DTCMMA: Efficient Wind-Power Forecasting Based on Dimensional Transformation Combined with Multidimensional and Multiscale Convolutional Attention Mechanism by Wenhan Song, Enguang Zuo, Junyu Zhu, Chen Chen, Cheng Chen, Ziwei Yan, Xiaoyi Lv

“…Experiments on multiple wind-farm datasets and energy-related datasets demonstrate that DTCMMA outperforms mainstream methods such as Transformer, iTransformer, and TimeMixer in long-sequence forecasting tasks, achieving improvements in MSE performance by 34.22%, 2.57%, and 0.51%, respectively. …”
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Artificial intelligence possibilities to improve analytical policy capacity: the case of environmental policy innovation labs and sustainable development goals by Adam M. Wellstead, Sidney M. Mechling, Angie Carter, Anat Gofen

“…Policy analysts dedicate a great deal of their time performing routine tasks including collecting information, identifying policy issues and options, and appraising policy options. …”
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From Peer-Reviewed to Peer-Reproduced in Scholarly Publishing: The Complementary Roles of Data Models and Workflows in Bioinformatics. by Alejandra González-Beltrán, Peter Li, Jun Zhao, Maria Susana Avila-Garcia, Marco Roos, Mark Thompson, Eelke van der Horst, Rajaram Kaliyaperumal, Ruibang Luo, Tin-Lap Lee, Tak-Wah Lam, Scott C Edmunds, Susanna-Assunta Sansone, Philippe Rocca-Serra

“…By structuring the information in the published paper using these data and scientific workflow modelling frameworks, it was possible to explicitly declare elements of experimental design, variables, and findings. …”
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GeoMM-SSL: Integrating Geospatial Object Relations in Multimodal Self-Supervised Learning for Semantic Segmentation of Remote Sensing Images by Yang Liu, Tong Zhang, Yanru Huang

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The skin allergy risk assessment-integrated chemical environment (SARA-ICE) defined approach to derive points of departure for skin sensitization by Emily N. Reinke, Joe Reynolds, Nicola Gilmour, Georgia Reynolds, Judy Strickland, Dori Germolec, David G. Allen, Gavin Maxwell, Nicole C. Kleinstreuer

“…This resulted in the development of defined approaches (DAs), as documented in OECD TG 497, for combining information sources in a prescriptive manner to provide a determination of risk or potency. …”
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'More than just numbers on a page?' A qualitative exploration of the use of data collection and feedback in youth mental health services. by Craig Hamilton, Kate Filia, Sian Lloyd, Sophie Prober, Eilidh Duncan

“…YMH services, healthcare commissioners should collaborate on ME plans and meaningfully involve young people and families where possible. Targets, performance indicators, and outcome measures should explicitly link to YMH service quality improvement; and ME plans should include qualitative data. …”
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LorDist: a novel method for calculating the distance based on functional data analysis with application to longitudinal microbial data by Xinhe Qi, Menghan Zhang, Tongqing Wei, Jinran Lin, Xingming Zhao, Yin Yao, Yueqing Hu, Yan Zheng

“…Our findings demonstrate LorDist’s robust performance on real-world data sets involving inflammatory bowel disease and infant gut development. …”
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Enhancing the sustainability of rabbit production from the perspective of animal genetics by Juan Pablo Sánchez

“…In this framework, omic tools will perform a valuable role for further investigation of the biological basis controlling the major drivers of rabbit production sustainability, and hopefully in the future this information could be directly incorporated into breeding programmes.…”
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Recurrent predictive coding models for associative memory employing covariance learning. by Mufeng Tang, Tommaso Salvatori, Beren Millidge, Yuhang Song, Thomas Lukasiewicz, Rafal Bogacz

“…This makes the structure of the model inconsistent with the known connectivity of CA3 and classical recurrent models such as Hopfield Networks, which learn the covariance of inputs through their recurrent connections to perform AM. Earlier PC models that learn the covariance information of inputs explicitly via recurrent connections seem to be a solution to these issues. …”
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Measurement-guided therapeutic-dose prediction using multi-level gated modality-fusion model for volumetric-modulated arc radiotherapy by Changfei Gong, Changfei Gong, Changfei Gong, Yuling Huang, Yuling Huang, Yuling Huang, Junming Jian, Junming Jian, Junming Jian, Wenheng Zheng, Wenheng Zheng, Wenheng Zheng, Xiaoping Wang, Xiaoping Wang, Xiaoping Wang, Shenggou Ding, Shenggou Ding, Shenggou Ding, Yun Zhang, Yun Zhang, Yun Zhang

“…The effective prediction model explicitly integrates the multi-scale features that are specific to CT and dose images, takes into account the useful spatial dose information and fully exploits the mutual promotion within the different modalities. …”
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A Novel Hybrid Quantum-Crypto Standard to Enhance Security and Resilience in 6G-Enabled IoT Networks by Kranthi Kumar Singamaneni, Anil Kumar Budati, Shayla Islam, Raenu A. L. Kolandaisamy, Ghulam Muhammad

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Perbandingan Pretrained Model Transformer pada Deteksi Ulasan Palsu by Aisyah Awalina, Fitra Abdurrachman Bachtiar, Fitri Utaminingrum

“…Abstract The ease of obtaining information today has helped our lives, like looking for reviews to weigh the place or item to choose. …”
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Multi-Level Feature Dynamic Fusion Neural Radiance Fields for Audio-Driven Talking Head Generation by Wenchao Song, Qiong Liu, Yanchao Liu, Pengzhou Zhang, Juan Cao

“…We initially developed a multi-level tri-plane hash representation that uses three sets of tri-plane hash networks with varying resolutions of limitation to capture the dynamic information of the face more accurately. Then, we introduce the idea of multi-head attention and design an efficient audio-visual fusion module that explicitly fuses audio features with image features from different planes, thereby improving the mapping between audio features and spatial information. …”
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Architecture-aware minimization (A2M): how to find flat minima in neural architecture search by Matteo Gambella, Fabrizio Pittorino, Manuel Roveri

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Loop-invariant Optimization in the Pifagor Language by Vladimir S. Vasilev, Alexander I. Legalov

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Charting progress in learning health systems: A systematic review of 5 years of definitions, models, and frameworks by Louise A. Ellis, Georgia Fisher, Maree Saba, Genevieve Dammery, Kate Churruca, Samantha Spanos, Carolynn L. Smith, Bianca Forrester, Yvonne Zurynski, Jeffrey Braithwaite

“…Articles were included that explicitly focused on LHSs and described an LHS definition, model, or framework. …”
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Combining Machine Learning With Real-World Data to Identify Gaps in Clinical Practice Guidelines: Feasibility Study Using the Prospective German Stroke Registry and the National Ac... by Sandrine Müller, Susanne Diekmann, Markus Wenzel, Horst Karl Hahn, Johannes Tuennerhoff, Ulrike Ernemann, Florian Hennersdorf, Max Westphal, Sven Poli

“…Using intravenous thrombolysis in large vessel occlusion stroke as a model, our findings suggest that treatment decisions may be influenced by factors not explicitly included in the current German guideline, such as patient age and pre-stroke functional status. …”
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Planning Amidst Uncertainty: Identifying Core CCS Infrastructure Robust to Storage Uncertainty by Daniel Olson, Sean Yaw

“…To address this challenge, we propose a novel optimization workflow that is based on mixed-integer linear programming and explicitly integrates probabilistic modeling of storage uncertainty into CCS infrastructure design. …”
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Uncertainty Quantification in Shear Wave Velocity Predictions: Integrating Explainable Machine Learning and Bayesian Inference by Ayele Tesema Chala, Richard Ray

“…Additionally, a Bayesian GLM is developed to explicitly account for uncertainties arising from geotechnical variability. …”
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Some Weighted Sum Formulas for Multiple Zeta, Hurwitz Zeta, and Alternating Multiple Zeta Values by Yuan He, Zhuoyu Chen

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