Carriers providing truckload freight delivery services can find value in having visibility into future demand for their services to deliver shipments (a.k.a. loads). In the extant literature, the predicted value of this visibility is improved profitability for carriers. We extend this literature by showing that profit is not the only criterion for assessing this visibility (termed future load visibility (FLV) herein). Through extensive computational experiments, we model the effects of FLV on carrier profits as well as on three other criteria that matter to other stakeholders in freight transport ecosystems: (i) ecological consequences of freight transport; (ii) customer service for freight consignors/consignees; (iii) prices that consignors pay for freight delivery. In addition to providing a multi-criteria analysis of FLV, another major novelty of our work is in showing that the level of inter-carrier competition factors into how FLV affects the various criteria. A particularly significant insight from our investigation of situations involving such competition is the seemingly paradoxical finding that carriers’ FLV possession can sometimes impede better outcomes on non-profit criteria. This and other findings yield the paper’s central conclusion that while the decision to acquire FLV is more evidently justified on the profit criterion, it is not an unequivocally optimal decision when non-profit criteria are considered.

The purpose of this investigation was to establish the connection between ownership arrangement and valuation of the ability of a business to carry on. The investigation's goal is to clarify how various ownership forms affect how to assess a company's ability to remain in business. The listed firms at ASE throughout the year 2016–2022, according to this study of 65 covers the years 2016–2022, a dynamic panel system GMM estimation, had demonstrated a substantial degree of ownership structure in line with higher going concern awareness and implementation in Jordan. This study indicated that family ownership, foreign ownership, and block holder ownership were particularly important in affecting Jordan's going concern. This study explores the complex relationship between ownership forms and a company's ability to continue operating. In light of our findings, it is crucial for both practitioners and policymakers to adopt a thoughtful and nuanced approach when assessing the continued viability of businesses. This involves considering the unique ownership structures and governance mechanisms of each company.

Recently, there has been an increase in the use of laser beam welding of mild steel in various industries, including petroleum refineries, power plants, pharmaceuticals, and even residential areas. This research paper focuses on studying the effects of laser welding process parameters, such as laser power and welding speed, on the tensile strength of welds. To do this, three types of laser beam oscillations (sinusoidal path, triangular path, and square path) were performed to weld 125mm x 60 and 1.8 thick sheets of ASTM A36 mild steel alloy. The researchers used statistical tools such as ANOVA to generate mathematical models and experimental designs using the Taguchi method. The results indicate that the optimal welded joint has good mechanical properties after laser welding. For ASTM A36 mild steel, the optimal parameters for laser welding are a laser power of 1800 W, a welding speed of 50 mm/s, and triangular welding mode.

The leaf spring is one of the main components in an automobile which carries the weight of the vehicle and passenger as well as absorbs the vibration and shock produced due to road irregularities. The weight, natural frequency, stress developed, energy absorption, fatigue life, etc. are the key factors that need to be considered to design a leaf spring. Towards that, a novel design integrating a Negative Stiffness Honeycomb Structure (NSHS) in the leaf spring is proposed. The proposed design and the traditional leaf spring are analyzed using the commercially available Finite Element Method (FEM) software Abaqus. Both the traditional and NSHS models were created using Solidworks and modal, harmonic, structural, and transient analyses were performed. It is found that the natural frequency of the NSHS leaf spring is well above the frequency produced due to road irregularities although it is lower than the traditional spring. The total weight of the NSHS spring structure is reduced significantly by 30.73% compared to the traditional spring. Structural analysis shows a lower stress development and higher energy absorption capacity for the NSHS leaf spring. Transient analysis reveals lower mean stress in the proposed NSHS spring. The fatigue life is also found to be 82.78 % higher in the proposed design. The NSHS-incorporated novel leaf spring design may be an excellent alternative to the traditional leaf spring.

Developing a sustainable and environmentally friendly product has become the primary concern in the car manufacturing industry. The new legislation “End of Life Vehicle” increased design complexities of car modules, subsystems, and components in a way that achieves the goals of reducing, reusing and recycling materi-als. The car bumper system is a complicated exterior module designed to prevent physical damage, reduce aer-odynamic drag force, and be aesthetically pleasing to the consumer in addition to End of Life vehicle pro-cessing, which employs dismantling, shredding and landfilling. Design for dismantling is the first step in ELV’s implementation to optimize, the separating of the components and recycling of the materials of the bumper system. This study focused on the analysis of the ELV’s value in redesigned solutions of a new car bumper system in comparison to the current bumper one (case study). It provided a guideline to address the critical considerations in selecting materials, dismantling bumpers’ components and joining bracket to facilitate dismantling, separating, and recycling.

This article introduces a comprehensive analysis of 20 leading companies, scrutinized through their financial metrics across various sectors. By deploying multi-criteria decision-making (MCDM) techniques, we aim to offer investors a clear and objective perspective on which companies stand out as the best investment options. Among the MCDM techniques, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is utilized, renowned for its efficiency in handling complex decision-making scenarios which is conducted by two clauses. 1) Implementing TOPSIS with assigning equal weights and same share to every chosen metrics as criteria and 2) employ BWM (Best Worst Method) to calculate these weights base on their significance and relevancy to the prosses of ranking. According to the Result gained from the computation, ranks 1 to 5 belong to the similar companies with both assumptions which are Ford Motor Co, BP plc, Tesla Inc, General Motors Co and Exxon Mobil Corp. The consistency in rankings across two different weighting assumptions highlights the robustness of the criteria used, ensuring stable and reliable outcomes. This enhances the credibility of the findings, making them more trustworthy and citable for those who seek reliable and robust methodologies for informed investment decisions.

This work aims to make a unique polymer to be used as a conductive and flexible chip antenna. Its properties are robustness, rigidity, stretchability, and good conduction. The fabricated composite is composed of two copolymers, Polydimethylsiloxane (PDMS) and Polyethylenimine (PEI), assembled with nano metals (Copper, Silver), and graphene nanoparticles as a matrix. Nano metals fill out the inter-layer space, and polymer voids reinforce the cross linker. Graphene/metal nanoparticles help make chelating complexes using metallic bonds, enhancing the polymer’s conductivity from 1.87 × 10-4 to 5.64 ×10-6 σ Scm-1. The conductivity, self-healing, and surface morphology of fabricated composite are analyzed using different spectroscopic techniques, such as electrochemical impedance (EIS), Scanning Electronic Microscopy (SEM), Transition Electronic Microscopy (TEM), Infrared spectroscopy (IR), UV-Visible spectroscopy (UV), and a particle size analyzer.

The rapid urbanization and digital transformation of modern cities demand intelligent infrastructure capable of supporting massive IoT deployments and real-time decision-making across diverse smart city applications. The evolution toward sixth-generation (6G) wireless networks introduces unprecedented challenges for task offloading due to ultra-low latency, massive connectivity, and heterogeneous device requirements in urban environments. Traditional methods face limitations in scalability, adaptability, and multi-agent coordination needed for city-scale deployments. To address these gaps, we propose the Heterogeneous Graph Transformer Deep Q-Network with Nash Equilibrium Integration (HGT-DQN-NEI), a novel framework that synergistically combines graph neural networks, transformer architectures, reinforcement learning, and game-theoretic principles for intelligent multi-agent task offloading. The heterogeneous graph transformer effectively models complex 6G topologies, while the Deep Transformer Q-Network enhances decision making under partial observability. A distributed Nash equilibrium mechanism ensures stable coordination among agents with provable convergence guarantees. Extensive experiments validate the proposed approach across diverse scenarios, including urban, highway, industrial, and rural deployments. Results demonstrate a 23.4% reduction in task completion latency, 31.7% improvement in energy efficiency, and 18.9% enhancement in resource utilization compared to state-of-the-art baselines. The framework achieves stable convergence within approximately 30–50 episodes and scales efficiently to networks with over 1000 heterogeneous agents, while maintaining sub-millisecond decision times essential for smart city applications.

This paper introduces a new algorithm in Steganography for concealing secret messages or images within digital images. The algorithm is designed to produce stego images that can be transmitted to recipients without detection by potential attackers, thereby ensuring secure communication channels. The proposed algorithm employs a multi-level randomization technique to embed data within randomly selected cover images, with each byte of the secret image distributed across multiple cover images. This approach contrasts with conventional methods that hide data within a single cover image. Moreover, the algorithm incorporates a load-balancing priority system, a critical feature that ensures uniform stego image quality across the dataset. This strategic approach minimizes variations in Peak-Signal-to-Noise-Ratio (PSNR) values, contributing to consistent performance during data hiding and extraction processes and enhancing communication security. The security and recoverability of the secret image are further improved by a simplified Cipher key system based on SHA-256, which facilitates pseudo-random number generation. This system ensures that the hidden image can be recovered at the receiver's end, even in the face of potential attacks. Experimental results demonstrate comparable PSNR quality to existing methods, particularly when utilizing equal total resolution to deep hiding algorithms. Notably, the proposed algorithm offers an alternative to encryption by leveraging randomization, thereby complicating data extraction for potential attackers by distributing data across multiple images with a randomly generated cipher key.

The influence of loading type on tensile and tearing fracture resistance of ballast rock was assessed using edge-notched diametrically compressed disc (ENDC) and edge-notched disc bend (ENDB) test geometries. The geometry of these two specimens was similar; however, their loading type (i.e., three-point bend and diametral compressive) was different affecting the geometry factors. The obtained pure tensile fracture toughness (KIc) using the ENDB test was higher than the ENDC test. In contrast to tensile fracture toughness, the pure tearing fracture toughness (KIIIc) in the ENDC test was higher than the ENDB fracture test. The obtained experimental data were explained in terms of crack propagation path, since two distinct trajectories were observed for both configurations under tearing deformation.