Mapping land-use and land-cover change along Bolivia's Corredor Bioceánico with CBERS and the Landsat series: 1975–2008

This study uses a combination of Landsat series data (Multispectral Scanner or MSS, Thematic Mapper or TM and Enhanced Thematic Mapper or ETM+) to map land-use and land-cover change (LULCC) from 1975 to 2001. It extends the land change record to 2008 using Chinese–Brazil Earth Resources Satellite (CBERS)-2 and CBERS-2B data on a multi-scene level. It also establishes a methodology to correct for systematic distortion inherent in CBERS imagery without the loss of information present in Landsat 7 ETM+ imagery post-2003. Image analysis focuses on a 63 000 km² strip of land along a main highway and railroad in southeastern Bolivia named the Corredor Bioceánico. This strip of land is one of the most important agriculturally driven deforestation hotspots in Latin America. It is also located in one of the most poorly understood forest biomes in the world in terms of LULCC – Southern Hemisphere seasonally dry tropical forests – which have very high conservation values globally. Over the 33-year study period, approximately 12 000 km² of forest was lost among the three sub-regions – which is an area nearly the size of Connecticut. Evidence suggests that agriculture-driven deforestation is pushing into sensitive areas threatening globally important ecosystems such as those in the Chaco, Chiquitano and Pantanal as well as noteworthy protected areas. The results also show that imagery of CBERS-2 and CBERS-2B can help to fill the imagery gap created by Landsat ETM's Scan Line Corrector (SLC) failure in 2003. They can help to extend the land change record forward in time.     

The effect of ISO 9000 implementation on flow management

This study proposes an innovative flow management system that includes product (product and logistics) and process (human, information and decision) flow management. We identify three levels of ISO 9000 implementation (basic, advanced and supportive) as enablers, and operational performance as the outcome. The model was tested using the data-set collected from 133 ISO 9001 certified manufacturing companies in Australia. The results show that advanced implementation is positively related to both product and process flow management; supportive implementation is only positively related to process flow management while basic implementation has no significant effect on either product or process flow management. The results also show that both product and process flow management are positively related to operational performance. This study provides managerial guidelines for companies that wish to improve their innovation capabilities through ISO 9000 implementation and flow management. It also contributes to the ISO 9000 and flow management literature.     

A model for preventive maintenance operations and forecasting

Equipment costs constitute the greatest majority of overall costs for semiconductor manufacturing. Therefore, maintaining high equipment availability has been regarded as one of the major goals in the industry. The ability to forecast correctly equipment preventive maintenance (PM) timing requirements not only can help optimizing equipment uptime but also minimizing negative impacts on manufacturing production efficiency. This research used grey theory and evaluation diagnosis to construct a PM forecasting model for prediction of PM timing of various machines. The results showed significant improvements of PM timing predictions compared to the existing method based on experience and an alternative method proposed by Li and Chang (Semiconductor Manufacturing Technology Workshop 2002: 10–11, pp. 275–277) for the same fab cases. Received: June 2005 / Accepted: December 2005     

Synergistic Computational‐Experimental Approach to Improve Ionene Polymer‐Based Functional Hydrogels

The manifold applications of ionene‐based materials such as hydrogels in daily life, biomedical sciences, and industrial processes are a consequence of their unique physical and chemical properties, which are governed by a judicious balance between multiple non‐covalent interactions. However, one of the most critical aspects identified for a broader use of different polyelectrolytes is the need of raising their gelation efficiency. This work focuses on surfactant‐free ionene polymers 1 ? 3 containing DABCO and N,N′‐(x‐phenylene)dibenzamide (x = ortho‐/meta‐/para‐) linkages as model systems to develop a combined computational‐experimental approach to improve the hydrogelation through a better understanding of the gelation mechanism. Molecular dynamics simulations of isomeric ionenes 1–3 with explicit water molecules point out remarkable differences in the assembly of the polymeric chains in each case. Interchain regions with high degree of hydration (i.e., polymer···water interactions) and zones dominated by polymer···polymer interactions are evident in the case of ortho‐ ( 1 ) and meta‐ ( 2 ) isomeric ionenes, whereas domains controlled by polymer···polymer interactions are practically inexistent in 3 . In excellent agreement, ortho‐ionene 1 provides experimentally the best hydrogels with unique features such as thixotropic behavior and dispersion ability for single‐walles carbon nanotubes.     

Initial Stages in the Metal-dusting Process on Alloy 800

The initial stages of the metal-dusting process on Alloy 800 at 620 °C were investigated by light optical microscopy, RAMAN spectroscopy, atomic-force microscopy, Auger electron spectroscopy, transmission-electron microscopy and electron back-scatter diffraction. As it turned out the incubation period for metal-dusting is characterized by simultaneous formation of a heterogeneously growing oxide scale and deposition of carbon. The material surface shows different tarnish colors depending on the substrate-grain orientation with different susceptibility to the beginning of metal-dusting attack. “Low-index” grains were not attacked within the times investigated while the other grain orientations showed pitting. Carbon is evidently incorporated into the oxide scale from the very beginning of exposure with different intensities depending on the underlying substrate-grain orientation leading to differences in the tarnish colors. As a consequence carbides are formed even underneath “dense” oxide layers. Evidently metal-dusting attack starts at positions of the oxide scale where “higher carbon concentrations” are present.     

Themal spray and adhesive bonding of optical fibres to high-temperature compsie materials

Microstructural characteristic were identified for three surface-mounted optical fibre sensors which were thermal spray bonded to high-temperature composite materials. The primary objective was to determine the defect generation mechanisms that occur during thermal cycling and to make processing and testing recommendations that would optimise the sensor performance. A second objective was to identify areas of microstructural research that would have the most significant impact on the development of high-temperature smart materials. The smart material systems of the present study were comprised of (1) silica optical fibre sessors bonded to titanium matrix composites (TMCs) using a nickel-based thermal spray, (2) silica optical fibre sensors bonded to TMCs using ceramic cement and (3) sapphire optical fibre sensors bonded to titanium matrix composites (TMCs) using a nickel-based thermal spray, (2) silica optical fibre sensors bonded to TMCs using ceramic cement and (3) saphire optical fibre sensors bonded to carbon–carbon composites (CCCs) using ceramic cement. The thermal and prior to any thermal stresscycling. In combination with the non-metallic spheroidal inclusions of the titanium matrix, the microcracking provided a mechanism for disbonding the optical fibres with a subsequent loss of sensor performance. A high degree of kporosity in both systems containing ceramic cements significantly reduced the interfacial bonding area. This, combined with the inherent ceramic brittleness, caused disbonding of the optical fibres in the cemented systems.     

Reduced order modelling and predictive control of multivariable nonlinear process

In this paper, an efficient model-predictive control strategy that can be applied to complex multivariable process is presented. A reduced order generalized predictive algorithm is proposed for online applications with reduction in complexity and time elapsed. The complex multivariable process considered in this work is a binary distillation column. The reduced order model is developed with a recently proposed hybrid algorithm known as Clustering Dominant Pole Algorithm and is able to compute the full set of dominant poles and their cluster centre efficiently. The controller calculates the optimal control action based on the future reference signals, current state and constraints on manipulated and controlled variables for a high-order dynamic simulated model of nonlinear multivariable binary distillation column process. The predictive control algorithm uses controlled auto-regressive integrated moving average model. The performance of constraint generalized predictive control scheme is found to be superior to that of the conventional PID controller in terms of overshoot, settling time and performance indices, mainly ISE, IAE and MSE.     

Stability analysis in spanwise-periodic double-sided lid-driven cavity flows with complex cross-sectional profiles

Three-dimensional linear instability analyses are presented of steady two-dimensional laminar flows in the lid-driven cavity defined by [15] and further analyzed in the present volume [1], as well as in a derivative of the same geometry. It is shown that in both of the geometries considered three-dimensional BiGlobal instability leads to deviation of the flow from the two-dimensional solution; the analysis results are used to define low- and high-Reynolds number solutions by reference to the flow physics. Critical conditions for linear global instability and neutral loops are presented in both geometries.     

Comparative resistance of food proteins to adult and infant in vitro digestion models

IgE‐mediated allergy to milk and egg is widespread in industrialised countries and mainly affects infants and young children. It may be connected to an incomplete digestion of dietary proteins causing an inappropriate immune response in the gut. In order to study this, a biochemical model of infant gastroduodenal digestion has been developed, which has reduced levels of protease (eightfold for pepsin and tenfold for trypsin and chymotrypsin), phosphatidylcholine and bile salts, compared with the adult model. This model has been used to study the behaviour of three characterised food‐relevant proteins (bovine β‐lactoglobulin (β‐Lg), β‐casein (β‐CN) and hen's egg ovalbumin), all of which are relevant cows' milk and hens' egg allergens. Digestion products were characterised using electrophoresis, immunochemical techniques and MS. These showed that ovalbumin and β‐CN were digested more slowly using the infant model compared with the adult conditions. Resistant fragments of β‐CN were found in the infant model, which correspond to previously identified IgE epitopes. Surprisingly, β‐Lg was more extensively degraded in the infant model compared with the adult one. This difference was attributed to the tenfold reduction in phosphatidylcholine concentration in the infant model limiting the protective effect of this phospholipid on β‐Lg digestion.     

Bootstrap Standard Error and Confidence Intervals for the Correlation Corrected for Range Restriction: A Simulation Study.

The standard Pearson correlation coefficient is a biased estimator of the true population correlation, ρ, when the predictor and the criterion are range restricted. To correct the bias, the correlation corrected for range restriction, rc, has been recommended, and a standard formula based on asymptotic results for estimating its standard error is also available. In the present study, the bootstrap standard-error estimate is proposed as an alternative. Monte Carlo simulation studies involving both normal and nonnormal data were conducted to examine the empirical performance of the proposed procedure under different levels of ρ, selection ratio, sample size, and truncation types. Results indicated that, with normal data, the bootstrap standard-error estimate is more accurate than the traditional estimate, particularly with small sample size. With nonnormal data, performance of both estimates depends critically on the distribution type. Furthermore, the bootstrap bias-corrected and accelerated interval consistently provided the most accurate coverage probability for ρ. (PsycINFO Database Record (c) 2010 APA, all rights reserved)