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Relevant bibliographies by topics / Modularized morphology

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Academic literature on the topic 'Modularized morphology'

Author: Grafiati

Published: 25 May 2024

Last updated: 31 July 2025

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Journal articles on the topic "Modularized morphology"

1

Katičić, Antigone. "Early verb development in one Croatian-speaking child." ZAS Papers in Linguistics 18 (January 1, 2000): 115–28. http://dx.doi.org/10.21248/zaspil.18.2000.61.

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This paper shows the early development of the first approximately 50 verbs found in the recorded speech production of one Croatian girl. The aim is to analyse and interpret the child's verb development in terms of the distinction of a pre- and a protomorphological phase before modularised morphology in language acquisition (Dressler & Karpf 1995). Furthermore, focus will be laid on the emergence of first verb paradigms.

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2

Black, Corinthia R., and Jonathan W. Armbruster. "Evolutionary integration and modularity in the diversity of the suckermouth armoured catfishes." Royal Society Open Science 9, no. 11 (2022). http://dx.doi.org/10.1098/rsos.220713.

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The evolution of morphological diversity has held a long-standing fascination among scientists. In particular, do bodies evolve as single, integrated units or do different body parts evolve semi-independently (modules)? Suckermouth armoured catfishes (Loricariidae) have a morphology that lends nicely to evolutionary modularity and integration studies. In addition to a ventrally facing oral jaw that directly contacts surfaces, the neurocranium and pectoral girdle are fused, which limits movement of the anterior part of the body. Functional constraints suggest it is likely the head and post-cran

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3

Cao, Jianfeng, Lihan Hu, Guoye Guan, et al. "CShaperApp: Segmenting and analyzing cellular morphologies of the developing Caenorhabditis elegans embryo." Quantitative Biology, May 16, 2024. http://dx.doi.org/10.1002/qub2.47.

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AbstractCaenorhabditis elegans has been widely used as a model organism in developmental biology due to its invariant development. In this study, we developed a desktop software CShaperApp to segment fluorescence‐labeled images of cell membranes and analyze cellular morphologies interactively during C. elegans embryogenesis. Based on the previously proposed framework CShaper, CShaperApp empowers biologists to automatically and efficiently extract quantitative cellular morphological data with either an existing deep learning model or a fine‐tuned one adapted to their in‐house dataset. Experimen

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4

Yuan, Jianbo, Yerui Fan, and Yaxiong Wu. "Design and input saturation control with full-state constraints of lightweight tendon-driven musculoskeletal arm." Robotic Intelligence and Automation, March 29, 2023. http://dx.doi.org/10.1108/ria-11-2022-0268.

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Purpose This study aims to propose a novel lightweight tendon-driven musculoskeletal arm (LTDM-arm) robot with a flexible series–parallel mixed skeletal joint structure and modularized artificial muscle system (MAMS). The proposed LTDM-arm exhibits human-like flexibility, safety and operational accuracy. In addition, to improve the safety and stability of the LTDM-arm, a control method is proposed to solve local artificial muscle overload accidents. Design/methodology/approach The proposed LTDM-arm comprises seven degrees of freedom skeletons, 15 MAMSs and various sensor systems (joint sensing

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Huang, Shin-Jhe, Chien-Chang Chen, Yamin Kao, and Henry Horng-Shing Lu. "Feature-aware unsupervised lesion segmentation for brain tumor images using fast data density functional transform." Scientific Reports 13, no. 1 (2023). http://dx.doi.org/10.1038/s41598-023-40848-5.

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AbstractWe demonstrate that isomorphically mapping gray-level medical image matrices onto energy spaces underlying the framework of fast data density functional transform (fDDFT) can achieve the unsupervised recognition of lesion morphology. By introducing the architecture of geometric deep learning and metrics of graph neural networks, gridized density functionals of the fDDFT establish an unsupervised feature-aware mechanism with global convolutional kernels to extract the most likely lesion boundaries and produce lesion segmentation. An AutoEncoder-assisted module reduces the computational

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Mohammedhasan, Mali, and Harun Uğuz. "A New Deeply Convolutional Neural Network Architecture for Retinal Blood Vessel Segmentation." International Journal of Pattern Recognition and Artificial Intelligence, August 26, 2020, 2157001. http://dx.doi.org/10.1142/s0218001421570019.

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This paper proposes an incoming Deep Convolutional Neural Network (CNN) architecture for segmenting retinal blood vessels automatically from fundus images. Automatic segmentation performs a substantial role in computer-aided diagnosis of retinal diseases; it is of considerable significance as eye diseases as well as some other systemic diseases give rise to perceivable pathologic changes. Retinal blood vessel segmentation is challenging because of the excessive changes in the morphology of the vessels on a noisy background. Previous deep learning-based supervised methods suffer from the insuff

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Dissertations / Theses on the topic "Modularized morphology"

1

Teveny, Sarah. "Acquisition des morphèmes grammaticaux libres par des enfants atteints de surdité moyenne; Analyse multidimensionnelle." Electronic Thesis or Diss., Paris 3, 2023. http://www.theses.fr/2023PA030035.

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Lorsqu’elle apparait dans les premiers mois de l’enfant, la surdité moyenne (pertes auditives entre 40dB et 70dB) peut entrainer des difficultés dans l’acquisition du langage, notamment en ce qui concerne la phonologie et la morphologie (Briscoe et al., 2001; Norbury et al., 2001; Tuller & Delage, 2014). Cette thèse étudie les réalisations des morphèmes grammaticaux libres en position prénominale et préverbale chez ces enfants, en étudiant l’influence de facteurs pragmatiques, morphologiques et phonologiques et l’interaction entre différents niveaux de difficulté. La variabilité des résult

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