3D Software Research Articles

Time Efficient & Cost Effective Online teaching tool with iConcepts in Orthodontics for DDS students @ UoM

Background Traditional teaching methods in Orthodontics include plaster models and photos which have been used for decades, however due to the nature of being static still images its difficult for 3-Dimensional (3D) changes in Orthodontics teaching, which has posed immense challenges as the learner is unable to clear concepts on the different planes that affect the final tooth positions not to mention the protracted treatment time ranges from 12 months (simple cases) to 36 months (complex cases). In 2024 with variety of platforms such as videos, 3D animations, interactive changes in face and teeth can be added to teaching tools for Orthodontics. Furthermore, orthodontic movements can pose difficulty in understanding the changes particularly in growing children adding to the 4th dimension. At UQ (Naser-ud-Din, 2015) and internationally (Bridges, 2015) provided experience with creating online teaching modules highlighting its strengths of flexibility, ease of access on demand and global presence. UQ developed SBLi -Scenario Based Learning interactive for Postgraduate Orthodontic students who found it highly engaging, with self-reflective and self-assessment elements useful. (Khoo et al., 2023; Naser-ud-Din, 2016). Generally simulations can be expensive to create (Kröger et al., 2017) and it’s essential to explore cost effective simulation teaching tools with industry partners for authentic learning experience. Aims There is a gap in the dental education sector, particularly with emerging CADCAM (Computer Assisted Design and Computer Assisted Manufacture), which can be used to enhance the learning of core concepts in biomechanics with the aid of 3D simulated online learning. This is reflected particularly for the university students in undergraduate courses who need to feel confident and clinically ready on graduation as Dentists. Thus, greater expectations to be aligned with current technological processes in dentistry. Over the past 5 years, in particular, there has been exponential improvements by the industry providing 3D simulations for treatment planning and patient communication, commonly referred to as the GPS for smile transformations. The aim of this presentation is to highlight the time efficiency and cost effectiveness of the learning tool in sync with contemporary demands in Orthodontics to provide authentic learning platform that prepares the clinician for real patients. Material & Methods Currently the CAD CAM technology provide 3D simulations as open access to general public and doctors portal which can be utilized for teaching core concepts related to biomechanics foundations for student learning, engagement and self-assessment. This project envisages to create a novel forum encompassing education revolution as massive changes in delivery will occur with speed and efficiency internationally with onlinelearning demands. Hence, robust online presence with an interactive textbook such as iConcepts in Orthodontics under the banner of UoM to assist students in Doctor of Dental Surgery at MDS shall pave the way to learning needs for the future. Results The purpose of iConcepts a digital interactive online textbook is to create lifelong learning opportunities in safe space for visual, auditory and kinesthetic with quizzes for interactive learning of concepts without pressure in class learning and feeling judged by peers. Interactive 3D Orthodontic learning directly translates into clinical applications for various orthodontic cases. In the past decade CAD CAM has become clinically relevant particularly with Clear Aligner Therapy adding to higher precision and patient satisfaction. Moreover, it is imperative to have Long Term Retention (LTR) (Irvine, 2020) of learning new tasks. It is essential that students in dentistry are aware of the digital workflows and have clinical preparedness on graduation as it’s the future and certainly here to stay. Both qualitative and quantitative data on student experience shall be collected and analysed to seek out the best practices and processes for instruction of delivery in Orthodontics for DDS cohort in particular and lifelong learning for all ages in general encompassing time efficiency and cost effectiveness. Conclusion The current iConcepts is developed by the author with Apple Education and prototype is being assessed with MSc Data Science cohort at UoM. Furthermore, it is refined by Master of Science Software Engineering students at UoM. Future Recommendations Novel teaching tools shall be marketed to developing universities internationally assisting the dissemination of information a flagship for UoM and revenue generation for department of Education at UoM. In future there will be more and more demand towards interactive concepts clarification (Poblete et al., 2020) and self-assessments hence iConcepts provides that ideal platform. Such technologies will become more prevalent in the future particularly with AI and translated into different languages/ sectors of education. Various faculties that showcase start to finish particularly lengthy/complex outcomes can benefit with timelapse videos and 3D CADCAM for clarity and comprehension for the entire process such as patient journey throughout treatment in Orthodontics.

Learning program enhances rehabilitation professionals’ perceived ease of using 3d printing: a pilot randomized controlled trial

The pilot study evaluated whether a learning program enhances a positive perception of 3D printing technology in rehabilitation professionals. Physical therapists, occupational therapists and speech-language-hearing therapists were recruited from a rehabilitation department in a middle-sized hospital. Participants were randomized to the control group (n = 13) or the intervention group (n = 14). An eight-week learning program consisted of a lecture on using a 3D printer and related software, a group discussion to integrate 3D printing into their clinical practices, and the implementation in their workplace. Outcome measures included the perception of 3D printing technology assessed by the Japanese version of the modified Technology Acceptance Model questionnaire for 3D printing technology (TAM-J). Assessment time points were pre-and post-intervention. As a result, all participants in the intervention group became capable of producing 3D-printed customized assistive devices. In the within-group analyses, the intervention group showed significant improvements in the TAM-J perception ease of use score (p = 0.012) with a large effect size (r = 0.75). Between-group analyses showed that the intervention group gained an additional improvement in the TAM-J perception ease of use score (p = 0.027) with a moderate effect size (r = 0. 43), indicating a significant improvement in the perceived ease of use of 3D printing technology in the intervention group. These observations suggest the 3D printing learning program could provide rehabilitation professionals with a positive perception of the technical aspect of 3D printing in their workplace.

A Novel Machine Learning Model and a Web Portal for Predicting the Human Skin Sensitization Effects of Chemical Agents

Skin sensitization is a significant concern for chemical safety assessments. Traditional animal assays often fail to predict human responses accurately, and ethical constraints limit the collection of human data, necessitating a need for reliable in silico models of skin sensitization prediction. This study introduces HuSSPred, an in silico tool based on the Human Predictive Patch Test (HPPT). HuSSPred aims to enhance the reliability of predicting human skin sensitization effects for chemical agents to support their regulatory assessment. We have curated an extensive HPPT database and performed chemical space analysis and grouping. Binary and multiclass QSAR models were developed with Bayesian hyperparameter optimization. Model performance was evaluated via five-fold cross-validation. We performed model validation with reference data from the Defined Approaches for Skin Sensitization (DASS) app. HuSSPred models demonstrated strong predictive performance with CCR ranging from 55 to 88%, sensitivity between 48 and 89%, and specificity between 37 and 92%. The positive predictive value (PPV) ranged from 84 to 97%, versus negative predictive value (NPV) from 22 to 65%, and coverage was between 75 and 93%. Our models exhibited comparable or improved performance compared to existing tools, and the external validation showed the high accuracy and sensitivity of the developed models. HuSSPred provides a reliable, open-access, and ethical alternative to traditional testing for skin sensitization. Its high accuracy and reasonable coverage make it a valuable resource for regulatory assessments, aligning with the 3Rs principles. The publicly accessible HuSSPred web tool offers a user-friendly interface for predicting skin sensitization based on chemical structure.

The metaverse-industrial complex

ABSTRACT This paper explores the role that Nvidia is playing in shaping the Metaverse for industrial applications in simulation and automation. As the world's largest manufacturer of Graphics Processing Units for computationally intensive tasks and one of the largest corporations by market capitalization, Nvidia has remained relatively overlooked within critical discussions of ‘Big Tech', the Metaverse, and Artificial Intelligence. This paper draws on news media reports and publicly accessible Nvidia publications such as developer documentation and press releases to understand the role of Nvidia in shaping the Metaverse for industrial enterprises. It conceptualises the ‘Metaverse-Industrial Complex' to theorise the processes of market capture, territorialization, and platform expansionism occurring within the convergence of the Metaverse and Artificial Intelligence that is reconfiguring the governance of public and private assets and infrastructure. Through an examination of Nvidia's ‘Omniverse' platform and network of industrial partnerships, the paper examines the Metaverse-Industrial Complex as an assemblage of developer tools, platforms, data standards, and industry partnerships that converge machine learning and 3D graphics into photo-realistic ‘digital twin’ simulations of physical objects and environments.

Sculpture Training Before the Development of Digital Sculpture and Artificial Intelligence (AI): A Comparison of Some Sculpture Undergraduate Programs in Vietnam and the USA

This article analyzes the impact of digital technology and AI on traditional sculpture, emphasizing the need to update Sculpture training programs in Fine Arts Universities in Vietnam. Based on survey data on the awareness of experts about the influence of AI in the field of sculpture and on the results of comparing the Sculpture training programs of domestic and foreign training schools in the Sculpture industry. The author has outlined training objectives, developed output standards, and created a knowledge system to equip learners with the skills, knowledge, and attitudes needed for modern job roles.

From Waste to Protein: Optimizing Rice Husk Utilization for Sustainable Single Cell Protein Production

The increasing global demand for protein has prompted a search for sustainable and cost-effective alternatives to traditional animal and dairy sources. Single-cell protein (SCP) produced from microorganism’s offers a promising solution due to its high protein content and rapid growth rates. This study addresses the challenge of utilizing rice husk, an abundant yet underutilized agricultural waste in Nigeria, as a substrate for SCP production. Through optimization of the production of SCP using Bacillus sp. AT-b3 and Bacillus sp. CMF 12 as model organisms. Molecular identification through 16S rRNA sequencing confirmed Bacillus sp. AT-b3 and Bacillus sp. CMF 12 as the most potent isolates for SCP production. Optimization studies were conducted using the One-Factor-at-a-Time (OFAT) method to determine the ideal fermentation conditions. The results showed that the optimal temperature for SCP production was 40 °C, with Bacillus sp. AT-b3 demonstrating superior production efficiency. pH optimization revealed that neutral pH (pH 7) was ideal for maximizing SCP production, with Bacillus spp. AT-b3 outperforming Bacillus sp. CMF 12 at this pH. Substrate concentration studies indicated that 2.0% was optimal for SCP production, and incubation time optimization indicated 48 hours as the optimal period for maximum yield. Amino acid profiling of the SCP produced showed significant variations between the two isolates. Bacillus sp. CMF 12 was richer in essential amino acids like Arginine and Methionine, while Bacillus sp. AT-b3 had a higher Glycine content at (p<0.05). The findings of this study suggest that both strains have potential applications in nutritional supplements, with Bacillus sp. AT-b3 being particularly suited for industrial-scale SCP production. This study concludes that Bacillus sp. AT-b3 is an efficient SCP producer under optimal conditions of neutral pH, moderate temperature, and appropriate substrate concentration. Further research is recommended to explore pilot-scale production, alternative substrates, and comprehensive safety assessments.

Condensate Banking Analysis Optimizes Reservoir Development in Permian Basin

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper URTeC 4044947, “Numerical Analysis of Condensate Banking and Development Optimization in the Deep Formation of the Permian Basin,” by Jichao Han, SPE, Sunil Lakshminarayanan, and Jiasen Tan, SPE, Oxy, et al. The paper has not been peer reviewed. _ In the context of unconventional reservoir development, the issue of condensate banking—a factor contributing to reduced productivity in gas condensate reservoirs when the reservoir pressure falls below the dewpoint pressure—poses a constant concern. Before implementation of any mitigation strategies, it is prudent to assess the potential of condensate banking in the future, based on the limited early production data. A specialized workflow was devised for a deep formation in the Permian Basin. This workflow aims to quantify the severity of condensate banking and subsequently optimize reservoir development strategies. Introduction Well A represents a single appraisal well situated within deep formations of the Permian Basin. With only 5 months of production data available, pressure/volume/temperature analysis and modeling identified it as a gas condensate reservoir, with the dewpoint very close to the critical point. This prompts two critical business inquiries: Are there any concerns regarding condensate banking for this well? And what are the optimal drawdown strategies tailored to this specific format surrounding the appraisal well? Model Setup and Calibration Modeling Workflow. This study uses the comprehensive simulation workflow derived from Hydraulic Fracturing Test Site 2, which can effectively handle integrated models to provide valuable insight for condensate banking analysis and reservoir development optimization (Fig. 1). Hydraulic fracture and reservoir simulations were conducted using GOHFER 3D and Navigator software, respectively. The integration of fracture and reservoir models poses a significant challenge in accurately transferring fracture geometry and conductivity information from fracture simulators to reservoir simulators. To address this challenge, an in‑house preprocessor was developed, designed to project results from the fracture simulator into the reservoir simulator seamlessly, ensuring the fidelity of complex fracture geometries. This preprocessor enables the extension or contraction of fracture geometries in proportion to reduce uncertainties imposed by production data. Additionally, fracture conductivity is determined through regional correlations among proppant concentration, net closure stress, and fracture conductivity. Model Introduction. The geological model has been simplified to enhance modeling efficiency while still meeting the project requirements. The 3D geological model adopts a layer-cake structure with a flat geostructure. To ensure accuracy, the well trajectory is adjusted to align with the desired formation. The reservoir model measures 4,000×10,000×330 ft, with a grid resolution of 200×25×10 ft. Fracture geometry is imported from the fracture simulator, while fracture conductivity is primarily determined based on proppant concentration data exported from the fracture simulator. Fracture height remains unaltered in the reservoir simulator, reflecting available geochemical measurements. A compositional simulation approach is adopted instead of a black-oil model. To improve the accuracy of pressure drop and condensate dropout predictions, the local grid refinement (LGR) approach is selected, resulting in denser grids. This approach proves superior to the dual-porosity, dual-permeability (DPDP) method.

Three-dimensional evaluation of stem placement accuracy with the conventional guide in reverse shoulder arthroplasty and its relevance to clinical outcomes

BackgroundPlacement of retroversion stem (RS) is important in reverse shoulder arthroplasty (RSA). A conventional guide, based on the forearm, has been used for stem placement; however, only a few studies have reported the accuracy of stem placement using conventional guides. In this study, a three dimensional (3D) postoperative evaluation software was used to investigate the accuracy of RS placement using a conventional guide and its effect on postoperative outcomes. MethodsThis retrospective study was performed by a single surgeon (a board-certified specialist with more than 15 years' experience in performing RSA) using the Exactech Equinoxe Reverse Shoulder System (Exactech Inc., Gainesville, FL, USA). Forty-nine patients who were followed up for at least 2 years were included. The target RS angle of the humeral component was set to 20°. Postoperative implant placement, including RS, was assessed with a 3D planning software using computed tomography (CT) images obtained postoperatively. Postoperative range of motion and its relationship with clinical outcomes were also evaluated as clinical assessment. Furthermore, a sub-analysis was performed comparing the 0–20° RS group with the other groups. ResultsThe mean postoperative RS was 13.2 ± 11.9° and was placed within 0–20° in 31/49 patients (63.3%). A correlation was observed between postoperative external rotation (ER) and RS (r=0.30, p=0.03). In a further sub-analysis, the Constant–Murley score was significantly higher in the 0–20° RS group (p=0.03). ConclusionPlacement of the RS using a conventional guide varied from the target position. RS correlated with postoperative ER, and RS within 0–20° significantly improved clinical outcomes. These results suggested that accurate placement of the RS may improve clinical outcomes. Therefore, the development of surgical assistive technologies for accurate placement is necessary to ensure accurate stem placement to avoid human error.

Expressive 3D Facial Animation Generation Based on Local-to-Global Latent Diffusion.

3D Facial animations, crucial to augmented and mixed reality digital media, have evolved from mere aesthetic elements to potent storytelling media. Despite considerable progress in facial animation of neutral emotions, existing methods still struggle to capture the authenticity of emotions. This paper introduces a novel approach to capture fine facial expressions and generate facial animations using audio synchronization. Our method consists of two key components: First, the Local-to-global Latent Diffusion Model (LG-LDM) tailored for authentic facial expressions, which can integrate audio, time step, facial expressions, and other conditions towards possible encoding of emotionally rich yet latent features in response to possibly noisy raw audio signals. The core of LG-LDM is our carefully designed Facial Denoiser Model (FDM) for aligning the local-to-global animation feature with audio. Second, we redesign an Emotion-centric Vector Quantized-Variational AutoEncoder framework (EVQ-VAE) to finely decode the subtle differences under different emotions and reconstruct the final 3D facial geometry. Our work significantly contributes to the key challenges of emotionally realistic 3D facial animation for audio synchronization and enhances the immersive experience and emotional depth in augmented and mixed reality applications. We provide a reproducibility kit including our code, dataset, and detailed instructions for running the experiments. This kit is available at https://github.com/wangxuanx/Face-Diffusion-Model.

PM2.5 Induces Developmental Neurotoxicity in Cortical Organoids

There is mounting evidence implicating the potential neurotoxic effects of PM2.5 during brain development, as it has been observed to traverse both the placental barrier and the fetal blood-brain barrier. However, the current utilization of 2D cell culture and animal models falls short in providing an accurate representation of human brain development. Consequently, the precise mechanisms underlying PM2.5-induced developmental neurotoxicity in humans remain obscure. To address this research gap, we constructed three-dimensional (3D) cortical organoids that faithfully recapitulate the initial stages of human cerebral cortex development. Our goal is to investigate the mechanisms of PM2.5-induced neurotoxicity using 3D brain organoids that express cortical layer proteins. Our findings demonstrate that exposure to PM2.5 concentrations of 5 μg/mL and 50 μg/mL induces neuronal apoptosis and disrupts normal neural differentiation, thereby suggesting a detrimental impact on neurodevelopment. Furthermore, transcriptomic analysis revealed PM2.5 exposure induced aberrations in mitochondrial complex I functionality, which is reminiscent of Parkinson's syndrome, potentially mediated by misguided axon guidance and compromised synaptic maintenance. This study is a pioneering assessment of the neurotoxicity of PM2.5 pollution on human brain tissues based on 3D cortical organoids, and the results are of great significance in guiding the formulation of the next air pollution prevention and control policies in China to achieve the sustainable improvement of air quality and to formulate pollution abatement strategies that can maximize the benefits to public health.

Study on the compressive strength and failure mechanism of fiber-reinforced polymer green filling materials

The utilization of industrial solid waste in the preparation of geopolymer filling materials offers benefits such as low carbon emissions and resource conservation showcasing broad application prospects. In this study, geopolymer filling materials are prepared using calcium carbide slag, slag, fly ash, and tailings, with the addition of 12 mm polypropylene fibers to enhance their strength and toughness. Conducting UCS experiments to investigate the effects of different calcium carbide slag content, fiber content, and water-solid ratio on the UCS of the materials; Utilizing SEM-EDS and XRD techniques to analyze the mechanisms of strength formation in filling materials and the mechanisms of fiber toughening and crack resistance at the micro level; Establishing a uniaxial compression test model using discrete element PFC 3D software and combining digital speckle technology to visually analyze the sample's failure process. The research results indicate that the stimulation of slag and fly ash by calcium carbide slag results in a large amount of C-(A)-S-H gel, effectively promoting the bond between aggregate and fiber, with the UCS of the samples gradually increasing with the addition of calcium carbide slag. With the increase in fiber content, the UCS of the samples shows a trend of first increasing and then decreasing, with the optimal fiber content being 6 ‰. The fibers exist in the matrix in the form of anchor rods and a three-dimensional network structure, playing a good reinforcing role and effectively inhibiting the expansion and development of cracks; The crack morphology of the samples in the PFC 3D numerical simulation process is close to the digital speckle failure morphology, and the axial load-displacement curve in the numerical simulation aligns well with the indoor test results. The research results can provide theoretical guidance for the preparation of fiber-reinforced green filling materials using all solid waste.

Bone to implant surface contact as a criterion for immediate implant placement with simultaneous sinus augmentation in the upper molars interradicular bone: A radiological CBCT study

Objectives: The aim of this study is to determine which type of vertical relationship (between molar apices and the sinus floor) is correlated with the most favorable bone to implant contact (BIC). Methods: The CBCT database of the Faculty of Dental Medicine was used for datasets. For each dataset, a prosthetically-driven virtual implant placement was placed in the remaining interradicular bone. Potential BIC was measured using two different implant macrogeometries (straight and tapered). Results: The study included 20 maxillary molars with divergent root anatomy: 90% of the molars had a type II vertical relationship with the sinus floor, while only 10% had type III. Mean pBIC surface for second molars was significantly higher for straight implants compared to tapered implants. However, no significant differences in BIC% means between straight and tapered implants for any of the comparisons was found. Conclusions: Implant macrogeometry was found to have an impact on achieving higher pBIC values in certain situations, such as for second molars and type II relationship with the sinus floor. The study highlights the need for incorporating 3D software analysis in pre-operative surgical planning.

High-throughput Bronchus-on-a-Chip system for modeling the human bronchus

Airway inflammation, a protective response in the human body, can disrupt normal organ function when chronic, as seen in chronic obstructive pulmonary disease (COPD) and asthma. Chronic bronchitis induces goblet cell hyperplasia and metaplasia, obstructing airflow. Traditional animal testing is often replaced by in vitro three-dimensional cultures of human epithelial cells to assess chronic cell responses. However, these cells are cultured horizontally, differing from the tubular structure of the human airway and failing to accurately reproduce airway stenosis. To address this, we developed the Bronchus-on-a-Chip (BoC) system. The BoC uses a novel microfluidic design in a standard laboratory plate, embedding 62 chips in one plate. Human bronchial epithelial cells were cultured against a collagen extracellular matrix for up to 35 days. Characterization included barrier integrity assays, microscopy, and histological examination. Cells successfully cultured in a tubular structure, with the apical side air-lifted. Epithelial cells differentiated into basal, ciliated, and secretory cells, mimicking human bronchial epithelium. Upon exposure to inducers of goblet cell hyperplasia and metaplasia, the BoC system showed mucus hyperproduction, replicating chronic epithelial responses. This BoC system enhances in vitro testing for bronchial inflammation, providing a more human-relevant and high-throughput method.

3D 패션 시뮬레이션을 활용한 섹슈얼리티 기반의 리조트웨어 샘플 개발

According to changing fashion trends, this study organized people’s perception for not only understanding of sexuality but also features of leisure activities in modern society that most people want to express themselves these days. In this study, 2 resort wear was designed and manufactured by using Z-WEAVE, a 3D fashion simulation program. The study recognized advantages of 3D fashion simulation program and actively used it. The study can supplement sexuality in the resort wear genre through analysis of people's perceptions of expressing themselves, and it is expected that the 3D fashion simulation program will be a workflow for fashion product development based on its advancements. As the digital industry environment continues to develop and expand, it is considered necessary to study the production of clothes using various digital technologies in addition to 3D simulation programs.

Sagittal Discrepancies of Intraoperative Results between 2D and 3D Planning in Orthognathic Surgery: A Series of 44 Cases

Pre-surgical planning in orthognathic surgery is a process of vital importance for obtaining satisfactory results for both the clinician and the patient. There are different planning methods, among which 3D software is one of the most important. These allow precise observation of the movements of bone and soft tissue structures, which until recently could not be predicted. Despite its advantages, many specialists continue to plan using the 2D method. The aim of this paper is to present the discrepancies between 2D and 3D preoperative planning and the intraoperative results of 44 patients undergoing bimaxillary orthognathic surgery and, together with this, to expose the variables that possibly influence the occurrence of these differences.

Innovative Design and Fast Iterative Manufacturing of Micro-Turbojet Engines at Low Cost

The turbojet is the foundation of the gas turbine engine, which combines knowledge of fluid dynamics, thermodynamics, heat transfer, mechanical design, manufacturing, and jet propulsion. This paper describes in detail the inspiration source, design process, fluid dynamics analysis, manufacturing steps, ignition test method and test process of small jet engines. 3D modeling software SolidWorks was used for the preliminary modeling and fluid simulation was performed to optimize the design. Part of the model was produced by 3D resin printing technology, and the turbine engine model was driven by compressed air for no-load testing to verify the feasibility and structural stability of the resin model. Subsequently, some parts were printed with metal materials, combined with traditional machining techniques to complete production and assembly, and finally successfully carried out static ignition tests. The micro turbojet engine designed in this paper has successfully achieved static ignition test and demonstrated the feasibility of efficient development with limited resources and low manufacturing cost. This exploration proves the feasibility of rapid iteration technology route. The market prospect and manufacturing cost of micro turbojet are also analyzed.

Model Construction of College Engineering Drawing Teaching System Based on Artificial Intelligence Network Technology

The integration of artificial intelligence (AI) in education, particularly in engineering drawing courses, enhances content richness and engagement, stimulating student enthusiasm and improving teaching quality. This paper examines the design of a multimedia teaching system incorporating virtual reality (VR) for engineering drawing. Key technologies such as graphics processing, 3D modeling, and dynamic databases are researched. Tools like Dreamweaver, Fireworks, SolidWorks, and 3DS MAX are used to create and integrate 3D models into web pages, forming a 3D model library. This library provides a flexible, content-rich, online learning environment that promotes self-study, enhances spatial imagination, and improves the quality of engineering drawing education. Establishing a virtual model library supports multimedia teaching and replaces traditional physical model rooms.

User Preference Maps: Quantifying the Built Environment

The built environment in which we live holds the potential to provide life experiences that allow pedestrians to observe, feel, learn, and grow through their surroundings in everyday urban spaces. If a city offers opportunities for careful observation and exploration according to users’ preferences, it will become more appealing to many people. This study selected Midtown, New York, as the research site and collected a total of seven datasets based on 30 intersections in the area. The data, categorized into three main areas—activity, comfort, and natural elements—were evaluated, visualized, and restructured using a path exploration algorithm to produce a final user-based map. For this, 3D modeling software Rhino version 7, visual programming tool Grasshopper, and Grasshopper verion 2023 plugin programs were used. The final result included 3D route information, quantitative measurement data, and multidimensional visual materials. This approach presents an alternative to traditional route navigation based on uniform criteria and, through data-driven design, is believed to ultimately enhance walkability, activate urban spaces, and contribute to the development of sustainable cities. The scope of related research can further expand as the targets, duration, and methods of data collection continue to evolve and as case studies in various cities increase.

TEKNOLOGI AUGMENTED REALITY SEBAGAI MEDIA BELAJAR BERBASIS ANDROID BAGI SISWA KELAS 4 SD NEGERI 11 SESETAN

Low learning interest among students, especially fourth-grade elementary school students, often becomes an obstacle in achieving optimal learning outcomes. To help make the learning process more effective and efficient, educational media are used as intermediaries between educators and learners that connect, provide information, and deliver messages. With the advancement of technology, the education world faces new challenges in applying technology to learning activities, particularly in the development of educational media. One technology that can support learning is Augmented Reality (AR). The main component of Augmented Reality is a 3D object that appears when a marker is scanned by software or an application. This will make students more interested in learning because of the animated 3D objects. In this research, the researcher developed "Augmented Reality Technology as an Android-Based Learning Media for Fourth-Grade Students at SD Negeri 11 Sesetan" to assist teachers and students in the learning process. With it students will become more interested in the learning process when using this AR-based educational media

Mechanical effect of taper position in abutment hole and screw taper angles on implant system and peri-implant tissue: a finite element analysis

Purpose The study aimed to investigate the mechanical effects of the taper position in the abutment hole and the screw taper angles on the implant system and peri-implant tissue using finite element analysis. Methods Four taper positions (L1, L2, L3, L4) in the abutment hole were established using 3D software and five screw taper angles (30°, 60°, 90°, 120°, 180°) were set. Result Taper position significantly affects the stresses in the implant system. The 30° and 180° angles (L4 position) showed less stress than other angles. Conclusion Elevated taper position and reasonable taper angle are beneficial in reducing the stress in the implant system.