Search Results (303)

We propose and experimentally validate an automatic urban water leakage detection architecture that leverages dark fiber links already deployed in telecommunication networks in underground conduits in the vicinity of water pipelines. The sensing stage relies on a differential-phase coherent optical time-domain reflectometry interrogator enhanced with optical pulse compression to improve sensitivity. Building on this vibration acquisition stage, automatic leakage detection algorithms are implemented by searching for leak-induced activity in the frequency domain, which is well suited to revealing leakage-related features. After acquiring a baseline calibration to characterize normal-condition vibrations at each sensing position, leakage candidates are identified by comparing distribution-based metrics computed over multiple measurements against the corresponding baseline statistics. Two automatic leakage detection strategies are developed. First, low-complexity feature-based metrics are implemented, enabling continuous monitoring with minimal computational requirements. Second, an autoencoder-based anomaly detection technique is introduced, which also relies on location-specific normal-condition calibration but reduces the dependence on prior knowledge of the expected leakage vibration signatures. A real-world field trial on an urban network demonstrates reliable detection and localization using controlled leak events generated in the field, with measurements performed over a 17 km sensing fiber and an effective spatial resolution of 2.6 m. Benchmarking against a commercial punctual electro-acoustic leak detector yields consistent trends. Overall, the proposed system could complement existing technologies by enabling automated, continuous city-scale monitoring over already deployed dark fiber infrastructure. Full article

Additive manufacturing offers a promising route to low-cost, rapidly deployable X-ray focusing optics with geometries that are difficult to realize by conventional machining. Here, we report polymer compound refractive lenses (CRLs) for hard X-ray focusing fabricated by projection micro-stereolithography (PµSL, DLP-based) and by two-photon polymerization (2PP). Two-dimensional bi-parabolic CRL elements were produced in multiple photopolymer resins (HTL, Tough, ST1400 for PμSL; IP-S for 2PP) and evaluated by at-wavelength metrology at the Shanghai Synchrotron Radiation Facility. The single-lens residual phase errors (RMS) less than 0.1 $\mathsf{\lambda }$ were measured for PµSL-fabricated HTL, and Toughlenses, respectively, while 2PP-fabricated IP-S lenses achieved 0.008 $\mathsf{\lambda }$. And the analysis indicates that PµSL lenses are primarily limited by systematic mid-order aberrations, whereas 2PP substantially suppresses coma but shows residual spherical aberration attributable to process calibration and shrinkage. Leveraging the higher fidelity of 2PP, a 65-element parabolic CRL array (radius of curvature of 100 µm) was fabricated and demonstrated hard X-ray focusing at 15 keV with focal spot sizes of 6.4 ± 1 µm (H) and 6.8 ± 1 µm (V), and a flux gain of 220. The measured performance agrees with theoretical expectations when accounting for X-ray source properties, detector resolution and chromatic aberration. These results establish a practical pathway for additively manufactured polymer CRLs with DLP and 2PP techniques as compact, customization focusing optics for synchrotron beamlines. Full article

Chitooligosaccharides (COS) are short-chain chitosan derivatives with a wide range of biomedical, agricultural, and environmental applications, including antimicrobial therapy, wound healing, and pollutant removal. Reliable quantification of COS is essential but currently relies on high-performance liquid chromatography, mass spectrometry, or capillary electrophoresis, which require costly equipment, complex sample preparation, and are unsuitable for routine or on-site applications. This study reports a rapid, solvent-free, colorimetric assay for COS based on the reaction of 5% aqueous ninhydrin with free amino groups in McIlvaine buffer. The assay was optimized using glucosamine as a model analyte, yielding maximal sensitivity at pH 7.0. The chromophore generated (Ruhemann’s purple) remained stable for over 120 min after reaction, allowing measurements to be taken without strict time constraints. Calibration was linear from 0.4 to 2.2 mM (R² = 0.9926), with low limits of detection (0.006 mM) and quantification (0.018 mM). Increasing absorbance with COS polymerization degree (DP1–DP6) demonstrates specificity for free amino groups, while N-acetyl glucosamine showed a negligible response. Furthermore, the assay was successfully adapted for solid-phase detection on ninhydrin-pretreated filter paper and nitrocellulose, with enhanced sensitivity. This simple, efficient, and low-cost method provides an accessible alternative to instrumental techniques, supporting COS monitoring in laboratory workflows and enabling portable applications in biomedicine, agriculture, and environmental diagnostics. Full article

Steels remain among the most widely used structural and engineering materials in modern infrastructure, energy systems, and industrial facilities. Their long-term reliability depends critically on the early detection of corrosion damage and microstructural degradation. This review surveys recent advances in two complementary families of non-destructive evaluation (NDE) methods: magnetic techniques, including magnetic Barkhausen noise (MBN), magnetic flux leakage (MFL), eddy current testing (ECT), and magnetic hysteresis analysis; and electrochemical methods including electrochemical impedance spectroscopy (EIS), linear polarization resistance (LPR), scanning vibrating electrode technique (SVET), and electrochemical noise (EN). Recent progress in sensor miniaturization, signal processing algorithms, and multi-technique integration is reviewed. Particular attention is given to the sensitivity of these methods to microstructural changes reported in the literature, including carbide dissolution, phase transformations, temper embrittlement, and sensitization in stainless steels, as well as to the conditions under which such sensitivity has been demonstrated. The potential synergy between magnetic and electrochemical monitoring is discussed as a possible pathway toward more robust, condition-based maintenance frameworks. Challenges related to field deployment, environmental interference, calibration, and data interpretation are identified, and future directions—including machine learning-assisted analysis and multi-physics sensor arrays—are outlined. Full article

Spectral demodulation is a crucial component of the extrinsic Fabry–Pérot interferometric (EFPI) sensing technology. In this study, a feedback-based linear spectral fitting demodulation method is proposed for interrogating EFPI sensors. This method utilizes a discrete function derivative and a feedback amplitude calibration technique to extract the complete spectral phase, and the cavity length of the EFPI sensor is determined by performing a linear fit to the relationship between the optical frequency and the spectral phase. The experimental results indicated a nonlinearity of 0.134% over a cavity length range of 50–260 μm, and the resolution was 6.6 nm at a cavity length of 170.210 μm. Pressure measurements obtained with the developed sensor exhibited a nonlinearity of 0.401%. Compared to traditional spectral minimum mean square error algorithms, the proposed method is simpler and faster, making it more suitable for implementation on commodity hardware and better aligned with the practical needs of engineering applications. Full article

Objectives: The aim of the work was to present a method for routine determination of antiarrhythmic drugs, propafenone (PPF), its two metabolites, 5-hydroxypropafenone (5OHPPF) and N-depropylpropafenone (NDPPF), mexiletine (MEX), amiodarone (AD) and desethylamiodarone (DEAD) in serum. Methods: A simple isocratic HPLC-UV system with a manual injector was applied. The separations were performed at ambient temperature on Supelcosil LC-CN column (150 × 4.6 mm, 5 μm). Two analytical procedures (A and B) were used: (A) for AD and (B) for PPF/MEX. The mobile phase for (A) was a mixture of: CH₃OH:CH₃CN:H₂O:0.5M KH₂PO₄ (200:100:194:6 v/v + 0.1 mL 85% H₃PO₄ per 500 mL). The slightly acidified serum sample was extracted with hexane and the analytes were detected at 240 nm. The mobile phase for (B) was a mixture of: CH₃CN:H₂O:0.5M KH₂PO₄ (185:310:5 v/v + 0.1 mL 85% H₃PO₄ per 500 mL). The alkalized serum sample was extracted with diisopropyl ether, then back extracted into 0.01M HCl and finally the analytes were detected at 210 nm. Results: The method was calibrated with adequate selectivity and specificity in the range of 20–4000 ng/mL for AD, DEAD and MEX, 10–4000 ng/mL for PPF and 10–500 ng/mL for 5OHPPF and NDPPF. For all analytes, precision and accuracy fulfilled EMA requirements, i.e., ≤15% (≤20% for LLOQ), ensuring the reliability of the measurements. Conclusions: The method can be suitable for laboratories equipped with basic HPLC apparatus as an economical alternative to the LC-MS/MS technique. Full article

Understanding hydrological, agricultural, and environmental processes in soils relies on accurately measuring volumetric water content (θ), matric potential (h), and hydraulic conductivity (K). These parameters are fundamental for quantifying plant-available water, optimizing irrigation scheduling in precision agriculture, modeling watershed responses, and studying the impacts of climate change in complex ecosystems. Among these parameters, θ is truly indispensable, as it represents the primary indicator of the water status of soils and a prerequisite for interpreting the other hydraulic variables. In recent years, capacitive sensors have become one of the most widely adopted technologies for θ estimation, owing to their favorable balance between accuracy, robustness, and affordability. These sensors infer soil moisture by measuring dielectric permittivity of soils, which is strongly governed by water content, making them particularly suitable for distributed monitoring and IoT-based environmental applications. The present study aimed to develop a low-cost capacitive sensor for θ estimation. This sensor can be made using 3D printing technology combined with conductive, nickel-based paint, which (once applied on the 3D-printed guides) forms the capacitive electrode. The capacitive component operates at an operational frequency of 60 MHz. The system was subjected to a rigorous testing protocol, including calibration and validation phases under laboratory conditions using three soils of different textures. Its performance was specifically compared with the time-domain reflectometry (TDR) technique, which is widely recognized in Soil Physics and Soil Hydrology as the reference method for θ estimation due to its reliability and accuracy. These tests confirmed the effective performance of the proposed sensor, which overall exhibited good reliability within the selected validation range, corresponding to a θ range of 0 to 0.40 cm³/cm³. Full article

This paper presents a secure 2.4 GHz frequency shift keying (FSK) transmitter front-end with minimal overhead on the data stream using analog obfuscation techniques applied to the modulated waveform. An off-chip true random number generator (TRNG) unit is used to generate the required key for the encryption. Moving away from traditional FSK schemes, which benefit from constant local oscillator (LO) frequency within the channel, the proposed secure FSK scheme shifts the LO frequency in very small steps using an innovative capacitor-bank structure with a calibrated digitally controlled oscillator (DCO). The proposed capacitor bank uses a combination of parallel switches and series capacitors to minimize the impact of the layout parasitics on the minimum capacitor in the bank, thereby reliably creating sub-fF unit capacitors. When combined with the proposed capacitor bank, the cross-coupled CMOS LC voltage-controlled oscillator (VCO) forms a digitally controlled oscillator (DCO). The post-layout simulation results of the DCO reveal that the proposed scheme can achieve a resolution of <20 kHz for the LO frequency shifting while maintaining the phase-noise performance. The reported phase shift allows an equivalent entropy > 6 bits in the implemented analog-inspired secure transmitter front-end. Full article

Climate change exerts a pronounced influence on streamflow regimes by altering precipitation characteristics and potential evapotranspiration, thereby affecting global water availability and hydrological functioning. This study investigates the hydrological behavior of the Upper Indus River Basin (UIRB), a strategically important transboundary mountainous watershed, under a range of future climate scenarios. An integrated modeling approach combining process-based simulation and data-driven techniques is employed to generate new insights relevant to the advancement of the Sustainable Development Goals (SDGs). The Soil and Water Assessment Tool (SWAT) and a Long Short-Term Memory (LSTM) neural network were calibrated and validated using daily streamflow observations spanning 1995–2014. During the calibration phase, SWAT yielded an R² of 0.71, a Nash–Sutcliffe Efficiency (NSE) of 0.59, and a PBIAS of 20.3%. In comparison, the LSTM model demonstrated improved predictive performance, achieving an R² of 0.72, an NSE of 0.71, and a PBIAS of −1.85%. Future discharge simulations were derived from bias-corrected climate projections obtained from 11 General Circulation Models under SSP245 and SSP585 scenarios for four future time slices (2015–2035, 2036–2055, 2056–2075, and 2076–2099), using 1995–2014 as the reference period. Under the high-emission SSP585 pathway, basin-wide precipitation is projected to increase by 14.7% by the late century, accompanied by substantial rises in maximum and minimum temperatures of 17.9% and 36.25%, respectively. SWAT simulations indicate streamflow increases of 7.1–9.9% under SSP245 and 10.1–11.7% under SSP585, whereas the LSTM model projects more pronounced increases of 17–25.6%. The outcomes of this research contribute significantly to multiple SDGs, with quantified impacts on SDG 6 (Clean Water and Sanitation, 35%), SDG 13 (Climate Action, 30%), SDG 2 (Zero Hunger, 15%), SDG 15 (Life on Land, 12%), and SDGs 8 and 9 (Economic Growth and Infrastructure, 8%). The proposed integrated modeling framework supports enhanced water security through optimized resource planning, reinforces climate resilience by strengthening adaptive capacity, promotes agricultural sustainability in irrigation-reliant regions, safeguards fragile mountain ecosystems under accelerating glacier retreat, informs the development of climate-resilient agricultural sustainability in irrigation-reliant regions, and informs the development of climate-resilient infrastructure. Collectively, these findings highlight the urgent necessity for adaptive water management policies to address climate-induced hydrological uncertainty in stressed transboundary river basins and offer a transferable framework for achieving water-related SDGs in climate-sensitive regions worldwide. Full article

Timing skew is a critical bottleneck in high-speed Time-Interleaved (TI) Analog-to-Digital Converters (ADCs) that severely degrades dynamic range. This paper presents a mathematically rigorous, data-driven synchronization framework for calibrating effective sampling timing in TI-ADCs based on the Kuramoto oscillator model. Conventional clock-alignment methods often fail to capture signal-path mismatches, such as sampling switch aperture delay, while correlation-based techniques suffer from signal-dependent “blind-spot” regions. Overcoming this fundamental limitation without analog complexity is achieved via a fully digital feedback loop where each sub-ADC channel is modeled as a coupled oscillator following discrete-time Kuramoto dynamics. Unlike traditional approaches that rely on auxiliary analog phase detectors, the proposed scheme utilizes the ADC outputs to estimate and correct the effective sampling instants directly. A Lyapunov-based stability analysis proves that global phase synchronization is guaranteed when the adaptive coupling strength exceeds a critical value $K_c$. Theoretical results show that the system ensures exponential convergence of phase alignment, driving the total inter-channel timing error toward zero without relying on input-signal statistics. Behavioral MATLAB R2025a simulations of a 12-bit, 4-channel, 10 GS/s TI ADC confirm the analytical predictions. The proposed Kuramoto-based calibration achieves a residual skew reduction of over 99% and an SFDR improvement of 55.12 dB compared to correlation-based methods, even at blind-spot input frequencies, while adaptively reducing digital control power through dynamic coupling adjustment. The study demonstrates that data-driven, synchronization-based calibration provides an input-independent, energy-efficient, and mathematically verifiable solution for system-level timing correction in TI ADCs. Full article

Interferometers are essential tools for quality control of optical surfaces. While interferometric techniques like phase-shifting interferometry offer high accuracy, they involve complex setups, require stringent calibration, and are sensitive to phase shift errors, noise, and surface inhomogeneities. In this research, we introduce an alternative algorithm that integrates Moving Average and Fast Fourier Transform (MAFFT) techniques with Polynomial Fitting. The proposed method achieves results comparable to a Zygo interferometer under standard conditions, with an error margin under 2%. It also maintains measurement stability in noisy environments and in the presence of significant local inhomogeneities, operating in real-time to enable wavefront measurements at 30 Hz. We have validated the algorithm through simulations assessing noise-induced errors and through experimental comparisons with a Zygo interferometer. Full article

Biomass briquettes are an environmentally friendly fuel and have extensive utilization prospects. Compaction pressure is a crucial factor during the production of biomass briquettes, affecting its densification and subsequent potassium release behavior. The release of alkali metals during combustion is typically studied using offline analytical techniques. However, these methods fail to provide real-time measurement of alkali metals release during the combustion process. Therefore, FES, through its equipment simplicity, low operational cost, real-time measurement, and robust adaptability to industrial environments, is commonly employed. In this study, the effect of compaction pressure (80, 130, and 180 MPa) of camphor wood briquettes on potassium release in a premixed flame was investigated by means of Flame Emission Spectroscopy. A spectrometer was used to obtain flame spontaneous emission spectra at three heights above the burner. Based on the proposed spectral analysis method and a calibration procedure, time-resolved flame temperature and concentration of gas-phase potassium in camphor wood briquette combustion were simultaneously measured. The experimental results at the three measurement heights showed that both peak concentration and the amount of gas-phase potassium released from biomass briquettes decreased with the increase in compaction pressure. Furthermore, the amount of potassium released from biomass briquettes at a compaction pressure of 180 MPa was the lowest at all three measurement heights, at 28.0, 14.5, and 21.8 ppm·s. Moreover, the potassium release rate from 0 to 63 s was rapid, and there was an exponential increase in the release ratio curve. The release ratio of potassium reached 50% before entering the ash stage under a compaction pressure of 80 and 130 MPa; in comparison, it only reached 35% under 180 MPa. The potassium release ratio at HAB = 4 cm under compaction pressures of 80, 130, and 180 MPa was 54%, 50%, and 35%, respectively. The findings of this study directly link compaction pressure to K release and demonstrate the applicability of FES for real-time alkali metal detecting, offering both theoretical and practical pathways toward cleaner biomass combustion. Full article

Digital fringe projection profilometry (DFPP) is a widely used technique for full-field, non-contact 3D surface measurement, offering precision from the sub-micrometer-to-millimeter scale depending on system geometry and fringe design. This review provides a consolidated synthesis of advances reported between 2022 and 2025, covering projection and imaging architectures, phase formation and unwrapping strategies, calibration approaches, high-speed implementations, and learning-based reconstruction methods. A central contribution of this review is the integration of these developments within a metrological perspective, explicitly relating phase–height transformation, fringe parameters, system geometry, and calibration to dominant uncertainty sources and error propagation. Recent progress highlights trade-offs between sensitivity, robustness, computational complexity, and applicability to non-ideal surfaces, while learning-based and hybrid optical–computational approaches demonstrate substantial improvements in reconstruction reliability under challenging conditions. Remaining challenges include measurements on reflective or transparent surfaces, dynamic scenes, environmental instability, and real-time operation. The review outlines emerging research directions such as physics-informed learning, digital twins, programmable optics, and autonomous calibration, providing guidance for the development of next-generation DFPP systems for precision metrology. Full article

The hadron calorimeter is a central component of the CMS detector, vital for measuring hadron energies and reconstructing missing transverse momentum. This paper reviews its performance before and after the Phase 1 upgrade (completed in 2019), which upgraded both back-end and front-end electronics, including photodetectors and charge-integrating ADC with precise-timing TDC, as well as its depth segmentation in the barrel and endcaps. This paper describes energy reconstruction algorithms that suppress out-of-time signals, along with high-precision timing alignment and multi-step energy calibration procedures to mitigate radiation damage and improve energy resolution Performance evaluations using proton–proton collision data demonstrate that the upgraded detector and reconstruction techniques achieve good resolution and robust operation under high-luminosity conditions. Full article

Background: Nowadays, flexor hand tendon repair represents a clinical need, and new suture patterns or devices are commonly tested on animal surrogates. Considering the literature, the most frequently adopted animal models for testing are the equivalent tendons taken from porcine specimens. The constitutive modelling of these tendons could open the way to the numerical testing of new repair techniques and the development of digital twins, reducing the use of animal models. Methods: Uniaxial tensile stress-relaxation tests at different strain levels during the loading and unloading phases on porcine tendons were performed. Constitutive formulations based on the assumptions of incompressible and nearly incompressible materials were evaluated. Results: The experimental data were evaluated considering the relaxation tests at different strain levels during both the loading and unloading phases. The experimental tests were used for the material parameter calibration of both models. Conclusions: The stress-relaxation tests conducted at different strain levels during the loading phase showed good agreement with previous findings reported in the literature. Both constitutive model formulations provided a reliable approximation for numerical simulations. Full article