Search Results (1,897)

During the interpretation of Borehole Radar (BHR) B-scan profiles, the accurate determination of the azimuth of geological targets in three-dimensional space is a critical issue for achieving precise anomaly localization and spatial structure inversion. However, existing directional BHR anomaly localization methods exhibit limited intelligence, insufficient adaptability to multi-site data, and weak generalization capability, rendering them inadequate for engineering applications under complex geological conditions. To address these challenges, a robust deep learning model, termed BSS-Pose-BHR, is developed based on YOLOv11n-pose for keypoint detection in directional BHR profiles. The model incorporates three key optimizations: Bi-Level Routing Attention (BRA) replaces Multi-Head Self-Attention (MHSA) in the backbone to improve computational efficiency; Conv_SAMWS enhances keypoint-related feature weighting in the backbone and neck; and Spatial and Channel Reconstruction Convolution (SCConv) is integrated into the detection head to reduce redundancy and strengthen local feature extraction, thereby improving suitability for keypoint detection tasks. In addition, a three-dimensional electromagnetic model of limestone containing a certain density of clay particles is established to construct a simulation dataset. On the simulated test set, compared with current mainstream deep learning approaches and conventional directional borehole radar anomaly localization algorithms, BSS-Pose-BHR achieves superior performance, with an mAP50(B) of 0.9686, an mAP50–95(B) of 0.7712, an mAP50(P) of 0.9951, and an mAP50–95(P) of 0.9952. Ablation experiments demonstrate that each proposed module contributes significantly to performance improvement. Compared with the baseline, BSS-Pose-BHR improves mAP50(B) by 5.39% and mAP50(P) by 0.86%, while increasing model weight by only 1.05 MB, thereby achieving a reasonable trade-off between detection accuracy and complexity. Furthermore, indoor physical model experiments validate the effectiveness of the method on measured data. Robustness experiments under different Peak Signal-to-Noise Ratio (PSNR) conditions and varying missing-trace rates indicate that BSS-Pose-BHR maintains high detection accuracy under moderate noise and data loss, demonstrating strong engineering applicability and practical value. Full article

Urban transformations outpace established urban design paradigm shifts. This acceleration widens the gap between inherited theory and contemporary urban realities This article addresses this condition by introducing epistemic urban design as a conceptual orientation and generative inheritance as its procedural extension within urban conditions described as unprecedented urbanism. Drawing on a critical interpretive synthesis of the literature spanning historical, theoretical, and technological developments, the study examines how urban design knowledge is produced, stabilized, and reinterpreted as urban complexity intensifies. The analysis unfolds in three phases. First, it traces how established paradigms historically structured design practices and how current conditions expose their operational limits. Second, it articulates how epistemic urban design treats design knowledge as an evolving resource, specifying analytical dimensions for interpreting diverse urban conditions. Third, it proposes how generative inheritance operationalizes epistemic urban design by linking inherited design knowledge to context-specific empirical situations. The article contributes to urban design research by supporting epistemic urban design with the procedural logic of generative inheritance. This shift enables theoretical insights to systematically inform design operations under conditions of unprecedented urbanism. Full article

Water scarcity compels wastewater reuse, but lax discharge standards generate a regulatory mirage, misleading the public about safety. Here, “regulatory mirage” refers to situations where formal compliance with discharge standards creates a false perception of safety while ecological risks and degradation persist. Despite formal compliance, treated effluent severely harms Iran’s effluent-dependent Kashaf River, driving eutrophication, salinization, and the downstream transport of unregulated contaminants of emerging concern, including fluorinated substances (PFAS) and pharmaceuticals. These pressures extend beyond the river channel to adjacent natural wetlands, which act as de facto nature-based treatment systems yet are progressively transformed into sacrificial sinks for excess nutrients, salts, heavy metals, and micropollutants. By benchmarking the Iranian Wastewater Discharge Standards (IWDS) against international guidelines (WHO, EU, FAO), this study quantifies a “Permissibility Gap” frequently greater than 10 for key parameters such as BOD₅, nutrients, and trace metals, revealing how concentration-based limits ignore cumulative mass load and mixture toxicity at the basin scale. The Kashaf River case demonstrates that current end-of-pipe regulation undermines both natural wetlands and planned nature-based solutions, including constructed wetlands, in arid regions where effluent reuse is unavoidable. The study argues that aligning discharge standards with global benchmarks, adopting mass-based permits, and explicitly regulating contaminants of emerging concern are prerequisites for truly safe wastewater reuse and for protecting wetland ecosystems in effluent-dependent basins. This study shows that permissive, concentration-based discharge standards in effluent-dependent basins create a regulatory mirage that accelerates river and wetland degradation, and that stricter, mass-based limits are essential for safe wastewater reuse. Full article

Within the Industry 5.0 paradigm, the management of critical assets requires advanced digital architectures capable of ensuring resilience and operational sustainability. The present systematic review analyzes the state of the art in predictive maintenance (PdM) technologies for turbines and turbomachinery, providing a technical examination of anomaly and fault detection frameworks, extended to remaining useful life (RUL) estimation and root cause analysis (RCA). The work addresses inherent sectoral challenges, ranging from the processing of high-dimensional multivariate time series (MTS) from Supervisory Control and Data Acquisition (SCADA) systems to labeled data scarcity and signal non-stationarity in real-world environments. Both purely data-driven frameworks and hybrid physics-informed models, such as Physics-Informed Neural Networks (PINNs), are critically evaluated against performance indicators. A significant contribution of this study lies in the classification of methodologies based on their readiness for real-time inference, emphasizing the role of Explainable AI (XAI) in providing transparent insights to domain experts, who remain central to decision-making processes. The primary objective of this review is to offer an analytical overview of progress to date against current technological gaps, tracing a clear trajectory for future developments. In this regard, the adoption of Generative AI and Large Language Models (LLMs) is identified as a fundamental step toward evolving into interactive, human-centric decision support systems. Full article

Both the Lower Silurian Longmaxi Formation and the Upper Permian Dalong Formation shales in southern China are organic-rich with well-developed nanoscale reservoir pores, demonstrating significant shale gas exploration potential. However, the current lack of in-depth research on the differential depositional and reservoir evolution characteristics of these two shale sequences has left the main controlling factors of the reservoirs unclear, thereby constraining breakthroughs in shale gas development. Focusing on the Longmaxi and Dalong formation shales in the Sichuan Basin, this study employed various analytical methods, including major and trace element analyses, X-ray diffraction (XRD), high-pressure mercury intrusion (HPMI), nitrogen adsorption, CO₂ adsorption, and scanning electron microscopy (SEM). Investigations into the depositional paleoenvironment, paleoproductivity, organic matter enrichment, and microscopic difference mechanisms of nanoscale reservoirs reveal that the Longmaxi Formation shale represents a passive continental margin shelf facies. It is characterized by strong terrigenous input, a predominance of quartz and clay minerals, and consists mainly of siliceous and argillaceous shale facies with high organic matter abundance. In contrast, the Dalong Formation shale was deposited in an intra-platform basin under the influence of intra-platform rifting. It features weak terrigenous input, highly reducing conditions, and strong paleoproductivity. Dominated by quartz and carbonate minerals, its lithofacies are primarily siliceous and calcareous shales. Within the Dalong Formation, the diagenetic dissolution of carbonate minerals promotes the development of micrometer-scale pores larger than 100 μm, while the extensive thermal evolution of organic matter fosters the formation of honeycomb- and embayment-like nanoscale micropores and mesopores, rendering it a relatively superior shale reservoir. Ultimately, the high-TOC shales in the lower part of the Longmaxi Formation and the upper part of the Dalong Formation are identified as the primary sweet spot intervals for future shale gas development. Full article

Deepfakes and adjacent synthetic-media capabilities have become a systemic challenge for information integrity, security, and digital trust. Countermeasures now span passive detection methods that infer manipulation from content traces, active provenance systems that cryptographically bind metadata to media, and watermarking approaches that embed detectable signals into content or generative processes. This review presents a rigorous synthesis of tools and technologies to combat deepfakes across modalities (image, video, audio, and selected multimodal settings), drawing primarily from the peer-reviewed literature, standardized benchmarks, and official technical specifications and reports. The review analyzes detection methods, provenance and authentication technologies, with emphasis on cryptographic manifests and threat models, watermarking and content provenance, including diffusion-era watermarking and industrial deployments, adversarial robustness and attacker adaptation, datasets and benchmarks, evaluation metrics across tasks, and deployment and scalability constraints. A dedicated section addresses legal, ethical, and policy issues, focusing on emerging transparency obligations and platform governance. The review finds that no single countermeasure is sufficient in realistic adversarial settings. The strongest practical approach is a layered defense that combines provenance, watermarking, content-based detection, and human oversight. The study concludes with limitations of the current evidence base and prioritized research directions to improve generalization, interoperability, and trustworthy user experiences. Full article

The urgent need to decarbonize the global cement industry is compounded by the declining availability of conventional supplementary cementitious materials (SCMs). Limestone-calcined clay cement (LC3) emerges as a highly sustainable alternative, enabling up to 50 percent clinker replacement and an approximate 40 percent reduction in carbon dioxide emissions. Unlike existing reviews that focus on basic material properties, this paper critically bridges the gap between fundamental hydration thermodynamics and next-generation sustainable engineering applications. Through a structured bibliographic analysis of 135 contemporary sources published between 2000 and 2026, it traces the evolution of LC3 from a laboratory innovation to a highly promising solution for large-scale industrial implementation and circular economy integration. The discussion highlights the synergistic alumina carbonate reaction. This reaction forms carboaluminate phases. These phases significantly densify the microstructure and enhance long term durability. Key engineering properties are examined, contrasting rheological challenges from high water demand and carbonation susceptibility against its exceptional chloride resistance in aggressive environments. The transition to field application is thoroughly assessed, emphasizing technological advances in flash calcination, environmental footprint reduction through life cycle assessment (LCA), and production scalability. Finally, rather than restating known challenges, this review exposes the limitations of current empirical mitigation strategies. It proposes a targeted research agenda focused on molecular-level green admixture design and field calibrated durability models to support the integration of LC3 into emerging sustainable technologies such as 3D concrete printing. Full article

Current 360-degree video streaming systems consider viewport prediction, adaptive bitrate allocation, tile selection, and quality-of-experience (QoE) estimation as independent activities, yielding fragmented pipelines that do not scale well across content type and network conditions and do not scale well to individual users. We propose ImmerseFM-3D, a foundation model that jointly solves all four sub-tasks through a single shared representation. Seven input modalities, namely video frames, network traces, head-motion trajectories, ambisonics audio, depth maps, eye-tracking signals, and CLIP scene semantics, are fused by four-layer cross-modal attention and compressed into a 256-dimensional bottleneck latent via a variational information bottleneck. Four task-specific decoders operate on this shared latent simultaneously. A model-agnostic meta-learning adapter augmented with episodic memory and a hypernetwork personalizes the model from as little as 1 s of user interaction data. An extended branch supports six-degrees-of-freedom volumetric content through spherical harmonic viewport decoding and depth-aware tile importance weighting. Trained and evaluated on the IMMERSE-1M combined dataset (1000 h of 360° and volumetric video, 524 users, and over 50,000 mean opinion scores), ImmerseFM-3D reduces the mean angular viewport error by 34%, lowers the bandwidth violation rate from 8.3% to 3.1%, and achieves a QoE Pearson correlation of 0.891. The personalization adapter reaches 90% of peak performance in 22 s, while zero-shot cross-format transfer attains 72% of full in-domain accuracy. Full article

Background: Persistent Postural-Perceptual Dizziness (PPPD) is a chronic vestibular disorder that has been receiving more research attention lately. Nonetheless, there is a lack of systematic bibliometric overviews tracing the conceptual evolution, knowledge structure, and emerging research frontiers within this field. The utilization of bibliometric and visualization analyses can enhance the understanding of trends and central themes in PPPD research, offering valuable insights for future studies. Methods: Data were retrieved from the Web of Science Core Collection, yielding a final dataset of 370 bibliographic records (“DATA”). We employed CiteSpace, HistCite, the Alluvial Generator, and R software to conduct multi-dimensional statistical and visualization analyses on publication trends, collaborative networks (countries/institutions/authors), disciplinary distribution, citation bursts, and the evolution of keyword clusters. Results: Starting from 2005, there has been a notable increase in publication volume, reaching its peak in 2024. The United States and Germany are at the forefront of national collaboration, with the University of Munich and the Mayo Clinic being key research institutions. The research focus has transitioned from a primary emphasis on Psychiatry to a broader scope encompassing Neurosciences, Otorhinolaryngology, and General Medicine. Keyword analysis reveals a shift towards standardized terminology, transitioning from “phobic postural vertigo” to “diagnostic criteria” and “consensus documents”. Current research trends are centered around comorbidity mechanisms like “vestibular migraine”, therapeutic approaches such as “vestibular rehabilitation”, and quality of life assessments using the “dizziness handicap inventory”. The 2017 consensus document by the Bárány Society is highlighted as a pivotal publication with significant citation impact. Conclusions: The intellectual structure of the field, as revealed by this bibliometric analysis, has transitioned from a phenomenological description to a conceptual unification. The bibliometric analysis indicates that the field is currently in a conceptually stabilized stage characterized by a research focus on refining diagnostic precision and comorbidity exploration, while scholarly attention remains biologically exploratory regarding objective biomarkers and pathophysiological mechanisms. Full article

Corporate sustainability programs in agri-food systems have expanded dramatically, yet emissions, deforestation, hunger, and land concentration intensify. Why does corporate sustainability systematically fail to deliver transformation? This paper applies Commonist Value Theory (CVT) to show that this failure is structural, not contingent. CVT distinguishes between True Value, the life-supporting qualities that sustain human and more-than-human flourishing, and Fetish Value, abstracted forms oriented toward capital accumulation. CVT traces how corporate sustainability programs convert the former into the latter through ‘decommonization’: the perversion and enclosure of shared life-supporting relations. Drawing on investor analyses, carbon market assessments, and critical scholarship, this paper demonstrates that corporate sustainability programs function as civilizing meta-mechanisms. Rather than transforming food systems, they stabilize existing arrangements by absorbing critique and redirecting transformative energies into regime-compatible forms. Farmers’ knowledge is captured as proprietary data, living ecosystems are reduced to tradeable metrics, collaborative relationships are fragmented by corporate platforms, and movements for genuine alternatives are channeled into supply chain optimization. The analysis concludes that corporate sustainability cannot deliver genuine transformation because its structural function is to stabilize rather than supersede the current value regime. Genuine transformation requires commons-based alternatives from below and political–legislative shifts from above that structurally constrain decommonization. Full article

Virtual plant models combined with ray-tracing simulations are an established tool for evaluating plant–light interactions. Current approaches often simplify leaf surface properties by assuming diffuse reflectance behavior, despite experimental evidence that leaf reflectance is direction-dependent across much of the visible spectrum. This study investigates whether incorporating measured, spectrally resolved and direction-dependent (BRDF) reflectance properties into these models affects simulation outcomes. Using virtual 3D cucumber (Cucumis sativus) plant models with PhongShader-based optical leaf characteristics for BRDF consideration, light absorption and local photon flux densities were simulated under a wide range of lighting conditions, including diffuse and directed sunlight scenarios. While total light absorption at the leaf level is only marginally affected (mean absolute percentage error, MAPE < 2%), spectral distortions in leaf surroundings, especially under direct light, exceeded 8% in the blue wavelength range. Beyond their relevance for estimating photosynthetic rates, such distortions directly affect the spectral composition within the canopy, which is particularly critical in greenhouse applications where optical sensors are used to monitor spectral ratios and, therefore, require the accurate prior simulation of canopy light conditions. This is particularly relevant for setups with directional artificial lighting. The findings suggest that BRDF modeling is not critical for calculating photosynthetic rates under most conditions, but is required in spectral analyses or for optimizing artificial lighting designs. Full article

Islands often suffer from relatively limited freshwater resources, and the effective utilization and distribution of water resources are a key issues for the sustainable development of island-based economies and societies. While island water security has been widely discussed, few studies trace the socio-technical construction of island water-supply systems across the stages of planning, construction, and operation. Integrating Actor-Network Theory with political ecology, this study investigates the water-supply infrastructure of Kinmen. Drawing on official archives, participant observation, and in-depth interviews, this research analyzes the collective actions mobilized to address Kinmen’s water scarcity following the lifting of martial law in 1992. These efforts jointly reshaped both water-supply practices and the infrastructural network. Over the past three decades, Kinmen’s water-supply system has transformed into a sophisticated technological network, integrating reservoirs, desalination plants, and advanced sewage infrastructure. The introduction of these technologies, which function as critical non-human actors within the system, marks a clear shift in how water is managed and distributed. However, the rapid expansion of water-intensive industries, especially tourism, liquor distilling, and cattle farming, has outpaced local ecological limits, precipitating the current water crisis. The study concludes that this shortage has been mitigated through the strategic integration of water sources, most notably the cross-strait pipeline from mainland China, which now provides more than 80 percent of the island’s water. This transition marks a profound shift in the island’s socio-technical and geopolitical network. Full article

As part of an ongoing investigation into the genus Polycarpon, the name P. prostratum var. littorale, described from Senegal in 1967 by J. Raynal and A. Raynal, was studied. It does not appear in World Flora Online (WFO), is unplaced in Plant Of the World Online (POWO) and in the International Plant Names Index (IPNI). Furthermore, no study appears to be published after that by J. Raynal and A. Raynal. With the aim to clarify the identity and taxonomic status of Raynal & Raynal’s variety, a detailed study of the type and other specimens is here presented. The name is lectotypified on a specimen preserved at P (barcode P00388964) and further two isolectotypes were traced (P00388965 and P00388966). Based on the morphology of Raynal & Raynal’s taxon and the current circumscription of the genus Polycarpon as monophyletic (with P. tetraphyullum) a nomenclatural change (P. tetraphyllum subps. littorale comb. et stat. nov.) is proposed. The subspecies is assessed as Endangered based on the IUCN criterion B2. Furthermore, a diagnostic key to the Polycarpon taxa occurring in Africa is presented. Full article

Document authentication remains a pressing challenge in various domains, including financial services, academic credentialing, healthcare, and supply chain management. Existing centralized verification systems are vulnerable to manipulation, inefficiency, and limited transparency. Blockchain technology, with its immutability and tamper-resistant capabilities, offers a strong decentralized alternative; however, many current implementations lack structured, issuer-bound relationships for documents. This paper proposes a blockchain-based model that leverages a hierarchical token structure to authenticate and trace the provenance of high-value digital documents, with a focus on financial records. The model introduces the concept of an issuer-bound parent token and document-linked child tokens, enforcing a structured trust relationship between a legitimate institution and the documents it issues. By combining on-chain cryptographic hashing with off-chain file references, the approach is designed to balance verifiability with scalability. We implement a proof-of-concept using Ethereum-compatible smart contracts on a permissioned blockchain and evaluate it in a consortium-style financial setting. Our functional analyses demonstrate the model’s ability to ensure document integrity, provenance, and resistance to document fraud. This work offers a practical and extensible foundation for secure digital document authentication and verification in financial and other trust-sensitive settings. Full article

As modern power markets integrate more renewable generation, day-ahead energy clearing remains the central procurement step, while flexibility products are procured to ensure that the cleared energy schedule can be operated securely. This paper proposes a closed-loop framework linking the Power Exchange (PX) and the Independent System Operator (ISO) to bridge energy-market settlement and network-feasible operation. The PX performs staged day-ahead clearing with energy settled first, followed by aAutomatic generation control (AGC) and spinning reserve (SR) procured from the residual headroom of committed (energy-awarded) units. The ISO then validates the cleared schedule using an equivalent current injection (ECI)-based screening. This paper uses a single-period (single-hour) IEEE 30-bus case setting; multi-period scheduling and intertemporal constraints are not modeled. When congestion is detected, power-flow tracing identifies the main contributors and guides a minimal-change redispatch. The ISO-feasible dispatch is then sent back to the PX for re-clearing, aligning prices and welfare with an executable operating point. The resulting nonconvex clearing problems with valve-point effects and prohibited operating zones are solved by Artificial Protozoa Optimizer with Social Learning (APO–SL) and evaluated against representative metaheuristic baselines. IEEE 30-bus studies show that off-peak and average-load cases pass ISO screening directly, whereas the peak case tightens reserve headroom (SR capped at 39.08 MW) and triggers congestion. After ISO feedback and energy re-clearing, line loadings return within limits. The ISO-feasible dispatch changes the marginal accepted offer and lifts the MCP (3.73 → 4.38 $/MWh). The welfare value reported here follows the paper’s settlement-based definition (purchase total minus accepted offer cost), and it increases accordingly (113.77 → 190.17 $/h). Full article