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We present a magnetic sensor with energy resolution per bandwidth ER < ħ. We show how a 87Rb single-domain spinor Bose–Einstein condensate, detected by nondestructive Faraday rotation probing, achieves single-shot low-frequency magnetic sensitivity of 72(8) fT measuring a volume V = 1,091(30) μm³ for 3.5 s, and thus, ER = 0.075(16)ħ. We measure experimentally the condensate volume, spin coherence time, and readout noise and use phase space methods, backed by three-dimensional mean-field simulations, to compute the spin noise. Contributions to the spin noise include one-body and three-body losses and shearing of the projection noise distribution, due to competition of ferromagnetic contact interactions and quadratic Zeeman shifts. Nonetheless, the fully coherent nature of the single-domain, ultracold two-body interactions allows the system to escape the coherence vs. density trade-off that imposes an energy resolution limit on traditional spin precession sensors. We predict that other Bose-condensed alkalis, especially the antiferromagnetic 23Na, can further improve the energy resolution of this method.

Monopoles and vortices are fundamental topological excitations that appear in physical systems spanning enormous scales of size and energy, from the vastness of the early universe to tiny laboratory droplets of nematic liquid crystals and ultracold gases. Although the topologies of vortices and monopoles are distinct from one another, under certain circumstances a monopole can spontaneously and continuously deform into a vortex ring with the curious property that monopoles passing through it are converted into anti-monopoles. However, the observation of such Alice rings has remained a major challenge, due to the scarcity of experimentally accessible monopoles in continuous fields. Here, we present experimental evidence of an Alice ring resulting from the decay of a topological monopole defect in a dilute gaseous 87 Rb Bose–Einstein condensate. Our results, in agreement with detailed first-principles simulations, provide an unprecedented opportunity to explore the unique features of a composite excitation that combines the topological features of both a monopole and a vortex ring. An Alice ring is related to the unusual topology of the monopole field and its decay. Here the authors demonstrate a topological monopole defect in the form of an Alice ring using gaseous Bose–Einstein condensates of 87Rb atoms.

Motor Imagery (MI)-based Brain–Computer Interfaces (BCIs) have been widely used as an alternative communication channel to patients with severe motor disabilities, achieving high classification accuracy through machine learning techniques. Recently, deep learning techniques have spotlighted the state-of-the-art of MI-based BCIs. These techniques still lack strategies to quantify predictive uncertainty and may produce overconfident predictions. In this work, methods to enhance the performance of existing MI-based BCIs are proposed in order to obtain a more reliable system for real application scenarios. First, the Monte Carlo dropout (MCD) method is proposed on MI deep neural models to improve classification and provide uncertainty estimation. This approach was implemented using Shallow Convolutional Neural Network (SCNN-MCD) and with an ensemble model (E-SCNN-MCD). As another contribution, to discriminate MI task predictions of high uncertainty, a threshold approach is introduced and tested for both SCNN-MCD and E-SCNN-MCD approaches. The BCI Competition IV Databases 2a and 2b were used to evaluate the proposed methods for both subject-specific and non-subject-specific strategies, obtaining encouraging results for MI recognition.

In 1869, Lord Kelvin found that the way vortices are knotted and linked in an ideal fluid remains unchanged in evolution, and consequently hypothesized atoms to be knotted vortices in a ubiquitous ether, different knotting types corresponding to different types of atoms. Even though Kelvin’s atomic theory turned out incorrect, it inspired several important developments, such as the mathematical theory of knots and the investigation of knotted structures that naturally arise in physics. However, in previous studies, knotted and linked structures have been found to untie via local cut-and-paste events referred to as reconnections. Here, in contrast, we construct knots and links of non-Abelian vortices that are topologically protected in the sense that they cannot be dissolved employing local reconnections and strand crossings. Importantly, the topologically protected links are supported by a variety of physical systems such as dilute Bose-Einstein condensates and liquid crystals. We also propose a classification scheme for topological vortex links, in which two structures are considered equivalent if they differ from each other by a sequence of topologically allowed reconnections and strand crossings, in addition to the typical continuous transformations. Interestingly, this scheme produces a remarkably simple classification. Ordered materials, such as liquid crystals and Bose-Einstein condensates, support topological vortices, which are analogous to vortices in water, but have qualitatively different properties. Here, the authors show that some links of topological vortices can exhibit much greater stability than analogous structures in water.

The development of Brain–Computer Interfaces based on Motor Imagery (MI) tasks is a relevant research topic worldwide. The design of accurate and reliable BCI systems remains a challenge, mainly in terms of increasing performance and usability. Classifiers based on Bayesian Neural Networks are proposed in this work by using the variational inference, aiming to analyze the uncertainty during the MI prediction. An adaptive threshold scheme is proposed here for MI classification with a reject option, and its performance on both datasets 2a and 2b from BCI Competition IV is compared with other approaches based on thresholds. The results using subject-specific and non-subject-specific training strategies are encouraging. From the uncertainty analysis, considerations for reducing computational cost are proposed for future work.

Backgrounds Exoskeletons development arises with a leading role in neurorehabilitation technologies; however, very few prototypes for upper limbs have been tested, contrasted and duly certified in terms of their effectiveness in clinical environments in order to incorporate into the health system. The purpose of this pilot study was to determine if robotic therapy of Hemiplegic Shoulder Pain (HSP) could lead to functional improvement in terms of diminishing of pain, spasticity, subluxation, the increasing of tone and muscle strength, and the satisfaction degree. Methods An experimental study was conducted in 16 patients with painful shoulder post- ischemic stroke in two experimental groups: conventional and robotic therapy. At different stages of its evolution, the robotic therapy effectiveness applied with anti-gravitational movements was evaluated. Clinical trial was developed at the Physical Medicine and Rehabilitation Department of the Surgical Clinical Hospital “Dr. Juan Bruno Zayas Alfonso” in Santiago de Cuba, from September 2016 - March 2018. Among other variables: the presence of humeral scapular subluxation (HSS), pain, spasticity, mobility, tone and muscle strength, and the satisfaction degree were recorded. Results with 95% reliability were compared between admission and third months of treatment. The Mann-Whitney U-Test, Chi-Square and Fisher’s Exact Tests were used as comparison criteria. Results Robotic therapy positively influenced in the decrease and annulment of pain and the spasticity degree, reaching a range increase of joint movement and the improvement of muscle tone.

Decoherence with recurrences appear in the dynamics of the one-body density matrix of an F=1 spinor Bose–Einstein condensate, initially prepared in coherent states, in the presence of an external uniform magnetic field and within the single mode approximation. The phenomenon emerges as a many-body effect of the interplay of the quadratic Zeeman effect, which breaks the rotational symmetry, and the spin-spin interactions. By performing full quantum diagonalizations, a very accurate time evolution of large condensates is analyzed, leading to heuristic analytic expressions for the time dependence of the one-body density matrix, in the weak and strong interacting regimes, for initial coherent states. We are able to find accurate analytical expressions for both the decoherence and the recurrence times, in terms of the number of atoms and strength parameters, which show remarkable differences depending on the strength of the spin-spin interactions. The features of the stationary states in both regimes are also investigated. We discuss the nature of these limits in light of the thermodynamic limit.

In actual work, slurry erosion behavior of three different HVOF sprayed cermet coatings has been studied. The coatings were developed using the powders feedstock having WC fine structured sizes, Cr3C2-NiCr 75-25 and NiCrWSiFeB, latter conventional grain sizes. The slurry erosion testing was performed using a laboratory made pot-type slurry erosion tester, at an impact velocity of 3.61m/s and 9.33 m/s and impact angle of 30 and 90º. The mechanism of material removal in slurry erosion was studied and discussed on microstructural investigations and mechanical properties under the erosion conditions. It was observed that the WC-CoCr cermet coating with fine WC grain exhibits higher erosion resistance as compared to conventional cermet coating due to its improved properties like low porosity, high micro-hardness and fracture toughness.

Marine gastropods of the genus Conus, comprising more than 800 species, have the characteristic of injecting worms and other prey with venom. These conopeptide toxins, highly diverse in structure and action, are highly potent and specific for their molecular targets (ion channels, receptors, and transporters of the prey’s nervous system), and thus are important research tools and source for drug discovery. Next-generation sequencing technologies are speeding up the discovery of novel conopeptides in many of these species, but only limited information is available for Conus spurius, which inhabits sandy mud. To search for new precursor conopeptides, we analyzed the transcriptome of the venous ducts of C. spurius and identified 55 putative conotoxins. Seven were selected for further study and confirmed by Sanger sequencing to belong to the M-superfamily (Sr3.M01 and Sr3.M02), A-superfamily (Sr1.A01 and Sr1.A02), O-superfamily (Sr15.O01), and Con-ikot-ikot (Sr21.CII01 and Sr22.CII02). Six of these have never been reported. To our knowledge, this report is the first to use high-throughput RNA sequencing for the study of the diversity of C. spurius conotoxins.

The Pelibuey sheep has adaptability to climatic variations, resistance to parasites, and good maternal ability, whereas some ewes present multiple births, which increases the litter size in farm sheep. The litter size in some wool sheep breeds is associated with the presence of mutations, mainly in the family of the transforming growth factor β (TGF-β) genes. To explore genetic mechanisms underlying the variation in litter size, we conducted a genome-wide association study in two groups of Pelibuey sheep (multiparous sheep with two lambs per birth vs. uniparous sheep with a single lamb at birth) using the OvineSNP50 BeadChip. We identified a total of 57 putative SNPs markers (p < 3.0 × 10−3, Bonferroni correction). The candidate genes that may be associated with litter size in Pelibuey sheep are CLSTN2, MTMR2, DLG1, CGA, ABCG5, TRPM6, and HTR1E. Genomic regions were also identified that contain three quantitative trait loci (QTLs) for aseasonal reproduction (ASREP), milk yield (MY), and body weight (BW). These results allowed us to identify SNPs associated with genes that could be involved in the reproductive process related to prolificacy.