Heat shock and structural proteins associated with meat tenderness in Nellore beef cattle,a Bos indicus breed

Nellore beef cattle, a Bos indicus (Zebu) breed, is well adapted to tropical conditions and has allowed Brazil to become one of the largest producers of red meat. Nevertheless, B. indicus breeds are reported to have less tender meat than Bos taurus. This study was designed to identify genes associated with meat tenderness and thus provides important information for breeding programs. A group of 138 animals was evaluated for longissimus thoracis muscle shear force (SF). Animals with the highest and lowest SF values (six animals each) were then selected for protein abundance studies. Samples were subjected to two-dimensional gel electrophoresis (2-DE) followed by peptide sequencing through mass spectrometry (MS) to identify differentially expressed proteins associated with SF values. Seventeen differentially expressed spots were observed (p < 0.05) between the two groups. The 13 proteins identified included structural proteins (alpha actin-1, MLC1, MLC3, MLC2F and tropomyosin), related to cell organization (HSPB1 and HSP70), metabolism (beta-LG, ACBD6 and Complex III subunit I) and some uncharacterized proteins. Results confirm the existence of differentially expressed proteins associated with SF, which can lead to a better understanding of mechanisms involved in meat tenderness.     

RE-tree: an efficient index structure for regular expressions

Due to their expressive power, regular expressions (REs) are quickly becoming an integral part of language specifications for several important application scenarios. Many of these applications have to manage huge databases of RE specifications and need to provide an effective matching mechanism that, given an input string, quickly identifies the REs in the database that match it. In this paper, we propose the RE-tree, a novel index structure for large databases of RE specifications. Given an input query string, the RE-tree speeds up the retrieval of matching REs by focusing the search and comparing the input string with only a small fraction of REs in the database. Even though the RE-tree is similar in spirit to other tree-based structures that have been proposed for indexing multidimensional data, RE indexing is significantly more challenging since REs typically represent infinite sets of strings with no well-defined notion of spatial locality. To address these new challenges, our RE-tree index structure relies on novel measures for comparing the relative sizes of infinite regular languages. We also propose innovative solutions for the various RE-tree operations including the effective splitting of RE-tree nodes and computing a "tight" bounding RE for a collection of REs. Finally, we demonstrate how sampling-based approximation algorithms can be used to significantly speed up the performance of RE-tree operations. Preliminary experimental results with moderately large synthetic data sets indicate that the RE-tree is effective in pruning the search space and easily outperforms naive sequential search approaches.Received: 16 September 2002, Published online: 8 July 2003Edited by R. Ramakrishnan     

Tracking set-expression cardinalities over continuous update streams

There is growing interest in algorithms for processing and querying continuous data streams (i.e., data seen only once in a fixed order) with limited memory resources. In its most general form, a data stream is actually an update stream, i.e., comprising data-item deletions as well as insertions. Such massive update streams arise naturally in several application domains (e.g., monitoring of large IP network installations or processing of retail-chain transactions). Estimating the cardinality of set expressions defined over several (possibly distributed) update streams is perhaps one of the most fundamental query classes of interest; as an example, such a query may ask what is the number of distinct IP source addresses seen in passing packets from both router R ₁ and R ₂ but not router R ₃?. Earlier work only addressed very restricted forms of this problem, focusing solely on the special case of insert-only streams and specific operators (e.g., union). In this paper, we propose the first space-efficient algorithmic solution for estimating the cardinality of full-fledged set expressions over general update streams. Our estimation algorithms are probabilistic in nature and rely on a novel, hash-based synopsis data structure, termed 2-level hash sketch. We demonstrate how our 2-level hash sketch synopses can be used to provide low-error, high-confidence estimates for the cardinality of set expressions (including operators such as set union, intersection, and difference) over continuous update streams, using only space that is significantly sublinear in the sizes of the streaming input (multi-)sets. Furthermore, our estimators never require rescanning or resampling of past stream items, regardless of the number of deletions in the stream. We also present lower bounds for the problem, demonstrating that the space usage of our estimation algorithms is within small factors of the optimal. Finally, we propose an optimized, time-efficient stream synopsis (based on 2-level hash sketches) that provides similar, strong accuracy-space guarantees while requiring only guaranteed logarithmic maintenance time per update, thus making our methods applicable for truly rapid-rate data streams. Our results from an empirical study of our synopsis and estimation techniques verify the effectiveness of our approach.Received: 20 October 2003, Accepted: 16 April 2004, Published online: 14 September 2004Edited by: J. Gehrke and J. Hellerstein.Sumit Ganguly: sganguly@cse.iitk.ac.in Current affiliation: Department of Computer Science and Engineering, Indian Institute of Technology, Kanpur, India     

On periodic resource scheduling for continuous-media databases

The Enhanced Pay-Per-View (EPPV) model for providing continuous-media services associates with each continuous-media clip a display frequency that depends on the clip's popularity. The aim is to increase the number of clients that can be serviced concurrently beyond the capacity limitations of available resources, while guaranteeing a constraint on the response time. This is achieved by sharing periodic continuous-media streams among multiple clients. The EPPV model offers a number of advantages over other data-sharing schemes (e.g., batching), which make it more attractive to large-scale service providers. In this paper, we provide a comprehensive study of the resource-scheduling problems associated with supporting EPPV for continuous-media clips with (possibly) different display rates, frequencies, and lengths. Our main objective is to maximize the amount of disk bandwidth that is effectively scheduled under the given data layout and storage constraints. Our formulation gives rise to -hard combinatorial optimization problems that fall within the realm of hard real-time scheduling theory. Given the intractability of the problems, we propose novel heuristic solutions with polynomial-time complexity. We also present preliminary experimental results for the average case behavior of the proposed scheduling schemes and examine how they compare to each other under different workloads. A major contribution of our work is the introduction of a robust scheduling framework that, we believe, can provide solutions for a variety of realistic EPPV resource-scheduling scenarios, as well as any scheduling problem involving regular, periodic use of a shared resource. Based on this framework, we propose various interesting research directions for extending the results presented in this paper. Received June 9, 1998 / Accepted October 13, 1998     

Development of an innovative information system: a fish identification e-key with update capabilities

A dichotomous identification key organizes fishes based on their similarities and differences, and is an essential tool in which ichthyologists, biologists, fishery biologists and others can use for accurate identification of specimens or finding information on correct names, biology and distribution of species. This research work focuses on the development and implementation of a totally new information system that is able to identify correctly fish species names. The developed system is a fully interactive fish identification e-key, which can be used in both forms; locally and remotely via the World Wide Web. This new dichotomous classification e-key provides the capability to identify any species in a compact and easy to use environment, which gives the user excellent operation capabilities and complete information about all included fish species. Moreover, the application provides the capability to search for a random fish species and to show a list which includes all the fish species that currently exist in the application's database. There is an extra attribute that makes the new system novel, and this is its expandability: the information system is fully dynamic having the capability to be extended every time a new species is identified. This attribute is innovative because, until now, there is not any fish identification e-key that gives the user the capability to insert new fish species into the application's database.     

Approximate query processing using wavelets

Approximate query processing has emerged as a cost-effective approach for dealing with the huge data volumes and stringent response-time requirements of today's decision support systems (DSS). Most work in this area, however, has so far been limited in its query processing scope, typically focusing on specific forms of aggregate queries. Furthermore, conventional approaches based on sampling or histograms appear to be inherently limited when it comes to approximating the results of complex queries over high-dimensional DSS data sets. In this paper, we propose the use of multi-dimensional wavelets as an effective tool for general-purpose approximate query processing in modern, high-dimensional applications. Our approach is based on building wavelet-coefficient synopses of the data and using these synopses to provide approximate answers to queries. We develop novel query processing algorithms that operate directly on the wavelet-coefficient synopses of relational tables, allowing us to process arbitrarily complex queries entirely in the wavelet-coefficient domain. This guarantees extremely fast response times since our approximate query execution engine can do the bulk of its processing over compact sets of wavelet coefficients, essentially postponing the expansion into relational tuples until the end-result of the query. We also propose a novel wavelet decomposition algorithm that can build these synopses in an I/O-efficient manner. Finally, we conduct an extensive experimental study with synthetic as well as real-life data sets to determine the effectiveness of our wavelet-based approach compared to sampling and histograms. Our results demonstrate that our techniques: (1) provide approximate answers of better quality than either sampling or histograms; (2) offer query execution-time speedups of more than two orders of magnitude; and (3) guarantee extremely fast synopsis construction times that scale linearly with the size of the data. Received: 7 August 2000 / Accepted: 1 April 2001 Published online: 7 June 2001     

An adaptive RFID middleware for supporting metaphysical data independence

Sensor devices produce data that are unreliable, low-level, and seldom able to be used directly by applications. In this paper, we propose metaphysical data independence (MDI), a layer of independence that shields applications from the challenges that arise when interacting directly with sensor devices. The key philosophy behind MDI is that applications do not deal with any aspect of physical device data, but rather interface with a high-level reconstruction of the physical world created by a sensor infrastructure. As a concrete instantiation of MDI in such a sensor infrastructure, we detail MDI-SMURF, a Radio Frequency Identification (RFID) middleware system that alleviates issues associated with using RFID data through adaptive techniques based on a novel statistical framework. Met·a·phys·ics: A division of philosophy that is concerned with the fundamental nature of reality and being [2].     

Finite element optimal design of transverse web frames

The objective of this paper is to propose an intergrated computerized method aimed at the structural design of web frames subjected to symmetrical loading.The design problem is approached by a three phase procedure employing the finite element method as an analysis strategy and mathematical programming techniques for the synthesis phase.The change of boundary conditions during the optimization is accounted for by an approximate method.