189 research outputs found
Intensive Wheat Management for Yield and Quality: The Role of Variety, Environment, and Management Practices
Management (M), variety (V), and environment (E) greatly influence wheat yield and quality. With the objective of determining the partial influence of V, E, and M, we conducted a field experiment where we imposed four management intensities to five wheat varieties during six site-years in Kansas and Oklahoma. Management intensities were 1) low-input (N fertility for a yield goal of 60 bu/a); 2) high-input (foliar fungicide, sulfur and chloride fertilizers, growth regulator, and nitrogen (N) fertility for a yield goal of 100 bu/a); 3) high-input minus fungicide; and 4) high-input minus additional N. We selected commonly grown wheat varieties with contrasting yield potential and quality characteristics. We used a split-plot design with M as whole-plots (established in randomized complete block design), and V as sub-plot (completely randomized within whole-plot). Variance component analyses suggested that E accounted for 63% of the variability in wheat yield and 55% of the variability in grain test weight; G accounted for 1 and 23% of the variability in yield and test weight, and M accounted for 1% of the variability of both. The interactions V × G and E × M accounted for 4 and 9% of the variability in yield, and 10 and 1% of the variability in test weight, respectively. Analysis of variance pooled across the entire dataset considering V and M fixed and E random suggested a significant G × M interaction on yield, which ranged from 49–61 bu/a. Meanwhile, both V and M affected test weight, which ranged from 52–58 lb/bu for the different V and from 55–57 lb/bu for the different M. These results suggest that E has the greatest impact in yield and quality, but there is room for yield improvement through V-specific M, and for quality improvement through V and M separately
Incorporating lessons from high-input research into a low-margin year
Increased soybean commodity prices in recent years have generated interest in developing high-input systems to increase yield. However, little information exists about the effects of input-intensive, high-yield management on soybean yield and profitability, as well as interactions with basic agronomic practices
Stability of narrow beams in bulk Kerr-type nonlinear media
We consider (2+1)-dimensional beams, whose transverse size may be comparable
to or smaller than the carrier wavelength, on the basis of an extended version
of the nonlinear Schr\"{o}dinger equation derived from the Maxwell`s equations.
As this equation is very cumbersome, we also study, in parallel to it, its
simplified version which keeps the most essential term: the term which accounts
for the {\it nonlinear diffraction}. The full equation additionally includes
terms generated by a deviation from the paraxial approximation and by a
longitudinal electric-field component in the beam. Solitary-wave stationary
solutions to both the full and simplified equations are found, treating the
terms which modify the nonlinear Schr\"{o}dinger equation as perturbations.
Within the framework of the perturbative approach, a conserved power of the
beam is obtained in an explicit form. It is found that the nonlinear
diffraction affects stationary beams much stronger than nonparaxiality and
longitudinal field. Stability of the beams is directly tested by simulating the
simplified equation, with initial configurations taken as predicted by the
perturbation theory. The numerically generated solitary beams are always stable
and never start to collapse, although they display periodic internal
vibrations, whose amplitude decreases with the increase of the beam power.Comment: 7 pages, 6 figures Accepted for publication in PR
Understanding factors associated with the translation of cardiovascular research: A multinational case study approach
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.This article has been made available through the Brunel Open Access Publishing Fund.Background: Funders of health research increasingly seek to understand how best to allocate resources in order to achieve maximum value from their funding. We built an international consortium and developed a multinational case study approach to assess benefits arising from health research. We used that to facilitate analysis of factors in the production of research that might be associated with translating research findings into wider impacts, and the complexities involved. Methods: We built on the Payback Framework and expanded its application through conducting co-ordinated case studies on the payback from cardiovascular and stroke research in Australia, Canada and the United Kingdom. We selected a stratified random sample of projects from leading medical research funders. We devised a series of innovative steps to: minimize the effect of researcher bias; rate the level of impacts identified in the case studies; and interrogate case study narratives to identify factors that correlated with achieving high or low levels of impact. Results: Twenty-nine detailed case studies produced many and diverse impacts. Over the 15 to 20 years examined, basic biomedical research has a greater impact than clinical research in terms of academic impacts such as knowledge production and research capacity building. Clinical research has greater levels of wider impact on health policies, practice, and generating health gains. There was no correlation between knowledge production and wider impacts. We identified various factors associated with high impact. Interaction between researchers and practitioners and the public is associated with achieving high academic impact and translation into wider impacts, as is basic research conducted with a clinical focus. Strategic thinking by clinical researchers, in terms of thinking through pathways by which research could potentially be translated into practice, is associated with high wider impact. Finally, we identified the complexity of factors behind research translation that can arise in a single case. Conclusions: We can systematically assess research impacts and use the findings to promote translation. Research funders can justify funding research of diverse types, but they should not assume academic impacts are proxies for wider impacts. They should encourage researchers to consider pathways towards impact and engage potential research users in research processes. © 2014 Wooding et al.; licensee BioMed Central Ltd.RAND Europe and HERG, with subsequent funding from the NHFA, the HSFC and the CIHR. This research was also partially supported by the Policy Research Programme in the English Department of Health
A comparison of arbitration procedures for risk averse disputants
We propose an arbitration model framework that generalizes many previous quantitative models of final offer arbitration, conventional arbitration, and some proposed alternatives to them. Our model allows the two disputants to be risk averse and assumes that the issue(s) in dispute can be summarized by a single quantifiable value. We compare the performance of the different arbitration procedures by analyzing the gap between the disputants' equilibrium offers and the width of the contract zone that these offers imply. Our results suggest that final offer arbitration should give results superior to those of conventional arbitration.Natural Sciences & Engineering Research Council (NSERC) Discovery Gran
Academic Performance and Behavioral Patterns
Identifying the factors that influence academic performance is an essential
part of educational research. Previous studies have documented the importance
of personality traits, class attendance, and social network structure. Because
most of these analyses were based on a single behavioral aspect and/or small
sample sizes, there is currently no quantification of the interplay of these
factors. Here, we study the academic performance among a cohort of 538
undergraduate students forming a single, densely connected social network. Our
work is based on data collected using smartphones, which the students used as
their primary phones for two years. The availability of multi-channel data from
a single population allows us to directly compare the explanatory power of
individual and social characteristics. We find that the most informative
indicators of performance are based on social ties and that network indicators
result in better model performance than individual characteristics (including
both personality and class attendance). We confirm earlier findings that class
attendance is the most important predictor among individual characteristics.
Finally, our results suggest the presence of strong homophily and/or peer
effects among university students
- …