Search Results (700)

In this article, we construct a framework for analyzing the equilibrium and stability of networked multi-sector economic systems via fixed-point analysis. We represent directional intersectoral dependencies, nonlinear feedback effects, and heterogeneous adjustment dynamics in the model by the coupled and tripled fixed-point theory in the graphically extended suprametric spaces. The graphical structure encodes supply-chain and influence networks, whereas asymmetric and nonuniform interaction strengths are encoded in the suprametric setting. Furthermore, we prove the existence, uniqueness, and convergence of equilibrium solutions under new generalized contraction conditions. We apply the theoretical findings in nonlinear state systems in which prices in interdependent markets are adjusted using integral equations. The results of numerical simulations show consistent convergence, and the sensitivity parameter of the network structure significantly influences the determination of economic stability and speed of adjustment. Full article

Racial diversity is normatively desirable in public organizations, but the social and psychological processes it activates may lead to employees’ negative work attitudes. Combining social categorization theory, perceived organizational support theory, and psychological contract theory, this study investigates whether racial diversity is negatively related to employee work engagement in U.S. federal agencies and whether the perceived effectiveness of agency ethics programs moderates this relationship. Using multilevel mixed-effects regression analyses with data from 10,088 employees nested within 24 federal agencies drawn from the 2016 Merit Principles Survey, we find that racial diversity was negatively associated with work engagement. However, this negative relationship was reduced when employees perceived their agency’s ethics program as more effective. At high levels of perceived effectiveness, the negative association was no longer statistically significant. These findings suggest that the perceived effectiveness of ethics programs is a meaningful organizational condition under which the negative association between racial diversity and work engagement may be attenuated. This pattern has implications for diversity management and human resource practice in ethical, high-performing, and sustainable public organizations. Full article

In this paper, we introduce a novel class of quadruple controlled metric-type spaces formulated in a four-dimensional setting. Within this framework, we extend the notion of a $\Theta$-contraction mapping to accommodate such spaces. By employing these concepts, we establish several new fixed-point theorems that significantly generalize and enhance the existing results in the literature. The validity and effectiveness of the proposed approach are demonstrated through carefully constructed illustrative examples within the defined space and for the derived fixed-point results. Finally, an application to a boundary value problem is presented, highlighting the potential of the developed theory. Furthermore, a coupled four-component thermo-chemical system was examined as an additional application, demonstrating the broader applicability of the proposed framework. Full article

Small- and medium-sized enterprises, especially in the agricultural food sector, struggle to implement end-to-end product traceability systems, such as enterprise resource planning (ERP), due to the high costs and complexity involved for businesses of this scale. As customer expectations and regulatory requirements place an increasing emphasis on traceability and transparency, the combined use of industrial Internet of things (IIoT) technologies and blockchain-based smart contracts offers a promising pathway to cost-effective automation of supply chain processes. This paper develops a conceptual, multi-layer architecture that integrates sensing, communication, integration and smart-contract layers to support affordable, automated and extensible traceability for agri-food supply chains. Building on information processing theory and transaction cost economics, the framework explains how such architecture can reduce information uncertainty, lower monitoring costs and strengthen the organisational trust in agri-food supply chains. The framework is empirically illustrated and tested through an implementation that links distributed sensing infrastructure with a blockchain-based smart contract in a real agricultural supply chain setting. The evaluation assesses operational performance, data integrity and cost-efficiency, demonstrating that the proposed architecture can serve as a viable alternative or most importantly complement to traditional ERP solutions for small- and medium-sized enterprises that seek end-to-end traceability, transparency and automation. Full article

In the digital twin (DT) network, effective edge data processing is essential to meet the real-time requirements of DT models. However, edge servers (ESs) are self-interested and have limited computation resources. The virtual content operator (VCO) cannot observe their true computing capabilities, leading to participation reluctance and information asymmetry. To address these challenges, this paper proposes a contract-learning integration method for computing incentive and data offloading. A two-dimensional computation-reward contract incentive mechanism is designed to motivate ESs to provide computation resources for data pre-processing, where both continuous and discrete distributions of ES types are considered. Then, ESs upload the processed results to the VCO for DT model mapping, synchronization, and final construction. Based on the individual rationality and incentive compatibility constraints, the optimal incentive reward and computing resource allocation strategies are analytically derived to maximize the VCO’s utility. Then, based on the signed contracts, a multi-agent double deep Q-network algorithm is developed to jointly optimize the binary data offloading decision, transmission bandwidth, and transmission power for the minimal system delay. The algorithm learns adaptive strategies in the dynamic network environment and mitigates Q-value overestimation. Numerical results demonstrate that the proposed method improves system performance in terms of computing incentive and data offloading. Full article

Classical fixed-point theorems for Rakotch, Edelstein, and Bianchini contractions require the contractive condition to hold for the mapping itself at every iteration, which severely limits their applicability to many real-world problems. In this paper, we break this limitation by shifting the contractive requirement to the p-th iterate of the mapping. We introduce three novel classes of p-Rakotch, p-Edelstein, and p-Bianchini contractions and prove that each guarantees the existence of a unique fixed point and global convergence of the Picard sequence from any initial point, under appropriate metric space assumptions (completeness for Rakotch and Bianchini; compactness with continuity for Edelstein). A key feature of our approach is that the original mapping T need not satisfy any contractive condition; only its p-th iterate $T^p$ needs to. This allows us to handle mappings where classical theorems simply do not apply. To validate our theoretical findings, we provide explicit numerical examples for $p=3,4,5$. More importantly, we demonstrate the practical power of our results through six diverse applications: ordinary differential equations with large coefficients; planar discrete dynamical systems; nonlinear Hammerstein integral equations; Caputo fractional differential equations with large linear terms; fractional equations exploiting the smoothing property; and implicit fractional differential equations. In each application, the classical contractive condition fails, yet our p-iterate approach succeeds. When $p=1$, all three theorems reduce to their classical counterparts, confirming that our framework is a natural and faithful generalization. Full article

This work presents a comprehensive study of entropy-based metrics for evaluating blockchain systems, focusing on on-chain ledger immutability, off-chain data integrity, and computational dynamics within blockchain virtual machines (BVMs). We develop a unified framework that models blockchain states as probabilistic distributions, quantifying uncertainty through Shannon entropy and examining its evolution under varying adversarial fractions. Extensive simulations demonstrate that on-chain entropy exhibits near-exponential decay, reflecting the cumulative reinforcement of honest consensus, while off-chain entropy remains static, highlighting the limitations of conventional data storage. Furthermore, the BVM is analyzed in terms of computation entropy, establishing its Turing completeness and demonstrating that smart-contract state evolution mirrors the information dynamics of arbitrary Turing machines. Our results provide quantitative evidence that entropy serves as both a theoretical and operational measure of immutability, tamper evidence, and protocol resilience. The proposed entropy framework offers practical tools for monitoring ledger integrity, detecting tampering, and assessing computational complexity, bridging the gap between information-theoretic principles and distributed ledger applications. This study advances both the theoretical understanding and practical evaluation of blockchain security, providing a principled methodology for analyzing distributed systems under adversarial conditions. Full article

In this study, the influence of thermal loading in a supersonic flight environment on the mechanical stiffness of elastic structures and the corresponding aeroelastic stability limits is investigated analytically. Recognizing that elevated temperatures inherently alter constituent elastic properties, a temperature-dependent continuous elasticity framework is incorporated directly into the governing differential operators of the structural domain. The macro-mechanical behavior of representative panel- and wing-type elements is modeled utilizing the Euler–Bernoulli beam formulation, while high-speed supersonic aerodynamic effects are represented through linearized first-order piston theory. The continuous spatial displacement fields are discretized by means of a modal expansion, and the coupled aeroelastic system is subsequently transformed into a finite set of dynamic state-space equations using the Ritz–Galerkin truncation method. The numerical and analytical outputs demonstrate that aerothermal softening not only induces continuous erosion in the material stiffness but also directly modulates the aeroelastic pole trajectories, thereby prematurely contracting the safe supersonic flight envelope. The primary novelty of the proposed framework lies in the derivation of explicit analytical expressions that directly map temperature-dependent stiffness variations onto supersonic aeroelastic instability boundaries. Because this approach is formulated in a generalized analytical form, it can be applied across diverse material systems, geometric profiles, and thermal conditions with reduced computational overhead compared to full fluid–structure interaction solvers, thereby providing a theoretical basis for preliminary stability assessment of supersonic aerospace configurations operating under high-temperature conditions. Full article

This paper investigates the asymptotic stability of a one-dimensional porous elastic system subject to a single boundary control of the fractional derivative type. The system consists of two coupled hyperbolic equations describing the displacement of an elastic solid and the volume fraction, with boundary conditions that include a generalized Caputo fractional derivative of order $\alpha \in (0,1)$ at $x=L$. This configuration has not been previously addressed in the literature. Using semigroup theory, we first reformulate the system as an abstract Cauchy problem and prove that the associated operator generates a $C_0$-semigroup of contractions on a suitable energy space, establishing global well-posedness. Under explicit and generic conditions on the physical parameters and the length L, we prove strong stability via the Arendt–Batty criterion, showing that all solutions tend to zero in the energy norm as $t\to \infty$. The main result is a polynomial decay rate: there exists $c>0$ such that ${\parallel S_{\mathcal{A}}\left(t\right)U_0\parallel }_{\mathcal{H}}\le c{t}^{-1/6}{\parallel U_0\parallel }_{D\left(\mathcal{A}\right)}$ for all initial data in the domain of the generator. The proof relies on the Borichev–Tomilov theorem and a detailed contradiction argument based on asymptotic expansions of the resolvent operator. Notably, the decay rate is independent of any relation between the wave propagation speeds, which distinguishes our result from many previous studies on porous elastic or Timoshenko systems. Full article

Turnover is a major concern for hotel and hospitality industry on a global scale. This research focuses on Dubai 5-star hotels in terms of transactional leadership and how employees perceive its influence on climate and contract fulfillment. This research combines the premises of social exchange, organizational support, and psychological contract, and organizational climate theories to support the development of hypotheses. A total of 24 employee interviews from two 5-star hotels in Dubai were gathered using semi-structured interviews. The research used inductive qualitative approach via thematic network analysis using QSR NVivo software (version 14). Transactional leadership can stabilize the execution of services by clarifying roles, adequate monitoring, and contingent exchanges in the luxury hotel setting. The thematic qualitative evidence demonstrates that organizational climate is an immediate interpretive medium, while psychological contract fulfillment is an emergent factor that is formed through repetitive interactions between employees and leadership. The results provide an in-depth understanding of these dynamics in the luxury hotel context, which can be beneficial for both scholars and practitioners alike. Full article

This paper establishes a rigorous mathematical foundation for modeling scientific research design as a dynamic, decision-centric system. We introduce the Scientific Decision Architecture for Complex Systems (SDA-CS), formalizing research configurations as trajectories within a complete neutrosophic metric space $\mathcal{D}$. By employing the Banach Fixed-Point Theorem, we prove that the research evolution operator $\Psi$ acts as a contraction mapping, ensuring convergence toward a unique, stable methodological state ${\mathrm{V}}_{\mathrm{d}}^{\ast }$ even under conditions of high initial indeterminacy. The framework integrates neutrosophic logic to explicitly characterize indeterminacy ($I$), and local stability is analyzed through the spectral radius of the methodological Jacobian matrix $J_{\Psi }$. Furthermore, we examine the system through information theory, demonstrating that the SDA-CS architecture acts as an entropy-reduction mechanism that promotes information gain by pruning inconsistent decision paths. These theoretical results provide a cybernetic basis for ensuring reproducibility and structural robustness in complex scientific investigations. Full article

Y₂SiO₅ (YSO) and Lu₂SiO₅ (LSO) are orthosilicates used in photonic and scintillation applications. Isovalent substitution on the rare-earth sublattice in YSO–LSO solid solutions enables systematic tuning of lattice parameters and elastic properties without changing the underlying monoclinic structural framework. A systematic ab initio study of structural, elastic, and vibrational properties of Ce-free YSO–LSO solid solutions is performed within density functional theory using a localized Gaussian-type orbital basis. Nine compositions spanning the full range from YSO to LSO with a Lu content step of 12.5% are investigated. A total of 76 symmetry-independent Y/Lu substitution patterns are explicitly constructed. For each configuration, full geometry optimization and calculation of second-order elastic constants are carried out using the stress–strain approach. Bulk, shear, and Young’s moduli, as well as Poisson’s ratio, are obtained using the Voigt, Reuss, and Hill averaging schemes. Sound velocities and Debye temperatures are derived from the Hill-averaged elastic moduli and density. The unit-cell volumes decrease smoothly with increasing Lu content and follow Vegard’s law, indicating uniform lattice contraction. The Hill-averaged bulk modulus increases from 92 GPa (YSO) to 115 GPa (LSO), the Young’s modulus rises from 151 to 180 GPa, and a strong directional anisotropy (ratio ∼2) is preserved across the entire series. The Debye temperature decreases monotonically from 518 K to 439 K, indicating that the increase in mass density outweighs the stiffening-induced tendency toward higher sound velocities. These results provide quantitative guidance for composition selection and stress management in LYSO-based crystal detectors. Full article

In this paper, we establish new fixed point results for Burton-type large contractions in complete b-metric spaces and introduce a Rakotch-type generalization in this setting. We establish existence and uniqueness results for fixed points, with an example to illustrate the applicability. Furthermore, an application to a fractional differential equation is presented. Our results generalize classical fixed point theorems and contribute to the theory of nonuniform contractions in generalized metric spaces. Full article

Background: The retention of Clinical Research Associates (CRAs) is critical for the integrity and sustainability of clinical trials in South Africa, an emerging hub for global clinical research. High CRA turnover threatens trial quality, data continuity, and site relationships, yet the context-specific drivers of turnover within the South African clinical research landscape remain poorly understood. This study explores the factors influencing job satisfaction and turnover intentions among CRAs to inform targeted retention strategies. Methods: A qualitative, interpretivist study was conducted using semi-structured interviews. Twelve CRAs with experience in South African Contract Research Organizations (CROs) were sampled on LinkedIn using purposive sampling. Data were analyzed iteratively using thematic analysis within Atlas.ti 26.0.1.33961 software, guided by Herzberg’s Two-Factor Theory and Mobley’s Turnover Model. Results: The analysis revealed a complex model of turnover drivers. Compensation was the most salient factor, operating not only as a hygiene factor but also as a direct motivator for job mobility in a competitive market. Unsustainable workload and a culture stigmatizing discussions of overload were key push factors. Intrinsic motivators were equally decisive: misalignment with therapeutic area preferences caused profound dissatisfaction, while alignment fostered engagement. Career growth manifested dual pathways: ambition for vertical progression and a redefined search for horizontal growth into roles offering greater work-life flexibility. Conclusions: CRA turnover is driven by an interplay of extrinsic pressures and intrinsic motivational deficits. To enhance retention, managers must adopt a multi-pronged strategy: implement market-competitive, well-being-oriented compensation; foster a culture that supports open workload dialogue; create transparent career architectures with dual progression tracks; and facilitate internal mobility across therapeutic areas. This study provides a foundational framework for developing context-sensitive retention policies, thereby contributing to the stability and quality of clinical research in South Africa. Full article

This study examines how employees’ perceptions of transactional and relational psychological contracts influence emotional labor strategies in contemporary work contexts where AI technologies are increasingly present through AI anxiety, general attitudes toward AI, and generative AI acceptance. Based on Conservation of Resources Theory, Cognitive Appraisal Theory, the Theory of Planned Behavior and technology acceptance frameworks (UTAUT), a conceptual model was tested using survey data from 869 employees across various sectors in Türkiye. Mediation and moderated mediation analyses were conducted using the PROCESS macro for SPSS 30. The results showed that transactional psychological contracts were positively correlated with surface acting, while relational psychological contracts were associated with deep acting. Serial mediation analyses indicated that relational psychological contracts were indirectly associated with higher levels of deep acting, primarily through more positive evaluations of AI, with the full sequential pathway through anxiety reduction not operating as hypothesized. Generative AI acceptance mediated the relationship between negative attitudes toward AI and surface acting. Moreover, generative AI acceptance mediated the relationship between positive attitudes toward AI and deep acting, indicating a pathway through which favorable technology evaluations translate into authentic emotional regulation. Finally, moderated mediation analyses suggest that emotional intelligence strengthens the impact of generative AI acceptance on employees’ emotional labor strategies. Full article