Digital Model Research Articles

3D printing of realistic body phantoms: Comparison of measured and simulated organ doses on the example of a CT scan on a pregnant woman

AbstractBackgroundMedical examinations or treatment of pregnant women using ionizing radiation are sometimes unavoidable. In such cases, the risk of harm to the embryo and fetus after exposure to ionizing radiation must be carefully estimated. However, no commercially available anthropomorphic body phantoms of pregnant women are available for dose measurements. A promising possibility for the production of body phantoms for patient groups that are not adequately represented by the phantoms of reference persons is 3D printing. However, this approach is still in the evaluation phase.PurposeTo print the abdomen of a woman in the late stage of pregnancy and compare the dose distribution measured using thermoluminescence dosimeters (TLDs) in the printed phantom for two different computed tomography (CT) protocols with the corresponding results of Monte Carlo simulations on voxel models of the pregnant woman.Materials and methodsThe physical phantom was produced through multi‐material extrusion printing using different print materials identified in previous studies to simulate homogeneous soft tissues and the mean compositions of maternal and fetal bones. The 3D printed abdomen was combined with a conventionally produced anthropomorphic female phantom to obtain a whole‐body phantom of a pregnant woman. Dose values resulting from two different CT scans acquired at tube voltages of 80 and 120 kV were measured using TLDs positioned in the physical phantom and cross‐validated with the results of Monte Carlo simulations performed for two different voxel models. The first was a voxelized model of the produced phantom itself and the second a realistic digital model of a pregnant woman. Representative CT values of the materials used in the printed phantom were determined from the acquired CT images.ResultsThe CT values of maternal and fetal tissue structures in the phantom are comparable to CT values of real human tissues. The difference between most organ doses measured in the 3D printed phantom and simulated in the voxel models was below 20% and equivalent within the measurement uncertainties. Only the dose to the fetal head was up to 50% higher and not equivalent for the realistic model and the 80 kV‐protocol. As expected, the agreement was better for the voxelized than for the realistic model. For both models a slight energy dependence was observed, with larger deviations for the 80‐kV protocol especially for organs located in the pelvic region.ConclusionIndividualized physical body phantoms, such as that of a pregnant woman, can be produced using 3D printing. The good agreement between measured and simulated doses to the fetus cross‐validates both dosimetric methods. Therefore, this study demonstrates the suitability of 3D printing phantoms for patients not adequately represented by commercially available body phantoms of reference persons.

Implementation of Digital Governance in One-Stop Integrated Licensing Services: A Case Study of the SAMIRINDU-PASTI BEDAS Application in Bandung Regency

This study aims to explain the running of digital governance in one-stop integrated services carried out at the Bandung Regency Investment and One-Stop Integrated Services Office (DPMPTSP) which has been running since the issuance of Regional Regulation Number 15 of 2018 concerning Amendments to Regional Regulation Number 12 of 2016 concerning the Formation and Composition of Regional Apparatus. The research method used in this study is a descriptive research method with a qualitative approach. where the researcher describes the facts about the problem that is the focus and is ringed with accurate interpretation through in-depth interviews. The digital governance model used in this study is the Welchaman Model (2015). The results of this study show that the Bandung Regency Government, through the One-Stop Investment and Integrated Services Office (DPMPTSP), implements an electronic licensing system through the SAMIRINDU - PASTI BEDAS application with the aim of simplifying the licensing process and improving the accessibility of services for the community. This application allows applicants to apply for permits online and print their permits through the application once approved. The digital governance of one-stop integrated services in Bandung Regency has been implemented quite well, but there are several disruptions to the server and a lack of understanding of licensing procedures are obstacles. So that the goal of integrated services, namely fast and precise, has not been achieved optimally.

Business model structuration in Industry 4.0: an analysis of the value-based strategies of smart service providers in Brazil

PurposeThis study examines the use of a dynamic value-based approach to analyze the business model structuration of smart service providers in Brazil, mapping their value creation, configuration and appropriation strategies, and determining how well-defined their current business models are.Design/methodology/approachThis is a qualitative study based on semi-structured interviews with entrepreneurs (or CEOs and directors of technology) of seven business ventures in three different phases of business model structuration: (1) academic: companies or innovation and research centers linked to universities; (2) startups: technology-based companies originating from the technological needs of clients, be they new branches of the traditional business of incumbents or new entrants and (3) autonomous service providers whose offerings are related to master’s or doctoral projects.FindingsWe propose a typology of business model structuration with four stages. At first (individual or initial business model), albeit with high skilling of owners, only manual or adaptation services are offered. In the second stage (platform business model), although services offered are oriented toward the entire process automatization of the client (Factory integrated), technologies are restricted to the client company (or even one department) and these clients' needs are mainly data processing and connectivity. In the third stage (scaling digital business model), although the services offered are oriented toward greater digitalization through an entire array of field devices connected to the internet (IoT) and organized in a more formalized structure, the business model is still being constructed, companies in this stage are mainly startups. In the fourth stage (innovation ecosystem business model), the entire manufacturing process is digitized, with integration and network connectivity, both between service providers and the extended supply chain of their clients, and new technologies are customized and developed through the interaction of a whole innovation ecosystem.Research limitations/implicationsMapping value-based strategies aids in understanding business model structuration in Industry 4.0. Future research should focus on parameterizing the dimensions founded of each value strategy.Originality/valueThis study advances the comprehension of the business model in |Industry 4.0 by providing a value-based strategy perspective of business model structuration. Practically, by focusing on smart service providers, it contributes to a greater understanding of smart service providers in Brazil and their strategic challenges.

Enhancing Urban Sustainability: Developing an Open-Source AI Framework for Smart Cities

To address the growing need for advanced tools that enable urban policymakers to conduct comprehensive cost-benefit analyses of traffic management changes, the Urbanite H2020 project has developed innovative artificial intelligence methods. Among them is a robust decision support system that assists policymakers in evaluating and selecting optimal urban mobility planning modifications by combining objective and subjective criteria. Utilising open-source microscopic traffic simulation tools, accurate digital models (or “digital twins”) of four pilot cities—Bilbao, Amsterdam, Helsinki, and Messina—were created, each addressing unique mobility challenges. These challenges include reducing private vehicle access in Bilbao’s city center, analysing the impact of increased bicycle traffic and population growth in Amsterdam, constructing a mobility-enhancing tunnel in Helsinki, and improving public transport connectivity in Messina. The research introduces five key innovations: the application of a consistent open-source simulation platform across diverse urban environments, addressing integration and consistency challenges; the pioneering use of Dexi for advanced decision support in smart cities; the implementation of advanced visualisations; and the integration of the machine learning tool, Orange, with a user-friendly GUI interface. These innovations collectively make complex data analysis accessible to non-technical users. By applying multi-label machine learning techniques, the decision-making process is accelerated by three orders of magnitude, significantly enhancing urban planning efficiency. The Urbanite project’s findings offer valuable insights into both anticipated and unexpected outcomes of mobility interventions, presenting a scalable, open-source AI-based framework for urban decision-makers worldwide.

A New Framework for Generating Indoor 3D Digital Models from Point Clouds

Three-dimensional indoor models have wide applications in fields such as indoor navigation, civil engineering, virtual reality, and so on. With the development of LiDAR technology, automatic reconstruction of indoor models from point clouds has gained significant attention. We propose a new framework for generating indoor 3D digital models from point clouds. The proposed method first generates a room instance map of an indoor scene. Walls are detected and projected onto a horizontal plane to form line segments. These segments are extended, intersected, and, by solving an integer programming problem, line segments are selected to create room polygons. The polygons are converted into a raster image, and image connectivity detection is used to generate a room instance map. Then the roofs of the point cloud are extracted and used to perform an overlap analysis with the generated room instance map to segment the entire roof point cloud, obtaining the roof for each room. Room boundaries are defined by extracting and regularizing the roof point cloud boundaries. Finally, by detecting doors and windows in the scene in two steps, we generate the floor plans and 3D models separately. Experiments with the Giblayout dataset show that our method is robust to clutter and furniture point clouds, achieving high-accuracy models that match real scenes. The mean precision and recall for the floorplans are both 0.93, and the Point–Surface Distance (PSD) and standard deviation of the PSD for the 3D models are 0.044 m and 0.066 m, respectively.

Development and validation of a digital biopsy model to predict microvascular invasion in hepatocellular carcinoma.

Microvascular invasion is a major histopathological risk factor of postoperative recurrence in patients with hepatocellular carcinoma. This study aimed to develop and validate a digital biopsy model using imaging features to predict microvascular invasion before hepatectomy. A total of 217 consecutive patients who underwent hepatectomy for resectable hepatocellular carcinoma were enrolled at two tertiary-care reference centers. An imaging-based digital biopsy model was developed and internally validated using logistic regression analysis with adjustments for age, sex, etiology of disease, size and number of lesions. Three imaging features, i.e., non-smoothness of lesion margin (OR = 16.40), ill-defined pseudocapsula (OR = 4.93), and persistence of intratumoral internal artery (OR = 10.50), were independently associated with microvascular invasion and incorporated into a prediction model. A scoring system with 0 - 3 points was established for the prediction model. Internal validation confirmed an excellent calibration of the model. A cutoff of 2 points indicates a high risk of microvascular invasion (area under the curve 0.87). The overall survival and recurrence-free survival stratified by the risk model was significantly shorter in patients with high risk features of microvascular invasion compared to those patients with low risk of microvascular invasion (overall survival: median 35 vs. 75 months, P = 0.027; recurrence-free survival: median 17 vs. 38 months, P < 0.001)). A preoperative assessment of microvascular invasion by digital biopsy is reliable, easily applicable, and might facilitate personalized treatment strategies.

National Cultures in Times of Digital Transformation of the Travel Industry: Qualitative Exploration of Effects on Digital Business Models

Globalization and digitalization raise questions about the contemporary role of national culture. Investigating digital business models (BMs) in the travel industry, this study clarifies the effects of national cultures on them. Thirty-nine impactful aspects of national cultures— 25 institutional and 14 ideational—are identified based on qualitative research. These aspects are derived from various cross-cultural frameworks and include three newly suggested cultural dimensions. The proposed model clarifies the mechanism of the impact. The study restates the significance of national cultures in the digital era and places emphasis on the importance of both institutional and ideational sides of national cultures. The study would be helpful to practitioners in deciding on suitable places for a business opening and localizing BMs across international borders.

MolPlay: Democratizing Interactive Molecular Simulations and Analyses with a Portable, Turnkey Platform.

Computer-based tools for visualizing and manipulating molecular structures in real-time hold immense potential for accelerating research and improving education, but are only used to a limited extent. This paper explores the possibilities of these powerful techniques and presents a classification of common interactive modeling tasks, such as assembly, deformation, sampling of rare events, along with relevant use cases, especially for the study of membranes and membrane proteins. I introduce MolPlay─a platform that provides a ready-to-use software environment with a curated set of hands-on examples to democratize access to interactive molecular simulations and analyses (IMSA). These research tools allow researchers to visualize, manipulate, and study digital models of molecules in real-time and can be started directly from a small, portable storage device. The portable, self-contained nature of MolPlay enables versatile deployment scenarios ranging from outreach to teaching in computer laboratories to facilitating the distribution of research software. Initial tests at an international workshop have shown that MolPlay appeals to different target groups and lowers the access barriers to IMSA. By consolidating more than a decade of expertise into one accessible platform, MolPlay represents a significant step toward broader adoption of these underutilized but powerful computational techniques in education and research.

Simulating vortex generation to investigate the propulsive and braking mechanisms of breaststroke kick using computational fluid dynamics on a breaststroke swimmer

Swimmers primarily increase their forward velocity through lower limb motion in breaststroke, making the breaststroke kick crucial for optimizing race times. Recent studies have highlighted the generation of vortices around the swimmer’s entire body to propel forward during swimming. However, the investigation of vortex generation during breaststroke kicks remains unexplored. This study aimed to reveal the propulsive and braking mechanisms of breaststroke kicks by simulating vortex generation using computational fluid dynamics (CFD). Kinematic data during the breaststroke kick and a three-dimensional digital model were collected to conduct CFD for a male breaststroke swimmer. Vortex generation was determined during one breaststroke kick from the CFD results. Vortices, which potentially induce a decrease in forward velocity, were generated by the swimmer’s lower legs and feet during the recovery phase. The swimmer generated vortices on the dorsal side of the feet and the posterior and lateral sides of the lower legs to increase the forward velocity during the out-sweep phase. The swimmer generated vortices on the lateral sides of the thighs and lower legs and the dorsal and lateral sides of the feet during the in-sweep phase to maintain forward velocity. Moreover, vortices generated from the out-sweep to the in-sweep merged and were shed backward relative to the swimming direction after the in-sweep phase. This study is the first to reveal the propulsive and braking mechanisms of breaststroke kicks by analyzing the vortex generation.

Development of Digital Transformation Maturity Assessment Model for Collaborative Factory Involving Multiple Companies

Recent advancements in digital transformation (DX) in the industrial sector have spotlighted digital collaborative factories, which emphasize relationships with partners, particularly in the manufacturing sector. However, existing DX maturity assessment models primarily focus on evaluating individual companies, lacking consideration of partnerships and thereby failing to reflect the complexities of collaborative systems. To address this limitation, this study aims to develop a DX maturity assessment model tailored to digital collaborative factories while accounting for collaborative relationships. Initially, 25 existing DX maturity assessment models were reviewed, and the evaluation elements related to collaboration were extracted from each. Accordingly, the maturity assessment model was created with 15 evaluation factors, including organizational aspects, process management, quality control, and logistics operations. Finally, to verify the applicability of the model, the DX maturity levels of a lead company—a forklift-manufacturing company—and its partner—an automotive component manufacturer—within the same value chain were assessed, and the model’s suitability was evaluated. The results indicate that the lead company needed to improve on the intelligence, connectivity, and automation aspects, while its partner needs to streamline production process operations and technological connectivity. This approach enables manufacturers to obtain more reliable information in resolving issues arising from collaboration with partners, as well as in establishing future strategies. The findings suggest that strengthening collaboration systems among partners and advancing DX based on digital collaboration will raise competitiveness within the manufacturing sector.

On-Demand and Marketplace Platforms: Gig Care Work Conditions on Two Digital Labour Platform Care Models

With worker shortages and the need for care workers projected to grow, personal care work through digital labour platforms (DLPs) is important to understand. This paper considers DLPs used by gig care workers providing personal care in Ontario, Canada. We recruited 20 women gig care workers for interviews. We examined socio-technical processes such as signing up on platforms, creating profiles, and searching for jobs. We draw on Institutional Ethnography to study the actual work on the following two DLP models: marketplace and on-demand. Marcusean theory provides a lens for the critical examination of DLP care work. We found job inequity between DLPs operating in the homecare sector, compared to DPs used in institutional settings. Jobs had disparate quality between the two platform types. Workers on both DLP types remained vulnerable to fluctuations in demand and had limited social security protections, and both models of DLP institutionalised precarity.

Matters of assuring functional dependability compliance of digital manufacturing

Aim. To propose a methodological approach to ensuring the functional dependability of industrial facilities using SMART documents in the context of import-independent digital processes. Methods. The evolving applicability of the dependability theory and information systems design has defined the methodological provisions for algorithmising the application of SMART standards for minimising functional faults and failures of industrial processes. Digital models of production lines were examined as tools for machine-recognisable representation of standards. The proposed form of regulatory documents is intended to enable the transition from machine-readable data to machine-understandable content. Findings. The application of the proposed methods of content systematisation in the context of manufacturing process standardisation shows that the classification of process data based on standardised characteristics of digital information exchange processes is one of the key methodological provisions ensuring unambiguous interpretation of regulatory requirements. Specialised projects often use individual provisions rather than complete regulatory documents. In this case, in order to ensure machine-understandability of the developed content, it is proposed using special identifiers, e.g., «paragraph», «graphic object», «table cell». The deployment of such identification tools will allow creating a class of SMART standards that collect into a single document the provisions regarding the delivery of intended results in situations when the operating equipment is diverse. Publications created using intelligent processing of SMART documents are considered as containers of structured and unstructured data that take into account the conditions of particular projects. The existing dynamics of the demand for advanced industrial products often determines the admissibility of its industrial production by various companies with the parallel use of unique technologies. The conditions of such an organisation impose their limitations on the comparability of various process requirements, therefore, it is proposed to harmonise the presentation of the results of managerial, design, and process engineering solutions using the term «manufacturing system asset». The introduction of relative result estimates as part of the digital format is an efficient mechanism for ensuring management consistency. In this context, the importance of a uniform regulatory framework as the foundation for such assessments is growing. As one of the ways of minimising faults and failures of industrial equipment, it is proposed to create a situation centre with a decision support system based on the regulatory data with harmonised manufacturing system asset requirements. An experience of Industry 4.0 regulation is described in the review of the ISA digital manufacturing series of standards. It was shown that the deployment of SMART standards improves the stability of interaction between information management systems and the functional dependability of production lines. The introduction of provisions regulating the use of algorithms for the development, editing, and examination of draft regulatory documents into the content machine-understandability facilities is an important factor in ensuring the functional dependability of products. Conclusions. The presented approach is focused on the methodology for developing standards that take into account requirements from various subject areas. In the context of ongoing import substitution in manufacturing, the paper examines the feasibility of minimizing digital process faults and failures caused by the use of regulatory frameworks that are not equivalent to the provisions of international documents and take into account the specificity of Russian industrial systems.

Development of a 3D-printed phantom for total skin electron therapy dose assessment.

Total skin electron therapy (TSET) is a complex radiotherapy technique, posing challenges in commissioning and quality assurance (QA), especially due to significant variability in patient body shapes. Previous studies have correlated dose with factors such as obesity index, height, and gender. However, current treatment planning systems cannot simulate TSET plans, necessitating heavy reliance on QA methods using standardized anthropomorphic phantoms and in-vivo dosimetry. Given the relatively few studies on rotational techniques, comprehensive data in commissioning could streamline the process. Developing a full-body phantom would enable a more thorough TSET commissioning process, including testing for position-specific dose distributions and comprehensive measurements across all body surfaces, unlike the typical torso-only phantoms. This was created using digital modeling software, fabricated using 3D-printing FDM technology, and filled with tissue-equivalent gelatine. The phantom was positioned at an SSD of 340cm and irradiated with a standard rotational TSET plan using the 6E HDTSE mode on a Varian TrueBeam linac at gantry angles of±18° from the horizontal. The dose was measured at over 50 points across the surface using Gafchromic EBT3 film. Dose distributions were generally consistent with existing literature values from in-vivo dosimetry, with several position-specific differences identified, including the hands and scalp compared to conventional positions. Hotspots were observed for the mid-dorsum of the foot and nose, with areas under 80% of the dose identified as the soles of the feet, perineum, vertex of the scalp, top of the shoulder, and palm of the hand. Additionally, analysis using an interpolated dose heatmap found that 90% of the pixel area received a dose within 10% of the prescribed dose, indicating good uniformity with the commissioned technique. With high agreement with the current literature, a 3D-printed phantom proves effective for measuring doses in areas typically unmeasurable in TSET commissioning.

CLASSIFICATION OF DATA CAPTURING AND BUILDING SURVEYING TECHNIQUES IN THE CONTEXT OF SELECTING THE OPTIMAL METHOD OF CREATING 3D BIM AND HBIM MODELS OF EXISTING BUILDINGS

When creating a BIM information model of an existing building, a number of surveying techniques may be applied. The choice of particular technique depends largely on the budget of the investor commissioning the task and, on the specialist, commissioned to do it. Methods of conducting very accurate architectural survey and creating a digital 3D model are still fairly expensive due to the need of using specialist equipment. On the other hand, more common and affordable methods often lack the accuracy in the final model. This paper attempts to present a new classification of data capturing and building surveying techniques for creating 3D BIM models of existing buildings. The authors discuss optimal ways of applying particular methods and combining them so as to reduce the overall cost of the commissioned task and to achieve high accuracy of the final model at the same time. The analysis presented in this paper allows to introduce some order in the methods of creating BIM models of existing buildings by offering a new classification adjusted to standards currently used in architectural surveying.

Geodatabase, metric reconstruction and a GIS platform of historical-archaeological sites in Aquino

This paper presents the contents of a geodatabase developed from the outcomes of survey operations carried out, in several stages since 2015, within the archaeological context of the Roman city of Aquinum, in southern Lazio. The proposed geodatabase integrates traditional topographic surveying techniques with total station, GPS and GNSS geodetic receivers with photogrammetric surveys and terrestrial laser-scanner (TLS) measurements, including the realization of HBIM (Historical Building Information Modeling) models, to investigate some specific historical-archaeological evidence useful to understand the Roman and medieval urban structure of the city. The processing and management of the metric and information datasets were entrusted to a GIS platform, implemented in the opensource Quantum-GIS software, to optimize the flowchart of the acquisition/processing process and to realize an intra-site Web-GIS useful for the visualization and dissemination of the results. The methodological-operational approach applied in the research activities highlights the fundamental contribution that the technological innovations of geomatics can provide for the construction of elaborate knowledge concerning cultural heritage, also becoming the base for the elaboration of more complex and detailed analyses. In this case, for example, the HBIM digital model of the Church of Santa Maria of Libera was also used for an in-depth study in the field of structural engineering, as input to model the masonry vaults of the aisles of the church and assess their structural safety through the analysis methodology denominated "Thrust Network Analysis (TNA)." In addition, the high-precision 3D models developed from detailed photogrammetric measurements of the archaeological fragments and human remains found in the excavation areas made it possible to create interesting "visual digital products" that are immediately understandable even for non-experts, and thus particularly useful for wide-ranging knowledge dissemination.

Deep learning-based minute-scale digital prediction model for temperature induced deflection of a multi-tower double-layer steel truss bridge

Bridge deflection serves as a vital and intuitive index for the evaluation of bridge safety. Temperature load has the greatest influence on the bridge deformation and studies on the temperature-induced deformation prediction of long-span bridge are in limited numbers. A digital prediction model based on deep learning in minute scale is established to study the bridge deflection caused by temperature. The wavelet transform (WT) is adopted to filter the high-frequency signals of the original deflection caused by the related load factors. Three different networks, long short-term memory (LSTM), bidirectional LSTM (Bi-LSTM), and Transformer variant, are studied and compared in the prediction process. Two different learning strategies considering different input data are also considered to optimize the prediction performance. The proposed prediction model is applied to the temperature induced deflection prediction of a multi-tower double-layer steel truss bridge. The results show that strategy A, which employs temperature time series data as input, is less effective than strategy B. Incorporating both temperature and deflection data as inputs is essential for predicting temperature-induced deflections. Moreover, the Transformer-variant network generally exhibits superior prediction performance compared to the LSTM and Bi-LSTM. The self-attention mechanism of the Transformer allows it to focus on key historical temperature points, thereby enhancing prediction accuracy.

A randomized trial testing digital medicine support models for mild-to-moderate alcohol use disorder

This paper reports the results of a hybrid effectiveness-implementation randomized trial that systematically varied levels of human oversight required to support the implementation of a digital medicine intervention for persons with mild-to-moderate alcohol use disorder (AUD). Participants were randomly assigned to three groups representing possible digital health support models within a health system: self-monitored use (SM; n = 185), peer-supported use (PS; n = 186), or a clinically integrated model CI; (n = 187). Across all three groups, the percentage of self-reported heavy drinking days dropped from 38.4% at baseline (95% CI [35.8%, 41%]) to 22.5% (19.5%, 25.5%) at 12 months. The clinically integrated group showed significant improvements in mental health and quality of life compared to the self-monitoring group (p = 0.011). However, higher attrition rates in the clinically integrated group warrant consideration in interpreting this result. Results suggest that making a self-guided digital intervention available to patients may be a viable option for health systems looking to promote alcohol risk reduction. This study was prospectively registered at clinicaltrials.gov on 7/03/2019 (NCT04011644).

Building Digital Twin Data Model Based on Public Data

This study aims to propose a method for constructing basic digital twin data in South Korea by adhering to international standards and by utilizing publicly available data. Specifically, the study focuses on designing and proposing a digital twin data model for buildings, as building-related digital twin data are the most applicable among the basic digital twin data. To achieve this, the first section provides essential background information, introduces concepts and requirements related to basic digital twin data, and offers a brief overview of City Geography Markup Language (CityGML). The second section explains the methodology and the data used in this study. The third section presents the main findings: the selection of public data (building data) for constructing basic digital twin data, the mapping process using CityGML, and the creation of Unified Modeling Language (UML) diagrams. The fourth section discusses these findings. Finally, the conclusion and recommendations for future research are provided. This approach enhances the accuracy of building-related digital twin data and supports the use of digital twin services in both public and private sectors by enabling various spatial analyses.

Effect of various active reminders via mobile phone on cooperation of orthodontic teenage patients regarding oral hygiene and ClassII elastics use : Athree-month follow-up prospective cohort study.

The purpose of this prospective cohort study was to assess the impact of reminders via mobile phone, such as text messages or video/multimedia images, on orthodontic patients' cooperation with regard to oral hygiene and the use of ClassII intermaxillary elastics. The study included 124 orthodontic patients aged 12-20years (mean age14.06 ± 2.0 years, 63females and 61males). The patients were divided into two groups: group1 (n = 56) was evaluated for oral hygiene, while group2 (n = 68) was evaluated for the use of ClassII intermaxillary elastics. Each main group was divided into three subgroups: text message group, video message group, and control group. Specific messages were sent to the participants in the study groups twice aweek for 12weeks. Data were collected at the beginning of the study (T0), after 6weeks (T1), and 12weeks (T2) and compared to determine the impact of the reminders. Oral hygiene was evaluated using plaque and gingival index scores, and the use of ClassII elastics was evaluated using digital model measurements. Between-subject comparisons were performed using Kruskal-Wallis or one-way analysis of variance (ANOVA). For within-subject comparisons (T0-T1, T1-T2, and T0-T2 time intervals), one-way repeated measures ANOVA or Friedman test was performed. There was no significant difference between the control group (1.49 ± 0.22) and the message groups (video: 1.58 ± 0.34 and text: 1.51 ± 0.28) in terms of plaque index scores and gingival index (control: 1.56 ± 0.26, text: 1.51 ± 0.36, video: 1.52 ± 0.26) scores. However, in the intragroup comparison, it was observed that both plaque index scores and gingival index scores at T0, T1, and T2 increased for both the study and control groups. While there was no difference between the subgroups in overjet measurement at T0 (control: 3.46 ± 1.20, video: 3.34 ± 1.20, text: 2.73 ± 1.03; p = 0.51), there was asignificant difference at T2 (control: 2.62 ± 0.85, video: 2.32 ± 1.41, text: 1.48 ± 0.72, p < 0.01). Mobile active reminders had no effect on improving oral hygiene. Despite repeated reminders, hygiene worsened over time. The use of ClassII elastics seemed to have increased as aresult of the mobile reminders.

Inertial Motion Capture-Driven Digital Human for Ergonomic Validation: A Case Study of Core Drilling.

In the evolving realm of ergonomics, there is a growing demand for enhanced comfortability, visibility, and accessibility in the operation of engineering machinery. This study introduces an innovative approach to assess the ergonomics of a driller's cabin by utilizing a digital human. Through the utilization of inertial motion capture sensors, the method enables the operation of a virtual driller animated by real human movements, thereby producing more precise and realistic human-machine interaction data. Additionally, this study develops a simplified model for the human upper limbs, facilitating the calculation of joint forces and torques. An ergonomic analysis platform, encompassing a virtual driller's cabin and a digital human model, is constructed using Unity 3D. This platform enables the quantitative evaluation of comfortability, visibility, and accessibility. Its versatility extends beyond the current scope, offering substantial support for product development and enhancement.