We live in a nature full of different colors around us. Different areas of science were interested understanding the means of colors been produced in nature. Three main sources have been identified for nature’s colors: pigments, structural colors and bioluminescence. Structural colors are a different way in producing color which is not based on pigments. Many various types of creatures such as beetles, butterflies and peacock feather show bright and attractive colors based on structural colors. Structural color is a special one, which is the color produced from complex interaction between light and sophisticated nano- or micro-structures. The most common mechanisms of structural colors are film interference, diffraction grating, scattering and photonic crystals. Film interference is the mostly used one. The mechanisms mentioned are used independently or combined with each other in nature. Along with animals which are best known for structural colors, there are many examples of plants in case too. This paper presents an overview of various relevant mechanisms in nature and focus on diffraction grating in details. Diffraction gating is rare than other methods and produces iridescent colors. Some examples of it have been recognized in opals, beetles, butterflies and some plants like hibiscus and tulip flowers.

Flexible risers are one of the crucial pieces of equipment for moving the output fluid from the well to the platform during the extraction of oil and gas from deep sea resources. One of the causes of collapse in these pipes is the high hydrostatic pressure that is applied to the riser in deep water. Its innermost layer, known as the carcass, is the layer that plays the most significant role in the resistance to external pressure. This article uses the finite element method to investigate the collapse (non-linear buckling) of the riser under pressure from the outside. A new design that draws inspiration from the structure of a beetle's exoskeleton has been presented to increase the load capacity of the carcass layer. This type of beetle's skeleton is constructed in such a way that it creates a strong connection between various parts of the external skeleton to produce high strength against external pressures while still allowing for the necessary movement flexibility. To assess how well the new design performs in comparison to the original, nonlinear buckling of the new structure under external pressure has been examined. The critical pressure in the new design is increased compared to the old design.

In this research, with the help of the recently developed Dung Beetle Optimizer (DBO) algorithm, the main dimensions of container ships in terms of their loading capacity and their speed with the aim of minimum hydrodynamic resistance along with several constraints such as permissible range of main dimensions, hydrostatic stability, and specified underwater volume, has been optimized. For this purpose, the governing equations were extracted from Holtrop's experimental method. For verification, the results obtained from the DBO algorithm were compared with the results of the Optimization library of Maple software.  The optimization results on the dimensions of a container ship with a capacity of 1000 TEU showed that the hydrodynamic resistance of the optimized ship at a speed of 15 knots can be reduced by about 14% and at a speed of 19 knots by about 21%. Also, in constant displacement, with the increase of the vessel speed, the optimized vessel length increases, but its draft decreases. In particular, the purpose of this research is to introduce the capabilities of the DBO algorithm and its application in solving optimization problems in marine engineering.

Industrial estates are concentrated in a geographical area that facilitates the production process due to the nature of their formation and creation. In Kerman province, which is one of the centers of weaving and production of handmade carpets, the establishment or development of weaving workshops in industrial estates has been a challenge. The process of producing handmade carpets is done in different ways at home and in the workshops (Centralized production workshops). Handmade carpets are one of the most important strategic goods in terms of job creation and non-oil exports. Handmade carpets are produced in the home or central workshops. In different cities, some central workshops are located in industrial towns. Each method of production has its own advantages and disadvantages. The purpose of this study was to explain the SWOT matrix for establishing hand woven-carpet manufacturing workshops in Kerman industrial towns. The statistical population included all the carpet experts and producers in Kerman. The statistical sample was 35 handwoven carpet experts who were tested using a bullet-proof method. The research data were collected through library studies, and questionnaires and data were analyzed using SPSS software and SWOT matrix. The results showed that the most important strengths of carpet workshops in Kerman industrial towns were: high added value compared to domestic production, high relative advantage for production costs, high quality of carpets, coherence of the production process at the workshops, and also the ability to fill vacant capacity through outsourcing. The most important weaknesses were: the high cost of transportation and maintenance of raw materials, human resource inflation, supply problems of raw materials, beetle damage for carpets, and high primary investment to start the work. The most important opportunities were: the use of raw material sources of the province (Sirjan wool), the abundant and relatively cheap labor, lowering the total price, and the most important threats are the volatility of the market for the purchase of raw materials, the weakness of distribution and transportation networks, the lack of standards and supervision, the lack of accurate statistics and information of carpet production conditions. The results showed Kerman has a general view of the infrastructure of the establishment of carpet workshops in industrial towns. However, there are still many threats that can be overcome if macro-management operates.

This paper explores the realm of optimization by synergistically integrating two unique metaheuristic algorithms: the Wild Horse Optimizer (WHO) and the Fireworks Algorithm (FWA). WHO, inspired by the behaviors of wild horses, demonstrates proficiency in global exploration, while FWA emulates the dynamic behavior of fireworks, thereby enhancing local exploitation. The goal is to harness the complementary strengths of these algorithms, achieving a harmonious balance between exploration and exploitation to enhance overall optimization performance. The study introduces a novel hybrid metaheuristic algorithm, WHOFWA, detailing its design and implementation. Emphasis is placed on the algorithm's ability to balance exploration and exploitation. Extensive experiments, featuring a diverse set of benchmark optimization problems, including general test functions and those from CEC 2005, CEC 2019, and 2022, assess WHOFWA's effectiveness. Comparative analyses involve WHO, FWA, and other metaheuristic algorithms such as Reptile Search Algorithm (RSA), Prairie Dog Optimization (PDO), Fick’s Law Optimization (FLA), and Ladybug Beetle Optimization (LBO). According to the Friedman and Wilcoxon signed-rank tests, for all selected test functions, WHOFWA outperforms WHO, FWA, RSA, PDO, FLA, and LBO by 42%, 55%, 74%, 71%, 48%, and 52%, respectively. Finally, the results derived from addressing real-world constrained optimization problems using the proposed algorithm demonstrate its superior performance when compared to several well-regarded algorithms documented in the literature. In conclusion, WHOFWA, the hybrid metaheuristic algorithm uniting WHO and FWA, emerges as a powerful optimization tool. Its unique ability to balance exploration and exploitation yields superior performance compared to WHO, FWA, and benchmark algorithms. The study underscores WHOFWA's potential in tackling complex optimization problems, making a valuable contribution to the realm of metaheuristic algorithms.