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The rapid uptake of electric vehicles presents both opportunities and challenges for modern power systems. As charging demand increases, intelligent and data-driven approaches are essential to predict and manage future grid impacts. This paper presents a probabilistic and data-driven approach for generating realistic electric vehicle charging profiles, which can be integrated into probabilistic lo
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Eye movements originally made during memory formation are often spontaneously reproduced during retrieval, even in the absence of visual input, directing gaze back to the locations where goal-relevant episodic information was previously encountered. This behavior, known as gaze reinstatement, is thought to support the reactivation of episodic content associated with those locations (e.g., Johansso
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SLOPE is a popular method for dimensionality reduction in high-dimensional regression. Its estimated coefficients can be zero, yielding sparsity, or equal in absolute value, yielding clustering. As a result, SLOPE can eliminate irrelevant predictors and identify groups of predictors that have the same influence on the response. The concept of the SLOPE pattern allows us to formalize and study its
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This research employed GC-MS metabolomics profiling on bulbs of three genera i.e., Ornithogalum, Loncomelos, and Melomphis (Asparagaceae), to elucidate their taxonomic relationships. The analysis of 30 specimens across 8 species (Ornithogalum comprising 3 species: O. cuspidatum, O. neurostegium, O. orthophyllum; Loncomelos including 4 species: L. arcuatum, L. brachystachys, L. bungei, L. kurdicum;
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This interview-based study seeks to gain insight into the varying motivations behind car usage across different societal groups, alongside their attitudes towards travel behavior and transportation options. Its overarching goal is to delve deeper into the factors and constraints that influences individuals’ car use and mode choice. The research methodology involves collecting one-month travel data