Validation of an interferon-gamma enzyme-linked immunosorbent spot assay to evaluate cell-mediated immunity against severe acute respiratory syndrome coronavirus 2 by Yunhwa Kim, Eun-Jeong Jang, Ji-Young Hwang, Kyung-Min Lee, Sivilay Xayaheuang, Seok-Tae Choi, Hosun Park

“…Taken together, we demonstrated that the IFN-γ ELISpot assay is feasible for evaluating SARS-CoV-2-specific cell-mediated immune function through validation based on standard operating procedures.…”
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AI-guided laser purification of human iPSC-derived cardiomyocytes for next-generation cardiac cell manufacturing by Prakaimuk Saraithong, Peyton Krajcarski, Yukako Kusaka, Moe Yamada, Junichi Matsumoto, Hailey Cunningham, Sama Salih, Darby Jones, Devika Baddhan, Christian Hausner, Justus Anumonwo, Anthony Rosenzweig, Mary M. Navarro, Luis Villa Diaz, Joseph Criscione, Deok-Ho Kim, Todd J. Herron

“…This streamlined process preserves cardiomyocyte viability and function, offering a scalable and efficient solution for cardiac regenerative medicine, disease modeling, and drug discovery.…”
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Data-driven modeling and regression analysis on ship resistance of in-service performance by Daehyuk Kim, Shin Hyung Rhee

“…The analysis of added resistance due to waves shows significant, but sometimes inconsistent, transfer function coefficients, suggesting simpler model structures could be more effective. …”
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Root‐Zone Water‐Storage Capacity and Uncertainty: An Intrinsic Factor Affecting Agroecosystem Resilience to Drought by Nunzio Romano, Caterina Mazzitelli, Paolo Nasta

“…Root‐zone water‐storage capacity (SR) is a commonly used variable of agroecosystem functioning, representing the maximum value of water stored within the root zone and accessible to vegetation for its productive growth. …”
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Compositional and nutritional value of lupin cultivars: Identifying high-protein seeds for enhanced protein isolate production and phytochemical valorisation by Pau Taberner-Pibernat, Albert Ribas-Agustí, Gisela Quinteros, Gerard Sabeña, Miguel López-Gómez, Rubén Domínguez-Valencia, Ricard Bou

“…The findings revealed significant inter- and intra-species variability in protein, total dietary fibre, and fat content among the studied cultivars. …”
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Advancing geohazard risk assessment – A digital tool for steep slope management by Cherry Rose Godes, One-Bin Lim, Shanelle Aira Rodrigazo, Yongseong Kim, Yongjin Kim, Seungjoo Lee, Jaeheum Yeon

“…Growing climatic variability and rapid urbanization have increased landslide occurrences, posing significant challenges for risk assessment. …”
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Same data, different results? Machine learning approaches in bioacoustics by Kaja Wierucka, Derek Murphy, Stuart K. Watson, Nikola Falk, Claudia Fichtel, Julian León, Stephan T. Leu, Peter M. Kappeler, Elodie F. Briefer, Marta B. Manser, Nikhil Phaniraj, Marina Scheumann, Judith M. Burkart

“…We investigated the impact of using different feature extraction (spectro‐temporal measurements, linear and Mel‐frequency cepstral coefficients (MFCC), as well as highly comparative time‐series analysis) and classification methods (discriminant function analysis, neural networks, random forests (RF), and support vector machines) on the consistency of caller identity classification accuracy across 16 mammalian datasets. …”
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Optimization of Mangiferin extraction from Mangifera Indica leaves Peruvian Criollo variation using ultrasound assisted surface response methodology by Elena Sofia Espinoza Rodríguez, Stephanie Elena Sosa Pulcha, Naysha Y. M․ Elguera, Abdel Alejandro Portocarrero Banda, Hugo Guillermo Jiménez Pacheco

“…Additionally, FTIR analysis demonstrated that the extracted mangiferin preserved key functional groups such as hydroxyl (-OH), carbonyl (C = O), and aromatic C = C bonds. …”
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On the added value of sequential deep learning for the upscaling of evapotranspiration by B. Kraft, B. Kraft, B. Kraft, J. A. Nelson, S. Walther, F. Gans, U. Weber, G. Duveiller, M. Reichstein, W. Zhang, M. Rußwurm, D. Tuia, M. Körner, Z. Hamdi, M. Jung

“…We compared different types of covariates (meteorological without precipitation, precipitation, remote sensing, and plant functional types) and their impact on model performance at the site level in a cross-validation setup.…”
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Integrated transportation system planning with gravitational search algorithm approach based on fuzzy mutant controller by Alireza Hosseinzadeh Kashani, Seyed Ahmad Shayannia, Mohammad Mehdi Movahedi, Soheila Sardar

“…The efficiency of the gravity search algorithm and the mutated gravity search algorithm is better in functions F4, F7, F11, F21. …”
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Improving Electrical Distance Accuracy for Cable Fault Location Based on the Prony Method by Xiang Ren, Zhiqiang Feng, Kai Zhou, Xueming Zhou, Jianjun Yuan, Yefei Xu, Li Zhang

“…By establishing a frequency-variable coupling model containing the transfer function of the cable with double joint structure, studying the mapping relationship between the cable attenuation constant and the electromagnetic wave velocity, and adopting the Prony estimation method combined with the singular value decomposition noise reduction algorithm to achieve the extraction of the attenuation constant and the decoupling of the segmented wave velocity, thus improving the electrical accuracy of fault location. …”
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Mobile machine design through dynamic load simulation on their drive units by S. A. Partko, L. M. Groshev, A. N. Sirotenko

“…The root cause for the occurrence of vibration effects is the profile irregularity of the mobile machine path, and the variability of physicomechanical characteristics of the soil. …”
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Intelligent Field Sensor Station for Monitoring Agrophysical Parameters and Phenotyping in Precision Agriculture System by S. A. Vasilyev, S. Ye. Limonov, S. A. Mishin

“…(Results and discussion) The intelligent field sensor station successfully demonstrated its efficiency, confirming both its functionality and reliability in simultaneous data collection. …”
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Observational partitioning of water and CO₂ fluxes at National Ecological Observatory Network (NEON) sites: a 5-year dataset of soil and plant components for spatial... by E. Zahn, E. Bou-Zeid

“…<p>Long-term time series of transpiration, evaporation, plant net photosynthesis, and soil respiration are essential for addressing numerous research questions related to ecosystem functioning. However, quantifying these fluxes is challenging due to the lack of reliable and direct measurement techniques, which has left gaps in the understanding of their temporal cycles and spatial variability. …”
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AESware: Developing AES-enabled low-power multicore processors leveraging open RISC-V cores with a shared lightweight AES accelerator by Eunjin Choi, Jina Park, Kyuseung Han, Woojoo Lee

“…AESware supports variable key lengths and ensures minimal power consumption with a compact design. …”
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Fuzzy rank fusion of deep neural networks for weed identification in groundnut crop by Akshay Dheeraj, Rajnish Kumar Chaturvedi, Sapna Nigam, Md. Ashraful Haque, Sudeep Marwaha

“…By combining selective and variable rate spraying, the smart herbicide sprayer effectively manages herbicide amounts. …”
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Artificial intelligence Defect Detection Robustness inReal-time Non-Destructive Testing of Metal Surfaces by Chaoyu Dong, Jovian Sanjaya Putra, Andrew A. Malcolm

“…Their structural integrity, durability, and functionality depend heavily on their quality, making surface inspection a vital process. …”
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Genome-wide association study of blood vitamin D metabolites and bone remodelling markers in pigs by Dipanwita Paul, Michael Oster, Siriluck Ponsuksili, Klaus Wimmers, Henry Reyer

“…Hence, mineral utilization efficiency might be indirectly improved which remains to be empirically demonstrated through further research.…”
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Toward generalizable prediction of antibody thermostability using machine learning on sequence and structure features by Ameya Harmalkar, Roshan Rao, Yuxuan Richard Xie, Jonas Honer, Wibke Deisting, Jonas Anlahr, Anja Hoenig, Julia Czwikla, Eva Sienz-Widmann, Doris Rau, Austin J. Rice, Timothy P. Riley, Danqing Li, Hannah B. Catterall, Christine E. Tinberg, Jeffrey J. Gray, Kathy Y. Wei

“…In this work, we show two machine learning approaches – one with pre-trained language models (PTLM) capturing functional effects of sequence variation, and second, a supervised convolutional neural network (CNN) trained with Rosetta energetic features – to better classify thermostable scFv variants from sequence. …”
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AER-Net: Attention-Enhanced Residual Refinement Network for Nuclei Segmentation and Classification in Histology Images by Ruifen Cao, Qingbin Meng, Dayu Tan, Pijing Wei, Yun Ding, Chunhou Zheng

“…Moreover, the coarse predictions and refined predictions are combined by using a loss function that employs cross-entropy loss and generalized dice loss to efficiently tackle the challenge of class imbalance among nuclei in histology images. …”
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