Many-Objective Truss Structural Optimization Considering Dynamic and Stability Behaviors by João Marcos P. Vieira, José Pedro G. Carvalho, Dênis E. C. Vargas, Érica C. R. Carvalho, Patrícia H. Hallak, Afonso C. C. Lemonge

“…This paper aims to propose seven innovative many-objective structural optimization problems (MOSOPs) applied to 25-, 56-, 72-, 120-, and 582-bar trusses, not yet presented in the literature, in which the main objectives, in addition to the structure’s weight, refer to the structures’ vibrational and stability aspects. …”
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Bridge service life and impact of maintenance events on the structural state index by Abdoul S. Bah, Yan Zhang, Kotaro Sasai, David Conciatori, Luc Chouinard, Nicolas Zufferey, Gabriel J. Power, Thomas Sanchez, Xuande Chen

“…Structure-specific simulations are obtained though a model that uses site-specific hourly historical meteorological data, and concrete properties from non-destructive permeability and resistivity measurements. …”
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Functional and structural analysis of missense variants in the human PDCD1 Gene by Hanâ Baba, Meryem Bouqdayr, Anass Abbad, Asmae Saih, Benson R. Kidenya, Mohamed A. Sesay, Simpson Addo, Lahcen Wakrim, Anass Kettani

“…Aim: This study investigates the functional and structural impact of missense single nucleotide polymorphisms in the human Programmed Cell Death 1 (PDCD1) gene. …”
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Structural Explanation of Urban Tourism Development Challenges in Chaharmahal and Bakhtiari Cities by Arash Fazeli, Nafiseh Marsousi, Mohsen Saghaei

“…Data were analyzed using structural equation modeling with PLS software. …”
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Expression and structural analysis of taste receptor genes in Iberian and Duroc pigs by Cristina Óvilo, Rita Benítez, Yolanda Núñez, Ramón Peiró-Pastor, Fabian García, Eduardo De Mercado, Emilio Gómez-Izquierdo, Juan García-Casco, Clemente López-Bote, María Muñoz

“…Results We performed a gene expression and structural analysis of ten taste receptor genes in Iberian and Duroc pigs. …”
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Multiparity induces persistent myocardial structural, functional and transcriptomic remodelling in mice by Ruth R. Magaye, Bing H. Wang, Hongyi R. Liu, Shanae Bailey, Rithy Nuon, Sabrina Sutano, Michael Nyugen, Helen Kiriazis, Kyah Grigolon, Luchen Shan, William W. H. Ho, Fumihiko Takeuchi, Daniel G. Donner, David M. Kaye

“…We evaluated blood pressure, body composition, gross weight and histologic cardiac structure. Cardiac function was assessed by echocardiography together with transcriptomic analysis of the left ventricular myocardium. …”
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Analysis of dairy farm assets in the Visegrad Group based on the Farm Accountancy Data Network 2015-2022 data by Ildikó VAJDÁNÉ SZABÓ, Nóra HEGEDŰSNÉ BARANYAI, Judit Poór

“…This study aims to investigate the milk production of the Visegrad countries (V4), to answer the question, of what differences and similarities characterize the asset structure of the dairy farms of these countries. Based on the Farm Accountancy Data Network (FADN), the size and the structure of the fixed assets, as well as the use of subsidies for investments is analyzed. …”
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Transcriptional patterns of brain structural abnormalities in CSVD-related cognitive impairment by Haixia Mao, Min Xu, Hui Wang, Hui Wang, Yuankun Liu, Feng Wang, Feng Wang, Qianqian Gao, Songyun Zhao, Lin Ma, Xiaoyun Hu, Xiaoxuan Zhang, Guangjun Xi, Guangjun Xi, Xiangming Fang, Yachen Shi, Yachen Shi

“…However, the molecular and cellular factors making the different brain structural regions more vulnerable to CSVD-related cognitive impairment remain largely unknown.Materials and methodsVoxel-based morphology (VBM) was performed on the structural magnetic resonance imaging data of 46 CSVD-related cognitive impairment and 73 healthy controls to analyze and compare the gray matter volume (GMV) between the 2 groups. …”
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IDEA: Image database for earthquake damage annotationZenodo by Ilaria Senaldi, Chiara Casarotti, Martina Mandirola, Alessio Cantoni

“…The data article presents the “Image Database for Earthquake damage Annotation (IDEA)”, an extended dataset of annotated real structural damage consisting of more than 5400 images, collected during post-event and ordinary field inspections. …”
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Structuring and centralizing breast cancer real-world biomarker data from pathology reports through C-LAB artificial intelligence platform by Florent Le Borgne, Camille Garnier, Camille Morisseau, Yanis Navarrete, Yanina Echeverria, Juan Mir, Jaume Calafell, Tanguy Perennec, Olivier Kerdraon, Jean-Sébastien Frenel, Judith Raimbourg, Mario Campone, Maria Fe Paz, François Bocquet

“…Results C-LAB ® achieved over 80% agreement with human extractions (precision, recall, and F1-score) in structuring biomarker data from complex, unstructured pathology reports, despite dataset variability and optical character recognition errors. …”
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Multi-temporal high-resolution data products of ecosystem structure derived from country-wide airborne laser scanning surveys of the Netherlands by Y. Shi, J. Wang, W. D. Kissling

“…<p>Recent years have seen a rapid surge in the use of light detection and ranging (lidar) technology for characterizing the structure of ecosystems. Even though repeated airborne laser scanning (ALS) surveys are becoming increasingly available across several European countries, so far, only a few studies have derived data products of ecosystem structure at a national scale, possibly due to a lack of free and open-source tools and the computational challenges involved in handling the large volumes of data. …”
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Estimating fine age structure and time trends in human contact patterns from coarse contact data: The Bayesian rate consistency model. by Shozen Dan, Yu Chen, Yining Chen, Melodie Monod, Veronika K Jaeger, Samir Bhatt, André Karch, Oliver Ratmann, Machine Learning & Global Health network

“…The Bayesian rate consistency model provides a model-based, non-parametric, computationally tractable approach for estimating the fine structure and longitudinal trends in social contacts and is applicable to contemporary survey data with coarsely reported age of contacts as long as the exact age of survey participants is reported.…”
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Seasonal genetic variation and genetic structure of Spodoptera exigua in Liaoning Province, Northeast China: insights from 11 years of microsatellite data by Ming-Li Yu, Xian-Zhi Xiu, Jin-Yang Wang, Xin-Yi Cao, Fa-Liang Qin, Xing-Ya Wang, Li-Hong Zhou

“…To control this pest effectively, it is crucial to investigate its seasonal genetic variation and population genetic structure in northern China. Methods In this study, we used eight nuclear microsatellite loci to investigate the seasonal genetic variation and genetic structure of BAW in Shenyang, Liaoning Province, Northeast China, from 2012–2022, collected from a single location on Welsh onion. …”
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The glucose-lowering therapy structure in special groups of type 2 diabetes mellitus patients based on data from the Moscow region register by Inna V. Misnikova, Yulia A. Kovaleva, Mikhail А. Isakov, Alexander V. Dreval

“…BACKGROUND: Data of real clinical practice in diabetes mellitus (DM) register allow to evaluate features and trends in structure of glucose-lowering therapy (GLT). …”
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Data Assimilation Informed Model Structure Improvement (DAISI) for Robust Prediction Under Climate Change: Application to 201 Catchments in Southeastern Australia by Julien Lerat, Francis Chiew, David Robertson, Vazken Andréassian, Hongxing Zheng

Subjects: “…model structure…”
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What determines export structure in the EU countries? The use of gravity model in international trade based on the panel data for the years 1995-2015 by Marek Maciejewski, Krzysztof Wach

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A dynamic key management and secure data transfer based on m-tree structure with multi-level security framework for Internet of vehicles by Hua Yi Lin, Meng-Yen Hsieh

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PATIENTS WITH ATRIAL FIBRILLATION IN MULTIDISCIPLINARY HOSPITAL: STRUCTURE OF HOSPITALIZATION, CONCOMITANT CARDIOVASCULAR DISEASES AND DRUG TREATMENT (DATA OF RECVASA AF-TULA REGISTRY) by M. N. Valiakhmetov, T. A. Gomova, M. M. Loukianov, S. Yu. Martsevich, K. N. Nadejkina, M. N. Artemova, D. N. Jilin, E. E. Fedotova, A. V. Zagrebelnyy, E. V. Kudryashov, S. A. Boytsov

“…All patients with a diagnosis of AF in the patient's chart (n=1225) were included into the RECVAZA AF-Tula registry; that is 4.2% of 29018 patients hospitalized to the Tula Regional Clinical Hospital in 2013. The structure of the associated cardiovascular diseases, as well as drug therapy, was evaluated on the basis of data in the medical documentation.Results. …”
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Detachment‐Fault Structure Beneath the TAG Hydrothermal Field, Mid‐Atlantic Ridge, Revealed From Dense Wide‐Angle Seismic Data by Szu‐Ying Lai, G. Bayrakci, B. J. Murton, T. A. Minshull

“…We used dense wide‐angle seismic data to define TAG's detachment structure at a finer scale than has previously been possible. …”
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A comparative study of regression methods to predict forest structure and canopy fuel variables from LiDAR full-waveform data by P. Crespo-Peremarch, L.A. Ruiz, A. Balaguer-Beser

“…Regression methods are widely employed in forestry to predict and map structure and canopy fuel variables. We present a study where several regression models (linear, non-linear, regression trees and ensemble) were assessed. …”
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