The effects of lignin removal and drying on the porosity and enzymatic hydrolysis of sugarcane bagasse

The porosity of lignocellulosic materials is a key feature for the enzymatic hydrolysis of the constituent polysaccharides, being affected by its drying and lignin content. Here we evaluated the influence of both parameters in the porosity of sugarcane bagasse, using raw and chlorite-delignified samples. A fraction of these samples was air dried at room temperature and the remainder one was kept wet. All the samples were subjected to porometry (solute exclusion technique), determination of water retention value and assessment of enzymatic saccharification of polysaccharides. Samples with higher lignin contents had lower porosities and exhibited worse enzymatic conversions of polysaccharides. Mild drying collapsed only the smaller pores, which already were inaccessible to enzymes, and therefore did not affect the efficiencies of saccharification. Our results show that the lignin content plays an important role in the porosity of the material and that its removal improves the enzymatic saccharification of the constituent polysaccharides.     

Antitrypanasomal activity of novel benzaldehyde-thiosemicarbazone derivatives from kaurenoic acid

A series of new thiosemicarbazones derived from natural diterpene kaurenoic acid were synthesized and tested against the epimastigote forms of Trypanosoma cruzi to evaluate their antitrypanosomal potential. Seven of the synthesized thiosemicarbazones were more active than kaurenoic acid with IC?? values between 2-24.0 mM. The o-nitro-benzaldehyde-thiosemicarbazone derivative was the most active compound with IC?? of 2.0 mM. The results show that the structural modifications accomplished enhanced the antitrypanosomal activity of these compounds. Besides, the thiocyanate, thiosemicarbazide and the p- methyl, p-methoxy, p-dimethylamine, m-nitro and o-chlorobenzaldehyde-thiosemicarbazone derivatives displayed lower toxicity for LLMCK? cells than kaurenoic acid, exhibing an IC?? of 59.5 mM.     

Heart rate variability analysis by chaotic global techniques in children with attention deficit hyperactivity disorder

Attention deficit hyperactivity disorder (ADHD) is characterized by decreased attention span, impulsiveness, and hyperactivity. Autonomic nervous system imbalance was previously described in this population. We aim to compare the autonomic function of children with ADHD and controls by analyzing heart rate variability (HRV). Children with ADHD (22 boys, mean age 9.964 years) and 28 controls (15 boys, mean age 9.857 years) rested in supine position with spontaneous breathing for 20 min. Heart rate was recorded beat by beat. HRV analysis was performed by use of chaotic global techniques. ADHD promoted an increase in the chaotic forward parameter. The algorithm which applied all three chaotic global parameters was only the second optimum statistically measured by Kruskal–Wallis (P < 0.0001) and low standard deviations. It was also highly influential by principal component analysis with almost all variation covered by the first two components. The third algorithm which lacked the (high spectral Detrended Fluctuation Analysis) parameter performed best statistically. However, we chose the algorithm which applied all three chaotic globals due to previous studies mentioned in the text—forward and inverse problems. Comparison of the autonomic function by analyzing HRV with chaotic global techniques suggests an increase in chaotic activity in children with ADHD in relation to the control group. © 2015 Wiley Periodicals, Inc. Complexity 21: 412–419, 2016     

Restart strategies for GRASP with path-relinking heuristics

GRASP with path-relinking is a hybrid metaheuristic, or stochastic local search (Monte Carlo) method, for combinatorial optimization. A restart strategy in GRASP with path-relinking heuristics is a set of iterations {i ₁, i ₂, …} on which the heuristic is restarted from scratch using a new seed for the random number generator. Restart strategies have been shown to speed up stochastic local search algorithms. In this paper, we propose a new restart strategy for GRASP with path-relinking heuristics. We illustrate the speedup obtained with our restart strategy on GRASP with path-relinking heuristics for the maximum cut problem, the maximum weighted satisfiability problem, and the private virtual circuit routing problem.     

Adaptive memory in multistart heuristics for multicommodity network design

This paper focuses on the use of different memory strategies to improve multistart methods. A network design problem in which the costs are given by discrete stepwise increasing cost functions of the capacities installed in the edges is used to illustrate the contributions of adaptive memory and vocabulary building strategies. Heuristics based on shortest path and maximum flow algorithms are combined with adaptive memory in order to obtain an approximate solution to the problem in the framework of a multistart algorithm. Furthermore, a vocabulary building intensification mechanism supported by the resolution of a linear program is also explored. Numerical experiments have shown that the proposed algorithm obtained the best known solutions for some instances in the literature. These results show the contribution of each memory component and the effectiveness of their combination.     

A Hybrid Improvement Heuristic for the One-Dimensional Bin Packing Problem

We propose in this work a hybrid improvement procedure for the bin packing problem. This heuristic has several features: the use of lower bounding strategies; the generation of initial solutions by reference to the dual min-max problem; the use of load redistribution based on dominance, differencing, and unbalancing; and the inclusion of an improvement process utilizing tabu search. Encouraging results have been obtained for a very wide range of benchmark instances, illustrating the robustness of the algorithm. The hybrid improvement procedure compares favourably with all other heuristics in the literature. It improved the best known solutions for many of the benchmark instances and found the largest number of optimal solutions with respect to the other available approximate algorithms.     

A Genetic Algorithm for Solving a Capacitated p-Median Problem

Facility-location problems have several applications, such as telecommunications, industrial transportation and distribution. One of the most well-known facility-location problems is the p-median problem. This work addresses an application of the capacitated p-median problem to a real-world problem. We propose a genetic algorithm (GA) to solve the capacitated p-median problem. The proposed GA uses not only conventional genetic operators, but also a new heuristic “hypermutation” operator suggested in this work. The proposed GA is compared with a tabu search algorithm.     

Probing the wave function of shallow Li and Na donors in ZnO nanoparticles

Electron paramagnetic resonance and electron nuclear double resonance (ENDOR) experiments on ZnO nanoparticles reveal the presence of shallow donors related to interstitial Li and Na atoms. The shallow character of the wave function is evidenced by the multitude of 67Zn ENDOR lines and further by the hyperfine interactions with the 7Li and 23Na nuclei that are much smaller than for atomic lithium and sodium. In the case of the Li-doped nanoparticles, an increase of the hyperfine interaction with the 7Li nucleus and with the 1H nuclei in the Zn(OH)(2) capping layer is observed when reducing the size of the nanoparticles. This effect is caused by the confinement of the shallow-donor 1s-type wave function that has a Bohr radius of about 1.5 nm, i.e., comparable to the dimension of the nanoparticles.