Health-enhancing Physical Activity During Practice Among Student Football Managers at a Division I University

Objective: Student football managers have demands on their time that may pose barriers Received 5 April 2018 to meeting recommended current physical activity (PA) guidelines. The study sought to assess the amount of PA obtained by student football managers at a NCAA Division I Football university. Participants: Subjects were student football managers (n¼14) with data collected in the fall 2015. Methods: Participants wore an Omron HJ-720ITFFP pedometer for seven consecutive days during football activities only, while self-reporting their overall PA on day 7. Measures were analyzed using repeated measures and mixed-design Athletics; epidemiology; ANOVAs. Results: Managers averaged 8474 steps/day for each practice/game. All PA health education; measures significantly varied by day and manager experience. Overall PA equated to physical activity 78 hours of walking. Conclusions: Student football managers easily met and surpassed the recommended aerobic health-enhancing PA guideline. While their manager-related PA was 140 minutes per week, other PA allowed them to easily reach significantly healthy levels of PA

Sustainable Community Redevelopment: A Plan for Detroit's Lower Eastside

In the city of Detroit, decades of discrimination, unrest, and disinvestment have left scores of vacant and abandoned property and thousands of impoverished residents. This is clearly apparent in Detroit’s lower eastside, located just inside the city limits and bordered by affluent suburban Grosse Pointe Park. Here, in the heart of the lower eastside, the Jefferson East Business Association (JEBA) works to restore economic vitality as a means of revitalizing the overall conditions of the neighborhood. To aid JEBA in their strategic planning process, we developed a replicable model of sustainable community redevelopment and delivered a set of tailored suggestions for the lower eastside. Our research began with a review of national case studies relevant to six core topic areas critical to redevelopment: Economic Prosperity, Human Health & Well-Being, Vibrant Communities, Energy Systems, Material & Resource Flows, and Ecosystem Services. Through the course of our research, common principles emerged and informed the creation of the sixstep REPAIR model for sustainable community redevelopment. In this report, we demonstrate the model through application to the lower eastside, provide our resulting assessment of the neighborhood, and suggest detailed next steps for JEBA and the community. While specific guidance is provided for Detroit, the key findings are universal: First, a data-driven approach is essential in guiding proper resource usage and investment. Second, there is often a plethora of organizations working for the betterment of hard-hit urban areas. It is essential that these disparate stakeholders collaborate on a common plan to avoid redundancy and while accelerating community redevelopment. Stakeholders must rally behind a strong leader to most effectively assemble crucial resources and increase the likelihood of success. Third, a truly sustainable community will need to prepare for future challenges through mitigation and adaptation strategies. These methods must be established to increase resilience and realize true sustainably. We highlight a process of continual improvement in which metrics and indicators are regularly checked for both changes in trends and continued relevancy.Master of ScienceNatural Resources and EnvironmentUniversity of Michiganhttp://deepblue.lib.umich.edu/bitstream/2027.42/69234/1/SCR-Paper.pd

ChatGPT and Bard Responses to Polarizing Questions

Recent developments in natural language processing have demonstrated the potential of large language models (LLMs) to improve a range of educational and learning outcomes. Of recent chatbots based on LLMs, ChatGPT and Bard have made it clear that artificial intelligence (AI) technology will have significant implications on the way we obtain and search for information. However, these tools sometimes produce text that is convincing, but often incorrect, known as hallucinations. As such, their use can distort scientific facts and spread misinformation. To counter polarizing responses on these tools, it is critical to provide an overview of such responses so stakeholders can determine which topics tend to produce more contentious responses -- key to developing targeted regulatory policy and interventions. In addition, there currently exists no annotated dataset of ChatGPT and Bard responses around possibly polarizing topics, central to the above aims. We address the indicated issues through the following contribution: Focusing on highly polarizing topics in the US, we created and described a dataset of ChatGPT and Bard responses. Broadly, our results indicated a left-leaning bias for both ChatGPT and Bard, with Bard more likely to provide responses around polarizing topics. Bard seemed to have fewer guardrails around controversial topics, and appeared more willing to provide comprehensive, and somewhat human-like responses. Bard may thus be more likely abused by malicious actors. Stakeholders may utilize our findings to mitigate misinformative and/or polarizing responses from LLM

The Fourteenth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the extended Baryon Oscillation Spectroscopic Survey and from the second phase of the Apache Point Observatory Galactic Evolution Experiment

The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) has been in operation since July 2014. This paper describes the second data release from this phase, and the fourteenth from SDSS overall (making this, Data Release Fourteen or DR14). This release makes public data taken by SDSS-IV in its first two years of operation (July 2014-2016). Like all previous SDSS releases, DR14 is cumulative, including the most recent reductions and calibrations of all data taken by SDSS since the first phase began operations in 2000. New in DR14 is the first public release of data from the extended Baryon Oscillation Spectroscopic Survey (eBOSS); the first data from the second phase of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE-2), including stellar parameter estimates from an innovative data driven machine learning algorithm known as "The Cannon"; and almost twice as many data cubes from the Mapping Nearby Galaxies at APO (MaNGA) survey as were in the previous release (N = 2812 in total). This paper describes the location and format of the publicly available data from SDSS-IV surveys. We provide references to the important technical papers describing how these data have been taken (both targeting and observation details) and processed for scientific use. The SDSS website (www.sdss.org) has been updated for this release, and provides links to data downloads, as well as tutorials and examples of data use. SDSS-IV is planning to continue to collect astronomical data until 2020, and will be followed by SDSS-V.Comment: SDSS-IV collaboration alphabetical author data release paper. DR14 happened on 31st July 2017. 19 pages, 5 figures. Accepted by ApJS on 28th Nov 2017 (this is the "post-print" and "post-proofs" version; minor corrections only from v1, and most of errors found in proofs corrected

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

The Zwicky Transient Facility Census of the Local Universe. I. Systematic Search for Calcium-rich Gap Transients Reveals Three Related Spectroscopic Subclasses

Using the Zwicky Transient Facility alert stream, we are conducting a large spectroscopic campaign to construct a complete, volume-limited sample of transients brighter than 20 mag, and coincident within 100" of galaxies in the Census of the Local Universe catalog. We describe the experiment design and spectroscopic completeness from the first 16 months of operations, which have classified 754 supernovae. We present results from a systematic search for calcium-rich gap transients in the sample of 22 low-luminosity (peak absolute magnitude M > −17), hydrogen-poor events found in the experiment. We report the detection of eight new events, and constrain their volumetric rate to ≳ 15% ± 5% of the SN Ia rate. Combining this sample with 10 previously known events, we find a likely continuum of spectroscopic properties ranging from events with SN Ia–like features (Ca-Ia objects) to those with SN Ib/c–like features (Ca-Ib/c objects) at peak light. Within the Ca-Ib/c events, we find two populations distinguished by their red (g − r ≈ 1.5 mag) or green (g - r ≈ 0.5 mag) colors at the r-band peak, wherein redder events show strong line blanketing features and slower light curves (similar to Ca-Ia objects), weaker He lines, and lower [Ca ii]/[O i] in the nebular phase. We find that all together the spectroscopic continuum, volumetric rates, and striking old environments are consistent with the explosive burning of He shells on low-mass white dwarfs. We suggest that Ca-Ia and red Ca-Ib/c objects arise from the double detonation of He shells, while green Ca-Ib/c objects are consistent with low-efficiency burning scenarios like detonations in low-density shells or deflagrations