A Comprehensive Survey of Fake Text Detection on Misinformation and LM-Generated Texts by Soonchan Kwon, Beakcheol Jang

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FusOn-pLM: a fusion oncoprotein-specific language model via adjusted rate masking by Sophia Vincoff, Shrey Goel, Kseniia Kholina, Rishab Pulugurta, Pranay Vure, Pranam Chatterjee

“…Employing a unique cosine-scheduled masked language modeling strategy, FusOn-pLM dynamically adjusts masking rates (15%–40%) to optimize feature extraction and representation quality, surpassing baseline embeddings in fusion-specific tasks, including localization, puncta formation, and disorder prediction. …”
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Application Analysis of the Language Model by Cai Bochao

“…Language models(LM) like Claude3, ChatGPT and Llamas have prominent development recent years. …”
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Deep Learning in Music Generation: A Comprehensive Investigation of Models, Challenges and Future Directions by Kong Xiangchen

“…The objective of emotion-conditioned models, such as ECMusicLM, is to combine music with emotional cues so that the output has a stronger emotional resonance. …”
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Performance Evaluation of Large Language Models in Cervical Cancer Management Based on a Standardized Questionnaire: Comparative Study by Warisijiang Kuerbanjiang, Shengzhe Peng, Yiershatijiang Jiamaliding, Yuexiong Yi

“…Seven models (ChatGPT-4.0 Turbo, Claude 2, Gemini Pro, Mistral-7B-v0.2, Starling-LM-7B alpha, HuatuoGPT, and BioMedLM 2.7B) provided stable responses. …”
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Assessing the role of genotype by environment interaction of winter wheat cultivars using envirotyping techniques in North China by Haiwang Yue, Yanbing Wang, Zhaoyang Chen, Jiashuai Zhu, Partha Pratim Behera, Pengcheng Liu, Haoxiang Yang, Jianwei Wei, Junzhou Bu, Xuwen Jiang, Xuwen Jiang, Wujun Ma

“…The Additive Main Effects and Multiplicative Interaction (AMMI) model indicates that the first three interaction principal component axes (IPCAs) account for over 70% of the GEI variance, thereby demonstrating the relevance of this model to the current study. …”
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International norms for adult handgrip strength: A systematic review of data on 2.4 million adults aged 20 to 100+ years from 69 countries and regions by Grant R. Tomkinson, Justin J. Lang, Lukáš Rubín, Ryan McGrath, Bethany Gower, Terry Boyle, Marilyn G. Klug, Alexandra J. Mayhew, Henry T. Blake, Francisco B. Ortega, Cristina Cadenas-Sanchez, Costan G. Magnussen, Brooklyn J. Fraser, Tetsuhiro Kidokoro, Yang Liu, Kaare Christensen, Darryl P. Leong, Mette Aadahl, Edimansyah Abdin, Julian Alcazar, Aqeel Alenazi, Bader Alqahtani, Cledir De A. Amaral, Thatiana L.M. Amaral, Alex Andrade Fernandes, Peter Axelsson, Jennifer N. Baldwin, Karin Bammann, Aline R. Barbosa, Ameline Bardo, Inosha Bimali, Peter Bjerregaard, Martin Bobak, Colin A. Boreham, Klaus Bös, João Carlos Bouzas Marins, Joshua Burns, Nadezda Capkova, Lilia Castillo-Martínez, Liang-Kung Chen, Siu Ming Choi, Rebecca K.J. Choong, Susana C. Confortin, Cyrus Cooper, Jorge E. Correa-Bautista, Amandine Cournil, Grace Cruz, Eling D. de Bruin, José Antonio De Paz, Bruno De Souza Moreira, Luiz Antonio Dos Anjos, María Cristina Enríquez Reyna, Eduardo Ferriolli, Gillian Forrester, Elena Frolova, Abadi K. Gebre, Atef M. Ghaleb, Tiffany K. Gill, Yasuyuki Gondo, M. Cristina Gonzalez, Citlali Gonzalez Alvarez, Mary K. Hannah, Nicholas C. Harvey, Jean-Yves Hogrel, Marie-Theres Huemer, Toshiko Iidaka, Lewis A. Ingram, Dmitri A. Jdanov, Victoria L. Keevil, Wolfgang Kemmler, Rose Anne Kenny, Dae-Yeon Kim, Tracy L. Kivell, Ingirid G.H. Kjær, Alexander Kluttig, Rumi Kozakai, Danit Langer, Lisbeth A. Larsen, Wei-Ju Lee, David A. Leon, Eric Lichtenstein, Bertis B. Little, Roberto Alves Lourenço, Rahul Malhotra, Robert M. Malina, Kiyoaki Matsumoto, Tal Mazor-Karsenty, Marnee J. McKay, Sinéad McLoughlin, Abhishek L. Mensegere, Mostafa Mohammadian, Virgilio Garcia Moreira, Hiroshi Murayama, Anne Murray, Anita Liberalesso Neri, Claudia Niessner, Gabriel Núñez Othón, Gabriel Olveira, Suzanne G. Orchard, Andrezj Pajak, Chan Woong Park, Julie A. Pasco, Maria E. Peña Reyes, Leani Souza Máximo Pereira, Annette Peters, Eric Tsz-Chun Poon, Margareth C. Portela, Jedd Pratt, Robinson Ramírez-Vélez, Wendy Rodríguez-García, Joanne Ryan, Mauricio A. San-Martín, Francisco José Sánchez-Torralvo, Mahnaz Saremi, Arno Schmidt-Trucksäss, Satoshi Seino, Shamsul Azhar Shah, Marc Sim, Bjørn Heine Strand, Mythily Subramaniam, Charlotte Suetta, Sophia X. Sui, Jonas S. Sundarakumar, Koya Suzuki, Abdonas Tamosiunas, Maw Pin Tan, Yu Taniguchi, Barbara Thorand, Anna Turusheva, Anne Therese Tveter, Jonathan Wagner, Dao Wang, Stuart J. Warden, Julia Wearing, Shiou Liang Wee, Leo D. Westbury, Agnieszka Wiśniowska-Szurlej, Alexander Woll, Noriko Yoshimura, Ruby Yu

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WNT11 Promotes immune evasion and resistance to Anti-PD-1 therapy in liver metastasis by Weiliang Jiang, Bingjie Guan, Hongcheng Sun, Yushuai Mi, Sanjun Cai, Rong Wan, Xinxiang Li, Peng Lian, Dawei Li, Senlin Zhao

“…Moreover, CAMKII inhibition increases the efficacy of anti-PD-1 therapy in mouse model of LM. Serum expression of WNT11 is identified as a potential minimally invasive biomarker in the management of colorectal cancer-LM with immunotherapy. …”
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Analysis of reservoir rock permeability changes due to solid precipitation during waterflooding using artificial neural network by Azizollah Khormali, Soroush Ahmadi, Aleksandr Nikolaevich Aleksandrov

“…Tansig was the most effective transfer function for the hidden layers. The ANN model using the Levenberg-Marquardt (LM) algorithm showed superior performance with the lowest mean squared error (MSE) for training, testing, and all data sets. …”
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Penerapan Decision Tree dan Random Forest dalam Deteksi Tingkat Stres Manusia Berdasarkan Kondisi Tidur by Sza Sza Amulya Larasati, Elok Nuraida Kusuma Dewi, Brahma Hanif Farhansyah, Fitra Abdurrachman Bachtiar, Fajar Pradana

“…In other words, the values of these three features are inversely proportional to the level of stress experienced. The Decision Tree model has an accuracy of 0.99, and the Random Forest model has an accuracy of 1.0. …”
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Ethanolamine-induced assembly of microcompartments is required for Fusobacterium nucleatum virulence by Dana S. Franklin, Yi-Wei Chen, Yimin Chen, Manuel Wittchen, Angela Agnew, Alexis Luu, Julian P. Whitelegge, Z. Hong Zhou, Andreas Tauch, Asis Das, Hung Ton-That

“…The formation of F. nucleatum BMCs, containing BMC shell proteins EutLM1M2N, is controlled by a two-component system, EutV-EutW, responsive to EA. …”
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Neural Network-Based Lower Limb Prostheses Control Using Super Twisting Sliding Mode Control by Adisu Tadese Demora, Chala Merga Abdissa

“…The neural network structure is built using Feed-forward Neural Network (FFNN) architecture and Levenberg-Marquardt (LM) back-propagation training algorithm for accuracy, fast convergence, and reliable optimization of nonlinear relationships. …”
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