Search Results (215)

Recently, the development of autonomous vehicles (AVs) and intelligent driver assistance systems has drawn significant attention from the public. Despite these advancements, AVs may encounter critical situations in real-world scenarios that can lead to severe traffic accidents. This review paper investigated these critical scenarios, categorizing them under weather conditions, environmental factors, and infrastructure challenges. Factors such as attenuation and scattering severely influence the performance of sensors and AVs, which can be affected by rain, snow, fog, and sandstorms. GPS and sensor signals can be disturbed in urban canyons and forested regions, which pose vehicle localization and navigation problems. Both roadway infrastructure issues, like inadequate signage and poor road conditions, are major challenges to AV sensors and navigation systems. This paper presented a survey of existing technologies and methods that can be used to overcome these challenges, evaluating their effectiveness, and reviewing current research to improve AVs’ robustness and dependability under such critical situations. This systematic review compares the current state of sensor technologies, fusion techniques, and adaptive algorithms to highlight advances and identify continuing challenges for the field. The method involved categorizing sensor robustness, infrastructure adaptation, and algorithmic improvement progress. The results show promise for advancements in dynamic infrastructure and V2I systems but pose challenges to overcoming sensor failures in extreme weather and on non-maintained roads. Such results highlight the need for interdisciplinary collaboration and real-world validation. Moreover, the review presents future research lines to improve how AVs overcome environmental and infrastructural adversities. This review concludes with actionable recommendations for upgrading physical and digital infrastructures, adaptive sensors, and algorithmic upgrades. Such research is important for AV technology to remain in the zone of advancement and stability. Full article

In order to investigate the bubble dynamics and thermal effects of stable cavitation under different acoustic fields, this study computes and analyzes a series of DNS (Direct Numerical Simulation) approaches with the VOF (Volume of Fluid) method. The analysis focuses on bubble clusters with a radius of 1.5 μm and a void ratio of ${10}^{-6}$, commonly encountered in ultrasound therapy. Firstly, the results show that the thermal effects of bubble cavitation are non-linearly positively correlated with the ultrasound amplitude and the volume changes of the bubbles. Meanwhile, acoustic scattering caused by ultrasound passing through the bubbles leads to acoustic pressure focusing, intensifying cavitation. Secondly, the thermal effect is most evident at an acoustic frequency of 250 kHz. When the ultrasound input frequency is higher than 250 kHz, acoustic attenuation occurs, while at frequencies lower than 250 kHz, the efficiency of bubbles’ energy absorption reduces. Finally, when the acoustic pressure amplitude on the bubble surface is above 210 kPa, the thermal effect of cavitation is significantly enhanced. However, the temperature rise in the flow domain gradually slows with time and eventually reaches a fixed rate. To sum up, to optimize and control the thermal effects of ultrasound therapy, the ultrasound frequency and amplitude must be carefully selected based on the targeted bubble cluster. Full article

The aim of this study was to develop a novel functional ingredient—goat’s skim milk enriched with Agrocybe aegerita (V. Brig.) Vizzini mushroom extract (ME/M)—using Central Composite Design (CCD). The optimized ME/M ingredient was evaluated for its physico-chemical, techno-functional, biological, and antimicrobial properties. Physico-chemical properties were analyzed using Attenuated Total Reflectance Fourier Transform Infrared (ATR-FTIR) spectroscopy, Scanning Electron Microscopy (SEM), and Dynamic Light Scattering (DLS). The ingredient exhibited a polymodal particle size distribution and contained glucans, along with a newly formed polypeptide resulting from the selective cleavage of goat milk proteins. A 0.1% ME/M solution demonstrated good emulsifying and foaming properties. Additionally, ME/M showed strong antiproliferative effects on human cancer cell lines, particularly Caco-2 (colorectal) and MCF7 (breast) cancer cells. The ingredient also promoted HaCaT cell growth without cytotoxic effects, suggesting its safety and potential wound-healing properties. Furthermore, the addition of ME/M to HaCaT cells inoculated with Staphylococcus aureus resulted in reduced IL-6 levels compared to the control (without ME/M), indicating a dose-dependent anti-inflammatory effect. The optimized ME/M ingredient also exhibited antibacterial, antifungal, anticandidal, and antibiofilm activity in one-fourth of MIC. These findings suggest that the formulated ME/M ingredient has strong potential for use in the development of functional foods offering both desirable techno-functional properties and bioactive benefits. Full article

In metabolically engineered plants, the target products are usually uniformly distributed in the whole plant or specific tissues. When engineering tobacco to produce astaxanthin, a ketocarotenoid with strong antioxidant activity and multiple bioactivities, a scattered distribution of astaxanthin-producing regions was observed in a small portion of astaxanthin-producing tobacco plants, which caused mosaic-like red and green spots on the leaves (ASTA-mosaic). A physiological assay showed that the non-astaxanthin green region (Mosaic_G) had relatively higher chlorophyll content and better chloroplast structure than the astaxanthin-producing red region (Mosaic_R). Then, metabolomics, proteomics, and small RNA transcriptomics were employed to analyze the uneven distribution of astaxanthin-producing regions in tobacco leaves. The results of metabolomics and proteomics revealed a decrease in carotenoid metabolism, chlorophyll biosynthesis, and chlorophyll degradation in the Mosaic_G region. Pheophorbide a, an intermediate of chlorophyll degradation, was found to be significantly reduced in the Mosaic_G region, which was accompanied by the attenuation of chlorophyllase and pheophytinase, which catalyze the formation of pheophorbide a in chlorophyll degradation. Reductions in photosynthetic antenna proteins and photosystem-associated proteins were observed in the Mosaic_R region, consistent with the better chloroplast structure of the Mosaic_G region. Small RNA transcriptomics showed that several small RNAs could target chlorophyll-degradative genes, but they were more effective in targeting the astaxanthin biosynthetic genes. This finding was supported by the fact that the Mosaic_G region can remain green up to the senescence of tobacco leaves. This work provides insights into the mechanism of the uneven distribution of astaxanthin-producing regions in tobacco leaves and may contribute to the specialized utilization of tobacco plants for metabolic engineering. Full article

Honey has been recognised for centuries for its potential therapeutic properties, and its application in wound healing has gained attention due to its antimicrobial, anti-inflammatory, and regenerative properties. With the rapid increase in multidrug resistance, there is a need for new or alternative approaches to traditional antibiotics. This paper focuses on the physicochemical changes that occur when formulating honey into Pluronic F127 hydrogels. The manual incorporation of honey, irrespective of quality type, presented the amelioration of Pluronic’s capacity to undergo sol–gel transitions, as investigated by parallel plate rheology. This novel finding was attributed to the formation of fractal aggregates via the hydrogen-bonding-induced irreversible aggregation of honey–PF127 micelles, which subsequently dominate the entire hydrogel system to form a gel. The hydrogen bonding of micelles was identified through Attenuated Total Reflectance Fourier-Transform Infrared Spectroscopy (ATR-FTIR), Differential Scanning Calorimetry (DSC), and Dynamic Light Scattering (DLS). This is the first known study to provide physicochemical insight into the effects that honey incorporation has on the thermogelation capacity of Pluronic F127 hydrogels for downstream dermal wound applications. Full article

The marine environment is complex and variable, with the absorption and scattering effects of seawater and turbulence causing significant attenuation of received optical signals and introducing random jitter, which limits the communication range and stability of underwater wireless optical communication systems. This paper presents the Superposition UEP-Spinal Code structure, which utilizes unequal error protection (UEP) to adjust the transmission performance of different types of information in underwater composite data communication by adjusting the superposition weighting factors in the encoding algorithm. This encoding method enhances the noise immunity of important data, and with the same bandwidth utilization, the overall decoding complexity is reduced by 13.3% compared to the previously improved Spinal code encoding algorithm. The results show that the Superposition UEP-Spinal Code provides a more stable, reliable, and efficient communication solution for underwater wireless optical communication systems with randomly varying channel conditions. Full article

(1) Background: Over 90% of hop crops are currently used in beer production, with a small part used in the cosmetics and pharmaceutical industries. Spent hops as a waste product contain one of the strongest antioxidants, xanthohumol. The aim of the study was to purify spent hop extracts by magnetic dispersive extraction using iron oxide nanoparticles (IONP) to obtain pure xanthohumol; (2) Methods: The extract from the waste product obtained after supercritical carbon dioxide extraction of hops was prepared by ultrasound-assisted extraction utilizing different solvents, i.e., ethyl acetate, propanol, acetone, 80% methanol, ethyl acetate-methanol (1:1, v/v), and propanol-methanol (1:1, v/v). The hydrodynamic diameters and zeta potential of IONPs before and after incubation were measured by dynamic light scattering (DLS). The extracts were analyzed by reversed-phase high-performance liquid chromatography (HPLC). Isolated xanthohumol was identified based on the DAD spectrum in the range of 200–600 nm and by Fourier transform infrared spectroscopy/attenuated total reflectance (FT-IR/ATR); The antioxidant activity of extracts before and after incubation with IONPs was assessed using SNPAC (Silver Nanoparticle Antioxidant Capacity), DPPH (2,2-diphenyl-1-picrylhydrazyl radical), and FRAP (Ferric Reducing Antioxidant Power) assays, as well as total phenolic content (TPC) and total flavonoid content (TFC). (3) Results: The amount of added IONPs, the kind of solvent, and the contact time of the extract with nanoparticles were optimized. We found that 80% MeOH extract after incubation with IONPs (865 µg IONPs/g of spent hops) at room temperature for 48 h contains 74.61% of initial xanthohumol content, providing a final xanthohumol concentration of 43 µg mL⁻¹. (4) Conclusions: The proposed method of magnetic dispersive extraction using IONPs allows for the purification of spent hops extract and obtaining a pure product, namely xanthohumol, with a wide potential for practical applications in medicine, pharmacy, cosmetics, and agriculture. This is clear evidence of the usefulness of IONP as an effective sorbent. The method allows the use of residues from the brewing industry, i.e., the biomass of used hop cones to obtain a valuable substance. Full article

Gamma radiation shielding is necessary for many applications; nevertheless, lead creates environmental risks. Eumelanin, a natural polymer, is a viable alternative, although its effectiveness is limited to lower gamma-ray energy. This research looks at how doping the herbal eumelanin polymer (Nigella sativa) with heavy metals including iron (Fe), copper (Cu), and zinc (Zn) affects its gamma radiation shielding characteristics. The inclusion of these metals considerably increases the linear attenuation coefficient (μ) and mass attenuation coefficient (μ_m) of eumelanin, especially at lower photon energies where the photoelectric effect is prominent. The μ value of pure eumelanin is 0.193 cm⁻¹ at 59.5 keV. It goes up to 0.309 cm⁻¹, 0.420 cm⁻¹, and 0.393 cm⁻¹ when Fe, Cu, and Zn are added, in that order. Similarly, the mass attenuation coefficients increase from 0.153 cm²/g for pure eumelanin to 0.230, 0.316, and 0.302 cm²/g for the Fe-, Cu-, and Zn-doped samples. At intermediate and higher energies (661.7 keV-to-1332.5 keV), where Compton scattering is the main interaction, differences in attenuation coefficients between samples are not as noticeable, which means that metal additions have less of an effect. The mean free path (MFP) and radiation protection efficiency (RPE) also show these behaviors. For example, at 59.5 keV the MFP drops from 5.172 cm for pure eumelanin to 3.244 cm for Mel-Fe, 2.385 cm for Mel-Cu, and 2.540 cm for Mel-Zn. RPE values also go up a lot at low energies. For example, at 59.5 keV Cu-doped eumelanin has the highest RPE of 34.251%, while pure eumelanin only has an RPE of 17.581%. However, at higher energies the RPE values for all samples converge, suggesting a more consistent performance. These findings suggest that doping eumelanin with Fe, Cu, and Zn is particularly effective for enhancing gamma-ray shielding at low energies, with copper (Cu) providing the most significant improvement overall, making these composites suitable for applications requiring enhanced radiation protection at lower gamma-ray energies. Full article

This paper theoretically and experimentally studies the effect of underwater waveguide interface scattering on the nonlinear sound field characteristics of parametric array (PA) radiation. Based on the image source method, the components of the sound field in the waveguide are first analyzed. Then, a non-paraxial model is developed to account for the influence of interface scattering. This model enables accurate calculation of the wide-angle sound field. The impact of the sound source depth and the interface reflection coefficient on the distribution of the difference-frequency wave (DFW) sound field in the waveguide is studied. The interface alters the phase distribution of the DFW’s virtual source density function, thereby affecting the sound field accumulation process. Waveguide interfaces with different absorption coefficients influence the amplitude oscillation caused by interface reflection and change the sidelobe size of the DFW beam. The DFW sound field distribution is measured at three typical frequencies. Simulation and experimental results show that the attenuation of the DFW’s axial sound pressure level in the waveguide oscillates, and the DFW’s beamwidth gradually widens as the frequency decreases. The calculated results from the proposed model agree well with the measured data, with average errors along the sound axis and depth being less than 3 dB and 6 dB, respectively. This demonstrates the model’s superior applicability compared to the existing free-field model. Full article

The propagation of interface acoustic waves (IAWs) in 128° YX-LiNbO₃/SU-8/overcoat structures was theoretically studied and experimentally investigated for different types of overcoat materials and thicknesses of the SU-8 adhesive layer. Three-dimensional finite element method analysis was performed using Comsol Multiphysics software to design an optimized multilayer configuration able to achieve an efficient guiding effect of the IAW at the LiNbO₃/overcoat interface. Numerical analysis results showed the following: (i) an overcoat faster than the piezoelectric half-space ensures that the wave propagation is confined mainly close to the surface of the LiNbO₃, although with minimal scattering in the overcoat; (ii) the presence of the SU-8, in addition to performing the essential function of an adhesive layer, can also promote the trapping of the acoustic energy toward the surface of the piezoelectric substrate; and (iii) the electromechanical coupling efficiency of the IAW is very close to that of the surface acoustic wave (SAW) along the bare LiNbO₃ half-space. The numerical predictions were experimentally assessed for some SU-8 layer thicknesses and overcoat material types. The propagation of the IAWs was experimentally measured in LiNbO₃/SU-8/fused silica, LiNbO₃/SU-8/(001)Si, and LiNbO₃/SU-8/c-Al₂O₃ structures for an SU-8 layer about 15 µm thick; the velocities of the IAWs were found in good agreement with the theoretically calculated values. Although the interest in IAWs was born many years ago for packageless applications, it can currently be renewed if thought for applications in microfluidics. Indeed, the IAWs may represent a valid alternative to standing SAWs, which are strongly attenuated when travelling beneath the walls of polydimethylsiloxane (PDMS) microfluidic channels for continuous flow particle manipulation, provided that the channel is excavated into the overcoating. Full article

Light scattering and attenuation in water degrade underwater images with low visibility and color distortion, which often interfere with the high-level visual tasks of underwater autonomous robots. Most existing deep learning methods for underwater image enhancement only supervise the final output of network and ignore the promotion effect of the intermediate results on the final feature representation. These supervision methods affect the feature representation ability, network efficiency, and ability. In this paper, we present a novel idea of multiple-stage supervision to guide the network to learn useful features correctly and progressively. With this idea, we propose a pixel-wise Progressive Guided Network (PGN) for underwater image enhancement to take advantage of the network’s intermediate results and promote the final enhancement effect. The Pixel-Wise Attention Module is designed by introducing supervision in each stage to progressively promote the representation ability of the features and the recovered image quality. The experimental results on several datasets demonstrate that our method outperforms recent state-of-the-art underwater image enhancement methods. Full article

Curcumae Longae Rhizoma (CLRh), Curcumae Radix (CRa), and Curcumae Rhizoma (CRh), derived from the different medicinal parts of the Curcuma species, are blood-activating analgesics commonly used for promoting blood circulation and relieving pain. Due to their certain similarities in chemical composition and pharmacological effects, these three herbs exhibit a high risk associated with mixing and indiscriminate use. The diverse methods used for distinguishing the medicinal origins are complex, time-consuming, and limited to intraspecific differentiation, which are not suitable for rapid and systematic identification. We developed a rapid analysis method for identification of affinis and different medicinal materials using attenuated total reflection-Fourier-transform infrared spectroscopy (ATR-FTIR) combined with machine learning algorithms. The original spectroscopic data were pretreated using derivatives, standard normal variate (SNV), multiplicative scatter correction (MSC), and smoothing (S) methods. Among them, 1D + MSC + 13S emerged as the best pretreatment method. Then, t-distributed stochastic neighbor embedding (t-SNE) was applied to visualize the results, and seven kinds of classification models were constructed. The results showed that support vector machine (SVM) modeling was superior to other models and the accuracy of validation and prediction was preferable, with a modeling time of 127.76 s. The established method could be employed to rapidly and effectively distinguish the different origins and parts of Curcuma species and thus provides a technique for rapid quality evaluation of affinis species. Full article

Quantum dots (QDs) have emerged as promising tools in advancing multiphoton microscopy (MPM) for deep brain imaging, addressing long-standing challenges in resolution, penetration depth, and light–tissue interactions. MPM, which relies on nonlinear photon absorption, enables fluorescence imaging within defined volumes, effectively reducing background noise and photobleaching. However, achieving greater depths remains limited by light scattering and absorption, compounded by the need for balanced laser power to avoid tissue damage. QDs, nanoscale semiconductor particles with unique optical properties, offer substantial advantages over traditional fluorophores, including high quantum yields, large absorption cross-sections, superior photostability, and tunable emission spectra. These properties enhance signal to background ratio at increased depths and reduce scattering effects, making QDs ideal for imaging subcortical regions like the hippocampus without extensive microscope modifications. Studies have demonstrated the capability of QDs to achieve imaging depths up to 2100 μm, far exceeding that of conventional fluorophores. Beyond structural imaging, QDs facilitate functional imaging applications, such as high-resolution tracking of hemodynamic responses and neural activity, supporting investigations of neuronal dynamics and blood flow in vivo. Their stability enables long-term, targeted drug delivery and photodynamic therapy, presenting potential therapeutic applications in treating brain tumors, Alzheimer’s disease, and traumatic brain injury. This review highlights the impact of QDs on MPM, their effectiveness in overcoming light attenuation in deep tissue, and their expanding role in diagnosing and treating neurological disorders, positioning them as transformative agents for both brain imaging and intervention. Full article

The fractional Brownian field is often used to reproduce the fractal properties of complex heterogeneous media, which closely represent real-world geological materials. Studying elastic wave transport in this type of heterogeneous media is essential for advancing knowledge in geophysics, seismology, and rock mechanics. In this paper, we numerically investigate the wavefield evolution and arrival behavior of elastic wave propagation in a two-dimensional fractional Brownian field characterized by the standard deviation (σ) and the Hurst exponent (H). Using a high-fidelity finite element model, we quantify the influence of these parameters on wavefront morphology, wave arrival synchronization, and energy decay. Our results reveal that increased matrix heterogeneity with higher σ and lower H values leads to pronounced wavefront roughness, asynchronous arrival phenomena, and increscent energy decay, attributed to enhanced scattering and modulus variability. For smaller H values, rougher modulus distributions scatter wave energy more intensely, producing more coda waves and distorted wavefronts, while smoother fields with larger H fields promote smoother wave propagation. Higher σ amplifies these effects by increasing modulus variability, resulting in more attenuated wave energy and substantial wavefield disturbance. This study contributes to a quantitative understanding of how fractal heterogeneity modulates wave transport and energy attenuation in random media. Our findings hold practical significance for geophysical exploration and seismic tomography, as well as aiding in subsurface imaging and structural evaluation within fractured or stratified rock formations. Full article

This study investigates the application of Phased Array Corrosion Mapping (PACM) as a non-destructive testing (NDT) method for detecting and monitoring corrosion growth on hot stainless steel (SS) surfaces, specifically focusing on SS 304 and SS 316. Conducted across a temperature range of 30 °C to 250 °C, the research evaluates the effectiveness of PACM in high-temperature environments typical of the petrochemical industry. Experiments were conducted using specimens with machined slots and flat-bottom holes (FBHs) to simulate corrosion defects. The results demonstrate that PACM effectively detects and maps corrosion indicators, with color-coded C-scan data facilitating easy interpretation. Temperature variations significantly influenced ultrasound signal characteristics, leading to observable changes in FBH indications, particularly at elevated temperatures. Increased ultrasound attenuation necessitated adjustments in decibel settings to maintain accuracy. SS 304 and SS 316 exhibited distinct responses to temperature changes, with SS 316 showing higher dB values and unique signal behaviors, including increased scattering and noise echoes at elevated temperatures. Detected depths for slots and FBHs correlated closely with designed depths, with deviations generally less than 0.5 mm; however, some instances showed deviations exceeding 2 mm, underscoring the need for careful interpretation. At temperatures above 230 °C, the disbanding of probe elements led to weak or absent signals, complicating data interpretation and requiring adjustments in testing protocols. This study highlights the feasibility and effectiveness of PACM for corrosion detection on hot SS surfaces, providing critical insights into material behavior under thermal conditions. Future research should include physical examination of samples using Scanning Electron Microscopy (SEM) to validate and enhance the reliability of the findings. The integration of non-contact NDT methods and optimization of calibration techniques are essential for improving PACM performance at elevated temperatures. Full article