Aid Of Computer Research Articles

Recent One Decade Trends in Mathematical Representation Research: Systematic Mapping Study

Research can change over time and can be influenced by technological developments, educational trends, and current social issues. Developments on trends in mathematical representation research over the past 10 years are discussed in this systematic mapping study (SMS). The question of review research with the systematic mapping study method is how the trend of mathematical representation research over the last 1 decade and what new topics have the opportunity to be researched by future researchers related to the themes of mathematical representation. The method used in this review is the PRISMA method which includes 5 stages carried out: 1) defining eligibility criteria, 2) determining information sources, 3) data selection, 4) data collection, and 5) data collection. In this systematic mapping study, it starts from searching for articles on the topic of mathematical representation during the last 1 decade, namely the range of 2013-2023, articles obtained from the scopus database in July 2023 with the keywords "representations" AND : Mathematics" initial data obtained 1907 articles after the exclusion process obtained 120 articles which were then analyzed using R-Studio and Vos-Viewer tools. The results of SMS obtained the relationship of representation topics in the last 10 years of research with the topics of visual, computer software, computer aid instruction, data mining, open source software, network architecture, natural language processing systems, intelligent systems and information analysis. In addition, research over the past 1 decade on the topic of representation has led more to data mining, security of data and STEM. Artificial Intelligence or artificial intelligence is the latest topic that over the past 3 years has grown in various articles that deal with the theme of mathematical representation and accompanied by the theme of multi-representation. The evolution of research topics related to mathematical representations that used to be only related to visual representations and image representations now leads to computer programs, programming algorithms and artificial intelligence, this shows that over the past 1 decade there has been an evolution of research in the implementation of representations in technology.

Quantum Chemical Insights into DNA Nucleobase Oxidation: Bridging Theory and Experiment.

The oxidation free energies of DNA nucleobases in aqueous solution are still matter of extensive discussion because of the contrasting results reported so far. With the aim of settling a longstanding debate about the oxidation potentials of DNA constituents, herein we report the results of state-of-the-art DFT-based molecular dynamics simulations, in which the whole solvent environment is modeled at the atomistic level, by using DFT supercell calculations, with periodic boundary conditions. Calculated vertical ionization energies are very close to those observed by photoelectron spectroscopy both in the gas phase and in solution. One-electron oxidation free energies in aqueous solution agree well with the results of differential pulse voltammetry measurements and with those inferred by photoelectron spectroscopy with the aid of theoretical computations to estimate vibrational relaxation.

Innovative approache for the nonlinear atangana conformable Klein-Gordon equation unveiling traveling wave patterns

The aim of current work is to establish novel traveling wave solutions of the nonlinear Atangana conformable Klein - Gordon equation using a new extended direct algebraic technique. The Klein - Gordon equation is the relativistic state of the Schrödinger equation with a second - order time derivative and zero spin. Complex wave variable transformation is used to convert Atangana conformable nonlinear differential equation into an ordinary differential equation. Using the proposed technique based on Maple software structure, various types of solutions, such as, generalized trigonometric, generalized hyperbolic, and exponential functions, are established. When special parameteric values are considered for this method, solitary wave solutions can be obtained through other methods, such as the (G′G)-expansion method, the modified Kudryashov method, the sub-equation method, and so forth. A physical explanation is provided for the solutions under consideration to enhance comprehension of the physical phenomena resulting from the obtained solutions, provided that the physical parameters are set appropriately using 3D, 2D, and contour simulations. The results demonstrated that the new extended direct algebraic method provides a more potent mathematical tool for solving numerous more nonlinear partial differential equations with the aid of symbolic computation.

Diagnosing skin cancer using social spider optimization (SSO) and error correcting output codes (ECOC) with weighted hamming distance

Skin cancer is a common disease resulting from genetic defects, and early detection is critical to improve treatment outcomes. Diagnostic programs that use computer aid especially those that use supervised learning are very useful in early diagnosis of skin cancer. This research therefore presents a new approach that integrates optimization methods with supervised learning to improve skin cancer diagnosis using machine vision approach. The presented method is initiated by data pre-processing that involves the removal of unnecessary data. Then, to segment the images, a combination of K-means clustering and social spider optimization technique is employed. The region of interest is then extracted from the segmented image and from this region a convolutional neural network extracts the significant features. To enhance the classification performance as compared with the standard classifiers, this research introduces a new concept of error correcting output codes coupled with a weighted Hamming distance in the group of gamma classifiers. The ability of the proposed approach in segmentation of skin lesions and classifying them was tested using samples from the ISIC-2017 and ISIC-2016 databases. The introduced method obtained state-of-the-art accuracy on both datasets (ISIC-2016: 97.10%, ISIC-2017: 95.17%). In particularly, the accuracy of the introduced approach for both these databases is at least 1.17% higher than the compared methods. This proves the high performance of the suggested method based on the usage of the convolutional neural networks for feature extraction and gamma classifiers with error correcting output codes for classification in skin cancer detection.

A Rationalized Approach to Design and Discover Novel Non-steroidal Derivatives through Computational Aid for the Treatment of Prostate Cancer.

Prostate cancer is one of the most prevalent cancers in men, leading to the second most common cause of death in men. Despite the availability of multiple treatments, the prevalence of prostate cancer remains high. Steroidal antagonists are associated with poor bioavailability and side effects, while non-steroidal antagonists show serious side effects, such as gynecomastia. Therefore, there is a need for a potential candidate for the treatment of prostate cancer with better bioavailability, good therapeutic effects, and minimal side effects. This current research work focused on identifying a novel non-steroidal androgen receptor antagonist through computational tools, such as docking and in silico ADMET analysis. Molecules were designed based on a literature survey, followed by molecular docking of all designed compounds and ADMET analysis of the hit compounds. A library of 600 non-steroidal derivatives (cis and trans) was designed, and molecular docking was performed in the active site of the androgen receptor (PDBID: 1Z95) using Auto- Dock Vina 1.5.6. Docking studies resulted in 15 potent hits, which were then subjected to ADME analysis using SwissADME. ADME analysis predicted three compounds (SK-79, SK-109, and SK-169) with the best ADME profile and better bioavailability. Toxicity studies using Protox-II were performed on the three best compounds (SK-79, SK-109, and SK-169), which predicted ideal toxicity for these lead compounds. This research work will provide ample opportunities to explore medicinal and computational research areas. It will facilitate the development of novel androgen receptor antagonists in future experimental studies.

N = 3−3 lines in the extreme ultraviolet spectrum of europium (Z = 63)

Using high-resolution flat-field spectrographs at the LLNL SuperEBIT electron beam ion trap, we have observed extreme ultraviolet spectra (λ 32–43 Å) of highly charged ions of Eu ( Z = 63) under a range of production conditions suitable for Na- through Zn-like ions. Almost 30 lines were identified with the aid of Flexible Atomic Code computations and spectral modeling. While some of the wavelength measurements are among the most accurate in this wavelength range, some of the identifications are still tentative. We discuss how experimental conditions and spectral complexity interact in the analysis process.

Phytochemicals in Drug Discovery-A Confluence of Tradition and Innovation.

Phytochemicals have a long and successful history in drug discovery. With recent advancements in analytical techniques and methodologies, discovering bioactive leads from natural compounds has become easier. Computational techniques like molecular docking, QSAR modelling and machine learning, and network pharmacology are among the most promising new tools that allow researchers to make predictions concerning natural products' potential targets, thereby guiding experimental validation efforts. Additionally, approaches like LC-MS or LC-NMR speed up compound identification by streamlining analytical processes. Integrating structural and computational biology aids in lead identification, thus providing invaluable information to understand how phytochemicals interact with potential targets in the body. An emerging computational approach is machine learning involving QSAR modelling and deep neural networks that interrelate phytochemical properties with diverse physiological activities such as antimicrobial or anticancer effects.

Prototype pipeline modelling using interval scanning point clouds

AbstractWith the aid of computer aided design (CAD) and building information modelling (BIM), as-built to as-designed comparison has seen many developments in improving the workflow of manufacturing and construction tasks. Recently, evolution has been centred around automation of scene interpretation from three-dimensional (3D) scan data. The scope of this paper is to assess assemblies as the installation process progresses and inferring if arising deviations are problematic (complex task). The adequacy of utilising unorganised point clouds to compliance check are trialled with a real life down-scaled prototype model in conjunction with a synthetic dataset. This work aims to highlight areas where large rework could be avoided, in part by the detection of potential clashes of components early in the pipeline installation process. With the help of an extracted model in the form of a point cloud generated from a scanned physical model and a 3D CAD model representing the nominal geometry, an operator can be made visually aware of potential deviations and component clashes during a pipeline assembly process.

Revision of ex vivo endodontic biofilm model using computer aided design

ObjectiveMost endodontic diseases are bacterium-mediated inflammatory or necrotic process induced by contaminated dental pulp. Although great advances are being performed to obtain more efficient antibacterial strategies for persistent infections, most studies lack of representative models to test their antibacterial effects and their outcomes cannot be promptly translated to clinical practice. Therefore, this study aimed to refine an ex vivo endodontic biofilm model combining human tooth, computer guided design and 3D printing to obtain a more reproducible and predictable model. MethodsMonoradicular teeth were cut using three different methods: hand-held (HCC), mechanical precision (MPC) and computer aid guided cutting (CGC). Then, blocks were reassembled. The different model preparations were assessed in terms of dimensional tolerance, surface analysis, liquid tightness and Enterococcus faecalis biofilm development for 21 days, which was studied by metabolic assays and confocal microscopy. Then, the proposed model was validated using different commercial disinfecting treatments. ResultsCGC exhibited significantly lower deviation and surface without defects compared to HHC and MPC, leading to superior liquid tightness. Similarly, mature biofilms with high metabolic activity and vitality were observed in all conditions, CGC showing the lowest variation. Regarding the model validation, all antibacterial treatments resulted in the complete eradication of bacteria in the standard 2D model, whereas commercial treatments exhibited varying levels of efficacy in the proposed ex vivo model, from moderately reduction of metabolic activity to complete elimination of biofilm. ConclusionsThe novel guided approach represents a more reliable, standardized, and reproducible model for the evaluation of endodontic disinfecting therapies. Clinical SignificanceDuring antibacterial treatment development, challenging 3D models using teeth substrates to test antibacterial treatments novel guided approach represents a more reliable, standardized, and reproducible model for the evaluation of endodontic disinfecting therapies.

Computer-Aided Design of 3D-Printed Clay-Based Composite Mortars Reinforced with Bioinspired Lattice Structures.

Towards a sustainable future in construction, worldwide efforts aim to reduce cement use as a binder core material in concrete, addressing production costs, environmental concerns, and circular economy criteria. In the last decade, numerous studies have explored cement substitutes (e.g., fly ash, silica fume, clay-based materials, etc.) and methods to mimic the mechanical performance of cement by integrating polymeric meshes into their matrix. In this study, a systemic approach incorporating computer aid and biomimetics is utilized for the development of 3D-printed clay-based composite mortar reinforced with advanced polymeric bioinspired lattice structures, such as honeycombs and Voronoi patterns. These natural lattices were designed and integrated into the 3D-printed clay-based prisms. Then, these configurations were numerically examined as bioinspired lattice applications under three-point bending and realistic loading conditions, and proper Finite Element Models (FEMs) were developed. The extracted mechanical responses were observed, and a conceptual redesign of the bioinspired lattice structures was conducted to mitigate high-stress concentration regions and optimize the structures' overall mechanical performance. The optimized bioinspired lattice structures were also examined under the same conditions to verify their mechanical superiority. The results showed that the clay-based prism with honeycomb reinforcement revealed superior mechanical performance compared to the other and is a suitable candidate for further research. The outcomes of this study intend to further research into non-cementitious materials suitable for industrial and civil applications.

Research on the Practice of Higher Vocational Mathematics Teaching Based on a Mathematical Experiment Platform

For most vocational colleges, the introduction of mathematics laboratory courses is still in the continuous exploration phase, and the views on mathematics laboratory courses vary from one institution to another. In the two years since the introduction of mathematics experiments, we have adopted a combination of basic mathematical experiments and modeling mathematical experiments to open up students' horizons, stimulate their enthusiasm for learning mathematics, cultivate their awareness and ability to use mathematical methods with the aid of computers to solve practical problems, and foster their innovative spirit.

Exploring the structural and electronic characteristics of phenethylamine derivatives: a density functional theory approach

Accurate structure elucidation of biologically active molecules is crucial for designing and developing new drugs, as well as for analyzing their pharmacological activity. In this study, density functional theory calculations are applied to explore the electronic structure and properties of phenethylamine derivatives, including Amphetamine, Methamphetamine, and Methylene Dioxy Methamphetamine(MDMA). The investigation encompasses various aspects such as geometry optimization, vibrational analysis, electronic properties, Molecular Electrostatic Potential analysis, and local and global descriptor analysis. Additionally, the study utilizes Natural Bond Orbital analysis and Quantum Theory of Atoms in Molecules to investigate the chemical bonding and charge density distributions of these compounds. Experimental techniques such as Fourier transform infrared (FT-IR) and Raman spectroscopic analysis are employed in the range of 4000-400 cm-1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$cm^{-1}$$\\end{document} and 4000-50 cm-1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$cm^{-1}$$\\end{document}, respectively. Theoretical vibrational analysis with Potential Energy Distribution(PED) assignments is conducted, and the resulting frequencies are compared to experimental spectral data, revealing good agreement. By correlating various structural parameters with the pharmacological activity of each derivative, computational structure elucidation aids in understanding the unique actions of phenethylamine derivatives. The obtained results offer a comprehensive understanding of the molecular behavior and properties of these drugs, facilitating the development of new drugs and therapies for addiction and related disorders.

A survey on recent advances in the computation of asymptotes

AbstractIn this paper, we summarize two algorithms for computing all the generalized asymptotes of a plane algebraic curve implicitly or parametrically defined. The approach is based on the notion of perfect curve introduced from the concepts and results presented in Blasco and Pérez-Díaz (Comput Aided Geom Des 31(2):81–96, 2014), Blasco and Pérez-Díaz (Comput Aided Geom Des 31(7-8):345–357, 2014), and Blasco and Pérez-Díaz (J Comput Appl Math 278:231–247, 2015). From these results, we derive a new method that allow to easily compute horizontal and vertical asymptotes.

Optical solitons for the Hirota–Ramani equation via improved G′G-expansion method

In this work, first it is shown that the Hirota–Ramani equation, which governs the nonlinear propagation of coupled Langmuir and dust-acoustec wave in a multicomponent dusty plasma, possesses kinds of wave profile such as singular periodic profile, periodic profile, singular soliton profile, M-shape rational profile, bright soliton profile, kink profile in the form of the trigonometric, hyperbolic, and rational solutions. With the aid of symbolic computation, we select the Hirota–Ramani equation with a source to investigate the validity and advantage of the improved [Formula: see text]-expansion method and construct some frames of the 3D profiles and the contour profiles to the equation along with the 2D profiles of some solutions to understand the traveling wave dynamics. Following the selection of appropriate values for the associated parameters, more generalized solutions are provided, along with certain patterns in the solutions that are examined. This improved method is effective, concise, reliable, and can be applied for further futuristic applications.

Rational design to improve the catalytic efficiency and stability of arginine deiminase

Arginine deiminase (ADI) has garnered significant interest because of its ability to objectively eradicate cancer cells and produce L-citrulline. To meet the production demands, this study focused on enhancing the enzyme activity and thermal stability of ADI. In this study, 24 ADI mutants were obtained through computer aid site-specific mutation in the ADI of Enterobacter faecalis. Notably, the specific enzyme activities of F44W, N163P, E220I, E220L, N318E, A336G, T340I, and N382F increased, reaching 1.33–2.53 times that of the original enzyme. This study confirmed that site-specific mutations are critical for optimizing enzyme function. Additionally, the F44W, N163P, E220I, T340I, and A336G mutants demonstrated good thermal stability. The optimal pH for mutant F44W increased to 8, whereas mutants E220I, I244V, A336G, T340I, and N328F maintained an optimal pH of 7.5. Conversely, the M109L, N163P, E220L, I244L, and N318E mutants shad an optimal pH of 7. This study revealed that mutant enzymes with increased activity were more likely to contain mutation sites situated near the four loops associated with catalytic residues, whereas mutations at the dimer junction sites had a higher tendency to enhance enzyme stability. These findings contribute to the development of ADI industrial applications and its modifications.

Non-animal models for blood–brain barrier permeability evaluation of drug-like compounds

Diseases related to the central nervous system (CNS) are major health concerns and have serious social and economic impacts. Developing new drugs for CNS-related disorders presents a major challenge as it actively involves delivering drugs into the CNS. Therefore, it is imperative to develop in silico methodologies to reliably identify potential lead compounds that can penetrate the blood–brain barrier (BBB) and help to thoroughly understand the role of different physicochemical properties fundamental to the BBB permeation of molecules. In this study, we have analysed the chemical space of the CNS drugs and compared it to the non-CNS-approved drugs. Additionally, we have collected a feature selection dataset from Muehlbacher et al. (J Comput Aided Mol Des 25(12):1095–1106, 2011. 10.1007/s10822-011-9478-1) and an in-house dataset. This information was utilised to design a molecular fingerprint that was used to train machine learning (ML) models. The best-performing models reported in this study achieved accuracies of 0.997 and 0.98, sensitivities of 1.0 and 0.992, specificities of 0.971 and 0.962, MCCs of 0.984 and 0.958, and ROC-AUCs of 0.997 and 0.999 on an imbalanced and a balanced dataset, respectively. They demonstrated overall good accuracies and sensitivities in the blind validation dataset. The reported models can be applied for fast and early screening drug-like molecules with BBB potential. Furthermore, the bbbPythoN package can be used by the research community to both produce the BBB-specific molecular fingerprints and employ the models mentioned earlier for BBB-permeability prediction.

Investigative Analysis of Cybercrime in Nigeria: Using Theft Triangle

Cybercrime or computer related crime is a criminal activity carried out with the aid of computer and the internet. The internet has contributed to the growth and development of the Nigerian economy and the world at large. However, the correlation between the growth of the internet and cybercrime in Nigeria is directly proportional to each other. Cyber insecurity is one of the biggest vices threatening the growth and advancement of the Nigerian economy. This paper provides investigative analysis of cybercrime in Nigeria using “theft triangle”. Theft triangle comprises of the three key elements that must be present before theft can take place which are “desire, motive and opportunity”. Nevertheless, since the desire and motive of a criminal cannot easily be controlled, the paper focuses more on “opportunity” as a measure to enhance the security of cyberspace in Nigeria. An experimental set-up was done to determine the security of cyberspace when “opportunity” was not controlled and when it was controlled over a period of time. The investigation revealed that cyberspace is subject to theft when “opportunity” was not controlled than when it was controlled. Hence, the study suggests appropriate modalities to enhance the security of cyberspace in Nigeria.

DERIVATION OF EXPRESSION FOR PHOTOCURRENT DENSITY FOR NON-DESTRUCTIVE TESTING OF 3D PRINTING FILAMENT BY MEANS OF TERAHERTZ SPECTROSCOPY

This report presents a revised expression for the photocurrent density in terahertz spectroscopy, which is a non-destructive testing technique of particular interest to the authors in the context of 3D printed parts. 3D printing, also known as additive manufacturing, involves creating three-dimensional objects based on computer-aided design (CAD) models. The process entails depositing, joining, or solidifying material under computer control, layer by layer.
 
 Defects in 3D printing, such as weak infill, gaps in thin walls, inconsistent extrusion, layer separation, and bed drop, can lead to low printing quality and render some printed parts unfit and unsafe for use. Moreover, the ability to tamper with internal layers without altering the exterior could result in the production of maliciously defective parts without detection. Therefore, it is crucial to test 3D printed details and filaments at each stage of processing using non-destructive methods.
 
 A comprehensive review of the relevant literature indicates the potential for enhancing measurement accuracy through various improvements in terahertz spectrometer models. The mathematical model for the photocurrent involves a convolution integral of the current density and the laser radiation pulse that irradiates the surface of the material under study. The expression within the integral incorporates parameters such as the duration of the optical pulse, carrier lifetime, and momentum relaxation time. By evaluating the integral, the result can be obtained as two terms, each being a product of an exponent and a complementary error function with the same parameters mentioned earlier.
 
 The calculation involves several steps, including a change of variables during integration. Verification using Maple software demonstrates agreement with analytical calculations and suggests a pathway for further refinement of the expression for the photocurrent density. The Maple program influenced the results by means of repeating same calculation with aid of computer and allowing to compare if analytical results are same and true, also it could be use for simulation and example calculation, for results graphical representation. 
 
 The connection between the obtained mathematical expression and its relation to 3D printing (additive manufacturing) exists. The explanation is in that the 3D printer uses filament, filament has defects, defectoscopy of filament in the terahertz domain have models and methods. The research of defectoscopy models and methods is helpful to increase accuracy of measurement of filament defect parameters and account on it and improve the quality of 3D printed details.

New Computerized Planning Algorithm and Clinical Testing of Optimized Nuss Bar Design for Patients with Pectus Excavatum.

BACKGROUND Computer-aided design (CAD) has been used in the Nuss procedure to determine the bar length and shape. Despite computer aid, the shape and design remain quite intuitive. We tested a new algorithm to determine the optimal bar shape. MATERIAL AND METHODS The normal sterno-vertebral distance was defined on computed tomography (CT) scans of patients without pectus excavatum (PEx) at the same level where the deepest depression was found on CT scans of 97 patients with PEx. Four points were marked on the CT scan of 60 patients with PEx at the deepest deformity: P1: edge of the vertebra; P2: edge of the deformity; P3: the expected contact point of the bar and the rib; and P4: the expected end of the bar. The algorithm generated 3 circles upon these points, and the fusion of the arcs drew the line of the ideal bar. Corrected and normal sterno-vertebral distance values were compared with the Mann-Whitney U test. Ten bars were bent manually guided by a 1: 1 printout of the designed bar and were implanted in 10 adolescents. RESULTS The shortest sterno-vertebral distance was 3 cm below the intermammillary line in PEx patients. The normal mean sterno-vertebral distance at this level was 10.16±1.35 cm in non-PEx patients. The mean virtually corrected sterno-vertebral distance was 10.28±1.27 cm. No significant difference was found (P=0.44). The bars were seamless and were successfully implanted. No bar needed adjustment, the operation time was shorter, and the patient satisfaction score was 9.4/10. CONCLUSIONS With our new algorithm, an optimal Nuss bar can be designed.

Developing a shortened spine functional index (SFI-10) for patients with sub-acute/chronic spinal disorders: a cross-sectional study

BackgroundBrief whole-spine patient-reported outcome measures (PROMs) provide regional solutions and future directions for quantifying functional status, evidence, and effective interventions. The whole-spine regional Spine Functional Index (SFI-25) is used internationally in clinical and scientific contexts to assess general sub-acute/chronic spine populations. However, to improve structural validity and practicality a shortened version is recommended. This study developed a shortened-SFI from the determined optimal number of item questions that: correlated with criteria PROMs being highly with whole-spine, moderately with regional-spine, condition-specific and patient-specific, and moderately-low with general-health and pain; retained one-dimensional structural validity and high internal consistency; and improved practicality to reduce administrative burden.MethodsA cross-sectional study (n = 505, age = 18-87 yrs., average = 40.3 ± 10.1 yrs) of sub-acute/chronic spine physiotherapy outpatients from an international sample of convenience. Three shortened versions of the original SFI-25 were developed using 1) qualitative ‘content-retention’ methodology, 2) quantitative ‘factorial’ methodology, and 3) quantitative ‘Rasch’ methodology, with a fourth ‘random’ version produced as a comparative control. The clinimetric properties were established for structural validity with exploratory (EFA) and confirmatory (CFA) factorial analysis, and Rasch analysis. Criterion validity used the: whole-spine SFI-25 and Functional Rating Index (FRI); regional-spine Neck Disability Index (NDI), Oswestry Disability Index (ODI), and Roland Morris Questionnaire (RMQ), condition-specific Whiplash Disability Questionnaire (WDQ); and patient-specific functional scale (PSFS); and determined floor/ceiling effect. A post-hoc pooled international sub-acute/chronic spine sample (n = 1433, age = 18-91 yrs., average = 42.0 ± 15.7 yrs) clarified the findings and employed the general-health EuroQuol-Index (EQ-5D), and 11-point Pain Numerical Rating Scale (P-NRS) criteria.ResultsA 10-item SFI retained structural validity with optimal practicality requiring no computational aid. The SFI-10 concept-retention-version demonstrated preferred criterion validity with whole-spine criteria (SFI-25 = 0.967, FRI = 0.810) and exceeded cut-off minimums with regional-spine, condition-specific, and patient-specific measures. An unequivocal one-dimensional structure was determined. Internal consistency was satisfactory (α = 0.80) with no floor/ceiling effect. Post-hoc analysis of the international sample confirmed these findings.ConclusionThe SFI-10 qualitative concept-retention version was preferred to quantitative factorial and Rasch versions, demonstrated structural and criterion validity, and preferred correlation with criteria measures. Further longitudinal research is required for reliability, error, and responsiveness, plus an examination of the practical characteristics of readability and administrative burden.