Description Of Structure Research Articles

J.R.R. TOLKIEN "THE FALL OF GONDOLIN": FORAYS INTO THE TEACHING OF SCIENCE AND MATHEMATICS

How can the narrative and thematic elements in "The Fall of Gondolin" by J.R.R. Tolkien be utilized as innovative pedagogical tools for teaching Natural Sciences and Mathematics? This was the guiding question for this text. The general objective was to analyze how the narrative and thematic elements in "The Fall of Gondolin" by J.R.R. Tolkien can be utilized as innovative pedagogical tools for teaching Natural Sciences and Mathematics. The specific objectives were to identify scientific and mathematical concepts present in "The Fall of Gondolin," investigate the descriptions of natural phenomena and architectural structures in the work, relating them to concepts of geology, biology, physics, and mathematics, develop pedagogical activities based on the narrative elements of the work as propositions for the teaching practices of Basic Education teachers, and create a guide of best practices for the use of "The Fall of Gondolin" in the teaching of Natural Sciences and Mathematics. Regarding the methodological aspects of the research, it is a study that uses a qualitative methodology. The main stages and methods of the study include: Content Analysis, with the objective of identifying and categorizing narrative and thematic elements of "The Fall of Gondolin" that can be correlated with concepts of geology, biology, physics, and mathematics, the development of Pedagogical Activities, with the objective of creating pedagogical activities based on the narrative elements identified in the content analysis, and the development of the Best Practices Guide for teaching Natural Sciences and Mathematics. The results of this study indicate that integrating narrative and thematic elements of "The Fall of Gondolin" into the teaching of Natural Sciences and Mathematics can promote an interdisciplinary approach that stimulates curiosity, engagement, and the development of critical and scientific skills among students. By connecting fantasy with scientific reality, Tolkien's work provides an engaging and meaningful context for learning, making scientific concepts more accessible and interesting.

A {Cr4Ln2} Complex with Exchange Coupled {Cr2} Units: Structural Description and Magnetic Study.

We have prepared and structurally characterized pivalate based {CrIII4LnIII2} complexes with Ln=Dy and Gd as well as the Y analogue, with the overall formula [CrIII4LnIII2(mdea)2(piv)10(OH)4], Ln= Gd, Dy and Y. We are reporting a detailed experimental magnetic properties study, including magnetization relaxation dynamics and calorimetric data, supported with quantum chemical calculations. The synthesis of the Y derivative, allowed to precisely identify the Cr(III)-Cr(III) exchange interaction magnitude which proved moderately strong and in agreement with known magneto-structural correlations. This result agrees with the observed double bridged {Cr2-mOH-mOR} units within the {Cr4Ln2} complexes.The Gd(III) complex magnetic properties can be properly described with the already established exchange coupled {Cr2} units, and a unique Gd(III)-Cr(III) exchange coupling parameter which proved anti-ferromagnetic in nature.The MCE characterization of this complexbased on magnetization and calorimetric data down to 2 K affords a moderate entropy change value, mainly affected by the strong Cr-Cr exchange interaction.The complex with Ln=Dy, showed SMM behaviour below 10 K under 0 DC applied field with negligible field dependence up to 3000 Oe and 10 kHz of AC field frequency. Two relaxation processes are clearly distinguished, with thermal barriers for an Orbach mechanism of ca. 20 cm-1 and 40 cm-1.

Typical Structure of Hereditary Graph Families. I. Apex‐free Families

ABSTRACTA family of graphs is hereditary if is closed under isomorphism and taking induced subgraphs. The speed of is the sequence , where denotes the set of graphs in with the vertex set . Alon et al. (2011) gave a rough description of typical graphs in a hereditary family and used it to show for every proper hereditary family there exist and an integer such that The main result of this paper gives a more precise description of typical structure for a restricted class of hereditary families. As a consequence we characterize hereditary families with the speed just above the threshold , generalizing a result of Balogh and Butterfield (2011).

Typical Structure of Hereditary Graph Families. II. Exotic Examples

ABSTRACTA graph is ‐free if it does not contain an induced subgraph isomorphic to . The study of the typical structure of ‐free graphs was initiated by Erdős, Kleitman, and Rothschild (1976), who have shown that almost all ‐free graphs are bipartite. Since then the typical structure of ‐free graphs has been determined for several families of graphs , including complete graphs, trees, and cycles. Recently, Reed and Scott proposed a conjectural description of the typical structure of ‐free graphs for all graphs , which extends all previously known results in the area. We construct an infinite family of graphs for which the Reed–Scott conjecture fails, and use the methods we developed in the prequel paper Norin and Yuditsky (2024) to describe the typical structure of ‐free graphs for graphs in this family. Using similar techniques, we construct an infinite family of graphs for which the maximum size of a homogenous set in a typical ‐free graph is sublinear in the number of vertices, answering a question of Loebl et al. (2010) and Kang et al. (2014).

Coordination geometry flexibility driving supramolecular isomerism of Cu/Mo pillared-layer hybrid networks.

Hydrothermal synthesis led to four novel 3D pillared-layer metal-organic frameworks: [Cu4(4,4'-bipy)4(MoO4)4·0.3H2O]n (1), [Cu(4,4'-bipy)0.5(MoO4)·0.25H2O]n (2), [Cu(4,4'-bipy)(MoO4)·0.1H2O]n (3), and [{Cu(4,4'-bipy)}2(Mo8O26)0.5]n (4). These compounds exhibit diverse supramolecular isomerism within their 3D coordination networks, each incorporating bimetallic {CuMoO} layers linked by 4,4'-bipyridine, demonstrating a remarkable structural diversity. Compound 1 features a 3D network derived from conformational supramolecular isomerism. Its bimetallic layer comprises fused 16-membered {Cu4Mo4O8} and eight-membered {Cu2Mo2O4} rings, with varying O-Cu-O bond angles affecting the network puckering and Cu-Cu distances. In contrast, the coordination networks observed in 2, 3, and 4 correspond to structural supramolecular isomers from the earlier stated networks. In 2, centrosymmetric Cu2+ dimers with distorted square-pyramidal geometry are linked along the c axis by 4,4'-bipyridine, forming 1D {Cu2(4,4'-bipy)}n chains with a Cu-Cu distance of 2.95 Å. Its oxide substructure comprises bilayers of fused 12-membered {Cu3Mo3O6} rings. Crystal structures 3 and 4 are particularly notable for their construction at the Cu+ centers. In compound 4, this isomerism is further influenced by the interplay between the distortion of the coordination geometry of both the Cu and Mo ions. The propensity to form these supramolecular isomers primarily stems from the flexible coordination environment of copper ions. Electron paramagnetic resonance measurements corroborated the structural descriptions of the paramagnetic compounds 1 and 2.

Molecular identification via molecular fingerprint extraction from atomic force microscopy images

Non–Contact Atomic Force Microscopy with CO–functionalized metal tips (referred to as HR-AFM) provides access to the internal structure of individual molecules adsorbed on a surface with totally unprecedented resolution. Previous works have shown that deep learning (DL) models can retrieve the chemical and structural information encoded in a 3D stack of constant-height HR–AFM images, leading to molecular identification. In this work, we overcome their limitations by using a well-established description of the molecular structure in terms of topological fingerprints, the 1024–bit Extended Connectivity Chemical Fingerprints of radius 2 (ECFP4), that were developed for substructure and similarity searching. ECFPs provide local structural information of the molecule, each bit correlating with a particular substructure within the molecule. Our DL model is able to extract this optimized structural descriptor from the 3D HR–AFM stacks and use it, through virtual screening, to identify molecules from their predicted ECFP4 with a retrieval accuracy on theoretical images of 95.4%. Furthermore, this approach, unlike previous DL models, assigns a confidence score, the Tanimoto similarity, to each of the candidate molecules, thus providing information on the reliability of the identification. By construction, the number of times a certain substructure is present in the molecule is lost during the hashing process, necessary to make them useful for machine learning applications. We show that it is possible to complement the fingerprint-based virtual screening with global information provided by another DL model that predicts from the same HR–AFM stacks the chemical formula, boosting the identification accuracy up to a 97.6%. Finally, we perform a limited test with experimental images, obtaining promising results towards the application of this pipeline under real conditions.Scientific contributionPrevious works on molecular identification from AFM images used chemical descriptors that were intuitive for humans but sub–optimal for neural networks. We propose a novel method to extract the ECFP4 from AFM images and identify the molecule via a virtual screening, beating previous state-of-the-art models.

Conic sections in ferroelectric nematics: Experiments and mathematical modeling

The domain structure of a fluid ferroelectric nematic is dramatically different from the domain structure of solid ferroelectrics since it is not restricted by rectilinear crystallographic axes and planar surface facets. We demonstrate that thin films of a ferroelectric nematic seeded by colloidal inclusions produce domain walls (DWs) in the shape of conics such as a parabola. These conics reduce the bound charge within the domains and at the DWs. An adequate description of the domain structures requires one to analyze the electrostatic energy, which is a challenging task. Instead, we demonstrate that a good approximation to the experimentally observed polydomain textures is obtained when the divergence of spontaneous polarization—which causes the bound charge—is heavily penalized by assuming that the elastic constant of splay in the Oseen-Frank energy is much larger than those for twist and bend. The model takes advantage of the fact that the polarization vector is essentially parallel to the nematic director throughout the sample. Published by the American Physical Society 2024

All-in-One CO2 Capture and Transformation: Lessons from Formylmethanofuran Dehydrogenases.

ConspectusCarbon-one-unit (C1) feedstocks are generally used in the chemical synthesis of organic molecules, such as solvents, drugs, polymers, and fuels. Contrary to the dangerous and polluting carbon monoxide mostly coming from fossil fuels, formate and formamide are attractive alternative feedstocks for chemical synthesis. As these are currently mainly obtained from the oil industry, novel synthetic routes have been developed based on the transformation of the greenhouse gas CO2. Such developments are motivated by the urgent need for carbon chemical recycling, leading to a sustainable future. The inert nature of CO2 represents a challenge for chemists to activate and specifically convert the molecule through an affordable and efficient process. The chemical transformation could be inspired by biological CO2 activation, in which highly specialized enzymes perform atmospheric CO2 fixation through relatively abundant metal catalysts. In this Account, we describe and discuss the potential of one of the most efficient biological CO2-converting systems: the formylmethanofuran dehydrogenase (abbreviated as FMD).FMDs are multienzymatic complexes found in archaea that capture CO2 as a formyl group branched on the amine moiety of the methanofuran (MFR) cofactor. This overall reaction leading to formyl-MFR production does not require ATP hydrolysis as compared to the CO2-fixing microbes relying on the reductive Wood-Ljungdahl pathway, highlighting a different operative mode that saves cellular energy. FMD reaction represents the entry point in hydrogenotrophic methanogenesis (H2 and CO2 dependent or formate dependent) and operates in reverse in other methanogenic pathways and microbial metabolisms. Therefore, FMD is a key enzyme in the planetary carbon cycle. After decades of investigations, recent studies have provided a description of the FMD structure, reaction mechanism, and potential for the electroreduction of CO2, to which our laboratory has been actively contributing.FMD is an "all-in-one" enzyme catalyzing a redox-active transformation coupled to a redox-neutral transformation at two very different metal cofactors where new C-H and C-N bonds are made. First, the principle of the overall reaction consisting of an exergonic CO2 reduction coupled with an endergonic formate condensation on MFR is resumed. Then, this Account exposes the molecular details of the active sites and provides an overview of each catalytic mechanism. It also describes the natural versatility of electron-delivery modules fueling CO2 reduction and extends it to the possibilities of using artificial systems such as electrodes.A perspective concludes on how the mechanistic of FMD could be applied to produce CO2-based chemical intermediates to synthesize organic molecules. Indeed, through its biochemical properties, the enzyme opens opportunities for CO2 electroreduction to generate molecules such as formate and formamide derivatives, which are all intermediates for synthesizing organic compounds. Transferring the chemical knowledge acquired from these biological systems would provide coherent models that can lead to further development in the field of synthetic biology and bio-inspired synthetic chemistry to perform large-scale CO2 conversion into building blocks for chemical synthesis.

Design strategies and applications of cyanine dyes in phototherapy.

Cyanine dyes have been widely used in phototherapy in recent years due to their excellent optical properties and diverse modifiable structures. This review provides detailed descriptions of the basic structures of various cyanines and their derivatives as well as their optical properties. It summarizes the strategies for constructing cyanine dyes for phototherapy and discusses their structure-effect relationship. Furthermore, a comprehensive classification and summary of the applications of cyanine dyes in phototherapy are presented. Importantly, this review also addresses both the advances made in this field as well as the challenges that need to be overcome. We hope that these profound insights into phototherapy using cyanine dyes will facilitate the design of future systems for clinical applications based on these compounds.

Dental professionals as clinical educators: A transcendental inquiry into training needs.

Clinical instructors are responsible for educating dental hygiene students in the patient care environment. While these instructors have experience in the dental field, they often do not have pedagogical training, or a background, related to education. The purpose of this qualitative, phenomenological study was to explore the experiences of dental professionals who transitioned from clinical practitioners to clinical instructors at one US dental hygiene program in 2022. As the theoretical underpinning for this study, andragogy offered a lens through which to tailor the creation of training opportunities distinctive to the needs of adult learners. The central research question for this study was, "What are the experiences of dentists and dental hygienists who have transitioned from clinical practice to the role of clinical instructors?" The subquestions guiding this study were "What forms of education, professional development, or support are necessary to help guide the transition from healthcare professional to clinical instructor?" and "How can this education, professional development, or support be delivered to clinical instructors in a way that meets their needs as adult learners?" A transcendental phenomenological approach enabled a deeper understanding of participants' experiences and their thought processes as they transitioned from clinical practitioners to their roles as clinical instructors. Purposeful sampling was used to recruit dentists and dental hygienists who served as clinical instructors in a dental hygiene program at a midwestern public university. Data collection was triangulated using individual interviews, photograph journals, and a virtual focus group. Data analysis was conducted using epoché, phenomenological reduction, imaginative variance, and synthesis of the structural and textural descriptions gathered during data collection. A total of 13 clinical faculty members participated in all three parts of the study. Five themes were derived from the data collection: life responsibilities, challenges faced, training received, training needed, and training delivery preferences. These themes helped to create an understanding of the phenomena of transitioning from clinical practitioner to clinical instructor as the participants experienced it in addition to training delivery preferences. The study's findings highlighted the importance of training dentists and dental hygienists to become clinical instructors while using andragogical principles. IRB approval: This project received Institutional Review Board (IRB) exemption from Liberty University (IRB-FY22-23-285).

Cs3LiGe4, One Compound with Two Complementary Structural Descriptions: Isolated [Ge4]4- Tetrahedral Clusters Coordinated by Li+ and Cs+ Cations or One-Dimensional [LiGe4]3- Polyanions Packed within a Matrix of Cs+ Cations?

Reported are the synthesis and structural characterization of Cs3LiGe4, the first structurally characterized lithium-containing cesium germanide. Single-crystal X-ray diffraction data indicate that Cs3LiGe4 crystallizes in an orthorhombic crystal system with the space group Cmcm (no. 63, Person symbol oS32) with unit cell parameters a = 6.950(2) Å, b = 15.503(3) Å, and c = 9.919(2) Å and V = 1068.65(4) Å3. The structure consists of [Ge]44- tetrahedral clusters with the Li atoms positioned in such a way that polyanionic [LiGe]43- chains could be considered as well. Electronic structure calculations indicate an intrinsic semiconductor with a band gap of 0.76 eV. To understand the nuances of the chemical bonding, position-space techniques based on the quantum theory of atoms in molecules, the electron localizability indicator, and their basin intersections were employed confirming the covalent character of the Ge-Ge bonding. The strong polarity of the interactions between [Ge]44- and the surrounding lithium and cesium cations suggests to interpret these as mainly ionic, further supporting the most basic structure rationalization [Cs+]3[Li+][Ge]44-, following the Zintl-Klemm concept. The electron localizability indicator topology affirms the striking similarities between [Ge]44- and molecular As4 tetrahedra in yellow arsenic, further supporting Klemm's pseudoatom concept on a quantum chemical basis.

Structural and Textural Characteristics of Municipal Solid Waste Incineration Bottom Ash Subjected to Periodic Seasoning

The objective of this study was to determine the structural and textural description of municipal solid waste incineration (MSWI) bottom ash that was subjected to a six-month seasoning process. Bottom ash samples, with a particle size fraction of 0.063–0.1 mm, were seasoned in a closed landfill and collected for laboratory analyses at monthly intervals. The research focused on determining the structural parameters, using methods such as nuclear magnetic resonance spectroscopy (1H NMR), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), ultraviolet-visible spectroscopy (UV-Vis), and the textural parameters, using low-pressure nitrogen adsorption (LPNA) at −196.15 °C. The analyses of the porous structure of the bottom ash samples revealed differences in texture of ASH 1 to ASH 6, specifically in the pore volume (micro- and mesopores), specific surface area, and pore size distribution. Changes in the structural and porous characteristics of the samples were attributed to the duration of the seasoning process. The results of the structural analysis of the bottom ash suggest its application in the concrete industry, potentially enhancing the long-term mechanical strength of concrete. The results of the textural analysis indicate the possible use of MSWI bottom ash in environmental applications, as the internal surface area could be further developed.

A Structural Description of Biases That Generate Immortal Time.

Immortal time may arise in survival analyses when individuals are assigned to treatment strategies based on post-eligibility information or selected based on post-assignment eligibility criteria. Selection based on eligibility criteria applied after treatment assignment results in immortal time when the analysis starts the follow-up at assignment. Misclassification of assignment to treatment strategies based on treatment received after eligibility results in immortal time when the treatment strategies are not distinguishable at the start of follow-up. Target trial emulation prevents the introduction of immortal time by explicitly specifying eligibility and assignment to the treatment strategies, and by synchronizing them at the start of follow-up. We summarize analytic approaches that prevent immortal time when longitudinal data are available to emulate the target trial from the time of treatment assignment. The term "immortal time bias" suggests that the source of the bias is the immortal time, but it is selection or misclassification that generates the immortal time, leading to bias.

Simple vertex algebras arising from congruence subgroups

For any congruence subgroup Γ, we consider the vertex algebra of Γ-invariant global sections of chiral de Rham complex on the upper half plane that are meromorphic at the cusps. We give a description of the linear structure of the Γ-invariant vertex algebra by exhibiting a linear basis determined by meromorphic modular forms, and generalize the Rankin-Cohen bracket of modular forms to meromorphic modular forms. We also show that the Γ-invariant vertex algebra is simple.

Description Generation Using Variational Auto-Encoders for Precursor microRNA.

Micro RNAs (miRNA) are a type of non-coding RNA involved in gene regulation and can be associated with diseases such as cancer, cardiovascular, and neurological diseases. As such, identifying the entire genome of miRNA can be of great relevance. Since experimental methods for novel precursor miRNA (pre-miRNA) detection are complex and expensive, computational detection using Machine Learning (ML) could be useful. Existing ML methods are often complex black boxes that do not create an interpretable structural description of pre-miRNA. In this paper, we propose a novel framework that makes use of generative modeling through Variational Auto-Encoders to uncover the generative factors of pre-miRNA. After training the VAE, the pre-miRNA description is developed using a decision tree on the lower dimensional latent space. Applying the framework to miRNA classification, we obtain a high reconstruction and classification performance while also developing an accurate miRNA description.

Tripartite interaction representation algorithm for crystal graph neural networks

Driven by emerging research paradigms, the application of artificial intelligence models presents innovative tools for designing materials and optimizing their performance. In the field of materials science, there is a current research emphasis on exploring techniques for characterizing material structures to achieve precise descriptions. This paper proposes a crystal graph convolution neural network model that incorporates a tripartite interaction approach. The model not only incorporates atomic information, bond lengths, and bond angles but also offers a method for updating atoms and bond lengths, facilitating accurate descriptions of crystal structures by capturing implicit structural information. Focusing on predicting the formation energy of crystalline compounds, our results demonstrate improved predictive accuracy compared to existing representation algorithms. The average error of the formation energy in the random dataset, demonstrating robust generalization, is merely 0.048eV/atom, with an impressive R2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$R^{2}$$\\end{document} value of 0.994. Additionally, this paper establishes a crystal graph neural network framework for predicting algorithm performance. By integrating automatic parallel algorithms and an automated process, we achieve a synthesis of these techniques, enhancing computational efficiency and streamlining algorithm usage.

Study on the pore structure and permeability evolution of tight sandstone under liquid nitrogen freezing‐thawing cycles based on NMR technology

To further raise the gas extraction efficiency of the tight sandstone, the liquid nitrogen (LN2) freezing-thawing cycles method can be employed to improve the permeability of the low-permeability reservoirs. Permeability is generally regarded as a macroscopic description of the pore structure and usually has functional relationship to pore structure properties. The permeability of the rock is closely related to the change of microscopic pore structure. The permeability of rock depends on how the subzero temperatures changed the microscopic pore structure of rock, but it has not yet been confirmed obviously. In this study, the nuclear magnetic resonance (NMR) technique was adopted to investigate the pore structure evolution law and permeability of the tight sandstone with different LN2 freezing-thawing cycles. The results demonstrate that the LN2 freezing-thawing cycles promotes pore development and micro-fracture connection, and enhances the pore connectivity. The proportion of meso-pores, macro-pores and micro-fractures in the sandstone samples increases significantly, which provides a channel for the sandstone gas flow and extraction. Total porosity and effective porosity of the samples present a trend of rapid increase as the number of LN2 freezing-thawing cycles increasing, while the residual porosity decreases as the number of LN2 freezing-thawing cycles increasing. Coates model, SDR model (mean T2 model) and PP model were used to calculate and evaluate the permeability of the samples subjected to different LN2 freezing-thawing cycles. Furthermore, PP model can provide a better permeability estimate than the classical Coates and SDR model.

Seasonal states and carbon dynamics in key areas of the carbon polygon in the Chechen Republic, Russia

The aim of the work was to analyze the relationship between carbon dynamics and changes in the states of natural territorial complexes in two key areas of the carbon polygon in the Chechen Republic from the standpoint of landscape and landscape‐geophysical approaches. The work was carried out at two sites of the carbon polygon in the Chechen Republic: in Chernorechye (the Chechen plain under water‐protective broad‐leaved forests, about 169 m above sea level) and Roshni‐Chu (low‐ mountain broad‐leaved forests, about 450 m above sea level).Methods: landscape‐geophysical description of geomasses, geohorizons and vertical structures in key areas, detailed microclimatic studies using installed loggers with temperature and humidity sensors, observations of the state of the vegetation cover, biomass dynamics, determination of mortmass fractions on the soil surface, as well as humus and basic nutrients.The relationship between carbon dynamics and changes in seasonal states of natural‐territorial complexes is expressed in changes in landscape‐ geophysical parameters: the ratio of geomasses, geohorizons and vertical structures. Seven seasonal states of natural‐territorial complexes with different carbon dynamics have been identified. Two of them are key to understanding the long‐term carbon balance. These states are determined by the dynamics of accumulation and decomposition of mortmass. The ways of changing the intensity of carbon deposition based on the creation of new phytocenoses, increasing soil fertility, including by optimising the carbon and nitrogen ratio have been identified. A more radical way – mortmass utilisation – requires detailed research and consideration of environmental consequences.

On the orthogonal matrix in the Casas-Ibarra parametrization for the Yukawa interactions of Majorana neutrinos

The Casas-Ibarra (CI) parametrization of the Yukawa coupling matrix of Majorana neutrinos is generalized by considering the exact seesaw relation and including non-unitarity of the 3×3 Pontecorvo-Maki-Nakagawa-Sakata (PMNS) flavor mixing matrix. With the help of a full 6×6 Euler-like block description of the flavor structure for the seesaw mechanism, we find that the orthogonal matrix O in the CI parametrization can be expressed as Oij=Mj/miFij with mi and Mj being the masses of light and heavy Majorana neutrinos and Fij consisting of the PMNS and active-sterile flavor mixing parameters (for i,j=1,2,3). Assuming a specific pattern of O is therefore equivalent to imposing some special conditions on the seesaw parameter space.

Overview of Finnish national patient data repository for research on medical risk assessment

The Kanta Patient Data Repository (PDR) contains healthcare data from the population of Finland for more than a decade. The repository is a continuously expanding real world dataset produced by many information systems and healthcare service providers. Kanta data has been available for secondary uses such as scientific research since 2019. The data can be requested from the Finnish authority Findata. However, before a request has been accepted, it is difficult to assess if the accumulated data allows answering a specific research question. Publicly available descriptions of data structures in the Kanta PDR do not tell how much they are used in practice. This publication enables future data use cases by providing a view on the overall availability of types of structured health data in the Kanta PDR based on a sample of 96 200 medical histories of over 18-year-old patients. We conclude that the Kanta PDR is a promising source of real world data for development and evaluation of medical risk calculators within the Finnish population. The wide coverage of the Finnish population and timeliness of the data are its strengths as a source of research data also outside of Finnish context. However, the limitations on data availability in variable level need to be considered on a case-by-case basis. Main challenges in the use of data in the Kanta PDR are multiple code systems for laboratory results, short durations of recorded data for specific data types, and missing or very rarely used structured format e.g., in cases of tobacco and alcohol use.