Search Results (466)

Conventional furniture design predominantly hinges on empirical expertise and subjective appraisal, absent systematic quantitative validation of users’ visual cognition. This research establishes a multimodal quantitative evaluation framework for round-back armchairs that integrates subjective weighting via AHP and objective eye tracking measurements. Four ocular physiological metrics are aggregated using the CRITIC–entropy composite weighting approach to characterize visual attention allocation. PCA distills three core perceptual dimensions, and Quantification Theory Type I constructs a mapping function linking component morphology to perceptual responses. Notable systematic divergence is identified between expert aesthetic preferences and users’ fixation patterns. Backrests govern volume perception, chair rings dominate concise shape perception, and foot stretchers determine stylistic elegance. Low-relief backrests, three-segment curved chair rings and inward horse hoof stretchers yield superior perceptual performance, whereas gooseneck front posts and connecting balusters exhibit trivial marginal optimization gains. A model-derived candidate morphological configuration, A2-B3-C1-D1-E2-F2, is identified with corresponding effect size estimation. This study provides an exploratory analytical framework and methodological reference for promoting the transition from experience-oriented to data-driven traditional furniture design. Full article

Repeated mining of shallow-buried close-distance coal seams can disturb the fractured strata remaining in the goaf of the upper coal seam. Under gully terrain, mining disturbance is coupled with surface-relief effects, which may reactivate the overburden structure and induce dynamic strata-pressure behavior. In particular, when the working face advances across gullies, the change in surface slope alters the spatial distribution of roof load, while lower-seam extraction further disturbs the fractured rock mass formed by upper-seam mining, increasing the risk of severe strata-pressure behavior and support-crushing accidents. Taking the cross-ditch mining of the 2⁻² and 3⁻¹ coal seams in Anshan Coal Mine as the research object, this study integrates field geological investigation, theoretical calculation, physical similarity simulation, and field engineering verification to analyze overburden structural evolution, key-stratum breaking characteristics, and support-load variation under gully terrain. The results show that gully landforms generate obvious nonuniform loading above the working face. During upslope advance, the roof load gradually increases from the goaf side to the solid-coal side, causing tensile stress concentration at the fixed end of the key stratum and accelerating rock-stratum failure. A cantilever rock-beam mechanical model subjected to parabolic nonuniform loading was established, and the maximum breaking interval of the key stratum was calculated as 24.09 m. With increasing gully slope angle, the load gradient intensifies, the rock-beam breaking interval decreases, and the risk of overburden instability increases. Physical similarity simulation indicates that, when the 2⁻² coal seam working face passes through the 45° steep-slope section, the fractured overburden is more likely to form a stepped rock-beam structure, accompanied by slope rotation, stepped surface subsidence, and a sharp increase in support pressure. Under the 30° gentle-slope condition, The lateral confinement effect is stronger, roof movement is more gradual, and support-pressure fluctuation is reduced. During subsequent extraction of the lower 3⁻¹ coal seam, repeated mining disturbance reactivates the overlying goaf structure, and the upper stepped rock beam and lower hinged rock beam couple to form a double composite structure. When the fracture lines of the upper and lower key strata are staggered, the instability load of the upper structure is mainly buffered by caved gangue and interburden strata. The calculated support resistance in the asynchronous breaking stage is 8248.04 kN, which agrees well with the field-measured value of 8273 kN. When the fracture lines tend to coincide and synchronous breaking occurs, the unstable load of the upper key block is transferred downward and superimposed on the structural load of the lower key block, increasing the required support resistance to 15,165.55 kN, far exceeding the rated working resistance of the ZY9200/15/29 hydraulic support. Sensitivity analysis indicates that gully slope angle is the dominant factor affecting support resistance. As the slope angle increases from 30° to 60°, the support resistance increases from 13,228.65 kN to 18,278.43 kN, and the normalized support-resistance index increases from 0.872 to 1.205. Therefore, synchronous breaking of double key strata is the main mechanical cause of sudden support-load increase and support-crushing risk during cross-ditch mining of shallow-buried close-distance coal seams. The results can provide a basis for hydraulic support selection, roof weakening, weighting-interval control, and dynamic strata-pressure prevention under similar conditions. Full article

Medical image resolution plays a crucial role in early disease detection and fine-structure observation. Super-resolution reconstruction technology can restore low-resolution images to high-resolution versions, thereby assisting physicians in making accurate diagnoses. To address challenges in medical image super-resolution reconstruction, including insufficient global information acquisition, excessive network complexity, and suboptimal loss function adaptation for medical imaging data, this paper proposes an image super-resolution reconstruction algorithm named IDCASR-MMF based on improved dilated convolution and multi-module fusion. First, multi-dilation-rate dilated convolution is introduced to expand the receptive field and integrated with a spatial attention mechanism to dynamically calibrate high-frequency features after feature extraction. Subsequently, the Squeeze-and-Excitation module is fused with dilated convolution as a channel attention mechanism to streamline the network architecture. Finally, a weighted fusion strategy combining adversarial loss and MSE loss is adopted, where the dynamic adjustment of weighting coefficients balances pixel-level structural accuracy and high-frequency detail authenticity, achieving synergistic optimization of objective precision and subjective quality for medical images. To validate the effectiveness of the proposed algorithm, IDCASR-MMF is compared with 11 state-of-the-art methods across five datasets (Set5, Set14, BSD100, Urban100, and Bone FD). Experimental results demonstrate that the proposed algorithm achieves superior PSNR and SSIM values on multiple datasets, confirming that IDCASR-MMF can effectively reconstruct high-resolution medical images from low-resolution inputs. Full article

The performance of ultra-high-performance fiber-reinforced concrete (UHPFRC) under repeated low-velocity impacts, particularly in the context of nominally fixed boundaries relevant to protective structures, remains underexplored. In practice, protective components made of UHPFRC, such as falling object barriers and vehicle parapet systems, are exposed to foreseeable repeated low-velocity impacts; however, no standardized design provisions or residual capacity assessment methods exist for such members, particularly under nominally fixed boundary conditions. This study presents an integrated experimental and numerical investigation into the progressive damage and failure mechanisms of a 50 mm thick UHPFRC plate with nominally fixed (bolted clamping) boundaries subjected to sequential low-velocity impacts. A custom drop-weight test setup was used for impact loading, while high-speed 3D digital image correlation (3D-DIC) captured the quarter-field transient kinematics, which were reconstructed back to the full field based on verified test symmetry and complemented by traditional accelerometer and strain gauge measurements. The results demonstrate a distinct progression of damage. Initial low-energy impacts (196 J/drop) caused negligible damage, highlighting the material’s tolerance. Subsequent higher-energy impacts induced a transition from flexural cracking to a combined flexural–punching shear failure mode. The model-assisted nominal secant stiffness indicator decreased by 5.3% over the repeated 0.5 m drops and fell by 50.8% after the 2.0 m drop, quantifying the transition in structural behavior. A finite element (FE) model, incorporating the concrete damaged plasticity (CDP) model with an energy-based degradation law, was developed and evaluated against the experimental data. This model replicated both the quantitative dynamic responses (with model-to-test ratios of peak acceleration, strain, and displacement between 0.86 and 1.30 across three energy levels) and the qualitative damage evolution. The model thus evaluated enabled a model-derived reconstruction of the critical impact force–time history, revealing the evolution of structural degradation toward the exhaustion of the plate’s global flexural resistance and the transition to a punching shear mechanism. Full article

The assessment of sustainable ecological carrying capacity (SECC) serves as a crucial scientific foundation for supporting high-quality urbanization, advancing ecological civilization, and achieving the strategic goals of the “Dual Carbon” initiative. However, existing assessment methods largely rely on subjective expert scoring, making them difficult to apply at the large-scale urban level; simultaneously, traditional fuzzy assessment frameworks lack effective mechanisms for representing uncertainty when dealing with objective panel data. This paper proposes a temporal-uncertainty-driven interval-valued Fermatean fuzzy set (TU-IVFFS) theoretical framework and integrates it with an improved decision-making trial and evaluation laboratory (DEMATEL), the method based on the removal effects of criteria (MEREC), and the measurement of alternatives and ranking according to compromise solution (MARCOS) approach to construct an integrated urban ecological carrying capacity assessment framework: TU-IVFF-DEMATEL-MEREC-MARCOS. Using panel data from 2021 to 2024 for 690 major Chinese cities (at the county-level-city level and above) as the sample, the analysis found that Beijing, Guangzhou, Shenzhen, Nanjing, and Chongqing ranked in the top five for SECC, while some small cities in the northeast and northwest ranked lower. Sensitivity analysis showed that the city rankings remained stable across the entire range of weight combination coefficients λ ∈ [0, 1], verifying the robustness of the proposed framework. This study provides a methodological breakthrough for the reproducible and generalizable assessment of urban ecological carrying capacity in large-scale samples. Full article

We develop a tensor-based dynamical framework for monetary flows in multi-sector, multi-agent economies and quantify the information destroyed when the monetary state is reduced to a scalar aggregate. The state is a third-order tensor encoding capital flows across sectors, agent classes, and time; deviations from equilibrium obey a tensor-indexed Langevin (multivariate Ornstein–Uhlenbeck) equation with a coupling operator and channel-specific friction rates. Using standard Lyapunov theory, we assemble a stability and convergence framework for the induced vectorized system, with a bound stated so as to remain valid for the non-normal system matrices generated by asymmetric economic coupling, and characterize the stochastically forced case in the mean-square sense. Shannon entropy, Kullback–Leibler divergence, and sector–agent mutual information measure the structural information discarded by scalar aggregation. We then study a stylized, heuristically calibrated $3\times 3$ economy subject to a shock inspired by the 2007–2009 crisis; we emphasize at the outset that the figures reported below are properties of that calibration and are not empirical estimates. In this scenario Finance absorbs an 18.9% peak capital loss while Manufacturing and Services suffer 5.8% and 3.9% secondary drops, against an aggregate contraction of only 8.6%; the Kullback–Leibler divergence of the sector–agent flow distribution recovers systematically later than the aggregate signal, a lag that is positive in 96.6% of a 1000-draw Monte Carlo ensemble, although its magnitude is calibration-dependent. Under a symmetric exit rule, a deficit-targeted stimulus restores equilibrium substantially faster than a share-weighted uniform stimulus in 100% of the ensemble while spending strictly less—its realized expenditure saturates below the uniform budget because it self-terminates as deficits close—and attains integrated disequilibrium within 18% of the exact linear-quadratic optimum at equal control effort while requiring no knowledge of the system matrix. The ordinal conclusions—aggregation masks the epicenter, structure lags the aggregate, and deficit targeting dominates uniformity—are robust across a wide neighborhood of the calibration, and identify the disaggregated state as the object that stabilization policy needs and that scalar aggregation destroys. Full article

In response to the increasingly complex secondary system of intelligent substations and the limitations of traditional evaluation methods such as data silos and single indicators, it is urgent to build a real-time high-precision status evaluation system. This article proposes a state evaluation method for the secondary system of intelligent substations based on digital twins and the combination weighting method. Firstly, a four-layer digital twin architecture consisting of physical entities, data interaction, virtual twins, and service applications is constructed to achieve precise mapping and real-time interaction of multi-source heterogeneous data in the secondary system. A comprehensive evaluation index system covering the operation status and information quality of key equipment in the secondary system of intelligent substations is built from multiple dimensions such as health status, information transmission, and environmental conditions. Next, a combined weighting evaluation model is established that integrates the subjective weights of the Analytic Hierarchy Process and the objective weights of the coefficient of variation method, and the principle of minimizing the sum of squares of subjective and objective deviations is introduced to achieve adaptive optimization of weight configuration. Finally, simulation analysis is conducted on the digital twin platform of the 220 kV intelligent substation, and the effectiveness and robustness of the proposed model are verified through multi-state evaluation, typical fault case verification, and ablation and sensitivity analysis. The results show that compared with the mainstream AHP entropy weight method, this method has a maximum deviation of 15.3% in evaluation indicators, a state evaluation score of 97.3164, a full process calculation time of about 2.6138 s, and communication delay that meets the requirements of the IEC 61850 standard. It can effectively improve the real-time accuracy of secondary system state perception and provide technical support for on-site operation and maintenance of intelligent substations. Full article

Sustainable olive production increasingly depends on innovative mechanical pruning systems that improve field efficiency while preserving canopy architecture and supporting long-term orchard and soil sustainability. This study evaluated the field performance of three mechanical pruning operations—under-canopy skirting, topping, and lateral hedging—conducted using the specific pruning machine assigned for each operation at four forward speeds (1.0, 1.5, 2.0, and 2.5 km h⁻¹) in intensive Arbequina and Arbosana olive orchards under Al-Jouf conditions, Saudi Arabia. Engineering performance was assessed through machine productivity, effective working time, pruning quality, and energy consumption, together with operational cost and vegetative response indicators, including severe cut ratio, cut surface quality, and canopy structural uniformity. These indicators were integrated into a novel Integrated Sustainable Pruning Performance Index (ISPPI) to provide a comprehensive evaluation of pruning machines’ performance. Forward speed significantly affected all evaluated variables. Increasing forward speed improved machine productivity while reducing energy consumption and operational cost; however, further increases in forward speed slightly reduced pruning quality and canopy uniformity. Machinery in Arbequina plots required less energy and incurred lower operational costs than machinery in Arbosana plots under the evaluated pruning conditions, while Arbequina showed greater canopy integrity indicators than Arbosana. A forward speed of 2.0 km h⁻¹ provided the best overall balance between engineering performance, pruning quality, economic efficiency, vegetative response, and sustainable field operation. The principal contribution of this study was the development of the Integrated Sustainable Pruning Performance Index (ISPPI), which provides a practical engineering decision-support tool by integrating engineering, economic, and vegetative performance into a single dimensionless indicator. The ISPPI was developed using an equal-weighting approach for the three performance components to ensure balanced representation and transparency and avoid subjective bias in the evaluation process. The ISPPI enables orchard managers to objectively compare pruning strategies, identify optimal operating conditions, and support sustainable decision-making for mechanized precision olive orchard management. Full article

Conventional solvent-based and hot-melt road marking paints face significant challenges regarding high volatile organic compound (VOC) emissions and limited durability, necessitating the development of eco-friendly, high-performance alternatives. In this study, a waterborne acrylic road marking paint was systematically formulated and optimized using an L₁₆(4⁵) orthogonal experimental design coupled with a comprehensive weighted scoring method integrating subjective and objective (entropy) weights. Four key formulation parameters (pigment-to-binder ratio, titanium dioxide content, ground calcium carbonate content, and coalescing agent dosage) were investigated, with abrasion resistance, hiding power, luminance factor, and stain resistance as evaluation criteria. The optimized formulation was identified through range analysis of comprehensive scores and subsequently subjected to rigorous performance characterization, including retroreflectivity optimization, Taber and accelerated abrasion testing, UV-accelerated weathering, skid resistance, and VOC emissions measurement using a self-designed sealed chamber system. Benchmark comparisons against commercial waterborne and hot-melt paints demonstrated that the developed formulation achieves superior abrasion resistance, exceptional weatherability, and meaningfully lower VOC emissions. Field application on an operational highway section in Liaoning Province, China, confirmed the practical constructability and performance reliability of the optimized paint under real-world construction conditions. This research provides both theoretical guidance and practical validation for the design of sustainable, durable, and highly visible road marking materials, contributing to the advancement of environmentally responsible transportation infrastructure. Full article

Driven by global carbon neutrality targets, the low-carbon transformation of power systems necessitates rigorous carbon evaluation of grid infrastructure. However, existing assessments of overhead transmission lines often exhibit incomplete life-cycle boundaries and lack a coordinated approach to subjective and objective weight allocation. To address these gaps, this study targets overhead transmission lines and constructs a comprehensive low-carbon evaluation index system comprising 14 indicators across four life-cycle stages, namely design, construction, operation, and recycling. A hybrid evaluation model is proposed based on the combined analytic hierarchy process and entropy weighting method. The analytic hierarchy process is utilized to derive expert-based subjective weights, while the entropy weighting method extracts objective data variations from multiple samples, which are then integrated to obtain robust composite weights. An empirical analysis conducted on a 500 kV double-circuit overhead transmission line project in China validates the proposed framework. The results reveal a comprehensive evaluation score of 80.219, corresponding to a “low-carbon” grade. Moreover, the line loss rate (0.234227), operational carbon emissions (0.133978), and steel consumption per unit length (0.122381) are identified as the pivotal indicators dominating the evaluation outcome. This research provides quantitative support and practical criteria for decision-making regarding low-carbon design, green construction, operational loss reduction, and resource-oriented retirement of transmission line projects. Full article

Sensory evaluation is the reference method for assessing specialty coffee quality; however, the descriptive narratives generated by certified Q Arabica Graders remain an underutilized source of information. This study developed an integrated analytical framework combining conventional sensory evaluation with natural language processing (NLP) to characterize the evolution of specialty coffee quality during accelerated storage under different packaging systems. Green and roasted coffee stored in eight packaging configurations were subjected to accelerated storage at 40, 50, and 60 °C, and sensory evaluations were performed according to the Specialty Coffee Association protocol. Textual sensory descriptions were analyzed using descriptor frequency analysis, term frequency–inverse document frequency (TF–IDF) weighting, co-occurrence networks, topic modeling, and topic prevalence analysis. The results demonstrated that the evaluated packaging–product configurations (PPCs), together with storage temperature, influenced the sensory stability of specialty coffee under accelerated storage conditions. Vacuum packaging and multilayer laminated bags more effectively preserved desirable sensory attributes and higher cup scores, whereas elevated temperatures and coffee grinding accelerated quality deterioration, leading to the progressive replacement of freshness-related descriptors by undesirable storage-related sensory characteristics. The combined application of multiple text-mining approaches consistently revealed systematic semantic changes in sensory perception that complemented conventional cup scores and provided a more comprehensive characterization of quality evolution during storage. These findings demonstrate that integrating conventional sensory evaluation with natural language processing transforms expert sensory narratives into reproducible quantitative information, providing a reproducible analytical framework for the objective characterization and comparison of sensory changes during accelerated storage of specialty coffee. Full article

The objective of this study was to identify chitosan formulations suitable for sustainable functional integration into composite materials. To this end, the influence of solvent type (acetic acid and lactic acid) and chitosan molecular weight on film formation, rheological behavior, thermal response, thermo-optical properties, chemical structure, and piezoelectric performance was systematically investigated. Optimized casting and drying procedures produced transparent, homogeneous, and mechanically stable films suitable for comprehensive characterization. Rheological and thermo-optical analyses demonstrated that solvent selection strongly influenced polymer network formation and molecular mobility. Films prepared using acetic acid exhibited denser and stiffer polymer networks with improved dimensional stability, whereas lactic acid produced more flexible and elastic films. Thermogravimetric analysis revealed only minor differences in the intrinsic thermal stability of the investigated films, while FTIR confirmed that the solvent systems did not alter the chemical structure of chitosan. Electrical measurements carried out whilst the system was subjected to periodic mechanical excitation revealed weak but equally periodic electrical signals, which demonstrate a sensor functionality. These results demonstrate that chitosan films possess tunable structural, thermal, and potential mechanoelectrical sensor properties and highlight their potential as sustainable, functionally integrated components in composite material systems. Full article

Relying solely on NEMA phases for urban green-wave control often restricts the feasible regions of network optimization, resulting in narrow bandwidths or unsolvable models. To address this limitation, this paper proposes a mixed-integer linear programming model for regional signal coordination based on a mixed-phase release strategy that integrates NEMA dual-ring phase and split phase. By utilizing shared lanes under split phasing, the model maximizes lane resource efficiency and extends coordination benefits to left-turn traffic. Introducing 0–1 decision variables establishes a unified formulation for internal phase offsets, enabling flexible, intersection-specific release selection. To balance network efficiency and fairness, the optimization objective minimizes the weighted sum of the red-wave bandwidth-to-cycle ratio, subject to spatiotemporal and clockwise closed-loop constraints. A real-world case study in Suzhou, solved via the branch-and-bound method, demonstrates that the optimal design deploys split phase at seven intersections and NEMA phases at two. VISSIM simulations confirm that compared to the NEMA-only approach, the proposed mixed model reduces red-wave bandwidth by 49.52%, average delays by 26.36%, and stops by 17.5%. The proposed model provides a system-level signal coordination framework for improving the adaptability and reliability of urban traffic control systems. Full article

Rock drillability classification provides an important basis for drilling-parameter optimization, equipment selection, and improved mining efficiency. Existing drillability evaluation methods often rely on fixed empirical weights and rigid grade boundaries, making it difficult to capture fuzzy transitions between adjacent grades under multi-indicator geological conditions or to explain classification deviations for boundary samples. This study proposes a quantitative rock drillability classification method that integrates FDAHP-based subjective weighting, objective weighting, and a multidimensional cloud model. A 12-indicator evaluation system is first established by considering rock physicomechanical properties, rock-mass structural conditions, and drilling-response characteristics. FDAHP is then used to derive subjective weights from judgment matrices provided by five experts, while the entropy weight method, CRITIC method, and coefficient of variation method are used to obtain objective weights. These weights are combined into a subjective–objective weighting scheme and incorporated into a multidimensional cloud model to represent the fuzziness and randomness of drillability grade boundaries. For incomplete-indicator samples, the comprehensive weights are projected onto the available indicator subset and renormalized, avoiding forced imputation of missing indicators. Validation using 15 complete samples and seven incomplete-indicator samples from the Sungun copper mine shows that the proposed combined weighting method achieves an accuracy of 93.33% for complete samples and correctly classifies six of seven incomplete-indicator samples, with an accuracy of 85.71%. The cloud-model analysis of the misclassified sample indicates that it lies near an adjacent-grade boundary, providing an interpretable explanation for its classification uncertainty. These results suggest that the proposed method can provide interpretable quantitative drillability classification for the Sungun case study and may support preliminary field drillability assessment under incomplete-information conditions. Full article

Background/Objectives: Wolfram syndrome is an ultra-rare, progressive multisystem disorder in which endocrine and sensory manifestations coexist with neurological involvement. Quantitative magnetic resonance imaging (MRI) may help characterize central nervous system involvement in this condition; however, evidence derived from small imaging cohorts requires cautious interpretation. This study aimed to examine the relationships between different MRI-derived attributes and neurological symptoms in Wolfram syndrome, with the goal of identifying exploratory imaging patterns that may suggest the involvement of specific neural systems. Methods: We analyzed a Spanish cohort of 45 genetically confirmed patients with Wolfram syndrome. A homogeneous subset of 15 patients with standardized 3-Tesla multimodal MRI and adequate image quality was included in the quantitative imaging analysis. T1-weighted MRI, T2-weighted/fluid-attenuated inversion recovery (FLAIR) imaging, and diffusion tensor imaging (DTI) were processed using a standardized workflow for brain extraction, anatomical segmentation, cortical reconstruction, and quantitative feature extraction. A total of 172 MRI-derived features were examined in relation to neurological phenotypes, including dysphagia, ataxia, gait instability, and cognitive impairment. Analyses included principal component analysis, exploratory factor analysis, correlation analyses, and symptom-specific group comparisons. Given the small MRI sample size and the high feature-to-subject ratio, all analyses were considered exploratory and hypothesis-generating, and the findings should be interpreted cautiously pending validation in larger, independent cohorts. Results: Multimodal MRI-derived features showed distributed associations with neurological manifestations. The most recurrent exploratory imaging correlates involved the thalamus, lateral geniculate nucleus, cerebellum, brainstem, ventricular system, corpus callosum, posterior cortical regions, and white-matter pathways. FLAIR-derived signal heterogeneity in the thalamus and lateral geniculate nucleus appeared repeatedly across several clinical manifestations. Dysphagia was associated with a distributed pattern involving cortical thinning, thalamic and brainstem volume reduction, reduced cerebellar white-matter integrity, increased FLAIR heterogeneity, and ventricular enlargement. Ataxia and gait instability showed overlapping but partially distinct imaging profiles, whereas cognitive impairment was associated with broader cortical, subcortical, callosal, cerebellar, and ventricular alterations. Conclusions: In this exploratory pilot study, multimodal MRI-derived features showed clinically plausible associations with neurological manifestations in Wolfram syndrome. The findings support a distributed model of neurological involvement affecting cerebello-thalamo-cortical circuits, visual relay structures, brainstem pathways, and long-range white-matter connections. These results should be interpreted as exploratory MRI-derived attributes rather than as validated biomarkers, prognostic indicators, or clinically applicable imaging signatures. Confirmation in future longitudinal, multicenter studies with harmonized imaging protocols and external validation will be required. Full article