Bone mineral density and turnover in children with systemic juvenile chronic arthritis

OBJECTIVE: To assess bone mineral status in a group of children with systemic type juvenile chronic arthritis (JCA), which places them at high risk to develop osteoporosis. METHODS: Bone mineral density (BMD) was measured in 17 children aged 6-18 yrs (mean 14.9 +/- 4.5) with systemic JCA and in 18 matched controls by dual energy x-ray absorptiometry. Bone turnover was determined by quantitative bone scintigraphy, using quantitative single photon emission computed tomography based on skeletal uptake of methylene diphosphonates (MDP uptake). Serum concentrations of minerals, osteocalcin, and bone alkaline phosphatase were determined. Nutrient intake was assessed by a 24 hour dietary recall. RESULTS: Patients with systemic JCA who received corticosteroid therapy had significantly reduced BMD in both the lumbar spine (p < 0.05) and the femoral neck (p < 0.05) compared to controls, whereas BMD values of the non-steroid systemic JCA patients were not different from controls. Bone turnover measurement by MDP uptake showed no difference between patients with JCA and controls. Levels of calcium, phosphorus, alkaline phosphatase. and osteocalcin were within normal limits in all patients. CONCLUSION: Patients with systemic JCA receiving longterm steroid treatment may develop a significant decrease in BMD. The normal MDP uptake values together with normal osteocalcin levels that we observed in our patients indicate that their disease is not associated with enhancement of bone turnover rates. These observations might have therapeutic implications for prevention and management of osteoporosis in JCA.     

Hierarchical Multicomponent Inorganic Metamaterials: Intrinsically Driven Self‐Assembly at the Nanoscale

Increasingly intricate in their composition and structural organization, hierarchical multicomponent metamaterials with nonlinear spatially reconfigurable functionalities challenge the intrinsic constraints of natural materials, revealing tremendous potential for the advancement of biochemistry, nanophotonics, and medicine. Recent breakthroughs in high‐resolution nanofabrication utilizing ultranarrow, precisely controlled ion or laser beams have enabled assembly of architectures of unprecedented structural and functional complexity, yet costly, time‐ and energy‐consuming high‐resolution sequential techniques do not operate effectively at industry‐required scale. Inspired by the fictional Baron Munchausen's fruitless attempt to pull himself up, it is demonstrated that metamaterials can undergo intrinsically driven self‐assembly, metaphorically pulling themselves up into existence. These internal drivers hold a key to unlocking the potential of metamaterials and mapping a new direction for the large‐area, cost‐efficient self‐organized fabrication of practical devices. A systematic exploration of these efforts is presently missing, and the driving forces governing the intrinsically driven self‐assembly are yet to be fully understood. Here, recent progress in the self‐organized formation and self‐propelled growth of complex hierarchical multicomponent metamaterials is reviewed, with emphasis on key principles, salient features, and potential limitations of this family of approaches. Special stress is placed on self‐assembly driven by plasma, current in liquid, ultrasonic, and similar highly energetic effects, which enable self‐directed formation of metamaterials with unique properties and structures.     

Distributed data clustering in sensor networks

Low overhead analysis of large distributed data sets is necessary for current data centers and for future sensor networks. In such systems, each node holds some data value, e.g., a local sensor read, and a concise picture of the global system state needs to be obtained. In resource-constrained environments like sensor networks, this needs to be done without collecting all the data at any location, i.e., in a distributed manner. To this end, we address the distributed clustering problem, in which numerous interconnected nodes compute a clustering of their data, i.e., partition these values into multiple clusters, and describe each cluster concisely. We present a generic algorithm that solves the distributed clustering problem and may be implemented in various topologies, using different clustering types. For example, the generic algorithm can be instantiated to cluster values according to distance, targeting the same problem as the famous k-means clustering algorithm. However, the distance criterion is often not sufficient to provide good clustering results. We present an instantiation of the generic algorithm that describes the values as a Gaussian Mixture (a set of weighted normal distributions), and uses machine learning tools for clustering decisions. Simulations show the robustness, speed and scalability of this algorithm. We prove that any implementation of the generic algorithm converges over any connected topology, clustering criterion and cluster representation, in fully asynchronous settings.     

Deleting files in the Celeste peer-to-peer storage system

Celeste is a robust peer-to-peer object store built on top of a distributed hash table (DHT). Celeste is a working system, developed by Sun Microsystems Laboratories. During the development of Celeste, we faced the challenge of complete object deletion, and moreover, of deleting “files” composed of several different objects. This important problem is not solved by merely deleting meta-data, as there are scenarios in which all file contents must be deleted, e.g., due to a court order. Complete file deletion in a realistic peer-to-peer storage system has not been previously dealt with due to the intricacy of the problem — the system may experience high churn rates, nodes may crash or have intermittent connectivity, and the overlay network may become partitioned at times. We present an algorithm that eventually deletes all file contents, data and meta-data, in the aforementioned complex scenarios. The algorithm is fully functional and has been successfully integrated into Celeste.     

Reliable Distributed Storage

A distributed storage service lets clients abstract a single reliable shared storage device using a collection of possibly unreliable computing units. Algorithms that implement this abstraction offer certain tradeoffs and vary according to dimensions such as complexity, the consistency semantics provided, and the types of failures tolerated.     

Keeping Denial-of-Service Attackers in the Dark

We consider the problem of overcoming (distributed) denial-of-service (DoS) attacks by realistic adversaries that have knowledge of their attack's successfulness, for example, by observing service performance degradation or by eavesdropping on messages or parts thereof. A solution for this problem in a high-speed network environment necessitates lightweight mechanisms for differentiating between valid traffic and the attacker's packets. The main challenge in presenting such a solution is to exploit existing packet-filtering mechanisms in a way that allows fast processing of packets but is complex enough so that the attacker cannot efficiently craft packets that pass the filters. We show a protocol that mitigates DoS attacks by adversaries that can eavesdrop and (with some delay) adapt their attacks accordingly. The protocol uses only available efficient packet-filtering mechanisms based mainly on addresses and port numbers. Our protocol avoids the use of fixed ports and instead performs "pseudorandom port hopping." We model the underlying packet-filtering services and define measures for the capabilities of the adversary and for the success rate of the protocol. Using these, we provide a novel rigorous analysis of the impact of DoS on an end-to-end protocol and show that our protocol provides effective DoS prevention for realistic attack and deployment scenarios.     

Nahalal: Cache Organization for Chip Multiprocessors

This paper addresses cache organization in chip multiprocessors (CMPs). We show that in CMP systems it is valuable to distinguish between shared data, which is accessed by multiple cores, and private data accessed by a single core. We introduce Nahalal, an architecture whose novel floorplan topology partitions cached data according to its usage (shared versus private data), and thus enables fast access to shared data for all processors while preserving the vicinity of private data to each processor. Nahalal exhibits significant improvements in cache access latency compared to a traditional cache design.     

Threshold of stimulated Brillouin scattering by use of a solar pumped laser

What is to our knowledge the first stimulated Brillouin scattering experiment using a high-power low-gain solar pumped laser is presented. A threshold reflectivity of 0.23% was reached when a peak power of 20.7 kW was used at 7.6 GHz. A cw solar pumped laser was Q-switched with an acousto-optic modulator, and the bandwidth was narrowed with an intracavity etalon. A high polarization ratio (>99.4%) was achieved by use of an intracavity configuration. Higher reflectivity values were limited because of the lack of availability of optical switches.     

Octopus: A fault-tolerant and efficient ad-hoc routing protocol

Mobile ad-hoc networks (MANETs) are failure-prone environments; it is common for mobile wireless nodes to intermittently disconnect from the network, e.g., due to signal blockage. This paper focuses on withstanding such failures in large MANETs: we present Octopus, a fault-tolerant and efficient position-based routing protocol. Fault-tolerance is achieved by employing redundancy, i.e., storing the location of each node at many other nodes, and by keeping frequently refreshed soft state. At the same time, Octopus achieves a low location update overhead by employing a novel aggregation technique, whereby a single packet updates the location of many nodes at many other nodes. Octopus is highly scalable: for a fixed node density, the number of location update packets sent does not grow with the network size. And when the density increases, the overhead drops. Thorough empirical evaluation using the ns2 simulator with up to 675 mobile nodes shows that Octopus achieves excellent fault-tolerance at a modest overhead: when all nodes intermittently disconnect and reconnect, Octopus achieves the same high reliability as when all nodes are constantly up. A preliminary version of this paper appears in Proceedings of the 24th IEEE Symposium on Reliable Distributed Systems (SRDS 2005) October 26–28, 2005, Orlando, Florida. Idit Keidar is a faculty member at the department of Electrical Engineering at the Technion Israel Institute of Technology, and a recipient of the national Alon Fellowship for new faculty members. She holds Ph.D., M.Sc. (summa cum laude), and B.Sc (summa cum laude) degrees from the Hebrew University of Jerusalem. She was a postdoctoral research associate at MIT’s laboratory for Computer Science, where she held post-doctoral fellowships from Rothschild Yad-Hanadiv and NSF CISE. Dr. Keidar has consulted for BBN Technologies (a Verizon Company) in the area of fault-tolerance and intrusion tolerance, and for Microsoft Research in the area of fault-tolerant storage systems. Dr. Keidar’s research focuses on reliability in distributed algorithms and system. She is the academic head of Software Systems Laboratory at the Technion. Dr. Keidar served as a member of the Steering Committee of the ACM Symposium on Principles of Distributed Computing (PODC), has served on numerous program committees of leading conferences in the area of distributed and parallel computing, has twice served as a vice-chair for the IEEE International Conference on Distributed Computing Systems (ICDCS), and once served as a vice-chair for Euro-Par. Yoav Barel is a Senior Business Line Manager at Sun Microsystems. He holds a B.Sc from the Technion—Israel Institute of Technology. Mr. Barel works with wireless carriers world wide and assists them in deploying innovative services based on cutting edge Java technologies. Roie Melamed is a research staff member at IBM Haifa Research Laboratory. He holds Ph.D. and B.A. (cum laude) degrees from the Technion—Israel Institute of Technology. Dr. Melamed’s research focuses on reliability in distributed systems.