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.

Membrane lipids: where they are and how they behave.

Abstract: Throughout the biological world, a 30 A hydrophobic film typically delimits the environments that serve as the margin between life and death for individual cells. Biochemical and biophysical findings have provided a detailed model of the composition and structure of membranes, which includes levels of dynamic organization both across the lipid bilayer (lipid asymmetry) and in the lateral dimension (lipid domains) of membranes. How do cells apply anabolic and catabolic enzymes, translocases and transporters, plus the intrinsic physical phase behaviour of lipids and their interactions with membrane proteins, to create the unique compositions and multiple functionalities of their individual membranes?

Nonpoint pollution of surface waters with phosphorus and nitrogen

Abstract: Agriculture and urban activities are major sources of phosphorus and nitrogen to aquatic ecosystems. Atmospheric deposition further contributes as a source of N. These nonpoint inputs of nutrients are difficult to measure and regulate because they derive from activities dispersed over wide areas of land and are variable in time due to effects of weather. In aquatic ecosystems, these nutrients cause diverse problems such as toxic algal blooms, loss of oxygen, fish kills, loss of biodiversity (including species important for commerce and recreation), loss of aquatic plant beds and coral reefs, and other problems. Nutrient enrichment seriously degrades aquatic ecosystems and impairs the use of water for drinking, industry, agriculture, recreation, and other purposes. Based on our review of the scientific literature, we are certain that (1) eutrophication is a widespread problem in rivers, lakes, estuaries, and coastal oceans, caused by overenrichment with P and N; (2) nonpoint pollution, a major source of P and N to surface waters of the United States, results primarily from agriculture and urban activity, including industry; (3) inputs of P and N to agriculture in the form of fertilizers exceed outputs in produce in the United States and many other nations; (4) nutrient flows to aquatic ecosystems are directly related to animal stocking densities, and under high livestock densities, manure production exceeds the needs of crops to which the manure is applied; (5) excess fertilization and manure production cause a P surplus to accumulate in soil, some of which is transported to aquatic ecosystems; and (6) excess fertilization and manure production on agricultural lands create surplus N, which is mobile in many soils and often leaches to downstream aquatic ecosystems, and which can also volatilize to the atmosphere, redepositing elsewhere and eventually reaching aquatic ecosystems. If current practices continue, nonpoint pollution of surface waters is virtually certain to increase in the future. Such an outcome is not inevitable, however, because a number of technologies, land use practices, and conservation measures are capable of decreasing the flow of nonpoint P and N into surface waters. From our review of the available scientific information, we are confident that: (1) nonpoint pollution of surface waters with P and N could be reduced by reducing surplus nutrient flows in agricultural systems and processes, reducing agricultural and urban runoff by diverse methods, and reducing N emissions from fossil fuel burning; and (2) eutrophication can be reversed by decreasing input rates of P and N to aquatic ecosystems, but rates of recovery are highly variable among water bodies. Often, the eutrophic state is persistent, and recovery is slow.

Using stable isotopes to estimate trophic position: models, methods, and assumptions

Abstract: The stable isotopes of nitrogen (8'5N) and carbon (8'3C) provide powerful tools for estimating the trophic positions of and carbon flow to consumers in food webs; however, the isotopic signature of a consumer alone is not generally sufficient to infer trophic position or carbon source without an appropriate isotopic baseline. In this paper, I develop and discuss methods for generating an isotopic baseline and evaluate the assump- tions required to estimate the trophic position of consumers using stable isotopes in multiple ecosystem studies. I test the ability of two primary consumers, surface-grazing snails and filter-feeding mussels, to capture the spatial and temporal variation at the base of aquatic food webs. I find that snails reflect the isotopic signature of the base of the littoral food web, mussels reflect the isotopic signature of the pelagic food web, and together they provide a good isotopic baseline for estimating trophic position of secondary or higher trophic level consumers in lake ecosystems. Then, using data from 25 north temperate lakes, I evaluate how 815N and 8'3C of the base of aquatic food webs varies both among lakes and between the littoral and pelagic food webs within lakes. Using data from the literature, I show that the mean trophic fractionation of b'5N is 3.4%o (1 SD = 1%M) and of 8'3C is 0.4%o (1 SD = 1.3%o), and that both, even though variable, are widely applicable. A sen- sitivity analysis reveals that estimates of trophic position are very sensitive to assumptions about the trophic fractionation of '5 N, moderately sensitive to different methods for gen- erating an isotopic baseline, and not sensitive to assumptions about the trophic fractionation of 8'3C when 8'3C is used to estimate the proportion of nitrogen in a consumer derived from two sources. Finally, I compare my recommendations for generating an isotopic baseline to an alternative model proposed by M. J. Vander Zanden and J. B. Rasmussen. With an appropriate isotopic baseline and an appreciation of the underlying assumptions and model sensitivity, stable isotopes can help answer some of the most difficult questions in food web ecology.

MATPOWER: Steady-State Operations, Planning, and Analysis Tools for Power Systems Research and Education

Abstract: MATPOWER is an open-source Matlab-based power system simulation package that provides a high-level set of power flow, optimal power flow (OPF), and other tools targeted toward researchers, educators, and students. The OPF architecture is designed to be extensible, making it easy to add user-defined variables, costs, and constraints to the standard OPF problem. This paper presents the details of the network modeling and problem formulations used by MATPOWER, including its extensible OPF architecture. This structure is used internally to implement several extensions to the standard OPF problem, including piece-wise linear cost functions, dispatchable loads, generator capability curves, and branch angle difference limits. Simulation results are presented for a number of test cases comparing the performance of several available OPF solvers and demonstrating MATPOWER's ability to solve large-scale AC and DC OPF problems.

Feature Pyramid Networks for Object Detection

Abstract: Feature pyramids are a basic component in recognition systems for detecting objects at different scales. But recent deep learning object detectors have avoided pyramid representations, in part because they are compute and memory intensive. In this paper, we exploit the inherent multi-scale, pyramidal hierarchy of deep convolutional networks to construct feature pyramids with marginal extra cost. A top-down architecture with lateral connections is developed for building high-level semantic feature maps at all scales. This architecture, called a Feature Pyramid Network (FPN), shows significant improvement as a generic feature extractor in several applications. Using FPN in a basic Faster R-CNN system, our method achieves state-of-the-art single-model results on the COCO detection benchmark without bells and whistles, surpassing all existing single-model entries including those from the COCO 2016 challenge winners. In addition, our method can run at 5 FPS on a GPU and thus is a practical and accurate solution to multi-scale object detection. Code will be made publicly available.