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Many optimization problems in engineering and industrial design applications can be formulated as optimization problems with highly nonlinear objectives, subject to multiple complex constraints. Solving such optimization problems requires sophisticated algorithms and optimization techniques. A major trend in recent years is the use of nature-inspired metaheustic algorithms (NIMA). Despite the popularity of nature-inspired metaheuristic algorithms, there are still some challenging issues and open problems to be resolved. Two main issues related to current NIMAs are: there are over 540 algorithms in the literature, and there is no unified framework to understand the search mechanisms of different algorithms. Therefore, this paper attempts to analyse some similarities and differences among different algorithms and then presents a generalized evolutionary metaheuristic (GEM) in an attempt to unify some of the existing algorithms. After a brief discussion of some insights into nature-inspired algorithms and some open problems, we propose a generalized evolutionary metaheuristic algorithm to unify more than 20 different algorithms so as to understand their main steps and search mechanisms. We then test the unified GEM using 15 test benchmarks to validate its performance. Finally, further research topics are briefly discussed.

Corrosion is an important problem that engineers and scientists must overcome to avoid the collapse of structures, chemical processing plants, and metallic objects, which can lead to not only economic loss but also environmental and human losses. One of the simplest and most widely used methods to quantify corrosion rates (CRs) is the immersion test. The usual approach that has been used to date, to quantify the CR by this method, is to assume that the initial surface area of the corroding object remains constant over time. It is shown that such approximations underestimate the true CR and that they may lead to significant errors. A formula to calculate the CR considering changes in the area is presented in this work. The formula herein can be used to accurately quantify the CR by the immersion test and improve the quality of experimental data and the analysis and modeling of corrosion phenomena.

In this study, four novel aromatic polyimides (PIs) with twisted backbone and bulky side substituents were prepared via chemical imidization reaction and two‐step condensation polymerization at reduced reaction temperature. The number‐average and weight‐average molecular weights of the resulting PIs are in the range of 1.98 × 104–4.10 × 104 and 2.66 × 104–5.32 × 104 g mol−1, respectively, while maintaining polydispersity indices consistently below 2.0. In addition, the obtained PIs showed excellent solubility in most common solvents, even in low‐boiling solvents, such as chloroform, dichloromethane, and tetrahydrofuran. The films casted from these PIs also displayed optical transparency with a cutoff wavelength in the range of 335–360 nm. Among the PIs, PAPOT‐OPDA, derived from 3,3′‐Diisopropyl‐4,4′‐diaminodiphenyl‐3″‐phenoxybenzylmethane (PAPOT) and 3,3′,4,4′‐diphenylethertetracarboxylic dianhydride (OPDA), exhibited the highest transparency of T450 = 81% and T500 = 85%, and the best solubility without compromising its thermal properties. [ABSTRACT FROM AUTHOR]

In this paper, a new metaheuristic algorithm that mimics the pollination process of flowers and is known as the flower pollination algorithm (FPA) has been proposed for the solution of the optimal capacitor placement (OCP) problem in a radial distribution system (RDS). The objective of this problem is to minimize the total power loss and cost of capacitor installation by optimal location and sizing of the capacitors. OCP also improves the voltage profile. In this work, the power flow and losses in the network are obtained with the help of load flow analysis using data structures. The proposed FPA approach has been applied to solve 33-, 34-, 69- and 85 bus RDSs. The results obtained are compared with those of the analytical method, fuzzy real coded genetic algorithm, two stage fuzzy approach and teaching learning based optimization algorithms. The comparison shows that FPA is a highly suitable optimization approach for solving capacitor placement problems. Keywords: Metaheuristic algorithm, Loss minimization, Voltage profile improvement, Capacitor placement, Radial distribution systems

This paper is devoted to a numerical study of defining of parameters of dynamical systems arising in financial and economic problems. The importance of parameters that are difficult to measure is great, so defining them will help to make forecasts and a work plan for the future at the governmental level. An effective way to restore parameters is to solve the inverse problem. The method of coefficient recovery using the algorithm of differential evolution, which was proposed by Rainer Storn and Kenneth Price, is presented in this paper. On the example of solving the direct problem of the mathematical model of neoclassical economic growth of Robert Solow and the results obtained, the inverse problem was solved and unknown parameters were determined. The Solow model is based on the Cobb-Douglas production function, taking into account labor, capital and exogenous neutral technical progress. Also, for further calculations, the economic model proposed by Mankiw-Romer-Weil based on the Solow model was considered, but with the addition of human capital, where the number of variables and coefficients that need to be restored has already increasing. A direct problem was also solved, results were obtained that were applied in the algorithm of differential evolution for parameters recovery.

Immune recognition of pathogen-associated molecular patterns (PAMPs) by pattern recognition receptors often activates proinflammatory NF-[kappa]B signalling.sup.1. Recent studies indicate that the bacterial metabolite d-glycero-[beta]-d-manno-heptose 1,7-bisphosphate (HBP) can activate NF-[kappa]B signalling in host cytosol.sup.2-4, but it is unclear whether HBP is a genuine PAMP and the cognate pattern recognition receptor has not been identified. Here we combined a transposon screen in Yersinia pseudotuberculosis with biochemical analyses and identified ADP-[beta]-d-manno-heptose (ADP-Hep), which mediates type III secretion system-dependent NF-[kappa]B activation and cytokine expression. ADP-Hep, but not other heptose metabolites, could enter host cytosol to activate NF-[kappa]B. A CRISPR-Cas9 screen showed that activation of NF-[kappa]B by ADP-Hep involves an ALPK1 (alpha-kinase 1)-TIFA (TRAF-interacting protein with forkhead-associated domain) axis. ADP-Hep directly binds the N-terminal domain of ALPK1, stimulating its kinase domain to phosphorylate and activate TIFA. The crystal structure of the N-terminal domain of ALPK1 and ADP-Hep in complex revealed the atomic mechanism of this ligand-receptor recognition process. HBP was transformed by host adenylyltransferases into ADP-heptose 7-P, which could activate ALPK1 to a lesser extent than ADP-Hep. ADP-Hep (but not HBP) alone or during bacterial infection induced Alpk1-dependent inflammation in mice. Our findings identify ALPK1 and ADP-Hep as a pattern recognition receptor and an effective immunomodulator, respectively.The bacterial metabolite ADP-heptose activates NF-[kappa]B in host cells via alpha-kinase 1 and the TIFA-TRAF signalling pathway., Author(s): Ping Zhou [sup.1] , Yang She [sup.1] [sup.2] [sup.3] , Na Dong [sup.4] , Peng Li [sup.1] , Huabin He [sup.1] , Alessio Borio [sup.5] , Qingcui Wu [sup.1] [...]