Search Results (179)

The growing demand for healthier food options has accelerated the development of innovative fat-replacement strategies in spreadable products. Oleogels are semi-solid systems formed by structuring edible oils. Recently, these systems have emerged as a promising solution for reducing saturated fat content without compromising product quality, texture, or sensory attributes. A systematic review was conducted following the PRISMA 2020 protocol, supplemented by a bibliometric analysis. Research was identified through searches in Web of Science, Scopus, Wiley, Springer, MDPI, and Google Scholar for studies published between 2020 and 2024. Inclusion criteria focused on original research articles in English involving food-sector applications of oleogels and aerogels in sweet spreads. Study quality and risk of bias were assessed by two independent reviewers based on methodological relevance and data integrity. Results were synthesized through a narrative approach and bibliometric mapping. After screening 490 records, 34 original research articles were included. Bibliometric data highlighted a clear trend shifting from foundational lipid structuring research in 2020 toward complex, product-specific functional applications by 2024. Overall, the results suggest that these structured systems are viable replacements for traditional saturated fats, providing comparable spreadability and stability. Funding: This work was supported by the Croatian Science Foundation under the project IP-2022-10-1960. This systematic review was not registered in a public database. Full article

Financial regulation assumes that parent firms reliably support distressed subsidiaries during crises. We test this assumption with evidence from the 2007–2009 financial crisis and find that parent support was selective rather than reliable. Using novel measures of sibling distress and granular parent-affiliate funding flows, our findings reveal that capital allocation within bank holding companies (BHCs) disproportionately favored stronger affiliates. The results show that BHCs channeled capital toward more liquid and resilient subsidiaries while limiting support to weaker ones. Profitable parents became increasingly selective under stress, and nonbank subsidiaries emerged as critical internal liquidity providers when external markets froze. This selective reallocation highlights a gap between regulatory doctrine and actual behavior: intra-group capital allocation mechanisms can amplify systemic stress rather than mitigate it. By examining overlooked internal market dynamics during this major financial crisis, the study offers insights for strengthening financial stability against future systemic shocks. Assessing parent firm strength alone appears insufficient. Effective crisis prevention requires supervisory frameworks that monitor sibling fragility across conglomerates, evaluate the liquidity roles of nonbank affiliates, and stress test intra-group capital flows. Full article

The thermally efficient and lightweight TRC/CLCi composite panels for functional and smart building envelopes, funded by the iclimabuilt project (Grant Agreement no. 952886), offer innovative solutions to sustainably address common failure risks in facade systems. This work specifically emphasizes strategies for mitigating structural, thermal, and fire-related failures through targeted material selection, advanced design methodologies, and rigorous validation protocols. To effectively mitigate structural failures, high-pressure concrete (HPC) reinforced with carbon fibers is utilized, significantly enhancing tensile strength, reducing susceptibility to cracking, and improving overall durability. To counteract thermal bridging—a critical failure mode compromising energy efficiency and structural integrity—the panels employ specially designed glass-fiber reinforced pins connecting HPC outer layers through the cellular lightweight concrete (CLC) insulation core that has a density of around 70 kg/m³ and a thermal conductivity in the range 35 mW/m∙K comparable to those of expanded polystyrene and Rockwool. These connectors ensure effective load transfer and maintain optimal thermal performance. A central focus of the failure mitigation strategy is robust fire behavior. The developed panels undergo rigorous standardized fire tests, achieving an exceptional reaction to fire classification of A2. This outcome confirms that HPC layers maintain structural stability and integrity even under prolonged fire exposure, effectively preventing catastrophic failures and ensuring occupant safety. In conclusion, this work highlights explicit failure mitigation strategies—reinforced concrete materials for structural stability, specialized glass-fiber connectors to prevent thermal bridging, rigorous fire behavior protocols, and comprehensive thermal performance validation—to produce a facade system that is robust, energy-efficient, fire-safe, and sustainable for modern buildings. Full article

Portfolio management (PM) is a broad investment strategy aimed at risk mitigation through diversified financial product investments. Acknowledging the significance of dynamic adjustments after establishing a portfolio to enhance stability and returns, we propose employing reinforcement learning (RL) to address dynamic decision-making challenges. However, traditional RL methods often struggle to adapt to significant market volatility, primarily by focusing on adjusting existing asset weights. Different from traditional RL methods, the multi-agent reinforcement learning correctable strategy (MAC) developed in this study detects and replaces potentially harmful assets with familiar alternatives, ensuring a resilient response to market crises. Utilizing the multi-agent reinforcement learning model, MAC empowers individual agents to maximize portfolio returns and minimize risk separately. During training, MAC strategically replaces assets to simulate market changes, allowing agents to learn risk-identification through uncertainty estimation. During testing, MAC detects potentially harmful assets and replaces them with more reliable alternatives, enhancing portfolio stability. Experiments conducted on a real-world US Exchange-Traded Fund (ETF) market dataset demonstrate MAC’s superiority over standard RL-based PM methods and other baselines, underscoring its practical efficacy for real-world applications. Full article

This article examines how European funding enhances the financial performance of Romanian SMEs, a sector facing growing regulatory pressure, market volatility, and resource constraints. The study combines a thematic analysis of InvestEU indicators and national SME financing data (2021–2023) with a firm-level difference-in-differences model comparing InvestEU-funded SMEs to a matched control group over 2023–2024. The qualitative evidence shows that InvestEU operates at the EU level as a multidimensional policy instrument fostering competitiveness, social inclusion, and long-term economic and environmental development, while Romanian SMEs continue to rely predominantly on their own funds and national co-financing, a conservative pattern that ensures stability but limits access to external capital and transformative investments. Econometric results indicate that funded SMEs record, on average, higher turnover and net profit growth than comparable non-funded firms and confirm a strong positive association between firm size and financial performance; however, the interaction term capturing the specific InvestEU effect is positive but not statistically significant at the 95% confidence level. The findings suggest that InvestEU has the potential to act as a catalyst for structural change but also highlight the need for longer observation periods, larger samples, and more comprehensive development indicators to assess its medium-and long-term impact on SME competitiveness. Full article

This study examines the evolution and main trends in the number of students, teaching staff and graduates in Romania’s pre-university education system over the period 1990–2024 (and 1990–2023 for graduates), employing ARIMA models to generate forecasts up to the year 2027. The research is grounded in the premise of profound structural transformations within the Romanian educational system, driven by demographic decline, external migration, recurrent reforms, and shifts in resource allocation. The descriptive analysis highlights a pronounced downward trend for all three variables (students, teaching staff and graduates), reflecting the continuous reduction in the school-age population and the restructuring of the educational network. The statistical tests employed, such as Shapiro–Wilk, Augmented Dickey–Fuller, Durbin–Watson, Breusch–Godfrey and ARCH, validate the selected optimal ARIMA models: ARIMA(1,1,1) for teaching staff, ARIMA(4,1,3) for students, and ARIMA(3,1,5) for graduates. The forecasting results indicate that this declining trend is expected to persist through 2027: the number of teaching staff is estimated to decrease to approximately 178,700 individuals, the number of students is estimated to decrease to around 2.78 million, and the number of graduates is projected to fall until 2026, followed by a potential slight stabilization in 2027. The Spearman correlation analysis indicates strong associations among all variables, suggesting that their dynamics are predominantly shaped by demographic and migratory factors. Granger causality analysis shows that changes in birth rates lead to rapid adjustments in teaching staff within 2–3 years. No significant short-term causality is found for the number of students or graduates, though demographic effects appear after 5–6 years for students, indicating long-term impacts on the school population. This study underscores the importance of econometric methods in informing educational policy, particularly in the context of the marked contraction of the school-age population. It also highlights the need for strategic planning regarding human resources in education, per-student funding, the reorganization of the school network, and curriculum adaptation. Full article

This study examines the financial resilience of small enterprises in Ukraine during the wartime crisis, addressing the lack of quantitative evidence on how regional military risks and adaptive strategies jointly shape SME stability. The analysis is based on a sample of 30 small agricultural enterprises from the eastern, central, and western regions of Ukraine using annual data for 2022–2024. To capture multidimensional resilience patterns, the study applies factor analysis, cluster analysis, and taxonomic assessment methods to evaluate financial performance, operational adaptability, and access to external resources. The findings show that resilience variation across the sample is strongly associated with enterprises’ ability to sustain revenue flows, control operating costs, and maintain a balanced capital structure. Three distinct resilience profiles were identified: high resilience in western regions (KT = 0.89), moderate resilience in central regions (KT = 0.81), and low resilience in eastern frontline regions (KT = 0.49). These results indicate substantial regional asymmetry linked to differentiated exposure to military threats. Building on these empirical insights, the study proposes a hybrid risk-management approach that integrates digitalization of financial operations, diversification of funding sources, and enhanced social engagement as mechanisms supporting adaptation under prolonged instability. The novelty of the research lies in combining regional risk exposure with multidimensional financial indicators to develop an evidence-based framework for assessing SME resilience in wartime conditions. Full article

Therapy farms are increasingly recognized as social innovations that respond to exclusion, mental health challenges, and youth disconnection, particularly in rural areas. While often praised for their inclusive and rehabilitative potential, their broader impact on structural social transformation remains under-examined. This study explores the House of Educational Experiences, a therapeutic farm in rural Lithuania, to critically assess how such initiatives function as both agents of inclusion and stabilizers of existing socio-economic arrangements. Drawing on a qualitative case study approach, the research analyses in-depth interview data through the lens of the social innovation cycle, focusing on novelty, process, heterogeneity, impact, scalability, and transformative potential. Our findings reveal that the therapeutic farm generates significant individual and community benefits, particularly in psychosocial well-being, social skills, and pathways back into education and employment. However, the initiative also operates within institutional constraints, relying on project-based funding and reproducing aspects of conventional care systems. As such, its transformative capacity appears limited by structural dependencies and policy fragmentation. The study concludes that therapy farms represent an ambivalent form of social innovation: capable of creating inclusive, localized change, but often constrained in their ability to catalyze systemic transformation. Policy recommendations emphasize the need for long-term funding, institutional integration, and cross-sector collaboration. Full article

Background/Objectives: Community health workers (CHWs) play a critical role in advancing health equity by bridging gaps in care for underserved populations. However, limited institutional support, inconsistent training, and lack of integration contribute to high rates of burnout. The Lunch and Learn program was launched in Maryland in fall 2023 as a virtual continuing education and peer-support initiative designed to foster professional development, enhance connections among CHWs, and align with Maryland state CHW certification requirements. This article describes the program’s first year of implementation as a proof-of-concept and model for scalable CHW workforce support. Methods: The program offered twice-monthly, one-hour virtual sessions that included expert-led presentations, Q&A discussions, and dedicated peer-support time. Participant engagement was assessed using attendance metrics, post-session surveys, and annual feedback forms to identify trends in participation, learning outcomes, and evolving professional priorities. Results: Participation increased over time with the program’s listserv expanding from 29 to 118 members and average session attendance more than doubling. CHWs highlighted the program’s value in meeting both educational and emotional support needs. Conclusions: The Lunch and Learn program demonstrates a promising model for addressing burnout through education and community connection. As an adaptable, CHW-informed initiative, it supports both professional growth and well-being. Ongoing development will focus on expanding access, incorporating experiential learning assessments, and advocating for sustainable funding to ensure long-term program impact and CHW workforce stability. Full article

Sustainable livelihoods remain a vital part of health and can significantly influence overall health outcomes. In sub-Saharan Africa, where HIV continues to affect household economic stability, small-scale but sustainable livelihood interventions have proven essential for economically vulnerable families. These economic empowerment initiatives, mainly funded by non-governmental organizations, are common across the region. Despite their important role in shaping health outcomes, there is a limited understanding of the theoretical frameworks that guide their implementation and results, especially among households affected by HIV. Using qualitative methods, we applied Pierre Bourdieu’s theory of capital to better understand how livelihood projects are implemented among young adults living with HIV in Kisumu. Our findings indicate that livelihood interventions need more than just economic capital to be successful. Social and cultural capital, for example, help overcome barriers like stigma and foster a sense of belonging, while economic capital enables start-up activities and knowledge sharing that support livelihoods. The insights from this study are important for guiding resource allocation toward economic development and social asset building as ways to leverage different types of capital. Full article

This paper explores the economic, environmental, and security issues created by the launch of satellite megaconstellations, which are networks of LEO (Low Earth Orbit) satellites planned to provide worldwide communications, data services, and research capabilities. Although such programs bring the potential to offer global coverage and substantial technology enhancements, they also pose significant challenges to fund and sustain. In order to address these issues, the approach assumes a Life Cycle Costing (LCC) scope that includes development, launch, operational, end-of-life, and environmental impacts. Based on this, we introduce an original model, which includes a Cooperative Game Theory component—more precisely the Shapley value—to devise fair and efficient cost-sharing mechanisms between multiple players. The model includes the effects of cooperation, free-rider phenomena, and the consideration of capacity limitations, providing a formalized approach to distribute costs fairly and ensure coalition stability. A three-operators case study demonstrates the real benefits achieved by collaboration: significant cost savings of up to 27% compared with independent approaches. However, the analysis also demonstrates the destabilizing effects of free riders, which undermine cooperation in the short run and may lead to a net increase in costs for contributing parties. The results indicate that resilient allocation mechanisms and policy protection are necessary to secure the sustainability of megaconstellations over the long time period, possibly also applicable to other critical infrastructures beyond space systems. Full article

Forecasting stock prices remains a central challenge in financial modelling, as markets are influenced by market sentiment, firm-level fundamentals and complex interactions between macroeconomic and microeconomic factors, for example. This study evaluates the predictive performance of both classical statistical models and advanced attention-based deep learning architectures for daily stock price forecasting. Using a dataset of major U.S. equities and Exchange Traded Funds (ETFs) covering 2012–2024, we compare traditional statistical approaches, Seasonal Autoregressive Integrated Moving Average (SARIMA) and Exponential Smoothing (ES) in the Error, Trend, Seasonal (ETS) framework, with deep learning architectures such as the Temporal Fusion Transformer (TFT), and a novel hybrid model, the TFT-Graph Neural Network (TFT-GNN), which incorporates relational information between assets. All models are assessed under consistent experimental conditions in terms of forecast accuracy, computational efficiency, and interpretability. Our results indicate that while statistical models offer strong baselines with high stability and low computational cost, the TFT outperforms them in capturing short-term nonlinear dependencies. The hybrid TFT-GNN achieves the highest overall predictive accuracy, demonstrating that relational signals derived from inter-asset connections provide meaningful enhancements beyond traditional temporal and technical indicators. These findings highlight the advantages of integrating relational learning into temporal forecasting frameworks and emphasise the continued relevance of statistical models as interpretable and efficient benchmarks for evaluating deep learning approaches in high-frequency financial prediction. Full article

This research demonstrates the potential of machine learning for revealing the fiscal effects of the Recovery and Resilience Facility (RRF) in the European Union. It focuses on the use of a hybrid approach, based on traditional econometric methods combined with advanced data machine learning techniques. For this purpose, the following were applied: a panel data model with fixed effects, difference-in-differences analysis, correlation analysis, and machine learning, specifically, random forest regression, for the period of 2020–2024, including indicators from all 27 EU member states. The results of the conducted tests establish the effectiveness of the Recovery and Resilience Facility for fiscal stabilization, but also its high vulnerability to specific economic conditions in the individual member states. The complex relationships between the amount of funds received and the fiscal outcomes, which classical models fail to capture, were derived. A positive stabilizing effect on the indebtedness of countries with a clearly expressed imbalance in the public debt-to-gross domestic product ratio was demonstrated. Full article

This paper examines the long-memory properties of the returns of exchange-traded funds (ETFs) that provide exposure to companies operating in the fields of artificial intelligence (AI) and robotics listed on the US market, along with other assets such as the WTI crude oil price (West Texas Intermediate), Bitcoin, the S&P 500 index, 10-year US Treasury bonds, and the VIX volatility index. The data frequency is daily and covers the period from 1 January 2023 to 23 June 2025. The adopted fractional integration framework is more general and flexible than those previously used in related studies and allows for a detailed assessment of the degree of persistence in returns. The results indicate that all return series exhibit a high degree of persistence, regardless of the error structure assumed, and that, in general, a linear model adequately captures their dynamics over time. These findings suggest that newly developed AI- and robotics-themed ETFs do not provide investors with additional hedging or diversification benefits compared to more traditional assets, nor do they create new challenges for policymakers concerned with financial stability. Full article

This paper presents an overview of a research line developed at the Istituto Centrale per il Restauro within the CHANGES (Cultural Heritage Active Innovation for Next-Gen Sustainable Society) project, funded under the Italian National Recovery and Resilience Plan. The research was developed in different phases: a first one dedicated to the study of the deep background and the state of the art in the ICR background: history, methodologies and research in the field; a second phase was dedicated to the selection of a specific urban art mural, as a key study with conservation problems connected to some of the principal preservation treatments related to the outdoor context; the mural was also identified as a beloved icon in the public space with a profound socio-cultural meaning for the community. Nido di Vespe, created in 2014 by the artist Lucamaleonte is part of a broader artistic project called M.U.Ro-Museum of Urban Art of Rome, an open-air public art museum located in the Quadraro district in Rome, designed by the artist Diavù. A third phase focused on the research in ICR laboratories, specifically addressing: cleaning, reintegration, and protection strategies adapted to dynamic outdoor environments. A multi-step cleaning system based on polyvinyl alcohol-borax semi-interpenetrated hydrogels loaded with nanostructured fluids was developed to selectively remove spray-paint vandalism while preserving the chemically similar original pictorial layers. The reintegration phase investigated acrylic and urea-aldehyde resins as binders to produce compatible, reversible, and UV-traceable retouching and infilling materials. For surface protection, multilayer coating systems incorporating nanoparticles with antimicrobial, photocatalytic, and UV-stabilizing properties were formulated to enhance durability and chromatic stability. Laboratory tests on mock-ups simulating typical street and urban art materials and morphologies showed satisfactory results, while diagnostic investigations on Nido di Vespe provided the reference data to calibrate the experiments with real mural conditions. Cleaning tests demonstrated promising removal efficiency, influenced by the chemical composition, thickness of the overpainted layers, and surface roughness. The reintegration system met the expected performance requirements, as the tested binders provided good results and allowed the development of compatible, reversible, and distinguishable solutions. Protective coatings showed good results in terms of chromatic stability and surface integrity; however, the long-term behavior of both reintegration, cleaning, and protection systems requires further evaluation. The results achieved so far support the development of sustainable and flexible conservation strategies for the conservation of contemporary street and urban murals and will guide the future application of the selected materials and methodologies in pilot conservation interventions on the mural chosen as a meaningful case study within the broader research. Full article