Search Results (12,710)

The application of plain bearings has become very famous in planetary gear stages in recent years. To improve load-carrying capacity, this study investigates a design method for axial profiling in which a sixth-order polynomial is iteratively derived from the curve of local minimum film thickness for each axial grid position. Two load cases with specific bearing loads of 12.0 MPa and 6.0 MPa at 0.5 m/s are considered for profile design. Calculation results and computational effort of strategies assuming rigid or elastic geometries during the optimization are compared. Results indicate that the consideration of deformation is already necessary in the design phase and a maximization of minimum film thickness leads to much higher load-carrying capacity than the minimization of the maximum film pressure. Furthermore, the impact of the lube oil pocket position on oil flow rate is experimentally and theoretically investigated to identify the optimization potential of this parameter. Results show that the oil flow varies by the factor of three if the lube oil pocket is shifted incrementally over an angular span of 180° outside the load zone. The results and possible extensions are critically discussed under the consideration of practically relevant restrictions in mechanically highly loaded planetary gearboxes. Full article

When a new vehicle is being created or developed, many technical parameters that affect dynamic characteristics must be investigated not only on a theoretical level, but also by natural experiments. Especially one of the most important characteristics for a vehicle that can tilt is tire–road contact, which later helps to calculate and simulate different driving conditions in different driving scenarios, applying internal and external forces. This paper presents a unique construction of a three-wheeled tilting vehicle prototype, tire–road contact determination, and evaluation of vehicle behaviour using the Pacejka tire model. To achieve this, the tire and road surface area were investigated. Using the computed method, experimentally determined contact areas were refined and compared with the actual measured. Determined tire–road contact areas were evaluated by applying dynamic external forces for further investigation. Selected a scenario to predict the behavior of a three-wheeled tilting vehicle and the force distribution during tilting, then determined certain vehicle parameters in the static position (load distribution, tire–road contact areas). The inclusion of asymmetric front-left and front-right tire loads under tilt resulted in observable differences in force distribution. The inner front tire unloaded while the outer tire gained load, introducing asymmetry in both lateral and longitudinal forces. This behaviour was not captured in the symmetric model. Full article

Cold-atom absolute gravimeters are widely used for measuring the acceleration of gravity, yet their sensitivity is often limited by ground vibrations. Existing vibration compensation algorithms struggle to strike a balance between search accuracy and computational efficiency and are prone to local optima. Here, we propose an improved whale optimization algorithm (IWOA) to address these issues. By combining Logistic-LHS (Latin hypercube sampling) chaotic initialization, adaptive adjustment, and a Gaussian mutation operator to prevent premature convergence, IWOA achieves higher search efficiency and superior sensitivity than traditional algorithms. The method is validated through multiple simulation studies and further assessed experimentally on the NIM-AGRb-1 cold-atom gravimeter system. The results show that IWOA reduces the uncertainty of the fitted phase parameter by 66%. The Pearson correlation between atomic transition probability and the calculated phase increases to a maximum of 0.98, and the gravity sensitivity improves to 47 $\mathsf{\mu }\mathrm{G}\mathrm{a}\mathrm{l}/\sqrt{\mathrm{H}\mathrm{z}}$ when the evolution time T is 80 ms. Full article

Background: Cancer patients are highly susceptible to microbial infections due to immune suppression, necessitating therapeutic strategies that integrate anticancer efficacy with effective antimicrobial intervention. Chalcone-derived nitrogen-fused heterocycles represent a promising platform for developing multi-target agents with relevance to antimicrobial drug delivery, particularly for localized infections. Methods: A series of chalcone-based pyrazoline-thiadiazole nitrogen-fused azole hybrids was synthesized via thiosemicarbohydrazide-functionalized intermediates and fully characterized. Antiproliferative activity was evaluated against MCF-7, HepG-2, HeLa, and HCT-116 cell lines, alongside selectivity toward WI-38 normal fibroblasts. Antibacterial, antibiofilm, and in vivo efficacy were assessed against methicillin-resistant Staphylococcus aureus (MRSA USA300) and Acinetobacter baumannii AB5057. Mechanistic investigations included cell-cycle analysis, apoptosis assays, ERK2, RIPK3, p53, BAX/Bcl-2 quantification, DNA gyrase inhibition, molecular docking, molecular dynamics simulations, and density functional theory calculations. Results: Compound 13 exhibited potent cytotoxicity, particularly against MCF-7 (IC₅₀ = 3.87 ± 0.2 µM), outperforming doxorubicin (IC₅₀ = 4.17 ± 0.2 µM), with high selectivity indices (SI = 10.7 for MCF-7). Mechanistically, compound 13 induced G₂/M arrest (40.16% vs. 14.15% control), increased apoptosis to 32.89%, up-regulated ERK2 (3.17-fold), RIPK3 (11.97-fold), and p53 (3.54-fold), and markedly increased the BAX/Bcl-2 ratio (~42-fold). Compounds 7 and 13 displayed bactericidal activity against MRSA and A. baumannii (MIC/MBC = 10 mg/mL), potent antibiofilm effects, and significant in vivo efficacy in an MRSA skin infection model. Compound 13 reduced bacterial load by ~5 log units, outperforming vancomycin. DNA gyrase inhibition (IC₅₀ = 17.10 ± 0.17 µM) and computational studies supported target engagement. Conclusions: Pyrazoline-thiadiazole-based nitrogen-fused azole hybrids, particularly compound 13, demonstrated quantifiable anticancer and antimicrobial efficacy with strong in vivo validation, supporting their potential as multi-target candidates relevant to antimicrobial drug delivery in infection-prone cancer patients. Full article

Static var compensators (SVCs) employing thyristor-controlled reactors (TCRs) are widely used to mitigate power-factor degradation by absorbing lagging reactive power. Conventional TCR control schemes use real-time firing-angle calculations, which require intensive computation and make practical real-time implementation difficult, especially under grid frequency variations. To address this issue, this paper proposes a grid-frequency-independent SVC control method based on a synchronous phase carrier technique that directly determines thyristor firing instants without explicit firing-angle calculations. The proposed control strategy uses a carrier signal synchronized with the system phase, enabling real-time TCR operation without relying on nominal grid frequency. The effectiveness of the proposed method is evaluated through simulations and hardware experiments. The results show that the proposed method ensures reliable real-time operation and improves the power factor without requiring firing-angle computation. Furthermore, stable performance under grid-frequency variations confirms the robustness of the proposed method. The proposed approach provides a practical and reliable solution for mitigating power-factor degradation in modern power systems. Full article

In this study, we develop and investigate a novel fractional discrete-time computer virus dynamics model in two dimensions with a memristive nonlinear coupling mechanism. The memristor introduces nonlinearity by having memory regulation that depends on the state and enhances the propagation dynamics of virus spread. By investigating both matching and non-matching fractional orders, it is then possible to derive useful knowledge with respect to cooperating roles in terms of fractional memory and memristive effects. The complexity behind it is confirmed via 3D phase portraits, bifurcation analysis with LE_max calculation, 0–1 chaos test, and SE complexity. Numerical results reveal rich dynamical phenomena, including periodic oscillations, quasi-periodicity, and strong chaos. In fact, positive LE_max values, Brownian-like trajectories, and high-complexity SE corroborate the chaotic nature of the regimes. Thereby, the fractional-order separation in noncommensurate conditions is a marker of chaotic motion, magnified in the emergently high-dimensional space introduced by the memristive element. As these results indicate that the derivative model proposed here provides an excellent fit for complex viruses present in scaffolds, it may prove to be a useful modeling tool. Full article

Human reliability analysis of the human–computer interaction process between users and systems is critical because human error can introduce significant system risks. Interaction systems designed with human reliability analysis can reduce human error. This study proposed a research methodology for analyzing human error to design interactive systems that align with users’ cognitive demands. First, the cognitive reliability and error analysis method (CREAM) is used to investigate cognitive function failures and determine the nominal cognitive failure probability. Next, fuzzy comprehensive evaluation (FCE) is used to assess the level of common performance conditions (CPCs). Subsequently, the decision-making trial and evaluation laboratory (DEMATEL) method is employed to compute the factor centrality weights of CPCs and human intrinsic factors (HIFs). The interactions among CPCs are analyzed, leading to the determination of cognitive impact weights. Then, the cognitive failure probability is calculated by combining factor centrality weights and cognitive impact weights. Finally, error causes are analyzed to propose optimization strategies and implement design improvements. An in-vehicle information system was used to validate the proposed approach. The findings revealed that this method effectively minimizes cognitive failure probability during system interaction. It also identifies the causes of human error in human–computer interactions and offers a systematic strategy to enhance human reliability in interaction design. Full article

Electrochromic devices have emerged as promising candidates for non-emissive displays due to their particular photoelectric performance in complex lighting environments. They exhibit considerable potential in emerging fields such as Internet of Things terminals, flexible wearables and human–computer interaction interfaces. In this study, we developed a low-power electrochromic display based on a Pt/FTO (Fluorine doped tin oxide) electrocatalytic counter electrode and a Poly(vinylidene fluoride-co-hexafluoropropylene) (PVDF-HFP) porous gel electrolyte. The Pt catalyst enhances Br⁻/Br³⁻ redox reactivity, which reduces the driving voltage from 2 V to 1 V, and accelerates the electrode reaction kinetics. It is systematically explained by the Density Functional Theory (DFT) calculations and electrochemical characterization. Furthermore, we demonstrate a proof-of-concept multicolor display incorporating the electrocatalytic counter electrode with various viologen derivatives. This approach provides a significant advancement toward next-generation high-performance displays and is supportive of the development of energy-efficient optoelectronic devices. Full article

In the present work, a novel series of eleven sulfonate derivatives with potent inhibitory activity against butyrylcholinesterase (BChE) is reported. Of these, compounds 2-[(E)-(2-Benzoylhydrazinylidene)methyl]phenyl 5-(dimethylamino)naphthalene-1-sulfonate (5c, IC₅₀ = 1.11 µM) and tert-butyl (2E)-2-[(2-{[5-(dimethylamino)naphthalene-1-sulfonyl]oxy}phenyl)methylidene]hydrazine-1-carboxylate (5b, IC₅₀ = 11.51 µM) exhibit stronger inhibitory activity than rivastigmine, the reference compound, and exhibit high selectivity for BChE over AChE (e.g., selectivity index 57 for 5c). Interestingly, compound 5c also exhibited anti-inflammatory effects, which is important for potential therapeutic applications, especially in Alzheimer’s disease. These new compounds were designed through a structure-based approach using molecular modeling techniques (docking, molecular dynamic (MD) simulations, and QTAIM (quantum theory of atoms in molecules) calculations). The most promising compounds show no detectable toxic effects and satisfy Lipinski’s rule of five, indicating that they represent attractive starting structures for the design of new derivatives acting as specific BChE inhibitors. In addition, our results indicate that relatively simple computational techniques such as docking calculations and toxicity prediction programs can be valuable when properly used in the search of new candidates for this particular target. Docking calculations show that the more active compounds of this series reach the bottom region of the gorge interacting with residues within the active site of BChE. However, our data further suggest that the use of more precise techniques, such as MD simulations and QTAIM analysis, is necessary to obtain detailed insight into ligand–enzyme interactions. Regarding QTAIM calculations, they demonstrate that such computations are very useful to evaluate the molecular interactions of the different molecular complexes. In summary, we report a new series of sulfonate derivatives as promising starting structures for the development of new selective BChE inhibitors. Full article

Based on the Direct Probability Integral Method (DPIM), this study investigates the global seismic reliability of reinforced concrete (RC) frame structures considering the randomness of material parameters and the non-stationarity of ground motions. A doubly non-stationary ground motion model is established using evolutionary power spectrum theory combined with the spectral representation–stochastic function method. A dimensionality reduction technique is adopted to generate ground motion samples compatible with the design response spectrum. A finite element model of the RC frame is developed in Abaqus. Modal analysis and deterministic time history analysis are conducted to obtain the dynamic characteristics and seismic responses of the structure. Based on 600 representative ground motion time histories generated using the maximum frontier (MF) discrepancy sampling method, nonlinear time history analyses are performed. The DPIM is then employed to calculate the statistical characteristics of structural responses and quantify response variability, enabling a rational evaluation of the structural safety margin. Finally, based on the equivalent extreme value event theory and DPIM, the reliability of the structure under a single failure mode and the global reliability under multiple failure modes are computed. The results show that the global reliability of the structure is 82.088%, which is significantly lower than that of any single failure mode. This study provides a quantitative reference for evaluating the global seismic reliability of RC frame structures subjected to nonstationary seismic excitation. Full article

Acinetobacter baumannii (A. baumannii) represents a major threat because of its multidrug resistance, achieved through its ability to control virulence, and its mechanisms of drug efflux resistance. In this study, we used a combined experimental–computational approach to create and evaluate antimicrobial peptides that targeted the two essential pathogenic proteins, BfmR and AbaQ. The genomic analysis of a clinical isolate showed an extensive resistome and virulence profile, which matched high-risk global lineages. This study conducted molecular docking of an experimental AMP (cathelicidin KR-12 screened from the literature) and a rationally designed synthetic AMP (modified KR-12 analog) with pathogenic proteins, followed by 200 ns molecular dynamics simulations to evaluate both the binding stability and inhibitory potential of the compounds. The disk diffusion assay and microdilution assay were performed against A. baumannii. The study used comparative trajectory analyses, including RMSD, RMSF, radius of gyration, solvent-accessible surface area, principal component analysis, and MM-PBSA free energy calculations, to show that the synthetic AMP created stable electrostatic and hydrogen-bond networks, which caused conformational locking, and reached lower energy states than the experimental peptide. The synthetic AMP showed significant inhibition in validation in vitro. Contrastingly, the experimental AMP had transient interactions and no specificity. The study demonstrates that rationally designed AMPs have therapeutic potential, while the results create a reliable in silico framework to combat multidrug-resistant A. baumannii. Full article

The common metabolic disorder, lactose intolerance, is often treated with oral lactase enzyme supplements, which can frequently cause gastrointestinal instability. This work utilizes Malbranchea cinnamomea’s AA9 lytic polysaccharide monooxygenase (LPMO) to target β-lactose (β-lactose) in an investigation of a new enzymatic approach for lactose breakdown. Potential possibilities for lactose breakdown are AA9 LPMOs, copper-dependent enzymes that oxidatively cleave glycosidic bonds in polysaccharides. We employed a combined in silico method that incorporated molecular docking, density functional theory (DFT) calculations, and molecular dynamics (MD) simulations. Docking studies revealed that β-lactose formed hydrogen bonds with key residues SER100, ASN54, and ARG56, exhibiting a greater binding affinity (−5.4 kcal/mol) toward LPMO compared to the control citric acid (−4.9 kcal/mol). Upon DFT analysis, (LPMO) showed excellent stability and appropriate reactivity for enzyme interaction. The higher stability of the LPMO-β-lactose complex was highlighted by MD simulation over 100 ns, which showed lower root mean square deviation (RMSD) and root mean square fluctuation (RMSF) values, greater structural compactness, and reduced solvent accessibility when compared to the control. These collective findings suggest that β-lactose interacts efficiently with the AA9 LPMO active site, supporting its potential as a novel enzymatic target for lactose degradation. This computational study provides a theoretical foundation for developing alternative therapeutic strategies for lactose intolerance, though further in vitro and in vivo investigations are required to validate these findings. Full article

In this study, variational Bayesian inference (VBI) with Gaussian mixture models is applied to update models of nonlinear structures, and then, the calibrated model is employed to estimate the failure probability of structures using a subset simulation (SS) algorithm. To improve the computation efficiency of probabilistic nonlinear model updating, a Gaussian Process (GP) model is used to construct a surrogate likelihood function in Bayesian inference using an active learning algorithm, and then, Gaussian mixture models (GMMs) are employed to approximate the unknown posterior probabilistic density functions (PDFs) of model parameters. The optimized hyperparameters of GMMs can be obtained by maximizing the evidence lower bound (ELBO), and the stochastic gradient search method is used to solve this optimization problem. Based on the optimized hyperparameters, the posterior distributions of model parameters can be approximated using a combination of multiple Gaussian components. Subsequently, the SS algorithm is used to calculate the earthquake-induced failure probability of structures based on the calibrated nonlinear model. To verify the feasibility and effectiveness of the proposed method, a numerical simulation of a two-span bridge structure subjected to seismic excitations was developed. Moreover, the proposed strategy is further applied to estimate the failure probability of a scaled monolithic column structure subjected to bi-directional earthquake excitations. Both numerical and experimental results indicate that the proposed method is feasible and effective for probabilistic nonlinear model updates, and the updated model can significantly enhance the accuracy of structural failure probability predictions. Full article

Based on density functional theory, the structural, mechanical, and photoelectric properties of the perovskite material Cs₂SeCl₆ were systematically studied under pressures ranging from 0 to 50 GPa. Analysis of structural parameters indicates that the lattice constant, unit cell volume, and bond length decrease progressively with increasing pressure. Notably, the material maintains structural stability across the entire pressure range. Electronic property calculations show that Cs₂SeCl₆ retains an indirect band gap under pressure, with the band gap value monotonically decreasing as pressure increases. The orbital contributions remain almost unchanged at different pressures. The conduction band is mainly composed of Cl-p and Se-p orbitals, while the valence band is dominated by Cl-p orbitals. The analysis of the effective mass indicates that the transport capability of charge carriers is enhanced under compression. Mechanical stability and ductility were evaluated by calculating the elastic constants and derived mechanical moduli, confirming that the material remains mechanically stable under high pressure. Optical properties were investigated by computing the dielectric function, reflectivity, refractive index, optical absorption coefficient, and extinction coefficient. Collectively, the findings of this work demonstrate that the pressurized Cs₂SeCl₆ exhibits excellent structural robustness, improved charge transport, and promising photoelectric performance, making it a strong candidate for applications in solar cells and other photoelectronic devices. Full article

This paper proposes a multimodal fusion-based localization state evaluation algorithm for a mobile RF power supply. The algorithm computes the information entropy between point cloud data acquired by the laser sensor on the mobile RF power supply platform and a preconstructed prior grid map; a higher entropy score indicates more accurate localization. Meanwhile, IMU/odometry data fusion is performed by estimating the platform pose from the localization system at consecutive timestamps, and then calculating the differences in Euclidean distance and rotational attitude between this estimated pose and the poses output by the IMU and odometer at the same timestamps. By jointly considering static and dynamic conditions, the laser point cloud matching scores are integrated with the IMU/odometry fusion results to obtain the final localization state evaluation. Experimental results demonstrate that the proposed algorithm can accurately characterize the localization state of the intelligent RF power supply positioning system, achieving an evaluation accuracy of 99%. Full article