Search Results (216)

Simulation-based laboratories have become an essential component of modern engineering education, particularly in courses where access to physical equipment is limited. This paper presents a structured methodology for teaching the fundamentals of optical fiber communication systems using OptiPerformer 18, i.e., a freely available optical communication simulation platform. The novelty of this work lies in integrating a complete set of parameter-driven laboratory exercises, covering eye-diagram analysis, chromatic dispersion and dispersion compensation, Gaussian pulse propagation, and BER/Q-factor evaluation, into both distance and face-to-face teaching, and validating their effectiveness across four academic years involving more than 200 students. Representative simulation results generated with OptiPerformer are provided to illustrate the learning process and to demonstrate how key transmission impairments and system-level behaviors can be visualized and quantitatively analyzed without specialized hardware. The pedagogical effectiveness of the approach is assessed through student surveys and final grades, showing consistently high learning outcomes and strong student engagement in both remote and in-person settings. These findings indicate that the proposed simulation-based laboratory framework offers a scalable, hardware-independent, and conceptually rich alternative to traditional fiber-optic laboratory classes, supporting deeper understanding of transmission physics and enhancing analytical and problem-solving skills essential in modern optical communication engineering. Full article

Adeno-associated viruses (AAVs) are a leading vector for gene therapy, yet their clinical utility is limited by the lack of robust quality control methods to distinguish between empty (AAV_empty), partially loaded (AAV_partial), and fully DNA loaded (AAV_full) capsids. Current analytical techniques provide partial insights but remain limited in sensitivity, throughput, or resolution. Here we present a multimodal plasmonic nanopore sensor that integrates optical trapping with electrical resistive-pulse sensing to characterize AAV9 capsids at the single-particle level in tens of μL sample volumes and fM range concentrations. As a model system, we employed AAV9 capsids not loaded with DNA, capsids loaded with a self-complementary 4.7 kbp DNA (AAV_scDNA), and ones loaded with single-stranded 4.7 kbp DNA (AAV_ssDNA). Ground-truth validation was performed with analytical ultracentrifugation (AUC). Nanosensor data were acquired concurrently for optical step changes (occurring at AAV trapping and un-trapping) both in transmittance and reflectance geometries, and electrical nanopore resistive pulse signatures, making for a total of five data dimensions. The acquired data was then filtered and clustered by Gaussian mixture models (GMMs), accompanied by spectral clustering stability analysis, to successfully separate between AAV species based on their DNA load status (AAV_empty, AAV_partial, AAV_full) and DNA load type (AAV_scDNA versus AAV_ssDNA). The motivation for quantifying the AAV_empty and AAV_partial population fractions is that they reduce treatment efficacy and increase immunogenicity. Likewise, the motivation to identify AAV_scDNA population fractions is that these have much higher transfection rates. Importantly, the results showed that the nanosensor could differentiate between AAV_scDNA and AAV_ssDNA despite their identical masses. In contrast, AUC could not differentiate between AAV_scDNA and AAV_ssDNA. An equimolar mixture of AAV_scDNA, AAV_ssDNA and AAV_empty was also measured with the sensor, and the results showed the expected population fractions, supporting the capacity of the method to differentiate AAV load status in heterogeneous solutions. In addition, less common optical and electrical signal signatures were identified in the acquired data, which were attributed to debris, rapid entry re-entry to the optical trap, or weak optical trap exits, representing critical artifacts to recognize for correct interpretation of the data. Together, these findings establish plasmonic nanopore sensing as a promising platform for quantifying AAV DNA loading status and genome type with the potential to extend ultra-sensitive single-particle characterization beyond the capabilities of existing methods. Full article

Future space detectors for Ultra High Energy neutrinos and cosmic rays will utilize Cherenkov telescopes to detect forward-beamed Cherenkov light produced by charged particles in Extensive Air Showers (EASs). A Cherenkov detector can be equipped with an array of Silicon Photo-Multiplier (SiPM) pixels, which offer several advantages over traditional Photo-Multiplier Tubes (PMTs). SiPMs are compact and lightweight and operate at lower voltages, making them well-suited for space-based experiments. The SiSMUV (SiPM-based Space Monitor for UV-light) is developing a SiPM-based Cherenkov camera for PBR (POEMMA Baloon with Radio) at INFN Napoli. To understand the response of such an instrument, a comprehensive simulation of the response of individual SiPM pixels to incident light is needed. For the accurate simulation of a threshold trigger, this simulation must reproduce the current produced by a SiPM pixel as a function of time. Since a SiPM pixel is made of many individual Avalanche Photo-Diodes (APDs), saturation and pileup in APDs must also be simulated. A Gaussian mixture fit to ADC count spectrum of a SiPM pixel exposed to low levels of laser light at INFN Napoli shows a significant amount of samples between the expected PE (Photo Electron) peaks. Thus, noise sources such as dark counts and afterpulses, which result in partially integrated APD pulses, must be accounted for. With static, reasonable values for noise rates, the simulation chain presented in this work uses the characteristics of individual APDs to produce the aggregate current produced by a SiPM pixel. When many such pulses are simulated and integrated, the ADC spectra generated by low levels of laser light at the INFN Napoli SiSMUV test setup can be accurately reproduced. Full article

Tidal flats play a vital role in coastal ecosystems by supporting biodiversity, mitigating natural hazards, and functioning as blue carbon reservoirs. However, monitoring their geomorphological changes remains challenging due to high turbidity, shallow depths, and tidal variability. Conventional approaches—such as satellite remote sensing, acoustic sounding, and topographic LiDAR—face limitations in resolution, accessibility, or coverage of submerged areas. Airborne bathymetric LiDAR (ABL), which uses green laser pulses to detect reflections from both the water surface and seabed, has emerged as a promising alternative. Unlike traditional discrete-return data, full waveform analysis offers greater accuracy, resolution, and reliability, enabling more flexible point cloud generation and extraction of additional signal parameters. A critical step in ABL processing is waveform decomposition, which separates complex returns into individual components. Conventional methods typically assume fixed models with three returns (water surface, water column, bottom), which perform adequately in clear waters but deteriorate under shallow and turbid conditions. To address these limitations, we propose an adaptive progressive Gaussian decomposition (APGD) tailored to tidal flat environments. APGD introduces adaptive signal range selection and termination criteria to suppress noise, better accommodate asymmetric echoes, and incorporates a water-layer classification module. Validation with datasets from Korea’s west coast tidal flats acquired by the Seahawk ABL system demonstrates that APGD outperforms both the vendor software and the conventional PGD, yielding higher reliability in bottom detection and improved bathymetric completeness. At the two test sites with different turbidity conditions, APGD achieved seabed coverage ratios of 66.7–70.4% and bottom-classification accuracies of 97.3% and 96.7%. Depth accuracy assessments further confirmed that APGD reduced mean depth errors compared with PGD, effectively minimizing systematic bias in bathymetric estimation. These results demonstrate APGD as a practical and effective tool for enhancing tidal flat monitoring and management. Full article

Passive and active targets, both implanted with gold nanoprisms, were designed to achieve enhanced, uniform power absorption during two-sided illumination with short laser pulses. The capabilities of uniform, single-peaked Gaussian and adjusted nanoresonator number density distributions were compared. The average local E-field inside the gain medium and at the nanoprism surface was mapped as a function of the pump E-field strength and dye concentration, and the optimal parameters were selected based on the achievable local E-field. A comparative study was performed on passive and active targets to determine the most favorable distribution type and to consider the advantages of dye doping. The adjusted distribution is proposed for both passive and active targets. Dye doping is advantageous in all distributions as it results in decreasing the minimal standard deviation of the near-field enhancement (NFE), the delay of the minimal standard deviation in the power loss and deposited energy, and the standard deviation of the NFE, while increasing the FOM of the NFE in the uniform and adjusted distributions. Dye doping allows for decreasing the delay of the minimal standard deviation in the NFE, increasing the mean NFE, and decreasing the standard deviation of the power loss and deposited energy in the uniform, Gaussian, and adjusted distribution, respectively. Full article

Neutron Resonance Transmission Analysis (NRTA) is a non-destructive technique allowing the elemental and isotopic characterization of materials and objects. This study represents a first step toward understanding the NRTA technique and developing a novel compact system adapted for industrial applications. The industrial feasibility of the NRTA was assessed by simulating a compact system using the Monte Carlo code MCNP 6.1. Neutron transmission spectra were generated for various metallic samples, ranging from 0.1 mm to 1 cm in thickness, and analyzed using a home-developed quantification method that incorporates nuclear cross sections from the ENDF/B-VIII.0 library and accounts for instrumental resolution. For this first study, an idealized configuration was considered, with a 0 µs pulsed neutron source and a Gaussian resolution function, to validate the methodology under a simple controlled condition. The results demonstrate that the areal densities of isotopes of Uranium and Plutonium can be determined with relative deviations below 10%, even under compact measurement conditions. This study validates the characterization method and represents a first step toward the continued development of an industrial NRTA prototype for rapid, non-destructive isotopic control of nuclear materials. Full article

Photoplethysmography (PPG) is widely used in health monitoring, but its reliability is often compromised by artifacts, limiting accurate peripheral arterial oxygen saturation (SpO2) estimation. Moreover, physiological and demographic factors can substantially alter PPG waveform morphology. We propose a lightweight, real-time predictive modeling approach that adapts to subject-specific PPG signal dynamics to improve monitoring robustness under conditions prone to artifacts. A total of 459 min of dual-wavelength PPG signals, together with reference SpO2 values, were collected from 17 healthy volunteers (2 female, 15 male, mean age $27\pm 3$ years old) undergoing controlled desaturation in the 85–100% range after being instructed to remain still. Cardiac pulses were segmented and decomposed into AC and DC components, and the adequacy of several signal models, ranging from sums of Gaussians to Fourier series, and polynomial expansions of different orders, was evaluated. A space of representative signal features was built from the best-performing model, and used to generate machine learning-based predictions for each pulse using the preceding four clean pulses. Predicted pulses could be directly compared with their originals, enabling accurate error estimation without simulated data. The predicted signals closely matched the originals, achieving mean $R^2$ scores above 0.9, and an SpO2 estimation RMSE of 1.28%. In practical use, the same approach could be applied to overcome artifact-corrupted segments if combined with a signal quality assessment module. Therefore, this algorithm provides a promising pathway toward more reliable SpO2 monitoring in wearable systems, particularly under hypoxic conditions. Full article

We investigate analog and digital pre-emphasis for ultra-high-bit-rate coherent dual-polarization 64-QAM (DP-64QAM) transmission using OptiSystem. Two representative single-wavelength configurations are studied: 64 Gbaud (600 Gb/s payload, 768 Gb/s line rate) and 100 Gbaud (1000 Gb/s payload, 1.2 Tb/s line rate). The transmitter employs raised-cosine pulse shaping (roll-off 0.1) and a 9-bit DAC, while the receiver uses a 9-bit ADC; bandwidth-limiting Bessel/Gaussian filters emulate practical transmitter (Tx) and receiver (Rx) front-end constraints. Analog pre-emphasis (APE) is realized by uploading a measured analog filter response immediately after the DAC to compensate high-frequency roll-off. Digital pre-emphasis (DPE) is implemented before the DAC as a finite-impulse-response (FIR) pre-distortion stage, with taps obtained from the measured frequency response via spectrum mirroring, inverse FFT, Hamming-window smoothing, and normalization. We compare four cases: (i) ideal reference without bandwidth limits; (ii) bandwidth-limited without pre-emphasis; (iii) APE; and (iv) DPE. Bit-error-rate–versus–optical signal-to-noise ratio (OSNR) results show that both APE and DPE substantially mitigate bandwidth-induced penalties and approach the theoretical bound, reducing the OSNR gap to 5.8 dB at 64 Gbaud and 6.6 dB at 100 Gbaud, with operation near the forward error correction (FEC) threshold ($\mathrm{BER}={10}^{-2}$). While DPE offers full programmability, it increases peak-to-average power ratio (PAPR) and may require additional gain headroom. Overall, APE provides an effective rapid-prototyping step prior to DPE deployment, confirming the feasibility of 768 Gb/s and 1.2 Tb/s DP-64QAM links with commercially realistic components, including a 150 GSa/s DAC operating at 1.5 samples/symbol for 100 Gbaud. Full article

Silicon carbide (SiC) is a promising semiconductor material for electronics and photonics. Ultrafast laser processing of SiC enables three-dimensional nanostructuring, enriching and expanding the functionalities of SiC devices. However, challenges arise in delivering uniform, high-aspect-ratio (length-to-width) nanostructures due to difficulties in confining light energy at the nanoscale while simultaneously regulating intense photo modifications. In this study, we report the controllable growth of long-distance, high-straightness, and high-parallelism multifilament structures in SiC using ultrafast laser processing. The mechanism is the formation of femtosecond multifilaments through the nonlinear effects of clamping equilibrium, which allow highly confined light to propagate without diffraction in parallel channels, further inducing high-aspect-ratio nanostripe-like photomodifications. By employing an elliptical Gaussian beam—rather than a circular one—and optimizing pulse durations to stabilize multifilaments with regular positional distributions, the induced multifilament structures can reach a length of approximately 90 μm with a minimum linewidth of only 28 nm, resulting in an aspect ratio of over 3200:1. Raman tests indicate that the photomodified regions consist of amorphous SiC, amorphous silicon, and amorphous carbon, and photoluminescence tests reveal that silicon vacancy color centers could be induced in areas with lower light power density. By leveraging femtosecond multifilaments for diffraction-less light confinement, this work proposes an effective method for manufacturing deep-subwavelength, high-aspect-ratio nanostructures in SiC. Full article

In nondestructive evaluation (NDE), pulsed phase thermography (PPT) is a commonly used technique which relies on phase contrast to detect defects. This study presents a methodology to investigate how changes in signal processing and geometrical parameters affect phase contrast. Analytically simulated thermal signals are used to evaluate the phase contrast for varying sample thicknesses and defect sizes, relative to a fixed defect depth. To address the issue of spectral leakage, phase contrasts are recorded using both rectangular and Hamming windows before transformation into the frequency domain. A Gaussian process regression (GPR) modelling scheme is used to observe the relationship between phase contrast and geometrical parameters. The results suggest that both the choice of windowing function and geometrical factors can influence defect detection, offering insights to improve the reliability of PPT-based inspections. Full article

Optical intrabody wireless nanosensor networks (OiWNSNs) enable groundbreaking biomedical applications via optical nanocommunication within biological tissues. Synchronization is critical for accurate data recovery in these energy- and size-constrained nanonetworks. In this study, we investigate timing synchronization in a highly dispersive and noisy intravascular optical channel, particularly under an on–off keying preamble comprising Gaussian optical pulses. We proposed a synchronization scheme based on the repetitive transmission of a preamble and noncoherent detection using continuous-time moving average filters with multiple integrator windows. The simulation results reveal that increasing the communication distance degrades the synchronization performance. To counter this degradation, we can increase the number of preamble repetitions, which markedly improves the system reliability and timing accuracy due to the averaging gain, although the performance saturates due to the dispersion floor inherent in the blood channel. Moreover, we found that low-resolution nanoreceivers with fewer integrators outperform high-resolution designs in dispersive environments, as they mitigate the energy-splitting problem due to pulse broadening. This tradeoff between temporal resolution and robustness highlights the importance of channel-aware receiver design. Overall, this study provides key insights into the physical layer design of OiWNSNs and offers practical guidelines for achieving robust synchronization under realistic biological conditions. Full article

This work presents an end-to-end encryption–decryption framework for securing electromagnetic signals processed through a nanoantenna. The system integrates amplitude normalization, uniform quantization, and Reed–Solomon forward error correction with key establishment via ECDH and bitwise XOR encryption. Two signal types were evaluated: a synthetic Gaussian pulse and a synthetic voice waveform, representing low- and high-entropy data, respectively. For the Gaussian signal, reconstruction achieved an RMSE = 11.42, MAE = 0.86, PSNR = 26.97 dB, and Pearson’s correlation coefficient = 0.8887. The voice signal exhibited elevated error metrics, with an RMSE = 15.13, MAE = 2.52, PSNR = 24.54 dB, and Pearson correlation = 0.8062, yet maintained adequate fidelity. Entropy analysis indicated minimal changes between the original signal and the reconstructed signal. Furthermore, avalanche testing confirmed strong key sensitivity, with single-bit changes in the key altering approximately 50% of the ciphertext bits. The findings indicate that the proposed pipeline ensures high reconstruction quality with lightweight encryption, rendering it suitable for environments with limited computational resources. Full article

Numerous studies on specific cannabis compounds (cannabinoids and phenolic acids) have demonstrated their therapeutic potential, with their administration methods remaining a key research focus. Transdermal drug delivery (TDD) systems are gaining attention due to their advantages, such as painless administration, controlled release, direct absorption into the bloodstream, and its ability to bypass hepatic metabolism. The thin films obtained via pulsed laser deposition consist of micro- and nanoparticles capable of migrating through skin pores upon contact. This study investigates the interaction of phenolic compounds in hemp seeds with pulsed laser beams. The main goal is to achieve the ablation and deposition of these compounds as thin films suitable for TDD applications. The other key objective is optimizing laser energy to enhance the industrial feasibility of this method. Thin layers were deposited on glass and hemp fabric using dual pulsed laser (DPL) ablation on a compressed hemp seed target held in a stainless steel ring. The target was irradiated for 30 min with two synchronized pulsed laser beams, each with parameters of 30 mJ, 532 nm, pulse width of 10 ns, and a repetition rate of 10 Hz. Each beam had an angle of incidence with the target surface of 45°, and the angle between the two beams was also 45°. To improve laser absorption, two approaches were used: (1) HS-DPL/glass and HS-DPL/hemp fabric, in which a portion of the stainless steel ring was included in the irradiated area, and (2) HST-DPL/glass and HST-DPL/hemp fabric—hemp seeds were mixed with turmeric powder, which is known to improve laser interaction and biocompatibility. The FTIR and Micro-FTIR spectroscopy (ATR) performed on thin films compared to the target material confirmed the presence of hemp-derived phenolic compounds, including tetrahydrocannabinol (THC), cannabidiol (CBD), ferulic acid, and coumaric acid, along with other functional groups such as amides. The ATR spectra have been validated against Gaussian 6 numerical simulations. Scanning electron microscopy (SEM) and substance transfer tests revealed the microgranular structure of thin films. Through the analyzes carried out, the following were highlighted: spherical structures (0.3–2 μm) for HS-DPL/glass, HS-DPL/hemp fabric, HST-DPL/glass, and HST-DPL/hemp fabric; larger spherical structures (8–13 μm) for HS-DPL/glass and HST-DPL/glass; angular, amorphous-like structures (~3.5 μm) for HS-DPL/glass; and crystalline-like structures (0.6–1.3 μm) for HST-DPL/glass. Microparticle transfer from thin films on the hemp fabric to the filter paper at a human body temperature (37 °C) confirmed their suitability for TDD applications, aligning with the “whole plant medicine” or “entourage effect” concept. Granular, composite, thin films were successfully developed, capable of releasing microparticles upon contact with a surface whose temperature is 37 °C, specific to the human body. Each of the microparticles in the thin films obtained with the DPL technique contains phenolic compounds (cannabinoids and phenolic acids) comparable to those in hemp seeds, effectively acting as “microseeds.” The obtained films are viable for TDD applications, while the DPL technique ensures industrial scalability due to its low laser energy requirements. Full article

A spectral filter utilizing dispersive prisms and an optical fiber collimator is presented as an attractive alternative to diffraction grating-based spectral filters. A simplified analytical expression for this prism-based spectral filter is derived. A spectral filter constructed using SF11 flint glass prisms demonstrates Gaussian spectral filter profiles with bandwidths of 8 nm and 4 nm, closely matching with theoretical predictions. Using these filters, we demonstrate two types of mode-locking regimes: a dissipative soliton (DS) pulse and a self-similar (SS) pulse. The dissipative soliton pulses deliver 3.3 nJ with dechirped pulse durations of 206 fs, while the self-similar pulses deliver 2.1 nJ with durations of 120 fs. The results demonstrate that the prism-based filters are well-suited for ultrafast mode-locked fiber lasers. Full article

Precise time interval generation is a cornerstone of modern measurement, automation, and distributed control systems, particularly within Internet of Things (IoT) architectures. This paper presents the design, implementation, and evaluation of a low-cost and high-precision time interval generator based on Complementary Metal-Oxide Semiconductor (CMOS) logic counters (Integrated Circuit (IC) IC 7493 and IC 4017) and inverter-based crystal oscillators (IC 74LS04). The proposed system enables frequency division from 1 MHz down to 1 Hz through a cascade of binary and Johnson counters, enhanced with digitally controlled multiplexers for output signal selection. Unlike conventional timing systems relying on expensive Field-Programmable Gate Array (FPGA) or Global Navigation Satellite System (GNSS)-based synchronization, this approach offers a robust, locally controlled reference clock suitable for IoT nodes without network access. The hardware is integrated with Arduino and ESP32 microcontrollers via General-Purpose Input/Output (GPIO) level interfacing, supporting real-time timestamping, deterministic task execution, and microsecond-level synchronization. The system was validated through Python-based simulations incorporating Gaussian jitter models, as well as real-time experimental measurements using Arduino’s micros() function. Results demonstrated stable pulse generation with timing deviations consistently below ±3 µs across various frequency modes. A comparative analysis confirms the advantages of this CMOS-based timing solution over Real-Time Clock (RTC), Network Time Protocol (NTP), and Global Positioning System (GPS)-based methods in terms of local autonomy, cost, and integration simplicity. This work provides a practical and scalable time reference architecture for educational, industrial, and distributed applications, establishing a new bridge between classical digital circuit design and modern Internet of Things (IoT) timing requirements. Full article