Search Results (2,576)

This study investigates the influence of vacancy engineering and nitrogen doping on the structural, electronic, and optical properties of T-graphene fragments (TFs) using density functional theory (DFT) and time-dependent DFT (TD-DFT). A central vacancy and five pyridinic nitrogen doping configurations are explored to modulate the optoelectronic behavior. All systems are thermodynamically stable, exhibiting tunable HOMO–LUMO gaps, orbital distributions, and charge transfer characteristics. Optical absorption spectra show redshifts and enhanced oscillator strengths in doped variants, notably v-NTF2 and v-NTF4. Nonlinear optical (NLO) analysis reveals significant enhancement in both static and frequency-dependent responses. v-NTF2 displays an exceptionally high first-order hyperpolarizability (⟨β⟩ = 1228.05 au), along with a strong electro-optic Pockels effect (β (−ω; ω, 0)) and second harmonic generation (β (−2ω; ω, ω)). Its third-order response, γ (−2ω; ω, ω, 0), also exceeds 1.2 × 10⁵ au under visible excitation. Conceptual DFT descriptors and energy decomposition analysis further supports the observed trends in reactivity, charge delocalization, and stability. These findings demonstrate that strategic nitrogen doping in vacancy-engineered TFs is a powerful route to tailor electronic excitation, optical absorption, and nonlinear susceptibility. The results offer valuable insight into the rational design of next-generation carbon-based materials for optoelectronic, photonic, and NLO device applications. Full article

Using Photoplethysmogram (PPG) signals for identity recognition has been proven effective in biometric authentication. However, in real-world applications, PPG signals are prone to interference from noise, physical activity, diseases, and other factors, making it challenging to ensure accurate user recognition and verification in complex environments. To address these issues, this paper proposes an improved MSF-SE ResNet50 (Multi-Scale Feature Squeeze-and-Excitation ResNet50) model based on 2D PPG signals. Unlike most existing methods that directly process one-dimensional PPG signals, this paper adopts a novel approach based on two-dimensional PPG signal processing. By applying Continuous Wavelet Transform (CWT), the preprocessed one-dimensional PPG signal is transformed into a two-dimensional time-frequency map, which not only preserves the time-frequency characteristics of the signal but also provides richer spatial information. During the feature extraction process, the SENet module is first introduced to enhance the ability to extract distinctive features. Next, a novel Lightweight Multi-Scale Feature Fusion (LMSFF) module is proposed, which addresses the limitation of single-scale feature extraction in existing methods by employing parallel multi-scale convolutional operations. Finally, cross-stage feature fusion is implemented, overcoming the limitations of traditional feature fusion methods. These techniques work synergistically to improve the model’s performance. On the BIDMC dataset, the MSF-SE ResNet50 model achieved accuracy, precision, recall, and F1 scores of 98.41%, 98.19%, 98.27%, and 98.23%, respectively. Compared to existing state-of-the-art methods, the proposed model demonstrates significant improvements across all evaluation metrics, highlighting its significance in terms of network architecture and performance. Full article

Precise recognition of individual ovine specimens plays a pivotal role in implementing smart agricultural platforms and optimizing herd management systems. With the development of deep learning technology, sheep face recognition provides an efficient and contactless solution for individual sheep identification. However, with the growth of sheep, their facial features keep changing, which poses challenges for existing sheep face recognition models to maintain accuracy across the dynamic changes in facial features over time, making it difficult to meet practical needs. To address this limitation, we propose the lifelong biometric learning of the sheep face network (LBL-SheepNet), a feature decoupling network designed for continuous adaptation to ovine facial changes, and constructed a dataset of 31,200 images from 55 sheep tracked monthly from 1 to 12 months of age. The LBL-SheepNet model addresses dynamic variations in facial features during sheep growth through a multi-module architectural framework. Firstly, a Squeeze-and-Excitation (SE) module enhances discriminative feature representation through adaptive channel-wise recalibration. Then, a nonlinear feature decoupling module employs a hybrid channel-batch attention mechanism to separate age-related features from identity-specific characteristics. Finally, a correlation analysis module utilizes adversarial learning to suppress age-biased feature interference, ensuring focus on age-invariant identifiers. Experimental results demonstrate that LBL-SheepNet achieves 95.5% identification accuracy and 95.3% average precision on the sheep face dataset. This study introduces a lifelong biometric learning (LBL) mechanism to mitigate recognition accuracy degradation caused by dynamic facial feature variations in growing sheep. By designing a feature decoupling network integrated with adversarial age-invariant learning, the proposed method addresses the performance limitations of existing models in long-term individual identification. Full article

To improve the efficiency and stability of the system, this paper proposes a monolithic integrated optical path design for a cavity optomechanical accelerometer based on a 250 nm top silicon thickness silicon-on-insulator (SOI) wafer instead of readout through U-shape fiber coupling. Finite Element Analysis (FEA) and Finite-Difference Time-Domain (FDTD) methods are employed to systematically investigate the performance of key optical structures, including the resonant modes and bandgap characteristics of photonic crystal (PhC) microcavities, transmission loss of strip waveguides, coupling efficiency of tapered-lensed fiber-to-waveguide end-faces, coupling characteristics between strip waveguides and PhC waveguides, and the coupling mechanism between PhC waveguides and microcavities. Simulation results demonstrate that the designed PhC microcavity achieves a quality factor (Q-factor) of 2.26 × 10⁵ at a 1550 nm wavelength while the optimized strip waveguide exhibits a low loss of merely 0.2 dB over a 5000 μm transmission length. The strip waveguide to PhC waveguide coupling achieves 92% transmittance at the resonant frequency, corresponding to a loss below 0.4 dB. The optimized edge coupling structure exhibits a transmittance of 75.8% (loss < 1.2 dB), with a 30 μm coupling length scheme (60% transmittance, ~2.2 dB loss) ultimately selected based on process feasibility trade-offs. The total optical path system loss (input to output) is 5.4 dB. The paper confirms that the PhC waveguide–microcavity evanescent coupling method can effectively excite the target cavity mode, ensuring optomechanical coupling efficiency for the accelerometer. This research provides theoretical foundations and design guidelines for the fabrication of high-precision monolithic integrated cavity optomechanical accelerometers. Full article

Forest trees have emerged as a promising passive solution for mitigating low-frequency ground vibrations generated by railway operations, offering ecological and cost-effective advantages. This study proposes a three-dimensional semi-analytical method developed for evaluating the dynamic responses of the coupled track–ground–tree system. The thin-layer method is employed to derive an explicit Green’s function corresponding to a har-monic point load acting on a layered half-space, which is subsequently applied to couple the foundation with the track system. The forest trees are modeled as surface oscillators coupled on the ground surface to evaluate the characteristics of multiple scattered wavefields. The vibration attenuation capacity of forest trees in mitigating railway-induced ground vibrations is systematically investigated using the proposed method. In the direction perpendicular to the track on the ground surface, a graded array of forest trees with varying heights is capable of forming a broad mitigation frequency band below 80 Hz. Due to the interaction of wave fields excited by harmonic point loads at multiple locations, the attenuation performance of the tree system varies significantly across different positions on the surface. The influence of variability in tree height, radius, and density on system performance is subsequently examined using a Monte Carlo simulation. Despite the inherent randomness in tree characteristics, the forest still demonstrates notable attenuation effectiveness at frequencies below 80 Hz. Among the considered parameters, variations in tree height exert the most pronounced effect on the uncertainty of attenuation performance, followed sequentially by variations in density and radius. Full article

Metasurfaces have drawn extensive research attention for their unique optical properties and vast application potential. Among the various resonant modes induced in metasurfaces, BIC and electric anapole modes stand out as particularly interesting due to their distinctive physical characteristics. In this work, we designed and investigated novel dimeric dumbbell-shaped metasurfaces incorporating two independently tunable asymmetric parameters. This structural innovation enables the simultaneous excitation of both electric anapole and QBIC modes under normally incident MIR illumination. More importantly, by adjusting these two asymmetric parameters, one can independently tune the resonance peaks of the two modes, thereby overcoming the performance limits of conventional single-peak modulation. This metasurface design demonstrates outstanding performance for dielectric environment-sensing applications. We conducted a comprehensive investigation of the sensing sensitivity for dumbbell-shaped metasurfaces of various geometries. Our simulation results show that the circular-shaped configuration achieved high sensitivity, reaching 20,930 GHz/RIU. This work offers a novel design paradigm for multi-mode control and functionalization of metasurface structures. Full article

Given that cryogenic pumps on liquefied natural gas (LNG) carriers are prone to cavitation under complex operating conditions, this paper examines the inducer of an LNG centrifugal pump to uncover how the inducer geometry affects both the cavitation behavior and internal flow-induced excitation at −163 °C. Through detailed numerical simulations, we evaluate the cavitation performance and flow excitation characteristics across a range of inducer designs, systematically varying the blade count, inlet and outlet angles, and blade wrap angle. Our results show that reducing the number of blades, together with properly optimized inlet/outlet and wrap angles, significantly enhances the cavitation resistance. These findings provide a solid theoretical basis and practical guidance for the engineering optimization of LNG ship pumps. Full article

This study details how 3-(naphthalen-2-yl)-1-phenylprop-2-en-1-one (3NPEO) behaves in terms of photophysics when exposed to different solvents. The solvatochromic effect study reveals significant polarity shifts in the excited states of the 3NPEO compound, likely due to an intramolecular proton transfer mechanism. Measurements of dipole moments provide insight into their resonance structures in both ground and excited states. Electrochemical analysis revealed a reversible redox process, indicating a favorable charge transport potential. HOMO and LUMO energies of the compound were computed via oxidation and reduction potential standards. 3NPEO exhibits optimal one-photon and two-photon absorption characteristics, validating its suitability for visible wavelength laser applications in photonic devices. Furthermore, molecular docking and dynamics simulations demonstrated strong interactions between 3NPEO and the progesterone receptor enzyme, supported by structure–activity relationship (SAR) analyses. In vitro cytotoxicity assays on the MDAMB-231 breast cancer cell line showed moderate tumor cell inhibitory activity. Apoptosis studies confirmed the induction of both early and late apoptosis. These findings suggest that 3NPEO holds promise as a potential anticancer agent targeting the progesterone receptor in breast cancer cells. Overall, the findings highlight the substantial influence of solvent polarity on the photophysical properties and the design of more effective and stable therapeutic agents. Full article

Energy harvesting systems (EHSs) are widely used to power wireless sensors. Piezoelectric harvesters have the advantage of producing an electric signal directly related to the exciting force and can thus be used to power condition monitoring sensors in dynamically loaded structures such as bridges. The need for such monitoring is exemplified by the fact that the condition of close to 25% of public roadway bridges in, e.g., Germany is not satisfactory. Stack-based piezoelectric energy harvesting systems (pEHSs) installed near bridge bearings could provide information about the traffic and dynamic loads on the one hand and condition-dependent changes in the bridge characteristics on the other. This paper presents an approach to co-optimizing the design of the mechanical and electrical components using a nonlinear solver. Such an approach has not been described in the open literature to the best of the authors’ knowledge. The mechanical excitation is estimated through a finite element simulation, and the electric circuitry is modeled in Simulink to account for the nonlinear characteristics of rectifying diodes. We use real traffic data to create statistical randomized scenarios for the optimization and statistical variation. A main result of this work is that it reveals the strong dependence of the energy output on the interaction between bridge, harvester, and traffic details. A second result is that the methodology yields design criteria for the harvester such that the energy output is maximized. Through the case study of an actual middle-sized bridge in Germany, we demonstrate the feasibility of harvesting a time-averaged power of several milliwatts throughout the day. Comparing the total amount of harvested energy for 1000 randomized traffic scenarios, we demonstrate the suitability of pEHS to power wireless sensor nodes. In addition, we show the potential sensory usability for traffic observation (vehicle frequency, vehicle weight, axle load, etc.). Full article

The dynamics of the vibrational mode of motion of the driving member of a nonideal system, a mixing–whipping device based on a simple slide-crank mechanism, was studied. The highly nonlinear differential equations of motion were solved numerically by the Runge–Kutta method. The interaction of the mixing–whipping device with the nonideal excitation source causes the rotational speed of the engine shaft and the rotation angle of the driving member to fluctuate, accomplishing a damped process. The parameters of the device and the nonideal energy source have an effect on the kinematic, vibrational and energy characteristics of the system. An increase in the engine’s torque, crank length, number and radius of piston holes, and piston mass, as well as a decrease in the fluid’s density, leads to a reduction in the oscillation range of the crank angle, amplitude and period of angular velocity oscillations of the engine shaft and the mixing–whipping force power. The effects of a nonideal energy source may be used in designing a mixing–whipping device based on a slider-crank mechanism to select effective system parameters and an energy-saving motor in accordance with the requirements of technological processes and products. Full article

The localization of multiple interference sources in Global Navigation Satellite Systems (GNSS) can be achieved using carrier-to-noise ratio (C/N₀) information provided by GNSS receivers, such as those embedded in smartphones. However, in increasingly prevalent complex scenarios—such as the coexistence of multiple directional interferences, increased diversity and density of GNSS interference, and the presence of multiple low-power interference sources—conventional localization methods often fail to provide reliable results, thereby limiting their applicability in real-world environments. This paper presents a multi-interference sources localization method using object detection in GNSS C/N₀ distribution maps. The proposed method first exploits the similarity between C/N₀ data reported by GNSS receivers and image grayscale values to construct C/N₀ distribution maps, thereby transforming the problem of multi-source GNSS interference localization into an object detection and localization task based on image processing techniques. Subsequently, an Oriented Squeeze-and-Excitation-based Faster Region-based Convolutional Neural Network (OSF-RCNN) framework is proposed to process the C/N₀ distribution maps. Building upon the Faster R-CNN framework, the proposed method integrates an Oriented RPN (Region Proposal Network) to regress the orientation angles of directional antennas, effectively addressing their rotational characteristics. Additionally, the Squeeze-and-Excitation (SE) mechanism and the Feature Pyramid Network (FPN) are integrated at key stages of the network to improve sensitivity to small targets, thereby enhancing detection and localization performance for low-power interference sources. The simulation results verify the effectiveness of the proposed method in accurately localizing multiple interference sources under the increasingly prevalent complex scenarios described above. Full article

The interaction between thermal fields and mechanical loads in thin-walled cylindrical shells introduces complex dynamic behaviors relevant to aerospace and mechanical engineering applications. This study investigates the axial stress wave propagation in a circular cylindrical shell subjected to combined thermal gradients and time-dependent harmonic compression. A semi-analytical model based on Donnell–Mushtari–Vlasov (DMV) shells theory is developed to derive the governing equations, incorporating elastic, inertial, and thermal expansion effects. Modal solutions are obtained to evaluate displacement and stress distributions across varying thermal and mechanical excitation conditions. Empirical Mode Decomposition (EMD) and Instantaneous Frequency (IF) analysis are employed to extract time–frequency characteristics of the dynamic response. Complementary Finite Element Analysis (FEA) is conducted to assess modal deformations, stress wave amplification, and the influence of thermal softening on resonance frequencies. Results reveal that increasing thermal gradients leads to significant reductions in natural frequencies and amplifies stress responses at critical excitation frequencies. The combination of analytical and numerical approaches captures the coupled thermomechanical effects on shell dynamics, providing an understanding of resonance amplification, modal energy distribution, and thermal-induced stiffness variation under axial harmonic excitation across thin-walled cylindrical structures. Full article

The time-domain electromagnetic method has been widely applied in mineral exploration, oil, and gas fields in recent years. However, its response characteristics remain unclear, and there is an urgent need to study the response characteristics of the borehole-surface transient electromagnetic(BSTEM) field. This study starts from the time-domain electric field diffusion equation and discretizes the calculation area in space using tetrahedral meshes. The Galerkin method is used to derive the finite element equation of the electric field, and the vector interpolation basis function is used to approximate the electric field in any arbitrary tetrahedral mesh in the free space, thus achieving the three-dimensional forward simulation of the BSTEM field based on the finite element method. Following validation of the numerical simulation method, we further analyze the electromagnetic field response excited by vertical line sources.. Through comparison, it is concluded that measuring the radial electric field is the most intuitive and effective layout method for BSTEM, with a focus on the propagation characteristics of the electromagnetic field in both low-resistance and high-resistance anomalies at different positions. Numerical simulations reveal that BSTEM demonstrates superior resolution capability for low-resistivity anomalies, while showing limited detectability for high-resistivity anomalies Numerical simulation results of BSTEM with realistic orebody models, the correctness of this rule is further verified. This has important implications for our understanding of the propagation laws of BSTEM as well as for subsequent data processing and interpretation. Full article

In this paper, a bearing- and transformer-integrated electric excitation synchronous motor excitation system (bearing-integrated rotary transformer) is proposed to support the motor rotor and energy transmission of excitation systems. Firstly, the working principle of the bearing-integrated rotary transformer is discussed. Secondly, the structure and electromagnetism of the bearing-integrated rotary transformer are designed through the processes and principles of pole slot matching, stator/rotor size, winding, and the magnetic regulating needle. Thirdly, the bearing-integrated rotary transformer undergoes an electromagnetic–thermal simulation. Finally, a prototype of the bearing-integrated rotary transformer is manufactured, and the electromagnetic and transmission characteristics are tested, verifying the correctness of the proposed scheme and providing additional ideas for the improvement of synchronous motor excitation systems. Full article

Functionally graded carbon nanotube reinforced composites (FG-CNTRCs) are a novel breed of polymer nanocomposite, in which the nonuniform distribution of the carbon nanotube (CNT) reinforcement is adopted to maximize the macro-mechanical performance of the polymer with a lower content of CNTs. Composite conical–cylindrical combined shells (CCCSs) are widely utilized as loading-bearing components in various engineering applications, and a comprehensive understanding of the vibration characteristics of these shells under different external excitations and boundary conditions is crucial for engineering applications. In this study, the free vibration behaviors of FG-CNTRC CCCSs supported by an elastic foundation are examined using the Haar wavelet discretization method (HWDM). First, by means of the HWDM, the equations of motion of each shell segment, the continuity and boundary conditions are converted into a system of algebraic equations. Subsequently, the natural frequencies and modes of the CCCSs are achieved by calculating the resultant algebraic equations. The convergence and accuracy are evaluated, and the results demonstrate that the proposed method has stable convergence, high efficiency, and excellent accuracy. Furthermore, an exhaustive parametric investigation is conducted to reveal the effects of foundation stiffnesses, boundary conditions, material mechanical properties, and geometric parameters on the vibration characteristics of the FG-CNTRC CCCS. Full article