Oklahoma State University–Stillwater

About: Oklahoma State University–Stillwater is a education organization based out in Stillwater, Oklahoma, United States. It is known for research contribution in the topics: Population & Large Hadron Collider. The organization has 18267 authors who have published 36743 publications receiving 1107500 citations. The organization is also known as: Oklahoma State University & OKState.

Further characterization of the E 1 ′ center in crystalline Si O 2

Abstract: Electron-spin resonance (ESR) is used to investigate the formation and thermal anneal characteristics of ${E}_{1}^{\ensuremath{'}}$ centers in high-quality synthetic quartz. These centers are produced by ionizing radiation near room temperature followed by annealing to 300\ifmmode^\circ\else\textdegree\fi{}C. The resulting concentration depends on the specific irradiation temperature, the nature of previous irradiation and thermal anneals, and whether the sample is air swept or unswept. Migration of interstitial alkali ions (${\mathrm{Li}}^{+}$ and/or ${\mathrm{Na}}^{+}$) as a result of irradiation correlates with the production of the ${E}_{1}^{\ensuremath{'}}$ centers, and a relationship between the ${[\mathrm{A}\mathrm{l}{\mathrm{O}}_{4}]}^{0}$-center concentration and the ${E}_{1}^{\ensuremath{'}}$-center concentration is also observed. Electron-nuclear double resonance is used to show that the two "weak" hyperfine interactions (8- and 9-G splittings) are with $^{29}\mathrm{Si}$ nuclei. From the angular dependence of the ESR data taken at 300 K, complete sets of spin-Hamiltonian parameters are determined for the $\stackrel{\ensuremath{\leftrightarrow}}{g}$ matrix and the three $^{29}\mathrm{Si}$ hyperfine (one strong and two weak) matrices.

Transfer Learning based Dynamic Multiobjective Optimization Algorithms

Abstract: One of the major distinguishing features of the dynamic multiobjective optimization problems (DMOPs) is the optimization objectives will change over time, thus tracking the varying Pareto-optimal front becomes a challenge. One of the promising solutions is reusing the "experiences" to construct a prediction model via statistical machine learning approaches. However most of the existing methods ignore the non-independent and identically distributed nature of data used to construct the prediction model. In this paper, we propose an algorithmic framework, called Tr-DMOEA, which integrates transfer learning and population-based evolutionary algorithm for solving the DMOPs. This approach takes the transfer learning method as a tool to help reuse the past experience for speeding up the evolutionary process, and at the same time, any population based multiobjective algorithms can benefit from this integration without any extensive modifications. To verify this, we incorporate the proposed approach into the development of three well-known algorithms, nondominated sorting genetic algorithm II (NSGA-II), multiobjective particle swarm optimization (MOPSO), and the regularity model-based multiobjective estimation of distribution algorithm (RM-MEDA), and then employ twelve benchmark functions to test these algorithms as well as compare with some chosen state-of-the-art designs. The experimental results confirm the effectiveness of the proposed method through exploiting machine learning technology.

Report on bereavement and grief research.

Abstract: focus of the project was on strengthening research on grief and bereavement with the ultimate goal of improving the care that grieving people receive. The project's mandate was to observe the field of grief research as a whole and develop strategies and recommendations to improve and support research. Goals of the project also included building connections among people working in the field and facilitating the use of research to guide the provision of the best possible care. To guide the work of the project, a scientific advisory committee (SAC) was formed, composed of senior researchers and practitioners with high credibility, broad expertise and vision. SAC members were invited to participate in round table discussions in the summer of 2001. A report of these discussions was one of the products of this project and served as a good foundation for the remaining work of the project (the report is available at www.cfah.org). The work of the project was broken into five work groups: monograph, research agenda, research funding, communication and bridging. Each group was tasked with a specific goal and objectives and SAC members elected to join a work group of their interest. The following publication would not have been possible without the contributions and significant guidance from members of the scientific advisory committee, most particularly the monograph work group of the SAC. However, the full committee was not asked to endorse the conclusions or recommendations for research included in the report, which they saw in draft form prior to final revisions before its release. Responsibility for the release version of the report rests with the Center for the Advancement of Health.

The impact of Indian job guarantee scheme on labor market outcomes: Evidence from a natural experiment

Abstract: Public works programs, aimed at building a strong social safety net through redistribution of wealth and generation of meaningful employment, are becoming increasingly popular in developing countries. The National Rural Employment Guarantee Act (NREGA), enacted in August 2005, is one such program in India. This paper assesses \emph{causal} impacts (Intent-to-Treat) of NREGA on public works participation, labor force participation, and real wages of casual workers by exploiting its phased implementation across Indian districts. Using nationally representative data from Indian National Sample Surveys (NSS) and Difference-in-Difference framework, we find that there is a strong gender dimension to the impacts of NREGA: it has a positive impact on the labor force participation and this impact is mainly driven by a much sharper impact on female labor force participation. Similarly, NREGA has a significant positive impact on the wages of female casual workers - real wages of female casual workers increased 8% more in NREGA districts compared with the increase experienced in non-NREGA districts. However, the impact of NREGA on wages of casual male workers has only been marginal (about 1%). Using data from pre-NREGA period, we also perform falsification exercise to demonstrate that the main conclusions are not confounded by pre-existing differential trends between NREGA and non-NREGA districts.

Neighborhood Disadvantage, Parent–Child Conflict, Neighborhood Peer Relationships, and Early Antisocial Behavior Problem Trajectories

Abstract: This study examined relations among neighborhood disadvantage, parent–child conflict, deviant peer involvement in the neighborhood, and early-starting antisocial trajectories Antisocial group patterns were identified in 218 low-income boys followed from ages 5 to 11, and neighborhood and family variables were evaluated as predictors in early and middle childhood Four trajectory groups emerged: one increasing pattern that corresponded with developmental theories of early-starting antisocial behavior; one with initially high and decreasing problems over time; and two low antisocial groups Parent–child conflict and neighborhood disadvantage were significantly associated with trajectory patterns, with youth in the 2 higher antisocial behavior groups characterized by more neighborhood problems and parent–child conflict than other groups The results suggest that in early childhood, neighborhood disadvantage and family conflict place children at risk for early-starting trajectories, and that involvement with deviant peers in the neighborhood takes on an increasingly important role in patterns of antisocial behavior over middle childhood