235 research outputs found

    Buckling of built-up columns of pultruded fiber-reinforced polymer C-sections

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    This paper presents the test results of an experimental investigation to evaluate the buckling behavior of built-up columns of pultruded profiles, subjected to axial compression. Specimens are assembled by using four (off the shelf) channel shaped profiles of E-glass fiber-reinforced polymer (FRP), having similar detailing to strut members in a large FRP structure that was executed in 2009 to start the restoration of the Santa Maria Paganica church in L’Aquila, Italy. This church had partially collapsed walls and no roof after the April 6, 2009, earthquake of 6.3 magnitude. A total of six columns are characterized with two different configurations for the bolted connections joining the channel sections into a built-up strut. Test results are discussed and a comparison is made with closed-form equation predictions for flexural buckling resistance, with buckling resistance values established from both eigenvalue and geometric nonlinear finite element analyses. Results show that there is a significant role played by the end loading condition, the composite action, and imperfections. Simple closed-form equations overestimate the flexural buckling strength, whereas the resistance provided by the nonlinear analysis provides a reasonably reliable numerical approach to establishing the actual buckling behavior

    Lower and upper probabilities in the distributive lattice of subsystems

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    yesThe set of subsystems ∑ (m) of a finite quantum system ∑(n) (with variables in Ζ(n)) together with logical connectives, is a distributive lattice. With regard to this lattice, the ℓ(m | ρn) = Tr ((m) ρn ) (where (m) is the projector to ∑(m)) obeys a supermodularity inequality, and it is interpreted as a lower probability in the sense of the Dempster–Shafer theory, and not as a Kolmogorov probability. It is shown that the basic concepts of the Dempster–Shafer theory (lower and upper probabilities and the Dempster multivaluedness) are pertinent to the quantum formalism of finite systems

    Combinatoriality in the vocal systems of nonhuman animals

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    A key challenge in the field of human language evolution is the identification of the selective conditions that gave rise to language's generative nature. Comparative data on nonhuman animals provides a powerful tool to investigate similarities and differences among nonhuman and human communication systems and to reveal convergent evolutionary mechanisms. In this article, we provide an overview of the current evidence for combinatorial structures found in the vocal system of diverse species. We show that considerable structural diversity exits across and within species in the forms of combinatorial structures used. Based on this we suggest that a fine‐grained classification and differentiation of combinatoriality is a useful approach permitting systematic comparisons across animals. Specifically, this will help to identify factors that might promote the emergence of combinatoriality and, crucially, whether differences in combinatorial mechanisms might be driven by variations in social and ecological conditions or cognitive capacities

    LensWatch: I. Resolved HST Observations and Constraints on the Strongly-Lensed Type Ia Supernova 2022qmx ("SN Zwicky")

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    Supernovae (SNe) that have been multiply-imaged by gravitational lensing are rare and powerful probes for cosmology. Each detection is an opportunity to develop the critical tools and methodologies needed as the sample of lensed SNe increases by orders of magnitude with the upcoming Vera C. Rubin Observatory and Nancy Grace Roman Space Telescope. The latest such discovery is of the quadruply-imaged Type Ia SN 2022qmx (aka, "SN Zwicky"; Goobar et al. 2022) at z = 0.3544. SN Zwicky was discovered by the Zwicky Transient Facility (ZTF) in spatially unresolved data. Here we present follow-up Hubble Space Telescope observations of SN Zwicky, the first from the multi-cycle "LensWatch" program (www.lenswatch.org). We measure photometry for each of the four images of SN Zwicky, which are resolved in three WFC3/UVIS filters (F475W, F625W, F814W) but unresolved with WFC3/IR F160W, and produce an analysis of the lensing system using a variety of independent lens modeling methods. We find consistency between time delays estimated with the single epoch of HST photometry and the lens model predictions constrained through the multiple image positions, with both inferring time delays of <1 day. Our lens models converge to an Einstein radius of (0.168+0.009-0.005)", the smallest yet seen in a lensed SN. The "standard candle" nature of SN Zwicky provides magnification estimates independent of the lens modeling that are brighter by ~1.5 mag and ~0.8 mag for two of the four images, suggesting significant microlensing and/or additional substructure beyond the flexibility of our image-position mass models

    An Agenda for Open Science in Communication

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    In the last 10 years, many canonical findings in the social sciences appear unreliable. This so-called “replication crisis” has spurred calls for open science practices, which aim to increase the reproducibility, replicability, and generalizability of findings. Communication research is subject to many of the same challenges that have caused low replicability in other fields. As a result, we propose an agenda for adopting open science practices in Communication, which includes the following seven suggestions: (1) publish materials, data, and code; (2) preregister studies and submit registered reports; (3) conduct replications; (4) collaborate; (5) foster open science skills; (6) implement Transparency and Openness Promotion Guidelines; and (7) incentivize open science practices. Although in our agenda we focus mostly on quantitative research, we also reflect on open science practices relevant to qualitative research. We conclude by discussing potential objections and concerns associated with open science practices

    Human Neural Stem Cells Differentiate and Promote Locomotor Recovery in an Early Chronic Spinal coRd Injury NOD-scid Mouse Model

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    Traumatic spinal cord injury (SCI) results in partial or complete paralysis and is characterized by a loss of neurons and oligodendrocytes, axonal injury, and demyelination/dysmyelination of spared axons. Approximately 1,250,000 individuals have chronic SCI in the U.S.; therefore treatment in the chronic stages is highly clinically relevant. Human neural stem cells (hCNS-SCns) were prospectively isolated based on fluorescence-activated cell sorting for a CD133(+) and CD24(-/lo) population from fetal brain, grown as neurospheres, and lineage restricted to generate neurons, oligodendrocytes and astrocytes. hCNS-SCns have recently been transplanted sub-acutely following spinal cord injury and found to promote improved locomotor recovery. We tested the ability of hCNS-SCns transplanted 30 days post SCI to survive, differentiate, migrate, and promote improved locomotor recovery.hCNS-SCns were transplanted into immunodeficient NOD-scid mice 30 days post spinal cord contusion injury. hCNS-SCns transplanted mice demonstrated significantly improved locomotor recovery compared to vehicle controls using open field locomotor testing and CatWalk gait analysis. Transplanted hCNS-SCns exhibited long-term engraftment, migration, limited proliferation, and differentiation predominantly to oligodendrocytes and neurons. Astrocytic differentiation was rare and mice did not exhibit mechanical allodynia. Furthermore, differentiated hCNS-SCns integrated with the host as demonstrated by co-localization of human cytoplasm with discrete staining for the paranodal marker contactin-associated protein.The results suggest that hCNS-SCns are capable of surviving, differentiating, and promoting improved locomotor recovery when transplanted into an early chronic injury microenvironment. These data suggest that hCNS-SCns transplantation has efficacy in an early chronic SCI setting and thus expands the "window of opportunity" for intervention

    Dipolar cortico-muscular electrical stimulation: a novel method that enhances motor function in both - normal and spinal cord injured mice

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    <p>Abstract</p> <p>Background</p> <p>Electrical stimulation of the central and peripheral nervous systems is a common tool that is used to improve functional recovery after neuronal injury.</p> <p>Methods</p> <p>Here we described a new configuration of electrical stimulation as it was tested in anesthetized control and spinal cord injury (SCI) mice. Constant voltage output was delivered through two electrodes. While the negative voltage output (ranging from -1.8 to -2.6 V) was delivered to the muscle via transverse wire electrodes (diameter, 500 ÎŒm) located at opposite ends of the muscle, the positive output (ranging from + 2.4 to +3.2 V) was delivered to the primary motor cortex (M1) (electrode tip, 100 ÎŒm). The configuration was named dipolar cortico-muscular stimulation (dCMS) and consisted of 100 pulses (1 ms pulse duration, 1 Hz frequency).</p> <p>Results</p> <p>In SCI animals, after dCMS, cortically-elicited muscle contraction improved markedly at the contralateral (456%) and ipsilateral (457%) gastrocnemius muscles. The improvement persisted for the duration of the experiment (60 min). The enhancement of cortically-elicited muscle contraction was accompanied by the reduction of M1 maximal threshold and the potentiation of spinal motoneuronal evoked responses at the contralateral (313%) and ipsilateral (292%) sides of the spinal cord. Moreover, spontaneous activity recorded from single spinal motoneurons was substantially increased contralaterally (121%) and ipsilaterally (54%). Interestingly, spinal motoneuronal responses and muscle twitches evoked by the test stimulation of non-treated M1 (received no dCMS) were significantly enhanced as well. Similar results obtained from normal animals albeit the changes were relatively smaller.</p> <p>Conclusion</p> <p>These findings demonstrated that dCMS could improve functionality of corticomotoneuronal pathway and thus it may have therapeutic potential.</p

    Masonry compressive strength prediction using artificial neural networks

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    The masonry is not only included among the oldest building materials, but it is also the most widely used material due to its simple construction and low cost compared to the other modern building materials. Nevertheless, there is not yet a robust quantitative method, available in the literature, which can reliably predict its strength, based on the geometrical and mechanical characteristics of its components. This limitation is due to the highly nonlinear relation between the compressive strength of masonry and the geometrical and mechanical properties of the components of the masonry. In this paper, the application of artificial neural networks for predicting the compressive strength of masonry has been investigated. Specifically, back-propagation neural network models have been used for predicting the compressive strength of masonry prism based on experimental data available in the literature. The comparison of the derived results with the experimental findings demonstrates the ability of artificial neural networks to approximate the compressive strength of masonry walls in a reliable and robust manner.- (undefined

    A Reflection on Economic Uncertainty and Fertility in Europe: The Narrative Framework

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    none5openVignoli, Daniele; Guetto, Raffaele; Bazzani, Giacomo; Pirani, Elena; Minello, AlessandraVignoli, Daniele; Guetto, Raffaele; Bazzani, Giacomo; Pirani, Elena; Minello, Alessandr

    The Science Performance of JWST as Characterized in Commissioning

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    This paper characterizes the actual science performance of the James Webb Space Telescope (JWST), as determined from the six month commissioning period. We summarize the performance of the spacecraft, telescope, science instruments, and ground system, with an emphasis on differences from pre-launch expectations. Commissioning has made clear that JWST is fully capable of achieving the discoveries for which it was built. Moreover, almost across the board, the science performance of JWST is better than expected; in most cases, JWST will go deeper faster than expected. The telescope and instrument suite have demonstrated the sensitivity, stability, image quality, and spectral range that are necessary to transform our understanding of the cosmos through observations spanning from near-earth asteroids to the most distant galaxies
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