Young Adult E-Cigarette Exposure: Implications for Policy and Prevention

Objective. The purpose of this study is to examine factors associated with e-cigarette use among college students to better understand their behavior. Using Ajzen’s Reasoned Action Approach, this study sought to better understanding the influence of attitudes, Social norms, and perceived behavioral controls (PBCs) on college students’ intention to try e-cigarettes (even one puff) in the next 30 days. Methodology. This study employed three phases for a mixed methods design that took place between December 2015 and April 2016. Phase 1 used Middlestadt’s salient belief elicitation procedure to capture responses through an open ended survey (n=58). Phase 2, a pilot sample (n=49), was employed to develop and validate a quantitative measure of the underlying RAA constructs, using responses from Phase 1. For Phase 3, a convenience samples (n=499) allowed for the assessment of the measurement models of both the underlying and global constructs of the RAA using exploratory factor analysis, confirmatory factor analysis, and structural equation modeling. All samples consisted of University of Arkansas students between the ages of 18 and 26 years of age. Results. Responses from Phase 1 were used to develop a 162 item measure of the underlying constructs that was reduced to 78 items during Phase 2. During Phase 3, the underlying constructs, attitude, injunctive norms, and PBC were found to significantly predict their respective global measure. Global constructs loaded onto the predicted four factors: intent, attitude, Social norms and PBC, after removing six items. In the final path model, global constructs attitude (.27, p Conclusion. The RAA allows for a better understanding of the values and beliefs people have about a given behavior and how these beliefs influence behavioral intention. College students’ attitudes toward e-cigarettes (e.g., cessation device, fear of addiction) may influence their intention to try these products. Moreover, disapproving referents (e.g., family, parents, and friends) may discourage the use of e-cigarettes for some college students

REACT: Recognize Every Action Everywhere All At Once

Group Activity Recognition (GAR) is a fundamental problem in computer vision, with diverse applications in sports video analysis, video surveillance, and social scene understanding. Unlike conventional action recognition, GAR aims to classify the actions of a group of individuals as a whole, requiring a deep understanding of their interactions and spatiotemporal relationships. To address the challenges in GAR, we present REACT (\textbf{R}ecognize \textbf{E}very \textbf{Act}ion Everywhere All At Once), a novel architecture inspired by the transformer encoder-decoder model explicitly designed to model complex contextual relationships within videos, including multi-modality and spatio-temporal features. Our architecture features a cutting-edge Vision-Language Encoder block for integrated temporal, spatial, and multi-modal interaction modeling. This component efficiently encodes spatiotemporal interactions, even with sparsely sampled frames, and recovers essential local information. Our Action Decoder Block refines the joint understanding of text and video data, allowing us to precisely retrieve bounding boxes, enhancing the link between semantics and visual reality. At the core, our Actor Fusion Block orchestrates a fusion of actor-specific data and textual features, striking a balance between specificity and context. Our method outperforms state-of-the-art GAR approaches in extensive experiments, demonstrating superior accuracy in recognizing and understanding group activities. Our architecture's potential extends to diverse real-world applications, offering empirical evidence of its performance gains. This work significantly advances the field of group activity recognition, providing a robust framework for nuanced scene comprehension.Comment: 10 pages, 4 figures, 5 table

Observing the Evolution of the Universe

How did the universe evolve? The fine angular scale (l>1000) temperature and polarization anisotropies in the CMB are a Rosetta stone for understanding the evolution of the universe. Through detailed measurements one may address everything from the physics of the birth of the universe to the history of star formation and the process by which galaxies formed. One may in addition track the evolution of the dark energy and discover the net neutrino mass. We are at the dawn of a new era in which hundreds of square degrees of sky can be mapped with arcminute resolution and sensitivities measured in microKelvin. Acquiring these data requires the use of special purpose telescopes such as the Atacama Cosmology Telescope (ACT), located in Chile, and the South Pole Telescope (SPT). These new telescopes are outfitted with a new generation of custom mm-wave kilo-pixel arrays. Additional instruments are in the planning stages.Comment: Science White Paper submitted to the US Astro2010 Decadal Survey. Full list of 177 author available at http://cmbpol.uchicago.ed

SoGAR: Self-supervised Spatiotemporal Attention-based Social Group Activity Recognition

This paper introduces a novel approach to Social Group Activity Recognition (SoGAR) using Self-supervised Transformers network that can effectively utilize unlabeled video data. To extract spatio-temporal information, we create local and global views with varying frame rates. Our self-supervised objective ensures that features extracted from contrasting views of the same video are consistent across spatio-temporal domains. Our proposed approach is efficient in using transformer-based encoders for alleviating the weakly supervised setting of group activity recognition. By leveraging the benefits of transformer models, our approach can model long-term relationships along spatio-temporal dimensions. Our proposed SoGAR method achieves state-of-the-art results on three group activity recognition benchmarks, namely JRDB-PAR, NBA, and Volleyball datasets, surpassing the current state-of-the-art in terms of F1-score, MCA, and MPCA metrics.Comment: 32 pages, 7 figures. arXiv admin note: text overlap with arXiv:2303.1214

The Origin of the Universe as Revealed Through the Polarization of the Cosmic Microwave Background

Modern cosmology has sharpened questions posed for millennia about the origin of our cosmic habitat. The age-old questions have been transformed into two pressing issues primed for attack in the coming decade: How did the Universe begin? and What physical laws govern the Universe at the highest energies? The clearest window onto these questions is the pattern of polarization in the Cosmic Microwave Background (CMB), which is uniquely sensitive to primordial gravity waves. A detection of the special pattern produced by gravity waves would be not only an unprecedented discovery, but also a direct probe of physics at the earliest observable instants of our Universe. Experiments which map CMB polarization over the coming decade will lead us on our first steps towards answering these age-old questions

Identification of seven new prostate cancer susceptibility loci through a genome-wide association study

Prostate cancer (PrCa) is the most frequently diagnosed male cancer in developed countries. To identify common PrCa susceptibility alleles, we have previously conducted a genome-wide association study in which 541, 129 SNPs were genotyped in 1,854 PrCa cases with clinically detected disease and 1,894 controls. We have now evaluated promising associations in a second stage, in which we genotyped 43,671 SNPs in 3,650 PrCa cases and 3,940 controls, and a third stage, involving an additional 16,229 cases and 14,821 controls from 21 studies. In addition to previously identified loci, we identified a further seven new prostate cancer susceptibility loci on chromosomes 2, 4, 8, 11, and 22 (P=1.6×10−8 to P=2.7×10−33)