From energy to ecology: decarbonization pathways for sustainable high-performance computing through global carbon-energy nexus analysis by Guancong Yu, Ziyan Wang, Yulan Xu, Zhuofan Javan Sun, Susan Chen

“…We analyzed data from the top 500 HPC centers, using linear regression to fill in missing values for max power due to a high Pearson correlation. …”
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KANDiff: Kolmogorov–Arnold Network and Diffusion Model-Based Network for Hyperspectral and Multispectral Image Fusion by Wei Li, Lu Li, Man Peng, Ran Tao

“…However, when dealing with multimodal data, it may prove challenging for the models to fully capture the intricate relationships between the modalities, which may result in incomplete information integration and a small amount of remaining noise in the generated images. …”
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Digital technology-enhanced reconstruction and rehabilitation following mandible fibular flap grafting with implants: a case report by Shuang Li, Shuang Li, Jian Liu, Jian Li, Baoheng Yin, Baoheng Yin, Yuanyong Feng, Yanshan Liu, Na Bai, Na Bai

“…ObjectiveIn this paper, we report a case of missing posterior teeth after mandibular fibular flap grafting and implant restoration by means of a digital restorative process, in the hope that the application of digital technology will help the patient to comfortably establish an adapted occlusal relationship.Case reportA 29-year-old male patient developed a left mandibular ameloblastoma measuring 35 mm × 35 mm × 25 mm, which did not invade the surrounding bone tissue, submandibular gland tissue, or lymph nodes. …”
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Factors affecting the quality of postoperative rehabilitation in children with cochlear implants based on the theory of knowledge, attitude and practice by Jing Ma, Xia Li, Ken Lin, Yiyun Zhang, Wenyue Chi, Xiuli Ma, Dong Su, Yuling Du, Tiesong Zhang

“…Responses were recorded meticulously.Setting Data were collected through a convenience sampling method at a children’s hospital.Participants Out of 840 questionnaires distributed, 683 completed questionnaires were retained for analysis after excluding responses with missing data.Results Parents’ average KAP score was 8.03 (SD = 3.13). …”
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Feature Enhancement Network for Infrared Small Target Detection in Complex Backgrounds Based on Multi-Scale Attention Mechanism by Sen Zhang, Weilin Du, Yuan Liu, Ni Zhou, Zheng Li

“…Furthermore, the integration of Normalized Wasserstein–Gaussian Distance (NWD) aims to tackle the convergence issues associated with the increased sensitivity of bounding box regression in identifying minor infrared targets. …”
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Large Language Models can extract morphological data from taxonomic descriptions, but their stochastic nature makes automation challenging: a test on Australian Asteraceae by Alexander N. Schmidt-Lebuhn, Nunzio Knerr

“…This makes their responses not fully reproducible and their integration into automated workflows difficult. Future work could explore if results can be improved using approaches such as Retrieval Augmented Generation or fine tuning of models on explanations of morphological terminology. …”
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Robust Gas Demand Prediction Using Deep Neural Networks: A Data-Driven Approach to Forecasting Under Regulatory Constraints by Kostiantyn Pavlov, Olena Pavlova, Tomasz Wołowiec, Svitlana Slobodian, Andriy Tymchyshak, Tetiana Vlasenko

“…Implementing these models requires careful integration with data management, regulatory frameworks, and operational workflows.…”
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National and Alternative Reports on the Implementation of the European Social Charter (Revised) as a Principle of Human Rights Compliance by Yu. F. Ivanov, M. V. Ivanova

“…It is emphasised that Ukraine's integration into the European legal space and the fulfilment of its obligations under the Association Agreement with the European Union require the harmonisation of national legislation with European standards. …”
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Towards including soil ecotoxicity of microplastics and tire wear particles into life cycle assessment by Merve Tunali, Bernd Nowack

“…Despite a lot of research of the effects of microplastics and tire wear particles on individual soil organisms, an evaluation of their overall impact on soil ecosystems is still missing. Thus, it is not possible to assess their complete effects. …”
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Perceived acceptance, intention to use and actual use behavior of digital information technologies among nursing professionals in Shanghai: a cross-sectional study by Hui Xie, Pengjie Zhang, Wei Zhu

“…Therefore, policies and interventions should be developed to enhance the integration of DITs into nursing professionals’ daily practice.…”
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Optimizing Stroke Risk Prediction: A Primary Dataset‐Driven Ensemble Classifier With Explainable Artificial Intelligence by Md. Maruf Hossain, Md. Mahfuz Ahmed, Md. Rakibul Hasan Rakib, Mohammad Osama Zia, Rakib Hasan, Md. Rakibul Islam, Md. Shohidul Islam, Md Shahariar Alam, Md. Khairul Islam

“…Additionally, Explainable Artificial Intelligence (XAI) techniques such as SHAP and LIME were integrated to elucidate key features influencing stroke prediction. …”
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Hybrid Machine Learning-Based Fault-Tolerant Sensor Data Fusion and Anomaly Detection for Fire Risk Mitigation in IIoT Environment by Jayameena Desikan, Sushil Kumar Singh, A. Jayanthiladevi, Shashi Bhushan, Vinay Rishiwal, Manish Kumar

“…These sensor issues, such as noise, missing values, outliers, sensor drift, and faulty readings, can lead to delayed or missed fire predictions, posing significant safety and operational risks in the oil and gas industrial IoT environment. …”
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Density Logging Curve Reconstruction Method Based on Bayesian-Optimized CNN-LSTM by LI Hongxi, CHEN Mingjiang, ZHANG Xiankun, YANG Bo, ZHAO Bin, LI Xiansheng, WANG Huanhuan

“…During logging operations, instrument malfunctions or borehole enlargement often lead to missing or distorted density logging data, compromising reservoir evaluation accuracy. …”
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Spatiotemporal Analysis and Anomalous Trends of Asia AOD (2001–2024): Insights from a Deep Learning Fusion Model and EOF Decomposition by Yu Ding, Wenjia Ni, Jiaxin Dong, Jie Yang, Shiyao Meng, Siwei Li

“…However, satellite-derived AOD datasets frequently suffer from missing values due to factors such as cloud cover, algorithmic limitations, and various atmospheric conditions. …”
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From manual clinical criteria to machine learning algorithms: Comparing outcome endpoints derived from diverse electronic health record data modalities. by Shreya Chappidi, Mason J Belue, Stephanie A Harmon, Sarisha Jagasia, Ying Zhuge, Erdal Tasci, Baris Turkbey, Jatinder Singh, Kevin Camphausen, Andra V Krauze

“…<h4>Background</h4>Progression free survival (PFS) is a critical clinical outcome endpoint during cancer management and treatment evaluation. Yet, PFS is often missing from publicly available datasets due to the current subjective, expert, and time-intensive nature of generating PFS metrics. …”
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The Insights Gained during the Development of a Personalised Nutrition Mobile App by Barbara Koroušić Seljak, Matevž Ogrinc, Andraž Simčič, Eva Valenčič, Robert Modic, Gordana Ispirova, Tome Eftimov

“…Additionally, methodologies were developed to support missing data imputation in a semi-automated way, and DBMS was designed to manage missing dietary recommendations in a machine-readable format. …”
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Classification and recognition method of dangerous behaviors of electric power operators based on improved OpenPose algorithm by Ningtao Liu, Jie Du, Shiliang Chang, Ke Zheng, Ji Xiao, Jiaming Zhang, Shishun Tan

“…Additionally, a spatiotemporal graph convolution model integrating a graph attention mechanism is constructed to analyze the spatiotemporal characteristics. …”
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Tensor-Based Uncoupled and Incomplete Multi-View Clustering by Yapeng Liu, Wei Guo, Weiyu Li, Jingfeng Su, Qianlong Zhou, Shanshan Yu

“…Specifically, the proposed method recovers missing samples in a low-dimensional feature space. …”
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Limited-angle x-ray nano-tomography with machine-learning enabled iterative reconstruction engine by Chonghang Zhao, Mingyuan Ge, Xiaogang Yang, Yong S. Chu, Hanfei Yan

“…Abstract A long-standing challenge in tomography is the ‘missing wedge’ problem, which arises when the acquisition of projection images within a certain angular range is restricted due to geometrical constraints. …”
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Few-Shot Flood Water Level Prediction Based on Mechanistic Models and Deep Learning: A Collaborative HEC-RAS-LSTM Framework by Li Faxian, Lv Mou, Li Hang

“…High-quality hydrological data are generated through HEC-RAS to address the issue of missing observed data. And the simulation data are used to drive a neural network model (LSTM) for flood water level prediction. …”
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