Structural characterization of carbon nanotubes via the vibrational density of states

The electrical and chemical properties of carbon nanotubes vary significantly with different chirality and diameter, making the experimental determination of these structural properties important. Here, we show that the vibrational density of states (VDOS) contains information on the structure of carbon nanotubes, particularly at low frequencies. We show that the diameter and chirality of the nanotubes can be determined from the characteristic low frequency $L$ and $L'$ modes in the VDOS. For zigzag nanotubes, the $L$ peak splits into two peaks giving rise to another low energy $L"$ peak. The significant changes in the frequencies and relative intensities of these peaks open up a route to distinguish among structurally different nanotubes. A close study of different orientations of Stone-Wales defects with varying defect density reveals that different structural defects also leave distinct fingerprints in the VDOS, particularly in the $L$ and $L'$ modes. With our results, more structural information can be obtained from experiments which can directly measure the VDOS, such as inelastic electron and inelastic neutron spectroscopy.Comment: 5 Figures, Accepted for publication in Carbo

The 1999 Center for Simulation of Dynamic Response in Materials Annual Technical Report

Introduction: This annual report describes research accomplishments for FY 99 of the Center for Simulation of Dynamic Response of Materials. The Center is constructing a virtual shock physics facility in which the full three dimensional response of a variety of target materials can be computed for a wide range of compressive, ten- sional, and shear loadings, including those produced by detonation of energetic materials. The goals are to facilitate computation of a variety of experiments in which strong shock and detonation waves are made to impinge on targets consisting of various combinations of materials, compute the subsequent dy- namic response of the target materials, and validate these computations against experimental data

Regularization of the Roy Equations with a Smooth Cut-Off

The Roy equations for ππ scattering are combined with unitarity to give a nonlinear system of equations for the determination of the low‐energy amplitudes. A Hölder continuous interpolation between the input high‐energy absorptive parts and the output low‐energy absorptive parts is implemented; and the resultant singular equations are regularized by means of an effective inelastic N/D method. If the scattering lengths, the CDD parameters, and the high‐energy absorptive parts satisfy certain constraints, then there exists a locally unique solution of the system

'GR 7' Grape

'GR 7' is an early / mid-season red wine grape for use primarily in red wine blends. It is distinguished from other red wine grapes grown in cool climates by its high degree of winter hardiness, adaptation to mechanized production systems, and ability to survive in older plantings where other red wine grapes are lost due to tomato and tobacco ringspot virus infections. ?GR 7? is a highly productive, easy to manage cultivar, and is the sixth wine grape to be developed by the New York State Agricultural Experiment Station of Cornell University

Multimodal Pilot Behavior in Multi-Axis Tracking Tasks with Time-Varying Motion Cueing Gains

In a large number of motion-base simulators, adaptive motion filters are utilized to maximize the use of the available motion envelope of the motion system. However, not much is known about how the time-varying characteristics of such adaptive filters affect pilots when performing manual aircraft control. This paper presents the results of a study investigating the effects of time-varying motion filter gains on pilot control behavior and performance. An experiment was performed in a motion-base simulator where participants performed a simultaneous roll and pitch tracking task, while the roll and/or pitch motion filter gains changed over time. Results indicate that performance increases over time with increasing motion gains. This increase is a result of a time-varying adaptation of pilots' equalization dynamics, characterized by increased visual and motion response gains and decreased visual lead time constants. Opposite trends are found for decreasing motion filter gains. Even though the trends in both controlled axes are found to be largely the same, effects are less significant in roll. In addition, results indicate minor cross-coupling effects between pitch and roll, where a cueing variation in one axis affects the behavior adopted in the other axis

Dual Extended Kalman Filter for the Identification of Time-Varying Human Manual Control Behavior

A Dual Extended Kalman Filter was implemented for the identification of time-varying human manual control behavior. Two filters that run concurrently were used, a state filter that estimates the equalization dynamics, and a parameter filter that estimates the neuromuscular parameters and time delay. Time-varying parameters were modeled as a random walk. The filter successfully estimated time-varying human control behavior in both simulated and experimental data. Simple guidelines are proposed for the tuning of the process and measurement covariance matrices and the initial parameter estimates. The tuning was performed on simulation data, and when applied on experimental data, only an increase in measurement process noise power was required in order for the filter to converge and estimate all parameters. A sensitivity analysis to initial parameter estimates showed that the filter is more sensitive to poor initial choices of neuromuscular parameters than equalization parameters, and bad choices for initial parameters can result in divergence, slow convergence, or parameter estimates that do not have a real physical interpretation. The promising results when applied to experimental data, together with its simple tuning and low dimension of the state-space, make the use of the Dual Extended Kalman Filter a viable option for identifying time-varying human control parameters in manual tracking tasks, which could be used in real-time human state monitoring and adaptive human-vehicle haptic interfaces

Assessing breast cancer risk among Iranian women using the gail model

Background: Breast cancer risk assessment is a helpful method for estimating development of breast cancer at the population level. Materials and Methods: In this cross-sectional study, participants consisted of a group of 3,847 volunteers (mean ± SD age: 463 ± 7.59 years) in a convenience sample of women referred to health centers affiliated to Tehran University of Medical Sciences in Tehran, Iran. The risk of breast cancer was estimated by applying the National Cancer Institute's online version of the Gail Risk Assessment Tool. Results: Some 24.9 of women reported having one first-degree female relative with breast cancer, with 8.05 of them having two or more first-degree relatives with breast cancer. The mean five-year risk of breast cancer for all participants was 1.61±0.73, and 9.36 of them had a five-year risk of breast cancer > 1.66. The mean lifetime risk of breast cancer was 11.7±3.91. Conclusions: The Gail model is useful for assessing probability of breast cancer in Iranian women. Based on the their breast cancer risk, women may decide to accept further screening services

Prevalence of food security in the UK measured by the Food Insecurity Experience Scale

Background Measurement of UK food insecurity has historically been inconsistent, making it difficult to understand trends. This study contributes by reporting and analysing data from a national survey conducted in line with UN Food and Agriculture Organization (FAO) recommendations and standard methods, providing an internationally comparable pre-coronavirus disease 2019 (COVID-19) snapshot of food insecurity. Methods Data came from a nationally representative 2019 UK sample (N = 2000) surveyed by Ipsos-Mori. Prevalence of food insecurity was assessed using the UN FAO Food Insecurity Experience Scale. Logistic regression was used to model food insecurity in relation to geographic and socio-demographic variables. Results Severe food insecurity was reported by 3% of the sample, an increase of 66.7% over the last directly comparable UK analysis (Gallup World Poll data from 2016 to 2018). Indication of some degree of food insecurity was reported by 14.2% of the sample and tended to be higher amongst younger age groups, those on lower incomes, and home renters (as opposed to owners). No geographic variables were significantly associated with food insecurity prevalence. Conclusions The finding that prevalence of severe food insecurity was already increasing before the COVID-19 pandemic, across all areas of the UK, is cause for concern. Our results provide an important benchmark for assessing the impact of COVID-19 on food insecurity