LSAP: A Learned Structure-Aware Pruning Point Cloud Classification Approach for Cyber Physical Social Intelligence by Xinhong Liu, Yangfan Li, Fengxiao Tang, Ming Zhao

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Interpretable machine learning excavates a low-alloyed magnesium alloy with strength-ductility synergy based on data augmentation and reconstruction by Qinghang Wang, Xu Qin, Shouxin Xia, Li Wang, Weiqi Wang, Weiying Huang, Yan Song, Weineng Tang, Daolun Chen

“…The data augmentation technique expands the original dataset through Gaussian noise. …”
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Acoustic Data on Vowel Nasalization Across Prosodic Conditions in L1 Korean and L2 English by Native Korean Speakers by Jiyoung Jang, Sahyang Kim, Taehong Cho

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Dataset for tilt-up solid and composite insulated wall panels under combined axial and lateral loadingMendeley Data by Salam Al-Rubaye, Marc Maguire

“…This dataset is of significant value to structural engineers, building code committees, and researchers in the field, as it provides crucial insights into the performance of both insulated and traditional tilt-up wall systems. …”
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The Optimal Cost Design of Reinforced Concrete Beams Using an Artificial Neural Network—The Effectiveness of Cost-Optimized Training Data by Jaemin So, Seungjae Lee, Jonghyeok Seong, Donwoo Lee

“…A SHAP analysis further confirms that the CSA-based model learns more meaningful structural relationships. The findings emphasize the critical role of high-quality training data in ANN-based structural design and suggest the potential for extending the framework to multi-objective design tasks.…”
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Analysis of the capabilities of an information system for improving sleep quality based on biometric data analysis by M.S. Graf, A.V. Yakoniuk, D.V. Krant, I.I. Golovach

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Remote Inspection of Bridges with the Integration of Scanning Total Station and Unmanned Aerial Vehicle Data by Piotr Olaszek, Edgar Maciejewski, Anna Rakoczy, Rafael Cabral, Ricardo Santos, Diogo Ribeiro

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Comparison of two methods in determining hearing loss type and hearing loss degree: mobile application coded with artificial neural networks and conditional structures by Ahmet Yasin Disci, Ozlem Konukseven, Rukiye Tanisir Disci

“…In this study, it is aimed to distinguish the types and degrees of hearing loss with loops created by codes written using deep learning methods and conditional structures. Method A data set consisting of 1000 pure tone airway and pure tone bone conduction hearing tests performed in the audiology clinic was prepared for this study. …”
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Sensing Techniques for Structural Health Monitoring: A State-of-the-Art Review on Performance Criteria and New-Generation Technologies by Ali Mardanshahi, Abhilash Sreekumar, Xin Yang, Swarup Kumar Barman, Dimitrios Chronopoulos

“…Recognizing these challenges, we explore next-generation advancements such as self-sensing structures, unmanned aerial vehicle deployment, IoT-enabled data fusion, and enhanced Digital Twin simulations. …”
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Structural and Rural Transformations and Poverty Reduction in Developing Asian Economies: An International Comparison Among China, the Philippines, and Vietnam by Qiu Chen, Jikun Huang, Mercedita A. Sombilla, Trang Truong

“…Based on a comparison with the provincial data from those three countries, both the graphic and regression analysis suggest that structural and rural transformations matter in rural poverty reduction in these three countries. …”
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Constructing Efficient Mesh-Based Global Grid Systems with Reduced Distortions by Lakin Wecker, John Hall, Faramarz F. Samavati

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Guest Editorial: Smart cities 2.0: How Artificial Intelligence and Internet of Things are transforming urban living by Zheng‐Yi Chai, Syed Attique Shah, Dirk Draheim, Sufian Hameed, Muhammad Mazhar Ullah Rathore

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From Tutte to Floater and Gotsman: On the Resolution of Planar Straight-line Drawings and Morphs by Giuseppe Di Battista, Fabrizio Frati

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Estimating Soybean Yields Using Causal Inference and Deep Learning Approaches With Satellite Remote Sensing Data by Fumin Wang, Jiale Li, Dailiang Peng, Qiuxiang Yi, Xiaoyang Zhang, Jueyi Zheng, Siting Chen

“…However, traditional machine learning methods rely on data correlation rather than causality, leading to poor interpretability. …”
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The frequency of occurrence of various variants of the structure of root canals and methods of their mechanical treatment in the practice of a dentist-therapist by T. L. Redinova, E. I. Pudova, I. Сh. Sharifullina, A. A. Yesyunina, I. V. Zagrebin

“…Evaluation of the frequency of occurrence of various variants of the structure of root canals and methods for their processing in the practice of a dentist-therapist.Material and methods. 30 doctors who worked in the specialty "therapeutic dentistry" for 2-20 years were interviewed using questionnaires in various dental institutions in Izhevsk and Sarapul in the Udmurt Republic; and also analyzed 81 medical record of patients who underwent primary endodontic treatment for caries complication at LLC Center for Professional Dentistry "APEX" in Izhevsk for 6 months of 2022. …”
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Determination of Dynamic Stresses and Displacements under the Action of an Impact Load on a Two-Layer Structure during the Indentation Process by N. E. Babushkina, A. A. Lyapin

“…Numerous researchers of the reliability of building structures pay attention to hardness, an important characteristic of the structural material. …”
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The choice of antimicrobial therapy for infective endocarditis in the conditions of gram-positive microorganism dominance in the etiological structure in the russian federation by A. I. Danilov, R. S. Kozlov, A. V. Evseev, L. L. Lyamets

“…The article presents the results of a multicenter study establishing the features of antimicrobial therapy in patients with infectious endocarditis under the conditions of the dominance of gram-positive microorganisms in the etiological structure in the Russian Federation. 440 cases of definite and probable infectious endocarditis in the period from September 2006 to December 2020 were analyzed.…”
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Enhancing construction supply chain Sustainability: The synergistic role of big data analytics and organizational culture using SEM by Amir Mohammad Norouzzadeh, Seyed Pendar Toufighi, Abolfazl Edalatipour, Jan Vang, Mooud Dabaghi Roodsari

Subjects: “…Big data…”
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Depressive and Negative Symptoms in the Early and Established Stages of Schizophrenia: Integrating Structural Brain Alterations, Cognitive Performance, and Plasma Interleukin 6 Lev... by Fabiana Corsi-Zuelli, Gary Donohoe, Siân Lowri Griffiths, Cristina M. Del-Ben, Andrew J. Watson, Tom Burke, Paris A. Lalousis, Declan McKernan, Derek Morris, John Kelly, Colm McDonald, Saahithh R. Patlola, Carmine Pariante, Nicholas M. Barnes, Golam M. Khandaker, John Suckling, Bill Deakin, Rachel Upthegrove, Maria R. Dauvermann

“…Methods: We evaluated whether higher plasma interleukin 6 (IL-6) levels would be associated with more severe negative or depressive symptoms in schizophrenia and explored illness stage utilizing early (BeneMin [Benefit of Minocycline on Negative Symptoms of Psychosis: Extent and Mechanism], n = 201, 72.8% male) and established (iRELATE [Immune Response & Social Cognition in Schizophrenia], n = 94, 67.3% male) schizophrenia cohorts. Using structural equation modeling in a subsample (iRELATE: n = 42, 69.0% male; BeneMin: n = 102, 76.5% male) with data on structural brain metrics (cortical thickness and volume), general cognitive performance, and plasma IL-6 levels, we assessed the interrelationships between these variables on depressive and negative symptom severity in early and established schizophrenia samples combined and in early schizophrenia only. …”
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Using Information Extraction to Normalize the Training Data for Automatic Radiology Report Generation by Yuxiang Liao, Haishan Xiang, Hantao Liu, Irena Spasic

“…We developed a joint entity and relation model and proposed a novel auxiliary component to enhance the model performance by interpreting token-level information. Using the annotated data, we trained the model for automatically converting information from a narrative radiology report into the structured representation, which achieved a micro-F1 of 96.6% and 96.1% on named entity recognition, 94.0% and 89.8% on entity attribute recognition, and 89.5% and 86.6% on relation extraction, on the MIMIC-CXR and CheXpert test sets, respectively. …”
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