Search Results (949)

Objectives: To systematically review and analyze electronic systems in competitive motorcycles (2020-2025), examining their technical specifications, performance impacts, and technological evolution across MotoGP, World Superbike (WSBK), MotoE, British Superbike (BSB), and Spanish Championship (ESBK) categories. Eligibility criteria: Included studies reporting technical specifications or performance data of electronic systems in professional motorcycle racing, published between January 2020 and December 2025 in English, Spanish, Italian, or Japanese. Excluded: opinion pieces, amateur racing, and studies without quantitative data. Information sources: IEEE Xplore, SAE Technical Papers, Web of Science, Scopus, and specialized motorsport databases were searched through December 15, 2025. Risk of bias: Modified Cochrane Risk of Bias tool for experimental studies and Newcastle-Ottawa Scale for observational studies. Synthesis of results: Synthesis of results: Random-effects meta-analysis using DerSimonian-Laird method for homogeneous outcomes; narrative synthesis for heterogeneous data. The complete PRISMA 2020 checklist is provided in Appendix . Included studies: 87 studies met inclusion criteria (52 experimental, 38 simulation, 23 technical descriptions, 14 comparative analyses). Electronic systems were categorized into six domains: Engine Control Units (ECU, 28 studies, 22%), Vehicle Dynamics (23 studies, 18%), Traction Control (19 studies, 15%), Data Acquisition (21 studies, 17%), Braking Systems (18 studies, 14%), and Emerging Technologies (18 studies, 14%). Note that studies could address multiple domains. Limitations of evidence: Proprietary restrictions limited access to 31% of technical details; 43% lacked cross-category comparisons. Interpretation: Electronic systems are primary performance differentiators, with computational power following Moore’s Law. Future developments point toward distributed architectures and 5G telemetry. Funding: This project has been funded by the R&D programme with reference TEC-2024/TEC-62 and acronym iRoboCity2030-CM, granted by the Comunidad de Madrid through the Dirección General de Investigación e Innovación Tecnológica, Orden 5696/2024. Full article

Evolutionary Algorithms (EAs) are those based on the phenomenon of survival of the fittest. Differential Evolution (DE) is a member of this family, and it is well-suited for handling problems with real-valued variables. However, to use DE to solve binary problems, it is necessary to employ some adaptation. The primary objective of the present study is to develop a new binary version of DE. The proposed algorithm is called Binary Differential Evolution with a limited maximum number of dimension changes (NBDE), and it was tested with the OneMax Problem, five variants of the Knapsack Problem (KP), and Feature Selection (FS). The results showed that NBDE is competitive and superior to the other tested algorithms in many instances. For the 0/1 KP and 0/1 Multidimensional KP, NBDE outperforms all the other algorithms for all instances. For the FS problem, the proposed algorithm demonstrates good accuracy as its primary quality. The proposed algorithm exhibits a satisfactory performance, particularly in high-dimensional problems, which appears to be a quality inherited from the method that inspired its creation. This is particularly interesting because it provides empirical evidence that the importation of operators can perpetuate a pattern of behavior in algorithms with different structures. Full article

Meeting the demands for advanced technology and superior quality in the automotive industry has become essential. Continuous evolution requires a rigorous analysis of every step taken. Customers demand high performance in the technology, design, and digitalization, as well as, of course, quality at a competitive price. To meet these expectations, engineers ensure transparency and trust at every stage of the project, guaranteeing flawless execution. This paper aims to highlight a clear and transparent approach to the 8D analysis method, demonstrating its effectiveness in identifying and solving engineering problems. Furthermore, quality planning and 8D analysis are fundamental pillars of quality management in the automotive industry. To ensure a comprehensive and well-founded approach, this paper combines several research methods: a review of the specialized literature, a hypothetical case study approach, and comparative analysis. The proposed methodology allows for a deep understanding of the concepts addressed, facilitating their applicability in real situations. The main conclusions drawn from this research are that quality planning in an automotive buckle development project has proven to be an essential and complex process, directly influencing the success of the project, the safety of end users, and their satisfaction. The analysis of the implementation of the quality planning process, as previously described, has highlighted several fundamental aspects that must be considered to ensure the success and performance of such a project. Full article

This study examines the evolution and current challenges of Catholic Higher Education (CHE) in South Korea within the context of globalization and neoliberal educational reform. It explores how Korean Catholic universities balance their distinctive mission with intensifying pressures for competitiveness, external validation, and adaptation to secular academic norms. Drawing on P. Boudieu’s field theory and H. Richard Niebuhr’s typology of Christian responses to culture, the analysis frames the ways institutions of Korean CHE navigate the sometimes contrary currents of their institutional aims—simultaneously striving for academic excellence and maintaining Catholic identity. Case studies of three major Korean Catholic universities illustrate how leadership and curricular programs reflect the ongoing negotiation between mission-driven imperatives and market demands. The paper contends that living within this tension is not a sign of deficiency. It can actually be a source of resilience and innovation. The Korean experience of CHE offers insights for Catholic universities facing similar dilemmas globally, suggesting that engaging proactively with the seemingly contrary paradoxical demands can sustain the integrity of mission while fostering adaptive capacity amid the rapidly changing landscape of higher education. Full article

Against the backdrop of global population growth and intensified resource competition, the sustainable development of the water-energy-food system (WEF) is facing challenges. Wetlands, as key ecological hubs, play a crucial role in regulating water cycles, energy metabolism, and food production, thus serving as a breakthrough point for resolving the bottleneck of resource synergy. Incorporating wetlands into the WEF framework helps us comprehensively understand and optimize the interrelationships among water, energy, and food. This paper proposes an indicator system based on WEFW to study the coupling of water-energy-food-wetland systems and analyzes the evolution of the comprehensive development index of WEFW and its coupling relationship in Jiangxi Province from 2001 to 2022. It uses the grey correlation model to explore the sustainable development capacity of wetland resources, water resources, energy resources, and food resources in Jiangxi Province, and employs a geographical detector model to quantify the contribution of wetlands to WEFW. The research results show that (1) the comprehensive evaluation of WEFW systems in various cities in Jiangxi Province has generally improved, but there is imbalance in regional development. Cities such as Nanchang and Jiujiang have performed well, while cities like Jingdezhen and Xinyu need to enhance resource integration and sustainable development. (2) The coupling coordination degree (CCD) has experienced a process of “stability-fluctuation-recovery”, with a significant increase after 2014, and the spatial differentiation characteristics are obvious. (3) Wetlands play a dominant role in the spatial differentiation of CCD, and their interaction with water, energy, and food resources significantly enhance the explanatory power of their impact on CCD. (4) The grey model indicates that the CCDs of WEFW systems in most cities of Jiangxi Province have a projected annual growth rate of 1.8% (2022–2032), reaching 0.71–0.73 in leading cities. These results emphasize the importance of wetland protection and sustainable resource management in promoting regional coordinated development. The research and prediction of the coupling coordination relationship of water-energy-food-wetland systems can provide a scientific basis for the sustainable development of Jiangxi Province and also offer important scientific references for other regions to achieve a balance between ecological protection and resource utilization. Full article

This study employs coarse-grained molecular dynamics simulations to investigate how the overlap distance between graphene nanosheets influences the mechanical properties of “brick-mortar”-structured graphene–polyethylene nanocomposites. Simulations are conducted in a fixed box size while varying the overlap distance from 2.4 to 24 nm. The stress–strain response exhibits three distinct stages: elastic increase, plastic plateau, and slow decrease. The yield strength increases nearly linearly from 115.3 ± 3.8 to 347.9 ± 33.0 MPa with increasing overlap distance, a trend well captured by an extended shear-lag model incorporating polymer stretch. The critical failure strain, marking the onset of strain localization, first increases and then decreases, peaking at an overlap distance of 4.8 nm. This non-monotonic behavior is attributed to a competition between polymer stretch and polymer shear in interfacial stress transfer. Similarly, the plateau stress and toughness show two-stage evolution: the plateau stress remains constant (~100 MPa) up to 4.8 nm before increasing significantly, while toughness rises from 16.9 ± 0.2 to 51.0 ± 4.0 MJ/m³ across the range. These findings reveal the nanoscale mechanisms behind strength and toughness in bioinspired nanocomposites and provide guidelines for optimizing performance through overlap distance tuning. Full article

This study investigates how AI-driven innovations are reshaping manufacturing value chains through the transition from Industry 4.0 to Industry 6.0, particularly in resource-intensive sectors such as ceramics. Addressing a gap in the literature, the research situates the evolution of manufacturing within the broader context of digital transformation, sustainability, and regulatory demands. A mixed-methods approach was employed, combining semi-structured interviews with key industry stakeholders and an extensive review of secondary data, to develop an Industry 6.0 model tailored to the ceramics industry. The findings demonstrate that artificial intelligence, digital twins, and cognitive automation significantly enhance predictive maintenance, real-time supply chain optimization, and regulatory compliance, notably with the Corporate Sustainability Reporting Directive (CSRD). These technological advancements also facilitate circular economy practices and cognitive logistics, thereby fostering greater transparency and sustainability in B2B manufacturing networks. The study concludes that integrating AI-driven automation and cognitive logistics into digital ecosystems and supply chain management serves as a strategic enabler of operational resilience, regulatory alignment, and long-term competitiveness. While the industry-specific focus may limit generalizability, the study underscores the need for further research in diverse manufacturing sectors and longitudinal analyses to fully assess the long-term impact of AI-enabled Industry 6.0 frameworks. Full article

This study investigates the morphological evolution of epitaxial indium antimonide (InSb) nanowires (NWs) grown via chemical vapor deposition (CVD). We systematically explored the influence of key growth parameters—temperature (300 °C to 480 °C), source material composition, gold (Au) nanoparticle catalyst size, and growth duration—on the resulting NW morphology, specifically focusing on NW length and tapering. Our findings reveal that the competition between axial and radial growth modes, which are governed by different growth mechanisms, dictates the final nanowire shape. An optimal growth condition was identified that yields straight and minimally tapered InSb NWs. High-resolution transmission electron microscopy (TEM) confirmed that these nanowires grow preferentially along the <110> direction, and electrical characterization via field-effect transistor (NW-FET) measurements showed that they are n-type semiconductors. Full article

Understanding how ecological factors shape viral evolution is essential for predicting adaptation in RNA viruses. In this study, we investigated the evolutionary dynamics of bacteriophage Qβ under varying host densities, focusing on two nonsynonymous mutations—A1930G and C2011A—located in the A1 protein. Using experimental evolution, phenotypic assays, and competition experiments, we found that C2011A is consistently selected at low bacterial densities, enhancing viral entry but reducing burst size. In contrast, A1930G is fixed at high densities, despite similar phenotypic effects, suggesting its advantage arises from interactions with additional mutations. Clonal analysis revealed that compensatory or beneficial mutations modulate the fitness of A1930G, enabling its fixation. The absence of both mutations in the same genome points to negative epistasis, confirmed by the poor performance of the double mutant generated by site-directed mutagenesis. Sequencing of intermediate transfers showed early emergence of A1930G, but its fixation was prevented by clonal interference with C2011A. These findings highlight how host availability, fitness trade-offs, epistasis, and competition among variants shape the adaptive landscape of RNA viruses. Full article

In recent years, the evolution of competitive road cycling has included the use of larger tires inflated at lower pressure compared to the thin, high-pressure tires used previously. This trend is also emerging in non-competitive cycling, where comfort is more important. An issue often reported by cyclist concerns discomfort in the hands and upper limbs due to handlebar vibrations. To evaluate the effect of certain tire characteristics on vibrations in the handlebar and the bicycle seat-post, a small, portable, wireless connected, measurement system has been developed and tested on the road. Experimental conditions included tire-related factors, such as pressure, width, and the presence of an internal air chamber, as well as two speed conditions, while keeping all the other factors constant and under strict control. Results confirm that lower pressure reduces vibration levels, and tire width is also an important factor. Full article

Accelerated digital transformations and the evolution of consumer behavior in recent years underscore the need for a systemic perspective in marketing analytics to better comprehend the complex interplay between technology, data, and the profound changes triggered by global events, such as the COVID-19 pandemic. The COVID-19 pandemic has catalyzed a massive shift toward digitalization and transformed e-commerce from an option to a necessity for both businesses and consumers. This paper analyzes the total store and non-store sales, as well as total e-commerce sales, of the US retail trade across six main business categories and nine subcategories from the first quarter of 2018 to the first quarter of 2024. The data was divided into three time spans, corresponding to pre-, during, and post-COVID-19 pandemic periods, to examine the changing behavior of US consumers over time for different business categories. The statistical and econometric methods employed are the partial autocorrelation function (PACF), autocorrelation function, autoregressive integrated moving average model, inferential statistics, and regression model. The results indicate that the pandemic significantly increased non-store retailer sales compared to the pre-pandemic period, underscoring the importance of e-commerce. When physical stores reopened, e-commerce sales did not decline to pre-pandemic levels. The PACF analysis showed seasonality and lagged correlations. Thus, the pandemic-induced buying behaviors of US consumers continue to influence current sales patterns. The pandemic was more than just a temporary disruption, which permanently changed the retail sector. Retailers that quickly adapted to online models gained a competitive edge, whereas US consumers became accustomed to the convenience and flexibility of e-commerce. The behavior of US consumers adapted not only in response to immediate needs during the pandemic but also led to longer-term shifts in spending patterns, with each category reacting uniquely based on product type and perceived necessity. The analysis of how the COVID-19 pandemic transformed consumer behavior in the US reveals several important implications for both consumers and trade policymakers. First, the long-lasting and structural shift toward e-commerce is confirmed, representing a fundamental change in the dynamics of demand and supply. For consumers, the convenience, flexibility, and accessibility of digital channels have moved beyond mere situational advantages to become a behavioral norm. This shift has empowered consumers by giving them greater access to price comparisons, more diverse options, and increased informational transparency. Additionally, the data shows the emergence of hybrid consumption models: essential goods are mainly purchased online, while purchases of branded clothing, electronics, furniture, luxury items, and similar products continue to favor the traditional retail experience. Full article

Elucidating the evolutionary origins of social behavior remains a major challenge due to the complexity of social systems across taxa. Here, we examine social behavior through the lens of competition and cooperation across the three domains of life—Bacteria, Archaea, and Eukarya. By focusing on gene-based mechanisms, we propose that sociality arises from conserved molecular pathways shaped by similar selective pressures, even in phylogenetically distant organisms. This cross-domain perspective highlights the potential for convergent evolutionary solutions and offers a foundation for identifying invariant principles underlying the emergence and maintenance of social behavior. Full article

The Wind Farm Layout Optimization Problem (WFLOP) aims to improve wind energy utilization and reduce wake-induced power losses through optimal placement of wind turbines. Genetic Algorithms (GAs) and Particle Swarm Optimization (PSO) have been widely adopted due to their suitability for discrete optimization tasks, yet they suffer from limited global exploration and insufficient convergence depth. Differential evolution (DE), while effective in continuous optimization, lacks adaptability in discrete and nonlinear scenarios such as WFLOP. To address this, the fractional-order differential evolution (FODE) algorithm introduces a memory-based difference mechanism that significantly enhances search diversity and robustness. Building upon FODE, this paper proposes FQFODE, which incorporates reinforcement learning to enable adaptive adjustment of the evolutionary process. Specifically, a Q-learning mechanism is employed to dynamically guide key search behaviors, allowing the algorithm to flexibly balance exploration and exploitation based on problem complexity. Experiments conducted across WFLOP benchmarks involving three turbine quantities and five wind condition settings show that FQFODE outperforms current mainstream GA-, PSO-, and DE-based optimizers in both solution quality and stability. These results demonstrate that embedding reinforcement learning strategies into differential frameworks is an effective approach for solving complex combinatorial optimization problems in renewable energy systems. Full article

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

Alternative proteins (APs) have the potential to contribute to the sustainable transition of food systems. This study aims to assess the current stage of development of the alternative protein industry, identifying factors, both barriers and enablers, that influence business growth. The analysis adopts a systematic literature review, following the PRISMA guidelines, identifying 50 studies. The S-curve model is then applied as an analytical tool to determine the development stage of the AP industry concerning plant-based, insect, and algae segments. The application of the S-curve provides a perspective on the evolution of innovative business such as AP. The results reveal significant differences in the maturity of the AP industry. The plant-based one is the most advanced, characterized by strong market organization and collaborations, despite challenges such as price competitiveness. The algae industry is promising due to its versatility, yet it is hindered due to production costs and unstable demand. Insects face the greatest barriers, including consumer acceptance and ethical concerns. The study emphasizes the importance of creating business strategies suited to each AP source to transform barriers into opportunities. This review contributes to the literature by comparing the unique peculiarities of the AP industry and providing insights from a cross-analysis of plant-based, algae, and insect development stages. Full article