Magnetostatic bias in multilayer microwires: theory and experiments

The hysteresis curves of multilayer microwires consisting of a soft magnetic nucleus, intermediate non-magnetic layers, and an external hard magnetic layer are investigated. The magnetostatic interaction between magnetic layers is proved to give rise to an antiferromagnetic-like coupling resulting in a magnetostatic bias in the hysteresis curves of the soft nucleus. This magnetostatic biasing effect is investigated in terms of the microwire geometry. The experimental results are interpreted considering an analytical model taking into account the magnetostatic interaction between the magnetic layers.Comment: 6 pages, 7 figure

Deep Learning of Transferable MIMO Channel Modes for 6G V2X Communications

In the emerging high mobility vehicle-to-everything (V2X) communications using millimeter wave (mmWave) and sub-THz, multiple-input multiple-output (MIMO) channel estimation is an extremely challenging task. At mmWaves/sub-THz frequencies, MIMO channels exhibit few leading paths in the space-time (ST) domain (i.e., directions or arrival/departure and delays). Algebraic low-rank (LR) channel estimation exploits ST channel sparsity through the computation of position-dependent MIMO channel eigenmodes leveraging recurrent training vehicle passages in the coverage cell. LR requires vehicles' geographical positions and tens to hundreds of training vehicles' passages for each position, leading to significant complexity and control signaling overhead. Here, we design a deep-learning (DL)-based LR channel estimation method to infer MIMO channel eigenmodes in V2X urban settings, starting from a single least squares (LS) channel estimate and without needing vehicle's position information. Numerical results show that the proposed method attains comparable mean squared error (mse) performance as the position-based LR. Moreover, we show that the proposed model can be trained on a reference scenario and be effectively transferred to urban contexts with different ST channel features, providing comparable mse performance without an explicit transfer learning procedure. This result eases the deployment in arbitrary dense urban scenarios

Position-agnostic Algebraic Estimation of 6G V2X MIMO Channels via Unsupervised Learning

MIMO systems in the context of 6G Vehicle-to-Everything (V2X) will require an accurate channel knowledge to enable efficient communication. Standard channel estimation techniques, such as Unconstrained Maximum Likelihood (U-ML), are extremely noisy in massive MIMO settings, while structured approaches, e.g., compressed sensing, are sensitive to hardware impairments. We propose a novel multi-vehicular algebraic channel estimation method for 6G V2X based on unsupervised learning which exploits recurrent vehicle passages in typical urban settings. Multiple training sequences from different vehicle passages are clustered via K-medoids algorithm based on their algebraic similarity to retrieve the MIMO channel eigenmodes, which can be used to improve the channel estimates. Numerical results show the presence of an optimal number of clusters and remarkable benefits of the proposed method in terms of Mean Squared Error (MSE) compared to standard U-ML solution (15 dB less)

Position-agnostic Algebraic Estimation of 6G V2X MIMO Channels via Unsupervised Learning

MIMO systems in the context of 6G Vehicle-to-Everything (V2X) will require an accurate channel knowledge to enable efficient communication. Standard channel estimation techniques, such as Unconstrained Maximum Likelihood (U-ML), are extremely noisy in massive MIMO settings, while structured approaches, e.g., compressed sensing, are sensitive to hardware impairments. We propose a novel multi-vehicular algebraic channel estimation method for 6G V2X based on unsupervised learning which exploits recurrent vehicle passages in typical urban settings. Multiple training sequences from different vehicle passages are clustered via K-medoids algorithm based on their algebraic similarity to retrieve the MIMO channel eigenmodes, which can be used to improve the channel estimates. Numerical results show the presence of an optimal number of clusters and remarkable benefits of the proposed method in terms of Mean Squared Error (MSE) compared to standard U-ML solution (15 dB less)

Assessing Creative Expressiveness In Children's Written Stories Using The Consensual Assessment Technique

The study investigated methodological issues relating to the use of the Consensual Assessment Technique (CAT) for measuring creativity in children’s written stories. The CAT is a commonly used measure to estimate creativity of a product, based on social recognition of creativity by independent judges. Across domains, the CAT has shown high inter-rater reliability. The present study utilised the CAT to assess creativity in children’s written stories. The stories were also evaluated for: Imagination, Novelty, Liking (how much the judges liked the story), Detail, Emotion, Vocabulary, Straightforwardness, Logic and Grammar. The sample consisted of 277 nine-year-olds. The results showed that to reach sufficient inter-rater reliability, 5 coders were needed. The results gave evidence of a 2-factor structure among the 10 dimensions, indexing ‘Creative Expressiveness’ and ‘Logic’ constructs related to individual differences in writing. Girls outperformed boys on both constructs. The story length was positively correlated with the constructs, explaining 63% of the variance in Creative Expressiveness, and 42% in Logic. Creative Expressiveness was positively correlated with verbal ability (r = .20) and with teacher rating of writing (r = .28). Similarly, Logic was also correlated with verbal ability (r = .34) and teacher rating of writing (r = .44). The findings inform future research employing the CAT to measure creativity in children’s storytelling

Growth modes of nanoparticle superlattice thin films

We report about the fabrication and characterization of iron oxide nanoparticle thin film superlattices. The formation into different film morphologies is controlled by tuning the particle plus solvent-to-substrate interaction. It turns out that the wetting vs. dewetting properties of the solvent before the self-assembly process during solvent evaporation plays a major role to determine the resulting film morphology. In addition to layerwise growth also three-dimensional mesocrystalline growth is evidenced. The understanding of the mechanisms ruling nanoparticle self-assembly represents an important step toward the fabrication of novel materials with tailored optical, magnetic or electrical transport properties

production and characterization of ni and cu composite coatings by electrodeposition reinforced with carbon nanotubes or graphite nanoplatelets

Electrodeposition is well-known as a versatile and economical processing technique to produce metal coatings on conductive substrates. Recently, it has been gaining increasing interest also for the production of tailored composite coatings, containing for instance floropolymers or silicon carbide. A more novel approach concerns the use of carbon nanotubes or even graphene, in the form of graphite nano-platelets. The production of Ni- and Cu-based nanocomposites containing carbon nanoreinforcements was carried out by using standard electrodeposition conditions, but with a particular attention to the dispersion of the nanotubes. The obtained coatings were strong and well adherent to the steel substrate, and presented rather well dispersed carbon nanotubes or graphite nanoplatelets, even if some agglomerates could be present in samples obtained from highly concentrated suspensions. In the case of nickel-based composite coatings, the size of nickel grains was reduced, and pin-on-disc tests demonstrated a significant increase in the life of the coating. In the case of copper-based composite coatings, thermal diffusivity measurements demonstrated that the carbon nanomaterial does not reduce the conductivity of the pure copper coating

Equity and health policy in Africa: Using concept mapping in Moore (Burkina Faso)

<p>Abstract</p> <p>Background</p> <p>This methodological article is based on a health policy research project conducted in Burkina Faso (West Africa). Concept mapping (CM) was used as a research method to understand the local views of equity among stakeholders, who were concerned by the health policy under consideration. While this technique has been used in North America and elsewhere, to our knowledge it has not yet been applied in Africa in any vernacular language. Its application raises many issues and certain methodological limitations. Our objective in this article is to present its use in this particular context, and to share a number of methodological observations on the subject.</p> <p>Methods</p> <p>Two CMs were done among two different groups of local stakeholders following four steps: generating ideas, structuring the ideas, computing maps using multidimensional scaling and cluster analysis methods, and interpreting maps. Fifteen nurses were invited to take part in the study, all of whom had undergone training on health policies. Of these, nine nurses (60%) ultimately attended the two-day meeting, conducted in French. Of 45 members of village health committees who attended training on health policies, only eight were literate in the local language (Moore). Seven of these (88%) came to the meeting.</p> <p>Results</p> <p>The local perception of equity seems close to the egalitarian model. The actors are not ready to compromise social stability and peace for the benefit of the worst-off. The discussion on the methodological limitations of CM raises the limitations of asking a single question in Moore and the challenge of translating a concept as complex as equity. While the translation of equity into Moore undoubtedly oriented the discussions toward social relations, we believe that, in the context of this study, the open-ended question concerning social justice has a threefold relevance. At the same time, those limitations were transformed into strengths. We understand that it was essential to resort to the focus group approach to explore deeply a complex subject such as equity, which became, after the two CMs, one of the important topics of the research.</p> <p>Conclusion</p> <p>Using this technique in a new context was not the easiest thing to do. Nevertheless, contrary to what local organizers thought when we explained to them this "crazy" idea of applying the technique in Moore with peasants, we believe we have shown that it was feasible, even with persons not literate in French.</p