Integrated gasification combined cycle and carbon capture: A risky option to mitigate CO2 emissions of coal-fired power plants

The power sectors of many big economies still rely on coal-fired plants and emit huge amounts of carbon dioxide. Emerging countries like Brazil, China and South Africa plan to expand the use of coal-fired thermal plants in the next decade. Integrated gasification combined cycle (IGCC) is an innovative technology that facilitates the implementation of carbon capture (CC). The present work analyzes the maturity and costs of the IGCC technology, with and without CC, and assesses the effect of the technology risk on its economic viability. Findings show that the inclusion of the risk in the economic analysis of IGCC plants raises the cost of CO₂ avoided from 36 US$/t_CO2 to 106 US$/t_CO2 in the case of Shell Gasifiers and from 39 US$/t_CO2 to 112 US$/t_CO2 in the case of GE Gasifiers. Thus, the introduction of IGCC with CC on a wider scale faces huge uncertainties. The feasibility of these plants will rely heavily on the overcoming of the technology risk. Besides, its implementation in the short run will depend on government incentives to bear with the additional cost incurred in the first-generation plants.     

Single stage photofermentative hydrogen production from glucose: An attractive alternative to two stage photofermentation or co-culture approaches

Photosynthetic bacteria have been extensively investigated for biohydrogen production due to their high intrinsic substrate conversion efficiency. Many studies have examined different aspects of photo fermentative hydrogen production using various volatile organic fatty acids under nitrogen limited conditions, and in some cases nearly stoichiometric hydrogen yields have been obtained. In addition, there has been great interest in using photosynthetic bacteria to increase the yields of dark fermentation of glucose through either two stage or co-culture approaches. Although these processes can achieve yields of about 7 mol of H₂ per mole of glucose, there have many drawbacks. Thus, we have begun the systematic investigation of a simple one stage system for the conversion of glucose to hydrogen through photofermentation by Rhodobacter capsulatus. Yields of about 3 mol of H₂ per moles of glucose have been obtained, which represents a yield of 25% yield. Thus improvement is needed and can be sought through a variety of means, including. process optimization and gene inactivation. These approaches could allow the development of a single stage process for the complete stoichiometric conversion of glucose, or glucose containing wastes, to hydrogen with a minimal lag phase and relative insensitivity to inhibition by fixed nitrogen. This would present an attractive simple alternative to either two stage or co-culture fermentations for the complete conversion of carbohydrate substrates to hydrogen.     

Ab initio studies of pristine and oxidized Cu3Au(100) and (111) surfaces

We review the previous literature and our recent work on first-principles studies of Cu₃Au(100) and (111) surfaces, with focus on the segregation of atomic species to the surface at pristine conditions and in the presence of oxygen. In particular, the combined use of experimental and theoretical tools to achieve chemical identification at an atomic level of the surface species is emphasized and discussed.     

Use of student ratings to benchmark universities: Multilevel modeling of responses to the Australian Course Experience Questionnaire (CEQ).

Recently graduated university students from all Australian Universities rate their overall departmental and university experiences (DUEs), and their responses (N = 44,932, 41 institutions) are used by the government to benchmark departments and universities. We evaluate this DUE strategy of rating overall departments and universities rather than individual teachers, and we juxtapose it with the traditional use of student ratings to evaluate individual teachers (SETs). Multilevel analyses of DUE overall ratings were not able to discriminate well between universities or departments—few universities or departments differed significantly from the grand mean. Although the a priori 5-factor structure for this DUE instrument was reasonably well-defined at the individual student level, none of the 5 factors separately or in combination discriminated well between departments or universities. In contrast to this pattern of results, we review studies showing that SETs do reliably differentiate between teachers and are valid in relation to many criteria of effective teaching. However, casual reviews of these research literatures should not use this support for SETs to justify the use of DUE-type strategies. We conclude that DUE-type ratings should be used with great caution, if at all, and should not be seen as an alternative to SETs. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

Fully deformable 3D digital partition model with topological control

We propose a purely discrete deformable partition model for segmenting 3D images. Its main ability is to maintain the topology of the partition during the minimization process. To do so, our main contribution is a new definition of multi-label simple points (ML simple point) that is easily computable. An ML simple point can be relabeled without modifying the overall topology of the partition. The definition is based on intervoxel properties, and uses the notion of collapse on cubical complexes. This work is an extension of a former restricted definition (Dupas et al., 2009) that prohibits the move of intersections of boundary surfaces. A deformation process is carried out with a greedy energy minimization algorithm. A discrete area estimator is used to approach at best standard regularizers classically used in continuous energy minimizing methods. We illustrate the potential of our approach with the segmentation of 3D medical images with known expected topology.     

Structural matching of 2D electrophoresis gels using deformed graphs

2D electrophoresis is a well-known method for protein separation which is extremely useful in the field of proteomics. Each spot in the image represents a protein accumulation and the goal is to perform a differential analysis between pairs of images to study changes in protein content. It is thus necessary to register two images by finding spot correspondences. Although it may seem a simple task, generally, the manual processing of this kind of images is very cumbersome, especially when strong variations between corresponding sets of spots are expected (e.g. strong non-linear deformations and outliers). In order to solve this problem, this paper proposes a new quadratic assignment formulation together with a correspondence estimation algorithm based on graph matching which takes into account the structural information between the detected spots. Each image is represented by a graph and the task is to find a maximum common subgraph. Successful experimental results using real data are presented, including an extensive comparative performance evaluation with ground-truth data.     

Generation of candidates' tree for the fault diagnosis of discrete event systems

This paper presents a discrete event model-based approach for Fault Detection and Isolation of manufacturing systems. This approach considers a system as a set of independent Plant Elements (PEs). Each PE is composed of a set of interrelated Parts of Plant (PoPs) modeled by a Moore automaton. Each PoP model is only aware of its local behavior. The degraded and faulty behaviors are added to each PoP model in order to obtain extended PoP ones. An extrapolation of Gaussian learning is realized to obtain acceptable temporal intervals between the time occurrences of correlated events. Finally based on the PoP extended models and the links between them, a fault candidates' tree is established for each plant element. This candidates' tree corresponds to a local on-line fault event occurrence observer, called diagnoser. Thus, the diagnosis decision is distributed on each plant element. An application example is used to illustrate the approach.     

Application of hazard analysis critical control points system for the control of aflatoxins in the Brazilian groundnut‐based food industry

This study was conducted to identify and assess the critical control points (CCPs) in groundnut‐based food production in southern Brazil in order to reduce or eliminate aflatoxin contamination. This methodology has been suggested by the Food and Agriculture Organization (FAO) of the United Nations. Reception of prime matter, groundnut storage, roasting and thermal treatment were the main CCPs identified. Critical factors were the determination of aflatoxin, moisture content and water activity (A_w) during groundnut reception and storage, control of temperature, roasting time and thermal treatment in the groundnut‐based food manufacturing. The critical limit for moisture was 8.2% and 0.6 was established for A_w. In Brazil, the limit for aflatoxins B₁, B₂, G₁ and G₂ has been established at 20 ppb. Temperatures of 180 °C/1 h and 80 °C/40 min were established for roasting and thermal treatment stages of groundnut‐based food, respectively.