Search Results (1,280)

Recent major advancements in cryo-electron microscopy (cryo-EM) have enabled high-resolution structural analysis, accompanied by developments in image processing software packages for single-particle analysis (SPA). SPA facilitates the 3D reconstruction of proteins and macromolecular complexes from numerous individual particles. In this study, we systematically evaluated the impact of symmetry parameters and particle quantity on the 3D reconstruction efficiency using the dihydrolipoyl acetyltransferase (E2) inner core of the pyruvate dehydrogenase complex (PDC). We specifically examined how inappropriate symmetry constraints can introduce structural artifacts and distortions, underscoring the necessity for accurate symmetry determination through rigorous validation methods such as directional Fourier shell correlation (FSC) and local-resolution mapping. Additionally, our analysis demonstrates that efficient reconstructions can be achieved with a moderate particle number, significantly reducing computational costs without compromising structural accuracy. We further contextualize these results by discussing recent developments in SPA workflows and hardware optimization, highlighting their roles in enhancing reconstruction accuracy and computational efficiency. Overall, our comprehensive benchmarking provides strategic insights that will facilitate the optimization of SPA experiments, particularly in resource-limited settings, and offers practical guidelines for accurately determining symmetry and particle quantity during cryo-EM data processing. Full article

Acoustic emission (AE) technology has been extensively applied in the damage assessment of steel strands; however, it remains inadequate in identifying and quantifying the number of strand fractures, which limits the accuracy and reliability of prestressed structure monitoring. In this study, a test platform based on practical engineering was built. The AE monitoring method using a waveguide rod was applied to identify signals from different numbers of strand fractures, and their acoustic characteristics were analyzed using Fourier transform and multi-bandwidth wavelet transform. The propagation attenuation behavior of the AE signals in the waveguide rod was then analyzed, and the optimal parameters for field monitoring as well as the maximum number of plates suitable for series beam plates were determined. The results show that AE signals decrease exponentially with an increasing propagation distance, and attenuation models for various AE parameters were established. As the number of strand fractures increases, the amplitude of the dominant frequency increases significantly, and the energy distribution shifts towards higher-frequency bands. This finding introduces a novel approach for quantifying fractures in steel strands, enhancing the effectiveness of AE technology in monitoring and laying a foundation for the development of related technologies. Full article

Currently, quantum steganography schemes utilizing the least significant bit (LSB) approach are primarily optimized for fixed-point data processing, yet they encounter precision limitations when handling extended floating-point data structures owing to quantization error accumulation. To overcome precision constraints in quantum data hiding, the EPlsb-MFQS and MVlsb-MFQS quantum steganography algorithms are constructed based on the LSB approach in this study. The multichannel floating-point quantum representation of digital signals (MFQS) model enhances information hiding by augmenting the number of available channels, thereby increasing the embedding capacity of the LSB approach. Firstly, we analyze the limitations of fixed-point signals steganography schemes and propose the conventional quantum steganography scheme based on the LSB approach for the MFQS model, achieving enhanced embedding capacity. Moreover, the enhanced embedding efficiency of the EPlsb-MFQS algorithm primarily stems from the superposition probability adjustment of the LSB approach. Then, to prevent an unauthorized person easily extracting secret messages, we utilize channel qubits and position qubits as novel carriers during quantum message encoding. The secret message is encoded into the signal’s qubits of the transmission using a particular modulo value rather than through sequential embedding, thereby enhancing the security and reducing the time complexity in the MVlsb-MFQS algorithm. However, this algorithm in the spatial domain has low robustness and security. Therefore, an improved method of transferring the steganographic process to the quantum Fourier transformed domain to further enhance security is also proposed. This scheme establishes the essential building blocks for quantum signal processing, paving the way for advanced quantum algorithms. Compared with available quantum steganography schemes, the proposed steganography schemes achieve significant improvements in embedding efficiency and security. Finally, we theoretically delineate, in detail, the quantum circuit design and operation process. Full article

This paper presents the assessment of the possibility of ammonia adsorption on biochars from banana peels, chemically activated with potassium hydroxide (KOH) at different temperatures. The obtained materials were characterized in detail using a number of analytical techniques, including nitrogen adsorption (BET), scanning electron microscopy (SEM), elemental analysis (CHNS), thermal analysis (TG, DTG, DTA), Fourier transform infrared spectroscopy (ATR-FTIR), Raman spectroscopy, Boehm titration method and biochar surface pH. They revealed a largely developed microporous structure and a large specific surface area, ranging from 1134 to 2332 m² g⁻¹. The adsorption tests against ammonia in the gas phase showed a large adsorption capacity of the materials, up to 5.94 mmol g⁻¹ at 0 °C and 3.83 mmol g⁻¹ at 20 °C. The adsorption properties of the obtained biochars were confirmed to be significantly influenced by the surface chemistry (presence of the acidic functional groups). The research results indicate that the waste-based biomass, such as banana peels, can be an ecological and economical raw material for the production of highly effective adsorbents, useful in the removal of ammonia and other toxic gases polluting the environment. Full article

In this study, polysulfone-based nanocomposites with carbon black (CB) nanoparticles were fabricated to evaluate their urea-removal properties. The nanocomposites were obtained using two different methods: solution mixing and melt extrusion. These materials were evaluated using Fourier transform infrared spectroscopy (FTIR), which allowed for the identification of the corresponding functional groups within the polysulfone polymer matrix. X-ray diffraction (XRD) analysis was performed, confirming the amorphous structure of the polysulfone. The addition of modified carbon black shifted the most intense peak of the polysulfone. Thermogravimetric analysis (TGA) showed an increase in thermal stability with the addition of different concentrations of modified carbon black for solution-mixing method. Scanning electron microscopy (SEM) revealed that the melt-extrusion method presented a better dispersion of the nanoparticles, since large agglomerates were not observed. Additionally, a urea adsorption study was conducted, obtaining removal percentages of 76% and 72% for the extrusion and solution-mixing methods, respectively. It was demonstrated that the nanocomposite can be used for up to five cycles without losing urea-removal efficiency, whereas the efficiency of pure polysulfone decreases as the number of cycles increases. Finally, the hemolysis test was performed, and the nanocomposites showed less than 1% hemolysis, indicating that the material is non-hemolytic. Full article

Energy generation from renewable sources has increased exponentially worldwide, particularly wind energy, which is converted into electricity through wind turbines. The growing demand for renewable energy has driven the development of horizontal-axis wind turbines with larger dimensions, as the energy captured is proportional to the area swept by the rotor blades. In this context, the dynamic loads typically observed in wind turbine towers include vibrations caused by rotating blades at the top of the tower, wind pressure, and earthquakes (less common). In offshore wind farms, wind turbine towers are also subjected to dynamic loads from waves and ocean currents. Vortex-induced vibration can be an undesirable phenomenon, as it may lead to significant adverse effects on wind turbine structures. This study presents a two-dimensional transient model for a rigid body anchored by a torsional spring subjected to a constant velocity flow. We applied a coupling of the Fourier pseudospectral method (FPM) and immersed boundary method (IBM), referred to in this study as IMERSPEC, for a two-dimensional, incompressible, and isothermal flow with constant properties—the FPM to solve the Navier–Stokes equations, and IBM to represent the geometries. Computational simulations, solved at an aspect ratio of $\varphi =4.0$, were analyzed, considering Reynolds numbers ranging from $Re=150$ to Re = 1000 when the cylinder is stationary, and $Re=250$ when the cylinder is in motion. In addition to evaluating vortex shedding and Strouhal number, the study focuses on the characterization of space–time symmetry during the galloping response. The results show a spatial symmetry breaking in the flow patterns, while the oscillatory motion of the rigid body preserves temporal symmetry. The numerical accuracy suggested that the IMERSPEC methodology can effectively solve complex problems. Moreover, the proposed IMERSPEC approach demonstrates notable advantages over conventional techniques, particularly in terms of spectral accuracy, low numerical diffusion, and ease of implementation for moving boundaries. These features make the model especially efficient and suitable for capturing intricate fluid–structure interactions, offering a promising tool for analyzing wind turbine dynamics and other similar systems. Full article

Bothus podas (wide-eyed flounder) is a benthic flatfish likely exposed to microplastic (MP) pollution. We investigated MP ingestion and associated physiological effects in wild B. podas collected from Mallorca (Balearic Islands), Spain. Markers of oxidative stress, detoxification, and immunity were quantified in intestinal, hepatic, and splenic tissues. MPs were observed in the gastrointestinal tracts of 87.5% of the 24 specimens analyzed, with an average of 3.8 ± 0.6 items per fish. Fiber-type MPs predominated in both the gastrointestinal tract (69.6%) and sediment samples (97%). Additionally, micro-Fourier transform infrared spectroscopy analysis confirmed that the majority of ingested MPs were composed of polyethylene, polypropylene, and polyester. Fish were categorized into low (<3 items) and high (≥3 items) MP groups based on the median number of plastic items found in the gastrointestinal tract to assess sublethal impacts. In the gut, high-MP fish exhibited significantly elevated activities of detoxification enzymes: ethoxyresorufin-O-deethylase (phase I) and glutathione s-transferase (phase II), along with increased antioxidant enzyme superoxide dismutase and inflammatory myeloperoxidase. Gut catalase and malondialdehyde (MDA) were not significantly different between groups. In liver tissues, no biomarkers differed significantly with MP exposure. In the spleen, lysozyme and alkaline phosphatase activities were significantly higher in high-MP fish, while splenic MDA remained unchanged. These results indicate that gastrointestinal MP exposure triggers local oxidative stress responses and systemic immune activation in B. podas. Overall, ingestion of environmentally relevant MP levels elicited detoxification and inflammatory responses without significant increases in MDA, an indicator of oxidative damage, highlighting the physiological stress imposed by plastic pollution on benthic fish. Full article

A quantitative characterization of the change in coal molecular structures with different cyclical microwave modification parameters and a better understanding of the reaction mechanism of the modification are of great significance for the commercial extraction of coal bed methane (CBM). Therefore, long-flame coal samples obtained from the Ordos Basin, China, were modified by microwave radiation with different times, and the long-flame coal molecular structure parameters were determined by solid-state ¹³C nuclear magnetic resonance (ss¹³C NMR), Fourier transform infrared (FTIR) spectrometry, and X-ray photoelectron spectrometry (XPS). Atomistic representations of the raw long-flame coal molecular model and modified long-flame coal molecular models were established. The temperature rise, pore volume increase, mineral removal, and functional group changes after the modification have a negative effect on methane adsorption. After the modification, the decrease in surface area of the micropores reduced the adsorption site of methane in coal. As a result, the methane adsorption amount decreased linearly with the decreasing surface area. The CH₄ adsorption isotherms of the long-flame models were dynamically simulated and analyzed. The results of this study can prove that after multiple cycles of microwave modifications, the functional groups in long-flame coal were fractured, and the number of micropores was reduced, which effectively decreased the methane adsorption performance in long-flame coal seams, thereby promoting methane extraction. Microwave modification is a promising method for enhancing CBM recovery. Full article

Laser-induced periodic surface structures (LIPSSs) produced via ultrafast laser-induced oxidation offer a promising route for high-quality nanostructuring, with reduced thermal damage compared to conventional ablation-based methods. However, the influence of laser repetition frequency on the formation and morphology of oxidized LIPSSs remains insufficiently explored. In this study, we systematically investigate the effects of varying the femtosecond laser repetition frequency from 1 kHz to 100 kHz while keeping the total pulse number constant on the oxidation-induced LIPSSs formed on amorphous silicon films. Scanning electron microscopy and Fourier analysis reveal a transition between two morphological regimes with increasing repetition frequency: at low frequencies, the long inter-pulse intervals result in irregular, disordered oxidation patterns; at high frequencies, closely spaced pulses promote the formation of highly ordered, periodic surface structures. Statistical measurements show that the laser-modified area decreases with frequency, while the LIPSS period remains relatively stable and the ridge width exhibits a peak at 10 kHz. Finite-difference time-domain (FDTD) and finite-element simulations suggest that the observed patterns result from a dynamic balance between light-field modulation and oxidation kinetics, rather than thermal accumulation. These findings advance the understanding of oxidation-driven LIPSS formation dynamics and provide guidance for optimizing femtosecond laser parameters for precise surface nanopatterning. Full article

Nowadays, biomass use has increased due to it being the most abundant raw material on the planet, and treating it is a difficult task, as a result of the number of existing methods and the applications’ diversification. This research work shows the results obtained using different delignification methods (physical and chemical) on water lily ((Eichhornia crassipes) fiber lignocellulosic biomass including a seldom exploited method, known as “electrohydrolysis” in order to determinate the removal efficiency of lignin and hemicellulose. The characterization of the physicochemical and morphological properties of the water lily (Eichhornia crassipes) fiber before and after the pretreatments were applied were by means of Fourier Transform Infrared (FT-IR), X-ray diffraction (XRD) and optical microscopy (OM). The results of FT-IR show a significant decrease in the bands associated with lignin and hemicellulose. By XRD, it was determined that the crystallinity of the cellulose increased by 60% for the treated samples with respect to the reference, and an increase in the surface roughness of the samples was observed by OM. In conclusion, it was determined that electrochemistry delignification is an efficient, environmentally friendly methodology to remove the soluble sugars, opening the possibility to use the water lily (Eichhornia crassipes) fiber to produce a green concrete. Full article

Several studies have revealed that patients with type 2 diabetes (T2D) infected with COVID-19 who were medicated with metformin showed higher recovery rates than those administered other antidiabetic drugs. To determine the mechanism of action of antidiabetic drugs against COVID-19, we developed a mathematical model that was based on the number of infected and recovered T2D patients. Moreover, the “diagnostic frequencies” of the infected T2D patients, determined using Fourier-Transform Infrared (FTIR) spectroscopy, were very helpful. In particular, the band at 1775 cm⁻¹, attributed to IgG antibodies, could be used as a “diagnostic frequency” for COVID-19 infection. The increased intensity of the band of vC-O-C sugar moieties suggests an increased number of OH chemical groups that enhance the binding sites of SARS-CoV-2 spike protein for entering host cells. The changes were more pronounced in patients medicated with thiazolidinediones than those using insulin and metformin. Both FTIR spectra and the developed mathematical model confirmed that patients using thiazolidinediones showed a higher risk of COVID-19 infection and mortality. The data support the hypothesis that the NH chemical groups of metformin molecules interact directly through the SARS-CoV-2 spike protein, preventing the entry of COVID-19 into the host membrane cells. Indirectly, metformin inhibits the host binding sites for COVID-19 entry by lowering AGE production. Full article

To address the limitations in time–frequency feature representation of shearer arm gear faults and the issues of parameter redundancy and low training efficiency in standard convolutional neural networks (CNNs), this study proposes a diagnostic method based on an improved S-transform and a Depthwise Separable Convolutional Neural Network (DSCNN). First, the improved S-transform is employed to perform time–frequency analysis on the vibration signals, converting the original one-dimensional signals into two-dimensional time–frequency images to fully preserve the fault characteristics of the gear. Then, a neural network model combining standard convolution and depthwise separable convolution is constructed for fault identification. The experimental dataset includes five gear conditions: tooth deficiency, tooth breakage, tooth wear, tooth crack, and normal. The performance of various frequency-domain and time-frequency methods—Wavelet Transform, Fourier Transform, S-transform, and Gramian Angular Field (GAF)—is compared using the same network model. Furthermore, Grad-CAM is applied to visualize the responses of key convolutional layers, highlighting the regions of interest related to gear fault features. Finally, four typical CNN architectures are analyzed and compared: Deep Convolutional Neural Network (DCNN), InceptionV3, Residual Network (ResNet), and Pyramid Convolutional Neural Network (PCNN). Experimental results demonstrate that frequency–domain representations consistently outperform raw time-domain signals in fault diagnosis tasks. Grad-CAM effectively verifies the model’s accurate focus on critical fault features. Moreover, the proposed method achieves high classification accuracy while reducing both training time and the number of model parameters. Full article

In this study, Mg-Al-Zn, MgO, Al₂O_3, and ZnO were synthesized via the co-precipitation method and evaluated as catalysts for the transesterification reaction of dimethyl carbonate (DMC) and ethanol. The crystal structure, morphological characteristics, pore structure properties, and alkaline properties of the catalysts were analyzed by X-ray diffraction (XRD), scanning electron microscopy (SEM), Brunauer-Emmett-Teller (BET) surface area analysis, temperature-programmed desorption of CO₂ (CO₂-TPD), and Fourier transform infrared spectroscopy (FTIR). The surface alkali strength and alkalinity of the solids were determined using the Hammett indicator method and non-aqueous titration. When Al₂O₃ and ZnO are used as catalysts for this transesterification, the conversion rate of dimethyl carbonate is relatively low. When MgO and Mg-Al-Zn are used as catalysts, the conversion rate of dimethyl carbonate is higher. This indicates that the alkali strength of the catalyst for the transesterification reaction needs to be greater than 9.3. Additionally, the activity of the catalysts is also related to the amount of the alkaline sites on the solid surface. The alkali strength of MgO is greater than 11; its excessively high alkali strength will react with CO₂ and H₂O during use, resulting in a reduction in the number of alkaline sites and thus showing unsatisfactory reactivity. The alkaline strength of the Mg-Al-Zn catalyst ranges from 9.3 to 11.0. When used for the first time, the number of alkaline sites decreases, and then the alkalinity remains at a certain value. Therefore, the alkaline strength of the solid catalyst for the transesterification reaction between DMC and ethanol needs to be between 9.3 and 11.0 so that the number of alkaline sites on the catalyst surface remains unchanged and the catalytic activity remains stable. Full article

The article presents a new method of passive dynamic weighing of vehicles based on the registration of seismic signals that occur when wheels pass through strips specially applied to the road surface. Signal processing is carried out using spectral methods, including fast Fourier transform, consistent filtering, and regularization methods for solving inverse problems. Special attention is paid to the use of linear-frequency-modulated signals, which make it possible to distinguish the responses of individual axes even when superimposed. Field tests were carried out on a real section of the road, during which signals from vehicles of various classes were recorded using eight geophones. The average error in determining the speed of 1.2 km/h and the weight of 8.7% was experimentally achieved, while the correct determination of the number of axles was 96.5%. The results confirm the high accuracy and sustainability of the proposed approach with minimal implementation costs. It is shown that this system can be scaled up for use in intelligent transport systems and applied in real traffic conditions without the need to intervene in the design of the roadway. Full article

Biochar is a solid product generated through the pyrolysis of biomass materials under anaerobic or hypoxic conditions, and it is characterized by its strong adsorption capacity. To investigate the phosphorus adsorption performance of biochar derived from wheat straw, bamboo, and water hyacinth in wastewater, iron modification treatments were applied to these biochars, and the most effective modified biochar was identified. The physicochemical properties of the modified biochars were characterized using Fourier Transform Infrared Spectroscopy (FTIR), X-ray Diffraction (XRD), and scanning electron microscopy (SEM). The results showed that optimal modification was achieved with an iron–carbon mass ratio of 0.70 for wheat straw biochar (Fe-WBC) and 0.45 for both bamboo biochar (Fe-BBC) and water hyacinth biochar (Fe-HBC). The maximum phosphorus adsorption capacities of the three modified biochars were as follows: 31.76 mg g⁻¹ (Fe-WBC) > 27.14 mg g⁻¹ (Fe-HBC) > 25.31 mg g⁻¹ (Fe-BBC). It was demonstrated that the adsorption behavior of Fe-BBC was predominantly multi-molecular layer adsorption, whereas the adsorption behavior of Fe-WBC and Fe-HBC was primarily monolayer adsorption. All three types of modified biochars reached adsorption equilibrium within 30 min, with Fe-WBC exhibiting the best adsorption performance. Analysis revealed that the modified biochars contained a large number of unsaturated C bonds and aromatic rings, indicating relatively stable structures. The surfaces of the modified biochars were rich in hydroxyl and carbonyl groups, which contributed to their strong adsorption properties. Post-modification analysis indicated that iron in the biochars predominantly existed in forms such as goethite (FeOOH) and hematite (Fe₂O₃). The iron content in each type of modified biochar constituted approximately 3.08% for Fe-WBC, 5.94% for Fe-BBC, and 5.68% for Fe-HBC relative to their total elemental composition. Overall, the iron-modified biochars employed in this study significantly enhanced the adsorption capacity and efficiency for phosphorus removal in wastewater. Full article