Search Results (8,490)

A series of Er³⁺–Tm³⁺–Yb³⁺ tri-doped fluorophosphate glasses with different molar compositions were synthesized using the conventional melt-quenching technique, and their optical properties were measured and analyzed. Under laser excitation at 980 nm, blue, green and red upconverted emissions were observed at around 475, 545 and 660 nm, respectively. Based on the results and the energy level diagrams, energy transfer processes were proposed to explain the population mechanisms of the emitting levels. A final characterization was developed within the framework of the CIE 1931 chromaticity coordinate diagram. Varying the doping concentrations of the optically active rare earth ions, as well as the laser pumping power, enabled modulation of the three primary colors, resulting in blue, green and relatively close to white light emissions. This tunability of the upconverted emissions highlights the potential of these fluorophosphate glasses as tunable optical devices, laser systems and visual show effects. 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

Near-field acoustic holography (NAH) provides an effective way to achieve wide-band, high-resolution visualization measurement of the sound insulation performance of building components. However, based on Green’s function, the microphone array’s inherent amplitude and phase mismatch errors will exponentially amplify the sound field inversion process, significantly reducing the measurement accuracy. To systematically evaluate this problem, this study combines numerical simulation with actual measurements in a soundproof room that complies with the ISO 10140 standard, quantitatively analyzes the influence of array system errors on NAH reconstructed sound insulation and acoustic images, and proposes an error correction strategy based on channel transfer function normalization. The research results show that when the array amplitude and phase mismatch mean values are controlled within 5% and 5°, respectively, the deviation of the weighted sound insulation measured by NAH can be controlled within 1 dB, and the error in the key frequency band of building sound insulation (200–1.6k Hz) does not exceed 1.5 dB; when the mismatch mean value increases to 10% and 10°, the deviation of the weighted sound insulation can reach 2 dB, and the error in the high-frequency band (≥1.6k Hz) significantly increases to more than 2.0 dB. The sound image shows noticeable spatial distortion in the frequency band above 250 Hz. After applying the proposed correction method, the NAH measurement results of the domestic microphone array are highly consistent with the weighted sound insulation measured by the standard method, and the measurement difference in the key frequency band is less than 1.0 dB, which significantly improves the reliability and applicability of low-cost equipment in engineering applications. In addition, the study reveals the inherent mechanism of differential amplification of system errors in the propagating wave and evanescent wave channels. It provides quantitative thresholds and operational guidance for instrument selection, array calibration, and error compensation of NAH technology in building sound insulation detection. Full article

Given the importance of turbidity as a key indicator of water quality, this study investigates the use of a convolutional neural network (CNN) to classify water samples into five turbidity-based categories. These classes were defined using ranges inspired by Mexican environmental regulations and generated from 33 laboratory-prepared mixtures with varying concentrations of suspended clay particles. Red, green, and blue (RGB) images of each sample were captured under controlled optical conditions, and turbidity was measured using a calibrated turbidimeter. A transfer learning (TL) approach was applied using EfficientNet-B0, a deep yet computationally efficient CNN architecture. The model achieved an average accuracy of 99% across ten independent training runs, with minimal misclassifications. The use of a lightweight deep learning model, combined with a standardized image acquisition protocol, represents a novel and scalable alternative for rapid, low-cost water quality assessment in future environmental monitoring systems. Full article

Traditional Foreign Object Debris (FOD) detection methods face challenges such as difficulties in large-size data acquisition and the ineffective application of detection algorithms with high accuracy. In this paper, image data augmentation was performed using generative adversarial networks and diffusion models, generating images of monitoring areas under different environmental conditions and FOD images of varied types. Additionally, a three-stage image blending method considering size transformation, a seamless process, and style transfer was proposed. The image quality of different blending methods was quantitatively evaluated using metrics such as structural similarity index and peak signal-to-noise ratio, as well as Depthanything. Finally, object detection models with a similarity distance strategy (SimD), including Faster R-CNN, YOLOv8, and YOLOv11, were tested on the dataset. The experimental results demonstrated that realistic FOD data were effectively generated. The Structural Similarity Index Measure (SSIM) and Peak Signal-to-Noise Ratio (PSNR) of the synthesized image by the proposed three-stage image blending method outperformed the other methods, reaching 0.99 and 45 dB. YOLOv11 with SimD trained on the augmented dataset achieved the mAP of 86.95%. Based on the results, it could be concluded that both data augmentation and SimD significantly improved the accuracy of FOD detection. Full article

Nanoparticle floating gate (NPFG) transistors have gained attention as synaptic devices due to their discrete charge storage capability, which minimizes leakage currents and enhances the memory window. In this study, we propose and evaluate a mesh-type floating gate transistor (Mesh-FGT) designed to emulate the characteristics of NPFG transistors. Individual floating gates with dimensions of 3 µm × 3 µm are arranged in an array configuration to form the floating gate structure. The Mesh-FGT is composed of an Al/Pt/Cr/HfO₂/Pt/Cr/HfO₂/SiO₂/SOI (silicon-on-insulator) stack. Threshold voltages (Vth) extracted from the transfer and output curves followed Gaussian distributions with means of 0.063 V (σ = 0.100 V) and 1.810 V (σ = 0.190 V) for the erase (ERS) and program (PGM) states, respectively. Synaptic potentiation and depression were successfully demonstrated in a multi-level implementation by varying the drain current (I_ds) and Vth. The Mesh-FGT exhibited high immunity to leakage current, excellent repeatability and retention, and a stable memory window that initially measured 2.4 V. These findings underscore the potential of the Mesh-FGT as a high-performance neuromorphic device, with promising applications in array device architectures and neuromorphic neural network implementations. Full article

Terahertz (THz) communications and simultaneous wireless information and power transfer (SWIPT) hold the potential to energize battery-less Internet-of-Things (IoT) devices while enabling multi-gigabit data transmission. However, severe path loss, blockages, and rectifier nonlinearity significantly hinder both throughput and harvested energy. Additionally, high-power THz beams pose safety concerns by potentially exceeding specific absorption rate (SAR) limits. We propose a sensing-adaptive power-focusing (APF) framework in which a reconfigurable intelligent surface (RIS) embeds low-rate THz sensors. Real-time backscatter measurements construct a spatial map used for the joint optimisation of (i) RIS phase configurations, (ii) multi-tone SWIPT waveforms, and (iii) nonlinear power-splitting ratios. A weighted MMSE inner loop maximizes the data rate, while an outer alternating optimisation applies semidefinite relaxation to enforce passive-element constraints and SAR compliance. Full-stack simulations at 0.3 THz with 20 GHz bandwidth and up to 256 RIS elements show that APF (i) improves the rate–energy Pareto frontier by 30–75% over recent adaptive baselines; (ii) achieves a 150% gain in harvested energy and a 440 Mbps peak per-user rate; (iii) reduces energy-efficiency variance by half while maintaining a Jain fairness index of 0.999;; and (iv) caps SAR at 1.6 W/kg, which is 20% below the IEEE C95.1 safety threshold. The algorithm converges in seven iterations and executes within <3 ms on a Cortex-A78 processor, ensuring compliance with real-time 6G control budgets. The proposed architecture supports sustainable THz-powered networks for smart factories, digital-twin logistics, wire-free extended reality (XR), and low-maintenance structural health monitors, combining high-capacity communication, safe wireless power transfer, and carbon-aware operation for future 6G cyber–physical systems. Full article

This paper presents a formulation for the dynamic analysis of dam–reservoir–foundation systems, employing a coupled finite element model that integrates displacements and reservoir pressures. An innovative coupled approach, without separating the solid and fluid equations, is proposed to directly solve the single non-symmetrical governing equation for the whole system with non-proportional damping. For the modal analysis, a state–space method is adopted to solve the coupled eigenproblem, and complex eigenvalues and eigenvectors are computed, corresponding to non-stationary vibration modes. For the seismic analysis, a time-stepping method is applied to the coupled dynamic equation, and the stress–transfer method is introduced to simulate the nonlinear behavior, innovatively combining a constitutive joint model and a concrete damage model with softening and two independent scalar damage variables (tension and compression). This formulation is implemented in the computer program DamDySSA5.0, developed by the authors. To validate the formulation, this paper provides the experimental and numerical results in the case of the Cahora Bassa dam, instrumented in 2010 with a continuous vibration monitoring system designed by the authors. The good comparison achieved between the monitoring data and the dam–reservoir–foundation model shows that the formulation is suitable for simulating the modal response (natural frequencies and mode shapes) for different reservoir water levels and the seismic response under low-intensity earthquakes, using accelerograms measured at the dam base as input. Additionally, the dam’s nonlinear seismic response is simulated under an artificial accelerogram of increasing intensity, showing the structural effects due to vertical joint movements (release of arch tensions near the crest) and the concrete damage evolution. Full article

The Moxi area in the Sichuan Basin hosts abundant deep geothermal resources, but their thermal regime and accumulation mechanisms remain poorly understood. Using 2D/3D seismic data, drilling records, and temperature measurements (DST), we analyze deep thermal fields, reservoir–caprock systems, and structural features. The following are our key findings: (1) Heat transfer is conduction-dominated, with thermal anomalies in Late Permian–Early Cambrian strata. Four mudstone/shale caprocks and three carbonate reservoirs occur, with the Longtan Formation as the key seal. Reservoir geothermal gradients (25.05–32.55 °C/km) exceed basin averages. (2) Transtensional strike-slip faults form E-W/NE/NW networks; most terminate at the Permian Longtan Formation, with few extending into the Lower Triassic while penetrating the Archean–Lower Proterozoic basement. (3) Structural highs positively correlate with higher geothermal gradients. (4) The deep geothermal reservoirs and thermal accumulation mechanisms in the Moxi area are jointly controlled by crustal thinning, basement uplift, and structural architecture. Mantle-derived heat converges at basement uplift cores, generating localized thermal anomalies. Fault networks connect these deep heat sources, facilitating upward fluid migration. Thick Longtan Formation shale seals these rising thermal fluids, causing anomalous heating in underlying strata and concentrated thermal accumulation in reservoirs—enhanced by thermal focusing effects from uplift structures. This study establishes a theoretical framework for target selection and industrial-scale geothermal exploitation in sedimentary basins, highlighting the potential for repurposing oil/gas infrastructure. Full article

This paper presents the development of a compact nanopositioning stage with long-range capabilities and six-degree-of-freedom (DOF) closed-loop control. The system, referred to as NPS6D100, provides Ø100 mm planar and 10 mm vertical travel range while maintaining direct force transfer to the moving platform (or slider) in all DOFs. Based on an integrated planar direct drive concept, the system is enhanced by precise vertical actuation and full 6D output feedback control. The mechanical structure, drive architecture, guiding, and measurement subsystems are described in detail, along with experimental results that confirm sub-10 nm servo errors under constant setpoint operation and in synchronized multi-axis motion scenarios. With its scalable and low-disturbance design, the NPS6D100 is well suited as a nanopositioning platform for sub-10 nm applications in nanoscience and precision metrology. Full article

This study provides a detailed dataset from two modern homes constructed inside an environmentally controlled chamber. These data are used to carefully calibrate a dynamic thermal simulation model of these homes. The calibrated models show good agreement with measurements taken under controlled conditions. The two case study homes, “The Future Home” and “eHome2”, were constructed within the University of Salford’s Energy House 2.0, and high-quality data were collected over eight days. The calibration process involved updating U-values, air permeability rates, and modelling refinements, such as roof ventilation, ground temperatures, and sub-floor void exchange rates, set as boundary conditions. Results demonstrated a high level of accuracy, with performance gaps in whole-house heat transfer coefficient reduced to 0.5% for “The Future Home” and 0.6% for “eHome2”, falling within aggregate heat loss test uncertainty ranges by a significant amount. The study highlights the improved accuracy of calibrated dynamic thermal simulation models, compared to results from the steady-state Standard Assessment Procedure model. By providing openly accessible calibrated models and a clearly defined methodology, this research presents valuable resources for future building performance modelling studies. The findings support the UK’s transition to dynamic modelling approaches proposed in the recently introduced Home Energy Model approach, contributing to improved prediction of energy efficiency and aligning with goals for zero carbon ready and sustainable housing development. Full article

Thermal sensors are widely used in medical, industrial and other fields, where the requirements for high sensitivity and portability continues to increase. Here we propose a suspended bridge structure fabricated using MEMS, which effectively shrinks the size and reduces heat loss. This study reviews current sensor-related theories of heat conduction, convective heat transfer and thermal radiation. Heat loss models for suspended and non-suspended bridge structures are established, and finite element analysis is conducted to evaluate their thermal performance. The thermal performance of the suspended bridge structure is further validated through infrared temperature measurements on the manufactured sensor device. Theoretical calculations demonstrate that the proposed suspension bridge structure reduces heat loss by 88.64% compared with traditional designs. Benefiting from this improved heat retention, which was also confirmed by infrared thermography, the thermal sensor fabricated based on the suspension bridge structure achieves an ultra-high sensitivity of 0.38 V/W and a fast response time of less than 200 ms, indicating a high accuracy in thermal characterization. The correlation coefficient obtained for the sensor output voltage and input power of the sensor is approximately 1.0. Based on this design, multiple microfluidic channels with suspended bridge structures can be integrated to realize multi-component detection, which is important for the development of multifunctional biomedical detection. Full article

In this study, we address the question of whether a waveguide with absorbing sidewalls can be considered pseudo free space and if the free-space transfer function is valid in such a medium. We test this hypothesis by applying a phase retrieval algorithm based on the free-space transfer function. First, optical measurements are carried out to measure the optical properties of a stack of thin films and select the parameters of simulations. Next, the propagation of light in a waveguide was simulated in COMSOL, and the phase of a wave was retrieved in MATLAB. Analysis was performed both for free-space conditions, and for a waveguide with absorbing sidewalls. The cross-correlation between the distributions of intensity under both conditions was about 0.40. The RMS error of the wave retrieved under free-space conditions was 0.378 rad, while that in the case of absorbing sidewalls was 0.323 rad, indicating successful retrieval. The successfully recovered phase of the input wave suggests that a waveguide with absorbing sidewalls can be approximated as pseudo free space and the free-space transfer function may be valid. These results may be used in future studies on how to shorten the phase retrieval of two-dimensional objects. Full article

Air pollution monitoring in ungauged zones presents unique challenges yet remains critical for understanding environmental health impacts and socioeconomic dynamics in the Eastern Mediterranean region. This study investigates air pollution patterns in northwestern Syria during 2019–2024, analyzing NO₂ and CO concentrations using Sentinel-5P TROPOMI satellite data processed through Google Earth Engine. Monthly concentration averages were examined across eight key locations using linear regression analysis to determine temporal trends, with Spearman’s rank correlation coefficients calculated between pollutant levels and five meteorological parameters (temperature, humidity, wind speed, atmospheric pressure, and precipitation) to determine the influence of political governance, economic conditions, and environmental sustainability factors on pollution dynamics. Quality assurance filtering retained only measurements with values ≥ 0.75, and statistical significance was assessed at a p < 0.05 level. The findings reveal distinctive spatiotemporal patterns that reflect the region’s complex political-economic landscape. NO₂ concentrations exhibited clear political signatures, with opposition-controlled territories showing upward trends (Al-Rai: 6.18 × 10⁻⁸ mol/m²) and weak correlations with climatic variables (<0.20), indicating consistent industrial operations. In contrast, government-controlled areas demonstrated significant downward trends (Hessia: −2.6 × 10⁻⁷ mol/m²) with stronger climate–pollutant correlations (0.30–0.45), reflecting the impact of economic sanctions on industrial activities. CO concentrations showed uniform downward trends across all locations regardless of political control. This study contributes significantly to multiple Sustainable Development Goals (SDGs), providing critical baseline data for SDG 3 (Health and Well-being), mapping urban pollution hotspots for SDG 11 (Sustainable Cities), demonstrating climate–pollution correlations for SDG 13 (Climate Action), revealing governance impacts on environmental patterns for SDG 16 (Peace and Justice), and developing transferable methodologies for SDG 17 (Partnerships). These findings underscore the importance of incorporating environmental safeguards into post-conflict reconstruction planning to ensure sustainable development. Full article

This paper presents the design and performance analysis of a compact wireless power transfer (WPT) system operating at 1.6 GHz. The transmitter (Tx) structure consists of a circular slot and a circular radiating element, excited from the backside of the substrate, while the receiver (Rx) comprises a slotted patch antenna miniaturized using two vertical vias. The initial power transfer efficiency (PTE), represented by the transmission coefficient $S_{21}$, was measured to be −31 dB with a 25 mm separation between Tx and Rx. To enhance the efficiency of the system, a dielectric matching media (MM) was introduced between the transmitter and receiver. Through the implementation of the MM, the PTE improved significantly, with $S_{21}$ increasing to −24 dB. A parametric study was conducted by varying the thickness of the MM from 1 mm to 10 mm and the relative permittivity (${\epsilon }_r$) from 5 to 30. The results demonstrate that both the thickness and dielectric constant of the MM play a crucial role in improving the coupling and overall efficiency of the WPT system. The optimal configuration was achieved with a matching media thickness of 10 mm and a relative permittivity of 25, which yielded the best improvement in transmission performance. This work offers a practical approach to enhance near-field WPT efficiency using simple matching structures and is particularly relevant for compact and low-profile energy transfer applications. Full article