University of Maine

About: University of Maine is a education organization based out in Orono, Maine, United States. It is known for research contribution in the topics: Population & Ice sheet. The organization has 8637 authors who have published 16932 publications receiving 590124 citations. The organization is also known as: University of Maine at Orono.

Frequency Dependence of Gold Nanoparticle Superassembly by Dielectrophoresis

Abstract: Dielectrophoresis is an effective method for capturing nanoparticles and assembling them into nanostructures. The frequency of the dielectrophoretic alternating current (ac) electric field greatly influences the morphology of resultant nanoparticle assemblies. In this study, frequency regimes associated with specific gold nanoparticle assembly morphologies were identified. Gold nanoparticles suspended in water were captured by microelectrodes at different electric field frequencies onto thin silicon nitride membranes. The resultant assemblies were examined by transmission electron microscopy. For this system, the major frequency-dependent influence on morphology appears to arise not from the Clausius-Mossotti factor of the dielectrophoretic force itself, but instead from ac electroosmotic fluid flow and the influence of the electrical double layer at the electrode-solution interface. Frequency regimes of technological interest include those forming one-dimensional nanoparticle chains, microwires, combinations of microwires and nanoparticle chains suitable for nanogap electrode formation, and dense three-dimensional assemblies with very high surface area.

On the Use of Comparable Corpora to Improve SMT performance

Abstract: We present a simple and effective method for extracting parallel sentences from comparable corpora. We employ a statistical machine translation (SMT) system built from small amounts of parallel texts to translate the source side of the non-parallel corpus. The target side texts are used, along with other corpora, in the language model of this SMT system. We then use information retrieval techniques and simple filters to create French/English parallel data from a comparable news corpora. We evaluate the quality of the extracted data by showing that it significantly improves the performance of an SMT systems.

Identifying Clusters of College Students at Elevated Health Risk Based on Eating and Exercise Behaviors and Psychosocial Determinants of Body Weight

Abstract: Weight gain and an increase in overweight and obesity in college students raise serious health concerns. Weight management interventions for college-age men and women might be more effective if they were tailored to subgroups of students with similar behavioral and psychosocial characteristics associated with body weight status. The purpose of this study was to use cluster analysis to identify homogenous subgroups of college-aged men and women enrolled in a weight gain prevention study (Project WebHealth) using baseline data collected in 2008. Project WebHealth was a 15-month nutrition and physical activity intervention designed to decrease the rate of unwanted weight gain in 1,689 college students at eight geographically diverse universities in the United States. Outcome measures included anthropometrics, fruit and vegetable intake, physical activity, cardiorespiratory fitness, and psychosocial variables associated with weight status in college students. Cluster analysis was performed separately by sex using a two-step clustering procedure using weight-related eating and exercise behaviors and psychosocial variables. Cluster groupings were validated against students' measured weight status and waist circumference as indicators of health risk. The study design was cross-sectional. Results showed that three similar clusters were identified for each sex. Validity of the cluster solution was supported by significant group differences in body mass index and waist circumference with the High Risk cluster at elevated health risk compared to the others. For men, variability in eating competence and cognitive restraint scores contributed most to the difference between clusters, whereas for women, emotional eating and uncontrolled eating scores did. These findings could be used to improve effectiveness of messages and interventions by tailoring them to subgroups of college students with similar behavioral and psychosocial characteristics associated with elevated health risk.

Geographic disparities and moral hazards in the predicted impacts of climate change on human populations

Abstract: Aim It has been qualitatively understood for a long time that climate change will have widely varying effects on human well-being in different regions of the world The spatial complexities underlying our relationship to climate and the geographical disparities in human demographic change have, however, precluded the development of global indices of the predicted regional impacts of climate change on humans Humans will be most negatively affected by climate change in regions where populations are strongly dependent on climate and favourable climatic conditions declineHere we use the relationship between the distribution of human population density and climate as a basis to develop the first global index of predicted impacts of climate change on human populations Location Global