Search Results (10,548)

With recent advancements in digital environments, user authentication is becoming increasingly important. Traditional authentication methods such as passwords and PINs suffer from inherent limitations, including vulnerability to theft, guessing, and replay attacks. Consequently, there has been a growing body of research on more accurate and efficient user authentication methods. One such approach involves the use of biometric signals to enhance security. However, biometric methods face significant challenges in ensuring stable authentication accuracy, primarily due to variations in the user’s environment, physical activity, and health conditions. To address these issues, this paper proposes a biometric-signal-based user authentication system using graph neural networks (GNNs). The feasibility of the proposed system was evaluated using an electromyogram (EMG) dataset specifically constructed by Chosun University for user authentication research. GNNs have demonstrated exceptional performance in modeling the relationships among complex data and attracted attention in various fields. Specifically, GNNs are well-suited for modeling user behavioral patterns while considering temporal and spatial relationships, making them an ideal method for adapting to dynamic and evolving user patterns. Unlike traditional neural networks, GNNs can dynamically learn and adapt to changes or evolutions in user behavioral patterns over time. This paper describes the design and implementation of a user authentication system using GNNs with an EMG dataset and discusses how the system can adapt to dynamic and changing user patterns. Full article

Graphoepitaxial directed self-assembly (DSA) of block copolymers (BCPs) has emerged as a promising strategy for sub-30 nm line spacing patterning in semiconductor nanofabrication. Among the available BCP systems, polystyrene-block-poly (methyl methacrylate) (PS-b-PMMA) has been extensively utilized due to its well-characterized phase behavior and compatibility with standard lithographic processes. However, achieving a high-fidelity pattern with PS-b-PMMA remains challenging, owing to its limited etch contrast and reliance on UV-assisted degradation for PMMA removal. In this study, we report the synthesis of an acid-cleavable lamellar BCP, PS-N=CH-PMMA, incorporating a dynamic Schiff base (-N=CH-) linkage at the junction. This functional design enables UV-free wet etching, allowing selective removal of PMMA domains using glacial acetic acid. The synthesized copolymers retain the self-assembly characteristics of PS-b-PMMA and form vertically aligned lamellar nanostructures, with domain spacings tunable from 36.1 to 40.2 nm by varying the PMMA block length. When confined within 193i-defined trench templates with a critical dimension (CD) of 55 nm (trench width), these materials produced well-ordered one-space-per-trench patterns with interline spacings tunable from 15 to 25 nm, demonstrating significant line spacing shrinkage relative to the original template CD. SEM and FIB-TEM analyses confirmed that PS-N=CH-PMMA exhibits markedly improved vertical etch profiles and reduced PMMA residue compared to PS-b-PMMA, even without UV exposure. Furthermore, Ohta–Kawasaki simulations revealed that trench sidewall angle critically influences PS distribution and residual morphology. Collectively, this work demonstrates the potential of dynamic covalent chemistry to enhance the wet development fidelity of BCP lithography and offers a thermally compatible, UV-free strategy for sub-30 nm nanopatterning. Full article

The environmental crisis demands transformative solutions on both technological and societal levels. Bioinspired approaches, which draw from the principles of natural systems, have emerged as a promising interdisciplinary framework to address these challenges. These approaches not only drive technological innovation but also provoke critical philosophical and ethical discourse, particularly in the field of biomimicry. Philosophical and ethical questions include: How can we ethically justify drawing inspiration from nature without exploiting it? How might a shift toward a bioinspired perspective alter our relationship with nature? How could a reorientation toward nature influence ethical frameworks and guide human behavior toward the environment? This narrative review systematically examines key philosophical and ethical perspectives within biomimicry, while focusing on potentials as well as limitations of these approaches to the environmental crisis. In doing so, it explores key perspectives such as “biomimetic ethics”, the “ontology of nature”, “bioinclusivity”, and the “naturalistic fallacy”. Full article

In lateral-joint-widening projects of multi-span continuous concrete box girder bridges, significant discrepancies in longitudinal shrinkage, creep deformation, and vertical displacement between the existing and newly added bridge sections can lead to stress concentration and subsequent concrete cracking. Notably, such incompatibility often results in pronounced overall lateral bending deformation, which compromises the structural safety and service reliability of the widened bridge. To address these challenges, this study proposes a novel sliding-type transverse connection structure. This innovative connection enables the independent development of longitudinal shrinkage and creep deformation in the new bridge superstructure relative to the old one through a sliding mechanism, thereby effectively mitigating stress concentration and minimizing overall bending deformation caused by differential deformations. To validate the feasibility and elucidate the load transfer mechanism of the proposed structure, both scaled model tests and finite element simulations were conducted. The results indicate that the connection not only effectively coordinates longitudinal deformation differences and accommodates vertical deformation between the flange plates of the new and old bridges, but also ensures efficient transverse load transfer through shear force transmission. The structural behavior is primarily governed by shear stress distribution. These findings demonstrate that the sliding-type transverse connection significantly improves deformation compatibility in bridge widening applications, thereby enhancing the mechanical performance and safety reliability of the overall structure. Full article

The use of vertically stacked architectures in three-dimensional integrated circuits (3DICs) offers a transformative path for advancing Moore’s Law by significantly boosting computational density. A key obstacle arises from the integration of heterogeneous materials, which introduces critical thermo-mechanical challenges, particularly due to the mismatch in the coefficients of thermal expansion (CTE) of silicon (Si) and copper (Cu). Such mismatches can compromise mechanical reliability and complicate the definition of the keep-out zone (KOZ) in dense systems. This paper provides a detailed analysis of the thermo-mechanical behavior of stacked 3DICs, exploring a range of device geometries and process conditions. The findings reveal that CTE-induced stress is the dominant factor influencing mechanical integrity, surpassing other mechanical forces. It is concluded that the KOZ must be no less than 1.5 times the feature diameter to adequately mitigate stress-related risks. Additionally, thermal stress interactions in configurations with adjacent structures can increase the KOZ requirement by up to 33.3% relative to isolated instances. Yet, multi-layered designs show enhanced thermal performance, a benefit attributed to the high thermal conductivity of copper. The knowledge gained from this study provides a valuable framework for optimizing the reliability and thermal management of 3DIC systems and is especially relevant for high-performance sensor devices where both mechanical stability and efficient heat dissipation are vital. Full article

The issue of in-orbit optimal safe surrounding control for service satellite (SSat) formation against a huge unknown target satellite (TSat) with specific structures is solved by using relative measurements only, and an optimal cooperative safe surrounding (OCSS) hybrid controller achieving both target tracking (TT) and configuration tracking (CT) is proposed corresponding to the two equal sub-objectives. Facing the challenges caused by incomplete information of the TSat, by using relative measurements only, the initial-condition-free boundaries are constructed by an arctan-based state transformation to directly constrain the target tracking error to perform prescribed transient and steady-state behaviors. Based on the shared TT control law, optimal collision-free CT controllers for all SSats are further solved via a nonzero-sum differential game, where the collision threat from all SSats and target structures are modeled by a novel circumscribed-sphere model. Finally, the effectiveness and advantages of the proposed OCSS control technique is verified by simulation results. Full article

Addressing the challenges of insufficient incentives, weak constraints, and superficial adoption in promoting human–robot collaboration (HRC) in the construction industry, this study develops a tripartite evolutionary game model among government, contractors, and on-site teams under bounded rationality. Lyapunov stability analysis and numerical simulation are employed to conduct parameter sensitivity analyses. The results show that a strategy profile characterized by flexible regulation, deep adoption, and high-effort collaboration constitutes a stable evolutionary outcome. Moderately increasing government incentives helps accelerate convergence but exhibits diminishing returns under fiscal constraints, indicating that subsidies alone cannot sustain genuine engagement. Reducing penalties for contractors and on-site teams, respectively, induces superficial adoption and low effort, whereas strengthening penalties for bilateral violations simultaneously compresses the space for opportunistic behavior. When the payoff advantage of deep adoption narrows or the payoff from perfunctory adoption rises, convergence toward the preferred steady state slows markedly. Based on the discussion and simulation evidence, we recommend dynamically matching incentives, sanctions, and performance feedback: prioritizing flexible regulation to reduce institutional frictions, configuring differentiated sanctions to maintain a positive payoff differential, reinforcing observable performance to stabilize frontline effort, and adjusting policy weights by project stage and actor characteristics. The study delineates how parameter changes propagate through behavioral choices to shape collaborative performance, providing actionable guidance for policy design and project governance in advancing HRC. Full article

The transport sector significantly contributes to global greenhouse gas emissions, making electromobility crucial in the race toward the United Nations Sustainable Development Goals. In recent years, the increasing competition among manufacturers, the development of cheaper batteries, the ongoing policy support, and people’s greater environmental awareness have consistently increased electric vehicles (EVs) adoption. Nevertheless, EVs charging needs—highly influenced by EV drivers’ behavior uncertainty—challenge their integration into the power grid on a massive scale, leading to potential issues, such as overloading and grid instability. Smart charging strategies can mitigate these adverse effects by using information and communication technologies to optimize EV charging schedules in terms of power systems’ constraints, electricity prices, and users’ preferences, benefiting stakeholders by minimizing network losses, maximizing aggregators’ profit, and reducing users’ driving range anxiety. To this end, accurately forecasting EV charging demand is paramount. Traditionally used forecasting methods, such as model-driven and statistical ones, often rely on complex mathematical models, simulated data, or simplifying assumptions, failing to accurately represent current real-world EV charging profiles. Machine learning (ML) methods, which leverage real-life historical data to model complex, nonlinear, high-dimensional problems, have demonstrated superiority in this domain, becoming a hot research topic. In a scenario where EV technologies, charging infrastructure, data acquisition, and ML techniques constantly evolve, this paper conducts a systematized literature review (SLR) to understand the current landscape of ML-based EV charging demand forecasting, its emerging trends, and its future perspectives. The proposed SLR provides a well-structured synthesis of a large body of literature, categorizing approaches not only based on their ML-based approach, but also on the EV charging application. In addition, we focus on the most recent technological advances, exploring deep-learning architectures, spatial-temporal challenges, and cross-domain learning strategies. This offers an integrative perspective. On the one hand, it maps the state of the art, identifying a notable shift toward deep-learning approaches and an increasing interest in public EV charging stations. On the other hand, it uncovers underexplored methodological intersections that can be further exploited and research gaps that remain underaddressed, such as real-time data integration, long-term forecasting, and the development of adaptable models to different charging behaviors and locations. In this line, emerging trends combining recurrent and convolutional neural networks, and using relatively new ML techniques, especially transformers, and ML paradigms, such as transfer-, federated-, and meta-learning, have shown promising results for addressing spatial-temporality, time-scalability, and geographical-generalizability issues, paving the path for future research directions. Full article

Background/Objectives: Idiopathic toe walking (ITW) is a diagnosis of exclusion in children who demonstrate a persistent toe-walking gait without an identifiable underlying neuromuscular or orthopedic pathology. The classification of toe-walking behavior (TWB) in children with Autism Spectrum Disorder (ASD) remains an area of debate, with some considering it a part of the broader ITW spectrum, while others view it as a distinct entity. Children with TWB associated with ASD (Autistic Toe Walking—ATW) present unique clinical challenges. This subgroup exhibits a higher prevalence of toe walking, and their gait patterns are often associated with underlying neurodevelopmental differences, frequently leading to increased resistance to conventional treatment approaches and higher rates of persistence and recurrence. This narrative review aims to summarize the available evidence on interventions for ATW, highlight differences compared to ITW and discuss implications for clinical practice. Methods: A literature search was performed, including articles that addressed interventions for toe walking in children with ASD. Results: The literature is limited and heterogeneous. Identified interventions include physiotherapy, orthoses, botulinum toxin injections, serial casting, and surgical procedures. Evidence of effectiveness is scarce, with most studies consisting of small case series. ATW differs from classic ITW in some aspects of pathophysiology and clinical presentation. Treatment decisions should balance potential benefits with risks, particularly regarding repeated anesthesia exposure during casting versus earlier surgical options. Conclusions: Evidence for managing ATW is limited. While comparisons to ITW may be useful, clinicians must recognize that they present distinct characteristics. Future research should focus on standardized definitions and controlled trials to guide management. Full article

Background: Adaptogens, commonly used as traditional herbal medicinal products for the relief of symptoms of stress, such as fatigue and exhaustion, belong to a category of physiologically active compounds related to the physiological process of adaptability to stressors. They are used both as pharmaceuticals in medicine and as dietary supplements or nutraceuticals in nutrition, depending on the doses, indications to treat diseases, or support health functions. However, such a dual-faced nature of adaptogens can lead to inconsistencies and contradictory outcomes from Food and Drug regulatory authorities in various countries. Aims: This narrative literature review aimed to (i) specify five steps of pharmacological testing of adaptogens, (ii) identify the sources of inconsistencies in the assessment of evidence the safety, efficacy, and quality of multitarget adaptogenic botanicals, and (iii) propose potential solutions to address some food and drug regulatory issues, specifically adaptogenic botanicals used for prevention and treatment of complex etiology diseases including stress-induced, and aging-related disorders. Overview: This critically oriented narrative review is focused on (i) five steps of pharmacological testing of adaptogens are required in a sequential order, including appropriate in vivo and in vitro models in animals, in vitro model, and mechanisms of action by a proper biochemical assay and molecular biology technique in combination with network pharmacology analysis, and clinical trials in stress-induced and aging-related disorders; (ii) the differences between the requirements for the quality of pharmaceuticals and dietary supplements of botanical origin; (iii) progress, trends, pitfalls, and challenges in the adaptogens research; (iv) inadequate assignment of some plants to adaptogens, or insufficient scientific data in case of Eurycoma longifolia; (v) inconsistencies in botanical risk assessments in the case of Withania somnifera. Conclusions: This narrative review highlights the importance of harmonized standards, transparent methodologies, and a balanced, evidence-informed approach to ensure consumers receive effective and safe botanicals. Future perspectives and proposed solutions include (i) establish internationally harmonized guidelines for evaluating botanicals based on their intended use (e.g., pharmaceutical vs. dietary supplement), incorporating traditional use data alongside modern scientific methods; (ii) encourage peer review and transparency in national assessments by mandating public disclosure of methodologies, data sources, and expert affiliations; (iii) create a tiered evidence framework that allows differentiated standards of proof for traditional botanical supplements versus pharmaceutical candidates; (iv) promote international scientific dialogs among regulators, researchers, and industry to develop consensus positions and avoid unilateral bans that may lack scientific rigor; (v) formally recognize adaptogens a category of natural products for prevention stress induced brain fatigue, behavioral, and aging related disorders. Full article

Clove oil is an essential oil used in food and pharmaceutical applications, with a market value of 300+ million dollars per year. Microemulsions have been used as effective clove oil delivery vehicles and could also be used to develop new extraction processes from clove buds. Eugenol, the main component of clove oil, is a polar oil that behaves as a surfactant and as an oil. This bifunctional behavior makes formulating clove oil microemulsions a challenging task. Here, we used a version of the Hydrophilic–Lipophilic Difference (HLD) + Net-Average Curvature (NAC) model that incorporates the bifunctional polar oil model to predict and fit the phase behavior of lecithin (surfactant) + polyglycerol-10 caprylate (hydrophilic linker) microemulsions using mixtures of heptane and clove oil as the oil phase. Using HLD-NAC parameters from the literature, the predicted HLD-NAC curves reproduced the expected phase transitions and the trends in Eugenol segregation toward the surfactant layer. Using these literature parameters as an initial guess to fit the experimental phase volumes produced accurate calculated phase volumes, and predicted interfacial tensions. This work demonstrates the application of heuristics and databases of HLD-NAC parameters in predicting the complex phase behavior of surfactant–oil–water (SOW) systems. Full article

Lanthanum-cerium rare earth (RE) elements play a vital role in metallurgy as essential microalloying elements. Their addition significantly modifies inclusion characteristics, enhances mechanical properties, and improves corrosion resistance. This review emphasizes the distinct and synergistic roles of lanthanum (La) and cerium (Ce) in steel at the atomic scale, elucidated through first-principles calculations based on density-functional theory (DFT). The primary focus includes the nucleation mechanisms and characteristics of rare earth inclusions, the solid solution and segregation behavior of rare earth atoms, and their microalloying effects on electronic structure and interfacial bonding. Although both elements form stable inclusions Re₂O₃ and ReAlO₃ and exhibit grain refinement effects, Ce exhibits a unique dual valence state (Ce³⁺/Ce⁴⁺). This results in nucleation behavior and oxide stability for Ce ions that differ slightly from those of La. Both elements alter the electronic structure of the Fe matrix through hybridization with d-orbitals, reducing magnetic moment and enhancing toughness. Compared to other alloying elements, La and Ce exhibit unique behaviors due to their large atomic radii and high chemical reactivity, which influence their solid solubility, segregation tendencies, and interactions with other atoms such as Cr, C, and N. Finally, this paper discusses the challenges that exist when first-principles computational methods are used to study the mechanism of action of RE elements in steel, and proposes measures and methods to address these challenges, aiming to provide an in-depth understanding of the mechanism of action of REs in steel at the microscopic level and to promote the application of computational chemistry in the field of metallurgy. Full article

Full-scale structural experiments significantly contribute to understanding reinforced concrete (RC) behavior but are often constrained by high costs, extensive time requirements, and practical spatial limitations. Alternatively, small-scale physical models offer a feasible solution, though accurately replicating nonlinear material behavior under load at reduced scales remains challenging. This research addresses these challenges by introducing a methodological approach to developing a novel scaled-down concrete material to emulate full-scale structural behavior. The developed material strictly adheres to Froude similitude criteria, ensuring an accurate representation of gravitational effects without requiring artificially induced gravity, such as centrifuge testing. Experimental validation demonstrates that this material model successfully replicates critical mechanical properties of full-scale concrete, with less than 2% variance observed in compressive strength, strain characteristics, and failure modes. Further validation through comparative testing of scaled-down and corresponding full-scale RC beams confirms the material’s capability to precisely capture structural responses. Consequently, the proposed scaled-down concrete model offers a reliable, economical, and effective approach to evaluating structural performance, overcoming traditional limitations associated with full-scale structural experimentation. Full article

Miscanthus × giganteus particles possess excellent advantages in biodegradability and sustainability. However, their susceptibility to ultraviolet (UV) degradation limits wider outdoor applications. In the present work, electron beam (e-beam) radiation-induced grafting was used for the first time to attempt covalent grafting of UV absorbers onto miscanthus particles to address a major challenge in natural fiber stabilization. Two UV absorbers, 2-hydroxy-4-(methacryloyloxy) benzophenone (HMB) and 2-(4-benzoyl-3-hydroxyphenoxy) ethyl acrylate (BHEA), were explored using both pre-irradiation and simultaneous approaches. Pre-irradiation grafting did not achieve useful covalent fixation of HMB or BHEA, due in part to the premature decay of radicals at elevated temperatures and with solvent use, and the lignin-based quenching of radicals. Solvent-free mutual irradiation grafting failed due to immobility of the UV absorbers, while grafting of HMB in solvent failed due to radical-scavenging behavior. Grafting of BHEA was successfully achieved under solvent-based simultaneous irradiation, reaching up to 38 wt % DG in a butanone/2.5% H₂SO₄ system. This condition led to the improved UV stability of miscanthus particles, in which color change was reduced significantly after 1000 h of accelerated weathering; this was mainly linked to a beneficial pre-darkening effect which was induced by the presence of the acid. This work proposes a route of grafting strategy that aims to improve the photostability of miscanthus particles, paving the way for durable bio-based materials in outdoor composite applications. Full article

Background/Objectives: Type 2 diabetes (T2D) is associated with elevated cardiovascular risk and mortality. While physical activity can reduce cardiovascular risk, sustaining behavioral change remains challenging. Wearable activity trackers offer a scalable approach to promote physical activity, but their effects on cardiovascular outcomes in adults with T2D have not been well studied. To evaluate the impact of a wrist-worn activity tracker on physical activity, cardiovascular markers, and metabolic outcomes in adults with T2D over four weeks. Methods: This pilot randomized controlled trial included eight adults with T2D (mean age 54.9 ± 12.6 years; intervention (FIT) group: n = 5; control (CON) group: n = 3). The intervention group received an activity tracker. Both groups used the Fitbit app to track daily activity. Physical activity metrics (steps, walking distance, energy expenditure) and cardiovascular markers (blood pressure, augmentation index, pulse wave velocity, subendocardial viability ratio [SEVR]) were assessed pre- and post-intervention. Non-parametric tests and Spearman correlations were used due to the small sample size. Results: The FIT group showed significant increases in walking distance and energy expenditure and reductions in systolic/diastolic blood pressure, pulse pressure, and mean arterial pressure (all p < 0.04). SEVR trended toward improvement (p = 0.07). No significant changes were seen in the CON group. Increased physical activity was strongly correlated with reductions in pulse pressure (ρ = −0.88) and fasting glucose (ρ = −0.82; both p < 0.05). Conclusions: A brief wearable-based intervention improved physical activity and cardiovascular markers in adults with T2D, supporting feasibility for diabetes care. Full article