Study of a partnership between a group of initial teacher training students and a group of gifted and talented pupils developing effective ways to teach business and citizenship.

This paper outlines the nature of a partnership between a cohort of University Initial Teacher Training students and a cohort of ‘gifted and talented’ school pupils. It examines the process of the partnership and subsequent developments. It investigates how the project altered with the input of the participants, in particular the pupils, as evaluations revealed that the priorities of educators were not necessarily the same as those of pupils. Pupil priorities appeared to be just as valid and would possibly lead to better educational outcomes. The narrative follows through the three years of the project in chronological order, with comments, analysis, discussions and conclusions about each year’s project. The analysis and proposals for further development are grounded in qualitative data from pupils who have seen the full three-year cycle of the study through (these pupils were aged 15 at the time). These comment on what they have both taught and learned and on possible improvements and developments to the programme. Pupil, student and staff comments are included, along with the researcher’s interpretation of how particular participant groups reacted to the conditions that were imposed. The paper concludes with implications and future research recommendations

Using data network metrics, graphics, and topology to explore network characteristics

Yehuda Vardi introduced the term network tomography and was the first to propose and study how statistical inverse methods could be adapted to attack important network problems (Vardi, 1996). More recently, in one of his final papers, Vardi proposed notions of metrics on networks to define and measure distances between a network's links, its paths, and also between different networks (Vardi, 2004). In this paper, we apply Vardi's general approach for network metrics to a real data network by using data obtained from special data network tools and testing procedures presented here. We illustrate how the metrics help explicate interesting features of the traffic characteristics on the network. We also adapt the metrics in order to condition on traffic passing through a portion of the network, such as a router or pair of routers, and show further how this approach helps to discover and explain interesting network characteristics.Comment: Published at http://dx.doi.org/10.1214/074921707000000058 in the IMS Lecture Notes Monograph Series (http://www.imstat.org/publications/lecnotes.htm) by the Institute of Mathematical Statistics (http://www.imstat.org

Gene Therapy for Cardiovascular Disease

The last decade has seen substantial advances in the development of gene therapy strategies and vector technology for the treatment of a diverse number of diseases, with a view to translating the successes observed in animal models into the clinic. Perhaps the overwhelming drive for the increase in vascular gene transfer studies is the current lack of successful long-term pharmacological treatments for complex cardiovascular diseases. The increase in cardiovascular disease to epidemic proportions has also led many to conclude that drug therapy may have reached a plateau in its efficacy and that gene therapy may represent a realistic solution to a long-term problem. Here, we discuss gene delivery approaches and target diseases

Comment: Monitoring Networked Applications With Incremental Quantile Estimation

Comment: Monitoring Networked Applications With Incremental Quantile Estimation [arXiv:0708.0302]Comment: Published at http://dx.doi.org/10.1214/088342306000000619 in the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

A Hardware Implementation of Artificial Neural Network Using Field Programmable Gate Arrays

An artificial neural network algorithm is implemented using a field programmable gate array hardware. One hidden layer is used in the feed-forward neural network structure in order to discriminate one class of patterns from the other class in real time. With five 8-bit input patterns, six hidden nodes, and one 8-bit output, the implemented hardware neural network makes decision on a set of input patterns in 11 clocks and the result is identical to what to expect from off-line computation. This implementation may be used in level 1 hardware triggers in high energy physics experimentsComment: 13 pages, 4 figures, submitted to Nucl. Instr. Meth.

Application of Neural Networks for Energy Reconstruction

The possibility to use Neural Networks for reconstruction of the energy deposited in the calorimetry system of the CMS detector is investigated. It is shown that using feed - forward neural network, good linearity, Gaussian energy distribution and good energy resolution can be achieved. Significant improvement of the energy resolution and linearity is reached in comparison with other weighting methods for energy reconstruction.Comment: 18 pages, 13 figures, LATEX, submitted to: Nuclear Instruments & Methods

Targeting Families to Receive Intensive Family Preservation Services: Assessing the Use of Imminent Risk of Placement as a Service Criterion

The process for targeting families to receive intensive family preservation services was examined for 71 child welfare agencies in the United States. The focus of this exploratory/descriptive study was the concept of imminent risk of placement as a criterion for providing services. Findings indicated that agencies had difficulty defining imminent risk and were unable to successfully restrict services to imminent risk cases. Several factors besides imminent risk were identified in relation to the targeting process