Search Results (1,406)

The silver carp (Hypophthalmichthys molitrix) is a filter-feeding fish species, characterized by significant morphological transformations in its filter-feeding apparatus, particularly the gill rakers, which are closely associated with dietary changes throughout its development. Despite the importance of these morphological innovations, the molecular mechanisms driving these changes remain largely unexplored. To investigate this, we employed an integrative approach combining scanning electron microscopy (SEM) and comparative transcriptomics to examine the gill rakers at five critical developmental stages (6, 15, 30, 45, and 60 days post-hatching, dph). SEM analysis revealed a structural evolution from sparse, bump-like protrusions to a dense, interlocking mesh. Simultaneously, transcriptomic analysis identified 10,184 differentially expressed genes (DEGs), which showed significant enrichment in pathways such as Focal Adhesion, ECM-Receptor Interaction, and the PI3K-Akt Signaling Pathway. Gene Set Enrichment Analysis (GSEA) indicated a coordinated upregulation of collagen and integrin gene families during the early developmental transition (6 vs. 15 dph), highlighting their crucial role in the formation of the sieve structure. This study reveals the molecular mechanisms of gill raker development in silver carp, providing initial insights into genetic regulation of morphology for ecological adaptation. The findings connect developmental biology, evolutionary biology, and ecology. Full article

Urban stormwater runoff, particularly during first-flush events, carries high loads of fine suspended solids and phosphorus that are difficult to remove with conventional best management practices (BMPs). This study developed and evaluated a laboratory-scale high-efficiency up-flow filtration system with Internet of Things (IoT)-based autonomous control. The system employed 20 mm fiber-ball media in a modular dual-stage up-flow configuration with optimized coagulant dosing to target fine particles (<3 μm) and total phosphorus (TP). Real-time turbidity and pressure monitoring via sensor networks connected to a microcontroller enabled wireless data logging and automated backwash initiation when thresholds were exceeded. Under manual operation, the two-stage filter achieved removals of 96.6% turbidity, 98.8% suspended solids (SS), and 85.6% TP while maintaining head loss below 10 cm. In IoT-controlled single-stage runs with highly polluted influent (turbidity ~400 NTU, SS > 1000 mg/L, TP ~1.6 mg/L), the system maintained >90% SS and ~58% TP removal with stable head loss (~8 cm) and no manual intervention. Turbidity correlated strongly with SS (R² ≈ 0.94) and TP (R² ≈ 0.87), validating its use as a surrogate control parameter. Compared with conventional BMPs, the developed filter demonstrated superior solids capture, competitive phosphorus removal, and the novel capability of real-time autonomous operation, providing proof-of-concept for next-generation smart BMPs capable of meeting regulatory standards while reducing maintenance. Full article

This work proposes a broadband, high-efficiency extended continuous class-F (ECCF) power amplifier (PA) with a negative-feedback network structure. Compared with the traditional direct cascade connection of a PA and a filter, the design introduces a novel negative feedback filter structure. The transistor and filter synthesis network co-design method aims to compensate for the gain and efficiency drop of this PA in both high and low frequency bands, resulting in relatively flat gain and efficiency performance over a wide band. Consequently, there is a need to enhance the security and efficiency of wireless communication systems. This work verifies the proposed method using a designed and fabricated 10 W GaN HEMT device. The measured data reveal that the designed PA achieves 100% relative bandwidth from 1.2 GHz to 3.6 GHz, with a drain efficiency (DE) of 59.5~67.4%, an output power of 38.8~41.8 dBm, and a large signal gain of 8.8~11.8 dB. Full article

Current microgrid research primarily focuses on radial topologies and their control strategies, while exploration of the time-domain dynamic behavior of closed-loop controlled microgrids remains relatively insufficient. This research gap makes it difficult to directly observe and deeply analyze the evolution mechanisms of critical phenomena, such as oscillations and instability, when they occur. Therefore, conducting time-domain analysis on closed-loop structures is crucial for revealing system instability mechanisms and ensuring their safe and stable operation. This paper establishes a state-space model for a closed-loop microgrid structure composed of multiple parallel inverters and conducts time-domain stability analysis under grid-connected operation. First, a mathematical model of the closed-loop microgrid system is constructed using state-space equations. Subsequently, time-domain analysis of small-signal stability is performed on the model. By varying key parameters such as the droop coefficient, the influence patterns on system stability are investigated. The results indicate that the droop control coefficient and LC filter parameters exert the most significant impact on system dynamic characteristics. Simulation experiments validate the correctness and effectiveness of the theoretical model. Finally, the time-domain characteristics of this model were further analyzed and validated through simulations. Results demonstrate that the system maintains robust stability under disturbances even in grid-connected mode. Full article

Narrowband Internet of Things (NB-IoT) was designed as a key Low-Power Wide-Area Network technology when 5G networks were established. The ideal quadrature demodulation in NB-IoT relies on the fundamental symmetry between the in-phase (I) and quadrature (Q) branches, characterized by a perfect 90-degree phase shift and matched amplitude. However, practical hardware imperfections in mixers, filters, and ADCs break this symmetry, leading to I/Q imbalances. Moreover, I/Q imbalance is coupled with carrier frequency offset (CFO), which arises from asymmetry in the frequency of the transceiver oscillator. In this paper, we propose a model-embedded lightweight network for joint CFO and I/Q imbalance estimation for NB-IoT systems. An I/Q imbalance compensation model is embedded as a layer to connect two subnetworks, I/Q estimation network (IQENET) and CFO estimation network (CFOENET). By embedding the physical model, the network gains the capability to learn the features of coupling effects during the training process, as the image signals caused by I/Q imbalance are removed before CFO estimation. A phased training strategy is also proposed. In the first phase, the two subnetworks are pre-trained independently. In the second phase, they are fine-tuned jointly to deal with the coupling effects. Simulation results show that the proposed network achieves high estimation accuracy while maintaining low complexity. Full article

Glaucoma is recognized as the second leading cause of blindness globally and a primary cause of irreversible blindness, estimated to affect over 80 million patients worldwide, including 4.5 million in the United States. Though the disease is multifactorial, the primary cause is elevated intraocular pressure (IOP), which damages the optic nerve fibers that connect the eye to the brain, thus interfering with the quality of vision. Current treatments have evolved, which consist of medications, laser therapies, and surgical interventions such as filtering procedures, glaucoma drainage devices (GDDs), and current innovations of minimally invasive glaucoma surgeries (MIGS). This paper aims to discuss the history and evolution of the design and biomaterials employed in GDDs and MIGS. Through a comprehensive review of the literature, we trace the development of these devices from early concepts to modern implants, highlighting advancements in materials science and surgical integration. This historical analysis, ranging from the mid-19th century, reveals a trend towards enhanced biocompatibility, improved efficiency in IOP reduction, and reduced complications. We conclude that the ongoing evolution of GDDs and MIGS underscores a persistent commitment to advancing patient care in glaucoma, paving the way for future device innovations and therapeutic trends to treat glaucoma. Full article

A class of nonlinear filtering problems connected with data fusion from various navigation sensors and a navigation system is considered. A special feature of these problems is that the posterior probability density function (PDF) of the state vector being estimated changes its character from multi-extremal to single-extremal as measurements accumulate. The algorithms based on sequential Monte Carlo methods, which, in principle, provide the possibility of attaining potential accuracy, are computationally complicated, especially when implemented in real time. Traditional recursive algorithms, such as the extended Kalman filter and its iterative modification prove to be inoperable in this case. Two algorithms, devoid of the above drawbacks, are proposed to solve this class of nonlinear filtering problems. The first algorithm, a Recursive Iterative Batch Linearized Smoother (RI-BLS), is essentially a nonrecursive iterative algorithm; at each iteration, it processes all measurements accumulated by the current time of measurement. However, to do this, it uses a recursive procedure: first, the measurements are processed from the first to the current one in the linearized Kalman filter, and then the obtained estimates are processed recursively in reverse time. The second algorithm, a Recursive Iterative Batch Multiple Linearized Smoother (RI-BMLS), is based on the simultaneous use of a set of RI-BLS running in parallel. The application of the proposed algorithms and their advantages are illustrated by a methodological example and solution of the map-aided navigation problem. The calculation of the computational complexity factor has shown that the RI-BLS is more than 15-fold simpler than the particle filter in computational terms, and the RI-BMLS, more than 20-fold with comparable estimation accuracy. Full article

This study presents a bibliometric review of scientific progress concerning the synergy between microbial fuel cells (MFCs) and textile dye remediation. Drawing from the Scopus database, the analysis spans the years 2005–2025 and applies systematic filters to derive a final corpus of 239 articles compatible with Bibliometrix software (4.2.1). Quantitative and structural analyses were conducted using RStudio with the Bibliometrix package, thematic network visualizations via VOSviewer (1.6.19), and frequency matrices, citation rates, and international collaboration indicators organized in Excel. Results reveal exponential growth in scholarly output, particularly within Environmental Sciences, Chemical Engineering, and Microbiology. China and India lead in publication volume, while countries such as the United Kingdom, United States, and Australia show high impact and international collaboration. Co-authorship networks reflect consolidated clusters, though connectivity gaps remain among emerging authors. Bioresource Technology is identified as a central journal, with terms like “wastewater treatment” and “microbial fuel cell” indicating thematic consolidation. Opportunities still exist in areas such as explainable artificial intelligence, integration with microalgae, and heavy metal remediation. Highly cited articles contribute key technical insights, highlighting hybrid configurations and advancements in electrode materials. Strategic mapping suggests that MFCs have evolved from experimental concepts to viable alternatives in industrial sustainability, though scalability, operational costs, and geographic representation remain significant challenges. This bibliometric review not only maps accumulated knowledge but also serves as a strategic compass for guiding future research toward integrated, accessible, and replicable bioelectrochemical technologies for textile dye treatment. Full article

This paper proposes a simplified adaptive filtering approach using a Hammerstein function and the spline interpolation based on a Fair cost function for denoising electrocardiogram (ECG) signals. The use of linear filters in real-world applications has many limitations. Adaptive nonlinear filtering is a key development in tackling the challenge of discovering the specific characteristics of biomimetic systems for each person in order to eliminate unwanted signals. A biomimetic system refers to a system that mimics certain biological processes or characteristics of the human body, in this case, the individual features of a person’s cardiac signals (ECG). Here, the adaptive nonlinear filter is designed to cope with ECG variations and remove unwanted noise more effectively. The objective of this paper is to explore an individual biomedical filter based on adaptive nonlinear filtering for denoising the corrupted ECG signal. The Hammerstein spline adaptive filter (HSAF) architecture consists of two structural blocks: a nonlinear block connected to a linear one. In order to make a smooth convergence, the Fair cost function is introduced for convergence enhancement. The affine projection algorithm (APA) based on the Fair cost function is used to denoise the contaminated ECG signals, and also provides fast convergence. The MIT-BIH 12-lead database is used as the source of ECG biomedical signals contaminated by random noises modelled by Cauchy distribution. Experimental results show that the estimation error of the proposed HSAF–APA–Fair algorithm, based on the Fair cost function, can be reduced when compared with the conventional least mean square-based algorithm for denoising ECG signals. Full article

This study presents an in-depth investigation of an eccentric double-ring microwave resonator comprising two asymmetrically coupled conductive loops connected at a single point. The configuration was systematically analyzed using analytical modeling, full-wave electromagnetic simulations (Ansys HFSS), and experimental characterization. Analytical formulations based on the resonant condition of thin conductive rings provided theoretical estimates of the fundamental and higher-order eigenmodes, while simulations yielded accurate resonance frequencies, transmission responses, and electric field distributions. The transmission coefficient (S₂₁) exhibited two distinct resonance dips at 436 MHz and 708 MHz, confirming strong inter-ring coupling and hybrid mode formation. Electric field mapping revealed pronounced confinement within the resonator region (E > 170 V/m) and substantial attenuation of the transmitted field (E < 13 V/m), demonstrating efficient electromagnetic energy suppression. Experimental results showed excellent consistency with theoretical predictions. This paper aims to establish a compact, low-cost, and tunable resonant structure capable of frequency-selective attenuation and field confinement without using lossy materials. Unlike conventional symmetric resonators, the eccentric configuration enables enhanced coupling control and modal diversity, making it highly relevant for the design of next-generation electromagnetic shielding, filtering, and sensing systems. Full article

As the primary interface for integrating renewable energy sources such as wind and solar power into the grid, inverters are prone to inducing sub-/super-synchronous or medium-to-high-frequency oscillations during grid-connected operation under weak grid conditions. Optimizing the control structure of a single wind turbine inverter struggles to address multi-mode resonance issues comprehensively. Therefore, a cooperative control strategy for parallel-coupled inverters is proposed. First, a frequency-domain impedance reconstruction method for parallel wind turbines is proposed based on the phase-neutralizing characteristics and damping variation patterns of parallel-coupled impedances. Second, the damping characteristics of inverters are enhanced through the design of an additional damping controller, while the phase-frequency characteristics of wind turbines are improved using active damping based on notch filters. Finally, simulation models based on 2.5 MW permanent magnet synchronous generator (PMSG) units validate the effectiveness of the control strategy. Research results demonstrate that this cooperative control strategy effectively suppresses sub-/super-synchronous and medium-to-high-frequency oscillations: In the 0~300 Hz key oscillation band, the amplitude suppression rate of oscillating current reaches ≥60%, the total harmonic distortion (THD) of the 5th harmonic at the grid connection point decreases from 4.465% to 3.518%. Full article

The proliferation of power converters in modern energy production systems has led to increased harmonic content due to the commutation of active switching devices. This increase in harmonics contributes to lower system efficiency, reduced power factor, and consequently, a higher reactive power requirement. To address these issues, this paper presents both simulation and experimental results of various control strategies implemented on Parallel Voltage Source Inverters (PVSI) for harmonic mitigation. The proposed control strategies are categorized into direct and indirect control methods. The direct control techniques implemented include the instantaneous power method (PQ), the synchronous algorithm (DQ), the maximum principle method (MAX), the algorithm based on synchronization of current with the voltage positive-sequence component (SEC-POZ), and two methods employing the separating polluting components approach using a band-stop filter and a low-pass filter. The main innovation in these active power filter (APF) control strategies, compared to traditional or existing technologies, is the real-time digital implementation on high-speed platforms, specifically FPGAs. Unlike slower microcontroller-based systems with limited processing capabilities, FPGA-based implementations allow parallel processing and high-speed computation, enabling the execution of complex control algorithms with minimal latency. Additionally, the enhanced reference current generation achieved through the seven applied methods provides precise harmonic compensation under highly distorted and nonlinear load conditions. Another key advancement is the integration with Smart Grid functionalities, allowing IoT connectivity and remote diagnostics, which enhances system monitoring and operational flexibility. Following validation on an experimental test bench, these algorithms were implemented and tested on industrial APF prototypes powered by a standardized three-phase network supply. All control strategies demonstrated an effective reduction in total harmonic distortion (THD) and improvement in power factor. Experimental findings were used to provide recommendations for choosing the most effective control solution, focusing on minimizing THD and enhancing system performance. Full article

Second-order notch filters (NFs) with constant coefficients are often used as part of feedback controllers in grid-connected power conversion systems to prevent unwanted harmonic content polluting the closed control loops. In practice, the value of the mains frequency resides within a certain known range rather than remaining constant. Hence, the correct selection of NF coefficients is crucial for ensuring that the desired performance is maintained within the whole expected mains frequency range. Bilinear transformation (BLT) with notch frequency prewarping is often adopted to convert an NF from a continuous to a digital form. While accurately preserving the notch frequency location, the method reduces the filter bandwidth. As a remedy, BLT with both notch frequency and damping ratio prewarping may be employed. Nevertheless, some inaccuracy remains under low sampling-to-notch frequency ratios. This technical note demonstrates that the issue may be solved by prewarping the boundary values of the expected harmonic frequency range rather than the notch frequency and/or damping factor before applying the BLT. Simulation results accurately support the presented issue and proposed solution. Full article

This study explores how research on carbon capture technologies (CCTs) has developed over time and shows how semantic text mining can improve the analysis of technology trajectories. Although CCTs are widely viewed as essential for net-zero transitions, the literature is still scattered across many subthemes, and links between engineering advances, infrastructure deployment, and policy design are often weak. Methods that rely mainly on citations or keyword frequencies tend to overlook contextual meaning and the subtle diffusion of ideas across these strands, making it difficult to reconstruct clear developmental pathways. To address this problem, we ask the following: How do CCT topics change over time? What evolutionary mechanisms drive these transitions? And which themes act as bridges between technical lineages? We first build a curated corpus using a PRISMA-based screening process. We then apply BERTopic, integrating Sentence-BERT embeddings with UMAP, HDBSCAN, and class-based TF-IDF, to identify and label coherent semantic topics. Topic evolution is modeled through a PCC-weighted, top-K filtered network, where cross-year connections are categorized as inheritance, convergence, differentiation, or extinction. These patterns are further interpreted with a Fish-Scale Multiscience mapping to clarify underlying theoretical and disciplinary lineages. Our results point to a two-stage trajectory: an early formation phase followed by a period of rapid expansion. Long-standing research lines persist in amine absorption, membrane separation, and metal–organic frameworks (MOFs), while direct air capture emerges later and becomes increasingly stable. Across the full period, five evolutionary mechanisms operate in parallel. We also find that techno-economic assessment, life-cycle and carbon accounting, and regulation–infrastructure coordination serve as key “weak-tie” bridges that connect otherwise separated subfields. Overall, the study reconstructs the core–periphery structure and maturity of CCT research and demonstrates that combining semantic topic modeling with theory-aware mapping complements strong-tie bibliometric approaches and offers a clearer, more transferable framework for understanding technology evolution. Full article

In electrical power systems, the extraction of the fundamental positive sequence (FPS) is paramount for synchronization, power calculation, and a wide variety of metering and control tasks. This work shows that a moving average filter (MAF) used in the synchronous reference frame to extract the FPS from electrical systems is equivalent to the cascade connection of a comb filter (CF) with a second-order harmonic oscillator (SOHO), with all its variables expressed in fixed reference frame coordinates. On the one hand, the CF introduces an infinite number of notches tuned at all integer harmonics of the fundamental frequency ${\omega }_0$, thus suppressing harmonic distortion in the incoming signal and acting as a repetitive-based pre-filter (RPF). On the other hand, the SOHO is responsible for delivering the fundamental component of the input signal with a unitary gain, while additionally reducing the effect of harmonic distortion. Then, it is shown that other RPFs built from previously reported repetitive schemes (all-harmonics, odd-harmonics, and the $6\ell \pm 1$ harmonics) can be placed instead of the CF, giving rise to a family of FPS detectors. In particular, this work also shows that the CF-SOHO is a special case of the FPS detector based on the all-harmonics RPF. This work provides the mathematical derivation of the FPS detector structure, tuning rules for the SOHO gain associated with each FPS detector, as well as experimental results under a reference signal subject to perturbations such as unbalance, harmonic distortion, phase, and amplitude jumps, exhibiting convergence in only half the fundamental period in most carried out tests. Full article