The tensorial nature of a quantity permits us to formulate transformation rules for its components under a change of basis. These rules are relatively simple and easily grasped by any engineering ...student familiar with matrix operators in linear algebra. More complex problems arise when one considers the tensor fields that describe continuum bodies. In this case general curvilinear coordinates become necessary. The principal basis of a curvilinear system is constructed as a set of vectors tangent to the coordinate lines. Another basis, called the dual basis, is also constructed in a special manner. The existence of these two bases is responsible for the mysterious covariant and contravariant terminology encountered in tensor discussions.
The rapid expansion of broad-band seismic networks over the last decade has paved the way for a new generation of global tomographic models. Significantly improved resolution of global upper-mantle ...and crustal structure can now be achieved, provided that structural information is extracted effectively from both surface and body waves and that the effects of errors in the data are controlled and minimized. Here, we present a new global, vertically polarized shear speed model that yields considerable improvements in resolution, compared to previous ones, for a variety of features in the upper mantle and crust. The model, SL2013sv, is constrained by an unprecedentedly large set of waveform fits (∼3/4 of a million broad-band seismograms), computed in seismogram-dependent frequency bands, up to a maximum period range of 11-450 s. Automated multimode inversion of surface and S-wave forms was used to extract a set of linear equations with uncorrelated uncertainties from each seismogram. The equations described perturbations in elastic structure within approximate sensitivity volumes between sources and receivers. Going beyond ray theory, we calculated the phase of every mode at every frequency and its derivative with respect to S- and P-velocity perturbations by integration over a sensitivity area in a 3-D reference model; the (normally small) perturbations of the 3-D model required to fit the waveforms were then linearized using these accurate derivatives. The equations yielded by the waveform inversion of all the seismograms were simultaneously inverted for a 3-D model of shear and compressional speeds and azimuthal anisotropy within the crust and upper mantle. Elaborate outlier analysis was used to control the propagation of errors in the data (source parameters, timing at the stations, etc.). The selection of only the most mutually consistent equations exploited the data redundancy provided by our data set and strongly reduced the effect of the errors, increasing the resolution of the imaging.
Our new shear speed model is parametrized on a triangular grid with a ∼280 km spacing. In well-sampled continental domains, lateral resolution approaches or exceeds that of regional-scale studies. The close match of known surface expressions of deep structure with the distribution of anomalies in the model provides a useful benchmark. In oceanic regions, spreading ridges are very well resolved, with narrow anomalies in the shallow mantle closely confined near the ridge axis, and those deeper, down to 100-120 km, showing variability in their width and location with respect to the ridge. Major subduction zones worldwide are well captured, extending from shallow depths down to the transition zone. The large size of our waveform fit data set also provides a strong statistical foundation to re-examine the validity field of the JWKB approximation and surface wave ray theory. Our analysis shows that the approximations are likely to be valid within certain time-frequency portions of most seismograms with high signal-to-noise ratios, and these portions can be identified using a set of consistent criteria that we apply in the course of waveform fitting.
Brain-machine interfaces (BMIs) combine methods, approaches, and concepts derived from neurophysiology, computer science, and engineering in an effort to establish real-time bidirectional links ...between living brains and artificial actuators. Although theoretical propositions and some proof of concept experiments on directly linking the brains with machines date back to the early 1960s, BMI research only took off in earnest at the end of the 1990s, when this approach became intimately linked to new neurophysiological methods for sampling large-scale brain activity. The classic goals of BMIs are
) to unveil and utilize principles of operation and plastic properties of the distributed and dynamic circuits of the brain and
) to create new therapies to restore mobility and sensations to severely disabled patients. Over the past decade, a wide range of BMI applications have emerged, which considerably expanded these original goals. BMI studies have shown neural control over the movements of robotic and virtual actuators that enact both upper and lower limb functions. Furthermore, BMIs have also incorporated ways to deliver sensory feedback, generated from external actuators, back to the brain. BMI research has been at the forefront of many neurophysiological discoveries, including the demonstration that, through continuous use, artificial tools can be assimilated by the primate brain's body schema. Work on BMIs has also led to the introduction of novel neurorehabilitation strategies. As a result of these efforts, long-term continuous BMI use has been recently implicated with the induction of partial neurological recovery in spinal cord injury patients.
In this work a comprehensive study is presented for the analysis of epitaxial graphene layers using Raman spectroscopy. A wide range of graphene types is covered, from defective/polycrystalline ...single layer graphene to multilayer graphene with low defect density. On this basis the influence of strain type, Fermi level and number of layers on the Raman spectrum of graphene is investigated. A detailed view on the 2D/G dispersion and the respective slopes of uniaxially and biaxially strained graphene is given and its implications on the asymmetry of the G peak analyzed. A linear dependency of the phonon mode asymmetry on uniaxial strain is presented in addition to the known Fermi level dependence. Additional impacts on the asymmetry are found to be arising from the defect density and transfer doping of adsorbates. The discovered transfer doping mechanism is contrary to pure phonon excitation through excitons and exhibits increasing asymmetry with increasing Fermi level. A new characteristic correlation between the 2D mode line width and the inverse I(D)/I(G) ratio is introduced that allows the determination of the strain type and layer number and explains the difference between Raman line widths of monolayer graphene on different substrates.
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•Analysis of epitaxial graphene by Raman spectroscopy regarding the parameters strain, Fermi level and layer number.•2D/G phonon dispersion of biaxially strained graphene is proven to exhibit a slope of 2.2.•Asymmetry of the G mode exhibits contributions from strain and Fermi level (e.g. transfer doping or adsorbate-induced).•The correlation of the 2D line width with the I(G)/I(D) ratio is found as a new characteristic for strain type determination.
Abstract
The rapid spread of conspiracy ideas associated with the recent COVID-19 pandemic represents a major threat to the ongoing and coming vaccination programs. Yet, the cognitive factors ...underlying the pandemic-related conspiracy beliefs are not well described. We hypothesized that such cognitive style is driven by delusion proneness, a trait phenotype associated with formation of delusion-like beliefs that exists on a continuum in the normal population. To probe this hypothesis, we developed a COVID-19 conspiracy questionnaire (CCQ) and assessed 577 subjects online. Their responses clustered into three factors that included Conspiracy, Distrust and Fear/Action as identified using principal component analysis. We then showed that CCQ (in particular the Conspiracy and Distrust factors) related both to general delusion proneness assessed with Peter’s Delusion Inventory (PDI) as well as resistance to belief update using a Bias Against Disconfirmatory Evidence (BADE) task. Further, linear regression and pathway analyses suggested a specific contribution of BADE to CCQ not directly explained by PDI. Importantly, the main results remained significant when using a truncated version of the PDI where questions on paranoia were removed (in order to avoid circular evidence), and when adjusting for ADHD- and autistic traits (that are known to be substantially related to delusion proneness). Altogether, our results strongly suggest that pandemic-related conspiracy ideation is associated with delusion proneness trait phenotype.
This work is devoted to the development and optimization of the parameters of graphene-based sensors. The graphene films used in the present study were grown on semi-insulating 6H-SiC substrates by ...thermal decomposition of SiC at the temperature of ~1700 °C. The results of measurements by Auger and Raman spectroscopies confirmed the presence of single-layer graphene on the silicon carbide surface. Model approach to the theory of adsorption on epitaxial graphene is presented. It is demonstrated that the Green-function method in conjunction with the simple substrate models permit one to obtain analytical results for the charge transfer between adsorbed molecules and substrate. The sensor structure was formed on the graphene film by laser. Initially, a simpler gas sensor was made. The sensors developed in this study demonstrated sensitivity to the NO
concentration at the level of 1-0.01 ppb. The results obtained in the course of development and the results of testing of the graphene-based sensor for detection of protein molecules are also presented. The biosensor was fabricated by the technology previously developed for the gas sensor. The working capacity of the biosensor was tested with an immunochemical system constituted by fluorescein and monoclonal antibodies (mAbs) binding this dye.
The promise of transcranial direct-current stimulation (tDCS) as a modulator of cognition has appealed to researchers, media, and the general public. Researchers have suggested that tDCS may increase ...effects of cognitive training. In this study of 123 older adults, we examined the interactive effects of 20 sessions of anodal tDCS over the left prefrontal cortex (vs. sham tDCS) and simultaneous working memory training (vs. control training) on change in cognitive abilities. Stimulation did not modulate gains from pre-to posttest on latent factors of either trained or untrained tasks in a statistically significant manner. A supporting meta-analysis (n = 266), including younger as well as older individuals, showed that, when combined with training, tDCS was not much more effective than sham tDCS at changing working memory performance (g = 0.07, 95% confidence interval, or CI = -0.21, 0.34) and global cognition performance (g = -0.01, 95% CI = -0.29, 0.26) assessed in the absence of stimulation. These results question the general usefulness of current tDCS protocols for enhancing the effects of cognitive training on cognitive ability.
Hypervariable T cell receptors (TCRs) play a key role in adaptive immunity, recognizing a vast diversity of pathogen-derived antigens. Our ability to extract clinically relevant information from ...large high-throughput sequencing of TCR repertoires (RepSeq) data is limited, because little is known about TCR-disease associations. We present Antigen-specific Lymphocyte Identification by Clustering of Expanded sequences (ALICE), a statistical approach that identifies TCR sequences actively involved in current immune responses from a single RepSeq sample and apply it to repertoires of patients with a variety of disorders - patients with autoimmune disease (ankylosing spondylitis AS), under cancer immunotherapy, or subject to an acute infection (live yellow fever YF vaccine). We validate the method with independent assays. ALICE requires no longitudinal data collection nor large cohorts, and it is directly applicable to most RepSeq datasets. Its results facilitate the identification of TCR variants associated with diseases and conditions, which can be used for diagnostics and rational vaccine design.
Laboratory facilities employing high pulsed currents and voltages, and called generally "pulsed-power facilities," allow experimenters to produce a variety of hydrodynamical structures replicating, ...often in a scalable fashion, a broad range of dynamical astrophysical phenomena. Among these are astrophysical jets and outflows, astrophysical blast waves, magnetized radiatively dominated flows, and, more recently, aspects of simulated accretion disks. The magnetic field thought to play a significant role in most of the aforementioned objects is naturally present and controllable in pulsed-power environments. The size of the objects produced in pulsed-power experiments ranges from a centimeter to tens of centimeters, thereby allowing the use of a variety of diagnostic techniques. In a number of situations astrophysical morphologies can be replicated down to the finest structures. The configurations and their parameters are highly reproducible; one can vary them to isolate the most important phenomena and thereby help in developing astrophysical models. This approach has emerged as a useful tool in the quest to better understand magnetohydrodynamical effects in astronomical environments. The present review summarizes the progress made during the last decade and is designed to help readers identify and, perhaps, implement new experiments in this growing research area. Techniques used for the generation and characterization of the flows are described.
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