Cornell University

About: Cornell University is a education organization based out in Ithaca, New York, United States. It is known for research contribution in the topics: Population & Gene. The organization has 102246 authors who have published 235546 publications receiving 12283673 citations. The organization is also known as: Cornell & CUI.

Conjoint Measurement for Quantifying Judgmental Data

Abstract: Conjoint measurement is a new development in mathematical psychology that can be used to measure the joint effects of a set of independent variables on the ordering of a dependent variable. In this...

A tunable carbon nanotube electromechanical oscillator

Abstract: Nanoelectromechanical systems (NEMS) hold promise for a number of scientific and technological applications. In particular, NEMS oscillators have been proposed for use in ultrasensitive mass detection, radio-frequency signal processing, and as a model system for exploring quantum phenomena in macroscopic systems. Perhaps the ultimate material for these applications is a carbon nanotube. They are the stiffest material known, have low density, ultrasmall cross-sections and can be defect-free. Equally important, a nanotube can act as a transistor and thus may be able to sense its own motion. In spite of this great promise, a room-temperature, self-detecting nanotube oscillator has not been realized, although some progress has been made. Here we report the electrical actuation and detection of the guitar-string-like oscillation modes of doubly clamped nanotube oscillators. We show that the resonance frequency can be widely tuned and that the devices can be used to transduce very small forces.

Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization

Abstract: Gatys et al. recently introduced a neural algorithm that renders a content image in the style of another image, achieving so-called style transfer. However, their framework requires a slow iterative optimization process, which limits its practical application. Fast approximations with feed-forward neural networks have been proposed to speed up neural style transfer. Unfortunately, the speed improvement comes at a cost: the network is usually tied to a fixed set of styles and cannot adapt to arbitrary new styles. In this paper, we present a simple yet effective approach that for the first time enables arbitrary style transfer in real-time. At the heart of our method is a novel adaptive instance normalization (AdaIN) layer that aligns the mean and variance of the content features with those of the style features. Our method achieves speed comparable to the fastest existing approach, without the restriction to a pre-defined set of styles. In addition, our approach allows flexible user controls such as content-style trade-off, style interpolation, color & spatial controls, all using a single feed-forward neural network.

A net carbohydrate and protein system for evaluating cattle diets: I. Ruminal fermentation.

Abstract: The Cornell Net Carbohydrate and Protein System (CNCPS) has a kinetic submodel that predicts ruminal fermentation. The ruminal microbial population is divided into bacteria that ferment structural carbohydrate (SC) and those that ferment nonstructural carbohydrate (NSC). Protozoa are accommodated by a decrease in the theoretical maximum growth yield (.50 vs .40 g of cells per gram of carbohydrate fermented), and the yields are adjusted for maintenance requirements (.05 vs .150 g of cell dry weight per gram of carbohydrate fermented per hour for SC and NSC bacteria, respectively). Bacterial yield is decreased when forage NDF is < 20% (2.5% for every 1% decrease in NDF). The SC bacteria utilize only ammonia as a N source, but the NSC bacteria can utilize either ammonia or peptides. The yield of NSC bacteria is enhanced by as much as 18.7% when proteins or peptides are available. The NSC bacteria produce less ammonia when the carbohydrate fermentation (growth) rate is rapid, but 34% of the ammonia production is insensitive to the rate of carbohydrate fermentation. Ammonia production rates are moderated by the rate of peptide and amino acid uptake (.07 g of peptide per gram of cells per hour), and peptides and amino acids can pass out of the rumen if the rate of proteolysis is faster than the rate of peptide utilization. The protein-sparing effect of ionophores is accommodated by decreasing the rate of peptide uptake by 34%. Validation with published data of microbial flow from the rumen gave a regression with a slope of .94 and an r2 of .88.