Search Results (2,599)

Nowadays, numerical simulation methods are advanced and widely used in industry, enabling the modeling of complex systems from printed circuit boards (PCBs) to full power converters. Among many isolated topologies, the phase-shift full-bridge (PSFB) topology is a well-established solution for isolated DC–DC conversion in electric vehicles. Therefore, this paper proposes a broadband electromagnetic compatibility (EMC) modeling methodology for a custom-designed 1 kW gallium nitride (GaN)-based PSFB converter intended for an electric vehicle (EV) DC powertrain. Moreover, the approach combines full-wave electromagnetic simulation with circuit-level simulation, including parasitic effects from PCB layout, power harnesses, and discrete components. Thus, the virtual prototype is assessed within a complete virtual test bench compliant with the standard Comité International Spécial des Perturbations Radioélectriques (CISPR) 25 over the 150 kHz–108 MHz range to capture common-mode (CM) and differential-mode (DM) conducted electromagnetic interference (EMI). Results show that the converter achieves efficiencies of 97.26% in standalone mode and 97.03% when integrated into the full DC powertrain. However, the conducted EMI assessment reveals that both CM and DM emissions exceed CISPR 25 Class 2 limits across the entire spectrum, with excess levels reaching up to 72 dBµV. Therefore, power harnesses significantly increase EMI levels at low frequencies due to the distributed inductance and stray capacitance. Finally, this study demonstrates the value of virtual prototyping for simulation-based EMI prediction in early-stage power converter design. Full article

Urban building color research has long been anchored in the “dominant-color” paradigm, which describes only the basic attributes of the most prevalent color and overlooks multi-color compositional relationships, thereby failing to reach evaluative dimensions such as color combination quality and spatial order. This study proposes a Fundamental–Compositional–Spatial (FCS) evaluation framework for building color quality, organizing ten indicators into three hierarchical layers: fundamental attributes, compositional structure, and spatial association. Using the Macao Special Administrative Region as an empirical case and drawing on building façade color data extracted from 8163 street-view sampling points, we systematically quantify the city-wide building color quality. Results show that (1) at 76.8% of the sampling points the dominant-color share lies within only 13–21%, so the dominant color holds no absolute areal advantage, and there is a significant intrinsic tension between colorfulness and harmony (r = −0.363) within the compositional structure; (2) Macao’s building colors are dominated by warm hues (warm-to-cool ratio ≈ 4.5:1), with saturation and value forming a systematic co-variation between a “dark-yet-colored” and a “bright-yet-colorless” mode, and color contrast exhibiting pronounced positive spatial autocorrelation (Moran’s I = 0.456); and (3) clustering based on the six C+S-layer indicators identifies four color-quality types—Subdued-Transitional (38.1%), Vibrant-Fragmented (13.5%), Dark-Harmonious (45.6%), and Monotonous-Clustered (2.7%)—whose spatial distribution is broadly consistent with the city’s historical construction strata. The study demonstrates that a multi-dimensional color-evaluation approach based on street-view big data can effectively transcend the limitations of dominant-color analysis and provides an operational technical pathway for fine-grained cognition and differentiated governance of urban color. Full article

Federated data spaces, established through initiatives such as IDSA and GAIA-X, enable organizations to share and monetize datasets under contractual terms. However, enforcing these contracts—particularly detecting unauthorized reuse or modification of datasets—remains an open challenge. We present the Off-Platform Contract Inspector, a component of the PISTIS framework, that implements a modular similarity-detection pipeline combining path-value Jaccard similarity, field-aware type-specific comparisons, and sentence-embedding-based semantic analysis across structured, semi-structured, and unstructured datasets. This contributes as follows: (i) an Inverse Document Frequency (IDF)-weighted structural similarity mechanism that discounts common domain vocabulary via Inverse Document Frequency weighting over the data space catalog, combined with a schema-evidence-gated fusion that reduces false positives from domain vocabulary overlap; (ii) an adaptive threshold optimization mechanism that learns modality-specific fusion weights and decision thresholds via cross-validated grid search; and (iii) a privacy-preserving similarity layer based on MinHash Locality-Sensitive Hashing signatures, Bloom filters with OR folding alignment, and Laplace noise for differential privacy, enabling cross-organizational dataset comparison without exposing raw data. Further, we contribute a threat taxonomy of seven dataset modification types ordered by detection difficulty, and evaluate the system on dataset pairs derived from real-world datasets across three smart-city application domains (Mobility, Energy, Automotive), with controlled augmentations applied to model adversarial behaviors. The IDF-weighted pipeline achieves high precision on intra-domain hard negatives—pairs of different tables from the same data space that share domain vocabulary—where text-similarity baselines produce false positives. The adaptive scheme learns per-modality fusion weights via cross-validated grid search. The privacy-preserving mode operates without accessing raw data and runs noticeably faster than the full pipeline, enabling screening while preserving data confidentiality. Full article

The study is driven by its importance in modern material processing and precision engineering, where understanding and controlling interfacial stability is crucial in maintaining reliable performance across various operating conditions. The interplay between the tangential magnetic field and temporal periodicity generates additional mechanisms of mode coupling and amplifies instability. These observations address critical shortcomings in nonlinear stability theory and suggest practical uses in flow regulation and the control of conductive fluids. The fluids are assumed as Eyring–Powell non-Newtonian and flow with uniform velocities through porous media. The analysis is conducted using a non-perturbative method that relies mainly on He’s frequency formulation. To facilitate the mathematical treatment, viscous potential theory is adopted. The governing linear partial differential equations describing the flow are then solved under nonlinear boundary conditions, resulting in a nonlinear characteristic equation that represents the displacement of the interface. A non-dimensional procedure is then applied to extract the key dimensionless physical parameters influencing the system behavior. A set of graphical results is provided to demonstrate how the system’s stability behavior is influenced by changes in the key dimensionless physical parameters. The validation of the innovative process is achieved using Mathematica Software. The study considers both uniform and periodically varying magnetic fields, and the associated stability conditions are evaluated for each case, where the impacts of various non-dimensional attributes are assessed. As density ratio increases, it stabilizes periodic magnetic fields while destabilizing uniform ones. A stronger MF enhances magnetic damping, reducing instability regions and promoting stable periodic interfacial motion. Enhanced conductivity improves Magnetohydrodynamic interactions, resulting in greater energy dissipation and stability. Full article

In this paper, a composite control framework integrating feedback linearization, an extended state observer, and an adaptive fractional-order sliding-mode controller is presented for autonomous underwater vehicles operating under uncertain hydrodynamics and external disturbances. The proposed algorithm, named adaptive fractional-order sliding-mode control with extended state observer, aims to enhance trajectory-tracking accuracy, disturbance rejection, and robustness against model uncertainties beyond what is offered by conventional active disturbance rejection control and integer-order sliding-mode control. First, a fractional-order sliding surface with an extended state observer is introduced to estimate and compensate lumped disturbances, where the fractional operator provides intrinsic filtering and memory effects to reduce chattering. Second, an adaptive exponential reaching law with smooth switching is formulated to overcome the trade-off between convergence speed and chattering, and a Levant differentiator is employed for sensorless velocity estimation. Finally, the uniform ultimate boundedness of the closed-loop system is proved via Lyapunov stability theory. Comparative simulation studies on step, sinusoidal, and circular trajectories under external disturbances, measurement noise, and 50% parametric uncertainties demonstrate that the proposed controller achieves zero overshoot, suppresses position fluctuations by 97%, and reduces root mean square tracking errors by 38–70% relative to conventional methods, confirming its superior performance. Full article

High-nickel NCA/Si–C 21700 cells exhibit strongly condition-dependent degradation, but the coupled influence of temperature and rate on electrochemical, thermal, and structural evolution remains insufficiently resolved. Here, Samsung INR21700-50E cells were aged under a 3 × 3 matrix of ambient temperatures (0, 23, and 40 °C) and C-rates (0.5C, 1C, and 2C). Periodic reference performance tests were used to track capacity, 10 s direct-current internal resistance, electrochemical impedance, pseudo-open-circuit voltage, differential voltage/incremental capacity behavior, heat generation, and post-mortem morphology. Guided by the hypothesis that temperature and rate history change not only the speed but also the dominant pathway of aging, the results show that both ambient temperature and the charge/discharge rate program govern the aging trajectory. Low-temperature cycling accelerates capacity loss and resistance growth through severe polarization and lithium plating, indicating dominant loss of lithium inventory. High-temperature operation promotes interfacial side reactions, impedance rise, and cathode structural degradation, leading to stronger loss of active material at later stages. An increasing C-rate amplifies these effects by raising overpotential and thermal load. Heat generation power increases markedly with aging and depends strongly on temperature–rate history. Scanning electron microscopy confirms cathode cracking, anode surface film thickening, and separator degradation under severe conditions. These experimental indicators are integrated into a mechanism-aware diagnostic framework that maps capacity retention, DCIR/EIS parameters, ICA/DVA indices, and heat generation metrics to dominant aging modes, supporting BMS state-of-health estimation, lifetime prediction, thermal management, and second-life screening of high-nickel NCA cells. The condition-averaged trajectories are further converted into a semi-empirical aging law that links capacity loss, resistance growth, and heat generation increase for BMS-oriented lifetime prediction. Full article

Sebaceous glands consist of epithelial cells, known as sebocytes, that undergo differentiation to deliver the components of sebum into the sebaceous duct and eventually to the hair and skin surface. The final step of the terminal differentiation program is called holocrine secretion because the entire cell content is converted into sebum. Holocrine secretion is a mode of programmed cell death, which involves the degradation of the nucleus and other organelles and the rupture of the cell membrane. Here, we review the current knowledge of differentiation-associated death of sebocytes and discuss open questions regarding its mechanism and functions. In vivo studies have provided evidence for degradation of nuclear and mitochondrial DNA by lysosomal deoxribonuclease 2 (DNase 2), indicating a key role of lysosomes in holocrine secretion. We discuss the influence of tight junctions on the spatial localization of holocrine secretion within glands, the regulation of holocrine cell death by autophagy and potential mediators of membrane lysis. Further studies of holocrine secretion are needed to fully uncover its molecular control and to determine potential clinical implications. Full article

This paper presents a 7-bit 1.6 GS/s hybrid capacitive-to-charge-injection DAC (C-CIDAC)-based flash-assisted time-interleaved (FATI) successive-approximation-register (SAR) analog-to-digital converter (ADC) that improves the limited input range and temperature-induced gain variation in conventional CIDAC-based SAR ADCs. In the proposed architecture, a DAC voltage common-mode (V_CM) shift up to 48 LSBs is internally generated during the coarse conversion, enabling a rail-to-rail ADC input range while improving V_CM independence. In addition, a fully on-chip background gain-calibration scheme is introduced to compensate for the gain error between the CDAC and CIDAC caused by temperature variation. By taking advantage of the pulse-activation-based CIDAC operation scheme, the proposed calibration achieves robust gain tracking without any external bias control. The proposed four-channel FATI-SAR ADC was designed using a 65 nm CMOS process and occupies 13,628 μm², including the background calibration circuitry. The peak differential nonlinearity (DNL) and integral nonlinearity (INL) are +0.60/−0.60 LSB and +0.72/−0.76 LSB at −40 °C and 105 °C, respectively. At Nyquist input, the simulated SNDR and SFDR are 41.52 dB and 53.36 dB, respectively. The ADC consumes 8.551 mW and achieves an FoM_W of 54.6 fJ/conversion step. Comprehensive post-layout simulation results show that the proposed FATI-SAR ADC operates at 1.6 GS/s and maintains an ENOB above 6.3 across a temperature range from −40 °C to 105 °C at Nyquist input. Full article

The electro-oxidation of persistent organic pollutants such as 2-chlorophenol (2-CPh) using boron-doped diamond (BDD) electrodes offers a promising wastewater treatment route, yet conventional mechanistic models (e.g., CFD) suffer from prohibitive computational costs. This study develops a hybrid physics-informed neural network (PINN) to model the electro-oxidation of 2-CPh in a flow-by reactor coupled with a continuous stirred tank under batch recirculation mode. The PINN integrates a diffusion–convection partial differential equation with a lumped-parameter ordinary differential equation for the tank, embedding physical constraints directly into the loss function. The model was trained on simulated data generated from a previously validated parametric model and optimized using a systematic hyperparameter grid search. The PINN achieved excellent agreement with experimental data, yielding a coefficient of determination (R²) of 0.9927, a mean square error of 0.0009, and a root mean square error of 0.0294—outperforming both the CFD and parametric models in accuracy. Sensitivity analysis revealed that the apparent kinetic constant is the most influential parameter (normalized sensitivity of 14.20). While the CFD model required 42 days and the parametric model 8 s, the PINN achieved a balanced trade-off with a runtime of 7.36 h. We conclude that the PINN provides a highly accurate, computationally feasible surrogate model suitable for integration into digital twins and real-time control frameworks for electrochemical wastewater treatment. Full article

Modular Mobile Robotic Systems (MMRSs) require simulation tools capable of supporting distributed control architectures, dynamic reconfiguration, and scalable experimentation. This work evaluates three complementary simulation strategies for a homogeneous MMRS composed of autonomous Two-Wheel Inverted Pendulum (TWIP) modules: (i) Webots, selected for rapid prototyping through its integrated GUI; (ii) Pinocchio, paired with the Jiminy simulator to enable modern rigid-body dynamics and control-oriented modeling; and (iii) PyBullet, chosen for programmatic flexibility and reinforcement learning (RL) compatibility. A minimal and controlled benchmark scenario was implemented across all platforms to isolate core simulation characteristics: two differentially driven robots were coupled using the most appropriate mechanism available in each environment and simulated for 1000 steps in headless mode while monitoring CPU usage, memory consumption, and execution time. In addition, a feature-based analysis focused on MMRS-relevant requirements, including dynamic reconfiguration, multi-agent scalability, and suitability for RL workflows. Full article

Background: Boswellia serrata has traditionally been used in Ayurvedic medicine for its anti-inflammatory and antioxidant properties. Although several studies support clinical analgesic efficacy, the underlying mechanisms have not been investigated in human experimental pain models. This randomized, double-blind, placebo-controlled, crossover pilot trial aimed to examine the mode of action of Boswellia serrata to differentiate between its peripheral and central effects. This exploratory pilot study was designed to generate preliminary effect size estimates and assess functional pain-processing outcomes, rather than to provide definitive evidence of clinical efficacy. Methods: Twelve healthy volunteers were recruited and received either 300 mg of Boswellia serrata extract or a visually identical placebo twice daily for 28 days, separated by a 4-week washout period. Pain and sensitization were induced using a topical capsaicin model. Outcomes included spontaneous pain intensity, mechanical allodynia, pinprick hyperalgesia, thermal thresholds, and conditioned pain modulation, alongside psychological assessments of mood, anxiety, sleep, and structured adverse-event monitoring. Results: Results showed no significant difference in the primary endpoint of spontaneous pain intensity between Boswellia and placebo (VAS 43 ± 21 vs. 47 ± 17; d = 0.18; p = 0.539). Conclusions: While Boswellia serrata did not significantly reduce acute peak pain in this model, the observed trends suggest a potential multi-level modulatory influence on nociceptive processing and endogenous pain inhibition. These findings warrant larger clinical trials to further elucidate its therapeutic potential, particularly in populations with impaired pain modulation. Full article

A novel semi-analytical computational approach is formulated and assessed for the dynamic aeroelastic stability analysis of flexible slender thin wings in incompressible flow, which can boost the preliminary airframe design and optimisation of lightweight aircraft, offering both theoretical and practical insights. Hencky’s bar-chain model is explicitly adopted as a discrete numerical implementation of the Euler–Bernoulli continuous beam idealisation for the flexible wing structure and its deformation, resulting in a linear system of coupled ordinary differential equations for its bending and torsion dynamics. Modified strip theory is employed for the unsteady sectional airload, where approximate yet effective analytical expressions are efficiently adopted for its build-up and distribution, combining two- and three-dimensional effects in subsonic potential flow. Once the natural vibration modes of the wing are obtained from its physical model, a reduced set is selected, and a modal approach is then employed to perform its aeroelastic stability analysis with either “p-k” or “p” method, depending on the aerodynamic model. Numerical results from such a reduced-order model are critically assessed for the flutter analysis of Goland’s, Loring’s, and Pazy wings and demonstrate excellent agreement with literature results for two- and three-dimensional airflow, also for the case of the swept wing. Full article

Background: The fruits of Rosa laxa Retz. (FRL) is a traditional medicinal and edible fruit widely used in Xinjiang for its potential health benefits. Its chemical variations across geographical origins remain poorly understood, as do the molecular mechanisms underlying its anti-hyperlipidemic effects. This study aimed to characterize the chemical profile of FRL extract (FRLE) from different origins, identify its bioactive constituents and metabolites in vivo, and evaluate its efficacy and potential mechanisms against HLP. Methods: UPLC-QTOF-MS was employed for qualitative and quantitative profiling, combined with PCA to differentiate samples from five origins. An HLP mouse model was established to evaluate the pharmacodynamic effects, while acute and sub-chronic toxicity tests assessed safety. Serum pharmacochemistry was used to track absorbed constituents and metabolites. Finally, network pharmacology, molecular docking, and Western blot were integrated to elucidate the underlying mechanisms. Results: A total of 60 compounds were identified in FRLE, with 20 key components quantified via the TOF-MRM mode. PCA indicated that the Yamalike Mountain samples possessed the most diverse chemical profile and the highest response of active markers. Pharmacodynamic results showed that FRLE (extraction yield 24.19%) significantly improved TC, LDL-C, and corrected abnormal HDL-C levels in HLP mice, while H&E staining confirmed the alleviation of hepatic steatosis. Safety evaluations revealed no significant acute or cumulative toxicity at the maximum feasible dose of 16.6 g/kg. In rat plasma, 15 prototypes and 14 metabolites were identified. FRLE acted on the “Lipid and Atherosclerosis” pathway by modulating key targets, including NFE2L2, CYP1A1, NOS3, and MAPK1. Conclusions: Our findings demonstrate that FRLE is a safe and effective candidate for the management of hyperlipidemia. This study establishes a link between the material basis and biological mechanisms of FRL, thereby providing a scientific foundation for its further resource development and clinical application. Full article

Procambarus clarkii, a prominent aquaculture species, are mainly cultured through conventional modes: pond culture and rice–crayfish co-culture. In the present study, we proposed a novel industrial recirculating aquaculture system (RAS) for the culture of Procambarus clarkii. The nutritional quality of Procambarus clarkii under different culture modes was evaluated. The results indicated that industrial culture achieved optimal amino acid profiles and a higher level of flavor amino acids. Crayfish cultured in RAS also showed more balanced textures with moderate hardness and good springiness. Moreover, distinct crayfish metabolites were identified across different culture modes. The main differential metabolites include amino acids, peptides (and their analogs), organic acids and acyl carnitines. Industrial culture prioritized metabolites linked to flavor and rapid growth, while other culture modes enriched metabolites associated with ecological resilience and nutritional diversity. Overall, industrial culture displays great potential in improving the nutritional quality and regulating metabolic characteristics of red swamp crayfish. Full article

This work presents the realization of a compact and embedded impedance-based sensor system for the characterization of lithium-ion batteries by means of electrical impedance spectroscopy (EIS). The analog magnitude-ratio and phase-difference detection (MRPDD) method is implemented and extended through a generalized formulation that models the shunt element as a frequency-dependent impedance and compensates the parasitic contributions of the printed circuit board. This reformulation corrects magnitude and phase errors introduced by the measurement hardware without increasing the overall complexity. The prototype comprises two main functional blocks: current-mode excitation and voltage-mode measurement. The excitation stage uses an operational transconductance amplifier and a power MOSFET to generate a voltage-controlled current source, whereas the sinusoidal voltage signal is generated by means of a direct digital synthesizer. The measurement chain relies on differential acquisition using instrumentation amplifiers and analog magnitude/phase detection based on the AD8302 vector detector under microcontroller control. The proposed method has been first validated by simulations using both a linear RC equivalent model and an extended Randles-type battery-equivalent model, and then experimentally characterized using a linear RC equivalent model of the device under test. Measurements show that the generalized formulation recovers the ideal impedance response in the presence of parasitic effects, both in the shunt device and in the printed circuit board. In the experimental validation with the RC model, a magnitude error of 1.65% is obtained at 1 kHz, which is adopted as the upper frequency limit for battery characterization, even though operation up to 10 kHz is possible. Phase measurements revealed that the input capacitive coupling of the vector detector, conceived for operation in the RF range, requires an adaptation for appropriate operation in the intended frequency range. The prototype has been also applied to the characterization of a commercial lithium-ion 18650 cell, enabling the measurement of battery impedance and the analysis of its dependence on the state-of-charge and on the discharge current. Full article