Scanning Spin Probe Based on Magnonic Vortex Quantum Cavities.

Performing nanoscale scanning electron paramagnetic resonance (EPR) requires three essential ingredients: First, a static magnetic field together with field gradients to Zeeman split the electronic energy levels with spatial resolution; second, a radio frequency (rf) magnetic field capable of inducing spin transitions; finally, a sensitive detection method to quantify the energy absorbed by spins. This is usually achieved by combining externally applied magnetic fields with inductive coils or cavities, fluorescent defects, or scanning probes. Here, we theoretically propose the realization of an EPR scanning sensor merging all three characteristics into a single device: the vortex core stabilized in ferromagnetic thin-film discs. On one hand, the vortex ground state generates a significant static magnetic field and field gradients. On the other hand, the precessional motion of the vortex core around its equilibrium position produces a circularly polarized oscillating magnetic field, which is enough to produce spin transitions. Finally, the spin-magnon coupling broadens the vortex gyrotropic frequency, suggesting a direct measure of the presence of unpaired electrons. Moreover, the vortex core can be displaced by simply using external magnetic fields of a few mT, enabling EPR scanning microscopy with large spatial resolution. Our numerical simulations show that, by using low damping magnets, it is theoretically possible to detect single spins located on the disc's surface. Vortex nanocavities could also attain strong coupling to individual spin molecular qubits with potential applications to mediate qubit-qubit interactions or to implement qubit readout protocols.

Eco-Friendly Approach for Graphene Oxide Synthesis by Modified Hummers Method.

The aim of this study is to produce graphene oxide using a modified Hummers method without using sodium nitrate. This modification eliminates the production of toxic gases. Two drying temperatures, 60 °C and 90 °C, were used. Material was characterized by X-Ray Diffraction, Fourier Transform Infrared Spectroscopy, Raman Spectroscopy and Scanning Electron Microscopy. FTIR study shows various functional groups such as hydroxyl, carboxyl and carbonyl. The XRD results show that the space between the layers of GO60 is slightly larger than that for GO90. SEM images show a homogeneous network of graphene oxide layers of ≈6 to ≈9 nm. The procedure described has an environmentally friendly approach.

Methodology for the Development of Augmented Reality Applications: MeDARA. Drone Flight Case Study.

Industry 4.0 involves various areas of engineering such as advanced robotics, Internet of Things, simulation, and augmented reality, which are focused on the development of smart factories. The present work presents the design and application of the methodology for the development of augmented reality applications (MeDARA) using a concrete, pictorial, and abstract approach with the intention of promoting the knowledge, skills, and attitudes of the students within the conceptual framework of educational mechatronics (EMCF). The flight of a drone is presented as a case study, where the concrete level involves the manipulation of the drone in a simulation; the graphic level requires the elaboration of an experiential storyboard that shows the scenes of the student's interaction with the drone in the concrete level; and finally, the abstract level involves the planning of user stories and acceptance criteria, the computer design of the drone, the mock-ups of the application, the coding in Unity and Android Studio, and its integration to perform unit and acceptance tests. Finally, evidence of the tests is shown to demonstrate the results of the application of the MeDARA.

Pattern Recognition of EMG Signals by Machine Learning for the Control of a Manipulator Robot.

Human Machine Interfaces (HMI) principles are for the development of interfaces for assistance or support systems in physiotherapy or rehabilitation processes. One of the main problems is the degree of customization when applying some rehabilitation therapy or when adapting an assistance system to the individual characteristics of the users. To solve this inconvenience, it is proposed to implement a database of surface Electromyography (sEMG) of a channel in healthy individuals for pattern recognition through Neural Networks of contraction in the muscular region of the biceps brachii. Each movement is labeled using the One-Hot Encoding technique, which activates a state machine to control the position of an anthropomorphic manipulator robot and validate the response time of the designed HMI. Preliminary results show that the learning curve decreases when customizing the interface. The developed system uses muscle contraction to direct the position of the end effector of a virtual robot. The classification of Electromyography (EMG) signals is obtained to generate trajectories in real time by designing a test platform in LabVIEW.

Convolutional Neural Networks Approach for Solar Reconstruction in SCAO Configurations.

Correcting atmospheric turbulence effects in light with Adaptive Optics is necessary, since it produces aberrations in the wavefront of astronomical objects observed with telescopes from Earth. These corrections are performed classically with reconstruction algorithms; between them, neural networks showed good results. In the context of solar observation, the usage of Adaptive Optics on solar differs from nocturnal operations, bringing up a challenge to correct the image aberrations. In this work, a convolutional approach is given to address this issue, considering SCAO configurations. A reconstruction algorithm is presented, "Shack-Hartmann reconstruction with deep learning on solar-prototype" (proto-HELIOS), to correct on fixed solar images, achieving an average 85.39% of precision in the reconstruction. Additionally, results encourage to continue working with these techniques to achieve a reconstruction technique for all the regions of the sun.

Comparative Study of Neural Network Frameworks for the Next Generation of Adaptive Optics Systems.

Many of the next generation of adaptive optics systems on large and extremely large telescopes require tomographic techniques in order to correct for atmospheric turbulence over a large field of view. Multi-object adaptive optics is one such technique. In this paper, different implementations of a tomographic reconstructor based on a machine learning architecture named "CARMEN" are presented. Basic concepts of adaptive optics are introduced first, with a short explanation of three different control systems used on real telescopes and the sensors utilised. The operation of the reconstructor, along with the three neural network frameworks used, and the developed CUDA code are detailed. Changes to the size of the reconstructor influence the training and execution time of the neural network. The native CUDA code turns out to be the best choice for all the systems, although some of the other frameworks offer good performance under certain circumstances.

(-)-Epicatechin induces physiological cardiac growth by activation of the PI3K/Akt pathway in mice.

SCOPE: The flavanol (-)-epicatechin (Epi) has cardioprotective effects and improves physical capacity in normal mice. In addition, Epi increases nitric oxide (NO) production by activation of both PI3K/Akt or Ca2+ /CaMI/CaMKII (where Akt is protein kinase B; PI3K is phosphoinositide 3-kinase; CaMI is calmodulin; CaMKII is Ca2+ /calmodulin-dependent protein kinase II) signaling pathways, which have been associated with physiological and pathological cardiac hypertrophy, respectively. Notwithstanding all this information, few studies have been carried out that aimed to determine the potential beneficial effects that Epi may have in normal heart. METHODS AND RESULTS: Mice were treated by oral gavage with the flavanol Epi. The treatment induced a significant increase in heart weight, size of the free walls, and size of the cardiac fibers. Also, no evidence of cardiac fibrosis was revealed. Furthermore, the phosphorylation level of PI3K/Akt/mTOR/p70S6K (where mTOR is mammalian target of rapamycin; p70S6K is ribosomal protein S6 kinase beta-1) proteins was significantly higher in the heart of Epi-treated animals. In contrast, a significantly decreased level of pathological cardiac hypertrophy markers atrial natriuretic peptide and brain natriuretic peptide was observed along with no modification in the level of ß myosin heavy chain beta, calmodulin, and Ca2+ /calmodulin-dependent protein kinase II proteins. Hemodynamic parameters indicated an improvement in mechanical heart performance after Epi treatment. Interestingly, morphometric parameters were similar between treated and untreated mice after 4 wk without treatment. CONCLUSION: These findings indicate that Epi treatment induced physiological cardiac growth in healthy mice by activation of the PI3K/Akt pathway.