Rapid microanalytical chlorine determination in polymers by ion selective electrode

A rapid microanalytical method has been developed for the determination of very small amounts of chlorine in polymers. The gist of the method comprises quantitative dechlorination by sodium biphenyl or dehydrochlorination bytert-BuOK, aqueous extraction of the Cl^? formed, followed by [Cl^?] quantitation by chloride ion selective electrode (CSE). The method has been tested and is now used routinely for chlorine end group quantitation of telechelic polyisobutylene (PIB), poly(2,4,6-trimethylstyrene) (PTMSt), and poly(p-chlorostyrene) (PpClSt).     

Bioaugmentation on hydrogen production from food waste

The aim of this work was to evaluate the effect of two hydrolytic (Paenibacillus polymyxa and Bacillus subtilis) and two fermentative (Clostridium saccharobutylicum and Clostridium beijerinckii) strains on hydrogen (H₂) production in dark fermentation by batch testing. Food waste was used as a substrate, pretreated anaerobic sludge was used as the inoculum, and different concentrations of the evaluated microorganisms were used. Bioaugmentation with 3.5 × 10⁹ CFU/mL/L_reactor B. subtilis showed the best performance, obtaining a production of 84.5 mL H₂/g SV and a reduction in the lag phase (from 7.9 h in control to 3.5 h). Bioaugmentation with B. subtilis in an anaerobic sequencing batch reactor exhibited a significant effect on volumetric productivity, reaching a maximal increase of 344% of H₂ production in comparison with that obtained without the addition of the strain. The increase in H₂ was observed in a short period of time (4 cycles), after which H₂ production returned to the original H₂ production baseline. During all reactor operations, the main volatile fatty acids produced were acetic acid and butyric acid. Microbial community analysis when bioaugmentation was applied showed an importance of lactic acid bacteria abundance, such as that of Bifidobacterium and Lactobacillus, whose metabolic activity was crucial in reactor performance. The added concentration of microorganisms is a critical parameter for the bioaugmentation process.     

Modelling of an EGSB treating sugarcane vinasse using first-order variable kinetics

An expanded granular sludge bed (EGSB) anaerobic reactor treating sugar cane vinasse was modelled using a simple model with two steps (acidogenesis and methanogenesis), two populations, two substrates and completely mixed conditions. A first-order kinetic equation for both steps with time-variant kinetic coefficients was used. An observer system was used to estimate the evolution of kinetic constants over time. The model was validated by comparing methane flow predictions with experimental values. An estimation of evolution of populations of microorganisms was also performed. This approach allows calculation of specific kinetic constants that reflect biological activity of microorganisms. Variation of specific kinetic constants reflects the influence of the fraction of raw vinasse in the feed. High salt concentrations in the reactor may have inhibited the process.     

Short Duration Overheating in a Steam Reformer: Consequences to the Catalyst Tubes

Catalytic reformer furnaces (steam reformers) produce hydrogen-rich gas by cracking natural gas or naphtha in the presence of steam and a catalyst. This hydrogen-rich gas is a raw material in different petrochemical processes and is also used in the hydrotreating process in petroleum refineries. Unexpected operational failures of these reformers can cause major economic losses. These failures can happen when the feedstock flow, that cools the catalyst tubes located in the radiation chamber, is unintentionally restricted without also reducing the fuel burn rate. The thermal imbalance created in this situation can quickly produce a temperature surge large enough to cause the failure of the catalyst tubes through formation of large longitudinal cracks. This paper discusses a case of a temperature surge followed by the rupture of 13 catalyst tubes. The data show that the catalyst tubes that survived the event may retain sufficient structural integrity to return to normal operation.     

Noncovalent functionalization of carbon nanotubes with porphyrins: meso-tetraphenylporphine and its transition metal complexes

Noncovalent functionalization of carbon nanotubes with meso-tetraphenylporphine (H2TPP) and its metal(II) complexes NiTPP and CoTPP was studied by means of different experimental techniques and theoretical calculations. As follows from the experimental adsorption curves, free H2TPP ligand exhibits the strongest adsorption of three porphyrins tested, followed by CoTPP and NiTPP. At the highest porphyrin concentrations studied, the adsorption at multi-walled carbon nanotubes was about 2% (by weight) for H2TPP, 1% for CoTPP, and 0.5% for NiTPP. Transmission electron microscopy observations revealed carbon nanotubes with a variable degree of surface coverage with porphyrin molecules. According to scanning electron microscopy, the nanotubes glue together rather than debundle; apparently, a large porphyrin excess resulting in polymolecular adsorption is essential for exfoliation/debundling of the nanotube ropes. The nanotube/porphyrins hybrids were studied by infrared and Raman spectroscopy, as well as by scanning tunneling microscopy. Electronic structure calculations were performed at the B3LYP/LANL2MB theoretical level with the unsubstituted porphine (H2P) and its Co(II) complex, on one hand, and open-end armchair (5,5) (ANT) and zigzag (8,0) (ZNT) SWNT models, on the other hand. The interaction of H2P with ANT was found to be by 3.9 kcal mol(-1) stronger than that of CoP. At the same time, CoP+ZNT complex is more stable by 42.7 kcal mol(-1) as compared to H2P+ZNT According to these calculated results, the free porphyrins interact less selectively with zigzag and armchair (i.e., semiconducting and metallic) nanotubes, whereas the difference becomes very large for the metal porphyrins. HOMO-LUMO structure, electrostatic potential and spin density distribution for the paramagnetic cobalt(II) complexes were analyzed.     

A new similarity measure for non-local means filtering of MRI images

In this paper, the application of non-local means (NLM) filtering on MRI images is investigated. An essential component of any NLM-based algorithm is its similarity measure used to compare pixel intensities. Unfortunately, virtually all existing similarity measures used to denoise MRI images have been derived under the assumption of additive white Gaussian noise contamination. Since this assumption is known to fail at low values of signal-to-noise ratio (SNR), alternative formulations of these measures which take into account the correct (Rician) statistics of the noise are required. Accordingly, the main contribution of the present work is to introduce a new similarity measure for NLM filtering of MRI images, which is derived under bona fide statistical assumptions and proves to posses important theoretical advantages over alternative formulations. The utility and viability of the proposed method is demonstrated through a series of numerical experiments using both in silico and in vivo MRI data.     

Dynamics identification and control of nonlinear MIMO coupled plant using supervised neural gas and comparison with recurrent neural controller

The dynamics identification and subsequent control of a nonlinear system is not a trivial issue. The application of a neural gas network that is trained with a supervised batch version of the algorithm can produce identification models in a robust way. In this paper, the neural model identifies each local transfer function, demonstrating that the local linear approximation can be done. Moreover, other parameters are analyzed in order to obtain a correct modeling. Furthermore, the algorithm is applied to control a nonlinear multi-input multi-output system composed of tanks. In addition, this plant is a coupled system where the manipulated input variables are influencing all the output variables. The aim of the work is to demonstrate that the supervised neural gas algorithm is able to obtain linear models to be used in a state space design scenario to control nonlinear coupled systems and guarantee a robust control method. The results are compared with the common approach of using a recurrent neural controller trained with a dynamic backpropagation algorithm. Regarding the steady-state errors in disturbance rejection, reference tracking and sensitivity to simple process changes, the proposed approach shows an interesting application to control nonlinear plants.

     

Agent-oriented modeling and development of a system for crisis management

The management of crisis situations has been a challenging problem from different points of views, such as communication efficiency and avoiding casualties. This paper presents a novel approach that includes an interaction organization pattern for Multi-agent Systems (MASs) in crisis management, abstracted from several existing case studies in which the agents follow a sequence of interactions and the organization must optimize the use of human resources. The pattern considers an emergent organization of peers that adopt different roles according to the circumstances. The key features of the organization are its robustness, scalability (in terms of both agents and roles), flexibility to deal with a changing environment, and the efficient use of resources. In order to validate the organization, the paper presents its modeling and development with the Ingenias methodology, conforming the corresponding MAS. This development follows a model-driven approach, which allows a smooth transition from the specification to the code, and a low-cost testing of the system with different settings. Another key aspect is the application of metrics for validating and improving the MAS in terms of response time. The MAS has been tested with 600 agents representing 200 citizens, showing its performance.     

On-board and Ground Visual Pose Estimation Techniques for UAV Control

In this paper, two techniques to control UAVs (Unmanned Aerial Vehicles), based on visual information are presented. The first one is based on the detection and tracking of planar structures from an on-board camera, while the second one is based on the detection and 3D reconstruction of the position of the UAV based on an external camera system. Both strategies are tested with a VTOL (Vertical take-off and landing) UAV, and results show good behavior of the visual systems (precision in the estimation and frame rate) when estimating the helicopter??s position and using the extracted information to control the UAV.