Search Results (3,168)

Traditional polyurethanes have gained widespread application due to their excellent mechanical properties, wear resistance, and processability. However, these materials are susceptible to cracking or fracture under environmental stresses. In recent years, self-healing polyurethanes have garnered significant attention as a critical research field owing to their key capabilities, such as repairing physical damage, restoring mechanical strength, structural adaptability, and cost-effective manufacturing. This review systematically examines the healing mechanisms, structural characteristics, and performance metrics of self-healing polyurethanes, with in-depth analysis of their repair efficacy across various applications—particularly in flexible electronic devices. It demonstrates that self-healing polyurethanes overcome traditional failure modes in flexible electronics through self-repair-function integration mechanisms. Their stimuli-responsive healing behavior is driving the evolution of this field toward an intelligent regenerative electronics paradigm. Full article

This study resolves the long-standing question of the origin of bilinear Low Cycle Fatigue (LCF) behavior in Ti-6Al-4V using a high-fidelity CPFEM-XFEM framework. We identify that the fundamental origin lies in a fundamental shift in the efficiency of converting macroscopic energy dissipation into microscopic damage. This energetic efficiency is directly governed by the evolution of plastic strain heterogeneity (quantified by the Coefficient of Variation, CV). At low strain amplitudes, high strain localization (high CV) creates a highly efficient “energy funnel,” concentrating dissipated energy into a few critical grains. This manifests physically as a single-crack failure mode, where the crack initiation phase is prolonged, consuming ~80% of the total fatigue life. Conversely, at high strain amplitudes, deformation homogenization (low CV) leads to inefficient, diffuse energy dissipation across many grains. The material must therefore activate a more drastic failure mechanism—multi-site crack initiation and coalescence—to accumulate sufficient damage, reducing the initiation phase to just ~45% of the total life. Therefore, the bilinear C-M curve is the macroscopic signature of this transition from an energetically efficient, localized damage mode to an inefficient, distributed one. This work provides a quantitative, mechanism-based framework for understanding and predicting the complex fatigue behavior of advanced metallic materials. Full article

Background and Objectives: Facial paralysis involves the complete or partial loss of facial movement due to damage to the facial nerve, leading to impaired voluntary muscle function and facial asymmetry. Given its significant physical and psychosocial impact, there is an urgent need to strengthen the evidence supporting non-pharmacological treatments. This umbrella review aims to compile the most reliable and current data to establish a consensus on the effectiveness of such interventions for patients with facial paralysis. Materials and Methods: This study is an umbrella review. A systematic search was conducted in PubMed, Embase, Scopus, and CINAHL (28 July 2024). The variables assessed included overall healing/recovery rate, facial disability, and facial function. Methodological quality was evaluated using the AMSTAR and ROBIS tools. Screening was performed independently by two reviewers, with a third reviewer resolving any discrepancies. Results: Five systematic reviews were included, all evaluating the impact of non-pharmacological interventions in facial paralysis. The findings suggest that acupuncture and electrical stimulation may improve recovery rates and facial function, although high heterogeneity and methodological limitations were noted in some studies. No definitive conclusions could be drawn regarding facial disability. Conclusions: The combination of electrotherapy with other complementary techniques, such as facial exercises or laser therapy, appears to be a safe and potentially effective approach for facial paralysis rehabilitation. Nonetheless, further research employing standardized protocols and higher methodological quality is necessary to establish more robust conclusions for physiotherapeutic practice. Full article

In the process of the exploration and development of shale oil, the influence of hydration on shale reservoirs is complex, as it can not only improve porosity and permeability, but also lead to reservoir instability. At present, there is a lack of systematic understanding of the influence of hydration on the physical and chemical properties of shale oil reservoirs. Therefore, in this study, taking the Gulong shale oil reservoir in Songliao Basin as the research object, X-ray diffraction mineral composition analysis, electron microscope scanning, and micro-CT scanning were used to study the micro–macro-changes in shale caused by hydration, and the effects of different fracturing fluids on hydration were evaluated. The results show the following: (1) Hydration increases the porosity and permeability of Gulong shale through clay dispersion and dissolution pore formation, though these transient effects may compromise long-term reservoir stability due to pore-throat clogging. (2) Prolonged hydration significantly enhanced pore structure complexity, with tortuosity increasing by 64.7% (from 2.19 to 3.60) and the fractal dimension rising by 7.5% (from 1.99 to 2.14) with hydration time, and the proportion of larger pores (50–100 μm) increased significantly. (3) Hydration leads to crack propagation and new cracks, and the intersection of cracks reduces the core strength, which may eventually lead to macroscopic damage. (4) The influence of different fracturing fluids on the hydration reaction is obviously different. The higher the concentration, the stronger the hydration effect. Distilled water helps to increase porosity and permeability, but long-term effects may affect reservoir stability. The results of this paper reveal the changes in micro- and macro-characteristics of shale oil reservoirs under hydration, which is of great significance for analyzing the mechanism of hydration and provides theoretical support for improving shale oil recovery. Full article

Stone cleaning for cultural heritage monuments is a critical conservation intervention that must effectively eliminate harmful surface contaminants while preserving the material’s physical, chemical, and historical integrity. This study investigated the removal of tenacious black biofilms formed by Nocardia species previously isolated from deteriorated limestone from the Bastet tomb in Tell Basta, Zagazig City, Egypt, using a Q-switched 1064 nm Nd:YAG laser. Experimental limestone specimens were systematically inoculated with Nocardia sp. under controlled laboratory conditions to simulate biodeterioration processes. Comprehensive testing revealed that a laser fluence of 0.03 J/cm² with a 5 ns pulse duration, applied under wet conditions with 500 pulses, achieved the complete elimination of the biological black film without damaging the underlying stone substrate. The cleaning efficacy was evaluated through an integrated analytical framework combining stereomicroscopy, scanning electron microscopy coupled with energy-dispersive X-ray analysis (SEM-EDX), X-ray diffraction (XRD), and laser-induced plasma spectroscopy (LIPS). These analyses demonstrated a remarkable transformation from a compromised mineralogical composition dominated by gypsum (62%) and anhydrite (13%) to a restored state of 98% calcite, confirming the laser treatment’s effectiveness in reversing biodeterioration processes. SEM micrographs revealed the complete elimination of mycelial networks that had penetrated to depths between 984 μm and 1.66 mm, while LIPS analysis confirmed the restoration of elemental signatures to near-control levels. The successful application of LIPS for real-time monitoring during cleaning provides a valuable tool for preventing overcleaning, addressing a significant concern in laser conservation interventions. This research establishes evidence-based protocols for the non-invasive removal of Nocardia-induced black biofilms from limestone artifacts, offering conservation professionals a precise, effective, and environmentally sustainable alternative to traditional chemical treatments for preserving irreplaceable cultural heritage. Full article

Spinal health depends on the dynamic interplay between mechanical forces, biochemical signaling, and cellular behavior. This review explores how key molecular pathways, including integrin, yeas-associated protein (YAP) and transcriptional coactivator with PDZ-binding motif (TAZ), Piezo, and Wingless/Integrated (Wnt) with β-catenin, actively shape the structural and functional integrity of spinal tissues. These signaling mechanisms respond to physical cues and interact with inflammatory mediators such as interleukin-1 beta (IL-1β), interleukin-6 (IL-6), and tumor necrosis factor alpha (TNF-α), driving changes that lead to disc degeneration, vertebral fractures, spinal cord injury, and ligament failure. New research is emerging that shows scaffold designs that can directly harness these pathways. Further, new stem cell-based therapies have been shown to promote disc regeneration through targeted differentiation and paracrine signaling. Interestingly, many novel bone and ligament scaffolds are modulating anti-inflammatory signals to enhance tissue repair and integration, as well as prevent scaffold degradation. Neural scaffolds are also arising. These mimic spinal biomechanics and activate Piezo signaling to guide axonal growth and restore motor function. Scientists have begun combining these biological platforms with brain–computer interface technology to restore movement and sensory feedback in patients with severe spinal damage. Although this technology is not fully clinically ready, this field is advancing rapidly. As implantable technology can now mimic physiological processes, molecular signaling, biomechanical design, and neurotechnology opens new possibilities for restoring spinal function and improving the quality of life for individuals with spinal disorders. Full article

Most numerical studies on carbon fiber-reinforced polymer (CFRP) lightning damages fail to account for delamination, a factor that plays a significant role in the subsequent analysis of residual strength. This study establishes an electro-thermo-mechanical coupled numerical model incorporating delamination effects to predict lightning-induced damage in carbon fiber-reinforced plastic (CFRP) composites. Subsequently, parametric investigations evaluate the influence of varying input loads and stacking sequences on interlaminar pyrolysis and delamination damage, with damage assessment quantitatively conducted based on simulated post-strike uniaxial ultimate compressive loads. Post-strike uniaxial compressive strength reduction with cohesive elements is 28.91%, demonstrating closer alignment with experimental reduction (36.72%) than the 21.12% reduction predicted by the interlaminar-effect-neglecting model. Under combined thermal expansion and shockwave overpressure, the 28.91% compressive strength reduction demonstrates closer alignment with the experimental 36.72% reduction than the 25.13% reduction observed under isolated shockwave overpressure. The results highlight the critical role of thermal delamination in compressive strength reduction, with distinct waveform-dependent mechanisms: under C-waveform lightning currents, arc thermal effects cannot be neglected; D-waveform strikes exhibit predominant contributions from impact loading to delamination damage, with thermally driven delamination likewise pronounced. Increased current amplitude correlates with amplified mechanical damage severity, while premature symmetry in ply stacking sequences exacerbates compressive performance degradation. This work enhances multi-physics modeling fidelity by bridging thermal delamination and mechanical degradation pathways, offering foundational insights for optimizing lightning strike resistance in advanced aerospace composite systems. Full article

Amid accelerating climate change, climate-related hazards—such as floods, wildfires, hurricanes, and sea-level rise—increasingly drive land transformations and pose growing risks to housing markets by affecting property valuations, insurance availability, mortgage performance, and broader financial stability. This review synthesizes recent progress in two distinct domains and their linkage: (1) assessing climate-related financial risks in housing markets, and (2) applying AI-driven remote sensing for hazard detection and land transformation monitoring. While both areas have advanced significantly, important limitations remain. Existing housing finance studies often rely on static models and coarse spatial data, lacking integration with real-time environmental information, thereby reducing their predictive power and policy relevance. In parallel, remote sensing studies using AI primarily focus on detecting physical hazards and land surface changes, yet rarely connect these spatial transformations to financial outcomes. To address these gaps, this review proposes an integrative framework that combines AI-enhanced remote sensing technologies with financial econometric modeling to improve the accuracy, timeliness, and policy relevance of climate-related risk assessment in housing markets. By bridging environmental hazard data—including land-based indicators of exposure and damage—with financial indicators, the framework enables more granular, dynamic, and equitable assessments than conventional approaches. Nonetheless, its implementation faces technical and institutional barriers, including spatial and temporal mismatches between datasets, fragmented regulatory and behavioral inputs, and the limitations of current single-task AI models, which often lack transparency. Overcoming these challenges will require innovation in AI modeling, improved data-sharing infrastructures, and stronger cross-disciplinary collaboration. Full article

Aster spp., a key grass species for the ecological restoration of alpine degraded grasslands on the Qinghai–Tibet Plateau, often suffers from pest damage during its flowering and seed maturation stages, severely limiting the effectiveness of ecological restoration and the sustainable utilization of germplasm resources. This study focused on nine widely distributed species of Aster in the Three River Source Region of Qinghai Province, systematically investigated the structure of arthropod communities and the spatiotemporal dynamics of pests, and developed an integrated pest management (IPM) strategy. Through systematic surveys at multiple sites, a total of 109 arthropod species were identified (57 families of insects, 96 species; 7 families of spiders, 13 species). The Diptera (Tephritidae) and Hemiptera (Miridae) were identified as dominant groups. Tephritis angustipennis was determined to be the key pest, with its population density reaching a peak in mid-to-late August (p < 0.05). Based on the occurrence patterns of the pest, an IPM strategy integrating physical, chemical, and biological control methods was proposed: flower head bagging as a physical barrier significantly reduced plant damage but required balancing the risk of seed sterility. A combination lure (broad-spectrum fruit fly lure + a mixture of sugar and vinegar) showed a significant effect in attracting and killing adult flies. In chemical control, spraying a combination of insecticides (DB: 10% β-Cypermethrin aqueous emulsion (9 mL/acre) + 5% avermectin (20 mL/acre)) during the leaf expansion stage to early flowering stage achieved approximately 80% pest mortality within 24 h; additionally, supplementary spraying of 5% broflanilide (30 mL/acre) during the full flowering stage prolonged the efficacy and delayed the development of insecticide resistance. In terms of natural enemy utilization, Lycosidae and Thomisidae demonstrated significant potential for naturally regulating pest populations. Physiological mechanism studies showed that the difference in responses between plant catalase (CAT) activity and insect glutathione S-transferase (GST) activity was a key factor driving control efficacy (the cumulative explanation rate reached 94%). This IPM strategy, by integrating physical barriers, dynamic trapping, targeted spraying, and natural enemy control, significantly enhances control efficiency and ecological compatibility, providing a theoretical basis and technical paradigm for the ecological restoration of degraded alpine grasslands and the sustainable management of medicinal plants in cold regions. Full article

This study investigates two cases of stage IVb de novo multi-metastatic nasopharyngeal carcinoma (NPC) that responded to immunotherapy but resulted in different outcomes. Case 1 involved a multi-metastatic NPC patient (T4N3M1) with extensive bone and lymphatic metastases and severely impaired physical condition (ECOG PS 2) who showed significant tumor reduction after one cycle of immunotherapy combined with non-platinum chemotherapy, with no radiation exposure. Due to financial difficulties, the patient received intermittent immunotherapy plus chemotherapy and survived 28 months with a good quality of life. Case 2 describes a multi-metastatic NPC patient (T3N2M1) with multi-organ (bone and liver) metastases and good performance status (ECOG PS 0) who underwent standard chemotherapy, immunotherapy, and radiotherapy but experienced rapid progression and died after 21 months. Immunotherapy combined with chemotherapy remains the standard for multi-metastatic NPC patients. Patients responsive to induction chemotherapy gain survival benefits from subsequent radiotherapy. However, the advantages and disadvantages of radiotherapy for immunotherapy-sensitive multi-metastatic NPC patients are still unclear. Radiotherapy (RT) can enhance local control and promote tumor antigen release, thereby complementing immunotherapy; yet it can also damage immune cells, leading to exhaustion and resistance. Therefore, balancing RT and chemotherapy is vital for optimizing immune synergy and preventing immune exhaustion. Full article

Glenoid labral tears are relatively common orthopedic injuries in adults. Anatomically, the glenoid labrum is a fibrocartilaginous structure that contributes to shoulder stability and function. The treatment for labral injury may be conservative, such as activity modification and rest, or operative, depending on the extent of tissue damage. Hydrogels are polymeric networks with great potential in treating glenoid labral tears and other cartilage-related injuries. Hydrogels are highly biocompatible, hydrophilic, and non-immunogenic, with tunable mechanical properties that support nutrient diffusion, cell viability, and angiogenesis, making them well suited for cartilage regeneration. Hydrogels can deliver growth factors like TGF-β or PDGF and may be combined with peptides or adhesion molecules to enhance tissue integration, repair, and even physical support. This article introduces current treatment options for glenoid labral injuries, reviews the role of hydrogels in cartilage regeneration, and summarizes recent translational research focused on hydrogel-based labral repair. Full article

The widespread adoption of Unmanned Aerial Vehicles (UAVs) in civilian domains, such as airport security and critical infrastructure protection, has introduced significant safety risks that necessitate effective countermeasures. High-Energy Laser Systems (HELSs) offer a promising defensive solution; however, when confronting large-scale malicious UAV swarms, the Dynamic Resource Target Assignment (DRTA) problem becomes critical. To address the challenges of complex combinatorial optimization problems, a method combining precise physical models with multi-agent reinforcement learning (MARL) is proposed. Firstly, an environment-dependent HELS damage model was developed. This model integrates atmospheric transmission effects and thermal effects to precisely quantify the required irradiation time to achieve the desired damage effect on a target. This forms the foundation of the HELS–UAV–DRTA model, which employs a two-stage dynamic assignment structure designed to maximize the target priority and defense benefit. An innovative MADDPG-IA (I: intrinsic reward, and A: attention mechanism) algorithm is proposed to meet the MARL challenges in the HELS–UAV–DRTA problem: an attention mechanism compresses variable-length target states into fixed-size encodings, while a Random Network Distillation (RND)-based intrinsic reward module delivers dense rewards that alleviate the extreme reward sparsity. Large-scale scenario simulations (100 independent runs per scenario) involving 50 UAVs and 5 HELS across diverse environments demonstrate the method’s superiority, achieving mean damage rates of 99.65% ± 0.32% vs. 72.64% ± 3.21% (rural), 79.37% ± 2.15% vs. 51.29% ± 4.87% (desert), and 91.25% ± 1.78% vs. 67.38% ± 3.95% (coastal). The method autonomously evolved effective strategies such as delaying decision-making to await the optimal timing and cross-region coordination. The ablation and comparison experiments further confirm MADDPG-IA’s superior convergence, stability, and exploration capabilities. This work bridges the gap between complex mathematical and physical mechanisms and real-time collaborative decision optimization. It provides an innovative theoretical and methodological basis for public-security applications. Full article

Exercise-induced muscle damage (EIMD) is the most common health risk in physical exercise. However, instant and non-invasive methods for EIMD prediction have not been reported. Urine is a promising tool for EIMD prediction. However, urinary metabolite variations after EIMD occurrence have not been revealed, and potential biomarkers have not been identified. In this study, eighteen young students without regular exercise habits were recruited to perform high-intensity rowing exercise. EIMD occurrence was determined using blood biochemical analyses and pain assessment. The changes in urinary metabolites were revealed by quasi-targeted metabolomics. Results demonstrated that high-intensity rowing exercise induced EIMD and obviously changed urinary metabolites, including 23 upregulated metabolites and 26 downregulated metabolites. These differential metabolites were related to energy metabolism, exercise performance, and antioxidant metabolism. Among these metabolites, potential urinary biomarkers were identified with high sensitivity and specificity. Full article

In this study, we present a wearable sensing system for monitoring the physiological status of damaged biological tissues based on a flexible, frequency-coded electromagnetic spiral resonator array. The physiological parameter evaluation is performed in a contactless way, avoiding the placing of electronically active elements directly upon the patient’s skin, thus ensuring safety and comfort. Firstly, we report in detail the physical principles behind the sensing strategy: a passive array is interrogated through an actively fed external single-loop probe that is inductively coupled with the double-layer spiral unit cells. The variation in the physiological parameters influences the array response, thus providing sensing information, due to the different complex dielectric permittivity values related to the tissue status. Moreover, the proposed frequency-coded approach allows for spatial information on the lesion to be retrieved, thus increasing the sensing ability. In order to prove the validity of this general methodology, we created a numerical test case, designing a practical implementation of the wearable sensing system working at a radiofrequency regime (10–100 MHz). In addition, we also fabricated prototypes, exploiting PCB technology, and realized stratified phantoms by incorporating opportune additives to control the dielectric properties. The numerical results and the experimental verification demonstrated the validity of the developed sensing strategy, showing satisfying agreement and, thus, proving the good sensibility and spatial resolution of the frequency-coded array. These results can open the path to a radically novel approach for self-care and monitoring of inflamed status and, more generally, for wearable sensing devices in biomedical applications. Full article

Accurately characterizing the energy evolution during rock failure is crucial in understanding instability mechanisms and enabling the real-time monitoring and early warning of geological hazards in mining and geotechnical engineering. However, the energy evolution characteristics and correlations of multi-physics signals like acoustic emission (AE) and infrared radiation (IR) require further investigation. This study specifically investigated the energy evolution of AE and IR and their correlation during the uniaxial compression failure process of phosphate rock. Tests were performed on specimens under different loading rates to analyze energy dissipation and damage progression. Based on damage mechanics theory, damage evolution models were developed to describe the relationship between the cumulative AE energy, IR radiation variations (specifically the change in the average infrared radiation temperature, ΔAIRT), and strain under varying loading conditions. The results indicate that the loading rate significantly influences the energy release mechanism, with higher rates intensifying rock damage. The peak AE energy rate coincides with the inflection point of the cumulative energy curve, marking substantial internal energy release at failure. Additionally, as the loading rate increases, high-temperature regions in IR thermograms appear earlier, while the variation in ΔAIRT follows a decreasing trend. From an energy perspective, the correlation between AE ringing counts and the average IR temperature was analyzed at both the precursor and failure stages, revealing a strong relationship between AE activity and thermal energy dissipation. Furthermore, mathematical expressions for rock damage variables and coupled relationship equations were derived and validated using experimental data, yielding correlation coefficients (R²) exceeding 0.92. These findings provide a theoretical and methodological foundation for the development of enhanced real-time rock monitoring and early warning systems, contributing to improved safety in geological and mining engineering. Full article