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Jiaming Li, Ning Xie and Tingting Zhao
In recent years, with the rapid advancements in Natural Language Processing (NLP) technologies, large models have become widespread. Traditional reinforcement learning algorithms have also started experimenting with language models to optimize training. ...
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Jessica A. Gonzalez, Nora M. A. Ponce, Mariana Lozada, Yasmín Daglio, Carlos A. Stortz and Hebe M. Dionisi
The glycoside hydrolase 107 (GH107) family includes fucanase enzymes from only two bacterial phyla, Bacteroidota and Pseudomonadota. The goal of this work was to explore the diversity of putative fucanase enzymes related to this family in organisms of th...
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Guangwei Jia, Sheng Li, Feilong Jie, Yanyan Ge, Na Liu and Fuli Liang
This study employs the Driving Force?Pressure?State?Response (DPSR) framework to establish an evaluation index system for the water resource carrying capacity (WRCC) in the Cele?Yutian Oasis (China). Utilizing the TOPSIS and obstacle degree models, we an...
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Jeonghoon Lee, Jeonghyeon Choi, Jiyu Seo, Jeongeun Won and Sangdan Kim
In the context of hydrological model calibration, observational data play a central role in refining and evaluating model performance and uncertainty. Among the critical factors, the length of the data records and the associated climatic conditions are p...
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Norah Abanmi, Heba Kurdi and Mai Alzamel
The prevalence of malware attacks that target IoT systems has raised an alarm and highlighted the need for efficient mechanisms to detect and defeat them. However, detecting malware is challenging, especially malware with new or unknown behaviors. The ma...
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