Search Results (32,252)

Bio-based alternatives to conventional rigid foams have proven to be good substitutes owing to their enhanced sustainability and competitive performance. However, because their manufacturing processes are complex and destructive testing is often impractical, this study investigates whether microstructural features can be correlated with mechanical properties in lignin-containing rigid polyurethane (PU) foams using machine learning approaches. Various types and percentages of lignin-based polyols were investigated as partial replacements for polyol, including LHO, DCA, DCA-D, LHO-O, Kraft lignin (KL), and LHO-MD, at polyol replacement levels ranging from 12.5% to 50%, together with a control formulation. Scanning electron microscopy (SEM) images and corresponding mechanical compression data were used to train a custom state-of-the-art dual-head convolutional neural network (CNN) targeting the specific prediction of density, specific compression modulus, specific yield stress, and specific compression strength. The CNN was optimized with a weighted multi-output loss function, achieving strong predictive performance with R² values ranging from 0.850 to 0.91 and correlation coefficients above 0.92, while maintaining mean absolute error percentages below ≈9%. This proves the trained network’s capability to predict and capture morphological features governing load-bearing responses. On the other hand, Grad-CAM visualization revealed that the network focused its predictions on physically meaningful microstructural regions such as cell walls and strut junctions, which confirms that the proposed network can be classified as an interpretable, non-destructive, and data-driven framework for predicting and understanding bio-based PU foams’ mechanical behavior, hence reducing the inconvenience caused by time-consuming manufacturing and destructive testing. Full article

The binary blend of poly(butylene adipate-co-terephthalate) (PBAT) and poly(lactic acid) (PLA) has emerged as the primary base material combination for biodegradable mulch films because of their favorable processability and biodegradability, offering a viable route to replace conventional polyethylene films in agricultural applications. However, the PBAT/PLA binary system suffers from thermodynamic incompatibility, limiting simultaneous achievement of mechanical, barrier, and optical properties. This study introduces poly(propylene carbonate) (PPC) as the third component and investigates its content (0–20%) on the microstructure and performance of PBAT/PLA/PPC ternary films. At PPC ≤ 10%, the system maintains an amorphous homogeneous structure, and PPC enriches the surface and improves interfacial adhesion. When the PPC content is 10%, the blend exhibited a transverse tensile strength of 43.3 MPa, an elongation at break of 338%, and a 29.8% reduction in water vapor permeability versus the neat blend. At 15% PPC, the compatibility threshold is exceeded, causing severe phase separation, a sharp drop in melt strength, and deteriorated mechanics. At 20%, phase separation induces PBAT/PLA crystallization, further enhancing barrier performance but reducing thermal stability and transparency. Differential scanning calorimetry and dynamic rheological analysis confirm the compatibility threshold, while X-ray photoelectron spectroscopy, X-ray diffraction, and scanning electron microscopy reveal abrupt changes in surface chemistry, crystal structure, and morphology. Overall, 10% PPC offers the best balanced properties. This work elucidates structure and property relationships, providing a basis for the rational formulation design of biodegradable mulch film. Further field weathering and biodegradation tests are required to validate their practical agricultural performance. Full article

The physicochemical properties of buccal films are vital for evaluating their suitability for mucosal applications. By focusing on these properties, researchers can enhance the mechanical functionality and mucoadhesion of the films. This study aimed to overcome the mechanical limitations of neat gellan gum and to produce biocomposite films with enhanced physicochemical properties and mucoadhesive properties for potential use in buccal drug delivery. Biocomposite films composed of gellan gum (GG) and pineapple stem fiber (PSF), with glycerine as a plasticizer, were prepared using the solvent casting method to develop a formulation suitable for this application. Fourier transform infrared (FTIR) spectroscopy, pH and thickness measurements, tensile test, folding endurance, swelling index, scanning electron microscope (SEM), mucoadhesion test and X-ray diffraction (XRD) analysis were conducted to determine the optimal PSF content in the GG-based biocomposite film formulation. The results indicated that the optimal formulation, GG/3PSF, was achieved with the incorporation of 3 wt% PSF relative to the GG mass. Specifically, the GG/3PSF biocomposite film exhibited a tensile strength of 17.10 ± 0.4 MPa (a 50% increase compared to neat GG), an elongation at break of 46.0 ± 2.5%, a tensile toughness of 41 ± 2.0 MPa, and an ex vivo mucoadhesive residence time of at 7.76 ± 0.51 h for GG/3PSF (compared to 3.90 ± 0.24 h for neat GG). Additionally, it maintained a moderate and optimal swelling index of 115.31 ± 2.3% after 60 min of hydration, which prevents structural instability associated with excessive swelling (such as 161.81 ± 4.7% observed in GG/7PSF), while possessing acceptable thickness (0.09 ± 0.005 mm) and neutral pH (7.0 ± 0.05). The developed buccal film is environmentally friendly due to the utilization of pineapple stem fiber, an agricultural by-product that can reduce material costs compared with synthetic fillers and shows considerable potential as a biocomposite film for buccal drug delivery applications. Full article

Background/Objectives: Elastic resistance bands are widely used in rehabilitation, injury prevention, and athletic conditioning because they are portable, inexpensive, and adaptable to multiple movement planes. However, their mechanical behavior and training dose are often insufficiently characterized. This structured narrative review aimed to synthesize current evidence on the neuromuscular mechanisms, prescription principles, and functional applications of elastic resistance bands in sports medicine and rehabilitation. Methods: PubMed, Scopus, Web of Science, and ScienceDirect were searched from inception to 31 May 2026. Peer-reviewed human studies and reviews were included when they addressed mechanical, neuromuscular, biomechanical, prescriptive, rehabilitative, injury-prevention, or performance-related aspects of elastic resistance exercise. Evidence was synthesized narratively to link mechanical configuration, neuromuscular responses, exercise prescription, and functional outcomes. Results: Elastic bands provide an ascending, position- and configuration-dependent resistance profile determined by band properties and exercise configuration. When effort and exercise configuration are controlled, elastic resistance can elicit muscle activation and strength adaptations comparable to conventional resistance, while supporting improvements in balance, functional capacity, power, sprint performance, change-of-direction ability, and selected sport-specific outcomes. Its directional versatility and capacity for gradual load adjustment support applications from early rehabilitation to return-to-sport and performance training. Nevertheless, prescription based on band color alone is inadequate, and inconsistent reporting limits reproducibility and study comparisons. Conclusions: Elastic resistance is a scalable and clinically relevant loading modality rather than an inherently low-load alternative. Evidence is more established for improvements in muscular strength and functional performance than for direct reductions in injury incidence or successful return-to-sport outcomes. Its effectiveness depends on explicit load quantification, individualized progression, appropriate exercise configuration, and transparent reporting of intervention parameters. Full article

Background/Objectives: Sleep and circadian disturbances are common in neurodevelopmental conditions, yet the developmental cortical programs linking clock-related transcriptional regulators to disease vulnerability remain unclear. Methods: Here, we integrated human developmental brain transcriptomes, weighted gene co-expression network analysis (WGCNA), human and mouse cortical single-cell atlases, prenatal immune activation transcriptomes, and ASD postmortem brain datasets to characterize the developmental architecture of BrainSpan-derived cortical programs and examine their behavior in perturbational and disease contexts. Results: In the BrainSpan frontal cortex, canonical clock-related genes followed structured but heterogeneous developmental trajectories rather than behaving as a coordinated oscillator-like unit. WGCNA identified a postnatal-rising BrainSpan-derived primary developmental module that was strongly associated with developmental age and enriched for synaptic signaling, neurotransmitter transport, ion transport, membrane excitability, cellular respiration, metabolic regulation, and proteostatic processes. Network analysis placed multiple canonical clock-related and clock-regulatory genes, including NPAS2, BHLHE40, BHLHE41, PER family members, RORA, NR1D1/2, and CLOCK, within a broader neuronal and homeostatic co-expression architecture, although their module-membership strengths varied substantially. Projection onto a human cortical developmental single-cell atlas revealed a non-uniform distribution of the corrected BrainSpan-derived developmental signature, with relatively higher scores in excitatory and inhibitory neuronal populations and lower scores in neuroblast and radial glial populations. A mouse cortical developmental single-cell atlas provided a comparative view of the stage- and cell-type-dependent expression of clock-related genes and the transferred developmental signature during corticogenesis. In a Poly(I:C)-based maternal immune activation dataset, litter-aware reanalysis identified stage-resolved genome-wide transcriptional responses following E12.5 exposure. However, neither the aggregate core clock-gene expression score nor the independently transferred BrainSpan-derived developmental signature showed a significant overall treatment effect or collection-stage-by-treatment interaction, indicating that this bulk dataset provides a perturbational context rather than evidence for selective disruption of the developmental program. An exploratory region-stratified analysis of GSE28521 yielded near-null effects for the BrainSpan-derived developmental signature, with confidence intervals crossing zero across all examined regions. These ASD postmortem findings were therefore treated as a boundary assessment rather than evidence of ASD-specific convergence. Conclusions: Collectively, these findings position clock-related genes as components of a developmentally regulated cortical maturation program enriched for neuronal signaling, synaptic maturation, metabolic regulation, and stress-response processes. Full article

Despite being usually discarded, agro-industrial by-products are rich in bioactive and nutritional compounds and can be redirected into new foods or food packaging. This study evaluated the nutritional composition of cardoon leaves (Cynara cardunculus L.), an agro-industrial by-product, and assessed the impact of the drying process on those characteristics. Furthermore, extracts of the dried leaves and dried leaves combined with lemon peel were incorporated into whey protein-based films at concentrations of 0.5%, 1.0%, and 2.0% (w/v). Their physical, barrier, mechanical, and thermal properties were also analysed. When compared on a dry weight (DW) basis, the dry leaves maintained a stable nutritional profile with no significant degradation of key components, presenting with high carbohydrates (15.4 ± 1.1 g/100 g), moderate protein (21.2 ± 0.4 g/100 g), and low fat (2.0 ± 0.1 g/100 g). The leaves were also a good source of dietary fibres (43.9 ± 1.8 g/100 g) and minerals (13.7 ± 0.2 g/100 g of ash). Incorporating the extracts altered the films’ physicochemical properties, reducing their water vapour permeability up to 4.05 ± 0.26 10⁻¹⁰ g/s.m.Pa, while their tensile strength decreased from 0.34 ± 0.06 to 0.23 ± 0.01 MPa depending on the formulation, and their elongation at break decreased by up to 6.58 ± 0.70%. In contrast, Young’s modulus increased by up to 0.11 ± 0.03 MPa, indicating higher rigidity. This behaviour may be attributed to the interactions between the phenolic compounds and the whey protein matrix, which restricted polymer chain mobility and increased film rigidity while reducing matrix cohesion and flexibility. The results demonstrate that while the extracts enhanced the barrier properties of the films, they reduced the mechanical properties. Overall, the results suggest that cardoon by-products have potential applications in active food packaging, contributing to the development of bio-based materials within a circular economy framework. Full article

The increasing demand for sustainable structural materials in the construction industry has intensified the need to develop high-performance and environmentally efficient reinforced concrete systems. In this context, the incorporation of functional material-enhanced concrete systems, including raw lightweight aggregates such as perlite, offers a promising pathway for reducing environmental impact while maintaining adequate structural performance. This study experimentally investigates the flexural behavior of reinforced concrete (RC) beams incorporating raw perlite aggregates within a functional material-enhanced structural framework. A total of four RC beams with identical geometry and reinforcement details were produced, including perlite aggregate beams (P25 and P40) and conventional aggregate beams (C25 and C40), corresponding to compressive strength classes of 25 MPa and 40 MPa. All specimens were tested under monotonic flexural loading conditions. The structural response was evaluated in terms of load–displacement behavior, stiffness degradation, ductility, energy dissipation capacity, moment–curvature response, and failure modes. The results indicate that perlite aggregate beams exhibit reduced stiffness and energy dissipation capacity compared to conventional counterparts at comparable mixture-average compressive-strength levels. However, the high-strength perlite beam (P40) demonstrated comparable flexural capacity and ductility to the normal-strength conventional beam (C25), highlighting its potential for sustainable structural applications. Furthermore, a building-scale environmental assessment based on a representative three-story reinforced concrete structure demonstrates that the use of raw perlite aggregates significantly reduces energy consumption, CO₂-equivalent emissions, and water usage. From a functional materials perspective, the findings provide a basis for the future development of multifunctional load-bearing concrete systems, where lightweight aggregate substrates can be combined with protective or performance-enhancing coating technologies to achieve improved durability, environmental resistance, and structural efficiency. This integration could further enhance durability and long-term structural performance in load-bearing applications. Full article

This work describes the formation of electrically charged nanobubbles and collective electrodynamical ordering in liquid water based upon the framework of the quantum electrodynamical theories of Del Giudice, Preparata, Vitiello and their co-workers. Nanobubbles with experimentally observed negative zeta potentials are predicted to generate interfacial electric fields on the order of 10⁵–10⁶ V m⁻¹, comparable to field strengths previously associated with collective vibrational coupling in electrically stressed water. The model addresses magnetic stabilization of the electrically induced vibronically coupled interfacial state, while the observed changes in nanobubble size and number are discussed within the broader framework, including a hypothesized preconditioning effect of the dynamically varying magnetic field on nanobubble formation. Under these conditions, regions of enhanced collective coupling of vibronic modes around a nanobubble with characteristic thicknesses of approximately 9.6–52.5 nm become physically plausible. Furthermore, a phenomenological Landau-type free-energy model is used to investigate the influence of external magnetic fields on the process. We suggest that magnetic fields primarily couple to the low-energy protonic and vibronic modes within this shell. These theoretical predictions are qualitatively consistent with recent experimental observations showing stronger negative zeta potentials, and higher nanobubble concentrations under the influence of magnetic fields, together with smaller characteristic nanobubble radii under an alternating field configuration. Our results support the interpretation that magnetic fields stabilize electrically induced mesoscopic coupling of vibronic modes that emerge transiently during cavitation-driven nanobubble formation. Full article

The large-scale integration of renewable energy causes grid strength to vary over a wide range, exposing grid-following (GFL) inverters to both mid- and high-frequency resonance and subsynchronous oscillation (SSO). Conventional fixed-parameter designs cannot simultaneously maintain stability and dynamic performance because the phase-locked loop (PLL) and grid-voltage feedforward (GVF) dominate different frequency bands. This paper therefore proposes a backpropagation-neural-network (BPNN)-based adaptive parameter control strategy with frequency-band-coordinated regulation. First, a q-axis small-signal output-admittance model incorporating the current loop, digital delay, PLL, and GVF is established. The model reveals that the GVF coefficient primarily shapes mid- and high-frequency admittance under strong and moderately weak grids, whereas the PLL bandwidth becomes the dominant factor in low-frequency and subsynchronous stability under ultra-weak grids. Based on this mechanism, a BPNN is constructed with the grid short-circuit ratio (SCR) as the input and the GVF coefficient and PLL bandwidth as the outputs. Training targets are generated offline using parameter sweeps and performance screening based on current total harmonic distortion, Point of Common Coupling (PCC) voltage error, and settling time. During operation, the GVF coefficient is adjusted first, and the PLL bandwidth is reduced only when the grid becomes ultra-weak. Simulation results over $\mathrm{SCR}=1.25$–10 demonstrate that the proposed strategy preserves stable operation while providing better transient and harmonic performance than fixed-parameter and single-parameter tuning schemes in the cases studied. Full article

Electrified mobility regulations and lifecycle emissions targets have increased the demand for lightweight structural materials in vehicle architectures. Bioinspired composite materials offer microstructural configurations that alter conventional trade-offs among specific stiffness, crash energy absorption, and manufacturing energy requirements. This review evaluates the translation of biological structural archetypes including nacre, bamboo, cortical bone, and lotus leaves into load-bearing and functional automotive components. Quantitative benchmarks of continuous natural-fiber laminates, bio-cellular lattices, and mycelium-based acoustic cores are compared against high-strength steel and aluminum alloys. Key mechanical and functional metrics, including specific energy absorption (ranging from 35 to 48 kJ kg⁻¹ for bioinspired crash structures), dynamic loss factors, and Cassie-Baxter superhydrophobic surface stability, are evaluated alongside high-throughput manufacturing routes such as high-pressure resin transfer molding (HP-RTM) and additive manufacturing. Methodological parameters for ISO 14040/14044-compliant Life Cycle Assessment (LCA) are synthesized, emphasizing component-level functional units over gravimetric mass equivalence. Furthermore, operational boundaries, specifically hygrothermal interfacial degradation, matrix glass transitions (T_g < 120 °C), and multi-axial loading sensitivity, are systematically outlined to define design limits for automotive deployment. Full article

The physical environment of a neighborhood, such as its road networks and land-use distribution, appears to be closely related to its ambient population density, but this relationship is difficult to measure quantitatively. A previous study based on Japanese neighborhoods addressed this challenge by developing an XGBoost baseline model to estimate Average Hourly Ambient Population Density (AHAPD) at a neighborhood scale using 16 physical environment-related features, achieving 75.9% accuracy. This study evaluates that baseline model by comparing it with human evaluators and multimodal AI models in a spatial reasoning task based on AHAPD estimation. A questionnaire-based benchmark with 29 sets of questions was developed to compare the three evaluator types across accuracy, reasoning, and confidence. The online questionnaire was distributed from 8 June–22 September 2025. In total, 100 responses were analyzed, comprising 94 human evaluators, 5 free-tier versions of multimodal AI models, and 1 output from the baseline model. The baseline model scored 16 points, compared with a mean of 15.1 points for the human evaluators and 14.2 points for the tested AI models. Its performance was also comparable to human evaluators with domain expertise and contextual familiarity, who averaged 16.0 points. The comparison further revealed differences in feature importance, confidence patterns, and characteristic errors among the evaluator types. Selected discrepancy cases highlighted possible strengths and weaknesses of each approach. The main contribution of this study is a questionnaire-based diagnostic benchmark for comparing evaluator types with different characteristics in spatial reasoning tasks. Full article

The lightweight design of an aircraft engine pylon requires an efficient structural layout capable of accommodating multiple load cases. An integrated lightweight design framework combining multi-load topology optimization and size optimization is developed. The three-field SIMP method with a weighted-compliance objective is employed to identify the dominant load-transfer paths under multiple representative load cases. Based on the resulting topology, a parametric model is constructed and optimized to reduce structural mass subject to strength and manufacturability constraints. The optimized member dimensions are subsequently used to reconstruct an engineering-manufacturable pylon configuration, whose structural performance is evaluated through finite element analysis. The results demonstrate that the multi-load topology optimization produces a stable primary load-bearing framework, while the subsequent size optimization reduces the structural mass from 238 kg to 156 kg, a reduction of 82 kg. The proposed framework provides a practical route for the lightweight design of aircraft engine pylons and can serve as a reference for other complex aerospace load-bearing structures. Full article

Reliable bonding between a cement-stabilized base and an asphalt surface course is essential to the integrity of semi-rigid base asphalt pavements. Accordingly, this study evaluated the environmental susceptibility of complete base–prime–seal–surface interlayer systems by introducing adverse conditions at selected construction contact planes and then measuring the peak shear response of the completed system. Four representative seal systems were investigated: a non-tracking emulsified asphalt seal, a fine-chip seal, a hot asphalt chip seal, and a slurry seal. Five specimens were initially prepared for each condition. Field-constructed 150 mm cement-stabilized base cores were combined with a 40 mm AC-13 layer and tested in direct shear at 25 °C. The investigated variables included clean, moist, and soil-contaminated interface conditions, grade 0 automotive diesel contamination, prime-coat omission, pre-placement substrate temperatures from −5 to 35 °C, and 0–10 freeze–thaw cycles. The results showed that diesel contamination at the seal–surface contact reduced strength retention to 73.6–83.6%. Meanwhile, prime-coat omission produced pronounced losses in the fine-chip and slurry systems, whereas the hot asphalt chip seal remained comparatively stable. The temperature response was material-specific: the fine-chip seal showed no significant overall temperature effect (p = 0.1019), while the hot asphalt chip seal reached the higher statistical category only at 25–35 °C. In contrast, the effects of short-term freeze–thaw cycling were relatively limited; after 10 freeze–thaw cycles, strength retention remained at 93.8–98.2%. Overall, the results support material-specific control of surface cleanliness, prime-coat application, and construction temperature. Full article

Basalt-fiber textile-reinforced engineered cementitious composite (BTR-ECC) combines favorable durability, cost-effectiveness, and mechanics, making it a viable option for structural retrofitting. Although axial behavior is well-documented, off-axis loading zones often constitute structural weak points. To address this gap, this study experimentally and theoretically examines the mechanical responses and failure mechanisms of BTR-ECC at off-axis tensile angles of 0°, 15°, 30°, and 45°. The results demonstrate that: (1) The tensile stress–strain curves exhibit a distinct trilinear characteristic (linear elastic, strain-hardening, and fracture), featuring densely distributed microcracks confined to 30–50 μm. Dominant failure modes include textile rupture, interfacial debonding and pull-out, and PVA fiber bridging. (2) With increasing angles, tensile strength at 0°, 15°, 30°, and 45° surpasses plain ECC by 84.8%, 73.6%, 52.9%, and 54.0%, respectively, confirming effective synergistic load transfer between the basalt-fiber textile and the matrix. Despite progressive strength degradation, the strain energy density remains relatively stable across all orientations, indicating robust energy dissipation capacity. (3) A phenomenological constitutive model based on the tangent modulus approach is established to describe the off-axis tensile response. The model shows good agreement with the experimental data and may serve as a reference for the analysis of BTR-ECC structures within the calibrated range of the four tested angles. Full article

Mirror segmentation aims to identify mirror pixels from a single RGB image, yet remains challenging because mirrors provide weak intrinsic texture cues and their appearance is dominated by scene-dependent reflections under varying illumination and viewpoints. While recent models improve performance by leveraging contextual contrast, symmetry priors, frequency/spectral cues, or additional modalities (e.g., depth), many cross-cue or symmetry-aware designs still rely on direct spatial-domain fusion, such as concatenation, addition, or attention. Such fusion can amplify reflection-induced high-frequency variations and lead to leakage, shape distortion, and unstable boundaries. In this paper, we propose a symmetry-aware mirror segmentation framework that stabilizes cross-branch interaction via a frequency-domain cross-conditioned fusion mechanism. We build a dual-path Siamese encoder using the original image and its horizontally flipped counterpart, and introduce Heat Conduction Operator-based Cross Fusion (HCOCF), which performs heat-conduction-inspired spectral attenuation in the DCT domain. Unlike conventional fusion, HCOCF generates a nonnegative cross-conditioned attenuation coefficient map from the opposite branch and applies it to the DCT coefficient grid of the target branch. This produces a DCT-domain attenuation mask that controls the spectral refinement strength of each target feature stream, enabling global context propagation while suppressing unstable reflection-induced high-frequency responses without aggressive direct feature mixing. For multi-scale decoding, we adapt the cross-scale decoder of the baseline symmetry-aware architecture by replacing simple addition with conditional feature aggregation, which refines the HCOCF-enhanced features and improves boundary recovery. Extensive experiments on MSD, PMD, and RGBD-Mirror demonstrate competitive performance against representative supervised mirror segmentation methods. In particular, our RGB-only model achieves 88.47% IoU on MSD and 73.72% IoU on PMD, and remains competitive on RGBD-Mirror without using depth input. Full article