Removal of fulvic acid from aqueous media by adsorption onto modified vermiculite

Clay minerals are low cost materials that can be structurally modified and exploited for removal of natural organic matter from freshwaters. The present study shows that vermiculites modified by ion exchange with hexadecyltrimethylammonium or intercalation with poly(hydroxy iron) cations are potential adsorbents for removal of fulvic acid, whereas the adsorption on the raw clay mineral is negligible. The efficiency of the modified vermiculite was evaluated by measuring adsorption isotherms by the batch technique using initial fulvic acid concentrations between 2.5 and 50.0 mg L^− 1, with one hour of contact time. At least 94% of the fulvic acid initially present in a 20 mg L^− 1 solution was sorbed onto either the intercalated poly(hydroxy iron) cations or the organically modified vermiculite. Up to an initial concentration of 5.0 mg L^− 1 the adsorption is irreversible, and no quantifiable fulvic acid was measured in the desorption experiments. For initial fulvic acid concentrations between 10.0 and 50.0 mg L^− 1, desorption was between 2.3% and 4.9% for Fe(III) intercalated vermiculite, and between 1.4% and 9.2% for the organoclay. The adsorption percentages on intercalated poly(hydroxy iron) cations increased upon lowering pH and increasing the ionic strength, indicating the occurrence of strong binding mechanisms such as ligand exchange. Adsorption percentage of fulvic acid onto the organoclay also increased with lowering of pH, but in this case the adsorption percentages showed a small decrease at high ionic strength, suggesting that electrostatic attraction plays an important role in the adsorption process.     

A quantitative feedback solution to the multivariable tracking error problem

This paper introduces a novel solution for the multi‐input multi‐output (MIMO) quantitative feedback theory control design problem with tracking error specifications. Looking for a minimum controller overdesign, the technique finds new controller quantitative feedback theory bounds based on necessary and sufficient conditions for the existence of suitable associated prefilter matrix elements. It improves previous approaches to the subject and includes (i) the possibility of a free selection of the nominal plant, (ii) a less conservative application of the Schwartz inequality to decisively reduce the potential controller overdesign, (iii) a methodology to design independently the elements of the prefilter matrix, and (iv) a scope of application to both sequential and nonsequential MIMO controller design methods. The benefits of the new control design technique are illustrated by means of two examples. The first one, a standard 2 × 2 MIMO problem, is provided for comparison purposes with previous approaches. The second example, included as a major control challenge, deals with a well‐known demanding distillation column benchmark problem. Copyright © 2013 John Wiley & Sons, Ltd.     

Thermodynamic Modeling of Alkali Metal Oxide-Silica Binary Melts

The evaluation of the thermodynamic properties as well as the phase diagrams for the binary Na₂O–SiO₂, K₂O–SiO₂, and Li₂O–SiO₂ systems are carried out with a structural model for silicate melts and glasses. This thermodynamic model is based on the assumption that each metallic oxide produces the depolymerization reaction of silica network with a characteristic free-energy change. A least squares optimization program permits all available thermodynamic and phase diagram data to be optimized simultaneously. In this manner, data for these binary systems have been analyzed and represented with a small number of parameters. The resulting equations represent the thermodynamic and phase diagram data for these alkali metal oxide–silica systems within experimental error limits. In particular, the measured limiting liquidus slope at     is well reproduced.     

When does personalization work on social media? a posteriori segmentation of consumers

The aim of this research is to find a segment of consumers of fashion products based on their personal visions of personalization of shoppable ads on mobile social media. To meet this objective, three operational objectives are defined. First, a theoretical model is evaluated based on the stimulus-organism-response framework (S–O–R). This examines, with a PLS-SEM approach, how the stimulation of personalization will affect consumers' internal cognitive state (perceived usefulness) and consequently generates a behavioral response (intention to buy). Second, we look for fashion consumer segments based on their perception of personalization through prediction-oriented segmentation (PLS-POS). Third, the segments are explained based on three constructs that were considered important in fashion consumption through mobile social networks: purchase intention, concern for privacy, and perception of trend. The inclusion of personalization and the perception of usefulness of advertisements can greatly help the intention to purchase clothing to be understood. The application of a posterior segmentation helps to better understand the different types of users exposed to shoppable ads on mobile social networks and their relationship with the purchase intention, concern for privacy and trend. While the measures and scales were tested in a context of mobile clothing trade, the methodology can be applied to other types of products or services.

     

Iron recovery from zinc mine tailings by magnetic separation followed by carbothermal reduction of self‐reducing briquettes

The volume of tailings produced by the extractive industry has been increasing due to the processing of the low‐grade ore. This issue can cause environmental accidents and require significant investment to control the disposal of tailings. Therefore, this study aims to recover iron from zinc mine tailings by wet magnetic separation followed by the carbothermal reduction of self‐reducing briquettes. Two magnetic separation routes were investigated to concentrate iron. Zinc mine tailings were processed by route I, in a rougher stage followed by a scavenger stage; and route II, in a rougher stage followed by a cleaner stage. The carbothermal reductions were performed using self‐reducing briquettes composed of Fe concentrate from the route with high Fe content and charcoal. The products were analyzed by scanning electron microscopy with energy dispersive spectroscopy (SEM‐EDS), x‐ray diffraction (XRD), inductively coupled plasma optical emission spectrometry (ICP‐OES), and volumetric chemical analysis. Magnetic separation route II provided the highest‐grade Fe concentrate, 52% Fe, while route I provided 33% Fe. In the carbothermal reductions, a metallization degree of 98% in the Fe concentrate briquette, 97% in the briquette with a 10% replacement of its raw material by Fe concentrate, and 99% in the hematite briquette was reached. The replacement of raw material by Fe concentrate showed no significant change in Fe recovery. Considering the whole process, magnetic separation and carbothermal reduction, the recovery of Fe from the zinc mine tailings was 67%. Therefore, the process route suggested in this study will not only reduce tailings disposal and consequently the risk of environmental accidents, but it will also provide profitable raw material for the steel industry.     

Biodegradability and improved mechanical performance of polyhydroxyalkanoates/agave fiber biocomposites compatibilized by different strategies

In this work, biocomposites made of polyhydroxyalkanoates (PHA) with natural fibers were produced via compression molding. In particular, polyhydroxybutyrate (PHB) and polyhydroxybutyrate-co-hydroxyvalerate (PHBV) were reinforced with 20 wt% of agave fibers. Different compatibilization strategies were investigated to improve the fiber-matrix interaction: fiber surface treatment in PHA solution, fiber surface treatment in maleated PHA solution, fiber propionylation, and extrusion with maleated PHA. The biocomposites were characterized in terms of morphology, mechanical properties, water absorption, and biodegradability by CO₂ production tracking. In general, fiber propionylation was the best strategy for mechanical properties enhancement and water uptake decreasing. Biocomposites with propionylated fibers showed improved flexural strength (170% for PHB and 84% for PHBV). The flexural modulus was also enhanced with propionylated fibers up to 19% and 18% compared to uncompatibilized biocomposites (PHB and PHBV, respectively). Tensile strength increased by 16% (PHB) and 14% (PHBV), and the water absorption was reduced using propionylated fibers going from 6.6% to 4.4% compared with biocomposites with untreated fibers. Most importantly, the impact strength was also improved for all biocomposites by up to 96% compared with the neat PHA matrices. Finally, it was found that the compatibilization did not negatively modify the PHA biodegradability.     

Influence of the corrosion products of copper on its atmospheric corrosion kinetics in tropical climate

In the present paper, the identification of the corrosion product phases formed on copper under different atmospheres of Cuban tropical climate is reported. Cuprite (Cu₂O), paratacamite (Cu₂Cl(OH)₃), posnjakite (Cu₄SO₄(OH)₆ · 2H₂O) and brochantite (Cu₄SO₄(OH)₆) were the main phases identified by X-ray diffraction (XRD) analysis and Fourier transform infrared spectroscopy (FTIR).Copper corrosion products are known to have a protective effect against corrosion. However, a different behaviour was obtained under sheltered coastal conditions. This can be due to the corrosion products morphology and degree of crystallisation, rather than their phase composition. A higher time of wetness and the accumulation of pollutants not washed away from the metal surface can also play an important role.     

Trajectory-based human action segmentation

This paper proposes a sliding window approach, whose length and time shift are dynamically adaptable in order to improve model confidence, speed and segmentation accuracy in human action sequences. Activity recognition is the process of inferring an action class from a set of observations acquired by sensors. We address the temporal segmentation problem of body part trajectories in Cartesian Space in which features are generated using Discrete Fast Fourier Transform (DFFT) and Power Spectrum (PS). We pose this as an entropy minimization problem. Using entropy from the classifier output as a feedback parameter, we continuously adjust the two key parameters in a sliding window approach, to maximize the model confidence at every step. The proposed classifier is a Dynamic Bayesian Network (DBN) model where classes are estimated using Bayesian inference. We compare our approach with our previously developed fixed window method. Experiments show that our method accurately recognizes and segments activities, with improved model confidence and faster convergence times, exhibiting anticipatory capabilities. Our work demonstrates that entropy feedback mitigates variability problems, and our method is applicable in research areas where action segmentation and classification is used. A working demo source code is provided online for academical dissemination purposes, by requesting the authors.     

Music staff removal with supervised pixel classification

This work presents a novel approach to tackle the music staff removal. This task is devoted to removing the staff lines from an image of a music score while maintaining the symbol information. It represents a key step in the performance of most optical music recognition systems. In the literature, staff removal is usually solved by means of image processing procedures based on the intrinsics of music scores. However, we propose to model the problem as a supervised learning classification task. Surprisingly, although there is a strong background and a vast amount of research concerning machine learning, the classification approach has remained unexplored for this purpose. In this context, each foreground pixel is labelled as either staff or symbol. We use pairs of scores with and without staff lines to train classification algorithms. We test our proposal with several well-known classification techniques. Moreover, in our experiments no attempt of tuning the classification algorithms has been made, but the parameters were set to the default setting provided by the classification software libraries. The aim of this choice is to show that, even with this straightforward procedure, results are competitive with state-of-the-art algorithms. In addition, we also discuss several advantages of this approach for which conventional methods are not applicable such as its high adaptability to any type of music score.     

Hefestos: an intelligent system applied to ubiquitous accessibility

This article proposes Hefestos, an intelligent system applied to ubiquitous accessibility. This model uses ubiquitous computing concepts to manage accessibility resources for people with disabilities. Among the concepts employed, context awareness, user profiles and trails management can be highlighted. The paper proposes an ontology for accessibility and delineates scenarios of its application in everyday life of people with disabilities. Moreover, the implementation of a smart wheelchair prototype and its application in a practical experiment is described. Ten users with a range of disability degrees tried the system and filled out a survey based on the technology acceptance model. This experiment demonstrated the main functionalities and the acceptance of the system. The results showed 96 % of acceptance regarding perceived easy of use and 98 % in perceived usefulness. These results were encouraging and show the potential for implementing Hefestos in real life situations.