Search Results (763)

This article examines the Unité Pédagogique d’Architecture in Toulouse (UPAT) as a paradigmatic example of the palimpsestic architectures that characterize many contemporary university campuses. Conceived in the immediate aftermath of May 1968, the school emerged at a moment when pedagogical reform, political commitment, and architectural experimentation became closely intertwined. These conditions gave rise to a singular spatial organization based on a combinatory grid, intended to give architectural form to a democratic ideal of education grounded in openness, flexibility, and collective agency. The study adopts a historical–critical methodology based on the systematic analysis of primary and secondary sources, complemented by original graphic interpretations. This approach makes it possible to read the UPAT simultaneously as a didactic instrument and as an ideological manifesto, one whose ambitions were inherently marked by internal tensions and contradictions. A diachronic examination of subsequent extensions and transformations reveals how these founding intentions were progressively reinterpreted, constrained, or displaced in response to changing institutional, social, and cultural conditions. Taken as a whole, the evolving trajectory of this “manifesto school” illuminates the ways in which architectural ideals—particularly the pursuit of openness—are negotiated over time, offering a critical perspective on the reciprocal shaping of architecture, pedagogy, and institutional identity within the history of university buildings. Full article

Background/Objectives: Successful interception of moving targets requires combining predictive control, which anticipates future target states, and reactive control, which compensates for ongoing sensory discrepancies. How these components evolve over time and are distributed across gaze and manual behavior remains unclear. We aimed to explore the time-resolved dynamics of predictive control during continuous interception and to dissociate eye and hand contributions. Methods: Human participants intercepted a moving target in a two-dimensional arena using a joystick while eye movements were recorded. Target speed was systematically varied, and visual information was selectively reduced by occluding either the target or the user-controlled cursor. Predictive control was assessed using two complementary metrics: a geometric strategy index capturing moment-to-moment spatial lead or lag relative to target motion, applied separately to gaze and manual trajectories, and root mean square error (RMSE) computed relative to current and forward-shifted target positions to quantify predictive alignment. Results: Successful interception was characterized by structured, speed-dependent transitions between predictive and reactive control rather than a fixed strategy. Predictive alignment emerged early and was dynamically reweighted as temporal constraints increased. Gaze and manual behavior showed complementary but partially dissociable predictive signatures. Occluding the target decreased predictive alignment, whereas occluding the user-controlled cursor had comparatively minor effects, indicating strong reliance on internal state estimation rather than continuous visual feedback of the effector. Conclusions: Predictive and reactive control are continuously and dynamically reweighted during interception. Their interaction unfolds within single trials and depends on target dynamics and sensory availability. These findings provide quantitative evidence for time-resolved coordination between anticipatory and feedback-driven control mechanisms in goal-directed behavior. Full article

The study of resilience has long focused on understanding how individuals positively adapt to adversity, a process that directly influences emotional stability. Resilience, defined as the capacity to confront, overcome, and transform complex challenges constructively while strengthening oneself in the process, represents a transversal trait in human development. It also entails engaging in a personal growth trajectory that fosters self-awareness and internal coherence. Within the context of high abilities, this construct assumes particular significance, as students with high cognitive potential, but they are not immune to socio-emotional and educational vulnerabilities. These vulnerabilities may arise from asynchronies between intellectual and emotional development, among other factors, and influence specific coping strategies that, in turn, affect academic and social outcomes. Furthermore, high abilities students often have unique educational needs that may be insufficiently recognized or supported within their socio-cultural environments. Consequently, resilience in high abilities students should be understood as a dynamic process shaped not only by individual cognitive resources but also by contextual factors. A thorough analysis of the specific vulnerabilities of this population, and their interactions with environmental influences, is essential for fostering resilience and designing psychoeducational interventions that enhance academic achievement, promote inclusive practices, and support overall well-being. Full article

Sustainability can be broadly understood as the capacity of human societies to operate within ecological limits while maintaining long-term social and economic stability. Within global policy frameworks, it has evolved from a normative ideal to a structured and measurable paradigm of governance. This article outlines the institutional and political evolution of sustainability, tracing how international agreements—from the 1972 Stockholm Conference to Agenda 2030 and the Paris Agreement—have transformed environmental concerns into quantifiable commitments. The modern concept of sustainability emphasises integration across sectors and scales, linking environmental protection with development, equity, and resilience. Understanding this trajectory is essential for interpreting current global governance mechanisms and for promoting coherent, data-driven approaches to sustainable development. Full article

The energy transition represents a complex, multi-level system subject to profound uncertainty and recurrent shocks. Current policy design approaches predominantly rely on static optimization frameworks (centralized, calculative models that presume stable conditions and predictable technological trajectories). Yet evidence from the 2021–2023 energy crisis in Europe, coupled with structural challenges in market liberalization and renewable integration, demonstrates persistent challenges in policy implementation. Price interventions affect competitive dynamics; subsidies influence technology selection; capacity mechanisms create coordination tensions; and rigid tariff structures create misalignments with evolving grid needs. This paper argues that these recurrent policy tensions stem not from implementation gaps, but from an inadequate theoretical foundation: the treatment of energy systems as optimizable rather than as complex, adaptive systems operating under Knight–Mises uncertainty and Huerta de Soto dynamic efficiency. This work explores an alternative framework grounded in dynamic efficiency, complex–uncertain systems, decentralized incentives, and adaptive governance (international–domestic, public–private, etc.). This review uses the theoretical and methodological framework of the Heterodox Synthesis, an alternative to the Neoclassical Synthesis. There is a reinterpretation of some insights from Knight and Mises (uncertainty), Hayek (distributed knowledge), Huerta de Soto (dynamic efficiency) and contemporary complexity economics into operational criteria applicable to energy policy design: (1) robustness to deep uncertainty; (2) preservation of price signals and risk-bearing mechanisms; (3) alignment of incentives across distributed actors; (4) institutional adaptability; and (5) minimization of ex post policy corrections. Through illustrative application to four critical policy instruments (price caps, renewable subsidies, capacity mechanisms, and network tariff design), it is shown how this framework identifies systematic tensions and consequences that conventional analysis overlooks. The contribution is exploratory in a bootstrap way: theoretical, by integrating classical and contemporary economics into energy governance; methodological, by operationalizing dynamic efficiency into evaluable criteria distinct from existing adaptive governance frameworks; and sectorial, by providing policymakers and regulators with diagnostic tools for assessing design robustness in conditions of deep uncertainty and rapid transition. According to this review, improved energy policy design under uncertainty is not achieved through more sophisticated optimization (in a calculative way), but through institutional architectures that preserve creative and adaptive learning, maintain distributed decision-making capacity, and remain functional when assumptions prove incorrect or not well-known. Full article

Hyperspectral unmixing (HU) is fundamental for conducting quantitative analyses in remote sensing, yet existing methods face a persistent tradeoff between model performance and physical interpretability. Although deep learning models achieve superior performance, even “gray-box” models that incorporate physical constraints still suffer from an intrinsically opaque decision-making process, which hinders their trustworthiness in critical applications. To address this challenge, this paper introduces a theory-guided unmixing framework aimed at enhancing mechanistic interpretability called the sparse and subspace-attentive transformer unmixing network (SSTU-Net). Unlike heuristic architectures, SSTU-Net is rigorously derived from the first principles of sparse rate reduction (SRR) theory. Its core modules—the multi-head subspace self-attention (MSSA) and the iterative shrinkage-thresholding algorithm (ISTA)—directly implement the essential mathematical steps of information compression and sparsification within the SRR theory, respectively. Extensive experiments on both synthetic and real hyperspectral datasets demonstrate that SSTU-Net achieves competitive performance compared to representative state-of-the-art methods—including advanced autoencoder-based networks (e.g., CyCU-Net and DAAN) and recent transformer-based unmixing architectures (e.g., DeepTrans and MAT-Net)—while strictly adhering to theoretically predicted evolutionary trajectories. More importantly, a series of specifically designed structural interpretability validation experiments mechanistically confirm the theoretically predicted behaviors, such as layer-wise information compression, feature sparsification, and subspace orthogonalization. These results reveal the internal working mechanisms of SSTU-Net, validating the feasibility and significant potential of our principled theory-guided framework for developing high-performance and trustworthy intelligent models in remote sensing. Full article

The COVID-19 pandemic, particularly during its declared Public Health Emergency of International Concern (PHEIC) period, has flattened the bid-rent curve and increased the rate of functional obsolescence of older office buildings. A critical question remains as to whether these trends have persisted or moderated following the official end of the PHEIC in May 2023. This study investigates the trajectory of office market dynamics in Hong Kong during and after the PHEIC period. Using secondary transaction data from Hong Kong, we find that the decline in the marginal value of proximity to the central business district (CBD), which was most pronounced during the PHEIC period, has subsequently moderated. In addition, this moderation is significantly stronger for high-end offices than for low-end ones. Furthermore, we find that the functional obsolescence of older office buildings not only accelerated during the PHEIC period but continued and further strengthened after the PHEIC period. Full article

Wetlands, frequently termed the “kidneys of the Earth,” represent one of the most vital global ecosystems. Despite their limited spatial extent, plateau wetlands function as unique ecological units that play a pivotal role in the global carbon cycle, water resource regulation, and biodiversity conservation, while exhibiting acute sensitivity to climate change. Advances in remote sensing technology—characterized by macro-scale cover-age, temporal efficiency, and non-invasive operations—have established it as a corner-stone for the dynamic monitoring and analysis of these environments. This study presents a bibliometric synthesis of 2138 publications (1982–2024) retrieved from the Web of Science Core Collection. We systematically evaluated publication trajectories, international collaborative networks, disciplinary shifts, core journals, and the spatiotemporal evolution of research hotspots. Our findings reveal an exponential growth in scholarly output alongside a marked diversification of research fields. Geographically, research is predominantly clustered around the Tibetan Plateau, flanked by the Alps and the Himalayas, with sparse representation in other regions. Future endeavors should prioritize underrepresented low-latitude and remote regions through strengthened international synergy and the integration of emerging technologies, such as UAVs and hyperspectral sensors. Full article

Intelligence metrics based on benchmark performance or population norms are useful for measuring comparative ability within defined test environments, but they do not directly evaluate the structural coherence of an agent’s trajectory across time, domains, and perturbations. This article introduces Reflexive Signature Intelligence (RSI) as a bounded theoretical framework for addressing that different problem. RSI is developed within a causal-symmetric informational perspective in which intelligence is understood as the capacity of a system to maintain and restore alignment with a structurally constrained invariant without collapsing the open gradient of development. On this basis, the paper formulates the Principle of Bounded Subjectivity and the Prohibition of Finality as framework-level principles, arguing that intelligence should be assessed not as arrival at a completed end state but as the quality of an asymptotic trajectory. The framework is then operationalized on two coupled levels: a micro-level proposed as a future measurement program linked heuristically to resilience and prediction-error dynamics, and a macro-level expressed through five dimensions of structural integrity, including reflexive regulation, cross-domain integration, internal consistency, stabilization, and signature-setting. The article concludes by outlining implications for AI evaluation and alignment, with particular relevance for distinguishing full agents, partial systems, and human–AI composite configurations. Full article

This study presents a novel data-driven framework for developing airport-specific landing policies and procedures from historical successful-landing data. The proposed process, termed the Airport-Dependent Landing Procedure (ADLP), is motivated by the fact that airports rely on uniquely tailored approach charts reflecting local operational constraints and environmental conditions. While existing approach charts and landing procedures are primarily designed based on expert knowledge, safety margins, and regulatory conventions, the authors argue that data science and data mining techniques offer a complementary and empirically grounded methodology for extracting operationally meaningful structures directly from historical landing data. In this work, we construct a probabilistic three-dimensional environment from real-world aircraft approach trajectories, capturing spatiotemporal relationships under varying atmospheric conditions during approach. The proposed methodology integrates Adversarial Inverse Reinforcement Learning (AIRL) with Recurrent Proximal Policy Optimization (R-PPO) to establish a foundation for automated landing without pilot intervention. AIRL infers reward functions that are consistent with behaviors exhibited in prior successful landings. Subsequently, R-PPO is employed to learn control policies that satisfy safety constraints related to airspeed, sink rate, and runway alignment. Application of the proposed framework to real approach trajectories at Guam International Airport demonstrates the efficiency and effectiveness of the methodology. Full article

This study presents a comprehensive regional analysis of the COVID-19 pandemic’s impact on tourism in Slovakia during 2018–2024, employing rigorous statistical methods to quantify sectoral transformations. Based on extensive data on visitor arrivals, revenues, and accommodation facility utilisation across eight NUTS III regions, the analysis identifies four distinct regional tourism clusters characterised by differentiated recovery trajectories. Paired t-tests confirmed statistically significant changes in international tourist arrival indices across seven regions (p < 0.05), validating fundamental structural reorientation in tourism demand. The findings reveal pronounced heterogeneity in recovery patterns: while the Bratislava Region and the Žilina Region achieved substantial revenue growth (46.04% and 146.54%, respectively), domestically oriented regions (Banská Bystrica, Košice, Nitra, Prešov, and Trenčín) demonstrated minimal recovery (8.19% aggregate growth). Critical findings include the persistence of passive tourism dominance (94.09% of national revenues), declining international competitiveness from traditional Western European source markets, and compensatory expansion from emerging markets (USA +398.73%, Oman +234.68%, and Poland +226.55%). The ANOVA analysis revealed no statistically significant differences between regional indices in 2024 (p = 0.362), indicating market stabilisation despite differentiated trajectories. The study emphasises the necessity of regionally calibrated sustainable strategic interventions to diversify experiential tourism, activate the domestic market, and enhance technological infrastructure to build sectoral resilience against future exogenous shocks. Full article

The hollow fiber membrane humidification modules are used for indoor humidification in hot–dry regions and heating in winter. The module is composed of several flexible hollow fiber membranes, which are bent and displaced by gravity and fluid forces. This paper is a further study of previous work that reveals the internal relationship between the forces generated by vortex shedding and fiber vibration. The central trajectories of fibers in the flow field are described for various pulsating flow and fiber structure parameters. The effects of fiber displacement on fluid flow, heat transfer, and mass transfer performance at different parameters are discussed. The results show that the fiber displacement in the flow field consists of two components: (i) deformation caused by fluid drag force and gravity and (ii) periodic vibration caused by periodic lift and drag force as vortices shed at the fiber surface. The fiber vibration facilitates the vortex shedding on the fiber surface, which enhances the convective heat and mass transfer performance on the fiber surface. The average friction factor (f_m,v), Nusselt number (Nu_m,v), and Sherwood number (Sh_m,v) increased by 12.9%, 39.3%, and 20.0%, respectively, when the fiber vibrated compared to non-vibration. This implies that inducing fiber vibration can optimize the heat and moisture transfer performance. Full article

This study investigates whether external terms of trade (TOT) and mining-sector GDP in Peru share a stable long-run relationship. Although mining has played a central role in the country’s growth trajectory, its performance remains highly exposed to international price cycles, raising questions about its structural sustainability under persistent external shocks. Using quarterly data for 2001–2024, the analysis applies Johansen cointegration techniques and estimates a bivariate Vector Error Correction Model (VECM) to evaluate long-run co-movement and short-run adjustment dynamics. The results identify a single cointegrating relationship in which mining GDP acts as the primary adjustment variable, gradually correcting deviations from long-run equilibrium, while short-run TOT shocks do not exert direct contemporaneous effects on mining growth. The estimated speed of adjustment is low, suggesting a prolonged convergence process consistent with the capital-intensive and rigid structure of the mining sector. Robustness exercises—including estimation with heteroskedasticity and autocorrelation consistent (HAC) standard errors and an extended specification incorporating gross fixed capital formation—confirm the stability of the long-run relationship. These findings indicate that the structural sustainability of mining output depends on the interaction between external price dynamics and the sector’s capacity to adjust to persistent international shocks. The study concludes that, in the Peruvian case, structural sustainability in the mining sector is not determined solely by global price trends, but is also conditioned by domestic productive and institutional factors that govern the speed of adjustment in the presence of sustained external volatility. Full article

Accurate monitoring of internal particle motion in dense granular flows remains a significant challenge across various fields, ranging from geophysics to industrial processes. To address the limitations of existing observational techniques, this study presents a novel high-precision magnetic array positioning system based on magnetic dipole theory for dynamically tracking individual particles within opaque granular media. The system integrates an array of nine magnetic sensors with a hybrid optimization algorithm that combines Particle Swarm Optimization (PSO) and gradient-based local refinement, achieving a dynamic positioning accuracy within the maximum measurable range, with a maximum dynamic error of 2.5 ± 0.5 mm and a trajectory continuity exceeding 99%. Deployed in a quasi-two-dimensional rotating drum, the system enables detailed investigation of particle segregation mechanisms. Reconstruction and analysis of the trajectories of a high-density intruder (magnetic bead) allow quantification of the competition among segregation mechanisms through the Froude number. The results reveal three distinct motion phases with increasing rotational speed: a gravity-dominated percolation stage, a transitional collision–diffusion competition stage, and a centrifugal diffusion-dominated stage. Each phase exhibits unique kinematic signatures governed by the interplay of inertial, gravitational, and contact forces. This work not only establishes a robust and accurate sensor-based method for internal granular flow monitoring but also provides new mechanistic insights into segregation dynamics, with implications for understanding geological hazards such as debris flows. Full article

The field of extracellular vesicle (EV) research offers a compelling example of a biological concept refined through continuous methodological innovation. This review traces the historical trajectory of the discipline chronologically, beginning with early observations in haemostasis, from Malpighi’s descriptions of blood clots and Chargaff and West’s identification of a procoagulant sedimentable plasma fraction, to Wolf’s “platelet dust,” Crawford’s microparticles characterised by electron microscopy, and the seminal work by Stahl and Johnstone demonstrating regulated vesicle biogenesis during reticulocyte maturation via multivesicular bodies. We highlight a pivotal conceptual shift, from viewing EVs as cellular debris to recognising them as regulated “communicasomes,” catalysed by Raposo’s discovery of antigen-presenting exosomes and subsequent evidence for EV-mediated transfer of functional receptors and nucleic acids, including the influential and sometimes debated model proposed by Ratajczak. By integrating findings from matrix vesicles, plant-derived vesicles, and diverse tissue contexts, we frame EV release as an evolutionarily conserved process with profound implications for immunity, regeneration, oncology, and cardiovascular pathology. A second central aim of this review is practical and methodological. We map how the expansion of biological claims has driven urgent standardisation efforts, notably through the establishment of the International Society for Extracellular Vesicles (ISEV) and the successive MISEV guidelines (2014, 2018, 2023). These are complemented by community resources such as EV-TRACK, MIFlowCyt-EV, and the databases ExoCarta and Vesiclepedia. We summarise core experimental choices across isolation and characterisation techniques, including ultracentrifugation, size exclusion chromatography, density gradients, flow cytometry, nanoparticle tracking analysis, and electron microscopy, while outlining persistent bottlenecks in purity, standardised nomenclature, and experimental reproducibility. Finally, we provide concise biographical sketches of key contributors and an overview of major EV-focused journals and ISEV meetings that anchor consensus-building and the translation of fundamental knowledge into clinical and industrial applications. Full article