Search Results (150)

Ubiquitous digital array radar (UDAR) extends the integration time of moving targets by deploying a wide transmitting beam and multiple narrow receiving beams to cover the entire observed airspace. By exchanging time for energy, it effectively improves the detection ability for weak targets. Nevertheless, target motion introduces severe across-range unit (ARU), across-Doppler unit (ADU), and across-beam unit (ABU) effects, dispersing target energy across the range–Doppler-beam space. This paper proposes a beam domain angle rotation compensation and keystone-matched filtering (BARC-KTMF) algorithm to address the “three-crossing” challenge. This algorithm first corrects ABU by rotating beam–domain coordinates to align scattered energy into the final beam unit, reshaping the signal distribution pattern. Then, the KTMF method is utilized to focus target energy in the time-frequency domain. Furthermore, a special spatial windowing technique is developed to improve computational efficiency through parallel block processing. Simulation results show that the proposed approach achieves an excellent signal-to-noise ratio (SNR) gain over the typical single-beam and multi-beam long-time coherent integration (LTCI) methods under low SNR conditions. Additionally, the presented algorithm also has the capability of coarse estimation for the target incident angle. This work extends the LTCI technique to the beam domain, offering a robust framework for high-speed weak target detection. Full article

Hyperspectral technology has been widely applied to the retrieval of soil properties, such as soil organic matter (SOM) and particle size distribution (PSD). However, most previous studies have focused on hyperspectral data acquired from the nadir direction, and the influence of viewing geometry on hyperspectral-based soil property retrieval remains unclear. In this study, bidirectional reflectance factors (BRFs) were collected at 48 different viewing angles for 154 soil samples with varying SOM contents and PSDs. SOM and PSD were then retrieved using combinations of ten spectral preprocessing methods (raw reflectance, Savitzky–Golay filter (SG), first derivative (D1), second derivative (D2), standard normal variate (SNV), multiplicative scatter correction (MSC), SG + D1, SG + D2, SG + SNV, and SG + MSC), one sensitive wavelength selection method, and three retrieval algorithms (partial least squares regression (PLSR), support vector machine (SVM), and convolutional neural networks (CNNs)). The influence of viewing geometry on the selection of spectral preprocessing methods, retrieval algorithms, sensitive wavelengths, and retrieval accuracy was systematically analyzed. The results showed that soil BRFs are influenced by both soil properties and viewing angles. The viewing geometry had limited effects on the choice of preprocessing method and retrieval algorithm. Among the preprocessing methods, D1, SG + D1, and SG + D2 outperformed the others, while PLSR achieved a higher accuracy than SVM and CNN when retrieving soil properties. The selected sensitive wavelengths for both SOM and PSD varied slightly with viewing angle and were mainly located in the near-infrared region when using BRFs from multiple viewing angles. Compared with single-angle data, multi-angle BRFs significantly improved retrieval performance, with the R² increasing by 11% and 15%, and RMSE decreasing by 16% and 30% for SOM and PSD, respectively. The optimal viewing zenith angle ranged from 10° to 20° for SOM and around 40° for PSD. Additionally, backward viewing directions were more favorable than forward directions, with the optimal viewing azimuth angles being 0° for SOM and 90° for PSD. These findings provide useful insights for improving the accuracy of soil property retrieval using multi-angle hyperspectral observations. Full article

We present lightning-induced ionospheric perturbations in narrowband very-low-frequency (VLF) signals from the transmitters NWC (21.82° S, 114.17° E, 19.8 kHz) and VTX (8.4° N, 77.8° E, 18.6 kHz) recorded at the low-latitude station Dehradun (DDN; 30.3° N, 78.0° E) over a 12-month period from September 2020 to October 2021. Early/slow VLF events, VLF LOREs, and step-like VLF LOREs associated with lightning were analyzed for their onset and recovery times. This study utilized data from the World Wide Lightning Location Network (WWLLN), which provides lightning locations and energy estimates. The results show that early/slow VLF events occur most frequently, accounting for approximately 68% of cases, followed by VLF LOREs at 12%, and step-like VLF LOREs at 10%. Furthermore, we observed that 100% of the VLF perturbing events occurred during the nighttime, which is not entirely consistent with previous studies. Moreover, more than 60% of VLF LOREs were associated with lightning energies of approximately 1 kJ, and about 40% were associated with lightning energies of ~10 kJ. Step-like VLF LOREs were linked to WWLLN energies between 1 and 5 kJ. The observed WWLLN energy range is somewhat lower than the energies reported in previous studies. Scattering characteristics revealed that 87.3% of events were associated with wide-angle scattering, while approximately 12.6% were linked to narrow-angle scattering. LWPC version 2.1 was used to simulate these perturbing events and to estimate the reflection height (H′, in km) and the exponential sharpness factor (β, in km⁻¹) corresponding to changes in D-region electron density. The reflection height (H′, in km) and the exponential sharpness factor (β, in km⁻¹) of the D-region varied from 83 to 87 km and from 0.42 to 0.79 km⁻¹ for early/slow VLF events, from 83 to 85 km and from 0.5 to 0.75 km⁻¹ for step-like VLF LOREs, and from 81 to 83 km and from 0.75 to 0.81 km⁻¹ for VLF LOREs, respectively. Full article

Okara, the soybean residue from soy milk and tofu production, offers significant potential as a sustainable, fiber-rich ingredient for starch-based and gluten-free food systems. This study investigates the comparative effects of whole okara and its extracted dietary fiber (DF) on the retrogradation, rheological properties, and nanostructural organization of rice starch (RS) gels. Rice starch suspensions were blended with 5–20% (dry basis) of either whole okara or DF, thermally gelatinized, and analyzed using dynamic rheology, synchrotron-based Wide-Angle X-ray Scattering (WAXS), and Fourier Transform Infrared (FTIR) spectroscopy. DF markedly reduced the gelation temperature and enhanced storage modulus (G′), indicating earlier and stronger gel network formation. WAXS analysis showed that DF more effectively disrupted long-range molecular ordering, as evidenced by suppressed crystallinity development and disrupted molecular ordering within the A-type lattice. FTIR spectra revealed intensified O–H stretching and new ester carbonyl bands, with progressively higher short-range molecular order (R_1047/1022) in DF-modified gels. While whole okara provided moderate retrogradation resistance and contributed to network cohesiveness via its matrix of fiber, protein, and lipid, DF exhibited superior retrogradation inhibition and gel stiffness due to its purity and stronger fiber–starch interactions. These results highlight the functional divergence of okara-derived ingredients and support their targeted use in formulating stable, fiber-enriched, starch-based foods. Full article

This manuscript delivers a comprehensive evaluation of five different ultra-high-performance concrete (UHPC) shear resistance models: FHWA-HRT-23-077 (2023), ePCI report (2021), French Standard NF-P-18-710 (2016), Canadian Standards A23.3-04 (2004), and Modified Eurocode2/German DAfStb (2023). The models differ in accounting for the steel fiber and shear reinforcement contribution and determining the angle of inclination of the diagonal compression strut. The evaluation was carried out using an experimental database of 198 UHPC specimens and focused on accuracy, conservatism, and ease of use for each considered model. The database included beams with prestressed and steel reinforcement, different shear reinforcement ratios, and a wide range of geometrical and material properties. In order to apply the FHWA method, a utilization tensile stress (f_t,loc) prediction equation was developed. Generally, the FHWA method showed superior performance to the other models in terms of statistical measures and consistent prediction conservatism across variable ranges. Although the ePCI methods yielded the highest conservatism, it can be said that the ePCI, AFGC, and CSA methods showed similar behavior with different degrees of conservatism. The DAfStb method showed the lowest prediction accuracy and the greatest scatter of data. Except for the FHWA method, all methods showed a reduction in conservatism at a high transverse reinforcement ratio. Full article

A Si/SiC/SiO₂ (53/44/3 wt.%) composite is evaluated as an anode material for Li-ion batteries. This material, a result of the high-energy ball-milling of a by-product of the carbothermal reduction of silica (Si slag), is predominantly made up of micrometric particles of amorphous or short-range order Si in which submicrometric SiC inclusions are dispersed. Its capacity is 860 mAh g⁻¹ (1.7 mAh cm⁻²) after 200 cycles in half-cell configuration and 1.6 mAh cm⁻² after 70 cycles in full-cell. The SiC component is not electroactive for lithiation but plays a key role in the electrode stability by preventing the formation of the c-Li₁₅S_i4 phase, known to accelerate electrode degradation. It is shown that capacity decay with cycling mainly originates from solid electrolyte interphase (SEI) growth rather than particle disconnections. Complementary wide angle X-ray scattering (WAXS) analyses confirm the SEI grows alongside cycling and allows for the highlighting of its major components, namely, Li₂CO₃ and LiF. The morphological evolution of the electrode upon cycling is studied by electrochemical dilatometry, operando optical microscopy, and focused ion beam (FIB) and broad ion beam (BIB) scanning electron microscopy (SEM). No particle cracking is observed. However, reconstructed 3D imaging of the electrodes before and after 10 and 200 cycles clearly shows that the particles progressively evolve a dendritic structure. The SEI grows on and within the particles and induces a significant decrease in the electrode’s porosity and an increase in its thickness. Full article

The eco-friendly flame retardancy of polycarbonate (PC) was achieved by blending with phosphorylated-PC in the range of 1–5% w/w. Dynamic properties were characterized using broadband dielectric relaxation spectroscopy (DRS), while structural and thermal properties were investigated using Fourier transform infrared spectroscopy, wide-angle X-ray diffraction, small-angle X-ray scattering, differential scanning calorimetry, and thermogravimetric analysis. A reduction in the single glass transition temperature with increasing phosphorylated-PC content was observed, indicating that the blends were miscible. No crystalline phases were detected in any of the samples. The thermo-oxidative stability and UL-94 ratings of flame-retardant polycarbonates (FRPCs) improved compared to neat PC, with char residue increasing as the phosphorylated-PC content rose. DRS analysis revealed the formation of a well-defined local (β) relaxation in the FRPC samples, originating from the motion of phosphorylated branches. All samples exhibited the segmental (α) relaxation of PC chains above the glass transition temperature. The size of the cooperatively rearranging domain played a significant role in the dynamic fragility of the rigid FRPCs. Additionally, DRS analysis highlighted the presence of physical crosslinks from nanoclusters of phosphorylated polar groups, approximately 14 nm in size. Full article

Thin-walled structures are widely used in aeronautical and aerospace engineering due to their light weight and high structural performance. Ensuring their integrity is crucial for safety and reliability, which is why structural health monitoring (SHM) methods, such as guided wave-based techniques, have been developed to detect and characterize damage in such components. This study presents a novel damage identification procedure for guided wave-based SHM using deep neural networks (DNNs) trained with experimental data. This technique employs the so-called wave damage interaction coefficients (WDICs) as highly sensitive damage features that describe the unique scattering pattern around possible damage. The DNNs learn intricate relationships between damage characteristics, e.g., size or orientation, and corresponding WDIC patterns from only a limited number of damage cases. An experimental training data set is used, where the WDICs of a selected damage type are extracted from measurements using a scanning laser Doppler vibrometer. Surface-bonded artificial damages are selected herein for demonstration purposes. It is demonstrated that smart DNN interpolations can replicate WDIC patterns even when trained on noisy measurement data, and their generalization capabilities allow for precise predictions for damages with arbitrary properties within the range of trained damage characteristics. These WDIC predictions are readily available, i.e., ad hoc, and can be compared to measurement data from an unknown damage for damage characterization. Furthermore, the fully trained DNN allows for predicting WDICs specifically for the sensing angles requested during inspection. Additionally, an anglewise principal component analysis is proposed to efficiently reduce the feature dimensionality on average by more than $90\%$ while accounting for the angular dependencies of the WDICs. The proposed damage identification methodology is investigated under challenging conditions using experimental data from only three sensors of a damage case not contained in the training data sets. Detailed statistical analyses indicate excellent performance and high recognition accuracy for this experimental data-based approach. This study also analyzes differences between simulated and experimental WDIC patterns. Therefore, an existing DNN trained on simulated data is also employed. The differences between the simulations and experiments affect the identification performance, and the resulting limitations of the simulation-based approach are clearly explained. This highlights the potential of the proposed experimental data-based DNN methodology for practical applications of guided wave-based SHM. Full article

Inverse synthetic aperture radar (ISAR) super-resolution imaging technology is widely applied in space target imaging. However, the performance limits of super-resolution imaging algorithms remain largely unexplored. Our work addresses this gap by deriving mathematical expressions for the upper and lower bounds of cross-range resolution in ISAR imaging based on the computational resolution limit (CRL) theory for line spectrum reconstruction. Leveraging these explicit expressions, we first explore influencing factors of these bounds, including the traditional Rayleigh limit, number of scatterers, and peak signal-to-noise ratio (PSNR) of the scatterers. Then, we elucidate the minimum resource requirements in ISAR imaging imposed by CRL theory to meet the desired cross-range resolution, without which studying super-resolution algorithms becomes unnecessary in practice. Furthermore, we analyze the tradeoffs between the cumulative rotation angle, radar transmit energy, and other factors that contribute to optimizing the resolution. Simulations are conducted to demonstrate these tradeoffs across various ISAR imaging scenarios, revealing their high dependence on specific imaging targets. Full article

Soft matter and biological materials are characterized by a complex morphology consisting of multiple structural levels that are either hierarchically organized or coexist over a length scale from a few Å up to the size of µm. For a structural characterization of such morphologies, an extended Q-range must be covered in X-ray and neutron scattering experiments. Neutrons offer the unique advantage of contrast variation and matching by D-labeling, which is of great value for the characterization of hydrocarbon systems, which are essentially the constituents of soft matter and biological materials. The combination of ultra- and small-angle neutron scattering techniques (USANS and SANS) on complementary beamlines has long been used for such experimental investigations. However, the combined use of USANS and SANS methods at the same beamline for simultaneous acquisition of scattering data over a wide Q-range is necessary when working with sensitive or expensive samples that require special preparation or in situ treatment during the structural characterization. For this reason, several pinhole SANS instruments have been equipped with focusing lenses to allow additional measurements at lower Q values, in the USANS range. The use of neutron lenses has the additional advantage of enhancing the intensity on the sample by providing the ability to work with larger samples while maintaining the same resolution as in pinhole mode. The experimental approach for using neutron lenses to enhance the intensity and extend the Q-range to lower values than in pinhole mode is presented using examples from studies on the pinhole SANS diffractometers equipped with focusing lenses. Full article

Background/Objectives: Many commercial light-emitting diode (LED) devices are available for consumer home usage. The performance characteristics in respect to the dosimetry of many of the devices, currently on direct sale to the public, have not been subject to formal appraisal. In order to ‘bridge the gap’ between the evidence-based photobiomodulation therapy (PBMT) community and other interested parties, an evaluation is made of a selection of torch type hand-held LED PBMT products currently available for home use. Methods: Five randomly chosen intra-oral and hand-held LED PBMT devices were selected. The optical delivery parameters of the devices were measured, including the beam divergence angle, surface area exposure as well as the output power at the level of the LEDs. The surface and sub-surface temperature changes in porcine tissue samples were assessed under standardised conditions. The manufacturer’s patient instructions were correlated to the measured optical parameters. Calculations were made of irradiance and surface radiant exposure. Consumer satisfaction ratings and feedback data were collated, and a relevant statistical analysis conducted. Results: The results were heterogeneous with a wide range of applied wavelengths, output power and irradiance. Power output stability was variable, and, together with a wide beam divergence angle of 74°, the manufacturer’s directions for dosimetry were found to be inconsistent with an accurate dose delivery. Conclusions: The manufacturer’s proposed dosimetry fails to consider the relevance of the beam divergence angle and optical attenuation in view of the scatter and absorption. Appropriate instructions on how best to gain and optimise an acceptable clinical outcome were inconsistent with an evidence-based approach. Subject to validation by well-planned clinical trials, the concept of home PBMT may open interesting new therapeutic approaches. Full article

The deformation behavior and instabilities occurring during the drawing of high-density polyethylene (HDPE) were investigated using wide- and small-angle X-ray scattering (WAXS and SAXS) and scanning electron microscopy (SEM) in plain HDPE and paraffin wax- and/or chloroform-modified samples. In contrast to neat HDPE, the modified materials demonstrated strongly suppressed cavitation. However, regardless of cavitation, the tensile deformation of all samples was found to be governed by crystallographic mechanisms active in the crystalline lamellae, supported by shear in the amorphous layers, i.e., the same mechanisms as those operating in other deformation modes. In addition to cavitation, which seems to be a tension-specific phenomenon that does not have a major effect on the deformation sequence, two other important deformation instabilities were observed: microbuckling followed by development of lamellar kinks, at true strain of e = 0.3–0.4, and slip localization instability leading to lamellar fragmentation at e > 0.6. These instabilities were found to be common and very important steps in the deformation sequence, greatly influencing the deformation behavior and occurring in similar strain ranges in both compression and tension, regardless of cavitation. In contrast, cavitation is not able to substitute or significantly modify the main deformation mechanisms, and, furthermore, it does not compete with the main instabilities associated with crystalline lamellae, especially microbuckling; therefore, it may be considered a tension-specific side effect that is not essential for plastic deformation behavior, although it can still significantly affect the final properties and appearance of the drawn material. Full article

The misfolding and amyloid aggregation of proteins have been attracting scientific interest for a few decades, due to their link with several diseases, particularly neurodegenerative diseases. Proteins can assemble and result in insoluble aggregates that, together with intermediate oligomeric species, modify the extracellular environment. Many efforts have been and are devoted to the search for cosolvents and cosolutes able to interfere with amyloid aggregation. In this work, we intensively study the effect of saponins, bioactive compounds, on human insulin aggregation. To monitor the kinetic of amyloid aggregation following secondary structure changes, we perform fluorescence and UV-Visible absorption spectroscopies, using Thioflavin T and Congo Red as amyloid specific probes, and Circular Dichroism. To study the overall structural features and size of aggregates, we perform Synchrotron Small-Angle X-ray Scattering and Dynamic Light Scattering experiments. The morphology of the aggregates was assessed by Atomic Force Microscopy. To deepen the understanding of the saponins interaction with insulin, a Molecular Dynamics investigation is performed, too. The reported data demonstrate that saponins interfere with the amyloid aggregation by inducing a strong inhibition on the formation of insulin fibrils, likely through specific interactions with insulin monomers. A dose-dependent effect is evident, and amyloid inhibition is already clear when saponins are just 0.01% w/w in solution. We suggest that saponins, which are natural metabolites present in a wide range of foods ranging from grains, pulses, and green leaves to sea stars and cucumbers, can be promising metabolites to inhibit human insulin aggregation. This basic research work can pave the way to further investigations concerning insulin amyloidosis, suggesting the use of saponins as amyloid inhibitors and/or stabilizing agents in solution. Full article

We explored the use of biomimetic structures, including those that mimic leaf structures, to enhance the angular color uniformity of flat phosphor-converted light-emitting diodes (pcLEDs). The distinct microstructures found on natural leaf surfaces, such as micro-scale bumps, ridges, and hierarchical patterns, have inspired the design of artificial microstructures that can improve light extraction, scattering, and overall optical performance in LED applications. The effects of these leaf surface microstructures on the phosphor layer of flat pcLEDs were evaluated. An imprinting technique was employed to directly replicate the surface morphology structures from fresh plant leaves. The results indicated that this method provided excellent scattering capability and reduced the disparity in light output between blue and yellow light emissions from flat pcLEDs at various angles. Subsequently, uniform correlated color temperature in the flat pcLEDs was achieved, reducing the yellow ring effect. Furthermore, the availability of diverse wrinkle and surface patterns from a wide range of natural prototypes could reduce design costs compared with traditional mold fabrication, making the method suitable for application in mass production. Full article

Laser based-powder bed fusion (LB-PBF) enables fast, efficient, and cost-effective production of high-performing products. While advanced functionalities are often derived from geometric complexity, the capability to tailor material properties also offers significant opportunities for technical innovation across many fields. This study explores the optimization of the LB-PBF process parameters for producing Ti6Al4V titanium alloy parts with controlled porosity. To this end, cuboid and lamellar samples were fabricated by systematically varying laser power, hatch distance, and layer thickness according to a full factorial Design of Experiments, and the resulting specimens were thoroughly characterized by analyzing envelope porosity, surface roughness and waviness, surface morphology, and surface area. A selection of specimens was further examined using small-angle X-ray scattering (SAXS) and wide-angle X-ray scattering (WAXS) to investigate the atomic structure and nanometric porosity of the material. The results demonstrated the possibility to finely control the porosity and surface characteristics of Ti6Al4V within specific LB-PBF process ranges. The pores were found to be mostly closed even for thin walls, while the surface roughness was recognized as the primary factor impacting the surface area. The lamellar samples obtained by exposing single scan tracks showed nearly an order-of-magnitude increase in both surface area and pore volume, thereby laying the groundwork for the production of parts with optimized porosity. Full article