Current status, uncertainty and future needs in soil organic carbon monitoring

Increasing human demands on soil-derived ecosystem services requires reliable data on global soil resources for sustainable development. The soil organic carbon (SOC) pool is a key indicator of soil quality as it affects essential biological, chemical and physical soil functions such as nutrient cycling, pesticide and water retention, and soil structure maintenance. However, information on the SOC pool, and its temporal and spatial dynamics is unbalanced. Even in well-studied regions with a pronounced interest in environmental issues information on soil carbon (C) is inconsistent. Several activities for the compilation of global soil C data are under way. However, different approaches for soil sampling and chemical analyses make even regional comparisons highly uncertain. Often, the procedures used so far have not allowed the reliable estimation of the total SOC pool, partly because the available knowledge is focused on not clearly defined upper soil horizons and the contribution of subsoil to SOC stocks has been less considered. Even more difficult is quantifying SOC pool changes over time. SOC consists of variable amounts of labile and recalcitrant molecules of plant, and microbial and animal origin that are often operationally defined. A comprehensively active soil expert community needs to agree on protocols of soil surveying and lab procedures towards reliable SOC pool estimates. Already established long-term ecological research sites, where SOC changes are quantified and the underlying mechanisms are investigated, are potentially the backbones for regional, national, and international SOC monitoring programs. © 2013 Elsevier B.V.

AC Biosusceptometry as a Tool for Monitoring the Gastrointestinal Transit of Multiparticulate Drug Delivery System

Drug delivery systems based on natural polysaccharides, such as chitosan (CS) and pectin (PC), rather than on synthetic polymers, have been widely studied. Some reasons for that are low toxicity and costs and high biodegradability of the formers. A multiparticulate system based on CS and PC was developed in our laboratories, including the addition of an enteric polymer, cellulose acetate phtalate (CAP). Such improvement promoted stronger gastric and enteric resistances, as assessed in vitro, making the systems more selective to enzymatic degradation in the colon. Although in vitro dissolution tests can simulate some properties concerning the gastrointestinal transit (GT), collaborating to characterize the systems behavior in the biological fluids, frequently they do not result in satisfactory in vitro/in vivo correlations. The objective of this work was to follow in vivo the GT of the particles developed by means of AC biosusceptometry (ACB), a non-invasive and of low cost methodology. The particles containing ferrite in powder form were prepared by complex coacervation using an ideal 3:1:1 mass ratio for PC:CS:CAP. The magnetic particles were administered to healthy volunteers by oral route. The GT was monitored by using multi-sensor ACB system and the signal acquisition was performed every IS min until the colonic region was reached. By means of ACB technique, it was possible to acquiring images generated by the magnetic particles within the whole gastrointestinal tract including the colonic region. Variable particles transit times were observed among the volunteers, but without interference on the mapping of the particles until the colonic region. The particles were able to produce magnetic field strong enough to generate signals adequate for mapping the particles. The results suggest that integral particles reached the colon, after they resisted against gastric and enteric media. Studies associating transit time and in vivo drug release are in development in order to confirm the efficiency of the systems.

A framework for monitoring and runtime recovery of web service-based applications

Service provisioning is a challenging research area for the design and implementation of autonomic service-oriented software systems. It includes automated QoS management for such systems and their applications. Monitoring, Diagnosis and Repair are three key features of QoS management. This work presents a self-healing Web service-based framework that manages QoS degradation at runtime. Our approach is based on proxies. Proxies act on meta-level communications and extend the HTTP envelope of the exchanged messages with QoS-related parameter values. QoS Data are filtered over time and analysed using statistical functions and the Hidden Markov Model. Detected QoS degradations are handled with proxies. We experienced our framework using an orchestrated electronic shop application (FoodShop).

In-process grinding monitoring by acoustic emission

This work aims to investigate the efficiency of digital signal processing tools of acoustic emission signals in order to detect thermal damages in grinding process. To accomplish such a goal, an experimental work was carried out for 15 runs in a surface grinding machine operating with an aluminum oxide grinding wheel and ABNT 1045. The acoustic emission signals were acquired from a fixed sensor placed on the workpiece holder. A high sampling rate data acquisition system at 2.5 MHz was used to collect the raw acoustic emission instead of root mean square value usually employed. Many statistics have shown effective to detect burn, such as the root mean square (RMS), correlation of the AE, constant false alarm (CFAR), ratio of power (ROP) and mean-value deviance (MVD). However, the CFAR, ROP, Kurtosis and correlation of the AE have been presented more sensitive than the RMS.

A new chart based on sample variances for monitoring the covariance matrix of multivariate processes

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

The Synthetic Control Chart Based on Two Sample Variances for Monitoring the Covariance Matrix

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Control charts for monitoring the mean vector and the covariance matrix of bivariate processes

In this article, we propose new control charts for monitoring the mean vector and the covariance matrix of bivariate processes. The traditional tools used for this purpose are the T (2) and the |S| charts. However, these charts have two drawbacks: (1) the T (2) and the |S| statistics are not easy to compute, and (2) after a signal, they do not distinguish the variable affected by the assignable cause. As an alternative to (1), we propose the MVMAX chart, which only requires the computation of sample means and sample variances. As an alternative to (2), we propose the joint use of two charts based on the non-central chi-square statistic (NCS statistic), named as the NCS charts. Once the NCS charts signal, the user can immediately identify the out-of-control variable. In general, the synthetic MVMAX chart is faster than the NCS charts and the joint T (2) and |S| charts in signaling processes disturbances.

Real-time multi-sensors measurement system with temperature effects compensation for impedance-based structural health monitoring

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Adaptive filter feature identification for structural health monitoring in an aeronautical panel

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Structural Health Monitoring in Smart Structures Through Time Series Analysis

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Ambulatory blood pressure monitoring in children with obstructive sleep apnea and primary snoring

Objective: To evaluate the systemic blood pressure (BP) during daytime and nighttime in children with sleep breathing disorders (SBD) and compare parameters of BP in children with diagnosis of obstructive sleep apnea syndrome (OSA) to those one with primary snoring (PS).Methods: Children, both genders, aged from 8 to 12 years, with symptoms of SBD realized an overnight polysomnography followed by a 24 h recording of ambulatory BP.Results: All subjects presented with a history of snoring 7 nights per week. Children who have apnea/hipoapnea index >= four or a apnea index >= one presented a mean BP of 93 +/- 7 mmHg and 85 +/- 9 mmHg diurnal and nocturnal respectively whereas children who have a apnea/hipoapnea < four or a apnea index < one presented 90 +/- 7 mmHg and 77 +/- 2 mmHg. Eight children out of fourteen, from OSA group, lost the physiologic nocturnal dipping of the blood pressure. Among OSA children 57% were considered non-dippers. Two (16%) have presented absence of nocturnal dipping among children with primary snoring. The possibility of OSA children loosing physiologic blood pressure dipping was 6.66 higher than the possibilities of patients from PS group.Discussion: Our results indicate that children with sleep apnea syndrome exhibit a higher 24 h blood pressure when compared with those of primary snoring in form of decreased degree of nocturnal dipping and increased levels of diastolic and mean blood pressure, according to previous studies in literature. OSA in children seems to be associated to the development of hypertension or other cardiovascular disease. (C) 2012 Elsevier B.V. All rights reserved.

International conferences on environmental mutagens in human populations - Opportunities, accomplishments and challenges

A major mission for organizing the series of International Conferences on Environmental Mutagens in Human Populations is to bring science and scientists to the sites where the field of environmental health is in developmental stages and environmental health is a serious concern. The mission has been fulfilled in each of the previous conferences that were held in Egypt, Czech Republic, Thailand and Brazil. These conferences have led to significant enhancement of regional scientific expertise from the acquisition of scientific knowledge and from the generation of sustainable collaborative programs. (C) 2003 Elsevier B.V. All rights reserved.

On the efficacy of texture analysis for crowd monitoring

The goal of this work is to assess the efficacy of texture measures for estimating levels of crowd densities ill images. This estimation is crucial for the problem of crowd monitoring. and control. The assessment is carried out oil a set of nearly 300 real images captured from Liverpool Street Train Station. London, UK using texture measures extracted from the images through the following four different methods: gray level dependence matrices, straight lille segments. Fourier analysis. and fractal dimensions. The estimations of dowel densities are given in terms of the classification of the input images ill five classes of densities (very low, low. moderate. high and very high). Three types of classifiers are used: neural (implemented according to the Kohonen model). Bayesian. and an approach based on fitting functions. The results obtained by these three classifiers. using the four texture measures. allowed the conclusion that, for the problem of crowd density estimation. texture analysis is very effective.

An adaptive chart for monitoring the process mean and variance

Traditionally, an (X) over bar chart is used to control the process mean and an R chart is used to control the process variance. However, these charts are not sensitive to small changes in the process parameters. The adaptive ($) over bar and R charts might be considered if the aim is to detect small disturbances. Due to the statistical character of the joint (X) over bar and R charts with fixed or adaptive parameters, they are not reliable in identifing the nature of the disturbance, whether it is one that shifts the process mean, increases the process variance, or leads to a combination of both effects. In practice, the speed with which the control charts detect process changes may be more important than their ability in identifying the nature of the change. Under these circumstances, it seems to be advantageous to consider a single chart, based on only one statistic, to simultaneously monitor the process mean and variance. In this paper, we propose the adaptive non-central chi-square statistic chart. This new chart is more effective than the adaptive (X) over bar and R charts in detecting disturbances that shift the process mean, increase the process variance, or lead to a combination of both effects. Copyright (c) 2006 John Wiley & Sons, Ltd.

Synthetic control chart for monitoring the pprocess mean and variance

In this article, we consider the synthetic control chart with two-stage sampling (SyTS chart) to control the process mean and variance. During the first stage, one item of the sample is inspected; if its value X, is close to the target value of the process mean, then the sampling is interrupted. Otherwise, the sampling goes on to the second stage, where the remaining items are inspected and the statistic T = Sigma [x(i) - mu(0) + xi sigma(0)](2) is computed taking into account all items of the sample. The design parameter is function of X-1. When the statistic T is larger than a specified value, the sample is classified as nonconforming. According to the synthetic procedure, the signal is based on Conforming Run Length (CRL). The CRL is the number of samples taken from the process since the previous nonconforming sample until the occurrence of the next nonconforming sample. If the CRL is sufficiently small, then a signal is generated. A comparative study shows that the SyTS chart and the joint X and S charts with double sampling are very similar in performance. However, from the practical viewpoint, the SyTS chart is more convenient to administer than the joint charts.