Boise State University

About: Boise State University is a education organization based out in Boise, Idaho, United States. It is known for research contribution in the topics: Population & Computer science. The organization has 3698 authors who have published 8664 publications receiving 210163 citations. The organization is also known as: BSU & Boise State.

Factors related to physical activity adherence in women: review and suggestions for future research.

Abstract: Approximately 50 percent of individuals who start an exercise program withdraw within 6 months. Thus, many individuals withdraw before health benefits have been realized. This is a disconcerting statistic considering the well known benefits of physical activity for decreasing risk of hypokinetic diseases and improving quality of life. The literature has suggested a plethora of factors to increase the number of individuals who initiate a physical activity program. However, little is known about the factors that keep women exercising-otherwise known as exercise adherence. The purpose of this paper is to: (a) systematically review the quantitative literature to discern the major factors contributing to adherence to physical activity in women and men and make recommendations for specific gender-based considerations that are important when designing PA interventions for women, and (b) suggest areas of future research related to increasing adherence to physical activity in women. Key factors reviewed in this paper may be useful in developing efficacious physical activity programs for women.

Gender Differences in Teacher and Student Perceptions of Gifted Students' Ability and Effort.

Abstract: This study investigated whether female gifted students viewed the quality and importance of their work, effort, and ability differently than male gifted students The study also investigated whether teachers perceived male and female students differently with respect to these areas in mathematics, language arts, social studies, and science The sample included 5,385 fourth through eighth grade students who were identified as gifted and talented by their teachers Teachers consistently rated females higher than males on effort and the quality of their work Teachers rated males and females similarly on all abilities except language arts in which they rated females higher Female students rated their language arts ability higher than males while the males rated their mathematics, science, and social studies abilities higher The correlation between ratings of students' ability and quality of work and ratings of students' effort and quality of work were significantly different for students and teachers

Magnetic Structure and Ordering of Multiferroic Hexagonal LuFeO 3

Abstract: We report on the magnetic structure and ordering of hexagonal ${\mathrm{LuFeO}}_{3}$ films of variable thickness grown by molecular-beam epitaxy on YSZ (111) and ${\mathrm{Al}}_{2}{\mathrm{O}}_{3}$ (0001) substrates. These crystalline films exhibit long-range structural uniformity dominated by the polar $P{6}_{3}cm$ phase, which is responsible for the paraelectric to ferroelectric transition that occurs above 1000 K. Using bulk magnetometry and neutron diffraction, we find that the system orders into a ferromagnetically canted antiferromagnetic state via a single transition below 155 K regardless of film thickness, which is substantially lower than that previously reported in hexagonal ${\mathrm{LuFeO}}_{3}$ films. The symmetry of the magnetic structure in the ferroelectric state implies that this material is a strong candidate for linear magnetoelectric coupling and control of the ferromagnetic moment directly by an electric field.

An Image Fusion Approach Based on Markov Random Fields

Abstract: Markov random field (MRF) models are powerful tools to model image characteristics accurately and have been successfully applied to a large number of image processing applications. This paper investigates the problem of fusion of remote sensing images, e.g., multispectral image fusion, based on MRF models and incorporates the contextual constraints via MRF models into the fusion model. Fusion algorithms under the maximum a posteriori criterion are developed to search for solutions. Our algorithm is applicable to both multiscale decomposition (MD)-based image fusion and non-MD-based image fusion. Experimental results are provided to demonstrate the improvement of fusion performance by our algorithms.