Search Results (1,851)

This paper argues that digital identity in AI-mediated environments has become a central mechanism through which contemporary societies organise recognition, participation, and belonging. Digital identity is no longer simply a technical representation of the individual. It is produced through infrastructural processes of classification, ranking, and credibility signalling that determine who becomes visible, who is treated as legitimate, and who is able to participate meaningfully in social and civic life. The paper develops a conceptual framework that treats AI-driven platforms as social infrastructures rather than neutral intermediaries. It shows how identity is inferred through data-driven systems rather than negotiated through social interaction, how recognition is operationalised through visibility and credibility metrics rather than ethical judgement, and how participation becomes conditional on algorithmic allocation of attention rather than guaranteed by access alone. Visibility is identified as the key conversion point through which inferred identity becomes social consequence. Drawing on interdisciplinary literature, the analysis demonstrates that misrecognition, exclusion, and inequality in platform environments are not primarily the result of isolated error or intentional bias. They are patterned outcomes of ordinary optimisation processes that distribute legitimacy and opportunity unevenly across social groups. These dynamics reshape group formation, harden social boundaries, and concentrate risk among populations that are already more vulnerable to misrecognition and reduced contestability. The paper concludes that governing digital identity is a societal challenge rather than a purely technical one. As platforms increasingly perform institutional functions without equivalent accountability, digital identity governance becomes a critical site of social ordering. Addressing this challenge requires public standards for how visibility, recognition, and participation are allocated, meaningful avenues for contestation, and protections against the normalisation of stratified belonging in AI-mediated societies. Full article

Background: Self-transcendence has been described in psychological literature as an orientation toward meaning beyond the individual self. However, because the present study does not directly measure transcendence as a psychological construct, we approach it cautiously as a candidate form of internally oriented attention, operationalized through EEG spectral dynamics. Although this construct has been linked to self-referential cognition and large-scale brain systems supporting internal mentation, electrophysiological evidence remains limited, especially in designs that compare spiritually oriented practices with non-spiritual internal-focus controls. Objective: We examined whether a candidate EEG-derived Transcendence Index (TI) is associated with EEG oscillatory activity across canonical frequency bands and whether prayer and relaxation show descriptively distinct oscillatory patterns. Methods: In a within-subject design, participants completed a psychological assessment battery including personality and anxiety measures and underwent EEG recording during two eyes-closed conditions (Prayer vs. Relaxation). Spectral power features were extracted for delta, theta, alpha (low/high), beta (low/high), and gamma (low/high, where signal quality permitted). We examined associations between TI and band-limited activity and explored condition-related oscillatory patterns across Prayer and Relaxation. Given the modest sample size (N = 39), the study was designed and interpreted as exploratory research. Results: Higher TI was associated with an oscillatory profile consistent with internally oriented attention and reflective self-processing, with the most consistent patterns observed in theta–alpha dynamics (and comparatively lower beta contribution). In addition, Prayer and Relaxation showed descriptively distinct oscillatory patterns, suggesting that prayer engages internal-focus processes that may not be fully captured by relaxation alone. Conclusions: These findings support the feasibility of examining internally oriented attentional dynamics potentially related to “transcendence” as a candidate construct through scalp EEG spectral activity. Integrating theory-informed indices with EEG features may help refine psychophysiological models of self-transcendence and inform digitally supported assessment approaches, pending further construct validation. These findings should therefore be interpreted as exploratory preliminary evidence supporting the feasibility of EEG-based indices of internally oriented attention. Full article

Ambient backscatter systems enable passive sensing and information transfer by utilizing the reflection and modulation of incident radio-frequency (RF) signals. However, in real-world scenarios involving non-cooperative targets such as off-the-shelf printed circuit boards (PCBs), the backscattered signal is extremely weak and often obscured by strong direct-path self-interference (SI) at the receiver. This issue becomes even more severe when unintentional PCB structures act as radiating elements. In this work, we explore ambient backscatter leakage from a compromised PCB using a realistic measurement setup that includes separated transmit and receive antennas and a direct-conversion Universal Software Radio Peripheral (USRP)-based receiver. We demonstrate that residual carrier frequency offset (CFO), caused by oscillator mismatch and hardware imperfections, can spread the dominant SI in the baseband and completely mask the weak backscattered signal. To solve this problem, a software-based post-processing framework is applied. This method leverages the complex baseband representation enabled by the homodyne receiver to jointly manage the carrier and SI components without relying on intermediate-frequency processing or prior knowledge of the target signal parameters. Experimental results show that this approach significantly improves the detectability of weak backscattered baseband information that would otherwise be concealed within the raw I/Q data. This study emphasizes the importance of CFO-aware digital processing in ambient backscatter systems and offers new insights into unintended electromagnetic leakage mechanisms from commercial PCB platforms. Full article

Field-Programmable Gate Arrays (FPGAs) have become an important platform for accelerating real-time communication systems, and System-on-Chip (SoC) devices provide the flexibility to design and optimize architectures that support high data rates, different modulation formats, and channel equalization schemes. Selecting the appropriate architecture can be guided through Design Space Exploration (DSE) using high-level synthesis tools, which enables the identification of numerical representations that balance performance with reduced hardware resource consumption. Despite their relevance, recent developments in communication systems often overlook the impact of numerical precision in Digital Signal Processing algorithms, particularly the trade-offs between floating- and fixed-point arithmetic when targeting hardware implementations. In this work, two widely used blind equalization algorithms, the Constant Modulus Algorithm (CMA) and the Multi-Modulus Algorithm (MMA), were implemented on a low-cost Ultra96 SoC-FPGA to analyze the effect of a fixed-point representation. A multi-objective Design Space Exploration methodology was applied to minimize hardware utilization while maintaining reliable transmission performance. Resource consumption, latency, and throughput were measured across different binary formats using the Minimum Mean Square Error (MMSE) criterion. Parallelization techniques were incorporated to improve throughput. The DSE generated comprehensive performance surfaces quantifying latency, MMSE convergence, and FPGA resource utilization (DSP48E/FF/LUT/BRAM) across fixed-point formats, achieving optimal 4 MS/s throughput configurations. Although this throughput is naturally lower than the Gigabit speeds required in backbone optical networks, the results demonstrate the effectiveness of numerical representation optimization in resource-constrained SoC-FPGA devices, offering a practical approach for real-time Edge and IoT implementations where cost and hardware limitations are critical. Full article

This study investigates the influence of microgravity on the fundamental frequency (F0) of astronauts’ speech. A speech corpus was compiled, including recordings in microgravity and on Earth, matched by speaker and content. The signal processing methodology included filtering with consideration of human auditory perception, segmentation of speech fragments, F0 estimation using digital signal processing techniques, and visualization through fundamental frequency dynamics plots. Results revealed a consistent increase in F0 for most astronauts under microgravity, with maximum values of 450 Hz for female speakers and 245 Hz for male speakers. Elevated F0 levels were observed for approximately 86% of the total duration of speech fragments recorded in microgravity, compared with 14% on Earth. These findings confirm that microgravity affects the speech apparatus and acoustic characteristics of voice. Practical implications include adapting voice-controlled systems and automatic speech recognition for space environments, monitoring crew condition, and studying speech physiology under extreme conditions. Full article

Ultrasonic testing is a prevalent method for non-destructive evaluation of railway rails; however, conventional Time-of-Flight (ToF) approaches applied in practical dry-coupled inspections often rely on simplified assumptions regarding wave propagation velocity and neglect complex waveform characteristics. This paper presents a robust depth estimation framework for surface-breaking cracks that enhances sizing accuracy through effective velocity calibration and Hilbert envelope extraction. Unlike standard methods that assume the free-space speed of sound in air (343 m/s) for wave propagation within the air-filled gap of a surface-breaking crack, we propose an effective velocity model derived from in situ calibration to account for the boundary layer viscosity and thermal conduction effects within narrow crack geometries. The signal processing chain incorporates spectral analysis, band-pass filtering, and Hilbert Transform-based envelope detection to mitigate noise and resolve phase ambiguities. Experimental validation on steel specimens with controlled defects (0.2–10.0 mm) demonstrates that the proposed method achieves an exceptional linear correlation (R² ≈ 0.9976). The calibrated effective velocity was determined to be 289.3 m/s, approximately 15.6% lower than the speed of sound in air, confirming the significant influence of confinement effects. Furthermore, excitation parameters were optimized, identifying that high-voltage excitation (≥110 V) and a tuned pulse width (≈150 ns) are critical for maximizing the signal-to-noise ratio. The results confirm that combining physical model calibration with advanced signal analysis significantly reduces systematic errors, paving the way for portable, high-precision rail inspection systems. Full article

Quantum Encryption in Phase Space (QEPS) is a physical-layer encryption framework that harnesses the quantum-mechanical properties of coherent states to secure optical communications against both classical and quantum computational threats. By applying randomized phase shifts, displacements, or their dynamic combinations—implemented as unitary transformations in phase space—QEPS disrupts the phase reference essential for coherent detection, establishing aphase synchronization barrier. This review synthesizes the theoretical foundations, security mechanisms, and experimental progress of the QEPS framework, encompassing its three principal variants: the round-trip Quantum Public Key Envelope (QPKE) protocol—a public-key-like scheme built upon phase randomization (QEPS-p), the symmetric phase-only QEPS-p, and the displacement-based QEPS-d. Experimental validations demonstrate that authorized users achieve bit-error rates (BERs) below the forward-error-correction threshold, whereas eavesdroppers are confined to BERs near 50%, equivalent to random guessing—all while utilizing standard coherent optical transceivers at data rates up to 200 Gb/s over 80 km of fiber. We further examine QEPS’s robustness to channel impairments, its seamless compatibility with existing digital signal processing (DSP) pipelines, and its distinctive position within the post-quantum cryptography landscape. Finally, we outline key challenges and future research directions toward deploying QEPS as a practical, quantum-resistant security layer for next-generation optical networks. Full article

Beyond supporting ultra-high-capacity data transmission, metropolitan and access networks are expected to enable real-time infrastructure monitoring, driving the emergence of integrated sensing and communication (ISAC). Distributed acoustic sensing (DAS) has proven to be well-suited to urban sensing application requirements, yet its seamless integration into ISAC remains challenging—conventional high-peak-power sensing pulses in DAS induce nonlinear crosstalk in communication channels. DAS inherently suffers from interference fading due to single-frequency laser sources, which limits sensitivity. Here, we propose an ISAC architecture based on an electro-optic (EO) comb and a 7-core fiber, achieving nonlinearity-suppressed self-homodyne transmission and fading-suppressed DAS. Unmodulated comb lines and sensing pulses are polarization-multiplexed into orthogonal polarization states within the central core to minimize nonlinear crosstalk while delivering local oscillators (LOs) for wavelength division multiplexing (WDM) coherent transmission within six outer cores—achieving 10.56 Tbit/s capacity. In addition to supporting WDM transmission, the EO comb’s wavelength diversity is also exploited to enhance DAS performance. Specifically, a dual-pulse probe loaded onto four comb lines yields a 6 dB signal-to-noise ratio gain and a 64% reduction in fading occurrences, achieving a sensitivity of 1.72 $p\epsilon /\sqrt{\mathrm{Hz}}$ with 8 m spatial resolution. Moreover, our system supports simultaneous multi-wavelength backscatter detection in sensing and simplified digital signal processing in self-homodyne communication, reducing receiver complexity and cost. Our work presents a scalable, energy-efficient ISAC framework that unifies high-capacity communication with high-sensitivity sensing, providing a blueprint for future intelligent optical networks. Full article

Injection-related errors remain a common clinical issue and can cause patient discomfort, hematoma formation, and procedural inefficiencies. The visualization of subcutaneous veins using near-infrared (NIR) imaging has gained attention as an effective approach to reducing such errors, as blood exhibits a higher absorption of NIR light than surrounding tissue. In this study, a low-cost, non-invasive vein visualization system is presented to support safer and more accurate venous access. The proposed system integrates an NIR illumination source and a modified webcam within a compact equipment enclosure, allowing subjects to be conveniently examined by placing their arm inside the device. Vein images are automatically acquired using a laptop-based platform, followed by digital image processing techniques for vein enhancement and visualization. Laboratory-scale experiments were conducted on healthy volunteers to evaluate system performance under multiple conditions, including different vein locations (upper and lower arm regions), varying distances between the NIR light source and the arm (15 cm and 20 cm), and ambient illumination interference (light sources on and off). The experimental results demonstrate the successful implementation and reliable operation of the proposed system. Effective vein visualization was achieved across all test conditions, as confirmed by qualitative visual assessment and quantitative image quality metrics, including the Peak Signal-to-Noise Ratio (PSNR) and Mean Squared Error (MSE). Overall, the proposed system offers a practical, accessible, and cost-effective solution for vein visualization, showing strong potential for clinical and experimental applications aimed at reducing injection errors and improving venous access reliability. Full article

Serial flow cytometry was recently introduced as a method that can estimate measurement uncertainty (i.e., imprecision, the coefficient of variation of repeated measurements of individual particles) independent from population characteristics. Replication of light sources and detectors at multiple sites along a flow cytometer’s microchannel requires more equipment and can complicate detector synchronization. Here, we introduce amplitude modulation to encode each region of a serial cytometer with a unique carrier frequency, which enables demultiplexing of the combined signal incident on a single photodetector by fast Fourier transform (FFT) peak magnitude. To facilitate validation of detection, matching, and uncertainty quantification of fluorescence signals, we designed a microfluidic amplitude modulation (AM) serial flow cytometer that has ground truth detectors on individual regions (serial cytometry) in parallel with the combined channel detection for AM demultiplexing. With this report, we present metrics for event detection and dynamic range, prevalence and processing of overlapping detections, region-decoding accuracy, process yield, and uncertainty quantification on a brightness ladder of calibration microspheres. Despite being operated with reduced light intensities, the AM cytometer was capable of high-fidelity performance in comparison to conventional serial cytometry. For events above the detection limit, over 97% were analyzed. Both conventional and AM serial cytometers achieved median imprecisions in the range of 0.53% to 2.1% after outlier removal, which was well below the inherent intensity distribution of any of the microsphere subpopulations. Overall, AM cytometry supports uncertainty quantification and temporal analyses of serial cytometry data with a reduced number of photodetectors, which offers simplification of chip design with multiple measurement regions and wide-field detectors. Full article

High-resolution microdisplay driver applications impose stringent requirements on the static linearity and dynamic performance of digital-to-analog converters (DACs). To meet these requirements, this paper presents a 200 MS/s 12-bit current-steering DAC. To reduce mismatches among high-weight current sources, a split–sort–symmetric grouping calibration (SSSGC) scheme is introduced, in which each most-significant-bit (MSB) current source is split into sub-cells and reorganized through sorting and symmetric pairing. This approach improves static linearity without complex current measurement or compensation loops. Additionally, a group-domain dynamic element matching (DEM) technique is employed to randomize current-source selection and suppress harmonic distortion. Designed in a 0.18 μm BCD process, the proposed DAC achieves an integral nonlinearity (INL) of 0.79 LSB, a differential nonlinearity (DNL) of 0.42 LSB, and a spurious-free dynamic range (SFDR) of 74.9 dB at an output signal of 4.05 MHz. Full article

This paper proposes a real-time active control strategy for a static volt–ampere reactive compensator (SVC) that can simultaneously respond to source phase variations and load fluctuations. Conventional SVC control schemes based on the total reactive power compensation suffer from degraded power factors and reduced power quality under unbalanced load conditions. In contrast, phase-wise control methods can maintain the power factor during load imbalance, which can result in reactive power overcompensation or undercompensation when source phase variations occur, leading to power factor deterioration. The proposed real-time active SVC control strategy effectively addresses both source phase variations and load fluctuations, thereby improving the power factor and overall power quality. PSIM version 2025 software-based simulations and digital signal processing-based hardware experiments were conducted to validate the effectiveness of the proposed method. The experimental results confirm that the proposed control strategy successfully achieved the target power factor even under simultaneous source phase variations and unbalanced load conditions. These results demonstrate the high applicability of the proposed method to practical industrial power systems and renewable energy-integrated systems. The method is expected to contribute to the efficient design of large-capacity power quality control systems in the future. Full article

This paper presents a subtractive-dither-assisted background calibration technique for a 2 GS/s 12 bit pipelined analog-to-digital converter (ADC). A large 7 bit pseudo-random dither is injected in both the flash and the multiplying digital-to-analog converter (MDAC) to decorrelate the differential nonlinearity (DNL) errors caused by the inherent quantization error nonlinearity, capacitor mismatching, and inter-stage amplifier nonlinearity from the input signal. Designed in a 28 nm CMOS process with a 1 V supply, post-layout simulations demonstrate a 10.2 dB improvement in spurious-free dynamic range (SFDR), from 73.8 dB to 84.4 dB, with dithering enabled under a close-to-Nyquist input frequency of 985 MHz. Although the injected dither cannot be completely removed in the digital domain, the proposed ADC exhibits only a 0.5 dB degradation in signal-to-noise-and-distortion ratio (SNDR) for full-scale input, achieving an SNDR of 62.3 dB and an effective number of bits (ENOB) of 10.1 bits. Dithering also improves static performance, with DNL and INL optimized to +0.54/−0.53 LSBs and +0.85/−0.88 LSBs, respectively. Moreover, the proposed dither-based calibration technique introduces an additional power consumption of less than 2 mW. Full article

A capsule endoscope (CE) provides noninvasive access to the gastrointestinal tract, offering diagnostic information that cannot be obtained through external imaging alone. However, during the examination inside the stomach, the CE’s posture may change rapidly as it moves within a dynamically deforming organ, making it difficult to determine its orientation using only the onboard camera feedback. To address this problem, this study proposes a method that employs an external array of Hall Effect Sensors (HES) to estimate the capsule’s position and orientation in real time, based on the magnetic field generated by a permanent magnet (PM) embedded inside the capsule, without the need for any additional internal sensors. This approach introduces a unified magnetic actuation and localization framework that enables real-time 5-degree-of-freedom posture estimation using only the internal PM of the capsule. Furthermore, the proposed system features an integrated architecture capable of simultaneous actuation and localization. To enhance system practicality, the sensor module and communication board were combined into a single unit that employs a digital serial communication scheme, eliminating the need for analog to digital conversion of sensing signals. By avoiding additional onboard sensors and employing a PM-based actuation system, the proposed system simplifies hardware configuration by preserving capsule miniaturization and by eliminating the high power consumption and thermal issues associated with electromagnet-based actuation, while maintaining accurate real-time tracking performance. Through an optimization process, the system achieved a position error of less than 2 mm and an angular error within 2° over a sensing range of up to 60 mm. Repeated experiments further validated the system’s effectiveness and reliability under realistic operating conditions, demonstrating its feasibility for compact and clinically applicable active capsule endoscopy systems. Full article

Cardiac fibrosis represents a final common pathway in a wide range of cardiac disorders, leading to structural remodeling, diastolic dysfunction, and heart failure. From a pathologist’s viewpoint, fibrotic remodeling displays distinctive morphologic patterns such as interstitial, perivascular, and replacement fibrosis, which mirror specific cellular and molecular mechanisms. Central to this process is the activation of cardiac fibroblasts into myofibroblasts, driven by profibrotic signaling cascades such as transforming growth factor beta (TGF-β)/mothers against decapentaplegic homolog proteins (SMAD), Wingless/Integrated signaling pathway (Wnt)/βeta-catenin, and Hippo-Yes-associated protein (YAP)/transcriptional coactivator with PDZ-binding motif (TAZ) pathways. Neurohumoral mediators, including angiotensin II and aldosterone, further amplify extracellular matrix synthesis and tissue stiffness. Epigenetic modulators and non-coding RNAs (n-c RNAs) orchestrate transcriptional programs that perpetuate fibroblast activation. Histopathological correlates of these molecular events, collagen deposition, alpha-smooth muscle actin (α-SMA) expression, and extracellular matrix (ECM) cross-linking, can be demonstrated through immunohistochemistry and digital morphometry. This review integrates molecular signaling and morphologic evidence to delineate the mechanisms of cardiac fibrosis, emphasizing the pathologist’s role as a link between molecular insight and diagnostic interpretation. Understanding these intertwined processes provides the foundation for novel antifibrotic therapies targeting key molecular nodes of fibroblast activation and matrix remodeling. Full article