Search Results (17,231)

In this work, models of the deformation behavior of polymer films of polyethylene and polyvinyl chloride are developed and analyzed, taking into account the influence of thickness, mechanical stress, temperature, time and dose of electron and ion irradiation. Experimental studies included tensile tests of polyethylene films of different thicknesses irradiated with krypton ions and electrons, as well as measuring the return deformation and its rate. It is shown that the quadratic and exponential models best describe the dependences of deformation on stress. Analytical formulas for the rate and acceleration of deformation are obtained, taking into account the influence of temperature and radiation dose. The results demonstrate a significant increase in the elastic properties and return deformation of irradiated samples, which is explained by the cross-linking of macromolecules and changes in the molecular structure under the influence of radiation. The proposed models and formulas can be effectively used in the development of devices and systems for monitoring the deformation of polymeric materials under radiation exposure in the aerospace, nuclear and electronic industries. Using the statistical analysis method, it was shown that the exponential model describes the dynamics of polyethylene deformation with a determination coefficient R² = 0.985, which significantly exceeds the accuracy of the linear model (R² = 0.85). Full article

Τhe self-assembly behavior of a series of amphiphilic diblock copolymers, each consisting of a hydrophilic poly(N-vinyl pyrrolidone) (PNVP) block and a hydrophobic block derived from n-alkyl vinyl esters, namely poly(vinyl butyrate) (PVBu), poly(vinyl decanoate) (PVDc), and poly(vinyl stearate) (PVSt), in aqueous solutions was investigated. Dynamic and static light scattering (DLS and SLS) techniques were employed to monitor the micellization behavior. In addition, the self-assembled structures were observed with Transmission Electron Microscopy (TEM). The effect of the nature of the hydrophobic block, the copolymer composition and the copolymer molecular weight on the self-assembly properties was thoroughly examined. The encapsulation of curcumin and indomethacin within the dry cores of the micellar structures was conducted in aqueous solutions for all block copolymers at various curcumin/indomethacin-to-polymer mass ratios. UV-Vis spectroscopy was used to evaluate the drug-loading capacity and efficiency (%DLC and %DLE). In several cases, the encapsulation of both hydrophobic drugs was found to be nearly quantitative. Combined with the observed stability of the micellar structures, these findings suggest that the block copolymers demonstrate significant potential as carriers for drug delivery applications. Full article

Fractional stochastic differential equations (FSDEs) are powerful tools for modeling real-world phenomena, as they incorporate both memory effects and stochastic noise. A central focus in their analysis is establishing the well-posedness and regularity of solutions. Moreover, the averaging principle offers a systematic approach to simplify complex dynamical systems by approximating their behavior through time-averaged models. In this paper, we develop a theoretical framework for a class of FSDEs involving the Hilfer–Katugampola derivative. Our main contributions include proving the well-posedness and regularity of solutions, establishing a generalized averaging principle, and demonstrating real-life applications solved via the Euler–Maruyama method. All numerical simulations were conducted using the Python programming language (version 3.11). These results are formulated for the $\tilde{\mathcal{P}}$th moment, providing a unified analysis that extends existing findings. Full article

The living environment of birds exhibits seasonal variations, and winter cold and food shortages are key limiting factors influencing the survival rate of many bird species. However, most previous studies have focused on dynamic habitat changes, with relatively few investigating how changes in birds’ behavioral rhythms and ecological adaptability respond to seasonal fluctuations in the environment. The Crested Ibis (Nipponia nippon) is an endangered species, with winter food shortage being a critical factor constraining its population growth. Through 211 days of monitoring on the communal roosting behavior and GPS tracking of 19 individuals, this study aimed to clarify seasonal variations in their time allocation and activity levels, and reveal how Crested Ibises respond to environmental changes. During the wintering period, Crested Ibises departed nocturnal roosts earlier relative to sunrise and returned later relative to sunset, thereby utilizing more dawn and dusk time for foraging and increasing daylight utilization. GPS tracking data showed that both daily movement distance and activity levels of Crested Ibises during the wintering period were significantly lower than in other seasons—a pattern likely representing an adaptive strategy to cope with limited food resources, as it serves to minimize energy expenditure and enhance survival rates. Thus, these findings indicate that Crested Ibises adapt to wintering environmental changes through three seasonal behaviors: extending the dawn and dusk activity window, increasing daylight utilization, and reducing daily movement distance and activity levels. Full article

Reclaimed coastal areas are highly susceptible to uneven subsidence caused by the consolidation of soft marine deposits, which can induce differential settlement, structural deterioration, and systemic risks to urban infrastructure. Further, engineering activities, such as construction and loadings, exacerbate subsidence, impacting infrastructure stability. Therefore, monitoring the integrity and vulnerability of linear urban infrastructure after construction on reclaimed land is critical for understanding settlement dynamics, ensuring safe and reliable operation and minimizing cascading hazards. Subsequently, in the present study, to monitor deformation of the linear infrastructure constructed over decades-old reclaimed land in Mokpo city, South Korea (where 70% of urban and port infrastructure is built on reclaimed land), we analyzed 79 Sentinel-1A SLC ascending-orbit datasets (2017–2023) using the Persistent Scatterer Interferometry (PSInSAR) technique to quantify vertical land motion (VLM). Results reveal settlement rates ranging from −12.36 to 4.44 mm/year, with an average of −1.50 mm/year across 1869 persistent scatterers located along major roads and railways. To interpret the underlying causes of this deformation, Casagrande plasticity analysis of subsurface materials revealed that deep marine clays beneath the reclaimed zones have low permeability and high compressibility, leading to slow pore-pressure dissipation and prolonged consolidation under sustained loading. This geotechnical behavior accounts for the persistent and spatially variable subsidence observed through PSInSAR. Spatial pattern analysis using Anselin Local Moran’s I further identified statistically significant clusters and outliers of VLM, delineating critical infrastructure segments where concentrated settlement poses heightened risks to transportation stability. A hyperbolic settlement model was also applied to anticipate nonlinear consolidation trends at vulnerable sites, predicting persistent subsidence through 2030. Proxy-based validation, integrating long-term groundwater variations, lithostratigraphy, effective shear-wave velocity (V_s³⁰), and geomorphological conditions, exhibited the reliability of the InSAR-derived deformation fields. The findings highlight that Mokpo’s decades-old reclamation fills remain geotechnically unstable, highlighting the urgent need for proactive monitoring, targeted soil improvement, structural reinforcement, and integrated InSAR-GNSS monitoring frameworks to ensure the structural integrity of road and railway infrastructure and to support sustainable urban development in reclaimed coastal cities worldwide. Full article

Distributed temperature sensing (DTS) has long been employed in the oil and gas industry to characterize reservoirs, optimize production, and extend well life. More recently, its application has expanded to geothermal energy development, where DTS provides critical insights into transient wellbore temperature profiles and flow behavior. A comprehensive understanding of such field measurements can be achieved by systematically comparing and interpreting DTS data in conjunction with robust numerical models. However, many existing wellbore models rely on steady-state heat transfer assumptions that fail to capture transient dynamics, while fully coupled wellbore–reservoir simulations are often computationally demanding and mathematically complex. This study aims to address this gap by developing a transient wellbore heat transfer model validated with DTS data. The model was formulated using a thermal-analogy approach based on the theoretical framework of Eickmeier et al. and implemented with a finite-difference scheme. Validation was performed by comparing thermal slug velocities predicted by the model with those extracted from DTS measurements. The results demonstrated strong agreement between modeled and measured slug velocities, confirming the model’s reliability. In addition, the modeled thermal slug velocity was lower than the corresponding fluid velocity, indicating that thermal front propagates more slowly than the fluid front. Consequently, this computationally efficient approach enhances the interpretation of DTS data and offers a practical tool for improved monitoring and management of geothermal operations. Full article

Per- and polyfluoroalkyl substances (PFASs) have attracted global attention due to their persistence and biological toxicity, becoming critical emerging contaminants in river and lake environments worldwide. Building upon existing studies, this work aims to comprehensively understand the pollution patterns, environmental behaviors, and potential risks of PFASs in freshwater systems, thereby providing scientific evidence and technical support for precise pollution control, risk prevention, and the protection of aquatic ecosystems and human health. Based on publications from 2002 to 2025 indexed in the Web of Science (WoS), bibliometric analysis was used to explore the temporal evolution and research hotspots of PFASs, and to systematically review their input pathways, pollution characteristics, environmental behaviors, influencing factors, and ecological and health risks in river and lake environments. Results show that PFAS inputs originate from both direct and indirect pathways. Direct emissions mainly stem from industrial production, consumer product use, and waste disposal, while indirect emissions arise from precursor transformation, secondary releases from wastewater treatment plants (WWTPs), and long-range atmospheric transport (LRAT). Affected by source distribution, physicochemical properties, and environmental conditions, PFASs display pronounced spatial variability among environmental media. Their partitioning, degradation, and migration are jointly controlled by molecular properties, aquatic physicochemical conditions, and interactions with dissolved organic matter (DOM). Current risk assessments indicate that PFASs generally pose low risks in non-industrial areas, yet elevated ecological and health risks persist in industrial clusters and regions with intensive aqueous film-forming foam (AFFF) use. Quantitative evaluation of mixture toxicity and chronic low-dose exposure risks remains insufficient and warrants further investigation. This study reveals the complex, dynamic environmental behaviors of PFASs in river and lake systems. Considering the interactions between PFASs and coexisting components, future research should emphasize mechanisms, key influencing factors, and synergistic control strategies under multi-media co-pollution. Developing quantitative risk assessment frameworks capable of characterizing integrated mixture toxicity will provide a scientific basis for the precise identification and effective management of PFAS pollution in aquatic environments. Full article

This paper presents a systematic approach for rapid assessment of the performance and robustness of linear control systems through geometric analysis in the complex plane. By combining indirect performance indices within a defined zone of desired performance in the complex s-plane, a connection is established with direct performance indices, forming a foundation for the synthesis of control algorithms that ensure root placement within this zone. Analytical relationships between the complex variables s and z are derived, thereby defining an equivalent zone of desired performance for discrete-time systems in the complex z-plane. Methods for verifying digital algorithms with respect to the desired performance zone in the z-plane are presented, along with a visual assessment of robustness through radii describing robust stability and robust performance, representing performance margins under parameter variations. Through parametric modeling of controlled processes and their projections in the complex s- and z-domains, the influence of the discretization method and sampling period, as forms of a priori uncertainty, is analyzed. This paper offers original derivations for MISO systems, facilitating the analysis, explanation, and understanding of the dynamic behavior of real-world controlled processes in both the continuous and discrete-time domains, and is aimed at integration into expert systems supporting control strategy selection. The practical applicability of the proposed methodology is related to discrete control systems in energy, electric drives, and industrial automation, where parametric uncertainty and choice of method and period of discretization significantly affect both robustness and control performance. Full article

Ritual prayer (ṣalāh) is one of the most central and enduring practices in Islam, widely recognized for its spiritual significance. However, its educational and formative role in shaping the Muslim’s inner self and moral identity remains insufficiently explored in contemporary scholarship. This paper aims to examine ritual prayer as a core pedagogical tool within Islamic education, focusing on its transformative power in the processes of self-purification (tazkiyah) and identity formation. The study seeks to analyze the ethical and psychological dimensions of ṣalāh, drawing on classical Islamic sources, as well as integrating insights from contemporary critical philosophy—particularly Byung-Chul Han’s Vita Contemplativa—and Islamic virtue ethics, including perspectives such as those advanced by Elizabeth Bucar. Through this framework, the paper explores how prayer shapes inner dispositions like humility, mindfulness, sincerity, patience, and submission, reinforcing both spiritual awareness and communal belonging. Employing a descriptive-analytical methodology, the study engages Qur’anic verses, prophetic traditions, and traditional pedagogical literature to investigate how ṣalāh functions as a lived and repeated experience that cultivates the soul and molds ethical behavior. The discussion highlights how regular performance of prayer integrates belief with action and contributes to the formation of a reflective and morally grounded Muslim identity. This paper contributes to the field of Islamic Practical Theology by demonstrating how ritual prayer operates as a dynamic and holistic model for moral and spiritual development. It provides educators and scholars with a theoretical and applied vision for incorporating ṣalāh-based character education into Islamic curricula. Future research may explore how prayer interacts with modern lifestyles, digital spiritual practices, and intergenerational transmission of religious identity in diverse contexts. Full article

Intensive mothering is a widespread cultural ideology positioning mothers as uniquely responsible for their children’s optimal development through emotionally and cognitively intensive caregiving. A key belief within this framework is maternal essentialism, which asserts that mothers are biologically and morally best suited for parenting young children. Guided by the Family Stress–Proximal Process (FSPP) model, this study examined whether maternal essentialist beliefs act as distal sociocultural stressors influencing children’s executive functioning indirectly through parenting stress and positive parenting behaviors. Data were collected via self-report from 255 U.S. mothers of 3- to 5-year-old children. Path analyses showed that stronger maternal essentialism was associated with increased parenting stress, which predicted lower engagement in positive parenting and greater reported difficulties in children’s executive functioning. The indirect effect of maternal essentialism on children’s executive functioning was statistically significant. These findings suggest that internalized cultural ideologies, often viewed as aspirational, may inadvertently increase parenting stress and reduce caregiving quality, which is associated with diminished child cognitive outcomes. This study extends prior research by linking maternal essentialist beliefs to child developmental outcomes through specified psychological and relational processes, supporting the usefulness of the FSPP framework in understanding how sociocultural pressures influence family dynamics and child development. Full article

Microencapsulation is a fundamental technology for protecting active compounds from environmental degradation by factors such as light, heat, and oxygen. This process significantly improves their stability, bioavailability, and shelf life by entrapping an active core within a protective matrix. Therefore, a thorough understanding of the physicochemical interactions between these components is essential for developing stable and efficient delivery systems. The composition of the microcapsule and the encapsulation method are key determinants of system stability and the retention of encapsulated materials. Recently, the application of computational tools to predict and optimize microencapsulation processes has emerged as a promising area of research. In this context, molecular dynamics (MD) simulation has become an indispensable computational technique. By solving Newton’s equations of motion, MD simulations enable a detailed study of the dynamic behavior of atoms and molecules in a simulated environment. For example, MD-based analyses have quantitatively demonstrated that optimizing polymer–core interaction energies can enhance encapsulation efficiency by over 20% and improve the thermal stability of active compounds. This approach provides invaluable insights into the molecular interactions between the core material and the matrix, ultimately facilitating the rational design of optimized microstructures for diverse applications, including pharmaceuticals, thereby opening new avenues for innovation in the field. Ultimately, the integration of computational modeling into microencapsulation research not only represents a methodological advancement but also pivotal opportunity to accelerate innovation, optimize processes, and develop more effective and sustainable therapeutic systems. Full article

This study evaluates the feasibility of using a lightweight, off-the-shelf sensing system for short-term stress detection during exergaming. Most existing studies in stress detection compare rest and task conditions, providing limited insight into continuous stress dynamics, and there is no agreement on optimal sensor configurations. To address these limitations, we investigated dynamic stress responses induced by a cognitive–motor task designed to simulate rehabilitation-like scenarios. Twenty-three participants completed the experiment, providing electrodermal activity (EDA), blood volume pulse (BVP), self-report, and in-game data. Features extracted from physiological signals were analyzed statistically, and shallow machine learning classifiers were applied to discriminate among stress levels. EDA-based features reliably differentiated stress conditions, while BVP features showed less consistent behavior. The classification achieved an overall accuracy of 0.70 across four stress levels, with most errors between adjacent levels. Correlations between EDA dynamics and perceived stress scores suggested individual variability possibly linked to chronic stress. These results demonstrate the feasibility of low-cost, unobtrusive stress monitoring in interactive environments, supporting future applications of dynamic stress detection in rehabilitation and personalized health technologies. Full article

Prior work has demonstrated that higher surprisal, a measure quantifying the unexpectedness of a trigger exposure, predicts headache onset over 12 to 24 h. However, these analyses relied on retrospective expectations of trigger exposure formed after extended data collection. To operationalize surprisal prospectively, Bayesian methods could update expectations dynamically over time. The objective of this study was to extend the application of surprisal theory for predicting migraine attack risk by developing methods to estimate trigger variable likelihood in real time, under conditions of limited personal observation. In a prospective daily diary study of individuals with migraine (N = 104), data were collected over 28 days, including stress, sleep, and exercise exposures. Bayesian models were applied to estimate daily expectations for each variable under uninformative and empirical priors derived from the sample. Stress was modeled using a hurdle-Gamma distribution, sleep using discrete outcomes from a Normal distribution, and exercise using a Bernoulli distribution. Surprisal was calculated based on the predictive distribution at each time point and compared to static empirical surprisal values obtained after full data collection. Dynamic Bayesian surprisal values systematically differed from retrospective empirical estimates, particularly early in the observation period. Divergence was larger and more variable under uninformative priors but attenuated over time. Empirically informed priors produced more stable, lower-bias surprisal trajectories. Substantial individual variability was observed across exposure types, especially for exercise behavior. Prospective surprisal modeling is feasible but highly sensitive to prior specification, especially in sparse data contexts (e.g., a binary exposure). Incorporating empirical or individually informed priors may improve early model calibration, though individual learning remains essential. These methods offer a foundation for real-time headache forecasting and dynamic modeling of brain–environment interactions. Full article

To better understand the relationship between meniscus instabilities and the high levels of turbulence in the fluid dynamics of a continuous medium slab mold, this study investigates the magnitudes of meniscus dynamics distortions and their fluid dynamic origin using a full-scale water modeling experiment and mathematical simulations. The three-dimensional mathematical model is composed of the continuity and momentum equations, together with the standard k-ε turbulence model and the volume of fluid model, to track the dynamics of the steel interface. The results show that the medium slab mold shares flow patterns common to both conventional slab molds and funnel thin slab molds, making its fluid dynamics more complex. Despite this, the fluid dynamics within the mold do not develop a dynamic distortion phenomenon but induce upward stream flows with instability and high velocities, which generate an unstable meniscus behavior characterized by significant surface oscillations, variations in velocity, and high deformations. These latter flow characteristics are the origin of meniscus dynamic distortion (MDD), which shows a constant frequency with non-constant periodicity and different median lifecycle ranges. Full article

This study introduces a novel control strategy aimed at achieving projective synchronization in incommensurate fractional-order chaotic systems (IFOCS). The approach integrates the mathematical framework of fractional calculus with the recursive structure of the backstepping control technique. A key feature of the proposed method is the systematic use of the Mittag–Leffler function to verify stability at every step of the control design. By carefully constructing the error dynamics and proving their asymptotic convergence, the method guarantees the overall stability of the coupled system. In particular, stabilization of the error signals around the origin ensures perfect projective synchronization between the master and slave systems, even when these systems exhibit fundamentally different fractional-order chaotic behaviors. To illustrate the applicability of the method, the proposed fractional order backstepping control (FOBC) is implemented for the synchronization of two representative systems: the fractional-order Van der Pol oscillator and the fractional-order Rayleigh oscillator. These examples were deliberately chosen due to their structural differences, highlighting the robustness and versatility of the proposed approach. Extensive simulations are carried out under diverse initial conditions, confirming that the synchronization errors converge rapidly and remain stable in the presence of parameter variations and external disturbances. The results clearly demonstrate that the proposed FOBC strategy not only ensures precise synchronization but also provides resilience against uncertainties that typically challenge nonlinear chaotic systems. Overall, the work validates the effectiveness of FOBC as a powerful tool for managing complex dynamical behaviors in chaotic systems, opening the way for broader applications in engineering and science. Full article