Search Results (2,102)

This study introduces two novel methodologies for solving systems of Fredholm integral equations, with particular emphasis on second-kind equations. The first method integrates the Sinc-collocation technique with a newly developed singular exponential transformation, enhancing convergence behavior and numerical stability. A comprehensive convergence analysis is conducted to support this approach. The second method employs a double exponential transformation, leading to a pair of linear equations whose solvability is established using the double projection method. Rigorous theoretical analysis is presented, including convergence theorems and newly derived error bounds. A system of two Fredholm integral equations is treated as a practical case study. Numerical examples are provided to illustrate the effectiveness and accuracy of the proposed methods, substantiating the theoretical results. Full article

With their superior switching speed, GaN high-electron-mobility transistors (HEMTs) enable high power density, reduce energy losses, and increase power efficiency in a wide range of applications, such as power electronics, due to their high breakdown voltage. GaN-HEMT devices are subject to long-term reliability due to the self-heating effect and lattice mismatch between the SiC substrate and the GaN. Depletion-mode GaN HEMTs are utilized for radio frequency applications, and this work investigates three wide-bandgap (WBG) GaN HEMT fixed-frequency oscillators with output buffers. The first GaN-on-SiC HEMT oscillator consists of an HEMT amplifier with an LC feedback network. With the supply voltage of 0.8 V, the single-ended GaN oscillator can generate a signal at 8.85 GHz, and it also supplies output power of 2.4 dBm with a buffer supply of 3.0 V. At 1 MHz frequency offset from the carrier, the phase noise is −124.8 dBc/Hz, and the figure of merit (FOM) of the oscillator is −199.8 dBc/Hz. After the previous study, the hot-carrier stressed RF performance of the GaN oscillator is studied, and the oscillator was subject to a drain supply of 8 V for a stressing step time equal to 30 min and measured at the supply voltage of 0.8 V after the step operation for performance benchmark. Stress study indicates the power oscillator with buffer is a good structure for a reliable structure by operating the oscillator core at low supply and the buffer at high supply. The second balanced oscillator can generate a differential signal. The feedback filter consists of a left-handed transmission-line LC network by cascading three unit cells. At a 1 MHz frequency offset from the carrier of 3.818 GHz, the phase noise is −131.73 dBc/Hz, and the FOM of the 2nd oscillator is −188.4 dBc/Hz. High supply voltage operation shows phase noise degradation. The third GaN cross-coupled VCO uses 8-shaped inductors. The VCO uses a pair of drain inductors to improve the Q-factor of the LC tank, and it uses 8-shaped inductors for magnetic coupling noise suppression. At the VCO-core supply of 1.3 V and high buffer supply, the FOM at 6.397 GHz is −190.09 dBc/Hz. This work enhances the design techniques for reliable GaN HEMT oscillators and knowledge to design high-performance circuits. Full article

Background: Prosthetic cementation using the biologically oriented preparation technique (BOPT) presents challenges in removing excess cement from the gingival sulcus, due to the absence of a finishing line and the impossibility of using absolute isolation with a rubber dam. This study aimed to evaluate the effectiveness of relative isolation using polytetrafluoroethylene (PTFE) tape in reducing cement retention during BOPT cementation. Methods: Fifteen 3D-printed resin models were created from an intraoral scan of a patient restored with BOPT in both upper central incisors. Each model included removable gingiva. Splinted polymethylmethacrylate (PMMA) provisional crowns were fabricated and cemented with temporary cement. One central incisor was isolated with PTFE (0.1 mm or 0.2 mm), while the contralateral tooth was left unisolated as a control. After debonding, digital scanning and volumetric analysis using root mean square (RMS) deviation were performed to quantify retained cement. Paired t-tests were applied to compare groups. Results: The mean RMS for the PTFE group was 0.1248 ± 0.0519 mm, compared to 0.1973 ± 0.0361 mm in the non-isolated group (p < 0.001). No significant difference was found between PTFE thicknesses of 0.1 mm and 0.2 mm (p = 0.388). Conclusions: PTFE tape is effective for relative isolation when rubber dam placement is not feasible in BOPT restorations. Further clinical studies are recommended to confirm these findings in vivo. Full article

The advance of 5G technology marks a significant evolution in wireless communications, characterized by ultra-high data rates, low latency, and massive connectivity across varied areas. A fundamental enabler of these capabilities is represented by beamforming, an advanced signal processing technique that focuses radio energy to a specific user equipment (UE), thereby enhancing signal quality—crucial for maximizing spectral efficiency. The work presents a classification of beamforming techniques, categorized according to the implementation within 5G New Radio (NR) architectures. Furthermore, the paper investigates beam management (BM) procedures, which are essential Layer 1 and Layer 2 mechanisms responsible for the dynamic configuration, monitoring, and maintenance of optimal beam pair links between gNodeBs and UEs. The article emphasizes the spectral spectrogram of Synchronization Signal Blocks (SSBs) generated under various deployment scenarios, illustrating how parameters such as subcarrier spacing (SCS), frequency band, and the number of SSBs influence the spectral occupancy and synchronization performance. These insights provide a technical foundation for optimizing initial access and beam tracking in high-frequency 5G deployments, particularly within Frequency Range (FR2). Additionally, the versatility of 5G’s time-frequency structure is demonstrated by the spectrogram analysis of SSBs in a variety of deployment scenarios. These results provide insight into how different configurations affect the synchronization signals’ temporal and spectral occupancy, which directly affects initial access, cell identification, and energy efficiency. Full article

Data over sound (DoS) is an established technique that has experienced a resurgence in recent years, finding applications in areas such as contactless payments, device pairing, authentication, presence detection, toys, and offline data transfer. This study introduces CardiaWhisper, a system that extends the DoS concept to the medical domain by using a medical data-over-sound (MDoS) framework. CardiaWhisper integrates wearable biomedical sensors with home care systems, edge or IoT gateways, and telemedical networks or cloud platforms. Using a transmitter device, vital signs such as ECG (electrocardiogram) signals, PPG (photoplethysmogram) signals, RR (respiratory rate), and ACC (acceleration/movement) are sensed, conditioned, encoded, and acoustically transmitted to a nearby receiver—typically a smartphone, tablet, or other gadget—and can be further relayed to edge and cloud infrastructures. As a case study, this paper presents the real-time transmission and processing of ECG signals. The transmitter integrates an ECG sensing module, an encoder (either a PLL-based FM modulator chip or a microcontroller), and a sound emitter in the form of a standard piezoelectric speaker. The receiver, in the form of a mobile phone, tablet, or desktop computer, captures the acoustic signal via its built-in microphone and executes software routines to decode the data. It then enables a range of control and visualization functions for both local and remote users. Emphasis is placed on describing the system architecture and its key components, as well as the software methodologies used for signal decoding on the receiver side, where several algorithms are implemented using open-source, platform-independent technologies, such as JavaScript, HTML, and CSS. While the main focus is on the transmission of analog data, digital data transmission is also illustrated. The CardiaWhisper system is evaluated across several performance parameters, including functionality, complexity, speed, noise immunity, power consumption, range, and cost-efficiency. Quantitative measurements of the signal-to-noise ratio (SNR) were performed in various realistic indoor scenarios, including different distances, obstacles, and noise environments. Preliminary results are presented, along with a discussion of design challenges, limitations, and feasible applications. Our experience demonstrates that CardiaWhisper provides a low-power, eco-friendly alternative to traditional RF or Bluetooth-based medical wearables in various applications. Full article

Understanding the interactions between specific cell types within tissue environments is essential for elucidating key biological processes, such as immune responses, cancer progression, inflammation, and development, in both physiological and pathological studies. The predominant methods for analyzing cell–cell interactions (CCI) rely primarily on statistical inference using mapping or network-based techniques. However, these approaches often struggle to prioritize meaningful interactions owing to the high sparsity and heterogeneity inherent in single-cell RNA sequencing (scRNA-seq) data, where small but biologically important differences can be easily overlooked. To overcome these limitations, we developed PriorCCI, a deep-learning framework that leverages a convolutional neural network (CNN) alongside Grad-CAM++, an explainable artificial intelligence algorithm. This study aims to provide a scalable, interpretable, and biologically meaningful framework for systematically identifying and prioritizing key ligand–receptor interactions between defined cell-type pairs from single-cell RNA-seq data, particularly in complex environments such as tumors. PriorCCI effectively prioritizes interactions between cancer and other cell types within the tumor microenvironment and accurately identifies biologically significant interactions related to angiogenesis. By providing a visual interpretation of gene-pair contributions, our approach enables robust inference of gene–gene interactions across distinct cell types from scRNA-seq data. Full article

Circulating fluidized bed fly ash (CFBFA) stockpiles release alkaline dust, high-pH leachate, and secondary CO₂/SO₂—an environmental burden that exceeds 240 Mt yr⁻¹ in China alone. Yet, barely 25% is recycled, because the high f-CaO/SO₃ contents destabilize conventional cementitious products. Here, we presents a pressurized flue gas heat curing (FHC) route to bridge this scientific deficit, converting up to 85 wt% CFBFA into structural lightweight gravel. The gypsum dosage was optimized, and a 1:16 (gypsum/CFBFA) ratio delivered the best compromise between early ettringite nucleation and CO₂-uptake capacity, yielding the highest overall quality. The optimal mix reaches 9.13 MPa 28-day crushing strength, 4.27% in situ CO₂ uptake, 1.75 g cm⁻³ bulk density, and 3.59% water absorption. Multi-technique analyses (SEM, XRD, FTIR, TG-DTG, and MIP) show that FHC rapidly consumes expansive phases, suppresses undesirable granular-ettringite formation, and produces a dense calcite/needle-AFt skeleton. The FHC-treated CFBFA composite gravel demonstrates 30.43% higher crushing strength than JTG/TF20-2015 standards, accompanied by a water absorption rate 28.2% lower than recent studies. Its superior strength and durability highlight its potential as a low-carbon lightweight aggregate for structural engineering. A life-cycle inventory gives a cradle-to-gate energy demand of 1128 MJ t⁻¹ and a process GWP of 226 kg CO₂-eq t⁻¹. Consequently, higher point-source emissions paired with immediate mineral sequestration translate into a low overall climate footprint and eliminate the need for CFBFA landfilling. Full article

We present a lightweight autonomous driving method that uses a low-cost camera, a simple end-to-end convolutional neural network architecture, and smoother driving techniques to achieve energy-efficient vehicle control. Instead of directly constructing a mapping from raw sensory input to the action, our network takes the frame-to-frame visual difference as one of the crucial inputs to produce control commands, including the steering angle and the speed value at each time step. This choice of input allows highlighting the most relevant parts on raw image pairs to decrease the unnecessary visual complexity caused by different road and weather conditions. Additionally, our network achieves the prediction of the vehicle’s upcoming control commands by incorporating a view synthesis component into the model. The view synthesis, as an auxiliary task, aims to infer a novel view for the future from the historical environment transformation cue. By combining both the current and upcoming control commands, our framework achieves driving smoothness, which is highly associated with energy efficiency. We perform experiments on benchmarks to evaluate the reliability under different driving conditions in terms of control accuracy. We deploy a mobile robot outdoors to evaluate the power consumption of different control policies. The quantitative results demonstrate that our method can achieve energy efficiency in the real world. Full article

Modeling mainshock–aftershock ground motions is essential for seismic risk assessment, especially in regions experiencing frequent earthquakes. Recent studies have often employed Copula-based joint distributions or machine learning techniques to simulate the statistical dependency between mainshock and aftershock parameters. While effective at capturing nonlinear correlations, these methods are typically black box in nature, data-dependent, and difficult to generalize across tectonic settings. More importantly, they tend to focus solely on marginal or joint parameter correlations, which implicitly treat mainshocks and aftershocks as independent stochastic processes, thereby overlooking their inherent spectral interaction. To address these limitations, this study proposes an explicit and parameterized modeling framework based on the evolutionary power spectral density (EPSD) of random ground motions. Using the magnitude difference between a mainshock and an aftershock as the control variable, we derive attenuation relationships for the amplitude, frequency content, and duration. A coherence function model is further developed from real seismic records, treating the mainshock–aftershock pair as a vector-valued stochastic process and thus enabling a more accurate representation of their spectral dependence. Coherence analysis shows that the function remains relatively stable between 0.3 and 0.6 across the 0–30 Rad/s frequency range. Validation results indicate that the simulated response spectra align closely with recorded spectra, achieving R² values exceeding 0.90 and 0.91. To demonstrate the model’s applicability, a case study is conducted on a representative frame structure to evaluate seismic vulnerability and economic loss. As the mainshock PGA increases from 0.2 g to 1.2 g, the structure progresses from slight damage to complete collapse, with loss rates saturating near 1.0 g. These findings underscore the engineering importance of incorporating mainshock–aftershock spectral interaction in seismic damage and risk modeling, offering a transparent and transferable tool for future seismic resilience assessments. Full article

Complex oxides with the general formula Gd₂(Ti_1−xZr_x)₂O₇ are promising candidates for radioactive waste immobilization due to their capacity to withstand radiation by dissipating part of the free energy driving defect creation and phase transitions. In this study, samples with varying zirconium content (xZr = 0.00, 0.15, 0.25, 0.375, 0.56, 0.75, 0.85, 1.00) were synthesized via the sol–gel method and thermally treated at 500 °C to obtain nanosized powders mimicking the defective structure of irradiated materials. Synchrotron-based techniques were employed to investigate their structural properties: High-Resolution X-ray Powder Diffraction (HR-XRPD) was used to assess long-range structure, while Pair Distribution Function (PDF) analysis and Extended X-ray Absorption Fine Structure (EXAFS) spectroscopy provided insights into the local structure. HR-XRPD data revealed that samples with low Zr content (xZr ≤ 0.25) are amorphous. Increasing Zr concentration led to the emergence of a crystalline phase identified as defective fluorite (xZr = 0.375, 0.56). Samples with the highest Zr content (xZr ≥ 0.75) were fully crystalline and exhibited only the fluorite phase. The experimental G(r) functions of the fully crystalline samples in the low r range are suitably fitted by the Weberite structure, mapping the relaxations induced by structural disorder in defective fluorite. These structural insights informed the subsequent EXAFS analysis at the Zr-K and Gd-L₃ edges, confirming the splitting of the cation–cation distances associated with different metal species. Moreover, EXAFS provided a local structural description of the amorphous phases, identifying a consistent Gd-O distance across all compositions. Full article

This study explores asymmetric volatility structures within multivariate hysteretic autoregressive (MHAR) models that incorporate conditional correlations, aiming to flexibly capture the dynamic behavior of global financial assets. The proposed framework integrates regime switching and time-varying delays governed by a hysteresis variable, enabling the model to account for both asymmetric volatility and evolving correlation patterns over time. We adopt a fully Bayesian inference approach using adaptive Markov chain Monte Carlo (MCMC) techniques, allowing for the joint estimation of model parameters, Value-at-Risk (VaR), and Marginal Expected Shortfall (MES). The accuracy of VaR forecasts is assessed through two standard backtesting procedures. Our empirical analysis involves both simulated data and real-world financial datasets to evaluate the model’s effectiveness in capturing downside risk dynamics. We demonstrate the application of the proposed method on three pairs of daily log returns involving the S&P500, Bank of America (BAC), Intercontinental Exchange (ICE), and Goldman Sachs (GS), present the results obtained, and compare them against the original model framework. Full article

Geometric morphometrics is performed on different species in different contexts. Here, the aim was to investigate morphological differences in the head of the Sanmartinero Creole bovine to examine head shape variations between sexes using geometric morphometric methods. A sample of cranial pictures of 43 animals (13 males and 30 females) was obtained, and form (size + shape) was studied by means of geometric morphometric techniques using a set of 14 landmarks. This approach eliminated potential dietary effects, ensuring that the observed shape variations were primarily due to intrinsic morphological differences. Sexual dimorphism was found in form (for both size and shape) of the head of the Sanmartinero Creole bovine breed. Males had significantly larger heads based on centroid size (U = 714, p = 0.0004), confirming true sexual size differences, and Principal Component Analysis revealed overlapping head shapes with sexual dimorphism concentrated at midline sagittal landmarks (between the most rostral and caudal orbit points) and paired lateral points, indicating that males have broader and longer heads. The two evaluated characters (head size and shape) are of special interest for the conservation of the breed, especially in those cases whose objectives are to maintain the uniqueness, distinctiveness, and uniformity of the populations. This study analyzed animals subjected to the same feeding program, ensuring the elimination of additional variables. Full article

We present HGC-Net, a hybrid pipeline for assessing geometric consistency between stereo image pairs. Our method integrates classical epipolar geometry with deep learning components to compute an interpretable scalar score A, reflecting the degree of alignment. Unlike traditional techniques, which may overlook subtle miscalibrations, HGC-Net reliably detects both severe and mild geometric distortions, such as sub-degree tilts and pixel-level shifts. We evaluate the method on the Middlebury 2014 stereo dataset, using synthetically distorted variants to simulate misalignments. Experimental results show that our score degrades smoothly with increasing geometric error and achieves high detection rates even at minimal distortion levels, outperforming baseline approaches based on disparity or calibration checks. The method operates in real time (12.5 fps on 1080p input) and does not require access to internal camera parameters, making it suitable for embedded stereo systems and quality monitoring in robotic and AR/VR applications. The approach also supports explainability via confidence maps and anomaly heatmaps, aiding human operators in identifying problematic regions. Full article

This paper presents three novel sufficient and necessary conditions for the admissibility of singular fractional-order systems (FOSs), a stabilization criterion, and a solution algorithm. The strict linear matrix inequality (LMI) stability criterion for integer-order systems is generalized to singular FOSs by using column-full rank matrices. This admissibility criterion does not involve complex variables and is different from all previous results, filling a gap in this area. Based on the LMIs in the generalized condition, the improved criterion utilizes a variable substitution technique to reduce the number of matrix variables to be solved from one pair to one, reflecting the admissibility more essentially. This improved result simplifies the programming process compared to the traditional approach that requires two matrix variables. To complete the state feedback controller design, the system matrices in the generalized admissibility criterion are decoupled, but bilinear constraints still occur in the stabilization criterion. For this case, where a feasible solution cannot be found using the MATLAB LMI toolbox, a branch-and-bound algorithm (BBA) is designed to solve it. Finally, the validity of these criteria and the BBA is verified by three examples, including a real circuit model. Full article

Text-to-music (TTM) models have recently revolutionized the automatic music generation research field, specifically by being able to generate music that sounds more plausible than all previous state-of-the-art models and by lowering the technical proficiency needed to use them. For these reasons, they have readily started to be adopted for commercial uses and music production practices. This widespread diffusion of TTMs poses several concerns regarding copyright violation and rightful attribution, posing the need of serious consideration of them by the audio forensics community. In this paper, we tackle the problem of detection and attribution of TTM-generated data. We propose a dataset, FakeMusicCaps, that contains several versions of the music-caption pairs dataset MusicCaps regenerated via several state-of-the-art TTM techniques. We evaluate the proposed dataset by performing initial experiments regarding the detection and attribution of TTM-generated audio considering both closed-set and open-set classification. Full article