Michigan State University

About: Michigan State University is a education organization based out in East Lansing, Michigan, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 60109 authors who have published 137074 publications receiving 5633022 citations. The organization is also known as: MSU & Michigan State.

Wild Pollinators Enhance Fruit Set of Crops Regardless of Honey Bee Abundance

Abstract: The diversity and abundance of wild insect pollinators have declined in many agricultural landscapes. Whether such declines reduce crop yields, or are mitigated by managed pollinators such as honey bees, is unclear. We found universally positive associations of fruit set with flower visitation by wild insects in 41 crop systems worldwide. In contrast, fruit set increased significantly with flower visitation by honey bees in only 14% of the systems surveyed. Overall, wild insects pollinated crops more effectively; an increase in wild insect visitation enhanced fruit set by twice as much as an equivalent increase in honey bee visitation. Visitation by wild insects and honey bees promoted fruit set independently, so pollination by managed honey bees supplemented, rather than substituted for, pollination by wild insects. Our results suggest that new practices for integrated management of both honey bees and diverse wild insect assemblages will enhance global crop yields.

New Evidence on Measuring Financial Constraints: Moving Beyond the KZ Index

Abstract: We collect detailed qualitative information from financial filings to categorize financial constraints for a random sample of firms from 1995 to 2004. Using this categorization, we estimate ordered logit models predicting constraints as a function of different quantitative factors. Our findings cast serious doubt on the validity of the KZ index as a measure of financial constraints, while offering mixed evidence on the validity of other common measures of constraints. We find that firm size and age are particularly useful predictors of financial constraint levels, and we propose a measure of financial constraints that is based solely on these firm characteristics. The Author 2010. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please e-mail: journals.permissions@oxfordjournals.org., Oxford University Press.

Teams in Organizations: From Input-Process-Output Models to IMOI Models

Abstract: This review examines research and theory relevant to work groups and teams typically embedded in organizations and existing over time, although many studies reviewed were conducted in other settings, including the laboratory. Research was organized around a two-dimensional system based on time and the nature of explanatory mechanisms that mediated between team inputs and outcomes. These mechanisms were affective, behavioral, cognitive, or some combination of the three. Recent theoretical and methodological work is discussed that has advanced our understanding of teams as complex, multilevel systems that function over time, tasks, and contexts. The state of both the empirical and theoretical work is compared as to its impact on present knowledge and future directions.

Image Super-Resolution via Deep Recursive Residual Network

Abstract: Recently, Convolutional Neural Network (CNN) based models have achieved great success in Single Image Super-Resolution (SISR). Owing to the strength of deep networks, these CNN models learn an effective nonlinear mapping from the low-resolution input image to the high-resolution target image, at the cost of requiring enormous parameters. This paper proposes a very deep CNN model (up to 52 convolutional layers) named Deep Recursive Residual Network (DRRN) that strives for deep yet concise networks. Specifically, residual learning is adopted, both in global and local manners, to mitigate the difficulty of training very deep networks, recursive learning is used to control the model parameters while increasing the depth. Extensive benchmark evaluation shows that DRRN significantly outperforms state of the art in SISR, while utilizing far fewer parameters. Code is available at https://github.com/tyshiwo/DRRN_CVPR17.

The mini-IPIP scales: tiny-yet-effective measures of the Big Five factors of personality.

Abstract: The Mini-IPIP, a 20-item short form of the 50-item International Personality Item Pool-Five-Factor Model measure (Goldberg, 1999), was developed and validated across five studies. The Mini-IPIP scales, with four items per Big Five trait, had consistent and acceptable internal consistencies across five studies (= at or well above .60), similar coverage of facets as other broad Big Five measures (Study 2), and test-retest correlations that were quite similar to the parent measure across intervals of a few weeks (Study 4) and several months (Study 5). Moreover, the Mini-IPIP scales showed a comparable pattern of convergent, discriminant, and criterion-related validity (Studies 2-5) with other Big Five measures. Collectively, these results indicate that the Mini-IPIP is a psychometrically acceptable and practically useful short measure of the Big Five factors of personality.