Combining shared-coin algorithms

This paper shows that shared-coin algorithms can be combined to optimize several complexity measures, even in the presence of a strong adversary. By combining shared coins of Bracha and Rachman (1991) [10] and of Aspnes and Waarts (1996) [7], this yields a shared-coin algorithm, and hence, a randomized consensus algorithm, with O(nlog²n)$O\left(n{log}^{2}n\right)$ individual work and O(n²logn)$O(n^{2}logn)$ total work, using single-writer registers. This improves upon each of the above shared coins (where the former has a high cost for individual work, while the latter reduces it but pays in the total work), and is currently the best for this model.     

Atomic snapshots using lattice agreement

Summary Thesnapshot object is an important tool for constructing wait-free asynchronous algorithms. We relate the snapshot object to thelattice agreement decision problem. It is shown that any algorithm for solving lattice agreement can be transformed into an implementation of a snapshot object. The overhead cost of this transformation is only a linear number of read and write operations on atomic single-writer multi-reader registers. The transformation uses an unbounded amount of shared memory. We present a deterministic algorithm for lattice agreement that usedO (log² n) operations on 2-processorTest & Set registers, plusO (n) operations on atomic single-writer multi-reader registers. The shared objects are used by the algorithm in adynamic mode, that is, the identity of the processors that access each of the shared objects is determined dynamically during the execution of the algorithm. By a randomized implementation of 2-processorsTest & Set registers from atomic registers, this algorithm implies a randomized algorthm for lattice agreement that uses an expected number ofO (n) operations on (dynamic) atomic single-writer multi-reader registers. Combined with our transformation this yields implementations of atomic snapshots with the same complexity.Cambridge Research Laboratory, Digital Equipment Corporation Hagit Attiya received the B.Sc. degreeiin Mathematics and Computer Science from the Hebrew University of Jerusalem, in 1981, the M.Sc. and Ph.D. degrees in Computer Science from the Hebrew University of Jerusalem, in 1983 and 1987, respectively. She is presently a senior lecturer at the departtment of Computer Science at the Technion, Israel Institute of Technology. Prior to this, she has been a post-doctoral research associate at the Laboratory for Computer Science at M.I.T. Her general research interests are distributed computation and theoretical computer science. More specific interests include fault-tolerance, timing-based and asynchronous algorithms. Maurice Herlihy received the A.B. degree in Mathematics from Harvard University, and the M.S. and the Ph.D. degrees in Computer Science from M.I.T. From 1984 to 1989 he was a faculty member in the Computer Science Department at Carnegie Mellon University in Pittsburgh, PA. In 1989 he joined the research staff at the Digital Equipment Corporation's Cambridge Research Laboratory in Cambridge MA. Since 1994, he has been on the faculty at the Computer Science Department at Brown University. Dr. Herlihy's research interests encompass practical and theoretical aspects of distributed and concurrent computation. Ophir achman received a B.A. in computer science from the Technion, Haifa, Israel in 1989 and M.Sc. in computer science from the Technion, Haifa, Israel, in 1992. He is now studying for a D.Sc. in computer science at the Technion. His currentarea of research is distributed computing, and in particular, asynchronous shared memory systems.This work appeared in preliminary form in proceedings ofthe 6th International Workshop on Distributed Algorithms [12]. This research was partially supported by grant No. 92-0233 from the United States-Israel Binational Science Foundation (BSF), Jerusalem, Technion V.P.R. funds — B. and G. Greenberg Research Fund (Ottawa), and the fund for the promotion of research in the TechnionPart of the work of this author was performed while visiting DEC Cambridge Research Laboratory     

Statistical Evaluation of Data for Detecting Adulteration of California Navel Orange Juice

Compositional data from California early-, mid-, and late-season navel orange juice, concentrate and two-stage pulpwash were analyzed by various statistical techniques (ratios, regression, chi-square, Linear combination, and discriminant analysis) for detecting adulteration. These techniques were evaluated according to applicability for detecting three types of adulteration: (1) addition of sugar and/or citric acid, (2) addition of excess or unauthorized pulpwash, and (3) addition of other constituents intended to mask the dilution. Most parameters were significantly affected by time of harvest following commercial maturity. Two-stage pulpwash showed small but significant differences from corresponding single strength juice. Product differences were of about the same magnitude as the differences due to harvest date.     

Efficient elections in chordal ring networks

We study the message complexity of the problem of distributively electing a leader in chordal rings. Such networks consist of a basic ring with additional links, the extreme cases being the oriented ring and the complete graph with a full sense of direction. We present a general election algorithm for these networks, and prove its optimality. As a corollary, we show thatO(logn) chords at each processor suffice to obtain an algorithm that uses at mostO(n) messages; this improves and extends a previous work, where an algorithm, also usingO(n) messages, was suggested for the case where alln-1 chords exist (the oriented complete network).     

Concurrency and the Principle of Data Locality

Interference among operations can affect the throughput of concurrent applications. The author explains the difficulties of alleviating this interference, suggests ways to measure it, and outlines future research directions.     

A micromechanical approach to fatigue in small notches*

The present work shows the application to small notches of a micromechanical model which describes the growth of a short crack across the steep stress gradient generated at the root of a notch. The model, based on the theory of distributed dislocations, takes into account the interaction between short cracks and material barriers such as grain boundaries. The term ‘small notches’ refers in this paper to stress raisers the size of which is of the same order as the characteristic microstructural unit of the material. Typical examples are superficial scratches, corrosion pits, inclusions or pores. Comparisons between predicted fatigue limits and experimental results reported in the literature for different materials containing small artificial defects are shown and discussed.     

Synthesis of the Bi2Sr2CaCu2O8+δ superconductor following a polymer matrix route

This paper presents a convenient polymer matrix synthesis route based on the use of metal acetates, which yields Bi2Sr2CaCu2O8+δ (2212 phase) with a Tc higher than 93 K, in air and within a short sintering time (6–12 h) at 855°C. The phase quality of the intermediate and final products has been analysed by powder X-ray diffraction and scanning electron microscopy with energy-dispersive spectroscopy. Macroscopic superconducting characteristics have been determined by alternating-current magnetic susceptibility and direct-current magnetization. The results obtained on a large number of samples suggest that this preparation route is highly reproducible and leads to black-grained powders with excellent homogeneity within a relatively short processing time. The usefulness of these powders to obtain textured superconducting products has been explored and representative results are presented here. This revised version was published online in November 2006 with corrections to the Cover Date.     

Nanoinformatics in Drug Delivery

The use of nanomedicine for targeted drug delivery, though well established, is still a growing and developing field of research with potential benefits to many biomedical problems. There is a plethora of nano-carriers with myriads of designs of shapes, sizes and composition that involves complex, trial and error based preparation protocols. The digital age brought an information revolution with automated data analysis, machine learning and data mining applied to almost every field of research including drug delivery. Indeed, nanomedicine has benefitted from the use of data science and information science to optimize, standardize, and understand the synthesis, characterization, and biological effects of nanomaterials. This short review will describe several concepts and a few examples of nanoinformatics, including Nano-Quantitative Structure-Activity Relationship (Nano-QSAR), the use of computational methods for predicting different properties of nanomedicine in drug delivery and propose an outlook for the future.     

Tuna Protein Nutritional Quality Changes after Canning

Albacore tuna (Thunnus alalunga) was steamed and canned in soy bean oil and sterilized at 115°C for 55 or 90 min. Proximate composition, total amino acid and available lysine content were determined during different phases of the process. Water and protein were lost in all phases and fat content increased. There was a decrease in available lysine during cooking but no loss in total amino acids. Nutritional evaluation of the protein showed differences in biological value and net protein utilization when the canned tuna was mixed with bread flour.