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Demonstrate proof-of-concept for conducting NFL Draft trades on a blockchain network using smart contracts.

Using Ethereum smart contracts, the authors model several types of draft trades between teams. An example scenario is used to demonstrate contract interaction and draft results.

The authors show the feasibility of conducting draft-day trades using smart contracts. The entire negotiation process, including side deals, can be conducted digitally.

Further work is required to incorporate the full-scale depth required to integrate the draft trading process into a decentralized user platform and experience.

Cutting time for the trade negotiation process buys decision time for team decision-makers. Gains are also made with accuracy and cost.

Full-scale adoption may find resistance due to the level of fan involvement; the draft has evolved into an interactive experience for both fans and teams.

This research demonstrates the new application of smart contracts in the inter-section of sports management and blockchain technology.

This study aimed to review various existing methods for improving the quality of recycled concrete aggregates (RCAs) as a possible substitution for natural aggregates (NAs) in concrete. It is vital as the old paste attached to the RCA weakens its structure. It is due to the porous structure of the RCA with cracks, weakening the interfacial transition zone (ITZ) between the RCA and binding material, negatively impacting the concrete's properties. To this end, various methods for reinforcement of the RCA, cleaning the RCA's old paste and enhancing the quality of the RCA-based concrete without RCA modification are studied in terms of environmental effects, cost and technical matters. Furthermore, this research sought to identify gaps in knowledge and future research directions.

The review of the relevant journal papers revealed that various methods exist for improving the properties of RCAs and RCA-based concrete. A decision matrix was developed and implemented for ranking these techniques based on environmental, economic and technical criteria.

The identified methods for reinforcement of the RCA include accelerated carbonation, bio deposition, soaking in polymer emulsions, soaking in waterproofing admixture, soaking in sodium silicate, soaking in nanoparticles and coating with geopolymer slurry. Moreover, cleaning the RCA's old paste is possible using acid, water, heating, thermal and mechanical treatment, thermo-mechanical and electro-dynamic treatment. Added to these treatment techniques, using RCA in saturated surface dry (SSD) mixing approaches and adding fibres or pozzolana enhance the quality of the RCA-based concrete without RCA modification. The study ranked these techniques based on environmental, economic and technical criteria. Ultimately, adding fibres, pozzolana and coating RCA with geopolymer slurry were introduced as the best techniques based on the nominated criteria.

The study supported the need for better knowledge regarding the existing treatment techniques for RCA improvement. The outcomes of this research offer an understanding of each RCA enrichment technique's importance in environmental, economic and technical criteria.

The practicality of the RCA treatment techniques is based on economic, environmental and technical specifications for rating the existing treatment techniques.

This paper aims to investigate how chief executive officer (CEO) responsible leadership impacts corporate social responsibility (CSR) and organization performance by considering diverse organizational climates (including ethical, service and initiative climates) as mediators and CEO founder status as a moderator.

This study analyzed survey data from 212 service organizations in China with structural equation modeling.

The results clearly established that CEO responsible leadership played a crucial role in augmenting both CSR and organization performance by shaping positive organizational climates. Notably, CEO responsible leadership significantly fostered ethical, service and initiative climates. Furthermore, an ethical climate promoted CSR and organization performance, whereas service and initiative climates specifically enhanced organization performance. Additionally, responsible CEOs with founder status exhibited a higher propensity for enhancing ethical, service and initiative climates within service organizations.

Service organizations should take measures to build CEO responsible leadership, especially for CEOs with founder status. Furthermore, service organizations should motivate employees to reach consensus on ethical conducts, superior service and proactive approach to work.

First, the findings on CEO responsible leadership’s effects on CSR and organization performance extend the research on responsible leadership outcomes. Second, this paper adds to responsible leadership literature through exploring the mediating effects of ethical, service and initiative climates. Finally, the finding on the moderating role of founder CEOs offers a novel perspective regarding the boundary condition of the effects of CEO responsible leadership.

The study focuses on drug safety regulation capture, reveals the inner mechanism and evolutionary characteristics of drug safety regulation capture and provides suggestions for effective regulation by pharmacovigilance.

The article introduces prospect theory into the game strategy analysis of drug safety events, constructs a benefit perception matrix based on psychological perception and analyzes the risk selection strategies and constraints on stable outcomes for both drug companies and drug regulatory authorities. Moreover, simulation was used to analyze the choice of results of different parameters on the game strategy.

The results found that the system does not have a stable equilibrium strategy under the role of cognitive psychology. The risk transfer coefficient, penalty cost, risk loss, regulatory benefit, regulatory success probability and risk discount coefficient directly acted in the direction of system evolution toward the system stable strategy. There is a critical effect on the behavioral strategies of drug manufacturers and drug supervisors, which exceeds a certain intensity before the behavioral strategies in repeated games tend to stabilize.

In this article, the authors constructed the perceived benefit matrix through the prospect value function to analyze the behavioral evolution game strategies of drug companies and FDA in the regulatory process, and to evaluate the evolution law of each factor.

This paper aims to study a neural network-based fault-tolerant controller to improve the tracking control performance of an unmanned autonomous helicopter with system uncertainty, external disturbances and sensor faults, using the prescribed performance method.

To ensure that the tracking error satisfies the prescribed performance, the authors adopt an error transformation function method. A control scheme based on the neural network and high-order disturbance observer is designed to guarantee the boundedness of the closed-loop system. A simulation is performed to prove the validity of the control scheme.

The developed adaptive fault-tolerant control method makes the system with sensor fault realize tracking control. The error transformation function method can effectively handle the prescribed performance requirements. Sensor fault can be regarded as a type of system uncertainty. The uncertainty can be approximated accurately using neural networks. A high-order disturbance observer can effectively suppress compound disturbances.

The tracking performance requirements of unmanned autonomous helicopter system are considered in the design of sensor fault-tolerant control. The inequality constraint that the output tracking error must satisfy is transformed into an unconstrained problem by introducing an error transformation function. The fault state of the velocity sensor is considered as the system uncertainty, and a neural network is used to approach the total uncertainty. Neural network estimation errors and external disturbances are treated as compound disturbances, and a high-order disturbance observer is constructed to compensate for them.

This paper forms an e-commerce supply chain that include a manufacturer providing products and an online platform providing service. The reselling platform mode and the agent platform mode are considered through an exploration of the manufacturer Stackelberg (MS), vertical Nash (VN), platform Stackelberg (PS) power structures. The purpose of this paper is to explore the pricing and platform service decisions under different platform selling modes and channel power structures.

Based on the game theory models, this paper investigates the interaction between the manufacturer and the online platform under four different scenarios. The optimal solutions of four models are provided. Through comparison analyses, this paper evaluates the impacts of platform selling mode and channel power structure on the pricing and platform service decisions and the members’ profits.

The manufacturer prefers the MS power structure in any platform mode. The online platform prefers the PS (MS) power structure under a low (high) service cost efficiency in the reselling platform mode, while prefers the PS and VN power structures in the agent platform mode. Moreover, the manufacturer prefers the agent (reselling) platform mode under a low (high) service cost efficiency in any power structure. The online platform prefers the reselling platform mode in the MS and PS power structures, while prefers the reselling (agent) platform mode under a low (high) service cost efficiency in the VN power structures.

The analysis result provides important managerial implications that help the supply chain members develop a better understanding of the selection of the platform selling mode and the effect of the channel power structure in the presence of platform service.

The metallic alloys and their components fabricated via laser powder bed fusion (LPBF) suffer from the microvoids formed inevitably due to the extreme solidification rate during fabrication, which are impossible to be removed by heat treatment. This paper aims to remove those microvoids in as-built AlSi10Mg alloys by hot forging and enhance their mechanical properties.

AlSi10Mg samples were built using prealloyed powder with a set of optimized LPBF parameters, viz. 350 W of laser power, 1,170 mm/s of scan speed, 50 µm of layer thickness and 0.24 mm of hatch spacing. As-built samples were preheated to 430°C followed by immediate pressing with two different thickness reductions of 10% and 35%. The effect of hot forging on the microstructure was analyzed by means of X-ray diffraction, scanning electron microscopy, electron backscattered diffraction and transmission electron microscopy. Tensile tests were performed to reveal the effect of hot forging on the mechanical properties.

By using hot forging, the large number of microvoids in both as-built and post heat-treated samples were mostly healed. Moreover, the Si particles were finer in forged condition (∼150 nm) compared with those in heat-treated condition (∼300 nm). Tensile tests showed that compared with heat treatment, the hot forging process could noticeably increase tensile strength at no expense of ductility. Consequently, the toughness (integration of tensile stress and strain) of forged alloy increased by ∼86% and ∼24% compared with as-built and heat-treated alloys, respectively.

Hot forging can effectively remove the inevitable microvoids in metals fabricated via LPBF, which is beneficial to the mechanical properties. These findings are inspiring for the evolution of the LPBF technique to eliminate the microvoids and boost the mechanical properties of metals fabricated via LPBF.

The UK government has taken the lead in accelerating the capacity of higher education to engage with sustainability accounting and adopting a novel systematic approach toward a collective implementation of and contribution to Sustainable Development Goals (SDGs). The UN SDG 16 “Peace, Justice & Strong Institutions” promotes the (re)building of effective and accountable institutions. In line with the institutional logics metatheory, we provide empirical evidence on how the alignment between social mechanisms alongside the reputation of higher education institutions (HEIs) and SDGs on transparent and responsible service (SDG 16) affect the students' overall experience. Using a sample of 142 UK HEIs, interpretative content analysis and ordinary least squares, the results show that integrating HEIs' responsible-oriented research agenda proactively with high sustainability reputation adds significantly to greater student satisfaction.

The purpose of this paper is to assess the hydrogen embrittlement sensitivity of carbon gradient heterostructure materials and to verify the reliability of the scratch method.

The surface-modified layer of 18CrNiMo7-6 alloy steel was delaminated to study its hydrogen embrittlement characteristics via hydrogen permeation, electrochemical hydrogen charging and scratch experiments.

The results showed that the diffusion coefficients of hydrogen in the surface and matrix layers are 3.28 × 10⁻⁷ and 16.67 × 10⁻⁷ cm²/s, respectively. The diffusible-hydrogen concentration of the material increases with increasing hydrogen-charging current density. For a given hydrogen-charging current density, the diffusible-hydrogen concentration gradually decreases with increasing depth in the surface-modified layer. Fracture toughness decreases with increasing diffusible-hydrogen concentration, so the susceptibility to hydrogen embrittlement decreases with increasing depth in the surface-modified layer.

The reliability of the scratch method in evaluating the fracture toughness of the surface-modified layer material is verified. An empirical formula is given for fracture toughness as a function of diffused-hydrogen concentration.

In order to meet the different quality of service (QoS) requirements of vehicle-to-infrastructure (V2I) and multiple vehicle-to-vehicle (V2V) links in vehicle networks, an efficient V2V spectrum access mechanism is proposed in this paper.

A long-short-term-memory-based multi-agent hybrid proximal policy optimization (LSTM-H-PPO) algorithm is proposed, through which the distributed spectrum access and continuous power control of V2V link are realized.

Simulation results show that compared with the baseline algorithm, the proposed algorithm has significant advantages in terms of total system capacity, payload delivery success rate of V2V link and convergence speed.

The LSTM layer uses the time sequence information to estimate the accurate system state, which ensures the choice of V2V spectrum access based on local observation effective. The hybrid PPO framework shares training parameters among agents which speeds up the entire training process. The proposed algorithm adopts the mode of centralized training and distributed execution, so that the agent can achieve the optimal spectrum access based on local observation information with less signaling overhead.