Search Results (1,282)

The study evaluated the effect of intercropping Paulownia (Paulownia spp.) with spring barley (Hordeum vulgare L., cv. KWS Thalis) on selected components of agroecosystem biodiversity under Polish conditions. A field experiment established in 2019 compared an alley cropping system with barley monoculture during the 2025 growing season. Weed infestation, soil microbial communities, mesofauna abundance, and crop yield were assessed. Weed abundance was lower in the intercropping system than in monoculture, reaching 5.6 vs. 15.6 plants m⁻² at BBCH 21 and 21 and 22.8 vs. 35.6 plants m⁻² at BBCH 75. Bacterial alpha diversity was significantly higher under intercropping conditions, with Shannon index values ranging from 5.12 to 5.25, compared with 4.98–5.09 in monoculture. Fungal diversity showed moderate differences between systems, whereas the abundance of Collembola and Acari was influenced mainly by seasonal variation rather than by cultivation system. No significant reduction in barley yield was observed under intercropping conditions. The results suggest that Paulownia-based alley cropping may reduce weed pressure and support selected soil biological properties without negatively affecting crop productivity. However, the observed responses varied depending on the analyzed parameter and sampling period, indicating the preliminary and context-dependent character of the results. Further long-term studies are required to better understand the ecological mechanisms operating in such agroforestry systems. Full article

Tea pest and disease named entity recognition (NER) faces challenges resulting from dense domain terminology, multi-granularity entity structures, and long-distance semantic dependencies. This paper proposes E-BERT-wwm-BiGRU-RAT-CRF, integrating whole-word masking E-BERT with three innovations—a trainable relative position bias matrix, a cross-layer hierarchical mask matrix, and a heterogeneous multi-head attention mechanism—followed by bidirectional gated recurrent units (BiGRU), residual attention (RAT), and conditional random fields (CRF). On a self-constructed tea pest and disease corpus of over 300,000 characters across seven entity categories, the model achieves 93.67% precision, 93.07% recall, and 93.37% F1-score, outperforming the baseline by 2.73 percentage points in F1-score. Ablation experiments confirm the contribution of each module. Full article

Humus substances are an important part of stable soil organic matter, which is also influenced by the soil tillage system, particularly indirectly through the mechanisms of stabilisation. This study evaluated relationships within the humus substances–cations–soil texture system and differences between invasive and non-invasive tillage systems in four soils. The influence of exchangeable cations (K⁺, Na⁺, Ca²⁺, Mg²⁺, Fe³⁺, Al³⁺) and particle size distribution (sand, silt, clay) on quantity (humic and fulvic acids) and quality (ratio of HA/FA, degree of humification, colour coefficients) of humus substances was studied. In reduced tillage, the humus substances interacted mainly with iron and aluminium. Higher humus substance contents were associated with higher K⁺; the influence of Ca²⁺ was greater in coarse-grain soils (Haplic Chernozem, Eutric Regosol); and Al³⁺ was positively correlated with humic acids and negatively with fulvic acids. The statistical associations indicate that in conventional tillage, humus substances interacted mainly with Ca²⁺. Higher humic acid contents indicate an association pattern with higher Na⁺ contents; the relationship of Ca²⁺ appears more pronounced in fine-grained soils (Mollic Fluvisol, Haplic Luvisol); and Al³⁺ was positively correlated with fulvic acids and negatively with humic acids. The soil tillage system influenced the humus substances indirectly by a combination of factors—cation composition and soil texture in different ways. In reduced tillage, clay and silt were statistically associated with iron and aluminium; in conventional tillage, there were two branches: clay with divalent cations and silt with trivalent cations. The soil tillage system can modify the impact of carbonates on humus substances and thus indirectly change the character of transformation processes in the soil. Depth is very important in evaluating the influence of the soil tillage system. Full article

Despite overwhelming scientific consensus that human activity drives climate change, public opinion in the United States remains sharply polarized along political lines. This project tests whether a theory-driven narrative intervention can reduce divergence between individuals skeptical of climate change and those who accept the scientific consensus. Guided by narrative transportation theory, we hypothesize that an inclusive, character-driven video grounded in the authentic language of skeptical audiences will reduce polarization and increase civic engagement. The study proceeds in three phases. Phase 1 uses focus group discussions to identify words, phrases, and perspectives used by skeptical and accepting participants. Phase 2 integrates these findings into the production of a 2–3 min narrative short film, refined through iterative audience testing. Phase 3 employs a stratified online experiment assessing climate attitudes, policy support, and activism behaviors before exposure, immediately after, and one week later. Mediators include narrative transportation, perceived similarity, and character identification. We test whether pre-exposure divergence narrows over time and whether engagement mechanisms explain observed changes. Findings will inform climate communication policy, intervention design, and broader research on depolarization in polarized public issues. Full article

This study examines the theological structure of Tengrism, understood here as a heuristic term for the broader Tengri-centered early Turkic belief system, its historical transformation, and its continuity in post-Islamic Turkic culture and folklore from an interdisciplinary perspective. Although the continuity of pre-Islamic Turkic beliefs in later Turkish folk culture has been noted in previous scholarship, the specific mechanisms through which Tengri-centered concepts survived as implicit theological structures within lived religion, folk belief, and Alevi-Bektashi ritual–poetic traditions have not been sufficiently systematized. The research argues that Tengrism should not be understood merely as an archaic remnant of belief but as a comprehensive theological paradigm shaping cosmology, political legitimacy, ethical order, and the perception of sacredness in early Turkic societies. In this context, epic and mythological texts such as the Orkhon Inscriptions, the Epic of Oghuz Khan, the Book of Dede Korkut, and the Epic of Manas constitute the primary textual sources of the study. The research is based on a qualitative design and employs phenomenological and hermeneutic approaches. The phenomenological perspective seeks to understand the theological principles of Tengrism and the perception of sacredness within their own cultural and symbolic universe, while hermeneutic analysis interprets the continuity of symbolic and mythological elements preserved in folkloric narratives. The findings indicate that the Tengri-centered and cosmologically structured character of early Turkic religiosity did not disappear after the adoption of Islam; rather, it persisted through folkloric narratives, popular beliefs, ritual practices, and the Alevi-Bektashi tradition. These findings demonstrate that Tengrism continues to function as a dynamic theological paradigm within Turkish cultural memory and popular religiosity. Full article

To mitigate the drawbacks of joint crossover (IoU) in complex detection scenarios, this paper proposes a normalized IoU strategy. This strategy enhances the matching robustness in multi-scale object detection by introducing target scale parameters. The proposed method shows comparable or superior average precision (mAP) performance to traditional methods on public datasets. In addition, we have designed a dual-center distance penalty mechanism that implicitly enforces symmetric constraints between bounding boxes, increasing the number of positive samples detected. Our method has been evaluated on mainstream public datasets and unmanned aerial vehicle (UAV) water level gauge datasets, as well as evaluated using the You Only Look Once (YOLO) framework. Our method increased the average number of positive samples by 2.28% compared to CIoU. It also surpasses the most advanced technology. The dual-center constraint enhances the spatial alignment between bounding boxes. This results in notable performance gains in challenging scenarios. These scenarios involve blurred and heavily occluded objects. After parameter optimization, the proposed method achieves significant accuracy improvements. These improvements are seen in detecting small-scale and occluded characters. Full article

To address prevalent challenges in stone inscription character detection—including glyph blurring, incompleteness, densely arranged characters, and substantial inter-object scale variation—this paper proposes PMN-YOLO, a lightweight, enhanced detection model built upon YOLOv11n. To enhance the detection performance of stele characters in complex scenarios, PP-LCNet is introduced to replace the original feature extraction structure. This not only reduces the model complexity but also enhances the feature expression ability for complex textures and blurred characters, providing effective support for subsequent recognition tasks. Consequently, the proposed model achieves a better balance between detection precision and computational efficiency. Second, we designed the MSAM-smallTarget module specifically for detecting small targets. By integrating multi-scale convolutional operations with spatial attention mechanisms, this module significantly enhances the model’s ability to perceive fine-grained features as well as blurred or fragmented characters commonly found in inscriptions. Furthermore, leveraging small convolutional kernels, dilated convolutions, and lightweight convolutional designs enables adaptive expansion of the receptive field while effectively constraining parameter count. Third, the NWD loss function based on the Wasserstein distance is introduced to replace the traditional IoU metric with a distribution-based similarity measure, thereby significantly improving the model’s localization robustness in scenarios involving densely distributed targets and ambiguous boundaries. The experimental results show that on the self-built stone inscription dataset, the precision of PMN-YOLO reaches 98.3%, the recall rate is 75.5%, and the mAP@50 and mAP@50-95 are 82.7% and 65.0% respectively. The model has 8.7% fewer parameters than the baseline. This method achieves lightweight performance and high detection accuracy, delivering a practical approach to automatically detect and digitally safeguard stone inscriptions. Full article

Hypophosphites (also known as phosphinates) are the salts of hypophosphorous acid (also known as phosphinic acid), H₃PO₂. Various hypophosphite salts are known such as calcium hypophosphite (Ca(H₂PO₂)₂) and sodium hypophosphite (Na(H₂PO₂)). Hypophosphites were proposed as a potential treatment for tuberculosis as early as the 1850s; however, they were found to be ineffective against this disease. Following this, there was a period of around 100 years during which no new studies on hypophosphites were published. Subsequent in vitro studies have shown that hypophosphites can be used as potential antibacterial food preservatives. Currently, calcium hypophosphite is used in commercial food supplements for children, as this compound is a suitable source of calcium ions. It also has other advantageous properties, including exceptionally high water solubility (154 g/L at 25 °C), a neutral taste, a high mass fraction of calcium per molecule (23.6%), and an excellent safety profile. Recent studies have shown its potential as an active ingredient in the field of oral care. Since biological mechanisms such as tooth and bone formation and natural remineralization due to saliva rely on calcium ions, calcium hypophosphite can be regarded as a biomimetic agent. Upon contact with phosphate from saliva, calcium hypophosphite forms hydroxyapatite; this imitation of physiological mineralization and crystallization processes in the human body further underlines its biomimetic character. This review summarizes and discusses the available literature on hypophosphites in human health and related fields. Full article

Magnesium hydroxide is attracting growing interest as a versatile, halogen-free flame retardant, and this review surveys its production routes, structure–property relationships and use in polymer systems from commodity polyolefins to advanced bio-based materials. Industrial Mg(OH)₂ is still predominantly obtained from mining or hydration of MgO, but increasing attention is being devoted to recovery from seawater and saltwork brines, where precipitation from Mg²⁺-rich streams followed by controlled rehydration or direct precipitation yields fine, high-purity powders suitable for flame retardant use and simultaneously valorizes saline wastes. In parallel, hydrothermal synthesis has been extensively explored to tailor particle size and morphology by adjusting the precursor, solvent, temperature and time, enabling high-surface-area Mg(OH)₂ or MgO with narrow size distributions that are attractive for high-performance composites also evaluated via ball milling, crushing and refining. More recently, process intensification strategies such as microwaves and ultrasounds have been proposed to shorten reaction times, lower temperatures and better control nucleation and growth, opening paths toward energy efficient production of structured Mg(OH)₂ from both conventional and brine-derived precursors. The second part of the review analyzes how the intrinsic endothermic decomposition and basic character of Mg(OH)₂ can be utilized across a broad range of polymer matrices and how surface functionalization strategies extend its applicability. In addition to “as received” powders, stearic acid and other fatty acids, metal soaps and various organic coupling agents are widely used to render the surface more hydrophobic, enhance dispersion and interfacial adhesion, and in some cases introduce additional char-forming or barrier functionality. In terms of the application, the review methodically synthesizes and contrasts fire and mechanical data for Mg(OH)₂-containing polyolefins (HDPE, LLDPE, PP and EVA) utilized in cables and building products, expandable polymers and foams, biopolymers (PLA and PBS), and elastomers. The review places particular emphasis on the balance between loading level, processability, flame performance and mechanical integrity. This review aims to provide a comprehensive framework for designing next-generation Mg(OH)₂-based flame-retardant systems for both conventional and emerging polymer technologies. To this end, it integrates advances in sustainable feedstocks, controlled synthesis and surface engineering with the rapidly expanding application space. Full article

Agricultural waste materials can serve as functional constituents in cement-based composites through three pathways: (i) organic bio-aggregates that lower density and alter thermal behavior, (ii) lignocellulosic fibers that control cracking and improve post-cracking resistance, and (iii) agro-ash supplementary cementitious materials (SCMs) that densify pore structure and reduce permeability when ash quality and curing are controlled. This review draws on 98 papers, with coconut shell aggregate and coir/coconut fibers as the core focus; agro-ash SCMs (notably palm oil fuel ash, POFA, and rice husk ash, RHA) enter where they clarify mechanisms or inform hybrid design. Rather than cataloging compressive-strength data, the synthesis is organized around controllable process inputs (feedstock conditioning, mix design, curing) and the interface-governed mechanisms that determine performance: interfacial transition zone (ITZ) character and pore connectivity. In coconut shell systems, density reductions come at a cost: elastic modulus drops and moisture sensitivity rises unless shell conditioning, particle packing, and matrix refinement are managed. In fiber systems, gains in toughness and residual capacity are bounded by mixing workability and by the long-term stability of the fiber–matrix bond under alkaline and wet–dry exposure. A mix must first meet strength, serviceability, and transport requirements before its embodied impact is compared with conventional alternatives. The contribution is to reframe these systems around controllable processing and interface mechanisms instead of tabulated strength values; preparation, treatment, and characterization data are consolidated into bounded design windows, an explicit core versus supporting evidence convention is applied, and sustainability is judged under functional equivalency rather than per-volume carbon. Full article

Traditional villages in the Chaoshan region serve as living repositories of local cultural heritage. Their concentrated and coordinated conservation and utilization can transcend administrative boundaries, enabling the integrated allocation of regional resources and the enhancement of cultural synergy. Currently, conservation practices for traditional villages are largely limited to piecemeal rescue efforts focused on individual villages. There is a lack of systematic understanding from a regional perspective and an explanation of the mechanisms underlying the formation of local landscapes, which hinders the realization of economies of scale in conservation and the development of cultural synergy. To explore effective approaches for the cluster-based conservation of traditional villages in China’s Lingnan coastal region, as well as the characteristics of human–land relationships and their adaptive mechanisms, this study focuses on 115 national and provincial-level traditional villages in the Chaoshan region. By introducing methods of single-factor and multi-factor cluster identification, the study innovatively constructs a four-dimensional cluster identification framework comprising “spatial proximity, geomorphological similarity, cultural convergence, and residential isomorphism,” and, utilizing the ArcGIS platform for coupled analysis, kernel density analysis, cluster identification, and field surveys, systematically analyzed the diverse typologies and landscape-specific characteristics of traditional village clusters in the Chaoshan region. The results indicate the following: (1) The identification of Chaozhou–Shantou traditional village clusters reveals three diverse types—comprehensive, distinctive, and potential—reflecting the richness and diversity of these clusters in the region. (2) Spatially proximate clusters exhibit a single-core, multi-point distribution, topographically similar clusters show differentiated distributions across plains and river valleys, culturally convergent clusters are significantly correlated with cultural carriers such as postal routes, water transport, and trade, and residential distributions are significantly correlated with topography and landforms, collectively constituting the unique character of Chaozhou–Shantou traditional village clusters. (3) Traditional villages in Chaoshan exhibit significant coupling with the natural environment, forming diverse spatial siting patterns in relation to mountains, water, forests, fields, and the sea, reflecting differentiated adaptation to and ingenious utilization of the natural environment. (4) The adaptive mechanism of the landscape of traditional Chaozhou–Shantou villages can be distilled into a three-tiered structure, natural adaptation as the foundation, social adaptation as the framework, and cultural adaptation as the soul, revealing the spatial planning wisdom of the Chaozhou–Shantou people in complex mountain and coastal environments. This study not only deepens our understanding of the human–land relationship in traditional villages of the Chaoshan region but also provides scientific evidence and theoretical support for the holistic preservation of cultural heritage and regional coordinated development. It holds significant practical value for promoting the protection and sustainable development of rural cultural heritage in the Lingnan coastal region. Full article

High-throughput sequencing and multi-omics are transforming Traditional Chinese Medicine (TCM) research from empirical descriptions toward data-driven mechanistic analyses. Unlike earlier systems pharmacology frameworks that relied primarily on static network topology and docking-based target prediction, current multi-omics approaches integrate genomic, transcriptomic, proteomic, and metabolomic data to capture dynamic, multi-scale biological responses. This review summarizes recent progress in four related areas: (i) genomic and epigenomic dissection of geo-authentic (Daodi) medicinal materials; (ii) biosynthetic pathway elucidation for major bioactive compound classes; (iii) synthetic biology platforms for heterologous production; and (iv) systems pharmacology integration for mechanism-of-action studies. We identify a central, recurrent gap: most published multi-omics analyses remain at the level of statistical association, and the biosynthetic and pharmacological pathways inferred from such data have not been validated at the causal level. To address this, we propose a tiered experimental validation framework—from biochemical target engagement through genetic perturbation to in vivo functional confirmation—and an iterative computational–experimental feedback loop. We further outline practical priorities for future work, including standardized data formats, community-endorsed metadata checklists, and coordinated DBTL pilot projects. By connecting descriptive multi-omics patterns to experimentally testable mechanistic models, TCM research can move toward precision-oriented medicine while preserving the multi-component character of traditional formulations. Full article

Hemp–lime composites are bio-based building materials with carbon sequestration potential, yet their properties exhibit significant variability depending on manufacturing variables, and standardized production guidelines remain lacking. This study investigates the influence of water-to-binder ratio (W/B = 1.75, 1.95, 2.15) and compaction degree (CD = 150%, 170%, 190%) on the thermal conductivity and compressive strength of hemp–lime composites using a full 3 × 3 factorial design at a binder-to-shiv ratio of B/S = 1:1. Results were synthesized with previously published investigations from a systematic research programme, enabling a comparative assessment of four technological variables across an extended dataset spanning densities from 227 to 518 kg/m³. The binder-to-shiv ratio was identified as the dominant factor governing both properties, primarily through its effect on bulk density and the mechanical character of the composite. Compaction degree was the most effective parameter for adjusting properties within a fixed mix design, with the strongest gains observed at the transition from CD = 150% to CD = 170%. The water-to-binder ratio exerted only marginal influence on bulk density and thermal conductivity, while its effect on compressive strength remained inconclusive at B/S = 1:1. Hemp shive particle size had a limited effect on thermal conductivity and no detectable influence on compressive strength. Both properties exhibited strong positive linear relationships with bulk density across the extended dataset. The findings support the standardization of hemp–lime composite production and the development of practical design guidelines. Full article

Named entity recognition (NER) of ancient Chinese texts is the foundation for their development and utilization. Previous studies have focused on the data-driven methodology which tries to utilize the semantic features of ancient Chinese text. With the continuous accumulation of ancient Chinese linguistic resources and textual data, how to fully utilize the data resource and lexical knowledge related to ancient Chinese text with the help of new-generation information technology, so as to improve the ability of semantic comprehension and achieve good performance of NER, has become a great challenge to be solved. In view of this, this paper proposes a named entity recognition model for ancient Chinese text by fusing explicit feature and implicit feature (NERM), on the basis of extracting the explicit features and implicit features of ancient Chinese texts using a pre-trained model and a multi-head attention mechanism. In this model, the GuwenBERT model is introduced to extract the semantic features of ancient Chinese texts, namely the explicit features. The implicit features include relative positional relations, part-of-speech, and character radicals. The experimental results on the corpus GuNER 2023 show that the proposed model NERM achieves an F1 value of 90.67%, outperforming the existing models. The ablation experimental results show that implicit features provide a modest but meaningful improvement over explicit features, and implicit features can be arranged in order of importance as follows: character radicals, part-of-speech, and relative positional relations. Full article

Neurodegenerative disorders, including Parkinson’s, Alzheimer’s, and multiple sclerosis, are significant global health issues characterized by escalating neuronal dysfunction and cognitive decline. Studies suggest that microbial toxins originating from fungi and bacteria may contribute to neurodegenerative processes by altering neuronal homeostasis in several ways. Toxins formerly associated with infectious diseases have now been associated with neuroinflammation, oxidative stress, and protein misfolding, all of which are common in neurodegenerative diseases. According to recent studies, microbial toxins generated by the gut microbiota may cross the blood–brain barrier and possibly contribute to neuroinflammatory cascades linked to the development of neurodegenerative diseases. The complex interplay of microbial metabolites, microbial responses, and mitochondrial dysfunction demonstrates the diverse character of neurodegenerative processes. This review delves into the current understanding of microbial toxins, which are produced by diverse bacteria and can have a direct or indirect impact on neuronal health via multiple signaling pathways. Understanding the signaling mechanisms of microbial and toxin-mediated neurodegenerative diseases could result in the development of effective alternative therapeutics for neurological disorders. Full article