This study analyzes the effects of COVID-19 confinement on the autonomous learning performance of students in higher education. Using a field experiment with 458 students from three different subjects at Universidad Autónoma de Madrid (Spain), we study the differences in assessments by dividing students into two groups. The first group (control) corresponds to academic years 2017/2018 and 2018/2019. The second group (experimental) corresponds to students from 2019/2020, which is the group of students that had their face-to-face activities interrupted because of the confinement. The results show that there is a significant positive effect of the COVID-19 confinement on students’ performance. This effect is also significant in activities that did not change their format when performed after the confinement. We find that this effect is significant both in subjects that increased the number of assessment activities and subjects that did not change the student workload. Additionally, an analysis of students’ learning strategies before confinement shows that students did not study on a continuous basis. Based on these results, we conclude that COVID-19 confinement changed students’ learning strategies to a more continuous habit, improving their efficiency. For these reasons, better scores in students’ assessment are expected due to COVID-19 confinement that can be explained by an improvement in their learning performance.

A method to form and manipulate the properties of nanometer-size liquid bridges by an external electric field is discussed. The properties of bridges are shown to be the result of an interplay among the field-induced polarization of the water layer adsorbed on the surface, the surface energy, and the water condensation from the humid air. For a given tip-sample separation, a simple model predicts the existence of a threshold voltage $V_{\mathrm{t}\mathrm{h}}$ to form the bridge in full agreement with experiments.

This study explores the effects of COVID-19 confinement in the students’ performance in higher education. Using a field experiment of 458 students from three different subjects in Universidad Autónoma de Madrid (Spain), we study the differences in assessments by dividing students into two groups. The first group (control) corresponds to academic years 2017/2018 and 2018/2019. The second group (experimental) corresponds to students from 2019/2020, which is the group of students that interrupted their face-to-face activities because of the confinement. The results show that there is a significant positive effect of the COVID-19 confinement on students’ performance. This effect is also significative in activities that did not change their format when performed after the confinement. We find that this effect is significative both in subjects that increased the number of assessment activities and subjects that did not change the workload of students. Additionally, an analysis of students’ learning strategies before confinement shows that students did not study in a continuous basis. Based on these results, we conclude that COVID-19 confinement changed students’ learning strategies to a more continuous habit, improving their efficiency. For these reasons, better scores in students’ assessment are expected due to COVID-19 confinement that can be explained by an improvement in their learning performance.

During the last decade there has been increasing use of artificial intelligence tools in nanotechnology research. In this paper we review some of these efforts in the context of interpreting scanning probe microscopy, the study of biological nanosystems, the classification of material properties at the nanoscale, theoretical approaches and simulations in nanoscience, and generally in the design of nanodevices. Current trends and future perspectives in the development of nanocomputing hardware that can boost artificial-intelligence-based applications are also discussed. Convergence between artificial intelligence and nanotechnology can shape the path for many technological developments in the field of information sciences that will rely on new computer architectures and data representations, hybrid technologies that use biological entities and nanotechnological devices, bioengineering, neuroscience and a large variety of related disciplines.

The energy dissipation process involved in the formation and rupture of a nanometer-sized capillary-condensed water bridge is theoretically analyzed. With the help of numerical simulations, the dissipation contrast in amplitude-modulated atomic force microscopy is shown to be a result of a nontrivial interplay between the energy dissipated in each rupture process and the bistable motion of the cantilever. In the repulsive high amplitude regime, the dissipated power is a function of the tip and sample contact angles being independent of the elastic properties of the system. Working in this regime, energy dissipation images in air can be regarded as surface hydrophobicity maps.