Search Results (47,331)

Despite the significant reduction in the overall cultivated area registered in recent decades, poplar still plays an important economic role in the Po Valley–Italy, where many farms involved in the plantation of this species are present, and the leading wood-processing industries are located. This paper describes the current organization of the poplar plywood wood-chain and explores the challenges in introducing new cultivars into the sector. In particular, it analyzes the main physico-mechanical properties of solid wood from five selected poplar clones (‘Dvina’, ‘Lux’, ‘Mella’, ‘Soligo’, ‘Taro’) that are characterized by fast growth, more sustainable agronomic practices, and increased disease resistance. These clones were cultivated in a seven-year-old linear plantation located in Northern Italy. This model, widely used in the past, is being re-proposed as a complement to the traditional system with square planting distances. The peeling yields and some performances of plywood manufactured from their veneers were also investigated. Results indicate that all clones have a much higher (from +30% to +56%) wood basic density than the ‘I-214’, which remains the lighter and preferred reference. These clones appeared also suitable for rotary cutting, but only ‘Lux’ and ‘Soligo’, and to a lesser extent ‘Mella’, provided veneers of the best quality class. Interesting mechanical features were registered for the sample plywood produced, especially in relation to the age of the harvested timber, which reached a diameter adequate for processing in a shorter time compared to the turnover adopted in conventional plantations. Except for ‘Dvina’, for all the clones, bending MOE and MOR were found to be comparable with those of spruce plywood made of similar thickness and the same lay-up. The findings suggest that the availability of new poplar cultivars and that of different cultivation models designed to enhance fast growth, when supported by targeted research and cooperation among multiple stakeholders (including farmers and industrial manufacturers), can lead to new applications where their plywood performances are valued. This, in turn, allows the resulting panels to meet specific needs in previously unexplored sectors, offering additional market opportunities. Full article

The increasing reliance on digital infrastructures has positioned electronic records management systems (ERMS) as critical mechanisms for supporting organisational governance, accountability, transparency, and effective service delivery. This study presents a structured qualitative literature review examining ERMS implementation across developed and developing institutional contexts to identify key determinants, recurring implementation challenges, and contextual variations in adoption patterns. Drawing on studies published between 2012 and 2026, the review adopts a socio-technical analytical framework that categorises implementation determinants into environmental, technological, and organisational dimensions, specifically: governance and policy alignment; technological infrastructure readiness; interoperability and system integration; and human re-source capacity and organisational culture. The findings indicate that successful ERMS implementation depends on the alignment and interaction of governance frameworks, technological capabilities, and organisational readiness. The analysis further demonstrates that these determinants are highly interdependent and vary according to levels of institutional and digital maturity. In developing contexts, implementation is primarily constrained by inadequate infrastructure, financial limitations, weak policy enforcement, and shortages of skilled personnel. In contrast, digitally mature environments increasingly focus on interoperability, metadata standardisation, usability optimisation, and long-term digital preservation. This study contributes to the literature by synthesising fragmented empirical findings into an integrated socio-technical framework, thereby advancing a more structured understanding of ERMS implementation across diverse governance environments. The review also identifies major methodological limitations within the existing literature, including limited empirical validation, weak longitudinal analysis, language bias, and the predominance of single-institution case study designs. The findings provide practical implications for policymakers, information managers, and institutions seeking to strengthen electronic records management and information governance practices. Future research should prioritise longitudinal, comparative, and cross-national studies to further advance theoretical and empirical understanding of ERMS implementation. Full article

Part II of this study builds upon the mathematical framework developed and validated in Part I for describing the geometry and volumetric performance indicators of an innovative three-rotor hydraulic pump with bilateral lantern meshing. This part focuses on the numerical investigation and multi-objective optimization of these indicators through the proper selection of geometric parameters. The aim of the study is to establish the isolated and combined influence of the dimensionless geometric parameters—number of teeth z, relative lantern radius r^*_c,  and cycloid shortening coefficient λ—on the actual flow rate Q and the volumetric efficiency η_v under various operating conditions, while maintaining the overall dimensions of the pump element in the radial and axial directions. Through detailed numerical analysis and subsequent rigorous analytical proof, it has been established that the optimal values of the geometric coefficients r^*_c,opt and λ_opt are strictly determined and provide a simultaneous global maximization of both indicators (Q, η_v), regardless of the operating pressure p, rotational speed n,  or the viscosity of the working fluid. However, an analytically irresolvable conflict regarding the number of teeth z has been identified: a small number maximizes the flow rate, whereas a large number increases the volumetric efficiency. To overcome this contradiction, the problem is formulated within the class of mixed-integer nonlinear programming (MINLP), and multicriteria Pareto optimization is applied, combined with the PSIMS method for the selection of optimal compromise solutions. An empirical relationship (with a coefficient of determination of R² = 0.9603) has been derived, which defines the optimal number of teeth z_opt as a function of the operating pressure and rotational speed. The proposed methodology provides a reliable and applicable tool for designing highly efficient three-rotor pumps tailored to specific operational requirements. Full article

Porcine circovirus type 2 (PCV2) is the primary causative agent of a spectrum of porcine circovirus-associated diseases (PCVDs) and remains a major threat to the global swine industry. In this study, ten monoclonal antibodies (mAbs) targeting the Cap protein of PCV2 were generated and characterized. One mAb, designated 4C4, which exhibited high reactivity, strong neutralizing activity, and superior blocking efficacy, was selected for horseradish peroxidase (HRP) labeling. After optimizing the reaction parameters, a blocking ELISA was developed for the detection of the anti-PCV2 antibody. Using receiver operating characteristic (ROC) curve analysis, a cutoff value of 40% was established to distinguish positive from negative serum samples. The sensitivity and specificity of this blocking ELISA method were 98.66% and 100%, respectively. No cross-reactivity was observed with serum antibodies against classical swine fever virus (CSFV), porcine epidemic diarrhea virus (PEDV), porcine deltacoronavirus (PDCoV), porcine reproductive and respiratory syndrome virus (PRRSV), or pseudorabies virus (PRV). Intra-assay and inter-assay repeatability tests yielded coefficients of variation (CVs) all below 10%, confirming the assay's excellent reproducibility. Simultaneous testing of 312 clinical porcine serum samples using the developed bELISA and a commercial indirect ELISA kit revealed an overall coincidence rate of 99.04%. In addition, the percentage inhibition (PI) in the bELISA was strongly correlated with serum anti-PCV2 neutralizing antibody titers. In conclusion, the blocking ELISA developed herein demonstrates high sensitivity, strong specificity, and good reproducibility, serving as a potentially effective tool for the detection of the anti-PCV2 antibody and epidemiological investigation. Full article

Alpine permafrost and seasonally frozen ground threaten the long-term safe operation of highway infrastructures. Aiming at the structural performance optimization of prefabricated corrugated steel plate retaining walls in alpine permafrost regions, this study adopted finite element numerical simulation combined with field test validation to systematically explore the influences of wall height, plate thickness, corrugation geometry, and tie reinforcement layout on structural deformation and internal force, and carried out targeted parameter optimization. The core innovations include the following: (1) Structural lateral displacement and internal force rise nonlinearly with the increase in wall height, and high retaining walls exhibit an accelerated growth trend of deformation and stress. (2) Increasing plate thickness can effectively reduce structural displacement and stress, while the improvement effect gradually weakens after exceeding a critical thickness. Specifically, when the thickness increases from 4 mm to 5 mm, the displacement decreases by 33.13%. (3) Appropriately increasing corrugation pitch and height improves structural equivalent stiffness and optimizes stress distribution. Increasing the corrugation pitch from 75 mm to 400 mm and corrugation height from 25 mm to 150 mm reduces the maximum horizontal displacement by 52.6%. This demonstrates that larger corrugation profiles significantly improve structural stiffness. For walls higher than 6 m, the spacing should be reduced to 0.8 m × 1.0 m to provide additional lateral restraint. (4) Furthermore, seasonal freeze–thaw cycles and a non-uniform temperature field significantly amplify structural displacement and stress. After 12 months of freeze–thaw cycles, the maximum horizontal displacement increases by 49.7% and the maximum equivalent stress increases by 56.9% compared to the initial state. This study clarifies the parameter control mechanism and temperature coupling effect and provides a reliable theoretical basis and design reference for the engineering application of prefabricated corrugated steel plate retaining walls in alpine permafrost areas. Full article

The continuous evolution of the SARS-CoV-2 virus, marked by the emergence of new variants, poses a significant threat to the efficacy of existing vaccines. However, a promising approach to addressing vaccine failure caused by viral mutations (particularly in the spike protein) is the development of a variant-proof (conserved), non-spike, multiepitope universal nanostructure vaccine with multifunctionality, biocompatibility, self-adjuvanticity, and structural similarity to pathogens in terms of size and shape. This study aimed to design a self-assembled nanostructure vaccine (SANV) featuring pentameric and trimeric coiled-coil peptide motifs, as well as other functional motifs, including epitopes, TAT, PADRE, and adjuvant. The cytotoxic T lymphocyte (CTL), helper T lymphocyte (HTL), and B lymphocyte (BL) epitopes of SANV were screened from the IEDB with more than 50% individual predicted population coverage (PPC) and fused using linkers to enable self-assembly. The multimerization of the 24 SANV monomers was modeled using the GalaxyHomomer and AlphaFold web servers. Subsequently, the leading SANV constructs with (SANVa9) and without (SANVb6) adjuvant were analyzed for their physicochemical profiles and assessed for antigenicity, allergenicity, solubility, and antioxidant potential. Furthermore, the molecular interactions, specificity, and stability of SANVa9 and SANVb6 with the broadly neutralizing sarbecovirus antibody 5817 and toll-like receptors (TLR2, TLR3, and TLR7) were analyzed using molecular docking and simulation over a 100-nanosecond time scale. Finally, the comparative immune simulation profiles of SANVa9 and SANVb6 with controls indicated stronger, broad-spectrum immune responses that could be translated into in vitro and in vivo studies and warrant further evaluation before clinical use. Full article

Graphite nozzles remain the dominant choice for small hybrid and solid rocket motors operating on laboratory and university budgets, owing to their low cost, ease of machining, and rapid turnaround during iterative design campaigns. These same programs, however, must contend with the fact that graphite erodes through coupled thermochemical and mechanical mechanisms when exposed to the oxidizing species generated by high-energy propellant combustion, and the resulting throat-area growth fundamentally alters the time histories of chamber pressure, thrust, and delivered specific impulse. This paper presents a nozzle-erosion reconstruction model that extracts the time-resolved throat area from coupled thrust and chamber-pressure measurements using the thrust coefficient relationship, scales the reconstructed area history against pre- and post-test throat measurements, identifies the onset and rate of erosion, and accounts for variable sensor lag between the thrust-stand and pressure-transducer signal chains. The model is exercised on two complementary sets of laboratory-scale GOX/ABS hybrid hot-fire data that together span roughly two orders of magnitude in total throat-area change and peak chamber pressures from 0.5 to 3.4 MPa: a controlled three-operating-point campaign conducted in support of the NASA Plume-Surface Interaction (PSI) program, and a set of higher-pressure firings from the laboratory development series in which the technique was matured. Reconstructed erosion-onset times, erosion rates, and total throat-diameter change are reported for each firing, the reconstruction accuracy is characterized as a function of erosion magnitude. A correlation of graphite erosion with chamber pressure is examined across the combined envelope. The results demonstrate the robustness of the reconstruction technique and provide a reusable framework for post-test reconstruction of transient nozzle geometry in rocket-engine ground testing. Full article

Lightweight resin lattice structures are prone to instability and failure under compressive loading, which leads to limited load bearing capacity and energy absorption performance. In this study, tough resin triply periodic minimal surface (TPMS) lattice scaffolds were fabricated using stereolithography-based 3D printing, and polyurethane foam (PUF) was subsequently infiltrated into three representative topologies, namely Schwarz Primitive (P), I-Wrapped Package (IWP), and Gyroid (G), to form interpenetrating phase composites (IPC). Quasi-static compression results show that PUF infiltration significantly improves the compressive response of all IPC architectures. The stress level in the plateau region is increased, while the magnitude of local stress drops is reduced, leading to a more stable progressive compression behavior. By comparing the stress–strain responses of IPC with the linear superposition of the pure resin scaffold and PUF phases, it is found that the actual energy absorption of IPC exceeds the predicted additive response, indicating a pronounced synergistic effect between the two phases. Among them, the IWP-based IPC achieves a specific energy absorption of 11.72 J/g. These results demonstrate that interpenetrating phase architectures can maintain lightweight characteristics while enhancing load bearing stability and energy absorption efficiency, providing useful guidance for topology selection and lightweight design of TPMS-based energy absorbing composite structures. Full article

Quantum computers are a new generation of computers, whose principles for designing algorithms have already been defined, despite their hardware implementation still being under development. Attracting more scientists to the field is crucial to developing new algorithms in order to make the most of quantum computers once they are available. Serious games can contribute a lot to this effort. This article focuses on the pilot evaluation of the Quantum Escape serious game, which is based on a 3D format for motivating students and a conceptual simplification strategy for making abstract concepts accessible. Specifically, the game design is grounded in the established Four-Dimensional framework, and it aims to transform abstract concepts like superposition and entanglement, as well as common quantum gates, into intuitive puzzles presented through probabilities. The design of Quantum Escape was evaluated by 27 Computer Science students and graduates, in terms of perceived player experience and perceived short-term learning using a questionnaire based on the established MEEGA+ evaluation framework. The design choices of Quantum Escape seem to be validated, since most novice participants found the game understandable and requiring no prior knowledge, while participants with relevant background in quantum computing also largely endorsed the content’s accuracy. Limitations in the extent of quantum computing concepts and the number of participants dictate further development and evaluation of the game. Full article

Modern agriculture in developing regions faces significant challenges due to labor scarcity and the health hazards associated with the manual application of chemical treatments. This study presents the design, development, and techno-economic evaluation of an experimental hexacopter unmanned ariel vehicle (UAV) platform specifically tailored for crop protection on fragmented, smallholder farmlands. The research aims to bridge the gap between expensive imported technology and the practical needs of small-scale farmers by providing a cost-effective, locally manufacturable solution. The methodology involved the integration of a modular spraying system and optimized control architecture into a high-stability hexacopter frame. Experimental evaluations focused on flight stability, payload capacity, and spray uniformity using water-sensitive media. The results indicate that the developed platform achieves high coverage efficiency while significantly reducing chemical waste compared to traditional manual methods. Furthermore, the economic analysis suggests that the operational costs are substantially lower than those of comparable imported systems, offering a favorable payback period within a few crop seasons. These findings demonstrate that an indigenous UAV spraying platform can enhance both operational safety and economic feasibility for smallholder agriculture. Full article

Hypergraph neural networks have shown strong potential for node classification due to their ability to capture high-order relationships and multi-granularity structural patterns. However, real-world hypergraphs are often sparse, which limits interaction modeling through node–hyperedge incidence and, in turn, weakens reliable attribute propagation and global dependency capture. To address this issue, we propose DDEC, a Dual Dependency-Enhanced Contrastive learning framework for sparse hypergraph node classification. To compensate for relational information lost under sparse structures, DDEC introduces an attribute view to complement the structural view. Since attribute information can be noisy and unreliable, we first design an entropy-guided feature recalibration mechanism to estimate node uncertainty and emphasize trustworthy attribute interactions. Building upon this, DDEC performs dual dependency enhancement from both structural and attribute perspectives. Specifically, we exploit the duality between a hypergraph and its line graph to perform line-graph transformation in both views, thereby constructing a shared dual relational space for interaction enhancement under sparse topologies. Within this dual space, we perform attention-based dependency enhancement in both views, so that the structural view captures explicit topological dependencies among hyperedges, while the attribute view uncovers latent semantic correlations beyond sparse incidence relations. The resulting representations from the two views are then adaptively fused, and collaborative contrastive learning is further performed at both the node and hyperedge levels to enforce multi-granularity semantic consistency. Experiments on eight public datasets demonstrate that DDEC consistently outperforms competitive baselines, validating its effectiveness and robustness. Full article

Mandibular angle fractures pose a significant clinical challenge in maxillofacial surgery, and conventional fixation systems often show merely adequate biomechanical performance. This study presents a new mini-plate geometric configuration and outlines its rigorous verification and a preliminary validation procedure. The proposed ‘U’-shaped grade 4 titanium mini-plate with self-tapping screws was developed specifically for the stable fixation of mandibular angle fractures. A three-dimensional mandible model incorporating an angular fracture gap exceeding 1 mm was constructed and analyzed using SolidWorks. Finite Element Analysis (FEA) was employed as a verification tool to evaluate stress, strain, and displacement distributions in the mandibular ramus, plate, and screws under bilateral masticatory muscle loading, with material integrity assessed against yield-strength thresholds using von Mises’ stress theory. Rapid and functional prototypes were subsequently fabricated to physically validate the proposed mini-plate. The maximum stress across the entire model was 446.8 MPa, localized at the middle lower screw, while the maximum stress at the designed plate was 110 MPa, which remains well within the safe limits and is approximately 60.7% lower than the reported maximum stress values for conventional fixation systems. The new mini-plate exhibited robust biomechanical performance, offering a more favorable mechanical environment conducive to bone healing. Full article

Long-term energy system planning depends on projections of future wind turbine characteristics, yet existing approaches rely on either costly expert elicitation or deterministic trend extrapolation without formal uncertainty quantification. We present a Bayesian logistic framework that models the temporal evolution of hub height, rotor diameter, and specific power as physically constrained growth and decay processes, producing full posterior predictive distributions via Markov Chain Monte Carlo sampling. The framework is validated across three major onshore wind markets: Austria (534 turbines, 2000–2025), Germany (31,202 turbines, 1988–2026), and the United States (71,457 turbines, 1986–2025); spanning different market structures, regulatory environments, and data availability. Systematic benchmarking against linear, polynomial, and maximum-likelihood alternatives demonstrates superior hindcast performance, particularly for long-range projections where physical saturation constraints become relevant. Prior sensitivity analysis reveals that posteriors are robust for data-rich regions but honestly reflect prior influence for small datasets, identifying where expert knowledge is essential. We extend the framework to climate-aware energy yield estimation by propagating turbine posteriors through synthetic power curves and site-specific wind resource projections under SSP2-4.5 and SSP5-8.5, decomposing the total uncertainty into technology and climate components. When climate uncertainty is measured by scenario spread alone, technology uncertainty dominates. However, accounting for the full inter-model spread across 13 CMIP6 global climate models reveals that climate uncertainty becomes substantial (14–56%) and region-dependent, underscoring that both sources require explicit quantification. The open-source pipeline is designed for direct adoption in energy system planning workflows. Full article

Air entrainment in self-compacting concrete (SCC) is governed by coupled interactions between chemical admixtures, empirical workability behaviour, aggregate-skeleton geometry and early air-bubble stability. In highly flowable mixtures, the hardened air-void system cannot be assessed reliably from total air content alone because bubble escape, redistribution and coalescence in the fresh state may change the final pore structure. This study evaluates the link between early fresh-air retention and hardened air-void characteristics in 25 SCC mixtures arranged according to a five-level Graeco-Latin square design. The analysed factors were air-entraining admixture (AEA) dosage (0.00–0.20% by mass of cement), binder type, water-to-binder ratio (0.29–0.41) and the volumetric paste-to-aggregate filling parameter φ (1.1–1.5). The aggregate skeleton was kept constant to separate paste-composition and volumetric-filling effects from aggregate grading. Fresh concrete was characterised by slump-flow diameter, T₅₀ flow time, density and air content after 5 and 15 min; these quantities were treated as empirical workability and early-retention indicators, not as direct rheological parameters. Hardened concrete was examined after 28 days according to EN 480-11 using total hardened air content A, spacing factor L, micropore content A₃₀₀ and specific surface α. The slump-flow diameter ranged from 50 to 79 cm, fresh air content after 5 min from 1.6% to 8.6%, air loss between 5 and 15 min from 0.41 to 1.12 percentage points, hardened air content from 1.20% to 8.59%, and spacing factor from 0.13 to 0.44 mm. Strong correlations were obtained between fresh and hardened air contents (A₅ vs. A: r = 0.920, R² = 0.846, p < 0.001, 95% CI for r: 0.824–0.964; A₁₅ vs. A: r = 0.922, R² = 0.849, p < 0.001, 95% CI for r: 0.828–0.965), while hardened air content was strongly and inversely related to spacing factor (A vs. L: r = −0.907, R² = 0.822, p < 0.001, 95% CI for r: −0.958 to −0.797). The recalculated ANOVA showed that statistical significance was response-dependent: w/b was significant for early air loss ΔA (F = 4.190, p = 0.040, partial η² = 0.677) and micropore content A₃₀₀ (F = 4.058, p = 0.044, partial η² = 0.670), whereas binder type showed near-threshold tendencies for fresh and hardened air contents. No single factor was statistically significant for all air-void descriptors. The SDI-based approach is therefore presented as a bounded explanatory framework, not as an externally validated prediction model. Direct durability claims, including freeze–thaw resistance, require separate experimental verification. Full article

Accurate and consistent self-localization is essential for multi-UAV aerial missions in complex dynamic environments. However, communication constraints and heterogeneous sensor reliability variations often lead to cumulative localization errors and degraded robustness in conventional fusion frameworks. To address these challenges, this paper proposes a distributed cooperative localization framework integrating deep temporal feature learning, heterogeneous multi-sensor fusion, and consistency-aware distributed state estimation. First, an LSTM-based staged fusion strategy is designed to integrate VIO, GPS, and UWB measurements for accurate single-UAV localization. Second, a Squeeze-and-Excitation LSTM Self-Attention (SE-LSTM-SA) network is developed to adaptively recalibrate heterogeneous sensor channels and enhance temporal feature extraction under dynamic sensing conditions. Finally, a consistency-aware distributed fusion mechanism based on the Labeled Multi-Bernoulli (LMB) framework is introduced to improve inter-UAV state consistency through iterative local-neighbor information exchange. Experiments conducted on the XTDrone platform demonstrate that the proposed framework achieves superior localization accuracy compared with traditional EKF and conventional LSTM-based methods. Specifically, the proposed method achieves lower RMSE, MAE, and Maximum Prediction Error (MaxPE), while significantly improving global consistency performance. Experimental results demonstrate that the proposed framework provides accurate and consistent localization performance for multi-UAV systems in complex dynamic environments. Full article