Search Results (2,473)

Functionally graded porous beams are increasingly used in lightweight engineering structures, where thermal effects and material inhomogeneity significantly influence vibration behavior. In this study, the thermoelastic free vibration of functionally graded porous Euler–Bernoulli beams with temperature-dependent material properties is investigated by considering uniform and symmetric porosity distributions, together with uniform, linear, and nonlinear temperature fields. The governing equations are derived based on classical Euler–Bernoulli beam theory and solved using the Differential Transformation Method, while the accuracy of the semi-analytical formulation is verified through a Hermite-based finite element model. The results show that increasing temperature reduces the bending stiffness due to thermal axial forces and leads to a rapid decrease in natural frequency as the critical buckling temperature is approached. Increasing porosity generally decreases the natural frequency, although a slight increase may occur in symmetric distributions because of the accompanying reduction in mass density. The present study provides a computational framework for the thermo-vibration analysis of functionally graded porous beams in lightweight structural applications. Full article

This study reports the synthesis, spectroscopic characterization, and biological evaluation of a novel moxifloxacin hydrazide derivative (MOX-H) and its metal complexes with Co(II), Ni(II), Cu(II), VO(IV), and Gd(III). The ligand was synthesized by hydrazinolysis of moxifloxacin hydrochloride, and the resulting hydrazide was subsequently complexed with the respective metal salts. The interaction between MOX-H and the metal ions yielded the corresponding complexes, formulated as [Co(H₂O)Cl(MOX-H)₂]Cl·2.5H₂O, [Ni(H₂O)Cl(MOX-H)₂]Cl.4.5H₂O, [VO(MOX-H)₂]SO₄.3.5H₂O, [Gd (H₂O)(MOX-H)₂(NO₃)₂]NO₃.2H₂O, and [Cu(MOX-H)₂(H₂O)Cl]Cl·xH₂O (where x = 2, 2.5, 0.5, for products synthesized via template, microwave-assisted, and hydrothermal methods, respectively). The synthesized analogues were characterized by elemental analysis (CHN), FT-IR, UV-visible, and ¹H NMR spectroscopy, and mass spectrometry, as well as thermogravimetric (TG/DTG) and magnetic measurements. FT-IR spectra confirmed coordination through the hydrazide carbonyl and amine groups, while UV–visible and magnetic data indicated predominantly octahedral geometries. The thermal behavior exhibited multistep decomposition with activation parameters supporting exothermic processes. When compared to the free ligand, the metal complexes showed increased antimicrobial activity against both Gram-positive and Gram-negative bacteria and fungus species, particularly for the Co(II) and Cu(II) complexes, which showed the largest inhibition zones. The Cu(II)–MOX-H complex exhibited the lowest MIC values (4.88–9.76 µg/mL) among all tested compounds, confirming its outstanding antibacterial potency and high sensitivity compared to the free ligand and standard drug. Cytotoxicity assays demonstrated selective anticancer activity, with the Cu(II)–MOX-H complex showing the highest potency (IC₅₀ ≈ 2.95 µM against MCF-7 and IC₅₀ ≈ 0.98 µM against HepG-2), while maintaining minimal toxicity toward normal cells. These findings were corroborated by molecular docking investigations, which showed that the MOX-H complexes had substantial binding affinities (−9 to −10 kcal/mol) toward DNA topoisomerase II, consistent with their observed biological effects. Full article

Monitoring forest density is essential for understanding ecosystem health, wildfire risk, and post-disturbance recovery. This study proposes a robust methodology to extract forest density classes exclusively using Sentinel-2 multispectral imagery combined with vegetation indices (VIs), textural parameters, and spatial clustering metrics. The approach was applied to the northern part of Euboea Island, Greece, as a pilot area severely affected by a wildfire in August 2021. Four cloud-free Sentinel-2 images (2017–2024) were selected to capture pre- and post-fire conditions. A set of nine VIs—representing vegetation vigor, chlorophyll content, soil exposure, and canopy moisture—were calculated and statistically assessed for independence. To enhance classification accuracy, texture measures (homogeneity, correlation, and entropy) and spatial autocorrelation metrics (Moran’s I, Getis-Ord Gi) were derived for selected VIs. Supervised classification was performed using the Maximum Likelihood algorithm, yielding overall accuracies up to 89.4% and kappa coefficients above 0.85 when combining VIs with texture and spatial metrics. Results revealed a dramatic 49.3% reduction in forest cover immediately after the wildfire, with partial recovery (to 77.9% of pre-fire levels) three years later, mainly as a low-density forest. Approximately 12.1% of forest cover failed to regenerate, indicating potential long-term ecosystem degradation. The proposed approach provides a computationally efficient, high-accuracy alternative to data-fusion methods involving (Light Detection and Ranging) LiDAR or (Synthetic Aperture Radar) SAR datasets, making it suitable for operational forest monitoring and fire-risk management. Full article

N-Heterocyclic carbene (NHC) catalysis has emerged as a powerful and versatile strategy for constructing silicon derivatives, offering a metal-free alternative to traditional transition-metal methods. This review comprehensively summarizes recent advances in the NHC-catalyzed synthesis of organosilicon derivatives. Key transformations discussed include both asymmetric and non-asymmetric silylation reactions, as well as the construction of silicon-stereogenic centers. The content is systematically organized according to the types of silicon products and their underlying catalytic mechanisms. Our own perspectives on future development within this rapidly evolving field are also outlined. Full article

Chitooligosaccharides (COS) are short-chain chitosan derivatives with a wide range of biomedical, agricultural, and environmental applications, including antimicrobial therapy, wound healing, and pollutant removal. Reliable quantification of COS is essential but currently relies on high-performance liquid chromatography, mass spectrometry, or capillary electrophoresis, which require costly equipment, complex sample preparation, and are unsuitable for routine or on-site applications. This study reports a rapid, solvent-free, colorimetric assay for COS based on the reaction of 5% aqueous ninhydrin with free amino groups in McIlvaine buffer. The assay was optimized using glucosamine as a model analyte, yielding maximal sensitivity at pH 7.0. The chromophore generated (Ruhemann’s purple) remained stable for over 120 min after reaction, allowing measurements to be taken without strict time constraints. Calibration was linear from 0.4 to 2.2 mM (R² = 0.9926), with low limits of detection (0.006 mM) and quantification (0.018 mM). Increasing absorbance with COS polymerization degree (DP1–DP6) demonstrates specificity for free amino groups, while N-acetyl glucosamine showed a negligible response. Furthermore, the assay was successfully adapted for solid-phase detection on ninhydrin-pretreated filter paper and nitrocellulose, with enhanced sensitivity. This simple, efficient, and low-cost method provides an accessible alternative to instrumental techniques, supporting COS monitoring in laboratory workflows and enabling portable applications in biomedicine, agriculture, and environmental diagnostics. Full article

Background/Objectives: Spotty liver disease (SLD), caused by Campylobacter hepaticus, is an emerging disease that leads to substantial production losses in the egg industry. The shift toward antibiotic-free and cage-free production systems has further intensified the impact of SLD. The current control measures largely rely on autogenous killed vaccines; however, their use is constrained by the slow and fastidious growth of C. hepaticus and inconsistent efficacy. To overcome these limitations, this study aimed to identify immunogenic mimotopes as vaccine candidates and express them on the surface of an avian pathogenic Escherichia coli (APEC) vector. Methods: To identify immunogenic mimotopes, Ph.D.-12 phage display peptide library was screened using the hyperimmune serum raised against killed whole-cell C. hepaticus in specific pathogen-free chickens. Subsequently, the outer membrane protein C (OmpC) of E. coli was used as a scaffold for constructing a surface display library. A single restriction site, PstI, located in the seventh external loop of OmpC, was strategically utilized to insert each 12-amino-acid mimotope with a six-histidine (6xHis) tag sequence at its N-terminus, generating ompC + mimotope fusion constructs. These constructs were cloned into the inducible expression vector pTrc and electroporated into an E. coli DH5α ∆ompC strain, which lacked ompC. The surface expression of the mimotopes was confirmed in vitro. The verified ompC + mimotope constructs were subsequently subcloned into the pYA3422 constitutive expression vector and electroporated into the APEC PSUO78 ∆aroA ∆asd vaccine vector strain. A chicken vaccination–challenge trial was conducted using nine groups of chickens, including an unvaccinated challenged control and an unvaccinated–unchallenged negative control. Each experimental group received a mixture of two recombinant E. coli strains carrying different mimotopes at a dose of 1 × 10⁹ CFU, which were administered orally twice at 16 and 18 weeks of age. Results: Fourteen immunogenic mimotopes corresponding to 13 different C. hepaticus proteins were identified as potential vaccine candidates. The expression of these mimotopes on the surface of the E. coli was successfully demonstrated using the OmpC-mediated surface display system. Of the 14 mimotopes tested, two flagellar-related peptides and one major outer membrane protein (MOMP)-derived peptide elicited significant immune responses and conferred protection against the C. hepaticus challenge. Conclusions: We successfully developed a functional E. coli surface display system that was capable of expressing 12-amino-acid mimotopes of C. hepaticus, providing a robust platform for evaluating vaccine candidates against SLD. Immunogenicity and efficacy studies in chickens demonstrated that three identified mimotopes conferred protection against C. hepaticus colonization of the bile and liver. Future in vivo investigations are necessary to develop and evaluate the immunogenicity and protective efficacy of a multivalent mimotope vaccine consisting of three identified mimotopes against both C. hepaticus and APEC, utilizing the ΔaroA Δasd APEC PSU078 strain as the vaccine vector. Full article

This study proposes a non-invasive, simplified muscle force estimation model (NSMFEM) designed for elderly individuals and stroke patients under slow walking conditions. The model estimates lower limb muscle forces dynamically using only kinematic parameters—with real-time muscle fiber length as the key variable—thus avoiding the limitations of traditional surface electromyography (sEMG)-based approaches such as environmental interference, signal noise, and difficulty in obtaining deep muscle sEMG. A personalized Digital Twin Musculoskeletal Model (DTMSM) was constructed by scaling a reference kinematic model and calibrating muscle origin/insertion markers based on individual anthropometry. Muscle architecture indices were derived from a multiple regression model with publicly available anatomical data. Twelve elderly subjects (eight healthy ESND and four post-stroke ESP) were evaluated at varying walking speeds. Results at slow speeds (X-slow and slow) show strong Pearson correlations between NSMFEM predictions and reference data for the majority of nine representative lower limb muscles (e.g., TFL, Iliacus, Pectineus, Tib_Ant, Soleus); passive forces of TFL, Iliacus, and Vas_Int also correlate strongly. As speed rises, correlations for some muscles (e.g., Vas_Int, Tib_Post) decline, reflecting the growing influence of segmental acceleration and muscle activation—factors omitted in the model. For stroke patient gait (ESP), Spearman analysis indicates maintained strong correlations for affected side muscles Glut_Max1, TFL, Pectineus, and Soleus, supporting the model’s utility in stroke rehabilitation assessment. Overall, NSMFEM offers a practical, sEMG free method for non-invasive dynamic muscle force estimation in slow walking elderly and post-stroke populations, aiding functional assessment and personalized rehabilitation planning. Future efforts will aim to incorporate muscle activation corrections to extend the model to faster walking speeds. Full article

Field-effect transistor (FET) biosensors using graphene have become one of the most promising biosensing platforms for the early diagnosis of diseases with features such as high sensitivity, label-free detection and application compatibility with point-of-care systems. Herein, we critically discuss recent advances in graphene FET (GFET) biosensor development toward clinically relevant biomarkers associated with representative diseases including cancer, neurodegenerative disease, infectious disease, and inflammatory conditions. Recent progress was reviewed to evaluate GFET architectures, surface functionalization methods, and detection quality. The biomarkers explored were clusterin in Alzheimer’s disease, thrombin in coagulopathy, estrogen receptor α (ER-α) in breast cancer, Carcinoembryonic antigen in lung cancer, microRNAs for malignant tumors, exosomes derived from HepG2 for the hepatocellular carcinoma (HCC) cell line, interleukin-6 (IL-6) for chronic obstructive pulmonary disease (COPD), Polyclonal antibodies and antigens (P24) for HIV and prostate-specific antigen for prostate cancer. The developed devices demonstrate ultralow detection limits at femtomolar to attomolar concentrations with the aid of designed antibodies, aptamers and nanomaterials. Herein, this review presents the sensing mechanisms and biomedical application of various GFET platforms, focusing on their emerging potential as next-generation platforms for rapid, non-invasive and point-of-care diagnostics. Full article

Background: Multiple myeloma remains an incurable malignancy in which patients ultimately experience relapses and refractory disease despite therapeutic advances. Triple-class exposed relapsed/refractory MM (TCE/RRMM) patients represent both a population with high unmet clinical needs and a substantial economic burden for the Italian National Health Service (NHS). Recently, BCMA-CD3 bispecific antibodies, including elranatamab and teclistamab, have expanded the treatment options for these patients. This study aimed to evaluate the cost-effectiveness of elranatamab versus teclistamab in adults with TCE/RRMM from the Italian NHS perspective. Methods: A partitioned survival model with three health states—progression-free survival, post-progression survival, and death—was developed over a 25-year lifetime horizon, adopting weekly cycles and a 3% annual discount rate. Clinical data for elranatamab were derived from the MagnetisMM-3 trial, while teclistamab outcomes were estimated through matching-adjusted indirect comparisons using MajesTEC-1 data. Direct medical costs included those associated with drug acquisition and administration, disease management, adverse event management, and end-of-life care. Utility values were obtained from EQ-5D-based assessments in MagnetisMM-3. Deterministic and probabilistic sensitivity analyses were performed to test model robustness. Results: Elranatamab yielded 3.31 life-years and 2.33 QALYs per patient, compared with 1.83 life-years and 1.27 QALYs for teclistamab. Total lifetime costs were lower for elranatamab (EUR 153,337) versus teclistamab (EUR 224,610), generating EUR 71,273 in savings. Thus, elranatamab is considered to be dominant, due to its higher efficacy and lower cost. Furthermore, the robustness of these findings was confirmed through sensitivity analyses. Conclusions: From the Italian NHS perspective, elranatamab represents a clinically superior and economically favorable option for patients with TCE/RRMM. The obtained results support its value and sustainability within the national treatment landscape. Full article

To overcome the drawbacks of conventional wedge cut blasting—high peak particle velocity (PPV), low blasthole utilization, and a high proportion of large fragments—this paper proposes a delayed blasting method for wedge cut blasting. By integrating the rock-fracturing process of wedge cut blasting, the mechanisms of rock breaking and vibration reduction are investigated and confirm the method through field tests. The results indicate that the rock breaking process can be divided into two stages, the stage of fracture propagation and the stage of cavity ejection, and a rock breaking criterion for wedge cut delayed blasting is established. Considering differences in the vibration waveforms generated by different types of cut holes, a vibration waveform fitting method for wedge cut delayed blasting is proposed. Furthermore, the generation time of the blast-induced free surface during the rock breaking process is calculated, and a calculation Equation for the optimal delayed time is derived. Field tests in the Qi Jiazhuang tunnel show that, compared with conventional blasting, the proposed delayed blasting method increases blasthole utilization by 23.8%, reduces the large fragment rate by 67.4%, lowers PPV by 53.7%, and increases the dominant vibration frequency by 42.0%. These results significantly improve the wedge cut blasting performance and construction safety. Full article

As modern power systems grow increasingly complex, there is a pressing need for stability analysis methods capable of handling nonlinear dynamics while providing physically meaningful and reliable stability indices. Port-Hamiltonian (PH) frameworks have emerged as strong candidates in this regard, offering inherently stable formulations, energy-consistent representations, and modular plug-and-play scalability. However, the practical deployment of PH-based stability analysis remains hindered by the absence of reliable, high-fidelity parameter identification methods that rely on sensor measurements to capture system dynamics while remaining compatible with PH model structures. This paper addresses that gap by proposing a comprehensive three-stage data-driven identification framework for PH modeling of synchronous generators—the central dynamic component of any power system. While the IEEE Standard 115 provides established procedures for transient parameter identification, it exhibits fundamental limitations when applied to PH modeling, including single-scenario identifiability constraints, noise-sensitive derivative-based formulations that amplify sensor measurement errors, and the inability to decouple generator-internal damping from grid contributions. The proposed framework resolves these limitations through multi-scenario excitation using sensor-acquired voltage and current signals, derivative-free state consistency optimization, and physics-based regularization that enforces PH structure preservation. Complete identification of eight key parameters (H, D, $X_d$, $X_q$, $X_d^{\prime }$, $X_q^{\prime }$, $T_{do}^{\prime }$, $T_{qo}^{\prime }$) is achieved with errors ranging from 1.26% to 9.10%, and validation confirms RMS rotor angle errors below 1.2° and speed errors below 0.15%, demonstrating suitability for transient stability analysis, passivity-based control design, and oscillation damping assessment. Full article

This paper presents a computational study of wave–bathymetry and wave–structure interaction problems using advanced numerical techniques based on high-fidelity, two-phase Navier–Stokes (TpNS) flow and reduced-order, fully nonlinear potential flow models. For high-fidelity simulations, the TpNS equations are discretized using the finite-element method, with free-surface evolution captured through a hybrid level-set (LS) and volume-of-fluid (VOF) formulation. A monolithic, phase-conservative LS equation is introduced to mitigate mass loss and interface smearing, combined with a semi-implicit projection scheme. Hydrodynamic forces are resolved using a high-order, phase-resolving cut finite-element method (CutFEM), which enables the representation of complex solid geometries within a fixed background mesh. An equivalent polynomial of Heaviside and Dirac distributions ensures accurate evaluation of surface and volume integrals. Hence, no explicit generation of cut cell meshes, adaptive quadrature, or local refinement is required. For reduced-order modeling, a fast regularized boundary integral method (RBIM) is employed to solve the fully nonlinear potential flow. Singular and near-singular integrals are treated using a subtract-and-addition technique based on auxiliary functions derived from Stokes’ theorem, allowing direct application of high-order quadrature without conventional boundary element discretization. An arbitrary Lagrangian–Eulerian (ALE) formulation is adopted to enforce free-surface boundary conditions while avoiding excessive mesh distortion. The proposed approaches are applied to investigate highly nonlinear wave transformation over complex bathymetry and wave-induced dynamics of floating structures, including eddy-making damping effects. Numerical results are validated against experimental measurements. These two modeling approaches represent complementary levels of physical fidelity and computational efficiency, and their systematic comparison clarifies the trade-offs between computational accuracy, efficiency, and cost for practical marine problems. Full article

Background/Objectives: Benefiting from their outstanding tumor-penetrating ability and cytotoxic proteins and cytokines, natural-killer-cell-derived exosomes (NEX) show great potential for cell-free tumor immunotherapy. To meet the clinical tumor therapeutic need, engineered NEX are highly required to further enhance their tumor-tropism and antitumor abilities. Methods: We proposed a NEX engineering strategy, using a structure of AS1411-bivalent-cholesterol (B-Chol) anchor equipped with photosensitizer zinc phthalocyanine (ZnPc) attached on the membrane of NEX to form A-P-NEX. It not only preferably maintains the spatial structure of the AS1411 aptamer via a B-Chol anchor contributing to the tumor-tropism and stability of NEX but also significantly improves the photodynamic therapy (PDT) effect by firmly binding ZnPc in the unique G-quadruplex structure in the AS1411 aptamer. Results: The results showed that A-P-NEX could promote the precise uptake of NEX and ZnPc by tumor cells and produce obvious synergistic NEX-based immunotherapy and PDT upon laser irradiation, demonstrating excellent targeted antitumor effects both in vitro and in vivo. Conclusions: This study demonstrates a reliable NEX engineering strategy and paves the way for developing a useful tumor-tropism PDT method. Full article

The control of surface residual stress is paramount for ensuring the mechanical performance and longevity of machined GH2132 superalloy bolts. However, direct measurement of residual stress remains challenging. This study introduces a novel, efficient approach by establishing a quantitative correlation between Vickers hardness and residual stress based on the energy indentation method. The core hypothesis leverages the principle that residual stress modifies the indentation work; the difference in energy dissipation between stressed and stress-free states provides a direct measure of residual stress. A mathematical model relating hardness (HV) to residual stress (σ) was derived. To validate the model and unravel the underlying microstructural mechanisms, orthogonal cutting experiments were conducted. Comprehensive microstructural characterization using SEM, XRD, and metallography revealed a synchronous relationship between hardness and residual stress. Both properties increased concurrently with greater grain refinement and higher volume fraction/distribution density of carbides and γ’ phases, which impede dislocation motion and introduce micro-strain. The model predictions showed excellent agreement (R² = 92.5%) with X-ray diffraction measurements, confirming its reliability. Furthermore, the influence of cutting parameters (speed V_c, feed f, depth of cut a_p) on residual stress was analyzed. Cutting depth was identified as the most significant factor. An optimal parameter combination (V_c = 20 m × min⁻¹, f = 1 mm × rev⁻¹, a_p = 1.2 mm) was identified to maximize beneficial compressive residual stress, corresponding to the most refined microstructure. This work presents a validated, hardness-based model for residual stress assessment in GH2132 and provides a microstructure-guided pathway for optimizing machining processes to enhance component life. Full article

This paper presents a comprehensive framework for the identification, state estimation, and robust control of a bistable Duffing–Holmes oscillator, validated through an experimental setup. First, to address parametric uncertainty, a Recursive Least Squares Method (RLSM) with a forgetting factor is applied to a filtered model representation, enabling accurate parameter convergence from noisy measurements. Subsequently, a Nonlinear Integral Extended State Observer (NIESO) is designed to reconstruct unmeasured states and estimate total disturbances. A key theoretical contribution is the derivation of explicit gain conditions that guarantee the observer’s stability, overcoming limitations of previous designs. For trajectory tracking, an observer-based backstepping controller is synthesized. Crucially, to bridge the gap between theory and practice, a drift-free integration scheme is implemented to generate feasible position commands for the shake table, preventing actuator saturation. Experimental results confirm the framework’s effectiveness, achieving a 3.7-fold reduction in RMS tracking error compared to open-loop operation, with the tracking error rapidly converging to a small neighborhood within approximately $0.2$ $\mathrm{s}$. Furthermore, the closed-loop system demonstrates superior energy efficiency, requiring significantly lower actuator voltage to sustain stable interwell oscillations. Full article