A system of systems engineering approach to design new smarter and energy efficient products

The concept of smartness of energy efficient products and systems from a business perspective has been investigated by several authors. The problem of understanding, designing, engineering and governing these technologies requires new concepts. The emergence of these modern technologies causes a myriad of interconnected systems, which are working together to satisfy the necessities of modern life. The problem of understanding, designing, engineering, and governing these technologies requires new concepts. Development of System of System Engineering (SoSE) is an attempt by the systems engineering and science community to fulfill this requirement.

Escherichia coli exhibits negative chemotaxis in gradients of hydrogen peroxide, hypochlorite, and N-chlorotaurine: products of the respiratory burst of phagocytic cells.

Escherichia coli can respond to gradients of specific compounds, moving up gradients of attractants and down gradients of repellents. Stimulated phagocytic leukocytes produce H2O2, OCl-, and N-chlorotaurine in a response termed the respiratory burst. E. coli is actively repelled by these compounds. Catalase in the suspending medium eliminated the effect of H2O2. Repulsion by H2O2 could be demonstrated with 1 microM H2O2, which is far below the level that caused overt toxicity. Strains with defects in the biosynthesis of glutathione or lacking hydroperoxidases I and II retained this response to H2O2, and 2.0 mM CN- did not interfere with it. Mutants with defects in any one of the four known methyl-accepting chemotaxis proteins also retained the ability to respond to H2O2, but a "gutted" mutant that was deleted for all four methyl-accepting chemotaxis proteins, as well as for CheA, CheW, CheR, CheB, CheY, and CheZ, did not respond to H2O2. Hypochlorite and N-chlorotaurine were also strongly repellent. Chemotaxis down gradients of H2O2, OCl-, and N-chlorotaurine may contribute to the survival of commensal or pathogenic microorganisms.

Real time optimization in chemical process: evaluation of strategies, improvements and industrial application.

The increasing economic competition drives the industry to implement tools that improve their processes efficiencies. The process automation is one of these tools, and the Real Time Optimization (RTO) is an automation methodology that considers economic aspects to update the process control in accordance with market prices and disturbances. Basically, RTO uses a steady-state phenomenological model to predict the process behavior, and then, optimizes an economic objective function subject to this model. Although largely implemented in industry, there is not a general agreement about the benefits of implementing RTO due to some limitations discussed in the present work: structural plant/model mismatch, identifiability issues and low frequency of set points update. Some alternative RTO approaches have been proposed in literature to handle the problem of structural plant/model mismatch. However, there is not a sensible comparison evaluating the scope and limitations of these RTO approaches under different aspects. For this reason, the classical two-step method is compared to more recently derivative-based methods (Modifier Adaptation, Integrated System Optimization and Parameter estimation, and Sufficient Conditions of Feasibility and Optimality) using a Monte Carlo methodology. The results of this comparison show that the classical RTO method is consistent, providing a model flexible enough to represent the process topology, a parameter estimation method appropriate to handle measurement noise characteristics and a method to improve the sample information quality. At each iteration, the RTO methodology updates some key parameter of the model, where it is possible to observe identifiability issues caused by lack of measurements and measurement noise, resulting in bad prediction ability. Therefore, four different parameter estimation approaches (Rotational Discrimination, Automatic Selection and Parameter estimation, Reparametrization via Differential Geometry and classical nonlinear Least Square) are evaluated with respect to their prediction accuracy, robustness and speed. The results show that the Rotational Discrimination method is the most suitable to be implemented in a RTO framework, since it requires less a priori information, it is simple to be implemented and avoid the overfitting caused by the Least Square method. The third RTO drawback discussed in the present thesis is the low frequency of set points update, this problem increases the period in which the process operates at suboptimum conditions. An alternative to handle this problem is proposed in this thesis, by integrating the classic RTO and Self-Optimizing control (SOC) using a new Model Predictive Control strategy. The new approach demonstrates that it is possible to reduce the problem of low frequency of set points updates, improving the economic performance. Finally, the practical aspects of the RTO implementation are carried out in an industrial case study, a Vapor Recompression Distillation (VRD) process located in Paulínea refinery from Petrobras. The conclusions of this study suggest that the model parameters are successfully estimated by the Rotational Discrimination method; the RTO is able to improve the process profit in about 3%, equivalent to 2 million dollars per year; and the integration of SOC and RTO may be an interesting control alternative for the VRD process.

Knowledge-Bearing Elites and Industrial Performance in France and Germany. CES Germany & Europe Working Papers, No. 04.5, December 1993

Most comparative studies of public policies for competitiveness focus on the links among public agencies and industrial sectors. This paper argues that the professions---or knowledge-bearing elites-that animate these organizational links are equally significant. For public policies to promote technological advance, the visions and self-images of knowledge-bearing elites are par­ ticularly important. By examining administrative and technical elites in France and Germany in the 1980s, the paper identifies characteristics that enable these elites to implement policy in some cases, but not in others. France's "state-created" elites were well-positioned to initiate and implement large technology projects, such as digitizing the telecommunications network. Germany's state-recognized elites were, by contrast, better positioned to facilitate framework­ oriented programs that aimed at the diffusion of new technologies throughout industry. The linkages among administrative and technical elites also explain why French policymakers had difficulty adapting policy to changing circumstances over time while German policymakers managed in many cases to learn more from previous policy experiences and to adapt subsequent initiatives accordingly.

What TRIPS is and what is is not

For industry people, journalists, activists, lawyers, diplomats, national legislators, and students of the World Trade Organization's Agreement on Trade-related Aspects of Intellectual Property (TRIPS) has awesome proportions. These are magnified by the fact that these groups lack detailed knowledge of either IP as such or international trade law. IP involves a broad spread of academic specialists and practitioners covering heterogeneous complex regimes of patents, copyright, trade marks, design, undisclosed information (trade secrets), and geographical indications. IP, and subsequently TRIPS, is the meeting point of many stakeholders and actors with conflicting interests spread between market aspirations and concepts of public good. In a globalized economy with deep interconnections across sectors, national borders challenged by inchoate technologies, dynamic social stakeholders, and converging technologies, it is fundamental to have a clear and uncluttered understanding of this Agreement. That is because TRIPS impinges on trade in many products of daily life, from pharmaceuticals to entertainment electronics, as well as mitigating and adaptive technologies for climate change and sustainable development. Given its saliency and ubiquity in economic life, TRIPS has often generated misunderstanding and controversy in the public debate. To complicate matters, technical and legal issues at the interface of technology, IP, and trade remain the province of an eclectic band of specialists and on the radar of interest groups with goals on opposite poles.

Hearing: in the matter of the minimum wage recommendations of Special Industry Committee no. 17-A for the silk, rayon, and nylon underwear division and the general division of the needlework and fabricated textile products industry in Puerto Rico, August 29 and 30, 1955.

Mode of access: Internet.

Source assessment : chemical and fertilizer mineral industry : state of the art /

Mode of access: Internet.

An illustrated sketch : St. Paul's Normal and Industrial School, Lawrenceville, Virginia.

Cover title.

Annual coal and non-metallic mineral report with directories of reporting firms for .

Description based on: 1952.

Economic geology of the United States, with briefer mention of foreign mineral products,

"List of authors and works referred to in the text": p. 483-486.

Typing mineral deposits using their grades and tonnages in an artificial neural network

A test of the ability of a probabilistic neural network to classify deposits into types on the basis of deposit tonnage and average Cu, Mo, Ag, Au, Zn, and Pb grades is conducted. The purpose is to examine whether this type of system might serve as a basis for integrating geoscience information available in large mineral databases to classify sites by deposit type. Benefits of proper classification of many sites in large regions are relatively rapid identification of terranes permissive for deposit types and recognition of specific sites perhaps worthy of exploring further. Total tonnages and average grades of 1,137 well-explored deposits identified in published grade and tonnage models representing 13 deposit types were used to train and test the network. Tonnages were transformed by logarithms and grades by square roots to reduce effects of skewness. All values were scaled by subtracting the variable's mean and dividing by its standard deviation. Half of the deposits were selected randomly to be used in training the probabilistic neural network and the other half were used for independent testing. Tests were performed with a probabilistic neural network employing a Gaussian kernel and separate sigma weights for each class (type) and each variable (grade or tonnage). Deposit types were selected to challenge the neural network. For many types, tonnages or average grades are significantly different from other types, but individual deposits may plot in the grade and tonnage space of more than one type. Porphyry Cu, porphyry Cu-Au, and porphyry Cu-Mo types have similar tonnages and relatively small differences in grades. Redbed Cu deposits typically have tonnages that could be confused with porphyry Cu deposits, also contain Cu and, in some situations, Ag. Cyprus and kuroko massive sulfide types have about the same tonnages. Cu, Zn, Ag, and Au grades. Polymetallic vein, sedimentary exhalative Zn-Pb, and Zn-Pb skarn types contain many of the same metals. Sediment-hosted Au, Comstock Au-Ag, and low-sulfide Au-quartz vein types are principally Au deposits with differing amounts of Ag. Given the intent to test the neural network under the most difficult conditions, an overall 75% agreement between the experts and the neural network is considered excellent. Among the largestclassification errors are skarn Zn-Pb and Cyprus massive sulfide deposits classed by the neuralnetwork as kuroko massive sulfides—24 and 63% error respectively. Other large errors are the classification of 92% of porphyry Cu-Mo as porphyry Cu deposits. Most of the larger classification errors involve 25 or fewer training deposits, suggesting that some errors might be the result of small sample size. About 91% of the gold deposit types were classed properly and 98% of porphyry Cu deposits were classes as some type of porphyry Cu deposit. An experienced economic geologist would not make many of the classification errors that were made by the neural network because the geologic settings of deposits would be used to reduce errors. In a separate test, the probabilistic neural network correctly classed 93% of 336 deposits in eight deposit types when trained with presence or absence of 58 minerals and six generalized rock types. The overall success rate of the probabilistic neural network when trained on tonnage and average grades would probably be more than 90% with additional information on the presence of a few rock types.

SubCM: A tool for improved visibility of software change in an industrial setting

Software Configuration Management is the discipline of managing large collections of software development artefacts from which software products are built. Software configuration management tools typically deal with artefacts at fine levels of granularity - such as individual source code files - and assist with coordination of changes to such artefacts. This paper describes a lightweight tool, designed to be used on top of a traditional file-based configuration management system. The add-on tool support enables users to flexibly define new hierarchical views of product structure, independent of the underlying artefact-repository structure. The tool extracts configuration and change data with respect to the user-defined hierarchy, leading to improved visibility of how individual subsystems have changed. The approach yields a range of new capabilities for build managers, and verification and validation teams. The paper includes a description of our experience using the tool in an organization that builds large embedded software systems.

Hydroxide carbonates and oxide carbonate hydrate of rare earths grown on glass via a hydrothermal route

Carbonates of rare-earths, specifically hydroxide carbonate or oxide carbonate hydrate, could be prepared on common glass by a hydrothermal process involving thiourea. Examples presented in this paper include LaOHCO3, CeOHCO3 and EU2O(CO3)(2) . H2O structures formed on glass from solutions of thiourea and the relevant rare-earth reactants. The crystal structure and habit on the substrates were dependent on the preparative conditions; the influence of the concentrations of reactants and temperature on the crystal morphologies is illustrated. Second harmonic generation was found to occur in the crystals. (C) 2004 Elsevier B.V. All rights reserved.