Intestinal obstruction and peritoneal carcinomatosis after endoscopic resection of transitional carcinoma of urinary bladder

Gut involvement in bladder tumours is low, even exceptional in the presence of surface, low-grade neoplasia. The authors explain their experience in the diagnosis and management of a patient treated endoscopically for a vesical surface tumour which subsequently exhibited peritoneal and gut metastatic seeding. The various mechanisms for gut dissemination of vesical neoplasias and the repercussion of their endoscopic management are discussed.     

Relationship between the enzymatic determination of starch and the starch iodine index in two varieties of cider apple

Monitoring the hydrolysis or disappearance of starch by the starch iodine test is a simple procedure for determining the maturity of cider apples, but it does not indicate the exact amount of starch present. So far, studies of starch in apples have dealt exclusively with dessert apples. In this paper the relationship between the visual starch index, the dark‐coloured surface area and the real starch content was studied in two varieties of cider apple commonly used in Normandy (France). Starch determination in cider apples required adapting the protocol provided by the Boehringer enzymatic kit. The work led to proposing a simplified index with five scales instead of 10. This index gives the correspondences between the new and old scales as well as the probable starch contents for each new scale. © 2002 Society of Chemical Industry     

Evaluation of messaging middleware for high-performance cloud computing

Cloud computing is posing several challenges, such as security, fault tolerance, access interface singularity, and network constraints, both in terms of latency and bandwidth. In this scenario, the performance of communications depends both on the network fabric and its efficient support in virtualized environments, which ultimately determines the overall system performance. To solve the current network constraints in cloud services, their providers are deploying high-speed networks, such as 10 Gigabit Ethernet. This paper presents an evaluation of high-performance computing message-passing middleware on a cloud computing infrastructure, Amazon EC2 cluster compute instances, equipped with 10 Gigabit Ethernet. The analysis of the experimental results, confronted with a similar testbed, has shown the significant impact that virtualized environments still have on communication performance, which demands more efficient communication middleware support to get over the current cloud network limitations.     

METIS-II: low resource machine translation

METIS-II was an EU-FET MT project running from October 2004 to September 2007, which aimed at translating free text input without resorting to parallel corpora. The idea was to use “basic” linguistic tools and representations and to link them with patterns and statistics from the monolingual target-language corpus. The METIS-II project has four partners, translating from their “home” languages Greek, Dutch, German, and Spanish into English. The paper outlines the basic ideas of the project, their implementation, the resources used, and the results obtained. It also gives examples of how METIS-II has continued beyond its lifetime and the original scope of the project. On the basis of the results and experiences obtained, we believe that the approach is promising and offers the potential for development in various directions.     

Rough set based approaches to feature selection for Case-Based Reasoning classifiers

This paper investigates feature selection based on rough sets for dimensionality reduction in Case-Based Reasoning classifiers. In order to be useful, Case-Based Reasoning systems should be able to manage imprecise, uncertain and redundant data to retrieve the most relevant information in a potentially overwhelming quantity of data. Rough Set Theory has been shown to be an effective tool for data mining and for uncertainty management. This paper has two central contributions: (1) it develops three strategies for feature selection, and (2) it proposes several measures for estimating attribute relevance based on Rough Set Theory. Although we concentrate on Case-Based Reasoning classifiers, the proposals are general enough to be applicable to a wide range of learning algorithms. We applied these proposals on twenty data sets from the UCI repository and examined the impact of feature selection over classification performance. Our evaluation shows that all three proposals benefit the basic Case-Based Reasoning system. They also present robustness in comparison to well-known feature selection strategies.     

F-MPJ: scalable Java message-passing communications on parallel systems

This paper presents F-MPJ (Fast MPJ), a scalable and efficient Message-Passing in Java (MPJ) communication middleware for parallel computing. The increasing interest in Java as the programming language of the multi-core era demands scalable performance on hybrid architectures (with both shared and distributed memory spaces). However, current Java communication middleware lacks efficient communication support. F-MPJ boosts this situation by: (1) providing efficient non-blocking communication, which allows communication overlapping and thus scalable performance; (2) taking advantage of shared memory systems and high-performance networks through the use of our high-performance Java sockets implementation (named JFS, Java Fast Sockets); (3) avoiding the use of communication buffers; and (4) optimizing MPJ collective primitives. Thus, F-MPJ significantly improves the scalability of current MPJ implementations. A performance evaluation on an InfiniBand multi-core cluster has shown that F-MPJ communication primitives outperform representative MPJ libraries up to 60 times. Furthermore, the use of F-MPJ in communication-intensive MPJ codes has increased their performance up to seven times.     

Automatic mapping of parallel applications on multicore architectures using the Servet benchmark suite

Servet is a suite of benchmarks focused on detecting a set of parameters with high influence on the overall performance of multicore systems. These parameters can be used for autotuning codes to increase their performance on multicore clusters. Although Servet has been proved to detect accurately cache hierarchies, bandwidths and bottlenecks in memory accesses, as well as the communication overhead among cores, up to now the impact of the use of this information on application performance optimization has not been assessed. This paper presents a novel algorithm that automatically uses Servet for mapping parallel applications on multicore systems and analyzes its impact on three testbeds using three different parallel programming models: message-passing, shared memory and partitioned global address space (PGAS). Our results show that a suitable mapping policy based on the data provided by this tool can significantly improve the performance of parallel applications without source code modification.     

Characterization and Technological Properties of Lactic Acid Bacteria Isolated from Traditional Argentinean Goat’s Milk Products

A total of 286 lactic acid bacteria isolated from goat’s dairy products in northwest of Argentina were characterized. Lactobacilli (38%) and cocci (62%) were identified according to morphological, physiological, and relevant technological properties. L. plantarum (14%) and Enterococcus (34%) were the predominant species. S. thermophilus, Pediococcus and L. plantarum were the highest acid producers. Eight strains of L. fermentum produced bacteriocins or metabolites similar to bacteriocins. The API-ZYM test was applied to 39 isolates. Eight strains were selected from their both technological properties and enzymatic activities for use as starter or adjunct culture in the manufacture of artisanal goat cheeses.