Search Results (19,440)

Concentrated sourcing is a structural property of the world economy rather than an occasional accident: across 168 national economies and 1118 four-digit product markets reconstructed from harmonized cross-border flow records, 27.7% of macro-level economy–product supply systems draw more than half of their imports from a single origin and 19.3% are critically dependent. Treating each such market as a system rather than as a set of bilateral links changes what can be asked of it, and this paper specifies the economy–product supply system in systems-engineering terms—boundary, elements, internal relations, external environment, state and state transition—and represents it as a time-evolving hyperedge over source countries. Three coupled questions follow, answered jointly by HyperSRM: which dependency state a system will occupy next year, whether it will diversify, reconcentrate, hold, or merely substitute one origin for another, and which origins are most consistent with the observed conditions preceding a material entry. Shared country and product embeddings support two temporal set-encoding branches, a candidate-conditioned branch for origin ranking and a candidate-free branch for state and mode forecasting, a sign-constrained gravity–capability–connectivity prior supplies an observational plausibility score with end use and maritime reachability as its context, and risk weights derived from the state head direct effort toward the most exposed systems. Developed on CEPII BACI, rebuilt independently on Eurostat Comext and audited against U.S. Census data at the level of the labels themselves, the framework returns calibrated state probabilities and a ten-origin shortlist that captures 58.1% of the following year’s risk-weighted material-entry mass and is accompanied by explicit out-of-pool diagnostics. These outputs describe the import-sourcing layer of resilience and are intended for analytical triage rather than a complete assessment of supply resilience. Three system-level regularities carry beyond the model: the arrival of a new origin is a weak proxy for diversification, critical dependency is close to absorbing for specified intermediate inputs but not for final goods, and the 2020–2021 contraction rearranged source sets without widening them—so resilience monitoring built on source counts misreads the direction of change. Full article

Background: Perfluorooctane sulfonate (PFOS) is a globally recognised persistent, bioaccumulative and toxic pollutant. Under China GB 5749-2022 and the US EPA 2024 drinking water MCL, permissible levels have fallen to 40 ng L⁻¹ and 4 ng L⁻¹, respectively, placing unprecedented demands on remediation technologies. Methods: An iron(III)–carboxylate metal–organic framework prepared from low-cost precursors (denoted MOF-LC, [Fe₃O(BDC)₃Cl]·x(solvent)) was synthesised via a one-pot solvothermal route from FeCl₃·6H₂O and terephthalic acid (H₂BDC). The material was characterised by PXRD, N₂ adsorption, FTIR, TGA, XPS, elemental analysis and ICP-OES. Adsorption performance was evaluated under varying initial concentrations, contact times, pH values, coexisting inorganic anions (Cl⁻, NO₃⁻, SO₄²⁻, HCO₃⁻, PO₄³⁻) and humic acid backgrounds, and by a panel of six water matrices. Results: MOF-LC exhibited a BET surface area of 1528 m² g⁻¹ and a dominant pore centred at 1.9 nm, which is geometrically compatible with the 1.36 nm molecular length of PFOS. Adsorption reached ≈95% of equilibrium capacity within 30 min and was best described by the pseudo-second-order model (R² = 0.998). Measured uptake reached 800.6 mg g⁻¹ at 298 K, corresponding to a Langmuir maximum capacity of 802 mg g⁻¹ (note that all adsorption experiments were conducted at mg L⁻¹ concentrations, several orders of magnitude above the regulatory limits cited above). Removal exceeded 88% across all six water matrices. PFOS removal efficiency fell from 99.2% to 85.8% over seven adsorption–regeneration cycles using a 1% NH₄Cl/methanol eluent, with 90.6% of the initial BET surface area retained and Fe leaching below 45 µg L⁻¹. Conclusions: Electrostatic, hydrophobic and pore confinement contributions are proposed as cooperative interpretations consistent with the observations. MOF-LC is identified as a technically promising laboratory-scale sorbent for PFOS removal from complex water matrices. Performance at environmentally relevant ng L⁻¹ concentrations and economic viability at scale remain to be established. Full article

Protected horticultural crops are commonly produced at high planting densities and have short production cycles; imbalances in water and fertilizer supply can rapidly affect plant vigor, yield, and quality. Non-destructive diagnostic methods are therefore needed to characterize plant nutritional status under greenhouse conditions. Spectral imaging can simultaneously capture spatial and spectral information associated with pigments, water status, tissue structure, and canopy phenotype. It does not directly detect nutrient ions; rather, it captures physiological and structural responses that may be associated with nutrient status and may also be influenced by water deficit, disease, temperature, salinity, phenology, and genotype. This review focuses on crops grown in soil, substrate, and hydroponic systems under greenhouse conditions. Studies conducted in vertical farms, growth chambers, and open fields are included only as supplementary references for sensor selection, model calibration, and inspection methods. This article synthesizes diagnostic indicators for nitrogen, phosphorus, and potassium, together with their associated physiological responses and spectral characteristics; compares the performance of hyperspectral, multispectral, and machine learning methods at the leaf, plant, and canopy scales; and examines fixed measurement, stop-and-go mobile inspection, continuous motion imaging, and autonomous plant revisitation. Existing studies have established a solid foundation for nutrient content retrieval, deficiency identification, and mobile monitoring. However, several challenges remain inadequately addressed under continuous inspection conditions, including radiometric–geometric joint calibration, plant identity preservation, acquisition of multi-element chemical truth values, model generalization across growth stages and greenhouse types, and long-term performance evaluation. Future work should refine standardized protocols for dynamic data collection and water–fertilizer environmental control, integrate mechanistic constraints with data driven approaches, and incorporate plant re-identification, spatiotemporal registration, uncertainty quantification, and online calibration. These efforts will contribute to constructing a long-term stable and comparable nutritional diagnostic system, thereby advancing the transition of facility vegetable nutritional monitoring from single-time static measurements toward continuous, traceable, and autonomously patrolled systems that may ultimately support precision irrigation and fertilization management after appropriate independent validation. Full article

Activity–travel pattern reconstruction infers latent paths, destinations, activities, and timing from incomplete mobility observations and supports travel-demand analysis and activity-based simulation. A structured search and citation tracking identified 157 core studies. Existing studies, however, remain fragmented across data sources, local reconstruction tasks, modeling techniques, and evaluation settings. This survey develops an integrated framework linking observation mechanisms, mathematical models, real-data applications, and performance evaluation. It first formulates reconstruction as inference over a latent activity–travel chain conditioned on partial observations and contextual information. Major mobility data sources are then compared according to their Eulerian or Lagrangian observation mechanisms and their spatial, temporal, and semantic information. Reconstruction methods are organized into model-driven, data-driven, and hybrid approaches, with emphasis on their mathematical structures, real-data applications, and ability to represent network, temporal, behavioral, and uncertainty constraints. Evaluation methods are reviewed at the element, chain, and population levels, while distinguishing missing-only performance from full-output performance. This review identifies four priorities for future research: joint reconstruction of complete chains, principled multi-source data fusion, calibrated uncertainty representation, and transferable benchmarks with realistic missingness and independent testing. This framework clarifies the current state of the field and supports the development of more reliable and behaviorally meaningful reconstruction methods. Full article

For the first time, for oxidative cross-linking of chitosan with a natural polyphenol, ferulic acid, the so-called small two-domain bacterial laccase, was used. Recombinant Streptomyces carpinensis laccase (ScaSL) has been shown to oxidize ferulic acid in neutral and alkaline environments, which is important for subsequent nucleophilic reactions of chitosan with oxidation products. The selected conditions (pH 7.0, molar ratio FA/NH₂ = 1:10) provide a cross-linking degree of more than 80%, which significantly exceeds the indicators previously achieved using other laccases. Based on the results of quantum chemical modeling and experimental studies using FTIR spectroscopy and XPS, as well as thermogravimetric and differential scanning calorimetry, a new mechanism for laccase-catalyzed cross-linking of chitosan with ferulic acid without the formation of Schiff bases is proposed. The resulting hydrogels have a uniform smooth microstructure, high oxygen permeability, a significant degree of swelling (270%), and stability over a wide pH range. The material neutralizes up to 95% of ABTS^+• cation radicals. Quantum chemical analysis within the framework of the Marcus theory has demonstrated that the chitosan–ferulic acid conjugate is superior in antioxidant capacity to ferulic acid dimers, despite the decrease in the matrix element of the bond. Application of two-domain bacterial laccase for modifying chitosan hydrogels with ferulic acid opens the way to the creation of environmentally friendly biomaterials with antioxidant protection. Full article

The work develops methods for synthesizing complex salts: [Co(NH₃)₆]₂(CrO₄)₃, [Co(NH₃)₆](CrO₄)(NO₃), [Co(NH₃)₆](CrO₄)Cl·3H₂O, [Co(NH₃)₆]₂(Cr₂O₇)₃·5H₂O, [Co(NH₃)₆](Cr₂O₇)(NO₃)·H₂O and [Co(NH₃)₆](Cr₂O₇)Cl·H₂O. The compounds were characterized by PXRD, IR and elemental analysis. It was demonstrated that mixed-anion complex salts ([Co(NH₃)₆](CrO₄)(NO₃) or [Co(NH₃)₆](CrO₄)Cl·3H₂O) form in the [Co(NH₃)₆]³⁺/(CrO₄)²⁻ system depending on the counterion of hexaamminecobalt(III), [Co(NH₃)₆](NO₃)₃ or [Co(NH₃)₆]Cl₃, respectively. Conversely, it was more difficult to obtain mixed-anion complexes in the [Co(NH₃)₆]³⁺/(Cr₂O₇)²⁻ system. Thus, to obtain [Co(NH₃)₆](Cr₂O₇)Cl·H₂O an excess of chloride ions in the solution is required. At the same time, when the initial dichromate solution is acidified, the complex [Co(NH₃)₆]₂(Cr₂O₇)₃·5H₂O is formed, exhibiting structural polymorphism: the crystal structure changes without altering the chemical composition when stored in a closed container. The process of thermal decomposition of all synthesized complex compounds in an inert atmosphere has been studied. The final product of the thermolysis of most compounds at a temperature of 600 °C is a nanoscale single-phase solid solution Co(Co_1−xCr_x)₂O₄ with a spinel structure (with crystallite sizes of no more than 15 nm), where the metal ratio corresponds to that of the initial complex salt. The smallest crystallite size (3–4 nm) was obtained through the thermolysis of [Co(NH₃)₆](CrO₄)Cl. Full article

Double-layer barrel vault roofs with double-layer vertical walls are widely used in important public buildings because of their high structural efficiency, favorable stiffness-to-weight ratio, and architectural versatility. Although incremental dynamic analysis (IDA) is a widely accepted approach for seismic assessment, it requires numerous nonlinear time-history analyses (NTHAs), resulting in high computational cost. This study presents an artificial neural network (ANN)-based surrogate modeling framework to accurately predict the seismic response of these structural systems, reducing the need for repeated NTHAs, enabling rapid estimation of structural dynamic responses, and facilitating direct development of seismic fragility curves. The proposed framework substantially decreases computational effort while maintaining an effective balance between accuracy and efficiency. A comprehensive seismic damage database is first generated using finite element (FE) models developed in OpenSees. Fragility curves are then obtained using both the conventional IDA procedure and the proposed ANN-based surrogate approach. Results show that the ANN surrogate accurately predicts the responses of structures subjected to scaled ground motions and effectively captures their nonlinear seismic behavior. Furthermore, the resulting fragility curves closely match those from the conventional IDA method, demonstrating the accuracy, reliability, and efficiency of the proposed framework for rapid seismic assessment of double-layer barrel vault structures with double-layer walls. Full article

This study hypothesises and explores the co-evolutionary patterns and potentially the bidirectional influence between computational modelling exercises and real-world practices by employing the elements of the co-evolutionary framework (i.e., technologies, formal institutions, user practices, business strategies and ecosystems) and focusing on the literature on the application of agent-based modelling and simulation (ABMS) for studying community energy systems (CESs). The study shows that modelling exercises are becoming more complex, including more elements and conditions from the real world. The results confirmed the co-evolutionary patterns and demonstrated that the evolution of technologies (e.g., from solar PV alone to multiple energy sources) and business strategies (e.g., peer-to-peer, real-time pricing and day-ahead market) is more significant than the other three elements. On the other hand, formal institutions and ecosystem elements received limited attention. The evolution of models of collective energy security is analysed as an example, further highlighting the evolution of technologies element. Given the detailed analysis of models developed to study CESs and the evolution of modelling practices, this study sheds light on the aspects and complexities that future studies should consider. The study and its findings contribute to strengthening modelling practices in the energy transition and, more broadly, in sustainability. Full article

This study develops a SCHISM-based hydrodynamic model and an offline Lagrangian virtual-particle workflow for the Zadar Channel, a geometrically complex island–mainland passage in the eastern Adriatic. Independent hourly observations from the MP Zadar tide gauge operated by the Hydrographic Institute of the Republic of Croatia (HHI) were used to evaluate the modelled free-surface response. After exclusion of the first 24 h ramping period, 192 matched hourly pairs gave a Pearson correlation of 0.913, a mean bias of 0.012 m, a mean absolute error of 0.051 m, and a root-mean-square error of 0.070 m; cross-correlation was maximized at zero lag. The model reproduced the timing of the observed oscillations but underestimated their amplitude, with simulated and observed standard deviations of 0.117 and 0.157 m, respectively. The adopted unstructured mesh contains 16,962 triangular elements and 9081 nodes. In four 24 h particle-sensitivity tests, maximum reach ranges from 8.4 to 14.2 km; a 15-fold change in horizontal diffusivity affects reach less than sampling a lower model layer, which reduces reach by 32.8%. In the June 2025 event calculation, cumulative numerical shoreline contact increases from zero to all 1000 particles. The approximately 4 km Copernicus regional product masks the narrow interior passages and is therefore used only to assess spatial representativeness, not to validate channel currents. The tide-gauge comparison supports the modelled sea-level response and its timing at one station, but does not constitute direct validation of local current velocities. The reported trajectories are current-driven passive-particle diagnostics; wave–current coupling, Stokes drift, and material-specific fate processes are not represented. Full article

The strip width in ultra-wide-strip tandem cold rolling changes not only the total rolling load, but also the transverse span over which the work roll (WR) is loaded. This study quantifies the isolated width effect on strip crown at 40 mm from the edge ($C_{40}$), flatness and WR elastic deformation in a 2180 mm CVC-6 tandem cold mill. A three-dimensional multi-stand elastic–plastic finite element (EPFE) model was established for five representative widths of 900, 1200, 1500, 1800 and 2100 mm, corresponding to contact-span ratios of 0.413–0.963. The results show that the strip width increased from 900 mm to 2100 mm, $C_{40}$ decreased from 20~80 μm to −50~−280 μm, and 1800 mm was the transition point from the positive crown to the negative crown. At the same time, the quadratic flatness component increased toward a center-wave mode, whereas the quartic component decreased toward an edge–center coupled-wave mode. Mechanistically, the relative WR axis deflection at the strip edge increased much faster than the local WR flattening compensation, producing an edge-open loaded roll gap. The findings indicate that strip width should be treated as an independent preset variable for WR bending, intermediate-roll bending and intermediate-roll shifting in ultra-wide cold rolling. Full article

Laser powder bed fusion (LPBF) is a disruptive additive manufacturing process for producing high-performance Inconel superalloy parts with complex shapes for the aerospace, energy, and other demanding industries. However, uniform part quality remains a persistent challenge, as process parameters, melt-pool dynamics, microstructural evolution, defect formation, and mechanical performance are closely coupled across a wide range of spatial and temporal scales. In previous reviews, these dimensions have been considered in isolation with limited insight into their interactions and implications for predictive process control. The present review aims to address this lacuna by proposing a unified Process–Structure–Property–Control (PSPC) framework for LPBF-produced Inconel 625, 718, and 738. The discussion begins with material attributes governing alloy processability, and then synthesises the melt-pool physics governing thermal behaviour, solidification, and energy transfer. Attention then turns to a critical assessment of grain evolution, defect formation, and process stability, showing how the thermal history governs microstructural development and, in turn, mechanical performance via linked process–structure–property relationships. Progress in multiscale numerical modelling, such as finite-element analysis, computational fluid dynamics, phase-field modelling, cellular automata, and phase-diagram calculation (CALPHAD), is reviewed to establish a comprehensive modelling ecosystem for predictive LPBF. The review also discusses the potential of emerging technologies, such as beam shaping, multi-laser processing, in situ monitoring, artificial intelligence, and powder recyclability, to increase the robustness and productivity of the process. Building on these advances, a digital-twin-enabled predictive-manufacturing framework that integrates physics-based models, data-driven algorithms, and real-time monitoring is introduced to enable closed-loop process optimisation. The review ends with a scientific synthesis and future research roadmap for intelligent, reliable, and autonomous LPBF of next-generation Inconel superalloys. Full article

Injection molding is a plastic material processing technique used in the polymer industry. Because it is a complex process that requires injection cycles to achieve the desired aesthetic quality in the molded parts, it is essential to evaluate and configure all process parameters to predict and reduce defects, thereby decreasing the processing time and energy consumption. This study presents the results of tests performed on molded HDPE parts, including modeling and simulation using ANSYS^® (2025 R1), a design of experiments (DOE), and 3D scanning of the molded parts. The study compares the behavior of defects (warpages and sink-marks) in molded parts using 3D scanning with the results obtained from coupled thermal-structural field finite element simulations. These simulations were performed using software to assess the residual thermal stress of the ejection phase. The results visually display information that helps designers and engineers in the polymer processing sector evaluate molding-process failures using different software. Full article

Owing to their exceptional thermal insulation and protective capabilities, thermal barrier coatings (TBCs) are widely applied to critical hot-section components of aero-engines. However, under increasingly harsh service environments, internal defects such as delamination tend to form within the coatings, posing a severe threat to engine operational safety and service life. To effectively evaluate delamination defects in TBCs, this study employs the immersion ultrasonic pulse-echo technique to inspect specimens subjected to various thermal cycling treatments. Four specimens, subjected respectively to 21, 32, 43, and 54 thermal cycles at 1200 °C, were tested. Ultrasonic response data were systematically acquired via normal incidence scanning from both the superalloy substrate side and the ceramic top coat side. Combining Fast Fourier Transform (FFT), Continuous Wavelet Transform (CWT) based on the generalized Morse wavelet, Wavelet Packet Energy Entropy (WPEE), and peak-to-peak amplitude variations of the second echo, multi-dimensional features were extracted from ultrasonic signals across the frequency domain, joint time-frequency domain, and energy distribution profiles. Through comparative analysis, ultrasonic waveform and time-frequency characteristics representing defect evolution were obtained. A significant monotonically decreasing trend of WPEE with the aggravation of interfacial delamination was established, characterizing the acoustic energy confinement process induced by interfacial damage. Furthermore, a multilayer finite element (FE) model reasonably reproduced dynamic acoustic wave propagation; numerical results are in agreement with experimental data, validating the feasibility of the proposed detection method. The detection and evaluation framework established in this study provides a reference for safety monitoring and lifespan prediction of aero-engine TBCs. Full article

Low Earth orbit (LEO) mega-constellations demand scalable routing that survives time-varying topologies, constrained onboard resources, and dynamic traffic. Deterministic shortest-path routing guarantees optimal paths but adapts poorly to real-time loads; distributed deep reinforcement learning (DRL) can introduce loops and inconsistent end-to-end decisions. This paper fuses deterministic inter-domain planning with DRL-based intra-domain forwarding in a single hierarchical framework. An evolutionary greedy algorithm partitions the constellation into compact domains. Dijkstra’s algorithm then computes backbone paths on the domain-level graph. Inside each domain, a context-enhanced Per-Action Dueling Double Deep Q-Network encodes individual neighbors through a weight-shared encoder and summarizes the valid-neighbor set via masked mean pooling. This design lets the policy compare a candidate against the current alternative set without injecting input-order bias. Local one- and two-hop topological features drive decentralized inference. A greedy–beam–Dijkstra fallback ladder guarantees reachability whenever the subgraph stays connected. On a 1584-satellite Starlink Gen1-1 topology, all 21 domain sizes and six inter-domain strategies reach 100% of test pairs; the best average hop count sits at 1.16× the global Dijkstra benchmark. Under an identical 52-dimensional state and training pipeline on 1000 held-out source–destination pairs, Context Per-Action uses 75.8% fewer parameters than a flat multilayer perceptron (MLP), lifts greedy success from 74.6% to 83.5%, and lifts greedy-plus-beam success from 88.3% to 94.5% (means over three independent training seeds). Centralized load-aware routing under dynamic traffic cuts high-load packet loss from 34–73% to 0–9.5% in the adopted flow-level model and preserves 99.2% reachability despite 30% link failures. Zero-shot transfer from ideal Walker topologies to real two-line element (TLE) snapshots and purely local load adaptation remain open; multi-snapshot training or online adaptation is the necessary next step. Full article

Rare surviving examples of late eighteenth-century French dress are exceptional. The robe à la circassienne examined in this study is preserved in an unusually intact state, likely due to its small size, which limited its suitability for later wearers, and the rapid shift in fashion that further reduced incentives for alteration or reuse. Discrepancies between the garment’s present coloration, early cataloguing records, and a non-matching reproduction petticoat prompted an investigation into its original appearance. The dress features a ground fabric woven with a pink warp and white weft, accented by vertical multicolored stripes. Organic colorants were analyzed using liquid chromatography–diode array detection–quadrupole time-of-flight mass spectrometry (LC-DAD-qToF-MS), and elemental composition was determined by X-ray fluorescence (XRF) spectroscopy. The dark pink stripe contained safflower (Carthamus tinctorius), a highly fugitive dye. The blue and green stripes showed mixtures of weld (Reseda luteola), an indigoid dye (Indigofera spp.), and Brazilwood (Caesalpinia or Haematoxylum spp.), consistent with historical recipes for bronze and wood shades. Brazilwood and an orchil dye detected in the ground fabric suggest an original reddish-purple hue rather than the pale pink visible today. Arsenic found in the pink fabric and trim provides the first material evidence for the French orchil-dyeing process known as Parelle d’Auvergne. By integrating analytical results with historical dye recipes and curatorial records, this study proposes a hypothesis for the garment’s original appearance and demonstrates how combined scientific and historical approaches deepen our understanding of fragile textile artifacts and the factors that shaped their creation and survival. Full article