Abstract: Mental health disorders profoundly shape individuals’ economic behaviors, influencing how they make decisions under risk, plan for the future, interact with markets, and allocate resources. This systematic review synthesizes empirical and theoretical literature on the economic consequences of common psychiatric conditions, including depression, anxiety, bipolar disorder, obsessive-compulsive disorder (OCD), post-traumatic stress disorder (PTSD), and schizophrenia. Drawing on interdisciplinary research from behavioral economics, psychiatry, and public health, the review identifies robust patterns in decision-making impairments associated with these disorders—particularly in domains of risk tolerance, time discounting, loss aversion, labor force participation, and consumption behavior.The review follows a systematic methodology based on PRISMA guidelines, screening peer-reviewed articles published between 2000 and 2024 across major academic databases (e.g., PubMed, PsycINFO, EconLit). Findings highlight that individuals with depressive and anxiety disorders tend to exhibit increased loss aversion and temporal discounting, while those with bipolar disorder display unstable and extreme shifts in risk preferences across manic and depressive states. Schizophrenia is linked to severe impairments in planning, probabilistic reasoning, and consistency in preferences. Across disorders, diminished cognitive control and heightened emotional reactivity emerge as central mechanisms underlying economic dysfunction.This paper underscores the need for integrating mental health considerations into economic modeling and policy design. By illuminating the systematic ways in which psychiatric disorders alter rationality assumptions, this review contributes to a growing literature on bounded rationality and mental health-informed behavioral economics.

Abstract: This paper explores the Many-Worlds Interpretation (MWI) of quantum mechanics as a conceptual framework for understanding fragmentation, uncertainty, and narrative divergence in global economic dynamics. We argue that the logic of Everettian branching –originally introduced to resolve the quantum measurement problem– offers a compelling metaphor for interpreting the proliferation of economic expectations, speculative bubbles, policy contradictions, and systemic crises in a multilateral, post-truth financial world. Situating our analysis within the emerging discourse of narrative economics and cognitive fragmentation, we draw parallels between physical decoherence and economic disconnection, highlighting how modern financial systems increasingly resemble a multiverse of incompatible but coexisting belief structures. We propose that modular tensor categories may eventually offer more refined topological frameworks for modeling such multiplicity. The paper con cludes by outlining ethical and policy implications for re-coherence and the role of observers in navigating global economic multiplicity.

Abstract: The labour market in India is undergoing a transition over the last three decades. While structural adjustment since the 1990s expanded the labour market, especially during the first few years of the new century, most of the new jobs were casual in nature. Thereafter, the story has been mostly that of a jobless growth, even job-loss growth in the 2011-2021 decade. In this paper, we have explored the situation in India in terms of employment quality and decent work deficit using NSS and PLFS data over the last two decades. While the foundation is ILO’s decent work framework (Anker et al, 2002), we have expanded and modified that to some extent to suit the available database in Indian context. Apart from aggregate situation, we have examined the pattern and trend across region, gender, social group and education. Our result shows that the situation in the country is far from satisfactory in terms of Employment Quality and there is substantial Decent Work Deficit. The only silver lining around this dark cloud is that Decent Work deficit is coming down during the 2011-23 period after a slump during 1999-2011 period. EQI is increasing and the proportion of workers in the two bottom-most groups have come down.

Abstract: This study presents the development of a custom dataset of L2 gap-fill exercises designed to enhance Long Short-Term Memory (LSTM) neural networks in CLIL (Content and Language Integrated Learning) settings for subject-specific courses. Targeting English for Special Purposes (ESP )vocabulary in cybersecurity, privacy, and data protection, the model addresses the dual challenge of domain-specific context mastery and language practice through structured neural network training. The custom dataset of gap-fill exercises for this LSTM model enables simultaneous prediction of missing words and semantic classification, offering learners contextualized language training that is a core requirement of CLIL methodology. Experimental results validate the model’s efficacy, demonstrating its potential as an adaptive support tool for CLIL-based education. This framework establishes a novel synergy between AI-enhanced language learning and subject-specific instruction, providing a scalable template for integrating neural networks into CLIL pedagogy.

Abstract: The present paper first reviews those psychological concepts used in artificial intelligence. The embedding of psychological properties and mind in artificial intelligence has advantages and challenges. Instead of doing philosophical enquiries, we assume as our working hypothesis that machine intelligence is a kind of platonic reality which needs working definitions in AI modeling. It argues that following Gödel and Tarski, Turing test enriched Artificial intelligence, resulting a new kind of independent results, which refers to machine intelligence. Machine intelligence is dual with human intelligence.

Abstract: A growing number of research studies show that children spend less time in natural environments, which may have detrimental effects to children`s mental and physical health. This study explores changes in children (6-12 years) nearby nature uses and constraints for not playing in nature between the year of 2013 and 2023. We apply an ecological approach including individual, social, and structural constraints for outdoor play. The study is based on national surveys of parents answering eight categories for different activities and nineteen categories for constraints/motivation. Findings reveal a decreasing tendency for time spent on all activity categories and increasing con-straints for 17 of 19 categories during the study period. Our ecological approach makes it visible that there is less time for children`s nature to use in contemporary society, and activities are more common at built areas than in nature. The survey identifies some important socio-cultural differences regarding gender, age, and residential set-tings. In future research, the focus should be on what kind of effects less connection to nature has on children’s mental and physical health, and beyond this has effects on the understanding and care for nature among future generations.

Abstract: Yale School of Medicine (YSM) has consistently been at the forefront of promoting equity and inclusiveness within the realms of research and patient care. Using YSM’s official data on Asian female faculty members (2001–2024) and students (2014–2024) as a starting point, this review traces a historical narrative spanning over a century (1924–2024), shedding light on the remarkable achievements and enduring challenges faced by Asian females at YSM. The journey begins with trailblazers such as Dr. Chenghui Ge, the first Chinese woman to earn a DrPH at YSM in 1926, and Dr. Gueh Djen Hsiung, who became Yale’s first Asian female department director in 1960. Their pioneering contributions laid the foundation for future generations of Asian women in medicine. In more recent decades, this article highlights the enduring impact of leaders from YSM and spotlights emerging young physicians and scientists trained in Yale’s residency programs and clinical or research fellowships, who are making progress in the early stages of their careers, showcasing the ongoing evolution of Asian female representation at YSM. Beyond celebrating these milestones, this review amplifies the voices of YSM’s Asian women, addressing persistent challenges such as identity-based discrimination, cultural barriers, the "glass ceiling" in leadership roles, and the balancing act of family responsibilities. By documenting these achievements and struggles, this digital collection aims to share YSM’s progress and lessons learned while advocating for greater awareness of how cultural identity shapes academic and professional advancement.

Abstract: As digital transformation becomes an increasingly central focus of national and regional policy agendas, parallel efforts are intensifying to stimulate innovation as a critical driver of firm competitiveness and high-quality economic growth. Yet regional disparities in innovation capacity persists. This study proposes an integrated framework in which regionally tracked digital economy indicators are leveraged to predict firm-level innovation performance, measured through patent activity, across China. Drawing on a comprehensive dataset covering 13 digital economic indicators from 2013 to 2022, the study spans core, broad, and narrow dimensions of digital development. Spatial dependencies among these indicators are assessed using global and local spatial autocorrelation measures, including Moran’s I and Geary’s C, to provide actionable insights for constructing innovation-conducive environments. To model the predictive relationship between digital metrics and innovation output, the study employs a suite of supervised machine learning techniques—Random Forest, Extreme Learning Machine (ELM), Support Vector Machine (SVM), XGBoost, and stacked ensemble approaches. The findings demonstrate the potential of digital infrastructure metrics to serve as early indicators of regional innovation capacity, offering a data-driven foundation for targeted policymaking, strategic resource allocation, and the design of adaptive digital innovation ecosystems.

Abstract: Rapid digital transformation demands educational approaches that effectively equip students with competencies crucial for addressing real-world sustainability challenges. This study introduces and evaluates a Living Lab-based educational model explicitly designed to enhance collaborative problem-solving (CPS), computational thinking (CT), and collaborative communication (CC) within elementary informatics education. Aligned with South Korea’s 2022 revised curriculum, this quasi-experimental research involved 196 elementary students actively engaged in structured, community-based tasks that integrated informatics concepts with authentic, real-world problems. Findings demonstrated significant improvements in CPS and CT competencies, including problem comprehension, algorithmic reasoning, abstraction, and ICT usage. However, advancements in CC were comparatively modest, highlighting the necessity for explicit and structured communication interventions within collaborative frameworks. The study confirms the effectiveness of the Living Lab-based educational model in cultivating comprehensive competencies essential for sustainable development, while underscoring the need for further integration of targeted communication strategies to maximize educational impact. Future implementations should prioritize structured communication training to fully leverage the model's interdisciplinary potential.

Abstract: We analyze long-range dependence (LRD) for word time series, understood as a slower than exponential decay of the two-point Shannon mutual information. We do it by examining the decay of the cosine correlation, a proxy object defined in terms of the cosine similarity between word2vec embeddings of two words, computed by an analogy to the Pearson correlation. By the Pinsker inequality, the squared cosine correlation between two random vectors lower bounds the mutual information between them. Using the Standardized Project Gutenberg Corpus, we find that the cosine correlation between word2vec embeddings exhibits a readily visible stretched exponential decay for lags roughly up to 1000 words, thus corroborating the presence of LRD. By contrast, for the Human vs. LLM Text Corpus entailing texts generated by large language models, there is no systematic signal of LRD. Our findings may support the need for novel memory-rich architectures in large language models that exceed not only hidden Markov models but also Transformers.

Abstract: This study aims to examine the integrated structure of biology activities implemented in Science and Art Centers (BİLSEM) in terms of their alignment with STEM (Science, Technology, Engineering, and Mathematics) components. Employing a qualitative case study design, semi-structured interviews were conducted with six biology consultant teachers and thirty gifted students across three different BİLSEM institutions. In addition to interview data, activity plans, student products, and observational records were analyzed. The data were evaluated through thematic analysis, and the degree of STEM integration was assessed using a rubric based on Bybee’s model. Findings indicate that science and technology components are prominently featured in the activities, while engineering is represented at a moderate level, and mathematics is often incorporated only superficially. Students demonstrated significant improvements in scientific process skills and exhibited creative problem-solving and prototyping abilities in design-oriented activities. However, their competencies in numerical analysis, data modeling, and statistical reasoning remained underdeveloped. Teachers emphasized that the STEM approach positively influences student motivation, interdisciplinary thinking, and scientific awareness. The results reveal that well-balanced and systematically structured STEM activities effectively support multidimensional learning in gifted students. In this regard, it is recommended that STEM-oriented biology activities be enriched through interdisciplinary collaboration, with a particular focus on more robust integration of the mathematics component.

Abstract: This study developed and validated a new multidimensional measure of connection to nature (CTN) - the DEEP Connection to Nature Scale. Addressing limitations of existing scales, the new scale attempts to emphasize self-integration with nature while capturing the three well-agreed upon aspects of connection to nature—cognitive, emotional, and behavioral. Using both exploratory and confirmatory factor analyses across a sample of 1152 and 657 adults, respectively, a four-factor structure was validated: (D)epth of identity, (E)motional connection, (E)xperiential connection, and (P)resence within nature. The scale demonstrated good internal consistency, convergent validity with existing CTN measures, and predictive validity for pro-environmental behavior (PEB) as well as a composite measure of well-being. Notably, the DEEP CTN Scale explained more variance in PEB (30%) compared to two widely used unidimensional measures. The Emotional and Presence dimensions emerged as the strongest unique predictors of PEB, while Depth and Presence positively predicted well-being. These relationships remained robust when controlling for relevant covariates. The multidimensional structure allows for more nuanced assessment of human-nature relationships and their outcomes. This psychometrically sound, theory-driven measure addresses key limitations of previous scales and provides a foundation for future CTN research across diverse populations. The DEEP CTN Scale offers researchers and practitioners a tool to better understand and cultivate meaningful connections with nature.

Abstract: This study examines the geopolitical contest in Myanmar’s Chin State, a critical theater of great-power rivalry involving China, India, and Western actors. Employing a qualitative case-study approach, we integrate expert interviews, media analyses, satellite imagery, and secondary literature to analyze how local insurgent groups navigate external influences. Our findings reveal that Chinese infrastructure projects foster economic dependency, India’s security partnerships provide limited counterbalance, and Western engagement remains largely symbolic. We argue that Chin State’s crisis exposes the limitations of realist theory in explaining secondary theaters of great-power competition, advocating for a regionally contextualized framework that accounts for local agency and interconnected security dynamics. The paper proposes comprehensive policy measures to stabilize the region, manage Sino-Indian rivalry, and foster cooperative regionalism, emphasizing multilateral diplomacy and local economic integration.

Abstract: Cities have emerged as unequal critical sites exposed to stresses and shocks related to climate variability and change, such as urban heat. However, urban studies and climate literature have paid limited attention to foregrounding heat through a social and spatial lens of investigation in marginalised and low-income communities. Instead, discussions of climate impacts such as flooding, rising sea levels and prolonged drought have had more substantial attention. Accordingly, this article focuses on the socio-spatial injustices associated with urban heat. We pay particular attention to marginalised and low-income communities and show that fragmented urban structures contribute to specific heat inequity and vulnerability patterns. First, the paper critically examines patterns of heat inequity worldwide. We focus on social groups in poor or marginalised communities in urban centres that are disproportionately exposed to higher temperatures and the urban heat. The paper then discusses the mechanisms of heat inequity through transitional injustice, green gentrification, urban science, intersectional adaptation praxis, and the implications for heat equity planning and heat vulnerability studies across scales. This allows for a deeper epistemic lens of climate justice, theorised and grounded in urban heat/thermal inequity, part of which requires acknowledging the embodied landscapes shaped by distributive and transitional injustice.

Abstract: This study examines the added value of territorial cooperation within the LEADER approach, a key pillar of the EU’s rural development policy. Both interterritorial and transnational cooperation projects empower Local Action Groups (LAGs) to tackle common challenges through innovative, community-driven strategies. Drawing on over 3,000 projects since 1994, LEADER cooperation has proven its ability to deliver tangible results—such as joint publications, pilot projects, and shared digital platforms—alongside intangible benefits like knowledge exchange, improved governance, and stronger social capital. By facilitating experiential learning and inter-organizational collaboration, cooperation enables stakeholders to work across territorial boundaries and build networks that respond to both national and transnational development issues. The interaction among diverse actors often fosters innovative responses to local and regional problems. Using a mixed-methods approach, including case studies of Italian LAGs, the research analyzes the dynamics, challenges, and impacts of cooperation, with a focus on learning processes, capacity building, and long-term sustainability. Therefore, the study focuses not only on project outcomes but also on the processes and learning dynamics that generate added value through cooperation. The findings highlight how cooperation promotes inclusivity, fosters cross-border dialogue, and supports the development of context-specific solutions, ultimately enhancing rural resilience and innovation. In conclusion, LEADER cooperation contributes to a more effective, participatory, and sustainable model of rural development, offering valuable insights for the broader EU cohesion policy.

Abstract: The slogan ‘Joy Bangla’ has been historically emblematic of the collective resistance against socio-political and economic exploitation in Bangladesh. Emerging as the rallying cry during the Liberation War of 1971, ‘Joy Bangla’ encapsulates national identity, dignity, and the struggle for justice and self-determination. This article explores the conceptual, historical, and political significance of ‘Joy Bangla’ as an indomitable protest against exploitation, oppression, and neo-colonial structures. Through qualitative research methodologies, including archival analysis, literature review, and interpretive political discourse analysis, the study evaluates how ‘Joy Bangla’ continues to shape resistance narratives in postcolonial and postliberation Bangladesh. The findings indicate that the slogan transcends generational boundaries, functioning as both a cultural signifier and a call for justice against exploitation in modern political contexts.

Abstract: Climate change intensifies Africa’s health and economic disparities by amplifying vulnerabilities among already at-risk populations. This study synthesises secondary data from peer-reviewed literature, institutional reports, and global databases such as the World Bank and WHO to examine the intersectionality of climate change, health outcomes, and economic development across the continent. The analysis reveals that rising temperatures, extreme weather events, and environmental disruptions disproportionately impact the health of children, women, and low-income communities, leading to increased disease burdens, malnutrition, and reduced life expectancy. These health challenges translate into significant economic losses, including diminished labour productivity, agricultural decline, and increased public spending on disaster relief and healthcare, collectively threatening sustainable development and widening existing inequalities. However, the findings also highlight emerging opportunities for resilience-building, such as green financing, renewable energy investments, and community-led adaptation strategies that foster inclusive economic growth and health system strengthening. Achieving Sustainable Development Goal (SDG)-aligned resilience by 2030 will require integrated, cross-sectoral policies that address the complex interplay between climate, health, and economic systems, while prioritising vulnerable populations and leveraging innovative financing and governance mechanisms to support sustainable, equitable development.

Abstract: Background/Objectives: Early care and education programs promote children’s social-emotional development, predicting later school success. The COVID-19 pandemic worsened an existing youth mental health crisis and increased teacher stress. Therefore, we applied an infant and early childhood mental health consultation model, Jump Start plus Covid Support (JS+CS), aiming to decrease behavior problems in children post-pandemic. Methods: A cluster randomized controlled trial compared JS+CS to an active control, Healthy Caregivers-Healthy Children (HC2), at 30 ECE centers in low-income areas of South Florida. Participants were not blinded to group assignment. Teachers reported on children’s social-emotional development at baseline and post-intervention using the Deveraux Early Childhood Assessment and Strengths and Difficulties Questionnaire. We assessed whether teacher stress, classroom practices, and self-efficacy mediated the relationship between JS+CS and child outcomes. We also explored whether baseline behavior problems moderated JS+CS effects on child protective factors, relative to HC2. Results: Direct group-by-time differences between JS+CS and HC2 were limited. However, JS+CS demonstrated significant within-group improvements in teacher-reported child protective factors, behavior support practices, and classroom safety practices. Classroom safety practices consistently mediated positive changes in child behaviors, including the DECA Total Protective Factor score and subdomains of Initiative and Self-Regulation. Additionally, teacher perceptions of behavior support mediated gains in child attachment. Conclusions: JS+CS shows promise in building protective systems around children through intentional support for teachers, underscoring the value of whole-child, whole-environment approaches in early intervention.

Abstract: This review explores how community-based mental health services (CBMHS) contribute to the development of social resilience. Drawing on interdisciplinary literature, it synthesizes theoretical foundations, empirical evidence, and implementation challenges. The analysis highlights that CBMHS foster resilience through psychosocial, structural, and cultural mechanisms—yet face persistent barriers in funding, equity, and systemic integration. Strategic policy recommendations are provided to support the institutionalization of CBMHS as key infrastructures of collective adaptation and wellbeing.

Abstract: Understanding daily mobility in Egypt remains a challenge due to lim-ited data availability. Traditional urban studies rely on census data and satellite imagery, offering static snapshots rather than a dynamic rep-resentation of movement. This study utilizes Facebook’s “Data for Good” program to analyze daily mobility patterns of over four million users in Egypt from April to October 2020, coinciding with the first wave of COVID-19. The Egyptian government's response, including curfews and reductions in public transport, aimed to curb the virus’s spread, yet our findings indicate that daily commuting persisted at sig-nificant levels, particularly in Greater Cairo. We assess the extent to which mobility restrictions influenced move-ment flows, highlighting the interplay between commuting patterns and urban structure. Mobility reduction was most pronounced at night and during religious holidays, particularly Ramadan and Eid al-Fitr. However, daytime movement remained substantial, driven by eco-nomic necessity. By mapping COVID-19 incidence across Cairo’s dis-tricts, we reveal a correlation between urban centrality and infection rates, emphasizing the role of daily circulation in virus diffusion. This study underscores the potential of social media mobility data to fill gaps in urban research, offering comparative insights into how differ-ent countries experienced mobility shifts during the pandemic.