Search Results (960)

This study comparatively assesses the Municipal Emission Reduction Plans (MERPs) of Spetses, Platanias, and Souli, examining their role as analytical and strategic tools for local climate planning, with particular emphasis on water-related infrastructure. A descriptive comparative analysis was conducted using secondary data extracted from officially approved MERPs, covering sectoral and total greenhouse gas emissions for 2019 and 2023, as well as reported mitigation actions and 2030 targets. The results reveal significant inter-municipal variations in emission patterns, driven by geomorphological characteristics, infrastructure configuration, and energy consumption, but also by governance structures and system boundaries. Water supply and irrigation systems are identified as highly energy-intensive sectors, particularly in municipalities with extensive, pumping-dependent networks. At the same time, the analysis shows that the inclusion or exclusion of outsourced services—such as water supply and wastewater management—substantially affects the representation of emissions and the prioritization of mitigation actions. The study concludes that MERPs can support climate planning at the municipal level, but their effectiveness is conditioned by data completeness, system boundaries, and governance models. These findings highlight the need to move beyond purely accounting-based approaches toward integrated planning frameworks that capture the full operational scope of municipal systems, enabling more accurate emission assessment and more effective, context-specific mitigation strategies within the water–energy–nexus. Full article

This paper argues that the most significant challenge artificial intelligence poses to theological anthropology is not ontological but epistemic. Rather than asking whether machines can think, feel, or bear the image of God, this paper redirects attention to the prior question of what happens to the human when core epistemic capacities, judgment, discernment, interpretive authority, and moral reasoning are progressively delegated to computational systems. Drawing on the concept of epistemic automation, understood as the systematic transfer of knowledge-producing functions from human agents to algorithmic processes, this paper develops a threefold analytical framework. First, it distinguishes epistemic authority from ontological status as the more productive locus for theological anthropological inquiry. Second, it introduces the distinction between fluency and understanding as an anthropological boundary condition that AI renders newly visible. Third, it analyses delegated cognition as a form of agency deformation with theological significance. The paper concludes that theological anthropology must move beyond reactive commentary on AI and instead generate a theory of the human under conditions of epistemic transformation. The argument engages constructively with philosophy of technology, social epistemology, and Christian theological traditions to offer a framework applicable across confessional boundaries. Full article

Phase change material (PCM)-based latent heat storage (LHS) systems help address the mismatch between renewable energy supply and thermal demand. However, their practical implementation is constrained by the strongly nonlinear and multiphysics nature of phase change, which makes high-fidelity simulations and real-time applications computationally expensive. This review examines mathematical reduced-order modeling (ROM) as an effective strategy to overcome this limitation by combining physics-based simplifications, projection methods, interpolation techniques, and data-driven models for PCM-based LHS systems. While physical simplifications (such as dimensional reduction and effective property approximations) represent an important first layer of model reduction, the primary focus of this work is on the mathematical ROM methodologies that operate on the governing equations after such physical simplifications have been applied. The review covers approaches including two-temperature non-equilibrium and analytical thermal-resistance models, Proper Orthogonal Decomposition (POD), CFD-derived look-up tables, kriging and ε-NTU grey/black-box metamodels, and machine-learning methods such as artificial neural networks and gradient-boosted regressors trained from CFD data. These ROM techniques have been applied to packed beds, PCM-integrated heat exchangers, finned enclosures, triplex-tube systems, and solar thermal components, achieving speed-ups from tens to over 80,000 times faster than full CFD simulations while maintaining prediction errors typically below 5% or within sub-Kelvin temperature deviations. A critical comparative analysis exposes the fundamental trade-off between interpretability, data dependence, and computational efficiency, leading to a practical decision-making framework that guides method selection for specific applications such as design optimization, real-time control, and system-level simulation. Remaining challenges—including accurate representation of phase change nonlinearity, moving phase boundaries, multi-timescale dynamics, generalization across geometries, experimental validation, and integration into industrial workflows—motivate a structured roadmap for future hybrid physics–machine learning developments, standardized validation protocols, and pathways toward industrial deployment. Full article

Efficient mixing is a persistent bottleneck in agricultural and agrochemical processing, where rapid and uniform mixing must be achieved under laminar flow with low energy input and gentle shear. Inspired by peristaltic transport in biological systems, this study investigates a bio-inspired flexible-wall squeezing mixer and establishes a two-dimensional computational framework to quantify how periodic wall deformation governs scalar homogenization in a flexible conduit. An Arbitrary Lagrangian–Eulerian dynamic mesh approach is implemented to resolve moving boundaries and to prescribe actuation, enabling the systematic evaluation of the separate and coupled effects of peak wall-normal velocity amplitude A and actuation frequency f on mixing performance. Mixing effectiveness is quantified using a variance-based mixing index MI and a sustained-threshold mixing time ts, and response surface methodology is employed to map the A–f design space and interpret the roles of time-dependent shear, interfacial stretching and folding, and vortex intensification. Relative to a non-actuated baseline, a peak wall-normal velocity amplitude of 3 × 10⁻³ m s⁻¹ at 2 Hz reduces t_s by 21.3%. At fixed f = 3 Hz, increasing A from 1 × 10⁻³ to 4 × 10⁻³ m s⁻¹ shortens t_s by 10.2%, while at fixed A = 3 × 10⁻³ m s⁻¹, raising f from 1 to 5 Hz further decreases t_s by 6.6% with diminishing gains at the lowest frequencies. The response surface identifies an operating optimum at A = 4 × 10⁻³ m s⁻¹ and f = 5 Hz, achieving a peak MI of 0.9557 and a minimum t_s of 7.81 s. A periodically squeezed physical mixing loop was further examined using fluorescence imaging to assess outlet homogeneity trends. The stabilized outlet coefficient of variation (CV) decreased from about 0.65 without squeezing to 0.60 at 1 Hz and 10 mm s⁻¹, 0.58 at 2 Hz and 10 mm s⁻¹, and 0.54 at 2 Hz and 30 mm s⁻¹, indicating that stronger and faster actuation improves outlet uniformity. The numerical and experimental results are therefore interpreted jointly as mechanistic and trend-level evidence, while a rigorous quantitative prediction for the cylindrical compliant device will require future three-dimensional, compliance-resolved simulations and broader experimental benchmarking. Full article

The physical characteristics of a heated non-Newtonian Eyring–Powell fluid in a conduit with sinusoidally moving ciliated walls are highlighted in this analytical study. The impact of mass transmission is considered in this model. The dimensional form of the governing equations is simplified using the long-wavelength estimation and suitable transformations to produce a set of dimensionless partial differential equations with pertinent boundary conditions. To solve it, the perturbation technique is utilized applying polynomial solutions. The solutions of temperature, concentrations, and velocity profiles are obtained, and then are further analyzed through graphical results. An accurate mathematical solution for the pressure gradient is achieved by integrating the velocity profile over the elliptic cross-section. The non-Newtonian Eyring–Powell fluid flows quicker through this vertical ciliated elliptic duct than the Newtonian fluid. Moreover, the cilia elliptic movement eccentricity and the wave number for metachronal wave have a dual effect on the velocity profile. Increasing the dimensionless flow rate and occlusion leads to an increase in closed contour size, as seen in the streamline description. Full article

The accelerated low-carbon transition of power systems and the widespread integration of Electric Vehicles (EVs) present both severe operational challenges and substantial flexible regulation potential for Active Distribution Networks (ADNs). This paper provides an integrative review of the coordinated control and multi-market bidding mechanisms for EV-centric Technical Virtual Power Plants (TVPPs). Moving beyond descriptive surveys, this review systematically synthesizes the fragmented literature across three critical dimensions: (1) the physical-economic bidirectional mapping, which considers nonlinear power flow constraints and node voltage limits within the TVPP framework; (2) multi-market coupling mechanisms, evolving from unilateral energy bidding to coordinated participation in carbon trading and ancillary services; and (3) real-time control strategies, critically evaluating the trade-offs between optimization techniques (e.g., Model Predictive Control) and cutting-edge artificial intelligence approaches (e.g., Deep Reinforcement Learning) in mitigating battery degradation. Furthermore, a transparent review methodology is adopted to ensure literature rigor. By explicitly outlining the boundaries between TVPPs, Commercial VPPs (CVPPs), and EV aggregators, this paper identifies core unresolved trade-offs among aggregation fidelity, market complexity, and communication latency, providing evidence-backed pathways for future engineering demonstrations and V2G applications. Full article

This work presents an integrated experimental and numerical determination of the aerodynamic (lift) characteristics of an ogive forebody equipped with all moving canards. Experimental testing was conducted in the subsonic custom-made wind tunnel of the Vlatacom Institute at a nominal free stream velocity of 32 m/s (and Mach number M = 0.09). Aerodynamic loads on the canards were measured using a custom one-component force balance, while free stream flow properties were obtained via a calibrated Pitot–Prandtl probe on the full-scale geometry model. On the numerical side, RANS simulations were performed in ANSYS Fluent using the k-ω SST turbulence model. Two geometric representations were considered: (a) a high-fidelity configuration explicitly resolving the physical gap between the canard and ogive, and (b) a simplified configuration with the gap removed. Boundary conditions, Reynolds number, and operating parameters were matched to the wind tunnel conditions to enable a strict one-to-one comparison. Particular emphasis was placed on examining the effect of geometric simplification on the predicted lift characteristics. The gap-resolved configuration reproduces the experimentally measured lift curve within approximately 10% across the investigated angle-of-attack range, satisfying conventional aerodynamic validation criteria. The results confirm both the robustness of the applied RANS approach for highly three-dimensional separated flows often found in engineering applications, as well as the reliability of the experimental measurement system. Full article

As an innovative metaheuristic algorithm, Genghis Khan Shark Optimization (GKSO) faces challenges, including a tendency towards local optima and poor convergence speed and accuracy. To mitigate these limitations, an improved Genghis Khan shark optimizer (IGKSO) is proposed in this paper. A population partitioning method based on cosine similarity and fitness is introduced, where individuals are strategically assigned to different evolutionary phases: Disadvantaged populations are responsible for the foraging stage. By contrast, advantaged populations dominate the moving stage. In the moving stage, the base vector is randomly selected from multiple candidates, which ensures the evolutionary direction of the population while maintaining its diversity. An adaptive step-size mechanism is introduced to avoid boundary overflow problems. A subspace method is employed to prevent diversity loss during foraging. Additionally, in the hunting stage, a novel opposition-based learning strategy is proposed to moderate the tendency of converging to suboptimal solutions. Furthermore, during the self-protection phase, a criterion for assessing the diversity of the whole population is employed to monitor and supplement diversity in real time. The results of the CEC2017 and CEC2019 benchmark test sets reveal that IGKSO exhibits substantial advantages over the GKSO algorithm and eight other high-performance algorithms in terms of convergence speed and accuracy. Full article

Over the past decade, far-right parties have moved from the political margins into the mainstream of several European democracies. This article examines how migration functions not primarily as a demographic driver of electoral change, but as a discursive resource through which democratic boundaries are redefined. Drawing on a qualitative comparative analysis of political speeches, party manifestos, and public debates in selected European countries between 2014 and 2022, the study investigates how migration is constructed as a threat to welfare systems, national cohesion, and liberal-democratic order. The analysis integrates three complementary frameworks of ethno-pluralism, welfare chauvinism, and civic nationalism to demonstrate how exclusion is legitimized through moralized appeals to culture, fairness, and liberal values. Rather than rejecting democracy outright, far-right actors reinterpret concepts such as citizenship, solidarity, and equality in conditional and culturally bounded terms. Migration thus operates as a symbolic condensation of broader anxieties related to globalization, economic insecurity, and political distrust. The findings show how democratic language itself can normalize exclusionary interpretations of membership, contributing to gradual forms of democratic erosion across Europe. Full article

Three-dimensional (3D) epicuticular wax coverage on plant surfaces contributes to multifunctional surface properties, such as enhanced water repellence, reduced pathogen adherence, modified optical properties, and reduced insect adhesion. The diversity in wax projection morphology, size, abundance, and spatial arrangement among plant species results in a broad spectrum of anti-adhesive effects, reflecting both phylogenetic history and ecological function. This study presents a numerical model consisting of 3D tubular-shaped structures randomly deposited on a substrate and forming a highly porous layer. The simulations based on this model demonstrate a strong reduction in adhesion to the contacting insect adhesive pad. It is found that a structure formed by sufficiently long tubes, where the length is enough to support the tubes in space and build a porous 3D structure with a very low density, at relatively weak attraction to the underlying substrate, leads to the weakest adhesion. The model is constructed on the basis of our recent works combining discrete and continuous approaches in biological modeling. It mainly exploits the technique of the movable digital automata, allowing modeling of numerous numerically elastic cylinders that can be moved in 3D space, elastically collide with one another and with boundaries, and build self-consistent surface structures, which can be used to mimic nano- or microscale surface coverages of real plants. Full article

This paper presents a detailed re-examination of the conformalcompactification $\overline{\mathbb{M}}$ of Minkowski space $\mathbb{M}$, constructed as the projective null cone of the six-dimensional space ${\mathbb{R}}^{4,2}$. We provide an explicit and basis-independent formulation, emphasizing geometric clarity. A central result is the explicit identification of $\overline{\mathbb{M}}$ with the unitary group $U\left(2\right)$ via a diffeomorphism, offering a clear matrix representation for points in the compactified space. We then systematically construct and analyze the action of the full conformal group $\mathrm{O}(4,2)$ and its connected component ${\mathrm{SO}}_0(4,2)$ on this manifold. A key contribution is the detailed study of the double cover, $\tilde{\mathbb{M}}$, which is shown to be diffeomorphic to $S^3\times S^1$. This construction resolves the non-effectiveness of the $\mathrm{SO}(4,2)$ action on $\overline{\mathbb{M}}$, yielding an effective group action on the covering space. A significant portion of our analysis is devoted to a precise and novel geometric characterization of the conformal infinity. Moving beyond the often-misrepresented “double cone” description, we demonstrate that the infinity of the double cover, ${\tilde{\mathbb{M}}}_{\infty }$, is a squeezed torus (specifically, a horn cyclide), while the simple infinity, ${\overline{\mathbb{M}}}_{\infty }$, is a needle cyclide. We provide explicit parametrizations and graphical representations of these structures. Finally, we explore the embedding of five-dimensional constant-curvature spaces, whose boundary is the compactified Minkowski space. The paper aims to clarify long-standing misconceptions in the literature and provides a robust, coordinate-free geometric foundation for conformal compactification, with potential implications for cosmology and conformal field theory. Full article

Electrophoresis titration sensors are widely used for biomarker detection. However, traditional methods rely on a visible boundary for signal readout. Although conventional capacitively coupled contactless conductivity detection avoids indicator dependence, its single-point detection method suffers from long measurement times, large amounts of redundant data, and the inability to dynamically monitor the moving reaction boundary. To address these issues, we developed a novel contactless scanning capacitively coupled conductivity-detection method for microchip electrophoretic titration sensors. This method enables the rapid tracking and monitoring of the boundary within the microfluidic channel through dynamic scanning. The spatial distribution of conductivity during electrophoretic titration was theoretically analyzed. To evaluate the method, glucose was chosen as a model analyte. Quantitative detection was achieved over the linear range of 0.2–50 mM, with the limit of detection of 0.1 mM. The method exhibited satisfactory stability with relative standard deviation values ranging from 0.9% to 4.3% (n = 3). While the detection limit is higher than optical methods (0.02 mM), the results confirmed that the novel method offers merits, such as compact size, low cost and label-free operation. Moreover, it demonstrated strong potential for portable, quantitative analysis of target analytes across a wide range of applications. Full article

On 4 December 2025, nearly two years after the 2024 Mw 7.0 Wushi earthquake, an Mw 5.8 event struck the nearby county of Aheqi, southwestern Tianshan. Owing to the subparallel strikes of both nodal planes and the interspersed hypocenter locations among regional structures in the reported focal mechanisms, the exact fault geometry of this event remains unresolved, impeding a better understanding of regional tectonic activity and the associated seismic hazards. To resolve this, we applied Interferometric Synthetic Aperture Radar (InSAR) technique to map the coseismic deformation and invert for the fault geometry and slip pattern. Significant tropospheric delays are mitigated using a moving-window linear model and a multi-interferogram weighted averaging strategy. The result shows significant uplift (~5.0 cm for ascending track and ~6.0 cm for descending track), indicating thrust-dominated mechanism. Bayesian inversion reveals two possible fault models: a 31.6° north-dipping blind thrust or a 54.4° south-dipping back-thrust. While both fault planes fit the InSAR observations, integrated evidence from the absence of back-thrust development conditions, the surface deformation pattern, and regional topography indicates that the north-dipping Aheqi fault is the causative structure. Together with the steeper Maidan fault to the north, it forms the Orogen Basin boundary along the southern Tianshan piedmont. Our findings highlight that resolving moderate blind-thrust seismogenic structures using InSAR requires integration with pre-existing structural and geomorphic evidence. Furthermore, Coulomb stress calculations indicate a rupture-promoting effect from the Wushi earthquake, which occurred on a reactivated fault, onto the Aheqi event, with stress loading exceeding 2 bar at the hypocenter. Thus, the potential for stress-driven sequential rupture between reactivated and present-day active structures necessitates an updated seismic hazard assessment in the southern Tianshan. Full article

As the global imperative for climate neutrality intensifies, hydrogen (H₂) from fossil fuels remains central to decarbonizing hard-to-abate sectors. Conventional production via steam methane reforming (SMR), however, is carbon-intensive and, even with carbon capture and storage (CCS), incurs energy penalties and long-term storage constraints. This review develops a harmonized well-to-gate, market-oriented framework to evaluate methane pyrolysis (MP) relative to SMR and autothermal reforming (ATR), with or without CCS, moving beyond reactor-focused assessments toward system-level commercialization analysis. MP decomposes methane into hydrogen and solid carbon, avoiding direct CO₂ formation and the need for CCS infrastructure. Integrating with the reverse water–gas shift (RWGS) reaction enables flexible syngas production with adjustable H₂:CO ratios for methanol and chemical synthesis. A central finding is the dominant role of the “carbon lever”: MP generates approximately 3 kg of solid carbon per kg of H₂, making the carbon market’s absorptive capacity the primary scalability constraint. While carbon monetization can reduce levelized hydrogen costs, large-scale deployment would rapidly saturate existing carbon black and specialty carbon markets. Techno-economic evidence indicates that carbon prices above $500/ton are required to achieve parity with gray hydrogen, whereas $150–200/ton enables competitiveness with blue hydrogen. Lifecycle assessments further show that climate superiority over SMR or ATR with CCS requires upstream methane leakage below 0.5% and very low-carbon electricity. Commercial readiness varies, with plasma MP at TRL 8–9 and thermal, catalytic, and molten-media pathways remaining at the pilot or demonstration stage. Parametric decision-space analysis under harmonized boundary assumptions shows that MP is not a universal substitute for reforming but a conditional pathway competitive only under aligned conditions of low-leakage gas supply, low-carbon electricity, credible carbon monetization, and supportive policy incentives. The review concludes with a roadmap that highlights standardized carbon certification, end-of-life accounting, and long-duration operational data as priorities for commercialization. Full article

Maintaining high-precision line-of-sight pointing in airborne electro-optical gimbals remains a significant challenge due to the simultaneous presence of heterogeneous disturbances and strict mechanical structural constraints within complex dynamic conditions. Traditional anti-disturbance methods often struggle to provide fine-grained compensation for multi-source uncertainties where low-frequency lumped disturbances (e.g., friction and unbalanced torques) and high-frequency harmonic vibrations (e.g., engine-induced vibrations and aerodynamic gusts) are intricately coupled. To address these challenges, this paper proposes a refined disturbance separation-based composite control scheme. First, a deep-coupled aircraft–gimbal dynamics model is constructed to reveal the spectral separation characteristics of multi-source disturbances under the “moving base” effect. Second, a Refined Disturbance Observer architecture is developed by coupling an Extended State Observer with a Harmonic Disturbance Observer, enabling the decoupled separation and precise estimation of heterogeneous disturbances based on their spectral characteristics. Furthermore, a finite-time composite controller incorporating a Barrier Lyapunov Function is designed to guarantee that the system output strictly adheres to inherent mechanical structural boundaries. Numerical simulations confirm high-precision tracking and strict constraint satisfaction of the scheme. Full article