Search Results (3,595)

Driven by the new wave of technological revolution and industrial transformation, firms are accelerating strategic change to gain new competitive advantages. Situated within a complex adaptive system, firms must adapt to highly dynamic and uncertain external environments by adjusting executive cognitive structures, reconfiguring resources and capabilities, and strengthening collaboration with industrial ecosystem elements; hence, digital strategic change is characterized by continuous evolution. Using a sample of Chinese A-share listed firms from 2015 to 2023, this study develops a “cognition–capability–strategy” pathway model grounded in upper echelons theory and dynamic capabilities theory to examine how executive cognitive styles, i.e., cognitive flexibility and cognitive complexity, drive digital strategic change via absorptive capacity and how environmental dynamism moderates these relationships. The findings show that executive cognition, as a decision node in strategic change, can dynamically adjust firms’ strategic paths by activating absorptive capacity in rapidly changing external information environments; environmental dynamism differentially affects the two cognitive styles. Heterogeneity tests further indicate that the role of executive cognition varies significantly with regional digital economy development levels, firm life cycle, and industry factor intensities. The study reveals how firms can respond to high environmental uncertainty through cognition–strategy alignment and resource capability reconfiguration in a complex adaptive system, providing theoretical references and practical insights for emerging economies to advance digital transformation and enhance competitiveness. Full article

This article examines the activities of the Bahá’í community in Iran after the Islamic Revolution, challenging the misconception that the community has remained disengaged from societal involvement which arises from a misinterpretation of its principle of non-involvement in partisan politics. Contrary to this belief, the Bahá’í community has been actively engaged in social change through a framework rooted in its principles, which emphasize constructive resilience and non-adversarial strategies. Informed by the Bahá’í teachings, the global Bahá’í experience, and contemporary theories of social change, the community has focused on translating its spiritual principles into practical actions, particularly in community building, social action, and participation in the prevalent discourse of society. These efforts, characterized by a commitment to unity and collaboration, differ from conventional adversarial activism and demonstrate the community’s significant yet often overlooked contribution to Iranian society. Despite severe persecution, the Bahá’í community has maintained a principled engagement with social change, challenging the narrative of disengagement and highlighting its ongoing involvement in the life of the nation. Full article

Background: Cardiovascular disease (CVD) remains a leading cause of morbidity and mortality, particularly in socioeconomically disadvantaged populations. Telemedicine offers a potential strategy to support risk factor management in such groups with limited access to care. Our aim was to assess the effectiveness of a telemedicine-supported intervention compared to usual care in improving cardiovascular risk parameters among adults from a socially deprived urban population. Materials and Methods: In this controlled intervention study, adult patients with one or more cardiovascular risk factors were recruited from a primary care center in a low-income urban neighborhood in Timişoara, Romania. Participants were allocated to either usual care or a six-month telemedicine-supported intervention group. The intervention consisted of regular phone calls by trained staff focusing on medication adherence, self-monitoring of blood pressure and glucose, smoking cessation, and lifestyle advice. No physical visits were delivered. Primary outcomes included changes in systolic and diastolic blood pressure, fasting glucose, and lipid profile. Data were collected at baseline and at six months. Results: A total of 144 patients were allocated to the telemedicine group and 142 to the usual care group. After 6 months, diastolic blood pressure decreased by 3.9 mmHg in the telemedicine group compared to 0.3 mmHg in the standard care group (p < 0.001). LDL-cholesterol was reduced by 18.0 mg/dL with telemedicine versus 5.7 mg/dL with usual care (p < 0.001). In contrast, fasting glucose improved more in the standard care group (–10.9 mg/dL vs. –2.0 mg/dL, p < 0.001). Patient satisfaction in the telemedicine group was high, with 84% rating the program as very useful. Conclusions: Basic telemedicine-supported interventions may represent a feasible and effective strategy for improving cardiovascular risk factors such as diastolic blood pressure and LDL-cholesterol in socially deprived populations. High satisfaction suggests strong acceptability; however, given the small sample size, short follow-up, and single-center design, these findings should be interpreted cautiously and confirmed in larger studies. Full article

The digital revolution has profoundly influenced the automotive industry, shifting the paradigm from conventional vehicles to smart cars (SCs). The SCs rely on in-vehicle communication among electronic control units (ECUs) enabled by assorted protocols. The Controller Area Network (CAN) serves as the de facto standard for interconnecting these units, enabling critical functionalities. However, inherited non-delineation in SCs— transmits messages without explicit destination addressing—poses significant security risks, necessitating the evolution of an astute and resilient self-defense mechanism (SDM) to neutralize cyber threats. To this end, this study introduces a lightweight intrusion mitigation mechanism based on an adaptive momentum-based deep denoising autoencoder (AM-DDAE). Employing real-time CAN bus data from renowned smart vehicles, the proposed framework effectively reconstructs original data compromised by adversarial activities. Simulation results illustrate the efficacy of the AM-DDAE-based SDM, achieving a reconstruction error (RE) of less than 1% and an average execution time of 0.145532 s for data recovery. When validated on a new unseen attack, and on an Adversarial Machine Learning attack, the proposed model demonstrated equally strong performance with RE < 1%. Furthermore, the model’s decision-making capabilities were analysed using Explainable AI techinques such as SHAP and LIME. Additionally, the scheme offers applicable deployment flexibility: it can either be (a) embedded directly into individual ECU firmware or (b) implemented as a centralized hardware component interfacing between the CAN bus and ECUs, preloaded with the proposed mitigation algorithm. Full article

In this paper, we investigate the geometric realization of $\mathrm{Spin}\left(8\right)$ triality through vector fields on the octonionic algebra $\mathbb{O}$. The triality automorphism group of $\mathrm{Spin}\left(8\right)$, isomorphic to ${\mathfrak{S}}_3$, cyclically permutes the three inequivalent 8-dimensional representations: the vector representation V and the spinor representations $S_{+}$ and $S_{-}$. While triality automorphisms are well known through representation theory, their concrete geometric realization as flows on octonionic space has remained unexplored. We construct explicit smooth vector fields $X_{\sigma }$ and $X_{{\sigma }^2}$ on $\mathbb{O}\cong {\mathbb{R}}^8$ whose flows generate infinitesimal triality transformations. These vector fields have a linear structure arising from skew-symmetric matrices that implement simultaneous rotations in three orthogonal coordinate planes, providing the first elementary geometric description of triality symmetry. The main results establish that these vector fields preserve the octonionic multiplication structure up to automorphisms in $G_2=\mathrm{Aut}\left(\mathbb{O}\right)$, demonstrating fundamental compatibility between geometric flows and octonionic algebra. We prove that the standard Euclidean metric on $\mathbb{O}$ is triality-invariant and classify all triality-invariant Riemannian metrics as conformal to the Euclidean metric with a conformal factor depending only on the isotonic norm. This classification employs Schur’s lemma applied to the irreducible $\mathrm{Spin}\left(8\right)$ action, revealing the rigidity imposed by triality symmetry. We provide a complete classification of triality-symmetric minimal surfaces, showing they are locally isometric to totally geodesic planes, surfaces of revolution about triality-fixed axes, or surfaces generated by triality orbits of geodesic curves. This trichotomy reflects the threefold triality symmetry and establishes correspondence between representation-theoretic decomposition and geometric surface types. For complete surfaces with finite total curvature, we establish global classification and develop explicit Weierstrass-type representations adapted to triality symmetry. Full article

Nuclear power continues to be a great promise in the green revolution, as it is a cost-effective, low-emission, and safer alternative to fossil fuels that is capable of continuous operation. A preliminary design evaluation is presented for a submersible nuclear power station capable of operating under its own power during emergencies and routine maintenance. Because it is stationed at sea, it offers a resilient solution to natural disasters such as earthquakes and tsunamis, giving it the capability to disengage and sail to deeper waters in less than a half of an hour. In the present evaluation, the hull dimensions of a very large existing submarine and the turbomachinery layout of a Pebble Bed Modular Reactor cycle were used as baselines. The conceptual design of the submersible nuclear power station includes reactor and turbomachinery integration, preliminary sizing (4 pressure hull design; total length of 57.74 m), and propulsion system analysis, demonstrating the technical viability of the proposed submersible power station. Full article

As the core driving force of the new generation of industrial revolution, artificial intelligence technology has brought new opportunities for empowering enterprise innovation and advancing sustainability. Focusing on Chinese A-share listed enterprises and based on the unbalanced panel data from 2011 to 2023, this study systematically examines the relationship mechanism between artificial intelligence (AI) application and enterprise breakthrough innovation, and further explores the mediating effect of knowledge recombination and the moderating role of market competition. The empirical results show that AI application has a significant promoting effect on the enterprise breakthrough innovation. Knowledge recombination creation and knowledge recombination reuse play mediating roles in the relationship between the AI application and enterprise breakthrough innovation, forming the key transmission path for empowering breakthrough innovation with AI. In addition, market competition positively moderates the relationship between knowledge recombination and enterprise breakthrough innovation and strengthens the driving effect of knowledge recombination on innovation output, thus fostering more sustainable competitive advantages. Full article

Industry Revolution Five (Industry 5.0) will shift the focus away from technology and rely more on to the collaboration between humans and AI-powered robots. This approach emphasizes a more human-centric perspective, enhanced resilience, optimized workplace processes, and a stronger commitment to sustainability. The humanoid robot market has experienced substantial growth, fueled by technological advancements and the increasing need for automation in industries such as service, customer support, and education. However, challenges like high costs, complex maintenance, and societal concerns about job displacement remain. Despite these issues, the market is expected to continue expanding, supported by innovations that enhance both accessibility and performance. Therefore, this article proposes the design and implementation of low-cost, remotely controlled humanoid robots via a mobile application for home-assistant applications. The humanoid robot boasts an advanced mechanical structure, high-performance actuators, and an array of sensors that empower it to execute a wide range of tasks with human-like dexterity and mobility. Incorporating sophisticated control algorithms and a user-friendly Graphical User Interface (GUI) provides precise and stable robot operation and control. Through an in-house developed code, our research contributes to the growing field of humanoid robotics and underscores the significance of advanced control systems in fully harnessing the capabilities of these human-like machines. The implications of our findings extend to the future development and deployment of humanoid robots across various industries and societal contexts, making this an ideal area for students and researchers to explore innovative solutions. Full article

Carrying out automobile stability and dynamic comfort involves a close examination of engine performance, such that fault detection at the early stage must be of the highest priority to reliability and effectiveness. The study evaluates the impact of malfunctions in mass air flow (MAF) sensors on diesel engine performance and stability, particularly on vibratory emissions. Employing experimental methods, defect and normal engine vibrations were analyzed in both time-domain and frequency spectral domain methodologies. Some statistical values, such as root mean square (RMS), kurtosis, mean, standard deviation, clearance factor, and shape factor, were employed to compare and characterize the vibration pattern. The results indicate that malfunctions in the MAF sensor are characterized by striking vibration amplitude enhancement and instability at high engine revolutions. These defects cause poor starting, misfire, and rough engine running, which affect combustion efficiency. Conclusions show excellent correlation among MAF sensor fault, combustion activity, and engine vibration, and this confirms the need for fault detection at the initial stage. With its enhancement in vibration analysis diagnostic capability, this contribution is significant to condition monitoring and predictive maintenance activities. Lastly, the study contributes to improving engine reliability, efficiency in operation, and performance overall in the automotive industry. Full article

The implementation and impact of inclusivity and accessibility in the banking sector are crucial to the banking sector’s participation of any country in achieving the United Nations’ Sustainable Development Goals (SDGs) 1, 4, 5, 8, 10, 11, 16 and 17. This study examines the implementation and impact of inclusivity and accessibility in the South African banking sector, with a focus on the Free State province. Guided by the Sustainable Livelihoods Framework (SLF) and Institutional Theory, this research employs a quantitative, deductive approach to assess two core objectives: (1) the alignment of fintech banking practices with selected Sustainable Development Goals (SDGs), and (2) the identification of barriers to inclusivity and accessibility for women and youth. A stratified random sample of 208 banking professionals—comprising front-line employees, supervisors, and managers—was surveyed using a Likert-type questionnaire. Data were analysed using SPSS version 21. The findings reveal significant progress toward SDGs 1, 4, 5, 8, 10, 11, 16, and 17, reflected in a female-majority workforce, a youthful and educated employee base, and a nationally oriented employment strategy. These attributes signal a strong institutional commitment to inclusive growth and sustainable development. The sector also demonstrates readiness for fintech innovation, supported by high levels of training adequacy, relevance, and accessibility, indicating robust human capital and institutional adaptability to the Fourth Industrial Revolution (4IR) and AI-driven transformation. However, persistent structural barriers—particularly in leadership representation and digital access for women and youth—highlight the need for targeted policy interventions. Integrating inclusive fintech strategies, equitable training frameworks, and development programs is essential to sustaining progress and achieving the goals of the National Development Plan (NDP) and the SDGs. The Free State banking sector offers a promising model for inclusive institutional transformation aligned with global sustainability agendas. Full article

The primary distinction between technical design and engineering design lies in the role of analysis and optimization. From its inception, descriptive geometry has supported military and engineering applications, and its graphical rules inherently reflect principles of optimization—similar to the core ideas of sparse representation and compressed sensing. This paper explores the geometric and mathematical significance of the center line in symmetrical objects and the axis of rotation in solids of revolution, framing these elements within the theory of sparse representation. It further establishes rigorous correspondences between geometric primitives—points, lines, planes, and symmetric solids—and their sparse representations in descriptive geometry. By re-examining traditional engineering drawing techniques from the perspective of optimization analysis, this study reveals the hidden mathematical logic embedded in geometric constructions. The findings not only support the deeper integration of mathematical reasoning in engineering education but also provide an intuitive framework for teaching abstract concepts such as sparsity and signal reconstruction. This work contributes to interdisciplinary understanding between descriptive geometry, mathematical modeling, and engineering pedagogy. Full article

Urban lifeline Natech events are coupled systems composed of multiple risks and entities with complex dynamic transmission chains. Predicting risk evolution probabilities is the core task for achieving the safety management of urban lifeline Natech events. First, the risk evolution mechanism is analyzed, where urban lifeline Natech events exhibit spatial evolution characteristics, which involves dissecting the parallel and synergistic effects of risk evolution in spatial dimensions. Next, based on fitting marginal probability distribution functions for natural hazard and urban lifeline risk evolution, a Multi-dimensional Copula (MdC) function for the joint probability distribution of urban lifeline Natech event risk evolution is constructed. Building upon the MdC function, a Markov Chain Monte Carlo (MCMC) model for predicting risk evolution probabilities of urban lifeline Natech events is developed using the Metropolis–Hastings (M-H) algorithm and Gibbs sampling. Finally, taking the 2021 Zhengzhou ‘7·20’ catastrophic rainstorm as a case study, joint probability distribution functions for risk evolution under Rainfall-Wind speed scenarios are fitted for traffic, electric, communication, water supply, and drainage systems (including different risk transmission chains). Numerical simulations of joint probability distributions for risk evolution are conducted, and visualizations of joint probability predictions for risk evolution are generated. Full article

This paper presents a novel large-span ring deployable perimeter truss for the mesh reflector deployable antennas, which is made up of two parts including a single-mobility driving mechanism and a ring deployable metamorphic mechanism. The mechanism design employs polygon approximation, and each side is treated as a basic unit using a modular design approach. By reasonable assembly, a ring deployable metamorphic mechanism with a small folded state and a large deployed state can be formed. Here, multiple singular positions, the axis of its three revolute joints being parallel and coplanar, are used in the fully deployed state, which forms multiple dead-center positions and changes the constraint conditions. The metamorphic motion is thus achieved, and a stable self-locking state is established that greatly enhances the stability. The paper first introduces the mechanism design and evaluation method; the kinematic and dynamic analysis is then conducted, and the simulation validation is also performed. Moreover, a principle design for cable-net structural setting and connection is illustrated. Finally, with the design of a driving system and the fabrication of a physical prototype, the deployable experiments are carried out, and the results show that the perimeter truss can efficiently act as the mesh reflector deployable antennas. Full article

In the context of Industry 4.0, technologies such as Digital Twin (DT) and Data Space (DS) have emerged as a revolution in the way physical assets are represented in simulation models and how their information and data are represented in cloud repositories. The aim of this work was to investigate the technologies of DTs and DSs, with a focus on their application in an industrial context, delving into the approaches and difficulties of the integration of both technologies, so that it can be explored and answered the respective challenges. To this end, literature reviews on these topics were explored by reading various sources, as well as analyzing different methodologies for implementing and integrating the two technologies. The result was a description of the main methodologies for integrating DTs with DSs, with the addition of a practical application using AASX Package Explorer, this being a platform enabling the virtual representations of industrial equipment in the molds of DT technologies, containing the association with server tools from other developers and specifications. Full article

The rational design of functional and sustainable polymers is central to addressing global environmental challenges. In this context, unmodified lignin derived from Sarkanda grass (Tripidium bengalense), an abundant agro-industrial lignocellulosic byproduct, was systematically investigated as a natural polymeric adsorbent for the remediation of aqueous media contaminated with heavy metals. The study evaluates lignin’s behavior toward nine metal(loid) ions: arsenic, cadmium, chromium, cobalt, copper, iron, nickel, lead, and zinc. Adsorption performance was systematically investigated under static batch conditions, optimizing key parameters, with equilibrium and kinetic data modeled using established isotherms and rate equations. Surface characterization and seed germination bioassays provided supporting evidence. Unmodified Sarkanda grass lignin demonstrated effective adsorption, exhibiting a clear preference for Cu(II) followed by other divalent cations, with lower capacities for As(III) and Cr(VI). Adsorption kinetics consistently followed a pseudo-second-order model, indicating chemisorption as the dominant mechanism. Thermodynamic studies revealed spontaneous and endothermic processes. Bioassays confirmed significant reduction in aqueous toxicity and strong metal sequestration. This work positions unmodified Sarkanda grass lignin as a bio-based, low-cost polymer platform for emerging water treatment technologies, contributing to circular bioeconomy goals and highlighting the potential of natural polymers in sustainable materials design. Full article