Search Results (5,030)

This work contextualizes the possibility of deriving a unifying artificial intelligence framework by walking in the footsteps of General, Explainable, and Verified Artificial Intelligence (GEVAI): by considering explainability not only at the level of the results produced by a specification but also considering the explicability of the inference process as well as the one related to the data processing step, we can not only ensure human explainability of the process leading to the ultimate results but also mitigate and minimize machine faults leading to incorrect results. This, on the other hand, requires the adoption of automated verification processes beyond system fine-tuning, which are essentially relevant in a more interconnected world. The challenges related to full automation of a data processing pipeline, mostly requiring human-in-the-loop approaches, forces us to tackle the framework from a different perspective: while proposing a preliminary implementation of GEVAI mainly used as an AI test-bed having different state-of-the-art AI algorithms interconnected, we propose two other data processing pipelines, LaSSI and EMeriTAte+DF, being a specific instantiation of GEVAI for solving specific problems (Natural Language Processing, and Multivariate Time Series Classifications). Preliminary results from our ongoing work strengthen the position of the proposed framework by showcasing it as a viable path to improve current state-of-the-art AI algorithms. Full article

As medical technology develops and digital demands grow, personal health records (PHRs) are becoming more patient-centered than before based on cloud-based health information exchanges. While enhancing data accessibility and sharing, these systems present privacy and security issues, including data breaches and unauthorized access. We developed a post-quantum, group-oriented encryption scheme using the Crystal-Kyber Key encapsulation mechanism (KEM). Leveraging lattice-based post-quantum cryptography, this scheme ensures quantum resilience and chosen ciphertext attack security for layered cloud PHR environments. It supports four encryption modes: individual, group, subgroup-specific, and authorized subgroup decryption, meeting diverse data access needs. With efficient key management requiring only one private key per user, the developed scheme strengthens the privacy and security of PHRs in a future-proof, flexible, and scalable manner. Full article

This study aims to understand the meaning nursing professionals attribute to their lived experiences of providing humanized care within a public hospital setting. Grounded in Jean Watson’s theory of human caring, the research adopts a qualitative, descriptive phenomenological design to capture the perceptions and emotions of nurses regarding humanized care. Data were collected through semi-structured interviews with nine experienced nurses, selected through purposive sampling. The interviews, conducted virtually between July and December 2024, were analyzed using Colaizzi’s method and supported by Atlas.ti software. Four main thematic categories emerged: institutional health policies, professional image and identity, strengths and challenges in care, and essential competencies for humanized care. The findings highlight the critical role of empathy, cultural sensitivity, ethical commitment, and emotional presence in delivering compassionate care. Participants emphasized that, beyond clinical procedures, humanized care requires relational and contextual sensitivity, often hindered by institutional limitations and excessive administrative burdens. The study concludes that nursing professionals are key agents in promoting ethical, empathetic, and culturally respectful practices that humanize health services. These insights offer valuable contributions for designing policies and training strategies aimed at strengthening humanized care as a cornerstone of quality healthcare systems. Full article

In recent years, growing concerns over environmental degradation and deepening awareness of the necessity of sustainable development have propelled green and low-carbon energy transition into a focal issue for both academia and policymakers. By decomposing energy transition into the transformation of energy structure and the upgrading of energy efficiency, this study investigates the impact and mechanisms of green finance on energy transition across 30 provinces (municipalities and autonomous regions) in China, with the exception of Tibet. In addition, the impact of climate change is incorporated into the analytical framework. Empirical results demonstrate that green finance development significantly accelerates energy transition, a conclusion robust to rigorous validation. Analysis of the mechanism shows that green finance promotes energy transition through the facilitation of technological innovation and the upgrade of industrial structures. Moreover, empirical evidence reveals that climate change undermines the promotional influence of sustainable finance on energy system transformation. The magnitude of this suppression varies nonlinearly across provincial jurisdictions with differing energy transition progress. Regional heterogeneity analyses further uncover marked discrepancies in climate–finance interactions, demonstrating amplified effects in coastal economic hubs, underdeveloped western provinces, and regions with mature eco-financial markets. According to these findings, actionable policy suggestions are put forward to strengthen green finance and accelerate energy transition. Full article

The Internet of Medical Things (IoMT) is revolutionizing healthcare by enabling continuous patient monitoring, early diagnosis, and personalized treatments. However, the het-erogeneity of IoMT devices and the lack of standardized protocols introduce serious security vulnerabilities. To address these challenges, we propose a hybrid BiLSTM-DNN intrusion detection system, named HBiLD-IDS, that combines Bidirectional Long Short-Term Memory (BiLSTM) networks with Deep Neural Networks (DNNs), leveraging both temporal dependencies in network traffic and hierarchical feature extraction. The model is trained and evaluated on the CICIoMT2024 dataset, which accurately reflects the diversity of devices and attack vectors encountered in connected healthcare environments. The dataset undergoes rigorous preprocessing, including data cleaning, feature selection through correlation analysis and recursive elimination, and feature normalization. Compared to existing IDS models, our approach significantly enhances detection accuracy and generalization capacity in the face of complex and evolving attack patterns. Experimental results show that the proposed IDS model achieves a classification accuracy of 98.81% across 19 attack types confirming its robustness and scalability. This approach represents a promising solution for strengthening the security posture of IoMT networks against emerging cyber threats. Full article

Under the rapid development of the digital economy, the interactive relationship between exports and the digital economy has become an important issue for promoting regional economic growth. Based on the panel data of 31 provinces and municipalities in China from 2012 to 2022, this paper systematically examines the impact of exports on economic growth and the moderating role of the digital economy, and it introduces research and development (R&D) investment to test its mediating mechanism. The research finds that exports significantly promote regional economic growth. The digital economy has a negative moderating effect on the export growth effect, and it is significant in the eastern region but not significant in the central and western regions, showing obvious regional heterogeneity. R&D investment has played a partial mediating role between exports and economic growth. This paper suggests that the government should focus on regional differences, promote the deep integration of the digital economy and exports, enhance technological innovation capabilities, formulate differentiated policies based on local conditions, strengthen the construction of digital infrastructure, optimize the export structure, support the development of R&D-driven enterprises, and build a digital export system that promotes regional coordination and high-quality growth, so as to achieve high-quality coordinated sustainable regional development. This paper also has certain reference value for other developing economies, in promoting the integration of the digital economy and trade. Full article

Distributed generation strengthens distribution network reliability by placing generators close to load centers. The integration of electric vehicle charging stations (EVCSs) with PV systems mitigates the effects of EV charging burden. In this research, the objective is to combineEVCSs with distributed generation (DG) units in the Puducherry smart grid system to obtain optimized locations and enhance their reliability. To determine the right nodes for DGs and EVCSs in an uneven distribution network, the modified decision-making (MDM) algorithm and the model predictive control (MPC) approach are used. The Indian utility 29-node distribution network (IN29NDN), which is an unbalanced network, is used for testing. The effects of PV systems and EVCS units are studied in several settings and at various saturation levels. This study validates the correctness of its findings by evaluating the outcomes of proposed methodological approaches. DIgSILENT Power Factory is used to conduct the simulation experiments. The results show that optimizing the location of the DG unit and the size of the PV system can significantly minimize power losses and make a distribution network (DN) more reliable. Full article

In line with the goals of “peak carbon emissions and carbon neutrality”, this study aims to develop a market-coordinated operation mechanism to promote renewable energy adoption and consumption, addressing the challenges of integrating medium- and long-term trading with spot markets in power systems with high renewable energy penetration. A three-stage joint operation framework is proposed. First, a medium- and long-term trading game model is established, considering multiple energy types to optimize the benefits of market participants. Second, machine learning algorithms are employed to predict renewable energy output, and a contract decomposition mechanism is developed to ensure a smooth transition from medium- and long-term contracts to real-time market operations. Finally, a day-ahead market-clearing strategy and an incentive-compatible settlement mechanism, incorporating the constraints from contract decomposition, are proposed to link the two markets effectively. Simulation results demonstrate that the proposed mechanism effectively enhances resource allocation and stabilizes market operations, leading to significant revenue improvements across various generation units and increased renewable energy utilization. Specifically, thermal power units achieve a 19.12% increase in revenue, while wind and photovoltaic units show more substantial gains of 38.76% and 47.52%, respectively. Concurrently, the mechanism drives a 10.61% increase in renewable energy absorption capacity and yields a 13.47% improvement in Tradable Green Certificate (TGC) utilization efficiency, confirming its overall effectiveness. This research shows that coordinated optimization between medium- and long-term/spot markets, combined with a well-designed settlement mechanism, significantly strengthens the market competitiveness of renewable energy, providing theoretical support for the market-based operation of the new power system. Full article

This study examines the progress, challenges, and successes in implementing Sustainable Development Goal 12 (SDG12), focusing on responsible consumption and production, using Qatar as a case study. The State has integrated Sustainable Consumption and Production (SCP) into national policies, established coordination mechanisms, and implemented action plans aligned with SDG12 targets. Achievements include renewable energy adoption, waste management reforms, and sustainable public procurement, though challenges persist in rationalizing fossil fuel subsidies, addressing data gaps, and enhancing corporate sustainability reporting. Efforts to reduce food loss and waste through redistribution programs highlight the country’s resilience, despite logistical obstacles. The nation has also advanced hazardous waste management, environmental awareness, and sustainable tourism policies, though gaps in data systems and policy coherence remain. Qatar’s approach provides a valuable local-to-global example of balancing resource-dependent economies with sustainability goals. Its strategies and lessons offer potential adaptability for other nations, especially those facing similar challenges in achieving SDG12. By strengthening data systems, enhancing policy integration, and fostering regional and international cooperation, Qatar’s efforts underscore the importance of aligning economic growth with environmental stewardship, serving as a blueprint for global sustainability initiatives. Full article

Although organizational resilience is well established, refining the systematic quantitative evaluation of health systems resilience (HSR) remains an ongoing opportunity for advancement. Research either focuses on individual HSR indicators, such as social welfare policy, public expenditure, health insurance, healthcare quality, and technology, or broadly examines socio-economic factors, highlighting the need for a more comprehensive methodological approach. This study employed the Slacks-Based Measure (SBM) within Data Envelopment Analysis (DEA) to analyze efficiency by maximizing outputs. It systematically examined key HSR factors across countries, providing insights for improved policymaking and resource allocation. Taking a five-year (2016–2020) dataset that covered 55 to 56 countries and evaluating 17 indicators across governance, health systems, and economic aspects, the paper presents that all sixteen top-ranked countries with a perfect efficiency score of 1 belonged to the high-income group, with ten in Europe, highlighting regional HSR differences. This paper concludes that adequate economic resources form the foundation of HSR and ensure stability and sustained progress. A properly supported healthcare workforce is essential for significantly enhancing health systems and delivering quality care. Last, effective governance and the equitable allocation of resources are crucial for fostering sustainable development and strengthening HSR. Full article

This study explores the transformative potential of blockchain technology in overhauling conventional housing rental systems. It specifically addresses persistent issues, such as information asymmetry, fraudulent listings, weak Rental Agreements, and data breaches. A comprehensive review of ten academic publications highlights the architectural frameworks, underlying technologies, and myriad benefits of decentralized rental platforms. The intrinsic characteristics of blockchain—immutability, transparency, and decentralization—are pivotal in enhancing the credibility of rental information and proactively preventing fraudulent activities. Smart contracts emerge as a key innovation, enabling the automated execution of Rental Agreements, thereby significantly boosting efficiency and minimizing reliance on intermediaries. Furthermore, Decentralized Identity (DID) solutions offer a robust mechanism for securely managing identities, effectively mitigating risks associated with data leakage, and fostering a more trustworthy environment. The suitability of platforms such as Hyperledger Fabric for developing such sophisticated rental systems is also critically evaluated. Blockchain-based systems promise to dramatically increase market transparency, bolster transaction security, and enhance fraud prevention. They also offer streamlined processes for dispute resolution. Despite these significant advantages, the widespread adoption of blockchain in the rental sector faces several challenges. These include inherent technological complexity, adoption barriers, the need for extensive legal and regulatory adaptation, and critical privacy concerns (e.g., ensuring compliance with GDPR). Furthermore, blockchain scalability limitations and the intricate balance between data immutability and the necessity for occasional data corrections present considerable hurdles. Future research should focus on developing user-friendly DID solutions, enhancing blockchain performance and cost-efficiency, strengthening smart contract security, optimizing the overall user experience, and exploring seamless integration with emerging technologies. While current challenges are undeniable, blockchain technology offers a powerful suite of tools for fundamentally improving the rental market’s efficiency, transparency, and security, exhibiting significant potential to reshape the entire rental ecosystem. Full article

Background: School-based tobacco control policies are critical for preventing youth tobacco use. While many districts adopt formal policies to create smoke- and vape-free environments, the degree to which these policies are enforced at the school level may vary, influencing their effectiveness. Little is known about how consistently such policies are implemented across schools within urban school districts. Objectives: This study aimed to examine the existence and enforcement of school-level tobacco control policies in an urban public school system, using Baltimore City schools as a case example. Methods: We conducted a survey of school personnel from 20 high schools in Baltimore City in 2024. The survey instrument assessed the presence and enforcement of policies related to tobacco use prevention, communication, signage, disciplinary actions, and institutional support. Descriptive statistics (frequencies and percentages) were used to summarize responses. Spearman correlations were also used for bivariate correlations. Additional school-level and neighborhood-level contextual data were collected from the internet (neighborhood socioeconomic status and school performance). Results: While many policies existed across the 20 participating schools, their enforcement was widely inconsistent. Most schools reported the existence of policies prohibiting tobacco use in school buildings (60%) and vehicles (55%). However, few schools had visible tobacco-free signage (35%) or offered cessation programs (15%). Communication of policies to students (70%) and staff (65%) was the most commonly enforced aspect of tobacco control policies. Conclusions: Findings suggest that while tobacco control policies may be adopted across urban school systems, their enforcement at the school level remains uneven. Greater attention may be needed to support policy implementation and to reduce variability in school-level practices. Baltimore City serves as a useful case study to understand these challenges and identify opportunities for strengthening school-based tobacco prevention efforts. Full article

Background: this research presents an integrated approach to enhancing the sustainability of plastic bag supply chains in Indonesia by addressing critical issues related to ineffective post-consumer waste management and low recycling rates. The objective of this study is to develop a combined framework of material flow analysis (MFA) and sustainable supply chain planning to improve demand forecasting and inflow management across the plastic bag lifecycle. Method: the research adopts a quantitative method using the XGBoost algorithm for forecasting and is supported by a polymer-based MFA framework that maps material flows from production to end-of-life stages. Result: the findings indicate that while production processes achieve high efficiency with a yield of 89%, more than 60% of plastic bag waste remains unmanaged after use. Moreover, scenario analysis demonstrates that single interventions are insufficient to achieve circularity targets, whereas integrated strategies (e.g., reducing export volumes, enhancing waste collection, and improving recycling performance) are more effective in increasing recycling rates beyond 35%. Additionally, the study reveals that increasing domestic recycling capacity and minimizing dependency on exports can significantly reduce environmental leakage and strengthen local waste management systems. Conclusions: the study’s novelty lies in demonstrating how machine learning and material flow data can be synergized to inform circular supply chain decisions and regulatory planning. Full article

Water governance in Europe faces mounting challenges from climate change, demographic pressures, and aging infrastructure—especially in Southern regions increasingly affected by drought and institutional fragmentation. In contrast, Nordic countries such as Denmark and Sweden exhibit coherent, integrated governance systems with strong regulatory oversight. This study introduces the Water Governance Maturity Index (WGMI), a document-based assessment tool designed to evaluate national water governance across five dimensions: institutional capacity, operational effectiveness, environmental ambition, equity, and climate adaptation. Applying the WGMI to eight EU countries—four Nordic and four Southern—reveals a persistent North–South divide in governance maturity. Nordic countries consistently score in the “advanced” or “model” range, while Southern countries face systemic gaps in implementation, climate integration, and territorial inclusion. Based on these findings, the study offers actionable policy recommendations, including the establishment of independent regulators, strengthening of river basin coordination, mainstreaming of climate-water strategies, and expansion of affordability and participation mechanisms. By translating complex governance principles into measurable indicators, the WGMI provides a practical tool for benchmarking reform progress and supporting the EU’s broader agenda for just resilience and climate adaptation. Unlike broader frameworks like SDG 6.5.1, the WGMI’s document-based, dimension-specific approach provides granular, actionable insights for governance reform, enhancing its utility for EU and global policymakers. Full article

To study the influence of curing agent structure on the properties of epoxy resin, four types of aromatic diamines with the structure of diphenyl methane (4,4′-methylenedianiline (MDA), 4,4′-methylenebis(2-ethylaniline) (MOEA), 4,4′-methylenebis(2-chloroaniline) (MOCA), and 4,4′-methylenebis(3-chloro-2,6-diethylaniline) (MCDEA)) and a high-performance epoxy resin, 3-(oxiran-2-ylmethoxy)-N,N-bis(oxiran-2-ylmethyl)aniline (AFG-90MH), were used in this study. The resulting resin systems were designated as AFG-90MH-MDA, AFG-90MH-MOEA, AFG-90MH-MOCA, and AFG-90MH-MCDEA. After curing, these systems were named AFG-90MH-MDA-C, AFG-90MH-MOEA-C, AFG-90MH-MOCA-C, and AFG-90MH-MCDEA-C. The influence of the structure of the diamines on the processability, curing reaction activity, and thermal and mechanical properties (including flexural and tensile properties) of the epoxy resins were investigated. These systems demonstrate excellent processability with wide processing windows ranging from 30 °C to 110–160 °C while maintaining low viscosity. Consistent apparent activation energy (E_a) trends via both Kissinger and Flynn-Wall-Ozawa methods were observed. The epoxy systems exhibit the following increasing E_a sequence: AFG-90MH-MDA < AFG-90MH-MOEA < AFG-90MH-MOCA < AFG-90MH-MCDEA. The processability and curing reaction kinetic results indicate that the reactivities of the diamines decrease in the order: MDA > MOEA > MOCA > MCDEA. Polar chlorine substituents in diamines strengthen intermolecular interactions, thereby enhancing mechanical performance. The flexural strength of cured epoxy systems decreases as follows with corresponding values: AFG-90MH-MOCA-C (165 MPa) > AFG-90MH-MDA-C (158 MPa) > AFG-90MH-MCDEA-C (148 MPa) > AFG-90MH-MOEA-C (136 MPa). Diamines with substituents like chlorine or ethyl groups reduce the glass transition temperatures (T_g) of the cured resin systems. However, the cured resin systems with the diamines containing chlorine demonstrate superior thermal performance compared to those with ethyl groups. The cured epoxy systems exhibit the following descending glass transition temperature order with corresponding values: AFG-90MH-MDA-C (213 °C) > AFG-90MH-MOCA-C (190 °C) > AFG-90MH-MCDEA-C (183 °C) > AFG-90MH-MOEA-C (172 °C). Full article