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3221
Modeling of settlement of shallow-founded rocking structures using explainable physics-guided machine learning
Published 2025-09-01“…Rocking foundation is an unorthodox seismic design philosophy of structures that enhances the performance of structures by absorbing and dissipating seismic energy into soil. …”
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3222
Influence of the phytoplankton community structure on the southern elephant seals' foraging activity within the Southern Ocean
Published 2025-04-01“…To investigate the complex composition of water constituents, notably the phytoplankton community, we used machine learning techniques to classify six bio-optical classes from a comprehensive ocean-color data time-series. In situ data from the Southern Ocean further characterized these classes by predominant phytoplankton types. …”
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3223
CAPITAL STRUCTURE AND FINANCIAL PERFORMANCE: EVIDENCE FROM NIGERIAN LISTED INDIGENOUS OIL AND GAS FIRMS
Published 2023-11-01“… The combination of equity capital and debt capital forms the capital structure of an enterprise which in achieving firms’ objective is the utmost aspect of managerial and financial decisions. …”
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3224
MaxComp: Predicting single-cell chromatin compartments from 3D chromosome structures.
Published 2025-05-01“…To address this, we present MaxComp, an unsupervised method, for inferring single-cell A/B compartments based on 3D geometric considerations in single-cell chromosome structures-derived either from multiplexed FISH-omics imaging or 3D structure models derived from Hi-C data. …”
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3225
Submeridional boundary zone in Asia: seismicity, lithosphere structure, and the distribution of convective flows in the upper mantle
Published 2018-10-01“…This article presents a comprehensive analysis based on comparison of the available data with the results obtained in our study using independent methods. …”
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3226
Spatiotemporal Deformation Prediction Model for Retaining Structures Integrating ConvGRU and Cross-Attention Mechanism
Published 2025-07-01“…With the exponential growth of engineering monitoring data, data-driven neural networks have gained widespread application in predicting retaining structure deformation in foundation pit engineering. …”
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3227
Novel Automatic Classification Method for Geological Structures in Carbonate Formations Based on Electrical Imaging Logging
Published 2025-02-01“…Finally, these features are used to train an extreme gradient boosting (XGBoost) model, enabling the automatic classification of different geological structures. Validation using actual carbonate logging data shows that the classification accuracy of this method exceeds an 80% agreement rate with core observations. …”
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3228
Development of a Multitype Wireless Sensor Network for the Large-Scale Structure of the National Stadium in China
Published 2013-12-01“…A total of 290 sensors were installed on the structure, and the data collection work has been carried out for more than one year. …”
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3229
A Numerical Approach to Calculate the Radiation Efficiency of Baffled Planar Structures Using the Far Field
Published 2014-06-01“…In this work a different approach is used, based in the so-called Propagating Matrix, which is useful for calculating the sound pressure of an arbitrary number of points into free space, and it can be employed to estimate the sound power by integrating over a finite number of pressure points over a hemispherical surface surrounding the vibrating structure. Through numerical analysis, the advantages/disadvantages of the current method are investigated, when compared with numerical methods based on near field data. …”
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3230
STaRT-RWE: structured template for planning and reporting on the implementation of real-world evidence studies
Published 2022-11-01“…To highlight the features of STaRT-RWE (a structured template for planning and reporting on research in real clinical practice — RWE).Materials and methods. …”
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3231
MODELING AND MATHEMATICAL PROCESSING OF GEODETIC LEVELING NETWORK WHILE MONITORING SETTLEMENT OF UNIQUE ENGINEERING STRUCTURES
Published 2009-05-01“…The paper shows that reliability and trust of geodetic structure monitoring are related with new principles of leveling network construction, their testing and mathematical processing. …”
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Micro and small scale enterprises growth and ownership structure in Hawassa city, Sidama region, Ethiopia
Published 2022-12-01“…Both descriptive statistics and econometric methods have been used to analyze the nexus between growth of micro and small enterprises and ownership structure and other driving factors. System GMM estimation technique was employed to analyze a dynamic panel data model. …”
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3235
Evaluating the structure of Antibiotic Stewardship Programme in Emirates Health Services hospitals in the United Arab Emirates
Published 2025-03-01“…Qualitative data from semi-structured interviews were thematically analyzed using NVIVO software. …”
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3236
Recent Advances in the Use of Drill Cuttings for Determining Subduction Zone Structure, Stratigraphy, and Stress State
Published 2025-05-01“…Combining these data with logging‐while‐drilling and mud gas logging data permits the generation of depth profiles of lithological variation and deformation structures. …”
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3237
Determination of the enthalpy of evaporation of pentaerythritol esters of various structures using gas chromatographic retention characteristics
Published 2025-07-01“…The enthalpies of evaporation calculated based on the enthalpies of sorption and logarithmic retention indices within the limits of error of the correlation dependencies coincide with the literature data and the values predicted by the quantitative structure–property relationship method. …”
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3239
Dependence of observables in elastic scattering of intermediate energy protons by 6He from its structure
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3240
Lagrangian Coherent Structure Analysis of Terminal Winds: Three-Dimensionality, Intramodel Variations, and Flight Analyses
Published 2015-01-01“…The LCS are contrasted among three independent models and against 2D coherent Doppler light detection and ranging (LIDAR) data. Addition of the velocity information perpendicular to the LIDAR scanning cone helps solidify flow structures inferred from previous studies; contrast among models reveals the intramodel variability; and comparison with flight data evaluates the performance among models in terms of Lagrangian analyses. …”
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