Semantic modelling of user interests based on cross-folksonomy analysis

The continued increase in Web usage, in particular participation in folksonomies, reveals a trend towards a more dynamic and interactive Web where individuals can organise and share resources. Tagging has emerged as the de-facto standard for the organisation of such resources, providing a versatile and reactive knowledge management mechanism that users find easy to use and understand. It is common nowadays for users to have multiple profiles in various folksonomies, thus distributing their tagging activities. In this paper, we present a method for the automatic consolidation of user profiles across two popular social networking sites, and subsequent semantic modelling of their interests utilising Wikipedia as a multi-domain model. We evaluate how much can be learned from such sites, and in which domains the knowledge acquired is focussed. Results show that far richer interest profiles can be generated for users when multiple tag-clouds are combine

Semantics, sensors, and the social web: The live social semantics experiments

The Live Social Semantics is an innovative application that encourages and guides social networking between researchers at conferences and similar events. The application integrates data and technologies from the Semantic Web, online social networks, and a face-to-face contact sensing platform. It helps researchers to find like-minded and influential researchers, to identify and meet people in their community of practice, and to capture and later retrace their real-world networking activities at conferences. The application was successfully deployed at two international conferences, attracting more than 300 users in total. This paper describes this application, and discusses and evaluates the results of its two deployment

The Performance Behaviour of a Grain Silo Foundation in Jeddah Supported on Stone Columns

This paper describes the ground treatment carried out and the subsequent load settlement behaviour of a grain silo in Jeddah, Saudi Arabia. Predicted performance based on the results of both SPT and cone penetration tests are compared with actual behaviour. The prediction based on the SPT results is poor, with the cone penetration analyses giving a significant improvement. A knowledge of cone resistance and hence modulus values for the full depth of influence of the silo would have further refined the prediction

Renal peroxiredoxin 6 interacts with anion exchanger 1 and plays a novel role in pH homeostasis.

Peroxiredoxin 6 (PRDX6) is one of the six members of the PRDX family, which have peroxidase and antioxidant activity. PRDX6 is unique, containing only one conserved cysteine residue (C47) rather than the two found in other PRDXs. A yeast two-hybrid screen found PRDX6 to be a potential binding partner of the C-terminal tail of anion exchanger 1 (AE1), a Cl(-)/HCO(3)(-) exchanger basolaterally expressed in renal α-intercalated cells. PRDX6 immunostaining in human kidney was both cytoplasmic and peripheral and colocalized with AE1. Analysis of native protein showed that it was largely monomeric, whereas expressed tagged protein was more dimeric. Two methionine oxidation sites were identified. In vitro and ex vivo pull-downs and immunoprecipitation assays confirmed interaction with AE1, but mutation of the conserved cysteine resulted in loss of interaction. Prdx6 knockout mice had a baseline acidosis with a major respiratory component and greater AE1 expression than wild-type animals. After an oral acid challenge, PRDX6 expression increased in wild-type mice, with preservation of AE1. However, AE1 expression was significantly decreased in knockout animals. Kidneys from acidified mice showed widespread proximal tubular vacuolation in wild-type but not knockout animals. Knockdown of PRDX6 by siRNA in mammalian cells reduced both total and cell membrane AE1 levels. Thus, PRDX6-AE1 interaction contributes to the maintenance of AE1 during cellular stress such as during metabolic acidosis.Human kidney sections were prepared by Suzy Haward, Addenbrooke's Human Research Tissue Bank, which is supported by the Cambridge Biomedical Research Centre. We thank Dr. Aron Fisher (Institute for Environmental Science, University of Pennsylvania) for the kind gift of Prdx6−/− mice and reagents, Carsten Wagner (Zurich) for antisera, Jane Clarke (University of Cambridge) for modified pRSET-A vector, and Kamburapola Jayawardena for mass spectrometry (CIMR). This work was funded by the Wellcome Trust (award 088489/Z/09/Z to FEKF and Strategic award 100140/Z/12/Z to the Cambridge Institute for Medical Research), and the Jack Kent Cooke Foundation (scholarship to SLS).This is the author accepted manuscript. The final version is available from Nature Publishing Group via http://dx.doi.org/10.1038/ki.2015.27

Semantic disambiguation and contextualisation of social tags

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-28509-7_18This manuscript is an extended version of the paper ‘cTag: Semantic Contextualisation of Social Tags’, presented at the 6th International Workshop on Semantic Adaptive Social Web (SASWeb 2011).We present an algorithmic framework to accurately and efficiently identify the semantic meanings and contexts of social tags within a particular folksonomy. The framework is used for building contextualised tag-based user and item profiles. We also present its implementation in a system called cTag, with which we preliminary analyse semantic meanings and contexts of tags belonging to Delicious and MovieLens folksonomies. The analysis includes a comparison between semantic similarities obtained for pairs of tags in Delicious folksonomy, and their semantic distances in the whole Web, according to co-occurrence based metrics computed with results of a Web search engine.This work was supported by the Spanish Ministry of Science and Innovation (TIN2008-06566-C04-02), and Universidad Autónoma de Madrid (CCG10-UAM/TIC-5877

Increasing Feed Conversion Efficiency in Automatic Milking Systems: The Impact of Grain-Based Concentrate Allocation and Kikuyu (\u3cem\u3ePennisetum clandestinum\u3c/em\u3e) Pasture State on Milk Production

Pasture is typically offered to dairy cows in three allocations in pasture-based automatic milking systems (AMS). However, due to voluntary cow movement and distribution of milkings, some dairy cows access fresh pasture and other cows access depleted (stale) pasture. The first cows moving to an allocation of fresh pasture are offered ad-libitum, high quality pasture as opposed to cows arriving to the same allocation during the middle or end of the day accessing poorer quality, high fibre (neutral detergent fibre, NDF) pasture. In addition, grain-based concentrate (GBC) is allocated independently to this pasture state. The ability to increase feed conversion efficiency and AMS herd milk production by targetedGBC supplementation to cows accessing differing pasture states is unknown. Therefore, the aim of the current experiment was to determine the impact of pasture state and GBC allocation on dairy cow milk production