Monitoring of ochratoxin a exposure of the Portuguese population through a nationwide urine survey — winter 2007

Ochratoxin A (OTA) is a mycotoxin produced by a variety of fungi, such as Penicillium verrucosum and Aspergillium spp., which has been found to have a wide number of potentially deadly toxic effects, and can enter the human organism through a variety of means. It then finds its way into the bloodstream and, after a lengthy process, is eventually excreted through the urine. It can thus be detected in its original form not only in blood samples but also in this biological medium. As such, and in an attempt to evaluate the exposure of the Portuguese population to this mycotoxin, morning urine samples were collected during the Winter of 2007, from each of five geographically distinct Portuguese locations — Bragança, Porto, Coimbra, Alentejo, and Algarve — and subjected to extraction by immunoaffinity columns and to OTA quantification through liquid chromatography coupled with fluorescence detection. Prevalent incidence was higher than 95% with Coimbra being the exception (incidence of 73.3%). In nearly all locations, the OTA content of most samples was found to be above the limit of quantification (LOQ) of 0.008 ng/ml. Indeed, excluding Coimbra, with an OTA content level of 0.014 ng/ml, all regions featured content values over 0.021 ng/ml.

SHõWA: A Self-healing Framework for Web-based Applications

The complexity of systems is considered an obstacle to the progress of the IT industry. Autonomic computing is presented as the alternative to cope with the growing complexity. It is a holistic approach, in which the systems are able to configure, heal, optimize, and protect by themselves. Web-based applications are an example of systems where the complexity is high. The number of components, their interoperability, and workload variations are factors that may lead to performance failures or unavailability scenarios. The occurrence of these scenarios affects the revenue and reputation of businesses that rely on these types of applications. In this article, we present a self-healing framework for Web-based applications (SHõWA). SHõWA is composed by several modules, which monitor the application, analyze the data to detect and pinpoint anomalies, and execute recovery actions autonomously. The monitoring is done by a small aspect-oriented programming agent. This agent does not require changes to the application source code and includes adaptive and selective algorithms to regulate the level of monitoring. The anomalies are detected and pinpointed by means of statistical correlation. The data analysis detects changes in the server response time and analyzes if those changes are correlated with the workload or are due to a performance anomaly. In the presence of per- formance anomalies, the data analysis pinpoints the anomaly. Upon the pinpointing of anomalies, SHõWA executes a recovery procedure. We also present a study about the detection and localization of anomalies, the accuracy of the data analysis, and the performance impact induced by SHõWA. Two benchmarking applications, exercised through dynamic workloads, and different types of anomaly were considered in the study. The results reveal that (1) the capacity of SHõWA to detect and pinpoint anomalies while the number of end users affected is low; (2) SHõWA was able to detect anomalies without raising any false alarm; and (3) SHõWA does not induce a significant performance overhead (throughput was affected in less than 1%, and the response time delay was no more than 2 milliseconds).