Sustainable deathstyles? The geography of green burials in Britain

In the context of a wider literature on ‘deathscapes’, we map the emergence of a new mode of burial and remembrance in Britain. Since a ‘green’ burial ground was established in Carlisle in 1993, sites for so-called ‘green, ‘natural’ or ‘woodland’ funerals have proliferated. There are now over 270 such sites in Britain. Drawing on a postal and email survey sent to all managers/owners and visits to 15 green burial grounds (enabling observations and semi-structured interviews with their managers), we chart their growth, establishment and regulation and describe the landscapes associated with them. This requires, and leads to, wider reflections on nature, capital, consumption, culture and the body

The "Coulomb phase" in frustrated systems

The "Coulomb phase" is an emergent state for lattice models (particularly highly frustrated antiferromagnets) which have local constraints that can be mapped to a divergence-free "flux". The coarse-grained version of this flux or polarization behave analogously to electric or magnetic fields; in particular, defects at which the local constraint is violated behave as effective charges with Coulomb interactions. I survey the derivation of the characteristic power-law correlation functions and the pinch-points in reciprocal space plots of diffuse scattering, as well as applications to magnetic relaxation, quantum-mechanical generalizations, phase transitions to long-range-ordered states, and the effects of disorder.Comment: 30 pp, 5 figures (Sub. to Annual Reviews of Condensed Matter Physics

XMM-Newton discovery of O VII emission from warm gas in clusters of galaxies

XMM-Newton recently discovered O VII line emission from ~2 million K gas near the outer parts of several clusters of galaxies. This emission is attributed to the Warm-Hot Intergalactic Medium. The original sample of clusters studied for this purpose has been extended and two more clusters with a soft X-ray excess have been found. We discuss the physical properties of the warm gas, in particular the density, spatial extent, abundances and temperature.Comment: 8 pages, 3 figures, conference "Soft X-ray emission from clusters of galaxies and related phenomena", ed. R. Lieu, Kluwer, in pres

Efficient reliable broadcast for commodity clusters

High-speed collective communication is the key to achieve high-performance computing in parallel computing. In the past, collective operations are usually implemented using unicast operations. We proposed a new architecture EQA (Enhanced Queue Architecture) for implementing high-speed collective operations in a cluster. With the incorporation of EQA and the hardware broadcast facility in network switches, an efficient reliable broadcast operation is implemented in a DP-SMP communication subsystem. With EQA, the computation, memory and network resources can be utilized efficiently. We evaluated the performance of the broadcast operation in a commodity cluster with fast Ethernet connection. We found that the hardware-based broadcast from DP-SMP with EQA outperforms the software-based broadcast operation. The use of EQA in broadcast operation could reduce the memory consumption by almost 40%. DP-SMP with EQA has proven to be an efficient communication mechanism for coupling commodity clusters.published_or_final_versio

End-to-End Localization and Ranking for Relative Attributes

We propose an end-to-end deep convolutional network to simultaneously localize and rank relative visual attributes, given only weakly-supervised pairwise image comparisons. Unlike previous methods, our network jointly learns the attribute's features, localization, and ranker. The localization module of our network discovers the most informative image region for the attribute, which is then used by the ranking module to learn a ranking model of the attribute. Our end-to-end framework also significantly speeds up processing and is much faster than previous methods. We show state-of-the-art ranking results on various relative attribute datasets, and our qualitative localization results clearly demonstrate our network's ability to learn meaningful image patches.Comment: Appears in European Conference on Computer Vision (ECCV), 201

Conditional Image-Text Embedding Networks

This paper presents an approach for grounding phrases in images which jointly learns multiple text-conditioned embeddings in a single end-to-end model. In order to differentiate text phrases into semantically distinct subspaces, we propose a concept weight branch that automatically assigns phrases to embeddings, whereas prior works predefine such assignments. Our proposed solution simplifies the representation requirements for individual embeddings and allows the underrepresented concepts to take advantage of the shared representations before feeding them into concept-specific layers. Comprehensive experiments verify the effectiveness of our approach across three phrase grounding datasets, Flickr30K Entities, ReferIt Game, and Visual Genome, where we obtain a (resp.) 4%, 3%, and 4% improvement in grounding performance over a strong region-phrase embedding baseline.Comment: ECCV 2018 accepted pape

Spotting the diffusion of New Psychoactive Substances over the Internet

Online availability and diffusion of New Psychoactive Substances (NPS) represent an emerging threat to healthcare systems. In this work, we analyse drugs forums, online shops, and Twitter. By mining the data from these sources, it is possible to understand the dynamics of drugs diffusion and their endorsement, as well as timely detecting new substances. We propose a set of visual analytics tools to support analysts in tackling NPS spreading and provide a better insight about drugs market and analysis

Tramp Ship Scheduling Problem with Berth Allocation Considerations and Time-dependent Constraints

This work presents a model for the Tramp Ship Scheduling problem including berth allocation considerations, motivated by a real case of a shipping company. The aim is to determine the travel schedule for each vessel considering multiple docking and multiple time windows at the berths. This work is innovative due to the consideration of both spatial and temporal attributes during the scheduling process. The resulting model is formulated as a mixed-integer linear programming problem, and a heuristic method to deal with multiple vessel schedules is also presented. Numerical experimentation is performed to highlight the benefits of the proposed approach and the applicability of the heuristic. Conclusions and recommendations for further research are provided.Comment: 16 pages, 3 figures, 5 tables, proceedings paper of Mexican International Conference on Artificial Intelligence (MICAI) 201

SECaps: A Sequence Enhanced Capsule Model for Charge Prediction

Automatic charge prediction aims to predict appropriate final charges according to the fact descriptions for a given criminal case. Automatic charge prediction plays a critical role in assisting judges and lawyers to improve the efficiency of legal decisions, and thus has received much attention. Nevertheless, most existing works on automatic charge prediction perform adequately on high-frequency charges but are not yet capable of predicting few-shot charges with limited cases. In this paper, we propose a Sequence Enhanced Capsule model, dubbed as SECaps model, to relieve this problem. Specifically, following the work of capsule networks, we propose the seq-caps layer, which considers sequence information and spatial information of legal texts simultaneously. Then we design a attention residual unit, which provides auxiliary information for charge prediction. In addition, our SECaps model introduces focal loss, which relieves the problem of imbalanced charges. Comparing the state-of-the-art methods, our SECaps model obtains 4.5% and 6.4% absolutely considerable improvements under Macro F1 in Criminal-S and Criminal-L respectively. The experimental results consistently demonstrate the superiorities and competitiveness of our proposed model.Comment: 13 pages, 3figures, 5 table