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1. Trends in Northern Hemispheric Snow Presence

Author

Jia, Yisu, Lund, Robert, Kong, Jiajie, Dyer, Jamie, Woody, Jonathan, and Marron, J. S.

Subjects
Statistics - Applications
Abstract

This paper develops a mathematical model and statistical methods to quantify trends in presence/absence observations of snow cover (not depths) and applies these in an analysis of Northern Hemispheric observations extracted from satellite flyovers during 1967-2021. A two-state Markov chain model with periodic dynamics is introduced to analyze changes in the data in a grid by grid fashion. Trends, converted to the number of weeks of snow cover lost/gained per century, are estimated for each study grid. Uncertainty margins for these trends are developed from the model and used to assess the significance of the trend estimates. Grids with questionable data quality are identified. Among trustworthy grids, snow presence is seen to be declining in almost twice as many grids as it is advancing. While Arctic and southern latitude snow presence is found to be rapidly receding, other locations, such as Eastern Canada, are experiencing advancing snow cover.

Published
2022

2. Utilizing Quantitative Analyses of Active Learning Assignments to Assess Learning and Retention in a General Biology Course

Author

Dyer, Jamie O. and Elsenpeter, Ryan L.

Abstract

Numerous studies have examined the use of active learning methods in undergraduate courses, suggesting that these methods increase learning and retention as well as student engagement. In order to investigate the benefits of particular active learning assignments involving presentations of 3-dimensional simulations in an introductory biology course for science majors, quantitative analyses of the effects of these assignments on learning and retention as assessed by unit and final exam scores were performed. Same student populations and varying student populations across multiple semesters were compared using t-test analyses, single factor ANOVA analyses, and Pearson correlation coefficients. These statistical analyses determined the simulation assignments as compared to other active learning assignments resulted in no consistent significant increase in learning or retention of material covered by these assignments for same student populations and varying student populations across multiple semesters. Based on these results, the simulation assignments were replaced with other active learning assignments and additional assessment found no significant difference in the learning and retention of course material. The approach described in this study can be used for other assignments in introductory majors' biology courses, as well as other courses to assess the effectiveness of course assignments for student learning and retention.

Published
2018

3. The Spectroscopic Signature of Variability in High-Redshift Quasars

Author

Dyer, Jamie C., Dawson, Kyle S., Bourboux, Hélion du Mas des, Vivek, M., Bizyaev, Dmitry, Oravetz, Audrey, Pan, Kaike, and Schneider, Donald P.

Subjects
Astrophysics - Astrophysics of Galaxies, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

Using 16,421 spectra from a sample of 340 quasars ($1.62

Published
2018
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4. 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

Author

Abolfathi, Bela, Aguado, D. S., Aguilar, Gabriela, Prieto, Carlos Allende, Almeida, Andres, Ananna, Tonima Tasnim, Anders, Friedrich, Anderson, Scott F., Andrews, Brett H., Anguiano, Borja, Aragon-Salamanca, Alfonso, Argudo-Fernandez, Maria, Armengaud, Eric, Ata, Metin, Aubourg, Eric, Avila-Reese, Vladimir, Badenes, Carles, Bailey, Stephen, Balland, Christophe, Barger, Kathleen A., Barrera-Ballesteros, Jorge, Bartosz, Curtis, Bastien, Fabienne, Bates, Dominic, Baumgarten, Falk, Bautista, Julian, Beaton, Rachael, Beers, Timothy C., Belfiore, Francesco, Bender, Chad F., Bernardi, Mariangela, Bershady, Matthew A., Beutler, Florian, Bird, Jonathan C., Bizyaev, Dmitry, Blanc, Guillermo A., Blanton, Michael R., Blomqvist, Michael, Bolton, Adam S., Boquien, Mederic, Borissova, Jura, Bovy, Jo, Diaz, Christian Andres Bradna, Brandt, William Nielsen, Brinkmann, Jonathan, Brownstein, Joel R., Bundy, Kevin, Burgasser, Adam J., Burtin, Etienne, Busca, Nicolas G., Canas, Caleb I., Cano-Diaz, Mariana, Cappellari, Michele, Carrera, Ricardo, Casey, Andrew R., Sodi, Bernardo Cervantes, Chen, Yanping, Cherinka, Brian, Chiappini, Cristina, Choi, Peter Doohyun, Chojnowski, Drew, Chuang, Chia-Hsun, Chung, Haeun, Clerc, Nicolas, Cohen, Roger E., Comerford, Julia M., Comparat, Johan, Nascimento, Janaina Correa do, da Costa, Luiz, Cousinou, Marie-Claude, Covey, Kevin, Crane, Jeffrey D., Cruz-Gonzalez, Irene, Cunha, Katia, Ilha, Gabriele da Silva, Damke, Guillermo J., Darling, Jeremy, Davidson Jr., James W., Dawson, Kyle, Lizaola, Miguel Angel C. de Icaza, de la Macorra, Axel, de la Torre, Sylvain, De Lee, Nathan, Agathe, Victoria de Sainte, Machado, Alice Deconto, Dell'Agli, Flavia, Delubac, Timothee, Diamond-Stanic, Aleksandar M., Donor, John, Downes, Juan Jose, Drory, Niv, Bourboux, Helion du Mas des, Duckworth, Christopher J., Dwelly, Tom, Dyer, Jamie, Ebelke, Garrett, Eigenbrot, Arthur Davis, Eisenstein, Daniel J., Elsworth, Yvonne P., Emsellem, Eric, Eracleous, Mike, Erfanianfar, Ghazaleh, Escoffier, Stephanie, Fan, Xiaohui, Alvar, Emma Fernandez, Fernandez-Trincado, J. G., Cirolini, Rafael Fernando, Feuillet, Diane, Finoguenov, Alexis, Fleming, Scott W., Font-Ribera, Andreu, Freischlad, Gordon, Frinchaboy, Peter, Fu, Hai, Chew, Yilen Gomez Maqueo, Galbany, Lluis, Perez, Ana E. Garcia, Garcia-Dias, R., Garcia-Hernandez, D. A., Oehmichen, Luis Alberto Garma, Gaulme, Patrick, Gelfand, Joseph, Gil-Marin, Hector, Gillespie, Bruce A., Goddard, Daniel, Hernandez, Jonay I. Gonzalez, Gonzalez-Perez, Violeta, Grabowski, Kathleen, Green, Paul J., Grier, Catherine J., Gueguen, Alain, Guo, Hong, Guy, Julien, Hagen, Alex, Hall, Patrick, Harding, Paul, Hasselquist, Sten, Hawley, Suzanne, Hayes, Christian R., Hearty, Fred, Hekker, Saskia, Hernandez, Jesus, Toledo, Hector Hernandez, Hogg, David W., Holley-Bockelmann, Kelly, Holtzman, Jon, Hou, Jiamin, Hsieh, Bau-Ching, Hunt, Jason A. S., Hutchinson, Timothy A., Hwang, Ho Seong, Angel, Camilo Eduardo Jimenez, Johnson, Jennifer A., Jones, Amy, Jonsson, Henrik, Jullo, Eric, Khan, Fahim Sakil, Kinemuchi, Karen, Kirkby, David, Kirkpatrick IV, Charles C., Kitaura, Francisco-Shu, Knapp, Gillian R., Kneib, Jean-Paul, Kollmeier, Juna A., Lacerna, Ivan, Lane, Richard R., Lang, Dustin, Law, David R., Goff, Jean-Marc Le, Lee, Young-Bae, Li, Hongyu, Li, Cheng, Lian, Jianhui, Liang, Yu, Lima, Marcos, Lin, Lihwai, Long, Dan, Lucatello, Sara, Lundgren, Britt, Mackereth, J. Ted, MacLeod, Chelsea L., Mahadevan, Suvrath, Maia, Marcio Antonio Geimba, Majewski, Steven, Manchado, Arturo, Maraston, Claudia, Mariappan, Vivek, Marques-Chaves, Rui, Masseron, Thomas, Masters, Karen L., McDermid, Richard M., McGreer, Ian D., Melendez, Matthew, Meneses-Goytia, Sofia, Merloni, Andrea, Merrifield, Michael R., Meszaros, Szabolcs, Meza, Andres, Minchev, Ivan, Minniti, Dante, Mueller, Eva-Maria, Muller-Sanchez, Francisco, Muna, Demitri, Munoz, Ricardo R., Myers, Adam D., Nair, Preethi, Nandra, Kirpal, Ness, Melissa, Newman, Jeffrey A., Nichol, Robert C., Nidever, David L., Nitschelm, Christian, Noterdaeme, Pasquier, O'Connell, Julia, Oelkers, Ryan James, Oravetz, Audrey, Oravetz, Daniel, Ortiz, Erik Aquino, Osorio, Yeisson, Pace, Zach, Padilla, Nelson, Palanque-Delabrouille, Nathalie, Palicio, Pedro Alonso, Pan, Hsi-An, Pan, Kaike, Parikh, Taniya, Paris, Isabelle, Park, Changbom, Peirani, Sebastien, Pellejero-Ibanez, Marcos, Penny, Samantha, Percival, Will J., Perez-Fournon, Ismael, Petitjean, Patrick, Pieri, Matthew M., Pinsonneault, Marc, Pisani, Alice, Prada, Francisco, Prakash, Abhishek, Queiroz, Anna Barbara de Andrade, Raddick, M. Jordan, Raichoor, Anand, Rembold, Sandro Barboza, Richstein, Hannah, Riffel, Rogemar A., Riffel, Rogerio, Rix, Hans-Walter, Robin, Annie C., Torres, Sergio Rodriguez, Roman-Zuniga, Carlos, Ross, Ashley J., Rossi, Graziano, Ruan, John, Ruggeri, Rossana, Ruiz, Jose, Salvato, Mara, Sanchez, Ariel G., Sanchez, Sebastian F., Almeida, Jorge Sanchez, Sanchez-Gallego, Jose R., Rojas, Felipe Antonio Santana, Santiago, Basilio Xavier, Schiavon, Ricardo P., Schimoia, Jaderson S., Schlafly, Edward, Schlegel, David, Schneider, Donald P., Schuster, William J., Schwope, Axel, Seo, Hee-Jong, Serenelli, Aldo, Shen, Shiyin, Shen, Yue, Shetrone, Matthew, Shull, Michael, Aguirre, Victor Silva, Simon, Joshua D., Skrutskie, Mike, Slosar, Anze, Smethurst, Rebecca, Smith, Verne, Sobeck, Jennifer, Somers, Garrett, Souter, Barbara J., Souto, Diogo, Spindler, Ashley, Stark, David V., Stassun, Keivan, Steinmetz, Matthias, Stello, Dennis, Storchi-Bergmann, Thaisa, Streblyanska, Alina, Stringfellow, Guy, Suarez, Genaro, Sun, Jing, Szigeti, Laszlo, Taghizadeh-Popp, Manuchehr, Talbot, Michael S., Tang, Baitian, Tao, Charling, Tayar, Jamie, Tembe, Mita, Teske, Johanna, Thaker, Aniruddha R., Thomas, Daniel, Tissera, Patricia, Tojeiro, Rita, Tremonti, Christy, Troup, Nicholas W., Urry, Meg, Valenzuela, O., Bosch, Remco van den, Vargas-Gonzalez, Jaime, Vargas-Magana, Mariana, Vazquez, Jose Alberto, Villanova, Sandro, Vogt, Nicole, Wake, David, Wang, Yuting, Weaver, Benjamin Alan, Weijmans, Anne-Marie, Weinberg, David H., Westfall, Kyle B., Whelan, David G., Wilcots, Eric, Wild, Vivienne, Williams, Rob A., Wilson, John, Wood-Vasey, W. M., Wylezalek, Dominika, Xiao, Ting, Yan, Renbin, Yang, Meng, Ybarra, Jason E., Yeche, Christophe, Zakamska, Nadia, Zamora, Olga, Zarrouk, Pauline, Zasowski, Gail, Zhang, Kai, Zhao, Cheng, Zhao, Gong-Bo, Zheng, Zheng, Zhou, Zhi-Min, Zhu, Guangtun, Zinn, Joel C., and Zou, Hu

Subjects
Astrophysics - Astrophysics of Galaxies, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract

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)

Published
2017
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5. Characterizing Asymptotic Dependence between a Satellite Precipitation Product and Station Data in the Northern US Rocky Mountains via the Tail Dependence Regression Framework With a Gibbs Posterior Inference Approach.

Author

Russell, Brook T., Ding, Yiren, Huang, Whitney K., and Dyer, Jamie L.

Subjects
EXTREME value theory, REGRESSION analysis, TELEMETRY, HETEROGENEITY
Abstract

The use of satellite precipitation products (SPP) allows for precipitation information to be collected nearly globally, but questions remain regarding their ability to reproduce extreme precipitation over mountainous terrain. In this work, we assess the ability of the precipitation estimation from remotely sensed information using artificial neural networks‐climate data record (PERSIANN‐CDR) to capture daily precipitation extremes by comparing PERSIANN‐CDR with corresponding station data in the summer at remote locations in the northern US Rocky Mountains of Wyoming, Idaho, and Montana. The assessment utilizes the regular variation framework from extreme value theory and consists of two parts: (1) evaluating the extent to which PERSIANN‐CDR can capture precipitation extremes through inference on an asymptotic dependence parameter, concluding that the level of asymptotic dependence is moderate throughout the region; (2) developing a tail dependence regression modeling framework and a Gibbs posterior approach for inference to investigate the degree to which elevation and topographic heterogeneity impact the level of asymptotic dependence, finding that the inclusion of a set of meteorological covariates, when combined with the PERSIANN‐CDR output, yields an increased level of asymptotic dependence with station data. [ABSTRACT FROM AUTHOR]

Published
2024
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6. 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

Author

Abolfathi, Bela, Aguado, DS, Aguilar, Gabriela, Prieto, Carlos Allende, Almeida, Andres, Ananna, Tonima Tasnim, Anders, Friedrich, Anderson, Scott F, Andrews, Brett H, Anguiano, Borja, Aragón-Salamanca, Alfonso, Argudo-Fernández, Maria, Armengaud, Eric, Ata, Metin, Aubourg, Eric, Avila-Reese, Vladimir, Badenes, Carles, Bailey, Stephen, Balland, Christophe, Barger, Kathleen A, Barrera-Ballesteros, Jorge, Bartosz, Curtis, Bastien, Fabienne, Bates, Dominic, Baumgarten, Falk, Bautista, Julian, Beaton, Rachael, Beers, Timothy C, Belfiore, Francesco, Bender, Chad F, Bernardi, Mariangela, Bershady, Matthew A, Beutler, Florian, Bird, Jonathan C, Bizyaev, Dmitry, Blanc, Guillermo A, Blanton, Michael R, Blomqvist, Michael, Bolton, Adam S, Boquien, Médéric, Borissova, Jura, Bovy, Jo, Diaz, Christian Andres Bradna, Brandt, William Nielsen, Brinkmann, Jonathan, Brownstein, Joel R, Bundy, Kevin, Burgasser, Adam J, Burtin, Etienne, Busca, Nicolás G, Cañas, Caleb I, Cano-Díaz, Mariana, Cappellari, Michele, Carrera, Ricardo, Casey, Andrew R, Sodi, Bernardo Cervantes, Chen, Yanping, Cherinka, Brian, Chiappini, Cristina, Choi, Peter Doohyun, Chojnowski, Drew, Chuang, Chia-Hsun, Chung, Haeun, Clerc, Nicolas, Cohen, Roger E, Comerford, Julia M, Comparat, Johan, do Nascimento, Janaina Correa, da Costa, Luiz, Cousinou, Marie-Claude, Covey, Kevin, Crane, Jeffrey D, Cruz-Gonzalez, Irene, Cunha, Katia, da Silva Ilha, Gabriele, Damke, Guillermo J, Darling, Jeremy, Davidson, James W, Dawson, Kyle, de Icaza Lizaola, Miguel Angel C, de la Macorra, Axel, de la Torre, Sylvain, De Lee, Nathan, de Sainte Agathe, Victoria, Machado, Alice Deconto, Dell’Agli, Flavia, Delubac, Timothée, Diamond-Stanic, Aleksandar M, Donor, John, Downes, Juan José, Drory, Niv, du Mas des Bourboux, Hélion, Duckworth, Christopher J, Dwelly, Tom, Dyer, Jamie, Ebelke, Garrett, Eigenbrot, Arthur Davis, Eisenstein, Daniel J, Elsworth, Yvonne P, and Emsellem, Eric

Subjects
Astronomical Sciences, Physical Sciences, atlases, catalogs, surveys, astro-ph.GA, astro-ph.IM, Astronomical and Space Sciences, Atomic, Molecular, Nuclear, Particle and Plasma Physics, Physical Chemistry (incl. Structural), Astronomy & Astrophysics, Astronomical sciences
Abstract

The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) has been in operation since 2014 July. This paper describes the second data release from this phase, and the 14th from SDSS overall (making this Data Release Fourteen or DR14). This release makes the data taken by SDSS-IV in its first two years of operation (2014-2016 July) public. 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; 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 the 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 web site (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.

Published
2018

8. Sloan Digital Sky Survey IV: Mapping the Milky Way, Nearby Galaxies, and the Distant Universe

Author

Blanton, Michael R., Bershady, Matthew A., Abolfathi, Bela, Albareti, Franco D., Prieto, Carlos Allende, Almeida, Andres, Alonso-García, Javier, Anders, Friedrich, Anderson, Scott F., Andrews, Brett, Aquino-Ortíz, Erik, Aragón-Salamanca, Alfonso, Argudo-Fernández, Maria, Armengaud, Eric, Aubourg, Eric, Avila-Reese, Vladimir, Badenes, Carles, Bailey, Stephen, Barger, Kathleen A., Barrera-Ballesteros, Jorge, Bartosz, Curtis, Bates, Dominic, Baumgarten, Falk, Bautista, Julian, Beaton, Rachael, Beers, Timothy C., Belfiore, Francesco, Bender, Chad F., Berlind, Andreas A., Bernardi, Mariangela, Beutler, Florian, Bird, Jonathan C., Bizyaev, Dmitry, Blanc, Guillermo A., Blomqvist, Michael, Bolton, Adam S., Boquien, Médéric, Borissova, Jura, Bosch, Remco van den, Bovy, Jo, Brandt, William N., Brinkmann, Jonathan, Brownstein, Joel R., Bundy, Kevin, Burgasser, Adam J., Burtin, Etienne, Busca, Nicolás G., Cappellari, Michele, Carigi, Maria Leticia Delgado, Carlberg, Joleen K., Rosell, Aurelio Carnero, Carrera, Ricardo, Cherinka, Brian, Cheung, Edmond, Chew, Yilen Gómez Maqueo, Chiappini, Cristina, Choi, Peter Doohyun, Chojnowski, Drew, Chuang, Chia-Hsun, Chung, Haeun, Cirolini, Rafael Fernando, Clerc, Nicolas, Cohen, Roger E., Comparat, Johan, da Costa, Luiz, Cousinou, Marie-Claude, Covey, Kevin, Crane, Jeffrey D., Croft, Rupert A. C., Cruz-Gonzalez, Irene, Cuadra, Daniel Garrido, Cunha, Katia, Damke, Guillermo J., Darling, Jeremy, Davies, Roger, Dawson, Kyle, de la Macorra, Axel, De Lee, Nathan, Delubac, Timothée, Di Mille, Francesco, Diamond-Stanic, Aleks, Cano-Díaz, Mariana, Donor, John, Downes, Juan José, Drory, Niv, Bourboux, Hélion du Mas des, Duckworth, Christopher J., Dwelly, Tom, Dyer, Jamie, Ebelke, Garrett, Eisenstein, Daniel J., Emsellem, Eric, Eracleous, Mike, Escoffier, Stephanie, Evans, Michael L., Fan, Xiaohui, Fernández-Alvar, Emma, Fernandez-Trincado, J. G., Feuillet, Diane K., Finoguenov, Alexis, Fleming, Scott W., Font-Ribera, Andreu, Fredrickson, Alexander, Freischlad, Gordon, Frinchaboy, Peter M., Galbany, Lluís, Garcia-Dias, R., García-Hernández, D. A., Gaulme, Patrick, Geisler, Doug, Gelfand, Joseph D., Gil-Marín, Héctor, Gillespie, Bruce A., Goddard, Daniel, Gonzalez-Perez, Violeta, Grabowski, Kathleen, Green, Paul J., Grier, Catherine J., Gunn, James E., Guo, Hong, Guy, Julien, Hagen, Alex, Hahn, ChangHoon, Hall, Matthew, Harding, Paul, Hasselquist, Sten, Hawley, Suzanne L., Hearty, Fred, Hernández, Jonay I. Gonzalez, Ho, Shirley, Hogg, David W., Holley-Bockelmann, Kelly, Holtzman, Jon A., Holzer, Parker H., Huehnerhoff, Joseph, Hutchinson, Timothy A., Hwang, Ho Seong, Ibarra-Medel, Héctor J., Ilha, Gabriele da Silva, Ivans, Inese I., Ivory, KeShawn, Jackson, Kelly, Jensen, Trey W., Johnson, Jennifer A., Jones, Amy, Jönsson, Henrik, Jullo, Eric, Kamble, Vikrant, Kinemuchi, Karen, Kirkby, David, Kitaura, Francisco-Shu, Klaene, Mark, Knapp, Gillian R., Kneib, Jean-Paul, Kollmeier, Juna A., Lacerna, Ivan, Lane, Richard R., Lang, Dustin, Law, David R., Lazarz, Daniel, Goff, Jean-Marc Le, Liang, Fu-Heng, Li, Cheng, LI, Hongyu, Lima, Marcos, Lin, Lihwai, Lin, Yen-Ting, de Lis, Sara Bertran, Liu, Chao, Lizaola, Miguel Angel C. de Icaza, Long, Dan, Lucatello, Sara, Lundgren, Britt, MacDonald, Nicholas K., Machado, Alice Deconto, MacLeod, Chelsea L., Mahadevan, Suvrath, Maia, Marcio Antonio Geimba, Maiolino, Roberto, Majewski, Steven R., Malanushenko, Elena, Malanushenko, Viktor, Manchado, Arturo, Mao, Shude, Maraston, Claudia, Marques-Chaves, Rui, Masters, Karen L., McBride, Cameron K., McDermid, Richard M., McGrath, Brianne, McGreer, Ian D., Peña, Nicolás Medina, Melendez, Matthew, Merloni, Andrea, Merrifield, Michael R., Meszaros, Szabolcs, Meza, Andres, Minchev, Ivan, Minniti, Dante, Miyaji, Takamitsu, More, Surhud, Mulchaey, John, Müller-Sánchez, Francisco, Muna, Demitri, Munoz, Ricardo R., Myers, Adam D., Nair, Preethi, Nandra, Kirpal, Nascimento, Janaina Correa do, Negrete, Alenka, Ness, Melissa, Newman, Jeffrey A., Nichol, Robert C., Nidever, David L., Nitschelm, Christian, Ntelis, Pierros, O'Connell, Julia E., Oelkers, Ryan J., Oravetz, Audrey, Oravetz, Daniel, Pace, Zach, Padilla, Nelson, Palanque-Delabrouille, Nathalie, Palicio, Pedro Alonso, Pan, Kaike, Parikh, Taniya, Pâris, Isabelle, Park, Changbom, Patten, Alim Y., Peirani, Sebastien, Pellejero-Ibanez, Marcos, Penny, Samantha, Percival, Will J., Perez-Fournon, Ismael, Petitjean, Patrick, Pieri, Matthew M., Pinsonneault, Marc, Pisani, Alice, Poleski, Radosław, Prada, Francisco, Prakash, Abhishek, Queiroz, Anna Bárbara de Andrade, Raddick, M. Jordan, Raichoor, Anand, Rembold, Sandro Barboza, Richstein, Hannah, Riffel, Rogemar A., Riffel, Rogério, Rix, Hans-Walter, Robin, Annie C., Rockosi, Constance M., Rodríguez-Torres, Sergio, Roman-Lopes, A., Román-Zúñiga, Carlos, Rosado, Margarita, Ross, Ashley J., Rossi, Graziano, Ruan, John, Ruggeri, Rossana, Rykoff, Eli S., Salazar-Albornoz, Salvador, Salvato, Mara, Sánchez, Ariel G., Aguado, David Sánchez, Sánchez-Gallego, José R., Santana, Felipe A., Santiago, Basílio Xavier, Sayres, Conor, Schiavon, Ricardo P., Schimoia, Jaderson da Silva, Schlafly, Edward F., Schlegel, David J., Schneider, Donald P., Schultheis, Mathias, Schuster, William J., Schwope, Axel, Seo, Hee-Jong, Shao, Zhengyi, Shen, Shiyin, Shetrone, Matthew, Shull, Michael, Simon, Joshua D., Skinner, Danielle, Skrutskie, M. F., Slosar, Anže, Smith, Verne V., Sobeck, Jennifer S., Sobreira, Flavia, Somers, Garrett, Souto, Diogo, Stark, David V., Stassun, Keivan, Stauffer, Fritz, Steinmetz, Matthias, Storchi-Bergmann, Thaisa, Streblyanska, Alina, Stringfellow, Guy S., Suárez, Genaro, Sun, Jing, Suzuki, Nao, Szigeti, Laszlo, Taghizadeh-Popp, Manuchehr, Tang, Baitian, Tao, Charling, Tayar, Jamie, Tembe, Mita, Teske, Johanna, Thakar, Aniruddha R., Thomas, Daniel, Thompson, Benjamin A., Tinker, Jeremy L., Tissera, Patricia, Tojeiro, Rita, Toledo, Hector Hernandez, de la Torre, Sylvain, Tremonti, Christy, Troup, Nicholas W., Valenzuela, Octavio, Valpuesta, Inma Martinez, Vargas-González, Jaime, Vargas-Magaña, Mariana, Vazquez, Jose Alberto, Villanova, Sandro, Vivek, M., Vogt, Nicole, Wake, David, Walterbos, Rene, Wang, Yuting, Weaver, Benjamin Alan, Weijmans, Anne-Marie, Weinberg, David H., Westfall, Kyle B., Whelan, David G., Wild, Vivienne, Wilson, John, Wood-Vasey, W. M., Wylezalek, Dominika, Xiao, Ting, Yan, Renbin, Yang, Meng, Ybarra, Jason E., Yèche, Christophe, Zakamska, Nadia, Zamora, Olga, Zarrouk, Pauline, Zasowski, Gail, Zhang, Kai, Zhao, Gong-Bo, Zheng, Zheng, Zhou, Zhi-Min, Zhu, Guangtun B., Zoccali, Manuela, and Zou, Hu

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

We describe the Sloan Digital Sky Survey IV (SDSS-IV), a project encompassing three major spectroscopic programs. The Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2) is observing hundreds of thousands of Milky Way stars at high resolution and high signal-to-noise ratio in the near-infrared. The Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey is obtaining spatially-resolved spectroscopy for thousands of nearby galaxies (median redshift of z = 0.03). The extended Baryon Oscillation Spectroscopic Survey (eBOSS) is mapping the galaxy, quasar, and neutral gas distributions between redshifts z = 0.6 and 3.5 to constrain cosmology using baryon acoustic oscillations, redshift space distortions, and the shape of the power spectrum. Within eBOSS, we are conducting two major subprograms: the SPectroscopic IDentification of eROSITA Sources (SPIDERS), investigating X-ray AGN and galaxies in X-ray clusters, and the Time Domain Spectroscopic Survey (TDSS), obtaining spectra of variable sources. All programs use the 2.5-meter Sloan Foundation Telescope at Apache Point Observatory; observations there began in Summer 2014. APOGEE-2 also operates a second near-infrared spectrograph at the 2.5-meter du Pont Telescope at Las Campanas Observatory, with observations beginning in early 2017. Observations at both facilities are scheduled to continue through 2020. In keeping with previous SDSS policy, SDSS-IV provides regularly scheduled public data releases; the first one, Data Release 13, was made available in July 2016., Comment: Published in Astronomical Journal

Published
2017
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10. Sloan Digital Sky Survey IV: Mapping the Milky Way, Nearby Galaxies, and the Distant Universe

Author

Blanton, Michael R, Bershady, Matthew A, Abolfathi, Bela, Albareti, Franco D, Prieto, Carlos Allende, Almeida, Andres, Alonso-García, Javier, Anders, Friedrich, Anderson, Scott F, Andrews, Brett, Aquino-Ortíz, Erik, Aragón-Salamanca, Alfonso, Argudo-Fernández, Maria, Armengaud, Eric, Aubourg, Eric, Avila-Reese, Vladimir, Badenes, Carles, Bailey, Stephen, Barger, Kathleen A, Barrera-Ballesteros, Jorge, Bartosz, Curtis, Bates, Dominic, Baumgarten, Falk, Bautista, Julian, Beaton, Rachael, Beers, Timothy C, Belfiore, Francesco, Bender, Chad F, Berlind, Andreas A, Bernardi, Mariangela, Beutler, Florian, Bird, Jonathan C, Bizyaev, Dmitry, Blanc, Guillermo A, Blomqvist, Michael, Bolton, Adam S, Boquien, Médéric, Borissova, Jura, van den Bosch, Remco, Bovy, Jo, Brandt, William N, Brinkmann, Jonathan, Brownstein, Joel R, Bundy, Kevin, Burgasser, Adam J, Burtin, Etienne, Busca, Nicolás G, Cappellari, Michele, Carigi, Maria Leticia Delgado, Carlberg, Joleen K, Rosell, Aurelio Carnero, Carrera, Ricardo, Chanover, Nancy J, Cherinka, Brian, Cheung, Edmond, Chew, Yilen Gómez Maqueo, Chiappini, Cristina, Choi, Peter Doohyun, Chojnowski, Drew, Chuang, Chia-Hsun, Chung, Haeun, Cirolini, Rafael Fernando, Clerc, Nicolas, Cohen, Roger E, Comparat, Johan, da Costa, Luiz, Cousinou, Marie-Claude, Covey, Kevin, Crane, Jeffrey D, Croft, Rupert AC, Cruz-Gonzalez, Irene, Cuadra, Daniel Garrido, Cunha, Katia, Damke, Guillermo J, Darling, Jeremy, Davies, Roger, Dawson, Kyle, de la Macorra, Axel, Dell’Agli, Flavia, De Lee, Nathan, Delubac, Timothée, Di Mille, Francesco, Diamond-Stanic, Aleks, Cano-Díaz, Mariana, Donor, John, Downes, Juan José, Drory, Niv, du Mas des Bourboux, Hélion, Duckworth, Christopher J, Dwelly, Tom, Dyer, Jamie, Ebelke, Garrett, Eigenbrot, Arthur D, Eisenstein, Daniel J, Emsellem, Eric, Eracleous, Mike, Escoffier, Stephanie, Evans, Michael L, Fan, Xiaohui, and Fernández-Alvar, Emma

Subjects
Space Sciences, Astronomical Sciences, Physical Sciences, cosmology: observations, galaxies: general, Galaxy: general, instrumentation: spectrographs, stars: general, surveys, astro-ph.GA, Astronomical and Space Sciences, Astronomy & Astrophysics, Astronomical sciences, Particle and high energy physics
Abstract

We describe the Sloan Digital Sky Survey IV (SDSS-IV), a project encompassing three major spectroscopic programs. The Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2) is observing hundreds of thousands of Milky Way stars at high resolution and high signal-to-noise ratios in the near-infrared. The Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey is obtaining spatially resolved spectroscopy for thousands of nearby galaxies (median z ∼ 0.03). The extended Baryon Oscillation Spectroscopic Survey (eBOSS) is mapping the galaxy, quasar, and neutral gas distributions between z ~ 0.6 and 3.5 to constrain cosmology using baryon acoustic oscillations, redshift space distortions, and the shape of the power spectrum. Within eBOSS, we are conducting two major subprograms: the SPectroscopic IDentification of eROSITA Sources (SPIDERS), investigating X-ray AGNs and galaxies in X-ray clusters, and the Time Domain Spectroscopic Survey (TDSS), obtaining spectra of variable sources. All programs use the 2.5 m Sloan Foundation Telescope at the Apache Point Observatory; observations there began in Summer 2014. APOGEE-2 also operates a second near-infrared spectrograph at the 2.5 m du Pont Telescope at Las Campanas Observatory, with observations beginning in early 2017. Observations at both facilities are scheduled to continue through 2020. In keeping with previous SDSS policy, SDSS-IV provides regularly scheduled public data releases; the first one, Data Release 13, was made available in 2016 July.

Published
2017

12. Teachers' Geoscience Career Knowledge and Implications for Enhancing Diversity in the Geosciences

Author

Sherman-Morris, Kathleen, Brown, Michael E., Dyer, Jamie L., McNeal, Karen S., and Rodgers, John C., III

Abstract

This study examines discrepancies between geoscience career knowledge and biology career knowledge among Mississippi science teachers. Principals and in-service teachers were also surveyed about their perception of geoscience careers and majors. Scores were higher for knowledge of what biologists do (at work) than about what geoscientists do. Career knowledge was enhanced by race, where African American teachers perceived higher biology career knowledge and lower geoscience career knowledge than other races; however, the difference was not significant. Teachers also rated their personal knowledge of 12 of the 2010 Earth and Space Science Content Strand topics. Perceived knowledge of geoscience concepts was significantly less than knowledge of more environmental topics. Race was not significant, but differences between the two topics were enhanced by race. Perceived knowledge of geoscience topics was also significantly lower among female educators across all ethnicities. Because of the lack of Earth science classes taught before college and the demonstrated gaps in geoscience career knowledge even among science teachers, strengthening geoscience career awareness as well as increasing geoscience content knowledge among science teachers would be useful overall, as well as in attempts to enhance diversity in the geosciences.

Published
2013

20. Application of multivariate storage model to quantify trends in seasonally frozen soil

Author

Woody Jonathan, Wang Yan, and Dyer Jamie

Subjects
seasonally frozen soil, climate change, geostatistics, storage model, stochastic model, Geology, QE1-996.5
Abstract

This article presents a study of the ground thermal regime recorded at 11 stations in the North Dakota Agricultural Network. Particular focus is placed on detecting trends in the annual ground freeze process portion of the ground thermal regime’s daily temperature signature. A multivariate storage model from queuing theory is fit to a quantity of estimated daily depths of frozen soil. Statistical inference on a trend parameter is obtained by minimizing a weighted sum of squares of a sequence of daily one-step-ahead predictions. Standard errors for the trend estimates are presented. It is shown that the daily quantity of frozen ground experienced at these 11 sites exhibited a negative trend over the observation period.

Published
2016
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24. Seasonal changes of trace elements, nutrients, dissolved organic matter, and coastal acidification over the largest oyster reef in the Western Mississippi Sound, USA

Author

Sankar, M. S., primary, Dash, Padmanava, additional, Lu, YueHan, additional, Hu, Xinping, additional, Mercer, Andrew E., additional, Wickramarathna, Sudeera, additional, Beshah, Wondimagegn T., additional, Sanders, Scott L., additional, Arslan, Zikri, additional, Dyer, Jamie, additional, and Moorhead, Robert J., additional

Published
2022
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26. Professional Development Strategies to Enhance Diversity in the Geosciences

Author

Sherman-Morris, Kathleen, Rodgers, John C., III, McNeal, Karen S., Brown, Michael E., and Dyer, Jamie L.

Abstract

Because of the historically low numbers of minorities in geoscience careers and college majors, an area of growing attention is how teacher professional development may be utilized to increase diversity in the geosciences (Pecore et al., 2007; Sedlock & Metzger, 2007). This paper examines teacher preferences for the timing, location and content of professional development, and how certain characteristics of professional development may contribute to or diminish the goal of increasing diversity in the geosciences. The results of two surveys of Mississippi science teachers indicate that African American teachers have distinct preferences for the location of the professional development as well as specific opinions about the outdoors. Despite the common practice of using field experiences to attract individuals to the geosciences, those African American science teachers who were surveyed more frequently chose laboratory experiences than outdoor or field-based professional development. Preferences of rural and urban/suburban participants were also compared. Urban/suburban participants expressed greater enjoyment in being outdoors than rural participants, but neither group was more likely to prefer professional development in the field or in a lab. Results of spatial clustering showed less preference for outdoor learning activities in the high-minority Mississippi Delta. (Contains 1 table and 5 figures.)

Published
2012

34. A Southeastern United States Warm Season Precipitation Climatology Using Unsupervised Learning.

Author

Mercer, Andrew and Dyer, Jamie

Subjects
CLIMATOLOGY, TROPICAL cyclones, EL Nino, PRINCIPAL components analysis, SEASONS, CLUSTER analysis (Statistics)
Abstract

Agriculture in the southeastern United States (SEUS) is heavily reliant upon water resources provided by precipitation during the warm season (June–August). The convective and stochastic nature of SEUS warm season precipitation introduces challenges in terms of water availability in the region by creating localized maxima and minima. Clearly, a detailed and updated warm season precipitation climatology for the SEUS is important for end users reliant on these water resources. As such, a nonlinear unsupervised learning method (kernel principal component analysis blended with cluster analysis) was used to develop a NARR-derived SEUS warm season precipitation climatology. Three clusters resulted from the analysis, all of which strongly resembled the mean spatially (r > 0.9) but had widely variable precipitation magnitude, as one cluster denoted a mean pattern, one a dry pattern, and one a wet pattern. The clusters were related back to major SEUS warm season precipitation moderators (tropical cyclone landfall and the El Niño–southern oscillation (ENSO)) and revealed a clearer ENSO relationship when discriminating among the cluster patterns. Ultimately, these updated SEUS precipitation patterns can help end users identify areas of notable sensitivity to different climate phenomena, helping to optimize the economic use of these critical water resources. [ABSTRACT FROM AUTHOR]

Published
2023
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39. Seasonal Changes of Trace Metal-Nutrient-Dissolved Organic Matter Conveyance Along with Coastal Acidification Over the Largest Oyster Reef in Western Mississippi Sound, Northern Gulf of Mexico

Author

Sankar, M. S., primary, Dash, Padmanava, additional, Lu, YueHan, additional, Hu, Xinping, additional, Mercer, Andrew E., additional, Wickramarathna, Sudeera, additional, Beshah, Wondimagegn T., additional, Sanders, Landon, additional, Arslan, Zikri, additional, Dyer, Jamie, additional, and Moorhead, Robert J., additional

Published
2021
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43. Big Data Text Summarization - Attack Westminster

Author

Gallagher, Colm, Dyer, Jamie, Liebold, Jeanine, Becker, Aaron, and Yang, Limin

Subjects
Pointer-generator Network, LSA, text summarization, extractive summary, abstractive summary, TextRank, natural language processing, Westminster Attack
Abstract

Automatic text summarization, a process of distilling the most important information from a text document, is to create an abridged summary with software. Basically, in this task, we can regard the "summarization" as a function which takes a single document or multiple documents as an input and has the summary as an output. There are two ways that we can manage to create a summary: extractive and abstractive. The extractive summarization means that we select the most relevant sentences from the input and concatenate them to form a summary. Graph-based algorithm like TextRank, Feature-based models like TextTeaser, Topic-based models like Latent Semantic Analysis (LSA), and Grammar-based models could be viewed as approaches to extractive summarization. Abstractive summarization aims to create a summary similar to humans. It keeps the original intent, but uses new phrases and words not found in the original text. One of the most commonly used models is the encoder-decoder model, a neural network model that is mainly used in machine translation tasks. Recently, there is another combination approach that combines both extractive and abstractive summarization, like Pointer-Generator Network, and the Extract then Abstract model. In this course, we're given both a small dataset (about 500 documents) and a big dataset (about 11,300 documents) that mainly consist of web archives about a specific event. Our group is focusing on reports about a terrorist event -- Attack Westminster. It occurred outside the Palace of Westminster in London on March 22, 2017. The attacker, 52 year-old Briton Khalid Masood, drove a car into pedestrians on the pavement, injuring more than 50 people, 5 of them fatally. The attack was treated as "Islamist-related terrorism". We first created a Solr index for both the small dataset and the big dataset, which helped us to perform various queries to know more about the data. Additionally, the index aided another team to create a gold standard summary of our dataset for us. Then we gradually delved into different concepts and topics about text summarization, as well as natural language processing. Specifically, we managed to utilize the NLTK library and the spaCy package to create a set of most frequent important words, WordNet synsets that cover the word, words constrained by part of speech (POS), and frequent and important named entities. We also applied the LSA model to retrieve the most important topics. By clustering the dataset with k-means clustering, and selecting important sentences from the clusters using an implementation of the TextRank algorithm, we were able to generate a multi-paragraph summary. With the help of named entity recognition and pattern-based matching, we confidently extracted information like the name of the attacker, date, location, nearby landmarks, the number killed, the number injured, and the type of the attack. We then drafted a template of a readable summary to fill in the slots and values. Each of these results individually formed a summary that captures the most important information of the Westminster Attack. The most successful results were obtained using the extractive summarization method (k-means clustering and TextRank), the slot-value method (named entity recognition and pattern-based matching), and the abstractive summarization method (deep learning). We evaluated each of the summaries obtained using a combination of ROUGE metrics as well as named-entity coverage compared to the gold standard summary created by team 3. Overall, the best summary was obtained using the extractive summarization method, with both ROUGE metrics and named-entity coverage outperforming other methods. NSF: IIS-1619028 AttackWestMinster_Team4_Project_Report.pdf: Final project report. AttackWestMinster_Team4_Project_Report_Overleaf.zip: Final project report archive from LaTeX project in Overleaf. AttackWestMinster_Team4_Final_Presentation.pdf: Final presentation in PDF format. AttackWestMinster_Team4_Final_Presentation.pptx: Final presentation in PowerPoint format. AttackWestminster_Team4_Code.zip: All source code related to our project.

Published
2018

48. The Arp2/3 complex, UNC-115/abLIM, and UNC-34/Enabled regulate axon guidance and growth cone filopodia formation in Caenorhabditis elegans

Author

Lundquist Erik A, Dyer Jamie O, and Norris Adam D

Subjects
Neurology. Diseases of the nervous system, RC346-429
Abstract

Abstract Background While many molecules involved in axon guidance have been identified, the cellular and molecular mechanisms by which these molecules regulate growth cone morphology during axon outgrowth remain to be elucidated. The actin cytoskeleton of the growth cone underlies the formation of lamellipodia and filopodia that control growth cone outgrowth and guidance. The role of the Arp2/3 complex in growth cone filopodia formation has been controversial, and other mechanisms of growth cone filopodia formation remain to be described. Results Here we show that mutations in genes encoding the Arp2/3 complex (arx genes) caused defects in axon guidance. Analysis of developing growth cones in vivo showed that arx mutants displayed defects in filopodia and reduced growth cone size. Time-lapse analysis of growth cones in living animals indicated that arx mutants affected the rate of growth cone filopodia formation but not filopodia stability or length. Two other actin modulatory proteins, UNC-115/abLIM and UNC-34/Enabled, that had been shown previously to affect axon guidance had overlapping roles with Arp2/3 in axon guidance and also affected the rate of filopodia initiation but not stability or length. Conclusion Our results indicate that the Arp2/3 complex is required cell-autonomously for axon guidance and growth cone filopodia initiation. Furthermore, they show that two other actin-binding proteins, UNC-115/abLIM and UNC-34/Enabled, also control growth cone filopodia formation, possibly in parallel to Arp2/3. These studies indicate that, in vivo, multiple actin modulatory pathways including the Arp2/3 complex contribute to growth cone filopodia formation during growth cone outgrowth.

Published
2009
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