Designing a Smart Leadership Model for Education Managers by mehdi oliyaee, aliakbar ajam, Ahmad Akbari, turaj falah mehne

“…Therefore, the present study, with the aim of designing and developing a model for smart leadership in education using the interpretive structural modeling technique, seeks to design and present a model for smart leadership in education, and answer the question: what the interpretive structural model of smart leadership in education looks like? …”
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Graph theoretical model of a sensorimotor connectome in zebrafish. by Michael Stobb, Joshua M Peterson, Borbala Mazzag, Ethan Gahtan

“…The lesion decreased the number of short paths between sensory and motor neurons analogous to the behavioral effects of the same lesion in zebrafish. This model is expandable and can be used to organize and interpret a growing database of information on the zebrafish connectome.…”
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Modelling Population Genetic Screening in Rare Neurodegenerative Diseases by Thomas P. Spargo, Alfredo Iacoangeli, Mina Ryten, Francesca Forzano, Neil Pearce, Ammar Al-Chalabi

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High‐Resolution National‐Scale Water Modeling Is Enhanced by Multiscale Differentiable Physics‐Informed Machine Learning by Yalan Song, Tadd Bindas, Chaopeng Shen, Haoyu Ji, Wouter J. M. Knoben, Leo Lonzarich, Martyn P. Clark, Jiangtao Liu, Katie vanWerkhoven, Sam Lamont, Matthew Denno, Ming Pan, Yuan Yang, Jeremy Rapp, Mukesh Kumar, Farshid Rahmani, Cyril Thébault, Richard Adkins, James Halgren, Trupesh Patel, Arpita Patel, Kamlesh Arun Sawadekar, Kathryn Lawson

“…Overall, our results show how neural‐network‐based parameterizations can improve NWM performance for providing operational flood predictions while maintaining interpretability and multivariate outputs. The modeling system supports the Basic Model Interface (BMI), which allows seamless integration with the next‐generation NWM. …”
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Longitudinal Data Regression Analysis Using Semiparametric Modelling by Abdulla Mamun, Sudhir Paul

“…With unconstrained structures, they also suggest future research on modelling the mean, the variance, and the correlations non-parametrically and semiparametrically. …”
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Assessing the Accuracy of Diagnostic Capabilities of Large Language Models by Andrada Elena Urda-Cîmpean, Daniel-Corneliu Leucuța, Cristina Drugan, Alina-Gabriela Duțu, Tudor Călinici, Tudor Drugan

“…<b>Background:</b> In recent years, numerous artificial intelligence applications, especially generative large language models, have evolved in the medical field. This study conducted a structured comparative analysis of four leading generative large language models (LLMs)—ChatGPT-4o (OpenAI), Grok-3 (xAI), Gemini-2.0 Flash (Google), and DeepSeek-V3 (DeepSeek)—to evaluate their diagnostic performance in clinical case scenarios. …”
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Knowledge Graphs and Their Reciprocal Relationship with Large Language Models by Ramandeep Singh Dehal, Mehak Sharma, Enayat Rajabi

“…Conversely, KGs serve as structured and interpretable data sources that improve the transparency, factual consistency and reliability of LLM-based applications, mitigating challenges such as hallucinations and lack of explainability. …”
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Finite element modeling of anatomical constitutional types of the lumbar spine and pelvis (Roussouly) for study of the biomechanical aspects by Shulga Alexey E., Ulyanov Vladimir Yu., Rozhkova Yuliya Yu., Shuvalov Stanislav D.

“…Results The highest von Mises stresses under compression were measured in the bodies and intervertebral discs (IVD) ThX–LI (2.961 MPa), posterior supporting structures LIV–SI (2.515 Mpa) with type I model; vertebral bodies and IVD of the thoracic and lumbar spine, mainly at the ThXII–LI (3.082 MPa) and LIV– LV (3.120 Mpa) levels with type II model; anterior aspects of the bodies and IVD ThXI–LII, posterior thirds of the bodies, pedicles and facet joints LI–SI (1.720 Mpa) with type III model; the bodies and intervertebral discs of the ThIX–LII vertebrae (1.811 MPa), posterior supporting structures of the LI–SI vertebrae (1.650 Mpa) with type IIIA model; in the spinous processes and articular portion of the arches of the LI–SI vertebrae (3.232 MPa) with type IV model. …”

Echo-ODE: A dynamics modeling network with neural ODE for temporally consistent segmentation of video echocardiograms by Wenliang Lu, Yuan Wang , Wenli Dai , Yingnan Wu , Hao Xu, Hao Xu, Dexing Kong

“…Stable and consistent segmentation of cardiac structures is essential for a reliable fully automatic echocardiogram interpretation.MethodsWe propose a novel framework Echo-ODE, where the heart is regarded as a dynamical system, and we model the representation of dynamics by neural ordinary differential equations. …”
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Developing Basic Football Techniques Model in Football Schools by Arsil Arsil, Anton Komaini, Sri Gusti Handayani, Heru Andika, Muhamad Ichsan Sabillah

“…The results of data analysis and interpretation show that (1) the model follows the principles of necessary skills training in playing football; (2) it is useful to be used to optimize the basic technical skills of playing football; and (3) it can be applied as a guide in carrying out the training process, especially for children aged 11–12 years…”
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From answers to questions: the Q-centric model of intelligence by Mehrdad Ghasemizadeh

“…One way to understand “answers” is as recombinations within lived interpretation—temporary syntheses that organize experience into coherent conceptual structures. …”
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The Formulation of Construction Model for the Future of Professional Sports in Iran by Zahra Sohrabi, Mehrdad Moharramzadeh, Abbas Naghizadeh-Baghi, Nasrin Azizan Kohan

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A Localized Model for Branding in the Iranian Dairy Industry by Shaghayegh Sabaghi, Alireza Rousta, Farzad Asayesh

“…The absence of a specific branding model can be interpreted as a primary factor contributing to the disregard of branding activities by dairy company managers. …”
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Network Receptive Field Modeling Reveals Extensive Integration and Multi-feature Selectivity in Auditory Cortical Neurons. by Nicol S Harper, Oliver Schoppe, Ben D B Willmore, Zhanfeng Cui, Jan W H Schnupp, Andrew J King

“…In conclusion, we demonstrate that fitting auditory cortical neural responses with feedforward network models expands on simple linear receptive field models in a manner that yields substantially improved predictive power and reveals key nonlinear aspects of cortical processing, while remaining easy to interpret in a physiological context.…”
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Prediction model for the selection of patients with glioma to proton therapy by Jesper Folsted Kallehauge, Siri Grondahl, Camilla Skinnerup Byskov, Morten Høyer, Slavka Lukacova

“…Background and purpose: The selection of patients with low-grade gliomas for proton therapy (PT) is often based on the comparison of photon and PT plans and demonstrating meaningful dose reduction to the healthy brain or critical structures. The aim of this retrospective study was to identify clinical parameters associated with referral to PT and build a prediction model. …”
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Synonymic and hypero-hyponymic paradigm of the delimitation between media discourse and mass communication media discourse by B. A. Shishkin

“…The research consisted of four stages, illustrating the relationships of the structural elements of the textual communication model. …”
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A hermeneutics of literary identities by Katica Kjulavkova

“…Therefore, its unriddling divinatory interpretation provides an excellent initial interpretative model for any fictional narrative text. …”
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Mechanics and analog modeling of the Huo-Ma-Tu thrust sheet in the southern Junggar Basin fold and thrust belt by YANG Geng, CHEN Zhuxin, LU Xuesong, ZHANG Yuqing

“…The physical modeling results also verify that the deformation pattern of strong deformation sheets/weak detachment fault thrust sheets generally conform to the structural interpretations of the seismic profiles. …”
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Advancing thyroid diagnosis: integrating AI-driven CAD framework with numerical data and ultrasound images by Saleh Ateeq Almutairi

“…The framework uses cutting edge technologies, including Vision Transformers (ViTs) and SHapley Additive exPlanations (SHAPs), to increase diagnostic accuracy, interpretability, and clinical applicability. The proposed CAD framework employs the sparse search algorithm (SSA) for optimized feature selection from numerical data and the tree-structured Parzen estimator for tuning the hyperparameters. …”
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Model for the peptide-free conformation of class II MHC proteins. by Corrie A Painter, Anthony Cruz, Gustavo E López, Lawrence J Stern, Zarixia Zavala-Ruiz

“…The binding observed for these probes is in agreement with the movements predicted by the model.<h4>Conclusion/significance</h4>This work presents a molecular model for peptide-free class II MHC proteins that can help to interpret the conformational changes known to occur within the protein during peptide binding and release, and can provide insight into possible mechanisms for DM action.…”
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