The effect of pretreatment on the reactivity of Fe-ZSM-5 catalysts for N2O decomposition: Dehydroxylation vs. steaming

The N₂O decomposition activity of the Fe-ZSM-5 catalysts, prepared by chemical vapor deposition (CVD) and aqueous ion exchange (IE), was studied after steaming and high temperature treatment at 1218 K (HT) and compared with the activity of the corresponding non-steamed catalysts after pretreatment at 873 K. FTIR spectra showed that dehydroxylation and/or dealumination took place during steaming and high temperature treatment of the catalysts, which leads to the formation of oxygen vacancies (i.e. lattice defect). These lattice defects leads to a change in electronic properties of the iron sites, which are associated with electron withdrawing Al Lewis centers. The iron sites in close proximity of defects are responsible for the initial higher N₂O decomposition (transient activity) of the steamed and HT catalysts. The increase in steady-state activity over steamed and HT catalysts can be mainly attributed to an increase in the number of active sites created by autoreduction of the iron centers during steaming and high temperature treatment. The above-mentioned trends are valid for both CVD and IE samples.     

Validation of multiparametric MRI by histopathology after nephrectomy: a case study

Magnetic Resonance Materials in Physics, Biology and Medicine - Renal multiparametric MRI (mpMRI) is a promising tool to monitor renal allograft health to enable timely treatment of chronic...     

Automated 3-D PDM construction from segmented images using deformable models

In recent years, several methods have been proposed for constructing statistical shape models to aid image analysis tasks by providing a priori knowledge. Examples include principal component analysis of manually or semiautomatically placed corresponding landmarks on the learning shapes [point distribution models (PDMs)], which is time consuming and subjective. However, automatically establishing surface correspondences continues to be a difficult problem. This paper presents a novel method for the automated construction of three-dimensional PDM from segmented images. Corresponding surface landmarks are established by adapting a triangulated learning shape to segmented volumetric images of the remaining shapes. The adaptation is based on a novel deformable model technique. We illustrate our approach using computed tomography data of the vertebra and the femur. We demonstrate that our method accurately represents and predicts shapes.     

Biosorption of Cu(II) onto agricultural materials from tropical regions

BACKGROUND: In Ghana, the discharge of untreated gold mine wastewater contaminates the aquatic systems with heavy metals such as copper (Cu), threatening ecosystem and human health. The undesirable effects of these pollutants can be avoided by treatment of the mining wastewater prior to discharge. In this work, the sorption properties of agricultural materials, namely coconut shell, coconut husk, sawdust and Moringa oleifera seeds for Cu(II) were investigated. RESULTS: The Freundlich isotherm model described the Cu(II) removal by coconut husk (R² = 0.999) and sawdust (R² = 0.993) very well and the Cu(II) removal by Moringa oleifera seeds (R² = 0.960) well. The model only reasonably described the Cu(II) removal by coconut shell (R² = 0.932). A maximum Cu(II) uptake of 53.9 mg g^?1 was achieved using the coconut shell. The sorption of Cu(II) onto coconut shell followed pseudo‐second‐order kinetics (R² = 0.997). FTIR spectroscopy indicated the presence of functional groups in the biosorbents, some of which were involved in the sorption process. SEM‐EDX analysis confirmed an exchange of Mg(II) and K(I) for Cu(II) on Moringa oleifera seeds and K(I) for Cu(II) on coconut shell. CONCLUSION: This study shows that coconut shell can be an important low‐cost biosorbent for Cu(II) removal. The results indicate that ion exchange, precipitation and electrostatic forces were involved in the Cu(II) removal by the biosorbents investigated. Copyright © 2011 Society of Chemical Industry     

A simulation methodology for heat and cold distribution in thermo-hydronic networks

This paper presents a simulation methodology to analyze hydronic heat distribution systems in a fast and user friendly way. As suggested in its name, the “Base Circuit Methodology” (BCM) is based on the observation that thermo-hydronic networks can be built up as a modular composition of elementary “Base Circuits” (BCs). Once the hydronic and thermodynamic behavior of such basic components is described in a set of dedicated equations, complex thermal distribution networks can easily be modeled by connecting the basic sub models. In addition to control performance simulations (accuracy, stability, speed) the BCM puts extra effort into energy efficiency analysis. In fact, every BC is a local sub unit in which heat flows are gathered, divided or changed in terms of temperature and/or flow. Therefore the BCM model setup yields the opportunity to analyze the net heat transport and its adaptations while crossing the network. Doing so, system designers get the efficiency variables more structured, leading to straightforward abilities to optimize heat and cold distribution. Practical examples prove the benefits of the methodology. Moreover, a test installation was built in which flows, pressures, and temperatures are confronted with the simulation results. The simulations are processed by means of the iterative equation solver EES (Engineering Equation Solver; ©F-chart) which has been experienced as a very compliant software package. As a result the methodology is delivered as a validated and open source library.     

Isolation of novel homopolysaccharide-producing lactic acid bacteria from Romanian raw milk and fermented dairy products

Traditionally fermented foods can be a rich source of diverse lactic acid bacteria (LAB) with interesting functional properties, such as exopolysaccharide (EPS) production. The objectives of this study were to map the mucoid and/or ropy LAB isolated from raw milk and traditionally fermented dairy products, collected in different regions of Romania, to study the species diversity within the samples and to further explore the EPS-producing capacity of the isolates. Seventy-three LAB strains were isolated and identified through (GTG)₅-PCR genomic fingerprinting and SDS-PAGE of whole-cell proteins. Lactococcus lactis was the most frequently encountered species, followed by Lactobacillus plantarum, Leuconostoc spp., and Enterococcus spp. Nine strains produced homopolysaccharides (HoPS, glucose monomers), namely L. lactis 1.8; Leuc. citreum 1.10, 1.11, 1.12, 2.8, and 4.11; Leuc. mesenteroides 21.2; Leuc. pseudomesenteroides 20.6; and Weisella confusa/cibaria 38.2, six of them in the concentrations above 10 g/L, both in milk and MRS medium supplemented with sucrose. In all EPS, the glucose constituents were connected by different α-linkages, among which α-1,6-linkages were the most prevalent.     

Ethanol's energy return on investment: a survey of the literature 1990-present

Various authors have reported conflicting values for the energy return on investment (rE) of ethanol manufacture. Energy policy analysts predisposed to or against ethanol frequently cite selections from these studies to supporttheir positions. This literature review takes an objective look at the disagreement by normalizing and comparing the data sets from ten such studies. Six of the reviewed studies treat starch ethanol from corn, and four treat cellulosic ethanol. Each normalized data set is also submitted to a uniform calculation of rEdefined as the total product energy divided by nonrenewable energy input to its manufacture. Defined this way rE > 1 indicates that the ethanol product has nominally captured at least some renewable energy, and rE > 0.76 indicates that it consumes less nonrenewable energy in its manufacture than gasoline. The reviewed corn ethanol studies imply 0.84 < or = rE < or = 1.65; three of the cellulosic ethanol studies imply 4.40 < or = rE < or = 6.61. The fourth cellulosic ethanol study reports rE= 0.69 and may reasonably be considered an outlier.     

Review of current status,requirements and opportunities for building performance simulation of adaptive facades†

Adaptive building envelope systems have the potential of reducing greenhouse gas emissions and improving the energy flexibility of buildings, while maintaining high levels of indoor environmental quality. The development of such innovative materials and technologies, as well as their real-world implementation, can be enhanced with the use of building performance simulation (BPS). Performance prediction of adaptive facades can, however, be a challenging task and the information on this topic is scarce and fragmented. The main contribution of this review article is to bring together and analyse the existing information in this field. In the first part, the unique requirements for successful modelling and simulation of adaptive facades are discussed. In the second part, the capabilities of five widely used BPS tools are reviewed, in terms of their ability to model energy and occupant comfort performance of adaptive facades. Finally, it discusses various ongoing trends and research needs in this field.     

Evidence for hierarchical categorization of coarticulated phonemes.

The reported research investigates how listeners recognize coarticulated phonemes. First, 2 data sets from experiments on the recognition of coarticulated phonemes published by D. H. Whalen (1989) are reanalyzed. The analyses indicate that listeners used categorization strategies involving a hierarchical dependency. Two new experiments are reported investigating the production and perception of fricative–vowel syllables. On the basis of measurements of acoustic cues on a large set of natural utterances, it was predicted that listeners would use categorization strategies involving a dependency of the fricative categorization on the perceived vowel. The predictions were tested in a perception experiment using a 2-dimensional synthetic fricative–vowel continuum. Model analyses of the results pooled across listeners confirmed the predictions. Individual analyses revealed some variability in the categorization dependencies used by different participants. (PsycINFO Database Record (c) 2010 APA, all rights reserved)