TY  - JOUR
A1  - De Angelis, A.
A1  - Tatischeff, V.
A1  - Grenier, I. A.
A1  - McEnery, J.
A1  - Mallamaci, Manuela
A1  - Tavani, M.
A1  - Oberlack, U.
A1  - Hanlon, L.
A1  - Walter, R.
A1  - Argan, A.
A1  - Von Ballmoos, P.
A1  - Bulgarelli, A.
A1  - Bykov, A.
A1  - Hernanz, M.
A1  - Kanbach, G.
A1  - Kuvvetli, I.
A1  - Pearce, M.
A1  - Zdziarski, A.
A1  - Conrad, J.
A1  - Ghisellini, G.
A1  - Harding, A.
A1  - Isern, J.
A1  - Leising, M.
A1  - Longo, F.
A1  - Madejski, G.
A1  - Martinez, M.
A1  - Mazziotta, Mario Nicola
A1  - Paredes, J. M.
A1  - Pohl, Martin
A1  - Rando, R.
A1  - Razzano, M.
A1  - Aboudan, A.
A1  - Ackermann, M.
A1  - Addazi, A.
A1  - Ajello, M.
A1  - Albertus, C.
A1  - Alvarez, J. M.
A1  - Ambrosi, G.
A1  - Anton, S.
A1  - Antonelli, L. A.
A1  - Babic, A.
A1  - Baibussinov, B.
A1  - Balbom, M.
A1  - Baldini, L.
A1  - Balman, S.
A1  - Bambi, C.
A1  - Barres de Almeida, U.
A1  - Barrio, J. A.
A1  - Bartels, R.
A1  - Bastieri, D.
A1  - Bednarek, W.
A1  - Bernard, D.
A1  - Bernardini, E.
A1  - Bernasconi, T.
A1  - Bertucci, B.
A1  - Biland, A.
A1  - Bissaldi, E.
A1  - Boettcher, M.
A1  - Bonvicini, V.
A1  - Bosch-Ramon, V.
A1  - Bottacini, E.
A1  - Bozhilov, V.
A1  - Bretz, T.
A1  - Branchesi, M.
A1  - Brdar, V.
A1  - Bringmann, T.
A1  - Brogna, A.
A1  - Jorgensen, C. Budtz
A1  - Busetto, G.
A1  - Buson, S.
A1  - Busso, M.
A1  - Caccianiga, A.
A1  - Camera, S.
A1  - Campana, R.
A1  - Caraveo, P.
A1  - Cardillo, M.
A1  - Carlson, P.
A1  - Celestin, S.
A1  - Cermeno, M.
A1  - Chen, A.
A1  - Cheung, C. C.
A1  - Churazov, E.
A1  - Ciprini, S.
A1  - Coc, A.
A1  - Colafrancesco, S.
A1  - Coleiro, A.
A1  - Collmar, W.
A1  - Coppi, P.
A1  - Curado da Silva, R.
A1  - Cutini, S.
A1  - De Lotto, B.
A1  - de Martino, D.
A1  - De Rosa, A.
A1  - Del Santo, M.
A1  - Delgado, L.
A1  - Diehl, R.
A1  - Dietrich, S.
A1  - Dolgov, A. D.
A1  - Dominguez, A.
A1  - Prester, D. Dominis
A1  - Donnarumma, I.
A1  - Dorner, D.
A1  - Doro, M.
A1  - Dutra, M.
A1  - Elsaesser, D.
A1  - Fabrizio, M.
A1  - Fernandez-Barral, A.
A1  - Fioretti, V.
A1  - Foffano, L.
A1  - Formato, V.
A1  - Fornengo, N.
A1  - Foschini, L.
A1  - Franceschini, A.
A1  - Franckowiak, A.
A1  - Funk, S.
A1  - Fuschino, F.
A1  - Gaggero, D.
A1  - Galanti, G.
A1  - Gargano, F.
A1  - Gasparrini, D.
A1  - Gehrz, R.
A1  - Giammaria, P.
A1  - Giglietto, N.
A1  - Giommi, P.
A1  - Giordano, F.
A1  - Giroletti, M.
A1  - Ghirlanda, G.
A1  - Godinovic, N.
A1  - Gouiffes, C.
A1  - Grove, J. E.
A1  - Hamadache, C.
A1  - Hartmann, D. H.
A1  - Hayashida, M.
A1  - Hryczuk, A.
A1  - Jean, P.
A1  - Johnson, T.
A1  - Jose, J.
A1  - Kaufmann, S.
A1  - Khelifi, B.
A1  - Kiener, J.
A1  - Knodlseder, J.
A1  - Kolem, M.
A1  - Kopp, J.
A1  - Kozhuharov, V.
A1  - Labanti, C.
A1  - Lalkovski, S.
A1  - Laurent, P.
A1  - Limousin, O.
A1  - Linares, M.
A1  - Lindfors, E.
A1  - Lindner, M.
A1  - Liu, J.
A1  - Lombardi, S.
A1  - Loparco, F.
A1  - Lopez-Coto, R.
A1  - Lopez Moya, M.
A1  - Lott, B.
A1  - Lubrano, P.
A1  - Malyshev, D.
A1  - Mankuzhiyil, N.
A1  - Mannheim, K.
A1  - Marcha, M. J.
A1  - Marciano, A.
A1  - Marcote, B.
A1  - Mariotti, M.
A1  - Marisaldi, M.
A1  - McBreen, S.
A1  - Mereghetti, S.
A1  - Merle, A.
A1  - Mignani, R.
A1  - Minervini, G.
A1  - Moiseev, A.
A1  - Morselli, A.
A1  - Moura, F.
A1  - Nakazawa, K.
A1  - Nava, L.
A1  - Nieto, D.
A1  - Orienti, M.
A1  - Orio, M.
A1  - Orlando, E.
A1  - Orleanski, P.
A1  - Paiano, S.
A1  - Paoletti, R.
A1  - Papitto, A.
A1  - Pasquato, M.
A1  - Patricelli, B.
A1  - Perez-Garcia, M. A.
A1  - Persic, M.
A1  - Piano, G.
A1  - Pichel, A.
A1  - Pimenta, M.
A1  - Pittori, C.
A1  - Porter, T.
A1  - Poutanen, J.
A1  - Prandini, E.
A1  - Prantzos, N.
A1  - Produit, N.
A1  - Profumo, S.
A1  - Queiroz, F. S.
A1  - Raino, S.
A1  - Raklev, A.
A1  - Regis, M.
A1  - Reichardt, I.
A1  - Rephaeli, Y.
A1  - Rico, J.
A1  - Rodejohann, W.
A1  - Fernandez, G. Rodriguez
A1  - Roncadelli, M.
A1  - Roso, L.
A1  - Rovero, A.
A1  - Ruffini, R.
A1  - Sala, G.
A1  - Sanchez-Conde, M. A.
A1  - Santangelo, A.
A1  - Parkinson, P. Saz
A1  - Sbarrato, T.
A1  - Shearer, A.
A1  - Shellard, R.
A1  - Short, K.
A1  - Siegert, T.
A1  - Siqueira, C.
A1  - Spinelli, P.
A1  - Stamerra, A.
A1  - Starrfield, S.
A1  - Strong, A.
A1  - Strumke, I.
A1  - Tavecchio, F.
A1  - Taverna, R.
A1  - Terzic, T.
A1  - Thompson, D. J.
A1  - Tibolla, O.
A1  - Torres, D. F.
A1  - Turolla, R.
A1  - Ulyanov, A.
A1  - Ursi, A.
A1  - Vacchi, A.
A1  - Van den Abeele, J.
A1  - Vankova-Kirilovai, G.
A1  - Venter, C.
A1  - Verrecchia, F.
A1  - Vincent, P.
A1  - Wang, X.
A1  - Weniger, C.
A1  - Wu, X.
A1  - Zaharijas, G.
A1  - Zampieri, L.
A1  - Zane, S.
A1  - Zimmer, S.
A1  - Zoglauer, A.
T1  - Science with e-ASTROGAM A space mission for MeV-GeV gamma-ray astrophysics
JF  - Journal of High Energy Astrophysics
Y1  - 2018
U6  - https://doi.org/10.1016/j.jheap.2018.07.001
SN  - 2214-4048
SN  - 2214-4056
VL  - 19
SP  - 1
EP  - 106
PB  - Elsevier
CY  - Amsterdam
ER  - 
TY  - JOUR
A1  - Barbosa, Luis Romero A.
A1  - Coelho, Victor Hugo R.
A1  - Gusmao, Ana Claudia V. L. F.
A1  - Fernandes, Lucila A. E.
A1  - da Silva, Bernardo B.
A1  - Galvao, Carlos de O.
A1  - Caicedo, Nelson O. L.
A1  - da Paz, Adriano R.
A1  - Xuan, Yunqing
A1  - Bertrand, Guillaume F.
A1  - Melo, Davi de C. D.
A1  - Montenegro, Suzana M. G. L.
A1  - Oswald, Sascha E.
A1  - Almeida, Cristiano das N.
T1  - A satellite-based approach to estimating spatially distributed groundwater recharge rates in a tropical wet sedimentary region despite cloudy conditions
JF  - Journal of hydrology
N2  - Groundwater recharge (GWR) is one of the most challenging water fluxes to estimate, as it relies on observed data that are often limited in many developing countries. 
This study developed an innovative water budget method using satellite products for estimating the spatially distributed GWR at monthly and annual scales in tropical wet sedimentary regions despite cloudy conditions. 

The distinctive features proposed in this study include the capacity to address 1) evapotranspiration estimations in tropical wet regions frequently overlaid by substantial cloud cover; and 2) seasonal root-zone water storage estimations in sedimentary regions prone to monthly variations. 

The method also utilises satellite-based information of the precipitation and surface runoff. The GWR was estimated and validated for the hydrologically contrasting years 2016 and 2017 over a tropical wet sedimentary region located in North-eastern Brazil, which has substantial potential for groundwater abstraction. 

This study showed that applying a cloud-cleaning procedure based on monthly compositions of biophysical data enables the production of a reasonable proxy for evapotranspiration able to estimate groundwater by the water budget method. 
The resulting GWR rates were 219 (2016) and 302 (2017) mm yr(-1), showing good correlations (CC = 0.68 to 0.83) and slight underestimations (PBIAS =-13 to-9%) when compared with the referenced estimates obtained by the water table fluctuation method for 23 monitoring wells. Sensitivity analysis shows that water storage changes account for +19% to-22% of our monthly evaluation. 

The satellite-based approach consistently demonstrated that the consideration of cloud-cleaned evapotranspiration and root-zone soil water storage changes are essential for a proper estimation of spatially distributed GWR in tropical wet sedimentary regions because of their weather seasonality and cloudy conditions.
KW  - remote sensing
KW  - water balance
KW  - groundwater recharge
KW  - water table
KW  - fluctuation
KW  - tropical climate
KW  - sedimentary aquifer
Y1  - 2022
U6  - https://doi.org/10.1016/j.jhydrol.2022.127503
SN  - 0022-1694
SN  - 1879-2707
VL  - 607
PB  - Elsevier
CY  - Amsterdam
ER  - 
TY  - JOUR
A1  - Tiegs, Scott D.
A1  - Costello, David M.
A1  - Isken, Mark W.
A1  - Woodward, Guy
A1  - McIntyre, Peter B.
A1  - Gessner, Mark O.
A1  - Chauvet, Eric
A1  - Griffiths, Natalie A.
A1  - Flecker, Alex S.
A1  - Acuna, Vicenc
A1  - Albarino, Ricardo
A1  - Allen, Daniel C.
A1  - Alonso, Cecilia
A1  - Andino, Patricio
A1  - Arango, Clay
A1  - Aroviita, Jukka
A1  - Barbosa, Marcus V. M.
A1  - Barmuta, Leon A.
A1  - Baxter, Colden V.
A1  - Bell, Thomas D. C.
A1  - Bellinger, Brent
A1  - Boyero, Luz
A1  - Brown, Lee E.
A1  - Bruder, Andreas
A1  - Bruesewitz, Denise A.
A1  - Burdon, Francis J.
A1  - Callisto, Marcos
A1  - Canhoto, Cristina
A1  - Capps, Krista A.
A1  - Castillo, Maria M.
A1  - Clapcott, Joanne
A1  - Colas, Fanny
A1  - Colon-Gaud, Checo
A1  - Cornut, Julien
A1  - Crespo-Perez, Veronica
A1  - Cross, Wyatt F.
A1  - Culp, Joseph M.
A1  - Danger, Michael
A1  - Dangles, Olivier
A1  - de Eyto, Elvira
A1  - Derry, Alison M.
A1  - Diaz Villanueva, Veronica
A1  - Douglas, Michael M.
A1  - Elosegi, Arturo
A1  - Encalada, Andrea C.
A1  - Entrekin, Sally
A1  - Espinosa, Rodrigo
A1  - Ethaiya, Diana
A1  - Ferreira, Veronica
A1  - Ferriol, Carmen
A1  - Flanagan, Kyla M.
A1  - Fleituch, Tadeusz
A1  - Shah, Jennifer J. Follstad
A1  - Frainer, Andre
A1  - Friberg, Nikolai
A1  - Frost, Paul C.
A1  - Garcia, Erica A.
A1  - Lago, Liliana Garcia
A1  - Garcia Soto, Pavel Ernesto
A1  - Ghate, Sudeep
A1  - Giling, Darren P.
A1  - Gilmer, Alan
A1  - Goncalves, Jose Francisco
A1  - Gonzales, Rosario Karina
A1  - Graca, Manuel A. S.
A1  - Grace, Mike
A1  - Grossart, Hans-Peter
A1  - Guerold, Francois
A1  - Gulis, Vlad
A1  - Hepp, Luiz U.
A1  - Higgins, Scott
A1  - Hishi, Takuo
A1  - Huddart, Joseph
A1  - Hudson, John
A1  - Imberger, Samantha
A1  - Iniguez-Armijos, Carlos
A1  - Iwata, Tomoya
A1  - Janetski, David J.
A1  - Jennings, Eleanor
A1  - Kirkwood, Andrea E.
A1  - Koning, Aaron A.
A1  - Kosten, Sarian
A1  - Kuehn, Kevin A.
A1  - Laudon, Hjalmar
A1  - Leavitt, Peter R.
A1  - Lemes da Silva, Aurea L.
A1  - Leroux, Shawn J.
A1  - Leroy, Carri J.
A1  - Lisi, Peter J.
A1  - MacKenzie, Richard
A1  - Marcarelli, Amy M.
A1  - Masese, Frank O.
A1  - Mckie, Brendan G.
A1  - Oliveira Medeiros, Adriana
A1  - Meissner, Kristian
A1  - Milisa, Marko
A1  - Mishra, Shailendra
A1  - Miyake, Yo
A1  - Moerke, Ashley
A1  - Mombrikotb, Shorok
A1  - Mooney, Rob
A1  - Moulton, Tim
A1  - Muotka, Timo
A1  - Negishi, Junjiro N.
A1  - Neres-Lima, Vinicius
A1  - Nieminen, Mika L.
A1  - Nimptsch, Jorge
A1  - Ondruch, Jakub
A1  - Paavola, Riku
A1  - Pardo, Isabel
A1  - Patrick, Christopher J.
A1  - Peeters, Edwin T. H. M.
A1  - Pozo, Jesus
A1  - Pringle, Catherine
A1  - Prussian, Aaron
A1  - Quenta, Estefania
A1  - Quesada, Antonio
A1  - Reid, Brian
A1  - Richardson, John S.
A1  - Rigosi, Anna
A1  - Rincon, Jose
A1  - Risnoveanu, Geta
A1  - Robinson, Christopher T.
A1  - Rodriguez-Gallego, Lorena
A1  - Royer, Todd V.
A1  - Rusak, James A.
A1  - Santamans, Anna C.
A1  - Selmeczy, Geza B.
A1  - Simiyu, Gelas
A1  - Skuja, Agnija
A1  - Smykla, Jerzy
A1  - Sridhar, Kandikere R.
A1  - Sponseller, Ryan
A1  - Stoler, Aaron
A1  - Swan, Christopher M.
A1  - Szlag, David
A1  - Teixeira-de Mello, Franco
A1  - Tonkin, Jonathan D.
A1  - Uusheimo, Sari
A1  - Veach, Allison M.
A1  - Vilbaste, Sirje
A1  - Vought, Lena B. M.
A1  - Wang, Chiao-Ping
A1  - Webster, Jackson R.
A1  - Wilson, Paul B.
A1  - Woelfl, Stefan
A1  - Xenopoulos, Marguerite A.
A1  - Yates, Adam G.
A1  - Yoshimura, Chihiro
A1  - Yule, Catherine M.
A1  - Zhang, Yixin X.
A1  - Zwart, Jacob A.
T1  - Global patterns and drivers of ecosystem functioning in rivers and riparian zones
JF  - Science Advances
N2  - River ecosystems receive and process vast quantities of terrestrial organic carbon, the fate of which depends strongly on microbial activity. Variation in and controls of processing rates, however, are poorly characterized at the global scale. In response, we used a peer-sourced research network and a highly standardized carbon processing assay to conduct a global-scale field experiment in greater than 1000 river and riparian sites. We found that Earth’s biomes have distinct carbon processing signatures. Slow processing is evident across latitudes, whereas rapid rates are restricted to lower latitudes. Both the mean rate and variability decline with latitude, suggesting temperature constraints toward the poles and greater roles for other environmental drivers (e.g., nutrient loading) toward the equator. These results and data set the stage for unprecedented “next-generation biomonitoring” by establishing baselines to help quantify environmental impacts to the functioning of ecosystems at a global scale.
Y1  - 2019
U6  - https://doi.org/10.1126/sciadv.aav0486
SN  - 2375-2548
VL  - 5
IS  - 1
PB  - American Assoc. for the Advancement of Science
CY  - Washington
ER  - 
TY  - JOUR
A1  - Denton, Richard E.
A1  - Ofman, L.
A1  - Shprits, Yuri Y.
A1  - Bortnik, J.
A1  - Millan, R. M.
A1  - Rodger, C. J.
A1  - da Silva, C. L.
A1  - Rogers, B. N.
A1  - Hudson, M. K.
A1  - Liu, K.
A1  - Min, K.
A1  - Glocer, A.
A1  - Komar, C.
T1  - Pitch Angle Scattering of Sub-MeV Relativistic Electrons by Electromagnetic Ion Cyclotron Waves
JF  - Journal of geophysical research : Space physics
N2  - Electromagnetic ion cyclotron (EMIC) waves have long been considered to be a significant loss mechanism for relativistic electrons. This has most often been attributed to resonant interactions with the highest amplitude waves. But recent observations have suggested that the dominant energy of electrons precipitated to the atmosphere may often be relatively low, less than 1 MeV, whereas the minimum resonant energy of the highest amplitude waves is often greater than 2 MeV. Here we use relativistic electron test particle simulations in the wavefields of a hybrid code simulation of EMIC waves in dipole geometry in order to show that significant pitch angle scattering can occur due to interaction with low-amplitude short-wavelength EMIC waves. In the case we examined, these waves are in the H band (at frequencies above the He+ gyrofrequency), even though the highest amplitude waves were in the He band frequency range (below the He+ gyrofrequency). We also present wave power distributions for 29 EMIC simulations in straight magnetic field line geometry that show that the high wave number portion of the spectrum is in every case mostly due to the H band waves. Though He band waves are often associated with relativistic electron precipitation, it is possible that the He band waves do not directly scatter the sub-megaelectron volts (sub-MeV) electrons, but that the presence of He band waves is associated with high plasma density which lowers the minimum resonant energy so that these electrons can more easily resonate with the H band waves.
KW  - electromagnetic ion cyclotron waves
KW  - EMIC
KW  - relativistic electron precipitation
KW  - pitch angle scattering
KW  - wave particle interaction
KW  - radiation belts
Y1  - 2019
U6  - https://doi.org/10.1029/2018JA026384
SN  - 2169-9402
VL  - 124
IS  - 7
SP  - 5610
EP  - 5626
PB  - American Geophysical Union
CY  - Washington
ER  - 
TY  - JOUR
A1  - van der Valk, Ralf J. P.
A1  - Kreiner-Moller, Eskil
A1  - Kooijman, Marjolein N.
A1  - Guxens, Monica
A1  - Stergiakouli, Evangelia
A1  - Saaf, Annika
A1  - Bradfield, Jonathan P.
A1  - Geller, Frank
A1  - Hayes, M. Geoffrey
A1  - Cousminer, Diana L.
A1  - Koerner, Antje
A1  - Thiering, Elisabeth
A1  - Curtin, John A.
A1  - Myhre, Ronny
A1  - Huikari, Ville
A1  - Joro, Raimo
A1  - Kerkhof, Marjan
A1  - Warrington, Nicole M.
A1  - Pitkanen, Niina
A1  - Ntalla, Ioanna
A1  - Horikoshi, Momoko
A1  - Veijola, Riitta
A1  - Freathy, Rachel M.
A1  - Teo, Yik-Ying
A1  - Barton, Sheila J.
A1  - Evans, David M.
A1  - Kemp, John P.
A1  - St Pourcain, Beate
A1  - Ring, Susan M.
A1  - Smith, George Davey
A1  - Bergstrom, Anna
A1  - Kull, Inger
A1  - Hakonarson, Hakon
A1  - Mentch, Frank D.
A1  - Bisgaard, Hans
A1  - Chawes, Bo Lund Krogsgaard
A1  - Stokholm, Jakob
A1  - Waage, Johannes
A1  - Eriksen, Patrick
A1  - Sevelsted, Astrid
A1  - Melbye, Mads
A1  - van Duijn, Cornelia M.
A1  - Medina-Gomez, Carolina
A1  - Hofman, Albert
A1  - de Jongste, Johan C.
A1  - Taal, H. Rob
A1  - Uitterlinden, Andre G.
A1  - Armstrong, Loren L.
A1  - Eriksson, Johan
A1  - Palotie, Aarno
A1  - Bustamante, Mariona
A1  - Estivill, Xavier
A1  - Gonzalez, Juan R.
A1  - Llop, Sabrina
A1  - Kiess, Wieland
A1  - Mahajan, Anubha
A1  - Flexeder, Claudia
A1  - Tiesler, Carla M. T.
A1  - Murray, Clare S.
A1  - Simpson, Angela
A1  - Magnus, Per
A1  - Sengpiel, Verena
A1  - Hartikainen, Anna-Liisa
A1  - Keinanen-Kiukaanniemi, Sirkka
A1  - Lewin, Alexandra
A1  - Alves, Alexessander Da Silva Couto
A1  - Blakemore, Alexandra I. F.
A1  - Buxton, Jessica L.
A1  - Kaakinen, Marika
A1  - Rodriguez, Alina
A1  - Sebert, Sylvain
A1  - Vaarasmaki, Marja
A1  - Lakka, Timo
A1  - Lindi, Virpi
A1  - Gehring, Ulrike
A1  - Postma, Dirkje S.
A1  - Ang, Wei
A1  - Newnham, John P.
A1  - Lyytikainen, Leo-Pekka
A1  - Pahkala, Katja
A1  - Raitakari, Olli T.
A1  - Panoutsopoulou, Kalliope
A1  - Zeggini, Eleftheria
A1  - Boomsma, Dorret I.
A1  - Groen-Blokhuis, Maria
A1  - Ilonen, Jorma
A1  - Franke, Lude
A1  - Hirschhorn, Joel N.
A1  - Pers, Tune H.
A1  - Liang, Liming
A1  - Huang, Jinyan
A1  - Hocher, Berthold
A1  - Knip, Mikael
A1  - Saw, Seang-Mei
A1  - Holloway, John W.
A1  - Melen, Erik
A1  - Grant, Struan F. A.
A1  - Feenstra, Bjarke
A1  - Lowe, William L.
A1  - Widen, Elisabeth
A1  - Sergeyev, Elena
A1  - Grallert, Harald
A1  - Custovic, Adnan
A1  - Jacobsson, Bo
A1  - Jarvelin, Marjo-Riitta
A1  - Atalay, Mustafa
A1  - Koppelman, Gerard H.
A1  - Pennell, Craig E.
A1  - Niinikoski, Harri
A1  - Dedoussis, George V.
A1  - Mccarthy, Mark I.
A1  - Frayling, Timothy M.
A1  - Sunyer, Jordi
A1  - Timpson, Nicholas J.
A1  - Rivadeneira, Fernando
A1  - Bonnelykke, Klaus
A1  - Jaddoe, Vincent W. V.
T1  - A novel common variant in DCST2 is associated with length in early life and height in adulthood
JF  - Human molecular genetics
N2  - Common genetic variants have been identified for adult height, but not much is known about the genetics of skeletal growth in early life. To identify common genetic variants that influence fetal skeletal growth, we meta-analyzed 22 genome-wide association studies (Stage 1; N = 28 459). We identified seven independent top single nucleotide polymorphisms (SNPs) (P < 1 x 10(-6)) for birth length, of which three were novel and four were in or near loci known to be associated with adult height (LCORL, PTCH1, GPR126 and HMGA2). The three novel SNPs were followed-up in nine replication studies (Stage 2; N = 11 995), with rs905938 in DC-STAMP domain containing 2 (DCST2) genome-wide significantly associated with birth length in a joint analysis (Stages 1 + 2; beta = 0.046, SE = 0.008, P = 2.46 x 10(-8), explained variance = 0.05%). Rs905938 was also associated with infant length (N = 28 228; P = 5.54 x 10(-4)) and adult height (N = 127 513; P = 1.45 x 10(-5)). DCST2 is a DC-STAMP-like protein family member and DC-STAMP is an osteoclast cell-fusion regulator. Polygenic scores based on 180 SNPs previously associated with human adult stature explained 0.13% of variance in birth length. The same SNPs explained 2.95% of the variance of infant length. Of the 180 known adult height loci, 11 were genome-wide significantly associated with infant length (SF3B4, LCORL, SPAG17, C6orf173, PTCH1, GDF5, ZNFX1, HHIP, ACAN, HLA locus and HMGA2). This study highlights that common variation in DCST2 influences variation in early growth and adult height.
Y1  - 2015
U6  - https://doi.org/10.1093/hmg/ddu510
SN  - 0964-6906
SN  - 1460-2083
VL  - 24
IS  - 4
SP  - 1155
EP  - 1168
PB  - Oxford Univ. Press
CY  - Oxford
ER  - 
TY  - CHAP
A1  - Tatischeff, V.
A1  - De Angelis, A.
A1  - Tavani, M.
A1  - Grenier, I.
A1  - Oberlack, U.
A1  - Hanlon, L.
A1  - Walter, R.
A1  - Argan, A.
A1  - von Ballmoos, P.
A1  - Bulgarelli, A.
A1  - Donnarumma, I.
A1  - Hernanz, Margarita
A1  - Kuvvetli, I.
A1  - Mallamaci, M.
A1  - Pearce, M.
A1  - Zdziarski, A.
A1  - Aboudan, A.
A1  - Ajello, M.
A1  - Ambrosi, G.
A1  - Bernard, D.
A1  - Bernardini, E.
A1  - Bonvicini, V.
A1  - Brogna, A.
A1  - Branchesi, M.
A1  - Budtz-Jorgensen, C.
A1  - Bykov, A.
A1  - Campana, R.
A1  - Cardillo, M.
A1  - Ciprini, S.
A1  - Coppi, P.
A1  - Cumani, P.
A1  - da Silva, R. M. Curado
A1  - De Martino, D.
A1  - Diehl, R.
A1  - Doro, M.
A1  - Fioretti, V.
A1  - Funk, S.
A1  - Ghisellini, G.
A1  - Giordano, F.
A1  - Grove, J. E.
A1  - Hamadache, C.
A1  - Hartmann, D. H.
A1  - Hayashida, M.
A1  - Isern, J.
A1  - Kanbach, G.
A1  - Kiener, J.
A1  - Knodlseder, J.
A1  - Labanti, C.
A1  - Laurent, P.
A1  - Leising, M.
A1  - Limousin, O.
A1  - Longo, F.
A1  - Mannheim, K.
A1  - Marisaldi, M.
A1  - Martinez, M.
A1  - Mazziotta, M. N.
A1  - McEnery, J. E.
A1  - Mereghetti, S.
A1  - Minervini, G.
A1  - Moiseev, A.
A1  - Morselli, A.
A1  - Nakazawa, K.
A1  - Orleanski, P.
A1  - Paredes, J. M.
A1  - Patricelli, B.
A1  - Peyre, J.
A1  - Piano, G.
A1  - Pohl, Martin
A1  - Rando, R.
A1  - Roncadelli, M.
A1  - Tavecchio, F.
A1  - Thompson, D. J.
A1  - Turolla, R.
A1  - Ulyanov, A.
A1  - Vacchi, A.
A1  - Wu, X.
A1  - Zoglauer, A.
ED  - DenHerder, JWA Nikzad
T1  - The e-ASTROGAM gamma-ray space observatory for the multimessenger astronomy of the 2030s
T2  - Space Telescopes and Instrumentation 2018: Ultraviolet to Gamma Ray
N2  - e-ASTROGAM is a concept for a breakthrough observatory space mission carrying a gamma-ray telescope dedicated to the study of the non-thermal Universe in the photon energy range from 0.15 MeV to 3 GeV. The lower energy limit can be pushed down to energies as low as 30 keV for gamma-ray burst detection with the calorimeter. The mission is based on an advanced space-proven detector technology, with unprecedented sensitivity, angular and energy resolution, combined with remarkable polarimetric capability. Thanks to its performance in the MeV-GeV domain, substantially improving its predecessors, e-ASTROGAM will open a new window on the non-thermal Universe, making pioneering observations of the most powerful Galactic and extragalactic sources, elucidating the nature of their relativistic outflows and their effects on the surroundings. With a line sensitivity in the MeV energy range one to two orders of magnitude better than previous and current generation instruments, e-ASTROGAM will determine the origin of key isotopes fundamental for the understanding of supernova explosion and the chemical evolution of our Galaxy. The mission will be a major player of the multiwavelength, multimessenger time-domain astronomy of the 2030s, and provide unique data of significant interest to a broad astronomical community, complementary to powerful observatories such as LISA, LIGO, Virgo, KAGRA, the Einstein Telescope and the Cosmic Explorer, IceCube-Gen2 and KM3NeT, SKA, ALMA, JWST, E-ELT, LSST, Athena, and the Cherenkov Telescope Array.
KW  - Gamma-ray astronomy
KW  - time-domain astronomy
KW  - space mission
KW  - Compton and pair creation telescope
KW  - gamma-ray polarization
KW  - high-energy astrophysical phenomena
Y1  - 2018
SN  - 978-1-5106-1952-4
U6  - https://doi.org/10.1117/12.2315151
SN  - 0277-786X
SN  - 1996-756X
VL  - 10699
PB  - SPIE - The International Society for Optical Engineering
CY  - Bellingham
ER  - 
TY  - JOUR
A1  - Noonan, Michael J.
A1  - Tucker, Marlee A.
A1  - Fleming, Christen H.
A1  - Akre, Thomas S.
A1  - Alberts, Susan C.
A1  - Ali, Abdullahi H.
A1  - Altmann, Jeanne
A1  - Antunes, Pamela Castro
A1  - Belant, Jerrold L.
A1  - Beyer, Dean
A1  - Blaum, Niels
A1  - Boehning-Gaese, Katrin
A1  - Cullen Jr, Laury
A1  - de Paula, Rogerio Cunha
A1  - Dekker, Jasja
A1  - Drescher-Lehman, Jonathan
A1  - Farwig, Nina
A1  - Fichtel, Claudia
A1  - Fischer, Christina
A1  - Ford, Adam T.
A1  - Goheen, Jacob R.
A1  - Janssen, Rene
A1  - Jeltsch, Florian
A1  - Kauffman, Matthew
A1  - Kappeler, Peter M.
A1  - Koch, Flavia
A1  - LaPoint, Scott
A1  - Markham, A. Catherine
A1  - Medici, Emilia Patricia
A1  - Morato, Ronaldo G.
A1  - Nathan, Ran
A1  - Oliveira-Santos, Luiz Gustavo R.
A1  - Olson, Kirk A.
A1  - Patterson, Bruce D.
A1  - Paviolo, Agustin
A1  - Ramalho, Emiliano Estero
A1  - Rosner, Sascha
A1  - Schabo, Dana G.
A1  - Selva, Nuria
A1  - Sergiel, Agnieszka
A1  - da Silva, Marina Xavier
A1  - Spiegel, Orr
A1  - Thompson, Peter
A1  - Ullmann, Wiebke
A1  - Zieba, Filip
A1  - Zwijacz-Kozica, Tomasz
A1  - Fagan, William F.
A1  - Mueller, Thomas
A1  - Calabrese, Justin M.
T1  - A comprehensive analysis of autocorrelation and bias in home range estimation
JF  - Ecological monographs : a publication of the Ecological Society of America.
N2  - Home range estimation is routine practice in ecological research. While advances in animal tracking technology have increased our capacity to collect data to support home range analysis, these same advances have also resulted in increasingly autocorrelated data. Consequently, the question of which home range estimator to use on modern, highly autocorrelated tracking data remains open. This question is particularly relevant given that most estimators assume independently sampled data. Here, we provide a comprehensive evaluation of the effects of autocorrelation on home range estimation. We base our study on an extensive data set of GPS locations from 369 individuals representing 27 species distributed across five continents. We first assemble a broad array of home range estimators, including Kernel Density Estimation (KDE) with four bandwidth optimizers (Gaussian reference function, autocorrelated‐Gaussian reference function [AKDE], Silverman's rule of thumb, and least squares cross‐validation), Minimum Convex Polygon, and Local Convex Hull methods. Notably, all of these estimators except AKDE assume independent and identically distributed (IID) data. We then employ half‐sample cross‐validation to objectively quantify estimator performance, and the recently introduced effective sample size for home range area estimation ( N̂ area
) to quantify the information content of each data set. We found that AKDE 95% area estimates were larger than conventional IID‐based estimates by a mean factor of 2. The median number of cross‐validated locations included in the hold‐out sets by AKDE 95% (or 50%) estimates was 95.3% (or 50.1%), confirming the larger AKDE ranges were appropriately selective at the specified quantile. Conversely, conventional estimates exhibited negative bias that increased with decreasing N̂ area. To contextualize our empirical results, we performed a detailed simulation study to tease apart how sampling frequency, sampling duration, and the focal animal's movement conspire to affect range estimates. Paralleling our empirical results, the simulation study demonstrated that AKDE was generally more accurate than conventional methods, particularly for small N̂ area. While 72% of the 369 empirical data sets had >1,000 total observations, only 4% had an N̂ area >1,000, where 30% had an N̂ area <30. In this frequently encountered scenario of small N̂ area, AKDE was the only estimator capable of producing an accurate home range estimate on autocorrelated data.
KW  - animal movement
KW  - kernel density estimation
KW  - local convex hull
KW  - minimum convex polygon
KW  - range distribution
KW  - space use
KW  - telemetry
KW  - tracking data
Y1  - 2018
U6  - https://doi.org/10.1002/ecm.1344
SN  - 0012-9615
SN  - 1557-7015
VL  - 89
IS  - 2
PB  - Wiley
CY  - Hoboken
ER  -