Search Results (4,590)

Surfactants are used in various washing applications with potential negative environmental and health impacts. The ion-pair 1,3-dioctadecyl-1H-1,2,3-triazol-3-ium-tetraphenylborate (DODTA–TPB) was used to fabricate the potentiometric sensor for the quantification of anionic surfactants. The computational analysis of the DODTA⁺–TPB⁻ adduct reveals a dynamic, thermodynamically favorable interaction driven primarily by hydrophobic C–H∙∙∙π contacts and the flexibility of the C-18 chains, rather than electrostatic or π–π stacking forces. These findings, supported by the MM-PBSA, RDF, and structural analyses, align with broader trends in molecular recognition and provide a foundation for designing advanced ion-pair-based sensors. The sensor showed advanced analytical properties to anionic surfactants with low interfering effects of selected anions. The response of the SDS was investigated in the range from 8.1 × 10⁻⁸ M to 1.0 × 10⁻² M, with a slope of −59.2 mV and a limit of detection (LOD) of 3.1 × 10⁻⁷ M; and DBS was in the range of 8.1 × 10⁻⁸ M to 2.5 × 10⁻³ M with a slope of −57.5 mV and an LOD of 5.9 × 10⁻⁷ M. The sensor was tested on potential interfering ions. Potentiometric titrations of technical-grade anionic surfactants had high recovery rates from 100.2 to 100.4%. The recovery test for spiked samples of surface waters was from 94.2 to 96.5%. The sensor was tested on commercial samples containing anionic surfactants, and the results were compared and showed a good agreement with the two-phase titration method. Full article

The increasing complexity and scale of service-oriented architectures in cloud computing have heightened the demand for intelligent, decentralized, and adaptive service composition techniques. This study proposes an advanced framework that integrates a Multi-Agent System (MAS) with a novel hybrid metaheuristic optimization method, the Integrated Particle-Ant Algorithm (IPAA), to achieve efficient, scalable, and Quality of Service (QoS)-aware service composition. The IPAA dynamically combines the global search capabilities of Particle Swarm Optimization (PSO) with the local exploitation strength of Ant Colony Optimization (ACO), thereby enhancing convergence speed and solution quality. The proposed system is structured into three logical layers—agent, optimization, and infrastructure—facilitating autonomous decision-making, distributed coordination, and runtime adaptability. Extensive simulations using a synthetic cloud service dataset demonstrate that the proposed approach significantly outperforms traditional optimization methods, including standalone PSO, ACO, and random composition strategies, across key metrics such as utility score, execution time, and scalability. Moreover, the framework enables real-time monitoring and automatic re-optimization in response to QoS degradation or Service-Level Agreement (SLA) violations. Through decentralized negotiation and minimal communication overhead, agents exhibit high resilience and flexibility under dynamic service availability. These results collectively suggest that the proposed IPAA-based framework provides a robust, intelligent, and scalable solution for service composition in complex cloud computing environments. Full article

Background/Objectives: Following the recent publication of reassuring outcomes from the ARA MED 330 protocol regarding long-term insulin use in pilots, combined with continuous advancements in diabetes technology, European aeromedical examiners are increasingly optimistic about establishing more flexible medical requirements for insulin-treated aviation professionals. These professionals have historically been considered unfit for duty due to hypoglycemic risks. According to current research, hypoglycemia, the primary incapacitation risk for flight crew, is considered virtually non-existent among air traffic controllers (ATCOs). Additionally, stress-induced hyperglycemia also represents a low-frequency risk in these professionals, who are experienced in managing highly stressful operational environments. This study presents a narrative review examining stress and its metabolic effects in healthy individuals, ATCOs, and people with diabetes (PwD). Methods: This narrative review was conducted based on a comprehensive PubMed search performed by two independent reviewers (GAR and AM) spanning January 2023 to January 2025. The search strategy focused on English-language, peer-reviewed studies involving human participants and addressed stress, glucose regulation, and occupational factors in ATCOs and people with diabetes. Additional relevant articles were identified through reference screening. A total of 33 studies met the inclusion criteria. Studies focusing solely on oxidative or molecular mechanisms were excluded from the analysis. Results: Stressful events consistently triggered the expected hyperglycemic reaction in both healthy individuals and PwD. However, the literature indicates ATCOs demonstrate remarkable stress resilience and adaptation to the demanding conditions of their work environment, suggesting a unique occupational profile regarding metabolic stress responses. Conclusions: These findings contribute valuable insights to ongoing discussions regarding aeromedical fitness standards. The evidence suggests that ATCOs may not face the same metabolic risks as flight crews, indicating that current medical certification processes for insulin-treated aviation professionals warrant reconsideration in light of this emerging evidence. This research supports the potential for more individualized, occupation-specific aeromedical standards that better reflect the actual risk profiles of different aviation roles. Full article

The integration of electric vehicles (EVs) into smart grids (SGs) is reshaping both energy systems and mobility infrastructures. This review presents a comprehensive and cross-disciplinary synthesis of current technologies, methodologies, and challenges associated with EV–SG interaction. Unlike prior reviews that address these aspects in isolation, this work uniquely connects three critical pillars: (i) the evolution of energy storage technologies, including lithium-ion, second-life, and hybrid systems; (ii) optimisation and predictive control techniques using artificial intelligence (AI) for real-time energy management and vehicle-to-grid (V2G) coordination; and (iii) cybersecurity risks and post-quantum solutions required to safeguard increasingly decentralised and data-intensive grid environments. The novelty of this review lies in its integrated perspective, highlighting how emerging innovations, such as federated AI models, blockchain-secured V2G transactions, digital twin simulations, and quantum-safe cryptography, are converging to overcome existing limitations in scalability, resilience, and interoperability. Furthermore, we identify underexplored research gaps, such as standardisation of bidirectional communication protocols, regulatory inertia in V2G market participation, and the lack of unified privacy-preserving data architectures. By mapping current advancements and outlining a strategic research roadmap, this article provides a forward-looking foundation for the development of secure, flexible, and grid-responsive EV ecosystems. The findings support policymakers, engineers, and researchers in advancing the technical and regulatory landscape necessary to scale EV–SG integration within sustainable smart cities. Full article

Online education has become an important channel for extensive, inclusive and flexible learning experiences. However, significant gaps persist in providing truly accessible, personalized and adaptable e-learning environments, especially for students with disabilities, varied language backgrounds, or limited bandwidth. This paper presents AccessiLearnAI, an AI-driven platform, which converges accessibility-first design, multi-format content delivery, advanced personalization, and Progressive Web App (PWA) offline capabilities. Our solution is compliant with semantic HTML5 and ARIA standards, and incorporates features such as automatic alt-text generation for images using Large Language Models (LLMs), real-time functionality for summarization, translation, and text-to-speech capabilities. The platform, built on top of a modular MVC and microservices-based architecture, also integrates robust security, GDPR-aligned data protection, and a human-in-the-loop to ensure the accuracy and reliability of AI-generated outputs. Early evaluations indicate that AccessiLearnAI improves engagement and learning outcomes across multiple ranges of users, suggesting that responsible AI and universal design can successfully coexist to bring equity through digital education. Full article

Electromagnetic induction (EMI) devices have become increasingly popular for their soil bulk properties, soil nutrient status, and use in taking non-invasive soil salinity measurements. However, the high cost of data acquisition (DAQ) systems has been a significant barrier to the widespread adoption of these devices. In this study, we addressed this challenge by developing a cost-effective, easy-to-use, open-source DAQ system, transferable to the end user. This system employs a Raspberry Pi 4 model, paired with various components, to monitor the speed and position of the EM38 (Geonics Ltd, Mississauga, ON, Canada) and compare these with a proprietary CR1000 system. Through our results, we demonstrate that the low-cost DAQ system can successfully extract the analogical signal from the device, which is strongly responsive to the variation in the soil’s physical properties. This cost-effective system is characterized by increased flexibility in software processes and provides performance comparable to the proprietary system in terms of its geospatial data and ECb measurements. This was validated by the strong correlation (R² = 0.98) observed between the data collected from both systems. With our zoning analysis, performed using the Kriging technique, we revealed not only similar patterns in the ECb data but also similar patterns to the Normalized Difference Vegetation Index (NDVI) map, suggesting that soil physical characteristics contribute to variability in crop vigor. Furthermore, the developed web application enabled real-time data monitoring and visualization. These findings highlight that the open-source DAQ system is a viable, cost-effective alternative for soil property monitoring in precision farming. Future enhancements will focus on integrating additional sensors for plant vigor and soil temperature, as well as refining the web application, supporting zone classification based on the use of multiple parameters. Full article

Tire deformation monitoring is a critical requirement for improving vehicle safety, performance, and intelligent transportation systems. However, most existing flexible strain sensors either lack directional sensitivity or have not been validated in real-world driving environments, limiting their practical application in smart tires. In this work, we report the fabrication of a flexible piezoresistive strain sensor based on a porous laser-induced graphene (LIG) network embedded in an Ecoflex elastomer matrix, with integrated directional force recognition. The LIG–Ecoflex sensor exhibits a high gauge factor of 9.7, fast response and recovery times, and stable performance over 10,000 cycles. More importantly, the anisotropic structure of the LIG enables accurate multi-directional stress recognition when combined with a convolutional neural network (CNN), achieving an overall classification accuracy exceeding 98%. To further validate real-world applicability, the sensor was mounted inside passenger car tires and tested under different loads and speeds. The results demonstrate reliable monitoring of tire deformation with clear correlations to load and velocity, confirming robustness under dynamic driving conditions. This study provides a new pathway for the integration of direction-aware, high-performance strain sensors into intelligent tire systems, with broader potential for wearable electronics, vehicle health monitoring, and next-generation Internet of Vehicles applications. Full article

Currently, flexible sensors based on electrochemical principles are predominantly limited to single-parameter detection, making it challenging to meet the demand for synchronous monitoring of multiple analytes in complex physiological environments. This study presents a 3D-printed flexible sensor for synchronous glucose/pH detection. Glucose was quantified via H₂O₂ oxidation current (GOD-catalyzed reaction), while pH was measured through polyaniline (PANI) resistance changes. The ionogel-based microneedle electrode ensures mechanical robustness. At 0.2 V, optimal signal decoupling was achieved: glucose oxidation current dominates, while PANI’s polarization effect is minimized. Neutral pH minimally affected glucose oxidase (GOD) activity, and low glucose concentrations induced negligible pH interference, ensuring orthogonality. In artificial interstitial fluid, the sensor showed glucose: linear response (0.5–2.5 g·L⁻¹, 0.288 μA·mM⁻¹·cm⁻²); pH: piecewise-linear sensitivity (0.155 Ω/pH·cm² for pH > 7; 0.135 Ω/pH·cm² for pH < 7). The design enables real-time multiparameter monitoring with high selectivity, addressing current limitations in flexible electrochemical sensors. Full article

With the increasing integration of renewable energy, virtual power plants (VPPs) have emerged as key market participants by aggregating distributed energy resources. However, their involvement in electricity markets is increasingly challenged by two major uncertainties: price volatility and the intermittency of renewable generation. This study presents the first application of Information Gap Decision Theory (IGDT) within a two-stage cooperative scheduling framework for VPPs. A novel bidding strategy model is proposed, incorporating both robust and opportunistic optimization methods to explicitly account for decision-making behaviors under different risk preferences. In the day-ahead stage, a risk-responsive bidding mechanism is designed to address price uncertainty. In the real-time stage, the coordinated dispatch of micro gas turbines, energy storage systems, and flexible loads is employed to minimize adjustment costs arising from wind and solar forecast deviations. A case study using spot market data from Shandong Province, China, shows that the proposed model not only achieves an effective balance between risk and return but also significantly improves renewable energy integration and system flexibility. This work introduces a new modeling paradigm and a practical optimization tool for precision trading under uncertainty, offering both theoretical and methodological contributions to the coordinated operation of flexible resources and the design of electricity market mechanisms. Full article

Male infertility affects 8–12% of couples worldwide and is solely responsible in up to 30% of cases. Assisted Reproductive Technologies (ARTs) provide potential solutions, particularly in conditions where spermatozoa display structural abnormalities or impaired motility, such as asthenozoospermia. Sperm metabolism demonstrates remarkable flexibility, shifting between glycolysis and oxidative phosphorylation to produce ATP required for motility. Glycerol kinase 2 (GK2) phosphorylates glycerol in the sperm midpiece, generating glycerol-3-phosphate, a key intermediate in glycolysis, lipid metabolism, and oxidative phosphorylation. The localization of GK2 suggests not only a regulatory role in sperm metabolism but also a possible association with VDAC proteins, contributing to ADP-ATP exchange between the cytosol and mitochondria. Elucidating the role of GK2 in spermatozoa is of particular relevance, as this enzyme not only contributes to key metabolic pathways but may also interact with VDAC proteins, influencing mitochondrial function and energy exchange. Such interactions could play a pivotal role in regulating sperm motility. A deeper understanding of these mechanisms could position GK2 as a valuable biomarker: in scenarios where GK2–VDAC interactions are confirmed, it may guide optimized sperm selection methods in ARTs, whereas the absence or impairment of such interactions could serve as a diagnostic indicator in asthenozoospermic men. Full article

Submarine gravity flows, e.g., debris flows and turbidity currents, pose a significant threat to offshore pipeline integrity. This risk primarily manifests through the imposition of substantial dynamic loads on pipelines or their large displacement when impacted by such flows. To enhance our understanding of these threats and facilitate the development of more robust pipeline design and protection strategies, this work reviewed the interactions between submarine gravity flows and offshore pipelines. For an individual pipeline, critical focus lies in characterizing the influence of key parameters—including Reynolds number, span height, impact angle, pipe geometry, ambient temperature, and surface roughness—on both the resultant impact forces and the fluid-structure interaction dynamics. Then, investigations into the interactions between gravity flows and multiple pipes are summarized, where the in-line spacing distance between two pipes is a key factor in reducing the impact force. Further, flow-induced vibration responses of a single pipeline and two tandem pipelines under gravity flows are presented. Building upon a thorough review, we conducted overall evaluations. There are few experimental studies and most investigations ideally treat the seabed to be horizontal, which does not always occur in practical engineering. Choosing empirical formulas to evaluate hydrodynamic loads should carefully consider the specific working conditions. An appropriate non-Newtonian fluid model is significantly important to avoid uncertainties. Some practical risk reduction measures such as streamlined structures and reduction in roughness are recommended. Finally, suggestions for future study and practice are proposed, including the requirement for three-dimensional numerical investigations, assessment of fatigue damage by flow-induced vibrations, consideration of flexible pipeline, and more attention to multiple pipelines. Full article

Organic light-emitting diodes (OLEDs) have emerged as a critical battleground in display technology due to their self-emissive and foldable properties. However, the adoption of polyimide (PI) as a flexible substrate material introduces technical challenges, particularly image sticking. This study proposes an interfacial polarization mechanism to explain this phenomenon, confirmed through dielectric and ferroelectric spectroscopy. The results show that introducing an amorphous silicon (α-Si) interlayer significantly improves interface compatibility, increasing the polarization response frequency from 74 Hz to 116 Hz and reducing residual polarization strength from 2.81 nC/cm² to 1.00 nC/cm². Practical tests on OLED devices demonstrate that the optimized structure (PI/α-Si/SiO₂) lowers the image sticking score from 3.46 to 1.67, validating the proposed mechanism. This research provides both theoretical insights and practical solutions for mitigating image sticking in flexible OLED displays. Full article

A physics-informed neural network (PINN) framework is developed to model the large deformation and coupled electromechanical response of dielectric elastomer tubes for energy harvesting. The system integrates incompressible neo-Hookean elasticity with radial electric loading and compressible gas inflation, leading to nonlinear equilibrium equations with deformation-dependent boundary conditions. By embedding the governing equations and boundary conditions directly into its loss function, the PINN enables accurate, mesh-free solutions without requiring labeled data. It captures realistic pressure–volume interactions that are difficult to address analytically or through conventional numerical methods. The results show that internal volume increases by over 290% during inflation at higher reference pressures, with residual stretch after deflation reaching 9.6 times the undeformed volume. The axial force, initially tensile, becomes compressive at high voltages and pressures due to electromechanical loading and geometric constraints. Harvested energy increases strongly with pressure, while voltage contributes meaningfully only beyond a critical threshold. To ensure stable training across coupled stages, the network is optimized using the Optuna algorithm. Overall, the proposed framework offers a robust and flexible tool for predictive modeling and design of soft energy harvesters. Full article

Problem-based learning (PBL) is a student-centered instruction approach focused on skills development in problem-solving, interaction, autonomy, and critical thinking to learn and act to co-create new knowledge and solutions. Rarely, but authors sometimes identify the benefits of PBL for educators, for example, by allocating instructional time more flexibly for monitoring student performance and discussing issues. However, in the era where collaboration among universities and industries is emphasized, the authors pay little attention to contextualizing PBL in a broader context, such as bringing benefits for relationship management with the industry and alumni, promoting regional development, corporate and social responsibility, marketing of educational organizations, and talent development to create a mutual benefit-based ecosystem. Academic discussions about PBL planning and implementation also neglect the needs and motivation of industry stakeholders to get involved, thus narrowing not only the possibilities for cooperation between both parties but also negatively affecting student learning outcomes, which also directly depend on industry partners. Full article

This article analyzes responses of museums and art institutions in Israel to the events of October 7th. It stresses the public role of museums in times of crisis, and the ways that diverse curatorial choices reflect upon their institutions’ pursuits. It focuses on the case study of curatorial empathy, enacted at the Tel Aviv University Art Gallery, noting its aptness at times of crisis and trauma. The article claims that in a society that experiences both internal and external conflicts, the approach of empathy offers flexibility and openness that allow the museum to respond to public need on the one hand, and poses challenging questions on the other. Such questions are explored through the method of artistic-scientific dialogue. As contentions multiply, overlap, and contrast, the expansion of circles of identification becomes a key strategy in addressing this crisis. This essay argues that empathy is a more thoughtful and productive curatorial approach, because it emphasizes connection rather than only identity. From this perspective, the crisis that started on October 7th is not only that of war, loss, and grief, but also that of a threat to humanness under extreme angst. Full article