A checkpointing-enabled and resource-aware Java Virtual Machine for efficient and robust e-Science applications in grid environments

Object-oriented programming languages presently are the dominant paradigm of application development (e. g., Java,. NET). Lately, increasingly more Java applications have long (or very long) execution times and manipulate large amounts of data/information, gaining relevance in fields related with e-Science (with Grid and Cloud computing). Significant examples include Chemistry, Computational Biology and Bio-informatics, with many available Java-based APIs (e. g., Neobio). Often, when the execution of such an application is terminated abruptly because of a failure (regardless of the cause being a hardware of software fault, lack of available resources, etc.), all of its work already performed is simply lost, and when the application is later re-initiated, it has to restart all its work from scratch, wasting resources and time, while also being prone to another failure and may delay its completion with no deadline guarantees. Our proposed solution to address these issues is through incorporating mechanisms for checkpointing and migration in a JVM. These make applications more robust and flexible by being able to move to other nodes, without any intervention from the programmer. This article provides a solution to Java applications with long execution times, by extending a JVM (Jikes research virtual machine) with such mechanisms. Copyright (C) 2011 John Wiley & Sons, Ltd.

2D PCA-Based localization for mobile robots in unstructured environments

In this paper a new PCA-based positioning sensor and localization system for mobile robots to operate in unstructured environments (e. g. industry, services, domestic ...) is proposed and experimentally validated. The inexpensive positioning system resorts to principal component analysis (PCA) of images acquired by a video camera installed onboard, looking upwards to the ceiling. This solution has the advantage of avoiding the need of selecting and extracting features. The principal components of the acquired images are compared with previously registered images, stored in a reduced onboard image database, and the position measured is fused with odometry data. The optimal estimates of position and slippage are provided by Kalman filters, with global stable error dynamics. The experimental validation reported in this work focuses on the results of a set of experiments carried out in a real environment, where the robot travels along a lawn-mower trajectory. A small position error estimate with bounded co-variance was always observed, for arbitrarily long experiments, and slippage was estimated accurately in real time.

On the assessment of exposure to airborne ultrafine particles in urban environments

The aim of this study was to contribute to the assessment of exposure levels of ultrafine particles in the urban environment of Lisbon, Portugal, due to automobile traffic, by monitoring lung deposited alveolar surface area (resulting from exposure to ultrafine particles) in a major avenue leading to the town center during late spring, as well as in indoor buildings facing it. Data revealed differentiated patterns for week days and weekends, consistent with PM2.5 and PM10 patterns currently monitored by air quality stations in Lisbon. The observed ultrafine particulate levels may be directly correlated with fluxes in automobile traffic. During a typical week, amounts of ultrafine particles per alveolar deposited surface area varied between 35 and 89.2 μm2/cm3, which are comparable with levels reported for other towns in Germany and the United States. The measured values allowed for determination of the number of ultrafine particles per cubic centimeter, which are comparable to levels reported for Madrid and Brisbane. In what concerns outdoor/indoor levels, we observed higher levels (32 to 63%) outdoors, which is somewhat lower than levels observed in houses in Ontario.

Monitorization of alveolar deposited surface area of nanoparticles and ultrafine particles in different environments

Nanotechnology is an important emerging industry with a projected annual market of around one trillion dollars by 2015. It involves the control of atoms and molecules to create new materials with a variety of useful functions. Although there are advantages on the utilization of these nano-scale materials, questions related with its impact over the environment and human health must be addressed too, so that potential risks can be limited at early stages of development. At this time, occupational health risks associated with manufacturing and use of nanoparticles are not yet clearly understood. However, workers may be exposed to nanoparticles through inhalation at levels that can greatly exceed ambient concentrations. Current workplace exposure limits are based on particle mass, but this criteria could not be adequate in this case as nanoparticles are characterized by very large surface area, which has been pointed out as the distinctive characteristic that could even turn out an inert substance into another substance exhibiting very different interactions with biological fluids and cells. Therefore, it seems that, when assessing human exposure based on the mass concentration of particles, which is widely adopted for particles over 1 μm, would not work in this particular case. In fact, nanoparticles have far more surface area for the equivalent mass of larger particles, which increases the chance they may react with body tissues. Thus, it has been claimed that surface area should be used for nanoparticle exposure and dosing. As a result, assessing exposure based on the measurement of particle surface area is of increasing interest. It is well known that lung deposition is the most efficient way for airborne particles to enter the body and cause adverse health effects. If nanoparticles can deposit in the lung and remain there, have an active surface chemistry and interact with the body, then, there is potential for exposure. It was showed that surface area plays an important role in the toxicity of nanoparticles and this is the metric that best correlates with particle-induced adverse health effects. The potential for adverse health effects seems to be directly proportional to particle surface area. The objective of the study is to identify and validate methods and tools for measuring nanoparticles during production, manipulation and use of nanomaterials.

On the assessment of exposure to airborne ultrafine particles in urban environments

The aim of this study was to contribute to the assessment of exposure levels of ultrafine particles in the urban environment of Lisbon, Portugal, due to automobile traffic, by monitoring lung deposited alveolar surface area (resulting from exposure to ultrafine particles) in a major avenue leading to the town center during late spring, as well as in indoor buildings facing it. Data revealed differentiated patterns for week days and weekends, consistent with PM2.5 and PM10 patterns currently monitored by air quality stations in Lisbon. The observed ultrafine particulate levels may be directly correlated with fluxes in automobile traffic. During a typical week, amounts of ultrafine particles per alveolar deposited surface area varied between 35 and 89.2 mu m2/cm3, which are comparable with levels reported for other towns in Germany and the United States. The measured values allowed for determination of the number of ultrafine particles per cubic centimeter, which are comparable to levels reported for Madrid and Brisbane. In what concerns outdoor/indoor levels, we observed higher levels (32 to 63%) outdoors, which is somewhat lower than levels observed in houses in Ontario.