Spanner is Google’s scalable, multiversion, globally distributed, and synchronously replicated database. It is the first system to distribute data at global scale and support externally-consistent distributed transactions. This article describes how Spanner is structured, its feature set, the rationale underlying various design decisions, and a novel time API that exposes clock uncertainty. This API and its implementation are critical to supporting external consistency and a variety of powerful features: nonblocking reads in the past, lock-free snapshot transactions, and atomic schema changes, across all of Spanner.

MOTIVATION: Exome sequencing has proven to be an effective tool to discover the genetic basis of Mendelian disorders. It is well established that copy number variants (CNVs) contribute to the etiology of these disorders. However, calling CNVs from exome sequence data is challenging. A typical read depth strategy consists of using another sample (or a combination of samples) as a reference to control for the variability at the capture and sequencing steps. However, technical variability between samples complicates the analysis and can create spurious CNV calls. RESULTS: Here, we introduce ExomeDepth, a new CNV calling algorithm designed to control for this technical variability. ExomeDepth uses a robust model for the read count data and uses this model to build an optimized reference set in order to maximize the power to detect CNVs. As a result, ExomeDepth is effective across a wider range of exome datasets than the previously existing tools, even for small (e.g. one to two exons) and heterozygous deletions. We used this new approach to analyse exome data from 24 patients with primary immunodeficiencies. Depending on data quality and the exact target region, we find between 170 and 250 exonic CNV calls per sample. Our analysis identified two novel causative deletions in the genes GATA2 and DOCK8. AVAILABILITY: The code used in this analysis has been implemented into an R package called ExomeDepth and is available at the Comprehensive R Archive Network (CRAN).

We consider the problem of state estimation of a discrete time process over a packet dropping network. Previous pioneering work on Kalman filtering with intermittent observations is concerned with the asymptotic behavior of E[Pk], i.e., the expected value of the error covariance, for a given packet arrival rate. We consider a different performance metric, Pr[Pkles M], i.e., the probability that Pkis bounded by a given M, and we derive lower and upper bounds on Pr[Pkles M]. We are also able to recover the results in the literature when using Pr[Pkles M] as a metric for scalar systems. Examples are provided to illustrate the theory developed in the paper.

History Unwired (HU, see http://web.mit.edu/frontiers) is a multi-year investigation of the narrative uses of mobile technology in historic cities. In 2004-2005 a team of researchers from MIT and University of Venice IUAV worked with local artists, citizens, and academics to develop a walking tour through one of Venice's more hidden neighborhoods, delivered over location-aware, multimedia phones and PDAs. The tour was presented at the 2005 Biennale of Contemporary Art and takes visitors around one of the lesser-traveled neighborhoods of Venice: Castello. The tour was tested on over 200 users, over half of whom filled out extensive surveys. In this paper we present the results of these surveys focusing on the how different types of physical and sociological spaces complemented the audio, video, interactive media and positioning capabilities of the handhelds. First we provide some background information on tourism and local culture in Venice. We then describe the narrative and technical structure of the History Unwired walking tour. We then go into the use of mobile media in closed, semi-open, and commercial spaces in Castello.

We present experimental results of thrust produced by a robotic propulsor, the design of which is inspired by the ribbon fin of the South American black ghost knifefish (Apteronotus albifrons). This remarkably nimble fish moves by oscillating its ribbon fin rays out of phase and thereby passing a traveling wave along the fin's length. Combinations of thrust from the ribbon fin and body rolls produced by the two pectoral fins enable the black ghost to swim in nearly any direction without bending its body. The fish's agile locomotor system is tightly integrated with its omnidirectional, active sensing system. The robotic ribbon fin has eight individually actuated metal rays which are linked by a thin latex sheet. The experimental results demonstrate the effect of varying the propulsive wave's frequency, amplitude and length on the robotic fin's thrust production. We found that thrust production peaks at particular combinations of the three variables and that the fin could produce steady forward thrust, despite the relatively small number of rays. The robotic ribbon fin has potential application as a propulsor for future underwater vehicles, in addition to being a valuable scientific instrument in understanding the swimming mechanics of the black ghost and similar fish

The architecture of an RISC (reduced instruction set computer) based on multiprocessor chip designed in the Briarcliff Multiprocessor Project is described. The processors operate in an MIMD (multiple instruction, multiple data) fashion, executing parallel instruction streams generated by a parallelizing compiler for the exploitation of fine-grained parallelism. Low-cost synchronization mechanisms are supported in hardware. The resulting system is tolerant of unpredictable delays in the progress of individual streams. Instruction level parallelism is exploited through the use of register channels and a mechanism for the collective branching of processors. For efficient synchronization during parallel execution of loops, fuzzy barriers are provided. On-chip memory is organized into multiple banks in order to provide sufficient bandwidth for the processors. The RISC processors are based upon the Sun SPARC architecture.>