Search Results (43)

Bacterial laccase exhibits substantial application potential in various fields. In this study, we constructed a mutation library of CotA laccase from Bacillus pumilus using error-prone PCR, and we performed four rounds of enrichment screening under malachite green (MG) pressure. The results demonstrated that the proportions of the four selected mutant strains were significantly increased. The enzyme activities of the four final mutants PW2, PW5, PW4G, and PW6 were 94.34, 75.74, 100.66, and 87.04 U/mg, respectively, representing a significant increase of approximately 2- to 3-fold compared to the wild-type CotA laccase. Notably, PW4 exhibited significantly improved thermal stability at 90 °C and pH tolerance at pH 12.0. Homology modeling analysis revealed that alterations in the amino acid sequence rendered the spatial structure of the enzyme’s catalytic site more favorable for substrate binding. For instance, the substitution of T262A in PW2 and V426I in PW4 shortened the side chains of the amino acids, thereby enlarging the substrate-binding cavity. The G382D mutation in PW2 and PW5 may induce altered protein conformation via spatial steric hindrance or electrostatic interactions, consequently impacting enzyme activity and stability. These findings provide valuable insights for enhancing the industrial application of bacterial laccase. Full article

This study employed a hydrothermal method to coat CuS onto PbS quantum dots loaded with ZnO, resulting in a core–shell-structured (PbS/ZnO)@CuS hetero-structured photocatalyst. The sulfide coating enhanced the photocatalyst’s absorption in the near-infrared to visible light range and effectively reduced electron–hole (h⁺) pair recombination during photocatalytic processes. Electron microscopy analysis confirmed the successful synthesis of this core–shell structure using polyvinylpyrrolidone (PVP); however, the spatial hindrance effect of PVP led to a disordered arrangement of the CuS lattice, facilitating electron–hole recombination. Comprehensive analyses using transmission electron microscopy (TEM), photoluminescence (PL), and Brunauer–Emmett–Teller (BET) methods revealed that the (PbS/ZnO)@CuS photocatalyst synthesized at a hydrothermal temperature of 170 °C exhibited optimal hydrogen production efficiency. After conducting a photocatalytic reaction for 5 h in a mixed aqueous solution containing 0.25 M Na₂S + Na₂SO₃ as a sacrificial agent, a hydrogen production rate of 3473 μmol·g⁻¹·h⁻¹ was achieved. Full article

In this paper, a coupled model is built to research the space-fractional magnetohydrodynamic (MHD) flow and heat transfer problem. The fractional coupled model is solved numerically by combining the matrix function vector products method in the temporal direction with the spectral method in the spatial direction. A fast method based on the numerical scheme is established to reduce the computational time. With the help of the Bayesian method, the space-fractional orders of the coupled model are estimated, and the problem of multi-parameter estimation in the coupled model is solved. Finally, a numerical example is carried out to verify the stability of the numerical methods and the effectiveness of the parameter estimation method. Results show that the numerical method is stable, which converges with an accuracy of $O({\tau }^2+N^{-r})$. The fast method is efficient in reducing the computational time, and the parameter estimation method can effectively estimate parameters in the space-fractional coupled model. The numerical solutions are discussed to describe the effects of several important parameters on the velocity and the temperature. Results indicate that the Lorentz force produced by the MHD flow blocks the movement of the fluid and prolongs the time for the fluid to reach a stable state. But the Hall parameter m weakens this hindrance. The Joule heating effects play a negative role in heat transfer. Full article

Semicircles and circular sectors are both ubiquitous in the natural realm. However, mathematically speaking they have represented an enigma since antiquity. In recent years, the author has worked in integral equations with sections of spheres as related to radiative heat transfer and their associated form factors, to the point of defining new postulates. The main theorems thus far enunciated refer to the radiative exchange between circles and half disks, but recently the possibility to treat circular sectors has arrived, thanks to the research already conducted. As is known, to find the exact expression of the configuration factor by integration is complex. In the above mentioned problem of the circular sectors, the author reached the first two steps of the basic formulation for radiant exchange. Subsequently, the novelty of the procedure lies in introducing a finite differences approach for the third and fourth integrals which still remain unsolved, once we have been able to find the preliminary integrals. This possibility had not been identified by former research and the output provides us with an ample variety of unexpected scenarios. As a consequence, we are able to analyze with more precision the spatial transference of radiant heat for figures composed of circular sectors. We already know that spherical shapes cannot be discretized with any accuracy. Therefore, we would be able to reduce a considerable amount of hindrance in the progress of thermal radiation science. Important sequels will be derived for radiation in the entrance to tunnels, aircraft design and lighting as well. Full article

Urban green spaces (UGSs) are considered an important natural approach for improving urban climatic conditions, promoting sustainable urban development, and advancing the global “Carbon Peak and Carbon Neutrality” targets. Previous studies have found that different vegetation spatial morphologies significantly impact the capacity to obstruct and absorb CO₂, but it is not yet well understood which morphology can retain and absorb more CO₂. This study takes Nantong Central Park as an example and conducts a CFD (Computational Fluid Dynamics) carbon flow simulation for CO₂ under different vegetation spatial morphologies to identify their CO₂ retention and absorption effects. First, the carbon sink benefits of elements such as “vegetation, soil, and wetlands” within the park were calculated, and the elements with the highest carbon sink benefits were identified. Then, the park was divided into carbon welcoming zones, carbon flow zones, and carbon shadow zones for carbon flow simulation with the highest carbon sink benefits. The results show that in the carbon welcome area, the one-block long fan-shaped plant community with a spatial density of 40 m thickness can best meet the requirements of absorption and induction of a small amount of carbon dioxide, with the smallest air vortex and uniform distribution of carbon dioxide in the surrounding area. In the carbon flow area, combined with the visual effect, the planting pattern of 6 m spacing herringbone combined with natural structure was adopted, which has a good carbon dioxide blocking and absorption capacity. In the carbon-shaded area, a herringbone planting pattern with a total width of 40 m and a base angle of 60° was chosen, which had the strongest hindrance and absorption capacity. Urban park environment optimization can use Fluent simulation to analyze the flow of carbon dioxide between different elements affected by wind dynamics at the same time. Based on the results, the form, layout, and spatial distance are adjusted and optimized. This study can better guide the spatial layout of vegetation and contribute to the realization of the goal of “carbon peak and carbon neutrality”. Full article

A power-law formulation rooted in percolation theory has proven effective in depicting the vertical distribution of soil organic carbon (SOC) in temperate forest subsoils. While the model suggests the solute as the primary factor distributing SOC, this may not hold true in the surface soil in which roots contribute significantly to the SOC. This study in the Changbai Mountains Mixed Forests ecoregion (CMMF) evaluates the SOC profiles in three forests to assess the model’s efficacy throughout the soil column. Prediction of the SOC profile based on the regional average values was also assessed using field data. The observed scaling aligned well with predictions in mixed broadleaved and broadleaved Korean pine mixed forests, but disparities emerged in birch forest, possibly due to waterlogging. The predicted SOC levels correlate strongly with the field data and align well with the normalized average SOC levels. The findings suggest that the model remains applicable in the CMMF when considering root-derived carbon. However, the hindrance of solute transport may have a greater impact than roots do. The spatial heterogeneity of the SOC means that a single predicted SOC value at a specific depth may not fit all sites, but the overall agreement highlights the potential of the model for predicting the average or representative SOC profiles, which could further aid in regional-scale carbon stock estimation. Full article

This project aimed to explore the influence of the interaction between ovotransferrin fibrils (OTF) and gum arabic (GA) on the formation mechanism, physicochemical properties, and curcumin delivery of the oleogel-in-water Pickering emulsion. Cryo-scanning electron microscopy results showed that OTF—GA complexes effectively adsorbed on the oil–water interface, generating spatial hindrance to inhibit droplet coalescence. The texture analysis also proved that OTF—GA complexes endowed oleogel-in-water Pickering emulsion with preferable springiness (0.49 ± 0.03 mm), chewiness (0.43 ± 0.07 mJ), and adhesion (0.31 ± 0.01 mJ). By exploring the coalescence stability, droplet size, and rheological properties of OTF—GA complexes–stabilized oleogel-in-water Pickering emulsion (OGPE), the higher coagulation stability, larger average droplet size (46.22 ± 0.08 μm), and stronger gel strength were observed. The microrheological results also exhibited stronger attraction between the OGPE droplets, a more pronounced solid-like structure, and a slower speed of movement than OTF-stabilized oleogel-in-water Pickering emulsion (OPE). Meanwhile, OGPE significantly enhanced the extent of lipolysis, stability, and bioaccessibility of curcumin, suggesting that it possessed superior performance as a delivery system for bioactive substances. This project provided adequate theoretical references for protein–polysaccharide complexes–stabilized oleogel-in-water Pickering emulsion, and contributed to expanding the application of oleogel-in-water Pickering emulsion in the food industry. Full article

A lignin modified salt-resistant branched high-performance water reducer was prepared via free radical polymerization. The water-reducing agent was identified through its NMR spectrum, elemental analysis, Fourier transform infrared analysis, thermal gravimetric analysis, and scanning electron microscopy. The experiment conducted on cement paste demonstrates that the water-reducing efficiency can reach a maximum of 44%. Additionally, the significant spatial steric hindrance of the application enhances the dispersal capability of the water-reducing agent, resulting in effective water reduction and reduced viscosity. In addition, its compressive strength is the highest after 3-day curing and 3-, 7-, 28-day standard curing, and it has the best overall performance both in water and saline water prepared systems. The application in oil cement slurry shows that it exhibits a good dispersibility in fresh water, saline water, and substitute ocean water. In the Halfaya and Missan Oilfields of Iraq, BHPWR was used in a slurry with a density of 2.28 g/cm³ for casing the salt paste layer of five wells. The cementing results exceeded expectations with 100% qualified including over 85% excellent. Full article

Hyperspectral images (HSIs) contain abundant spectral and spatial structural information, but they are inevitably contaminated by a variety of noises during data reception and transmission, leading to image quality degradation and subsequent application hindrance. Hence, removing mixed noise from hyperspectral images is an important step in improving the performance of subsequent image processing. It is a well-established fact that the data information of hyperspectral images can be effectively represented by a global spectral low-rank subspace due to the high redundancy and correlation (RAC) in the spatial and spectral domains. Taking advantage of this property, a new algorithm based on subspace representation and nonlocal low-rank tensor decomposition is proposed to filter the mixed noise of hyperspectral images. The algorithm first obtains the subspace representation of the hyperspectral image by utilizing the spectral low-rank property and obtains the orthogonal basis and representation coefficient image (RCI). Then, the representation coefficient image is grouped and denoised using tensor decomposition and wavelet decomposition, respectively, according to the spatial nonlocal self-similarity. Afterward, the orthogonal basis and denoised representation coefficient image are optimized using the alternating direction method of multipliers (ADMM). Finally, iterative regularization is used to update the image to obtain the final denoised hyperspectral image. Experiments on both simulated and real datasets demonstrate that the algorithm proposed in this paper is superior to related mainstream methods in both quantitative metrics and intuitive vision. Because it is denoising for image subspace, the time complexity is greatly reduced and is lower than related denoising algorithms in terms of computational cost. Full article

Continuous, robust, and precise localization is pivotal in enabling the autonomous operation of robots and aircraft in intricate environments, particularly in the absence of GNSS (global navigation satellite system) signals. However, commonly employed approaches, such as visual odometry and inertial navigation systems, encounter hindrances in achieving effective navigation and positioning due to issues of error accumulation. Additionally, the challenge of managing extensive map creation and exploration arises when deploying these systems on unmanned aerial vehicle terminals. This study introduces an innovative system capable of conducting long-range and multi-map visual SLAM (simultaneous localization and mapping) using monocular cameras equipped with pinhole and fisheye lens models. We formulate a graph optimization model integrating GNSS data and graphical information through multi-sensor fusion navigation and positioning technology. We propose partitioning SLAM maps based on map health status to augment accuracy and resilience in large-scale map generation. We introduce a multi-map matching and fusion algorithm leveraging geographical positioning and visual data to address excessive discrete mapping, leading to resource wastage and reduced map-switching efficiency. Furthermore, a multi-map-based visual SLAM online localization algorithm is presented, adeptly managing and coordinating distinct geographical maps in different temporal and spatial domains. We employ a quadcopter to establish a testing system and generate an aerial image dataset spanning several kilometers. Our experiments exhibit the framework’s noteworthy robustness and accuracy in long-distance navigation. For instance, our GNSS-assisted multi-map SLAM achieves an average accuracy of 1.5 m within a 20 km range during unmanned aerial vehicle flights. Full article

The accumulation of salt through natural causes and human artifice, such as saline inundation or mineral weathering, is marked as salinization, but the hindrance toward spatial mapping of soil salinity has somewhat remained a consistent riddle despite decades of efforts. The purpose of the current study is the spatial mapping of soil salinity in Kot Addu (situated in the south of the Punjab province, Pakistan) using Landsat 8 data in five advanced machine learning regression models, i.e., Random Forest Regressor, AdaBoost Regressor, Decision Tree Regressor, Partial Least Squares Regression and Ridge Regressor. For this purpose, spectral data were obtained between 20 and 27 of January 2017 and a field survey was carried out to gather a total of fifty-five soil samples. To evaluate and compare the model’s performances, the coefficient of determination (R²), Mean Squared Error (MSE), Mean Absolute Error (MAE) and the Root-Mean-Squared Error (RMSE) were used. Spectral data of band values, salinity indices and vegetation indices were employed to study the salinity of soil. The results revealed that the Random Forest Regressor outperformed the other models in terms of prediction, achieving an R² of 0.94, MAE of 1.42 dS/m, MSE of 3.58 dS/m and RMSE of 1.89 dS/m when using the Differential Vegetation Index (DVI). Alternatively, when using the Soil Adjusted Vegetation Index (SAVI), the Random Forest Regressor achieved an R² of 0.93, MAE of 1.46 dS/m, MSE of 3.90 dS/m and RMSE of 1.97 dS/m. Hence, remote sensing technology with machine learning models is an efficient method for the assessment of soil salinity at local scales. This study will contribute to mitigating osmotic stress and minimizing the risk of soil erosion by providing early warnings regarding soil salinity. Additionally, it will assist agriculture officers in estimating soil salinity levels within a shorter time frame and at a reduced cost, enabling effective resource allocation. Full article

So far, it has been difficult to directly compare diverse characteristic gelation mechanisms over different length and time scales. This paper presents a universal water structure analysis of several gels with different structures and gelation mechanisms including polymer gels, supramolecular gels composed of surfactant micelles, and cement gels. The spatial distribution of water molecules was analyzed at molecular level from a diagram of the relaxation times and their distribution parameters (τ–β diagrams) with our database of the 10 GHz process for a variety of aqueous systems. Polymer gels with volume phase transition showed a small decrease in the fractal dimension of the hydrogen bond network (HBN) with gelation. In supramolecular gels with rod micelle precursor with amphipathic molecules, both the elongation of the micelles and their cross-linking caused a reduction in the fractal dimension. Such a reduction was also found in cement gels. These results suggest that the HBN inevitably breaks at each length scale with relative increase in steric hindrance due to cross-linking, resulting in the fragmentation of collective structures of water molecules. The universal analysis using τ–β diagrams presented here has broad applicability as a method to characterize diverse gel structures and evaluate gelation processes. Full article

Advancements in remote sensing technology and very-large-scale integrated circuit (VLSI) have significantly augmented the real-time processing capabilities of spaceborne synthetic aperture radar (SAR), thereby enhancing terrestrial observational capacities. However, the inefficiency of voluminous data storage and transfer inherent in conventional methods has emerged as a technical hindrance, curtailing real-time processing within SAR imaging systems. To address the constraints of a limited storage bandwidth and inefficient data transfer, this study introduces a three-dimensional cross-mapping approach premised on the equal subdivision of sub-matrices utilizing dual-channel DDR3. This method considerably augments storage access bandwidth and achieves equilibrium in two-dimensional data access. Concurrently, an on-chip data transfer approach predicated on a superscalar pipeline buffer is proposed, mitigating pipeline resource wastage, augmenting spatial parallelism, and enhancing data transfer efficiency. Building upon these concepts, a hardware architecture is designed for the efficient storage and transfer of SAR imaging system data, based on the superscalar pipeline. Ultimately, a data storage and transfer engine featuring register addressing access, configurable granularity, and state monitoring functionalities is realized. A comprehensive imaging processing experiment is conducted via a “CPU + FPGA” heterogeneous SAR imaging system. The empirical results reveal that the storage access bandwidth of the proposed superscalar pipeline-based SAR imaging system’s data efficient storage and transfer engine can attain up to 16.6 GB/s in the range direction and 20.0 GB/s in the azimuth direction. These findings underscore that the storage exchange engine boasts superior storage access bandwidth and heightened data storage transfer efficiency. This considerable enhancement in the processing performance of the entire “CPU + FPGA” heterogeneous SAR imaging system renders it suitable for application within spaceborne SAR real-time processing systems. Full article

In this study, poly(thiourethane) (PTU) with different structures is synthesized by click chemistry from trimethylolpropane tris(3-mercaptopropionate) (S3) and different diisocyanates (hexamethylene diisocyanate, HDI, isophorone diisocyanate, IPDI and toluene diisocyanate, TDI). Quantitative analysis of the FTIR spectra reveals that the reaction rates between TDI and S3 are the most rapid, resulting from the combined influence of conjugation and spatial site hindrance. Moreover, the homogeneous cross-linked network of the synthesized PTUs facilitates better manageability of the shape memory effect. All three PTUs exhibit excellent shape memory properties (R_r and R_f are over 90%), and an increase in chain rigidity is observed to negatively impact the shape recovery rate and fix rate. Moreover, all three PTUs exhibit satisfactory reprocessability performance, and an increase in chain rigidity is accompanied by a greater decrease in shape memory and a smaller decrease in mechanical performance for recycled PTUs. Contact angle (<90°) and in vitro degradation results (13%/month for HDI-based PTU, 7.5%/month for IPDI-based PTU, and 8.5%/month for TDI-based PTU) indicate that PTUs can be used as long-term or medium-term biodegradable materials. The synthesized PTUs have a high potential for applications in smart response scenarios requiring specific glass transition temperatures, such as artificial muscles, soft robots, and sensors. Full article

Macrocycles have attracted significant attention from academia due to their various applications in organic field-effect transistors, organic light-emitting diodes, organic photovoltaics, and dye-sensitized solar cells. Despite the existence of reports on the application of macrocycles in organic optoelectronic devices, these reports are mainly limited to analyzing the structure–property relationship of a particular type of macrocyclic structure, and a systematic discussion on the structure–property is still lacking. Herein, we conducted a comprehensive analysis of a series of macrocycle structures to identify the key factors that affect the structure–property relationship between macrocycles and their optoelectronic device properties, including energy level structure, structural stability, film-forming property, skeleton rigidity, inherent pore structure, spatial hindrance, exclusion of perturbing end-effects, macrocycle size-dependent effects, and fullerene-like charge transport characteristics. These macrocycles exhibit thin-film and single-crystal hole mobility up to 10 and 26.8 cm² V⁻¹ s⁻¹, respectively, as well as a unique macrocyclization-induced emission enhancement property. A clear understanding of the structure–property relationship between macrocycles and optoelectronic device performance, as well as the creation of novel macrocycle structures such as organic nanogridarenes, may pave the way for high-performance organic optoelectronic devices. Full article