Traditional Theory Research Articles

Re-Evaluating Components of Classical Educational Theories in AI-Enhanced Learning: An Empirical Study on Student Engagement

The primary goal of this research was to empirically identify and validate the factors influencing student engagement in a learning environment where AI-based chat tools, such as ChatGPT or other large language models (LLMs), are intensively integrated into the curriculum and teaching–learning process. Traditional educational theories provide a robust framework for understanding diverse dimensions of student engagement, but the integration of AI-based tools offers new personalized learning experiences, immediate feedback, and resource accessibility that necessitate a contemporary exploration of these foundational concepts. Exploratory Factor Analysis (EFA) was utilized to uncover the underlying factor structure within a large set of variables, and Confirmatory Factor Analysis (CFA) was employed to verify the factor structure identified by EFA. Four new factors have been identified: “Academic Self-Efficacy and Preparedness”, “Autonomy and Resource Utilization”, “Interest and Engagement”, and “Self-Regulation and Goal Setting.” Based on these factors, a new engagement measuring scale has been developed to comprehensively assess student engagement in AI-enhanced learning environments.

Boosting third-order optical nonlinearity in ITO/Au multilayer films via interfacial effects

We present the enhancement of third-order optical nonlinearity in indium tin oxide (ITO)/Au multilayer films via interfacial effects. The overall thickness of prepared ITO and Au layer was kept as 200 nm and 14 nm, respectively, and thus multilayers are 214 nm, i.e., for the sandwich structure ITO/Au/ITO, the thickness of ITO and Au is 100 nm and 14 nm, respectively, while the thickness of ITO and Au is 40 nm and 3.5 nm in the nine-layer films composed of five layers of ITO and four layers of Au. The measured nonlinear refractive index (n2) and absorption coefficient (β) of the multilayers rise as the number of layers increases. The maximum n2 and β in the nine-layer film are 2.6×10−14 m2/W and −3.7×10−8 m/W, which are 3.8 and 2.3 times larger than the values in the pure ITO film, respectively. Such enhancement of optical nonlinearity as the number of layers increases originates from the increase of carrier concentrations in multilayers due to contact of metals/semiconductors (interfacial effects), not following the traditional effective media theory and epsilon-near-zero effect. The results pave a way to modulate the optical nonlinearity in special metal-dielectric multilayers of interfacial effects and indicates the promising applications in nonlinear photonics.

Portfolio Optimization Strategies: New Approaches Based on Machine Learning Forecasting

This study provides an in-depth discussion and comprehensive review of the latest applications of machine learning techniques in the field of portfolio optimization. The article begins with an overview of traditional portfolio optimization theory and its limitations, and then focuses on how machine learning predictive models, which have flourished in recent years, can provide new perspectives and tools for solving the problems of non-linearity, dynamics and uncertainty in investment decision-making. This paper provides a detailed overview of the application practices of various machine learning algorithms (e.g., deep learning, reinforcement learning, integrated learning, etc.) in the areas of asset return prediction, risk assessment, and optimal weight allocation, and analyses their advantages and challenges compared to traditional methods. The analysis of relevant research cases reveals the significant effect of machine learning predictions in increasing expected portfolio returns, reducing risk exposure, and achieving effective diversification. The study also explores possible future trends and potential research directions for machine learning in portfolio optimization, highlighting the importance of combining domain knowledge with big data-driven intelligent investment decisions. This review aims to provide financial scholars and practitioners with a new way of thinking about portfolio optimization, and to promote the combination of theoretical research and practical operation in the fields of financial engineering and investment management, so as to achieve more accurate and efficient investment decisions.

A Study on the Phenomenon of Conspicuous Consumption in South Korea’s Luxury Market Under Economic Uncertainty

This paper investigates the phenomenon of conspicuous consumption in South Korea’s luxury market under conditions of economic uncertainty. While traditional economic theories suggest that luxury spending should decrease during periods of financial instability, the South Korean market demonstrates a contrasting trend, where luxury consumption not only persists but often intensifies. Through qualitative interviews with consumers, industry experts, and market analysts, this study explores the cultural, social, and psychological factors driving this behavior. The findings reveal that social status, identity, and emotional coping mechanisms play crucial roles in sustaining luxury consumption, even amidst economic downturns. Furthermore, the influence of K-Culture and social media amplifies the desire for luxury goods, especially among younger consumers. The study also highlights the complex interplay between economic variables, such as GDP growth, unemployment rates, and consumer confidence, and their impact on luxury spending patterns. This paper contributes to a deeper understanding of the unique dynamics at play in the South Korean luxury market and offers insights for luxury brands, marketers, and policymakers to develop effective strategies in this rapidly evolving environment.

Strategies for Online Market Entry: The Role of Network Anchors in China’s Live Streaming Sales Ecosystem

ABSTRACT Purpose This study explores the strategic implications of live-streaming sales and network anchors in China’s e-commerce landscape, particularly focusing on how different types of network anchors influence consumer trust and purchasing decisions. Methodology/approach A scenario-based experimental design was employed, utilizing a 2 x 2 factorial structure to analyze the effects of network anchor types (celebrity anchors vs. internet celebrity anchors) and product types (search goods vs. experience goods) on consumer behavior. Data were collected from 500 participants through an online survey, ensuring a robust statistical analysis of the main and interaction effects. Findings The results reveal that celebrity anchors generate significantly higher levels of consumer trust and purchase intention for search goods, while internet celebrity anchors are more effective for experience goods. Trust was found to play a partial mediating role in these relationships, particularly for experience goods. Research implications The study contributes to the existing literature by integrating traditional endorsement theories with the modern context of live streaming, offering new insights into the differential impacts of network anchor types across various product categories. It also highlights the need for a nuanced understanding of consumer trust in digital marketplaces. Practical implications Marketers and online enterprises can leverage these findings to optimize their live-streaming strategies by aligning the choice of network anchors with the specific characteristics of the products being promoted. This strategic alignment can enhance consumer engagement, trust, and ultimately, purchase intentions. Originality/value/contribution This research advances the theoretical discourse on digital marketing by elucidating the complex interplay between network anchor types, product characteristics, and consumer trust. It offers a comprehensive framework for understanding and optimizing live-streaming sales strategies in the context of China’s rapidly evolving e-commerce environment.

Study of interfacial competitive distribution and synergistic permeation in nanofiltration separation of Salvia divinorum acids from the aqueous extract

The contact between solution and membrane during nanofiltration separation produces the interfacial layer fluid, and the competitive distribution laws of solutes in the interfacial layer are difficult to be analyzed, giving rise to diversified separation results that are challenging to explain using traditional nanofiltration separation theory. Four Salvia divinorum phenolic acid components—sodium salvinorin, protocatechuic aldehyde, rosmarinic acid, and salvianolic acid B—which have gradient relative molecular masses and dissociation constants, were selected as the objects of study. The nanofiltration separation parameters, such as membrane flux and permeation rate of the Salvia divinorum phenolic acids and their variability with the monomer solution under the complex solution environment were systematically analyzed. Based on the correlation between the concentration of the interfacial layer and the initial concentration, membrane flux and mass transfer coefficient in the theory of concentration polarization, the concentration of the interfacial layer of the nanofiltration membrane was calculated. This was combined with the state of association characterized by the distribution of particle sizes in the solution, the research model based on the ‘Associative State-Interfacial Competition-Separation Behavior’ was constructed, and the competitive and synergistic membrane separation regulations of the constituents of salvia phenolic acids were clarified. In acidic solutions, van der Waals forces dominate the interfacial competition, and of the four phenolic acids, salvinorin acid B diffused most easily to the membrane surface, showing that the component with the larger relative molecular mass inhibited the penetration of the smaller component; In alkaline solution, Coulomb force and Van der Waals force together dominate the interfacial competition, and the more acidic sodium salvinorin, etc., would preferentially react with hydroxide. At the same time, combined with the feature that the more molecular states in the particle size distribution of the solution are more likely to form aggregates, it was proven that the dissociation of protocatechuic acid aldehyde was inhibited, and its molecular state was more complete. It was shown that the more acidic sodium salvinorin and others facilitated the less acidic protocatechuic aldehyde to pass through the membrane.

Artistic Living for the Elderly of Shanghai

Over-60 seniors in Shanghai have at their disposal arts courses, community activities, and arts education, all geared toward their physical and mental well-being, according to the traditional Chinese theory of “artistic living.” If current university programs for the elderly accurately identify the artistic needs of the elderly, further individualizing curricula and holding more varied events at community centers, it would help to solve elderly people’s anxieties around loneliness and social marginalization, while allowing them to live in harmony with nature.

Research on a new method for the degree of freedom analysis of parallel mechanism

At present, traditional analysis methods sometimes show incompatibility when analyzing the degree of freedom (DOF) of parallel mechanisms. In this research, a new DOF analysis method (MV-DOF method) based on primary-ancillary motion theory is developed. The 4PPRRR series-parallel mechanism is taken as an example, the analysis results by using the MV-DOF method are compared with those of traditional inverse helix theory and modified Grübler-Kutzbach formula, respectively. The comparison shows that this MV-DOF method can always analyze the DOF of the 4PPRRR series-parallel mechanism accurately, while the other two traditional methods show inapplicability sometimes. During the analysis, an important rule is also found that the ancillary motion is equivalent to local constraint helix motion, but it is not always true in turn. Based on this MV-DOF method, a DOF cutting analysis way is also suggested. Any output point on a complex mechanism can be taken as a cutting point, along which the mechanism can be cut into two independent sub-mechanisms. The output DOF of each sub-mechanism can be analyzed separately by using the MV-DOF method, then the intersection can be obtained as the DOF of the whole mechanism at this output point. This research provides a new and effective analytical way for DOF analysis of parallel mechanisms.

The steady-state solution of wave–current interaction based on the third-order Stokes wave theory

This manuscript reports on the interaction of a current-free monochromatic surface wave field with a wave-free uniform current field. The existing reasonable theories of wave–current interactions are primarily based on weak current assumptions and derived from linear theory, resulting in calculation bias in the analysis of nonlinear wave–current interactions. Moreover, experimental data on high-order wave–current interactions still need to be collected. Thus, steady-state solutions named the third-order wave–current theory based on the third-order wave dispersion relationship and the principle of wave–current energy conservation were derived. The wave–current interaction experiment was set up to cover 164 sets of experimental conditions, including 33 types of periodic waves from the second to the fifth order and six different current velocities. The effects of water depth, current velocity, wave period, and height on the wave height and wavelength in the wave–current interaction field were investigated. A comparison of the mean relative error (MRE) and the determination coefficient (R2) of the wavelength with the experimental data revealed that the third-order wave–current theory outperformed the traditional linear theory, with an optimal reduction of 75% and an enhancement of 25%, respectively. Additionally, the third-order wave–current theory reduces the MRE by 25%–40% in the wave height calculation, with R2 consistently outperforming the linear theory. The third-order wave–current theory can significantly improve the calculation accuracy of the theoretical method in solving nonlinear wave–current interactions.

Digital transformation, information and lending distance -Evidence from Chinese bank branch data

This research aims to empirically investigate the relationship between bank digital transformation and lending distance. In traditional financial geography theory, banks have a natural geographical proximity preference in their credit decision-making, which might lead to suboptimal credit allocation. Can the rapid development of digitalization improve the situation that banks are only capable of undertaking ex ante due diligence and ex post monitoring of proximate borrowers, given that fintech has greatly improved the overall efficiency of the financial industry? Using bank loan data of listed enterprises in China from 2013 to 2021, this paper finds that the digital transformation of banks can significantly extend the lending distance between banks and enterprises. The moderating effect analysis suggests that distance extending effect of bank digitalization is more pronounced for firms with poor information quality and in competitive banking sector. Further, digital transformation extends the lending distance without increasing risk preferences, as evidenced by the empirical finding that the non-performing loan ratio remains unaffected by the increased distance. Also, geographical expansion in lending distance reduces loan concentration. The research in this paper supports the conclusion that banks' digital transformation positively impacts corporate credit allocation and is beneficial to achieving financial stability by improving loan performances.

The impact of real estate market risks on the issuance costs of urban investment bonds: Evidence from China

It has been widely believed that bond spreads are positively correlated with related market risks. However, some studies in China's urban investment bond (UIB) market indicate that an increase in real estate market risks usually narrows UIB spreads. This article focused on such puzzle and introduced a quadratic form regression to detect a U-shaped relationship between housing price volatility and UIB spreads, which confirms that UIB pricing is actually in consistence with the traditional bond theory. We further indicated that spreads of guaranteed UIBs were barely affected by housing price volatility, and fiscal transparency seemed to mitigate such volatility's impact on the issuance costs of UIBs. Those findings not only illuminate ways of mitigating risks in the UIB market in China using market instruments but also have important implications for how local governments around the world can mitigate their debt-related problems.

Scientific exploration and hypotheses concerning the meridian system in traditional Chinese medicine

The meridian theory is an important component of traditional Chinese medicine, playing a crucial role in disease diagnosis, treatment, and health preservation. Serving as the media for the effects of acupuncture, moxibustion, herbal medicine, and acupressure massage, meridians exert undeniable impact on the human body. However, the essence of meridians remains a topic of debate. Recent research has primarily focused on their anatomical structures, leading to numerous hypotheses. Simultaneously, other researchers have approached this subject from an energetic perspective, discovering information interactions within the meridian system. These findings suggest that meridians possess both physical and information dimensions, indicating that a singular approach to their study is insufficient. To bridge this gap, a shift from purely structural research toward an exploration of the information aspects of meridians is necessary. By integrating this information approach with traditional meridian theory, it may be possible to develop a new, modernized meridian theory that is aligned with contemporary concepts, making it more accessible and applicable in clinical settings.

Exploring resveratrol against Alzheimer's disease and Parkinson's disease through integrating network pharmacology, bioinformatics, and experimental validation strategy in vitro

BackgroundThe study aims to investigate the pharmacological basis and molecular mechanisms of resveratrol in the treatment of Alzheimer's disease (AD) and Parkinson's disease (PD) through the approach of treating different diseases with the same method, guided by traditional Chinese medicine theory. Utilizing network pharmacology and bioinformatics methods, this research aims to provide modern medical evidence for the theory of treating different diseases with the same method in traditional Chinese medicine. MethodsOmnibus from Swiss Target Prediction, TCMSP, SuperPred, SEA, HIT, CTD, TCMIP and Gene Expression Disease datasets for resveratrol related genes, Alzheimer's disease, and Parkinson's disease were obtained from the GEO database. Core targets were identified by weighted gene coexpression network analysis (WGCNA) and minimum absolute contraction and selection operator (LASSO). The expression of core targets was verified in AD and PD cell models. The immune characteristics of AD and PD were analyzed by CIBERSORT algorithm. Finally, the potential mechanism of resveratrol intervention on the core target was studied by molecular docking technique. ResultsThe results of network pharmacological analysis showed that resveratrol acted on 85 common targets such as STAT3 and CASP3, affected AGE-RAGE signaling pathway and PI3K-Akt signaling pathway, and showed the effect of "same disease and different treatment" for AD and PD. Three core targets associated with AD and PD (PLK4, FCGRT, and PRKAR2A) were finally identified through comprehensive transcriptome analysis, and experimentally verified in cell models of AD and PD. At the same time, the analysis of immune cell infiltration suggested that AD and PD had dysregulation of inflammation, and the core target was significantly related to M2 macrophages. ConclusionResveratrol may play a potential mechanism of "treating the same disease with different diseases" and target three core targets (PLK4, FCGRT and PRKAR2A) to improve the disease process of AD and PD by participating in the regulation of immune and inflammatory pathways. These findings have potential implications for clinical practice and future research.

The Inhibitory Impact of a Co-Assembly Gel with Natural Carrier-Free Binary Small Molecules, as Used in Traditional Chinese Medicine, on the Viability of SW1990 Cells.

Chinese herbs are a huge treasure trove of natural products and an important source of many active molecules. The theory of traditional Chinese medicine compatibility (TCMC) is widely applied in clinical practice, but its mechanism is still ambiguous. This study aims to open a new window for this predicament by studying the interaction between the main active ingredients from a drug pair. Carrier-free assembly of natural products improves the shortcomings of traditional nanodelivery systems and opens a new path for the development of new nanomaterials. The drug pair "Pueraria and Hedyotis diffusa" has been commonly used in clinical practice, with a predominant therapeutic effect. This study is devoted to the study of the binary small molecule co-assembly of the main active molecules from the drug pair. In this study, we introduce a carrier-free composite gel, formed by the co-assembly of puerarin (PUE) and deacetylasperulosidic acid (DAA) via non-covalent bonds including π-π packing, intermolecular hydrogen bonding, and C=O π interactions. With a strain point 7-fold higher than that of P gel, the P - D gel exhibited favorable rheological properties. The survival rate of SW1990 cells in the P - D group was only 21.39% when the concentration of administration reached 200 μM. It thus demonstrated activity in inhibiting SW1990 cells' survival, suggesting potential in combating pancreatic cancer. Furthermore, this research offers a valuable concept for enhancing the mechanical properties and bioactivity of hydrogel materials through the utilization of a multi-component natural small molecule co-assembly approach. More importantly, this provides new ideas and methods for the treatment of pancreatic cancer and the analysis of traditional Chinese medicine compatibility theory.

Determinants of Utilization of Home-Based Care in Kisumu County.

Purpose: To examine the factors influencing the utilization of Home-Based Care in Kisumu Central. It examined the influence of predisposing factors, enabling factors, the environment and Health Behaviors on utilization of Home-Based Care. Methodology: This was a mixed research design which employed both qualitative and quantitative methods to examine and characterize the elements that impact the use of home-based care. The study samples consist of 120 respondents selected from among home based care users. The data was collected through structured questionnaires that were self-administered to home-based care users. The collected data was quantitative and analyzed using descriptive and statistical tools like SPSS (version27). The findings were displayed in tables. Descriptive statistics, Bivariate correlation and multivariate regression models were utilized to determine the relationship between the independent and dependent variables. Findings: The study found that predisposing factors, enabling factors, the environment and health behaviors were significant factors influencing the utilization of home-based care in Kisumu Central Sub County with significant p=.000 each. Unique contribution to theory, practice and policy (recommendations): Theory: The study challenges traditional theories by demonstrating that predisposing factors, enabling factors and the environment are more significant than health behaviors in influencing Home-Based Care utilization. Policymakers should implement strategies that target investments in and support for Home Based Care as a vital component of healthcare delivery, particularly for individuals with chronic illnesses and those requiring personalized and accessible care within their homes.

Systematic Improvement of Quantum Monte Carlo Calculations in Transition Metal Oxides: sCI-Driven Wavefunction Optimization for Reliable Band Gap Prediction.

Accurate determination of the electronic properties of correlated oxides remains a significant challenge for computational theory. Traditional Hubbard-corrected density functional theory (DFT+U) frequently encounters limitations in precisely capturing electron correlation, particularly in predicting band gaps. We introduce a systematic methodology to enhance the accuracy of diffusion Monte Carlo (DMC) simulations for both ground and excited states, focusing on LiCoO2 as a case study. By employing a selected configuration interaction (sCI) approach, we demonstrate the capability to optimize wavefunctions beyond the constraints of single-reference DFT+U trial wavefunctions. We show that the sCI framework enables accurate prediction of band gaps in LiCoO2, closely aligning with experimental values and substantially improving traditional computational methods. The study uncovers a nuanced mixed state of t2g and eg orbitals at the band edges that is not captured by conventional single-reference methods, further elucidating the limitations of PBE+U in describing d-d excitations. Our findings advocate for the adoption of beyond-DFT methodologies, such as sCI, to capture the essential physics of excited-state wavefunctions in strongly correlated materials. The improved accuracy in band gap predictions and the ability to generate more reliable trial wavefunctions for DMC calculations underscore the potential of this approach for broader applications in the study of correlated oxides. This work not only provides a pathway for more accurate simulations of electronic structures in complex materials but also suggests a framework for future investigations of the excited states of other challenging systems.

Analysis of the Mechanisms Behind the "China Money Mystery"

The growth rate of China's broad money supply (M2) significantly exceeds the combined rates of economic growth and inflation, leading to a continuous rise in the ratio of M2 to GDP. This phenomenon is referred to as the "China Money Mystery." The explanation for this phenomenon involves several factors. Firstly, interest rate and exchange rate controls in the financial market lead to excessive increases in money demand. Secondly, financial repression results in excessive use of indirect financing and a lack of investment channels, further distorting money supply. Thirdly, the financial hoarding theory suggests that a large amount of money flows in the virtual economy rather than being invested in the real economy, thus failing to induce noticeable inflation. Finally, the applicability of traditional quantity theory of money in the modern credit money system is gradually diminishing, failing to explain the relationship between money supply and prices. By integrating these factors, a better understanding of the abnormal monetary supply phenomenon in China and its implications can be achieved.

Ideological Mind-Shaping or Brain-Shaping: Fusing Empirical Biopolitics and Political Philosophy of Mind

There are two primary philosophical approaches to examining the relationship between human bodies and political bodies. The first, reflected in traditional political theory on the body politic, is concerned with the question of how individuals aggregate into functioning or malfunctioning collectives—how singular citizen bodies come to constitute wider political entities. The second approach, maturing later in 20th century social and political philosophy, considers the opposite relation: instead of evaluating how the body politic emerges from the bottom-up, it focuses on how bodies become politicized from the top-down. This, more sociological, perspective explores how human bodies are disciplined and learn to self-discipline into particular physical forms and functions. Dominant ideologies can infiltrate the bodies of adherents, and the task of the social critic or political philosopher is to delineate how, why, where, and when political structures shape the minds and bodies of citizens, as well as whether the effects are coercive, destructive, or liberatory. I will argue that a political philosophy of mind cannot flourish without attention to the cognitive science of ideologies. Until recently there has been little serious dialogue between biology and political philosophy, partly due to disciplinary balkanization and mostly because of the infancy of empirical biopolitics, the science of how cognitive and neurobiological processes are molded by political ideologies. I will suggest that attending to the emerging science of ideological cognition can allow us to build a stronger, more compelling, and provocative thesis on the mind-shaping consequences of immersion in ideologies than is possible with conceptual tools alone

Pompeiu-Hausdorff Fuzzy <i>b</i>-metric Spaces Are Associated with a Common Fixed Point and Multivalued Mappings

The notion of fuzzy logic was introduced by Zadeh. Unlike traditional logic theory, where an element either belongs to the set or does not, in fuzzy logic, the affiliation of the element to the set is expressed as a number from the interval [0, 1]. The study of the theory of fuzzy sets was prompted by the presence of uncertainty as an essential part of real-world problems, leading Zadeh to address the problem of indeterminacy. The theory of a fixed point in fuzzy metric spaces can be viewed in different ways, one of which involves the use of fuzzy logic. Fuzzy metric spaces, which are specific types of topological spaces with pleasing ”geometric” characteristics, possess a number of appealing properties and are commonly used in both pure and applied sciences. Metric spaces and their various generalizations frequently occur in computer science applications. For this reason, a new space called a Pompeiu-Hausdorff fuzzy <i>b</i>-metric space is constructed in this paper. In this space, some new fixed point results are also formulated and proven. Additionally, a general common fixed point theorem for a pair of multi-valued mappings in Pompeiu-Hausdorff fuzzy <i>b</i>-metric spaces is investigated. The findings obtained in fuzzy metric spaces, such as those discussed in Remark 3.1, are generalized by the results in this paper, and additional specific findings are produced and supported by examples. The study of denotational semantics and their applications in control theory using fuzzy <i>b</i>-metric spaces and Pompeiu-Hausdorff fuzzy <i>b</i>-metric spaces will be an important next step.

Views, Knowledge, and Self-Reported Practices of Early Childhood Educators: Sociocultural Theory’s Practicability

Vygotsky's Sociocultural Theory is a well-known theory that focuses on the cognitive development by combining it with a social perspective. In the literature, Sociocultural Theory is seen as an alternative to the traditional theories of cognitive development in early childhood education. Teachers' perceptions of the theory may be important in the children's learning process. The current study aims to investigate the views, knowledge, and self-reported practices of early childhood educators regarding the practicability of Vygotsky’s Sociocultural theory. Phenomenological research design, as a qualitative research method, is applied. The data is collected through semi-structured interviews with early childhood educators who worked in private kindergartens in Ankara, and convenience sampling is used to reach the participants. Two researchers analyzed the data with the thematic analysis method. The findings show that although participants used some of the implications of the theory, they do not have explicit information about the implications, especially about the scaffolding and peer learning. It is recommended that more support and training regarding the theory, especially peer learning and scaffolding, should be offered to the in-service teachers.