Asphaltic concrete mixtures are among the most common construction materials for the pavement of roads. As a multi-phase composite mixture with randomly distributed aggregates inside the mastic part, the mechanical properties of such materials can be influenced by different factors. Cracking and induced fracture is among the common degradation and failure modes in these construction mixtures that often takes place in cold regions. In this research, the effects of some influencing parameters including temperature, air void percentage and loading rate are investigated experimentally on the fracture toughness (K_Ic) and work of fracture (W_Ic) of hot mix asphalt material. Edge notched semi-circular bend (SCB) specimen was employed to conduct mode I fracture experiments. The thickness of SCB samples were considered as variable and the HMA mixtures were tested with two SCB thicknesses of 30 and 60 mm. The experimental results showed that both fracture toughness and fracture work are increased by increasing the thickness. However, the effect of thickness on the fracture work was much more significant than the K_Ic value. Also, the fracture and cracking resistance parameters were increased by decreasing the temperature and air void content. Both K_Ic and W_Ic values were also increased by increasing the loading rate in the investigated range of 1 to 8 mm/min. The most influencing parameters on the change of fracture resistance parameters were the temperature, loading rate, air void content and thickness, respectively.

The intention of this paper is to propose some similarity measures between Fermatean fuzzy sets (FFSs). Firstly, we propose some score based similarity measures for finding similarity measures of FFSs and also propose score based cosine similarity measures between FFSs. Furthermore, we introduce three newly scored functions for effective uses of Fermatean fuzzy sets and discuss some relevant properties of cosine similarity measure. Fermatean fuzzy sets introduced by Senapati and Yager can manipulate uncertain information more easily in the process of multi-criteria decision making (MCDM) and group decision making. Here, we investigate score based similarity measures of Fermatean fuzzy sets and scout the uses of FFSs in pattern recognition. Based on different types of similarity measures a pattern recognition problem viz. personnel appointment is presented to describe the use of FFSs and its similarity measure as well as scores. The counterfeit results show that the proposed method is more malleable than the existing method(s). Finally, concluding remarks and the scope of future research of the proposed approach are given.

The Zinc doped calcium borate (Zn-CaB) was synthesized by the co-precipitation method. Zinc was known to exhibit a good antimicrobial effect without causing any environmental issues. However, the antimicrobial activity of zinc is relatively low as compared to silver or copper analogues. In the present investigation, an attempt was made to incorporate zinc in the matrix of calcium borates to enhance the antibacterial effect. Cosmetic products were made using the zinc-calcium-borates and the antibacterial/antifungal activity was evaluated and compared with the commercial products. The studies revealed that the antibacterial activity of Zn-CaB was equivalent to that commercially available product with a maximum of 99% reduction in bacterial strains and above 95% reduction in fungal strains. An attempt was made to incorporate a bacteriostatic effect on fabric by adding zinc-calcium-borates to detergent which exhibited prolonged antibacterial activity, even after 3 washing cycles. The cosmetic products were also evaluated for their thermal and photostability.

Most job shops in practice are constrained by both machine and labor availability. Worker assignment in these so-called Dual Resource Constrained (DRC) job shops is typically solved in the literature via the use of meta-heuristics, i.e. “when” and “where” rules, or heuristic assignment rules. While the former does not necessarily lead to optimal results, the latter suffers from high computational time and complexity, especially when there is a large number of workstations. This paper uses game theory to propose a new worker assignment rule for DRC job shops. The Gale-Shapley model (also known as the stable marriage problem) forms a ‘couple’ made up of a worker and machine following a periodic review strategy. Simulation is used to evaluate and compare the proposed model to “when” and “where” rules previously proposed in the literature. Simulation experiments under different conditions demonstrate that the Gale-Shapley model provides better results for worker assignments in complex DRC systems, particularly when the workers have different efficiency levels. The implications of the findings for research and practice are outlined.

Gas Metal Arc Welding (GMAW) is an extensively implemented arc welding process through the control of input process parameters and the metal from the filler wire. Despite its popular use in various industries, the complex interrelationship between the actual bead and the varying welding parameters makes it challenging to predict appropriate bead geometries via mathematical modeling in a continually changing welding process. In this study, the Regression Learner App was used to compare the performance of supervised Machine Learning (ML) predictive models comprising the Linear Regression (LR), Regression Tree (RT), Support Vector Machine (SVM), Ensembles of Tree (ET), Gaussian Process Regression (GPR), and Artificial Neural Network (ANN) using GMAW dataset. The dataset was scaled and normalized at a range of -1 to +1 to facilitate the visualization of the variation effect. The wire feed speed, voltage, weld velocity, unmelted wire length, and melted wire volume were considered as the input parameters to predict the bead geometry. In addition, the five-fold cross-validation was employed to avoid overfitting and poor generalization. Finally, statistical indicators, namely the Coefficient of Determination (R²), Root Mean Squared Error (RMSE), and Mean Absolute Error (MAE), were performed on all developed models to evaluate their performance. Thus, the fine tree and ANN models achieved the highest prediction accuracies of 88–91%, signifying their potential use in future research. In short, the present study demonstrated the performance of various supervised ML algorithms for bead geometry prediction, which would assist the selection of appropriately supervised ML algorithms in future studies.

Multicriteria Decision Making (MCDM) is one the most important branches of decision theory. Due to the fact that MCDM methods have the utmost significance in management, scholars try to develop more MCDM methods. Since calculating the weights of criteria is an important step in any MCDM method, increasing the accuracy of weight calculating methods can highly affect these methods. This accuracy can be improved by less pairwise comparison between criteria. To this end, the present study seeks to make a comparison between two new weight calculating techniques, namely BWM and FUCOM in a fuzzy environment using a real-world case study Results of this study shows that FUCOM-F provides more reliable results compared to FBWM since its consistency is less than FBWM by a great amount.

The FT-IR spectrum of salicylic acid (SA) was studied in the region 10-4000 cm-1. The optimized molecular geometry and fundamental vibration frequencies are interpreted using structural optimizations based on the Functional Density Theory (DFT) method. Additionally, we used B3LYP / 6-311G (d, p) to determine the chemical descriptor, the ionization potential (I), the electron affinity (A), the chemical potential (μ), the chemical hardness (η). Nonlinear optical descriptors (NLO) such as dipole moment (μ), polarizability (α), first hyperpolarizability (β) and second hyperpolarizability (γ), 3D maps of HOMO and LUMO orbitals, lengths and Bond angles of salicylic acid isomers are also determined by both DFT and MP2 (The Møller-Plesset theory of order 2 perturbation) methods. The overall descriptors and the non-linear optical properties confirmed that salicylic acid is the reactive molecule and para-hydroxybenzoic acid is the stable molecule. An electrostatic molecular potential (MEP) study was also performed to determine the reactivity of molecules.

This paper introduces a covering model for collaborative bidirectional multi-period vehicle routing problems under profit-sharing agreements (CB-VRPPA) in bulk transportation (BT) networks involving one control tower and multiple shippers and carriers. The objective is to maximize the total profits of all parties subject to profit allocation constraints among carriers, terminal capability limitations, transport capability limitations and time-window constraints. The proposed method includes three stages: (a) generate all feasible routes of each carrier, (b) eliminate unattractive feasible routes via a proposed screening technique to reduce the initial problem size, and (c) solve the reduced problem using a branch-and-bound algorithm. Computational experiments are performed for real-life, medium- and large-scale instances. The proposed method provides satisfactory results when applied to solve the CB-VRPPA. We also conduct a sensitivity analysis on a critical parameter of the profit-sharing agreement to confirm the effectiveness of the proposed method.

Mini-Hydrostatic Pressure Apparatus (MHSPA), of spatial size 230×210×210 mm³, was developed for individual or limited number of users to promote Covid-19 social distance protocol. A solid hemisphere with an inclined circular segment made from gypsum material (CaSO₂.0.5H₂ O) and coated with filler putty and oil paint, is used in place of the regular quadrants. With the solid attached to a horizontal beam mounted over a pivot, hydrostatic forces due to liquids were measured at different heights of water. The results showed that the assembly could be used to demonstrate variation of hydrostatic pressure on circular surfaces at different heights of liquid with an average difference of 4.38% against average theoretical values. Compared to other results from the use of conventional quadrants in literature, the associated error is minimal, and indicates the possibility of adopting the apparatus in school laboratories for static pressure demonstration.

Field experiments were carried out for two consecutive seasons at the Experimental Shandaweel Agricultural Research Station, Sohag Governorate, Upper Egypt, during the growing seasons of 2013 and 2014, to study the effect of irrigation intervals and foliar spray of zinc and silicon treatments on chemical composition of maize. Results indicated that scheduling at every 10 days produced the N% , Crude protein%, Cu%, P%, K%, Zn%, Si%, Mn% and Fe% and foliar spray of zinc and silicon treatments produced the highest chemical composition of maize crop. The best N%, Crude protein%, Cu% and Mn were obtained from zinc + silicon treatments followed by zinc, silicon treatments. In contrast, untreated treatments produced the lowest values. It can be concluded that the scheduling at every 10 days and application of foliar spray of zinc + silicon treatments as the effective one could be recommended for scheduling irrigation at every 10 days with application of foliar spray of zinc, silicon or zinc +silicon treatments of maize crop at Shandaweel Agricultural Research Station, Sohag Governorate, Upper Egypt to obtain the best results from chemical composition of maize.