Magnetorheological landing gear: 2. Validation using experimental data

Aircraft landing gears are subjected to a wide range of excitation conditions with conflicting damping requirements. A novel solution to this problem is to implement semi-active damping using magnetorheological (MR) fluids. In part 1 of this contribution, a methodology was developed that enables the geometry of a flow mode MR valve to be optimized within the constraints of an existing passive landing gear. The device was designed to be optimal in terms of its impact performance, which was demonstrated using numerical simulations of the complete landing gear system. To perform the simulations, assumptions were made regarding some of the parameters used in the MR shock strut model. In particular, the MR fluid's yield stress, viscosity, and bulk modulus properties were not known accurately. Therefore, the present contribution aims to validate these parameters experimentally, via the manufacture and testing of an MR shock strut. The gas exponent, which is used to model the shock strut's nonlinear stiffness, is also investigated. In general, it is shown that MR fluid property data at high shear rates are required in order to accurately predict performance prior to device manufacture. Furthermore, the study illustrates how fluid compressibility can have a significant influence on the device time constant, and hence on potential control strategies

Differential Reinforcement of Alternative Behavior Increases Resistance to Extinction: Clinical Demonstration, Animal Modeling, and Clinical Test of One Solution

Basic research with pigeons on behavioral momentum suggests that differential reinforcement of alternative behavior (DRA) can increase the resistance of target behavior to change. This finding suggests that clinical applications of DRA may inadvertently increase the persistence of target behavior even as it decreases its frequency. We conducted three coordinated experiments to test whether DRA has persistence-strengthening effects on clinically significant target behavior and then tested the effectiveness of a possible solution to this problem in both a nonhuman and clinical study. Experiment 1 compared resistance to extinction following baseline rates of reinforcement versus higher DRA rates of reinforcement in a clinical study. Resistance to extinction was substantially greater following DRA. Experiment 2 tested a rat model of a possible solution to this problem. Training an alternative response in a context without reinforcement of the target response circumvented the persistence-strengthening effects of DRA. Experiment 3 translated the rat model into a novel clinical application of DRA. Training an alternative response with DRA in a separate context resulted in lower resistance to extinction than employing DRA in the context correlated with reinforcement of target behavior. The value of coordinated bidirectional translational research is discusse

Structure and Magnetism of Neutral and Anionic Palladium Clusters

The properties of neutral and anionic Pd_N clusters were investigated with spin-density-functional calculations. The ground state structures are three-dimensional for N>3 and they are magnetic with a spin-triplet for 2<=N<=7 and a spin nonet for N=13 neutral clusters. Structural- and spin-isomers were determined and an anomalous increase of the magnetic moment with temperature is predicted for a Pd_7 ensemble. Vertical electron detachment and ionization energies were calculated and the former agree well with measured values for anionic Pd_N clusters.Comment: 5 pages, 3 figures, fig. 2 in color, accepted to Phys. Rev. Lett. (2001

Deep Learning Criminal Networks

Recent advances in deep learning methods have enabled researchers to develop and apply algorithms for the analysis and modeling of complex networks. These advances have sparked a surge of interest at the interface between network science and machine learning. Despite this, the use of machine learning methods to investigate criminal networks remains surprisingly scarce. Here, we explore the potential of graph convolutional networks to learn patterns among networked criminals and to predict various properties of criminal networks. Using empirical data from political corruption, criminal police intelligence, and criminal financial networks, we develop a series of deep learning models based on the GraphSAGE framework that are capable to recover missing criminal partnerships, distinguish among types of associations, predict the amount of money exchanged among criminal agents, and even anticipate partnerships and recidivism of criminals during the growth dynamics of corruption networks, all with impressive accuracy. Our deep learning models significantly outperform previous shallow learning approaches and produce high-quality embeddings for node and edge properties. Moreover, these models inherit all the advantages of the GraphSAGE framework, including the generalization to unseen nodes and scaling up to large graph structures.Comment: 14 two-column pages, 5 figure

The relation of C - reactive protein to chronic kidney disease in African Americans: the Jackson Heart Study

<p>Abstract</p> <p>Background</p> <p>African Americans have an increased incidence and worse prognosis with chronic kidney disease (CKD - estimated glomerular filtration rate [eGFR] <60 ml/min/1.73 m²) than their counterparts of European-descent. Inflammation has been related to renal disease in non-Hispanic whites, but there are limited data on the role of inflammation in renal dysfunction in African Americans in the community.</p> <p>Methods</p> <p>We examined the cross-sectional relation of log transformed C-reactive protein (CRP) to renal function (eGFR by Modification of Diet and Renal Disease equation) in African American participants of the community-based Jackson Heart Study's first examination (2000 to 2004). We conducted multivariable linear regression relating CRP to eGFR adjusting for age, sex, body mass index, systolic and diastolic blood pressure, diabetes, total/HDL cholesterol, triglycerides, smoking, antihypertensive therapy, lipid lowering therapy, hormone replacement therapy, and prevalent cardiovascular disease events. In a secondary analysis we assessed the association of CRP with albuminuria (defined as albumin-to-creatinine ratio > 30 mg/g).</p> <p>Results</p> <p>Participants (n = 4320, 63.2% women) had a mean age ± SD of 54.0 ± 12.8 years. The prevalence of CKD was 5.2% (n = 228 cases). In multivariable regression, CRP concentrations were higher in those with CKD compared to those without CKD (mean CRP 3.2 ± 1.1 mg/L vs. 2.4 ± 1.0 mg/L, respectively p < 0.0001). CRP was significantly associated with albuminuria in sex and age adjusted model however not in the multivariable adjusted model (p > 0.05).</p> <p>Conclusion</p> <p>CRP was associated with CKD however not albuminuria in multivariable-adjusted analyses. The study of inflammation in the progression of renal disease in African Americans merits further investigation.</p

TOROS optical follow-up of the advanced LIGO–VIRGO O2 second observational campaign

We present themethods and results of the optical follow-up, conducted by the Transient Optical Robotic Observatory of the South Collaboration, of gravitational wave events detected during the Advanced LIGO–Virgo second observing run (2016 November–2017 August). Given the limited field of view (∼100 arcmin) of our observational instrumentation, we targeted galaxies within the area of high localization probability that were observable from our sites. We analysed the observations using difference imaging, followed by a random forest algorithm to discriminate between real and spurious transients. Our observations were conducted using telescopes at Estacion Astrofısica de Bosque Alegre, Cerro Tololo Inter-American Observatory, the Dr. Cristina V. Torres Memorial Astronomical Observatory, and an observing station in Salta, Argentina

Development and Validation of Risk Prediction Models for Cardiovascular Events in Black Adults: The Jackson Heart Study Cohort

Cardiovascular risk assessment is a fundamental component of prevention of cardiovascular disease (CVD). However, commonly used prediction models have been formulated in primarily or exclusively white populations. Whether risk assessment in black adults is dissimilar to that in white adults is uncertain