Retrieving shallow shear-wave velocity profiles from 2D seismic-reflection data with severely aliased surface waves

The inversion of surface-wave phase-velocity dispersion curves provides a reliable method to derive near-surface shear-wave velocity profiles. In this work, we invert phase-velocity dispersion curves estimated from 2D seismic-reflection data. These data cannot be used to image the first 50 m with seismic-reflection processing techniques due to the presence of indistinct first breaks and significant NMO-stretching of the shallow reflections. A surface-wave analysis was proposed to derive information about the near surface in order to complement the seismic-reflection stacked sections, which are satisfactory for depths between 50 and 700 m. In order to perform the analysis, we had to overcome some problems, such as the short acquisition time and the large receiver spacing, which resulted in severe spatial aliasing. The analysis consists of spatial partitioning of each line in segments, picking of the phase-velocity dispersion curves for each segment in the f-k domain, and inversion of the picked curves using the neighborhood algorithm. The spatial aliasing is successfully circumvented by continuously tracking the surface-wave modal curves in the f-k domain. This enables us to sample the curves up to a frequency of 40 Hz, even though most components beyond 10 Hz are spatially aliased. The inverted 2D VS sections feature smooth horizontal layers, and a sensitivity analysis yields a penetration depth of 20–25 m. The results suggest that long profiles may be more efficiently surveyed by using a large receiver separation and dealing with the spatial aliasing in the described way, rather than ensuring that no spatially aliased surface waves are acquired.Fil: Onnis, Luciano Emanuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; ArgentinaFil: Osella, Ana Maria. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; ArgentinaFil: Carcione, Jose M.. Istituto Nazionale di Oceanografia e di Geofisica Sperimentale; Itali

Social Network Limits Language Complexity

Natural languages vary widely in the degree to which they make use of nested compositional structure in their grammars. It has long been noted by linguists that the languages historically spoken in small communities develop much deeper levels of compositional embedding than those spoken by larger groups. Recently, this observation has been confirmed by a robust statistical analysis of the World Atlas of Language Structures. In order to examine this connection mechanistically, we propose an agent\u2010based model that accounts for key cultural evolutionary features of language transfer and language change. We identify transitivity as a physical parameter of social networks critical for the evolution of compositional structure and the hierarchical patterning of scale\u2010free distributions as inhibitory

Improved statistical learning abilities in adult bilinguals

Using multiple languages may confer distinct advantages in cognitive control, yet it is unclear whether bilingualism is associated with better implicit statistical learning, a core cognitive ability underlying language. We tested bilingual adults on a challenging task requiring simultaneous learning of two miniature grammars characterized by different statistics. We found that participants learned each grammar significantly better than chance and both grammars equally well. Crucially, a validated continuous measure of bilingual dominance predicted accuracy scores for both artificial grammars in a generalized linear model. The study thus demonstrates the first graded advantage in learning novel statistical relations in adult bilinguals

Is statistical learning trainable?

Statistical learning (SL) is the ability to implicitly extract regularities in the environment, and likely supports various higher-order behaviors, from language to music and vision. While specific patterns experience are likely to influence SL outcomes, this ability is tacitly conceptualized as a fixed construct, and few studies to date have investigated how experience may shape statistical learning. We report one experiment that directly tested whether SL can be modulated by previous experience. We used a prepost treatment design allowing us to pinpoint what specific aspects of \u201cprevious experience\u201d matter for SL. The results show that performance on an artificial grammar learning task at post-test depends on whether the grammar to be learned at post-test matches the underlying grammar structures learned during treatment. Our study is the first to adopt a pre-post test design to directly modulate the effects of learning on learning itself

Novel 2-amino-isoflavones exhibit aryl hydrocarbon receptor agonist or antagonist activity in a species/cell-specific context

The aryl hydrocarbon receptor (AhR) mediates the induction of a variety of xenobiotic metabolism genes. Activation of the AhR occurs through binding to a group of structurally diverse compounds, most notably dioxins, which are exogenous ligands. Isoflavones are part of a family which include some well characterised endogenous AhR ligands. This paper analysed a novel family of these compounds, based on the structure of 2-amino-isoflavone. Initially two luciferase-based cell models, mouse H1L6.1c2 and human HG2L6.1c3, were used to identify whether the compounds had AhR agonistic and/or antagonistic properties. This analysis showed that some of the compounds were weak agonists in mouse and antagonists in human. Further analysis of two of the compounds, Chr-13 and Chr-19, was conducted using quantitative real-time PCR in rat H4IIE and human MCF-7 cells. The results indicated that Chr-13 was an agonist in rat but an antagonist in human cells. Chr-19 was shown to be an agonist in rat but more interestingly, a partial agonist in human. Luciferase induction results not only revealed that subtle differences in the structure of the compound could produce species-specific differences in response but also dictated the ability of the compound to be an AhR agonist or antagonist. Substituted 2-amino-isoflavones represent a novel group of AhR ligands that must differentially interact with the AhR ligand binding domain to produce their species-specific agonist or antagonist activity and future ligand binding analysis and docking studies with these compounds may provide insights into the differential mechanisms of action of structurally similar compounds

A family of higher genus complete minimal surfaces that includes the Costa-Hoffman-Meeks one

In this paper, we construct a one-parameter family of minimal surfaces in the Euclidean $3$-space of arbitrarily high genus and with three ends. Each member of this family is immersed, complete and with finite total curvature. Another interesting property is that the symmetry group of the genus $k$ surfaces $\Sigma_{k,x}$ is the dihedral group with $4(k+1)$ elements. Moreover, in particular, for $|x|=1$ we find the family of the Costa-Hoffman-Meeks embedded minimal surfaces, which have two catenoidal ends and a middle flat end.Comment: 17 figures, 17 page

Statistical learning bias predicts second-language reading efficiency

Statistical learning (SL) is increasingly invoked as a set of general-purpose mechanisms upon which language learning is built during infancy and childhood. Here we investigated the extent to which SL is related to adult language processing. In particular, we asked whether SL proclivities towards relations that are more informative of English are related to efficiency in reading English sentences by native speakers of Korean. We found that individuals with a stronger statistical learning sensitivity showed a larger effect of conditional word probability on word reading times, indicating that they more efficiently incorporated statistical regularities of the language during reading. In contrast, L2 English proficiency was related to overall reading speed but not to the use of statistical regularities

Critical role for prokineticin 2 in CNS autoimmunity

Objective: To investigate the potential role of prokineticin 2 (PK2), a bioactive peptide involved in multiple biological functions including immune modulation, in CNS autoimmune demyelinating disease. Methods: We investigated the expression of PK2 in mice with experimental autoimmune encephalomyelitis (EAE), the animal model of multiple sclerosis (MS), and in patients with relapsing-remitting MS. We evaluated the biological effects of PK2 on expression of EAE and on development of T-cell response against myelin by blocking PK2 in vivo with PK2 receptor antagonists. We treated with PK2 immune cells activated against myelin antigen to explore the immune-modulating effects of this peptide in vitro. Results: Pk2 messenger RNA was upregulated in spinal cord and lymph node cells (LNCs) of mice with EAE. PK2 protein was expressed in EAE inflammatory infiltrates and was increased in sera during EAE. In patients with relapsing-remitting MS, transcripts for PK2 were significantly increased in peripheral blood mononuclear cells compared with healthy controls, and PK2 serum concentrations were significantly higher. A PK2 receptor antagonist prevented or attenuated established EAE in chronic and relapsing-remitting models, reduced CNS inflammation and demyelination, and decreased the production of interferon (IFN)-γ and interleukin (IL)-17A cytokines in LNCs while increasing IL-10. PK2 in vitro increased IFN-γ and IL-17A and reduced IL-10 in splenocytes activated against myelin antigen. Conclusion: These data suggest that PK2 is a critical immune regulator in CNS autoimmune demyelination and may represent a new target for therapy

Exploring the fatty acid amide hydrolase and cyclooxygenase inhibitory properties of novel amide derivatives of ibuprofen

Inhibition of fatty acid amide hydrolase (FAAH) reduces the gastrointestinal damage produced by non-steroidal anti-inflammatory agents such as sulindac and indomethacin in experimental animals, suggesting that a dual-action FAAH-cyclooxygenase (COX) inhibitor could have useful therapeutic properties. Here, we have investigated 12 novel amide analogues of ibuprofen as potential dual-action FAAH/COX inhibitors. N-(3-Bromopyridin-2-yl)−2-(4-isobutylphenyl)propanamide (Ibu-AM68) was found to inhibit the hydrolysis of [3H]anandamide by rat brain homogenates by a reversible, mixed-type mechanism of inhibition with a Ki value of 0.26 µM and an α value of 4.9. At a concentration of 10 µM, the compound did not inhibit the cyclooxygenation of arachidonic acid by either ovine COX-1 or human recombinant COX-2. However, this concentration of Ibu-AM68 greatly reduced the ability of the COX-2 to catalyse the cyclooxygenation of the endocannabinoid 2-arachidonoylglycerol. It is concluded that Ibu-AM68 is a dual-acting FAAH/substrate-selective COX inhibitor

Design, synthesis and in vitro and in vivo biological evaluation of flurbiprofen amides as new fatty acid amide hydrolase/cyclooxygenase-2 dual inhibitory potential analgesic agents

Compounds combining dual inhibitory action against FAAH and cyclooxygenase (COX) may be potentially useful analgesics. Here, we describe a novel flurbiprofen analogue, N-(3-bromopyridin-2-yl)-2-(2-fluoro-(1,1'-biphenyl)-4-yl)propanamide (Flu-AM4). The compound is a competitive, reversible inhibitor of FAAH with a Ki value of 13 nM and which inhibits COX activity in a substrate-selective manner. Molecular modelling suggested that Flu-AM4 optimally fits a hydrophobic pocket in the ACB region of FAAH, and binds to COX-2 similarly to flurbiprofen. In vivo studies indicated that at a dose of 10 mg/kg, Flu-AM4 was active in models of prolonged (formalin) and neuropathic (chronic constriction injury) pain and reduced the spinal expression of iNOS, COX-2, and NFκB in the neuropathic model. Thus, the present study identifies Flu-AM4 as a dual-action FAAH/substrate-selective COX inhibitor with anti-inflammatory and analgesic activity in animal pain models. These findings underscore the potential usefulness of such dual-action compounds