Biofilm adaptation to sulfate reduction in anaerobic immobilized biomass reactors sujected to different COD/sulfate ratios.

Various aspects of biofilm adaptation to sulfate reduction in horizontal-flow anaerobic immobilized biomass (HAIB) reactors subjected to increasing sulfate concentrations and different COD/sulfate ratios are presented and discussed. Four bench-scale HAIB reactors filled with vegetal carbon (R1 and R2) and polyurethane foam matrices (R3 and R4) were utilized. Influent sulfate concentrations ranging from 500 to 3000 mg/L were applied at COD/sulfate ratios ranging from 5.0 to 1.7. Reactors R1 and R4 were operated with higher sulfate loads than those applied to R2 and R3. For the same COD/sulfate ratio, the highest sulfate reduction efficiency (approximately 80%) was displayed by the vegetal carbon reactor (R2) subjected to low sulfate loads. According to the results of our molecular biology analyses, the different support materials provided different biomass colonization conditions. The lowest diversity of sulfate-reducing bacteria was found in the HAIB filled with polyurethane foam matrices operating with high sulfate loads.     

Active Tuning of Intrinsic Camera Parameters

In the last years, the research effort of the scientific community to study systems for ambient intelligence has been really strong. Usually, the systems developed so far base their analysis on images acquired by automatic cameras. In this paper, we propose a way to develop new smart systems that are able to actively decide both what to see and how to see it. In particular, the main idea is to tune the acquisition parameters on the basis of what the system desires to acquire. The regulation strategy is based on two camera parameters, focus and iris. It aims to identify an optimal sequence of steps to enhance the acquisition quality of an object of interest. To this end, a hierarchy of neural networks has been employed first to select which parameter must be regulated then to adjust it. The proposed solution can be applied to both static and moving cameras. The results show how the proposed technique can be applied to images acquired by a moving camera with zoom capabilities for surveillance purposes.     

Invariant feature extraction and neural trees for range surfaceclassification

In this paper, a neural tree-based approach for classifying range images into a set of nonoverlapping regions is presented. An innovative procedure is applied to extract invariant surface features from each pixel of the range image. These features are: 1) robust to noise, and 2) invariant to scale, shift, rotations, curvature variations, and direction of the normal. Then, a generalized neural tree is used to classify each image point as belonging to one of the six surface models of differential geometry, i.e., peak, ridge, valley, saddle, pit, and flat. Comparisons with other methods and experiments on both synthetic and real three-dimensional range images are proposed.     

Morphological and Chemical/Physical Characterization of Fe‐Doped Synthetic Chrysotile Nanotubes

In the field of thin‐layer‐structured inorganic nanotubes, morphological, structural, and chemical/physical modifications induced in synthetic stoichiometric chrysotile nanotubes have been evaluated as a function of the extent of Fe doping. Fe‐doped synthetic chrysotile nanocrystals have been obtained in the range from 0.29 wt.‐% up to 1.37 wt.‐% Fe. A partial Fe replacement for Si and Mg has been observed through the modification of Fourier‐transform infrared (FTIR) absorption bands. FTIR spectroscopic, X‐ray diffraction, and thermogravimetric analyses provide evidence for Fe inclusion into the chrysotile crystal structure, in both octahedral and tetrahedral sites, which induces a flattening of the curved brucite‐like layers in the stoichiometric chrysotile. Further characterization by morphological analysis (scanning electron microscopy, transmission electron microscopy, and atomic force microscopy) has revealed the effect of Fe doping on the aggregation of chrysotile nanotubes. The results appear interesting in light of the proposed possibilities of synthetic chrysotile fibers to represent an alternative to carbon nanotubes for innovative technological applications.     

Enantioselective esterification of ibuprofen with ethanol as reactant and solvent catalyzed by immobilized lipase: experimental and molecular modeling aspects

BACKGROUND: In recent years enantioselective esterification of racemic ibuprofen performed in organic co‐solvent media such as isooctane and cyclohexane and catalyzed by lipases, has been proposed as an effective way to increase the concentration of S‐ibuprofen in the racemic mixture. In this contribution, the enantioselective enzymatic esterification of (R,S)‐ibuprofen with ethanol catalyzed by commercial Novozym 435 without the addition of a co‐solvent is thoroughly investigated. Experimental data are further analyzed considering the results of extensive molecular modeling calculations. RESULTS: The conversion of ibuprofen towards the ethyl esters and the enantiomeric excess towards S‐ibuprofen are greatly affected by the ethanol and water contents of the reaction media. The optimum conditions for the esterification of racemic ibuprofen in a batch‐type reactor were as follows: molar ratio of ethanol to ibuprofen = 7, 4.8% v/v of water, 160 mg of Novozym 435, 45 °C and 200 rpm. Under these conditions an enantiomeric excess of 54% and 63% of ibuprofen conversion were reached. CONCLUSIONS: Results showed that the reaction in excess of the esterifying alcohol in a system free of additional organic solvents is possible if the proper conditions are set. Molecular modeling calculations demonstrated that the formation of dead‐end compounds between the enzyme and ethanol/water may account for lipase inhibition at high concentrations of those compounds. Copyright © 2009 Society of Chemical Industry     

Effects of Integrated Graphical Displays on Situation Awareness in Anaesthesiology

Anaesthetic information displays have been shown to influence anaesthesiologists’ situation awareness. In study 1 an object display was compared with the traditional display currently used. Twelve anaesthesiologists (residents and faculty members) participated in a simulator evaluation of the displays. Reaction times for detection of critical events and situation awareness were measured. The object display improved situation awareness for one of four test scenarios. Low-level situation awareness was higher with the traditional display, and medium-level situation awareness was higher with the new display. In study 2, an integrated 3D display was compared to the traditional display. Twelve students participated in the evaluation. The new 3D display helped the observers to see changes more rapidly. In one scenario, situation awareness was higher with the new display than with the traditional display. In summary, during 63% of the simulated scenarios, reliable differences were found in favour of the new displays. Thus, by introducing integrated graphical displays in the operating room, anaesthesiologists’ performance may be improved.     

Visual correlation of network alerts

The VisAlert visual correlation tool facilitates situational awareness in complex network environments by providing a holistic view of network security to help detect malicious activities. Information visualization techniques and methods in many applications have effectively increased operators' situational awareness, letting them more effectively detect, diagnose, and treat anomalous conditions. Visualization elevates information comprehension by fostering rapid correlation and perceived associations. Our visualization technique integrates the information in log and alert files into an intuitive, flexible, extensible, and scalable visualization tool - VisAlert - that presents critical information concerning network activity in an integrated manner, increasing the user's situational awareness.     

Automatic visual recognition of deformable objects for grasping and manipulation

This paper describes a vision-based system that is able to automatically recognize deformable objects, to estimate their pose, and to select suitable picking points. A hierarchical self-organized neural network is used to segment color images based on texture information. A morphological analysis allows the recognition of the objects and the picking points extraction. The proposed approach is useful in all of the situations where texture properties are significant for detecting regions of interest on deformable objects. Several tests on a large number of images, acquired in real operative working conditions, demonstrate the effectiveness of the system.     

Positivity of pleural fluid cytologic examination in transudative pleural effusions

Because of the increased fragility of a freshly dissected aorta, the anastomosis between the aortic root and a tubular prosthesis is not forgiving of technical imperfections and may lead to troublesome bleeding. Providing an appropriate everting surface of contact and a homogeneous distribution of tension between the graft and aorta, as described here, should help obtain a hemostatic suture line.     

Electrostatic effect of specifically adsorbed electroinactive ions upon electrode processes

The electrostatic effect exerted by specifically adsorbed electroinactive ions upon electrode processes is accounted for by introducing into the Frumkin equation the average potential at the position occupied by the reacting particle in the transition state. The value of this potential is obtained from a simple model of the double layer in the presence of specific ionic adsorption. It is thus shown that the logarithm of the rate constant k_f at constant applied potential is expected to vary linearly with the charge density q_i at the inner Helmholtz plane. Some examples in support to the above theoretical prediction are reported.