Search Results (2,505)

Wood is one of the most widely used sustainable lignocellulosic materials, with numerous applications in consumer goods and the construction sector. Despite its positive properties, such as a high strength-to-weight ratio, thermal insulation, and low density, wood’s natural thermal degradation can limit its potential applications. In composite applications like wood–plastic composites, the particle morphology and surface topography must be preserved to support intimate polymer–wood contact and mechanical interlocking. This study investigated the efficacy of a thin silica coating for thermal protection, which was applied via an in situ sol–gel method using the precursor tetraethoxysilane (TEOS). The wood particles and treatments were characterized using particle size analysis, physisorption, FTIR, SEM, XRD, and TGA analyses. After treatment, the specific and microporous surface area of wood particles increased by 118% and 97%, respectively, an effect of the porosity of silica itself. FTIR spectra of the silica-treated wood displayed peaks corresponding to Si stretching, and SEM micrographs confirmed a successful silica coating formation. TGA showed that the silica coating increased the temperatures needed to degrade the underlying hemicellulose and cellulose by 16 °C for all treatment levels. This particle-scale coating provided a promising method for producing thermally protected, functionalizable wood fillers for composites that maintain the filler geometry and potential mechanical interlocking, offering an attractive upcycling pathway for wood residues. Full article

Biologically treated swine farm wastewater still contains high levels of refractory organics, humic substances and antibiotic residues, posing environmental risks and limiting opportunities for water reuse. Wastewater treatment by ozonation alone suffers from low mass transfer efficiency and selective oxidation. To overcome these limitations, a catalytic ozonation process (O₃/Fe²⁺/H₂O₂) was applied and optimized using Response Surface Methodology (RSM) based on single-factor experiments and Central Composite Design (CCD) for advanced swine farm wastewater treatment. The optimal conditions ([O₃] = 25.0 mg/L, [Fe²⁺] = 25.9 mg/L, [H₂O₂] = 41.1 mg/L) achieved a COD removal of 44.3%, which was 86.8% higher than that of ozonation alone, and increased TOC removal to 29.5%, indicating effective mineralization. Biodegradability (BOD₅/COD) of swine farm wastewater effluent increased from 0.01 to 0.34 after the catalytic ozonation treatment. Humic-like and fulvic-like substances were removed by 93.7% and 95.4%, respectively, and antibiotic degradation was significantly accelerated and enhanced. The synergistic process improved ozone utilization efficiency by 33.1% and removed 53.95% of total phosphorus through Fe³⁺-mediated coprecipitation. These findings demonstrate that with catalytic ozone decomposition and production of hydroxyl radicals, the O₃/Fe²⁺/H₂O₂ system effectively integrates enhanced ozone utilization efficiency, radical synergy, and simultaneous pollutant removal, providing a cost-effective and technically feasible strategy for advanced swine farm wastewater treatment and safe reuse. Full article

Microplastics entering the gastrointestinal environment rapidly acquire protein coronas that alter their surface chemistry and analytical detectability. We investigated the physicochemical interactions between fluorescently labeled bovine serum albumin (BSA) and polyethylene terephthalate (PET) microplastics during simulated intestinal exposure and evaluated the stability of the resulting hard corona. Using fluorescence tracking, SDS-PAGE, and FTIR spectroscopy, we showed that BSA forms a persistent corona that resists oxidative-only treatments. Only a combination of oxidation with an alkaline (KOH) or surfactant step (SDS) effectively removed the corona. None of the protocols applied affected polymer integrity. Residual protein in less effective protocols did not show changes on PET spectra in ATR FTIR. To validate the protocol under physiologically relevant complexity, we extended it to PET incubated with single digestive enzymes. FTIR spectra confirmed the removal of protein-specific signals in both systems, with no degradation of PET ester or aromatic functional groups nor signals of protein–polymer interactions. Our results highlight the robustness of protein–PET interactions in biological conditions and provide a variety of protocols for protein corona removal, suitable for diverse applications of microplastic analysis and toxicological studies. Full article

Unidirectional carbon fiber-reinforced polymer (UD-CFRP) composites demonstrate superior tensile creep strain and stress relaxation behavior along fiber orientation. However, prolonged transverse compressive loading in structural connection zones induces significant interfacial stress relaxation and creep deformation, primarily driven by resin matrix degradation and interfacial slippage under thermal-mechanical interactions, and remains poorly understood. This study systematically investigates the transverse stress relaxation characteristics of UD-CFRP through controlled experiments under varying thermal conditions (20–80 °C) and compressive stress levels (30–80% ultimate strength). Post-relaxation mechanical properties were quantitatively evaluated, followed by the development of a temperature-stress-time-dependent predictive model aligned with industry standards. The experimental results reveal bi-stage relaxation behavior under elevated temperatures and compressive stresses, characterized by a rapid primary phase and stabilized secondary phase progression. Notably, residual transverse compressive strength remained almost unchanged, while post-relaxation elastic modulus increased by around 10% compared to baseline specimens. Predictive modeling indicates that million-hour relaxation rates escalate with temperature elevation, reaching 51% at 60 °C/60% stress level—about 1.8 times higher than equivalent 20 °C conditions. These findings provide crucial design insights and predictive tools for ensuring the long-term integrity of CFRP-based structures subjected to transverse compression in various thermal environments. Full article

This work provides a comparison of two commercial carbon fiber reinforced plastic (CFRP) materials: HexPly^® M18 1/G939 and RTM6/G939. Differences due to the additional thermoplastic in one CFRP are investigated for the two otherwise nearly identical, aromatic epoxy-based composites with respect to thermal degradation. The scenario chosen for testing is based on real incidents of repeated overheating by hot gases between roughly 200 and 320 °C, leading to moderate thermal damage. A special test setup is designed to continuously and alternately load CFRP with hot air in a rapid change. Post-mortem analysis is performed by mass loss, ultrasonic, and mechanical testing. Polymer degradation is analyzed by infrared spectroscopy. Even if the temperature-resistant thermoplastic polyetherimide (PEI) in the M18-1 matrix is enriched between the plies and a compensation of thermal strain during rapid temperature changes is expected, only a weak improvement is observed for residual strength in the presence of PEI, for continuous as well as alternating thermal loading. Thermally induced delaminations are even more pronounced in M18-1/G939. Deep insight is gained into degradation after repeated overheating of CFRP within the chosen scenario. Multivariate data analyses based on infrared spectroscopy allow for the determination of thermal history and residual strength, valuable for failure analysis. Full article

The persistent residual tumor cells that survive after chemotherapy are a major cause of treatment failure, but their survival mechanisms remain largely elusive. These cancer cells are typically characterized by a quiescent state with suppressed activity of MYC and MTOR. We observed that the MYC-suppressed persistent triple-negative breast cancer (TNBC) cells are metabolically flexible and can upregulate mitochondrial oxidative phosphorylation (OXPHOS) genes and respiratory function (“OXPHOS-high” cell state) in response to DNA-damaging anthracyclines such as doxorubicin, but not to taxanes. The elevated biomass and respiratory function of mitochondria in OXPHOS-high persistent cancer cells were associated with mitochondrial elongation and remodeling, suggestive of increased mitochondrial fusion. A genome-wide CRISPR editing screen in doxorubicin-persistent OXPHOS-high TNBC cells revealed the BCL-XL gene as the top survival dependency in these quiescent tumor cells, but not in their untreated proliferating counterparts. Quiescent OXPHOS-high TNBC cells were highly sensitive to BCL-XL inhibitors, but not to inhibitors of BCL2 and MCL1. Interestingly, inhibition of BCL-XL in doxorubicin-persistent OXPHOS-high TNBC cells rapidly abrogated mitochondrial elongation and respiratory function, followed by caspase 3/7 activation and cell death. The platelet-sparing proteolysis-targeted chimera (PROTAC) BCL-XL degrader DT2216 enhanced the efficacy of doxorubicin against TNBC xenografts in vivo without induction of thrombocytopenia that is often observed with the first-generation BCL-XL inhibitors, supporting the development of this combinatorial treatment strategy for eliminating dormant tumor cells that persist after treatment with anthracycline-based chemotherapy. Full article

Efficient recycling of polyamide 6 (PA6) requires selective depolymerization routes that recover monomers under moderate conditions. This study investigates microwave-assisted acid hydrolysis of four PA6 waste streams, two oligomer-rich residues (WS-13, WS-24), an industrial fiber (C-fiber), and a commercial resin (C-resin) to elucidate degradation kinetics, activation energies, and product yields. Thermogravimetric analysis revealed multi-step solid-state decomposition, while microwave hydrolysis (125–200 °C, 15–60 min, 400 W) demonstrated strong dependence on acid type. HCl achieved complete conversion, whereas phosphoric and formic acids exceeded 95%. Kinetic analysis under H₃PO₄ followed pseudo-first-order behavior, with rate constants (0.015–0.141 min⁻¹ at 200 °C) and activation energies reflecting feedstock structure: 53.1 kJ mol⁻¹ (WS-13), 56.5 kJ mol⁻¹ (WS-24), 87.1 kJ mol⁻¹ (C-resin), and 99.9 kJ mol⁻¹ (C-fiber). Monomer yields varied by substrate: WS-13 achieved 62.4% at 200 °C and 45 min (ACA 46%, CPL 16%), WS-24 yielded 62.0% (primarily ACA), C-fiber reached 69.7% (ACA-dominant), and C-resin produced 53.8%. These results show that oligomer-rich wastes are kinetically favored for rapid hydrolysis at lower energy cost, while C-fiber maximizes aminocaproic acid recovery. Overall, microwave-assisted hydrolysis provides a selective, energy-efficient pathway for PA6 circularity, offering design parameters for reactor operation and process optimization. Full article

To mitigate the degradation of positioning accuracy in sixth-generation mobile communication systems under dynamic line-of-sight (LOS) and non-line-of-sight (NLOS) conditions, this paper proposes an improved adaptive Kalman filter positioning method based on Orthogonal Time Frequency Space (OTFS)-modulated signals. Firstly, the distance can be measured by using the OTFS-modulated signals transmitted between base stations and nodes. Secondly, the distance information is converted into the distance difference information to establish the time difference of arrival (TDOA) positioning equation, which is preliminarily solved using the Chan algorithm. Thirdly, residuals are calculated based on the preliminary positioning results, dividing the complex environment into distinct regions and adaptively determining corresponding genetic factors for each region. Finally, the selected genetic parameters are substituted into the Sage–Husa adaptive Kalman filter equations to estimate positioning results. The simulation analysis demonstrates that in complex environments featuring both line-of-sight and non-line-of-sight conditions, the vehicle motion trajectories estimated using this method more closely approximate actual trajectories. Additionally, both the accuracy and stability of positioning results show significant improvement compared to traditional methods. Full article

For the first time, the kinetics of isothermal curing and thermal degradation of polyethylene glycol maleate (pEGM)–based systems and their composites with mineral fillers were investigated in the presence of a benzoyl peroxide/N,N-Dimethylaniline redox-initiating system. DSC analysis revealed that the curing process at 20 °C can be described by the modified Kamal autocatalytic model; the critical degree of conversion (α_c) decreases with increasing content of the unsaturated polyester pEGM and in the presence of fillers. In particular, for unfilled systems, α_c was 0.77 for pEGM45 and 0.60 for pEGM60. TGA results demonstrated that higher pEGM content and the incorporation of fillers lead to increased thermal stability and residual mass, along with a reduction in the maximum decomposition rate (dTGₘₐₓ). Calculations using the Kissinger–Akahira–Sunose and Friedman methods also confirmed an increase in the activation energy of thermal degradation (E_a): E_KAS was 419 kJ/mol for pEGM45 and 470 kJ/mol for pEGM60, with the highest values observed for pEGM60 systems with fillers (496 kJ/mol for SiO₂ and 514 kJ/mol for CaCO₃). Rheological studies employing three-interval thixotropy tests revealed the onset of thixotropic behavior upon filler addition and an increase in structure recovery after deformation of up to 56%. These findings underscore the potential of pEGM-based systems for low-temperature curing and for the design of composite materials with improved thermal resistance. Full article

Deep learning algorithms have significantly reduced the computational time and improved the spatial resolution of particle image velocimetry (PIV). However, the models trained on synthetic datasets might have degraded performances on practical particle images due to domain gaps. As a result, special residual patterns are often observed for the vector fields of deep learning-based estimators. To reduce the special noise step by step, we employ a denoising diffusion model (FlowDiffuser) for PIV analysis. And a data-hungry iterative denoising diffusion model is trained via a transfer learning strategy, resulting in our PIV-FlowDiffuser method. Specifically, we carry out the following: (1) pre-training a FlowDiffuser model with multiple optical flow datasets of the computer vision community, such as Sintel and KITTI; (2) fine-tuning the pre-trained model on synthetic PIV datasets. Note that the PIV images are upsampled by a factor of two to resolve small-scale turbulent flow structures. The visualized results indicate that our PIV-FlowDiffuser effectively suppresses the noise patterns. Therefore, the denoising diffusion model reduces the average endpoint error ($AEE$) by $59.4\%$ over the RAFT256-PIV baseline on the classic Cai’s dataset. In addition, PIV-FlowDiffuser exhibits enhanced generalization performance on unseen particle images due to transfer learning. Overall, this study highlights transfer-learning-based denoising diffusion models for PIV. Full article

Accurate brain tumor classification from MRI is often constrained by limited labeled data. We systematically compare conventional machine learning, deep learning, and few-shot learning (FSL) for four classes (glioma, meningioma, pituitary, no tumor) using a standardized pipeline. Models are trained on the Kaggle Brain Tumor MRI Dataset and evaluated across dataset regimes (100%→10%). We further test generalization on BraTS and quantify robustness to resolution changes, acquisition noise, and modality shift (T1→FLAIR). To support clinical trust, we add visual explanations (Grad-CAM/saliency) and report per-class results (confusion matrices). A fairness-aligned protocol (shared splits, optimizer, early stopping) and a complexity analysis (parameters/FLOPs) enable balanced comparison. With full data, Convolutional Neural Networks (CNNs)/Residual Networks (ResNets) perform strongly but degrade with 10% data; Model-Agnostic Meta-Learning (MAML) retains competitive performance (AUC-ROC ≥ 0.9595 at 10%). Under cross-dataset validation (BraTS), FSL—particularly MAML—shows smaller performance drops than CNN/ResNet. Variability tests reveal FSL’s relative robustness to down-resolution and noise, although modality shift remains challenging for all models. Interpretability maps confirm correct activations on tumor regions in true positives and explain systematic errors (e.g., “no tumor”→pituitary). Conclusion: FSL provides accurate, data-efficient, and comparatively robust tumor classification under distribution shift. The added per-class analysis, interpretability, and complexity metrics strengthen clinical relevance and transparency. Full article

This paper discusses whether the principal response features of composites subjected to fatigue loadings, including residual strength and lifetime statistics under variable amplitude (VA) loadings, can be resolved based on constant amplitude (CA) fatigue life data. The approach is based on the strength-residual strength-life equal-rank assumption (SRSLERA), providing a statistical correspondence between the static strength, residual strength, and fatigue life distribution functions under CA loadings. Under VA loadings, the strength degradation progression and then the fatigue lifetime are calculated by dividing the loading spectrum into a sequence of CA block loadings of given extents (including one cycle), and assuming that the strength at the end of a generic block loading equals the strength at the start of the consecutive one, namely the equivalent residual strength assumption (ERSA). The consequences of SRSLERA and ERSA are first discussed by re-elaborating a series of uniaxial, statistically sound CA residual strength and fatigue life data obtained under different loading ratios, R, ranging from pure tension to mixed tension–compression to pure compression. It is shown that the static strength Weibull’s shape and scale parameters, as well as the fatigue formulation parameters recovered under pure compression or tension loadings, represent the fingerprint of composite materials subjected to fatigue and characterize their uniqueness. The residual strength statistics, fatigue probability density functions (PDFs), and constant life diagram (CLD) construction are theoretically reported. Then, based on ERSA, the statistical lifetimes under VA loadings and the cycle-by-cycle damage progressions of block repeated loadings are analyzed, and a residual strength-based damage rule is compared to Miner’s rule. Full article

To address the issue of output anomalies that frequently occur in position sensors of permanent magnet synchronous motors within electromechanical actuation systems operating in harsh environments and can lead to degradation in system performance or operational interruptions, this paper proposes an integrated method for fault diagnosis and fault-tolerant control based on the Cubature Kalman Filter (CKF). This approach effectively combines state reconstruction, fault diagnosis, and fault-tolerant control functions. It employs a CKF observer that utilizes innovation and residual sequences to achieve high-precision reconstruction of rotor position and speed, with convergence assured through Lyapunov stability analysis. Furthermore, a diagnostic mechanism that employs dual-parameter thresholds for position residuals and abnormal duration is introduced, facilitating accurate identification of various fault modes, including signal disconnection, stalling, drift, intermittent disconnection, and their coupled complex faults, while autonomously triggering fault-tolerant strategies. Simulation results indicate that the proposed method maintains excellent accuracy in state reconstruction and fault tolerance under disturbances such as parameter perturbations, sudden load changes, and noise interference, significantly enhancing the system’s operational reliability and robustness in challenging conditions. Full article

Lignocellulosic agricultural residues represent a rich source of potential feedstock for biorefinery applications, but their valorization remains challenging. The white-rot fungus Irpex lacteus J2 exhibited a promising degradation effect, but its molecular mechanisms of lignocellulose degradation remained largely uncharacterized. Here, we performed high-quality whole-genome sequencing and untargeted metabolomic profiling of I. lacteus J2 during the degradation of corn straw as the sole carbon source. The assembled I. lacteus J2 genome contained 14,647 protein-coding genes, revealing a rich genetic repertoire for biomass degradation and secondary metabolite synthesis. Comparative genomics showed high synteny (mean amino acid sequence identity 92.28%) with I. lacteus Irplac1. Untargeted metabolomic analysis unveiled a dynamic metabolic landscape during corn straw fermentation. Dominant metabolite classes included organic acids and derivatives (27.32%) and lipids and lipid-like molecules (25.40%), as well as heterocyclic compounds (20.41%). KEGG pathway-enrichment analysis highlighted significant activation of core metabolic pathways, with prominent enrichment in global metabolism (160 metabolites), amino acid metabolism (99 metabolites), carbohydrate metabolism (24 metabolites), and lipid metabolism (19 metabolites). Fermentation profiles at 3 and 15 days demonstrated substantial metabolic reprogramming, with up to 210 upregulated and 166 downregulated metabolites. Correlation analyses further revealed complex metabolic interdependencies and potential regulatory roles of key compounds. These integrated multi-omics insights significantly expand our understanding of the genetic basis and metabolic versatility, enabling I. lacteus J2 to efficiently utilize lignocellulose. Our findings position I. lacteus J2 as a robust model strain and provide a valuable foundation for developing advanced fungus-based strategies for sustainable bioprocessing and valorization of agricultural residues. Full article

Advanced oxidation processes (AOPs) utilizing peroxymonosulfate (PMS) have recently gained attention for effectively removing organic dyes. Biochar, a carbon-based material, can act as a catalyst carrier for PMS activation. This study developed a nitrogen-doped biochar catalyst (NCMR800–2) from waste Chinese medicine residue (CMR) through one-step pyrolysis to efficiently remove Rhodamine B (RhB) from wastewater. Results indicate that NCMR800–2 rapidly achieved complete removal of 20 mg/L Rhodamine B (RhB), the primary focus of this study, within 30 min, while maintaining high degradation efficiencies for other pollutants and significantly outperforming the unmodified material. The material demonstrates strong resistance to ionic interference and operates effectively across a wide pH range. Quenching experiments and in situ testing identified singlet oxygen (¹O₂) as the primary active species in RhB degradation. Electrochemical analysis showed that nitrogen doping significantly enhanced the electrical conductivity and electron transfer efficiency of the catalyst, facilitating PMS decomposition and RhB degradation. Liquid chromatography–mass spectrometry (LC-MS) identified intermediate products in the RhB degradation process. Seed germination experiments and TEST toxicity software confirmed a significant reduction in the toxicity of degradation products. In conclusion, this study presents a cost-effective, efficient catalyst with promising applications for removing persistent organic dyes. Full article