the learning accessible to deaf or blind students? Most likely we have made an important step in the right direction, but this might be only one challenge in the wider pedagogy and student experience. If MOOCs can teach thousands for free without any cost or entry requirements, does that mean they are increasing access? Perhaps, but are they also creating barriers for some through the pedagogical and technical design? In this chapter we will unpack how these issues have been tackled through research

2010 Northwest Federal Market Assessment Report

The primary intent of this market assessment is to provide insights on the effectiveness of current energy efficiency and renewable energy program offerings available to Federal sites in the region. The level of detail, quality and currency of the data used in this market assessment varies significantly by Federal agency and energy efficiency service provider. Limited access to some Federal sites, limited availability of key points of contact, time/resource constraints, and other considerations limited the total number of Federal agencies and energy efficiency service providers participating in the survey

Reconstructing charged particle track segments with a quantum-enhanced support vector machine

Reconstructing the trajectories of charged particles from the collection of hits they leave in the detectors of collider experiments like those at the Large Hadron Collider (LHC) is a challenging combinatorics problem and computationally intensive. The tenfold increase in the delivered luminosity at the upgraded High Luminosity LHC will result in a very densely populated detector environment. The time taken by conventional techniques for reconstructing particle tracks scales worse than quadratically with track density. Accurately and efficiently assigning the collection of hits left in the tracking detector to the correct particle will be a computational bottleneck and has motivated studying possible alternative approaches. This paper presents a quantum-enhanced machine learning algorithm that uses a support vector machine (SVM) with a quantum-estimated kernel to classify a set of three hits (triplets) as either belonging to or not belonging to the same particle track. The performance of the algorithm is then compared to a fully classical SVM. The quantum algorithm shows an improvement in accuracy versus the classical algorithm. Model complexity metrics are used to hint at an explanation for favorable performance of the quantum kernel