Four experiments were conducted to examine the extent to which readers construct elaborative inferences on-line during reading. In Experiment 1, gaze durations were measured while subjects read anaphors to target antecedents that referenced a particular category member either explicitly or implicitly. When the context strongly suggested a particular category member, gaze durations on an anaphor were the same following either an implicit or an explicit antecedent. When the context did not suggest any particular category member, gaze durations were significantly longer following an implicit antecedent. The results confirmed that, with sufficient context, readers will generate a simple elaborative inference on-line. These results were replicated in Experiment 2 in which the materials did not strongly signal the inference but a sentence designed to encourage subjects to infer was included. In Experiment 3, this "demand sentence" was not included, and readers did not appear to construct the targeted inference. The results of Experiment 4 confirmed that once generated, elaborative inferences are stored as part of the long-term-memory representation of a passage.
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http://dx.doi.org/10.1037//0278-7393.14.3.410 | DOI Listing |
Small Methods
January 2025
Department of Pathology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, 510080, China.
Accurately defining cell boundaries for spatial transcriptomics is technically challenging. The current major approaches are nuclear staining or mathematical inference, which either exclude the cytoplasm or determine a hypothetical boundary. Here, a new method is introduced for defining cell boundaries: labeling cell membranes using genetically coded fluorescent proteins, which allows precise indexing of sequencing spots and transcripts within cells on sections.
View Article and Find Full Text PDFInt J Mol Sci
January 2025
School of Mathematics and Computer Science, Gannan Normal University, Ganzhou 341000, China.
Due to advances in big data technology, deep learning, and knowledge engineering, biological sequence visualization has been extensively explored. In the post-genome era, biological sequence visualization enables the visual representation of both structured and unstructured biological sequence data. However, a universal visualization method for all types of sequences has not been reported.
View Article and Find Full Text PDFBMC Med Res Methodol
January 2025
University of Michigan, Ann Arbor, MI, USA.
Background: The generation of metainferences is a core and significant feature of mixed methods research. In recent years, there has been some discussion in the literature about criteria for appraising the quality of metainferences, the processes for generating them, and the critical role that assessing the "fit" of quantitative and qualitative data and results plays in this generative process. However, little is known about the types of insights that emerge from generating metainferences.
View Article and Find Full Text PDFComput Struct Biotechnol J
December 2024
Systems Biology Center, Key Laboratory of Engineering Biology for Low-carbon Manufacturing, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China.
DNA holds immense potential as an emerging data storage medium. However, the recovery of information in DNA storage systems faces challenges posed by various errors, including IDS errors, strand breaks, and rearrangements, inevitably introduced during synthesis, amplification, sequencing, and storage processes. Sequence reconstruction, crucial for decoding, involves inferring the DNA reference from a cluster of erroneous copies.
View Article and Find Full Text PDFInterdiscip Sci
January 2025
School of Life Sciences, Northwestern Polytechnical University, Xi'an, 710072, China.
Metabolism in vivo turns small molecules (e.g., drugs) into metabolites (new molecules), which brings unexpected safety issues in drug development.
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