The CFHTLS Deep Catalog of Interacting Galaxies I. Merger Rate Evolution to z=1.2

We present the rest-frame optical galaxy merger fraction between 0.2<z<1.2, as a function of stellar mass and optical luminosity, as observed by the Canada-France-Hawaii Telescope Legacy Deep Survey (CFHTLS-Deep). We developed a new classification scheme to identify major galaxy-galaxy mergers based on the presence of tidal tails and bridges. These morphological features are signposts of recent and ongoing merger activity. Through the visual classification of all galaxies, down to i_vega<22.2 (~27,000 galaxies) over 2 square degrees, we have compiled the CFHTLS Deep Catalog of Interacting Galaxies, with ~1600 merging galaxies. We find the merger fraction to be 4.3% +/-0.3% at z~0.3 and 19.0% +/-2.5% at z~1, implying evolution of the merger fraction going as (1+z)^m, with m=2.25 +/-0.24. This result is inconsistent with a mild or non-evolving (m4sigma level of confidence. A mild trend, where massive galaxies with M>10^10.7 M_sun are undergoing fewer mergers than less massive systems M~10^10 M_sun), consistent with the expectations of galaxy assembly downsizing is observed. Our results also show that interacting galaxies have on average SFRs double that found in non-interacting field galaxies. We conclude that (1) the optical galaxy merger fraction does evolve with redshift, (2) the merger fraction depends mildly on stellar mass, with lower mass galaxies having higher merger fractions at z<1, and (3) star formation is triggered at all phases of a merger, with larger enhancements at later stages, consistent with N-body simulations.Comment: e.g.: 17 pages, 14 figures, accepted for publication in Ap

The nature of assignment and non-assignment clauses

The purpose of this article is to examine the nature of assignment as it relates to contractual debts and contractual rights in general, before addressing problems presented by non-assignment clauses.1 The assignment of things in action sits precariously between contract law and property law and non-assignment clauses cannot properly be understood without an appreciation of this hybrid character of assignment.2 Non-assignment clauses pose the question whether and in what circumstances contractual rights are items of property. They also demand an examination of the doctrine of privity of contract and a response to the question whether one contracting party has the right unilaterally to vary the contract. Finally, non-assignment clauses set two primary values at odds with each other, namely freedom of contract and the free alienation of items of property. To a significant extent, the practical problems presented by non-assignment clauses will diminish when expected secondary legislation nullifying non-assignment clauses in the field of receivables (or book debts) comes into force,3 but some of the leading cases do not involve receivables and the subject therefore continues to merit attention for practical as well as for theoretical reasons

Improved recommendation of photo-taking locations using virtual ratings

We consider the task of collaborative recommendation of photo-taking locations. We use datasets of geotagged photos. We map their locations to a location grid using a geohashing algorithm, resulting in a user x location implicit feedback matrix. Our improvements relative to previous work are twofold. First, we create virtual ratings by spreading users' preferences to neighbouring grid locations. This makes the assumption that users have some preference for locations close to the ones in which they take their photos. These virtual ratings help overcome the discrete nature of the geohashing. Second, we normalize the implicit frequency-based ratings to a 1-5 scale using a method that has been found to be useful in music recommendation algorithms. We demonstrate the advantages of our approach with new experiments that show large increases in hit rate and related metrics

A comparison of calibrated and intent-aware recommendations

Calibrated and intent-aware recommendation are recent approaches to recommendation that have apparent similarities. Both try, to a certain extent, to cover the user's interests, as revealed by her user profile. In this paper, we compare them in detail. On two datasets, we show the extent to which intent-aware recommendations are calibrated and the extent to which calibrated recommendations are diverse. We consider two ways of defining a user's interests, one based on item features, the other based on subprofiles of the user's profile. We find that defining interests in terms of subprofiles results in highest precision and the best relevance/diversity trade-off. Along the way, we define a new version of calibrated recommendation and three new evaluation metrics

Following basal stem rot in young oil palm plantings

The PCR primer GanET has previously been shown to be suitable for the specific amplification of DNA from Ganoderma boninense. A DNA extraction and PCR method has been developed that allows for the amplification of the G. boninense DNA from environmental samples of oil palm tissue. The GanET primer reaction was used in conjunction with a palm-sampling programme to investigate the possible infection of young palms through cut frond base surfaces. Ganoderma DNA was detected in frond base material at a greater frequency than would be expected by comparison with current infection levels. Comparisons are made between the height of the frond base infected, the number of frond bases infected, and subsequent development of basal stem rot. The preliminary results suggest that the development of basal stem rot may be more likely to occur when young lower frond bases are infected

Harvesting Lithium: water, brine and the industrial dynamics of production in the Salar de Atacama

Geographical research on lithium and other renewable energy materials explores the geopolitical dimensions of resource supply and the 'new geographies' associated with an expanding resource frontier. The material characteristics and environmental conditions of lithium production, however, are largely overlooked in this perspective. In the context of a global speculative boom for lithium linked to its growing role in energy storage, this paper adopts a grounded, exploratory approach to investigate the dynamics of production and resource management at one of the world's most significant sources of lithium: the brine deposits of the Atacama Salt Flat/Salar de Atacama in northern Chile. We show how lithium production from brine has a distinctive 'eco-regulatory' character as it involves managing a series of hydrogeological conditions and physical processes that are largely external to capital. The paper highlights the infrastructures (pumps, pipes, ponds) associated with the harvesting of lithium from brine and examines how production on the salar generates a series of ecological contradictions (notably around water depletion) with potential to disrupt accumulation. We also examine the multiple flexibilities afforded by the eco- regulatory character of production, and show how these enable lithium producers to adapt fixed infrastructures to dynamic political economic conditions. By focusing on both contradictions and flexibilities of lithium production, the paper draws attention to trajectories of capitalisation in the lithium value chain and their environmental consequences; and considers the political-economic incentives shaping further capitalisation. The paper concludes by considering the implications of this exploratory case study for critical resource geography

An exploration of the portrayal of the UK soft drinks industry levy in UK national newspapers.

OBJECTIVE: News media play a role in politics through the portrayal of policies, influencing public and policymaker perceptions of appropriate solutions. This study explored the portrayal of sugar and sugar-sweetened beverage (SSB) taxes in UK national newspapers. Findings aid understanding of the role newspapers play in shaping understanding and acceptance of policies such as the UK Soft Drink Industry Levy (SDIL). DESIGN: Articles discussing sugar or SSB taxes published in six UK national newspapers between 1 April 2016 and 1 May 2019 were retrieved from the LexisNexis database. Articles were thematically analysed to reveal policy portrayal. SETTING/PARTICIPANTS: Analysis of UK newspaper articles. RESULTS: Two hundred and eighty-six articles were assessed. Sugar and SSB taxes were discussed across the sample period but publication peaked at SDIL announcement and introduction. Themes were split according to support for or opposition to taxation. Supportive messaging consistently highlighted the negative impacts of sugar on health and the need for complex actions to reduce sugar consumption. Opposing messages emphasised individual responsibility for health and the unfairness of taxation both for organisations and the public. CONCLUSIONS: Sugar and SSB taxes received considerable media attention between 2016 and 2019. All newspapers covered arguments in support of and opposition to taxation. Health impacts of excess sugar and the role of the soft drink industry in reducing sugar consumption were prevalent themes, suggesting a joined-up health advocacy approach. Industry arguments were more varied, suggesting a less collaborative argument. Further research should investigate how other media channels portray taxes such as the SDIL

Towards Question-based Recommender Systems

Conversational and question-based recommender systems have gained increasing attention in recent years, with users enabled to converse with the system and better control recommendations. Nevertheless, research in the field is still limited, compared to traditional recommender systems. In this work, we propose a novel Question-based recommendation method, Qrec, to assist users to find items interactively, by answering automatically constructed and algorithmically chosen questions. Previous conversational recommender systems ask users to express their preferences over items or item facets. Our model, instead, asks users to express their preferences over descriptive item features. The model is first trained offline by a novel matrix factorization algorithm, and then iteratively updates the user and item latent factors online by a closed-form solution based on the user answers. Meanwhile, our model infers the underlying user belief and preferences over items to learn an optimal question-asking strategy by using Generalized Binary Search, so as to ask a sequence of questions to the user. Our experimental results demonstrate that our proposed matrix factorization model outperforms the traditional Probabilistic Matrix Factorization model. Further, our proposed Qrec model can greatly improve the performance of state-of-the-art baselines, and it is also effective in the case of cold-start user and item recommendations.Comment: accepted by SIGIR 202