Search Results (91)

With the large-scale integration of renewable energy and the increasing use of power electronics, the issue of wide-band oscillations in power grids has become increasingly prominent. The scarcity and uneven distribution of oscillation samples pose significant challenges for training data-driven models, and traditional generative models struggle to ensure fidelity in both time and frequency domains. To address this, this paper proposes a Time–Frequency Fusion Generative Adversarial Network (TFF-GAN) for generating power grid oscillation risk scenarios. The method constructs a dual-path generation and discrimination framework, where the generator decomposes the signal using Short-Time Fourier Transform (STFT), with time-domain features extracted by a convolutional neural network (CNN) and frequency-domain features extracted from the STFT representation by a dedicated spectral network. These features are then fused using a U-Net structure. The discriminator simultaneously evaluates the authenticity of both the time-domain waveform and the frequency-domain spectrum. A composite loss function, incorporating time-domain loss, frequency-domain loss, and adversarial loss, is used for joint optimization. Experimental results demonstrate that the proposed method generates oscillation scenarios with high fidelity in both time-domain waveforms and frequency-domain spectra, effectively supporting power grid oscillation risk assessment and control strategy validation. Full article

Studying the mechanisms by which Gram-negative heterotrophic bacteria transition from active metabolism to dormancy is an important task, as it is directly related to the problem of bacterial antibiotic resistance and the spread of nosocomial infections. Using electron microscopy, microbiology, and molecular modeling, we investigated the dose-dependent mechanisms of action of 4-hexylresorcinol (4HR), a chemical analog of the anabiosis autoinducer, on the cell membranes of Gram-negative bacteria (using Escherichia coli as an example), leading to the formation of stressed, dormant, and mummified cells. It was shown that 4HR penetrates membranes equally easily both as single molecules and as micelles, distributing itself across the membrane so that the hydrocarbon radicals are aligned parallel to the lipid tails. When micelles penetrate the membrane, uneven distribution of 4HR within and between leaflets occurs, as well as lipid redistribution within the membrane, leading to the appearance of a third peak on the phospholipid electron density profile and a third black band in the membrane region in TEM images of such cells. At 4HR concentrations in solution of 200 µM, its micelles cover the cell membranes in a thick layer, penetrate into the membrane, and completely saturate it. Even higher concentrations create agglomerates or actually micellar arrays within the cell membranes, leading to cell death through mummification. Full article

Objectives: This study evaluated and compared the sealing ability and elemental composition of a resin-based endodontic sealer (AH Plus) used with three root canal obturation techniques: single cone (SC), lateral compaction (LC), and warm vertical condensation (WVC). The investigation focused on microstructural characteristics, interfacial integrity, and elemental distribution within filled root canals. Material and Methods: Sixty extracted single-root teeth were instrumented using the ProTaper Gold system and randomly assigned to three groups (n = 20) according to the obturation technique. The AH Plus Jet sealer was applied in all cases. Following obturation, samples were subjected to radiographic investigation and analyzed using optical microscopy and scanning electron microscopy (SEM) coupled with energy-dispersive X-ray spectroscopy (EDX) to assess the sealing performance and chemical composition. Results: Radiographic and microscopic assessments indicated that the SC method showed strong gutta-percha adhesion to dentin with a thin cement layer, whereas WVC provided excellent adaptation and penetration of gutta-percha. The LC technique demonstrated good adhesion but displayed occasional structural irregularities. SC has the thicker adhesion layer with uneven distribution regarding coronal, median, and apical, regions ranging from 45 to 80 μm, while WVC ensures a thin and uniform sealing layer of about 35 μm in all regions. SEM and EDX analyses detailed the interfacial microstructure and confirmed the presence of carbon (C), oxygen (O), calcium (Ca), zinc (Zn), barium (Ba), and sulfur (S) across all groups. Conclusions: All three obturation techniques (SC, WVC, LC) achieved effective sealing when combined with the AH Plus sealer. The main difference between the methods consists of the sealer layer thickness and its even distribution regarding gutta-percha cones. Full article

In this work, nickel oxide nanoparticles (NiO NPs) were synthesized sonochemically in the ionic liquid 1,2-(propanediol)-3-methylimidazolium hydrogen sulfate ([PDOHMIM⁺][HSO₄⁻]) at different loadings (8 wt.%, 15 wt.%, and 30 wt.%), and subsequently coated with polyethylene glycol (PEG). Structural characterization (XRD, FTIR, TEM, TGA) confirmed a cubic NiO spinel phase with an average crystallite size of ~8 nm, which increased to 20–28 nm after PEG coating. Electrical measurements (100 Hz–1 MHz) showed that AC conductivity (σAC) increased with both frequency and NiO content, whereas the dielectric constant (ε′) and loss tangent (tan δ) decreased with frequency. DFT calculations (B3LYP/6–311+G(2d,p)) on the [PDOHMIM⁺][HSO₄⁻] ion pair showed that there were strong hydrogen bonds, an uneven charge distribution, and stable electrostatic interactions that help keep NiO NPs stable and spread them evenly in the ionic liquid. In general, both experimental and theoretical studies show that PEG-coated [NiO NPs + IL] nanostructures exhibit improved dielectric stability, enhanced interfacial polarization, and tunable electronic properties. Full article

The Internet of Medical Things (IoMT) with edge computing provides opportunities for the rapid growth and development of a smart healthcare system (SHM). It consists of wearable sensors, physical objects, and electronic devices that collect health data, perform local processing, and later forward it to a cloud platform for further analysis. Most existing approaches focus on diagnosing health conditions and reporting them to medical experts for personalized treatment. However, they overlook the need to provide dynamic approaches to address the unpredictable nature of the healthcare system, which relies on public infrastructure that all connected devices can access. Furthermore, the rapid processing of health data on constrained devices often leads to uneven load distribution and affects the system’s responsiveness in critical circumstances. Our research study proposes a model based on AI-driven and edge computing technologies to provide a lightweight and innovative healthcare system. It enhances the learning capabilities of the system and efficiently detects network anomalies in a distributed IoMT network, without incurring additional overhead on a bounded system. The proposed model is verified and tested through simulations using synthetic data, and the obtained results prove its efficacy in terms of energy consumption by 53%, latency by 46%, packet loss rate by 52%, network throughput by 56%, and overhead by 48% than related solutions. Full article

Background: Pre-retrofit auditing and pre-demolition auditing (PRA/PDA) are important in material reuse, waste reduction, and regulatory compliance in the building sector. An emphasis on sustainable construction practices has led to a higher requirement for PRA/PDA. However, traditional auditing processes demand substantial time and manual effort and are more easily to create human errors. As a developing technology, artificial intelligence (AI) can potentially assist PRA/PDA processes. Objectives: This scoping review aims to review the potential of AI in assisting each sub-stage of PRA/PDA processes. Eligibility Criteria and Sources of Evidence: Included sources were English-language articles, books, and conference papers published before 31 March 2025, available electronically, and focused on AI applications in PRA/PDA or related sub-processes involving structured elements of buildings. Databases searched included ScienceDirect, IEEE Xplorer, Google Scholar, Scopus, Elsevier, and Springer. Results: The review indicates that although AI has the potential to be applied across multiple PRA/PDA sub-stages, actual application is still limited. AI integration has been most prevalent in floor plan recognition and material detection, where deep learning and computer vision models achieved notable accuracies. However, other sub-stages—such as operation and maintenance document analysis, object detection, volume estimation, and automated report generation—remain underexplored, with no PRA/PDA specific AI models identified. These gaps highlight the uneven distribution of AI adoption, with performance varying greatly depending on data quality, available domain-specific datasets, and the complexity of integration into existing workflows. Conclusions: Out of multiple PRA/PDA sub-stages, AI integration was focused on floor plan recognition and material detection, with deep learning and computer vision models achieving over 90% accuracy. Other stages such as operation and maintenance document analysis, object detection, volume estimation, and report writing, had little to no dedicated AI research. Therefore, although AI demonstrates strong potential in PRA/PDA, particularly for floor plan and material analysis, broader adoption is limited. Future research should target multimodal AI development, real-time deployment, and standardized benchmarking to improve automation and accuracy across all PRA/PDA stages. Full article

This research proposes a non-penetration lap welding process for joining T2 copper power module terminals in high-frequency and high-power electronic applications, using a hybrid laser system combining a 445 nm blue diode laser and a 1080 nm fiber laser. The composite laser beam, formed by coupling a circular blue laser beam with a spot-shaped fiber laser beam, was oscillated along circular, sinusoidal, and 8-shaped trajectories to control weld geometry and joint quality. Results indicate that all trajectories produced U-shaped weld cross-sections with smooth toe transitions and good surface quality. Specifically, the circular trajectory provided uniform energy distribution and stable weld formation; the 8-shaped trajectory achieved a balanced width-to-depth ratio; and the sinusoidal trajectory exhibited sensitivity to welding speed, often resulting in uneven fusion width. Increased welding speed promoted grain refinement, but excessive speed led to porosity and poor surface quality in both 8-shaped and sinusoidal trajectories. Oscillating laser welding facilitated equiaxed grain formation, with the circular and 8-shaped trajectories yielding more uniform microstructures. The circular trajectory maintained consistent weld dimensions and hardness distribution, while the 8-shaped trajectory exhibited superior tensile strength. This work highlights the potential of circular and 8-shaped trajectories in hybrid laser welding for regulating weld microstructure, enhancing mechanical performance and ensuring weld stability. Full article

Micro- and nanopatterning is crucial for advanced photonic, electronic, and sensing devices. Yet achieving large-area periodic nanostructures with a 75 nm half-pitch on low-cost laboratory systems remains difficult, because conventional near-ultraviolet laser interference lithography (LIL) suffers from Gaussian-beam non-uniformity and a narrow exposure latitude. Here, we report a cost-effective deep-ultraviolet (DUV) dual-beam LIL system based on a 266 nm laser and diffractive flat-top beam shaping, enabling large-area patterning of periodical nanostructures. At this wavelength, a moderate half-angle can be chosen to preserve a large beam-overlap region while still delivering 150 nm period (75 nm half-pitch) structures. By independently tuning the incident angle and beam uniformity, we pattern one-dimensional (1D) gratings and two-dimensional (2D) arrays over a Ø 1.0 cm field with critical-dimension variation < 5 nm (1σ), smooth edges, and near-vertical sidewalls. As a proof of concept, we transfer a 2D pattern into Si to create non-metal-coated nanodot arrays that serve as surface-enhanced Raman spectroscopy (SERS) substrates. The arrays deliver an average enhancement factor of ~1.12 × 10⁴ with 11% intensity relative standard deviation (RSD) over 65 sampling points, a performance near the upper limit of all-dielectric SERS substrates. The proposed method overcomes the uneven hotspot distribution and complex fabrication procedures in conventional SERS substrates, enabling reliable and large-area chemical sensing. Compared to electron-beam lithography, the flat-top DUV-LIL approach offers orders-of-magnitude higher throughput at a fraction of the cost, while its centimeter-scale uniformity can be scaled to full wafers with larger beam-shaping optics. These attributes position the method as a versatile and economical route to large-area photonic metasurfaces and sensing devices. Full article

Thermal impregnation (TI) is a traditional method of sugar infusion, but it has disadvantages such as long processing time and uneven sugar distribution. Therefore, developing sugar impregnation methods to enhance product flavor, nutritional value, and processing efficiency is critical for addressing potential quality loss and efficiency bottlenecks in traditional preserve processing technologies. This study took the TI process widely adopted in Xinjiang over the long term as a reference and systematically compared the effects of vacuum impregnation (VI) and ultrasonic-assisted impregnation (UI) on the flavor characteristics and physicochemical properties of plum preserves. Volatile organic compounds (VOCs) were identified using gas chromatography–ion mobility spectrometry (GC-IMS) coupled with multivariate analysis, while taste attributes were quantified via electronic tongue (E-tongue). Physicochemical parameters, including titratable acidity (TA), browning index (BI), color parameters (L*, a*, b*), total polyphenol content (TPC), total flavonoid content (TFC), and texture profile analysis (TPA), were also evaluated. GC-IMS identified 60 VOCs, predominantly comprising aldehydes (20), alcohols (10), ketones (6), acids (4), esters (3), furans (3), ketols (2), and unidentified compounds (12). The VI-treated samples exhibited distinct aromatic profiles, retaining a higher proportion of key volatile compounds. E-tongue results showed that VI significantly enhanced sourness, umami, and aftertaste complexity compared with UI and TI (p < 0.05). Physicochemical analyses showed that VI maximally preserved bioactive compounds, with a TPC of 1.23 ± 0.07 mg GAE/g and TFC of 17.55 ± 0.81 mg RE/g. Additionally, VI minimized enzymatic browning (BI: 0.37 ± 0.03), maintained color brightness (L*: 31.85 ± 1.56), maintained favorable textural properties (hardness: 187.63 ± 4.04 N), and retained the highest TA content (0.77 ± 0.05%). In contrast, UI and TI led to significant quality degradation, characterized by pronounced browning and texture deterioration: the BI values were 0.61 ± 0.02 (UI) and 0.83 ± 0.03 (TI), and hardness values were 176.53 ± 5.81 N (UI) and 156.25 ± 4.55 N (TI). These findings provide critical references for sugar impregnation techniques and a scientific basis for flavor regulation in prune preserve production. Full article

The alloying elements usually lead to the precipitation of second phases in steel, readily forming at grain boundaries, and the type and distribution of these phases significantly influence the mechanical properties of the matrix. In the present contribution, the austenitic matrix fcc-Fe, the precipitate NbN, and the interface properties between them are investigated by first-principles calculations in detail. The effects of vacancy and alloying element content on the interface performance are examined. The results indicate that the density of states (DOS) of the former is primarily contributed by the Fe d-orbitals, and both exhibit elastic anisotropy. Under a tensile strain of 20%, the maximum tensile strength of fcc-Fe reaches 32.6 GPa. For NbN, the maximum tensile strength comes to 29 GPa at a strain of 10%, after which the stress rapidly decreases with the increasing of strain. In the meantime, the uneven distribution of electron cloud density increases in both. Regarding the interface, the introduction of vacancies enhances atomic interaction and improves interface stability by altering electron cloud distribution. As the Co doping content increases, the covalent interactions between atoms strengthen at the interface, enhancing interface stability. However, excessive V doping may reduce the interface stability. Furthermore, when the vacancies coexist with alloying elements, the stronger covalent characteristics are observed due to shortened bond lengths and positive bond population values. These insights provide a data foundation and theoretical basis for designing high-performance austenitic stainless steels. Full article

The battery pack is a critical component of electric vehicles, with lithium-ion cells being a frequently preferred choice. Lithium-ion cells are known for long life, high power and energy density, and are reliable for a broad range of temperatures. However, these batteries have a drawback of over-voltage, under-voltage, thermal runaway, and especially, state of charge or voltage imbalance. Among these, the cell imbalance is particularly important because it causes an uneven power dissipation in each cell, resulting in non-uniform temperature distribution. This uneven temperature distribution negatively affects the lifetime and efficiency of a battery pack. Cell imbalance is mitigated by cell balancing techniques, of which several methods have been presented over the last few years. These methods consider different power electronics circuits and control approaches to optimise cell balancing characteristics. This paper reviews basic to advanced cell balancing techniques and compares their circuit designs, costs, switching stresses, complexity, sizes, and control techniques to highlight the recent trends and future directions. This paper also compares the recent trend of machine learning integration with basic cell balancing topologies and provides a critical analysis of the outcomes. Full article

The growing demands for highly functional biomedical implants necessitate introducing innovative and easy-to-apply surface functionalization techniques, especially when it comes to stainless steel substrates. This study investigated the co-deposition of chitosan and Cu-doped bioactive glass on AISI 316L steel surfaces, with the latter providing a matrix in which fine bioactive glass powders are distributed. Cu-doping into the matrix of bioactive glass was conducted to assess its influence on the bioactivity, antibacterial properties, and structural integrity of the coating. The microstructure, mechanical properties, phase composition, and surface roughness of coated specimens were investigated through a scanning electron microscope (SEM), X-ray diffraction analysis (XRD), energy-dispersive X-ray spectroscopy (EDS), inductively coupled plasma (ICP), contact angles, adhesion tensile tests, and laser profilometry analyses. Results of adhesion tests indicated that Cu addition did not have a major implication for the mechanical properties of the coating layers. Results also revealed that the Cu-doped bioactive glass featured a hydrophilic and a rather uneven surface, both being upsides for biomedical properties. The cytotoxicity and antibacterial assessments showed promising cell viability and antibacterial properties of the deposited coatings. Full article

Heating, ventilation, and air conditioning (HVAC) systems and microgrids have garnered significant attention in recent research, with temperature control and renewable energy integration emerging as key focus areas in urban distribution power systems. This paper proposes a robust predictive temperature control (RPTC) method and a microgrid control strategy incorporating asymmetrical challenges, including uneven power load distribution and uncertainties in renewable outputs. The proposed method leverages a thermodynamics-based R-C model to achieve precise indoor temperature regulation under external disturbances, while a multisource disturbance compensation mechanism enhances system robustness. Additionally, an HVAC load control model is developed to enable real-time dynamic regulation of airflow, facilitating second-level load response and improved renewable energy accommodation. A symmetrical power tracking and voltage support secondary controller is also designed to accurately capture and manage the fluctuating power demands of HVAC systems for supporting operations of distribution power systems. The effectiveness of the proposed method is validated through power electronics simulations in the Matlab/Simulink/SimPowerSystems environment, demonstrating its practical applicability and superior performance. Full article

Exploring advanced sulfur cathode materials is important for the development of lithium-sulfur batteries (LSBs), but they still present challenges. Herein, zinc oxide dots-modified vanadium nitride flower-like heterojunctions (Zn-QDs-VN) as sulfur hosts are prepared by a phase separation strategy. Characterizations confirm that the flower structure with high specific surface area and pores improves active site exposure and electron/mass transfer. In situ phase separation enriches the Zn-QDs-VN interface, addressing the issues of uneven distribution and interface reduction of Zn-QDs-VN. Further theoretical computations reveal that ZnO-QDs-VN with optimized intermediate spin states can constitute a stable LiS* bond sequence, which can conspicuously facilitate the adsorption and conversion of LiPSs and reduce the battery reaction energy barrier. Therefore, the ZnO-QDs-VN@S cathode shows a high initial specific capacity of 1109.6 mAh g⁻¹ at 1.0 C and long cycle stability (maintaining 984.2 mAh g⁻¹ after 500 cycles). Under high S loading (8.5 mg cm⁻²) and lean electrolyte conditions (E/S = 6.5 μL mg⁻¹), it also exhibits a high initial area capacity (10.26 mAh cm⁻²) at 0.2 C. The interfacial synergistic effect accelerates the adsorption and conversion of LiPSs and reduces the energy barriers in cell reactions. The study provides a new method for designing heterojunctions to achieve high-performance LSBs. Full article

The influence of heat input (HI) on the microstructure, microhardness, electrochemical corrosion performance of cold metal transfer additively manufactured (CMTAM) nickel–aluminum bronze alloys was investigated. The nickel–aluminum bronze exhibited an α-Cu austenite matrix with minor γ₂-Cu₉Al₄ and κ phases. As HI increased, the microstructure coarsened progressively. Electron backscatter diffraction (EBSD) analysis revealed that with increasing HI, the grain size gradually increased and the Schmid factor increased. Consequently, the microhardness declined from 198.3 HV to 171.7 HV. The decrease in microhardness with increasing heat input is primarily attributed to the grain coarsening and the coarsening and uneven distribution of the κ phase. As the heat input (HI) increased from 243.8 J/mm to 644.7 J/mm, the corrosion current density rose significantly from 2.56 ± 0.04 μA/cm² to 7.52 ± 0.07 μA/cm². This result indicates a marked deterioration in the material’s corrosion resistance. This phenomenon can be attributed to the grain coarsening and the distribution of Al solute within the microstructure. The CMTAM nickel–aluminum bronze alloys hold significant potential for enhancing the reliability and long-term protection of marine engineering equipment. Full article