Search Results (2,831)

This study examines how individual political predispositions and national mobilisation contexts jointly structure protest participation in contemporary Europe across the pre-pandemic, pandemic and post-pandemic periods. Using data from Rounds 9, 10 and 11 of the European Social Survey (2018–2023), the analytical sample includes 106,106 respondents from 33 countries. Descriptively, protest participation remains a minority behaviour, yet displays pronounced cross-national heterogeneity, with participation rates ranging from below 3% in several Central and Eastern European countries to nearly 20% in the most mobilised contexts and remains remarkably stable across rounds at approximately 8.5%. Building on resource mobilisation theory, political process approaches and New Social Movements perspectives, the analysis conceptualises protest participation not as an isolated behavioural act but as the outcome of interactions between individual resources, evaluative orientations toward democratic institutions and broader mobilisation environments. Logistic regression models, country fixed-effects specifications and multilevel models with random intercepts are used to assess these relationships. At the individual level, political engagement emerges as the strongest predictor of participation: higher political interest is associated with substantially higher protest propensity, while ideological self-placement indicates lower participation among respondents positioned further to the right. Younger age and higher education also increase participation. Lower satisfaction with democracy and stronger perceptions of inequality are consistently associated with protest behaviour, supporting grievance-based interpretations linked to democratic evaluations rather than material deprivation alone. Country fixed-effects and multilevel models confirm that these individual-level associations are robust within countries, while significant between-country variation persists (random-intercept SD = 0.554), indicating that national mobilisation environments shape baseline levels of protest participation. Multilevel results further reveal that protest participation was significantly lower during the pandemic period (Round 10) relative to the pre-pandemic baseline, with only partial recovery in the post-pandemic period. A cross-round comparison demonstrates that the core individual-level associations are stable across all three periods, indicating that these relationships reflect durable structural patterns rather than dynamics specific to any particular mobilisation cycle. Beyond this overall stability, the analysis identifies two theoretically informative exceptions: subjective financial difficulty is significant only in the pre-pandemic period and gender differences in protest participation attenuate over time—patterns consistent with broader shifts in protest repertoires during and after the pandemic. These findings make three contributions to the comparative literature on contentious politics. First, by extending the analysis across three ESS rounds, the study demonstrates the temporal robustness of individual-level determinants of protest—an empirical question rarely addressed in the existing literature. Second, the multilevel design with round fixed effects allows for direct estimation of pandemic-related suppression and post-pandemic recovery in protest activity at the aggregate level. Third, the cross-national scope and temporally structured comparison provide new evidence on how individual political predispositions interact with shifting mobilisation environments across a period of exceptional socio-political strain in Europe. Full article

Structural vibrations caused by dynamic wind action are critical for high-rise buildings such as the DC2 Tower due to the potential for occupant discomfort. To ensure that the top acceleration remained below the required 1.5% g comfort limit, the tower’s stiffness was assessed through actual modal parameters—natural frequencies, mode shapes, and damping ratios—obtained through an innovative framework combining real-time 3D monitoring with a real-time digital twin model during construction. The digital twin was based on operational modal analysis (OMA) and continuously updated, allowing comparisons between measured parameters and static design-based values at different construction stages. When the first quarter of the tower was completed, it was already possible to observe that the vibration modes corresponded in shape to those estimated in the static design. However, the natural frequencies and damping ratios were higher than initially estimated, confirming greater stiffness. Consequently, the static design model was tuned early to match the measured frequencies obtained from the digital twin model, enabling accurate prediction of the final-state response. This prediction confirmed compliance with comfort criteria, eliminating the need for a tuned mass damper for vibration control. The prognosis was verified by the natural frequencies measured in the final state of the DC2 Tower. Full article

This study investigates the seismic behaviour of the Hüsrev Pasha Minaret, a historical masonry structure located in Diyarbakır, Türkiye, characterized by two distinct transition segments and material variation along its height. The dynamic features of the minaret were identified through ambient vibration tests, while material properties were estimated using non-destructive testing methods. A three-dimensional numerical model was then generated and calibrated based on the experimentally identified natural frequencies, achieving an average frequency difference of 2.04%. Nonlinear dynamic analyses were conducted using six earthquake time series scaled to three seismic hazard levels (DD-1, DD-2, and DD-3) defined in the Turkish Building Earthquake Code (TBEC-2018). The results indicate that the second transition segment is the most critical region in terms of damage concentration. Ground motions corresponding to the DD-1 level led to exceedance of the Collapse Prevention (CP) displacement limits, while DD-2 and DD-3 levels resulted in limited or near-limit responses. In addition, compression-only support conditions were found to influence the base shear response, whereas material transitions between basalt and limestone did not significantly affect the overall seismic behaviour of the minaret. Full article

The microstructure of semicrystalline bioresorbable polymers is central to their biomedical performance because the crystalline content influences both the mechanical stability and the degradation behaviour. Experimental studies have shown that crystallinity evolves concurrently with mass loss during enzymatic degradation. However, most existing models represent the material as a single homogeneous structure, preventing them from capturing this microstructural evolution or the state-selective mechanisms that drive it. We present a one-dimensional partial differential equation model for the enzymatic degradation of thin films, which treats the crystalline and amorphous states as distinct reactive components. Calibrated to poly($\epsilon$-caprolactone) (PCL) degraded by Candida antarctica lipase in vitro, the model accurately reproduces both the observed weight-loss profile and the concurrent decline in crystallinity. Parameter uncertainty analysis indicates that while there are varying degrees of confidence in individual parameter values, the overall model predictive uncertainty is well constrained. Parameter sensitivity analysis shows that the amorphous catalytic rate (the rate at which the enzyme degrades the amorphous region) is the dominant driver of degradation dynamics. The identified model parameters are used to explore the role of film thickness on the rates of mass and crystallinity loss. It was found that thin films remain largely reaction-limited, whereas thicker specimens become increasingly transport-influenced, with slower degradation and delayed structural evolution in the material interior. The model provides a useful tool to explore the effect of changing PCL film thickness on degradation rate and crystallinity-related properties without extensive experimentation. Full article

Regular physical activity is essential for physical and mental health, yet participation among Norwegian university students remains below nationally recommended levels. This study explored facilitators and barriers for physical activity among first-year students, using the COM-B model as a conceptual framework. Fifteen physically active first-year students from two higher education campuses in Bodø were interviewed in spring 2025, and the data were analysed using inductive thematic analysis. Analysis showed that students’ activity behaviours were shaped by a dynamic interaction between physical and psychological capabilities, particularly in relation to technical competence, previous injuries, and self-regulation strategies. Opportunity-related factors—such as time constraints, financial limitations, commuting distance, and access to facilities—substantially influenced students’ ability to maintain regular activity, while social support from friends, family, and peers functioned as an important facilitator. Motivation emerged through a mixture of automatic processes—including stress reduction, enjoyment, and habits—and reflective processes such as goal-setting and health-oriented decision-making. For students in physically demanding study programmes, professional identity and body-related expectations also contributed to their engagement. Overall, this study highlights the need for institutional strategies that simultaneously address structural, social, and psychological factors to support sustainable physical activity habits during the transition to university life. Full article

Graphene oxide (GO) has been widely investigated as a nanoreinforcement for cementitious composites; however, its effectiveness depends on stable dispersion within the highly alkaline, calcium-rich environment of fresh cement paste. This study evaluates the dispersion behaviour of GO in deionised (DI) water and saturated calcium hydroxide (Ca(OH)₂) under controlled conditions and assesses the effectiveness of anionic and cationic surfactants in both environments. GO was synthesised using the modified Hummers method and verified by comprehensive physicochemical characterisation. Dispersion stability was assessed using UV-Vis spectroscopy at GO concentrations of 0.04–0.08 mg/mL in DI water, and the 0.08 mg/mL system was further studied in saturated Ca(OH)₂ with and without sodium dodecylbenzene sulphonate (SDBS) and cetyltrimethylammonium bromide (CTAB) at a 1:1 mass ratio. Zeta potential and dynamic light scattering measurements were performed to understand the relation between the surface charge and agglomeration of GO. In DI water, GO retained close to 70% of its initial absorbance after 60 min, and both surfactants improved retention to above 90%. In saturated Ca(OH)₂, retention fell to approximately 40%, and neither surfactant restored stability despite producing zeta values that would conventionally support stable dispersion. The findings indicate that GO aggregation in calcium ion (Ca²⁺)-rich alkaline environments is not governed by net surface charge alone, consistent with the established mechanism of Ca²⁺ chemical cross-linking with GO carboxyl groups. Full article

This paper presents a Digital Twin (DT)-based framework for the control, monitoring, and intelligent optimization of an Assembly/Disassembly/Repair Mechatronic Production Line (A/D/R MPL), developed as a laboratory platform aligned with Industry/Education 4.0/5.0 paradigms. The A/D/R MPL is assisted by two complementary cyber–physical robotic systems: an Assembly/Disassembly/Replacement Cyber–Physical Robotic System (A/D/R CPRS), and a Mobile Cyber–Physical Robotic System (MCPRS), enabling both fixed and mobile intelligent operations. The CPRS is equipped with an industrial robotic manipulator (IRM) responsible for A/D/R tasks, while the A/D Mechatronic Line (A/D ML) consists of seven interconnected workstations (WS1–WS7) dedicated to storage, transport, quality control, and final product handling. MCPRS includes a wheeled mobile robot (WMR), carrying a robotic manipulator (RM) and Mobile Visual Servoing System (MVSS). Each workstation is connected to a local slave programmable logic controller (PLC), which communicates via PROFIBUS with a master PLC located at the CPRS level. Additional communication infrastructures include LAN PROFINET and LAN Ethernet for local integration, and WAN Ethernet connectivity enabled through open platform Communication-Unified Architecture (OPC-UA), ensuring interoperability, scalability, and remote accessibility. Also, MODBUS TCP as serial industrial communication is used between the master PLC and the MCPRS. Virtual environment supports task planning through Augmented Reality (AR) and real-time monitoring through Virtual Reality (VR). The system behaviour is modelled with synchronized hybrid Petri Nets (SHPNs) which describe the discrete and hybrid dynamics of A/D/R processes. Artificial intelligence (AI) techniques are integrated into the DT framework for optimal task scheduling and adaptive decision-making. As a laboratory-scale implementation, the proposed system provides a comprehensive platform for experimentation, validation, and education. It supports Education 4.0/5.0 objectives by facilitating hands-on learning, human–machine interaction, and the integration of emerging technologies such as AI, Digital Twins, AR/VR, and cyber–physical systems. At the same time, it embodies Industry 4.0/5.0 principles, including interoperability, decentralization, sustainability, robustness, and human-centric design. Full article

Plants are constantly exposed to a wide range of abiotic stresses that have significant negative impacts on growth and yield. Plant acclimation to these stresses is governed by integrated classical phytohormone and plant peptide hormone signalling networks that control the ability of a plant to survive and adapt to extreme environments. Classical phytohormones, including abscisic acid, auxins, gibberellins, cytokinins, jasmonates, salicylic acid, brassinosteroids, and the recently recognised phytomelatonin, act in concert with peptide-based plant hormones, among which C-terminally encoded peptides (CEPs) play prominent roles in coordinating stress perception, signal transduction, and adaptive responses throughout the plant. These integrated networks control stomatal behaviour, photosynthesis, osmolyte and antioxidant levels, root architecture, and energy metabolism, thereby helping plants maintain homeostasis and optimise survival while sustaining minimal growth under unfavourable conditions. Under stressful conditions, these networks do not operate in isolation but form highly dynamic, context-dependent regulatory circuits in which each physiological process is simultaneously regulated by multiple hormones acting through convergent and overlapping signalling pathways. Phytomelatonin has emerged as a particularly important integrative node within these networks, functioning both as a potent direct antioxidant through sequential ROS-scavenging catabolite cascades and as a bidirectional regulator of classical phytohormone signalling under diverse abiotic stresses. New technologies in the fields of transcriptomics, proteomics, phosphoproteomics, metabolomics, and systems biology have provided new information on the dynamic relationships between classical phytohormones and plant peptide hormones, revealing candidate regulatory nodes and transcription factor networks that mediate stress adaptation at molecular, biochemical, and physiological levels. However, it is important to distinguish between correlative associations identified through omics profiling and causal regulatory relationships validated through rigorous genetic and biochemical experimentation, as most omics-derived candidates remain to be functionally established. Empirical studies demonstrate how these networks can be used to improve crops by increasing stress tolerance through modulating classical phytohormone and plant peptide hormone signalling, including through exogenous phytomelatonin application, CRISPR-mediated hormone pathway editing, and CEP pathway manipulation, to produce resilient cultivars without reducing yields. Although these advances represent significant progress, challenges remain, including the inherent complexity and redundancy of the networks, context-dependence and severity-dependence of hormonal responses, the persistence of a significant translational gap between laboratory findings and field application, and incomplete mechanistic understanding of peptide hormone roles under combined stress conditions. Addressing these challenges will require integrative multi-omics approaches, higher-order computational modelling, and rigorous field-based functional validation alongside emerging tools such as synthetic biology and precision breeding. Full article

The optical complexity of shallow Case 2 waters challenges remote sensing accuracy due to the non-linear behaviour of optically active constituents. This study evaluates the spectral divergence between the target-derived effective attenuation ($K_{\mathrm{e}\mathrm{f}\mathrm{f}}$) and the ambient scalar attenuation coefficient ($K_0$) across 12 Baltic Sea locations. Using hyperspectral radiometry and K-Means clustering, three optical water types (OWTs) were identified. We demonstrate that the historical static approximation based on the diffuse attenuation coefficient ($K_{\mathrm{e}\mathrm{f}\mathrm{f}}$ ≈ 2$K_{\mathrm{d}}$) is systematically biased in scattering-dominated environments. Our empirical results yielded a regional relationship of $K_{\mathrm{e}\mathrm{f}\mathrm{f}}$ = 2.33$K_0$ ($R^2$ = 0.65); however, residual analysis reveals that linear multipliers fail to capture non-linear light decay. Random Forest regression identified total suspended matter (TSM) as the primary driver of $K_{\mathrm{e}\mathrm{f}\mathrm{f}}$ variance (28.0%), confirming that “geometric rejection” of scattered photons artificially inflates signal loss in turbid waters. This divergence is most pronounced in the 500–650 nm range, where low absorption facilitates multiple scattering events. We conclude that active remote sensing requires a sensor-fusion approach, utilising passive OWT classification to dynamically parameterise active attenuation models. Full article

Sand grain size strongly influences the physical and hydraulic behaviour of sandy soils, particularly water retention, pore distribution, and water movement under unsaturated conditions. This study evaluated the effect of five sand grain-size classes, ranging from very coarse to very fine, on pore distribution, aeration, water retention, and unsaturated hydraulic conductivity. Quartz sand samples with different particle sizes were saturated and subjected to matric tensions ranging from 10 to 15,000 hPa. Very fine sand (0.053–0.106 mm) showed the highest field capacity (0.38 m³ m⁻³) and available water content (0.30 m³ m⁻³), which were associated with a predominance of pores between 0.2 and 3 μm in diameter. In contrast, coarser sand fractions were dominated by macropores (>50 μm) and exhibited lower water retention. Permanent wilting point values remained low and similar among grain-size classes (≈0.02 m³ m⁻³). Under unsaturated conditions (matric tensions > 100 hPa), very fine sand exhibited hydraulic conductivity values up to ten times greater than those of coarser fractions. Overall, decreasing sand particle size increased water retention and plant-available water while reducing macroporosity and aeration capacity. These findings demonstrate that sand grain-size distribution plays a major role in regulating water dynamics in sandy soils and may support the development of more efficient irrigation and soil management strategies to improve water conservation and plant water availability in drought-prone environments. Full article

Protective coatings and surface-protection systems improve structural durability, but the long-term performance of durability-sensitive infrastructure also depends on the cyclic stability of supporting soil–rock mixture (SRM) foundations. In this study, undrained multistage strain-controlled cyclic triaxial tests were conducted on reconstructed SRMs with rock block contents of 0%, 10%, 20%, 40%, and 60% under confining pressures of 100, 200, and 400 kPa. Hysteresis-loop morphology, secant shear modulus, normalized shear modulus ratio, damping ratio, normalized damping ratio, and fitting parameters were evaluated. The results show that hysteresis loops evolved from narrow and steep to wider and fuller forms as strain amplitude increased, indicating stiffness degradation and enhanced hysteretic dissipation. The secant shear modulus decreased from 35.835 to 158.871 MPa to 3.296–12.854 MPa, corresponding to an overall reduction of approximately 85%–94%, while the damping ratio increased from 0.036 to 0.063 to 0.195–0.268. Higher rock block content and stronger confinement increased absolute stiffness, but rock block content advanced normalized degradation and damping development, whereas confinement delayed these normalized responses. These findings provide experimental evidence for dynamic-parameter selection, deformation-compatibility evaluation, and cyclic stability assessment of complex SRM foundations. Full article

Neurodegenerative diseases are among the most consequential disorders of later life, not only because of their increasing prevalence, rising from approximately 1–2% at age 65 to over 30% by age 85, but also because they develop within the broader clinical context of ageing, multimorbidity, frailty, and polypharmacy. In older adults, these conditions rarely present as isolated and static diagnostic entities; rather, they unfold as dynamic clinical trajectories involving the progressive interaction of cognitive decline, behavioural-neuropsychiatric symptoms, and extrapyramidal-motor dysfunction. In this review, we propose a trajectory-based framework for the interpretation and management of major neurodegenerative disorders in later life, including Alzheimer’s disease, frontotemporal dementia, Parkinson’s disease and Parkinson’s disease dementia, dementia with Lewy bodies, and vascular cognitive impairment. Building on a conceptual model organized around three major symptom spheres: cognitive, behavioural-neuropsychiatric, and extrapyramidal-motor, we argue that each disorder can be understood according to the relative predominance and temporal evolution of these domains. Alzheimer’s disease is typically cognition-led, frontotemporal dementia behaviour-led, and Parkinsonian syndromes motor-led, whereas dementia with Lewy bodies shows early multidomain convergence across all three spheres simultaneously. Vascular and mixed dementias follow more heterogeneous trajectories shaped by lesion burden, network disruption, and copathology. This framework has direct implications for diagnosis, prognostic stratification, and treatment selection, because interventions targeting one sphere may destabilize another and generate prescription cascades, delirium, or functional decline. We further discuss how biomarker-based diagnosis, disease-modifying therapies, non-pharmacological interventions, multidisciplinary care, deprescribing strategies, and palliative planning can be integrated within a trajectory-based approach. Interpreting neurodegeneration through clinical trajectories rather than diagnostic labels alone offers a more realistic and therapeutically useful model for precision geriatric neurology across the full course of disease. Full article

Pitch control is the standard approach to regulating the rotational speed of large wind energy systems when the wind speed goes over its rated value. However, the pitch control system can also be used to reduce blade loads. In this last case, it is necessary to extend the classic collective pitch control system by including a complicated mechanism, which involves a Coleman or a Clarke transformation. This extension is known as the individual pitch control (IPC). While the performance of the IPC is satisfactory regarding the load alleviation, its dynamics remain insufficiently comprehended, especially due to the previously mentioned embedded transformations. Hence, the tuning of the IPC is sometimes challenging, and the controller can exhibit unexpected behaviours. The idea of this work is to formulate the IPC as a multivariable controller in the input/output representation such that the classic tools for the analysis and control of linear systems can be applied. As a result, some lesser-known properties as well as limitations are disclosed. Specifically, the approach makes apparent the existence of proportional-resonant controllers, which are crucial for dynamical behaviour. This additional knowledge can assist in the design of control systems and the tuning of controllers. A simulation study completes the presentation, including qualitative and quantitative analysis. Full article

This study investigates the mechanical behaviour of continuous carbon-fibre-reinforced additively manufactured composite structures aimed at applications in aeronautical structures, through a combination of experimental testing and numerical simulation. Tensile, compressive, and shear tests established stiffness and failure characteristics, while finite element analyses were used for a preliminary calibration-based reproduction of the measured coupon response, with an emphasis on the initial elastic part of the impact event. The integration of measured data with structural modelling provides a clearer understanding of load transfer and damage initiation in continuous-fibre AM, supporting more accurate simulation-based design of additively manufactured composite components. Experimental results show pronounced anisotropy, and a stable, rate-dependent impact response. The preliminary numerical model based on CT-derived homogenized properties accurately reproduces the initial part of the measured quasi-static and dynamic responses. Full article

Endometrial cancer (EC) is increasingly recognized as a heterogeneous disease, yet current treatment strategies often fail to explain why tumors with similar molecular profiles respond differently or develop resistance. This gap points to regulatory mechanisms beyond static genomic alterations. Epigenetic dysregulation through DNA methylation, histone modification, and non-coding RNA (ncRNAs) networks acts as a dynamic and reversible system that governs how tumors adapt under therapeutic pressure. In EC, alterations affecting key regulators such as MLH1, PTEN, and hormone receptors directly influence sensitivity to immunotherapy, targeted therapy, and endocrine treatment, defining treatment-responsive and treatment-resistant states. These observations shift the role of epigenetics from a descriptive feature of tumor biology to a determinant of therapeutic behaviour. Epigenetic states influence immune recognition, pathway activation, and cell cycle control, thereby shaping response to chemotherapy and immune checkpoint blockade. Biomarkers derived from these alterations, including methylation signatures and circulating RNAs, offer opportunities for patient stratification and longitudinal monitoring of treatment response. Therapeutically, targeting epigenetic regulators provides a strategy to reverse resistance and restore treatment sensitivity. DNA methyltransferase and histone deacetylase inhibitors, particularly in combination with established therapies, have shown potential to enhance treatment efficacy. Emerging approaches, including locus-specific epigenetic editing and liquid biopsy–guided monitoring, further support adaptive treatment strategies. Integrating epigenetic reprogramming into clinical decision-making offers a practical path toward improving treatment response and overcoming resistance in EC. Here, we propose an Epigenetic State–Response Framework (ESRF) in which dynamic epigenetic states define treatment-sensitive and resistant phenotypes, map to specific therapeutic vulnerabilities, and can be actively reprogrammed to restore treatment response. Full article