Volume 25

https://doi-xx0.org/6812/17671051479640 Shiying Zhang1,a, Hui Wang2,b, Yanhong Lu3,c, Haoxin Xiu4,d,*  1Business School of Nankai University, Tianjin, 300071, Tianjin, China; 2Institute of Economics, Shandong Academy of Social Sciences, Jinan, 250002, Shandong, China 3School of Economics and Management, Hebei University of Technology,Tianjin, 300401 ,Tianjin,China 4Qingdao Hospital, University of Health and Rehabilitation Sciences（Qingdao Municipal Hospital), Qingdao, 266011, Shandong, China aEmail: shiying.zhang@mail.nankai.edu.cn bEmail: ouc_wanghui@163.com cEmail: luyanhong2015@163.com dEmail: xhx19931011@163.com *Corresponding Author Abstract Amidst concurrent internal and external economic pressures, Chinese firms confront a critical challenge: the allocation of scarce resources. This study addresses this dilemma by introducing a leverage point framework. Utilizing firm-level data, our approach employs interpretable machine learning. The goal is to algorithmically discern the pivotal drivers of corporate sustainability within a severely resource-constrained environment. The empirical basis for our framework is a substantial dataset. It comprises 19,518 firm-year observations of Chinese A-share companies from 2010 to 2022. We deploy high-dimensional predictive models, specifically advanced ensemble algorithms like Random Forest and XGBoost. Sustainable operation is defined through two key metrics: the Sustainable Growth Rate (SGR) and Profit Volatility (PV). Following model construction, we examined feature importance and created Partial Dependence Plots (PDPs) to interpret the model, revealing key determinants and significant non-linear relationships. The results offer compelling insights. Financial Performance and Green Development emerged as the highest-ranking determinants of corporate sustainability overall. Our modeling also uncovered critical non-linear thresholds. An optimal range for R&D investment was identified between a ratio of 0.125 and 0.20. Similarly, a supplier concentration level around 20% was found to maximize sustainable performance. Furthermore, the analysis exposed a variety of significant interaction effects, notably between the ROE growth rate and the adoption of green management practices. This research significantly advances the understanding of corporate sustainability drivers. It presents a novel, interpretable, and data-driven framework for strategic resource allocation. This framework is particularly valuable for firms navigating competing demands during periods of economic strain. Ultimately, the study provides actionable, evidence-based guidance. This advice aims to ensure firms not only capture value generation but also cultivate the resilience necessary for long-term growth. Keywords: Financial Performance, Green Development, R&D Investment, Supply Chain Management, Machine Learning 1 Introduction Modern Chinese businesses are facing a collision of serious external and internal pressures that undermine their underlying operational viability and potential for long-term sustainability. Externally, geopolitical tensions have manifested as strategic technology embargoes related to access to important semiconductors, and imposition of tariffs on significant exports like new energy vehicles. Internally, the economy is dealing with the repercussions of a severe real estate slump. Collapsing builders, such as Evergrande Group, have created a domino effect for upstream construction suppliers in terms of capital flow, not to mention that downstream home buyers have properties that they likely will never get. This has tightened liquidity across the economy, with firms in every industry being forced to either reduce salaries or lay-off staff, exacerbating corporate instability in every sector and lack of resources. In this “economic winter”, the businesses are in a strategic conundrum. On the one hand, firms must urgently restrict costs and remain focused on core activities for short-term survival and, on the other, national policy requires firms to make major forward-looking investments. The government’s “dual carbon” targets are forcing firms to transition to green development and requiring significant capital expenditures for environmental protection and energy-saving initiatives. The ideological thrust for innovation-based growth from the strategic directions outlined in the 20th National Congress requires firms to commit substantial funds to R&D. These long-term implications are critical to developing national competitiveness and accountability for ecological well-being, yet firms may not have the financial means to support this longer-term focus.The most notable effect of this resource constraint is the broken capital chain and disrupted supply chain activities that make it extremely challenging for managers to finance green initiatives and R&D in addition to making sure they stay financially solvent and their supply chains resilient. Therefore, how to make the best use of severely constrained resources has become the biggest issue for corporate viability and sustainable development. Existing literature on resource constraints has some valuable suggestions to offer. For example, it is found that firms following a ‘balanced’ strategy, allocating constrained resources to functions like marketing and R&D, perform better than firms allocating in only one function [1]. Another body of literature suggests that resource constraints can paradoxically spur innovation because firms must think creatively and make good use of resource constraints [2]. However, much of this literature has significant limitations in light of today’s complicated crisis. First, the studies tend to lack multi-dimensional analyses examining the role of the constraints on a single domain, say innovation, without consideration of the fact that green development, supply chain management and financial health are all now connected. Second, the type of analytical models used are often linear models which examine how investments, say in R&D, affect financial performance without consideration of the reciprocal and synergetic nature of these domains [3]. Scholarly literature, in general, does not allow for a unified framework of the relational, and at times conflicting, relationships among these three investment areas. This is important when thinking about the complexities faced in today’s environment. In order to move forward in a way that rejects the path of standard linear analysis, this study takes a machine learning (ML) approach. We have selected reasoning for a computational perspective because ML will allow for modelling of the complex, non-linear and bidirectional relationships that comprise corporate investment systems. Standard econometric approaches encounter endogeneity and multi-collinearity among variables and therefore routinely cannot model the multilayered complex interactions. Management uses simultaneous ML algorithms to simulate and forecast outcomes. Rather than limiting the analytical approach to cause and effect analysis pursued in traditional economics, the focus of the current research uses a whole-portfolio effect of a combination of investments that create the necessary green development, innovation and supply chain mix to achieve a baseline financial objectives as well as enable sustainable operation. ML model, by estimating prior data, identifies baseline variables and index points that would

https://doi-xx0.org/6812/17670800716792 Abstract Zailan Tian1* 1Guangdong Polytechnic Normal University *Corresponding author:Zailan Tian Email: hrtian2017@126.com ABSTRACT Based on 412 teacher questionnaires from S University, a moderated mediation model was constructed to examine the impact mechanism of digital leadership on higher education technology adoption. The results showed that digital leadership significantly predicts technology acceptance, with digital organizational culture partially mediating this path. Resource endowment positively moderates mediation strength, with the indirect effect reaching 0.38 in high-resource groups and 0.18 in low-resource groups (Δ=0.20). The bootstrap 95%CI [0.10,0.30] excludes zero. The study confirms that resource abundance amplifies the leadership-culture-technology chain, providing contextual boundary explanations for university digital transformation. Keywords Digital leadership; digital organizational culture; technology acceptance; resource endowment; moderated mediation model Introduction Under the impetus of China’s national digital education strategy, universities commonly face the dilemma of “policy enthusiasm but implementation stagnation” in technology adoption. The case of S University’s “Smart Teaching 2.0” demonstrates that platform login rates remain below 40%, indicating that mere technical provision cannot drive behavioral changes among faculty. While existing research predominantly focuses on individual perceptions or system characteristics, it overlooks the critical absence of leadership and cultural influence in the loosely coupled context of higher education. Systematic validation remains lacking regarding whether digital leadership can enhance technology adoption through shared norms, and how resource conditions such as funding, infrastructure, and literacy amplify this process. Clarifying these mechanisms not only fills gaps in technology acceptance theories within higher education contexts but also provides evidence-based foundations for developing differentiated governance strategies. Building on transformational leadership and social information processing theories, this study constructs a mediation model where “digital leadership → digital organizational culture → technology acceptance” is moderated by resource endowment. Through structural equation modeling and bootstrap methods, empirical testing was conducted on 412 faculty members across 18 departments to reveal the internal logic and boundary conditions of technology diffusion in higher education institutions. 1 Background and Problem Definition During the overlapping period of the “Double First-Class” initiative and national education digitalization strategy, higher education institutions are expected to leverage technology to drive pedagogical innovation. S University’s 2021 “Smart Teaching 2.0” five-year plan, built on three pillars—5G Plus campus networks, big data platforms, and immersive smart classrooms—aims to achieve real-time classroom data collection, instant learning analytics feedback, and dynamic teaching optimization. However, a significant gap exists between policy requirements and actual implementation: by the third semester, platform login rates remained at 38.6%, with less than 15% of faculty using it routinely. Existing research attributes this gap to technological maturity or individual acceptance, while overlooking the unique governance context of universities as loosely coupled organizations. Digital leadership is seen as the key to overcoming the “last mile” challenge, as its ability to shape digital visions, orchestrate resources, and provide institutional support directly influences technology adoption trajectories. Meanwhile, digital organizational culture—through shared cognitive frameworks, collaborative norms, and data-driven discourse—provides teachers with sustained meaning in technology use. When digital leadership is absent and vision signals weaken, faculty struggle to develop collective recognition of technological value. When digital organizational culture remains thin and data-driven practices are not yet established, even skilled teachers may revert to traditional approaches. Thus, the core logic explaining technological stagnation in higher education lies in the interplay between digital leadership, digital organizational culture, and technology adoption. Furthermore, universities exhibit significant inter-institutional disparities in funding availability, infrastructure completeness, and faculty digital literacy. The endowment of resources may amplify or suppress these transmission pathways, thereby creating a moderated mediating context. By focusing on University S as a single case study, we can not only conduct in-depth tracking of policy implementation processes but also capture marginal differences in resource regulation through departmental heterogeneity. This approach provides reusable mechanism explanations and governance paradigms for the digital transformation of higher education. 2. Theoretical Framework and Research Hypotheses 2.1 Direct effects of digital leadership on technology adoption In loosely coupled university governance contexts, digital leadership is conceptualized as a direct driving force exerted by university presidents and IT directors on faculty technology adoption through digital vision building, empowerment, and institutional incentives. Empirical evidence from S University’s “Smart Teaching 2.0” initiative demonstrates that when leadership frequently articulates transformational visions, presents clear roadmaps, and quantifies performance metrics to demonstrate necessity, faculty perceived usefulness of smart classrooms and big data platforms significantly increases, thereby driving adoption willingness. Transformational leadership theory posits that leaders can reduce teachers’ uncertainty avoidance toward new technologies through idealized influence and personalized care. The technology acceptance model further defines perceived usefulness and perceived ease of use as pre-cognitive factors shaping willingness. In higher education settings, digital leadership directly enhances perceived usefulness through strategic alignment communication, prioritized resource allocation, and risk mitigation commitments, bypassing the indirect path of perceived ease of use in traditional Technology Acceptance Model (TAM). Specifically, presidents consistently incorporate “data-driven decision-making” into departmental evaluation metrics during annual teaching conferences, while IT offices simultaneously publish platform usage white papers and offer early adopters class hour reductions and research credits. These signals reinforce faculty’s understanding of the instrumental connection between technological tools and career rewards. Consequently, the impact of digital leadership on technology acceptance can be abstracted into a single-path structural equation, highlighting its independent main effect. Among them, represents the teachers’ willingness to use the intelligent teaching system, represents the digital leadership intensity of principals and information managers, represents the path coefficient, and represents the error term. 2.2 The Mediating Mechanism of Digital Organizational Culture In higher education institutions, digital organizational culture manifests as a three-dimensional interactive system of group norms characterized by collaboration, data-driven practices, and continuous learning. Its formation and reinforcement rely on sustained leadership signals. During the implementation of S University’s “Smart Teaching 2.0” initiative, the president and IT director established a governance framework for data sharing, created cross-departmental teaching innovation communities, and incorporated learning analytics into faculty promotion criteria. These measures conveyed expectations of “collaborative lesson planning, data-driven decision-making, and lifelong professional development,” transforming individual cognition into collective action. The collaboration dimension reduces transaction costs for resource complementarity, the data-driven

DOI:https://doi-xx0.org/6812/17707151636243 Abstract Future travel trends are significantly influenced by big data technologies. The current study explored the effect of tourist’s destination perceptions on tourism online content management information system in the context of big data. The present study hypothesized that big data has a moderating function in the development of tourist’s behavioral intentions. Moreover, the present study also analyzed the mediating role of tourism online content management information system in the relationship between tourist’s destination perceptions and tourist’s behavioral intentions. The information was gathered from 511 tourists in China’s Shanghai and Beijing cities. PLS-SEM results revealed a direct association between tourist’s destination perceptions and tourism online content management information system. The findings also confirmed the underlying role of big data as a moderating variable. Moreover, the results highlighted the implications of tourism online content management information system using big data technologies in the global tourism industry. Keywords: Tourist’s destination perceptions, tourism online content management information system, tourist’s behavioral intentions, big data. Introduction Before booking a trip, most tourists begin planning stage by doing internet research on the finest vacation spots and hotels (Not, 2021). For many years now, the internet has been the go-to resource for gathering details on fun activities to do in one’s spare time. Tourists’ access to ICT gadgets like computers, tablets, iPads, and smartphones has increased worldwide internet usage for tourism-related purposes including research, advertising, and consumption (Torres, 2022). Information on popular tourist destinations may be accessible through many online resources including social media, search engines, websites, and weblogs thanks to the meteoric rise of online shopping and booking in the hospitality sector. This has helped spread the word about the tourist and hospitality industries all across the globe. Tourists may now easily find, communicate with, compare, and decide to buy online tourism and hospitality bargains thanks to cutting-edge ICT and the internet (Liu, Wang, & Gretzel, 2022; Ravi & Vairavasundaram, 2016; Zhang, Wu, & Fan, 2019). Because consumers’ online search habits can be used to predict what they will buy from virtual markets, smart business technologies focus on collecting information about users’ online browsing history to influence their purchase decisions, satisfaction, happiness, and spreading behaviors (Silaban, Chen, Nababan, Eunike, & Silalahi, 2022). Organizations promoting tourist destinations hope that establishing a strong online presence will attract curious travelers looking for information online, and that providing such travelers with up-to-date and reliable data will prompt their current customers to leave positive reviews that can be easily accessed with a few mouse clicks (Mapanga, 2022; Sun, Liu, & Zhang, 2021). Positive feelings and plans to act, like wanting to go to a tourist spot, can come from using the internet in a good way (Jiménez-Barreto, Rubio, Campo, & Molinillo, 2020). Tourists’ experiences with tourism online content management information systems, such as the quality of online information and how easy it is to access, may have a big impact on their plans to travel (Lee, Lee, Jeong, & Oh, 2020). The rise of virtual markets for online shopping, on the other hand, often makes people worry about how safe and reliable online platforms are (Majeed, Zhou, Lu, & Ramkissoon, 2020b). Threats in the online business environment, like the possibility of losing personal information and payment identity information, may make customers less likely to shop online. This could help find out what travelers like and dislike about buying tourism and hospitality services online (Yu, Moon, Chua, & Han, 2022). The literature on tourism also investigates the link between satisfaction and tourists’ behavioral goals (Chen & Chen, 2010). But in the online tourism industry, the role of the tourism online content management information system as a link between how tourists feel about a destination and what they plan to do there hasn’t been studied yet. In recent years, the modern information society has moved into the age of “big data.” “Big data” has grown quickly into a well-known field that academics and businesses value, and it has been used in many ways (Chen & Li, 2022; Zhao, Zhou, & Mu, 2021). In recent years, artificial intelligence technology has grown quickly. The technology in the field of artificial intelligence has a lot of things that make it unique and complicated (Samala, Katkam, Bellamkonda, & Rodriguez, 2020). Teradata uses “big data” to help people plan their trip to the 2021 London Olympics through a dedicated website. It does this by sifting through the data and sending out emails that are more specific. This helped people avoid the crowds during the games, which affected about 35% of people’s travel decisions (Xie & He, 2022). With big data as the background, it is a great chance for the tourism industry to grow (Xu, 2020). But tourist marketing has several flaws: the idea is old, the techniques are old, and the methods are old. All of these things make it harder for tourism to grow in a sustainable way (Florek & Gazda, 2021; Richards, 2003; Xie & He, 2022). So, the goal of this study was to find out how it affects the link between a tourism online content management information system and tourists’ plans for how they will behave. This study tried to figure out how these things happened in China, which was one of the first places to have smart tourism. Also, the active growth of smart tourism in China is being driven by the following (Guo & Gu, 2022). China thinks that smart tourism is important for the country as a whole. At the beginning of 2011, China’s National Tourism Administration (CNTA) announced that it would start a smart tourism initiative. The goal of this initiative is to make China’s tourism more information-based within 10 years. Since then, China has made a lot of progress in smart tourism (Wang, Zhen, Tang, Shen, & Liu, 2021). In November 2013, the CNTA made the tourism theme “Beautiful China-2014 Year of Smart Travel” official. Smart tourism is a big part of the country’s plan to grow tourism (Jia et al., 2022). So, the main goal

https://doi-xx0.org/6812/17651843533908 第一作者英文名1 ,a , Yuan Gao Department： Keyboard discipline University：Shenyang Conservatory of Music City：Shenyang Country：China（英文单位）   *Corresponding author:gao13700046969@hotmail.com   13700046969@163.com   Funding（基金项目）   Abstract— This study rigorously interrogates the differential impacts of Augmented Reality (AR) and Virtual Reality (VR) on piano pedagogy and performance anxiety regulation through a stratified randomized controlled trial involving 60 intermediate-level pianists across three experimental arms: conventional instruction (control), AR-enhanced learning, and VR-based performance simulation. Quantitative analysis revealed that AR yielded the most pronounced improvement in motoric accuracy (Δ = +11 pp; Pre: 73% ± 9, Post: 84% ± 6) by leveraging real-time visuospatial feedback to facilitate proprioceptive calibration and procedural consolidation. Conversely, VR demonstrated superior efficacy in psychophysiological desensitization, reflected in a dramatic reduction in Music Performance Anxiety Inventory scores (Δ = −13; d = 2.29) and minimal vagal withdrawal under recital stress (RMSSD Δ = −1 ms), thereby supporting its application as an immersive exposure-based regulatory intervention. The control group exhibited only marginal gains across cognitive-affective metrics (e.g., accuracy Δ = +3 pp; MPAI Δ = −2), underscoring the limitations of traditional pedagogy in achieving bidirectional neurocognitive optimization. These findings substantiate the theoretical and empirical proposition that immersive AR and VR modalities serve as potent neuropedagogical vectors for synchronously enhancing fine-motor acquisition and affective regulation in high-performance musical contexts. Keywords— Augmented Reality, Virtual Reality, Piano Pedagogy, Performance Anxiety, Motor Learning, Heart Rate Variability, Immersive Technology, Neuropedagogy Introduction The integration of immersive technologies—particularly Augmented Reality (AR) and Virtual Reality (VR)—into educational frameworks has yielded a transformative paradigm in cognitive and sensorimotor training [1]. In the domain of music education, and specifically piano pedagogy, the application of these technologies has not merely introduced novel tools but has also provoked a reconfiguration of conventional instructional modalities [2]. AR overlays have the potential to deliver real-time, spatially contextualized visual feedback during performance, thus engaging learners in a multi-sensory feedback loop that reinforces motor planning and execution through embodied cognition principles. Similarly, VR offers a unique capacity for controlled ecological validity, allowing pianists to engage with hyperrealistic performance environments that simulate the psychophysiological stressors associated with live recital conditions, hence rendering it a promising tool in affective-behavioral desensitization frameworks [3]. Figure 1 Mixed reality strategies for piano education [3] Despite growing enthusiasm in adjacent fields such as medical simulation and engineering education, empirical evidence evaluating the efficacy of AR and VR in structured piano pedagogy remains sparse and methodologically fragmented [4]. Prior studies have largely relied on heuristic metrics or anecdotal practitioner reports, lacking the empirical granularity necessary to establish causality between immersive interventions and improvements in both cognitive–motor integration and performance anxiety regulation [5]. Moreover, the neuropsychological mechanisms through which immersive modalities may influence musical skill acquisition—such as visuomotor entrainment, attentional modulation via dopaminergic salience networks, and sympathetic nervous system attenuation—are only beginning to be elucidated [6]. This study seeks to bridge this lacuna by employing a rigorous experimental protocol with objective and validated psychometric and physiological instrumentation [7]. Central to the theoretical foundation of this investigation is the dual-faceted nature of music performance, which necessitates both the development of fine motor precision and the regulation of performance-related anxiety (PRA), often operationalized through indices such as the Music Performance Anxiety Inventory (MPAI) and autonomic biomarkers including heart-rate variability (HRV). Performance anxiety has been demonstrated to adversely impact procedural memory recall, auditory working memory, and kinaesthetic control, all of which are critical for proficient pianism [8]. Leveraging VR as a controlled exposure environment offers a promising analogue to systematic desensitization techniques, aligning with theories of affective habituation and cognitive reappraisal under the broader umbrella of the psychophysiological model of PRA [9]. Simultaneously, AR-based systems capable of delivering gesture-level feedback through computer vision overlays and haptic-augmented prompts may enhance acquisition of motoric schemas in ways that traditional teacher-led instruction cannot match. This is particularly relevant in the context of skill automatization and chunking theory, where distributed sensory engagement accelerates the consolidation of spatial–temporal mappings [10]. Additionally, AR can induce a state of flow through congruent task-oriented feedback and reduced cognitive load, thus fostering deeper procedural encoding. Such enhancements align with constructivist and enactive learning theories, which posit that skill mastery emerges not solely from observation and repetition, but from active sensorimotor participation in ecologically valid contexts [11]. Accordingly, this research study aims to undertake a tripartite comparative evaluation of traditional instruction, AR-enhanced piano pedagogy, and VR-based exposure therapy to assess their respective impacts on (a) the rate and quality of piano performance accuracy, and (b) the modulation of psychometric and physiological indicators of performance anxiety [12]. Through a randomized controlled trial employing robust within- and between-subject statistical methodologies (e.g., mixed ANOVA with effect size correction), this study contributes not only to applied music education practices but also to the interdisciplinary literature on embodied cognition, digital therapeutic interventions, and neuroeducational engineering [13]. The findings are anticipated to inform both pedagogical praxis and clinical strategies for anxiety mitigation in high-stakes performance domains. Literature Review Augmented Reality (AR) in Sensorimotor Music Training Augmented Reality has increasingly been utilized in fine motor skill training due to its capacity to deliver real-time multimodal feedback overlays that are precisely mapped to anatomical landmarks, thus facilitating the realignment of kinaesthetic errors through immediate perceptual correction. In piano pedagogy, the utilization of AR interfaces—particularly those employing spatially registered note cues and gesture recognition algorithms—has demonstrated efficacy in enhancing visuomotor synchronization and intermanual coordination among novice learners [5]. The underlying computational architecture of AR-based feedback systems enables continuous monitoring of spatial-temporal accuracy, allowing for the dynamic modulation of difficulty parameters, which has been shown to improve cognitive-motor entrainment in domain-specific psychomotor learning [13]. Moreover, evidence from neuroergonomics supports the notion that AR interventions can modulate functional connectivity between the dorsolateral prefrontal cortex and premotor cortices, suggesting that AR may influence not only performance outcomes but also the neurocognitive substrates underpinning musical learning [21]. The pedagogical potential of AR is further supported by findings in embodied cognition, where sensorimotor contingencies are posited as critical variables in the encoding of procedural knowledge. Studies involving digital overlay systems have demonstrated that real-time augmented feedback facilitates the internalization of spatial heuristics—such

https://doi-xx0.org/6812/17651865015813 第一作者英文名1 ,a , Xiaofan Ding 通信作者英文名1,b* Department：College of music education University：Shenyang Conservatory of Music City：Shenyang Country：China（英文单位）   aEmail:ding19880409@hotmail.com   Funding（基金项目） Abstract— This study critically investigates the impact of algorithmically generated musical content on the interpretive, expressive, and motoric dimensions of professional piano performance, with particular emphasis on three core variables: interpretative depth, perceived authenticity, and performative creativity. Utilizing a between-subjects design involving AI-generated and human-composed musical stimuli, the research employed expert evaluation, Delphi-based creativity scoring, self-reported authenticity metrics, and high-resolution MIDI-derived performance fluency analytics. Results indicate that AI-generated music elicits significantly attenuated interpretive engagement, with reduced mean scores across all aesthetic and biomechanical domains, including expert-rated interpretation (–23.6%), perceived creativity (–18.1%), and authenticity (–33.8%). Moreover, quantitative fluency parameters such as note onset deviation, articulation variability, and pedaling efficiency reflected degraded temporal precision and expressive motor output in the AI condition. Effect sizes across all domains ranged from large to extremely large (Cohen’s d > 1.19–2.22), suggesting a systematic and functionally disruptive disconnect between algorithmic compositional structure and the cognitive-embodied mechanisms underpinning expressive human performance. These findings reveal foundational limitations in current generative music systems and challenge the presupposition that algorithmic music can function as an interpretively equivalent substrate within professional performance practice. Keywords— AI-generated music, piano performance, musical interpretation, performance authenticity, computational creativity, expressive fluency, music cognition, algorithmic composition Introduction The exponential evolution of artificial intelligence in creative domains has engendered a paradigmatic shift in music composition, performance, and pedagogy. Algorithmic models such as OpenAI’s MuseNet and AIVA now generate highly structured, stylistically coherent music that is ostensibly indistinguishable from that produced by human composers [1]. These systems utilize deep generative architectures—including transformer-based models and variational autoencoders—to simulate complex harmonic progressions, temporal motifs, and dynamic phrasing [2]. However, despite the sophistication of these generative processes, the ontological status of AI-generated music remains contested in terms of intentionality, emotional valence, and structural teleology [3]. Within the performance domain, pianists serve as an ideal population to assess the cognitive and expressive ramifications of engaging with AI-generated material. Piano performance is deeply embodied and interpretive, involving highly nonlinear mappings between symbolic scores and expressive micro-gestures such as rubato, agogics, pedaling, and articulation [4]. Previous research demonstrates that performers rely not only on the syntactic content of a score but also on inferred composer intentionality and stylistic authenticity to shape interpretive decisions [5]. When such intentionality is obscured—as is often the case with AI-composed works—musicians may experience reduced affective resonance and diminished expressive agency [6]. Unveiling a Pianist’s Expression through AI as shown in Figure 1 Figure 1 Unveiling a Pianist’s Expression through AI The epistemic uncertainty surrounding AI-authored music also intersects with cognitive-affective constructs such as authenticity and creativity. Authenticity in performance is often rooted in the perceived alignment between the score’s idiomaticity and the performer’s interpretive logic, a relationship that may be disrupted by algorithmically constructed outputs lacking embodied musical intention [7]. Moreover, research in creativity studies suggests that AI-generated music may impose cognitive constraints on performers, who often rely on narrative coherence and stylistic norms to scaffold novel yet coherent interpretations [8]. Without a clearly defined expressive grammar or teleological form, performers may default to mechanical rendering, thereby attenuating the spontaneous, emergent features characteristic of creative musicianship [9]. While prior literature has examined the structural attributes of AI-composed music and audience perception of its quality, few empirical studies have investigated how such music directly impacts the pianist’s interpretive behavior, perceived authenticity, and expressive creativity in a performance context [10]. This research aims to fill that lacuna by conducting a comparative analysis between performances of AI-generated and human-composed piano works. Drawing on both quantitative and qualitative metrics—including expert ratings, performance fluency data, and performer self-reports—this study interrogates how AI-authored scores influence not only technical execution but also deeper affective and creative processes [11]. Ultimately, this research contributes to the evolving discourse on human–machine co-creativity, challenging traditional models of authorship and offering critical insight into the embodied dynamics of AI–human musical interaction [12]. Literature Review The Computational Foundations of AI-Generated Music New developments in artificial intelligence have allowed the generation of complicated musical compositions by using deep learning algorithms to imitate stylistic, harmonic and rhythmic patterns. OpenAI MuseNet and Google MusicLM are models based on multi-layered transformer networks that have been trained on large corpora of MIDI and audio data in order to learn to predict note sequences and structure of composition with impressive faithfulness [1]. These architectures learn long-term dependencies and can generate AI systems that can simulate compositional hierarchies, previously believed to only require human cognitive intent [2]. Nevertheless, the syntactic meaningfulness of the works generated by such systems is, in most cases, devoid of semantic purpose, which begs the question of the ontology of algorithmic authorship in the artistic realms [3]. Hybrid systems involving symbolic logic, probabilistic grammar modeling, and variational autoencoders are becoming more commonly used as algorithms to generate music, permitting generative models to produce stylistically rich output that can imitate historical and contemporary styles [4]. However, such systems although can generate notational artifacts that resemble those of canonical composers, are not embodied sensorimotor grounded, but this is a key feature of human music-making [5]. Also, even when stylistic precision is enhanced, the majority of music generated by an AI lacks the telos-driven development and motivic change, which are two characteristics of music written by humans [6]. Interpretation and Expressive Intent in Piano Performance Piano performance interpretation is a multilayered holistic practice through which performers negotiate textual, structural and affective levels of musical score. The mediation is comprised of active micro-decisions, namely, timing inflection, articulation, pedaling, and phrasing, all of which add to an emergent expressive identity [7]. Interpretive approach of the pianist is highly dependent on the perceived composer intent, historical context and familiarity with style which all determine expressive coherence [8]. Ambiguous or algorithmically-determined, without the intentionality of a human being, such cues can lead the performer to expressive disorientation and a lack of ability to participate in the meaning-making process [9]. The cognitive-motor

https://doi.org/10.65281/639319 Jianfei Shi1, Meiyuan Yun2,* 1College of Fine Arts, Beihua University, Jilin 132013, China E-mail address: shijianfei@vip.163.com 2College of Fine Arts, Beihua University, Jilin 132013, China E-mail address: 343204463@qq.com *Corresponding author Abstract This study explores the cosmic tree symbol in Northeast Asian shamanic culture through an ecosemiotic and visual communication lens, proposing a four-dimensional model: Nature→Symbol→Visual→Communication. It examines how the ecological characteristics of native tree species are symbolized and integrated into cultural practices. Using fieldwork and multi-source data, the research analyzes the cosmic tree’s ecological prototypes and symbolic mappings in shamanic rituals. It applies Charles S. Peirce’s triadic sign model to deconstruct its semiotic structure, focusing on index, icon, and interpretant. Using Kress and Van Leeuwen’s visual grammar, the study investigates the tree’s representation in traditional embroidery, sculpture, and digital design. Cross-cultural comparisons reveal both differences and shared innovations between the shamanic tree and other cultural representations, offering insights into sustainable communication strategies for preserving cultural heritage through multimodal design. Keywords Northeast Asian Shamanic Culture, Cosmic Tree Symbol, Ecosemiotics, Visual Communication, Cross-Cultural Transmission Introduction 1.1 Research Background Shamanism, as a primordial religious system originating in prehistoric times, stands among the oldest and most enduring spiritual traditions in human history. At its core lies the belief in animism the notion that every element of the natural world, whether trees, rivers, or animals, possesses a distinct spiritual essence. This animistic worldview not only shaped early cosmological understanding but also provided a foundational framework for articulating the human–nature relationship. In the Northeast Asian region (which includes Northeast China, Mongolia, the Korean Peninsula, and the Russian Far East, Fig. 1) this cultural paradigm is particularly prominent within the shamanic traditions of Tungusic, Mongolic, and other indigenous groups. Figure 1: Forest Coverage in Northeast China Source: 星球研究所 The cosmological framework of shamanic culture positions the “tree” as a central element in both ritual practice and visual symbolism, establishing a vertical axis that connects the celestial, terrestrial, and human realms. This symbolic form commonly referred to as the Cosmic Tree or Axis Mundi serves simultaneously as a concrete representation of ecological reality (e.g., Pinus sylvetriformis, Spruce) and as a visualized expression of spiritual belief. While existing scholarship has extensively explored the religious functions of the shamanic tree (Eliade, 1964) or its symbolic narratives within singular cultural contexts, it has largely overlooked the dynamic interplay between its ecological foundations and its visual grammar. Against the backdrop of emerging ecosemiotic theory and multimodal visual communication studies, there is a pressing need to deconstruct the symbolic logic of the shamanic tree from an interdisciplinary perspective specifically, to examine how natural properties are transfigured through artistic practice into enduring cultural mythologies. 1.2 Research Objective This study aims to investigate the transformation of the shamanic tree symbol from ecological prototype to cultural emblem within the shamanic traditions of Northeast China, employing an ecosemiotic framework. It further applies visual communication theory to uncover how this symbol adapts to and functions within cross-cultural modes of transmission. 1.3 Research Questions This research addresses three core questions: (1) How do the ecological characteristics of tree species native to Northeast China (such as the height of the Pinus sylvetriformis and the evergreen quality of the Spruce) inform the form and meaning of the cosmic tree symbol? (2) How does its visual grammar (specifically axial symmetry and color coding) mediate and express cosmological narratives? (3) In what ways can traditional symbols be semantically reinterpreted through contemporary design for global cultural contexts? 1.4 Significance of the Research At the theoretical level, by centering on the ecological and cultural specificity of Northeast China, this study constructs a four-dimensional analytical model “Nature→Symbol→Visual→Communication” which offers a methodological innovation for the study of regional cultural symbolism. At the practical level, by tracing the contemporary transformations of the shamanic tree symbol, the research proposes new paradigms for the living transmission and global articulation of Northeast Asian cultural heritage, aligning with UNESCO’s dual imperatives of cultural diversity and ecological sustainability. Theoretical Framework 2.1 An Ecosemiotic Perspective Ecosemiotics, situated at the intersection of cultural semiotics and the environmental humanities, underscores the co-creative dynamics between natural systems and sign systems. Centering on the bidirectional exchange of meaning between nature and culture, ecosemiotics posits that ecological properties become integral to cultural construction through processes of symbolization. Drawing on Peirce’s triadic model of the sign, this study deconstructs the shamanic tree symbol into its representamen, object, and interpretant. Within this framework, the material characteristics of tree species are encoded into cultural symbols via shamanic rituals and artistic practices, thereby enacting a “Nature → Sign” transformation. For instance, the vertical stature of the Changbai pine is imbued with the religious significance of “linking the three realms,” while its ecological symbiosis with avian species is reconceptualized as a visual metaphor for “soul migration.” By incorporating an ecosemiotic lens, this research gains both a methodological tool for dissecting the mechanisms of symbol formation and a means to illuminate the active role of natural landscapes in cultural memory. Table 1. Deconstruction of the Shamanic Tree Symbol Representamen Object Interpretant Vertical morphology of the Changbai pine Temperate forest ecosystem Symbol of the cosmic axis Source: Prepared by the author. 2.2 Visual Communication Theory The study of visual communication has evolved from functional transmission models to multimodal analytical paradigms. Kress and Van Leeuwen’s Visual Grammar framework integrates elements such as composition, modality and information value into the semiotic domain, emphasizing that images possess both syntactic structure and rhetorical function. Within this paradigm, the visual is not merely a passive means of display but an active system for constructing cultural meaning. In the case of the World Tree, its visual manifestations—axial symmetry, vertical ascending linear structures, symbolic color schemes and decorative motifs all serve distinct visual-grammar functions and interlock with the action sequences and spatial arrangements of shamanic rituals to form a compound visual embodied–cultural nexus. Moreover, visual communication theory offers a multimodal fusion perspective, facilitating an understanding of how traditional imagery may be deconstructed and reconstituted within digital contexts. 2.3 Theoretical Integration To

Dr Nong Shim Ningbo University China Abstract This study explored the use of AI in a foreign language (FL) writing by foreign language majors at Faculty of languages and translation, King Khalid University. The role of translation, and specifically online translation tools (OLT). The present study tried to document students’ existing use free online translation (FOT) tools, and their views about these tools. The tools of the study involved video observations and questionnaires regarding FOT use. Twenty-one university students enrolled in a writing course.  Follow-up interviews were done with the students who were observed using FOT tools widely on the video recordings. Results indicated those students have a primarily positive attitude toward FOT tools. In addition, most of students said that they use such tools frequently. Results are discussed in the context of the continuing debate over whether and how translation technology should be used in FL classrooms. These findings show the importance of providing teachers and students with instruction on (FOL), as well as the need for additional research on the effects of AI on writing acquisition. Keywords Artificial Intelligence, Elementary School Students,Free Online Tools, Translation, Writing Skill The Development of Artificial Intelligence Artificial Intelligence (AI) had appeared a long way since the presence of AI research in the 1950s when Turing developed the well-known Turing Test to inspect whether machines could think. Early trends in AI research displayed a philosophical difference between Weak AI and Strong AI. The vision of AI as a building system that can think like humans was known as Strong AI. Interchangeably, allowing systems to work without figuring out the difficulties of human thinking was seen as Weak AI (Marr, 2018). Strong AI has been thought as a threatening perception, since it aims to reproduce human intelligence and take over control from humans. The definition of twenty-first-century of AI has been reformed as follows: AI is “a science and a number of computational technologies that are inspired by—but usually operate quite differently from—the ways people use their nervous systems and bodies to sense, learn, reason, and take action.” (Stone et al., 2016). We do not have enough knowledge about the complications of human cognition to approximate it via machines. That being said, as research has progressed, it has moved beyond the perspectives of Strong and Weak AI. A third objective of AI is to build models based on human cognitive without the end goal of reproducing difficult human thinking (Marr, 2018). One such new development related to this third objective is the “partnership on AI to benefit people and society.” This partnership was cofounded in 2016 by Amazon, IBM, Google, Facebook, and Microsoft to study how AI is being used, and to examine AI’s influence on people and society. (Hern, 2016). By creating an open platform for discussions, this partnership sets up a type of transparency for studying the big influence of AI. Stanford University showed a “100-year report on AI” in 2016. By providing historical documentation and future directions, this report released to examine eight factors related to AI, containing the factor of education. While AI provided great promise for language learning, the early work of AI lessened because of its limited ability to promote deep learning. Today, AI has permeated many aspects of everyday lives, from smart applications on our mobile devices to self-driving cars. (Stone et. al, 2016). For a long time translation and language learning developed together as the grammar translation model used to teach languages, mainly for reading and writing knowledge was applied to the teaching and learning of languages. The separation between grammar-translation models and theories of foreign language acquisition resulted to the development of communicative teaching methods to language learning and teaching during the last half of the 20th century. This does not mean translation has disappeared from the classroom, however. Wilkerson (2018) shows that even when the instructor aims to use the target language, English is frequently used to translate classroom dialogue. While the place of the native language in the classroom language is the subject of continuing debate–see, for example, Rell (2015)– ,mentioned that “the activities and teaching strategies outlined here are intended to encourage student reflection on the translation method and on the changes between languages and not to replace communicative learning and teaching in the target language”. While translation is inattentive from modern teaching methods, the training and profession of translation are alive. With globalization has come a bad need to translate texts ranging from employee handbooks to television programs. Also, advances in natural language processing and the increasing of the Internet have presented into the world of translation a new tool: Web-based machine translation (WBMT). The automatic online translators, including Google Translate, and FreeTranslation.com, were originally designed to give customers a basic translation of Web pages or short texts written in another language; and most center on the translation of English writings into other languages. Recently, however, WBMT has found a new user in the foreign language student. Williams (2016) The Role of Translation in Language Teaching and Learning  Laviosa (2014) declares the reintroduction of translation as an educational tool in the FL classrooms in academic settings. She believes that the re-emergence of translation in the FL classrooms is easily justified in light of the current changes in FL teaching and learning methods and Applied Linguistics. According to her, cultural variety in today’s globalized world and multicultural educational schemes has changed the relationship between culture— as a unified individual personality— and language learning. The use of L1 in FL learning environments is becoming more of a traditional method than two or three decades ago. Web-based Machine Translation (WBMT) in the English Language Classes: Problems and Solutions Language specialists are conscious of the deficiencies of all types of machine translation (MT), as expressed briefly in Barreiro and Ranchhod (2015): “the most clear failure of MT is that it is unable to render publication-ready text” (p. 3). Williams (2016) quotes various examples of incorrect English-French translations produced by WBMT, all associated with problems of

1This research is supported by the Research Grants Council Committee of the University Grants Council of HongKong ((1) General Research Fund (GRF) Project No. 844012 “Quadrasyllabic Idiomatic Expressions (QIEs) in Chineseand neighboring Languages: An Investigation into Linguistic and Cultural History” and (2) GRF Project No.148908 “AQuantitative and Qualitative Comparison of Word Formation in Modern Standard Chinese and Early Modern Chinese”).I am grateful for comments leading up to this paper from co-investigators in the two projects: Andy Chin, HintatCheung, and particularly Shin Kataoka who has drawn my attention to many of the examples in this paper.39On the other hand, when two related languages have dissimilar terms to express similar objects orevents, then the difference could well represent salient non-linguistic variations. For example, theword for government in Indonesia is Pemerintah and in Malay Kerajaan. In the latter case ofMalay, the word reflects the structure of government involving constitutional monarchy (asindicated by “Rajah”) whereas the case of Indonesian reflects an organization structure presidedover by a leader. The form Selamat means “hello” in Indonesia and Malaysia, originating fromSemitic languages: Arabic Salam “peace” e.g. Salaam Alaikum “peace be with you” and HebrewShalom (peace). But in the Philippine languages, it means “thank you”. This shift of meaning maynot be unreasonable if we consider the broader context of language contact interaction in which wefind the universal and customary conversation opening and closing moves, which are the same inIslamic societies (Salaam Alaikum), in stark contrast to English (with hello-hi and goodbyerespectively) and other languages. In the exchange of identical but multifunctional pragmaticexpressions during the opening and closing communicative moves among participants, a possiblesemantic switching taking place could be understandable.In Asia, two long standing major classical traditions have been recognized:(I) Sanskrit base [Indosphere2]Devanagari, on which the Sanskrit writing system is based, has influenced the writing systems ofIndosphere languages of the South Asian subcontinent, Burmese, Thai, Lao, Tibetan etc, but notIndonesia and Malaysia in which once dominant Hindu Kingdoms in the Indonesian archipelagohave given way to Islamic sultanates, with exceptions to be found in Bali, for example. In theselanguages, there has not been much evidence of the Indic past in non-materialistic terms, other thanloan words, while Jawi, the script derived from Arbic, still survives.(II) Sinitic base [Sinosphere]Its emblematic logographic writing system has greatly influenced the historical development ofSinosphere writing systems in Japan, Korea, Vietnam, and among other ethnic groups like the Nasietc, on which the associated classical traditions, including the Chinese classical language have hadsignificant impact. Thus their students to this day are often exposed to literary classics of Chineseorigin such as the Chronicles of Three Kingdoms (三國演義) and Water Margin or All Men andBrothers (水滸傳). This tradition bears interesting comparison with the lesser trend of students inThailand, Laos, and Cambodia (but not Indonesia or Malaysia) studying the Indic epic Ramayama.One distinctive feature of languages associated with Sinosphere is the importance given torelatively unique idiomatic expressions such as 不三不四 [not-3-not-4] “improper”, similar toEnglish “neither fish nor fowl” but with stronger negative connotations. For example, civil servantsin Japan, Korea and Vietnam, in order to gain promotion, have to take language examinations inwhich there are expectations on familiarity with such expressions. This is often seen as a difficultand arduous task because of the drastic typological linguistic differences between Japanese, Koreanand Vietnamese on the one hand, and Chinese on the other hand. Thus, considerable efforts have tobe made by the civil servant aspiring to promotion.It is interesting to note that whereas Korea and Japan, for example, have adopted the Chineselogographic writing system, and have even incorporated it into basically at one time or another 2 Matisoff (1990) proposed the terms Sinosphere and Indosphere to distinguish between two major and oftensuperimposed cultural traditions within Asia.40bimodal writing systems. On the other hand, related languages such as Mongolians and Manchusswitched to the Chinese language when they conquered all of China, rather than imposed their ownlanguage as the native language, with possible adaptation or adoption of the logographic script.There were some minor unsuccessful attempts such as that by the Kitan Kingdom (契丹) whichdeveloped a demotic script, and the use of Phags-Pa script of the Mongols, which though squarishin shape and written from right to left, was much more influenced by the writing system of theTibetans who have shared Lamaism as a common religion. 3This is because in puritanical times, churches would have been good examples of frugality and so there would nothave been much leftover for the resident mice there. The use of QIE in Chinese is pervasive in many domains of discourse and language use. Forexamples:(13) Greetings: 好久不見 [very-long-no-see] “long time no see”, 不見不散 [no-see-no-disperse] “wait until we meet”(14) Slogans: 安全第一 [safe-whole-number one] “safety is top priority”, 酒後勿駛[drink-after-don’t-drive] “don’t drive if you drink”(15) Movie names: 窈窕淑女 [slim-fit-gentle-lady] “My Fair Lady”, 浩劫重生[calamity-again-alive] “Cast Away”(16) Advertisement (Real Estate): 全海靚裝 [all-sea-beautiful-renovation] “fullseaview”, 樓皇氣派 [building-emperor-air-atmosphere] “imperial bearing”Chinese QIEs are relatively distinct linguistic structures, standing out from regular language,comparable to the use in English of Latin or Latinate expressions Lacuna/ lacunae; Caveat emptor.Specifically, some defining characteristics of QIEs may be summarized as follows:a) Four syllables or logographsb) Relatively fixed structure and patternsc) Figurative meaning and semantic opacityThe quadrasyllabic structure draws on a basic disyllabic propensity in Chinese, reflecting, forexample, a common reduplicative tendency in addressing close relatives:媽 ma à 媽媽 ma-ma “mother”爸 ba à 爸爸 ba-ba “father”姐 jie à 姐姐 jie-jie “sister”The quadrasyllabic propensity is further evidenced by contractions from pentasyllabic expressions,for examples: (17) 傻人有傻福 à 傻有傻福[Silly-person-has-silly-blessing] à [silly-has-silly-blessing]“Innocence is blessing”(18) 新瓶裝舊酒 à 新瓶舊酒[New-bottle-contains-old-wine] à [new-bottle-old-wine]“New wine in old bottle” 4Zhu-ge-liang 諸葛亮 and Kong-ming 孔明 are names of the same minister whose wisdom is legendary from theChronicles of the Three Kingdoms. In everyday language, quadrasyllabic, pentasyllabic expressions or expressions ofother length may be found but the more frequent use of the former, especially in more formal discourse, would signifyerudition.43QIEs involve discoursal opacity, which entails metalinguistic ability to differentiate between literaland metaphorical usage, which in turn can draw on logical deduction and can project positive ornegative polar sentiments as rhetorical devices. For instance, the QIE 孤男寡女 [lonely-mansingle-woman] “unmarried couple” has negative