Lithospheric structure in the Baikal–central Mongolia region from integrated geophysical‐petrological inversion of surface‐wave data and topographic elevation by J. Fullea, S. Lebedev, M. R. Agius, A. G. Jones, J. C. Afonso

“…Here, we test an integrated geophysical‐petrological inversion of Rayleigh‐ and Love‐wave phase‐velocity curves for fine‐scale lithospheric structure. The main parameters of the grid‐search inversion are the lithospheric and crustal thicknesses, mantle composition, and bulk density and seismic velocities within the crust. …”
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Three‐dimensional density structure of La Soufrière de Guadeloupe lava dome from simultaneous muon radiographies and gravity data by M. Rosas‐Carbajal, Kevin Jourde, Jacques Marteau, Sébastien Deroussi, Jean‐Christophe Komorowski, Dominique Gibert

“…Here we jointly invert muon data from three simultaneous telescope acquisitions together with gravity data to estimate the three‐dimensional density structure of the La Soufrière de Guadeloupe lava dome. …”
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Analysis of the Spatial Structure of Regional Enterprises and Its Impact on Regional Economic Development Based on the Data Envelopment Analysis Model (DEA) by Lei Wang, Yuan He, Tongwen Wang

“…This paper adopts the data envelopment analysis (DEA) model to conduct an in-depth study and analysis of the spatial structure of regional enterprises and their impact on regional economic development and to apply the analysis of the impact between the two. …”
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Small language models enable rapid and accurate extraction of structured data from unstructured text: An example with plants and their specialized metabolites by Lucas Busta, Alan R. Oyler

“…Small language models (SLMs), however, also have potential in this area as they have smaller compute footprints and allow users to keep data in-house. Here, we quantitatively evaluate the ability of SLMs to: (i) score references according to project-specific relevance and (ii) extract and structuring data from unstructured sources (scientific abstracts). …”
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Mobile Phone Data in Urban Commuting: A Network Community Detection-Based Framework to Unveil the Spatial Structure of Commuting Demand by Qing Yu, Weifeng Li, Dongyuan Yang, Haoran Zhang

“…In this paper, a methodology framework is proposed to describe the spatial structure of commuting demand in a city using mobile phone data. …”
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Remotely Sensing Phytoplankton Size Structure in the Mediterranean Sea: Insights from In Situ Data and Temperature-Corrected Abundance-Based Models by John A. Gittings, Eleni Livanou, Xuerong Sun, Robert J. W. Brewin, Stella Psarra, Manolis Mandalakis, Alexandra Peltekis, Annalisa Di Cicco, Vittorio E. Brando, Dionysios E. Raitsos

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Individual, household structure, and socioeconomic predictors of COVID-19 testing and vaccination outcomes: a whole population linked data analysis by Nicole Satherley, Andrew Sporle

“…We aimed to identify policy amenable socioeconomic factors associated with COVID-19 outcomes while adjusting for relevant individual factors and household structure. We also aimed to examine whether ethnic group differences are smaller when accounting for these socioeconomic factors and household structure. …”
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Identifying long-term conditions in New Zealand general practice using structured and unstructured data: a cross-sectional study by Vanessa Selak, Katrina Poppe, Sue Wells, Yeunhyang Catherine Choi, Allan Ronald Moffitt, Claris Yee Seung Chung, Jane Ullmer

“…Objectives This study examined whether incorporating free-text entries into structured general practice records improves the detection of long-term conditions (LTCs) and multimorbidity (MM) in New Zealand (NZ) general practices.Methods Data from 374 071 deidentified individuals in general practices were analysed to identify 61 LTCs. …”
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Observations of a middle atmosphere thermal structure over Durban using a ground-based Rayleigh LIDAR and satellite data by Nkanyiso Mbatha, Venkataraman Sivakumar, Hassan Bencherif, Sandile Malinga, Sadhasivan Pillay, Ashokabose Moorgawa, Max Michaelis

“…Observations of a middle atmosphere thermal structure over Durban, South Africa (29.9°S, 31.0°E) using the Durban Rayleigh Light Detection and Ranging (LIDAR) data collected over 277 nights from April 1999 to July 2004, including closest overpasses of the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) and Halogen Occultation Experiments (HALOE) satellites, are presented in this paper. …”
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Structure and growth of a Danish research infrastructure and support unit for health research – OPEN (Open Patient data Explorative Network) by Katrine Hass Rubin, Emilie Rosenfeldt Christensen, Janni Brødbaek, Tanja Gram Petersen, Anna Skat Nielsen

“…Methods This paper presents a descriptive case on the structure of the research support unit OPEN (Open Patient data Explorative Network). …”
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Using genome-wide data to ascertain taxonomic status and assess population genetic structure for Houston toads (Bufo [= Anaxyrus] houstonensis) by Shashwat Sirsi, David Rodriguez, Michael R. J. Forstner

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Protein secondary structure determined from independent and integrated infra-red absorbance and circular dichroism data using the algorithm SELCON by Søren Vrønning Hoffmann, Nykola C. Jones, Alison Rodger

“…Protein circular dichroism (CD) and infrared absorbance (IR) spectra are widely used to estimate the secondary structure content of proteins in solution. A range of algorithms have been used for CD analysis (SELCON, CONTIN, CDsstr, SOMSpec) and some of these have been applied to IR data, though IR is more commonly analysed by bandfitting or statistical approaches. …”
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Enhancing Frailty Assessments for Transcatheter Aortic Valve Replacement Patients Using Structured and Unstructured Data: Real-World Evidence Study by Mamoun T Mardini, Chen Bai, Anthony A Bavry, Ahmed Zaghloul, R David Anderson, Catherine E Crenshaw Price, Mohammad A Z Al-Ani

“…ObjectiveThis study aimed to enhance frailty assessments of TAVR candidates by integrating real-world structured and unstructured data. MethodsThis study analyzed data from 14,000 patients between January 2018 and December 2019 to assess frailty in TAVR patients at the University of Florida. …”
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DEEP STRUCTURE, TECTONIC EVOLUTION AND HYDROCARBON POTENTIAL OF THE KALAMIT SWELL (NORTHWESTERN SHELF OF THE BLACK SEA) ACCORDING TO DENSITY MODELING DATA by M.V. Kozlenko, Yu.V. Kozlenko

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Enhancing the assessment of in situ beam–column strength through probing and machine learning by Jin Terng Ma, Luke Lapira, M. Ahmer Wadee

“…Therefore, when assessing the structural health of an in situ beam–column, both of these load effects must be considered. …”
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Multiple Structural Breaks in Profit Share Rates of Participation Banks in Turkey: Are They Caused by the Recent Global Crises? by Mehmet Levent Erdas

“…I used the monthly data covering the period 1998-2018 for the estimated structural break dates. …”
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A Semi-Supervised Deep Network Embedding Approach Based on the Neighborhood Structure by Wenmao Wu, Zhizhou Yu, Jieyue He

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Manufacturing cycle prediction using structural equation model toward industrial early warning system simulation: The Indonesian case by Tirta Wisnu Permana, Gatot Yudoko, Eko Agus Prasetio

“…Specifically, it investigates the relationships among CLIs to forecast Indonesia's Manufacturing Cycle (ManC) using Partial Least Squares-Structural Equation Modeling (PLS-SEM).Building on an extensive literature review, the study employs quarterly data spanning from Q1 2010 to Q2 2022, incorporating five constructs representing key economic sectors influencing the manufacturing cycle. …”
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Editorial: Approaches to improve the performance of virtual screening: scoring functions, structural filtration, prediction of physicochemical properties/pharmacological activity by Hélcio Silva Dos Santos, Hélcio Silva Dos Santos, Hélcio Silva Dos Santos, Alexander Veselovsky, Dmitry Nilov

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Decomposing the Sri Lanka Yield Curve Using Principal Component Analysis to Examine the Term Structure of the Interest Rate by K P N Sanjeewa Dayarathne, Uthayasanker Thayasivam

“…Our analysis encompasses data spanning from January 2010 to August 2022. The study applied several PCA variants such as multivariate PCA, Randomized PCA, Incremental PCA, Sparse PCA, Functional PCA, and Kernel PCA on smoothed data. …”
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