Hub location is crucial for resilient and uninterrupted supply chain operations, particularly during disruptions or unforeseen events. In this paper, we propose a resilience hub location framework for Third Party Logistics (3PL) companies with two key objectives: optimizing demand flows and establishing a resilient network capable of with-standing sudden disruptions. The study aims to identify the key criteria that contribute to the successful implementation of the resilient center. The proposed structure utilizes a two-phase decision-making methodology. The first phase presents a new Multi-Criteria Decision-Making (MCDM) approach called SWARA-EDAS method that evaluates and ranks potential locations based on resiliency criteria. The second phase proposes an optimization model to determine the optimal hub location. To illustrate the approach, a real-world case study of a 3PL company in Tehran is included. Due to the absence of precise demand data in the case study, a novel clustering approach is proposed to estimate the demand flow. Each cluster can be considered as a distinct demand point, and a clustering analysis involving 122 regions within Tehran is conducted, taking into account various factors such as population, economic index, accessibility to the Internet, and the number of business units. To enhance the resiliency of the network, mobile distribution centers are also deployed. These mobile centers not only provide flexibility but also serve as backup capabilities in the event of a disruption or failure at the fixed hub. The proposed structure offers practical in-sights for 3PL companies seeking to implement a resilient network structure.

This paper investigates experimentally and numerically the influence of geometry and loading conditions on the fracture response of rock materials. Seven different test samples namely “Edge-Notched-Disc-Bend (ENDB), Semi-Circular-Bend (SCB), Three-Point-Bend-Inclined-Crack (TPB-IC), Single-Edge-Notched-Bending (SENB), Asymmetric-Three-Point-Bend (ATPB), Edge-Notched-Disc-Compression (ENDC) and Double-Notched-Disc-Compression (DNDC)” made of a marble rock were manufactured and tested under bending and compressive loading conditions. The results showed that the failure loads of all samples increase with the change of pure mode I to pure mode III. However, the corresponding fracture toughness values of ENDB, SCB, TPB-IC, SENB and ATPB specimens decreased, while the ENDC and DNDC samples experienced an increase in the fracture toughness. Among the studied specimens, only the ENDB, ENDC and DNDC samples presented pure mode III with KIIIc/KIc ratio ranging from 0.735 for the ENDB specimen to 2.076 for the DNDC sample. The highest mode-I fracture toughness among all the studied specimens was obtained for the SENB and TPB-IC samples, with a value of 1.54 MPa m0.5, while the lowest value was obtained for the DNDC specimen with a value of 1.21 MPa m0.5. The sign and the magnitude of T-stress considerably depended on the loading condition and geometry of the specimens. The crack trajectories of all specimens under study were also investigated.

Retraction: The editors of Engineering Solid Mechanics retract this article [1] due to severe plagiarism.

Considering the increasing demand for cosmetic surgery and the number of private cosmetic surgery clinics, it is essential to measure and manage the quality of services provided by these clinics. Obtaining sufficient knowledge about the content perceived by the clients of the quality of services provided by specialized clinics can affect identifying improvement opportunities and criteria that will cause their competitive advantage, and on the other hand, it also prevents wasting resources. For this purpose, this study aims to identify, evaluate, and prioritize the criteria for quality improvement in cosmetic surgery clinics. First, the effective criteria focus on the quality of medical services have been identified by reviewing the research background. Then, the identified criteria in the case study are customized by the Delphi method, and then the DEMATEL-based analytic network process method (DANP) is applied to reveal their causal relationships between criteria and sub-criteria to determine the direct and indirect influences, and finally, all of them are prioritized. In the end, based on the obtained results and knowledge of experienced medical experts in the case study, some managerial solutions are proposed to improve the quality of the provided medical services.

This paper reviews context and results of a software tool, named SaTrade, for Model Based System Engineering in System Design of a CubeSat. This tool helps designers to go through system design trade offs easily in System and Subsystem Levels. To achieve this, Modeling for subsystem design has been made using Block Diagram Definitions and implemented in codes with Inputs from System Design and Outputs to Subsystem specifications and Design Integration. Another Feature of SaTrade is change and modification control and management, where it can be from Requirements or other Inputs from System Design or Interfaces. Changes will be affected on the System Design to allow the Designers follow the process by simulations for Integrity check and Evaluation. The first version of SaTrade focuses on Satellite Structure Design and Configuration Management more, using its Neural Network Algorithms dedicated for this purpose, however, it is intended to make paperless automated design available for the whole CubeSat System in the next version.

Hyperbranched polyester polyols have emerged as a promising candidate for polyurethane coatings due to their unique structure and properties. In this context, this paper aims to synthesize a new hyperbranched polyester polyol and evaluate its potential as a polyol for polyurethane coating applications. In this study, the synthesis of hyperbranched polyester polyol involves the reaction between a multifunctional alcohol and a multifunctional carboxylic acid or anhydride. It is further modified by incorporating 2-hydroxyethyl methacrylate and styrene. The properties of the polyester polyol were characterized using various analytical techniques, including FTIR, NMR, SEM and TGA. This paper also provides a discussion on the potential applications of the synthesized hyperbranched polyester polyol in several industries such as automotive, aerospace and construction.

This research investigates the relationships between investors’ behavioral biases and compares their relative importance. For this purpose, a survey is conducted, and analytical methods are used. The sample for this study has been 512 individual investors of the Tehran Stock Exchange who completed an online questionnaire. The respondents replied about their behavior in different situations to analyze the prevalence of asymmetric discounting, mental accounting, shifting risk preference, loss aversion, regret aversion, overconfidence, proxy decision making, ambiguity aversion bias, anchoring, and herd behavior as significant fields of behavioral biases in their investment decisions. The data is analyzed using two different analytical techniques. A model based on structural equations is designed and tested to analyze the relations between these fields. Another integrated method, the DEMATEL-based analytic network process, is also used to prioritize and rank these behavioral biases. Finally, the results are compared and confirmed by each other. Analyzing the results proves the existence of 19 positive and statistically significant relations between these fields. Thus, an increase or decrease in the intensity of a particular field of behavioral biases in one’s decisions significantly affects the intensity of other fields. The present study finds that shifting risk preference, anchoring, loss aversion, and regret aversion are the most important fields of behavioral biases based on their prevalence among investors and their correlations with other biases.

While decent work has emerged as the central theme of the psychology of work theory and a global concept and directive for promoting social, political, and economic justice, it has garnered increasing scientific and political attention in the past two decades. However, until now, no defined measurement scale for the pharmaceutical supply chain exists. The present study aims to design and validate key performance indicators (KPIs) for 'decent work' in the pharmaceutical industry supply chain of Iran, using the Decent Work Daffi Scale (2017) as a reliable framework with five sub-scales and 15 items, tested and validated. For the validation of the Decent Work Scale, a quantitative survey study was conducted among selected pharmaceutical industry experts with a sample size of 228 individuals in the year 2023. The current study adopted an exploratory factor analysis approach using SPSS software and a confirmatory factor analysis through AMOS version 24 software. In this context, the factor structure, convergent validity, discriminant validity, and Cronbach's alpha coefficients were examined. The results showed that the five-factor structure outperforms the one-factor model with evidence supporting the convergent, discriminant, and predictive validity of the five-factor scale. Thus, the measurement of decent work in the pharmaceutical industry of Iran comprises five sub-scales: occupational safety conditions, access to healthcare, adequate remuneration, Free time and rest, and alignment of organizational values with family and societal values. This scale can serve as a useful tool for industrial and organizational psychology research, as well as for studies on the sustainability of social supply chains.

Adhesive joints play a vital role in different industries owing to their advantages and ease of application compared to other joining methods. This research focuses on enhancing the mechanical properties of epoxy adhesives by incorporating graphene nanoplatelets (G) and iron-oxide nanofillers (Fe3O4). Single-lap adhesive joints, including both G and Fe3O4 nanoparticles, are fabricated at 2%, 3%, and 4% weight percentages and tested under tensile load at ambient, 45°C, and 88°C. The results reveal that adding G and Fe3O4 nanofillers enhances shear strength at elevated and room temperatures without altering the epoxy glass transition temperature (Tg). Furthermore, G nanofiller performs better in improving shear strength than Fe3O4. The optimal weight percentage is identified as 3 wt% for G and Fe3O4, as higher percentages lead to decreased shear strength due to agglomeration

Maintenance philosophies and their activities have always been a major concern in industry. So, every industrial complex needs a clear and comprehensive maintenance plan to keep its equipment reliable and available. In this study, we proposed an AHP model combined with the BOCR method to select the most reliable maintenance strategy for a combined cycle power plant (GTG-HRSG). Five well-known maintenance alternatives including root cause analysis, condition-based maintenance, reliability-centered maintenance, run-to-failure and preventive maintenance are chosen to be evaluated by several experts from various departments of operation, planning and maintenance via three priorities of economic, technical and operation and 30 sub criteria and controls. Then, five different BOCR synthesize methods have been utilized to rank maintenance alternatives. The final result shows that four out of five synthesize methods have ranked RCA as the top maintenance strategy and RCM as second. In one other method, the rank of these two strategies is vice versa.