Search Results (328)

This article illuminates the cosmology of Raa Haqi (often called Dersim Alevism or Kurdish Alevism), a rarely examined strand within Alevi Studies. Existing scholarship’s emphasis on identity politics and sparse ethnography has left Raa Haqi’s mythological and cosmological dimensions underexplored. This paper approaches Raa Haqi through a dual authority framework: (1) Ocak lineages and Ocak–talip relations—sustained by kinship institutions like kirvelik, musahiplik, and communal rites such as the cem—and (2) jiares, non-human agents from the Batın realm that manifest in Zahir as sacred places, objects, and animals. Methodologically, I conduct a close, motif-based reading of folktales compiled by Caner Canerik (2019, Dersim Masalları I), treating them as ethnographic windows into living theology. The analysis shows that tales encode core principles—rızalık (mutual consent), ikrar (vow), sır (the secret knowledge), fasting and calendrical rites, ritual kinship, and moral economies involving humans, animals, and Batın beings. Dreams, metamorphosis, and jiare-centered orientations structure time–space, ethics, and authority beyond the Ocak, including in individual re-sacralizations of objects and sites. I conclude that these narratives do not merely reflect belief; they actively transmit, test, and renew Raa Haqi’s cosmological order, offering Alevi Studies a theory-grounded, source-proximate account of Kurdish Alevi mythic thought. Full article

A reluctance actuator integrated into the double-sided dog clutch of a gearbox can significantly simplify the gear shifting system. However, its disadvantage is that an axial position sensor is required to shift the neutral gear. The sensor is placed in the aggressive environment of a gearbox and reduces the reliability of the entire system. Sensorless methods proposed in the literature deal with electrical machines or actuators with one degree of freedom (linear motion or rotation). In the dog clutch, the shift sleeve rotates and moves along its rotation axis simultaneously, moreover, the coil inductances are highly dependent not only on the axial position but also on the relative angular position between the shift sleeve teeth and the slots of its counterpart. This work proposes an original algorithm of sensorless control, which main novelty is the applicability for systems with two degrees of freedom, such as the considered actuator. The voltage induced in one of the coils and the prediction of the shift sleeve motion, which is based on the electromechanical model of the clutch, are used to control the currents. Not only an axial position sensor but also angular encoders are not required to apply the proposed method. The algorithm was tested both in simulations and experiments under different conditions. The results show that the proposed method allows to shift the neutral gear sensorless at different rotation speeds and different loads on the sleeve, regardless of what gearwheel is initially engaged. Full article

As urbanization intensifies, the challenge of preserving industrial heritage while fostering authentic intergenerational connections has become increasingly salient. This study investigates how artificial intelligence (AI) and augmented reality (AR) technologies can be applied to enhance authenticity and promote both hedonic and eudaimonic well-being within the context of heritage tourism. Using a facility in Shanghai as a case study, we propose a cultural co-creation mechanism that transforms implicit intergenerational memories into shared cultural resources through digital interaction. The study first evaluates public awareness and participation needs in the context of industrial heritage revitalization. In response, we design an immersive platform that enables visitors of different generations to co-create meaning through historical scene reconstruction, multisensory engagement, and collaborative storytelling. A novel five-sense encoding strategy is introduced to reinterpret the enclosed spatial characteristics of industrial architecture as an experiential form of storytelling. This process fosters a deeper connection to place, contributing to authenticity and well-being. Prototype testing results suggest that this AI-AR-enabled co-creation system supports meaningful cultural attachment, improves authenticity, and facilitates the sustainable transmission of heritage. This research provides a replicable model for integrating digital technology, community participation, and authenticity in the well-being-oriented revitalization of industrial heritage sites. Full article

Taxonomic clarity within the genus Antithamnion is critical for understanding its molecular phylogeny and biodiversity. Here we report Antithamnion hubbsii for the first time from the Korean coast. This finding highlights the need to re-evaluate its relationship with the previously reported, morphologically very similar A. nipponicum in this region, raising the question of whether the newly identified A. hubbsii represents a local variant of A. nipponicum or a recently introduced invasive species via nearby ports. Specimens collected from Gangneung were analyzed using plastid-encoded rbcL and psaA genes, confirming their identity as A. hubbsii. Morphological features such as indeterminate lateral axes, oppositely arranged pinnae and pinnules, and distinctive adaxial gland cells supported this identification. Molecular analyses revealed minimal divergence between A. hubbsii and A. nipponicum (1–3 bp in rbcL, none in psbA), and contrasting results from different species delimitation methods. Phylogenetic analyses nevertheless placed the Korean specimens in a strongly supported A. hubbsii/A. nipponicum clade. Taken together, our results suggest that the North American invasive A. nipponicum and the Korean A. hubbsii may represent a single species with broad intraspecific variation. Definitive resolution will require molecular analyses of the type specimens of both taxa. Full article

This article offers a new perspective on Miriam’s red jewel in Nathaniel Hawthorne’s The Marble Faun (1860), interpreting it as a symbol of Jewish femininity, diasporic memory, and aesthetic resistance. Although the jewel has received little critical attention, this study suggests that it plays a central role in shaping Miriam’s identity and in articulating broader cultural anxieties around gender, ethnicity, and visibility. Through intertextual readings of Shakespeare’s Jessica and Walter Scott’s Rebecca and Rowena, the essay situates Miriam within a literary tradition of Jewish women whose identities are mediated through symbolic adornments. In addition to literary analysis, the article draws on visual art history—particularly Carol Ockman’s interpretation of Jean-Auguste-Dominique Ingres’s 1848 portrait of Baronne de Rothschild—to explore how 19th-century visual culture contributed to the eroticization and exoticization of Jewish women. By placing Hawthorne’s portrayal of Miriam in dialogue with such visual representations, the essay highlights how the red jewel functions as a site of encoded cultural meaning. The analysis is further informed by feminist art theory (Griselda Pollock) and postcolonial critique (Edward Said), offering an interdisciplinary approach to questions of identity, marginalization, and symbolic resistance. While not claiming to offer a definitive reading, this article aims to open new interpretive possibilities by foregrounding the jewel’s narrative and symbolic significance. In doing so, it contributes to ongoing conversations in Hawthorne studies, Jewish cultural history, and the intersections of literature and visual art. Full article

Coastal regions are among the areas most affected by climate change, facing rising sea levels, frequent flooding, and accelerated erosion that place renewable energy infrastructures under serious threat. Solar farms, which are often built along shorelines to maximize sunlight, are particularly vulnerable to salt-induced corrosion, storm surges, and wind damage. These challenges call for monitoring solutions that are not only accurate but also scalable and privacy-preserving. To address this need, Q-MobiGraphNet, a quantum-inspired multimodal classification framework, is proposed for federated coastal vulnerability analysis and solar infrastructure assessment. The framework integrates IoT sensor telemetry, UAV imagery, and geospatial metadata through a Multimodal Feature Harmonization Suite (MFHS), which reduces heterogeneity and ensures consistency across diverse data sources. A quantum sinusoidal encoding layer enriches feature representations, while lightweight MobileNet-based convolution and graph convolutional reasoning capture both local patterns and structural dependencies. For interpretability, the Q-SHAPE module extends Shapley value analysis with quantum-weighted sampling, and a Hybrid Jellyfish–Sailfish Optimization (HJFSO) strategy enables efficient hyperparameter tuning in federated environments. Extensive experiments on datasets from Norwegian coastal solar farms show that Q-MobiGraphNet achieves 98.6% accuracy, and 97.2% F1-score, and 90.8% Prediction Agreement Consistency (PAC), outperforming state-of-the-art multimodal fusion models. With only 16.2 M parameters and an inference time of 46 ms, the framework is lightweight enough for real-time deployment. By combining accuracy, interpretability, and fairness across distributed clients, Q-MobiGraphNet offers actionable insights to enhance the resilience of coastal renewable energy systems. Full article

Non-Intrusive Load Monitoring (NILM) aims to disaggregate a household’s total aggregated power consumption into appliance-level usage, enabling intelligent energy management without the need for intrusive metering. While deep learning has improved NILM significantly, existing NILM models struggle to capture load patterns across both longer time intervals and subtle timings for appliances involving brief or overlapping usage patterns. In this paper, we propose a novel GRU+BERT hybrid architecture, exploring both unidirectional (GRU+BERT) and bidirectional (Bi-GRU+BERT) variants. Our model combines Gated Recurrent Units (GRUs) to capture sequential temporal dependencies with Bidirectional Encoder Representations from Transformers (BERT), which is a transformer-based model that captures rich contextual information across the sequence. The bidirectional variant (Bi-GRU+BERT) processes input sequences in both forward (past to future) and backward (future to past) directions, enabling the model to learn relationships between power consumption values at different time steps more effectively. The unidirectional variant (GRU+BERT) provides an alternative suited for appliances with structured, sequential multi-phase usage patterns, such as dishwashers. By placing the Bi-GRU or GRU layer before BERT, our models first capture local time-based load patterns and then use BERT’s self-attention to understand the broader contextual relationships. This design addresses key limitations of both standalone recurrent and transformer-based models, offering improved performance on transient and irregular appliance loads. Evaluated on the UK-DALE and REDD datasets, the proposed Bi-GRU+BERT and GRU+BERT models show competitive performance compared to several state-of-the-art NILM models while maintaining a comparable model size and training time, demonstrating their practical applicability for real-time energy disaggregation, including potential edge and cloud deployment scenarios. Full article

Intelligent robotic systems frequently operate under stringent energy limitations, especially in complex and dynamic environments. To enhance both adaptability and reliability, this study introduces a semantic planning framework that integrates ontology-driven reasoning with energy awareness. The framework estimates energy consumption based on the platform-specific behavior of sensing, actuation, and computational modules while continuously updating place-level semantic representations using real-time execution data. These representations encode not only spatial and contextual semantics but also energy characteristics acquired from prior operational history. By embedding historical energy usage profiles into hierarchical semantic maps, this framework enables more efficient route planning and context-aware task assignment. A shared semantic layer facilitates coordinated planning for both single-robot and multi-robot systems, with the decisions informed by energy-centric knowledge. This approach remains hardware-independent and can be applied across diverse platforms, such as indoor service robots and ground-based autonomous vehicles. Experimental validation using a differential-drive mobile platform in a structured indoor setting demonstrates improvements in energy efficiency, the robustness of planning, and the quality of the task distribution. This framework effectively connects high-level symbolic reasoning with low-level energy behavior, providing a unified mechanism for energy-informed semantic decision-making. Full article

A novel Gram-negative bacterium, designated strain SN16^T, was isolated from a harmful algal bloom (HAB). Strain SN16^T exhibited potent, broad-spectrum algicidal activity against the colony-forming alga Phaeocystis globosa and eight other HAB-causing species, highlighting its potential as a promising candidate for the biological control of HABs. A phylogenetic analysis of 16S rRNA gene sequences placed strain SN16^T within the genus Flagellimonas. The average nucleotide identity (ANI) and digital DNA–DNA hybridization (dDDH) values between strain SN16^T and its relatives were 75.4–91.4% and 19.3–44.0%, respectively. These values fall below the established thresholds for species delineation, confirming that SN16^T represents a novel species. A chemotaxonomic analysis revealed its dominant cellular fatty acids to be iso-C_15:0 and iso-C_15:1 G. The major polar lipid was phosphatidylethanolamine, and the primary respiratory quinone was menaquinone-6. Genome mining identified 11 biosynthetic gene clusters (BGCs), including those encoding for terpenes, ribosomal peptide synthetases, and non-ribosomal peptide synthetases. By integrating BGC analysis with the observed algicidal activities, we predicted that pentalenolactone and xiamycin analogues are the likely causative compounds. Based on this polyphasic evidence, strain SN16^T is proposed as a novel species of the genus Flagellimonas, named Flagellimonas algicida sp. nov. This is the first report of Flagellimonas species exhibiting broad-spectrum algicidal activity, including activity against the colonial form of P. globosa—a key ecological challenge in HAB mitigation. Full article

The Collatz conjecture is a famous unsolved problem in mathematics, known for its deceptively simple rules that generate complex, unpredictable behaviour. It can be efficiently modelled using a Petri net that represents its inverse graph, where each place corresponds to an integer and each transition encodes an inverse rule. The net, constructed up to a bound n, reveals the tree-like structure of predecessors and highlights properties such as recurrence, reachability, and liveness. Token flows simulate possible trajectories towards 1. This formal approach enables the investigation of the problem through discrete event systems theory and opens perspectives for parametric or inductive extensions beyond the bounded domain. The model proposed provides a structured framework for visualising and analysing the inverse dynamics of the conjecture. Some key numerical results highlight the challenges of working within a finite domain: for $n_{max}=1000$, the constructed Petri net comprises 1000 places and 667 transitions, including 417 source nodes (no predecessors), 333 sink nodes (no successors), and 218 isolated orphans, i.e., nodes only reachable via $\mathrm{Div}2$ transitions with no incoming $3n+1$ edge. Full article

A new negative-strand RNA virus was identified in grapevines from a 38-year-old ‘Chardonnay’ block in Idaho through high-throughput sequencing (HTS) of total RNA. This virus was tentatively named grapevine-associated cogu-like Idaho virus (GaCLIdV). GaCLIdV has three negative-sense, single-stranded RNA genome segments of ca. 7 kb, 1.9 kb, and 1.3 kb, encoding L protein (RNA-dependent RNA polymerase, RdRP), a movement protein (MP), and a nucleocapsid protein (NC), respectively, identified based on pair-wise comparisons with other cogu- and cogu-like viruses. In phylogenetic analysis based on the RdRP, GaCLIdV grouped within the family Phenuiviridae and was placed in a lineage of plant-infecting phenuiviruses as a sister clade of the genus Laulavirus, clustering most closely with switchgrass phenui-like virus 1 (SgPLV-1) and more distantly related to grapevine-associated cogu-like viruses from the Laulavirus and Coguvirus clades. Both GaCLIdV and SgPhLV-1 are proposed to form a new genus, Switvirus, within the family Phenuiviridae. The presence of GaCLIdV in the original ‘Chardonnay’ samples was confirmed by RT-PCR amplification and Sanger sequencing. This new virus was found in five wine grape cultivars and in six vineyards sampled in Idaho and in Oregon during the 2020–2024 seasons. GaCLIdV may have contributed to the decline observed in the old ‘Chardonnay’ block, although the role of the virus in symptom development awaits further investigation. Full article

Floccularia luteovirens is a valuable medicinal and edible ectomycorrhizal fungus that is endemic to alpine meadows on the Qinghai–Tibet Plateau. It is of significant ecological and pharmacological importance. To overcome the genomic limitations of previous fragmented assemblies, we present the first haplotype-phased, chromosome-scale genome of the Qinghai-derived QHU-1 strain using an integrated approach of PacBio HiFi, Hi-C, and Illumina sequencing. The high-contiguity assembly spans 13 chromosomes with 97.6% BUSCO completeness. Phylogenomic analysis of 31 basidiomycetes clarified a historical misclassification by placing F. luteovirens closest to Mycocalia denudata/Crucibulum laeve, thus confirming its distinct lineage from Armillaria spp. through low synteny and divergent gene family dynamics. Analyses of adaptive evolution revealed strong purifying selection and stable transposable elements, suggesting genomic adaptations to extreme UV/cold stress. AntiSMASH identified 15 biosynthetic gene clusters (BGCs), which encode diverse terpenoids (7), NRPS-like enzymes (4), PKSs (2), and a hybrid synthase with unique KS-AT-PT-A domains, which have the potential to generate novel metabolites. This chromosome-level resource sheds light on the genetic basis of F. luteovirens’ taxonomy, alpine survival, and symbiotic functions while also unlocking its potential for bioprospecting bioactive compounds. Full article

N, as plants’ most essential nutrient, profoundly shapes root system architecture (RSA), with LRs being preferentially regulated. This review synthesizes the intricate molecular mechanisms underpinning N sensing, signaling, and its integration into developmental pathways governing LR initiation, primordium formation, emergence, and elongation. We delve deeply into the roles of specific transporters (NRT1.1, nitrate transporter 2.1 (NRT2.1)), transcription factors (Arabidopsis nitrate regulated 1 (ANR1), NLP7, TGACG motif-binding factor (TGA), squamosa promoter-binding protein-like 9 (SPL9)) and intricate hormone signaling networks (auxin, abscisic acid, cytokinins, ethylene) modulated by varying N availability (deficiency, sufficiency, excess) and chemical forms (NO₃⁻, NH₄⁺, organic N). Emphasis is placed on the systemic signaling pathways, including peptide-mediated long-distance communication (CEP—C-terminally encoded peptide receptor 1 (CEPR1)) and the critical role of the shoot in modulating root responses. Furthermore, we explore the emerging significance of carbon–nitrogen (C/N) balance, post-translational modifications (ubiquitination, phosphorylation), epigenetic regulation, and the complex interplay with other nutrients (phosphorus (P), sulfur (S)) and environmental factors in shaping N-dependent LR plasticity. Recent advances utilizing single-cell transcriptomics and advanced imaging reveal unprecedented cellular heterogeneity in LR responses to N. Understanding this sophisticated regulatory network is paramount for developing strategies to enhance nitrogen use efficiency (NUE) in crops. This synthesis underscores how N acts as a master regulator, dynamically rewiring developmental programs through molecular hubs that synchronize nutrient sensing with root morphogenesis—a key adaptive strategy for resource acquisition in heterogeneous soils. Full article

This study introduces a novel deep learning architecture for vessel trajectory prediction based on Automatic Identification System (AIS) data. The motivation stems from the increasing importance of maritime transport and the need for intelligent solutions to enhance safety and efficiency in congested waterways—particularly with respect to collision avoidance and real-time traffic management. Special emphasis is placed on river navigation scenarios that limit maneuverability with the demand of higher forecasting precision than open-sea navigation. To address these challenges, we propose a Principal Component Analysis (PCA)-driven layered attention mechanism integrated within an encoder–decoder model to reduce redundancy and enhance the representation of spatiotemporal features, allowing the layered attention modules to focus more effectively on salient positional and movement patterns across multiple time steps. This dual-level integration offers a deeper contextual understanding of vessel dynamics. A carefully designed evaluation framework with statistical hypothesis testing demonstrates the superiority of the proposed approach. The model achieved a mean positional error of 0.0171 nautical miles (SD: 0.0035), with a minimum error of 0.0006 nautical miles, outperforming existing benchmarks. These results confirm that our PCA-enhanced attention mechanism significantly reduces prediction errors, offering a promising pathway toward safer and smarter maritime navigation, particularly in traffic-critical riverine systems. While the current evaluation focuses on short-term horizons in a single river section, the methodology can be extended to complex environments such as congested ports or multi-ship interactions and to medium-term or long-term forecasting to further enhance operational applicability and generalizability. Full article

Novel waterfowl reoviruses (nWRVs) have been reported in several countries, but their circulation and genetic characteristics in Vietnam remain poorly understood. In this study, we investigated nWRVs in northern Vietnam through molecular detection, virus isolation, experimental infection in ducklings, and molecular analysis of the sigma C-encoding (sC) gene. We also applied immunoinformatic tools to explore the antigenic and structural features of the sC protein. nWRVs were detected in 15.6% of tested samples across ten provinces. Three isolates were successfully recovered, all showing a characteristic cytopathic effect—syncytium formation—in Vero cells. When tested in ducklings (n = 72), the isolates caused disease of varying severity, but all induced characteristic gross and microscopic lesions, particularly ecchymotic hemorrhages and large necrotic foci in the liver and spleen. Phylogenetic analysis based on sC sequences placed the Vietnamese isolates (n = 14) within the nWRV clade, with evidence of two genetically distinct groups. Our immunoinformatic analysis identified four predicted B-cell epitopes located in the head and body domains of the sC protein, with little variation. Full article