Energy storage has been of paramount importance in addressing the disparity between energy production and consumption periods, particularly in the context of renewable energy sources. The stored energy can be harnessed for heating, cooling, or generating electricity. Despite rapid advances in scientific research and technology, bibliometric analyses in the field of energy storage have shown that studies on thermocline energy storage systems remain scarce. These studies examine 649 documents, including research articles, review articles, books and book chapters published in the Scopus database between 1990 and 2024, using the software programs R, RStudio, VOSviewer and OriginPro. The evolution of publications in the field of sensible heat thermal energy storage over the past 34 years are presented, analyzing trends by country, international collaborations, publication year, affiliations, authors, citations, and the connections between author communities. Based on the analyzed publications, China emerges as the most productive country, benefiting from its growing interest in scientific research, particularly in the energy sector. The study reveals that many investigations have centred on unconventional sensible thermal energy storage materials, such as rocks, sand, and solid industrial waste, which are considered low-cost alternative solutions. These innovative solutions could be key to achieving sustainable development goals, particularly UN Sustainable Development Goals (SDGs) 7 and 13, provided that scientific research evolves to become applicable on an industrial scale. • Bibliometric review of 649 TES papers (1996–2024) and 252 references. • China leads with 19.6% of global output; 10 of its universities rank in top 20. • Middle East and North Africa and Gulf TES research grew rapidly in last decade, driven by energy transitions. • Modeling studies need validation through large-scale experimental systems. • Large-scale TES pilots are rare: Morocco (6.5 MW th ) and Switzerland (12 MW th ).

Recent studies have shown the interest of automating the classification of rock images using deep learning architectures. The biggest issue for practitioners when applying these methods to real-world data sets generated during mineral exploration is the long time required to create and label a data set. This study proposes a complete workflow to label and classify drill core photographs with minimal time required for labeling through five successive steps: i) using exploration drill core photographs, rock cores are separated from wooden trays using morphological operators; ii) feature descriptors are then extracted from rock images using color histograms for colorimetric information and Gabor filters for texture information; iii) features extractors then serve as input data for self-organizing maps (SOM) for generating clusters that can be partially labeled by geologists for generating a labeled data set with limited efforts, generating a data set made of labeled and unlabeled images; iv) the partially labeled data set can then be used to train either fully supervised or semi-supervised deep learning architectures for generating classifications; v) the classification model obtained can then be re-used on unseen data to automate logging process. This study presents this workflow separately for two different geological domains, namely a data set of sedimentary rocks classified according to the intensity of bleaching features and a data set of crystalline basement rocks classified by lithological domains. Software code and data set are made publicly available. • Development of a complete workflow to transform drill-core photographs datasets (directly obtained from mineral exploration) into a labeled dataset usable for deep-learning tasks. • Evaluation of the possibility of inferring lithological (for the basement subset) and alteration (for the basin subset) classes based on a self-labeling strategy. • Evaluation of the potential to improve classification accuracy by using unlabeled samples in a semi-supervised way.

International audience

Synthesis of pyrazine derivative-substituted phthalocyanines: evaluation of their Sono/photochemical and antimicrobial properties supported by DFT studies.

TeleCritical Care Reimagined: Efficiency Through Digital Communication Application.

This article presents the principles, software architecture, and performance analysis of the GPU port of the lattice Boltzmann software library Palabos [J. Latt et al., “Palabos: Parallel lattice Boltzmann solver”, Comput. Math. Appl. 81, 334–350, (2021)] . A hybrid CPU-GPU execution model is adopted, in which numerical components are selectively assigned to either the CPU or the GPU, depending on considerations of performance or convenience. This design enables a progressive porting strategy, allowing most features of the original CPU-based codebase to be gradually and seamlessly adapted to GPU execution. The new architecture builds upon two complementary paradigms: a classical object-oriented structure for CPU execution, and a data-oriented counterpart for GPUs, which reproduces the modularity of the original code while eliminating object-oriented overhead detrimental to GPU performance. Central to this approach is the use of modern C++, including standard parallel algorithms and template metaprogramming techniques, which permit the generation of hardware-agnostic computational kernels. This facilitates the development of user-defined, GPU-accelerated components such as collision operators or boundary conditions, while preserving compatibility with the existing codebase and avoiding the need for external libraries or non-standard language extensions. The correctness and performance of the GPU-enabled Palabos are demonstrated through a series of three-dimensional multiphysics benchmarks, including the laminar–turbulent transition in a Taylor–Green vortex, lid-driven cavity flow, and pore-scale flow in Berea sandstone. Despite the high-level abstraction of the implementation, the single-GPU performance is similar to CUDA-native solvers, and multi-GPU tests exhibit good weak and strong scaling across all test cases. Beyond the specific context of Palabos, the porting methodology illustrated here provides a generalizable framework for adapting large, complex C++ simulation codes to GPU architectures, while maintaining extensibility, maintainability, and high computational performance. Program Title: Palabos: Parallel Lattice Boltzmann Solver CPC Library link to program files: https://doi.org/10.17632/cx7j83pr69.1 Developer’s repository link: https://gitlab.com/unigespc/palabos Licensing provisions: AGPLv3 Programming language: C++17, using C++ parallel algorithms Supplementary material: A compressed file containing a snapshot of the described code version Nature of problem: The lattice Boltzmann method (LBM) is a widely used approach in computational fluid dynamics (CFD) for simulating flows in complex geometries, turbulence, multiphase systems, and thermal transport. The Palabos library was designed to provide the scientific community with a flexible and efficient parallel LBM platform, implementing a broad range of physical and numerical models. Until now, Palabos has been CPU-based, relying on distributed-memory parallelism through MPI. However, with modern simulation platforms and supercomputers increasingly dominated by GPU accelerators, a CPU-only implementation no longer provides competitive performance. This work presents a complete redesign of the Palabos architecture to run efficiently on multi-GPU systems. The new code supports hybrid execution: legacy CPU components remain functional, new GPU-optimized modules can be developed within a compatible programming model, and both can interact seamlessly. This version supersedes the original CPU-only implementation and will serve as the basis for all future development of Palabos. Solution method: The GPU version of Palabos introduces a new data container, the AcceleratedLattice , designed specifically for accelerator execution. It preserves the user interface of the CPU-based MultiBlockLattice , but replaces its array-of-structures layout and virtual-function polymorphism with a structure-of-arrays layout, thread-safe collision–streaming schemes, and integer tags for model selection. These changes enable efficient memory access, fine-grained parallelism, and compatibility with GPU execution models, while maintaining backward compatibility and supporting hybrid CPU/GPU workflows. Parallelism is expressed through C++17 standard parallel algorithms, compiled with the NVIDIA HPC SDK. Fundamental parallel algorithms such as for_each , transform_reduce , and exclusive_scan are used to implement the essential building blocks of the lattice Boltzmann method, including linear processing, reductions, and data packing for MPI communication. This data-oriented design yields a portable and maintainable GPU implementation, preserves modularity, and ensures that existing Palabos applications can be ported to GPU with minimal modifications. Additional comments including restrictions and unusual features: The GPU version currently relies on the platform-independent framework of C++ parallel algorithms but has, as of now, only been tested with NVIDIA GPUs (compiled with nvc++) supports NVIDIA architectures with CUDA-compatible compilers (tested with nvc++). The current version of the code does not compile with the 25.X series of the nvc++ compiler.

We introduce CuPyMag , an open-source, Python-based framework for large-scale micromagnetic simulations with magnetostriction. CuPyMag solves micromagnetics with finite elements in a GPU-resident workflow in which key operations, such as right-hand-side assembly, spatial derivatives, and volume averages, are tensorized using CuPy’s BLAS-accelerated backend. Benchmark tests show that the GPU solvers in CuPyMag achieve a speedup of up to two orders of magnitude compared to the CPU codes. Its runtime grows linearly/sublinearly with problem size, demonstrating high efficiency. Additionally, CuPyMag uses the Gauss-Seidel projection method for time integration, which not only allows stable time steps (up to 11 ps) but also solves each governing equation with only 1–3 conjugate-gradient iterations without preconditioning. CuPyMag accounts for magnetoelastic coupling and far-field effects arising from the boundary of the magnetic body, both of which play an important role in magnetization reversal in the presence of local defects. CuPyMag solves these computationally-intensive multiphysics simulations with a high-resolution mesh (up to 3M nodes) in under three hours on an NVIDIA H200 GPU. This acceleration enables micromagnetic simulations with non-trivial defect geometries and resolves nanoscale magnetic structures. It expands the scope of micromagnetic simulations towards realistic, large-scale problems that can guide experiments. More broadly, CuPyMag is developed using widely adopted Python libraries, which provide cross-platform compatibility, ease of installation, and accessibility for adaptations to diverse applications. Program Title: CuPyMag CPC Library link to program files: https://doi.org/10.17632/pmkz4vzz7w.1 Developer’s repository link: https://github.com/hongyiguan/CuPyMag OSF repository link: https://osf.io/6nmsv/?view_only=dbd8fa339f8740a6bd009c03499ea23f Licensing provisions: Apache-2.0 Programming language: Python 3 Nature of problem: The program addresses large-scale micromagnetic simulations that are computationally demanding due to the solution of magnetoelastic coupling (mechanical equilibrium with magnetostriction at each time step), far-field demagnetization effects, and arbitrarily shaped inclusion-like defects that require unstructured finite-element meshes. Solution method: CuPyMag implements a GPU-resident, tensorized workflow built on CuPy’s BLAS-accelerated backend. This design exploits highly optimized linear algebra kernels, enabling efficient parallel execution and maintaining high GPU utilization. It uses an ellipsoid theorem to account for far-field demagnetization effects, and the Gauss-Seidel projection method for stable and efficient time integration.

In this work, we report a new version of the HOS-Ocean code which is an open-source solver for deterministic nonlinear ocean wave propagation. The numerical model makes use of the so-called High-Order Spectral method, which ensures high efficiency and accuracy. This new release includes i) additional physical features such as spatially varying current and bathymetry together with dedicated models to account for wave-breaking, and ii) numerical developments with parallelization of the code through MPI as well as a more user-friendly code (pre-built binaries available, and simplified building procedure and operation). HOS-Ocean v2.1 is released as open-source, available from GitLab , developed and distributed under the terms of GNU General Public License (GPLv3). Along with the source code, detailed documentation under Sphinx format is available. Program Title: HOS-Ocean CPC Library link to program files: (to be added by Technical Editor) Developer’s repository link: https://gitlab.com/lheea/HOS-Ocean Code Ocean capsule: (to be added by Technical Editor) Licensing provisions(please choose one): GPLv3 Programming language: Fortran Supplementary material: Journal reference of previous version: Comput. Phys. Commun. 203 (2016) 245–254. Does the new version supersede the previous version?: Yes Reasons for the new version: Enhancement of capabilities and ease of use Summary of revisions: Implementation of additional physical features: spatially varying current and bathymetry, and inclusion of dedicated models to account for wave-breaking. Numerical developments with parallelization of the code through a Message Passing Interface (MPI) [1] and more user-friendly code (pre-built binaries available, and simplified building procedure and operation). Nature of problem: HOS-Ocean has been developed to study the propagation of highly nonlinear sea-states over large domains and long duration. Regular and irregular wave fields can be studied, including the effect of directionality (short-crested seas). Solution method: HOS-Ocean provides an implementation of the High-Order Spectral method, which solves the problem formulated on the free surface by means of a pseudo-spectral method. Time integration uses an adaptive Runge-Kutta 4(5) scheme. Additional comments including restrictions and unusual features: In short-crested seas, the individual treatment of wave-breaking events with the Barthelemy-Tian model [1,2] is not yet available. The simulation of directional sea states is consequently limited to non-breaking conditions with this breaking model. The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. [1] http://www.mpi-forum.org [2] B.R. Seiffert, G. Ducrozet, F. Bonnefoy. Simulation of breaking waves using the high-order spectral method with laboratory experiments: wave-breaking onset. Ocean Modelling, 119:94–104, 2017.[3]B.R. Seiffert, G. Ducrozet. Simulation of breaking waves using the high-order spectral method with laboratory experiments: wave-breaking energy dissipation. Ocean Dynamics, 68(1):65–89, 2018.

To develop SXRNSCLC-PRSP software which can predict the prognostic risk and survival of resected T1-3N0-2M0 (according to the 9th AJCC/UICC TNM stage of lung cancer) non-small cell lung cancer (NSCLC) patients in Shanxi Province China more comprehensively, accurately and conveniently, and provide reference and help for clinicians tailoring patients'follow-up adjuvant therapy and care. Patients with NSCLC whose tumor stage is T1-3N0-2M0 underwent surgical treatment only were selected from the medical records of Shanxi Tumor Hospital. The clinicopathological features that may affect the prognosis of these patients'survival outcome and survival time were collected (there are no missing data), and then the survival data set was established. In the survival data set, 70% of the patients were randomly selected as the training set, and the rest were composed of the test set. A prognostic model of resected T1-3N0-2M0 NSCLC patients in Shanxi Province China was constructed using the training set, and the model was validated using the test set. SXRNSCLC-PRSP software was developed to implement the model for prognostic risk and survival prediction in such patients. The software can be used free of charge by clinicians who log on to a specific website. After they register and log on to the software, they can select the corresponding clinicopathological characteristics of the patient and obtain the prognostic risk and survival prediction results of the patient. Using a Cox proportional hazard regression model, we determined the independent prognostic factors and obtained a prognostic index (PI) eq. PI = [Formula: see text] = -0.392X2 + 0.927X71 + 1.695X72 + 0.537X111 + 0.401X112-0.434X113. Using the PI equation, we determined the PI value of every patient. According to the quantile of the PI value, patients were divided into three risk groups: low-, intermediate-, and high-risk groups with significantly different survival rates. Meanwhile, we obtained the restricted mean survival times and 1-5-year survival rates of the three groups. Based on the construction of prognostic risk and survival prediction model and the programming in JAVA language, we developed the SXRNSCLC-PRSP software to determine the prognostic risk and associated survival of patients with resected T1-3N0-2M0 NSCLC in Shanxi Province China. At last, we have established a Risk Assessment System(RAS). In this system, clinicians can use the software. clinicians can input URL https://www.sxrnsclcpps.com into one of browsers (latest versions of Chrome, Firefox, Safari, Microsoft Edge which have passed the compatibility test for the login function) to reach its login screen. By processing clinical parameter inputs, the software stratifies patient risk levels and generates Restricted Mean Survival Time (RMST) estimates and survival rate projections, providing clinical support for follow-up care planning, adjuvant therapy selection, and patient screening. After prognostic factor analysis, prognostic risk grouping and corresponding survival assessment, we developed a novel software program and established the Risk Assessment System (RAS). It is practical and convenient for clinicians to evaluate the prognostic risk and corresponding survival of patients with resected T1-3N0-2M0 NSCLC in Shanxi Province China. Additionally, it has guiding significance for clinicians to make decisions about complementary treatment for patients.

There have been proposals of single imputation and improper multiple imputation based on the support vector machine (SVM) in the literature. By applying the algorithms of bootstrapping and multivariate imputation by chained equations (mice) to the SVM, the current study proposes proper multiple imputation based on the SVM that works well for a binary variable with general missing patterns in high-dimensional data. Evidence based on Monte Carlo simulations shows that the proposed method works better than the state-of-the-art method in terms of the bias, the coverage rate of confidence intervals (CIs), the average CI lengths, and the computational efficiency. Additional evidence based on the European Values Study also confirms similar results. Furthermore, this article provides an easy-to-use software program that can be used in conjunction with the R package mice. Therefore, the finding in the current study is an important addition to the literature of missing data and causal inference.

ABSTRACT The aim of the study is to develop and test a methodology for training qualified interpreters in audio description interpreting, thereby ensuring the accessibility of information for visually impaired individuals. The methodology includes a combination of theoretical and empirical research, with a focus on experimentation to assess its effectiveness. Additional research methods employed include system analysis, logical analysis, comparison, synthesis, deduction, and classification. The study involved students studying translation and linguistics at national universities in Kazakhstan, who participated in the training to develop audio description interpreting skills. The findings highlight the importance of audio description interpreting as a vital tool for providing visually impaired people with equal access to multimedia content. The study emphasises the role of audio description interpreters in enhancing the user experience and in collaboration with assistive technology developers to create more accessible digital resources. Furthermore, the study explores the development of essential skills, including Braille literacy, interpreting audio materials, and utilising specialised computer programmes for audio and text processing. The results from the experimental group showed significant improvement in these skills, confirming the efficacy of the developed methodology.

Microcomputed tomography analysis of marginal adaptation and internal fit of zirconia frameworks with direct-to-abutment connections using a deep learning artificial intelligence model.

To compare whole-brain histogram analysis (WBHA) of amyloid-β (Aβ) positron emission tomography (PET) using several magnetic resonance imaging (MRI)-based brain extraction (brain extraction tool [BET]) methods, to evaluate a novel quantitative analysis method, namely the Top 20% Gray and White Matter Ratio (GW-ratio), to determine appropriate thresholds, and to evaluate diagnostic performance in comparison with the Centiloid scale (CL). We analyzed structural MRI, 18F-flutemetamol amyloid PET images, and dementia severity scores (Global Clinical Dementia Rating [G-CDR] and Mini-Mental State Examination [MMSE]) of 262 participants. For WBHA, BET was performed using structural MRI and three different BET software programs, namely High-Definition-BET (HD-BET), FMRIB Software Library (FSL), and Statistical Parametric Mapping (SPM). Skewness and mode-to-mean ratio (MMR) were measured using brain-extracted PET. The Top 20% Map was generated from SPM BET images, separated into gray and white matter voxels, and their ratio was calculated as the GW-ratio. The CL value was computed using structural MRI. Aβ-negativity or positivity was visually determined. Skewness from three BET methods was strongly negatively correlated with CL. Skewness (HD-BET) showed the strongest correlation (R = -0.9043). Moreover, the GW-ratio strongly correlated with CL (R = 0.8332), whereas MMR, particularly MMR (FSL) (R = 0.2112), showed poor correlation. All indicators significantly distinguished Aβ-negative from Aβ-positive visuals. CL had the highest area under the curve (AUC, 0.9959), followed by skewness (HD-BET) (0.9927), Top 20% GW-ratio (0.9872), and skewness (SPM) (0.9779), with no statistical difference between CL and skewness (HD-BET) (P = 0.5763). Based on mean and SD values from 118 cognitively unimpaired (G-CDR = 0, MMSE ≥ 28) and visually Aβ-negative participants, 95% cut-off limits for Aβ-negative individuals without dementia symptoms were: CL ≤ 12.9, skewness (HD-BET) ≥ 0.1769, MMR (HD-BET) ≤ 0.9372, skewness (FSL) ≥ 0.1819, MMR (FSL) ≤ 1.9132, skewness (SPM) ≥ -0.0382, MMR (SPM) ≤ 1.1274, and GW-ratio ≤ 0.1079. WBHA using MRI-based BET and GW-ratio showed strong correlations with CL and demonstrated a diagnostic performance comparable to that of CL.

ABSTRACT Background and Context Digital technologies have become part of our lives. Meanwhile, computer programming, the activity that mediates the communication between humans and technology, has expanded to fields and practitioners beyond Computer Science. Programmers who give instructions to digital artifacts should have proper awareness of the artifacts’ states and environments. This often requires them to change their point of view in order to better interact with those systems. Notably, this skill resembles a fundamental human ability that can be learned and developed over time: empathy. Objective In this study, we probed potential connections between computer programming activities (object-oriented programming, educational coding games, educational robotics) and programmers’ level of empathy, to gain further insights into human-technology interactions. Method Through a quantitative approach, an online survey was implemented and data were collected from 104 adults in Greece with prior experience in computer programming. The majority of the participants work in education or education-related fields (58%). Findings According to the results, statistically valid relationships were observed between ease of programming and empathy, either directly with it or with at least one of its components (cognitive empathy, emotional empathy and social skills). Implications The indicated correlations between computer programming and empathy could represent a paradigm shift in the field of Education and lead to a deeper understanding of Computer Science Education and Didactics.

ABSTRACT Background and Context Integrating computational thinking (CT) into K-12 education is hindered by insufficient teacher training, gender biases in STEM, and challenges in evaluating professional development (PD) programs due to limited assessment tools. Most research overlooks affective and contextual variables, focusing only on CT skills. Objective The study aims to understand the factors that enable an effective integration of CT teaching practices and gender affirmative actions, after teachers participate in a PD program. Method We used a sequential explanatory mixed methods design to examine a nationwide PD program for middle and high school teachers in a middle-income country. Pretest-posttest surveys (n = 3790) and classroom observations (n = 383) assessed teachers’ CT knowledge, technological self-efficacy, practices, and gender bias, while three focus groups involving 17 teachers explored the mechanisms influencing these outcomes. Findings The PD program significantly improved teachers’ content knowledge in CT, technological self-efficacy, and reduced gender bias in STEM. However, classroom observations revealed incomplete implementation of CT practices and gender equity strategies. Qualitative findings suggest key mechanisms shaping teacher implementation practices: teachers’ cognitive shifts toward recognizing CT’s relevance across disciplinary domains and school subjects; perceived capacity in managing technological tools and technological complexity; the importance of institutional support; and, reflective processes triggered by observing increased engagement among female students. Implications Teachers’ cognitive shifts, self-efficacy, and institutional support are pivotal for effective CT integration into school practices. Our findings underscore the necessity of PD programs to address these aspects, fostering the intentional application of CT practices and gender equity strategies.

Effect of material and connector position on the accuracy of CAD-CAM milled posts.

Accurate and rapid identification of large vessel occlusion (LVO) on CT angiography (CTA) is crucial for optimal management, especially regarding endovascular therapy decisions. Automated tools for LVO detection, including RapidAI and Viz.ai, have been employed in some small studies, but their accuracy has rarely been compared in a large consecutive patient series. The purpose of this study was to evaluate RapidAI and Viz.ai's LVO detection software on CTA in a consecutive series of suspected stroke patients at a comprehensive stroke center. Both software programs were used in parallel for two years to compare the diagnostic accuracy. CTA data from 1,589 consecutive stroke alerts were retrospectively reviewed. Radiology reports and expert review of CTA and CTP imaging confirmed the LVO diagnosis. LVO was defined as occlusion or high-grade stenosis of the intracranial ICA or MCA M1 segment. Cases were excluded if not sent to the software or if there was poor bolus, metal artifact, or brain hemorrhage. 1,523 cases met the inclusion criteria. Among these, 147 (10%) had LVOs. RapidAI processed 1,521 cases (>99%), and Viz.ai processed 1,430 (90%). RapidAI identified 144 LVO cases (98%) vs. 108 (73%) by Viz.ai (P<0.0001). RapidAI correctly identified 94% of LVO-negative cases vs. 91% by Viz.ai (P=0.004). RapidAI detected a higher percentage of LVOs compared to Viz.ai (98% vs 73%) and correctly identified more LVO-negative cases (94% vs 91%). Viz.ai did not detect 39 LVOs. The number of LVOs missed by the Viz.ai software (26%) could potentially lead to delays in LVO diagnosis and treatment times.

Diabetic foot ulcers are serious skin wounds that affect many people with diabetes, often leading to severe infections or even the loss of a limb. This paper explores how artificial intelligence -computer programs that can learn from data-is changing the way doctors find and treat these wounds. By reviewing 68 recent studies, we looked at how these smart technologies analyze different types of medical images to help patients. Our findings show that AI can help doctors identify health risks much earlier than traditional methods. These computer tools are also excellent at measuring how a wound is healing and predicting which treatments will work best for each individual. Because AI can spot tiny patterns in images that the human eye might miss, it makes medical care more precise and consistent. In conclusion, using AI to manage diabetic foot wounds offers a powerful way to improve patient health. By helping doctors make better, data-driven decisions, this technology can lead to faster healing and reduce the risk of serious complications for people living with diabetes.

Despite the importance of scientific software for research, it is often not formally recognized and rewarded. This is especially true for foundational libraries, which are hidden below packages visible to the users (and thus doubly hidden, since even the packages directly used in research are frequently not visible in the paper). Research stakeholders like funders, infrastructure providers, and other organizations need to understand the complex network of computer programs that contemporary research relies upon. In this work, we use the CZ Software Mentions Dataset to map the upstream dependencies of software used in biomedical papers and find the packages critical to scientific software ecosystems. We propose centrality metrics for the network of software dependencies, analyze three ecosystems (PyPi, CRAN, Bioconductor), and determine the packages with the highest centrality.

Passive fit and trueness are keys to the success of complete-arch implant-supported cobalt chromium frameworks, so this study aimed to assess and compare the passive fit and trueness of cobalt chromium (Co-Cr) complete-arch implant-supported frameworks fabricated using milling and three-dimensional (3D) printing technologies with those produced using the conventional lost wax technique. A maxillary typodont with 5 implant digital analogs was scanned using a desktop scanner, a complete-arch implant-supported framework was designed, and the design's standard tessellation language (STL) file was designated as the reference file. A total of 24 frameworks were fabricated. In the first group, the frameworks were initially milled from wax blanks and subsequently processed using the conventional lost wax technique. In the second group, frameworks were milled from Co-Cr blanks, while in the third group, frameworks were 3D printed utilizing the selective laser melting technique from Co-Cr powder. Frameworks were scanned, and corresponding STL files were imported into a surface-matching software program to assess trueness. Passive fit was evaluated using a one-screw test and a handheld digital microscope. Statistical analysis was performed using one-way and two-way ANOVA followed by the Tukey post hoc test (α = 0.05) for pairwise comparison. Significant differences were found among fabrication techniques for both passive fit and trueness. The milled group demonstrated the lowest mean of vertical gap during passive fit assessment, while the conventional lost wax group exhibited the highest mean. Correspondingly, trueness values were lowest for the milled frameworks, intermediate for 3D-printed frameworks, and highest for conventional lost-wax. Digital fabrication techniques, particularly CAD-CAM milling, provided superior fit and trueness compared to conventional casting of Co-Cr complete-arch implant frameworks.