A 66-year-old man presented with acute respiratory distress due to a tracheal tumor involving the posterior wall of the upper trachea, with nearly complete airway obstruction. Partial debulking of the tumor's endoluminal component, via rigid bronchoscopy and yttrium-aluminum-perovskite laser, allowed timely and effective airway restoration. The diagnosis was benign tracheal glomus tumor. Two weeks later, elective tracheal sleeve resection with end-to-end anastomosis allowed complete resection of the lesion. No tumor recurrence was found at 21-month follow-up. We describe the multidisciplinary management of this extremely rare tracheal tumor, and review its features.

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One of the major challenges in today's computing world is energy management in portable devices and servers. Power management is essential to increase battery life. High end server systems use large clusters of machines that consume enormous amount of power. Past research has devised both software and hardware techniques to memory energy management but has overlooked the performance of applications in such environments. The result is that some of these techniques slowed down an application by 835%. In this paper, we look at software techniques for memory energy management without compromising on performance. The paper conceives of a new approach called BOS - Ballooning in the OS inspired from the VMware ESX server. The BOS approach consists of a kernel daemon which continuously monitors the accesses to memory chips and disk I/O. Based on the profiled information, the BOS daemon decides about powering down/up chips. Powering down is emulated within the kernel using mechanisms such as page migration and invisible buddy. Results indicate that chips with more allocated pages may not always be the most frequently accessed ones. A study has been done analyzing the effect of decreased memory size on disk activity and based on the study, a threshold based policy is proposed which is found to settle in the operating point for a simple applicaton. A single page migration incurs a cost of approximately 13μs and is one of the bottlenecks in the BOS approach.

In this paper, we explore real time N-way video communication over enterprise networks based on scalable video coding, SVC (Scalable extension of H.264/AVC). We present a bit stream extraction strategy based on GOP size prediction and perceptual importance of temporal and quality enhancements, and validate the strategy through initial subjective testing. We also compare it with extraction based on average bit rate of each constituent layer of the bitstream. Our extraction is adaptive with respect to variations in available bandwidth and is proxy driven, in that the decision process and the adaptation are preformed at proxy servers located at the edges of the backbone network. The main goals are to 1)maximize the user perceived quality even during deteriorating channel conditions, 2) maximize the reaction speed to changes in available bandwidth and 3) minimize the extraction delay. We report objective and subjective results for the N=2 case, with HD video clips encoded at 600 -900 kbps. With a channel utilization of 92.7%, our extraction algorithm based on GOP size prediction shows an average increase in PSNR of about 2.2 dB over the extraction based on average bit rate. Initial subjective tests also prove that our layer extraction strategy is perceptually more efficient than other extraction schemes.

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