Delayed Scattering of Solitary Waves from Interfaces in a Granular Container

In granular media, the characterization of the behavior of solitary waves around interfaces is of importance in order to look for more applications of these systems. We study the behavior of solitary waves at both interfaces of a symmetric granular container, a class of systems that has received recent attention because it posses the feature of energy trapping. Hertzian contact is assumed. We have found that the scattering process is elastic at one interface, while at the other interface it is observed that the transmitted solitary wave has stopped its movement during a time that gets longer when the ratio between masses at the interfaces increases. The origin of this effect can be traced back to the phenomenon of gaps opening, recently observed experimentally.Comment: To appear in Physical Review E, vol 7

Ultrasensitive Displacement Noise Measurement of Carbon Nanotube Mechanical Resonators

Mechanical resonators based on a single carbon nanotube are exceptional sensors of mass and force. The force sensitivity in these ultra-light resonators is often limited by the noise in the detection of the vibrations. Here, we report on an ultra-sensitive scheme based on a RLC resonator and a low-temperature amplifier to detect nanotube vibrations. We also show a new fabrication process of electromechanical nanotube resonators to reduce the separation between the suspended nanotube and the gate electrode down to $\sim 150$~nm. These advances in detection and fabrication allow us to reach $0.5~\mathrm{pm}/\sqrt{\mathrm{Hz}}$ displacement sensitivity. Thermal vibrations cooled cryogenically at 300~mK are detected with a signal-to-noise ratio as high as 17~dB. We demonstrate $4.3~\mathrm{zN}/\sqrt{\mathrm{Hz}}$ force sensitivity, which is the best force sensitivity achieved thus far with a mechanical resonator. Our work is an important step towards imaging individual nuclear spins and studying the coupling between mechanical vibrations and electrons in different quantum electron transport regimes.Comment: 9 pages, 5 figure

A fast cardiac electromechanics model coupling the Eikonal and the nonlinear mechanics equations

We present a new model of human cardiac electromechanics for the left ventricle where electrophysiology is described by a Reaction-Eikonal model and which enables an off-line resolution of the reaction model, thus entailing a big saving of computational time. Subcellular dynamics is coupled with a model of tissue mechanics, which is in turn coupled with a Windkessel model for blood circulation. Our numerical results show that the proposed model is able to provide a physiological response to changes in certain variables (end-diastolic volume, total peripheral resistance, contractility). We also show that our model is able to reproduce with high accuracy and with a considerably lower computational time the results that we would obtain if the monodomain model should be used in place of the Eikonal model

On the short-term relationship between solar soft X-ray irradiances and equatorial total electron content (TEC)

[1] The relationship between total electron content (TEC) and the solar soft X-ray irradiances is presented. Three bands ( 2 - 7 nm, 6 - 19 nm, and 17 - 20 nm) of solar soft X-ray measurements from the Student Nitric Oxide Explorer (SNOE) satellite are examined and all show a similar relationship with TEC. The TEC data are from a GPS receiver near Ancon, Peru ( - 11.78 degrees latitude, - 77.15 degrees longitude) from 11 March 1998 to 23 August 1999 and 2 October 1999 to 10 June 2000. During these periods the average TEC measurement was calculated from all observations whose ionospheric pierce point occurred within - 12 +/- 2 degrees latitude and - 77 +/- 2 degrees longitude and within the hour selected. TEC shows a more significant correlation with soft X-ray irradiances than with F10.7. The X rays lead the TEC by approximately 0.8 - 1.3 days, which is consistent with the neutral density affecting the TEC. The magnitude of these short term ( 27 days or less) changes is approximately 0.18 of the total TEC. During the period examined geomagnetic activity, as represented by Ap, could account for half as much variation in TEC (0.1 of the total TEC) as the solar irradiance

Mining Posets from Linear Orders

There has been much research on the combinatorial problem of generating the linear extensions of a given poset. This paper focuses on the reverse of that problem, where the input is a set of linear orders, and the goal is to construct a poset or set of posets that generates the input. Such a problem finds applications in computational neuroscience, systems biology, paleontology, and physical plant engineering. In this paper, several algorithms are presented for efficiently finding a single poset that generates the input set of linear orders. The variation of the problem where a minimum set of posets that cover the input is also explored. It is found that the problem is polynomially solvable for one class of simple posets (kite(2) posets) but NP-complete for a related class (hammock(2,2,2) posets)

A note about the quantum of area in a non-commutative space

In this note we show that in a two-dimensional non-commutative space the area operator is quantized, this outcome is compared with the result obtained by Loop Quantum Gravity methods.Comment: 6 pages, references added, minor correction

Feature selection for chemical sensor arrays using mutual information

We address the problem of feature selection for classifying a diverse set of chemicals using an array of metal oxide sensors. Our aim is to evaluate a filter approach to feature selection with reference to previous work, which used a wrapper approach on the same data set, and established best features and upper bounds on classification performance. We selected feature sets that exhibit the maximal mutual information with the identity of the chemicals. The selected features closely match those found to perform well in the previous study using a wrapper approach to conduct an exhaustive search of all permitted feature combinations. By comparing the classification performance of support vector machines (using features selected by mutual information) with the performance observed in the previous study, we found that while our approach does not always give the maximum possible classification performance, it always selects features that achieve classification performance approaching the optimum obtained by exhaustive search. We performed further classification using the selected feature set with some common classifiers and found that, for the selected features, Bayesian Networks gave the best performance. Finally, we compared the observed classification performances with the performance of classifiers using randomly selected features. We found that the selected features consistently outperformed randomly selected features for all tested classifiers. The mutual information filter approach is therefore a computationally efficient method for selecting near optimal features for chemical sensor arrays

Intrathoracic impedance and pulmonary wedge pressure for the detection of heart failure deterioration

n/

Stock comovement and financial flexibility

We develop a dynamic model of corporate investment and financing, in which shocks to the value of collateralizable assets generate variation in firms’ debt capacity. We show that the degree of similarity among firms’ financial flexibility forecasts cross-sectional variation in return correlation. We test the implications of the model with firm-level data in two empirical analyses using i) an instrumental variable approach based on shocks to the value of collateralizable corporate assets and ii) the outbreak of the COVID-19 crisis as an event study. We find that firms in the same percentile of the cross-sectional distribution of financial flexibility have 62% higher correlation in stock-return residuals than firms 50 percentiles apart

Characterization of Sequential Collagen-Poly(Ethylene Glycol) Diacrylate Interpenetrating Networks and Initial Assessment of Their Potential for Vascular Tissue Engineering

Collagen hydrogels have been widely investigated as scaffolds for vascular tissue engineering due in part to the capacity of collagen to promote robust cell adhesion and elongation. However, collagen hydrogels display relatively low stiffness and strength, are thrombogenic, and are highly susceptible to cell-mediated contraction. In the current work, we develop and characterize a sequentially-formed interpenetrating network (IPN) that retains the benefits of collagen, but which displays enhanced mechanical stiffness and strength, improved thromboresistance, high physical stability and resistance to contraction. In this strategy, we first form a collagen hydrogel, infuse this hydrogel with poly(ethylene glycol) diacrylate (PEGDA), and subsequently crosslink the PEGDA by exposure to longwave UV light. These collagen-PEGDA IPNs allow for cell encapsulation during the fabrication process with greater than 90% cell viability via inclusion of cells within the collagen hydrogel precursor solution. Furthermore, the degree of cell spreading within the IPNs can be tuned from rounded to fully elongated by varying the time delay between the formation of the cell-laden collagen hydrogel and the formation of the PEGDA network. We also demonstrate that these collagen-PEGDA IPNs are able to support the initial stages of smooth muscle cell lineage progression by elongated human mesenchymal stems cells