•A comprehensive review of the monarch butterfly algorithm is proposed.•The different variants based on monarch butterfly algorithm are analyzed.•The hybridizations of monarch butterfly algorithm are ...reviewed.•The applications of monarch butterfly algorithm are described.
Swarm intelligence (SI) is the collective behavior of decentralized, self-organized natural or artificial systems. Monarch butterfly optimization (MBO) algorithm is a class of swarm intelligence metaheuristic algorithm inspired by the migration behavior of monarch butterflies. Through the migration operation and butterfly adjusting operation, individuals in MBO are updated. MBO can outperform many state-of-the-art optimization techniques when solving global numerical optimization and engineering problems. This paper presents a comprehensive review of the MBO algorithm including its modifications, hybridizations, variants, and applications. Additionally, further research directions for MBO are discussed. This review study serves as a solid reference for future studies in the arena of SI and in particular the MBO algorithm.
Cellulose nanofibers (CNFs) with an average diameter of 22 nm were prepared from sugar beet pulp (SBP) via an environmentally-friendly method. Steam-explosion pretreated SBP was treated with hydrogen ...peroxide (H₂O₂) bleaching, high-speed blending, and ultrasonic treatment. Thermogravimetric analysis showed that hemicellulose was partially hydrolyzed in the steam-cooking stage, pectin was removed in the explosion stage, and lignin was removed by H₂O₂ bleaching. The removal of non-cellulosic components was confirmed by Fourier-transform infrared (FT-IR) spectroscopy. Morphological analysis showed that steam-explosion pretreatment largely extracted the binder materials of hemicellulose and pectin. This exposed the microfibrillated cellulosic fibers, which promoted subsequent nanofibrillation. X-ray diffraction showed that the CNFs had a crystallinity index of 62.3%. The CNFs had good thermal stability, and thus have potential for use as fillers in polymer matrices. The only chemical reagent used in this green method was H₂O₂. Combining H₂O₂ bleaching with steam explosion, high-speed blending, and ultrasonic treatment reduced the overall energy consumption and increased the efficiency of the CNFs extraction. The method, therefore, has potential application in industrial processes.
Large‐scale and low‐cost preparation of carbon‐based potassium anode with long life and high capacity is one of the footstones for the development of potassium ion batteries (PIBs). Herein, a ...low‐cost carbon‐based material, cross‐linked hollow graphitic carbon (HGC), is large scale synthesized to apply for PIBs anode. Its hollow structure can afford sufficient space to overcome the damage caused by the volume expansion of graphitic carbon (GC). While the cross‐linked structure forms a compact interconnection network that allows electrons to rapid transfer between different GC frameworks. Electrochemical measurements demonstrated that the HGC anode exhibited low charge/discharge plateau (about 0.25 V and 0.1 V) and excellent specific capacity as high as 298 mA h g−1 at the current density of 50 mA g−1. And more important, after 200 cycles the capacity of HGC anode still shows 269 mA h g−1 (the decay rate of per cycle is only 0.048%). Meanwhile, the use of commercial traditional electrolyte (KPF6) and cheap raw materials that provide new hope for trying and realizing the large‐scale production of PIBs based on carbon anode materials.
The unique three‐dimensional structure with cross‐linked of hollow graphitic carbon (HGC) is successfully prepared, which achieve excellent potassium storage performance when used as the anode of potassium ion batteries.
The discounted {0–1} knapsack problem (D{0–1}KP) is a kind of knapsack problem with group structure and discount relationships among items. It is more challenging than the classical 0–1 knapsack ...problem. A more effective hybrid algorithm, the discrete hybrid teaching-learning-based optimization algorithm (HTLBO), is proposed to solve D{0–1}KP in this paper. HTLBO is based on the framework of the teaching-learning-based optimization (TLBO) algorithm. A two-tuple consisting of a quaternary vector and a real vector is used to represent an individual in HTLBO and that allows TLBO to effectively solve discrete optimization problems. We enhanced the optimization ability of HTLBO from three aspects. The learning strategy in the Learner phase is modified to extend the exploration capability of HTLBO. Inspired by the human learning process, self-learning factors are incorporated into the Teacher and Learner phases, which balances the exploitation and exploration of the algorithm. Two types of crossover operators are designed to enhance the global search capability of HTLBO. Finally, we conducted extensive experiments on eight sets of 80 instances using our proposed approach. The experiment results show that the new algorithm has higher accuracy and better stability than do previous methods. Overall, HTLBO is an excellent approach for solving the D{0–1}KP.
A novel hierarchical architecture—N-doped hollow carbon fibers decorated with N-doped carbon clusters (NHCF@NCC)—was synthesized for high-performance anode material of potassium ion batteries (PIBs). ...The material is formulated with porous N-doped hollow carbon fibers as the backbone, which effectively shortens the diffusion length of potassium ion and increases the interface between the electrode and electrolyte. In addition, the N-doped carbon clusters attached on the hollow carbon fibers can provide abundant reactive sites. Specially, NHCF@NCC could form a freestanding electrode with a three dimensional interconnected conductive network owing to the ultrahigh aspect ratio. In this way, NHCF@NCC delivers an excellent electrochemical performance as free-standing anode materials of PIBs, exhibiting a high reversible capacity of 310 mA h g
−1
at a current density of 100 mA g
−1
, a long cycling stability of 1000 cycles with negligible degradation, and a superior rate performance of 153 mA h g
−1
at a large current density of 2000 mA g
−1
.
Display omitted
•TiO2 coated MWCNTs were synthesized in aqueous solution.•The dielectric constant of PLA composite was improved significantly with a low increase in dielectric loss.•The thermal ...stability and storage modulus of PLA were enhanced.
Titanium dioxide decorated multi-walled carbon nanotubes (MWCNTs@TiO2) were fabricated in aqueous solution via a facile sol-gel method. The results of TEM, XRD, XPS and TGA confirmed that TiO2 had been coated on the surface of MWCNTs successfully. The polylactide (PLA) nanocomposites containing various content of MWCNTs@TiO2 were prepared by a solution mixing method, followed by a hot compression process. The results revealed that the introduction of MWCNTs@TiO2 enhanced the thermal stability and crystallinity of PLA without affecting the crystal phase. Moreover, the PLA nanocomposite containing of 5 wt% MWCNTs@TiO2 had a dielectric constant of 26.6, which was 8.3 times higher than that of the pure PLA (3.2), while the dielectric loss still remains at a low value of 0.2 at 1000 Hz. The decorated TiO2 nanoparticles on the surface of MWCNTs could serve as insulating layers to suppress the dielectric loss effectively.
Protein kinase R (PKR)-like endoplasmic reticulum kinase (PERK) is activated in response to a variety of endoplasmic reticulum stresses implicated in numerous disease states. Evidence that PERK is ...implicated in tumorigenesis and cancer cell survival stimulated our search for small molecule inhibitors. Through screening and lead optimization using the human PERK crystal structure, we discovered compound 38 (GSK2606414), an orally available, potent, and selective PERK inhibitor. Compound 38 inhibits PERK activation in cells and inhibits the growth of a human tumor xenograft in mice.
Understanding the effects of green credit on green total factor productivity (GTFP) is conductive to promoting the sustainable economy development. This paper examines the total effects, influence ...mechanism, and heterogeneous impacts of green credit on GTFP based on GTFP data of 30 provinces in China from 2008 to 2017. The findings show that, firstly, on the whole, green credit significantly increases GTFP, which is tested by the panel regression model. Secondly, according to the result of the panel quantile model, the increasing effect of green credit on GTFP is strengthened by the improvement of GTFP. Thirdly, green credit has heterogeneous impact on GTFP, which is reflected in economic development with different level, especially for different degrees of environmental regulation. Fourthly, under the full samples, green credit impacts GTFP through green technology innovation, but it has no effect on energy consumption structure. Besides, the influence mechanism is heterogeneous in the variation of sample characteristics. Finally, some significant policy recommendations are provided for policymakers based on these conclusions.
PDF
