Improving learning and confidence through small group, structured otoscopy teaching: a prospective interventional study by Peng You, Saad Chahine, Murad Husein

“…In this study, we aimed to examine the effect of a small-group, structured teaching session on medical students’ confidence with and learning of otoscopic examination. …”
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University-based physical education as a structured temporal and spatial opportunity for shaping health-oriented lifestyles by Lu Zhang, Tao Zhong, Kui Dong

“…Logistic regression analyses confirmed that PE attendance was a protective factor against these unhealthy behaviors, with significant gender-based differences observed in lifestyle patterns.ConclusionThis study highlights the importance of PE in promoting healthier lifestyles among university students and underscores the need for continued access to structured PE programs throughout the undergraduate years.…”
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Bayesian deep-learning structured illumination microscopy enables reliable super-resolution imaging with uncertainty quantification by Tao Liu, Jiahao Liu, Dong Li, Shan Tan

“…Abstract The objective of optical super-resolution imaging is to acquire reliable sub-diffraction information on bioprocesses to facilitate scientific discovery. Structured illumination microscopy (SIM) is acknowledged as the optimal modality for live-cell super-resolution imaging. …”
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Impact of a Structured Social Skills Training Program on Adolescents and Young Adults with Level 1 Autism by Leonardo Zoccante, Sara Sabaini, Erika Rigotti, Sophia Marlene Bonatti, Camilla Lintas, Marco Zaffanello

“…This study aims to evaluate the effectiveness of a structured social skills training programme for adolescents and young adults with level 1 ASD. …”
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Is AI the future of evaluation in medical education?? AI vs. human evaluation in objective structured clinical examination by Murat Tekin, Mustafa Onur Yurdal, Çetin Toraman, Güneş Korkmaz, İbrahim Uysal

“…Abstract Background Objective Structured Clinical Examinations (OSCEs) are widely used in medical education to assess students’ clinical and professional skills. …”
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Diabetes care in the pandemic era in the Midwestern USA: a semi-structured interview study of the patient perspective by Shakoora A Sabree, Kimberly Dukes, Carolina Gonzalez Bravo, Morolake J Adeagbo, Sarai Edwards, Kasey Wainwright, Sienna E Schaeffer, Aneli Villa, Aloha D Wilks, Martha L Carvour

“…Objectives To understand patients’ experiences with diabetes care during the COVID-19 pandemic, with an emphasis on rural, medically underserved, and/or minoritised racial and ethnic groups in the Midwestern USA.Design Community-engaged, semi-structured interviews were conducted by medical student researchers trained in qualitative interviewing. …”
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Predicting the Flexural Modulus of Variable Pitch Angle, Porous Bouligand Structured 3D Printed Polymer by Praveenkumar S. Patil, Edward D. McCarthy, Parvez Alam

“…Our model is expressed as <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>E</mi><mi>f</mi></msub><mo>=</mo><msub><mi>E</mi><mrow><mi>p</mi><mi>o</mi><mi>r</mi><mi>o</mi></mrow></msub><mrow><mo>(</mo><mi>a</mi><msubsup><mi>θ</mi><mi>f</mi><mn>3</mn></msubsup><mo>+</mo><mi>b</mi><msubsup><mi>θ</mi><mi>f</mi><mn>2</mn></msubsup><mo>+</mo><mi>c</mi><msub><mi>θ</mi><mi>f</mi></msub><mo>+</mo><mi>d</mi><mo>)</mo></mrow></mrow></semantics></math></inline-formula>, and we derive this by applying non-linear regression to our experimental data. This model predicts the flexural modulus, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>E</mi><mi>f</mi></msub></semantics></math></inline-formula>, of porous Bouligand structured polymer as a function of both porosity and pitch angle. …”
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Spatiotemporal tensor analysis for effective information mining of hydraulic structures considering environmental excitation and vibration response by Hui Li, Zhang Han, Tengfei Bao, Xiaohan Duan, Guang Yang, Xianyu Xiong, Yibo Ouyang, Jiankang Lou

“…Abstract The vibration response data is a key foundation of vibration-based hydraulic structures’ online damage diagnosis. …”
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Optimisation of the performance and structure of soluble ball seat metal sealing rings based on response surface by CHEN Zhen, RAN Qingjie, CHEN Nengpeng, WANG Qiaomu

“…On this basis, the Box-Behnken design is used to construct a four-factor and three-level experimental scheme, and a second-order response surface agent model is established by 25 sets of simulation data, with the dual optimization objectives of minimizing the equivalent force and maximizing the contact pressure, and the relationship between the structural parameters and the equivalent force and the contact pressure as the optimization function, and the range of geometrical parameters as the boundary conditions. …”
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Structural Parameter Identification Using Multi-Objective Modified Directional Bat Algorithm by LIU Li-jun, LIN Ying-hai, SU Yong-hui, LEI Ying

“…ObjectiveStructural parameter identification based on swarm intelligent optimization methods has become one of the popular methods for finite element model modification. …”
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Bridge Cable Performance Warning Method Based on Temperature and Displacement Monitoring Data by Yan Shi, Yan Wang, Lu-Nan Wang, Wei-Nan Wang, Tao-Yuan Yang

Subjects: “…structural health monitoring…”
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A unified model for metallic materials reliability data and its application in NIMS metallic materials database (Kinzoku) by Asahiko Matsuda, Masahiko Demura, Masayoshi Yamazaki, Takuya Kadohira, Toshihiro Ashino, Yoshiyuki Furuya, Kota Sawada, Nobutaka Nishikawa

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Integrated Wavelet-Grey-Neural Network Model for Heritage Structure Settlement Prediction by Yonghong He, Pengwei Jin, Xin Wang, Shaoluo Shen, Jun Ma

“…To address the issue of insufficient prediction accuracy in traditional GM(1,1) models caused by significant nonlinear fluctuations in time-series data for ancient building structural health monitoring, this study proposes a wavelet decomposition-based GM(1,1)-BP neural network coupled prediction model. …”
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A Novel Hyper-Heuristic Algorithm with Soft and Hard Constraints for Causal Discovery Using a Linear Structural Equation Model by Yinglong Dang, Xiaoguang Gao, Zidong Wang

“…To solve this problem, we propose the use of expert knowledge as a hard constraint and the structural prior gained via data learning as a soft constraint. …”
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Predicting the impact of public events and mobility in Smart Cities by Elena Bellodi, Riccardo Zese, Carlo Petrovich, Angelo Frascella, Francesco Bertasi

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23 Generative artificial intelligence for automated unstructured MRI data extraction in prostate cancer care by William Pace, Andrew Liu, Marvin Carlisle, Robert Krumm, Janet Cowan, Peter Carroll, Matthew Cooperberg, Anobel Odisho

“…Objectives/Goals: Magnetic resonance imaging (MRI) reports are stored as unstructured text in the electronic health record (EHR), rendering the data inaccessible. …”
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Structural Characteristics of the Turning End of the Kaiping Syncline and Its Influence on Coal Mine Gas by Zhenning Chen, Yanming Zhu, Hanyu Zhang, Jin Li

“…This study, drawing on previous theories, research, and practical coal mine production data, analyzes the structural characteristics of the Kaiping syncline, with particular emphasis on the structural differentiation at its northeastern uplifted end. …”
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Support of Home-Based Structured Walking Training and Prediction of the 6-Minute Walk Test Distance in Patients With Peripheral Arterial Disease Based on Telehealth Data: Prospective Cohort Study by Fabian Wiesmüller, Andreas Prenner, Andreas Ziegl, Gihan El-Moazen, Robert Modre-Osprian, Martin Baumgartner, Marianne Brodmann, Gerald Seinost, Günther Silbernagel, Günter Schreier, Dieter Hayn

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Primary disability of children in the Astrakhan region: analysis of statistical data for 2018-2022 by A. A. Antonova, E. B. Starodubova, A. A. Svetlichkina, S. I. Stepanova, E. O. Bobyr

“…A systematic analysis of primary childhood disability and its structure in the Astrakhan region for 2018-2022 was carried out. …”
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Evaluation of chemical kinetic models for simulations of hydrogen detonations by comparison with experimental data by Vigneshwaran Sankar, Karl P. Chatelain, Deanna A. Lacoste

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