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Testing the Inference Accuracy of Accelerator-Friendly Approximate Phylogeny Tracking

Testing the Inference Accuracy of Accelerator-Friendly Appro...

2025 IEEE Symposium on Computational Intelligence in Artificial Life and Cooperative Intelligent Systems, ALIFE-CIS 2025

作者： Moreno, Matthew Andres Ranjan, Anika Dolson, Emily Zaman, Luis University of Michigan Department of Ecology and Evolutionary Biology Ann Arbor United States Center for the Study of Complex Systems University of Michigan Ann Arbor United States Michigan Institute for Data and Ai in Society University of Michigan Ann Arbor United States Undergraduate Research Opportunities Program University of Michigan Ann Arbor United States Michigan State University Department of Computer Science and Engineering East Lansing United States Program in Ecology Evolution and Behavior Michigan State University East Lansing United States

ISBN: (纸本)9798331508371

computer simulations are an important tool for studying the mechanics of biological evolution. In particular, agent-based approaches provide an opportunity to collect high-quality records of ancestry relationships. Such phylogenies can provide insight into evolutionary dynamics within these simulations. Previous work generally tracks lineages directly, yielding an exact phylogenetic record of evolutionary history. However, challenges exist in scaling direct ancestrytracking approaches to highly-distributed, many-processor evolution in silico. An alternative approach is to estimate phylogenetic history via noncoding annotations on digital genomes, akin to how bioinformaticians build phylogenies by assessing genetic similarities between organisms. Recent work has extended this 'hereditary stratigraphy' approach to support powerful hardware accelerator platforms, such as the Cerebras Wafer-Scale Engine. Although these second-generation 'surface'-based hereditary stratigraphy algorithms have demonstrated order-ofmagnitude speedups over first-generation 'column'-based algorithms, it remains unknown how they impact the accuracy of reconstructed phylogenies. To address this question, we assessed reconstruction accuracy under alternative configurations across a matrix of evolutionary conditions varying in selection pressure, spatial structure, and ecological dynamics. Encouragingly, we find that the second-generation approaches provide higher reconstruction quality across most surveyed conditions. © 2025 IEEE.

关键词： Biostratigraphy

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Slang Generation as Categorization 41

Slang Generation as Categorization

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41st Annual Meeting of the cognitive science Society: Creativity + Cognition + Computation, CogSci 2019

作者： Sun, Zhewei Zemel, Richard Xu, Yang Department of Computer Science University of Toronto Canada Department of Computer Science University of Toronto Vector Institute Canada Department of Computer Science Cognitive Science Program University of Toronto Canada

ISBN: (纸本)0991196775

Slang is a common device for expressivity in natural language. While slang has been studied extensively as a social phenomenon, its cognitive bases are not well understood. We formulate the processes of slang generation as a categorization problem. We explore a set of cognitive models of categorization that recommend slang words based on intended referents of the speaker beyond the existing senses of words. We test these models against a large repertoire of slang sense definitions from the Online Slang Dictionary and show that the categorization models predict slang word choices substantially better than chance, without explicit consideration of external social factors. We also show that words similar in existing senses tend to extend to similar novel slang senses, reflecting a process of parallel semantic change. Our work helps to ground theories of slang in cognitive models of categorization and provides the potential for machine processing of informal natural language. © cognitive science Society: Creativity + Cognition + Computation, CogSci *** rights reserved.

关键词： Computation theory

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ENIGMA-Meditation: Worldwide Consortium for Neuroscientific Investigations of Meditation Practices

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Biological Psychiatry: cognitive Neuroscience and Neuroimaging 2025年第4期10卷 425-436页

作者： Ganesan, Saampras Barrios, Fernando A. Batta, Ishaan Bauer, Clemens C.C. Braver, Todd S. Brewer, Judson A. Brown, Kirk Warren Cahn, Rael Cain, Joshua A. Calhoun, Vince D. Cao, Lei Chetelat, Gaël Ching, Christopher R.K. Creswell, J. David Dagnino, Paulina Clara Davanger, Svend Davidson, Richard J. Deco, Gustavo Dutcher, Janine M. Escrichs, Anira Eyler, Lisa T. Fani, Negar Farb, Norman A.S. Fialoke, Suruchi Fresco, David M. Garg, Rahul Garland, Eric L. Goldin, Philippe Hafeman, Danella M. Jahanshad, Neda Kang, Yoona Khalsa, Sahib S. Kirlic, Namik Lazar, Sara W. Lutz, Antoine McDermott, Timothy J. Pagnoni, Giuseppe Piguet, Camille Prakash, Ruchika S. Rahrig, Hadley Reggente, Nicco Saccaro, Luigi F. Sacchet, Matthew D. Siegle, Greg J. Tang, Yi-Yuan Thomopoulos, Sophia I. Thompson, Paul M. Torske, Alyssa Treves, Isaac N. Tripathi, Vaibhav Tsuchiyagaito, Aki Turner, Matthew D. Vago, David R. Valk, Sofie Zeidan, Fadel Zalesky, Andrew Turner, Jessica A. King, Anthony P. Department of Biomedical Engineering The University of Melbourne Carlton VIC Australia Contemplative Studies Centre Melbourne School of Psychological Sciences The University of Melbourne Melbourne VIC Australia Systems Lab of Neuroscience Neuropsychiatry and Neuroengineering The University of Melbourne Parkville VIC Australia Universidad Nacional Autónoma de México Instituto de Neurobiolgía México Querétaro Mexico Center for Translational Research in Neuroimaging and Data Science: Georgia State University Georgia Institute of Technology and Emory University Atlanta GA United States Department of Psychology Northeastern University Boston Massachusetts Brain and Cognitive Science McGovern Institute for Brain Research Massachusetts Institute of Technology Cambridge Massachusetts Department of Psychological and Brain Sciences Washington University St. Louis Missouri Department of Behavioral and Social Sciences Brown University School of Public Health Providence Rhode Island Department of Psychology Carnegie Mellon University Pittsburgh PA United States University of Southern California Department of Psychiatry & Behavioral Sciences Los Angeles California University of Southern California Center for Mindfulness Science Los Angeles California Institute for Advanced Consciousness Studies Santa Monica California Department of Psychiatry and Behavioral Health The Ohio State University College of Medicine Columbus OH United States Normandie University Université de Caen Normandie INSERM U1237 Neuropresage Team Cyceron Caen France Imaging Genetics Center Mark and Mary Stevens Neuroimaging and Informatics Institute Keck School of Medicine of the University of Southern California Los Angeles California Desert-Pacific Mental Illness Research Education and Clinical Center VA San Diego Healthcare System San Diego California Computational Neuroscience Group Center for Brain and Cognition Department of Information and Communication Technologies Universitat Pompeu Fa

Meditation is a family of ancient and contemporary contemplative mind-body practices that can modulate psychological processes, awareness, and mental states. Over the last 40 years, clinical science has manualized meditation practices and designed various meditation interventions that have shown therapeutic efficacy for disorders including depression, pain, addiction, and anxiety. Over the past decade, neuroimaging has been used to examine the neuroscientific basis of meditation practices, effects, states, and outcomes for clinical and nonclinical populations. However, the generalizability and replicability of current neuroscientific models of meditation have not yet been established, because they are largely based on small datasets entrenched with heterogeneity along several domains of meditation (e.g., practice types, meditation experience, clinical disorder targeted), experimental design, and neuroimaging methods (e.g., preprocessing, analysis, task-based, resting-state, structural magnetic resonance imaging). These limitations have precluded a nuanced and rigorous neuroscientific phenotyping of meditation practices and their potential benefits. Here, we present ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis)–Meditation, the first worldwide collaborative consortium for neuroscientific investigations of meditation practices. ENIGMA-Meditation will enable systematic meta- and mega-analyses of globally distributed neuroimaging datasets of meditation using shared, standardized neuroimaging methods and tools to improve statistical power and generalizability. Through this powerful collaborative framework, existing neuroscientific accounts of meditation practices can be extended to generate novel and rigorous neuroscientific insights that account for multidomain heterogeneity. ENIGMA-Meditation will inform neuroscientific mechanisms that underlie therapeutic action of meditation practices on psychological and cognitive attributes, thereby advancing the f

关键词： Consortium ENIGMA Magnetic resonance imaging (MRI) Meditation Mindfulness Neuroimaging

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Artificial visual perception neural system using a solution-processable MoS_(2)-based in-memory light sensor

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Light(science & Applications) 2023年第8期12卷 1583-1594页

作者： Dayanand Kumar Lana Joharji Hanrui Li Ayman Rezk Ammar Nayfeh Nazek El-Atab Smart Advanced Memory Devices and Applications(SAMA)LaboratoryElectrical and Computer Engineering ProgramComputer Electrical Mathematical Science and Engineering DivisionKing Abdullah University of Science and Technology(KAUST)Thuwal 23955Kingdom of Saudi Arabia Department of Electrical Engineering and Computer Science Khalifa UniversityAbu Dhabi 127788United Arab Emirates

Optoelectronic devices are advantageous in in-memory light sensing for visual information processing,recognition,and storage in an energy-efficient ***,in-memory light sensors have been proposed to improve the energy,area,and time efficiencies of neuromorphic computing *** study is primarily focused on the development of a single sensing-storage-processing node based on a two-terminal solution-processable MoS2 metal-oxide-semiconductor(MOS)charge-trapping memory structure—the basic structure for charge-coupled devices(CCD)—and showing its suitability for in-memory light sensing and artificial visual *** memory window of the device increased from 2.8 V to more than 6V when the device was irradiated with optical lights of different wavelengths during the program ***,the charge retention capability of the device at a high temperature(100 ℃)was enhanced from 36 to 64%when exposed to a light wavelength of 400 *** larger shift in the threshold voltage with an increasing operating voltage confirmed that more charges were trapped at the Al_(2)O_(3)/MoS_(2) interface and in the MoS_(2) layer.A small convolutional neural network was proposed to measure the optical sensing and electrical programming abilities of the *** array simulation received optical images transmitted using a blue light wavelength and performed inference computation to process and recognize the images with 91%*** study is a significant step toward the development of optoelectronic MOS memory devices for neuromorphic visual perception,adaptive parallel processing networks for in-memory light sensing,and smart CCD cameras with artificial visual perception capabilities.

关键词： visual neural process

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CHARACTERISTICS OF JUNCTIONS MADE BETWEEN PB AND BI2SR2CACU2O8+X

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IEEE TRANSACTIONS ON MAGNETICS 1991年第2期27卷 935-938页

作者： YANG, YF NORDMAN, JE Materials Science Program Department of Electrical and Computer Engineering University of Wisconsin Madison Madison WI USA

Investigations on the junctions made between Pb and polycrystalline Bi2Sr2CaCu2O8+x (BSCCO) are reported. The BSCCO surfaces were treated with number of methods including mechanically scraping, plasma sputtering, plasma oxidation, and Br etch before junctions were fabricated. The current-voltage characteristics and dynamic resistance (dV/dI) vs voltage have been measured at both 77K and 4.2K. We observed, among other features, a Pb gap structure similar to that seen in Pb/YBa2Cu3O7-delta junctions, a magnetic dependent supercurrent, an asymmetric I-V curve, and narrow resistance peaks. Properties of junctions prepared in different manners are compared. Both XPS and electrical studies indicated that Br etch is not suitable for the BiSrCaCuO system in spite of its successful application in YBa2Cu3O7-delta.

关键词： Plasma measurements Bismuth compounds Plasma applications Plasma properties Strontium Surface resistance Surface treatment Sputtering Oxidation Sputter etching

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Time-Frequency Masking for Speech Separation and Its Potential for Hearing Aid Design

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Trends in Amplification 2008年第4期12卷 332-353页

作者： Wang, Deliang Department of Computer Science & Engineering Center for Cognitive Science The Ohio State University Columbus Ohio United States

A new approach to the separation of speech from speech-in-noise mixtures is the use of time-frequency (T-F) masking. Originated in the field of computational auditory scene analysis, T-F masking performs separation in the time-frequency domain. This article introduces the T-F masking concept and reviews T-F masking algorithms that separate target speech from either monaural or binaural mixtures, as well as microphone-array recordings. The review emphasizes techniques that are promising for hearing aid design. This article also surveys recent studies that evaluate the perceptual effects of T-F masking techniques, particularly their effectiveness in improving human speech recognition in noise. An assessment is made of the potential benefits of T-F masking methods for the hearing impaired in light of the processing constraints of hearing aids. Finally, several issues pertinent to T-F masking are discussed. © 2008, SAGE Publications. All rights reserved.

关键词： computational auditory scene analysis hearing aids ideal binary mask time-frequency masking

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Prototype theory and emotion semantic change 42

Prototype theory and emotion semantic change

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42nd Annual Meeting of the cognitive science Society: Developing a Mind: Learning in Humans, Animals, and Machines, CogSci 2020

作者： Xu, Aotao Stellar, Jennifer Xu, Yang Department of Computer Science University of Toronto Canada Department of Psychology University of Toronto Canada Department of Computer Science Cognitive Science Program University of Toronto Canada

An elaborate repertoire of emotions is one feature that distinguishes humans from animals. Language offers a critical form of emotion expression. However, it is unclear whether the meaning of an emotion word remains stable, and what factors may underlie changes in emotion meaning. We hypothesize that emotion word meanings have changed over time and that the prototypicality of an emotion term drives this change beyond general factors such as word frequency. We develop a vector-space representation of emotion and show that this model replicates empirical findings on prototypicality judgments and basic categories of emotion. We provide evidence that more prototypical emotion words have undergone less change in meaning than peripheral emotion words over the past century, and that this trend holds within each family of emotion. Our work extends synchronic theories of emotion to its diachronic development and offers a computational characterization of emotion semantics in natural language use. © 2020 The Author(s)

关键词： Semantics

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Tracing the emergence of gendered language in childhood 42

Tracing the emergence of gendered language in childhood

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42nd Annual Meeting of the cognitive science Society: Developing a Mind: Learning in Humans, Animals, and Machines, CogSci 2020

作者： Prystawski, Ben Grant, Erin Nematzadeh, Aida Lee, Spike W.S. Stevenson, Suzanne Xu, Yang Computer Science and Cognitive Science Programs University of Toronto Canada Department of Electrical Engineering & Computer Sciences University of California Berkeley United States DeepMind Rotman School of Management Department of Psychology University of Toronto Canada Department of Computer Science University of Toronto Canada Department of Computer Science Cognitive Science Program University of Toronto Canada

Are gender associations in general language reflected in the words spoken to and by children? Previous work has suggested that language reveals gender differences in discourse, speech style, language use and acquisition. Work in artificial intelligence has shown that word embeddings trained on large corpora reflect human gender associations. We connect this work to developmental psychology by exploring whether gender associations in word embeddings are present in the linguistic input and output of children, and if so, how early gendered language emerges. We present a computational method that quantifies the gender associations of words and use a corpus of child-caretaker speech to show that these gender associations correlate significantly with those in word embeddings. We discover that gendered word use emerges in English-speaking children around age 2, and the gender associations cannot be explained solely by variables including word length, frequency, concreteness, and valence. © 2020 The Author(s)

关键词： Embeddings

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Quantitative Analysis of Colonic Epithelial Cell Aging in a Cell-cycle like Model: Changes in Nucleus and Cytoplasm Along the Crypt Axis

Quantitative Analysis of Colonic Epithelial Cell Aging in a ...

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Medical Imaging 2025: Digital and Computational Pathology

作者： Bao, Shunxing Wang, Yaohong Rudravaram, Gaurav Zhang, Rendong Deng, Ruining Yu, Xin Gao, Chenyu Li, Jia Li, Yike Roland, Joseph T. Zuo, Lianrui Liu, Qi Lau, Ken S. Coburn, Lori A. Wilson, Keith T. Landman, Bennett A. Huo, Yuankai Department of Electrical and Computer Engineering Vanderbilt University NashvilleTN United States Department of Anatomical Pathology UT MD Anderson Cancer Center HoustonTX United States Department of Computer Science Vanderbilt University NashvilleTN United States Department of Biostatistics Vanderbilt University Medical Center Nashville United States Department of Otolaryngology-Head and Neck Surgery Vanderbilt University Medical Center NashvilleTN United States Department of Surgery Vanderbilt University Medical Center NashvilleTN United States Department of Cell and Developmental Biology Vanderbilt University School of Medicine NashvilleTN United States Vanderbilt University Medical Center Division of Gastroenterology Hepatology and Nutrition Department of Medicine Nashville United States Vanderbilt University Medical Center Vanderbilt Center for Mucosal Inflammation and Cancer Nashville United States Vanderbilt University School of Medicine Program in Cancer Biology Nashville United States Veterans Affairs Tennessee Valley Healthcare System NashvilleTN United States Vanderbilt University Medical Center Department of Pathology Microbiology and Immunology NashvilleTN United States

ISBN: (纸本)9781510686045

Understanding epithelial cell aging in bowel tissue can provide critical insights into gastrointestinal (GI) health, potentially leading to improved diagnosis, treatment, and prevention strategies for various GI conditions. Despite the significance of cellular aging in the GI tract, previous studies have not quantified epithelial cell maturity development along the base-to-surface axis of colon crypts due to the labor-intensive nature of manual quantification and the lack of a clear definition of cellular age. Moreover, the process faces tremendous challenges when tissue is cut in 2D and examines results solely from one or a few biopsy cuts without reconstructing the full 3D space, as the original cell structure is 3D, leading to variability based on the cut angle. This research addresses these challenges by systematically analyzing the relationship between epithelial cell morphology and their position from the base to the surface in colon crypt tissue. Our approach involves using multiplex immunofluorescence (MxIF) imaging for cell nuclei segmentation, identifying the potential full longitudinal cut, and manually annotating the surface and base of the colon crypts. By analyzing the epithelial cells, we create density maps to investigate the relationship between nucleus size and the surface-to-base distance ratio, defining this ratio as cell age. We also examine the nucleus-to-cytoplasm (N/C) ratio in relation to cell age. For the statistical analysis, we use a robust linear regression model to remove outliers and a random effects model for the final regression. Our results show a decreasing trend in both the N/C ratio and nucleus size as epithelial cells move from the base to the surface. These findings provide a quantitative pipeline for single-cell profiling in a spatial manner, facilitating broader analysis of epithelial cell aging and its implications for GI health. © 2025 SPIE.

关键词： Linear regression

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Answer set programming on expert feedback to populate and extend dynamic ontologies

Answer set programming on expert feedback to populate and ex...

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21th International Florida Artificial Intelligence Research Society Conference, FLAIRS-21

作者： Niepert, Mathias Buckner, Cameron Allen, Colin Indiana University Department of Computer Science Indiana University Department of Philosophy Indiana University Department History and Philosophy of Science Program in Cognitive Science

ISBN: (纸本)9781577353652

The next generation of online reference works will require structured representations of their contents in order to support scholarly functions such as semantic search, automated generation of cross-references, tables of contents, and ontology-driven conceptual navigation. Many of these works can be expected to contain massive amounts of data and be updated dynamically, which limits the feasibility of "manually" coded ontologies to keep up with changes in content. However, relationships relevant to inferring an ontology can be recovered from statistical text processing, and these estimates can be verified with carefully-solicited expert feedback. In this paper, we explain a method by which we have used answer set programming on such expert feedback to dynamically populate and partially infer an ontology for a well-established, open-access reference work, the Stanford Encyclopedia of Philosophy. Copyright © 2008, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Ontology

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