Search Results (2,333)

Accurate and up-to-date knowledge of land use and land cover represents one of the central challenges in spatial planning and landscape sciences. In this context, the present work introduces GANCIU (Geospatial Analysis with Neural Classification and Image Understanding), an original hybrid pipeline for the automatic extraction of man-made infrastructure from high-resolution satellite imagery. The primary methodological contribution lies in the sequential integration of four technologically heterogeneous components: a per-pixel Random Forest classifier, a guided image modulation step, edge detection via the Mumford–Shah variational functional solved through the Ambrosio–Tortorelli approximation, and final object delineation via the Segment Anything Model (SAM). Each component does not operate independently but conditions and informs the next: The RF probability map guides the modulation, which in turn directs the sensitivity of the variational step exclusively towards regions of interest; the AT edges provide spatial prompts to SAM, for which its masks are finally filtered by the RF probability in an adaptive manner through a Gaussian Mixture Model. This progressive conditioning scheme constitutes the architectural core of GANCIU and distinguishes it from approaches that combine classification and segmentation in parallel or in purely sequential fashion with each stage conditioning the next but without any reverse correction between them. The Random Forest classifier was trained on 44 manually annotated scenes, geographically disjoint from the twelve independent scenes used for quantitative validation. This validation, based on an instance matching protocol (precision, recall, F1 score, and IoU), confirms the contribution of the full pipeline over a Random-Forest-only baseline: Pooled false positives fall by close to two orders of magnitude (from 8320 to 209), while true positives rise nearly twentyfold (from 5 to 95), with a mean IoU of 0.742 ± 0.060 on correctly matched objects. Notably, the entire pipeline—including SAM-based segmentation—runs end-to-end on a modest, GPU-free consumer laptop (four logical CPU cores, under 16 GB RAM), demonstrating that competitive infrastructure-extraction performance does not require specialised computing hardware. Full article

This paper investigates practical finite-time adaptive fuzzy control for uncertain nonlinear systems subject to full-state constraints and unmeasured state variables. To deal with the inaccessibility of some state variables, an observer is constructed. A state-dependent nonlinear mapping is introduced to ensure that all system states remain within their prescribed bounds. In contrast to typical barrier Lyapunov function (BLF)-based schemes, the presented method manages full-state constraints without imposing any extra prerequisites on virtual control signals. Fuzzy logic systems (FLSs) act as estimators for the unknown nonlinearities emerging in the control law design, while the integration of dynamic surface control techniques helps circumvent the “complexity explosion” characteristic of conventional backstepping approaches. Subsequently, a practical finite-time adaptive fuzzy tracking controller is constructed, which guarantees the semi-global practical finite-time stability of the closed-loop system, with all closed-loop signals remaining bounded for all time and the tracking error converging to a residual set within finite time. Simulation results demonstrate that the tracking error enters a small residual set within finite time and that all system states remain within their prescribed constraints. Full article

Planning debates increasingly recognise that climate adaptation, community wellbeing, and tourism development cannot be treated as separate domains; yet existing place-based frameworks rarely integrate Indigenous governance, multidimensional wellbeing, and visitor dynamics within a single cohesive model. This article develops the Relational Resilient Place Framework as a conceptual model for understanding how culturally grounded landscapes can balance Indigenous authority, local community interests, and destination pressures. Drawing on mātauranga Māori (Indigenous knowledge) scholarship, therapeutic landscapes research, and the destination governance literature, the framework positions place as relational infrastructure. In this model, ecological vitality (mauri), collective wellbeing, cultural integrity, and visitor engagement are treated as interdependent rather than competing objectives. The framework is structured through six lenses: partnership integrity, cultural safety, community wellbeing, climate transition capacity, visitor–resident alignment, and long-term stewardship. The article establishes a conceptual basis for evaluating the theoretical conditions under which places function as resilient systems across rural, regional, and destination contexts. It argues that Indigenous governance principles provide a structural foundation for aligning wellbeing and tourism without reproducing extractive or growth-centric logics. In doing so, the framework demonstrates how Indigenous ontologies can move beyond symbolic inclusion to underpin resilient, non-extractive approaches to place-based planning. Full article

Extreme spatial intensification in affordable housing exposes the structural limitations of conventional room-based zoning, yet existing generative design methods often fail to deeply couple spatial automation with volatile occupant behavioral logic. This study proposes a generalizable Structure–Behavior–Function (SBF)-based generative framework to realize the transition from top-down rigid zoning to bottom-up behavioral adaptation. The framework deconstructs traditional rooms into three coupled layers: minimal ergonomic action domains (structural), 3D Design Structure Matrix-based activity correlation quantification (behavioral), and multi-objective optimization metrics encoding (functional). A discrete grid-based evolutionary approach with a hard–soft dual-constraint mechanism is introduced, combining geometric collision detection for physical feasibility and behavioral correlation rules for spatial zoning reward–punishment. Layout performance is validated via pedestrian circulation simulations. Using a representative megacity affordable housing standard as a case study, controlled computational experiments reveal an empirical power-law scaling boundary between minimum viable area and occupancy size. We establish an Adaptability Surcharge Index (ASI) to quantify the 3.0–7.2% spatial efficiency degradation from rigid structural constraints. The framework achieves 30.3–45.7% floor area reduction versus traditional benchmarks while maintaining comparable circulation efficiency. Validation using an existing residential case further confirms the practical applicability of the proposed framework. This work provides a scalable computational methodology for hyper-dense spatial optimization and a quantitative foundation for future residential space standard formulations. Full article

As the construction of new-type power systems continues, the extensive integration of renewable energy and power-electronic devices has significantly increased the risk of cascading failures in power grids, making accurate prediction of cascading-failure evolution paths crucial for grid security. However, real-world fault samples are extremely scarce, and conventional physics-based simulations are too computationally intensive for real-time online early warning. To address these challenges, this paper proposes a cascading failure evolution path prediction method based on massive event chain mining and prior knowledge constraints. First, we construct a refined cascading-failure simulation model that incorporates the action logic of the three defense lines to generate a large standardized event-chain dataset, thereby addressing the data scarcity faced by data-driven models. Second, a sequence-prediction engine that combines word embeddings, LSTM-based temporal modeling, and prior-knowledge constraints is developed; the physical action logic of the power system is explicitly incorporated into the loss function to improve the physical plausibility of the predictions. Finally, an evaluation framework from event prediction to third-defense-line early warning is constructed to assess system-level security risks. Based on simulations of the IEEE 39-bus AC/DC hybrid system, the proposed method is shown to achieve single-step Top-1 accuracies of 97.0% and 96.8% for the system-level critical events of frequency limit violation and system instability, respectively, with corresponding Top-3 accuracies of 99.2% and 99.4%. The overall Top-1 and Top-3 accuracies are 89.8% and 98.2%, respectively; the mean single-inference time is approximately 9.6 ms, corresponding to a speedup of more than 4700 times over conventional time-domain simulation, and the weighted mean early-warning lead time is 1.78 s. Full article

Under globalization, architectural forms, spatial logic, and consumption experiences have become increasingly homogeneous, making placelessness particularly evident in large-scale commercial complexes. Establishing meaningful connections between globalized commercial spaces and local culture, urban memory, and everyday life has consequently become an important issue in research on architectural cultural sustainability. Guided by critical regionalism, this study takes placelessness as its point of departure and cultural sustainability as its evaluative perspective. It develops a two-level analytical framework comprising architectural analysis and user perception evaluation and applies this framework to the Chengdu New Century Global Center. Architectural analysis examines the building’s objective characteristics in terms of spatial image, functional organization, environmental setting, and cultural expression. User perception data were collected through a questionnaire survey and semi-structured interviews, followed by descriptive statistics and comparative analysis across four corresponding dimensions: spatial, functional, environmental, and cultural perception. The results indicate that the building’s megascale form, contemporary architectural appearance, and multifunctional organization contribute to higher levels of spatial and functional perception. Environmental perception is also relatively positive, although deficiencies remain in resting facilities, route organization, and detailed spatial experience. By contrast, cultural perception is substantially lower than the other dimensions. The marine theme, exoticized settings, and entertainment-oriented imagery are more closely associated with a globalized consumer landscape than with the spatial translation of Chengdu’s local culture, urban memory, and everyday life. Consequently, the building’s thematic identity has not been effectively translated into users’ recognition of place-specific characteristics, suggesting that the production of commercial complex space continues to prioritize consumption efficiency over cultural expression. By operationalizing the critical regionalist concept of sense of place as an empirically assessable analytical tool, this study extends its applicability to large-scale commercial complexes and provides a diagnostic framework and practical strategies for enhancing their cultural sustainability. Full article

Industry 5.0 demands that engineering graduates develop competencies that integrate technical knowledge with human-centricity, sustainability and resilience. However, engineering education has not always advanced at the same pace, and effective educational designs that operationalise these principles within applied learning contexts remain scarce. This paper presents Innovation Day, a four-hour challenge-based learning experience that operationalises Industry 5.0 principles through an artificial intelligence (AI)-supported cyber–physical logistics challenge in management engineering master’s programmemes. The activity engaged 47 students organised into 14 teams across two master’s degrees at the Universitat Politècnica de València. Students progressively developed and integrated data structuring, QR-based identification, sequencing and storage assignment logic, computer vision and collaborative robotics within a single supervised automation workflow. All 14 teams completed the first three phases, while completion rates reached 71% in Phase 4 and 64% in Phase 5, reflecting the increasing demands of system integration. Results also show that generative AI acted as a pedagogical tool, enabling students with limited programming experience to develop functional Python applications while maintaining human validation and accountability. The experience demonstrates that complex Industry 5.0 scenarios can be translated into manageable, transferable educational activities through phased challenge design, functional validation gates and structured AI-supported learning. Full article

Alphonse Mucha’s oeuvre is frequently categorized as a formalist paradigm of ornamentation within the Art Nouveau movement. This study, however, contends that Mucha’s signature Q Formula is far from a mere aesthetic redundancy or a utilitarian embellishment; rather, it manifests as Autonomous Ornament—an autonomous generative process and an inherent rhythm. Adopting a synchronic structural perspective that transcends linear historical causality, this research frames ornament as a dynamic relational medium connecting individual perception with collective evolution across geocultural boundaries. With Theosophy serving as a historical mediation and synthesizing Rudolf Arnheim’s psychology of visual perception with Gilles Deleuze’s philosophy of the ornamental refrain (ritornello), this paper traces the cross-cultural construction of the Q Formula—from Mucha’s Moravian Catholic roots to the avant-garde Theosophical milieu of Paris. Through a horizontal comparative analysis with contemporary fin-de-siècle artists—specifically contrasting Gustav Klimt’s ornamental dissolution and Aubrey Beardsley’s ironic fragmentation—the study underscores Mucha’s distinct integrative strategy. Furthermore, it demonstrates a profound structural homology in topological energy between the Q Formula and the Eastern Kālacakra Mandala. Within this pure and vital ornamental logic, the circular main body acts as a centripetal anchor referencing Emptiness (Śūnyatā), while the boundary-crossing media serve as a metaphor for centrifugal Dependent Origination (Pratītyasamutpāda) and worldly manifestation through clothed repetition. Such ornamental rhythms collapse the classical hierarchy between structure and surface. Amidst the pervasive anxiety of fin-de-siècle industrialization, these forms exerted a visual soothing function, providing deep emotional and psychological efficacy. Mucha’s ornamental schemata reveal how repetitive and structural rhythms successfully transmuted traditional religious paradigms into channels for the internal integration of the modern subject. The paper thus reaffirms ornament as a form of critical imagination and an independent artistic force, which not only reshapes the psychological homeostasis of the modern subject but also constructs a profound resonance between form and life within a cross-cultural context. Full article

Digital ecosystems, misinformation exposure, mental-health vulnerability and unequal access to care create distinctive challenges for young people. Although youth participation in health governance is increasingly advocated internationally, structured evidence from youth deliberative processes remains limited in Portugal. This study synthesises priorities expressed in two Portuguese deliberative initiatives coordinated by the Sociedade Portuguesa de Literacia em Saúde: the Mini-Assemblies of Health 2022–2023, with particular attention to the 3rd Mini-Assembly on Fighting Health Misinformation, and the Youth Health Choices Forum 2024. Both processes used a structured nominal-group logic to support idea generation, clarification, recording and prioritisation. The analysis used low-inference cross-session thematic aggregation to preserve propositional integrity and remain close to participants’ formulations. Five priority domains were identified: digital health communication and information credibility; curriculum-integrated and peer-mediated health literacy; low-friction mental-health access and stigma reduction; equity and functional service accessibility and governance, accountability and youth participation. Participant quotations are retained, in translated form, to preserve youth voice and to show how recommendations emerged from concrete deliberative formulations. The findings suggest that nominal group technique (NGT)-based youth deliberation can generate operational recommendations for policy and practice, including credibility mechanisms for digital health information, school-based health-literacy integration, autonomy-preserving access routes for mental-health support, and permanent youth participation structures. The findings support recognising young people not only as vulnerable recipients of health information but also as interpreters of digital health ecosystems and contributors to the design of more responsive health governance. Full article

The rapid growth of cloud and distributed computing systems has increased the complexity of real-time request distribution under dynamic and multi-factor conditions. In such environments, load-balancing decisions must simultaneously consider uncertain and interdependent parameters, including server load, response time, and resource capacity. Fuzzy logic is an effective tool for modeling such uncertainty; however, the expansion of linguistic variables often leads to a rule-explosion problem, which increases computational complexity and reduces the real-time applicability of fuzzy load-balancing systems. This study proposes an explainable multi-objective quantum-inspired fuzzy optimization approach for scalable load balancing in complex computing environments. The proposed model integrates fuzzy inference with a Grover-inspired classical search strategy to optimize the selection of fuzzy rule subsets. The Grover-inspired component is implemented as a classical simulation rather than a gate-based quantum circuit. A multi-objective evaluation function is formulated to jointly assess rule accuracy, coverage, interpretability, and compactness. This formulation enables the model to reduce redundant fuzzy rules while preserving decision transparency and maintaining reliable load distribution performance. The proposed approach is evaluated in a simulated cloud computing environment with heterogeneous servers and dynamic request arrival patterns. Comparative experiments are conducted against classical load-balancing strategies, conventional fuzzy load balancing, and evolutionary fuzzy optimization methods, including GA-FLB and PSO-FLB. The experimental results show that the proposed model reduces the size of the fuzzy rule base while maintaining competitive response time, load distribution quality, SLA compliance, and decision interpretability. These findings indicate that the integration of Grover-inspired classical search mechanisms with fuzzy reasoning provides a promising direction for developing scalable, compact, and explainable load-balancing models for next-generation intelligent computing systems. Full article

Synaptic failure is the most accurate pathological correlate of cognitive and motor decline in neurodegenerative diseases. However, the molecular logic governing selective synaptic vulnerability in Alzheimer’s (AD) and Parkinson’s (PD) remains a fundamental enigma. This review dissects the hierarchical organization of the synaptome, arguing that synaptic decay is not a generic process of attrition but a specific collapse of subsynaptic domains (SSDs) and trans-synaptic nanocolumns, considered here within the framework of the tetrapartite synapse, which comprises the presynaptic and postsynaptic compartments together with glia and the perisynaptic extracellular matrix. We use the term pathological convergence in a restricted sense, to denote that, although the primary aggregates differ, the two diseases converge on the same postsynaptic scaffolding hubs and on a comparable loss of condensate fluidity. We propose a biophysical model where the Post-Synaptic Density (PSD) matrix, governed by liquid–liquid phase separation (LLPS), may undergo a pathological liquid-to-solid transition—characterized by condensate maturation and the formation of insoluble protein aggregates—driven by proteotoxic species. Specifically, we analyze how Aβ-mediated zinc sequestration disrupts the Shank-SAM scaffold hierarchy in AD, while α-synuclein aggregates arrest presynaptic vesicle dynamics and mitochondrial homeostasis in PD. Furthermore, we explore the emerging frontier of “Precision Synaptopharmacology,” highlighting how targeted modulation of protein–protein interaction (PPIs), synthetic synaptic organizers (e.g., CPTX), and phase-stabilizing chaperones can restore nanocolumn alignment and synaptic fluidity. We also set out the principal limitations of these strategies, including blood–brain barrier delivery, off-target effects, the immaturity of condensate-directed pharmacology and the incomplete translation of rodent findings to human disease, and we consider the vascular and peripheral contributions that modify the synaptic environment. By integrating recent advances in super-resolution microscopy, systems biology, and activity-based neurorehabilitation, we provide a comprehensive framework for shifting neuroprotective strategies toward the precision engineering and functional recovery of synaptic nano-architecture. Full article

Breast cancer treatment still faces challenges including local recurrence, systemic toxicity, tumor heterogeneity, drug resistance, and immunosuppression. Conventional systemic administration provides limited exposure at the tumor site and exhibits significant toxicity. Injectable hydrogels, combining the properties of minimally invasive administration, in situ gelation, local retention, and sustained release, have become a key platform for local precision drug delivery. Compared with nanomedicines or free drugs, hydrogels can both prolong drug retention time and achieve on-demand release through the modulation of crosslinking density, degradation rate, and responsive chemical bonds. This review is organized around the material logic of such systems. Injectable hydrogels are first classified into natural, synthetic, hybrid, supramolecular, nanocomposite, and self-healing systems, the in situ gelation chemistries available to each are compared, and network parameters such as crosslinking density, mesh size, swelling, porosity, modulus, and rheology are related to release kinetics and intratumoral retention. Current research is primarily advancing along two directions: one is the construction of pH-, enzyme-, redox/ROS-, hypoxia-, ATP-, glucose-or thermo-responsive hydrogels; the other is achieving active targeting by integrating functionalized hydrogels with targets such as CD44, folate receptor, integrins, EGFR, transferrin receptor, and HER2 or with biomimetic cell-membrane coatings. On this basis, hydrogels have been extended to cancer vaccines, immune checkpoint modulation, local delivery of CAR-T/CAR-NK, as well as combination therapies involving chemotherapy, photothermal therapy, photodynamic therapy, chemodynamic therapy, sonodynamic therapy, radiosensitization, gene therapy, and theranostics. The constraints imposed on hydrogel design by different payload classes, including small molecules, natural products, proteins and peptides, nucleic acids, antibodies, exosomes, and gene-editing machinery, are further examined, and imaging-integrated theranostic gels are discussed together with the emerging role of machine learning and digital fabrication in hydrogel optimization. Based on the biological foundations of breast cancer, this review summarizes advances in the material design, microenvironment-responsive release, targeting strategies, immunomodulation, and combination therapy of hydrogels, critically evaluates the limitations of each strategy, and aims to provide a reference for the design of mechanistically well-defined and translatable hydrogel delivery systems for breast cancer. Full article

Application-specific instruction set processors (ASIPs) often employ specialized hardware to improve performance, but this introduces complexity in resource management and programming. Existing compiler solutions, including LLVM’s default schedulers, lack fine-grained structural conflict analysis for complex arithmetic logic unit (ALU) instructions, leading to suboptimal performance or runtime errors. This limitation becomes critical when targeting very long instruction word (VLIW) architectures with instruction fusion units that exhibit pipeline-stage-level resource contention. In this paper, we propose a compile-time instruction scheduling method that models sub-cycle resource usage and analyzes both data and structural dependencies at fine granularity. Unlike coarse-grained resource tables used in existing compilers, our approach tracks functional unit occupancy at the pipeline stage level, enabling precise detection of structural hazards in complex execution units. We implement this scheduler as a backend pass in the LLVM compiler framework and validate it on the Sayram VLIW processor for wireless communication. Experimental results show that our approach achieves 100% scheduling correctness while improving execution efficiency by 23% on average compared with in-order scheduling, with benefits up to 38% for highly parallel kernels such as PRACH, and reducing average running time by 66% compared with atomic execution. Full article

Metro stations, while essential for urban transportation, pose unique evacuation challenges due to confined layouts and high densities; existing models often struggle to accurately capture individual pedestrian behaviors and the dynamic spread of fires. This study introduces a human–fire–agent interaction model designed to enhance the understanding and simulation of critical interactions among pedestrians, fire dynamics, and the underground environment of a metro station. The model integrates social force modeling and fluid dynamics to accurately represent pedestrian behavior and fire spread, for a more complete analysis of evacuation scenarios. Using Lumu Station in Suzhou as a case study, this study develops a detailed simulation framework implemented in an integrated PyroSim-Python-AnyLogic platform to model the evacuation process. The framework is employed to evaluate the effectiveness of turnstile reversal strategies—an approach that involves temporarily reversing the direction of turnstiles to facilitate faster evacuation during emergencies. Beyond mitigation, this study extends to the preparedness phase by functioning as a high-fidelity digital twin. It enables immersive “Serious Game” training and provides a quantitative tool for railway managers, decision-makers, and engineers to optimize operating procedures and performance-based station designs. Full article

The central objective of this study is to demonstrate the possibility of constructive dialogue between Christianity and Islam through a comparative examination of two concepts closely related to the transmission and expansion of religious faith: mission and da’wah. Although both terms refer fundamentally to the communication of one’s faith to others—and may, therefore, appear to be associated with a logic of competition between religions—each also contains an intrinsic dimension of respect for the other. This dimension becomes particularly evident when their authentic meaning is understood not in terms of coercion or violence, but as a form of witness expressed through one’s way of life. Moreover, these concepts should not be interpreted solely as activities directed toward those outside the religious community. They also function as dynamics addressed to the believing community and to the individual believers themselves, with the purpose of deepening, renewing, and revitalizing faith. In this sense, the Christian notion of first proclamation—understood qualitatively as a renewed encounter with the Gospel—and the Islamic understanding of da’wah directed to the umma as a call to spiritual conversion reveal a significant point of convergence. This shared perspective may, therefore, provide an important foundation for constructive dialogue between the two religious traditions. Full article