Search Results (31,521)

Accurate and real-time monitoring of low-frequency electromagnetic field (EMF) is essential in power and industrial environments, yet most conventional approaches still suffer from limited spatial coverage, manual operation, and insufficient digitization. To address these challenges, this paper proposes an intelligent EMF monitoring system that integrates six-axis magnetic field sensing, temperature compensation, vector synthesis, Sub-1 GHz wireless communication, and real-time data visualization. The system supports simultaneous measurement of both AC and DC magnetic fields across the 30 Hz–100 kHz range, with specific optimization for power-frequency conditions (50/60 Hz). Designed with modular integration and low power consumption, it is suitable for portable deployment in field scenarios. Comprehensive laboratory and substation tests demonstrate high accuracy, with maximum measurement errors of 1.17% under zero-field and 1.42% under applied-field conditions—well below the ±5% tolerance defined by international standards. Wireless performance tests further confirm stable long-distance communication, achieving ranges of up to 5 km without significant transmission errors, while overall system measurement error reached as low as 0.015%. These results verify the system’s robustness, fidelity, and compliance with international safety standards. Overall, the proposed platform provides a practical and scalable solution for intelligent EMF monitoring, offering strong potential for deployment in industrial environments and infrastructure-critical applications. Full article

Non-perturbative approaches to linear and nonlinear responses (NLR) of atoms, molecules, and molecular aggregates are reviewed in relation to low and high harmonic generations (HG) by laser fields. These response properties are effective for the generation of entangled light pairs for quantum information processing by spontaneous parametric downconversion (SPDC) and stimulated four-wave mixing (SFWM). Quasi-energy derivative (QED) methods, such as QED Møller–Plesset (MP) perturbation, are reviewed as time-dependent variational methods (TDVP), providing analytical expressions of time-dependent linear and nonlinear responses of open-shell atoms, molecules, and molecular aggregates. Numerical Liouville methods for the low HG (LHG) and high HG (HHG) regimes are reviewed to elucidate the NLR of molecules in both LHG and HHG regimes. Three-step models for the generation of HHG in the latter regime are reviewed in relation to developments of attosecond science and spectroscopy. Orbital tomography is also reviewed in relation to the theoretical and experimental studies of the amplitudes and phases of wave functions of open-shell atoms and molecules, such as molecular oxygen, providing the Dyson orbital explanation. Interactions between quantum lights and molecules are theoretically examined in relation to derivations of several distribution functions for quantum information processing, quantum dynamics of molecular aggregates, and future developments of quantum molecular devices such as measurement-based quantum computation (MBQP). Quantum dynamics for energy transfer in dendrimer and related light-harvesting antenna systems are reviewed to examine the classical and quantum dynamics behaviors of photosynthesis. It is shown that quantum coherence plays an important role in the well-organized arrays of chromophores. Finally, applications of quantum optics to molecular quantum information and quantum biology are examined in relation to emerging interdisciplinary frontiers. Full article

The remediation of contaminated soils is essential for restoring land productivity and soil health. Pteris vittata L., an arsenic hyperaccumulator, has been widely used for phytoremediation, yet its ecological effects on soil systems remain insufficiently understood. In this field study, we evaluated the influence of Pteris vittata L. remediation on soil physico-chemical properties, microbial diversity, and molecular ecological networks. The results showed that long-term arsenic contamination significantly reduced soil total carbon, total nitrogen, and available phosphorus, simplified bacterial network structures, and markedly altered the keystone taxa that maintain microbial interactions. In contrast, soils under Pteris vittata L. remediation exhibited higher nutrient availability, greater bacterial diversity, and more complex microbial networks than contaminated soils, indicating partial recovery of ecosystem functions. These findings demonstrate that Pteris vittata L. remediation can mitigate arsenic-induced soil degradation and provide an important scientific basis for assessing the long-term impacts of arsenic contamination and the role of remediation measures in soil health evolution. Full article

In this paper, the impact of SiN passivation on dynamic-R_ON degradation of AlGaN/GaN HEMTs devices is put in evidence. To this end, samples showing different SiN passivation stoichiometry are considered, labeled as Sample A and Sample B. For dynamic-R_ON tests, two different experimental setups are employed to investigate the R_ON-drift showing up during conventional switch mode operation by driving the DUTs under both (i) resistive load and (ii) soft-switching trajectory. This allows to discern the impact of hot carriers and off-state drain voltage stress on the R_ON parameter drift. Measurements performed with both switching loci shows similar dynamic-R_ON response, indicating that hot carriers are not involved in the degradation of tested devices. Nevertheless, a significant difference was observed between Sample A and Sample B, with the former showing an additional R_ON-degradation mechanism, not present on the latter. This additional drift is totally ascribed to the SiN passivation layer and is confirmed by the different leakage current measured across the two SiN types. The mechanism is explained by the injection of negative charges from the Source Field-Plate towards the AlGaN surface that are captured by surface/dielectric states and partially depletes the 2DEG underneath. Full article

Background/Objective: Understanding the training effect in high-level running is important for performance optimization and injury prevention. This includes awareness of how different running surface types (e.g., hard versus soft) may modify biomechanics. Recent studies have demonstrated that deep learning algorithms, such as convolutional neural networks (CNNs), can accurately classify human activity collected via body-worn sensors. To date, no study has assessed optimal signal type, sensor location, and model architecture to classify running surfaces. This study aimed to determine which combination of signal type, sensor location, and CNN architecture would yield the highest accuracy in classifying grass and asphalt surfaces using inertial measurement unit (IMU) sensors. Methods: Running data were collected from forty participants (27.4 years + 7.8 SD, 10.5 ± 7.3 SD years of running) with a full-body IMU system (head, sternum, pelvis, upper legs, lower legs, feet, and arms) on grass and asphalt outdoor surfaces. Performance (accuracy) for signal type (acceleration and angular velocity), sensor configuration (full body, lower body, pelvis, and feet), and CNN model architecture was tested for this specific task. Moreover, the effect of preprocessing steps (separating into running cycles and amplitude normalization) and two different data splitting protocols (leave-n-subject-out and subject-dependent split) was evaluated. Results: In general, acceleration signals improved classification results compared to angular velocity (3.8%). Moreover, the foot sensor configuration had the best performance-to-number of sensor ratio (95.5% accuracy). Finally, separating trials into gait cycles and not normalizing the raw signals improved accuracy by approximately 28%. Conclusion: This analysis sheds light on the important parameters to consider when developing machine learning classifiers in the human activity recognition field. A surface classification tool could provide useful quantitative feedback to athletes and coaches in terms of running technique effort on varied terrain surfaces, improve training personalization, prevent injuries, and improve performance. Full article

Proton spin–lattice and spin–spin NMR relaxation studies were conducted on lung tissue samples from 10 patients. For each case, relaxation properties of tumor tissue were compared with those of the corresponding reference tissue. The spin–lattice relaxation measurements were performed over a wide frequency range, from 10 kHz to 10 MHz, spanning three orders of magnitude. These were complemented by both spin–lattice and spin–spin relaxation data acquired at 18.7 MHz. Notably, the spin–spin relaxation process exhibited a bi-exponential character. This relaxation behavior was quantitatively analyzed using dedicated models to achieve two main goals: to evaluate the diagnostic potential of low-field NMR relaxometry, and to gain insights into the dynamics of water and macromolecules in tissue, in comparison with aqueous solutions of proteins and polymers. The frequency dependence of the spin–lattice relaxation rates was well described by a power-law function, with an exponent of approximately 0.3 closely matching the theoretical prediction for reptation dynamics in polymer systems, associated with the intermolecular relaxation contribution. The combined analysis of spin–lattice and spin–spin relaxation data revealed specific parameters (such as ratios between the relaxation rates or between the amplitudes of individual relaxation components) that can be considered as potential markers of pathological changes affecting molecular dynamics in tissues. Full article

We experimentally investigate the structural, magnetic, transport, and electronic properties of two d⁵ iridate double perovskite materials La₂BIrO₆ (B = Mg, Zn). Notably, despite similar crystallographic structure, the two compounds show distinctly different magnetic behaviors. The M = Mg compound shows an antiferromagnetic-like linear field-dependent isothermal magnetization below its transition temperature, whereas the M = Zn counterpart displays a clear hysteresis loop followed by a noticeable coercive field, indicative of ferromagnetic components arising from a non-collinear Ir spin arrangement. The local structure studies authenticate perceptible M/Ir antisite disorder in both systems, which complicates the magnetic exchange interaction scenario by introducing Ir-O-Ir superexchange pathways in addition to the nominal Ir-O-B-O-Ir super-superexchange interactions expected for an ideally ordered structure. While spin–orbit coupling (SOC) plays a crucial role in establishing insulating behavior for both these compounds, the rotational and tilting distortions of the IrO₆ (and MO₆) octahedral units further lift the ideal cubic symmetry. Finally, by measuring the Ir-L₃ edge resonant inelastic X-ray scattering (RIXS) spectra for both the compounds, giving evidence of spin–orbit-derived low-energy inter-J-state (intra t_2g) transitions (below ~1 eV), the charge transfer (O 2p → Ir 5d), and the crystal field (Ir t_2g → e_g) excitations, we put forward a qualitative argument for the interplay among effective SOC, non-cubic crystal field, and intersite hopping in these two compounds. Full article

The sustainability of Arctic ecosystems that are extremely vulnerable is contingent upon the state of cryosoils. Understanding the principles of ecosystem stability in permafrost conditions, particularly under external natural or human-induced influences, necessitates an examination of the thermal and moisture regimes of the seasonally thawed soil layer. The study concentrated on the variability in the soil’s thermophysical properties in Central Siberia’s permafrost zone (the northern part of Krasnoyarsk Region, Taimyr, Russia). In the industrially affected area of interest, we evaluated and contrasted the differences in the thermophysical properties of soils between two opposing types of landscapes. On the one hand, these are soils that are characteristic of the natural landscape of flat shrub tundra, with a well-developed moss–lichen cover. An alternative is the soils in the landscape, which have exhibited significant degradation in the vegetation cover due to both natural and human-induced factors. The heat-insulating properties of background areas are controlled by the layer of moss and shrubs, while its disturbance determines the excessive heating of the soil at depth. In comparison to the background soil characteristics, degradation of on-ground vegetation causes the active layer depth of the soils to double and the temperature gradient to decrease. With respect to depth, we examine the changes in soil temperature and heat flow dynamics (q, W/m²). The ranges of thermal conductivity (λ, W/(m∙K)) were assessed using field-measured temperature profiles and heat flux values in the soil layers. The background soil was discovered to have lower thermal conductivity values, which are typical of organic matter, in comparison to the soil of the transformed landscape. Thermal diffusivity coefficients for soil layers were calculated using long-term temperature monitoring data. It is shown that it is possible to use an adjusted model of the thermal conductivity coefficient to reconstruct the dynamics of moisture content from temperature dynamics data. A satisfactory agreement is shown when the estimated ($W_{calc}$, %) and observed ($W_{exp}$, %) moisture content values in the soil layer are compared. The findings will be employed to regulate the effects on landscapes in order to implement sustainable nature management in the region, thereby preventing the significant degradation of ecosystems and the concomitant risks to human well-being. Full article

Mikania micrantha, commonly known as mile-a-minute weed, is listed among the world’s top 10 worst weeds. Although native to humid regions of South America, it has recently been found to colonize arid habitats as well. Despite pronounced seasonal hydroclimatic variations in South China and increasing drought due to global climate change, the mechanisms underlying M. micrantha’s drought tolerance remain poorly understood. In this study, we compared the photosynthetic responses of M. micrantha leaves and stems between the dry (June) and wet (December) seasons through field experiments. We measured changes in phenotype, photosynthetic characteristics, and the content of antioxidant and osmotic adjustment substances, using the co-occurring native vine Paederia scandens as a control. The results revealed that during the dry season, M. micrantha leaves exhibited wilting, along with significant reductions in relative water content (RWC), chlorophyll (Chl), soluble sugar (SS), and soluble protein (SP). In contrast, the stems of M. micrantha maintained relatively stable phenotypes and chlorophyll levels compared to those of P. scandens. Notably, M. micrantha stems exhibited significant increases in vessel wall thickness, vessel density, total phenol content, and the activities of peroxidase (POD) and ascorbate peroxidase (APX). Furthermore, compared to P. scandens, M. micrantha stems displayed a greater increase in cortex proportion, flavonoid content, and soluble protein content. Expression analysis of bZIP transcription factors further revealed drought-responsive upregulation of specific genes (bZIP60, ZIP42-1), suggesting their potential involvement in drought response. These results indicate that although the leaves of M. micrantha are susceptible to prolonged drought, the stems exhibit considerable resilience, which may be attributed to a combination of traits including structural modifications in stem anatomy, enhanced antioxidant capacity, and osmotic adjustment. These insights suggest that stem-specific adaptations are key to its drought tolerance, providing a theoretical foundation for understanding the habitat distribution of M. micrantha and informing effective management strategies. Full article

Objectives: Recent studies have shown that highly aspheric lenslets (HAL) are effective in slowing myopia progression. Moreover, research indicates that an enhancement in choroidal thickness might serve as a biomarker for evaluating the efficacy of myopia control treatments. Therefore, this study examined the short-term effects of HAL and full-field +3.00 diopters (D) myopic defocus on sub-foveal choroidal thickness (SFCHR). Design: Prospective experimental study. Participants: Twenty-five participants aged 20–30 (mean 24.56 ± 2.467) years with a refraction error of emmetropia to −5.0 D (mean −2.255 ± 1.514 D). The contralateral non-dominant eye was used as control for each participant. Methods: The participants watched a movie projected at 6 m for 90 min on two separate occasions while wearing HAL or +3 D full-field myopic defocus lenses on their dominant eye. The control eye wore only a single-vision contact lens with the best-corrected distance vision. Three measurements of AL and SFCHR were captured before defocus, and after 60 and 90 min of defocus for both eyes. The main outcome measures were changes in SFCHR and AL over time. Results: Exposure to HAL and +3 D myopic defocus significantly increased SFCHR in the defocused eyes compared to the baseline (p < 0.001). The increase in SFCHR was 6.62 ± 6.32 µm with the HAL intervention and 7.36 ± 8.83 µm with the +3 D intervention. The difference between the two interventions was not statistically significant (p = 0.595). A significant mean difference of 3.176 ± 1.318 µm in SFCHR increase was observed with +3.00 D full-field defocus in the defocused eyes compared to the control eyes over the measurement period (p = 0.020). Conclusions: Short-term exposure to full-field myopic defocus increased choroidal thickness, which was comparable with that observed in peripheral myopic defocus with HAL, although the effect appears less pronounced. Full article

(1) Background: The global increase in life expectancy has generated growing interest in strategies that support functional independence and quality of life among older adults. Functional fitness—including strength, mobility, flexibility, and aerobic endurance—is essential for preserving autonomy during aging. In this context, physical exercise, particularly High-Intensity Interval Training (HIIT), has gained attention for its time efficiency and physiological benefits. This randomized controlled trial aimed to evaluate the effects of a group-based HIIT program on functional fitness in older adults; (2) Methods: Functional outcomes were assessed before, during, and after a 65-week intervention using standardized field tests, including measures of upper and lower body strength, flexibility, aerobic endurance, and agility. This study was prospectively registered at ClinicalTrials.gov (NCT07170579); (3) Results: Significant improvements were observed in the HIIT group across multiple domains of functional fitness compared to the control group, notably in upper body strength, lower limb flexibility, cardiorespiratory endurance, and mobility; (4) Conclusions: These results suggest that HIIT is an effective and adaptable strategy for improving functional fitness in older adults, with the potential to enhance performance in daily activities and support healthy aging in community settings. Full article

Cycling-induced vibration significantly affects riding comfort, with road surface conditions and vehicle type identified as primary contributing factors. This study developed a vibration measurement system based on ISO 2631-1, and proposed a method for generating cycling comfort maps grounded in vibration severity levels. Field measurements on 30 campus roads in Nanchang, China, used a Mountain Bike, Shared E-bike, and Shared Bicycle. Triaxial acceleration data were collected to evaluate vibration exposure, and comfort levels were classified to produce spatially resolved maps. Results show the proposed system has strong stability and adaptability across urban environments. The maps effectively captured vibration intensity variations along road segments. Among the three vehicle types, Mountain Bikes showed the lowest vibration exposure, with approximately 90% of segments rated as comfortable. Shared E-bike exhibited moderate vibration levels, with 42% of segments deemed uncomfortable, while Shared Bicycles experienced the highest vibration, with 80% of routes potentially inducing discomfort and only 1% meeting comfort standards. This study offers a framework for objective acquisition and visualization of cycling vibration data. The developed system and mapping method provide tools for assessing vehicle vibration, guiding route selection, and offer potential value for road quality monitoring. Full article

Fish species’ biological vocalizations serve as essential acoustic signatures for passive acoustic monitoring (PAM) and ecological assessments. However, limited availability of high-quality acoustic recordings, particularly for region-specific species like the brown croaker (Miichthys miiuy), hampers data-driven bioacoustic methodology development. In this study, we present a framework for reconstructing brown croaker vocalizations by integrating fk14 wavelet synthesis, PSO-based parameter optimization (with an objective combining correlation and normalized MSE), and deep learning-based validation. Sensitivity analysis using a normalized Bartlett processor identified delay and scale (length) as the most critical parameters, defining valid ranges that maintained waveform similarity above 98%. The reconstructed signals matched measured calls in both time and frequency domains, replicating single-pulse morphology, inter-pulse interval (IPI) distributions, and energy spectral density. Validation with a ResNet-18-based Siamese network produced near-unity cosine similarity (~0.9996) between measured and reconstructed signals. Statistical analyses (95% confidence intervals; residual errors) confirmed faithful preservation of SPL values and minor, biologically plausible IPI variations. Under noisy conditions, similarity decreased as SNR dropped, indicating that environmental noise affects reconstruction fidelity. These results demonstrate that the proposed framework can reliably generate acoustically realistic and morphologically consistent fish vocalizations, even under data-limited scenarios. The methodology holds promise for dataset augmentation, PAM applications, and species-specific call simulation. Future work will extend this framework by using reconstructed signals to train generative models (e.g., GANs, WaveNet), enabling scalable synthesis and supporting real-time adaptive modeling in field monitoring. Full article

Aim: This study analyzed the concurrent validity of the Optojump infrared photocell system for estimating lower limb peak power by comparing it with the 15 s Wingate anaerobic test (WAnT) and examining relationships with sprint performance indicators. Methods: Twelve physically active university students (ten males, two females; age: 23.39 ± 1.47 years; body mass: 73.08 ± 9.19 kg; height: 173.67 ± 6.97 cm; BMI: 24.17 ± 1.48 kg·m⁻²) completed a cross-sectional validation protocol. Participants performed WAnT on a calibrated Monark ergometer (7.5% body weight for males, 5.5% for females), 30 s continuous jump tests using the Optojump system (Microgate, Italy), and 30 m sprint assessments with 10 m and 20 m split times. Peak power was expressed in absolute (W), relative (W·kg⁻¹), and allometric (W·kg^−0.67) terms. Results: Thirty-second continuous jump testing produced systematically higher peak power values across all metrics (p < 0.001). Mean differences indicated large effect sizes: relative power (Cohen’s d = 0.99; 18.263 ± 4.243 vs. 10.99 ± 1.58 W·kg⁻¹), absolute power (d = 0.86; 1381.71 ± 393.44 vs. 807.28 ± 175.45 W), and allometric power (d = 0.79). Strong correlations emerged between protocols, with absolute power showing the strongest association (r = 0.842, p < 0.001). Linear regression analysis revealed that 30 s continuous jump-derived measurements explained 71% of the variance in Wingate outcomes (R² = 0.710, p < 0.001). Sprint performance showed equivalent predictive capacity for both tests (Wingate: R² = 0.66; 30 s continuous jump: R² = 0.67). Conclusions: The Optojump infrared photocell system provides a valid and practical alternative to laboratory-based ergometry for assessing lower limb anaerobic power. While it systematically overestimates absolute values compared with the Wingate anaerobic test, its strong concurrent validity (r > 0.80), large effect sizes, and equivalent predictive ability for sprint performance (R² = 0.66–0.71) confirm its reliability as a field-based assessment tool. These findings underscore the importance of sport-specific, weight-bearing assessment technologies in modern sports biomechanics, providing coaches, practitioners, and clinicians with a feasible method for monitoring performance, talent identification, and training optimization. The results further suggest that Optojump-based protocols can bridge the gap between laboratory precision and ecological validity, supporting both athletic performance enhancement and injury prevention strategies. Full article

The intrinsic noise of giant magnetoresistive (GMR) sensors is large at low frequencies, and their resolution is inevitably significantly limited. Investigation of GMR noise requires the use of measurement systems that have lower noise than the sample. In this context, the main purpose of this study is to evaluate the effectiveness of two electronic noise measurement configurations of a single GMR sensing element. The first method connects the sample in a voltage divider configuration and the second method connects in a Wheatstone bridge configuration. Three amplification set-ups were investigated: a low-noise amplifier, an ultra-low-noise amplifier and an instrumentation amplifier. Using cross-correlation, the noise of the measurement system introduced by the amplifiers was reduced. Noise spectra were recorded at room temperature in the frequency range of 0.5 Hz to 10 kHz, under different sample bias voltages. The measurements were performed in zero applied magnetic field and in a field corresponding to the maximum sensitivity of the sensor. From the noise spectra, the detectivity of the sensor was determined to be in the 200–300 nT/√Hz range. Good agreement was observed between the results obtained using all three set-ups, suggesting the effectiveness of the noise measurement systems applied to the magnetoresistive sensor. Full article