Model Checking of Distributed Systems with Affine Data Structures by N. O. Garanina

“…A new data structure is suggested for symbolic model checking of distributed systems defined by linear functions of integer variables.…”
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Data structures for deductive simulation of HDL conditional operators by Yevhenii Shovkovyi, Olena Grinyova, Serhii Udovenko, Larysa Chala

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Data structures for deductive simulation of HDL conditional operators by Євгеній Шовковий, Олена Гриньова, Сергій Удовенко, Лариса Чала

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Structural controls of gold mineralisation in Birrimian structures, Western Mali: insights from magnetic data analysis by Imen Hamdi Nasr, Adama Youssouf Koné, Wajdi Belkhiria, Adnen Amiri, Aboubacar Denon, Souleymane Sangaré, Mohamed Hedi Inoubli, Saïdou Ly

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STRUCTURAL FEATURES OF THE DEEP STRUCTURE OF THE SOUTHEASTERN YANA-KOLYMA FOLD SYSTEM FROM COMPLEX GEOPHYSICAL DATA by N. K. Gayday, N. A. Goryachev, I. M. Khasanov, E. Yu. Goshko

“…Ore deposits of the Magadan region are now in the focus of comprehensive studies as information on their deep structure is needed for both subsoil prospecting and regional development planning. …”
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On Bornological Structure by Anwar.N.I, Sh.K.Said Husain

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Structured noise champagne: an empirical Bayesian algorithm for electromagnetic brain imaging with structured noise by Sanjay Ghosh, Sanjay Ghosh, Chang Cai, Ali Hashemi, Yijing Gao, Stefan Haufe, Kensuke Sekihara, Ashish Raj, Srikantan S. Nagarajan

“…To the best of our knowledge, no existing algorithm has addressed the brain source estimation problem with such structured noise. We propose to apply a robust empirical Bayesian framework for iteratively estimating the brain source activity and the statistics of the structured noise. …”
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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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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

“…Programmatic text classification has demonstrated high performance and identified many more patients receiving LTC care.Conclusions Combining structured and unstructured data optimises MM detection in NZ general practices and has the potential to improve case management, follow-up care and allocation of healthcare resources.…”
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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

“…ConclusionsIntegrating unstructured clinical notes and structured EHR data led to a notable enhancement in predicting frailty. …”
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Structural Data Recognition With Graph Model Boosting by Tomo Miyazaki, Shinichiro Omachi

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Navigating the unstructured by evaluating alphafold's efficacy in predicting missing residues and structural disorder in proteins. by Sen Zheng

“…The incorporation of pLDDT, IUPred scores, and sequence data into the LSTM model has improved the differentiation between structured and unstructured residues, particularly for shorter unstructured regions. …”
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On calculating structural similarity metrics in population-based structural health monitoring by Daniel S. Brennan, Timothy J. Rogers, Elizabeth J. Cross, Keith Worden

“…The newly introduced discipline of Population-Based Structural Health Monitoring (PBSHM) has been developed in order to circumvent the issue of data scarcity in “classical” SHM. …”
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Building a Data Store with the Dynamic Structure by Yu. N. Artamonov

“…A new logical model of the data warehouse with dynamic structure is proposed. …”
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Structure preserving t-SNE of matrix framed data by Soohyun Ahn, Johan Lim, Wei Jiang, Sungim Lee, Xinlei Wang

“…These elements can take various forms, such as scalars, vectors, time series, matrices, or arrays. Existing data visualization methods aim to represent data elements of different groups without considering the underlying two-dimensional structure present in matrix-framed data. …”
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Knowledge and theme discovery across very large biological data sets using distributed queries: a prototype combining unstructured and structured data. by Uma S Mudunuri, Mohamad Khouja, Stephen Repetski, Girish Venkataraman, Anney Che, Brian T Luke, F Pascal Girard, Robert M Stephens

“…In order to achieve useful results, researchers require methods that consolidate, store and query combinations of structured and unstructured data sets efficiently and effectively. …”
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Doubly Structured Data Synthesis for Time-Series Energy-Use Data by Jiwoo Kim, Changhoon Lee, Jehoon Jeon, Jungwoong Choi, Joseph H. T. Kim

“…This paper introduces Doubly Structured Data Synthesis (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mi>DS</mi><mn>2</mn></msup></semantics></math></inline-formula>), a novel method to tackle privacy concerns in time-series energy-use data. …”
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Leveraging AlphaFold2 structural space exploration for generating drug target structures in structure-based virtual screening by Keisuke Uchikawa, Kairi Furui, Masahito Ohue

“…However, the absence of experimentally determined three-dimensional protein structures often limits the applicability of structure-based VS. …”
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Structured Dynamics in the Algorithmic Agent by Giulio Ruffini, Francesca Castaldo, Jakub Vohryzek

“…In the Kolmogorov Theory of Consciousness, algorithmic agents utilize inferred compressive models to track coarse-grained data produced by simplified world models, capturing regularities that structure subjective experience and guide action planning. …”
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Sensory structures of lungs and airways by L. V. Filippova, A. D. Nozdrachev

“…In article the review of currently existing data about morphology and functional characteristics of sensitive pulmonary structures is presented: slowly adapting stretch receptors, rapidly adapting receptors, C-fiber receptors and neuroepithelial bodies.…”
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