Search Results (12,777)

University orientation programmes are a primary mechanism through which new students become familiar with campus facilities, academic spaces, and institutional procedures. However, many orientation activities are delivered as single in-person sessions, limiting opportunities for students to revisit spatial and procedural information after the event. To help address this constraint, a digital twin-inspired metaverse orientation application, the Digital Twin Metaverse Orientation (DTMO), was designed in Unity and hosted on Spatial.io as a spatially faithful virtual replica of a faculty environment. An exploratory pilot evaluation was conducted with 30 university students from multiple faculties after a facilitator-guided orientation session. The System Usability Scale (SUS), Net Promoter Score (NPS), and two open-ended questions were used to examine perceived usability, recommendation intention, and the reasons underpinning recommendation decisions. The application obtained a mean SUS score of 86.83, corresponding to an excellent perceived-usability rating, and an NPS of 53.33, indicating positive immediate recommendation intention. Qualitative responses suggested that participants valued the DTMO for engagement, accessibility, ease of navigation, and support for spatial familiarisation, while some participants emphasised that it should complement rather than replace physical orientation. These pilot findings indicate promising user reception in a small, guided-session sample, but they do not establish orientation effectiveness, learning transfer, wayfinding performance, retention, belonging, institutional integration, or sustained use. Further research with broader samples and outcome-based measures is therefore needed. Full article

The transient heat-transfer behavior of hybrid natural-fiber-reinforced epoxy composites containing 0–5 wt% conch shell filler and 20–35 wt% combined banana–bagasse fiber reinforcement was evaluated using active infrared thermography. A standardized protocol comprising 30 s of convective heating with 100 °C hot air followed by 60 s of natural cooling was applied to seven composite configurations tested in triplicate. The transient response was analyzed in three phases: active heating (0–30 s), thermal lag (30–57 s), and natural cooling (57–90 s). Maximum temperature ($T_{max}$), heating rate ($R_h$), cooling rate ($R_c$), and a thermal retention ratio ($TR$) were extracted and statistically validated by one-way ANOVA with Bonferroni correction. For specimens exhibiting zero within-group variance at the camera display resolution, significance was confirmed using exact permutation tests. Filler incorporation (3–5 wt%) was the dominant factor governing peak-temperature reduction; F5B15S10 (5 wt% filler, 25 wt% total fiber) achieved the lowest $T_{max}$ (33.80 °C, 4.57 °C below neat epoxy). Cooling efficiency was primarily governed by fiber content; F3B15S20 (3 wt% filler, 35 wt% total fiber) demonstrated the most efficient heat dissipation ($TR=0.721$). These findings demonstrate that heating resistance and cooling efficiency are governed by partially independent mechanisms, enabling tailored material design. This study indicates that the proposed transient thermographic protocol provides a valuable reference to thermal management design of hybrid biocomposites in automotive interior and building envelope applications. Full article

Background: Buddleja globosa Hope (matico) is a Chilean medicinal plant traditionally used in Mapuche and Aymara ethnomedicine. However, no systematic synthesis of its phytochemical composition and pharmacological evidence has been previously reported. Methods: A PRISMA 2020-compliant systematic review was conducted using Google Scholar, PubMed, EBSCOhost, and Springer Nature databases from inception to March 2026. Studies reporting phytochemical characterization and/or biological activities of B. globosa were included. Methodological quality was assessed using an adapted five-criterion tool for non-clinical studies. The protocol was registered in OSF. Results: Fourteen studies (1989–2026), mainly from Chilean research groups, identified 27 bioactive compounds across leaves, roots, and flowers. These included phenylethanoid glycosides (e.g., verbascoside/acteoside, echinacoside, forsitoside B, and linarin), flavonoids (luteolin 7-O-glucoside, apigenin 7-O-glucoside, myricetin, catechin, and epicatechin), pentacyclic triterpenes (α/β-amyrins and β-sitosterol), iridoid glycosides, and clerodane diterpenoids (buddledines A–C), as well as four newly reported phenylethanoids. Antioxidant activity was the most frequently evaluated endpoint (11/14 studies), mainly mediated through hydrogen atom transfer and single-electron transfer mechanisms linked to caffeoyl and flavonoid structures. Anti-inflammatory effects (five studies) involved COX and 5-LOX inhibition and reduced PGE₂ production in LPS-stimulated macrophages. Additional reported activities included antihepatotoxic, antiplatelet, wound-healing, antibacterial, and antifungal effects. Conclusions:B. globosa exhibits a coherent phytochemical profile supporting strong preclinical antioxidant and anti-inflammatory activities. The main limitation for clinical translation is the low oral bioavailability of phenylethanoid glycosides. Nanoformulation strategies, investigation of colonic metabolites, and topical delivery systems represent promising approaches to bridge the preclinical-to-clinical gap. Full article

Background: Human breast milk (HBM), as the initial food for humans, is quite essential for infant development and also for health throughout the lifespan. Exosomes are bioactive components in HBM, yet their nutritional role remains poorly recognized. Objectives: This study investigates how HBM exosomes change with lactation and their potential role in infant growth and development. Methods: HBM samples were obtained at 2 and 6 months postpartum from a well-established birth cohort. Purified exosomes were detected using transcriptomic, lipidomic, and proteomic approaches. Then, multi-omics data were analyzed to compare differentially expressed miRNAs, lipids, and proteins along with different lactation periods and their association with the infant growth process. Results: Compared with the 2-month postpartum group, the expression levels of miR-214-3p, miR-199a-5p, miR-126-3p, miR-127-5p, miR-144-3p, and miR-4787-5p were down-regulated in the 6-month postpartum group. In addition, 190 lipids and 269 proteins were up-regulated in the 6-month postpartum group, whereas 15 lipids and 244 proteins were down-regulated. Enrichment analysis revealed that the predicted target genes of differentially expressed miRNAs were primarily involved in cell communication and axon guidance. In parallel, the differentially expressed proteins were enriched in biosynthesis of unsaturated fatty acids and fatty acid metabolism pathway, implying a potential role in adipogenesis and neurodevelopment. Conclusions: This study reveals that the cargo contents of HBM exosomes change with the lactation period and may adapt to the needs of infant growth and development, particularly adipogenesis and neurodevelopment. HBM exosomes may play an important role in transferring genetic information from mothers to infants and be related to infants’ development. The underlying mechanisms warrant further investigation and validation. Full article

Fluidized solidified soil piles combine slurry-like constructability with post-hardening strength development and provide a potential approach for soft ground improvement. This study investigated the vertical bearing behavior and load-transfer mechanism of fluidized solidified soil piles in layered soft ground through field single-pile vertical static load tests, core drilling, and three-dimensional numerical simulation. The field tests and core drilling provided experimental evidence for evaluating load–settlement behavior, pile integrity, and material strength, while the internal load-transfer mechanism and geometric parameters were mainly interpreted using the numerical model. The field results showed that the Q-s curves exhibited staged deformation characteristics, with relatively stable settlement development during the main loading stage and more pronounced nonlinearity under high load levels. The ultimate vertical bearing capacities of the 10 m and 20 m test piles were 1050 kN and 950 kN, respectively. Core drilling indicated that the two pile groups had similar material strength, suggesting that the bearing capacity difference was mainly associated with the pile toe bearing stratum rather than pile material strength. After comparison with the measured Q-s curves, the numerical analysis showed that the 20 m pile mobilized a longer shaft resistance range and a higher shaft resistance contribution, but its pile toe extended into the lower mucky soil layer, resulting in reduced pile toe resistance. Parametric analysis indicated that increasing pile length does not necessarily improve bearing performance when the pile toe bearing stratum is unfavorable, whereas increasing pile diameter more directly reduces pile head settlement under the same pile toe bearing condition. These findings highlight the need to consider both shaft resistance mobilization and pile toe bearing stratum in the design of fluidized solidified soil piles in layered soft ground. Full article

Metal oxide nanoparticles serve as crucial drivers in modern biomedical, catalytic, environmental, and energy technologies due to their high surface-to-volume ratios and quantum confinement properties. Traditional chemical and physical synthesis methods remain limited by significant energy footprints, high costs, and the use of hazardous reagents. To address these challenges, bioinspired (“green”) synthesis has emerged as a sustainable paradigm that employs biological systems as nature nanofactories. This critical review provides a provides a comprehensive and systematic analysis of the green synthesis of major metal oxide systems (ZnO, TiO₂, Fe₃O₄/Fe₂O₃, CuO, Co₃O₄, CeO_2, and MnO₂) using diverse biological templates, including plant extracts, bacteria, fungi, algae, and biopolymers. Moving beyond simple descriptive summaries, we critically evaluate the foundational electron-transfer and nucleation mechanism, systematically correlate processing parameters with physical outcomes, and offer a rigorous comparative analysis across different biological kingdoms. Finally, we directly address the underlying challenges facing the field: reproducibility bottlenecks, scalability limits, environmental safety variations, and regulatory hurdles necessary for industrial translation. Full article

Urban heat stress is intensifying under climate change, particularly in outdoor public spaces where conventional mechanical cooling is impractical. This study develops a climate-driven, system-level numerical framework to evaluate the pre-deployment feasibility of modular, solar-powered spray cooling canopies across 110 cities in Türkiye. Hourly Typical Meteorological Year (TMYx) weather files, representing a single typical year constructed from 2009 to 2023 source data, are used to estimate photovoltaic (PV) energy yield, electrical load, feasible misting duration, water demand, and PV-to-load autonomy under summer daytime conditions. The misting operation is governed by a rule-based adaptive control strategy based on air temperature, relative humidity, and plane-of-array irradiance. To support transferable comparison, the cities are classified into six summer climate-archetype zones using k-means clustering of standardized climate variables, including temperature, humidity, irradiance, wind speed, and summer precipitation. Results show that evaporative cooling feasibility is governed primarily by humidity rather than temperature alone. Hot–Dry Inland cities exhibit the longest mean misting duration (501.90 h) and highest water demand (30,152 L per module), but the lowest PV-to-load autonomy ratio (1.55) because of high pump-driven electrical demand. In contrast, Humid Black Sea cities show minimal misting duration (11.43 h) and water use (465 L per module), but the highest autonomy ratio (39.68) due to very limited system activation. Thus, high autonomy does not necessarily indicate high cooling usefulness. The proposed framework provides a reproducible screening tool for identifying where PV-powered spray cooling canopies are climatically suitable, where water and PV sizing become limiting, and where alternative outdoor heat-mitigation strategies may be more appropriate. Full article

Objectives: Skeletal muscle architecture (SMA) defines the mechanical limits of force production. However, its associations with force–time strategy under externally loaded conditions have received little research attention. This exploratory study examined associations between vastus lateralis (VL) and lateral gastrocnemius (LG) architecture and force–time strategy, jump-height retention, and stretch–shortening cycle (SSC) transfer-efficiency in collegiate basketball players. Methods: Seventeen collegiate male basketball players completed B-mode ultrasonographic assessment of VL and LG architecture, including muscle thickness, pennation angle (PA), and fascicle length. Athletes performed the squat jump (SJ), loaded squat jump (LSJ), countermovement jump (CMJ), and loaded countermovement jump (LCMJ) on force platforms, with a 20 kg external load applied for loaded conditions. Loaded retention, defined as the percentage of jump height preserved under load, was proposed as a unified construct. Pearson’s correlations were calculated, with Benjamini–Hochberg false discovery rate (FDR) corrections applied within predefined functional groups and pooled across morphology-sensitive correlations. Results: LG PA showed a large negative association with LCMJ rate of force development (r = −0.68 [−0.87, −0.30]) and a large positive association with LCMJ time to peak force (r = 0.68 [0.29, 0.87]), both surviving within-group FDR correction. VL PA was associated with eccentric acceleration time and concentric time across jump conditions (r = 0.52 to 0.61), interpreted as exploratory. Transfer-efficiency indices showed no significant associations with SMA, except for the LCMJ/LSJ concentric time ratio, which showed a moderate negative association with LG PA (r = −0.49 [−0.79, −0.01]). Conclusions: Resting muscle architecture was associated with the temporal and rate characteristics of force expression under load, rather than with the gross preservation of jump height. Integrating architectural assessment with loaded force–time profiling warrants further investigation as a means of characterizing individual force-development strategies. Full article

Adversarial camouflage has attracted growing research attention owing to its ability to execute multi-view, persistent attacks in real physical environments, outperforming conventional single-view adversarial patches. However, most existing methods are confined to non-targeted attacks, which induce arbitrary incorrect detection results without specifying target categories. This ambiguity weakens attack destructiveness and stealthiness, posing limitations for security evaluation of real-world vision systems. To address this gap, we present TACT, an approach built upon the full-coverage physical camouflage pipeline. By replacing the original category supervision with a predefined target class, TACT redirects the optimization gradient to guide 3D texture toward the target category features. Such a scheme only employs the inherent feature alignment mechanism of off-the-shelf object detectors, without redesigning network modules, defining novel loss functions, or modifying the rendering pipeline. Extensive experiments across digital and physical domains validate its effectiveness: on seven mainstream general-purpose object detectors, TACT-person achieves an average targeted attack success rate of 51.91%, and delivers cross-architecture and cross-version transferability. In physical tests, TACT-bird reduces mAP50-95 by 59.87% on YOLOv8, yet a TCER–TASR gap suggests that the physical pipeline acts as a low-pass filter: coarse-grained target classes transfer robustly while fine-grained ones suffer feature collapse. These results confirm the viability of native supervision redirection and reveal an empirical pattern: coarse-grained target classes transfer more robustly through the physical pipeline than fine-grained ones, suggesting that target class feature granularity consistently influences physical-domain attack effectiveness. Full article

Cardiovascular disease (CVD) is the leading cause of morbidity and mortality worldwide, accounting for a substantial proportion of global deaths. Increasing evidence indicates that cardiovascular susceptibility is shaped during fetal development, where the intrauterine environment plays a critical role. Maternal–fetal crosstalk, mediated largely through placental function, coordinates the transfer of metabolic, endocrine, and immune signals that are essential for normal cardiac and vascular development. Disruptions in maternal physiology—including metabolic disorders, hypertensive conditions, inflammation, and environmental stress—can perturb this communication network and alter the intrauterine milieu. These changes induce persistent modifications in cardiomyocyte growth, endothelial function, and key regulatory pathways, thereby contributing to long-term cardiovascular risk. Emerging studies highlight that cardiovascular programming is governed by interconnected mechanisms involving epigenetic regulation, mitochondrial function, immune signaling, and intercellular communication. This review synthesizes current evidence on how maternal–fetal crosstalk shapes cardiovascular development beyond genetic determinants and provides an integrated framework linking early-life exposures to lifelong cardiovascular health. Full article

Public concrete datasets often contain duplicate records, coupled variables, and cross-source distribution shifts, which may lead to overly optimistic model evaluation. Based on a deduplicated UCI high-performance concrete dataset (1005 samples), this study develops a leakage-controlled data-driven workflow with applicability-domain assessment. TabPFN, SHAP, and NSGA-II are used for compressive strength prediction, model-response attribution, and scenario-based candidate mix screening, respectively. Model evaluation follows a unified data split, inner training-set cross-validation, and an independent test-set protocol. In addition, 502 non-overlapping records from the Mendeley PCC dataset are used as an external benchmark to examine cross-source transferability and sensitivity to distribution shift. The results show that TabPFN achieves the highest R² and the lowest RMSE, MAE, and MAPE on the internal UCI test set, with values of 0.953, 3.744 MPa, 2.265 MPa, and 7.580%, respectively; however, its advantage over strong baselines such as CatBoost is limited. On the external Mendeley PCC dataset, TabPFN remains competitive, with R², RMSE, and MAE values of 0.490, 15.175 MPa, and 11.457 MPa, respectively, but its performance is close to that of random forest, XGBoost, and CatBoost. The 5NN applicability-domain stratification shows that external samples located within the 95% 5NN applicability domain achieve improved performance (R² = 0.634 and RMSE = 12.367 MPa), suggesting that external prediction errors are associated with the distance from the source-domain distribution. SHAP results indicate that cement, ground granulated blast-furnace slag, curing age, and water are the main attribution variables in the model output; their response directions should be interpreted as statistical attributions rather than material causal mechanisms. The Pareto candidate mixes generated by NSGA-II satisfy basic engineering constraints. Nevertheless, because the external benchmark reveals sensitivity to cross-source distribution shift, the resulting mix proportions should be treated as pre-experimental screening candidates rather than engineering-validated low-GWP concrete mix proportions. Full article

Bisphenol A type epoxy resin has the problem of relatively high brittleness after curing. Although traditional polysiloxane toughening methods can improve toughness, they often come at the expense of strength. In this paper, methylphenyl dimethoxysilane (MPS) was used as a monomer to synthesize end-hydroxyl poly(methylphenyl)siloxane (PMPS), which was then used to modify E51 epoxy resin. The structure and reaction degree were characterized by infrared spectroscopy, proton nuclear magnetic resonance spectroscopy, matrix-assisted laser desorption/ionization time-of-flight/time-of-flight mass spectrometry and viscosity tests. The mechanical test results show that when the PMPS content is 20 wt%, the tensile, flexural, compressive and impact strengths of the modified resin increase by 31.26%, 26.16%, 18.53% and 98.66%, respectively, compared with the unmodified resin, and the tensile and flexural elastic moduli increase by 38.36% and 32.25%, respectively. The fracture toughness increases by 60.29%, indicating that the strength, stiffness and toughness of the material have all been improved. Dynamic mechanical analysis shows that the glass transition temperature and crosslinking density of the system gradually decrease with increasing PMPS content. Thermogravimetric analysis shows that the introduction of PMPS increases the char yield and decreases the maximum thermal decomposition rate, thereby enhancing the thermal stability of the system. Microscopic morphology analysis by optical microscopy, scanning electron microscopy and atomic force microscopy shows that the system has good compatibility, and the internal different modulus phases are distributed in a network-like manner, forming a uniform co-continuous or bicontinuous phase structure. This structure effectively promotes stress transfer and energy dissipation, alleviates local stress concentration, and thus comprehensively improves the mechanical properties of the resin system. Full article

This study aimed to investigate the effects of cold storage time and matcha addition on the multi-scale structure and functionality of gluten protein and starch in re-steamed bread. Results showed that prolonged cold storage destroyed the integrity of gluten networks by breaking disulfide bonds and altering protein secondary structures, accompanied by moisture loss and migration; meanwhile, starch retrogradation was significantly promoted, resulting in increased hardness and decreased specific volume. The addition of 0.5–1.0% of matcha stabilized disulfide bonds and inhibited starch retrogradation, thus alleviating quality decline. When the addition amount exceeded 1.0%, high concentrations of polyphenols depolymerized gluten proteins and accelerated moisture transfer, causing a further drop in specific volume. Pearson correlation analysis verified the close correlations between macroscopic quality and microstructural characteristics. This study explored the mechanisms underlying the effects of cold storage time and matcha addition on the quality of re-steamed bread, providing a systematic scientific basis for the application of tea flour products in cold storage. Full article

This paper provides a systematic synthesis of recent developments in physics-informed neural networks (PINNs) applied to aerospace engineering, with an emphasis on their role in physically consistent surrogate modeling, forward simulation, and inverse parameter estimation. Using a PRISMA-based methodology, the study surveys peer-reviewed works published between 2017 and 2025 across aviation- and space-related domains, including aerodynamics, structural mechanics, aeroelasticity, propulsion, control, structural health monitoring, satellite-orbit prediction, space-debris collision avoidance, and spacecraft radiation-impact modeling. The analysis shows that embedding governing equations, boundary conditions, and observational data into composite loss functions enables PINNs to improve predictive consistency, reduce dependence on dense simulation or experimental datasets, and support parameter identification under sparse or noisy measurements. Attention is given to architectural variants such as XPINNs, cPINNs, gPINNs, operator-learning approaches, and hybrid PINN-CFD/FEM formulations, as well as to training strategies based on adaptive sampling, domain decomposition, transfer learning, and dynamic loss weighting. Reported benefits include reduced approximation error, improved convergence in selected high-gradient or multiphysics problems, and enhanced interpretability compared with purely data-driven models. At the same time, the review identifies persistent open challenges, including scalability to large aerospace domains, sensitivity to loss-weighting and collocation strategies, limited robustness under noise and uncertainty, high computational cost, and the lack of standardized aerospace benchmarks. Overall, the review highlights PINNs as a promising but still developing framework for fast, interpretable, and physically consistent modeling of aircraft and spacecraft systems. Full article

Tree-derived bio-based polymer materials, including natural rubber, raw lacquer, pine resin, and tree gums, are important renewable resources for sustainable forestry and green manufacturing. However, their collection still largely depends on manual operations, which may cause unstable yield, tree damage, and low operational efficiency. This review examines intelligent identification technologies for tree-derived material collection from the perspectives of multimodal perception and machine learning. The collection requirements and recognition targets of typical materials are first analyzed, including trunk localization, tapping line detection, bark feature extraction, tree state assessment, and safe tool–bark interaction. Visual, RGB-D, LiDAR, spectral, force/tactile, and environmental sensing technologies are then reviewed, and their roles in complex forest perception and robotic operation are discussed. Machine learning methods, including traditional classifiers, object detection, image segmentation, point cloud processing, temporal modeling, few-shot learning, transfer learning, and uncertainty-aware evaluation, are further examined. Representative cases in rubber tapping, lacquer collection, and pine resin harvesting are compared to reveal the transition from single-sensor recognition to perception–decision–execution integration. Key challenges are identified in dataset standardization, model generalization, edge deployment, force-aware control, and biological mechanism integration. Future directions are proposed toward autonomous, low-damage, and high-yield intelligent collection systems. Full article