The rapid uptake of battery electric vehicles (BEVs) has intensified the demand for accessible and efficient parking and charging infrastructure, particularly in dense urban environments. Leveraging household-based sharing of such facilities offers a potential solution to alleviate infrastructure constraints, yet drivers’ adoption behavior remains largely underexplored. This study develops an error component mixed logit (ECML) model, estimated with stated preference data, to jointly examine BEV drivers’ parking and charging choices across household-shared and conventional public-open facilities, explicitly accounting for unobserved heterogeneity, correlated error structures, and waiting time uncertainty. The results reveal significant preference heterogeneity that female, highly educated, and sharing-aware drivers exhibit stronger preferences for household-shared facilities. Historical driving patterns further influence BEV drivers’ parking and charging behavior, with high-mileage drivers motivated by cost savings. Moreover, activity-travel contexts, such as state-of-charge (SoC), unplanned activity duration, and time pressure significantly affect decisions, whereas cost- and time-related attributes exert negative effects, as confirmed by elasticity analysis. Nest effects captured through error components indicate correlated preferences across household-shared, public, and integrated options, emphasizing the need for coordinated facility design. These findings highlight practical interventions such as targeted pricing strategies, access improvement, and real-time information systems to enhance the adoption of household-shared facilities and improve urban BEV charging accessibility.
This study presents a numerical analysis of mean-field games in large-scale stochastic systems with state delays. We first formulate a stabilization problem using a state feedback strategy that incorporates both the individual state and the mean-field term. Nash equilibrium strategies are then employed to determine the equilibrium point associated with the upper bounds of the cost functions. The minimization of these bounds is achieved using the Karush-Kuhn-Tucker (KKT) conditions, which lead to a system of large-scale coupled Sylvester-type matrix equations (CSMEs). However, as the number of decision makers approaches infinity, solving the CSMEs becomes computationally challenging. To address this challenge, we propose a decentralized numerical algorithm based on a simplified Newton’s method that ensures solution convergence and achieves a linear convergence rate. Finally, numerical experiments are conducted to verify the practicality and effectiveness of the proposed approach.
Sample return missions play a significant role in planetary science by providing pristine extraterrestrial materials. JAXA's Hayabusa2 and NASA's OSIRIS-REx missions have returned samples from the C-type asteroids Ryugu and Bennu, respectively. The chemical and mineralogical compositions of these samples closely resemble those of CI chondrites, the traditional reference material for solar system abundances. Based on the findings of the Hayabusa2 mission, JAXA launched the Ryugu Reference Project (RRP) to maximize the scientific value of the returned samples and formed the RRP Measurement Definition Team (RRP-MDT) to elucidate the RRP's scientific goal and objectives. The RRP-MDT defined the goal of RRP to reassess the elemental abundances and isotopic compositions of the solar system through comprehensive analyses of the returned asteroid samples and CI chondrites. To this end, the team recommended preparing homogeneously powdered Ryugu reference materials (RRM) using approximately 750 and 400 mg of samples from Chambers A and C, respectively, to address observed compositional heterogeneities. The team proposed to measure the elemental abundances and isotopic compositions of the RRM by analytical techniques involving seven specific measurement groups. Through comprehensive analytical methodologies, interlaboratory calibration, and statistical evaluation, the RRP aims to refine our understanding of solar system formation and evolution.
Human brain organoids (HBOs) are three-dimensional structures derived from human stem cells that model aspects of brain development and function, offering potentially unprecedented opportunities for studying neurological disorders and for developing treatments. This consensus paper presents recommendations from the Asia Pacific Neuroethics Working Group, developed through interdisciplinary collaboration among scientists, bioethicists, philosophers, and legal scholars who convened in Singapore in November 2024. We provide a comprehensive analysis of the ethical, legal, and sociocultural dimensions of HBO research, addressing both current realities and future possibilities. The paper examines key ethical considerations, including the potential moral status of HBOs, particularly regarding sentience and consciousness, while identifying and dispelling common misconceptions and “ethical red herrings” arising from sensationalized portrayals. We analyze consent frameworks for cell donation, privacy concerns, dual-use risks, and questions of distributive justice. Legal challenges are explored, including the categorical ambiguity of HBOs within existing regulatory frameworks, intellectual property issues, and cross-border inconsistencies in standards. Sociocultural perspectives emphasize the importance of public understanding, cross-cultural engagement, and empirical research on diverse community attitudes toward HBO research. In our recommendations, we advocate for evidence-based ethical discussions, anticipatory frameworks addressing potential future developments, contextualized analysis comparing HBOs to related experimental models, robust informed consent processes, proportionate responses to consciousness concerns, development of adaptive regulatory frameworks, responsible science communication to manage public expectations, and sustained interdisciplinary collaboration. We emphasize a balanced approach that promotes scientific innovation while maintaining rigorous ethical oversight, recognizing HBOs’ significant potential for advancing neuroscience and medicine. This represents the first comprehensive ethical framework for HBO research from the Asia Pacific region, helping to establish foundational principles for responsible development of this rapidly advancing field.
The escalating global demand for renewable energy positions wave power as a critical sustainable resource. However, the widespread adoption of Wave Energy Converters (WECs) is impeded by challenges in optimizing hydrodynamic efficiency and reducing lifecycle costs. This paper provides a comprehensive review of the technological evolution of WECs, focusing on design optimization methods and emergent trends. A three-step methodology was employed, integrating descriptive analysis, bibliometric mapping, and a systematic review of optimization strategies. Our findings reveal a significant research trajectory towards hybrid energy systems, which co-locate WECs with offshore wind platforms to enhance energy capture and economic viability. The study underscores the pivotal role of advanced computational techniques, such as hybrid optimization algorithms, in elevating WEC performance. Nevertheless, critical gaps persist, primarily the lack of extensive experimental validation for numerical models and the need for algorithms with faster convergence. This review synthesizes the current state-of-the-art, offering valuable insights to direct future research toward more efficient and commercially viable WEC technologies.
