Search Results (36,426)

Four perovskite manganite samples, La_0.80Ag_0.20MnO₃ (LA), La_0.78Eu_0.02Ag_0.20MnO₃ (LEA), La_0.80Pb_0.05Ag_0.15MnO₃ (LPA), and La_0.77Eu_0.03Pb_0.05Ag_0.15MnO₃ (LEPA), were prepared by the Pechini sol–gel method. The samples were characterized by X-ray diffraction, scanning electron microscopy, energy-dispersive spectroscopy, X-ray photoelectron spectroscopy, and a magnetic property measurement system. A systematic investigation was conducted into the individual effects of Eu and Pb doping, as well as their co-doping, on the microstructural, magnetic and magnetocaloric properties of the materials. The results show that all samples are mainly composed of a rhombohedral perovskite phase with the R$\overline{3}$c space group, accompanied by a trace amount of Ag. Addition of Eu³⁺ and Pb²⁺ induces lattice contraction and expansion, respectively. Under the same processing conditions, the average crystallite and particle sizes of the LEA sample (45.3 nm and 0.18 μm) are smaller than those of the other three samples (69.6~80.6 nm and 0.38~0.44 μm), indicating that the introduction of Eu alone suppresses crystallization ability, which can be avoided through Eu/Pb co-doping. All samples undergo a second-order ferromagnetic–paramagnetic transition, and the Curie temperature T_C shifts to either lower or higher temperatures upon the introduction of Eu or Pb alone (from 310.8 K to 298.0 K or 318.0 K, respectively), which is attributed to the variation of the Mn³⁺/Mn⁴⁺ double-exchange (DE) interaction resulting from the ionic size mismatch and lattice distortion. In the LPA sample, an additional contribution arises from the altered Mn³⁺/Mn⁴⁺ ratio and enhanced DE interaction caused by the substitution of Pb²⁺ for Ag⁺. By modifying the Eu/Pb ratio, the T_C of the LEPA sample was tuned to 299.3 K, and its maximum magnetic entropy change was enhanced to 3.90 J·kg⁻¹·K⁻¹ ($∆$H = 2 T). These results indicate that multicomponent synergistic regulation can improve the magnetocaloric performance of La-based perovskite manganites, providing a useful strategy for the development of room-temperature magnetic refrigeration materials. Full article

Background/Objectives: Altered lumbar sagittal alignment is associated with degenerative and mechanical musculoskeletal disorders. However, conventional angle-based measurements, such as the Cobb angle, may not fully reflect the overall curvature pattern of the lumbar spine. This pilot study investigated whether curvature distribution profiling on sagittal lumbar radiographs is associated with clinically confirmed lumbar musculoskeletal disorders. Methods: This retrospective pilot study included 50 adults who underwent standing sagittal lumbar radiography. Patients were classified as disease-positive or disease-negative according to radiographic findings, short-term clinical follow-up, and chart review. Vertebral body centroids from T12 to S1 were manually identified to construct continuous lumbar curvature profiles. Curvature height was normalized to a standardized baseline for cross-case comparison. Distribution patterns of curvature deviation were analyzed between groups. Total curvature was also calculated as a quantitative descriptor of overall lumbar bending, and group-wise comparisons were performed using the Kruskal–Wallis test. Results: The disease-negative group showed a predominantly unimodal and symmetric curvature distribution, whereas the disease-positive group showed greater dispersion at both hypo-lordotic and hyper-lordotic extremes. The hypo-lordosis subgroup demonstrated a more consistent deviation pattern, whereas the hyper-lordosis subgroup partially overlapped with the disease-negative distribution. These pattern-based findings suggest that deviation from a central curvature profile, rather than lordosis magnitude alone, may be associated with lumbar musculoskeletal disorders. In exploratory quantitative analysis, total curvature showed a distributional shift in the disease-positive group, although the overall between-group difference did not reach statistical significance (p = 0.096). Conclusions: Curvature distribution profiling may provide complementary morphological information in conjunction with conventional angle-based assessment. Both reduced and exaggerated lumbar curvature patterns were observed in association with lumbar musculoskeletal disorders. Larger studies are needed to validate these preliminary findings and to determine the clinical relevance of this approach. Full article

This study investigates sodium polyacrylate (NaPA) as a rheology modifier and selective depressant in the flotation of Cu²⁺-activated kaolin–chalcopyrite under industrial water (IW) and seawater (SW) conditions. The work addresses a critical gap in saline systems: how an anionic polymer simultaneously influences clay activation, sulfide floatability, aggregate dispersion, and pulp rheology by varying the medium’s ionic composition. Microflotation, zeta potential, adsorption, yield strength, and Focused Beam Reflectance Measurement (FBRM) assays were used to establish structure–property–response relationships. In IW, Cu²⁺ strongly promoted NaPA adsorption onto both minerals, shifting them toward more negative potentials and significantly reducing selectivity: kaolin recovery decreased from 86.5% to 40.0% at 50 ppm NaPA. In comparison, chalcopyrite recovery fell below 30% at 100 ppm NaPA. In SW, NaPA maintained its depressant effect on kaolin without affecting chalcopyrite flotation, which remained above 90%. This behavior is consistent with reduced polymer adsorption at high ionic strength, where ionic shielding and coiling limit its interaction with chalcopyrite but allow sufficient adsorption onto kaolin to inhibit the collector’s action. Rheological and FBRM results support this interpretation, showing a decrease in yield strength and aggregate size after NaPA addition, with a more pronounced effect in IW than in SW. Full article

Blood pressure is a central marker of cardiovascular risk, but continuous monitoring remains difficult because cuff-based measurements are intermittent and uncomfortable. Photoplethysmography (PPG) is already ubiquitous in wearables and can, in principle, enable cuffless blood pressure estimation from a single optical signal. However, many deep learning approaches that perform well in floating-point are impractical for microcontroller-class devices, where memory budgets, latency, and integer-only arithmetic constrain what can be deployed. A key open question is which neural architectures retain accuracy after full-integer quantization, rather than only under desktop inference. Here, we show an end-to-end, microcontroller-oriented evaluation framework that benchmarks multiple 1D convolutional models for cuffless systolic and diastolic pressure estimation from single-channel PPG, jointly optimizing estimation error, model footprint, and quantization robustness. We find that floating-point accuracy alone is a poor predictor of deployability: some lightweight CNNs exhibit substantial performance drift after INT8 conversion, whereas a compact residual 1D CNN preserves its predictions with near-identical error statistics after integer quantization. We then deploy the selected integer-only model on an STM32N6 microcontroller using an industrial toolchain and confirm that on-device inference maintains low bias and limited error dispersion while meeting real-time constraints for continuous operation. These results highlight architecture-dependent quantization stability as a critical design dimension for sensor-edge intelligence and support the feasibility of fully on-device cuffless blood pressure monitoring without multimodal sensing or cloud processing. Full article

This study evaluates the robustness and time consistency of GNSS coordinate solutions obtained from a suite of scientific and legacy commercial software packages, with the aim of assessing their suitability for rapid preliminary framing of institutional geodetic networks. The analysis includes Pinnacle 1.0, Topcon Tools v.8, TGOffice 1.63, Leica Geo Office Combined 7.0, NDA Lite, and the scientific-grade NDA Professional, together with PPP solutions generated through the CSRS service. A one-year dataset from the UNIPA GNSS CORS network was processed to derive monthly coordinate estimates, which were compared in terms of geocentric (ΔXYZ), horizontal (ΔEN), and vertical (ΔUp) deviations, as well as temporal behavior and statistical significance (Welch’s t-test). The results show that NDA Professional provides the most stable and time-consistent solutions, with mean horizontal and vertical dispersions typically below 2–3 mm. Topcon Tools and Pinnacle also exhibit good performance, with average ΔEN values of approximately 3–4 mm and ΔH values generally within 5–7 mm. In contrast, Leica LGO and NDA Lite display larger variability, particularly in the vertical component, where monthly deviations may exceed 10 mm. The CSRS solution, due to its PPP-based intrinsic nature, reveals a statistically significant temporal trend (on the order of 5–8 mm/year), which prevents direct comparison with static network solutions; however, once detrended, its dispersion becomes comparable to the best-performing static software, with ΔEN and ΔUp values of 2–4 mm. Full article

Antarctic krill protein (AKP) was conjugated with three reducing monosaccharides (ribose, glucose, fructose) and five polysaccharides (xanthan gum, konjac glucomannan, inulin, κ-carrageenan, and pectin) via a controlled Maillard-type glycation process (pH 7.0, 90 °C, 24 h). We comparatively evaluated glycation reactivity (color change and degree of glycation), structural responses (particle size, FTIR, intrinsic fluorescence, surface hydrophobicity, and microstructure), and key techno-functional properties (solubility, water- and oil-holding capacities, and emulsifying performance). Monosaccharide-conjugated AKP exhibited stronger browning and higher apparent glycation activity, consistent with the higher reactivity of small-molecule sugars. In contrast, polysaccharide-conjugated AKP showed more pronounced improvements in dispersion-related and interfacial functions, reflecting enhanced steric stabilization and hydration after polysaccharide grafting. Notably, κ-carrageenan conjugation delivered the strongest overall functional enhancement (water-holding capacity ≈ 22.1 g/g; oil-holding capacity ≈ 10 g/g) and the most stable emulsions. These findings clarify how glycosylating-agent size and architecture steer AKP glycation outcomes, providing a practical basis for tailoring AKP ingredients for aqueous and emulsion-based foods. Full article

To improve the predictive accuracy of wind-field distributions during fires in high-rise buildings, this study targets the shortcomings of traditional prediction methods, including insufficient information fusion and dispersed feature representations under high-rise fire conditions. An efficient attention mechanism, termed Adaptive Channel and Multi-Scale Spatial Fusion Attention Mechanism (CSFAM), is proposed, which endows the model with enhanced adaptive focusing and multi-scale integration capabilities. CSFAM can account for environmental features across multiple dimensions to enable high-spatial-resolution wind-field reconstruction, thereby improving robustness and prediction accuracy in complex environments. To validate the effectiveness of CSFAM for predicting wind fields under high-rise-fire conditions, CFD-based scenario modeling was employed to generate a dataset of 1050 CFD-derived wind-field distributions across diverse inflow-wind and fire-source scenarios, partitioned into training, testing, and validation sets according to the fire-source size. When applying the CSFAM-enhanced multi-layer perceptron (MLP), the wind-field predictions achieved a mean squared error (MSE) of 0.0004, a mean absolute error (MAE) of 0.0141, and an R² of 0.9766, outperforming state-of-the-art methods. The results demonstrate that CSFAM plays a significant role in markedly improving wind-speed prediction accuracy during high-rise-building fires, and enhances the model’s ability to identify and express vortex-like and other key aerodynamic features generated by the fire, thereby improving the capture of the complex nonlinear aerodynamic structures induced by fire. Full article

The disposal of waste tyres presents a significant environmental challenge, necessitating sustainable, high-value recycling solutions. This study explores the incorporation of waste tyre metal fibre (WTMF) into hot mix asphalt (HMA) to enhance mechanical performance while reducing its electrical resistivity as well as the landfill burden. The primary goal of this research is to apply response surface methodology (RSM) to experimental data for modelling and optimizing WTMF-modified HMA mixes by capturing the coupled effects of fibre reinforcement and binder content on mechanical and functional performance. The microstructural characteristics of WTMF were examined using scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), and X-ray diffraction (XRD). WTMF-modified mixes containing five WTMF dosages (from 0% to 1.50%) and bitumen contents from 4% to 6% were prepared and tested in the laboratory. The resulting dataset was used for RSM modelling, with WTMF and bitumen contents as input factors and Marshall stability, flow, porosity, and electrical resistivity as response variables. The central composite design (CCD) technique was employed to quantify interaction effects and to identify statistically significant trends. The developed models were validated using statistical indicators, and optimal mixture compositions were determined and experimentally verified. Microstructural analysis revealed WTMF’s irregular, rough surface with microcracks and pits, aiding crack-bridging and stress transfer. RSM results indicated 0.71% WTMF and 5.1% bitumen as an optimal combination of factors. Furthermore, high R² (>0.80) and adequate precision (>4.0) values from analysis of variance (ANOVA) underscore the significance of the proposed models, revealing a robust correlation between experimental and predicted data. This study demonstrated WTMF’s potential to be used in conventional HMA mixes, offering a sustainable recycling pathway for waste tyres. Full article

Modern agriculture depends heavily on machinery to maximize operational efficiency and, consequently, profitability, but the wear-and-tear on the mechanical components of machinery due to ageing can lead to reduced efficiency, more downtime, and higher maintenance expenses, thus raising the operative costs. These problems have been addressed by the use of specific lubricant additives for machinery; however, additives have known disadvantages, such as compatibility restrictions and environmental concerns, which represent critical issues especially in case of possible dispersion in the environment. Modern industry is always looking for techniques and solutions to increase efficiency and productivity, and this study investigates the possible advantages of employing nanotechnology in lubricant formulations. Amongst all possible substances, SiO₂ nanoparticles are increasingly promising as lubricant additives due to their unique properties, which include heat resistance, high levels of stability, and good biocompatibility. Moreover, biolubricants, derived from renewable sources, offer an environmentally friendly alternative to conventional lubricants. This article contributes to the field of agricultural technology by demonstrating the potential of SiO₂ nanoparticles in formulations of biolubricants thought to be used in agricultural machines. Key degradation parameters, including density, viscosity, total acid number (TAN), total base number (TBN), oxidation, and elemental composition, were systematically analysed. The results showed that SiO₂ nanoparticles mitigate viscosity loss and density increase, optimize TAN and TBN, reduce oxidation of the biolubricants by up to 17.7% at 1.00 wt% SiO₂, and stabilize elemental composition during ageing. Nanoparticles remained uniformly dispersed without sedimentation for over 30 days. This provides insights that can prevent machinery performance degradation over time, reduce lubricant changes, and suggest a more sustainable and environmentally friendly lubrication solution, thus promoting more sustainable industry. Full article

Joint modulation format identification (MFI) and optical signal-to-noise ratio (OSNR) monitoring constitutes one of the most critical functions integrated in digital coherent receivers, ensuring high flexibility and stability in elastic optical networks (EONs). Since signal amplitude information captures inherent characteristics associated with modulation formats and fluctuations induced by OSNR variations, a simple and effective optical performance monitoring (OPM) scheme based on an amplitude-analytic complex plane is proposed. By employing a multi-task learning algorithm incorporating the multi-order gated aggregation (MOGA) module, the proposed scheme enables simultaneous MFI and OSNR monitoring for polarization division multiplexed (PDM)-QPSK/-16QAM/-32QAM/-64QAM/-128QAM signals. The performance of the proposed scheme is numerically verified in 28 GBaud coherent optical communication systems of various configurations. Numerical simulation results show that 100% identification accuracy is obtainable for all five modulation formats, even at OSNR values lower than the corresponding theoretical 20% forward error correction (FEC) limit. Meanwhile, the mean absolute error (MAE) of OSNR monitoring for QPSK, 16QAM, 32QAM, 64QAM, and 128QAM are 0.16 dB, 0.15 dB, 0.17 dB, 0.28 dB, and 0.33 dB, respectively. Furthermore, simulation results show that the proposed scheme is robust to residual chromatic dispersion (CD) and the nonlinear effects with strong generalization capability. These results suggest that the proposed scheme is promising for applications in next-generation EONs. Full article

Floating rafts are thin, flat mineral layers that precipitate at still air–water interfaces. They are composed of calcite, aragonite, vaterite, gypsum, trona, carnallite, and/or halite. Floating rafts present a flat surface at the top in contact with air, and a rough surface at the bottom, which develops as they grow into the water. In this work, we describe floating rafts from hypersaline environments using imaging and analytical microscopy techniques. The four rafts studied consist of interconnected polycrystalline grains. Scanning electron microscopy (SEM) showed that the top surfaces were flat, whereas in the bottom surfaces, the grains protrude into the water. High magnification revealed nanoparticles arranged in stacks, suggesting growth through the organized agglutination of nanocrystals. Electron diffraction of two of the rafts indicates that they consist of aragonite. Accordingly, electron energy-loss spectroscopy (EELS) shows the C K-edges characteristic of carbonates, along with O and Ca edges. Energy-dispersive spectroscopy (EDS) in the SEM also revealed a few Ca sulfate crystals on the bottom surface. In addition, the presence of cubic shapes indicates the presence of halite. We hypothesize that the genesis of these rafts is driven by evaporation of still water, which increases supersaturation at the very surface, leading to mineral nucleation at the air–water interface, where the activation energy is lower. Full article

This study examines the effect of tool rotational speed on the microstructure and dry sliding wear behavior of brass–tungsten (brass/W) surface composites fabricated through friction stir processing. Microstructural analysis confirmed a uniform distribution of tungsten particles within the stir zone, with no observable clustering. Improved properties were achieved at a lower traverse speed of 40 mm/min combined with a higher rotational speed of 1168 rpm, which promoted finer grain formation (~4 µm) and better particle dispersion. An increase in rotational speed led to a corresponding rise in hardness, from 142 HV at 832 rpm to 165 HV at 1168 rpm. In terms of wear behavior, the sample processed at lower rotational speed exhibited abrasive and micro-cutting wear, whereas the sample processed at higher rotational speed predominantly showed adhesive wear. Full article

In tunnel engineering, the integration of aseismic materials and structural designs has become a prevalent strategy to reduce earthquake-induced damage. However, previous studies on the seismic performance of tunnel structures predominantly employed deterministic methods, overlooking the spatial variability of the surrounding rock mass. This oversight often leads to an overestimation of structural performance, posing potential risks to the project. This study develops a probabilistic framework based on random field theory to evaluate the aseismic performance of tunnel linings incorporating a rubber–sand–concrete (RSC) constrained damping layer. The analysis systematically evaluates the aseismic performance of RSC across varying peak ground acceleration (PGA) levels and tunnel depth conditions. The findings are compared with results from traditional deterministic approaches. The probabilistic analysis indicates the following: (1) a reduction of approximately 70% in the dispersion of maximum principal stresses across various PGAs; (2) a decrease in RSC’s aseismic performance with greater burial depths, though it remains substantial overall, and (3) a reduction in the failure probability from 31.8% to 16.3% at PGA = 1.2 g. Furthermore, deterministic methods tend to produce overly optimistic estimates of tunnel aseismic performance, highlighting the need for probabilistic analysis. Full article

Ultrafast fiber lasers operating near 2 μm have emerged as a critical platform for advancing mid-infrared photonics due to their narrow pulse durations, high peak powers, and broad tunability. These sources exploit the rich energy-level structures of Tm³⁺ and Ho³⁺ doped fibers and reside within an atmospheric transmission window, enabling applications spanning nonlinear microscopy, precision micromachining, optical frequency metrology, biophotonics, and free-space optical communication. Recent progress in low-loss fiber fabrication, dispersion-engineered cavity design, and mode-locking technologies has significantly expanded the performance boundaries of 2 μm ultrafast fiber lasers. This review systematically examines the underlying pulse-formation mechanisms and categorizes state-of-the-art mode-locking approaches. Representative laser architectures are compared with respect to pulse duration, energy scalability, repetition-rate enhancement, spectral characteristics, and environmental stability. Key application pathways in high-resolution spectroscopy, biomedical diagnostics, and mid-IR supercontinuum generation are highlighted. Finally, the remaining challenges and prospective research directions are discussed to inform the development of next-generation ultrafast photonic sources in the 2 μm band. Full article

Printed biosensors have attracted increasing attention as platforms for rapid, low-cost, and portable diagnostics because they can be fabricated on flexible or rigid substrates using scalable printing techniques. Their performance is strongly influenced by both the printing process and the materials employed, since factors such as ink rheology, particle dispersion, interfacial behavior, and post-processing conditions directly affect device architecture, sensing performance, and manufacturing reliability. This review summarizes recent advances in printed biosensors from the combined perspectives of printing technologies and functional materials. Commonly employed printing techniques, including inkjet, screen, aerosol jet, and roll-to-roll gravure printing, are discussed with emphasis on their processing characteristics and material requirements. The review also examines key material platforms used in printed biosensors, including carbon-based nanomaterials, metal oxides, metal nanoparticles, conductive polymers, dielectric materials, and hybrid composites, highlighting their roles in electrical conductivity, catalytic activity, biomolecule immobilization, mechanical flexibility, and overall analytical performance. Finally, current challenges and emerging research directions are outlined with respect to ink stability, post-processing strategies, sensor reliability, manufacturability, and practical translation. Overall, this review emphasizes that the development of high-performance printed biosensors depends on the synergistic integration of rational material design with optimized printing strategies. Full article