Search Results (1,948)

Signal transducer and activator of transcription 3 (STAT3) is a transcription factor that regulates a broad spectrum of genes with oncogenic potential, thereby serving as a critical driver of tumorigenesis. Canonical STAT3 function is mediated through tyrosine phosphorylation, which enables dimerization and transcriptional activation, whereas serine phosphorylation of STAT3 has a postulated role in fine-tuning canonical functions and contributes to non-canonical roles as well. One of the transcriptional targets of STAT3 is the anti-apoptotic B-cell lymphoma 2 (Bcl-2) protein, itself subject to phosphorylation-dependent regulation. In this study, we investigated the effect of chelidonine, an alkaloid component of Chelidonium majus L., on STAT3/Bcl-2 signaling in human T leukemia/lymphoma cells, reported to have numerous effects in common with microtubule-targeting agents (MTAs). Flow cytometry and confocal microscopy revealed that chelidonine transiently increased both serine-phosphorylated STAT3 (pSer-STAT3) and Bcl-2 levels in a distinct subpopulation of cells, with near-complete overlap between the affected cells. This effect appeared at least partially independent of interleukin-2 (IL-2) and was associated with the M-phase of the cell cycle, as indicated by enhanced phosphorylation of Bcl-2 at serine 70 and nuclear morphology characteristic of mitosis. Our study provides the first single-cell evidence that STAT3 and Bcl-2 undergo concurrent serine phosphorylation as a response to chelidonine treatment, with the effect tightly linked to the M-phase. Full article

As the brain’s resident macrophages, microglia on the one side are increasingly recognized as essential players in discrete developmental stages, where immune, metabolic, and activity-derived signals are coordinately integrated to guide brain development. On the other side, the precise temporal and molecular coordination of microglial maturation is imperative for the structural and functional integrity of the developing central nervous system (CNS). In this review, we synthesize recent data that reposition microglia from a uniform population of immune sentinels to temporally programmed and regionally specialized regulators of circuit maturation. This involves dissecting the embryonic origins and migratory pathways of microglial progenitors in mouse and human systems and illustrating how gradual transcriptional and morphological maturation aligns the biology of microglia with progressive phases of neurogenesis, synaptic fine-tuning, myelination, and vascular stabilization. In addition, we discuss how individual gene mutations, inflammatory insults during perinatal life, and environmental disturbances intersect with these temporal programs to alter microglial phenotypes and compromise circuit formation. With a special emphasis on epilepsy and autism spectrum disorder, often sharing the common etiology, we illustrate how early malfunction of microglia may drive neural network dysfunction. Full article

This study explores the influence of precursor nature on the structural and mechanical characteristics of hydroxyapatite–yttria partially stabilized zirconia (HAp–YSZ) nanocomposites designed for biomedical applications. Precursor powders for obtaining these ceramic composites were synthesized via wet coprecipitation, using different calcium phosphate precursors: dibasic and monobasic ammonium phosphates for hydroxyapatite, and zirconyl chloride with yttrium acetate for YSZ. The dried precipitated powders were thermally treated at 600 °C and 800 °C and characterized by X-ray diffraction (XRD), thermal analysis (DTA–TG), transmission electron microscopy (TEM), and BET surface area measurements. The nanocomposites containing 70–90 wt.% HAp and 10–30 wt.% YSZ were sintered between 1000 °C and 1400 °C. Microstructural and physical properties were evaluated using scanning electron microscopy (SEM), open porosity, and compressive strength testing. Results revealed that precursor type and calcination temperature strongly affected crystallinity, particle size, and phase composition, influencing both porosity and mechanical strength of the final materials. An optimal sintering temperature of approximately 1200 °C was identified, balancing densification and phase stability. The findings demonstrate that controlling precursor chemistry and heat treatment enables fine-tuning of nanocomposite structure and performance, supporting their potential as bioactive, mechanically enhanced ceramics for orthopedic implant applications. Full article

A central challenge in reconfigurable photonics based on quasi bound states in the continuum (quasi-BICs) is to move beyond binary switching toward multistate and polarization-aware programmability. Here we propose a dual-phase-change material (PCM) metasurface that enables four-state nonvolatile switching and polarization-divergent dispersion rewriting within a single unit cell. Two independently switchable PCM layers provide four addressable configurations (0-0, 0-1, 1-0, 1-1) at a fixed geometry, allowing the resonance landscape to be reprogrammed through complex-index rewriting without structural modification. Angle-resolved transmission maps reveal fundamentally different evolution pathways for orthogonal polarizations. For p polarization, the quasi-BIC exhibits strong state sensitivity with dispersion reshaping and multi-branch features near normal incidence; the resonance red-shifts from ~1331 nm to ~1355 nm while the quality factor decreases from ~6.7 × 10⁴ to ~4.0 × 10⁴. In contrast, for s polarization, a single weakly dispersive branch translates coherently across states, producing a much larger shift from ~1635 nm to ~1790 nm while the quality factor increases from ~9.0 × 10³ to ~1.8 × 10⁴. The opposite quality-factor trajectories, together with the polarization-contrasting tuning ranges, demonstrate that dual-PCM programming reconfigures polarization-selective radiative coupling rather than imposing a uniform resonance shift. This compact two-bit metasurface platform provides multistate, high-Q control with active dispersion engineering, enabling polarization-multiplexed reconfigurable filters, state-addressable sensors, and other programmable photonic devices. Full article

Hardware-in-the-loop (HIL) simulation is an essential tool for rapid and cost-effective development and validation of power-electronic systems. The primary objective of this work is to validate and fine-tune a PLECS-based HIL model of a single dual active bridge (DAB) DC-DC converter, thereby laying the foundation for building more complex models (e.g., multiple converters connected in series or parallel). To this end, the converter is experimentally characterized, and the HIL model is validated across a wide range of operating conditions by varying the PWM phase-shift angle, voltage gain, switching frequency, and leakage inductance. Power transfer and efficiency are analyzed to quantify the influence of these parameters on converter performance. These experimental trends provide insight into the optimal modulation range and the dominant loss mechanisms of the DAB under single phase shift (SPS) control. A detailed comparison between HIL simulations and hardware measurements, based on transferred power and efficiency, shows close agreement across all the tested operating points. These results confirm the accuracy and robustness of the proposed HIL model, demonstrate the suitability of the PLECS platform for DAB development and control validation, and support its use as a scalable basis for more complex multi-converter studies, reducing design time and prototyping risk. Full article

In the context of fifth-generation (5G) communications and the dawn of sixth-generation (6G) networks, a surged societal demand on bandwidth and data rate and more stringent commercial requirements on transmission efficiency, cost, and reliability are increasingly evident and, hence, driving the maturity of reconfigurable millimeter-wave (mmW) and terahertz (THz) devices and systems, in particular, liquid crystal (LC)-based tunable solutions for delay line phase shifters (DLPSs). However, the field of LC-combined electronics has witnessed only incremental developments in the past decade. First, the tuning principle has largely been unchanged (leveraging the shape anisotropy of LC molecules in microscale and continuum mechanics in macroscale for variable polarizability). Second, LC-enabled devices’ performance has yet to be standardized (suboptimal case by case at different frequency domains). In this context, this work points out three underestimated knowledge gaps as drawn from our theoretical designs, computational simulations, and experimental prototypes, respectively. The first gap reports previously overlooked physical constraints from the analytical model of an LC-embedded coaxial DLPS. A new geometry-dielectric bound is identified. The second gap deals with the lack of consideration in the suboptimal dispersion behavior in differential delay time (DDT) and differential delay length (DDL) for LC phase-shifting devices. A new figure of merit (FoM) is proposed and defined at the V-band (60 GHz) to comprehensively evaluate the ratios of the DDT and DDL over their standard deviations across the 54 to 66 GHz spectrum. The third identified gap deals with the in-depth explanation of our recent experimental results and outlook for partial leakage attack analysis of LC phase shifters in modern eavesdropping. Full article

To meet the requirements of non-mechanical beam scanning and acquisition in space laser communication, this study proposes a two-dimensional scanning and acquisition method based on a silicon-based optical phased array (OPA). The OPA utilizes thermo-optic phase modulation to achieve horizontal beam pointing, while vertical beam pointing is controlled by wavelength tuning. By combining the OPA with a rectangular spiral scanning strategy, non-mechanical scanning is realized and beam acquisition experiments are carried out. Experimental results demonstrate that for an 8° step signal, the horizontal and vertical rise times are 156.8 μs and 214.76 ms, respectively. A full scan of 440 points covering a ±4° field of view is completed in 8.119 s. Acquisition experiments were conducted assuming a Gaussian-distributed uncertainty region (standard deviation $\sigma =1°$). Out of 106 independent trials, a success rate of 97.17% was achieved with an average acquisition time of 0.41 s. This work experimentally applies a rectangular spiral scanning strategy to an OPA-based acquisition system, addressing a capability that has been largely missing in previous studies. These results verify that the OPA technology has good scanning efficiency and acquisition robustness in space laser communication applications. Full article

We experimentally and theoretically demonstrate coexistence of three different wavelength-multiplexed bound dual-frequency pulses in an all-fiber mode-locked fiber laser, effectively achieved by exploiting polarization-dependent loss effects and two uneven gain peaks of Er-doped fiber. With the single wall carbon-nanotube-based intensity modulation, wavelength-multiplexed dual-frequency pulses located at 1531.1 nm and 1556.6 nm are obtained. Changing the polarization rotation angles in the fiber cavity, one of the two asynchronous pulses evolves into a bound state of a doublet, in which the center wavelength of the bound solitons is centered at ~1530 nm or ~1556 nm. The relative phase between the two bound solitons or modulation depth of bound solitons can be switched by a polarization controller. A simulation method based on coupled Ginzburg–Landau equations is provided to characterize the laser physics and understand the mechanism behind the dynamics of tuning between different bound dual-frequency pulses. The proposed fiber laser will provide a potential way to understand multiple soliton dynamics and implementation in optical frequency combs generation. Full article

This study provides a practice-oriented sensitivity analysis of DeePC for pressure management in water distribution systems. Two public benchmark systems were used, Fossolo (simpler) and Modena (more complex). Each run fixed a monitored node and pressure reference, applied the same randomized identification phase followed by closed-loop control, and quantified performance by the mean absolute error (MAE) of the node pressure relative to the reference value. To better characterize closed-loop behavior beyond MAE, we additionally report (i) the maximum deviation from the reference over the control window and (ii) a valve actuation effort metric, normalized to enable fair comparison across different numbers of valves and, where relevant, different control update rates. Motivated by the need for practical guidance on how hydraulic boundary conditions and algorithmic choices shape DeePC performance in complex water networks, we examined four factors: (1) placement of an additional internal PRV, supplementing the reservoir-outlet PRVs; (2) the control time step $(\Delta t)$; (3) a uniform reservoir-head offset $(\Delta h)$; and (4) DeePC regularization weights ${(\lambda }_g,{\lambda }_u,{\lambda }_y)$. Results show strong location sensitivity, in Fossolo, topologically closer placements tended to lower MAE, with exceptions; the baseline MAE with only the inlet PRV was 3.35 [m], defined as a DeePC run with no additions, no extra valve, and no changes to reservoir head, time step, or regularization weights. Several added-valve locations improved the MAE (i.e., reduced it) below this level, whereas poor choices increased the error up to ~8.5 [m]. In Modena, 54 candidate pipes were tested, the baseline MAE was 2.19 [m], and the best candidate (Pipe 312) achieved 2.02 [m], while pipes adjacent to the monitored node did not outperform the baseline. Decreasing $\Delta t$ across nine tested values consistently reduced MAE, with an approximately linear trend over the tested range, maximum deviation was unchanged (7.8 [m]) across all $\Delta t$ cases, and actuation effort decreased with shorter steps after normalization. Changing reservoir head had a pronounced effect: positive offsets improved tracking toward a floor of ≈0.49 [m] around $\Delta h$ ≈ +30 [m], whereas negative offsets (below the reference) degraded performance. Tuning of regularization weights produced a modest spread (≈0.1 [m]) relative to other factors, and the best tested combination (λy, λg, λu) = (10², 10⁻³, 10⁻²) yielded MAE ≈ 2.11 [m], while actuation effort was more sensitive to the regularization choice than MAE/max deviation. We conclude that baseline system calibration, especially reservoir heads, is essential before running DeePC to avoid biased or artificially bounded outcomes, and that for large systems an external optimization (e.g., a genetic-algorithm search) is advisable to identify beneficial PRV locations. Full article

Speed-of-sound (SoS) heterogeneities introduce pronounced artifacts in full-ring photoacoustic tomography (PAT), degrading imaging accuracy and constraining its practical use. We introduce a transfer learning-based deep neural framework that couples an ImageNet-pretrained ResNet-50 encoder with a tailored deconvolutional decoder to perform end-to-end artifact correction on photoacoustic tomography reconstructions. We propose a two-phase curriculum learning protocol, initial pretraining on simulations with uniform SoS mismatches, followed by fine-tuning on spatially heterogeneous SoS fields, to improve generalization to complex aberrations. Evaluated on numerical models, physical phantom experiments and in vivo experiments, the framework provides substantial gains over conventional back-projection and U-Net baselines in mean squared error, structural similarity index measure, and Pearson correlation coefficient, while achieving an average inference time of 17 ms per frame. These results indicate that the proposed approach can reduce the sensitivity of full-ring PAT to SoS inhomogeneity and improve full-view reconstruction quality. Full article

Effective engineering modeling requires simultaneously addressing feature selection and hyperparameter interdependence, a challenge exacerbated by high-dimensional data characteristics in complex engineering modeling. Traditional optimization methods typically address these two aspects separately, which limits overall model performance. This study introduces a hybrid framework to enhance the performance of extreme gradient boosting (XGBoost) in engineering applications. The framework comprises two main phases: first, preliminary feature selection guided by prior domain knowledge and statistical analysis to reduce data dimensionality while preserving interpretability; second, a discrete symbiotic organisms search algorithm with adaptive feature mutation (DMSOS) simultaneously optimizes feature subsets and XGBoost hyperparameters. The DMSOS employs a discretization strategy to separate feature selection from hyperparameter tuning, facilitating focused searches within distinct spaces. An adaptive mutation mechanism dynamically adjusts exploration intensity based on iteration progress and feature importance. Additionally, evaluations on 1414 field-measured blasting vibration data demonstrate that the proposed DMSOS-XGBoost model achieves superior prediction performance, with an r² of 0.96696 and RMSE of 0.02636, outperforming models optimized via traditional sequential approaches. Further interpretability analysis highlights spatial geometry and explosive load as critical features, offering actionable insights for environmental risk management. This research provides a valuable methodological reference for engineering modeling scenarios requiring simultaneous optimization of features and hyperparameters. Full article

The miniaturization of dielectric sensing has driven the development of both oscillator- and receiver-based sensors. Wide-frequency-range and low-power-consumption voltage-controlled oscillators (VCOs) are required as a reference clock for receiver-based dielectric spectroscopy. In this paper, we propose a switched coupled inductor VCO offering sufficiently wide bandwidth in a power-efficient manner. The proposed switched coupled inductor offers higher coupling factor and mutual inductance compared to direct switched inductor schemes along with a higher quality factor and tuning range. The proposed switched coupled inductor improved the frequency tuning range by 21% compared to the conventional VCO. The measurement results show that the proposed VCO oscillates from 4.7 to 8.8 GHz frequency, suitable for dielectric spectroscopy sensors. With only 4.5 mW power consumption, the proposed VCO can achieve −103.3 dBc/Hz phase noise at 1 MHz offset, with a resulting tuning range figure-of-merit (FOMT) of −187.4 dBc/Hz. Full article

To achieve accurate voltage sag prediction and early warning, thereby improving power quality, a hybrid voltage sag prediction framework is proposed by integrating Kernel Entropy Component Analysis (KECA) with an improved Northern Goshawk Optimization (NGO) algorithm for hyperparameter tuning of a CNN-LSTM model. First, to address the limitations of the original NGO, such as proneness to falling into local optima and high randomness of the initial population distribution, a refraction-opposition-based learning mechanism is introduced to enhance population diversity and expand the search space. Furthermore, a sine–cosine strategy (SCA) with nonlinear weight coefficients is integrated into the exploration phase to dynamically adjust the search step size, optimizing the balance between global exploration and local exploitation, thereby boosting convergence speed and accuracy. The improved algorithm (SCNGO) is then utilized to optimize the hyperparameters of the CNN-LSTM model. Second, KECA is applied to voltage-sag-related data to extract key features and eliminate redundant information, and the resulting dimensionally reduced data are fed as input to the SCNGO-CNN-LSTM model to further improve prediction performance. Experimental results demonstrate that the SCNGO-CNN-LSTM model outperforms other comparative models significantly across multiple evaluation metrics. Compared with NGO-CNN-LSTM, GWO-CNN-LSTM, and the original CNN-LSTM, the proposed method achieves a mean squared error (MSE) reduction of 53.45%, 44.68%, and 66.76%, respectively. The corresponding root mean squared error (RMSE) is decreased by 25.33%, 18.61%, and 36.92%, while the mean absolute error (MAE) is reduced by 81.23%, 77.04%, and 86.06%, respectively. These results confirm that the proposed framework exhibits superior feature representation capability and significantly improves voltage sag prediction accuracy. Full article

We propose an external-cavity laser that combines wide tunability with narrow linewidth. The design utilizes a low-loss Si₃N₄ waveguide and a thermally tuned cascaded triple-ring resonator to enable continuous wavelength tuning. The numerical simulations indicate that the proposed laser exhibits a tuning range of 64 nm with a sub-kHz linewidth, an SMSR of more than 80 dB, an output power of 24 mW and a linewidth of 193 Hz at 1550 nm. Furthermore, we perform comparative system-level simulations using QPSK and 16QAM coherent optical fiber links at 50 Gbaud over 100 km. Under identical conditions, when the laser linewidth is reduced from 1 MHz level to 193 Hz, the BER of 16QAM decreases from 1.5 × 10⁻³ to 5.3 × 10⁻⁵. These results indicate that a narrow linewidth effectively mitigates phase noise degradation in high-order modulation formats. With its narrow linewidth, wide tuning range, high SMSR, and high output power, this laser serves as a promising on-chip light source for high-resolution sensing and coherent optical communications. Full article

As a highly integrated and compact power unit, the motor-pump finds critical applications in emerging electric vehicle (EV) domains such as electro-hydraulic braking and steering systems, where its vibration and noise performance directly impacts cabin comfort. A key factor limiting its NVH (Noise, Vibration, and Harshness) performance is the electromagnetic vibration and noise induced by the cogging torque of the built-in brushless DC motor (BLDCM). Traditional suppression methods that rely on stator auxiliary slots exhibit certain limitations. To address this issue, this paper proposes a collaborative optimization method integrating multi-parameter scanning and response surface methodology (RSM) for the design of auxiliary slots on the motor-pump’s stator teeth. The approach begins with a multi-parameter scanning phase to identify a promising region for global optimization. Subsequently, an accurate RSM-based prediction model is established to enable refined parameter tuning. Results demonstrate that the optimized stator structure achieves a 91.2% reduction in cogging torque amplitude for the motor-pump. Furthermore, this structure effectively suppresses radial electromagnetic force, leading to a 5.1% decrease in the overall sound pressure level. This work provides a valuable theoretical foundation and a systematic design methodology for cogging torque mitigation and low-noise design in motor-pumps. Full article