Evaluation of leukocyte dynamic in mouse retinal circulation with scanning laser ophthalmoloscopy (Video report)

http://bjo.bmj.com/content/suppl/2001/06/20/85.7.DC1 Leukocyte-endothelial cell interactions play an important role in the pathogenesis of various types of retinal vascular diseases, including diabetes, uveitis, and ischemic lesions. Over the last few years, several methods have been devised in which the scanning laser ophthalmoscope (SLO) is used to study leukocyte-endothelial interactions in vivo [1,2]. Previously we reported a noninvasive in vivo leukocyte tracking method using the SLO in rat. In this method, a nontoxic fluorescent agent (6-carboxyfluorescein diacetate, CFDA) was used to label leukocytes in vitro. Leukocyte velocities within the retinal and choroidal circulations were be quantified simultaneously [3]. None of the previous methods has been developed for imaging the murine fundus, mainly due to problems arising from the small size of the mouse eye. However, there are many advantages of using a murine model to study retinal vascular diseases such as enhanced genetic definition, increased range of reagents available for immunological studies and cost reduction. We have developed our SLO method such that we can track leukocytes in the mouse retinal and choroidal circulations.

Clustered indexing for branch predictors

As a result of resource limitations, state in branch predictors is frequently shared between uncorrelated branches. This interference can significantly limit prediction accuracy. In current predictor designs, the branches sharing prediction information are determined by their branch addresses and thus branch groups are arbitrarily chosen during compilation. This feasibility study explores a more analytic and systematic approach to classify branches into clusters with similar behavioral characteristics. We present several ways to incorporate this cluster information as an additional information source in branch predictors.

The use of interactive video in teaching teachers: an evaluation of a link with a primary school

This paper presents an evaluation of the use of videoconferencing in learning and teaching in a United Kingdom higher education institution involved in initial teacher education. Students had the opportunity to observe naturalistic teaching practices without physically being present in the classroom. The study consisted of semi-structured interviews with the co-ordinator of the link, the head of ICT services in Stranmillis University College and the teacher of the classroom being observed. Students were invited to complete an online questionnaire. The views of the students, the co-ordinator of the link, the teacher of the classroom being observed and the head of ICT services in Stranmillis University College were then triangulated to gain an overall view of the effectiveness of the videoconferencing link. Interviews suggested students benefited in terms of pedagogy. In the early stages of the project, the teacher thought it acted as a form of classroom control. Technical problems were encountered initially and camera control was modified in the light of these. The online questionnaire suggested that students viewed this experience in a positive way and were impressed with the content, technical quality, and potential benefits of the use of this example of new technologies.

Behaviours in video

With a significant increment of the number of digital cameras used for various purposes, there is a demanding call for advanced video analysis techniques that can be used to systematically interpret and understand the semantics of video contents, which have been recorded in security surveillance, intelligent transportation, health care, video retrieving and summarization. Understanding and interpreting human behaviours based on video analysis have observed competitive challenges due to non-rigid human motion, self and mutual occlusions, and changes of lighting conditions. To solve these problems, advanced image and signal processing technologies such as neural network, fuzzy logic, probabilistic estimation theory and statistical learning have been overwhelmingly investigated.