Application of the Rietveld method to assess chromium(VI) speciation in chromite ore processing residue

The Rietveld method allows the quantification of crystalline phases and amorphous material identified by X-ray powder diffraction (XRPD) and other diffraction methods. The method assists in determining the speciation of contaminants in solid matrices both qualitatively and quantitatively in a statistically defensible approach, as it does not focus on a microscale. Rietveld was applied to chromite ore processing residue (COPR), a cementitious waste containing hexavalent chromium. Calcium aluminum chromium oxide hydrates (CACs) were the crystalline phases identified by XRPD that bind Cr(6+) in COPR according to their chemical formula. Rietveld quantification, combined with mass balances on Cr(6+), showed that CACs may bind Cr(6+) in variable percentages, ranging from 25% to 85%. Analysis of duplicate samples showed that material variability is the predominant factor of uncertainty in evaluating the role of CACs in Cr(6+) speciation, provided that a consistent quantification strategy is pursued. The choice of strategy was performed on the basis of the pertinent literature, preliminary analyses of the equipment and the software settings, and mass balances. The correlation between the average CAC-bound Cr(6+) concentration and the total Cr(6+) for five samples (R(2)=0.94), extracted from different zones and soil borings, suggests that CACs are a primary sink for Cr(6+) in COPR.     

Development of surrogate models for the prediction of the flow around an aircraft propeller

In the present work, the derivation of two surrogate models (SMs) for modelling the flow around a propeller for small aircrafts is presented. Both methodologies use derived functions based on computations with the detailed propeller geometry. The computations were performed using k–ω shear stress transport for modelling turbulence. In the SMs, the modelling of the propeller was performed in a computational domain of disk-like geometry, where source terms were introduced in the momentum equations. In the first SM, the source terms were polynomial functions of swirl and thrust, mainly related to the propeller radius. In the second SM, regression analysis was used to correlate the source terms with the velocity distribution through the propeller. The proposed SMs achieved faster convergence, in relation to the detail model, by providing also results closer to the available operational data. The regression-based model was the most accurate and required less computational time for convergence.     

Stress in interactive applications: analysis of the valence-arousal space based on physiological signals and self-reported data

Measuring users’ emotional reaction to interactive multimedia and hypermedia is important. One particularly popular self-reported method for emotion assessment is the Valence-Arousal (VA) Scale: a 9?×?9 affective grid. This paper aims to identify specific stress region(s) in the VA space by combining self-reported ratings (pairs of VA) and physiological signals (skin conductance). To this end, 31 healthy volunteers participated in an experiment by performing five stressful interaction tasks while their skin conductance was monitored. The selected interaction tasks were most frequently listed as stressful by a separate group of 15 interviewees. After each task, participants expressed their perceived emotional experience using the VA rating space. Our findings show which regions in the VA rating space may reliably indicate self-reported stress that is in alignment with one’s measured skin conductance while using interactive applications. One additional important contribution of this work is the proposed approach for the empirical identification of affect regions in the VA space based on physiological signals.     

Infrastructure,automation and model-based operation strategy in a stand-alone hydrolytic solar-hydrogen production unit

An autonomous power system that exploits solar energy for the production of hydrogen through water electrolysis is fully assessed in terms of system implementation and optimal operating strategy. A 10 kW_p photovoltaic array supplies energy to a PEM electrolyzer rated at 6.9 kW_p. In order to maintain a smooth operation regardless of the inherent weather fluctuations, a 1000 Ah/24 V lead–acid accumulator stores energy excess and provides it when needed. The monitoring and control of the system is implemented through a Supervisory Control and Data Acquisition system (SCADA), while the interactions between electrical and chemical subsystems are addressed by a complete automation infrastructure. The mathematical models of each subsystem are validated based on real operational data and a model-based power management strategy is proposed and assessed through a parameter sensitivity analysis. Further on, an off-line optimization framework is evaluated regarding the optimal operation of the system in two diverse, but representative time periods. The optimal parameters are identified and their effect on hydrogen production and accumulator utilization is reported.     

Grammatical Evolution for Features of Epileptic Oscillations in Clinical Intracranial Electroencephalograms

This paper presents grammatical evolution (GE) as an approach to select and combine features for detecting epileptic oscillations within clinical intracranial electroencephalogram (iEEG) recordings of patients with epilepsy. Clinical iEEG is used in preoperative evaluations of a patient who may have surgery to treat epileptic seizures. Literature suggests that pathological oscillations may indicate the region(s) of brain that cause epileptic seizures, which could be surgically removed for therapy. If this presumption is true, then the effectiveness of surgical treatment could depend on the effectiveness in pinpointing critically diseased brain, which in turn depends on the most accurate detection of pathological oscillations. Moreover, the accuracy of detecting pathological oscillations depends greatly on the selected feature(s) that must objectively distinguish epileptic events from average activity, a task that visual review is inevitably too subjective and insufficient to resolve. Consequently, this work suggests an automated algorithm that incorporates grammatical evolution (GE) to construct the most sufficient feature(s) to detect epileptic oscillations within the iEEG of a patient. We estimate the performance of GE relative to three alternative methods of selecting or combining features that distinguish an epileptic gamma (~65-95 Hz) oscillation from normal activity: forward sequential feature-selection, backward sequential feature-selection, and genetic programming. We demonstrate that a detector with a grammatically evolved feature exhibits a sensitivity and selectivity that is comparable to a previous detector with a genetically programmed feature, making GE a useful alternative to designing detectors.     

Industrial growth, economic integration and structural change: evidence from the EU new member-states regions

The article evaluates the pre-accession experience of new European Union member-states, coming from the former Eastern bloc, estimating an empirical model used to account for regional–industrial employment growth in the early transition period, 1991–2000. The results obtained indicate the adverse impact of the economic integration dynamics and detect the interplay among structural characteristics and geographical coordinates that determines the relative winners. The findings of the article have important implications for both theory and policy.     

Human Motion Planning Based on Recursive Dynamics and Optimal Control Techniques

This paper presents an efficient optimal control and recursive dynamics-based computer animation system for simulating and controlling themotion of articulated figures. A quasi-Newton nonlinear programmingtechnique (super-linear convergence) is implemented to solve minimumtorque-based human motion-planning problems. The explicit analyticalgradients needed in the dynamics are derived using a matrix exponentialformulation and Lie algebra. Cubic spline functions are used to make thesearch space for an optimal solution finite. Based on our formulations,our method is well conditioned and robust, in addition to beingcomputationally efficient. To better illustrate the efficiency of ourmethod, we present results of natural looking and physically correcthuman motions for a variety of human motion tasks involving open andclosed loop kinematic chains.     

Aerosol lidar intercomparison in the framework of the EARLINET project. 1. Instruments

In the framework of the European Aerosol Research Lidar Network to Establish an Aerosol Climatology (EARLINET), 19 aerosol lidar systems from 11 European countries were compared. Aerosol extinction or backscatter coefficient profiles were measured by at least two systems for each comparison. Aerosol extinction coefficients were derived from Raman lidar measurements in the UV (351 or 355 nm), and aerosol backscatter profiles were calculated from pure elastic backscatter measurements at 351 or 355, 532, or 1064 nm. The results were compared for height ranges with high and low aerosol content. Some systems were additionally compared with sunphotometers and starphotometers. Predefined maximum deviations were used for quality control of the results. Lidar systems with results outside those limits could not meet the quality assurance criterion. The algorithms for deriving aerosol backscatter profiles from elastic lidar measurements were tested separately, and the results are described in Part 2 of this series of papers [Appl. Opt. 43, 977-989 (2004)]. In the end, all systems were quality assured, although some had to be modified to improve their performance. Typical deviations between aerosol backscatter profiles were 10% in the planetary boundary layer and 0.1 x 10(-6) m(-1) sr(-1) in the free troposphere.     

Combining low-, high-level and empirical domain knowledge for automated segmentation of ultrasonic breast lesions

Breast cancer is the most frequently diagnosed malignancy and the second leading cause of mortality in women. In the last decade, ultrasound along with digital mammography has come to be regarded as the gold standard for breast cancer diagnosis. Automatically detecting tumors and extracting lesion boundaries in ultrasound images is difficult due to their specular nature and the variance in shape and appearance of sonographic lesions. Past work on automated ultrasonic breast lesion segmentation has not addressed important issues such as shadowing artifacts or dealing with similar tumor like structures in the sonogram. Algorithms that claim to automatically classify ultrasonic breast lesions, rely on manual delineation of the tumor boundaries. In this paper, we present a novel technique to automatically find lesion margins in ultrasound images, by combining intensity and texture with empirical domain specific knowledge along with directional gradient and a deformable shape-based model. The images are first filtered to remove speckle noise and then contrast enhanced to emphasize the tumor regions. For the first time, a mathematical formulation of the empirical rules used by radiologists in detecting ultrasonic breast lesions, popularly known as the "Stavros Criteria" is presented in this paper. We have applied this formulation to automatically determine a seed point within the image. Probabilistic classification of image pixels based on intensity and texture is followed by region growing using the automatically determined seed point to obtain an initial segmentation of the lesion. Boundary points are found on the directional gradient of the image. Outliers are removed by a process of recursive refinement. These boundary points are then supplied as an initial estimate to a deformable model. Incorporating empirical domain specific knowledge along with low and high-level knowledge makes it possible to avoid shadowing artifacts and lowers the chance of confusing similar tumor like structures for the lesion. The system was validated on a database of breast sonograms for 42 patients. The average mean boundary error between manual and automated segmentation was 6.6 pixels and the normalized true positive area overlap was 75.1%. The algorithm was found to be robust to 1) variations in system parameters, 2) number of training samples used, and 3) the position of the seed point within the tumor. Running time for segmenting a single sonogram was 18 s on a 1.8-GHz Pentium machine.