A New Method of Current Switching for Linear Wide-Range Measurement Systems

This new and general method here called overflow current switching allows a fast, continuous, and smooth transition between scales in wide-range current measurement systems, like electrometers. This is achieved, using a hydraulic analogy, by diverting only the overflow current, such that no slow element is forced to change its state during the switching. As a result, this approach practically eliminates the long dead time in low-current (picoamperes) switching. Similar to a logarithmic scale, a composition of n adjacent linear scales, like a segmented ruler, measures the current. The use of a linear wide-range system based on this technique assures fast and continuous measurement in the entire range, without blind regions during transitions and still holding suitable accuracy for many applications. A full mathematical development of the method is given. Several computer realistic simulations demonstrated the viability of the technique.

Analysis of the interplay between knowledge and performance management in industrial clusters

The concept of industrial clustering has been studied in-depth by policy makers and researchers from many fields, mainly due to the competitive advantages it may bring to regional economies. Companies often take part in collaborative initiatives with local partners while also taking advantage of knowledge spillovers to benefit from locating in a cluster. Thus, Knowledge Management (KM) and Performance Management (PM) have become relevant topics for policy makers and cluster associations when undertaking collaborative initiatives. Taking this into account, this paper aims to explore the interplay between both topics using a case study conducted in a collaborative network formed within a cluster. The results show that KM should be acknowledged as a formal area of cluster management so that PM practices can support knowledge-oriented initiatives and therefore make better use of the new knowledge created. Furthermore, tacit and explicit knowledge resulting from PM practices needs to be stored and disseminated throughout the cluster as a way of improving managerial practices and regional strategic direction. Knowledge Management Research & Practice (2012) 10, 368-379. doi:10.1057/kmrp.2012.23

Turbidimetric Spectroscopy for the Evaluation of Metalworking Fluids Stability

The stability of oil-in-water (O/W) emulsions used as metalworking fluids is a key factor for the economical and environmental balance of the entire metalworking process because used and broken fluids must be recycled or disposed. In this study, the ability of turbidimetric spectroscopy in the ultraviolet and visible light range to detect metalworking fluids destabilization was evaluated. Destabilization was achieved by adding calcium chloride, thus achieving accelerated aging, which leads to coalescence, creaming, and complete emulsion separation. The stability of the metalworking fluids at 5% volumetric concentration in deionized water was monitored using a spectroscopic turbidimeter composed of an optical probe for in-line measurements. Destabilization was also monitored by measuring the vertical profile of backscattered and transmitted light. The results of this offline measurement system were compared with those from the in-line spectroscopic sensor, indicating that the latter can provide local, real-time information on emulsion destabilization, thus enabling control actions.

Urban Air Pollutants are Significant Risk Factors for Asthma and Pneumonia in Children: The Influence of Location on the Measurement of Pollutants

Background: Air pollution is associated with a substantial burden on human health; however, the most important pollutants may vary with location. Proper monitoring is necessary to determine the effect of these pollutants on respiratory health. Objectives: This study was designed to evaluate the role of outdoor, indoor and personal exposure to combustion-related pollutants NO2 and O-3 on respiratory health of children in a non-affluent urban area of Sao Paulo, Brazil. Methods: Levels of NO2 and O-3 were continuously measured in outdoor and indoor air, as well as personal exposure, for 30 days using passive measurement monitors. Respiratory health was assessed with a Brazilian version of the ISAAC questionnaire. Results: Complete data were available from 64 children, aged 6-10 years. Respiratory morbidity was high, with 43 (67.2%) reporting having had wheezing at any time, 27 (42.2%) wheezing in the last month, 17 (26.6%) asthma at any time and 21(32.8%) pneumonia at any time. Correlations between levels of NO2 and O-3 measured in the three locations evaluated were poor. Levels of NO2 in indoor air and personal exposure to O-3 were independently associated with asthma (both cases P=.02), pneumonia (O-3, P=.02) and wheezing at any time (both cases P<.01). No associations were seen between outdoor NO2 and O-3 and respiratory health. Conclusions: Exposure to higher levels of NO2 and O-3 was associated with increased risk for asthma and pneumonia in children. Nonetheless, the place where the pollutants are measured influences the results. The measurements taken in indoor and personal exposure were the most accurate. (C) 2012 SEPAR. Published by Elsevier Espana, S.L. All rights reserved.

Stochastic simulation of time-series models combined with geostatistics to predict water-table scenarios in a Guarani Aquifer System outcrop area, Brazil

Stochastic methods based on time-series modeling combined with geostatistics can be useful tools to describe the variability of water-table levels in time and space and to account for uncertainty. Monitoring water-level networks can give information about the dynamic of the aquifer domain in both dimensions. Time-series modeling is an elegant way to treat monitoring data without the complexity of physical mechanistic models. Time-series model predictions can be interpolated spatially, with the spatial differences in water-table dynamics determined by the spatial variation in the system properties and the temporal variation driven by the dynamics of the inputs into the system. An integration of stochastic methods is presented, based on time-series modeling and geostatistics as a framework to predict water levels for decision making in groundwater management and land-use planning. The methodology is applied in a case study in a Guarani Aquifer System (GAS) outcrop area located in the southeastern part of Brazil. Communication of results in a clear and understandable form, via simulated scenarios, is discussed as an alternative, when translating scientific knowledge into applications of stochastic hydrogeology in large aquifers with limited monitoring network coverage like the GAS.