Search Results (57,222)

This article investigates the use of bent metal strips on the top of a SiO₂ layer for the suppression of spurious modes in temperature-compensated surface acoustic wave (TC-SAW) resonators employing a SiO₂/Cu/128°YX-LiNbO₃ structure. The proposed metal strip method includes two parts: a primary metal strip located at the edge of the interdigital transducer (IDT) aperture region and a secondary metal strip in the gap region. The impact of the geometric parameters of bent metal strips was calculated by the 3D finite element method (FEM), and theoretical simulation results show that this method can effectively suppress the transverse modes and mitigate the gap modes originating from the gap region in conventional TC-SAW resonators. Furthermore, experimental validation further confirms that the proposed method can effectively suppress nearly all spurious modes without degrading the performance of the quality factor. Full article

Sirtuin 1 (SIRT1) is an NAD⁺-dependent deacetylase implicated in various physiological and pathological processes, including cardiovascular diseases. The lead compound for SIRT1, resveratrol (1), as well as natural-derived and synthetic SIRT1-activating compounds demonstrated to exert cardioprotective effects. In the present work, we evaluated a small series of diarylimidazoles, of which 4 emerged, in in vitro enzymatic assays, as an activator of SIRT1 endowed with a similar potency compared with that of 1. Therefore, 4 was subjected to pharmacological investigation, where it was proven to reduce myocardial damage induced by ischemia/reperfusion injury in isolated rat hearts, thus demonstrating its cardioprotective properties. An in silico study suggested the binding mode of this derivative within SIRT1 in the presence of the p53-AMC-peptide. These promising results could pave the way to further expand and optimize this chemical class of new SIRT1 activators as potential cardioprotective agents. Full article

Installing energy storage devices can improve the frequency modulation ability of offshore wind farms to participate in the grid. The lifecycle and wear of energy storage devices are significantly influenced by ambient temperature, charge and discharge rates, cycle depths, and operating environments. To extend the lifecycle and reduce the replacement frequency of these devices, their operation mode must be carefully considered. However, existing energy storage optimization configurations rarely consider these factors, particularly when addressing the frequency stability of offshore wind power systems. To address this gap, an optimization method is proposed for energy storage allocation that incorporates system frequency support, energy storage cost, and the devices’ lifecycle and degradation. This approach ensures a reasonable and efficient allocation of energy storage. Full article

Very-Low Earth Orbit Synthetic Aperture Radar (VLEO SAR) satellites, defined as SAR satellites operating at orbital altitudes 350 km or below, offer distinct technical advantages compared to conventional SAR satellites. Equipped with a high-resolution SAR payload, the Haishao-1 (HS-1) satellite was successfully launched on 4 December 2024. According to publicly available information, the HS-1 satellite represents the world’s first VLEO SAR satellite and has successfully demonstrated 1-m resolution Stripmap mode imaging with continuous azimuth coverage. Through an analysis of the HS-1 satellite’s system parameters and imaging results, this paper comprehensively explores the advantages of VLEO SAR satellites over traditional orbit SAR satellites, particularly in terms of enhanced resolution, reduced payload costs, and improved constellation deployment capabilities. VLEO SAR satellites possess significant advantages, including the potential for higher-resolution imagery and lower-cost payload designs, positioning them for extensive application prospects in fields such as space-based military reconnaissance, natural resource surveying, and natural disaster monitoring. Full article

Predicting the behavior of Internet of Things (IoT) networks under irregular topologies and heterogeneous battery conditions remains a significant challenge. Simulation tools can capture these effects but can require high manual effort and computational capacity, motivating the use of machine learning surrogates. This work introduces an automated pipeline for generating large-scale IoT network datasets by bringing together the Contiki-NG firmware, parameterized topology generation, and Slurm-based orchestration of Cooja simulations. The system supports a variety of network structures, scalable node counts, randomized battery allocations, and routing protocols to reproduce diverse failure modes. As a case study, we conduct over 10,000 Cooja simulations with 15–75 battery-powered motes arranged in sparse grid topologies and operating the RPL routing protocol, consuming 1300 CPU-hours in total. The simulations capture realistic failure modes, including unjoined nodes despite physical connectivity and cascading disconnects caused by battery depletion. The resulting graph-structured datasets are used for two prediction tasks: (1) estimating the last successful message delivery time for each node and (2) predicting network-wide spatial coverage. Graph neural network models trained on these datasets outperform baseline regression models and topology-aware heuristics while evaluating substantially faster than full simulations. The proposed framework provides a reproducible foundation for data-driven analysis of energy-limited IoT networks. Full article

In this study, for the first time, the genes encoding the mammalian steroidogenesis system—cytochrome P450scc (CYP11A1), and its native redox partners adrenodoxin and adrenodoxin reductase—were successfully expressed in the methylobacterium Methylorubrum extorquens. The advantage of using methylobacteria as an expression chassis is that they grow on inexpensive mineral media, use methanol as a carbon and energy source, and do not possess their own sterol catabolism systems. Using recombinant methylobacteria, the valuable steroid pregnenolone was obtained as a sole metabolite from cholesterol. The effect of media composition, bioconversion conditions such as methanol and N-sources content, modes of substrate addition, detergents, methyl-β-cyclodextrin, biomass, and aeration on pregnenolone accumulation was investigated. Under optimized conditions, its yield exceeded 100 mg/L. The results demonstrate a proof of concept relating to the use of bacteria lacking their own steroid degradation systems as microbial chassis for heterologous steroidogenesis systems, including mammalian cytochrome CYP11A1. Full article

DC distribution networks exhibit inherent symmetry in their balanced power distribution and modular structure, offering high operational flexibility and making them particularly suitable for the integration of distributed generation and modern loads. This symmetric framework positions DC networks as a vital component of new power systems and a key development direction for future power supply systems in industrial and mining enterprises. However, pole-to-pole short-circuit faults disrupt this symmetry, characterized by low system damping, high fault currents, and extremely rapid current rise rates, which pose serious threats to system security and necessitate ultra-fast fault clearance. To address this issue, this paper proposes a novel pilot protection scheme inspired by symmetry principles, based on the slope of the line-mode current for pole-to-pole short-circuit faults in DC distribution networks. First, an equivalent circuit of the system before converter blocking under a pole-to-pole fault is established, and an analytical expression of the fault current is derived, incorporating symmetric analysis of modal components. Subsequently, the variation trends, amplitudes, and phase characteristics of the fault current under faults occurring in different zones of the DC line are analyzed from the perspective of modal symmetry, highlighting the symmetric and asymmetric behaviors of line-mode and zero-mode currents. Furthermore, considering the distinct symmetric properties of these currents during lightning disturbances and pole-to-pole faults, the least squares method is employed to perform linear fitting on the line-mode current, thereby capturing its symmetric variation trend. A pilot protection scheme utilizing the slope of the line-mode current is then proposed, leveraging symmetry in fault discrimination. Finally, simulation models built in MATLAB/Simulink (R2022a) are used for validation. The results demonstrate that the proposed protection method can quickly identify faults within 1.5 ms while exhibiting strong tolerance to a 20 Ω transitional resistance and 50 dB signal noise, indicating good feasibility and broad applicability, with symmetry-based analysis enhancing robustness. Full article

This study reexamines Learner Englishes (LEs)–New Englishes (NEs) continuum by considering intervarietal variation, mode differences, and multiple linguistic levels. Relying on comparable written and spoken corpus data, we investigate the valency patterns and senses of the verb TAKE across two LEs (Mainland Chinese English (MCE) and Belgian French-speaking English (BFE)) and two NEs (Singapore English (SgE) and Hong Kong English (HKE)) within the Extra- and Intra-territorial Forces (EIF) Model. The study examines whether internal linguistic factors, namely, mode (writing and speech) and linguistic levels (valency patterns and senses), influence the variety positioning along the LEs-NEs continuum and whether this positioning reflects the expected proximity cline to native English (NativeE) (BFE > MCE > HKE > SgE) established within the EIF Model. Our quantitative results reveal that individual varieties intermingle depending on mode and linguistic levels rather than occupying stable positions along the LEs-NEs continuum. Dendrogram analyses yield distinct variety clustering patterns that contradict the expected proximity cline to NativeE. Qualitatively, we identify some shared linguistic features across LEs and NEs that suggest common underlying language learning strategies. These results contribute to variationist linguistics by demonstrating that English varieties exhibit dynamic development trajectories shaped by language-internal factors (e.g., mode and linguistic levels). We propose refining the EIF Model to incorporate language-internal dimensions, thereby bridging the gap between LEs and NEs through a more nuanced theoretical framework. Full article

In extremely harsh high-temperature environments in aerospace, industrial manufacturing and other fields, traditional ultrasonic temperature measurement technology has certain limitations. This paper proposes a differential single crystal sapphire ultrasonic temperature measurement method based on the magnetostrictive effect. This method abandons the traditional sensitive flexural structure and uses two single-crystal sapphire waveguides of the same material, same diameter, and slightly different lengths as sensing elements. By measuring the time delay difference between their end-face echoes, the sound velocity is inverted and the temperature is measured. COMSOL multi-physics v6.1 simulation was used to optimize the bias magnetic field design of the magnetostrictive transducer, which improved the system’s energy conversion efficiency and high-temperature stability. Experimental results show that in the range of 300–1200 °C, the sensor delay increases monotonically with increasing temperature, the sound speed shows a downward trend, and the repeatability error is less than 5%; the differential processing method effectively suppresses common mode noise in the range of 300–700 °C, and still shows high sensitivity above 800 °C. This research offers a technical solution with high reliability and accuracy for temperature monitoring in extreme environments such as those characterized by high temperatures and high pressures. Full article

With an emphasis on common-mode voltage (CMV) and leakage current suppression, this research offers a thorough examination of three-phase, two-level buck inverter topologies for transformerless (TL) grid-tied photovoltaic (PV) systems. A comprehensive classification and comparative evaluation of modern voltage-source inverter (VSI) and current-source inverter (CSI) topologies, such as H6, H7, H8, H10, and hybrid setups, constitute the paper’s main contribution. The main conclusions show that CSIs naturally offer better leakage current suppression, albeit at the expense of cost and complexity, while sophisticated VSIs (such as specific H8 and H10 topologies) in conjunction with specialized modulation techniques (like modified discontinuous PWM) provide balanced performance. The study finds intriguing research possibilities for further work in this area and indicates that the ideal topology depends on the specific application. Full article

Bearing fault diagnosis encounters limitations including insufficient accuracy, elevated model complexity, and demanding hyperparameter optimization. This research introduces a diagnostic framework combining variational mode decomposition (VMD) and fast Fourier transform (FFT) for extracting comprehensive temporal–spectral characteristics from vibration data. The methodology employs a hybrid deep learning architecture integrating convolutional neural networks (CNNs) with Transformers, where CNNs identify local features while Transformers capture extended dependencies. Meta-learning-enhanced Bayesian optimization and HyperBand (Meta-BOHB) is utilized for efficient hyperparameter selection. Evaluation on the Case Western Reserve University (CWRU) dataset using 5-fold cross-validation demonstrates a mean classification accuracy of 99.91% with exceptional stability (±0.08%). Comparative analysis reveals superior performance regarding precision, convergence rate, and loss metrics compared to existing approaches. Cross-dataset validation using Mechanical Fault Prevention Technology (MFPT) and Paderborn University (PU) datasets confirms robust generalization capabilities, achieving 100% and 98.75% accuracy within 5 and 7 iterations, respectively. Ablation studies validate the contribution of each component. Results demonstrate consistent performance across diverse experimental conditions, indicating significant potential for enhancing reliability and reducing operational costs in industrial fault diagnosis applications. The proposed method effectively addresses key challenges in bearing fault detection through advanced signal processing and optimized deep learning techniques. Full article

In the literature, there is a scarcity of studies examining the combined effects of vortex-induced vibrations (VIV) and surface roughness on a bluff body. This paper contributes to the limited studies and literature on VIV by highlighting the pronounced influence of roughness on the vortex formation modes of a circular cylinder forced to oscillate with respect to the freestream. The numerical approach utilizes a purely Lagrangian description through the discrete vortex method with a roughness model. Recent results obtained by our research group have shown that a two-dimensional roughness model is more sensitive than a simple turbulence model in capturing nonlinear multi-physics phenomena with a variety of applications in different engineering areas. In particular, the control of drag force and vortex shedding frequency can be studied based on the expected physics of viscous flow. In the present paper, the dimensionless oscillation amplitude is fixed at A/D = 0.13 (D is the outer cylinder diameter), and the cylinder forcing frequency varies in the range of 0.04 ≤ f_o ≤ 0.80 at a high Reynolds number value of Re = 1.0 × 10⁵. Three relative roughness sizes are chosen, i.e., ε/D = 0.001, 0.0045, and 0.007 (ε is the average roughness). The test cases without roughness effects are compared to experimental visualizations to capture two basic anti-symmetrical modes, namely the A-I and A-IV modes, the symmetric S-I (Type-I) mode, and the Chaotic mode categorized as C-I. Our strategy to identify these wake modes verifies the synchronization between the vortex shedding frequency f_CD, interpreted from temporal history of the drag force on an oscillating cylinder, and the body forcing frequency. In the test cases using the roughness model, it is possible to identify a desynchronization between the frequencies f₀ and f_CD as well as significant variations in the drag force. The roughness effect also provokes a regime of vortex formation, here classified as “A-IV mode with coalescence”. Full article

This research explored the technical feasibility of creating a controlled chemical composition for Fe-Ni alloys using a Directed Energy Deposition (DED) arc metal additive manufacturing (AM) process in its twin wire feed mode. This method employs two independently controlled arc power sources to feed two different wires into a single torch, creating a unified melt pool protected by a single shielding gas nozzle. The research focused on producing Invar 36 (EN 1.3912), a low thermal expansion alloy, by melting and mixing steel and Ni-Fe wires using Cold Metal Transfer-Twin (CMT-Twin) technology. This method enables the fabrication of multi-material components featuring regions with distinct chemical compositions, including functional gradients, with the aim of leveraging the advantageous properties of each individual material. Furthermore, this new manufacturing route offers the possibility to avoid using some alloying elements, such as Nb, an element considered a critical raw material (CRM) in the European Union (EU). Microstructure and mechanical properties were analyzed and compared to commercial Invar 36 obtained by DED-Arc with single wire as well as the effect of the absence of Nb. Results showed that the in situ obtained alloy had 10–20% lower strength but exhibited 10–15% higher elongation compared to the commercial alloy, making it a promising alternative for advanced manufacturing by using this new manufacturing route. Full article

This study develops an interpretable and calibrated XGBoost framework for probabilistic slope stability assessment using a 627-case database of circular-mode failures. Six predictors, namely, unit weight (γ), cohesion (c), friction angle (φ), slope angle (β), slope height (H), and pore-pressure ratio (r_u), were used to train a gradient-boosted tree model optimized through Bayesian hyperparameter search with five-fold stratified cross-validation. Physically based monotone constraints ensured that failure probability (P_f) decreases as c and φ increase and increases with β, H, and r_u. The final model achieved strong performance (AUC = 0.88, Accuracy = 0.80, MCC = 0.61) and reliable calibration, confirmed by a Brier score of 0.14 and ECE/MCE of 0.10/0.19. A 1000-iteration bootstrap quantified both epistemic and aleatoric uncertainties, providing 95% confidence bands for P_f-feature curves. SHAP analysis validated physically consistent influence rankings (φ > H ≈ c > β > γ > r_u). Predicted probabilities were classified into Low (P_f < 0.01), Medium (0.01 ≤ P_f ≤ 0.10), and High (P_f > 0.10) risk levels according to geotechnical reliability practices. The proposed framework integrates calibration, uncertainty quantification, and interpretability into a comprehensive, auditable workflow, supporting transparent and risk-informed slope management for infrastructure, mining, and renewable energy projects. Full article

Analysis of nonlinear plasma waves, formulated and applied for ionospheric HF heating experiments, indicates that Langmuir/upper hybrid waves excited by parametric instabilities can evolve into traveling solitary waves accompanied by self-induced cavitons. To explore these cavitons, a digisonde operating in fast mode was utilized. Significant results were observed in ionograms recorded two minutes after the activation of the O-mode heater. These ionograms displayed two distinct bumps in the virtual height spread, located slightly below both the HF reflection height and the upper hybrid resonance height. It is notable that these heights are also slightly below the excitation regions where Langmuir/upper hybrid Parametric Decay Instabilities (PDIs) are typically generated by an O-mode HF heater. These observations correlate with the theory and provide valuable insights into the dynamics of nonlinear plasma waves and their interaction with the ionosphere during HF heating experiments. Full article