University of Hawaii at Manoa

About: University of Hawaii at Manoa is a education organization based out in Honolulu, Hawaii, United States. It is known for research contribution in the topics: Population & Sea surface temperature. The organization has 13693 authors who have published 25161 publications receiving 1023924 citations.

Gravitaxis of asymmetric self-propelled colloidal particles

Abstract: Gravitaxis describes the ability of microorganisms to adjust their swimming motion on the gravitational field, yet its mechanism remains unclear. Here, the authors show that an asymmetric shape of colloidal particles is alone sufficient to induce gravitactic motion in the absence of density inhomogeneity.

Cox-nnet: An artificial neural network method for prognosis prediction of high-throughput omics data

Abstract: Artificial neural networks (ANN) are computing architectures with many interconnections of simple neural-inspired computing elements, and have been applied to biomedical fields such as imaging analysis and diagnosis. We have developed a new ANN framework called Cox-nnet to predict patient prognosis from high throughput transcriptomics data. In 10 TCGA RNA-Seq data sets, Cox-nnet achieves the same or better predictive accuracy compared to other methods, including Cox-proportional hazards regression (with LASSO, ridge, and mimimax concave penalty), Random Forests Survival and CoxBoost. Cox-nnet also reveals richer biological information, at both the pathway and gene levels. The outputs from the hidden layer node provide an alternative approach for survival-sensitive dimension reduction. In summary, we have developed a new method for accurate and efficient prognosis prediction on high throughput data, with functional biological insights. The source code is freely available at https://github.com/lanagarmire/cox-nnet.

Video Self-Modeling Intervention in School-Based Settings A Review

Abstract: Research indicates that video self-modeling is an effective means for improving academic skills and behaviors. Nearly 200 video self-modeling studies or applications have been reported over the past three decades. The purpose of this review was to examine studies in which video self-modeling was applied in school-based settings. Eighteen studies met strict criteria for inclusion in this review. Descriptive summaries and analyses of outcomes are provided for each study, as well as suggestions and resources for educators to implement video self-modeling interventions. These school-based studies verify the functional control of targeted academic skills and behavior(s) and support the efficacy of video self-modeling to improve student outcomes. Evidence for generalization across settings and maintenance over time is also presented.