University of Texas at Arlington

About: University of Texas at Arlington is a education organization based out in Arlington, Texas, United States. It is known for research contribution in the topics: Population & Large Hadron Collider. The organization has 11758 authors who have published 28598 publications receiving 801626 citations. The organization is also known as: UT Arlington & University of Texas-Arlington.

Higher predation risk for insect prey at low latitudes and elevations

Abstract: Biotic interactions underlie ecosystem structure and function, but predicting interaction outcomes is difficult We tested the hypothesis that biotic interaction strength increases toward the equator, using a global experiment with model caterpillars to measure predation risk Across an 11,660-kilometer latitudinal gradient spanning six continents, we found increasing predation toward the equator, with a parallel pattern of increasing predation toward lower elevations Patterns across both latitude and elevation were driven by arthropod predators, with no systematic trend in attack rates by birds or mammals These matching gradients at global and regional scales suggest consistent drivers of biotic interaction strength, a finding that needs to be integrated into general theories of herbivory, community organization, and life-history evolution

On Stellar Activity Enhancement Due to Interactions with Extrasolar Giant Planets.

Abstract: We present a first attempt to identify and quantify possible interactions between recently discovered extrasolar giant planets (and brown dwarfs) and their host stars, resulting in activity enhancement in the stellar outer atmospheres. Many extrasolar planets have masses comparable to or larger than Jupiter and are within a distance of 0.5 AU, suggesting the possibility of their significant influence on stellar winds, coronae, and even chromospheres. Beyond the well-known rotational synchronization, the interactions include tidal effects (in which enhanced flows and turbulence in the tidal bulge lead to increased magnetoacoustic heating and dynamo action) and direct magnetic interaction between the stellar and planetary magnetic fields. We discuss relevant parameters for selected systems and give preliminary estimates of the relative interaction strengths.

Neural dynamics of attentionally modulated Pavlovian conditioning: blocking, interstimulus interval, and secondary reinforcement

Abstract: Selective information processing in neural networks is studied through computer simulations of Pavlovian conditioning data. The model reproduces properties of blocking, inverted-U in learning as a function of interstimulus interval, anticipatory conditioned responses, secondary reinforcement, attentional focusing by conditioned motivational feedback, and limited capacity short-term memory processing. Conditioning occurs from sensory to drive representations (conditioned reinforcer learning), from drive to sensory representations (incentive motivational learning), and from sensory to motor representations (habit learning).The conditionable pathwas contain long-term memory traces that obey a non-Hebbian associative law. The neural model embodies a solution to two key design problems of conditioning, the synchronization and persistence problems. This model of vertebrate learning is compared with data and models of invertebrate learning. Predictions derived from models of vertebrate learning are compared with data about invertebrate learning, including data from Aplysia about facilitator neurons and data from Hermissenda about voltage-dependent Ca(2+) currents. A prediction is stated about classical conditioning in all species, called the secondary conditioning alternative, and if confirmed would constitute an evolutionary invariant of learning.

Optimal Placement of PMUs by Integer Linear Programming

Abstract: This letter presents a simple optimal placement algorithm of phasor measurement units (PMU) by using integer linear programming. Cases with and without conventional power flow and injection measurements are considered. The measurement placement problems under those cases are formulated as an integer linear programming which saves the CPU computation time greatly. Simulation results show that the proposed algorithm can be used in practice.

Exploring How Intangibility Affects Perceived Risk

Abstract: Studies have found that product intangibility increases consumers’ perception of risk. However, most of these studies measured the intangibility and perceived risk constructs unidimensionally. The primary objective of this article is to examine the effects of the multiple dimensions of intangibility on the various types of risk. An empirical investigation revealed that, of the three intangibility dimensions, physical intangibility was the least correlated to the consumers’ perception of risk in most situations, whereas mental intangibility and generality had a great impact on most dimensions of perceived risk. However, there were variations in the strength of the relationships between the intangibility dimensions and the risk dimensions when contrasting goods and services, generic products and brands, and online and offline purchase contexts. Theoretical and practical contributions to the service marketing literature are discussed.