Analysis of the backward bending modes in damped rotating beams

[EN] This article presents a study of the backward bending mode of a simply supported rotating Rayleigh beam with internal damping. The study analyses the natural frequency behaviour of the backward mode according to the internal viscous damping ratio, the slenderness of the beam and its spin speed. To date, the behaviour of the natural frequency of the backward mode is known to be a monotonically decreasing function with spin speed due to gyroscopic effects. In this article, however, it is shown that this behaviour of the natural frequency may not hold for certain damping and slenderness conditions, and reaches a minimum value (concave function) from which it begins to increase. Accordingly, the analytical expression of the spin speed for which the natural frequency of the backward mode attains the minimum value has been obtained. In addition, the internal damping ratio and slenderness intervals associated with such behaviour have been also provided.The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The authors gratefully acknowledge the financial support of Ministerio de Ciencia, Innovacion y Universidades Agencia Estatal de Investigacion and the European Regional Development Fund (project TRA2017-84701-R), as well as Generalitat Valenciana (project Prometeo/2016/007) and European Commission through the project 'RUN2Rail - Innovative RUNning gear soluTiOns for new dependable, sustainable, intelligent and comfortable RAIL vehicles' (Horizon 2020 Shift2Rail JU call 2017, grant number 777564)Martínez Casas, J.; Denia Guzmán, FD.; Fayos Sancho, J.; Nadal, E.; Giner Navarro, J. (2019). Analysis of the backward bending modes in damped rotating beams. Advances in Mechanical Engineering. 11(4):1-13. https://doi.org/10.1177/1687814019840474S113114Zorzi, E. S., & Nelson, H. D. (1977). Finite Element Simulation of Rotor-Bearing Systems With Internal Damping. Journal of Engineering for Power, 99(1), 71-76. doi:10.1115/1.3446254Ku, D.-M. (1998). FINITE ELEMENT ANALYSIS OF WHIRL SPEEDS FOR ROTOR-BEARING SYSTEMS WITH INTERNAL DAMPING. Mechanical Systems and Signal Processing, 12(5), 599-610. doi:10.1006/mssp.1998.0159Dimentberg, M. F. (2005). Vibration of a rotating shaft with randomly varying internal damping. Journal of Sound and Vibration, 285(3), 759-765. doi:10.1016/j.jsv.2004.11.025Vatta, F., & Vigliani, A. (2008). Internal damping in rotating shafts. Mechanism and Machine Theory, 43(11), 1376-1384. doi:10.1016/j.mechmachtheory.2007.12.009Rosales, M. B., & Filipich, C. P. (1993). Dynamic Stability of a Spinning Beam Carrying an Axial Dead Load. Journal of Sound and Vibration, 163(2), 283-294. doi:10.1006/jsvi.1993.1165Mazzei, A. J., & Scott, R. A. (2003). Effects of internal viscous damping on the stability of a rotating shaft driven through a universal joint. Journal of Sound and Vibration, 265(4), 863-885. doi:10.1016/s0022-460x(02)01256-7Ehrich, F. F. (1964). Shaft Whirl Induced by Rotor Internal Damping. Journal of Applied Mechanics, 31(2), 279-282. doi:10.1115/1.3629598Vance, J. M., & Lee, J. (1974). Stability of High Speed Rotors With Internal Friction. Journal of Engineering for Industry, 96(3), 960-968. doi:10.1115/1.3438468Vila, P., Baeza, L., Martínez-Casas, J., & Carballeira, J. (2014). Rail corrugation growth accounting for the flexibility and rotation of the wheel set and the non-Hertzian and non-steady-state effects at contact patch. Vehicle System Dynamics, 52(sup1), 92-108. doi:10.1080/00423114.2014.881513Glocker, C., Cataldi-Spinola, E., & Leine, R. I. (2009). Curve squealing of trains: Measurement, modelling and simulation. Journal of Sound and Vibration, 324(1-2), 365-386. doi:10.1016/j.jsv.2009.01.048Bauer, H. F. (1980). Vibration of a rotating uniform beam, part I: Orientation in the axis of rotation. Journal of Sound and Vibration, 72(2), 177-189. doi:10.1016/0022-460x(80)90651-3Shiau, T. N., & Hwang, J. L. (1993). Generalized Polynomial Expansion Method for the Dynamic Analysis of Rotor-Bearing Systems. Journal of Engineering for Gas Turbines and Power, 115(2), 209-217. doi:10.1115/1.2906696Hili, M. A., Fakhfakh, T., & Haddar, M. (2006). Vibration analysis of a rotating flexible shaft–disk system. Journal of Engineering Mathematics, 57(4), 351-363. doi:10.1007/s10665-006-9060-3Young, T. H., Shiau, T. N., & Kuo, Z. H. (2007). Dynamic stability of rotor-bearing systems subjected to random axial forces. Journal of Sound and Vibration, 305(3), 467-480. doi:10.1016/j.jsv.2007.04.016Wang, J., Hurskainen, V.-V., Matikainen, M. K., Sopanen, J., & Mikkola, A. (2017). On the dynamic analysis of rotating shafts using nonlinear superelement and absolute nodal coordinate formulations. Advances in Mechanical Engineering, 9(11), 168781401773267. doi:10.1177/1687814017732672Lee, C.-W. (1993). Vibration Analysis of Rotors. Solid Mechanics and Its Applications. doi:10.1007/978-94-015-8173-8Genta, G. (1999). Vibration of Structures and Machines. doi:10.1007/978-1-4612-1450-2Cheng, C. C., & Lin, J. K. (2003). Modelling a rotating shaft subjected to a high-speed moving force. Journal of Sound and Vibration, 261(5), 955-965. doi:10.1016/s0022-460x(02)01374-

Lateral Orbitofrontal Cortex Involvement in Initial Negative Aesthetic Impression Formation

It is well established that aesthetic appreciation is related with activity in several different brain regions. The identification of the neural correlates of beauty or liking ratings has been the focus of most prior studies. Not much attention has been directed towards the fact that humans are surrounded by objects that lead them to experience aesthetic indifference or leave them with a negative aesthetic impression. Here we explore the neural substrate of such experiences. Given the neuroimaging techniques that have been used, little is known about the temporal features of such brain activity. By means of magnetoencephalography we registered the moment at which brain activity differed while participants viewed images they considered to be beautiful or not. Results show that the first differential activity appears between 300 and 400 ms after stimulus onset. During this period activity in right lateral orbitofrontal cortex (lOFC) was greater while participants rated visual stimuli as not beautiful than when they rated them as beautiful. We argue that this activity is associated with an initial negative aesthetic impression formation, driven by the relative hedonic value of stimuli regarded as not beautiful. Additionally, our results contribute to the understanding of the nature of the functional roles of the lOFC

Rapid Insulinotropic Action of Low Doses of Bisphenol-A on Mouse and Human Islets of Langerhans: Role of Estrogen Receptor β

Bisphenol-A (BPA) is a widespread endocrine-disrupting chemical (EDC) used as the base compound in the manufacture of polycarbonate plastics. It alters pancreatic β-cell function and can be considered a risk factor for type 2 diabetes in rodents. Here we used ERβ−/− mice to study whether ERβ is involved in the rapid regulation of KATP channel activity, calcium signals and insulin release elicited by environmentally relevant doses of BPA (1 nM). We also investigated these effects of BPA in β-cells and whole islets of Langerhans from humans. 1 nM BPA rapidly decreased KATP channel activity, increased glucose-induced [Ca2+]i signals and insulin release in β-cells from WT mice but not in cells from ERβ−/− mice. The rapid reduction in the KATP channel activity and the insulinotropic effect was seen in human cells and islets. BPA actions were stronger in human islets compared to mouse islets when the same BPA concentration was used. Our findings suggest that BPA behaves as a strong estrogen via nuclear ERβ and indicate that results obtained with BPA in mouse β-cells may be extrapolated to humans. This supports that BPA should be considered as a risk factor for metabolic disorders in humans

Storage of Correlated Patterns in Standard and Bistable Purkinje Cell Models

The cerebellum has long been considered to undergo supervised learning, with climbing fibers acting as a ‘teaching’ or ‘error’ signal. Purkinje cells (PCs), the sole output of the cerebellar cortex, have been considered as analogs of perceptrons storing input/output associations. In support of this hypothesis, a recent study found that the distribution of synaptic weights of a perceptron at maximal capacity is in striking agreement with experimental data in adult rats. However, the calculation was performed using random uncorrelated inputs and outputs. This is a clearly unrealistic assumption since sensory inputs and motor outputs carry a substantial degree of temporal correlations. In this paper, we consider a binary output neuron with a large number of inputs, which is required to store associations between temporally correlated sequences of binary inputs and outputs, modelled as Markov chains. Storage capacity is found to increase with both input and output correlations, and diverges in the limit where both go to unity. We also investigate the capacity of a bistable output unit, since PCs have been shown to be bistable in some experimental conditions. Bistability is shown to enhance storage capacity whenever the output correlation is stronger than the input correlation. Distribution of synaptic weights at maximal capacity is shown to be independent on correlations, and is also unaffected by the presence of bistability

Integrated information increases with fitness in the evolution of animats

One of the hallmarks of biological organisms is their ability to integrate disparate information sources to optimize their behavior in complex environments. How this capability can be quantified and related to the functional complexity of an organism remains a challenging problem, in particular since organismal functional complexity is not well-defined. We present here several candidate measures that quantify information and integration, and study their dependence on fitness as an artificial agent ("animat") evolves over thousands of generations to solve a navigation task in a simple, simulated environment. We compare the ability of these measures to predict high fitness with more conventional information-theoretic processing measures. As the animat adapts by increasing its "fit" to the world, information integration and processing increase commensurately along the evolutionary line of descent. We suggest that the correlation of fitness with information integration and with processing measures implies that high fitness requires both information processing as well as integration, but that information integration may be a better measure when the task requires memory. A correlation of measures of information integration (but also information processing) and fitness strongly suggests that these measures reflect the functional complexity of the animat, and that such measures can be used to quantify functional complexity even in the absence of fitness data.Comment: 27 pages, 8 figures, one supplementary figure. Three supplementary video files available on request. Version commensurate with published text in PLoS Comput. Bio

Optimal learning rules for familiarity detection

It has been suggested that the mammalian memory system has both familiarity and recollection components. Recently, a high-capacity network to store familiarity has been proposed. Here we derive analytically the optimal learning rule for such a familiarity memory using a signalto- noise ratio analysis. We find that in the limit of large networks the covariance rule, known to be the optimal local, linear learning rule for pattern association, is also the optimal learning rule for familiarity discrimination. The capacity is independent of the sparseness of the patterns, as long as the patterns have a fixed number of bits set. The corresponding information capacity is 0.057 bits per synapse, less than typically found for associative networks

Urinary Bisphenol A and Type-2 Diabetes in U.S. Adults: Data from NHANES 2003-2008

Bisphenol A (BPA) is found in plastics and other consumer products; exposure may lead to insulin resistance and development of type-2 diabetes mellitus (T2DM) through over-activation of pancreatic β-cells. Previous studies using data from the National Health and Nutrition Examination Survey (NHANES) showed an inconsistent association between prevalence of self-reported T2DM and urinary BPA. We used a different diagnosis method of T2DM (hemoglobin A1c (HbA1c)) with a larger subset of NHANES.We analyzed data from 4,389 adult participants who were part of a sub-study of environmental phenol measurements in urine from three NHANES cycles from 2003 to 2008. T2DM was defined as having a HbA1c ≥6.5% or use of diabetes medication. The weighted prevalence of T2DM was 9.2%. Analysis of the total sample revealed that a two-fold increase in urinary BPA was associated with an odds ratio (OR) of 1.08 of T2DM (95% confidence interval (CI), 1.02 to 1.16), after controlling for potential confounders. However, when we examined each NHANES cycle individually, we only found a statistically significant association in the 2003/04 cycle (n = 1,364, OR = 1.23 (95% CI, 1.07 to 1.42) for each doubling in urinary BPA). We found no association in either the NHANES cycle from 2005/06 (n = 1,363, OR = 1.05 (95% CI, 0.94 to 1.18)); or 2007/08 (n = 1,662, OR = 1.06 (95% CI, 0.91 to 1.23)). Similar patterns of associations between BPA and continuous HbA1c were also observed.Although higher urinary BPA was associated with elevated HbA1c and T2DM in the pooled analysis, it was driven by data from only one NHANES cycle. Additional studies, especially of a longitudinal design with repeated BPA measurements, are needed to further elucidate the association between BPA and T2DM

Nonspecific synaptic plasticity improves the recognition of sparse patterns degraded by local noise

Safaryan, K. et al. Nonspecific synaptic plasticity improves the recognition of sparse patterns degraded by local noise. Sci. Rep. 7, 46550; doi: 10.1038/srep46550 (2017). This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ © The Author(s) 2017.Many forms of synaptic plasticity require the local production of volatile or rapidly diffusing substances such as nitric oxide. The nonspecific plasticity these neuromodulators may induce at neighboring non-active synapses is thought to be detrimental for the specificity of memory storage. We show here that memory retrieval may benefit from this non-specific plasticity when the applied sparse binary input patterns are degraded by local noise. Simulations of a biophysically realistic model of a cerebellar Purkinje cell in a pattern recognition task show that, in the absence of noise, leakage of plasticity to adjacent synapses degrades the recognition of sparse static patterns. However, above a local noise level of 20 %, the model with nonspecific plasticity outperforms the standard, specific model. The gain in performance is greatest when the spatial distribution of noise in the input matches the range of diffusion-induced plasticity. Hence non-specific plasticity may offer a benefit in noisy environments or when the pressure to generalize is strong.Peer reviewe

Tag-Trigger-Consolidation: A Model of Early and Late Long-Term-Potentiation and Depression

Changes in synaptic efficacies need to be long-lasting in order to serve as a substrate for memory. Experimentally, synaptic plasticity exhibits phases covering the induction of long-term potentiation and depression (LTP/LTD) during the early phase of synaptic plasticity, the setting of synaptic tags, a trigger process for protein synthesis, and a slow transition leading to synaptic consolidation during the late phase of synaptic plasticity. We present a mathematical model that describes these different phases of synaptic plasticity. The model explains a large body of experimental data on synaptic tagging and capture, cross-tagging, and the late phases of LTP and LTD. Moreover, the model accounts for the dependence of LTP and LTD induction on voltage and presynaptic stimulation frequency. The stabilization of potentiated synapses during the transition from early to late LTP occurs by protein synthesis dynamics that are shared by groups of synapses. The functional consequence of this shared process is that previously stabilized patterns of strong or weak synapses onto the same postsynaptic neuron are well protected against later changes induced by LTP/LTD protocols at individual synapses