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2,326 results on '"Delpierre, P. A."'

1. Llama Guard 3-1B-INT4: Compact and Efficient Safeguard for Human-AI Conversations

Author

Fedorov, Igor, Plawiak, Kate, Wu, Lemeng, Elgamal, Tarek, Suda, Naveen, Smith, Eric, Zhan, Hongyuan, Chi, Jianfeng, Hulovatyy, Yuriy, Patel, Kimish, Liu, Zechun, Zhao, Changsheng, Shi, Yangyang, Blankevoort, Tijmen, Pasupuleti, Mahesh, Soran, Bilge, Coudert, Zacharie Delpierre, Alao, Rachad, Krishnamoorthi, Raghuraman, and Chandra, Vikas

Subjects
Computer Science - Distributed, Parallel, and Cluster Computing, Computer Science - Artificial Intelligence
Abstract

This paper presents Llama Guard 3-1B-INT4, a compact and efficient Llama Guard model, which has been open-sourced to the community during Meta Connect 2024. We demonstrate that Llama Guard 3-1B-INT4 can be deployed on resource-constrained devices, achieving a throughput of at least 30 tokens per second and a time-to-first-token of 2.5 seconds or less on a commodity Android mobile CPU. Notably, our experiments show that Llama Guard 3-1B-INT4 attains comparable or superior safety moderation scores to its larger counterpart, Llama Guard 3-1B, despite being approximately 7 times smaller in size (440MB).

Published
2024

2. Llama Guard 3 Vision: Safeguarding Human-AI Image Understanding Conversations

Author

Chi, Jianfeng, Karn, Ujjwal, Zhan, Hongyuan, Smith, Eric, Rando, Javier, Zhang, Yiming, Plawiak, Kate, Coudert, Zacharie Delpierre, Upasani, Kartikeya, and Pasupuleti, Mahesh

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Computation and Language
Abstract

We introduce Llama Guard 3 Vision, a multimodal LLM-based safeguard for human-AI conversations that involves image understanding: it can be used to safeguard content for both multimodal LLM inputs (prompt classification) and outputs (response classification). Unlike the previous text-only Llama Guard versions (Inan et al., 2023; Llama Team, 2024b,a), it is specifically designed to support image reasoning use cases and is optimized to detect harmful multimodal (text and image) prompts and text responses to these prompts. Llama Guard 3 Vision is fine-tuned on Llama 3.2-Vision and demonstrates strong performance on the internal benchmarks using the MLCommons taxonomy. We also test its robustness against adversarial attacks. We believe that Llama Guard 3 Vision serves as a good starting point to build more capable and robust content moderation tools for human-AI conversation with multimodal capabilities.

Published
2024

3. The Relationship Between Maturation Size and Maximum Tree Size From Tropical to Boreal Climates

Author

Journé, Valentin, Bogdziewicz, Michał, Courbaud, Benoit, Kunstler, Georges, Qiu, Tong, Acuña, Marie‐Claire Aravena, Ascoli, Davide, Bergeron, Yves, Berveiller, Daniel, Boivin, Thomas, Bonal, Raul, Caignard, Thomas, Cailleret, Maxime, Calama, Rafael, Camarero, J Julio, Chang‐Yang, Chia‐Hao, Chave, Jerome, Chianucci, Francesco, Curt, Thomas, Cutini, Andrea, Das, Adrian, Daskalakou, Evangelia, Davi, Hendrik, Delpierre, Nicolas, Delzon, Sylvain, Dietze, Michael, Calderon, Sergio Donoso, Dormont, Laurent, Espelta, Josep Maria, Farfan‐Rios, William, Fenner, Michael, Franklin, Jerry, Gehring, Catherine, Gilbert, Gregory, Gratzer, Georg, Greenberg, Cathryn H, Guignabert, Arthur, Guo, Qinfeng, Hacket‐Pain, Andrew, Hampe, Arndt, Han, Qingmin, Hanley, Mick E, Lambers, Janneke Hille Ris, Holík, Jan, Hoshizaki, Kazuhiko, Ibanez, Ines, Johnstone, Jill F, Knops, Johannes MH, Kobe, Richard K, Kurokawa, Hiroko, Lageard, Jonathan, LaMontagne, Jalene, Ledwon, Mateusz, Lefèvre, François, Leininger, Theodor, Limousin, Jean‐Marc, Lutz, James, Macias, Diana, Mårell, Anders, McIntire, Eliot, Moran, Emily V, Motta, Renzo, Myers, Jonathan, Nagel, Thomas A, Naoe, Shoji, Noguchi, Mahoko, Norghauer, Julian, Oguro, Michio, Ourcival, Jean‐Marc, Parmenter, Robert, Pearse, Ian, Pérez‐Ramos, Ignacio M, Piechnik, Łukasz, Podgórski, Tomasz, Poulsen, John, Redmond, Miranda D, Reid, Chantal D, Samonil, Pavel, Scher, C Lane, Schlesinger, William H, Seget, Barbara, Sharma, Shubhi, Shibata, Mitsue, Silman, Miles, Steele, Michael, Stephenson, Nathan, Straub, Jacob, Sutton, Samantha, Swenson, Jennifer J, Swift, Margaret, Thomas, Peter A, Uriarte, Maria, Vacchiano, Giorgio, Whipple, Amy, Whitham, Thomas, Wright, S Joseph, Zhu, Kai, Zimmerman, Jess, Żywiec, Magdalena, and Clark, James S

Subjects
Biological Sciences, Ecology, Trees, Tropical Climate, Climate Change, Reproduction, Forests, allometry, life history, seed production, size, tree fecundity, tree maturation, Ecological Applications, Evolutionary Biology, Ecological applications, Environmental management
Abstract

The fundamental trade-off between current and future reproduction has long been considered to result in a tendency for species that can grow large to begin reproduction at a larger size. Due to the prolonged time required to reach maturity, estimates of tree maturation size remain very rare and we lack a global view on the generality and the shape of this trade-off. Using seed production from five continents, we estimate tree maturation sizes for 486 tree species spanning tropical to boreal climates. Results show that a species' maturation size increases with maximum size, but in a non-proportional way: the largest species begin reproduction at smaller sizes than would be expected if maturation were simply proportional to maximum size. Furthermore, the decrease in relative maturation size is steepest in cold climates. These findings on maturation size drivers are key to accurately represent forests' responses to disturbance and climate change.

Published
2024

4. The Llama 3 Herd of Models

Author

Grattafiori, Aaron, Dubey, Abhimanyu, Jauhri, Abhinav, Pandey, Abhinav, Kadian, Abhishek, Al-Dahle, Ahmad, Letman, Aiesha, Mathur, Akhil, Schelten, Alan, Vaughan, Alex, Yang, Amy, Fan, Angela, Goyal, Anirudh, Hartshorn, Anthony, Yang, Aobo, Mitra, Archi, Sravankumar, Archie, Korenev, Artem, Hinsvark, Arthur, Rao, Arun, Zhang, Aston, Rodriguez, Aurelien, Gregerson, Austen, Spataru, Ava, Roziere, Baptiste, Biron, Bethany, Tang, Binh, Chern, Bobbie, Caucheteux, Charlotte, Nayak, Chaya, Bi, Chloe, Marra, Chris, McConnell, Chris, Keller, Christian, Touret, Christophe, Wu, Chunyang, Wong, Corinne, Ferrer, Cristian Canton, Nikolaidis, Cyrus, Allonsius, Damien, Song, Daniel, Pintz, Danielle, Livshits, Danny, Wyatt, Danny, Esiobu, David, Choudhary, Dhruv, Mahajan, Dhruv, Garcia-Olano, Diego, Perino, Diego, Hupkes, Dieuwke, Lakomkin, Egor, AlBadawy, Ehab, Lobanova, Elina, Dinan, Emily, Smith, Eric Michael, Radenovic, Filip, Guzmán, Francisco, Zhang, Frank, Synnaeve, Gabriel, Lee, Gabrielle, Anderson, Georgia Lewis, Thattai, Govind, Nail, Graeme, Mialon, Gregoire, Pang, Guan, Cucurell, Guillem, Nguyen, Hailey, Korevaar, Hannah, Xu, Hu, Touvron, Hugo, Zarov, Iliyan, Ibarra, Imanol Arrieta, Kloumann, Isabel, Misra, Ishan, Evtimov, Ivan, Zhang, Jack, Copet, Jade, Lee, Jaewon, Geffert, Jan, Vranes, Jana, Park, Jason, Mahadeokar, Jay, Shah, Jeet, van der Linde, Jelmer, Billock, Jennifer, Hong, Jenny, Lee, Jenya, Fu, Jeremy, Chi, Jianfeng, Huang, Jianyu, Liu, Jiawen, Wang, Jie, Yu, Jiecao, Bitton, Joanna, Spisak, Joe, Park, Jongsoo, Rocca, Joseph, Johnstun, Joshua, Saxe, Joshua, Jia, Junteng, Alwala, Kalyan Vasuden, Prasad, Karthik, Upasani, Kartikeya, Plawiak, Kate, Li, Ke, Heafield, Kenneth, Stone, Kevin, El-Arini, Khalid, Iyer, Krithika, Malik, Kshitiz, Chiu, Kuenley, Bhalla, Kunal, Lakhotia, Kushal, Rantala-Yeary, Lauren, van der Maaten, Laurens, Chen, Lawrence, Tan, Liang, Jenkins, Liz, Martin, Louis, Madaan, Lovish, Malo, Lubo, Blecher, Lukas, Landzaat, Lukas, de Oliveira, Luke, Muzzi, Madeline, Pasupuleti, Mahesh, Singh, Mannat, Paluri, Manohar, Kardas, Marcin, Tsimpoukelli, Maria, Oldham, Mathew, Rita, Mathieu, Pavlova, Maya, Kambadur, Melanie, Lewis, Mike, Si, Min, Singh, Mitesh Kumar, Hassan, Mona, Goyal, Naman, Torabi, Narjes, Bashlykov, Nikolay, Bogoychev, Nikolay, Chatterji, Niladri, Zhang, Ning, Duchenne, Olivier, Çelebi, Onur, Alrassy, Patrick, Zhang, Pengchuan, Li, Pengwei, Vasic, Petar, Weng, Peter, Bhargava, Prajjwal, Dubal, Pratik, Krishnan, Praveen, Koura, Punit Singh, Xu, Puxin, He, Qing, Dong, Qingxiao, Srinivasan, Ragavan, Ganapathy, Raj, Calderer, Ramon, Cabral, Ricardo Silveira, Stojnic, Robert, Raileanu, Roberta, Maheswari, Rohan, Girdhar, Rohit, Patel, Rohit, Sauvestre, Romain, Polidoro, Ronnie, Sumbaly, Roshan, Taylor, Ross, Silva, Ruan, Hou, Rui, Wang, Rui, Hosseini, Saghar, Chennabasappa, Sahana, Singh, Sanjay, Bell, Sean, Kim, Seohyun Sonia, Edunov, Sergey, Nie, Shaoliang, Narang, Sharan, Raparthy, Sharath, Shen, Sheng, Wan, Shengye, Bhosale, Shruti, Zhang, Shun, Vandenhende, Simon, Batra, Soumya, Whitman, Spencer, Sootla, Sten, Collot, Stephane, Gururangan, Suchin, Borodinsky, Sydney, Herman, Tamar, Fowler, Tara, Sheasha, Tarek, Georgiou, Thomas, Scialom, Thomas, Speckbacher, Tobias, Mihaylov, Todor, Xiao, Tong, Karn, Ujjwal, Goswami, Vedanuj, Gupta, Vibhor, Ramanathan, Vignesh, Kerkez, Viktor, Gonguet, Vincent, Do, Virginie, Vogeti, Vish, Albiero, Vítor, Petrovic, Vladan, Chu, Weiwei, Xiong, Wenhan, Fu, Wenyin, Meers, Whitney, Martinet, Xavier, Wang, Xiaodong, Wang, Xiaofang, Tan, Xiaoqing Ellen, Xia, Xide, Xie, Xinfeng, Jia, Xuchao, Wang, Xuewei, Goldschlag, Yaelle, Gaur, Yashesh, Babaei, Yasmine, Wen, Yi, Song, Yiwen, Zhang, Yuchen, Li, Yue, Mao, Yuning, Coudert, Zacharie Delpierre, Yan, Zheng, Chen, Zhengxing, Papakipos, Zoe, Singh, Aaditya, Srivastava, Aayushi, Jain, Abha, Kelsey, Adam, Shajnfeld, Adam, Gangidi, Adithya, Victoria, Adolfo, Goldstand, Ahuva, Menon, Ajay, Sharma, Ajay, Boesenberg, Alex, Baevski, Alexei, Feinstein, Allie, Kallet, Amanda, Sangani, Amit, Teo, Amos, Yunus, Anam, Lupu, Andrei, Alvarado, Andres, Caples, Andrew, Gu, Andrew, Ho, Andrew, Poulton, Andrew, Ryan, Andrew, Ramchandani, Ankit, Dong, Annie, Franco, Annie, Goyal, Anuj, Saraf, Aparajita, Chowdhury, Arkabandhu, Gabriel, Ashley, Bharambe, Ashwin, Eisenman, Assaf, Yazdan, Azadeh, James, Beau, Maurer, Ben, Leonhardi, Benjamin, Huang, Bernie, Loyd, Beth, De Paola, Beto, Paranjape, Bhargavi, Liu, Bing, Wu, Bo, Ni, Boyu, Hancock, Braden, Wasti, Bram, Spence, Brandon, Stojkovic, Brani, Gamido, Brian, Montalvo, Britt, Parker, Carl, Burton, Carly, Mejia, Catalina, Liu, Ce, Wang, Changhan, Kim, Changkyu, Zhou, Chao, Hu, Chester, Chu, Ching-Hsiang, Cai, Chris, Tindal, Chris, Feichtenhofer, Christoph, Gao, Cynthia, Civin, Damon, Beaty, Dana, Kreymer, Daniel, Li, Daniel, Adkins, David, Xu, David, Testuggine, Davide, David, Delia, Parikh, Devi, Liskovich, Diana, Foss, Didem, Wang, Dingkang, Le, Duc, Holland, Dustin, Dowling, Edward, Jamil, Eissa, Montgomery, Elaine, Presani, Eleonora, Hahn, Emily, Wood, Emily, Le, Eric-Tuan, Brinkman, Erik, Arcaute, Esteban, Dunbar, Evan, Smothers, Evan, Sun, Fei, Kreuk, Felix, Tian, Feng, Kokkinos, Filippos, Ozgenel, Firat, Caggioni, Francesco, Kanayet, Frank, Seide, Frank, Florez, Gabriela Medina, Schwarz, Gabriella, Badeer, Gada, Swee, Georgia, Halpern, Gil, Herman, Grant, Sizov, Grigory, Guangyi, Zhang, Lakshminarayanan, Guna, Inan, Hakan, Shojanazeri, Hamid, Zou, Han, Wang, Hannah, Zha, Hanwen, Habeeb, Haroun, Rudolph, Harrison, Suk, Helen, Aspegren, Henry, Goldman, Hunter, Zhan, Hongyuan, Damlaj, Ibrahim, Molybog, Igor, Tufanov, Igor, Leontiadis, Ilias, Veliche, Irina-Elena, Gat, Itai, Weissman, Jake, Geboski, James, Kohli, James, Lam, Janice, Asher, Japhet, Gaya, Jean-Baptiste, Marcus, Jeff, Tang, Jeff, Chan, Jennifer, Zhen, Jenny, Reizenstein, Jeremy, Teboul, Jeremy, Zhong, Jessica, Jin, Jian, Yang, Jingyi, Cummings, Joe, Carvill, Jon, Shepard, Jon, McPhie, Jonathan, Torres, Jonathan, Ginsburg, Josh, Wang, Junjie, Wu, Kai, U, Kam Hou, Saxena, Karan, Khandelwal, Kartikay, Zand, Katayoun, Matosich, Kathy, Veeraraghavan, Kaushik, Michelena, Kelly, Li, Keqian, Jagadeesh, Kiran, Huang, Kun, Chawla, Kunal, Huang, Kyle, Chen, Lailin, Garg, Lakshya, A, Lavender, Silva, Leandro, Bell, Lee, Zhang, Lei, Guo, Liangpeng, Yu, Licheng, Moshkovich, Liron, Wehrstedt, Luca, Khabsa, Madian, Avalani, Manav, Bhatt, Manish, Mankus, Martynas, Hasson, Matan, Lennie, Matthew, Reso, Matthias, Groshev, Maxim, Naumov, Maxim, Lathi, Maya, Keneally, Meghan, Liu, Miao, Seltzer, Michael L., Valko, Michal, Restrepo, Michelle, Patel, Mihir, Vyatskov, Mik, Samvelyan, Mikayel, Clark, Mike, Macey, Mike, Wang, Mike, Hermoso, Miquel Jubert, Metanat, Mo, Rastegari, Mohammad, Bansal, Munish, Santhanam, Nandhini, Parks, Natascha, White, Natasha, Bawa, Navyata, Singhal, Nayan, Egebo, Nick, Usunier, Nicolas, Mehta, Nikhil, Laptev, Nikolay Pavlovich, Dong, Ning, Cheng, Norman, Chernoguz, Oleg, Hart, Olivia, Salpekar, Omkar, Kalinli, Ozlem, Kent, Parkin, Parekh, Parth, Saab, Paul, Balaji, Pavan, Rittner, Pedro, Bontrager, Philip, Roux, Pierre, Dollar, Piotr, Zvyagina, Polina, Ratanchandani, Prashant, Yuvraj, Pritish, Liang, Qian, Alao, Rachad, Rodriguez, Rachel, Ayub, Rafi, Murthy, Raghotham, Nayani, Raghu, Mitra, Rahul, Parthasarathy, Rangaprabhu, Li, Raymond, Hogan, Rebekkah, Battey, Robin, Wang, Rocky, Howes, Russ, Rinott, Ruty, Mehta, Sachin, Siby, Sachin, Bondu, Sai Jayesh, Datta, Samyak, Chugh, Sara, Hunt, Sara, Dhillon, Sargun, Sidorov, Sasha, Pan, Satadru, Mahajan, Saurabh, Verma, Saurabh, Yamamoto, Seiji, Ramaswamy, Sharadh, Lindsay, Shaun, Feng, Sheng, Lin, Shenghao, Zha, Shengxin Cindy, Patil, Shishir, Shankar, Shiva, Zhang, Shuqiang, Wang, Sinong, Agarwal, Sneha, Sajuyigbe, Soji, Chintala, Soumith, Max, Stephanie, Chen, Stephen, Kehoe, Steve, Satterfield, Steve, Govindaprasad, Sudarshan, Gupta, Sumit, Deng, Summer, Cho, Sungmin, Virk, Sunny, Subramanian, Suraj, Choudhury, Sy, Goldman, Sydney, Remez, Tal, Glaser, Tamar, Best, Tamara, Koehler, Thilo, Robinson, Thomas, Li, Tianhe, Zhang, Tianjun, Matthews, Tim, Chou, Timothy, Shaked, Tzook, Vontimitta, Varun, Ajayi, Victoria, Montanez, Victoria, Mohan, Vijai, Kumar, Vinay Satish, Mangla, Vishal, Ionescu, Vlad, Poenaru, Vlad, Mihailescu, Vlad Tiberiu, Ivanov, Vladimir, Li, Wei, Wang, Wenchen, Jiang, Wenwen, Bouaziz, Wes, Constable, Will, Tang, Xiaocheng, Wu, Xiaojian, Wang, Xiaolan, Wu, Xilun, Gao, Xinbo, Kleinman, Yaniv, Chen, Yanjun, Hu, Ye, Jia, Ye, Qi, Ye, Li, Yenda, Zhang, Yilin, Zhang, Ying, Adi, Yossi, Nam, Youngjin, Yu, Wang, Zhao, Yu, Hao, Yuchen, Qian, Yundi, Li, Yunlu, He, Yuzi, Rait, Zach, DeVito, Zachary, Rosnbrick, Zef, Wen, Zhaoduo, Yang, Zhenyu, Zhao, Zhiwei, and Ma, Zhiyu

Subjects
Computer Science - Artificial Intelligence, Computer Science - Computation and Language, Computer Science - Computer Vision and Pattern Recognition
Abstract

Modern artificial intelligence (AI) systems are powered by foundation models. This paper presents a new set of foundation models, called Llama 3. It is a herd of language models that natively support multilinguality, coding, reasoning, and tool usage. Our largest model is a dense Transformer with 405B parameters and a context window of up to 128K tokens. This paper presents an extensive empirical evaluation of Llama 3. We find that Llama 3 delivers comparable quality to leading language models such as GPT-4 on a plethora of tasks. We publicly release Llama 3, including pre-trained and post-trained versions of the 405B parameter language model and our Llama Guard 3 model for input and output safety. The paper also presents the results of experiments in which we integrate image, video, and speech capabilities into Llama 3 via a compositional approach. We observe this approach performs competitively with the state-of-the-art on image, video, and speech recognition tasks. The resulting models are not yet being broadly released as they are still under development.

Published
2024

5. Introducing v0.5 of the AI Safety Benchmark from MLCommons

Author

Vidgen, Bertie, Agrawal, Adarsh, Ahmed, Ahmed M., Akinwande, Victor, Al-Nuaimi, Namir, Alfaraj, Najla, Alhajjar, Elie, Aroyo, Lora, Bavalatti, Trupti, Bartolo, Max, Blili-Hamelin, Borhane, Bollacker, Kurt, Bomassani, Rishi, Boston, Marisa Ferrara, Campos, Siméon, Chakra, Kal, Chen, Canyu, Coleman, Cody, Coudert, Zacharie Delpierre, Derczynski, Leon, Dutta, Debojyoti, Eisenberg, Ian, Ezick, James, Frase, Heather, Fuller, Brian, Gandikota, Ram, Gangavarapu, Agasthya, Gangavarapu, Ananya, Gealy, James, Ghosh, Rajat, Goel, James, Gohar, Usman, Goswami, Sujata, Hale, Scott A., Hutiri, Wiebke, Imperial, Joseph Marvin, Jandial, Surgan, Judd, Nick, Juefei-Xu, Felix, Khomh, Foutse, Kailkhura, Bhavya, Kirk, Hannah Rose, Klyman, Kevin, Knotz, Chris, Kuchnik, Michael, Kumar, Shachi H., Kumar, Srijan, Lengerich, Chris, Li, Bo, Liao, Zeyi, Long, Eileen Peters, Lu, Victor, Luger, Sarah, Mai, Yifan, Mammen, Priyanka Mary, Manyeki, Kelvin, McGregor, Sean, Mehta, Virendra, Mohammed, Shafee, Moss, Emanuel, Nachman, Lama, Naganna, Dinesh Jinenhally, Nikanjam, Amin, Nushi, Besmira, Oala, Luis, Orr, Iftach, Parrish, Alicia, Patlak, Cigdem, Pietri, William, Poursabzi-Sangdeh, Forough, Presani, Eleonora, Puletti, Fabrizio, Röttger, Paul, Sahay, Saurav, Santos, Tim, Scherrer, Nino, Sebag, Alice Schoenauer, Schramowski, Patrick, Shahbazi, Abolfazl, Sharma, Vin, Shen, Xudong, Sistla, Vamsi, Tang, Leonard, Testuggine, Davide, Thangarasa, Vithursan, Watkins, Elizabeth Anne, Weiss, Rebecca, Welty, Chris, Wilbers, Tyler, Williams, Adina, Wu, Carole-Jean, Yadav, Poonam, Yang, Xianjun, Zeng, Yi, Zhang, Wenhui, Zhdanov, Fedor, Zhu, Jiacheng, Liang, Percy, Mattson, Peter, and Vanschoren, Joaquin

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence
Abstract

This paper introduces v0.5 of the AI Safety Benchmark, which has been created by the MLCommons AI Safety Working Group. The AI Safety Benchmark has been designed to assess the safety risks of AI systems that use chat-tuned language models. We introduce a principled approach to specifying and constructing the benchmark, which for v0.5 covers only a single use case (an adult chatting to a general-purpose assistant in English), and a limited set of personas (i.e., typical users, malicious users, and vulnerable users). We created a new taxonomy of 13 hazard categories, of which 7 have tests in the v0.5 benchmark. We plan to release version 1.0 of the AI Safety Benchmark by the end of 2024. The v1.0 benchmark will provide meaningful insights into the safety of AI systems. However, the v0.5 benchmark should not be used to assess the safety of AI systems. We have sought to fully document the limitations, flaws, and challenges of v0.5. This release of v0.5 of the AI Safety Benchmark includes (1) a principled approach to specifying and constructing the benchmark, which comprises use cases, types of systems under test (SUTs), language and context, personas, tests, and test items; (2) a taxonomy of 13 hazard categories with definitions and subcategories; (3) tests for seven of the hazard categories, each comprising a unique set of test items, i.e., prompts. There are 43,090 test items in total, which we created with templates; (4) a grading system for AI systems against the benchmark; (5) an openly available platform, and downloadable tool, called ModelBench that can be used to evaluate the safety of AI systems on the benchmark; (6) an example evaluation report which benchmarks the performance of over a dozen openly available chat-tuned language models; (7) a test specification for the benchmark.

Published
2024

12. Linking seed size and number to trait syndromes in trees

Author

Bogdziewicz, Michal, Acuña, Marie‐Claire Aravena, Andrus, Robert, Ascoli, Davide, Bergeron, Yves, Brveiller, Daniel, Boivin, Thomas, Bonal, Raul, Caignard, Thomas, Cailleret, Maxime, Calama, Rafael, Calderon, Sergio Donoso, Camarero, J Julio, Chang‐Yang, Chia‐Hao, Chave, Jerome, Chianucci, Francesco, Cleavitt, Natalie L, Courbaud, Benoit, Cutini, Andrea, Curt, Thomas, Das, Adrian J, Davi, Hendrik, Delpierre, Nicolas, Delzon, Sylvain, Dietze, Michael, Dormont, Laurent, Farfan‐Rios, William, Gehring, Catherine A, Gilbert, Gregory S, Gratzer, Georg, Greenberg, Cathryn H, Guignabert, Arthur, Guo, Qinfeng, Hacket‐Pain, Andrew, Hampe, Arndt, Han, Qingmin, Hoshizaki, Kazuhiko, Ibanez, Ines, Johnstone, Jill F, Journé, Valentin, Kitzberger, Thomas, Knops, Johannes MH, Kunstler, Georges, Kobe, Richard, Lageard, Jonathan GA, LaMontagne, Jalene M, Ledwon, Mateusz, Leininger, Theodor, Limousin, Jean‐Marc, Lutz, James A, Macias, Diana, Marell, Anders, McIntire, Eliot JB, Moran, Emily, Motta, Renzo, Myers, Jonathan A, Nagel, Thomas A, Naoe, Shoji, Noguchi, Mahoko, Oguro, Michio, Kurokawa, Hiroko, Ourcival, Jean‐Marc, Parmenter, Robert, Perez‐Ramos, Ignacio M, Piechnik, Lukasz, Podgórski, Tomasz, Poulsen, John, Qiu, Tong, Redmond, Miranda D, Reid, Chantal D, Rodman, Kyle C, Šamonil, Pavel, Holik, Jan, Scher, C Lane, Van Marle, Harald Schmidt, Seget, Barbara, Shibata, Mitsue, Sharma, Shubhi, Silman, Miles, Steele, Michael A, Straub, Jacob N, Sun, I‐Fang, Sutton, Samantha, Swenson, Jennifer J, Thomas, Peter A, Uriarte, Maria, Vacchiano, Giorgio, Veblen, Thomas T, Wright, Boyd, Wright, S Joseph, Whitham, Thomas G, Zhu, Kai, Zimmerman, Jess K, Zywiec, Magdalna, and Clark, James S

Subjects
fecundity, functional traits, leaf economics, life history strategies, size syndrome, tree recruitment, Ecology
Published
2023

14. Globally, tree fecundity exceeds productivity gradients

Author

Journé, Valentin, Andrus, Robert, Aravena, Marie‐Claire, Ascoli, Davide, Berretti, Roberta, Berveiller, Daniel, Bogdziewicz, Michal, Boivin, Thomas, Bonal, Raul, Caignard, Thomas, Calama, Rafael, Camarero, Jesús Julio, Chang‐Yang, Chia‐Hao, Courbaud, Benoit, Courbet, Francois, Curt, Thomas, Das, Adrian J, Daskalakou, Evangelia, Davi, Hendrik, Delpierre, Nicolas, Delzon, Sylvain, Dietze, Michael, Calderon, Sergio Donoso, Dormont, Laurent, Espelta, Josep Maria, Fahey, Timothy J, Farfan‐Rios, William, Gehring, Catherine A, Gilbert, Gregory S, Gratzer, Georg, Greenberg, Cathryn H, Guo, Qinfeng, Hacket‐Pain, Andrew, Hampe, Arndt, Han, Qingmin, Lambers, Janneke Hille Ris, Hoshizaki, Kazuhiko, Ibanez, Ines, Johnstone, Jill F, Kabeya, Daisuke, Kays, Roland, Kitzberger, Thomas, Knops, Johannes MH, Kobe, Richard K, Kunstler, Georges, Lageard, Jonathan GA, LaMontagne, Jalene M, Leininger, Theodor, Limousin, Jean‐Marc, Lutz, James A, Macias, Diana, McIntire, Eliot JB, Moore, Christopher M, Moran, Emily, Motta, Renzo, Myers, Jonathan A, Nagel, Thomas A, Noguchi, Kyotaro, Ourcival, Jean‐Marc, Parmenter, Robert, Pearse, Ian S, Perez‐Ramos, Ignacio M, Piechnik, Lukasz, Poulsen, John, Poulton‐Kamakura, Renata, Qiu, Tong, Redmond, Miranda D, Reid, Chantal D, Rodman, Kyle C, Rodriguez‐Sanchez, Francisco, Sanguinetti, Javier D, Scher, C Lane, Van Marle, Harald Schmidt, Seget, Barbara, Sharma, Shubhi, Silman, Miles, Steele, Michael A, Stephenson, Nathan L, Straub, Jacob N, Swenson, Jennifer J, Swift, Margaret, Thomas, Peter A, Uriarte, Maria, Vacchiano, Giorgio, Veblen, Thomas T, Whipple, Amy V, Whitham, Thomas G, Wright, Boyd, Wright, S Joseph, Zhu, Kai, Zimmerman, Jess K, Zlotin, Roman, Zywiec, Magdalena, and Clark, James S

Subjects
Climate Change Impacts and Adaptation, Biological Sciences, Ecology, Environmental Sciences, Regenerative Medicine, Biodiversity, Climate, Fertility, Forests, Seeds, Trees, climate, competition, forest regeneration, seed consumption, species interactions, tree fecundity, Ecological Applications, Evolutionary Biology, Ecological applications, Environmental management
Abstract

Lack of tree fecundity data across climatic gradients precludes the analysis of how seed supply contributes to global variation in forest regeneration and biotic interactions responsible for biodiversity. A global synthesis of raw seedproduction data shows a 250-fold increase in seed abundance from cold-dry to warm-wet climates, driven primarily by a 100-fold increase in seed production for a given tree size. The modest (threefold) increase in forest productivity across the same climate gradient cannot explain the magnitudes of these trends. The increase in seeds per tree can arise from adaptive evolution driven by intense species interactions or from the direct effects of a warm, moist climate on tree fecundity. Either way, the massive differences in seed supply ramify through food webs potentially explaining a disproportionate role for species interactions in the wet tropics.

Published
2022

15. Limits to reproduction and seed size-number trade-offs that shape forest dominance and future recovery

Author

Qiu, Tong, Andrus, Robert, Aravena, Marie-Claire, Ascoli, Davide, Bergeron, Yves, Berretti, Roberta, Berveiller, Daniel, Bogdziewicz, Michal, Boivin, Thomas, Bonal, Raul, Bragg, Don C, Caignard, Thomas, Calama, Rafael, Camarero, J Julio, Chang-Yang, Chia-Hao, Cleavitt, Natalie L, Courbaud, Benoit, Courbet, Francois, Curt, Thomas, Das, Adrian J, Daskalakou, Evangelia, Davi, Hendrik, Delpierre, Nicolas, Delzon, Sylvain, Dietze, Michael, Calderon, Sergio Donoso, Dormont, Laurent, Espelta, Josep, Fahey, Timothy J, Farfan-Rios, William, Gehring, Catherine A, Gilbert, Gregory S, Gratzer, Georg, Greenberg, Cathryn H, Guo, Qinfeng, Hacket-Pain, Andrew, Hampe, Arndt, Han, Qingmin, Hille Ris Lambers, Janneke, Hoshizaki, Kazuhiko, Ibanez, Ines, Johnstone, Jill F, Journé, Valentin, Kabeya, Daisuke, Kilner, Christopher L, Kitzberger, Thomas, Knops, Johannes MH, Kobe, Richard K, Kunstler, Georges, Lageard, Jonathan GA, LaMontagne, Jalene M, Ledwon, Mateusz, Lefevre, Francois, Leininger, Theodor, Limousin, Jean-Marc, Lutz, James A, Macias, Diana, McIntire, Eliot JB, Moore, Christopher M, Moran, Emily, Motta, Renzo, Myers, Jonathan A, Nagel, Thomas A, Noguchi, Kyotaro, Ourcival, Jean-Marc, Parmenter, Robert, Pearse, Ian S, Perez-Ramos, Ignacio M, Piechnik, Lukasz, Poulsen, John, Poulton-Kamakura, Renata, Redmond, Miranda D, Reid, Chantal D, Rodman, Kyle C, Rodriguez-Sanchez, Francisco, Sanguinetti, Javier D, Scher, C Lane, Schlesinger, William H, Schmidt Van Marle, Harald, Seget, Barbara, Sharma, Shubhi, Silman, Miles, Steele, Michael A, Stephenson, Nathan L, Straub, Jacob N, Sun, I-Fang, Sutton, Samantha, Swenson, Jennifer J, Swift, Margaret, Thomas, Peter A, Uriarte, Maria, Vacchiano, Giorgio, Veblen, Thomas T, Whipple, Amy V, Whitham, Thomas G, Wion, Andreas P, Wright, Boyd, Wright, S Joseph, Zhu, Kai, and Zimmerman, Jess K

Subjects
Agricultural, Veterinary and Food Sciences, Biological Sciences, Ecology, Contraception/Reproduction, Fertility, Forests, Reproduction, Seeds, Trees
Abstract

The relationships that control seed production in trees are fundamental to understanding the evolution of forest species and their capacity to recover from increasing losses to drought, fire, and harvest. A synthesis of fecundity data from 714 species worldwide allowed us to examine hypotheses that are central to quantifying reproduction, a foundation for assessing fitness in forest trees. Four major findings emerged. First, seed production is not constrained by a strict trade-off between seed size and numbers. Instead, seed numbers vary over ten orders of magnitude, with species that invest in large seeds producing more seeds than expected from the 1:1 trade-off. Second, gymnosperms have lower seed production than angiosperms, potentially due to their extra investments in protective woody cones. Third, nutrient-demanding species, indicated by high foliar phosphorus concentrations, have low seed production. Finally, sensitivity of individual species to soil fertility varies widely, limiting the response of community seed production to fertility gradients. In combination, these findings can inform models of forest response that need to incorporate reproductive potential.

Published
2022

16. Influence of socio-economic status on functional recovery after ARDS caused by SARS-CoV-2: the multicentre, observational RECOVIDS study

Author

Declercq, Pierre-Louis, Fournel, Isabelle, Demeyere, Matthieu, Berraies, Anissa, Ksiazek, Eléa, Nyunga, Martine, Daubin, Cédric, Ampere, Alexandre, Sauneuf, Bertrand, Badie, Julio, Delbove, Agathe, Nseir, Saad, Artaud-Macari, Elise, Bironneau, Vanessa, Ramakers, Michel, Maizel, Julien, Miailhe, Arnaud-Felix, Lacombe, Béatrice, Delberghe, Nicolas, Oulehri, Walid, Georges, Hugues, Tchenio, Xavier, Clarot, Caroline, Redureau, Elise, Bourdin, Gaël, Federici, Laura, Adda, Mélanie, Schnell, David, Bousta, Mehdi, Salmon-Gandonnière, Charlotte, Vanderlinden, Thierry, Plantefeve, Gaëtan, Delacour, David, Delpierre, Cyrille, Le Bouar, Gurvan, Sedillot, Nicholas, Beduneau, Gaëtan, Rivière, Antoine, Meunier-Beillard, Nicolas, Gélinotte, Stéphanie, Rigaud, Jean-Philippe, Labruyère, Marie, Georges, Marjolaine, Binquet, Christine, and Quenot, Jean-Pierre

Published
2023
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17. Masting is uncommon in trees that depend on mutualist dispersers in the context of global climate and fertility gradients

Author

Qiu, Tong, Aravena, Marie-Claire, Ascoli, Davide, Bergeron, Yves, Bogdziewicz, Michal, Boivin, Thomas, Bonal, Raul, Caignard, Thomas, Cailleret, Maxime, Calama, Rafael, Calderon, Sergio Donoso, Camarero, J. Julio, Chang-Yang, Chia-Hao, Chave, Jerome, Chianucci, Francesco, Courbaud, Benoit, Cutini, Andrea, Das, Adrian J., Delpierre, Nicolas, Delzon, Sylvain, Dietze, Michael, Dormont, Laurent, Espelta, Josep Maria, Fahey, Timothy J., Farfan-Rios, William, Franklin, Jerry F., Gehring, Catherine A., Gilbert, Gregory S., Gratzer, Georg, Greenberg, Cathryn H., Guignabert, Arthur, Guo, Qinfeng, Hacket-Pain, Andrew, Hampe, Arndt, Han, Qingmin, Holik, Jan, Hoshizaki, Kazuhiko, Ibanez, Ines, Johnstone, Jill F., Journé, Valentin, Kitzberger, Thomas, Knops, Johannes M. H., Kunstler, Georges, Kurokawa, Hiroko, Lageard, Jonathan G. A., LaMontagne, Jalene M., Lefevre, Francois, Leininger, Theodor, Limousin, Jean-Marc, Lutz, James A., Macias, Diana, Marell, Anders, McIntire, Eliot J. B., Moore, Christopher M., Moran, Emily, Motta, Renzo, Myers, Jonathan A., Nagel, Thomas A., Naoe, Shoji, Noguchi, Mahoko, Oguro, Michio, Parmenter, Robert, Pearse, Ian S., Perez-Ramos, Ignacio M., Piechnik, Lukasz, Podgorski, Tomasz, Poulsen, John, Redmond, Miranda D., Reid, Chantal D., Rodman, Kyle C., Rodriguez-Sanchez, Francisco, Samonil, Pavel, Sanguinetti, Javier D., Scher, C. Lane, Seget, Barbara, Sharma, Shubhi, Shibata, Mitsue, Silman, Miles, Steele, Michael A., Stephenson, Nathan L., Straub, Jacob N., Sutton, Samantha, Swenson, Jennifer J., Swift, Margaret, Thomas, Peter A., Uriarte, Maria, Vacchiano, Giorgio, Whipple, Amy V., Whitham, Thomas G., Wion, Andreas P., Wright, S. Joseph, Zhu, Kai, Zimmerman, Jess K., Zywiec, Magdalena, and Clark, James S.

Published
2023
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21. The potential impact of the COVID-19 pandemic on global antimicrobial and biocide resistance: an AMR Insights global perspective

Author

Ansari, Shamshul, Hays, John P, Kemp, Andrew, Okechukwu, Raymond, Murugaiyan, Jayaseelan, Ekwanzala, Mutshiene Deogratias, Ruiz Alvarez, Maria Josefina, Paul-Satyaseela, Maneesh, Iwu, Chidozie Declan, Balleste-Delpierre, Clara, Septimus, Ed, Mugisha, Lawrence, Fadare, Joseph, Chaudhuri, Susmita, Chibabhai, Vindana, Wadanamby, JM Rohini WW, Daoud, Ziad, Xiao, Yonghong, Parkunan, Thulasiraman, Khalaf, Yara, M’Ikanatha, Nkuchia M, van Dongen, Maarten BM, Barkema, Herman W, Strathdee, Steffanie, Benyeogor, Emmanuel, Ighodalo, Uzairue Leonard, Prasad, Kurcheti Pani, M, Carlos, Gu, Yoshiaki, Essack, Sabiha, de Silva, Dilan, Vellinga, Akke, Mommtaz Ghannam, Wagih, Tsoho, Najib Auwal, Sakeena, MHF, Ilenwabor, Rhoda, Shetty, Dhanuraj Raj, Ayebare, Arnold, Traore, Zoumana Isaac, Henry, Ola, Kiran, Amritanjali, Toro, Luisa Fernanda, Smail, Adil, Amulele, Anne, Founou, Luria Leslie, Sawant, Prathamesh S, Buregyeya, Esther, Castro-Sanchez, Enrique, Moreno-Morales, Javier, Izadjoo, Mina, Gori, Andrea, Goff, Debra, Blocker, Arielle, Forte, Giovanna, Tahir, Muhammad Farooq, Diggle, Mathew, Chakraborty, Dipanjan, Asamoah, Anita E, and Aberi, Humphrey

Subjects
Medical Microbiology, Biomedical and Clinical Sciences, Clinical Sciences, Emerging Infectious Diseases, Antimicrobial Resistance, Prevention, Biodefense, Vaccine Related, Infectious Diseases, Infection, Good Health and Well Being, Global AMR Insights Ambassador Network, Clinical sciences, Medical microbiology, Pharmacology and pharmaceutical sciences
Abstract

The COVID-19 pandemic presents a serious public health challenge in all countries. However, repercussions of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections on future global health are still being investigated, including the pandemic's potential effect on the emergence and spread of global antimicrobial resistance (AMR). Critically ill COVID-19 patients may develop severe complications, which may predispose patients to infection with nosocomial bacterial and/or fungal pathogens, requiring the extensive use of antibiotics. However, antibiotics may also be inappropriately used in milder cases of COVID-19 infection. Further, concerns such as increased biocide use, antimicrobial stewardship/infection control, AMR awareness, the need for diagnostics (including rapid and point-of-care diagnostics) and the usefulness of vaccination could all be components shaping the influence of the COVID-19 pandemic. In this publication, the authors present a brief overview of the COVID-19 pandemic and associated issues that could influence the pandemic's effect on global AMR.

Published
2021

22. Author Correction: The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data.

Author

Pastorello, Gilberto, Trotta, Carlo, Canfora, Eleonora, Chu, Housen, Christianson, Danielle, Cheah, You-Wei, Poindexter, Cristina, Chen, Jiquan, Elbashandy, Abdelrahman, Humphrey, Marty, Isaac, Peter, Polidori, Diego, Reichstein, Markus, Ribeca, Alessio, van Ingen, Catharine, Vuichard, Nicolas, Zhang, Leiming, Amiro, Brian, Ammann, Christof, Arain, M Altaf, Ardö, Jonas, Arkebauer, Timothy, Arndt, Stefan K, Arriga, Nicola, Aubinet, Marc, Aurela, Mika, Baldocchi, Dennis, Barr, Alan, Beamesderfer, Eric, Marchesini, Luca Belelli, Bergeron, Onil, Beringer, Jason, Bernhofer, Christian, Berveiller, Daniel, Billesbach, Dave, Black, Thomas Andrew, Blanken, Peter D, Bohrer, Gil, Boike, Julia, Bolstad, Paul V, Bonal, Damien, Bonnefond, Jean-Marc, Bowling, David R, Bracho, Rosvel, Brodeur, Jason, Brümmer, Christian, Buchmann, Nina, Burban, Benoit, Burns, Sean P, Buysse, Pauline, Cale, Peter, Cavagna, Mauro, Cellier, Pierre, Chen, Shiping, Chini, Isaac, Christensen, Torben R, Cleverly, James, Collalti, Alessio, Consalvo, Claudia, Cook, Bruce D, Cook, David, Coursolle, Carole, Cremonese, Edoardo, Curtis, Peter S, D'Andrea, Ettore, da Rocha, Humberto, Dai, Xiaoqin, Davis, Kenneth J, De Cinti, Bruno, de Grandcourt, Agnes, De Ligne, Anne, De Oliveira, Raimundo C, Delpierre, Nicolas, Desai, Ankur R, Di Bella, Carlos Marcelo, di Tommasi, Paul, Dolman, Han, Domingo, Francisco, Dong, Gang, Dore, Sabina, Duce, Pierpaolo, Dufrêne, Eric, Dunn, Allison, Dušek, Jiří, Eamus, Derek, Eichelmann, Uwe, ElKhidir, Hatim Abdalla M, Eugster, Werner, Ewenz, Cacilia M, Ewers, Brent, Famulari, Daniela, Fares, Silvano, Feigenwinter, Iris, Feitz, Andrew, Fensholt, Rasmus, Filippa, Gianluca, Fischer, Marc, Frank, John, Galvagno, Marta, and Gharun, Mana

Abstract

The following authors were omitted from the original version of this Data Descriptor: Markus Reichstein and Nicolas Vuichard. Both contributed to the code development and N. Vuichard contributed to the processing of the ERA-Interim data downscaling. Furthermore, the contribution of the co-author Frank Tiedemann was re-evaluated relative to the colleague Corinna Rebmann, both working at the same sites, and based on this re-evaluation a substitution in the co-author list is implemented (with Rebmann replacing Tiedemann). Finally, two affiliations were listed incorrectly and are corrected here (entries 190 and 193). The author list and affiliations have been amended to address these omissions in both the HTML and PDF versions.

Published
2021

23. Global transpiration data from sap flow measurements: the SAPFLUXNET database

Author

Poyatos, Rafael, Granda, Víctor, Flo, Víctor, Adams, Mark A, Adorján, Balázs, Aguadé, David, Aidar, Marcos PM, Allen, Scott, Alvarado-Barrientos, M Susana, Anderson-Teixeira, Kristina J, Aparecido, Luiza Maria, Arain, M Altaf, Aranda, Ismael, Asbjornsen, Heidi, Baxter, Robert, Beamesderfer, Eric, Berry, Z Carter, Berveiller, Daniel, Blakely, Bethany, Boggs, Johnny, Bohrer, Gil, Bolstad, Paul V, Bonal, Damien, Bracho, Rosvel, Brito, Patricia, Brodeur, Jason, Casanoves, Fernando, Chave, Jérôme, Chen, Hui, Cisneros, Cesar, Clark, Kenneth, Cremonese, Edoardo, Dang, Hongzhong, David, Jorge S, David, Teresa S, Delpierre, Nicolas, Desai, Ankur R, C., Frederic, Dohnal, Michal, Domec, Jean-Christophe, Dzikiti, Sebinasi, Edgar, Colin, Eichstaedt, Rebekka, El-Madany, Tarek S, Elbers, Jan, Eller, Cleiton B, Euskirchen, Eugénie S, Ewers, Brent, Fonti, Patrick, Forner, Alicia, Forrester, David I, Freitas, Helber C, Galvagno, Marta, Garcia-Tejera, Omar, Ghimire, Chandra Prasad, Gimeno, Teresa E, Grace, John, Granier, André, Griebel, Anne, Guangyu, Yan, Gush, Mark B, Hanson, Paul J, Hasselquist, Niles J, Heinrich, Ingo, Hernandez-Santana, Virginia, Herrmann, Valentine, Hölttä, Teemu, Holwerda, Friso, Irvine, James, Ayutthaya, Supat Isarangkool Na, Jarvis, Paul G, Jochheim, Hubert, Joly, Carlos A, Kaplick, Julia, Kim, Hyun Seok, Klemedtsson, Leif, Kropp, Heather, Lagergren, Fredrik, Lane, Patrick, Lang, Petra, Lapenas, Andrei, Lechuga, Víctor, Lee, Minsu, Leuschner, Christoph, Limousin, Jean-Marc, Linares, Juan Carlos, Linderson, Maj-Lena, Lindroth, Anders, Llorens, Pilar, López-Bernal, Álvaro, Loranty, Michael M, Lüttschwager, Dietmar, Macinnis-Ng, Cate, Maréchaux, Isabelle, Martin, Timothy A, Matheny, Ashley, McDowell, Nate, McMahon, Sean, Meir, Patrick, and Mészáros, Ilona

Subjects
Life on Land, Atmospheric Sciences, Geochemistry, Physical Geography and Environmental Geoscience
Abstract

Plant transpiration links physiological responses of vegetation to water supply and demand with hydrological, energy, and carbon budgets at the land-atmosphere interface. However, despite being the main land evaporative flux at the global scale, transpiration and its response to environmental drivers are currently not well constrained by observations. Here we introduce the first global compilation of whole-plant transpiration data from sap flow measurements (SAPFLUXNET, https://sapfluxnet.creaf.cat/, last access: 8 June 2021). We harmonized and quality-controlled individual datasets supplied by contributors worldwide in a semi-automatic data workflow implemented in the R programming language. Datasets include sub-daily time series of sap flow and hydrometeorological drivers for one or more growing seasons, as well as metadata on the stand characteristics, plant attributes, and technical details of the measurements. SAPFLUXNET contains 202 globally distributed datasets with sap flow time series for 2714 plants, mostly trees, of 174 species. SAPFLUXNET has a broad bioclimatic coverage, with woodland/shrubland and temperate forest biomes especially well represented (80% of the datasets). The measurements cover a wide variety of stand structural characteristics and plant sizes. The datasets encompass the period between 1995 and 2018, with 50% of the datasets being at least 3 years long. Accompanying radiation and vapour pressure deficit data are available for most of the datasets, while on-site soil water content is available for 56% of the datasets. Many datasets contain data for species that make up 90% or more of the total stand basal area, allowing the estimation of stand transpiration in diverse ecological settings. SAPFLUXNET adds to existing plant trait datasets, ecosystem flux networks, and remote sensing products to help increase our understanding of plant water use, plant responses to drought, and ecohydrological processes. SAPFLUXNET version 0.1.5 is freely available from the Zenodo repository (10.5281/zenodo.3971689; Poyatos et al., 2020a). The "sapfluxnetr"R package-designed to access, visualize, and process SAPFLUXNET data-is available from CRAN.

Published
2021

25. The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data.

Author

Pastorello, Gilberto, Trotta, Carlo, Canfora, Eleonora, Chu, Housen, Christianson, Danielle, Cheah, You-Wei, Poindexter, Cristina, Chen, Jiquan, Elbashandy, Abdelrahman, Humphrey, Marty, Isaac, Peter, Polidori, Diego, Reichstein, Markus, Ribeca, Alessio, van Ingen, Catharine, Vuichard, Nicolas, Zhang, Leiming, Amiro, Brian, Ammann, Christof, Arain, M Altaf, Ardö, Jonas, Arkebauer, Timothy, Arndt, Stefan K, Arriga, Nicola, Aubinet, Marc, Aurela, Mika, Baldocchi, Dennis, Barr, Alan, Beamesderfer, Eric, Marchesini, Luca Belelli, Bergeron, Onil, Beringer, Jason, Bernhofer, Christian, Berveiller, Daniel, Billesbach, Dave, Black, Thomas Andrew, Blanken, Peter D, Bohrer, Gil, Boike, Julia, Bolstad, Paul V, Bonal, Damien, Bonnefond, Jean-Marc, Bowling, David R, Bracho, Rosvel, Brodeur, Jason, Brümmer, Christian, Buchmann, Nina, Burban, Benoit, Burns, Sean P, Buysse, Pauline, Cale, Peter, Cavagna, Mauro, Cellier, Pierre, Chen, Shiping, Chini, Isaac, Christensen, Torben R, Cleverly, James, Collalti, Alessio, Consalvo, Claudia, Cook, Bruce D, Cook, David, Coursolle, Carole, Cremonese, Edoardo, Curtis, Peter S, D'Andrea, Ettore, da Rocha, Humberto, Dai, Xiaoqin, Davis, Kenneth J, Cinti, Bruno De, Grandcourt, Agnes de, Ligne, Anne De, De Oliveira, Raimundo C, Delpierre, Nicolas, Desai, Ankur R, Di Bella, Carlos Marcelo, Tommasi, Paul di, Dolman, Han, Domingo, Francisco, Dong, Gang, Dore, Sabina, Duce, Pierpaolo, Dufrêne, Eric, Dunn, Allison, Dušek, Jiří, Eamus, Derek, Eichelmann, Uwe, ElKhidir, Hatim Abdalla M, Eugster, Werner, Ewenz, Cacilia M, Ewers, Brent, Famulari, Daniela, Fares, Silvano, Feigenwinter, Iris, Feitz, Andrew, Fensholt, Rasmus, Filippa, Gianluca, Fischer, Marc, Frank, John, Galvagno, Marta, and Gharun, Mana

Abstract

The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.

Published
2020

28. Correction: Influence of socio-economic status on functional recovery after ARDS caused by SARS-CoV-2: the multicentre, observational RECOVIDS study

Author

Declercq, Pierre-Louis, Fournel, Isabelle, Demeyere, Matthieu, Berraies, Anissa, Ksiazek, Eléa, Nyunga, Martine, Daubin, Cédric, Ampere, Alexandre, Sauneuf, Bertrand, Badie, Julio, Delbove, Agathe, Nseir, Saad, Artaud-Macari, Elise, Bironneau, Vanessa, Ramakers, Michel, Maizel, Julien, Miailhe, Arnaud-Felix, Lacombe, Béatrice, Delberghe, Nicolas, Oulehri, Walid, Georges, Hugues, Tchenio, Xavier, Clarot, Caroline, Redureau, Elise, Bourdin, Gaël, Federici, Laura, Adda, Mélanie, Schnell, David, Bousta, Mehdi, Salmon-Gandonnière, Charlotte, Vanderlinden, Thierry, Plantefeve, Gaëtan, Delacour, David, Delpierre, Cyrille, Le Bouar, Gurvan, Sedillot, Nicholas, Beduneau, Gaëtan, Rivière, Antoine, Meunier-Beillard, Nicolas, Gélinotte, Stéphanie, Rigaud, Jean-Philippe, Labruyère, Marie, Georges, Marjolaine, Binquet, Christine, and Quenot, Jean-Pierre

Published
2023
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32. The 2018 European heatwave led to stem dehydration but not to consistent growth reductions in forests

Author

Salomón, Roberto L., Peters, Richard L., Zweifel, Roman, Sass-Klaassen, Ute G. W., Stegehuis, Annemiek I., Smiljanic, Marko, Poyatos, Rafael, Babst, Flurin, Cienciala, Emil, Fonti, Patrick, Lerink, Bas J. W., Lindner, Marcus, Martinez-Vilalta, Jordi, Mencuccini, Maurizio, Nabuurs, Gert-Jan, van der Maaten, Ernst, von Arx, Georg, Bär, Andreas, Akhmetzyanov, Linar, Balanzategui, Daniel, Bellan, Michal, Bendix, Jörg, Berveiller, Daniel, Blaženec, Miroslav, Čada, Vojtěch, Carraro, Vinicio, Cecchini, Sébastien, Chan, Tommy, Conedera, Marco, Delpierre, Nicolas, Delzon, Sylvain, Ditmarová, Ľubica, Dolezal, Jiri, Dufrêne, Eric, Edvardsson, Johannes, Ehekircher, Stefan, Forner, Alicia, Frouz, Jan, Ganthaler, Andrea, Gryc, Vladimír, Güney, Aylin, Heinrich, Ingo, Hentschel, Rainer, Janda, Pavel, Ježík, Marek, Kahle, Hans-Peter, Knüsel, Simon, Krejza, Jan, Kuberski, Łukasz, Kučera, Jiří, Lebourgeois, François, Mikoláš, Martin, Matula, Radim, Mayr, Stefan, Oberhuber, Walter, Obojes, Nikolaus, Osborne, Bruce, Paljakka, Teemu, Plichta, Roman, Rabbel, Inken, Rathgeber, Cyrille B. K., Salmon, Yann, Saunders, Matthew, Scharnweber, Tobias, Sitková, Zuzana, Stangler, Dominik Florian, Stereńczak, Krzysztof, Stojanović, Marko, Střelcová, Katarína, Světlík, Jan, Svoboda, Miroslav, Tobin, Brian, Trotsiuk, Volodymyr, Urban, Josef, Valladares, Fernando, Vavrčík, Hanuš, Vejpustková, Monika, Walthert, Lorenz, Wilmking, Martin, Zin, Ewa, Zou, Junliang, and Steppe, Kathy

Published
2022
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34. Is lower motor control on the trunk in patients with non-specific chronic low back pain linked to difficulties in working despite functional restoration programs?

Author

Delpierre, Yannick A., Michaud, Sophie A., and Guênê, Vincent F.

Abstract

In the case of patients with Chronic Low Back Pain (cLBP), Functional Restoration Programs (FRP) can improve their condition. Chronicity may reoccur and lead to difficulties in the ability to work related to Fear-Avoidance Beliefs, which may depend on lower motor control. Rationale of the study : Whereas a limited clinical scale evaluates these beliefs, our study is justified by the search to define motor control parameters that can be used as quantified indicators of fear-avoidance beliefs associated with work activity. The aim of this study is to explore whether difficulty in working one year after participating in the FRP was related to low motor control in patients with cLBP. Two groups were defined as: "the patients who could work one year after FRP" (called W-Group) and "the patients who could not work one year after FRP because of cLBP" (called NW-Group). The clinical analysis is based on the assessment of pain intensity and the Fear-Avoidance Belief Questionnaire (or FABQ). Gait stability and coefficients of attenuation on four back levels were considered. The NW-Group had a significantly higher FABQ score than the W-Group one year after FRP (p = 0.02) without any difference regarding pain intensity (p = 0.31). The NW-Group (0.11 ± 0.02) presented significantly higher RMS values for the low back in the anteroposterior axis than the W-group (0.09 ± 0.01), showing lower gait stability in the NW-group. Motor control parameters reveal significant differences between these groups. Motor control and fear-avoidance beliefs are associated with work. [ABSTRACT FROM AUTHOR]

Published
2024
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40. Impact of a health literacy intervention combining general practitioner training and a consumer facing intervention to improve colorectal cancer screening in underserved areas: protocol for a multicentric cluster randomized controlled trial

Author

Durand, Marie-Anne, Lamouroux, Aurore, Redmond, Niamh M., Rotily, Michel, Bourmaud, Aurélie, Schott, Anne-Marie, Auger-Aubin, Isabelle, Frachon, Adèle, Exbrayat, Catherine, Balamou, Christian, Gimenez, Laëtitia, Grosclaude, Pascale, Moumjid, Nora, Haesebaert, Julie, Massy, Helene Delattre, Bardes, Julia, Touzani, Rajae, Diant, Laury Beaubrun en Famille, Casanova, Clémence, Seitz, Jean François, Mancini, Julien, and Delpierre, Cyrille

Published
2021
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42. Gene regulation contributes to explain the impact of early life socioeconomic disadvantage on adult inflammatory levels in two cohort studies

Author

Carmeli, Cristian, Kutalik, Zoltán, Mishra, Pashupati P., Porcu, Eleonora, Delpierre, Cyrille, Delaneau, Olivier, Kelly-Irving, Michelle, Bochud, Murielle, Dhayat, Nasser A., Ponte, Belen, Pruijm, Menno, Ehret, Georg, Kähönen, Mika, Lehtimäki, Terho, Raitakari, Olli T., Vineis, Paolo, Kivimäki, Mika, Chadeau-Hyam, Marc, Dermitzakis, Emmanouil, Vuilleumier, Nicolas, and Stringhini, Silvia

Published
2021
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43. Hypothermia for expanded criteria organ donors in kidney transplantation in France (HYPOREME): a multicentre, randomised controlled trial

Author

Canet, Emmanuel, Brule, Noëlle, Pere, Morgane, Feuillet, Fanny, Blancho, Gilles, Martin-Lefevre, Laurent, Garandeau, Claire, Asehnoune, Karim, Rozec, Bertrand, Duveau, Agnès, Dube, Laurent, Pierrot, Marc, Humbert, Stanislas, Tirot, Patrice, Boyer, Jean-Marc, Labadie, François, Robert, René, Benard, Thierry, Kerforne, Thomas, Thierry, Antoine, Lesieur, Olivier, Vincent, Jean-François, Lesouhaitier, Mathieu, Larmet, Raphaëlle, Vigneau, Cécile, Goepp, Angélique, Bouju, Pierre, Quentin, Charlotte, Egreteau, Pierre-Yves, Huet, Olivier, Renault, Anne, Le Meur, Yannick, Venhard, Jean-Christophe, Buchler, Matthias, Voellmy, Marie-Hélène, Herve, Fabien, Schnell, David, Courte, Anne, Glotz, Denis, Amrouche, Lucile, Hazzan, Marc, Kamar, Nassim, Moal, Valérie, Bourenne, Jérémy, Le Quintrec, Moglie, Morelon, Emmanuel, Kamel, Toufik, Grimbert, Philippe, Heng, Anne-Elisabeth, Merville, Pierre, Garin, Aude, Hiesse, Christian, Fermier, Brice, Mousson, Christiane, Guyot-Colosio, Charlotte, Bouvier, Nicolas, Rerolle, Jean-Philippe, Durrbach, Antoine, Drouin, Sarah, Caillard, Sophie, Frimat, Luc, Girerd, Sophie, Albano, Laetitia, Rostaing, Lionel, Bertrand, Dominique, Hertig, Alexandre, Westeel, Pierre-François, Montini, Florent, Delpierre, Eric, Dorez, Didier, Alamartine, Eric, Ouisse, Carole, Sébille, Véronique, and Reignier, Jean

Abstract

Expanded criteria donors help to increase graft availability, but provide organs with an increased risk of delayed graft function. We aimed to investigate whether donor hypothermia decreases the risk of delayed graft function compared with normothermia.

Published
2024
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