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In the domain of anatomy, some Chinese characters in anatomical terms possess distinctive morphological significance. Chinese characters evolved from pictographic characters, with some of these pictographs being created by ancient people based on their own body structure. This implies that the comprehension and depiction of the human body structure have been integral since the inception of Chinese characters, and this knowledge has been passed down and developed through the continued inheritance of Chinese characters. Even today, certain characters retain the appearance to reflect the shape of the human body structure. By examining the characters related to vertebrae, cranial fontanel and heart, we can find the unique and enduring link between Chinese characters and the fields of anatomy as well as Chinese traditional medicine. [ABSTRACT FROM AUTHOR]

This article examines the impact of Jesuit translations of Chinese classics on European culture during the early modern period. The Jesuits aimed to convert China to Catholicism by adapting Confucianism to Christianity, which influenced Enlightenment political theory and values such as secularism and religious tolerance. The article discusses the challenges faced by the Jesuits in translating Chinese culture and the controversies surrounding their translations. A collection of essays further explores the historical and cultural exchanges between East and West through the translation of canonical texts, emphasizing the importance of cultural sensitivity and dialogue between different intellectual traditions. These translations have fostered a deeper understanding and appreciation of different cultures and have contributed to a more nuanced understanding between Western and Chinese intellectual traditions. [Extracted from the article]

In the seventeenth century, missionaries in China translated a vast array of Chinese works, including classics, official histories, and legal documents. Their translations have been analysed through several perspectives, yet their use of Chinese dictionaries has been largely overlooked. In the context of the Rites Controversy, between the Jesuits on one side and the Dominican and Franciscan friars on the other, precise references to authoritative Chinese dictionaries were made to corroborate their interpretation of Chinese rituals as either religious or secular. This article first describes why and how missionaries started from the early beginning of the mission in the 1580s to write their own bilingual dictionaries based on existing Western and Chinese dictionaries. Then, it considers how the same dictionaries became an important reference when the Rites Controversy erupted in the 1630s. Based on manuscript and printed documents written until 1670, three Chinese characters which became the focus of competing interpretations are discussed: miao as temple versus hall, ji as sacrifice versus offering, and sheng as prophet versus wise man. Besides the problem of biased translations on both sides, we shall show that there was a more fundamental reason which prevented the missionaries from settling their controversy using dictionaries. [ABSTRACT FROM AUTHOR]

Round and square are important concepts in Chinese aesthetics. The legacy of Chinese calligraphy aesthetics has led the way to modern design. In HCI, interface typefaces influence users' reading experiences. Users' aesthetic preferences may influence their reading experiences as well. The investigation of how human aesthetic preferences are affected by character visual features (e.g., character size and character weight) in type design has received substantial attention. However, it is difficult to accurately study human aesthetic preferences through these visual features in Chinese calligraphy-type design. How Chinese character visual features affect human aesthetic preferences is not clear. Inspired by graphic design, different visual features (e.g., color and texture) can cause changes in impression expressions (e.g., modern and classical), thus affecting human aesthetic preferences. In this article, we introduced a character impression analysis method to investigate how human aesthetic preferences are affected by Chinese character visual features. First, we proposed two impression expressions of character (round and square) from the concepts of Chinese aesthetics; Then, for these two impression expressions, we modeled four visual features of calligraphy characters from the principles of Gestalt psychology. Finally, we conducted two studies to investigate how visual features affect impression expressions and explored the relationship between aesthetic preferences. The results clearly explain how character visual features affect human aesthetic preferences. The present study can give designers a deep understanding of how visual features affect human aesthetic preferences based on character impression analysis. It can guide designers to make better type design decisions to achieve a high aesthetic preference for users. Furthermore, the findings of the present study can potentially provide new insights into Latin type design. [ABSTRACT FROM AUTHOR]

We present a psycholinguistic study investigating lexical effects on simplified Chinese character recognition by deaf readers. Prior research suggests that deaf readers exhibit efficient orthographic processing and decreased reliance on speech-based phonology in word recognition compared to hearing readers. In this large-scale character decision study (25 participants, each evaluating 2500 real characters and 2500 pseudo-characters), we analyzed various factors influencing character recognition accuracy and speed in deaf readers. Deaf participants demonstrated greater accuracy and faster recognition when characters were more frequent, were acquired earlier, had more strokes, displayed higher orthographic complexity, were more imageable in reference, or were less concrete in reference. Comparison with a previous study of hearing readers revealed that the facilitative effect of frequency on character decision accuracy was stronger for deaf readers than hearing readers. The effect of orthographic-phonological regularity differed significantly for the two groups, indicating that deaf readers rely more on orthographic structure and less on phonological information during character recognition. Notably, increased stroke counts (i.e., higher orthographic complexity) hindered hearing readers but facilitated recognition processes in deaf readers, suggesting that deaf readers excel at recognizing characters based on orthographic structure. The database generated from this large-scale character decision study offers a valuable resource for further research and practical applications in deaf education and literacy. [ABSTRACT FROM AUTHOR]

The article discusses Professor Zhang Yihua's Chinese-English Dictionary of Chinese Folklore and Customs (DCFC), which covers various aspects of Chinese culture. While the dictionary is praised for its innovative approach and extensive coverage, it is also criticized for its deficiencies. The article highlights omissions of certain terms, an imbalance in the inclusion of related words, and inaccurate translations. Suggestions for improvements include deleting inaccurate or superfluous equivalents, adding transliterations and loan translations, and providing better usage labels and cross-references. Despite its shortcomings, the DCFC is recognized for its valuable contribution to the study of Chinese folklore and customs. [Extracted from the article]

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Readers of Chinese characters need to recognize how they are formed in order to identify them correctly. However, our understanding of the cognitive processing of characters in working memory is limited. In Experiment 1, using the character N‐back task paradigm, electrophysiological data were recorded from 26 participants to investigate the effects of the visual feature of radicals on neural activity during the character recognition, updating and maintenance in the N‐back task. Results showed that compound characters required longer response times than single‐component characters. For the event‐related potentials (ERPs), the compound character condition had more negative N2pc and lower P300 amplitudes than the single‐component character condition. In Experiment 2, data from 26 participants were used to analyse the effect of the phonological feature of radicals on neural activity during the character recognition, updating and maintenance in the N‐back task. Results showed that there was a larger P200 in the irregular character condition than in the regular character condition, but there was no difference between the regular and the irregular characters in the N2pc, P300 and slow wave (SW) components. The visual feature and the phonological feature of the radicals may have different effects on the character processing. This study reveals the neural effects of Chinese character radicals on cognitive processing in a working memory task and provides behavioural and electrophysiological evidence for a theoretical model of verbal working memory subprocesses. [ABSTRACT FROM AUTHOR]

The graphic units in Chinese are Chinese characters (characters), most of which often join with others to form words of two or more characters. High-frequency two-character words (2C-words) tend to be composed of high-frequency characters. However, whether similarities exist between 2C-words and their constituent characters in other features remains an open question. The present study used a sample of 7,311 commonly used 2C-words (2CWs) and their constituent characters (CCs) to compare correlations among features that are common to 2CWs and characters. For both the 2CWs and the CCs, age of acquisition (AoA) was negatively correlated with frequency, sensory experience arousal was positively correlated with concreteness and emotion arousal and imageability was positively correlated with concreteness, sensory experience arousal, and emotion arousal. However, as the result of changes in AoA, skilled readers were more likely to be aware of changes in concreteness, imageability, and sensory experience arousal for the 2CWs than for the CCs. They might be less aware of valence, concreteness, number of strokes, and number of meanings but more conscious of emotion arousal and imageability of the 2CWs than of the CCs. The implications are that words and characters are important units in parallel and that words are both associated with and independent of their constituent characters. This may suggest a resolution to the debates about whether words or characters should be taken as the basic structural units in the Chinese language. [ABSTRACT FROM AUTHOR]

The purpose of this study was to explore the reasons for low retention rates among students in the Chinese classes in upper secondary education in the Czech Republic. The principal research question was whether Chinese characters were the main reason why many students decided to stop attending their Chinese classes. Semi-structured interviews with former and present secondary students of Chinese were employed in order to understand the students' attitudes and beliefs regarding learning Chinese characters and the Chinese language in general. It was found that the characters did not deter students from continuing the class, even though they were perceived as challenging and difficult. On the contrary, they were typically the students' favourite aspect of Chinese. A lack of personal motivation was identified as the main factor that differentiated the students who quit their Chinese course from their more successful counterparts. [ABSTRACT FROM AUTHOR]

This article examines the variation and reconstruction of Chinese translations of Jonathan Swift's "Gulliver's Travels" from 1872 to 1948. The translations underwent changes to make the story more familiar and understandable to Chinese readers, including renaming, converting measurements, and altering the concept of time. The translators also incorporated traditional Chinese literary devices and techniques to make the text more appealing to the local audience. The article highlights the significance of variation and reconstruction in cross-cultural mediation and the impact of cultural and socio-political factors on literary translation. [Extracted from the article]

Research has shown that arts-based approaches facilitate literacy learning in children; however, few studies have focused on the integration of art and early writing in community-based Chinese heritage language classes, which have been marginalized from the formal educational discourse in the United States. By drawing on the theoretical perspectives on social semiotics, this paper explored how young Chinese heritage learners engage in "writing" Chinese characters using fallen leaves. The data sources included field notes of observations, video recordings of the class, and the artifacts made by the children. Multimodal analysis revealed that the teacher invited the students to write together and created a social context for children to compose writing artwork. Children engaged with their composition through a variety of modes. This study has implications for research, practice, and policy. [ABSTRACT FROM AUTHOR]

The influence of orthographic neighbors on visual word recognition is well established in alphabetic scripts. To determine the universality of this effect across writing systems, researchers have been keen on exploring its presence and nature in Chinese word recognition. Given that Chinese is logographic, it necessitates a different definition for orthographic neighbors from the ones used in alphabetic scripts. One popular approach is to consider words that share characters as orthographic neighbors. Adopting this definition, a facilitative effect has been observed for characters that can create more words. However, as characters are also morphemes in Chinese, the facilitation found might actually come from a larger morphological family size. This possibility was tested in the present study by analyzing data from the Chinese Lexicon Project (CLP; Tse et al., Behavior Research Methods, 49, 1503–1519, 2017, Behavior Research Methods, 49, 1503–1519, 2022), a megastudy of two-character word recognition in traditional Chinese. If the effects of character-sharing are indeed morphological in nature, the facilitation should be smaller for ambiguous characters because the words formed are distributed over several morphological families. The results of the analyses were consistent with this hypothesis, revealing interactions between the number of words formed by a character and the number of meanings of the character. The implications of these findings were discussed in the context of definitions of orthographic neighbors and theories of word recognition in Chinese. [ABSTRACT FROM AUTHOR]

Previous studies have explored the validity of the Menzerath-Altmann law in spoken languages from a physical perspective. It has been found that this law fits better when the length of the constituents is measured in physical units, i.e. acoustic time durations. We hypothesize that it may also apply to written languages. To investigate this hypothesis, this study intends to explore the validity of the Menzerath-Altmann law at the character level in written Chinese from both symbolic (i.e. measured in strokes) and physical (i.e. measured in writing time durations) perspectives. The findings reveal a significant negative correlation between the character length and the average component length, aligning with the Menzerath's law. The results from both measurement approaches show that their relationship conforms to the Menzerath-Altmann law. More importantly, the law can be better fitted when the length of components is measured in physical units (i.e. writing time durations), which indicates a physical basis of the linguistic law. These findings may have significant implications for structural regularities within written linguistic systems. However, it should be noted the generalizability of this study may be limited since it only investigates one linguistic law, focusing on a limited set of character types in one language. [ABSTRACT FROM AUTHOR]

Chinese calligraphy is a significant aspect of traditional culture, as it involves the art of writing Chinese characters. Despite the development of numerous deep learning models for generating calligraphy characters, the resulting outputs often suffer from issues related to stroke accuracy and stylistic consistency. To address these problems, an end-to-end generation model for Chinese calligraphy characters based on dense blocks and a capsule network is proposed. This model aims to solve issues such as redundant and broken strokes, twisted and deformed strokes, and dissimilarity with authentic ones. The generator of the model employs self-attention mechanisms and densely connected blocks to reduce redundant and broken strokes. The discriminator, on the other hand, consists of a capsule network and a fully connected network to reduce twisted and deformed strokes. Additionally, the loss function includes perceptual loss to enhance the similarity between the generated calligraphy characters and the authentic ones. To demonstrate the validity of the proposed model, we conducted comparison and ablation experiments on the datasets of Yan Zhenqing's regular script, Deng Shiru's clerical script, and Wang Xizhi's running script. The experimental results show that, compared to the comparison model, the proposed model improves SSIM by 0.07 on average, reduces MSE by 1.95 on average, and improves PSNR by 0.92 on average, which proves the effectiveness of the proposed model. [ABSTRACT FROM AUTHOR]

Offline handwritten Chinese character recognition involves the application of computer vision techniques to recognize individual handwritten Chinese characters. This technology has significantly advanced the research in online handwriting recognition. Despite its widespread application across various fields, offline recognition faces numerous challenges. These challenges include the diversity of glyphs resulting from different writers' styles and habits, the vast number of Chinese character labels, and the presence of morphological similarities among characters. To address these challenges, an optimization method based on a separated pre-training model was proposed. The method aims to enhance the accuracy and robustness of recognizing similar character images by exploring potential correlations among them. In experiments, the HWDB and Chinese Calligraphy Styles by Calligraphers datasets were employed, utilizing precision, recall, and the Macro-F1 value as evaluation metrics. We employ a convolutional self-encoder model characterized by high recognition accuracy and robust performance. The experimental results demonstrated that the separated pre-training models improved the performance of the convolutional auto-encoder model, particularly in handling error-prone characters, resulting in an approximate 6% increase in precision. [ABSTRACT FROM AUTHOR]

A molecular design strategy for the precise regulation of full‐color‐tunable emission organic luminescence materials is not yet systematically established for pyrene chemistry. To fabricate color‐tunable and highly‐efficiency pyrene‐based emitters, this article presents novel pyrene‐based molecules with donating‐π‐accepting structures, which exhibit bright, relatively narrow‐band FWHM emission, broad color‐tunable from deep blue (439 nm) to orange‐red (599 nm) both in solution and in the solid state. Moreover, the compounds 2a, 2d–g exhibit typical aggregation‐induced emission (AIE) characteristics, with an enhanced fluorescence quantum yield in the solid state. The experimental results indicated that the presence of the sterically bulky meta‐substituted biphenyl adopts an out‐of‐plane twist conformation, which can strengthen the rigidity of the molecular conformation and suppress the intermolecular π–π stacking in the aggregated state, resulting in an enhanced emission in the solid state. The prepared pyrene‐based AIEgens are applied as fluorescent inks to write Chinese characters and art with a vivid pattern. Thus, this article not only presents an efficient molecular strategy to construct pyrene‐based AIEgen with broad color‐tunable emission properties for practical applications, but also display a powerful combination of the strong alliance between the advanced luminescent materials, art and Chinese traditional culture. [ABSTRACT FROM AUTHOR]

The article discusses the challenges and complexities of defining the terms "religion" and "esotericism" in the context of academic research. It highlights the lack of consensus among scholars and the motivations behind defining these terms. The authors argue that instead of seeking rigid definitions, it is more fruitful to explore the historical and cultural entanglements of these concepts. They emphasize the importance of context-dependent fluidity in understanding these terms and suggest that confusion can provide valuable insights. [Extracted from the article]

The article examines the film "El futuro perfecto" and its use of acousmatic sound to challenge fixed notions of Argentine identity and the immigrant experience. It follows Xiaobin, a Chinese immigrant in Buenos Aires, as she learns Spanish and navigates daily interactions. The film's use of acousmatic sound, where the source is unseen, prompts viewers to question assumptions about the characters' identities. It critiques the association between being Argentine and being white, while also highlighting the historical context of immigration in Argentina. The article explores how the film challenges assumptions about who can sound Argentine and encourages viewers to question their own beliefs and assumptions. It also analyzes scenes that simulate acousmatic conditions and how they contribute to the film's exploration of language and identity. The article discusses the concept of the acousmatic voice and its ability to challenge assumptions, as well as the portrayal of race, listening, and voice in the film. It emphasizes the importance of listening and understanding different voices and experiences. The article also examines the subway scenes in the film as a representation of a quiet and introspective space. Overall, the film "El futuro perfecto" explores migration and identity, challenging stereotypes and embracing multiple possibilities for a more inclusive future. [Extracted from the article]

This study investigates the impact of varying extrusion ratios on the microstructure and mechanical properties of AlSiCuFeMnYb alloy. Following hot extrusion, significant enhancements are observed in the microstructure of the cast rare earth aluminium alloy. Within the cross-sectional microstructure, the α-Al phase is reduced in size, and its dendritic morphology is eliminated. The morphology of the eutectic Si phase transitions from long strips to short rods, fine fibres, or granular forms. Similarly, the Fe-rich phase changes from a coarse skeletal and flat noodle shape to small strips and short skeletal forms resembling Chinese characters. The CuAl2 phase evolves from large blocks to smaller blocks and granular forms, while the Yb (Ytterbium)-rich rare earth phase shifts from large blocks to smaller, more uniformly distributed blocks. In the longitudinal section, the structure aligns into strips along the extrusion direction, with the spacing between these strips decreasing as the extrusion ratio increases. At an extrusion ratio of 22.56, the alloy demonstrates superior mechanical properties with a tensile strength of 325.50 MPa, a yield strength of 254.44 MPa, a hardness of 143.90 HV, and an elongation of 15.47%. These represent improvements of 27.8%, 36.5%, 38.9%, and 236.4%, respectively, compared with the as-cast rare earth alloy. In addition, the fracture surface of the extruded rare earth alloy exhibits obvious ductile fracture characteristics. Additionally, the alloy undergoes dynamic recrystallisation and dislocation entanglement during hot extrusion. The emergence of a twinned Si phase and a dynamically precipitated nanoscale CuAl2 phase are critical for enhancing deformation strengthening, modification strengthening, and dynamic precipitation strengthening of the extruded alloys. [ABSTRACT FROM AUTHOR]

Asian scripts that are significantly different from Roman-derived alphabets usually impose difficulties in learning. Translanguaging has therefore been explored as a pedagogical tool for the language classroom, including Chinese. While learning Chinese characters is thought to be one of the main challenges for students learning Chinese as a foreign language (CFL), there seems to be a paucity of up-to-date research into the strategies that adult students use to learn this logographic script. Situated in the translanguaging framework, this study employs the think-aloud method to investigate strategies utilised by a group of CFL beginner adult learners when learning characters. Drawing on the results of five think-aloud exercises with CFL learners over five weeks, as well as follow-up tests of their long-term memory of Chinese characters, this study shows that a variety of translanguaging strategies were utilised during the process of learning Chinese characters, and that overall three types of translanguaging strategies were observed: a) embodiment, b) translanguaging resemblance, and c) hybrid. The proposed typology of translanguaging strategies contributes to the further application of translanguaging as a methodology. It also sheds light on future learning strategy research across different linguistic systems. [ABSTRACT FROM AUTHOR]

This article discusses the concept of translanguaging in the context of Chinese language teaching. Translanguaging is a theory that challenges monolingualism and promotes the use of multiple languages and semiotic resources in education. The article highlights the lack of research on translanguaging in Asian languages, including Chinese, and aims to fill this gap by providing new scholarship on translanguaging in Mandarin Chinese. The article includes seven empirical studies that explore how translanguaging can be used to challenge monolingual ideologies, improve student engagement and learning experiences, and enhance Chinese character teaching and assessment design. The authors hope that this Special Issue will contribute to the recognition and adoption of translanguaging in Chinese language teaching and inspire further research on alternative ways of teaching and learning that move away from Eurocentric perspectives. [Extracted from the article]

Abstract The arrangement of Chinese characters has a significant impact on the visual effect and information dissemination in graphic design. In traditional Chinese layout, vertical arrangement of characters is predominant, but in recent times, there has been a gradual transition towards horizontal arrangement. To compare the influence of different character arrangement forms on visual meaning generation and information dissemination, This study employed an eye-tracking experiment to investigate two common Chinese character layouts in posters—horizontal and vertical, and collected data such as eye-tracking heatmap, pupil diameter and eye-tracking trajectory map. Based on objective eye-tracking data, combined with post-test interviews and questionnaire surveys, it was found that vertical character arrangement in Chinese typography is more effective in attracting visual attention and facilitating the expression and stimulating interest in viewing/reading under the premise of meeting formal requirements, which may provide guidance and inspiration for the practical application of Chinese characters in layout design, advertising design, packaging design, exhibition design, UI design, and other related fields.

Incomplete handwritten Dongba character often appears in heritage documents and its recognition is significant for heritage and philology. However, all previous methods always suppose that a complete Dongba character is used as input, and thus fail to achieve satisfactory performance when applied to incomplete Dongba character recognition. In this paper, an end-to-end network (DB2RNet) is proposed for incomplete handwritten Dongba character image recognition by multiscale feature restoration. Specifically, we first develop datasets that contain different levels of incomplete Dongba characters. A restoration module is proposed to restore the input incomplete Dongba character, and then a recognition module is employed to recognize Dongba character. By introducing an inter-module residual connection between the restoration module and recognition module, the DB2RNet can strengthen feature information transmission and boost the recognition performance. In addition, novel multiscale feature blocks are introduced, which can provide more effective texture and contextual information transmission for Dongba character image restoration, and thus yielding better restoration effects and better recognition results. Extensive experiments are conducted on Dongba character, Chinese character and Oracle character datasets and validate the effectiveness, superiority and robustness of our methods. Experiments results demonstrate that our proposed DB2RNet achieves competitive Dongba character restoration and recognition performance and outperforms the current state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Negotiation of meaning (NoM) has played a facilitative role in second language acquisition. However, the existing studies have primarily focused on adult English language learners. This study investigated the impact of task type and task complexity on NoM strategies among young learners of Chinese as a second language, an underexplored group. The participants were 110 students in Hong Kong aged 10–12, mainly from Pakistan, India, Philippines, and Nepal. They were asked to perform four tasks with different task types and levels of task complexity in Cantonese (the primary Chinese dialect spoken in Hong Kong). In terms of task type, the study found that required information exchange tasks (i.e., information gap tasks) produced significantly more clarification requests, confirmation checks, self-repetitions, and other repetitions in terms of total numbers and numbers per 100 Chinese characters than the optional exchange tasks (i.e., decision-making tasks). Complex tasks, on the other hand, elicited significantly more confirmation checks than simple tasks. These findings provide useful insights for designing tasks that can promote greater use of NoM strategies in classroom practice. [ABSTRACT FROM AUTHOR]

The arrangement of Chinese characters has a significant impact on the visual effect and information dissemination in graphic design. In traditional Chinese layout, vertical arrangement of characters is predominant, but in recent times, there has been a gradual transition towards horizontal arrangement. To compare the influence of different character arrangement forms on visual meaning generation and information dissemination, This study employed an eye-tracking experiment to investigate two common Chinese character layouts in posters—horizontal and vertical, and collected data such as eye-tracking heatmap, pupil diameter and eye-tracking trajectory map. Based on objective eye-tracking data, combined with post-test interviews and questionnaire surveys, it was found that vertical character arrangement in Chinese typography is more effective in attracting visual attention and facilitating the expression and stimulating interest in viewing/reading under the premise of meeting formal requirements, which may provide guidance and inspiration for the practical application of Chinese characters in layout design, advertising design, packaging design, exhibition design, UI design, and other related fields. [ABSTRACT FROM AUTHOR]

Considering the complex structure of Chinese characters, particularly the connections and intersections between strokes, there are challenges in low accuracy of Chinese character stroke extraction and recognition, as well as unclear segmentation. This study builds upon the YOLOv8n-seg model to propose the YOLOv8n-seg-CAA-BiFPN Chinese character stroke fine segmentation model. The proposed Coordinate-Aware Attention mechanism (CAA) divides the backbone network input feature map into four parts, applying different weights for horizontal, vertical, and channel attention to compute and fuse key information, thus capturing the contextual regularity of closely arranged stroke positions. The network's neck integrates an enhanced weighted bi-directional feature pyramid network (BiFPN), enhancing the fusion effect for features of strokes of various sizes. The Shape-IoU loss function is adopted in place of the traditional CIoU loss function, focusing on the shape and scale of stroke bounding boxes to optimize the bounding box regression process. Finally, the Grad-CAM++ technique is used to generate heatmaps of segmentation predictions, facilitating the visualization of effective features and a deeper understanding of the model's focus areas. Trained and tested on the public Chinese character stroke datasets CCSE-Kai and CCSE-HW, the model achieves an average accuracy of 84.71%, an average recall rate of 83.65%, and a mean average precision of 80.11%. Compared to the original YOLOv8n-seg and existing mainstream segmentation models like SegFormer, BiSeNetV2, and Mask R-CNN, the average accuracy improved by 3.50%, 4.35%, 10.56%, and 22.05%, respectively; the average recall rates improved by 4.42%, 9.32%, 15.64%, and 24.92%, respectively; and the mean average precision improved by 3.11%, 4.15%, 8.02%, and 19.33%, respectively. The results demonstrate that the YOLOv8n-seg-CAA-BiFPN network can accurately achieve Chinese character stroke segmentation. [ABSTRACT FROM AUTHOR]

Dongba characters are ancient ideographic scripts with abstract expressions that differ greatly from modern Chinese characters; directly applying existing methods cannot achieve the font style transfer of Dongba characters. This paper proposes an Attention-based Font style transfer Generative Adversarial Network (AFGAN) method. Based on the characteristics of Dongba character images, two core modules are set up in the proposed AFGAN, namely void constraint and font stroke constraint. In addition, in order to enhance the feature learning ability of the network and improve the style transfer effect, the Convolutional Block Attention Module (CBAM) mechanism is added in the down-sampling stage to help the network better adapt to input font images with different styles. The quantitative and qualitative analyses of the generated font and the real font were conducted by consulting with professional artists based on the newly built small seal script, slender gold script, and Dongba character dataset, and the styles of the small seal script and slender gold script were transferred to Dongba characters. The results indicate that the proposed AFGAN method has advantages in evaluation indexes and visual quality compared to existing networks. At the same time, this method can effectively learn the style features of small seal script and slender gold script, and transfer them to Dongba characters, indicating the effectiveness of this method. [ABSTRACT FROM AUTHOR]

The printing of Chinese characters, as well as their combination with alphabetic letters, has been one of the great challenges for Western typographers. When the missionary Paul Perny published his Dictionnaire français-latin-chinois de la langue mandarine parlée [ French-Latin-Chinese dictionary of the spoken Mandarin language ] (1869) in Paris, the conceptual design of the structure of its entries as well as the typographical quality of the Chinese characters he used were outstanding in their functionality and, hence, at a level far more advanced than the dictionaries of Chinese in combination with Western languages published in France up to that time. This paper explores the factors that enabled this dictionary to mark a turning point in the printing of Chinese characters in France. [ABSTRACT FROM AUTHOR]

The flourishing blossom of deep learning has witnessed the rapid development of Chinese character recognition. However, it remains a great challenge that the characters for testing may have different distributions from those of the training dataset. Existing methods based on a single-level representation (character-level, radical-level, or stroke-level) may be either too sensitive to distribution changes (e.g., induced by blurring, occlusion, and zero-shot problems) or too tolerant to one-to-many ambiguities. In this paper, we represent each Chinese character as a stroke tree, which is organized according to its radical structures, to fully exploit the merits of both radical and stroke levels in a decent way. We propose a two-stage decomposition framework, where a Feature-to-Radical Decoder decomposes each character into a radical sequence and a Radical-to-Stroke Decoder further decomposes each radical into the corresponding stroke sequence. The generated radical and stroke sequences are encoded as a radical-structured stroke tree (RSST), which is fed into a Tree-to-Character Translator based on the proposed Weighted Edit Distance to match the closest candidate character in the RSST lexicon. We have conducted extensive experiments on various datasets, such as handwritten, printed artistic, scene character datasets. The experimental results demonstrate that the proposed method outperforms the state-of-the-art single-level methods by increasing margins as the distribution difference becomes more severe in the blurring, occlusion, and zero-shot scenarios. For example, compared with the previous SOTA method, our method improve performance by 1.74–7.58% in the handwritten character zero-shot settings. [ABSTRACT FROM AUTHOR]

As a professor emeritus of the Department of English, National Taiwan University, Perng Ching-Hsi (1945-) has dedicated his lifetime to literary translation and Shakespeare Studies for more than half a century. His Chinese translations of Shakespeare's plays are adopted by local Taiwan drama companies for their outstanding lingual performability on the stage for the audience of our times. The paper seeks to explore how Perng manages to render the various Shakespearean poetic styles of Hamlet into equivalent, readable and performable Chinese language. First, the investigation will focus on the way Perng resorts to sophisticated domestication strategy in translating the proper names of the play into corresponding Chinese character names, names that are in most cases highly revealing of the characters' essential roles as well as dramatic functions in the play. Second, the research will probe into Perng's special literary expressions in the Chinese language, a language that hallmarks formal and semantic fidelity to Shakespeare's original rhetorics and poetics. Altogether, I argue that Perng Ching-Hsi's Chinese translation of Shakespeare's Hamlet features a dual contextualization, with which he attempts not merely to represent the original poetic styles of the play, but also to incarnate the poetics of Chinese literary convention. [ABSTRACT FROM AUTHOR]

The Intelligent Evaluation System for Calligraphy Characters (IESCC) is used for teaching calligraphy, and users can learn calligraphy through the modifications given by the system. Chinese character skeleton extraction is an important step in the intelligent evaluation algorithm of calligraphic characters. The skeletons of Chinese characters extracted by traditional refinement algorithms are prone to redundant branches and deformed skeletons, which can lead to skeleton extraction results that do not conform to the topology of the original character. In this study, the focus lies on hard‐pen regular script, and skeleton repair and extraction are performed for these characters. According to the writing characteristics of regular script, the redundant burs are removed and the deformation zone of the thinned skeleton is detected, and then the idea of first splitting is used, then restructuring, to propose a skeleton extraction algorithm based on stroke characterization and ambiguous zone detection for hard‐pen regular script, referred to as SCAD. First, a thinning algorithm is used to extract the skeleton of Chinese characters and remove redundant pixels. By analyzing the stroke characteristics of regular script, the burrs are classified and different conditions are set to detect and remove the burrs. Then the ambiguous zones are detected according to the different kinds of junction points. Then, curvature, stroke width and direction deviation are used to analyze the continuity of stroke segments, and the decision function is used to classify the stroke segments. Finally, the stroke segments with optimal pairings were compensated by interpolation according to the direction trend. This concludes the skeleton extraction. Skeleton extraction is performed on 1000 sample characters, and the SCAD algorithm can extract the skeleton of Chinese characters with an accuracy of up to 98.37%. It is proved that the SCAD method proposed here is a practical and effective method to extract the skeleton of hard‐pen regular script. [ABSTRACT FROM AUTHOR]

Ancient Chinese characters known as oracle bone inscriptions (OBIs) were inscribed on turtle shells and animal bones, and they boast a rich history dating back over 3600 years. The detection of OBIs is one of the most basic tasks in OBI research. The current research aimed to determine the precise location of OBIs with rubbing images. Given the low clarity, severe noise, and cracks in oracle bone inscriptions, the mainstream networks within the realm of deep learning possess low detection accuracy on the OBI detection dataset. To address this issue, this study analyzed the significant research progress in oracle bone script detection both domestically and internationally. Then, based on the YOLOv8 algorithm, according to the characteristics of OBI rubbing images, the algorithm was improved accordingly. The proposed algorithm added a small target detection head, modified the loss function, and embedded a CBAM. The results show that the improved model achieves an F-measure of 84.3%, surpassing the baseline model by approximately 1.8%. [ABSTRACT FROM AUTHOR]

Sinojackia Hu. comprises five to eight Chinese endemic species with high ornamental and medicinal value. However, the generic limits, interspecific relationships and evolutionary history of the genus remain unresolved. In this study, we newly sequenced three plastomes of S. oblongicarpa and compared them with those of the other congeneric species to explore the taxonomic delimitation of the species and the evolutionary history of the genus. The plastome structure of Sinojackia species was extremely conserved in terms of number of genes, sequence length, and GC content. The codon usage patterns revealed that natural selection may be the main factor shaping codon usage bias. Our phylogenetic tree shows that Sinojackia is monophyletic and can be divided into two clades. Sinojackia oblongicarpa as a distinct species is supported for it is distantly related to S. sarcocarpa. The evolutionary analysis of morphological features indicates that the woody mesocarp is an ancestral feature. Sinojackia originated in central Southeast China during the early Miocene. In this period, it experienced elevated diversification and migrated from central Southeast China to the Hunan Province and the Sichuan Province with the development of the Asian monsoon and East Asian flora. Glacial–interglacial interactions with the monsoon climate may provide favorable expansion conditions for Sinojackia on a small scale. [ABSTRACT FROM AUTHOR]

The place and placeness are believed to be a crucial perspective for comprehending the transformative dynamics of tourist destinations in the context of globalization and the rapid development of the tourism industry. As the material carrier of language, linguistic landscape is an intermediary for people to endow emotions and personalities into the place, becoming an effective path for exploring the place-making in a certain area. Mogan Mountain is a famous national tourist resort, which is located in Mogan Mountain Town, Deqing County, Huzhou City, China. This is a good case area for studying the relationship between linguistic landscape and place-making in tourist destinations. There are two theories that form the theoretical foundation of the study, namely the place and the geosemiotics. Firstly, the results showed the overall style of the linguistic landscape. Multilingual labelling (52.7%), official signs (55.3%), and standardized Chinese characters predominantly shaped the linguistic landscape, with English and other languages being complementary. Secondly, from the perspective of three dimensions of the geosemiotics framework, such as inscription, language preference, and placement position, we conduct a comprehensive semiotic analysis of the linguistic landscape, which encompasses diverse facets such as fonts, materials, shifts in state, text vectors, and symmetrical arrangements. Finally, we explore the influence of linguistic landscapes on the place-making of Mogan Mountain through the dimensions of location, locale, and sense of place. The information on linguistic landscapes indicates the geographical location. These linguistic landscapes play an important role in constructing the language order, nostalgic atmosphere, exotic atmosphere, and elegant and tasteful lifestyle of the public space in Mogan Mountain. Readers of linguistic landscapes, including tourists and residents, generate and identify with the unique sense of place in Mogan Mountain. These linguistic landscapes construct the destination placeness of Mogan Mountain that combines both foreign and nostalgic styles, and the integration of Chinese and Western cultures. It will help promote the image positioning of tourism destinations and have practical guiding significance for the tourism planning, landscape-making, language management, and other aspects of tourism destinations. [ABSTRACT FROM AUTHOR]

The article discusses the book "Computational Approaches to Semantic Change," which explores the interest among computational linguists in studying diachronic semantic change. The book consists of eleven chapters covering various topics and methodologies related to lexical semantic change. It includes a survey of computational techniques for detecting semantic change, case studies on specific concepts in English and scientific fields, discussions on lexicographic challenges, and examinations of meaning changes in sub-word units. While the book is more useful for computational linguists, it provides a comprehensive overview of state-of-the-art methodologies in the field. The article also highlights different computational approaches to studying semantic change, such as probabilistic models, cross-linguistic comparisons, periodizing diachronic document collections, Bayesian mixture models, and visualization tools. It concludes by acknowledging the challenges and potential future directions for computational research on lexical semantic change, while emphasizing the potential quantitative support these methodologies can provide for theoretical work in historical linguistics. [Extracted from the article]

Resonant actuation and multi‐degree‐of‐freedom (DoF) actuation can optimize the output matrices and greatly expand the versatility of dielectric elastomer actuators (DEAs) for practical applications. However, developing a multi‐DoF resonant DEA that benefits both from the maximized stroke outputs in resonant actuation and the versatility in multi‐DoF actuation remains a challenging task due to the slow responses of the widely adopted acrylic elastomers and the exponentially scaled complexity in the nonlinear dynamics. Herein, a multi‐DoF resonant DEA is reported by adopting four radially organized planar DE units fabricated by low‐loss silicone elastomers to output versatile programmable two‐dimensional quasi‐static and resonant trajectories. The rich nonlinear dynamics of the proposed quad‐unit DEA (QUDEA) are characterized and the critical parameters for two‐dimensional trajectory programming are uncovered through extensive modeling and experimental studies. To showcase the two‐dimensional trajectory programming capabilities of the QUDEA, demonstrations of Chinese characters writing and hummingbird flapping patterns mimicking using the proposed QUDEA are developed. The proposed QUDEA is expected to have potential in various applications such as in experimental biology, biomimetic robotics, and industrial manufacturing devices. [ABSTRACT FROM AUTHOR]

Lexical semantic changes spanning centuries can reveal the complicated developing process of language and social culture. In recent years, natural language processing (NLP) methods have been applied in this field to provide insight into the diachronic frequency change for word senses from large-scale historical corpus, for instance, analyzing which senses appear, increase, or decrease at which times. However, there is still a lack of Chinese diachronic corpus and dataset in this field to support supervised learning and text mining, and at the method level, few existing works analyze the Chinese semantic changes at the level of morpheme. This paper constructs a diachronic Chinese dataset for semantic tracking applications spanning 3000 years and extends the existing framework to the level of Chinese characters and morphemes, which contains four main steps of contextual sense representation, sense identification, morpheme sense mining, and diachronic semantic change representation. The experiment shows the effectiveness of our method in each step. Finally, in an interesting statistic, we discover the strong positive correlation of frequency and changing trend between monosyllabic word sense and the corresponding morpheme. [ABSTRACT FROM AUTHOR]

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Oracle bone inscriptions (OBIs) are the earliest Chinese characters and reserve abundant historical information. OBIs are detected by locating their positions in digital images. This has been a foundational task in modern archeological studies. Due to the development of deep neural networks(DNNs) in computer vision, detecting OBIs can be implemented by a more concise method instead of designing complicated hand-crafted features. However, existing models cannot perform well when noise areas are similar to some inscriptions. In this work, we present a simple but effective pseudo-label-based architecture for OBIs detection. Different from previous approaches, our method performs OBIs detection with the employment of information from multilabel annotations rather than single location information. We append a plug-and-play module that predicts the pseudo-label of an inscription after the backbone network for learning the particular structure prior to each inscription and brings this information to the backbone network by means of feature fusion. We make remarkable improvements on different backbone networks when using the proposed method on an OBIs detection dataset. The quantitative and qualitative results show that the proposed model can detect OBIs well and is an effective tool for assisting in the discovery and recognition of ancient writing. [ABSTRACT FROM AUTHOR]

One of the most well-known instructional methods used to enhance Chinese character reading (CCR) is Chinese stem-deriving instruction (CSDI). In this method, CCR is taught via a group of characters (e.g., 清, 情, and 靚) that share the same stem (e.g., 青). However, the effectiveness of CSDI on the CCR of Chinese children with dyslexia remains inconsistent, and the reason may be the diverse designs of this method across studies. Thus, this study aimed to use a quasiexperiment-design study to compare the effects of various forms of CSDI based on the (in)consistency of the extending characters' sounds, their appearances, and their amount (i.e., how many of them). In total, 122 Chinese third to sixth graders with dyslexia were recruited from primary schools, and they were randomly assigned to one of three groups: (a) visuospatially controlled CSDI (n = 37; all taught characters shared the same pronunciation), (b) verbally controlled CSDI (n = 45; all taught characters shared the same structure), and (c) noncontrolled CSDI (n = 40; all taught characters selected only on the basis of their frequencies). They were tested by CCR and dictation before and after the instruction. We found that CCR was significantly improved in all three CSDI groups, whereas only the verbally controlled CSDI group showed significant improvements in dictation. Furthermore, verbally and visuospatially controlled CSDI earned the greatest benefits in decreasing the visual errors and phonetic errors in CCR and decreasing the radical errors and homophone errors in dictation. Our findings shed light on the effectiveness of CSDI in terms of diverse designs, and frontline practitioners should take our findings into consideration when using CSDI. [ABSTRACT FROM AUTHOR]

The decipherment of ancient Chinese scripts, such as oracle bone and bronze inscriptions, holds immense significance for understanding ancient Chinese history, culture, and civilization. Despite substantial progress in recognizing oracle bone script, research on the overall recognition of ancient Chinese characters remains somewhat lacking. To tackle this issue, we pioneered the construction of a large-scale image dataset comprising 9233 distinct ancient Chinese characters sourced from images obtained through archaeological excavations. We propose the first model for recognizing the common ancient Chinese characters. This model consists of four stages with Linear Embedding and Swin-Transformer blocks, each supplemented by a CoT Block to enhance local feature extraction. We also advocate for an enhancement strategy, which involves two steps: firstly, conducting adaptive data enhancement on the original data, and secondly, randomly resampling the data. The experimental results, with a top-one accuracy of 87.25% and a top-five accuracy of 95.81%, demonstrate that our proposed method achieves remarkable performance. Furthermore, through the visualizing of model attention, it can be observed that the proposed model, trained on a large number of images, is able to capture the morphological characteristics of ancient Chinese characters to a certain extent. [ABSTRACT FROM AUTHOR]

Research has established that two cognitive processes, cognitive control and irrelevant stimulus-response (S-R) learning, may underlie the proportion congruency effect, which refers to the findings that the size of interference effects (e.g., the Stroop, Simon, or Eriksen flanker effect) reduces with increasing the proportion of incongruent trials. Further studies have begun to investigate the interaction between these two cognitive processes, which not only provide more plausible accounts for empirical data, but also advance theories. The present study set out to investigate whether cognitive control can modulate the effect of irrelevant S-R learning. In two experiments, we combined a color-letter contingency task, in which we manipulated the contingencies (low vs. high) of irrelevant S-R associations, with a color-Chinese character Stroop task, in which we manipulated the ratio of neutral to incongruent trials (mostly neutral (MN) versus mostly incongruent (MI)). Experiment 1 showed a proportion neutral effect (the Stroop effect was smaller in the MI than in the MN condition), suggesting changes in control demand. Critically, the contingency effect (faster responses in the high- than in the low-contingency condition) reduced in the MI than in the MN condition. Experiment 2 (preregistered) increased the number of Chinese characters to exclude a familiarity account for the proportion neutral effect, which replicated the findings of Experiment 1. These results suggest that cognitive control induced in the Stroop task transferred to the contingency task and modulated the contingency effect. Thus, this study provides clear evidence that cognitive control can modulate the effect of irrelevant S-R learning. [ABSTRACT FROM AUTHOR]