1,354,149 research outputs found
Fidelity-Outcomes Relationships in the Expect Respect Program
No full textThe effects of program fidelity, gender, socioeconomic status, and school level were tested on various outcomes of a dating violence prevention program, Expect Respect. Fidelity data was collected from program facilitators, and individual posttest scores were gathered for individuals nested within each programmatic site. Multiple HLM models indicated that main effects for fidelity were present for the knowledge gained outcome scale, such that higher program fidelity led to higher posttest scores for participants. No other site level predictors affected outcomes or the fidelity-outcome relationship. Results from this study point towards the importance of implementing program fidelity when cognitive gains are a central goal of the program, whereas a more flexible program approach may be more optimal in conveying other programmatic components
MOOSS: Mask-Enhanced Temporal Contrastive Learning for Smooth State Evolution in Visual Reinforcement Learning
No full textIn visual Reinforcement Learning (RL), learning from pixel-based observations poses significant challenges on sample efficiency, primarily due to the complexity of extracting informative state representations from high-dimensional data. Previous methods such as contrastive-based approaches have made strides in improving sample efficiency but fall short in modeling the nuanced evolution of states. To address this, we introduce MOOSS, a novel framework that leverages a temporal contrastive objective with the help of graph-based spatial-temporal masking to explicitly model state evolution in visual RL. Specifically, we propose a self-supervised dual-component strategy that integrates (1) a graph construction of pixel-based observations for spatial-temporal masking, coupled with (2) a multi-level contrastive learning mechanism that enriches state representations by emphasizing temporal continuity and change of states. MOOSS advances the understanding of state dynamics by disrupting and learning from spatial-temporal correlations, which facilitates policy learning. Our comprehensive evaluation on multiple continuous and discrete control benchmarks shows that MOOSS outperforms previous state-of-the-art visual RL methods in terms of sample efficiency, demonstrating the effectiveness of our method. Our code is released at https://github.com/jsun57/MOOSS.WACV 202
Reversible Stress Cardiomyopathy Presenting as Acute Coronary Syndrome with Elevated Troponin in the Absence of Regional Wall Motion Abnormalities: A Forme Fruste of Stress Cardiomyopathy?
No full textWe present a case of reversible stress cardiomyopathy in a surgical patient, described here as a forme fruste due to its atypical features. It is important to recognize such unusual presentation of stress cardiomyopathy that mimics acute coronary syndrome. Stress cardiomyopathy commonly presents as acute coronary syndrome and is characterized by typical or atypical variants of regional wall motion abnormalities. We report a 60-year-old Caucasian male with reversible stress cardiomyopathy following a sternal fracture fixation. Although the patient had several typical features of stress cardiomyopathy including physical stress, ST-segment elevation, elevated cardiac biomarkers and normal epicardial coronaries, there were few features that were atypical, including unusual age, gender, absence of regional wall motion abnormalities, high lateral ST elevation, and high troponin-ejection fraction product. In conclusion, this could represent a forme fruste of stress cardiomyopathy
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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