diff --git a/INFO_DP.bib b/INFO_DP.bib
index d7aa966..acb47aa 100644
--- a/INFO_DP.bib
+++ b/INFO_DP.bib
@@ -2,13 +2,26 @@
 %% http://bibdesk.sourceforge.net/
 
 
-%% Created for Nigel Stanger at 2011-07-29 15:45:38 +1200 
+%% Created for Nigel Stanger at 2011-08-04 09:32:37 +1200 
 
 
 %% Saved with string encoding Western (Mac OS Roman) 
 
 
 
+@techreport{dp2011-07,
+	Abstract = {Second Life is a multi-purpose online virtual world that is increasingly being used for applications and simulations in diversified areas such as education, training, entertainment, and even for applications related to Artificial Intelligence. For the successful implementation and analysis of most of these applications, it is important to have a robust mechanism to extract low-level data from Second Life in high frequency and high accuracy. However, currently Second Life does not have a reliable or scalable inbuilt data extraction mechanism, nor the related research provides a better alternative. This paper presents a robust and reliable data extraction mechanism from Second Life. We also investigate the currently existing data extraction mechanisms in detail, identifying their limitations in extracting data with high accuracy and high frequency.},
+	Address = {Dunedin, New Zealand},
+	Author = {Surangika Ranathunga and Stephen Cranefield and Martin Purvis},
+	Date-Added = {2011-08-04 09:31:25 +1200},
+	Date-Modified = {2011-08-04 09:31:25 +1200},
+	Institution = {Department of Information Science, University of Otago},
+	Month = jul,
+	Number = {2011/07},
+	Title = {Extracting data from Second Life},
+	Type = {Discussion paper},
+	Year = {2011}}
+
 @techreport{dp2011-06,
 	Abstract = {Over the last few years, the voluminous increase in the academic research publications has gained significant research attention. Research has been carried out exploring novel ways of providing information services using the research content. However, the task of extracting meaningful information from research documents remains a challenge. This paper presents our research work carried out for developing intelligent information systems, exploiting the research content. We present in this paper, a linked data application which uses a new semantic publishing model for providing value added information services for the research community. The paper presents a conceptual framework for modelling contexts associated with sentences in research articles and discusses the Sentence Context Ontology, which is used to convert the information extracted from research documents into machine-understandable data. The paper also reports on supervised learning experiments carried out using conditional probabilistic models for achieving automatic context identification.},
 	Address = {Dunedin, New Zealand},
@@ -104,16 +117,16 @@
 	Type = {Discussion paper},
 	Year = {2010}}
 
-@techreport{dp2011-07,
-	Abstract = {Second Life is a multi-purpose online virtual world that is increasingly being used for applications and simulations in diversified areas such as education, training, entertainment, and even for applications related to Artificial Intelligence. For the successful implementation and analysis of most of these applications, it is important to have a robust mechanism to extract low-level data from Second Life in high frequency and high accuracy. However, currently Second Life does not have a reliable or scalable inbuilt data extraction mechanism, nor the related research provides a better alternative. This paper presents a robust and reliable data extraction mechanism from Second Life. We also investigate the currently existing data extraction mechanisms in detail, identifying their limitations in extracting data with high accuracy and high frequency.},
+@techreport{dp2011-08,
+	Abstract = {Video mediated and augmented reality technologies can challenge our sense of what we perceive and believe to be ``real''. Applied appropriately, the technology presents new opportunities for understanding and treating a range of human functional impairments as well as studying the underling psychological bases of the phenomenon. This paper describes our ``augmented mirror box'' (AMB) technology which builds on the potential of optical mirror boxes by adding augmentations that can be applied in therapeutic and scientific settings. Here we test hypotheses about limb presence and perception, belief, and pain using laboratory studies to demonstrate proof of concept. The results of these studies provide evidence that the AMB can be used to manipulate beliefs and perceptions and alter the reported experience of pain. We conclude that the system has considerable potential for use in experimental and in clinical settings.},
 	Address = {Dunedin, New Zealand},
-	Author = {Surangika Ranathunga and Stephen Cranefield and Martin Purvis},
+	Author = {Holger Regenbrecht and Elizabeth Franz and Graham McGregor and Brian Dixon and Simon Hoermann},
 	Date-Added = {2010-11-17 14:50:10 +1300},
-	Date-Modified = {2011-07-29 15:45:23 +1200},
+	Date-Modified = {2011-08-04 09:32:33 +1200},
 	Institution = {Department of Information Science, University of Otago},
-	Month = jul,
-	Number = {2011/07},
-	Title = {Extracting data from Second Life},
+	Month = aug,
+	Number = {2011/08},
+	Title = {From mirror therapy to augmentation},
 	Type = {Discussion paper},
 	Year = {2011}}