Search Results (1,221)

In Chinese character learning, distinguishing similar characters is challenging for learners regardless of their proficiency. This is due to the complex orthography (visual word form) linking symbol, pronunciation, and meaning. Multimedia learning is a promising approach to implement learning strategies for Chinese characters. However, the availability of multimodal resources specifically designed for distinguishing similar Chinese characters is limited. With the advanced development of generative artificial intelligence (GenAI), we propose a practical framework for constructing multimodal resources, enabling flexible and semi-automated resource generation for Chinese character learning. The framework first constructs image illustrations due to their broad applicability across various learning contexts. After that, other four types of multimodal resources implementing learning strategies for similar character learning can be developed in the future, including summary slide, micro-video, self-test question, and basic information. An experiment was conducted with one group receiving the constructed multimodal resources and the other receiving the traditional text-based resources for similar character learning. We explored the participants’ learning performance, motivation, satisfaction, and attitudes. The results showed that the multimodal resources significantly improved performance on distinguishing simple characters, but were not suitable for non-homophones, i.e., visually similar characters with different pronunciations. Micro-videos introducing character formation knowledge significantly increased students’ learning motivation for character evolution and calligraphy. Overall, the resources received high satisfaction, especially for micro-videos and image illustrations. The findings regarding the effective design of multimodal resources for implementing learning strategies (e.g., using visual mnemonics, character formation knowledge, and group reviews) and implications for different Chinese character types are also discussed. Full article

To address the complex challenge of recognizing mixed handwritten text in practical scenarios such as examination papers and to overcome the limitations of existing methods that typically focus on a single category, this paper proposes MHTR, a Multimodal Handwritten Text Adaptive Recognition algorithm. The framework comprises two key components, a Handwritten Character Classification Module and a Handwritten Text Adaptive Recognition Module, which work in conjunction. The classification module performs fine-grained analysis of the input image, identifying different types of handwritten content such as Chinese characters, digits, and mathematical formula. Based on these results, the recognition module dynamically selects specialized sub-networks tailored to each category, thereby enhancing recognition accuracy. To further reduce errors caused by similar character shapes and diverse handwriting styles, a Context-aware Recognition Optimization Module is introduced. This module captures local semantic and structural information, improving the model’s understanding of character sequences and boosting recognition performance. Recognizing the limitations of existing public handwriting datasets, particularly their lack of diversity in character categories and writing styles, this study constructs a heterogeneous, integrated handwritten text dataset. The dataset combines samples from multiple sources, including Chinese characters, numerals, and mathematical symbols, and features high structural complexity and stylistic variation to better reflect real-world application needs. Experimental results show that MHTR achieves a recognition accuracy of 86.63% on the constructed dataset, significantly outperforming existing methods. Furthermore, the context-aware optimization module demonstrates strong adaptive correction capabilities in various misrecognition scenarios, confirming the effectiveness and practicality of the proposed approach for complex, multi-category handwritten text recognition tasks. Full article

Loess landslide disasters are influenced by a multitude of factors, including slope conditions, triggering mechanisms, and spatial attributes. Extracting these factors from unstructured geological texts is challenging due to nested entities, semantic ambiguity, and rare domain-specific terms. This study proposes a joint extraction framework guided by a domain ontology that categorizes six types of loess landslide influencing factors, including spatial relationships. The ontology facilitates conceptual classification and semi-automatic nested entity annotation, enabling the construction of a high-quality corpus with eight tag types. The model integrates a Soft-Lexicon mechanism that enhances character-level GloVe embeddings with explicit lexical features, including domain terms, part-of-speech tags, and word boundary indicators derived from a domain-specific lexicon. The resulting hybrid character-level representations are then fed into a BiLSTM-CRF architecture to jointly extract entities, attributes, and multi-level spatial and causal relationships. Extracted results are structured using a content-knowledge model to build a spatially enriched knowledge graph, supporting semantic queries and intelligent reasoning. Experimental results demonstrate improved performance over baseline methods, showcasing the framework’s effectiveness in geohazard information extraction and disaster risk analysis. Full article

Alginate-based materials are widely studied for biomedical use, but their limited mechanical properties and variable biocompatibility pose challenges. In this work, hybrid composites composed of alginate, calcium, and graphene oxide were fabricated using a freeze-drying method and cross-linked with calcium ions via calcium chloride at different concentrations. Structural and morphological features were assessed using SEM, EDS, ICP-MS, and BET analysis. The resulting composites exhibited a porous architecture, with calcium incorporation confirmed by elemental analysis. Surface characteristics and pore parameters were influenced by the presence of graphene oxide and the cross-linking process. The effects of the materials on haemostasis were evaluated through activated partial thromboplastin time (aPTT) and prothrombin time (PT) assays, revealing modulation of the intrinsic coagulation pathway without significant changes in the extrinsic pathway. In this study, we analysed the effect of alginate–graphene oxide composites on the viability of peripheral blood mononuclear (PBM) cells and human foreskin fibroblasts from the Hs68 cell line. We also assessed the genotoxic potential of alginate–graphene oxide composites on these cells. Our results showed no cyto- or genotoxic effects of the material on either cell type. These findings suggest the biocompatibility and safe character of alginate–graphene oxide composites for use with blood and skin cells. Full article

Alloys and metals exhibit high sensitivity to corrosion and aggressive environments. Hence, the development of protective treatments through accessible methods with a high degree of protection has become a necessity. This paper presents a method for treating the hydrophilic surface of aluminum alloys using two types of unsaturated fatty acids, thereby increasing the degree of hydrophobicity and protecting the material. The samples were cleaned by a chemical process, followed by immersion in oleic acid (C₁₈H₃₄O₂, 18:1 cis-9) and elaidic acid (C₁₈H₃₄O₂, 18:1 trans-9), and they were then treated at a temperature of 80 °C. Morphological and microstructural analyses were conducted using OM, FE-SEM, EDX, and FTIR to understand the influence of unsaturated monocarboxylic fatty acids on the alloy surfaces. The wettability capacity of the alloys was investigated by measuring the contact angle (CA). The results revealed that the cleaning step and modification treatment with fatty acids are essential steps for increasing the hydrophobic character of the surface. This study can be applied to various types of metallic substrates to enhance their corrosion resistance and long-term chemical stability in aggressive environments, making it adaptable for use in different industrial fields. Full article

The hybrid inorganic–organic material concept plays a bold role in multifunctional materials, combining different features on one platform. Once varying properties coexist without cancelling each other on one matrix, a new type of supermaterial can be formed. This concept showed that silver nanoparticles can be embedded together with inorganic and organic surface coatings and silicon quantum dots for symbiotic antibacterial character and UV-excited visible light fluorescent features. Additionally, fluorosilane material can be coupled with this prepolymeric structure to add the hydrophobic feature, showing water contact angles around 120°, providing self-cleaning features. Optical properties of the components and the final material were investigated by UV-Vis spectroscopy and PL analysis. Atomic investigations and structural variations were detected by XPS, SEM, and EDX atomic mapping methods, correcting the atomic entities inside the coating. FT-IR tracked surface features, and statistical analysis of the quantum dots and nanoparticles was conducted. Multifunctional final materials showed antibacterial properties against E. coli and S. aureus, exhibiting self-cleaning features with high surface contact angles and visible light fluorescence due to the silicon quantum dot incorporation into the sol-gel-produced nanocomposite hybrid structure. Full article

Since wheats used for use in brewing mainly belong to the winter red hard hybrid endosperm type, this paper examined the influence of different proportions of wheat of this type (seven varieties) in the ratio of 0–100% in the grist, both unmalted and as wheat malt. The quality of the starting wheats, the resulting malts and mashs with different added wheat proportions (100, 80, 60, 40, 20 and 0%) were examined. The obtained results show that the maximum shares of wheat/wheat malt in the infusion are significantly different between varieties of similar initial quality. However, they can differ considerably for the same variety when it is used as unmalted raw material and when it is used as wheat malt. Wheat malt can be added to the mixture in a significantly larger proportion compared to unmalted wheat. Furthermore, when an extended number of criteria (parameters) are applied, some varieties may be acceptable that otherwise would not be if the basic number of parameters were applied (total protein—TP, total soluble protein—TSP and viscosity—VIS) and vice versa. The inclusion of other parameters—filtration speed (FIL), saccharification time (SAC), color (COL), proportion of fine extract (EXT) and fermentability of pomace (FAL) (some of which have the character of so-called “cumulative parameters”)—complicates a clear classification into the aforementioned qualitative groups but also increases the number of varieties acceptable or conditionally acceptable for brewing. Full article

The landscapes of China’s multi-ethnic areas are rich in natural and cultural value, but they are threatened by homogenization and urbanization. This study aims to establish a method for identifying and classifying the landscape characters in China’s multi-ethnic areas to support the protection and sustainable development of the landscape in these areas. Taking the Miao Frontier Corridor as an example, the study optimized a parameterization method of landscape character assessment (LCA), integrated relevant cultural and natural elements, and used the K-means clustering algorithm to determine the landscape character types and regions of the Miao Frontier Corridor. The results show that (1) the natural conditions, ethnic exchanges, and historical institutions of the Miao Frontier Corridor have had a significant impact on its overall landscape; and (2) using ethnic group culture as a cultural element in LCA helps to reveal the unique cultural value of areas with different landscape characters. This study expands the LCA framework and applies it to multi-ethnic areas in China, thereby establishing a database that can serve as the basis for cross-regional landscape protection, management, and development planning in these areas. The research methods can be widely used in other multi-ethnic areas in China. Full article

Small towns in mountainous regions face significant challenges in formulating effective landscape zoning strategies due to pronounced landscape fragmentation, which is driven by both the dominance of large-scale forest resources and the lack of coordination between administrative planning departments. To tackle this problem, this study focused on Yuqian, a quintessential small mountainous town in Hangzhou, Zhejiang Province. The town’s layout was divided into a grid network measuring 70 m × 70 m. A two-step cluster process was employed using ArcGIS and SPSS software to analyze five landscape variables: altitude, slope, land use, heritage density, and visual visibility. Further, eCognition software’s semi-automated segmentation technique, complemented by manual adjustments, helped delineate landscape character types and areas. The overlay analysis integrated these areas with administrative village units, identifying four landscape character types across 35 character areas, which were recategorized into four planning and management zones: urban comprehensive service areas, agricultural and cultural tourism development areas, industrial development growth areas, and mountain forest ecological conservation areas. This result optimizes the current zoning types. These zones closely match governmental sustainable development zoning requirements. Based on these findings, we propose integrated landscape management and conservation strategies, including the cautious expansion of urban areas, leveraging agricultural and cultural tourism, ensuring industrial activities do not impact the natural and village environment adversely, and prioritizing ecological conservation in sensitive areas. This approach integrates spatial and administrative dimensions to enhance landscape connectivity and resource sustainability, providing key guidance for small town development in mountainous regions with unique environmental and cultural contexts. Full article

Background/Objectives: Increasing evidence suggests that lncRNAs are core regulators in the field of tumor progression, with context-specific functions in oncogenic tumorigenesis. LINC01133, a lncRNA that has been identified as both an oncogene and a tumor suppressor, remains largely unexplored in terms of its molecular mechanisms. The purpose of this study was to conduct an in silico analysis, incorporating literature research on various cancer types, to investigate the structural and functional duality of LINC01133. This analysis aimed to identify pathways influenced by LINC01133 and evaluate its mechanism of action as a potential therapeutic target and diagnostic biomarker. Methods: In silico analyses and a narrative review of the literature were performed to predict conserved structural elements, functional internal loops, and overall conservation of the LINC01133 sequence among different vertebrate organisms, summarizing the empirical evidence regarding its roles as a tumor suppressor and tumor-promoting roles in various types of tumors. Results: LINC01133 harbors the evolutionarily conserved structural regions that might allow for binding to relevant driver signaling pathways, substantiating its specific functionality. Its action extends beyond classical tumor mechanisms, affecting proliferation, migration, invasion, and epigenetic pathways in various types of tumors, as indicated by the in silico results and narrative review of the literature we present here. Clinical outcome associations pointed to its potential as a biomarker. Conclusions: The dual character of LINC01133 in tumor biology further demonstrates its prospective therapeutic value, but complete elucidation of its mechanisms of action requires further investigation. This study establishes LINC01133 as a multifaceted lncRNA, supporting context-specific strategies in targeting its pathways, and calls for expanded research to harness its full potential in oncology. Full article

Background: Ligusticum L. plants exhibit significant morphological variation in leaves, flowers, bracteoles and mericarps, thus the classifications of members for the genus have always been controversial. Among them, the taxonomic problem of Ligusticum multivittatum Franch. is the most prominent, which has not been sufficiently resolved so far. Methods: to clarify the taxonomic position of Ligusticum multivittatum, we performed phylogenetic analyses based on plastome data and ITS sequences. Meanwhile, we conducted comprehensively comparative plastome analyses between Ligusticum multivittatum and fifteen Ligusticopsis species. Results: Both analyses robustly supported that Ligusticum multivittatum nested in genus Ligusticopsis Leute and formed a clade with fifteen Ligusticopsis species, belonged to the Selineae tribe, which was distant from the type species of Ligusticum (Ligusticum scoticum), located in the Acronema clade.The comparative results showed that sixteen plastomes were highly similar and conservative in genome structure, size, gene content and arrangement, codon bias, SSRs and SC/IR. These findings imply that Ligusticum multivittatum is a member of Ligusticopsis, which was further verified by their shared morphological characters: stem base clothed in fibrous remnant sheaths, white petals, pinnate bracteoles, dorsally compressed mericarps with slightly prominent dorsal ribs, winged lateral ribs and numerous vittae in the commissure and in each furrow. Therefore, combining with the evidences of phylogenetic analyses, plastome comparison and morphological features, we affirmed that Ligusticum multivittatum indeed belonged to Ligusticopsis and transformed it into Ligusticopsis conducted by Pimenov was reasonable. Conclusions: Our study not only confirms the classification of Ligusticum multivittatum by integrating evidences, but also provides a reference for resolving taxonomy of contentious taxa. Full article

Processing ancient text images presents significant challenges due to severe visual degradation, missing glyph structures, and various types of noise caused by aging. These issues are particularly prominent in Chinese historical documents and stone inscriptions, where diverse writing styles, multi-angle capturing, uneven lighting, and low contrast further hinder the performance of traditional OCR techniques. In this paper, we propose a unified neural framework, UniText, for the detection, recognition, and glyph restoration of Chinese characters in images of historical documents and inscriptions. UniText operates at the character level and processes full-page inputs, making it robust to multi-scale, multi-oriented, and noise-corrupted text. The model adopts a multi-task architecture that integrates spatial localization, semantic recognition, and visual restoration through stroke-aware supervision and multi-scale feature aggregation. Experimental results on our curated dataset of ancient Chinese texts demonstrate that UniText achieves a competitive performance in detection and recognition while producing visually faithful restorations under challenging conditions. This work provides a technically scalable and generalizable framework for image-based document analysis, with potential applications in historical document processing, digital archiving, and broader tasks in text image understanding. Full article

Glow discharge optical emission spectroscopy (GDOES) is a powerful and well-established method of elemental analysis of metals, coatings and surface-modified materials. This review contains essential information needed to establish and successfully run a GDOES laboratory and perform accurate, quantitative GDOES analyses. The basics of the methodology, instrumentation and analytical interpretation of experimental data are presented, and examples of typical depth profiling applications are given. Special attention is paid to application-specific calibrations, their assumptions and prerequisites. The calibration model of GDOES is special; besides the composition of calibration samples, their sputter rates (sputter factors) need to be accounted for. Typical analytical performance of GDOES is discussed (precision, accuracy), as well as the depth quantification in depth-profiling applications. Links to some other methods, complementary to GDOES, are mentioned, including the type and the character of analytical information each method can deliver. Full article

This study proposes a new benchmark to evaluate the cultural understanding and natural language processing capabilities of large language models based on Sino-Korean words and four-character idioms. Those are essential linguistic and cultural assets in Korea. Reflecting the official question types of the Korean Hanja Proficiency Test, we constructed four question categories—four-character idioms, synonyms, antonyms, and homophones—and systematically compared the performance of GPT-based and non-GPT LLMs. GPT-4o showed the highest accuracy and explanation quality. However, challenges remain in distinguishing the subtle nuances of individual characters and in adapting to uniquely Korean meanings as opposed to standard Chinese character interpretations. Our findings reveal a gap in LLMs’ understanding of Korea-specific Hanja culture and underscore the need for evaluation tools reflecting these cultural distinctions. Full article

The mechanisms of chemoreception in fig wasps (Hymenoptera, Agaonidae) are of primary importance in their co-evolutionary relationship with the fig trees they pollinate. As the supplementary receptors to odorant receptors (ORs) and gustatory receptors (GRs) in insects, we compare the evolutionary characters of ionotropic receptors (IRs) among 25 fig wasp taxa in six genera. In total, we identified 205 IRs in 25 fig wasps, with each taxon recording from 5 to 12 IR genes. We found 189 IR genes clustered into 18 orthologous groups that can be divided into three types: IRco, antennal IRs, and divergent IRs. More IRs belong to antennal IRs in fig wasps, which can be sensitive to acids, aldehydes, polyamines, salt, amino acids, and temperature/humidity according to homology comparison. Additionally, some IR genes in fig wasps do not cluster with those of outgroup species (e.g., Drosophila melanogaster, Apis mellifera), suggesting they may represent a unique group and may have special functions in fig wasps. Divergent IRs are very few, with large sequence variation between species. Compared to ORs and GRs in fig wasps, gene sequences in most IR orthologous groups are more conserved between genera, with the lowest sequence similarity in 10 orthologous groups (including three IRco) exhibiting above 58.5%. Gene sequences are consistent with the phylogenetic relationships among fig wasps, which is the same as ORs and GRs. Strong purifying selection of IR genes was detected, as shown by the low ω values. Signatures of positive selection were detected in loci from three orthologous groups. Our results provide important molecular information for further studies on chemosensory mechanisms in fig wasps. Full article