A comprehensive survey: artificial bee colony (ABC) algorithm and applications

Swarm intelligence (SI) is briefly defined as the collective behaviour of decentralized and self-organized swarms. The well known examples for these swarms are bird flocks, fish schools and the colony of social insects such as termites, ants and bees. In 1990s, especially two approaches based on ant colony and on fish schooling/bird flocking introduced have highly attracted the interest of researchers. Although the self-organization features are required by SI are strongly and clearly seen in honey bee colonies, unfortunately the researchers have recently started to be interested in the behaviour of these swarm systems to describe new intelligent approaches, especially from the beginning of 2000s. During a decade, several algorithms have been developed depending on different intelligent behaviours of honey bee swarms. Among those, artificial bee colony (ABC) is the one which has been most widely studied on and applied to solve the real world problems, so far. Day by day the number of researchers being interested in ABC algorithm increases rapidly. This work presents a comprehensive survey of the advances with ABC and its applications. It is hoped that this survey would be very beneficial for the researchers studying on SI, particularly ABC algorithm.     

Treatment of phenol formaldehyde production wastewater by electrooxidation-electrofenton successive processes

ABSTRACT

Treatments of phenol formaldehyde producing wastewater (PFPW) by electrooxidation (EO) and electro-Fenton (EF) successive processes were carried out in a batch electrolytic reactor using graphite (Gr) and stainless steel (Ss) electrodes. After the completion of the EO process, the wastewater was further treated with EF process. The influence of operating variables such as current density, operating time, initial pH_i and H₂O₂ concentration was evaluated for removals of phenol, TOC and COD in PFPW. Gr/Gr, Gr/Ss or Ss/Ss and Ss/Gr electrode pair were used as anode and cathode. The best removal efficiency in the EO process was obtained with Gr/Gr (93%) as compared to Gr/Ss (82%), Ss/Ss (63%) and Ss/Gr (55%). The removal efficiencies for the EO process using Gr-Gr electrode pair were obtained as 93% for phenol, 61% for COD and 44% for TOC at initial pH_i 7,5 g/L of NaCl, 50 mA/cm² and 5 h. In the EF process, the removal efficiencies at pH_i 3,5 mA/cm² and 30 mM H₂O₂ and 45 min were 100% for phenol, 76% for COD and 59% for TOC. This study provided that the successive processes are an effective method for the removal of phenolic compounds from the wastewater.     

Fuzzy functions based ARX model and new fuzzy basis function models for nonlinear system identification

In this study, auto regressive with exogenous input (ARX) modeling is improved with fuzzy functions concept (FF-ARX). Fuzzy function with least squares estimation (FF-LSE) method has been recently developed and widely used with a small improvement with respect to least squares estimation method (LSE). FF-LSE is structured with only inputs and their membership values. This proposed model aims to increase the capability of the FF-LSE by widening the regression matrix with lagged input–output values. In addition, by using same idea, we proposed also two new fuzzy basis function models. In the first, basis of the fuzzy system and lagged input–output values are structured together in the regression matrix and named as “L-FBF”. Secondly, instead of using basis function, the membership values of the lagged input–output values are used in the regression matrix by using Gaussian membership functions, called “M-FBF”. Therefore, the power of the fuzzy basis function is also enhanced. For the corresponding models, antecedent part parameters for the input vectors are determined with fuzzy c-means (FCM) clustering algorithm. The consequent parameters of the all models are estimated with the LSE. The proposed models are utilized and compared for the identification of nonlinear benchmark problems.     

Robust microencapsulated phase change materials in concrete mixes for sustainable buildings

For passive building applications, phase change materials (PCMs) are microencapsulated to avoid leakage of PCM from concrete structure. The primary challenge of using microencapsulated PCM (MPCM) is its weak shell structure. New MPCMs with different shell compositions to prevent breakage during mixing in fresh concrete are needed. In this study, free radical polymerization method to microencapsulate capric acid–myristic acid mixture as PCM with two different methyl methacrylate co‐polymers is proposed to produce robust MPCMs for building applications. Two new microcapsules (MPCM‐1 and MPCM‐2) having latent heats of 91.9 and 97.3 J/g were synthesized. SEM analyses showed the size of microcapsules being in the range of 400–850 nm for MPCM‐1 and 250–475 nm for MPCM‐2. Analyses also reveal that the shells of MPCMs were not harmed, as they were added into concrete mixes. The microsphere's geometry was preserved, and distribution was homogeneous. The MPCMs were also studied under thermal tests of 1000 heating/cooling cycles. No significant changes in thermal properties were observed after thermal cycling tests. Copyright © 2016 John Wiley & Sons, Ltd.     

Statistical thermal stability of PVC

Experimental design was used to optimize the processing parameters for the decomposition of poly(vinyl chloride). Factorial design and face centered composite design (FCC) were applied to determine the optimum conditions. A total of 10 g PVC powder was mixed with different amounts of zinc stearate (ZnSt₂) and natural zeolite and tested for thermal stability. Factorial fitted model was explained by first order pattern due to the significant main effect regression constants, and FCC model was described by second order model owing to higher order polynomial coefficients. FCC design was superior to factorial design as FCC considers not only its pure quadratic effects contribution but also its higher overall desirability for thermal stability of PVC. For factorial design the optimum conditions were determined as 163.06 mg for ZnSt₂, 399.99 mg for zeolite, and 140°C for temperature with desirability of 0.933. However, 400 mg for ZnSt₂, 333.24 mg for zeolite, and 140°C for temperature with desirability of 0.956 were obtained as the optimum conditions by FCC design. © 2010 Wiley Periodicals, Inc. J Appl Polym Sci, 2010     

A novel approach to simulate growth of multi-stem willow in bioenergy production systems with a simple process-based model (3PG)

An important requirement for commercialization of willow biomass production in short-rotation crop (SRC) plantations is the reliable and cost-efficient estimation of biomass yield. Predictions and simulations of willow stand biomass have been problematic due to issues with modeling the multi-stem growth form of willow. The aim of this paper was to develop a new approach for managing allometric measurements from multi-stemmed willow for stand growth simulations. The 3PG model (Physiological Principles in Predicting Growth) was parameterized for willow and was used for biomass yield simulation for an entire 22-yr cycle (seven 3-yr rotations) of willow in SRC plantations. The multi-stemmed growth form was transformed into a single-stem modeling form by deriving whole plant willow allometric relationships using detailed stem-level measurements of basal area, stem biomass and volume. 3PG model predictions for plant diameter, height, biomass, and stand biomass and volume were within the 95% confidence range of mean plot values. Model simulations showed that after seven 3-yr rotations only 20% of planted cuttings would survive (a decrease from 15,152 to 3022 plants ha⁻¹), but stand volume would increase continuously with each subsequent rotation. 3PG predictions for cumulative (for 22 yr) aboveground biomass was 272 Mg ha⁻¹ and mean annual yield was 12 Mg ha⁻¹ yr⁻¹, comparing favorably with other findings. To our knowledge, this work is the first where the 3PG model was calibrated and used for willow species. Once parameterized for a specific willow clone, 3PG can predict biomass accumulation for any agricultural land in North America using only available soil and climate data.     

Biosorption of copper (II) from aqueous solutions by wheat shell

The adsorption capacity of wheat shell for copper (II) was studied at various pH (2-7), agitation speeds (50-250 rpm) and initial metal ion concentrations (Co, from 10 to 250 mg.L⁻¹). Maximum biosorption of copper onto wheat shell occurred at 240 rpm agitation speed and at pH between 5 and 6. The biosorption values of copper (11) were increased with increasing pH from 2 to 5 and decreased with increasing copper/wheat shell (x/m) ratios from 0.83 to 10.84 mgCu(II).g⁻¹ wheat shell. The biosorption efficiencies at these x/m ratios were 99% and 52%, respectively, at the end of the 120 min contact time (t). The equilibrium isotherms and kinetics were obtained from batch adsorption experiments at 298 K. It was observed that wheat shell was a suitable biosorbent for removing Cu(II) from aqueous solutions.     

Epicardial fat thickness is associated with impaired coronary flow reserve in hemodialysis patients

Cardiovascular disease (CVD) is the main cause of mortality in hemodialysis (HD) patients. Epicardial fat tissue (EFT) is a new risk factor in CVD. The aim of this study was to evaluate the association between EFT and coronary artery flow reserve (CFR), which is an early indicator of endothelial dysfunction in coronary vessels of HD patients. We performed a cross‐sectional study including 71 chronic HD patients and 65 age‐ and sex‐matched healthy controls. Epicardial fat tissue was significantly higher in HD patients when compared to healthy controls (6.53 ± 1.01 mm vs. 5.79 ± 1.06 mm, respectively, P < 0.001). On transthoracic Doppler echocardiography, CFR values were significantly lower in HD patients when compared to healthy controls (1.73 ± 0.11 vs. 2.32 ± 0.28, P < 0.001). Correlation analysis showed CFR values to be inversely correlated with EFT (r = ?0.287, P < 0.05). Multiple linear regression analysis was used to define independent determinants of EFT in HD patients. Artery flow reserve, age, body mass index and total cholesterol levels were independently correlated with EFT thickness. This study demonstrated that EFT was significantly higher among HD patients compared to healthy controls. In addition, this study was the first to demonstrate an inverse correlation between EFT and CFR in this patient population.     

Engineered Biomolecular Recognition of RDX by Using a Thermostable Alcohol Dehydrogenase as a Protein Scaffold

There are many biotechnology applications that would benefit from simple, stable proteins with engineered biomolecular recognition. Here, we explored the hypothesis that a thermostable alcohol dehydrogenase (AdhD from Pyrococcus furiosus) could be engineered to bind a small molecule instead of a cofactor or molecules involved in the catalytic transition state. We chose the explosive molecule 1,3,5‐trinitro‐1,3,5‐triazine (royal demolition explosive, RDX) as a proof‐of‐concept. Its low solubility in water was exploited for immobilization for biopanning by using ribosome display. Docking simulations were used to identify two potential binding sites in AdhD, and a randomized library focused on tyrosine or serine mutations was used to determine that RDX was binding in the substrate binding pocket of the enzyme. A fully randomized binding pocket library was selected, and affinity maturation by error‐prone PCR led to the identification of a mutant (EP‐16) that gained the ability to bind RDX with an affinity of (73±11) μm . These results underscore the way in which thermostable enzymes can be useful scaffolds for expanding the biomolecular recognition toolbox.     

Etablierung eines Frühwarnsystems zur Erkennung lebensmittelbedingter Risiken in Bayern – risikoorientierte Lebensmittelüberwachung weiter gefasst

Recent and past food scandals highlight the urgent need for food safety authorities to anticipate future risks in order to enable improved and proactive response mechanisms. With this goal in mind, the Bavarian Health and Food Safety Authority (LGL) has established an early warning system aimed at early identification of potential health risks and fraudulent practices in the food sector. The early warning approach allows intervention at different stages of risk development. On the one hand, the scanning of a broad area of the food production chain (horizon scanning) may enable prospective risk identification. To this end, relevant factors of influence (drivers) need to be identified, observed and analyzed. On the other hand, the retrospective analysis of case studies may unravel novel cause-effect associations that could be transferred to other products and production technologies, possibly leading to the identification of new drivers (root cause analysis). Additionally, various datasets emanating from food safety authorities, for example data from the European Rapid Alert System for Food and Feed (RASFF) and from Bavarian-wide laboratory analyses and food business inspections, will be closely observed and analyzed. The multidisciplinary character of the LGL has proven to be essential for the realization of the early warning approach, the analysis of inflowing data and implementation of consequences such as food business inspections and sampling for analysis. This article details the objectives and methodical approaches of the project. The acquisition of systematically compiled information as well as its analysis and assessment are comprehensively described. The early warning system presented here has already contributed significantly to the risk-oriented food inspection practiced to date, by integrating novel risk-relevant aspects.