Abstract: The accuracy of financing demand prediction has a direct impact on the return on investment and risk exposure in fintech investment and asset allocation. Nevertheless, the real world financial transaction data often displays significant nonstationary features — for example, cyclical fluctuations, event shocks, and short-term anomalies — which make the traditional forecasting approach unstable in the real investment scenarios. This study builds a data set that includes 34 reproducible variables — including daily financing requirements, transaction peaks, capital occupation duration, and risk exposure levels — on the basis of 180 consecutive days of investment and operating data from a leading financial services firm. It systematically compares ARIMA, Prophet, Random Forest, and XGBoost models for financing demand forecasting. Empirical results show that XGBoost maintains a low forecast error (MAPE of 8.2%) in the case of market fluctuations and unusual events, which reduces the average error by about 22% in comparison with the baseline model. Based on these results, a model is built to analyze the effect of forecast errors on the stability of investment returns and the efficiency of capital turnover. Results show that keeping the forecast error under 10% significantly reduces the risk of capital misallocation in times of high volatility, while at the same time improving the stability of overall investment returns. This study provides a reusable model workflow and engineering reference for the establishment of the investment allocation and risk management system of the financial institutions.

Abstract: Urban shrinkage, driven by demographic and socioeconomic change, has become a pressing issue across Europe, particularly in small peripheral towns and semi-urban settlements that have historically relied on a single industry or company. This study investigates the demographic and socioeconomic factors contributing to the decline in Latvian mono-towns, thereby filling a void in empirical research on urban development in post-socialist contexts. Principal component analysis (PCA) was applied to a set of key demographic and socioeconomic indicators derived from census and administrative data to identify the principal dimensions driving urban shrinkage. The analysis reveals three principal components explaining 87% of the variance: socioeconomic vitality (57.1%), population change and peripherality (17.2%), and aging society dynamics (12.6%). The results contribute to a nuanced understanding of how mono-functional urban contexts shape the intensity and character of shrinkage. These results establish a basis for specific policy measures designed to promote resilience in small-settlement settings and contribute to the understanding of spatial planning and regional development approaches in the post-socialist urban transition context. The research underscores the need for context-specific approaches to address the multifaceted challenges of urban shrinkage.

Abstract: Inequalities persist throughout the globalized world. The overall economies of the Global South pales in comparison to the Global North. The difference between the haves and have nots are becoming more and more pronounced as the free economy continues to operate. In this study, we try to determine the factors that affect the differing degree of prosperity gained from globalization. Although we understand that there are numerous factors that contribute to a country’s prosperity that do not relate to the psychology of its constituents, we theorize that human behavior and psychology defined by cultural differences play a major role in how countries take advantage of globalization. Identifying the cause for inequalities in globalization will allow governments to tackle the root causes of their challenges, creating a more productive global community.

Abstract:

Unregulated Housing (UrH) is a widespread urban phenomenon in Morocco, largely driven by rapid population growth and accelerated urbanization. It has expanded mainly on the outskirts of cities and within housing developments that already benefit from basic infrastructure and superstructure services. In response to this challenge, public authorities have adopted several urban planning instruments, particularly the Land Management Plan (LMP). According to Law No. 12-90 on urban planning, the LMP seeks to regulate urban expansion, improve the architectural and aesthetic quality of the built environment, and preserve the overall coherence of developed areas. As a legally binding planning document, the LMP establishes strict land-use regulations, and any breach of these rules constitutes an offence. Traditionally, detecting such violations requires on-site inspections by control officers, followed by the preparation of official reports submitted to the competent legal authorities. However, recent advances in aerial image acquisition and processing technologies provide powerful tools to improve and facilitate the monitoring of urban planning compliance. This paper proposes a conceptual framework that integrates artificial intelligence with urban planning regulations to enable the automatic detection of urban planning offences using RGB orthophotos covering areas subject to a Land Management Plan, relying on deep learning techniques.

Abstract: When tightly-knit communities suddenly show electoral volatility, does it signal weakening group identity, or does it reveal something deeper? This question matters wherever centralized authority structures shape bloc voting. Conventional wisdom interprets such shifts as boundary erosion. This paper presents evidence for the opposite.Drawing on an extreme-case design, I exploit a natural experiment — Israel’s 2019–2022 political deadlock — to track voter transitions within ultra-Orthodox communities, where ethnically distinct subgroups maintain near-total political separation despite shared religious practice. Using ecological inference on ballot-box data from five population centers across six elections (2019–2022), I find exceptionally high baseline party loyalty (90–95%), a dramatic disruption during the March 2020 – March 2021 transition when switching surged to 12–19%, and a swift return to high loyalty within 13 months — though the shifted voters remained with their new parties.The synchronized switch of voting loyalty across geographically dispersed cities, occurring without residential mobility, is consistent with elite-mediated bloc realignment rather than emerging voter independence. Paradoxically, the capacity for mass switching may reflect stronger, not weaker, institutional control.These findings challenge how scholars of party–voter linkages interpret electoral volatility in identity-based voting blocs: apparent instability may reflect disciplined coordination, and what looks like boundary erosion may actually reveal institutional strength operating through collective action.

Abstract: The global regulatory landscape is shifting from voluntary corporate social responsibility (CSR) to mandatory Environmental, Social, and Governance (ESG) disclosure. This study investigates the causal impact of mandatory ESG disclosure on firm value and operational decarbonization using a comprehensive balanced panel of 1,612 listed firms from the EU and the US between 2018 and 2025.Employing a Difference-in-Differences (DiD) design and an event study analysis, our empirical results yield three primary findings. First, consistent with Agency Theory, mandatory disclosure significantly increases firm value (Tobin’s Q) immediately following the 2021 regulatory shock (Post×Treat=0.5212, p< 0.01), indicating that standardized transparency reduces information asymmetry (H1). Second, we document a progressive and cumulative reduction in carbon intensity, providing robust evidence of substantive execution rather than mere ceremonial compliance (H2). The "downward-sloping" trajectory in the event study confirms that the mandate drives real-world operational transitions over time, refuting Decoupling Theory. Third, we find that internal governance mechanisms play a crucial moderating role in this transition (H3); the reduction in carbon intensity is significantly more pronounced in firms with higher board independence and established ESG committees. These findings suggest that "hard-law" transparency mandates effectively align corporate incentives with global climate goals. The synergy between external regulatory pressure and internal governance oversight is essential for bridging the "talk-walk" gap, offering critical implications for global policymakers designing the next generation of climate-related reporting standards.

Abstract: Living history tourism is traditionally framed through heritage preservation and edu-cational interpretation, yet the motivational mechanisms translating visitor engage-ment into behavioral commitment remain insufficiently theorized. This study develops and tests an integrated structural model conceptualizing living history environments as experiential systems operating under conditions of late-modern acceleration. Data were collected from 1,066 visitors at Skansen (Sweden) and analyzed using structural equation modeling. The findings indicate that detachment-oriented motives signifi-cantly activate experiential immersion, which emerges as the central psychological mechanism within the model. Immersion strengthens perceptions of historical authen-ticity and constitutes the dominant predictor of behavioral intention, whereas educa-tional motives exert a comparatively weaker effect. Mediation analysis demonstrates that the influence of escape on behavioral commitment operates indirectly through immersion, confirming a fully mediated experiential pathway. These results suggest that living history destinations function not primarily as didactic heritage platforms but as structured experiential environments enabling temporary disengagement from routine pressures. By integrating immersion, authenticity construction, and behavioral intention within a unified framework, the study repositions living history tourism as an experiential counter-space embedded in accelerated modernity.

Abstract: The integration of artificial intelligence (AI) and algorithmic decision-making into international relations represents a significant evolution that current theoretical frameworks have not fully accommodated. Established International Relations (IR) paradigms—realism, liberalism, and constructivism—typically conceptualize technology as a tool for statecraft rather than as an influential factor actively shaping the decision-making environment. This paper asserts that such a conceptual omission is increasingly untenable. Utilizing an integrative analysis spanning IR theory, AI ethics, security studies, and political economy, this work examines three principal aspects of "algorithmic diplomacy": (1) the ways in which algorithmic bias within systems operated by international organizations perpetuates structural inequalities between North and South; (2) the impact of AI incorporation into nuclear command and control systems on the logic of Mutually Assured Destruction (MAD) and crisis management timelines; and (3) the emergence of computational power imbalances in trade and climate negotiations as a novel form of diplomatic influence. The conclusion presents an initial framework for machine-mediated international relations and emphasizes the necessity for normative and governance responses at both national and multilateral levels.

Abstract: Smart city governance increasingly relies on AI-enabled planning systems, digital twins, vulnerability scoring tools, and capital investment prioritization platforms to allocate climate-resilient housing and infrastructure investments. Yet existing smart-urbanism and adaptation frameworks under-specify how such systems should encode (i) well-being, (ii) equity, and (iii) climate uncertainty in the decision logic that translates urban data into ranked projects and funded portfolios. This paper develops a governance-centered framework, Caring Urban AI, through a replicable conceptual synthesis that integrates research on (a) climate risk decision-making under deep un-certainty, (b) built-environment pathways relevant to psychosocial well-being, and (c) algorithmic accountability and fairness for public-sector decision infrastructures. The framework specifies a five-layer architecture linking (1) urban form and infrastruc-ture, (2) climate exposure and environmental resources, (3) psychosocial mediators of well-being, (4) algorithmic design choices (data, objective functions, equity constraints, uncertainty handling, documentation), and (5) institutional governance (procurement, auditing, participation, redress), with explicit feedback loops. The primary outputs are: (i) the five-layer Caring Urban AI architecture operationalized as auditable decision infrastructure; (ii) eight mechanism-based propositions that render the framework empirically testable via audits and quasi-experimental policy evaluations; and (iii) an operational specification guide illustrating objective-function forms, equity con-straints, robustness logic, and documentation artifacts for prioritization workflows. The analysis concludes that aligning Urban AI with SDG 11 requires treating well-being-supportive living conditions as a decision objective, constraining optimiza-tion with equity conditions, and institutionalizing auditability and contestability to prevent distributive and psychosocial harm in climate-resilient investment planning.

Abstract: Open Educational Resources (OER) are widely promoted as mechanisms for expanding access to knowledge and supporting sustainability in higher education. Yet their long-term viability remains constrained by fragmented governance, unstable funding arrangements, weak faculty incentives, policy gaps, and uneven digital infrastructure. This article develops a conceptual and policy-oriented framework that reconceptual-izes OER as sustainable knowledge commons embedded within higher education sys-tems rather than merely repositories of open content. Using an integrative review and thematic synthesis of global scholarship on OER sustainability, commons governance, and higher education policy, the study identifies four interrelated governance dimen-sions: institutional embedding, participatory stewardship, equitable access and inclu-sion, and long-term resource sustainability. The analysis shows that sustainable OER ecosystems depend not only on open licensing and technological platforms but also on coherent policy design, institutional alignment, academic recognition structures, and collaborative governance arrangements. Each dimension is associated with indicative governance mechanisms and policy indicators such as institutional OER strategies, faculty incentive programs, and shared digital infrastructure. The framework also recognizes institutional diversity, emphasizing that governance models must be adapted to different policy environments, academic cultures, and stages of OER adop-tion across higher education systems. By conceptualizing OER as governable knowledge commons, the article clarifies how open knowledge initiatives can con-tribute to social equity, educational resilience, and sustainable transformation in higher education.

Abstract: Background: Motivation research has generated many constructs, yet many theories remain structurally under-specified, relying on flexible verbal accounts or models whose functional form is optimized to data rather than fixed in advance. This limits falsifiability, cross-domain comparison, and principled failure. Theory: Lagun’s Law proposes a fixed six-variable structural equation of volitional drive specifying ignition gating, nonlinear amplification, divisive resistance, and an explicit variability term. The law is defined by its functional architecture rather than by any particular semantic interpretation or measurement instantiation. Objective: This study evaluates Lagun’s Law using straight structural validation: assessing whether a pre-specified equation exhibits recurring empirical signatures when applied without reparameterization, optimization, or post hoc modification. The aim is to test structural admissibility. Method: The equation was instantiated using pre-defined proxies across four independent secondary datasets spanning learning analytics, intelligent tutoring systems, naturalistic smartphone sensing, and laboratory neurophysiology. All proxies respected temporal precedence and outcome non-overlap. Where full instantiation was not possible, analyses were treated as reduced-form tests. Results: Recurring structural signatures were observed across all four datasets. Readiness functioned as a prerequisite rather than a graded predictor, divisive resistance effects were observed in three of four datasets, and independent behavioral variability persisted across contexts. Nonlinear amplification was directly testable in two datasets and attenuated or untestable elsewhere due to measurement constraints. Conclusion: These findings provide empirical grounding for Lagun’s Law as a structurally admissible constraint on volitional drive, clarifying its scope conditions and falsification pathways while avoiding claims of causality, universality, or optimal measurement.

Abstract: As the core pillar of basic disciplines, the cultivation of top innovative mathematical talents is a key measure to address the country’s core technological bottlenecks and support technological self-reliance and self-improvement. In the traditional mathematical talent training model, there are significant connection barriers between undergraduate and postgraduate stages. Problems such as fragmented scientific research training and delayed stimulation of innovative potential seriously restrict the growth of high-level top mathematical talents. Taking the major of Mathematics and Applied Mathematics in Qian Weichang College of Shanghai University as the practice carrier, and in conjunction with the Professional Committee of Educational Mathematics of the Chinese Society of Higher Education, this study takes the "knowledge rediscovery" concept as the core educational guidance, and systematically constructs and practices the "3+1+X" undergraduate-master-doctoral integrated training model. This model breaks the traditional linear teaching logic of "definition-theorem-proof-example", guides students to re-experience the generation process of mathematical knowledge as "quasi-researchers", and realizes the seamless connection of knowledge learning, scientific research training and thinking improvement between undergraduate and postgraduate stages through the whole-cycle training link of "foundation consolidation-scientific research connection-flexible further study". After 6 years of practical testing (2019-2025), the model has trained a total of 74 students, with an further study rate of 81\%. Students' scientific research capabilities and academic achievements have been significantly improved, and the training model has formed a good demonstration effect of on-campus promotion and off-campus radiation. This paper systematically explains the inherent compatibility between the "knowledge rediscovery" concept and the undergraduate-master-doctoral integrated cultivation of top mathematical talents, details the core design and key implementation measures of the "3+1+X" training model, summarizes the practical effects and core experiences, and puts forward the direction of future in-depth development, providing a replicable and promotable practical paradigm for the integrated cultivation of top innovative talents in mathematics and other basic disciplines in China.

Abstract: Previous studies suggest that elevated competitive anxiety may increase the likeli-hood of injury. The present research aims to examine the role of competitive anxiety as a predictor of injury occurrence, frequency, and severity. A cross-sectional, correlational de-sign was conducted with 131 athletes, (mean age = 16.49 years), predominantly male. In-juries data were obtained through medical record review, and competitive anxiety was assessed using the Competitive Anxiety Inventory-2. Empirical frequency distributions, descriptive statistics, non-parametric tests, and logistic and ordinal regression models were employed. A high incidence of injuries was observed, although most were minor. Competitive anxiety was characterized by elevated levels of cognitive anxiety and self-confidence. Injured athletes exhibited greater overall competitive anxiety (r = .31, p < .001), with higher levels observed among those who sustained more injuries (ε² = .12, p = .001), and a very large effect was found in relation to injury severity (ε² = .17, p < .001). The occurrence of injury can only be predicted in 10.9–14.7% of cases through increased cogni-tive and somatic anxiety, whereas an increase across all dimensions of competitive anxi-ety predicts a greater number (13–14%) and severity (20.3–21.8%) of injuries. These find-ings underscore the importance of developing skills to manage competitive anxiety, par-ticularly its cognitive dimension and maintaining optimal levels of self-confidence in young athletes.

Abstract: Urban regeneration frequently encounters a critical trade-off: whether to accelerate planning and implementation of design solutions or safeguard participation. To address this challenge, the paper introduces the concept of the governance “grey zone”—an informal yet institutional interface that flexibly reconfigures the relationship between planning and design to transcend the impasse. This perspective is grounded in an analysis of the recent urban regeneration of Hsinchu City, where a weekly, mayor-led coordination forum with external consultants functioned as an informal yet institutional organizational hub. This forum broke down departmental silos, unified multiple design teams under shared principles, and expedited implementation of numerous projects—all while maintaining public scrutiny and inclusivity. The study draws on interviews with high-profile administrators, planners, and designers involved in Hsinchu’s regeneration, as well as official documents. Elaborating on this, the paper finally advances a set of implications regarding urban regeneration scholarship with attention to aspects of urban design governance.

Abstract: In the 20^th century, the imperative of promoting endeavours that cultivate competencies for sustainability became evident. However, fostering these competencies is not enough; there is a need to rigorously evaluate such endeavours’ outcomes and the evolution of the competencies themselves. The aim of this paper is to initiate a discussion on the development of a questionnaire to evaluate the conceptions of participants in initiatives aiming to promote sustainability competencies, regarding their ability to promote those competencies. To this end, this contribution reports the results of a literature review that was conducted in Scopus, Web of Science and Eric to map the research on data collection tools for evaluating these competencies. The systematized review process, integrating a set of the recommendations of the PRISMA 2020 statement, did not yield the anticipated outcome, due to the absence of identified or explicit data collection instruments suitable within this context, as only two documents met the defined inclusion criteria. However, this review did contribute to a more comprehensive understanding of the necessity for standardizing nomenclatures and, concurrently, facilitate the development of a questionnaire that will align with the initial objectives. To this end, the two academic papers that have been identified, which will inspire and inform the subsequent stage of research, where a questionnaire will be developed, either ex novo or based on pre-existing.

Abstract: This study investigates the causes of language learning difficulties among beginner-level international students studying Chinese at a university in China, with a specific focus on the role of classroom interactions. The purpose of the research was to move beyond traditional explanations of language anxiety, such as lack of prior exposure or personal motivation, and examine how teacher behavior contributes to student distress. Survey data were collected from 51 international students and 15 Chinese language instructors. The findings reveal that teacher-mediated social comparisconsenton, perceived favoritism toward proficient learners, and public criticism are primary sources of anxiety for struggling students. These behaviors were found to negatively affect learner motivation, reduce classroom participation, and diminish self-confidence. The results indicate that for students with limited Chinese proficiency, the quality of the teacher-student relationship functions as a central determinant of their emotional experience in the classroom. The study concludes that addressing teacher-induced anxiety requires targeted interventions, including professional development programs focused on equitable teaching practices, differentiated instruction strategies, and institutional policies that ensure support for vulnerable learners. Recommendations for creating more inclusive and low-anxiety learning environments are discussed.

Abstract: This study explains cryptocurrency investment decisions by integrating personality traits, influencer credibility, and social influence within the Stimulus–Organism–Response (SOR) framework. The position model of openness, extraversion, conscientiousness, influencer credibility, and social influence as stimuli; heuristic bias and herding behaviour as organism states; and cryptocurrency investment decision as the response, with risk tolerance operating as a serial mediating mechanism. Data were collected from 367 Indonesian retail cryptocurrency investors using an online survey and analysed with SEM-PLS (SmartPLS) and one-tailed significance testing. The measurement model demonstrates adequate convergent validity and reliability, and discriminant validity is supported by HTMT values below the recommended threshold. Structural results support all hypothesized relationships (H1–H12). Openness (β = 0.132), extraversion (β = 0.326), and conscientiousness (β = 0.195) positively influence the tendency toward heuristic bias. Influencer credibility (β = 0.303) and social influence (β = 0.285) positively influence herding behaviour. Heuristic bias positively affects risk tolerance (β = 0.585) and investment decision (β = 0.407), while herding behaviour positively affects risk tolerance (β = 0.185) and investment decision (β = 0.106). Risk tolerance positively affects investment decision (β = 0.354) and mediates the effects of heuristic bias (indirect β = 0.200) and herding behaviour (indirect β = 0.078) on investment decision. The model explains substantial variance in investment decisions (Adjusted R² = 0.623) and moderate variance in risk tolerance (Adjusted R² = 0.507). The findings extend SOR to sentiment-driven digital asset markets by showing that cognitive shortcuts and socially transmitted cues shape risk tolerance before translating into investment actions, and they highlight the importance of behavioural risk-mitigation and disclosure practices in crypto ecosystems.

Abstract: This study advances the Law of the Trio as a universal law of linguistics, positing that reality, thought, and language are ontologically equivalent yet formally distinct modalities of existence. Unlike prior frameworks that isolate language as computation, code, or communicative tool, the Trio establishes a foundational architecture: the recursive coupling of entity and state/behavior, enriched by layered modifiers. Sentences are reframed as semantic DNA, encoding identity, transformation, and relational depth across modalities. To formalize this claim, the paper introduces EMi/VMi,j notation, where i indexes modifier type and j denotes recursion depth. Worked examples and cross‑linguistic analysis (English, Korean, Basque) confirm semantic invariance across typologically distinct languages. Direct mapping to event semantics and thematic roles highlights both alignment and innovation, with recursion depth providing a computable dimension absent from existing models. Comparative analysis shows how the Trio consolidates and extends generative grammar, cognitive science, pedagogy, and semiotics by resolving their limitations through recursive semantic geometry. Applications in pedagogy and natural language processing demonstrate practical relevance. By restructuring linguistics into semantic geometry, the Trio offers a testable, falsifiable, and universal law of language that unifies theory and practice.

Abstract: Analysis of a digitalized databank of books indicates that the topic of life’s meaning first emerged around 1800 and increased sharply in frequency during the middle of the 19th century, with take-off dates fairly similar across the six literatures we searched (American English, British English, French, German, Italian, and Spanish). We discuss major historical changes around this time that likely impacted people’s psychological approaches toward understanding their lives. Of five major needs for meaning, purpose and value were severely impacted, efficacy and self-worth found new contexts, and comprehensibility / continuity was also challenged. Important changes in society included the following. Secularization reduced the sense that the world operated under divine plan and also undermined the presumptive basis for moral values. The industrial revolution disrupted society with new kinds of goals but new problems, including changing the meaning and nature of work. Urbanization offered new life paths for many while weakening the reputational basis for morality. Cognitive changes including expanded education and literacy, thereby exposing people to new ideas. Political upheavals raised questions about how society should be organized and what the individual’s duty was. Social mobility in both directions transformed individual lives in unprecedented fashion.

Abstract: The main aim of this study was to investigate the association between areas of work life and engagement in the development of burnout syndrome in self-employed and sub-ordinate psychologists. Using a cross-sectional approach with quantitative and qualitative elements, three scales validated for the Brazilian population were applied: Burnout Assessment Tool (BAT), Areas of Worklife Survey (AWS) and Utrecht Work Engagement Scale (UWES). 180 psychology professionals took part, with a predominance of females (88.3%) and a majority aged between 24 and 29. The results revealed a strong negative correlation between the BAT domains and aspects assessed by the UWES, confirming the inverse association between engagement and burnout. In addition, the positive associa-tion between areas of work life and engagement was confirmed. However, there was no confirmation of the negative association between areas of work life and burnout, and no evidence was found that these areas act as mediators in the relation between engagement and burnout. Thus, although the areas of work life have been shown to influence en-gagement and burnout independently, their role as mediators in this relationship has not been confirmed. Although some hypotheses were confirmed and significant associations were found, the research also encountered unexpected results and limitations that deserve to be considered in future investigations such as this one.