Digital Model Research Articles

Accuracy of One-Piece vs. Segmented Three-Dimensional Printed Transfer Trays for Indirect Bracket Placement

Objective: To assess the accuracy of three-dimensional (3D) printed one-piece vs. multiple segmented transfer trays for indirect bonding techniques in moderate and severe crowding cases. Methods: Eighty digital maxillary dental models were produced by an extraoral scanner. 3D-printed one-piece and segmented trays were virtually designed utilizing Maestro 3D Ortho Studio® v4 and printed using a NextDent printer. The sample was classified into two groups: Group 1 (moderate crowding) included 40 digital models with a space deficiency of 6–7 mm, and Group 2 (severe crowding) included 40 digital models with a space deficiency of 10 mm. Ortho classic brackets were then placed into the 3D printed models with the aid of the transfer trays, and the models with the final bracket positioning were scanned using iTero scanner. Four measurements were selected on each tooth to perform the analysis. Mann–Whitney and Kruskal–Wallis tests were used for comparisons. A p-value of ≤ 0.05 was considered statistically significant. Results: In the moderate crowding group, statistically significant differences were detected between the one-piece, segmented, and control groups for three measurements (p < 0.001), while the rest of the measurements showed no significant differences (p > 0.05). In the severe crowding group, no significant differences were detected for any of the measurements. Conclusions: One-piece and segmented 3D-printed transfer trays are considered accurate tools for indirect bonding in moderate and severe malocclusion cases. The severity of crowding did not affect the accuracy of bracket transfer in indirect bonding.

Voxel-wise segmentation for porosity investigation of additive manufactured parts with 3D unsupervised and (deeply) supervised neural networks

AbstractAdditive Manufacturing (AM) has emerged as a manufacturing process that allows the direct production of samples from digital models. To ensure that quality standards are met in all samples of a batch, X-ray computed tomography (X-CT) is often used in combination with automated anomaly detection. For the latter, deep learning (DL) anomaly detection techniques are increasingly used, as they can be trained to be robust to the material being analysed and resilient to poor image quality. Unfortunately, most recent and popular DL models have been developed for 2D image processing, thereby disregarding valuable volumetric information. Additionally, there is a notable absence of comparisons between supervised and unsupervised models for voxel-wise pore segmentation tasks. This study revisits recent supervised (UNet, UNet++, UNet 3+, MSS-UNet, ACC-UNet) and unsupervised (VAE, ceVAE, gmVAE, vqVAE, RV-VAE) DL models for porosity analysis of AM samples from X-CT images and extends them to accept 3D input data with a 3D-patch approach for lower computational requirements, improved efficiency and generalisability. The supervised models were trained using the Focal Tversky loss to address class imbalance that arises from the low porosity in the training datasets. The output of the unsupervised models was post-processed to reduce misclassifications caused by their inability to adequately represent the object surface. The findings were cross-validated in a 5-fold fashion and include: a performance benchmark of the DL models, an evaluation of the post-processing algorithm, an evaluation of the effect of training supervised models with the output of unsupervised models. In a final performance benchmark on a test set with poor image quality, the best performing supervised model was UNet++ with an average precision of 0.751 ± 0.030, while the best unsupervised model was the post-processed ceVAE with 0.830 ± 0.003. Notably, the ceVAE model, with its post-processing technique, exhibited superior capabilities, endorsing unsupervised learning as the preferred approach for the voxel-wise pore segmentation task.

Transformation of e-commerce business models in the digital economy

Purpose. Research on the transformation of e-commerce business models in the conditions of the digital economy, analysis of the main directions of changes in business processes, as well as the determination of key differences between Internet commerce, e-commerce and online commerce, substantiation of the difference in the sources of generation of added value and identification of the factors that facilitate the transition from traditional e-commerce business models to digital ones. Methodology. When conducting the research, the trends of the development of electronic commerce and the factors contributing to their transformation in the conditions of the digital economy were revealed by the method of formal analysis. Findings. This study presents an analysis of trends and factors affecting the development of digital commerce and the transformation of digital commerce business models. The directions of integration of digital technologies into business processes and strategic aspects of the implementation of digital solutions into business practice are substantiated. The key factors that contribute to the transformation of e-commerce business models into digital commerce business models are identified, in particular, in the creation and implementation of new business models that allow for effective adaptation to the conditions of the digital economy. It is found that the economic basis of transformations of business models is the sources of creation of added value. It has been proven that digital technologies, which form the basis of e-business, are carriers and main sources of added value creation, which is reflected in business monetization models. The impact of artificial intelligence on the prospects and further development of digital commerce business models is analyzed. Originality. The scientific novelty obtained as a result of this research consists in the definition and substantiation of a new factor – added value, which is the main factor influencing the transformation of e-commerce business models into a digital commerce business model, which takes place under the influence of the digital economy. The novelty of the obtained research results in terms of substantiation of added value as a factor of transformation is proven by confirming the hypothesis that the formation of e-commerce business models and their transformation into digital commerce models take place under the influence of digital sources of added value creation.

Evaluating the Implementation and Clinical Effectiveness of an Innovative Digital First Care Model for Behavioral Health Using the RE-AIM Framework: Quantitative Evaluation.

In the United States, innovation is needed to address the increasing need for mental health care services and widen the patient-to-provider ratio. Despite the benefits of digital mental health interventions (DMHIs), they have not been effective in addressing patients' behavioral health challenges as stand-alone treatments. This study evaluates the implementation and effectiveness of precision behavioral health (PBH), a digital-first behavioral health care model embedded within routine primary care that refers patients to an ecosystem of evidence-based DMHIs with strategically placed human support. Patient demographic information, triage visit outcomes, multidimensional patient-reported outcome measure, enrollment, and engagement with the DMHIs were analyzed using data from the electronic health record and vendor-reported data files. The RE-AIM (Reach, Effectiveness, Adoption, Implementation, Maintenance) framework was used to evaluate the implementation and clinical effectiveness outcomes of PBH. PBH had a 47.58% reach rate, defined as patients accepting the PBH referral from their behavioral health integrated clinician. PBH patients had high DMHI registration rates (79.62%), high activation rates (76.54%), and high retention rates at 15 days (57.69%) and 30 days (44.58%) compared to literature benchmarks. In total, 74.01% (n=168) of patients showed clinical improvement, 22.47% (n=51) showed no clinical change, and 3.52% (n=8) showed clinical deterioration in symptoms. PBH had high adoption rates, with behavioral health integrated clinicians referring on average 4.35 (SD 0.46) patients to PBH per month and 90%-100% of clinicians (n=12) consistently referring at least 1 patient to PBH each month. A third (32%, n=1114) of patients were offered PBH as a treatment option during their triage visit. PBH as a care model with evidence-based DMHIs, human support for patients, and integration within routine settings offers a credible service to support patients with mild to moderate mental health challenges. This type of model has the potential to address real-life access to care problems faced by health care settings.

Georecon: a coarse-to-fine visual 3D reconstruction approach for high-resolution images with neural matching priors

ABSTRACT Visual 3D reconstruction enables rebuilding 3D scenes from captured images, serving as a fundamental data source for digital earth modeling and intelligent cities. In the foundational step, recent methods leverage learning-based descriptors for image registration and achieve tremendous advances in precision and robustness. However, these methods inevitably execute down sampling towards high-resolution images to fit the needs of neural networks, which leads to precision degradation of feature localization and matching. Thus, we propose GeoRecon: a novel coarse-to-fine visual 3D reconstruction method that optimally utilizes high-resolution images for high-quality visual 3D reconstruction. Firstly, the coarse stage conducts coarse reconstruction from downsampled images by performing neural matching with geometric priors. Secondly, we define the fine-grained stage, proposing a GPU-based algorithm for generating image-patch correspondences based on the neural matching priors to perform fine-grained image registration. Finally, based on the optimized camera poses under this coarse-to-fine paradigm, progressive dense reconstruction leveraging efficient neural radiance fields is proposed to accomplish the high-quality MVS reconstruction. Comparative experiments across various scenarios demonstrate the proposed method’s superior precision, robustness, and reconstruction quality.

Frequency dependence of reflections on radar landmarks

Purpose. Reducing the dispersion of radar reflections from local objects, with multi-frequency sensing, to solve the problem of orientation by radar reflections from objects. Methodology. Reflections from local objects in the entire frequency range of the radar station (RS) at the same radio engineering position were measured by three independent radars of the same type on different days and at different antenna elevations. The deviation of the radar stations in the position did not exceed 500 meters. Coordinates (azimuth, range) of reflections of several separate local objects were allocated for each radar. The average values of reflections from local objects and their dispersion in the frequency range were calculated. Using various algorithms, individual frequencies were sampled and the reflected signals were averaged at these frequencies. The decrease in the dispersion of the reflected signal from the number of frequencies at which reflections were measured and from the algorithm for selecting these frequencies was investigated. Findings. Averaging the values of reflections from local objects for several frequencies leads to a decrease in dispersion and, as a result, to a more accurate correspondence of the reflected signal level to the geometric size of the local object. The variance decreases most rapidly for a small number of frequencies selected for averaging when selecting frequencies located in an interval of at least 1% relative to each other. Originality. To solve the problem of orientation based on radar reflections from local objects, it is necessary to identify the landmarks selected on a digital terrain model. Due to the fact that local objects (hills) are a collection of many reflectors falling into the allowed volume of the radar, with different levels of reflections and random phases, there may not be radar reflection from a local object at a certain frequency, or it may be very small. In order to unambiguously identify all landmarks, measurements must be carried out at several frequencies. The work has established how many frequencies measurements should be performed at and on what principle these frequencies should be selected. Practical value. The advent of digital terrain models made it possible to solve the problem of terrain orientation by comparing radar reflections from local objects with reflection models based on digital terrain maps. Radar reflection models use mathematical expectations of reflection values, unlike real reflections, which have random deviations in signal levels depending on the operating frequency. Reducing the variance of these deviations increases the accuracy of identifying characteristic local objects (landmarks) used to orient the radar in the absence of data from satellite navigation systems.

Expecting the expected – learning from the past to provide forward scenarios through geomorphic change detection, monitoring and modeling

This paper tells the story of a landslide, its origins, its activity and the actions undertaken to mitigate the risks that it poses. The Rotolon landslide is a large Deep-seated Gravitational Slope Deformation (DGSD), located in the Eastern Italian Alps, whose unremitting movements provide a sediment supply for large-scale debris flow events. It has been active since at least 1789, threatening the valley where the thermal baths town of Recoaro Terme is located. In 2010, a major reactivation of the landslide channelled 320,000 m3 of material towards the town causing significant concern, the evacuation of the exposed population and threatening several buildings. A few days after the emergency, the personnel of the Research Institute for Geo-Hydrological Protection of the Italian Research Council (IRPI-CNR) deployed a monitoring system consisting of an automatic total station, several extensometers and web cameras to monitor the evolution of the unstable slope and set up an early warning and alarm system equipped with sirens to warn the local population. Subsequently, after the emergency phase, the 2010 event was studied through multi-temporal LiDAR Digital Terrain Models (DTMs) and modeling. The authors have continued monitoring and actively studying this landslide ever since. In 2020, a new LiDAR survey of the area allowed assessment of the sediment dynamics within the catchment through the comparison with the post-2010 event LiDAR DTM. Based on DEM of difference maps, new insight into the behaviour of the catchment emerged, which appears to be influenced both by natural processes and anthropic activities. The authors were able to assess the amount of sediment that could be stored in the channel without causing overflooding and to calculate the expected damage to the built environment should another event occur. Furthermore, the considerable amount of data collected by the monitoring system throughout the years has allowed identification of two active sectors of the DGSD that may be prone to detachment, and through numerical modeling, future hazard scenarios were produced. Based on these outcomes, a second-tier targeted monitoring campaign was implemented, consisting of a network of four permanent GNSS receivers, additional topographic benchmarks and web cameras, and a new early warning protocol, in an ever-updating cycle of monitoring, modeling and mitigation.

The role of modern digital marketing in modeling of relationships with consumers of goods and services in virtual markets

Subject. The article considers digital marketing modeling as a tool to increase the size of business and the number of potential customers, reduce advertising costs thus increase overall sales. Objectives. The focus is on underpinning the role of modern digital marketing in customer relationship modeling in virtual markets. Methods. The study employs the systems approach, methods of theoretical generalization, comparison, data grouping, synthesis, concretization, and analysis. Results. We offered our own definition of the concept of digital marketing and established its role in the digital economy, presented a bonus card of communication with consumers in virtual markets, demonstrating the main effects that arise in a virtual environment as a result of relationships between sellers and buyers. Our designed model of managing consumer relations in the virtual market includes the main steps for a company to attract and retain customers. Conclusions. Understanding the needs of the audience, developing effective interaction strategies, data analysis, and optimization enable companies to successfully manage customer relationships and achieve high results in the digital environment.

Research on the method of digital technology assisted direct resin composite restoration for deep distal caries in mandibular second molars

Objective: To explore the digital design and fabrication technology of personalized restorative matrix for dental filling, and to explore the feasibility of direct resin restoration for deep caries lesions in distal neck of mandibular second molar. Methods: For patients with deep caries lesions in the distal neck of the mandibular second molar who visited the Department of Cariology and Endodontology of Peking University School and Hospital of Stomatology from September 2023 to April 2024, after preparing the cavity and gingival retractor, a three-dimensional intraoral scanner was used to obtain three-dimensional data of the patient's dentition. In the dental restoration computer-aided design software, the inlay function was used to generate the restored tooth morphology. The edge range of the personalized restorative matrix was drawn on the restored model by three-dimensional reverse engineering software to achieve edge sealing effect. The selected edge range data was processed with distal shelling to generate a digital model of a personalized restorative matrix with a thickness of 0.5 mm. A metal three-dimensional printer was used to fabricate the titanium alloy restorative matrix, and its application was completed in 10 clinical cases. The marginal adaptation and retention stability of the personalized restorative matrix were evaluated under a dental microscope, and forming effect evaluation was performed through immediate postoperative periapical radiographs. Results: The preliminary clinical application of the personalized restorative matrix fabricated using digital technology revealed that, in the treatment of 10 affected teeth, rubber dam isolation was successfully ensured, resulting in clinically effective direct resin composite restorations with optimal marginal adaptation and reasonable contours. Immediate postoperative periapical radiographs showed good convexity of the filling body, with no overhangs found. Both marginal adaptation and retention stability met the requirements of clinical treatment. Conclusions: The personalized restorative matrix designed in this study can solve the clinical problems of moisture separation and resin forming in the treatment of deep caries lesions in distal neck of the mandibular second molar, and can achieve stable and reliable adhesive restoration effects.

MEASUREMENT AND CHARACTERISTIC ANALYSIS OF SKELETAL GEOMETRIC PARAMETERS IN CHINESE HUMANS

Problem: Significant differences exist between the body dimensions of Chinese and Western individuals, and these differences affect the injury characteristics of passengers in traffic accidents. Most current parametric finite element human models are based on Western body data, which does not adequately assess the injury risks for Chinese individuals. Therefore, it is imperative to establish a digital model that reflects the anatomical features of Chinese humans. This requires comprehensive anthropometric data specific to the Chinese population. Aim: This study aims to collect and analyze skeletal geometric parameters from various representative regions in China across different age groups to fill the gap in Chinese anthropometric data. Additionally, it seeks to explore regional and age-related differences in these parameters, providing a scientific basis for developing finite element models that reflect the characteristics of the Chinese population. Methods: Clinical CT data of skeletal geometric parameters were collected from 224 individuals across seven representative regions of China, including parameters of the head, chest, and lower limbs. Descriptive statistics, K-W tests, and U-tests were used to analyze regional differences. Spearman correlation and linear regression analyses were employed to assess the impact of age. Furthermore, weighted averages and weighted variances of skeletal geometric parameters were calculated to reflect the characteristics of individuals from various regions across the country, which will be applied in the development of Chinese human models. Results: The results indicate significant regional differences in the skeletal geometric parameters of Chinese individuals, exhibiting regional patterns between the north–south and east–west areas. While skeletal geometric parameters showed significant differences with age, no clear statistical pattern was observed. Conclusion: This study systematically extracts and analyzes the skeletal geometric parameters of the Chinese population from regional and age perspectives for the first time. These data will be applied in the development of Chinese human models, providing crucial support for improving passenger safety in traffic accidents, enhancing vehicle safety design, and establishing anthropometric standards suitable for the Chinese context.

Application and Effect of Computer-Aided Design in Table Tennis Training

The application of computer technology in the field of sports training is more and more extensive. This paper discusses the application and effect of computer-aided design in table tennis training. More and more automatic control systems which rely on digital model control appear in people’s lives. There is also a lack of introduction of automatic control systems for the training of table tennis players to improve their training efficiency and reaction ability. Therefore, based on an artificial intelligence algorithm, a genetic algorithm is integrated. According to the patting and kicking action of the automatic control system and the camera imaging device, the feature points in the motion process are divided. Based on an artificial intelligence algorithm, feature points are taken as initial values. Through testing, the matrix orthogonality of motion attitude is determined. The influence of computer-aided design on the training effect of table tennis was analyzed. Finally, we will summarize the advantages of computer-aided design in table tennis training and its future development direction.

3D Printing with Self-Healing Materials and Applications

3D printing also called as the additive manufacturing. It is revolutionizing various industries by enabling the production of complex objects directly from digital models. This technology offers significant advantages over traditional manufacturing methods. Especially in reducing material waste and increased design flexibility. The range of 3D printing application contains healthcare to aerospace, reflecting its growing importance in modern society. Recently, 3D printing advancements have introduced in self-healing (SH) materials, it saved limitations related to the durability and repairability of printed objects. SH materials are categorized into external and internal systems. External SH materials use embedded healing agents that repair damage through chemical reactions, while internal systems rely on dynamic bonding within the material itself. This innovation not only extends the functional life of 3D printed items but also supports trends in mass customization and sustainability. This paper explores the mechanisms, types, and applications of SH materials in 3D printing, and mainly focus on their potential to enhance product longevity and functionality across medical, construction, and consumer goods sectors.

Predictability of Maxillary Expansion with Invisalign® First: Treatment Planning vs. Outcome

The aim of this study is to retrospectively investigate the predictability of maxillary arch expansion with Invisalign ® First in mixed dentition. In a sample of 64 treated patients, 3D digital models from the ClinCheck® software were compared with post-treatment digital models. Predicted maxillary expansion was related to the final outcome of expansion. At the cuspidal level, there was observed a predictability of 59.68% for deciduous canines, 63.77% for first deciduous molars, 66.99% for second deciduous molars, and 55.61% for first permanent molars. At the gingival level, there was observed a predictability of 49.87% for deciduous canines, 53.11% for first deciduous molars, 53.36% for second deciduous molars, and 45.16% for first permanent molars. The difference between the predicted and achieved expansion was statistically significant (p < 0.05). Within the present limitations, our results suggest that, with Invisalign® First, it is possible to expand the upper arch in mixed dentition in an effective and predictable way. Clear aligners could represent a new and valid alternative for arch expansion in growing patients.

Gain-based Green Ant Colony Optimization for 3D Path Planning on Remote Sensing Images

Metaheuristic algorithms are powerful methods for handling complexities in 3D environments because of their adaptability property. This paper proposes a gain-based, green-ant colony optimization (GGACO) method for 3D path planning on remote sensing images. Shortest paths do not always imply minimum energy consumption. Moreover, computational complexity tends to increase in the case of higher-dimensional data. A novel method is proposed to alleviate this issue, one that provides an efficient path with minimum energy consumption by adding a gain quantity during its search. The results are validated using performance measures, viz., path length, time, and energy cost. Real-time images, along with their corresponding ground truth and “digital surface models (DSM)”, have been sourced from the “International Society for Photogrammetry and Remote Sensing (ISPRS)”. Comparisons have been made against state-of-the-art algorithms and analyzed. Finally, the convergence and stability of the proposed method have been verified; it has been found that the proposed method outperforms the existing method by 6%, 11% and 5% regarding length, computation time, and energy, respectively.

A Low-Computational-Complexity Digital Predistortion Model for Wideband Power Amplifier

This paper proposes a Composition Piecewise Memory Polynomial (CPMP) digital predistortion model based on a Vector Switched (VS) behavioral model to address the challenges of severe nonlinearity and strong memory effects in wideband power amplifiers (PAs). To tackle this issue, two thresholds are calculated and used to segment the envelope values of the input signal according to the nonlinear distortion characteristics of the PA. In this approach, a Generalized Memory Polynomial (GMP) model is employed for the lower segment, a Memory Polynomial (MP) model is employed for the middle segment, and a higher-order GMP model is employed for the upper segment. By sharing the fundamental MP among the proposed segmented models and leveraging a design methodology that configures different cross terms, memory depths, and polynomial orders for each segment, this model achieves superior linearization performance while simultaneously reducing the computational complexity associated with model extraction. The experimental results demonstrate that the adjacent channel power ratio (ACPR) of the predistorted PA output signal using the proposed model improves from −36 dBc to −54 dBc, matching the performance of the GMP model. Furthermore, this performance is 0.5 dBc better than the Piecewise Dynamic Deviation Reduction (PDDR) and Decomposed Vector Rotation (DVR) models. Notably, the complexity of the proposed parameter extraction process is 28.8% of the DVR model, 21.79% of the GMP model, and 12.83% of the PDDR model.

Structural and Karst Studies Using 3D Digital Outcrop Model: A Case Study in Gunung Keriang, Kedah, Peninsular Malaysia

A digital outcrop model (DOM) of the Permo-Triassic limestone of Gunung Keriang, Kedah, was constructed for structural analysis and karst study. Structural analysis of beddings and fractures within the DOM revealed that the limestone beds are characterized by gently inclined planes with NE ̶ SW and NW ̶ SE strikes, forming an upright N ̶ S trending synclinal fold, and being cross-cut by four steeply-dipping fracture sets (NE ̶ SW, NW ̶ SE, N ̶ S, and E ̶ W). The synthesis of these fracture sets indicates that the NW ̶ SE and NE ̶ SW fractures form a conjugate pattern suggestive of E ̶ W shortening, which aligns with the observed N ̶ S fold. Karst development, including elongated sinkholes and cave paths oriented in the NE ̶ SW direction, correlates with the fracture patterns, highlighting the NE ̶SW fracture network significant role in karst formation. The integrated data supports the hypothesis that these fracture patterns are major factors in the dissolution and development of karst features in the region.

Regulatory Support of Digital Model of Urban Territory in the Russian Federation

The article studies the digital model of the urban area as a mandatory tool for managing urban processes. The study of the regulatory support of the digital model is of great importance in the light of the rapid development of digital technologies in the urban environment. Purpose: To determine the regulatory support significance in creating the digital model of the urban area and its tools. Geographic information platforms of citywide importance are studied as well as their formation in the legislative field of the Russian Federation. It is assumed that the process of creating the digital model of the urban area, is inevitable in view of the development trend of urban planning in the Russian Federation.Methodology/approach: Based on theoretical analysis and synthesis of various sources of information, the diagram is constructed for information sources on the digital model of the urban area. The regulatory support of the digital model is specified as a basis for the development of geographic information system at all levels of significance. Requirements for regulatory acts of the construction industry for the digital model are formulated. Aspects of the legal field are identified as tools that require reflection in the digital model of the urban area.Value: This research can underlie the creation of regulations or their transformation to contribute to the sustainable and harmonious development of the urban environment.

A new digital model for Italian Integrated Home Care: strengths, barriers, and future implications

Abstract Issue/Problem After the COVID-19 pandemic, Italy’s National Health Service (NHS) is transforming by adopting telemedicine through its National Recovery and Resilience Plan, aiming to modernize healthcare delivery and ensure equity. In this plan Territorial Coordination Centers (COT) were designed to improve patient access and continuity of care. However, regulatory challenges hinder the widespread adoption of telemedicine. Our work describes the technical, structural, and operational aspects of the new Italian Integrated Home Care (IHC) digital model, addressing strengths, barriers, and future implications. Description of the problem The implementation of the IHC digital model faces multiple challenges. Italy’s poor technical infrastructure, especially in rural areas, hampers access to critical services. Resistance to change among rural systems and the elderly, coupled with low digital literacy, inhibits telemedicine adoption. Fragmentation in the NHS leads to resource disparities, particularly disadvantaging southern regions. Italy also grapples with a severe shortage of healthcare professionals, posing a threat to the model’s sustainability. Results The National Digital Health Agency enacts the IHC model by overseeing telemedicine services through a cloud-based protocol. Each Region provides “Basic Telemedicine Services”: healthcare professionals’ and patient teleconsultation, telemonitoring, teleassistance. Communication between services, infrastructures, and local health authorities is facilitated by a modular interoperability layer, ensuring data standards and quality. A national telemedicine dissemination portal will contain data on all telemedicine solutions provided. Lessons Clear communication is essential for telemedicine acceptance. COTs enhance coordination and management. Bridging the technology gap for disadvantaged groups, supporting frontline employees and addressing adoption factors is vital to overcome the challenges faced. Key messages • The National Digital Health Agency drives telemedicine services under the IHC model. Each region offers Basic Telemedicine Services, ensuring data standards, quality and interoperability of data. • Italy’s telemedicine adoption faces poor infrastructure, resistance and workforce shortages. Focusing on equity, healthcare workers support and bridging the technology gap will be key.

Looking to the past, considering the present and preparing for the future: digital technologies and the business model canvas

Purpose This paper aims to propose a reconfiguration of the business model canvas (BMC) to highlight the relevant, and often critical, role of digital technologies (DTs). Design/methodology/approach The authors review the business model literature to further clarify its dynamic nature (expressed by innovation, adaptation and experimentation) and the factors that may affect it. Ultimately, to better capture the role of DTs, the authors posit a new iteration of the BMC (namely, the digital business model canvas [DiBMC]). Findings Historically, DTs were not clearly represented in the BMC, often resulting in them being disparately woven into other boxes or not clearly captured at all. By reconfiguring the nine original building blocks, and adding two new ones related to DTs, the DiBMC supports a more complete visualization of how value is created and the role of DTs. Originality/value DTs are too relevant in today’s business environment to not more formally model them on BMCs. The proposed reconfiguration of the BMC into the DiBMC improves the utility of the tool for practitioners, scholars and students alike.

Building credibility for human systems integration in model‐based systems engineering

AbstractRobust and trusted digital human representations are necessary to successfully account for human considerations in model‐based systems engineering (MBSE). Multiple domains and modeling frameworks leverage verification, validation, and accreditation (VV&A) processes to characterize when and under what conditions a model is valid to establish credibility. A literature review was completed on mathematical, physics‐based, software development, discrete event simulation, agent‐based, system dynamics, and MBSE models with the goal of proposing a process for performing VV&A on digital engineering (DE) and MBSE models for sociotechnical systems. However, this research also revealed the need for a broader framework to characterize the risk associated with using these models for making high‐consequence decisions. While accomplishing the literature review, another approach to building credibility was identified that is used heavily in the financial industry, namely model risk management (MRM). This process is extended by leveraging MRM approaches from within the financial community to propose a framework for sociotechnical model users to characterize the risk of using MBSE models to make programmatic decisions. The primary contribution of this work is to document a meta‐analysis of model VV&A while proposing an alternative approach to characterizing and communicating credibility that was discovered during this analysis. This approach could be a viable option for ensuring the credibility of human systems integration in MBSE models.