This study focused on the formulation and characterization of silver nanoparticles (AgNP) functionalized with d-limonene. The nanoparticles were functionalized by phase inversion and the synthesis of the nanoparticles was performed in situ; particle size was determined by laser diffraction, zeta potential and optical colloidal stability using Multiscan 20 for a period of 24 hours at 37 °C; the minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) of the formulated material on Escherichia coli ATCC 25922, Staphylococcus aureus ATCC 29213, Klebsiella oxytoca ATCC 700324, Enterococcus casseliflavus ATCC 700327, Escherichia coli BLEE, carbapenem-resistant Pseudomona aeruginosa were determined. The nanoparticles showed colloidal stability at a d-limonene concentration of 3.93%, silver ions at 1.61 × 10⁻³%, non-ionic adjuvant at 24% and ascorbic acid at 5.88%; citric acid/citrate (1:1) 0.48M for a pH of 4.5 was used as a buffer system. The formulation was classified as a polydisperse system (PD = 0.0851), with a zeta potential of −11.6 mV and average particle size of 81.5 ± 0.9 nm. A particle migration velocity of −0.199 ± 0.006 mm∙h⁻¹, a constant transmission profile and backscattering profile with variations of 10% were evidenced, which represents a stable formulation. The nanoparticles presented an MIC and an MBC of 28 μg∙mL⁻¹ (5.6 × 10⁻²% d-limonene and 4.7 × 10⁻⁵% AgNP) against all tested bacteria.

Developing countries have witnessed a rise in infrastructure spending over the past decades; however, infrastructure spending in most developed countries, particularly the US, continues to decline. As a result, in 2021, the US Congress passed a Bipartisan Infrastructure Bill, which invests $1 trillion in the country’s infrastructure every year. Using the principal component analysis and VAR estimation, we analyzed the impact of infrastructure (transportation and water, railway networks, aviation, energy, and fixed telephone lines) on economic growth in the US. Our findings show that infrastructure spending positively and significantly impacted economic growth. Additionally, the impulse response analysis shows that shocks to infrastructure spending had positive and persistent effects on economic growth. Our results suggest that infrastructure investment spurs economic growth. Based on our findings, sustained public spending on transport and water, railway networks, aviation, energy, and fixed telephone lines infrastructure by the US government will positively impact economic growth in the country. The study also suggests that policies that promote infrastructure spending, such as the Bipartisan Infrastructure Law (Infrastructure Investment and Jobs Act) passed by the US Congress, should be enhanced to boost economic growth in the US. 

Magnetite magnetic nanoparticles (MNP) exhibit superparamagnetic behavior, which gives them important properties such as low coercive field, easy superficial modification and acceptable magnetization levels. This makes them useful in separation techniques. However, few studies have experimented with the interactions of MNP with magnetic fields. Therefore, the aim of this research was to study the influence of an oscillating magnetic field (OMF) on polymeric monolithic columns with vinylated magnetic nanoparticles (VMNP) for capillary liquid chromatography (cLC). For this purpose, MNP were synthesized by coprecipitation of iron salts. The preparation of polymeric monolithic columns was performed by copolymerization and aggregation of VMNP. Taking advantage of the magnetic properties of MNP, the influence of parameters such as resonance frequency, intensity and exposure time of a OMF applied to the synthesized columns was studied. As a result, a better separation of a sample according to the measured parameters was obtained, so that a column resolution (R_s) of 1.35 was achieved. The morphological properties of the columns were evaluated by scanning electron microscopy (SEM). The results of the chromatographic properties revealed that the best separation of the alkylbenzenes sample occurs under conditions of 5.5 kHz and 10 min of exposure in the OMF. This study constitutes a first application in chromatographic separation techniques for future research in nanotechnology.

Map is the basic language of geography and an indispensable tool for spatial analysis. But for a long time, maps have been regarded as an objective and neutral scientific achievement. Inspired by critical geography, critical cartography/GIS came into being with the goal of clarifying the discourse embedded in cartographic practice. Power relationship challenges the untested assumption in map representation that is taken for granted. After more than 40 years of debate and running in, this research field has initially shown an outline, and critical cartography/GIS has roughly formed two research directions: the deconstruction path mainly starts from the identity of cartography subject and the process of map knowledge production, and analyzes the inseparable relationship between cartography and national governance and its internal power mechanism respectively; the construction path mainly relies on cooperative mapping and anti-mapping to realize the reproduction of map data. Domestic critical cartography/GIS research has just started, and it is necessary to continue to absorb the achievements of critical geography and carry out research in different historical periods. The deconstruction research of different types of maps also needs to strengthen the in-depth bridging between the construction path and the deconstruction path, and to be more open to the public. Impartial map application research, and actively apply the research results to social practice.

In order to strengthen the study of soil-landscape relationships in mountain areas, a digital soil mapping approach based on fuzzy set theory was applied. Initially, soil properties were estimated with the regression kriging (RK) method, combining soil data and auxiliary information derived from a digital elevation model (DEM) and satellite images. Subsequently, the grouping of soil properties in raster format was performed with the fuzzy c-means (FCM) algorithm, whose final product resulted in a fuzzy soil class variation model at a semi-detailed scale. The validation of the model showed an overall reliability of 88% and a Kappa index of 84%, which shows the usefulness of fuzzy clustering in the evaluation of soil-landscape relationships and in the correlation with soil taxonomic categories.

The wide distribution of the common beech (Fagus sylvatica) in Europe reveals its great adaptation to diverse conditions of temperature and humidity. This interesting aspect explains the context of the main objective of this work: to carry out a dendroclimatic analysis of the species Fagus sylvatica in the Polaciones valley (Cantabria), an area of transition with environmental conditions from a characteristic Atlantic type to more Mediterranean, at the southern limit of its growth. The methodology developed is based on the analysis of 25 local chronologies of growth rings sampled at different altitudes along the valley, generating a reference chronology for the study area. Subsequently, the patterns of growth and response to climatic variations are estimated through the response and correlation function, and the most significant monthly variables in the annual growth of the species are obtained. Finally, these are introduced into a Geographic Information System (GIS) where they are cartographically modeled in the altitudinal gradient through multivariate analysis, taking into account the different geographic and topographic variables that influence the zonal variability of the species response. The results of the analyses and cartographic models show which variables are most determinant in the annual growth of the species and the distribution of its climatic response according to the variables considered.