Aiming at the problem of road network multi-scale matching, a multi-scale road matching method under the constraint of road mesh of small-scale data has been proposed. First, two road meshes with different scale data are constructed; Secondly, under the constraint of the small-scale road mesh, the composite mesh composed of several road meshes in the large-scale road is extracted, and the mesh matching with the small-scale road mesh is completed; Then, many-to-many matching of road meshes with different scales is realized; finally, the matching relationship between composite mesh and small-scale road mesh is transformed into the matching between multi-scale road mesh boundary roads and internal roads, and the matching of the whole road network is completed. The experimental results show that this method can better realize the matching of multi-scale road network.

An image adaptive noise reduction enhancement algorithm based on NSCT is proposed to perform image restoration preprocessing on the defocused image obtained under the microscope. Defocused images acquired under micro-nano scale optical microscopy, usually with inconspicuous details, edges and contours, affect the accuracy of subsequent observation tasks. Due to its multi-scale and multi-directionality, the NSCT transform has superior transform functions and can obtain more textures and edges of images. Combined with the characteristics of micro-nanoscale optical defocus images, the NSCT inverse transform is performed on all sub-bands to reconstruct the image. Finally, the experimental results of the standard 500 nm scale grid, conductive probe and triangular probe show that the proposed algorithm has a better image enhancement effect and significantly improves the quality of out-of-focus images.

At present, states and entire regions that possess significant reserves of sought-after minerals have great potential to maintain and even improve their socio-economic position in the foreseeable future. Since the beginning of 2000, the increase in mining volumes of minerals has been more than 50%; however, more than half of all extracted raw materials fall to only five leading countries: China, the USA, the Russian Federation, Australia, and India. This article presents the results of the analysis of the global structure of mineral production by type and geographic region. The article provides an in-depth analysis of the world’s leading mining companies, identifying the key players in the industry. A comprehensive overview of each company’s performance, including key financial indicators and production statistics, is presented. The main environmental risks as a result of the continued increase in the global scale of mining have been identified. The prospects for the development of the mining sector are shown. The results of the study can be used by the scientific community as an information source.

Heat removal has become an increasingly crucial issue for microelectronic chips due to increasingly high speed and high performance. One solution is to increase the thermal conductivity of the corresponding dielectrics. However, traditional approach to adding solid heat conductive nanoparticles to polymer dielectrics led to a significant weight increase. Here we propose a dielectric polymer filled with heat conductive hollow nanoparticles to mitigate the weight gain. Our mesoscale simulation of heat conduction through this dielectric polymer composite microstructure using the phase-field spectral iterative perturbation method demonstrates the simultaneous achievement of enhanced effective thermal conductivity and the low density. It is shown that additional heat conductivity enhancement can be achieved by wrapping the hollow nanoparticles with graphene layers. The underlying mesoscale mechanism of such a microstructure design and the quantitative effect of interfacial thermal resistance will be discussed. This work is expected to stimulate future efforts to develop light-weight thermal conductive polymer nanocomposites.

A failsafe network design recovering from the stressed condition against a massive supply disruption is generally useful for various applications. Water flow in plants under a tension is inherently vulnerable to an embolism, a water supply cut off, causing a death. However, the function of the network structures of leaf veins and xylem stems effectively reduces the embolism-induced failure. In this study, water transport in plants under the pressurized conditions compared to the normal physiological conditions is observed by X-ray imaing. By examining embolism-induced water supply limits in the architecturally diverse leaf and stem networks, a progressive hydraulic rule has been found: the limited flows in the selected parts of the network structures against a total fail. For a scientific explanation on nanoscale water flow dynamics occurring in plants, temporal meniscus development in the nanomembrane model system is investigated. The pressure-driven hydrodynamic transport phenomena can be explained to follow network dynamics of the modified imbibition typically occuring in nanostrutcures. This study contributes to a variety of design technologies of networked materials against the spread of flow damages under the stressed conditions.

Low levels of financial literacy cause people to have lower savings rates, higher transaction costs, larger debts and the loans acquisition with higher interest rates, therefore it becomes relevant to analyze the determinants of financial literacy. The aim of this research is to identify whether there is an association between the financial literacy level and sociodemographic characteristics. The Mexican Petroleum Company (Pemex) employees is the population analyzed. Pemex is the state-owned oil and natural gas producer, transporter, refiner and marketer in Mexico. A non-probabilistic convenience sampling was performed and 404 responses were obtained. The analysis of data was carried out with the Bayesian method. The results show that there is an association between Pemex employees’ level of financial literacy and their level of education, income, age and type of retirement saving. No association was found between their level of financial literacy and gender, marital status and whether or not they have children.