RECOVERY OF URANIUM FROM ACID MINE DRAINAGE WATERS BY ION EXCHANGE

Of the many applications involving the use of ion exchange, the removal of contaminants in effluents ranks as one that has aroused considerable attention. In the present study, this process was used to remove and recover uranium from acid mine waters at Caldas Uranium Mining and Extraction Plant, in the southeast of Brazil. Studies of sorption and NaCl elution to recovery uranium as a commercial product, are presented. Lime precipitation tests with the effluent from the resin revealed an overall uranium decontamination level of 94% in the sludge when compared with the actual lime precipitation treatment of acid mine water.     

Experimental campaign,modeling, and sensitivity analysis for the molecular distillation of petroleum residues 673.15 K+

This research activity proposes a sensitivity analysis of the molecular distillation process by focusing the attention on the response of the overall distillate flow rate under several conditions of distillation temperature and feed flow rate. Specific equations to characterize physicochemical properties of petroleum residues have been formulated by means of ASTM-based experimental campaigns combined with specific optimization techniques.     

Method validation for the determination of total mercury in fish muscle by cold vapour atomic absorption spectrometry

A method was validated for the determination of total Hg in fish muscle using continuous flow cold vapour atomic absorption (CVAAS) after microwave digestion in closed vessels. The method was validated according to European Union Regulations 333/2007 and 657/2002, considering the maximum level for the metal in fish, established by European Union regulation 1881/2006. The procedure for determining linear range, selectivity, recovery, precision, trueness, decision limit (CCα), detection capability (CCβ), measurement uncertainty and robustness of the method is reported. The results of the validation process demonstrate the method fulfils the provisions of the Commission Regulation. The selectivity study indicated that there was no matrix effect on the calibration curve between the concentration range of 1.0 and 30.0 μg Hg l(-1). The mean recovery calculated at six levels of fortification was in the range of 94-104%. The limit of detection (LOD) and limit of quantification (LOQ) values were 4.90 and 15.7 μg kg(-1), while the CCα and CCβ values were 0.517 and 0.533 mg kg(-1), respectively, for the maximum contaminant level of 0.500 mg kg(-1). The relative expanded measurement uncertainty of the method was 0.055 mg kg(-1). The method was not affected by slight variations of some critical factors (ruggedness minor changes) as sample mass and volume of the HNO(3) and H(2)O(2) used in the digestion step. The method allowed accurate confirmation analyses of the CRM DORM 3. In fact, the Z-scores attained in a proficiency test round were well below the reference value of 2.0, proving the excellent performance of the laboratory.     

The segmentation of the left ventricle of the heart from ultrasound data using deep learning architectures and derivative-based search methods

We present a new supervised learning model designed for the automatic segmentation of the left ventricle (LV) of the heart in ultrasound images. We address the following problems inherent to supervised learning models: 1) the need of a large set of training images; 2) robustness to imaging conditions not present in the training data; and 3) complex search process. The innovations of our approach reside in a formulation that decouples the rigid and nonrigid detections, deep learning methods that model the appearance of the LV, and efficient derivative-based search algorithms. The functionality of our approach is evaluated using a data set of diseased cases containing 400 annotated images (from 12 sequences) and another data set of normal cases comprising 80 annotated images (from two sequences), where both sets present long axis views of the LV. Using several error measures to compute the degree of similarity between the manual and automatic segmentations, we show that our method not only has high sensitivity and specificity but also presents variations with respect to a gold standard (computed from the manual annotations of two experts) within interuser variability on a subset of the diseased cases. We also compare the segmentations produced by our approach and by two state-of-the-art LV segmentation models on the data set of normal cases, and the results show that our approach produces segmentations that are comparable to these two approaches using only 20 training images and increasing the training set to 400 images causes our approach to be generally more accurate. Finally, we show that efficient search methods reduce up to tenfold the complexity of the method while still producing competitive segmentations. In the future, we plan to include a dynamical model to improve the performance of the algorithm, to use semisupervised learning methods to reduce even more the dependence on rich and large training sets, and to design a shape model less dependent on the training set.     

Short communication: Changes in gait symmetry in healthy and lame dairy cows based on 3-dimensional ground reaction force curves following claw trimming

Lameness is a frequent health problem in dairy cows. This preliminary study aimed to detect gait differences between healthy and lame walking cows using 3-dimensional force plates. We examined left–right leg symmetry changes of healthy and lame Holstein dairy cows following claw trimming. Gait scoring (GS) was performed on d −5, 0, 1, and 7 relative to claw trimming. Before the experiment, 5 cows walked normally (initial GS = 1) and 4 cows limped moderately on a hind leg (initial GS = 3). Gait was measured on d −2, −1, 0, 1, and 7 relative to trimming by obtaining ground reaction forces as cows walked repeatedly across 2 parallel 3-dimensional force plates. From the ground reaction forces, stance phase data were derived using computerized procedures. Left–right leg symmetries of entire curves in the 3 force directions were calculated. Effects of lameness and trimming were analyzed in a mixed model, using a low lameness threshold (GS > 1). One week after claw trimming, only one cow was mildly lame. In addition, the symmetries of all 3 dimensions were significantly improved shortly after trimming. Importantly, lameness significantly worsened vertical symmetry. Lame cows walked significantly more slowly than healthy cows. In conclusion, all force symmetries seemed capable of detecting gait responses to claw trimming. Although our results are based on a small number of animals, vertical leg symmetry was affected by lameness.     

Behavior of the high frequency Raman modes of double-wall carbon nanotubes after doping with bromine or iodine vapors

The effects of two different halogen dopants (bromine and iodine) at different concentrations on the higher frequency modes (the so-called G and G′ bands) of the Raman spectra of double-wall carbon nanotube (DWCNT) “buckypaper” are investigated. The effects of dopants on different DWCNT configurations (metallic inner/semiconducting outer and vice versa) are studied by changing the laser excitation energy. The doping causes the loss of the Breit–Wigner–Fano line shape and the appearance of less metallic behavior. An increase of the relative intensity of the G⁺ band, which is more sensitive for the outer metallic tubes, is clearly observed with increasing Br₂ concentration in the sample. By analysis of the G⁺ band and the G′ band it is possible to measure the changes in the electron–phonon coupling, due to the charge-transfer between the dopant (Br₂ or I₂) and the tubes in the DWCNT. The doping effect causes an upshift of the G⁺ band and a suppression of the contribution of the inner tubes to the G′ band signal and as a consequence, the observed G′ band is dominated by the contribution from the outer tubes.     

Moisture Prediction During Paste Drying in a Spouted Bed

The objective of this work was to derive and experimentally verify a hybrid CST/neural network model to determine the moisture content of the powders produced during paste drying in a spouted bed and describe the highly coupled heat and the mass transfer. The model was derived from overall energy and mass balances with effective drying kinetics given by a neural network. Simulations were performed in MatLab and drying experiments for model verification were carried out for different pastes in a conical, semi-pilot-scale spouted bed.     

An adaptive potential for robust shape estimation

This paper describes an algorithm for shape estimation in cluttered scenes. A new image potential is defined based on strokes detected in the image. The motivation is simple. Feature detectors (e.g. edge points detectors) produce many outliers, which hamper the performance of boundary extraction algorithms. To overcome this difficulty we organize edges in strokes and assign a confidence degree (weight) to each stroke. The confidence degrees depend on the distance of the stroke points to the boundary estimates and they are updated during the estimation process. A deformable model is used to estimate the object boundary, based on the minimization of an adaptive potential function which depends on the confidence degree assigned to each stroke. Therefore, the image potential changes during the estimation process. Both steps (weight update, energy minimization) are derived as the solution of a maximum likelihood estimation problem using the EM algorithm.Experimental tests are provided to illustrate the performance of the proposed algorithm.     

The Influence of Surfactant Solution Injection in Oil Recovery by Spontaneous Imbibition

Imbibition is the spontaneous displacement of fluids through porous media that occurs until capillary equilibrium is reached. Factors such as wettability and high interfacial tensions may negatively affect the process, requiring additional work to enhance oil recovery. This work aims to explain some aspects of the dynamics of oil recovery by spontaneous imbibition using different fluids. Static imbibition and contact angle experiments were performed using sandstones of the Botucatu Formation (Brazil). The plug samples were exposed to immersion in brine and in surfactant solutions, and the progression of oil recovery was monitored with time. The results showed that the capillary imbibition rate and the oil recovery factor were higher when an ionic surfactant was used. The inverse Bond number and the shape of the recovery profile showed different trends of the capillary imbibition dynamics. Higher oil recovery factors for ionic surfactant were also an effect of the contact angles observed.