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This paper aims to investigation of processes for Pb²⁺ elimination from water/wastewater as a significant public health issue in many parts of world. The removal of Pb²⁺ ions by various nanocomposites has been explained from water/wastewaters. ZnO-based nanocomposites, as eco-friendly nanoparticles with unique physicochemical properties, have received increased attention to remove Pb²⁺ ions from water/wastewaters.

In this review, different ZnO-based nanocomposites were reviewed for their application in the removal of Pb²⁺ ions from the aqueous solution, typically for wastewater treatment using methodology, such as adsorption. This review focused on the ZnO-based nanocomposites for removing Pb²⁺ ions from water and wastewaters systems.

The ZnO-based nanocomposite was prepared by different methods, such as electrospinning, hydrothermal/alkali hydrothermal, direct precipitation and polymerization. Depending on the preparation method, various types of ZnO-based nanocomposites like ZnO-metal (Cu/ZnO, ZnO/ZnS, ZnO/Fe), ZnO-nonmetal (PVA/ZnO, Talc/ZnO) and ZnO-metal/nonmetal (ZnO/Na-Y zeolite) were obtained with different morphologies. The effects of operational parameters and adsorption mechanisms were discussed in the review.

The findings may be greatly useful in the application of the ZnO-based nanocomposite in the fields of organic and inorganic pollutants adsorption.

The present study is novel, because it investigated the morphological and structural properties of the synthesized ZnO-based nanocomposite using different methods and studied the capability of green-synthesized ZnO-based nanocomposite to remove Pb²⁺ ions as water contaminants.

The current review can be used for the development of environmental pollution control measures.

This paper reviews the rapidly developing field of nanocomposite technology.

The paper aims to present an innovative method for identification of flight modes in the spin maneuver, which is highly nonlinear and coupled dynamic.

To fix the mode mixing problem which is mostly happen in the EMD algorithm, the authors focused on the proposal of an optimized ensemble empirical mode decomposition (OEEMD) algorithm for processing of the flight complex signals that originate from FDR. There are two improvements with the OEEMD respect to the EEMD. First, this algorithm is able to make a precise reconstruction of the original signal. The second improvement is that the OEEMD performs the task of signal decomposition with fewer iterations and so with less complexity order rather than the competitor approaches.

By applying the OEEMD algorithm to the spin flight parameter signals, flight modes extracted, then with using systematic technique, flight modes characteristics are obtained. The results indicate that there are some non-standard modes in the nonlinear region due to couplings between the longitudinal and lateral motions.

Application of the proposed method to the spin flight test data may result accurate identification of nonlinear dynamics with high coupling in this regime.

First, to fix the mode mixing problem in EMD, an optimized ensemble empirical mode decomposition algorithm is introduced, which disturbed the original signal with a sort of white Gaussian noise, and by using white noise statistical characteristics the OEEMD fix the mode mixing problem with high precision and fewer calculations. Second, by applying the OEEMD to the flight output signals and with using the systematic method, flight mode characteristics which is very important in the simulation and controller designing are obtained.

The purpose of this paper is to solve large-scale many-to-many hub location-routing problem (MMHLRP) using variable neighborhood search (VNS). The MMHLRP is a combination of a single allocation hub location and traveling salesman problems that are known as one of the new fields in routing problems. MMHLRP is considered NP-hard since the two sub-problems are NP-hard. To date, only the Benders decomposition (BD) algorithm and the variable neighborhood particle swarm optimization (VNPSO) algorithm have been applied to solve the MMHLRP model with ten nodes and more (up to 300 nodes), respectively. In this research, the VNS method is suggested to solve large-scale MMHLRP (up to 1,000 nodes).

Generated MMHLRP sample tests in the previous work were considered and were added to them. In total, 35 sample tests of MMHLRP models between 10 and 1,000 nodes were applied. Three methods (BD, VNPSO and VNS algorithms) were run by a computer to solve the generated sample tests of MMHLRP. The maximum available time for solving the sample tests was 6 h. Accuracy (value of objective function solution) and speed (CPU time consumption) were considered as two major criteria for comparing the mentioned methods.

Based on the results, the VNS algorithm was more efficient than VNPSO for solving the MMHLRP sample tests with 10–440 nodes. It had many similarities with the exact BD algorithm with ten nodes. In large-scale MMHLRP (sample tests with more than 440 nodes (up to 1,000 nodes)), the previously suggested methods were disabled to solve the problem and the VNS was the only method for solving samples after 6 h.

The computational results indicated that the VNS algorithm has a notable efficiency in comparison to the rival algorithm (VNPSO) in order to solve large-scale MMHLRP. According to the computational results, in the situation that the problems were solved for 6 h using both VNS and VNPSO, VNS solved the problems with more accuracy and speed. Additionally, VNS can only solve large-scale MMHLRPs with more than 440 nodes (up to 1,000 nodes) during 6 h.

The purpose of this paper is to develop a new ontology for knowledge management (KM) technologies, determining the relationships between these technologies and classification of them.

The study applies NOY methodology – named after Natalya F. Noy who initiated this methodology. Protégé software and ontology web language are used for building the ontology. The presented ontology is evaluated with abbreviation and consistency criteria and knowledge retrieval of KM technologies by experts.

All the main concepts in the scope of KM technologies are extracted from existing literature. There are 241 words, 49 out of them are domain concepts, eight terms are about taxonomic and non-taxonomic relations, one term relates to data property and 183 terms are instances. These terms are used to develop KM technologies’ ontology based on three factors: facilitating KM processes, supporting KM strategies and the position of technology in the KM technology stage model. The presented ontology is created a common understanding in the field of KM technologies.

Lack of specific documentary about logic behind decision making and prioritizing criteria in choosing KM technologies.

Uploading the presented ontology in the web environment provides a platform for knowledge sharing between experts from around the world. In addition, it helps to decide on the choice of KM technologies based on KM processes and KM strategy.

Among the many categories of KM technologies in literature, there is no classifying according to several criteria simultaneously. This paper contributes to filling this gap and considers KM processes, KM strategy and stages of growth for KM technologies simultaneously to choice the KM technologies and also there exists no formal ontology regarding KM technologies. This study has tried to propose a formal KM technologies’ ontology.

This study aims to apply a numerical meshless method, namely, the boundary knot method (BKM) combined with the meshless analog equation method (MAEM) in space and use a semi-implicit scheme in time for finding a new numerical solution of the advection–reaction–diffusion and reaction–diffusion systems in two-dimensional spaces, which arise in biology.

First, the BKM is applied to approximate the spatial variables of the studied mathematical models. Then, this study derives fully discrete scheme of the studied models using a semi-implicit scheme based on Crank–Nicolson idea, which gives a linear system of algebraic equations with a non-square matrix per time step that is solved by the singular value decomposition. The proposed approach approximates the solution of a given partial differential equation using particular and homogeneous solutions and without considering the fundamental solutions of the proposed equations.

This study reports some numerical simulations for showing the ability of the presented technique in solving the studied mathematical models arising in biology. The obtained results by the developed numerical scheme are in good agreement with the results reported in the literature. Besides, a simulation of the proposed model is done on buttery shape domain in two-dimensional space.

This study develops the BKM combined with MAEM for solving the coupled systems of (advection) reaction–diffusion equations in two-dimensional spaces. Besides, it does not need the fundamental solution of the mathematical models studied here, which omits any difficulties.

This paper aims to propose an adaptive method for the numerical solution of the shallow water equations (SWEs). The authors provide an arbitrary high-order method using high-order spline wavelets. Furthermore, they use a non-linear shock capturing (SC) diffusion which removes the necessity of post-processing.

The authors use a space-time weak formulation of SWEs which exploits continuous Galerkin (cG) in space and discontinuous Galerkin (dG) in time allowing time stepping, also known as cGdG. Such formulations along with SC term have recently been proved to ensure the stability of fully discrete schemes without scarifying the accuracy. However, the resulting scheme is expensive in terms of number of degrees of freedom (DoFs). By using natural adaptivity of wavelet expansions, the authors devise an adaptive algorithm to reduce the number of DoFs.

The proposed algorithm uses DoFs in a dynamic way to capture the shocks in all time steps while keeping the representation of approximate solution sparse. The performance of the proposed scheme is shown through some numerical examples.

An incorporation of wavelets for adaptivity in space-time weak formulations applied for SWEs is proposed.