Digital In Situ Data Collection in Earth Observation, Monitoring and Agriculture—Progress towards Digital Agriculture

Digital solutions in agricultural management promote food security and support the sustainable use of resources. As a result, remote sensing (RS) can be seen as an innovation for the fast generation of reliable information for agricultural management. Near real-time processed RS data can be used as a tool for decision making on multiple scales, from subplot to the global level. This high potential is not yet fully applied, due to often limited access to ground truth information, which is crucial for the development of transferable applications and acceptance. In this study we present a digital workflow for the acquisition, processing and dissemination of agroecological information based on proprietary and open-source software tools with state-of-the-art web-mapping technologies. Data is processed in near real-time and thus can be used as ground truth information to enhance quality and performance of RS-based products. Data is disseminated by easy-to-understand visualizations and download functionalities for specific application levels to serve specific user needs. It thus can increase expert knowledge and can be used for decision support at the same time. The fully digital workflow underpins the great potential to facilitate quality enhancement of future RS products in the context of precision agriculture by safeguarding data quality. The generated FAIR (findable, accessible, interoperable, reusable) datasets can be used to strengthen the relationship between scientists, initiatives and stakeholders.

Three-dimensional Quantification of Enamel Preservation in Tooth Preparation for Porcelain Laminate Veneers: A Fully Digital Workflow In Vitro Study

SUMMARY Objective: This in vitro study aimed to evaluate the preservation of enamel after tooth preparation for porcelain laminate veneers (PLVs) at different preparation depths based on a fully digital workflow. Methods and Materials: Sixty extracted human maxillary anterior teeth, including 20 maxillary central incisors (MCIs), 20 maxillary lateral incisors (MLIs), and 20 maxillary canines (MCs) underwent microcomputed tomography (CT) scanning, and were reconstructed as three-dimensional (3D) enamel and dentin models. Subsequently, the three-dimensional (3D) enamel models were imported into Materialise, where each enamel model underwent seven types of virtual preparation for PLVs at preparation depths at 0.1-mm increments from 0.1-0.3-0.5 mm (D1) to 0.7-0.9-1.1 mm (D7). The enamel surface was depicted by merging the virtual preparation and, respective, dentin models. The enamel area and prepared surface were measured to calculate the percentage of enamel (R%). The data were statistically analyzed using one-way analysis of variance (ANOVA) (α=0.05). Results: The group-wise mean (standard deviation) R values for the MCIs were as follows: D1-D3: 100.00 (0) each, and D4-D7: 74.70 (2.45), 51.40 (5.12), 24.40 (3.06), and 0.00 (0), respectively. The group-wise mean R values for the MLIs were 100.00 (0), 73.70 (3.40), 53.50 (3.44), 25.20 (3.79), and 0.90 (0.99) for the D1-D5 groups, respectively; and 0.00 (0) each for the D6-D7 groups. The group-wise mean (standard deviations) R values for the MCs were as follows: D1-D3: 100.00 (0) each, and D4-D7: 99.00 (1.34), 77.10 (3.28), 74.20 (3.61), and 52.20 (4.09), respectively. The one-way ANOVA revealed significant differences between the seven groups in the MCIs, MLIs, and MCs (p<0.05). Conclusions: Our results recommended preparation depths of up to 0.3-0.5-0.7 mm (MCIs), 0.1-0.3-0.5 mm (MLIs), and 0.4-0.6-0.8 mm (MCs) to facilitate complete intraenamel preparation. Moreover, 50% enamel was preserved at preparation depths of 0.5-0.7-0.9 mm (MCIs), 0.3-0.5-0.7 mm (MLIs), and 0.7-0.9-1.1 mm (MCs).

An In-Vitro Evaluation of Articulation Accuracy for Digitally Milled Models vs. Conventional Gypsum Casts

With the advent of a digital workflow in dentistry, the inter-occlusal articulation of digital models is now possible through various means. The Cadent iTero intraoral scanner uses a buccal scan in maximum intercuspation to record the maxillomandibular relationship. This in-vitro study compares the occlusion derived from conventionally articulated stone casts versus that of digitally articulated quadrant milled models. Thirty sets of stone casts poured from full arch polyvinyl siloxane impressions (Group A) and thirty sets of polyurethane quadrant models milled from digital impressions (Group B) were used for this study. The full arch stone casts were hand-articulated and mounted on semi-adjustable articulators, while the digitally derived models were pre-mounted from the milling center based on the data obtained from the buccal scanning procedure. A T-scan sensor was used to obtain a bite registration from each set of models in both groups. The T-scan data derived from groups A and B were compared to that from the master model to evaluate the reproducibility of the occlusion in the two groups. A statistically significant difference of the contact region surface area was found on #11 of the digitally articulated models compared to the master. An analysis of the force distribution also showed a tendency for a heavier distribution on the more anterior #11 tooth for the digitally articulated models. Within the limitations of this study, the use of a digitally articulated quadrant model system may result in a loss of accuracy, in terms of occlusion, the further anteriorly the tooth to be restored is located. Care must be taken to consider the sources of inaccuracies in the digital workflow to minimize them for a more efficient and effective restorative process.

Software Details in Occlusal Splint Creation through 3Shape Design Studio

Introduction: Occlusal splints are usually the first choice in the treatment of bruxism. Splints can also be the only treatment or can be ended with adhesive restoration, orthodontic or prosthetic treatment. Methods: This article demonstrates the steps of a digital workflow through the 3Shape Design system - splint studio. The initial units are virtual models, scanned by Trios Color Scanner (3Shape). Results: The digital protocol includes eight steps that allow precise and detailed creation of the searched object. Each step is described from the perspective of a clinician, prosthetist and orthodontist, not a dental technician. Possible complications and ways to management with them are described. Conclusion: Digital protocol of occlusal splint creation gives many opportunities according to design, thickness and occlusion.

Assembled

<p>Profound innovations in assembly process of construction have been absent since the dawn of 2d planimetric drawing. However with advancements in augmented reality (AR) technology and computational tools, the process of assembly has the potential to significantly change. As architectural firms become more adept with 3d modelling and computational design there is a drive to support that work through the manifestation of the built form. By using methods of computational design, advanced fabrication techniques, and AR in assembly processes, a pure digital methodology is achieved that can seamlessly transfer data from one stage to the next. The digital workflow results in a connection from conceptual design to finished product. Researching methods into the process of assembly with AR is a way of advancing architecture into the future and completing the digital continuum, from conception to on site building.</p>

Assembled

<p>Profound innovations in assembly process of construction have been absent since the dawn of 2d planimetric drawing. However with advancements in augmented reality (AR) technology and computational tools, the process of assembly has the potential to significantly change. As architectural firms become more adept with 3d modelling and computational design there is a drive to support that work through the manifestation of the built form. By using methods of computational design, advanced fabrication techniques, and AR in assembly processes, a pure digital methodology is achieved that can seamlessly transfer data from one stage to the next. The digital workflow results in a connection from conceptual design to finished product. Researching methods into the process of assembly with AR is a way of advancing architecture into the future and completing the digital continuum, from conception to on site building.</p>

Case Studies of Digitalized Locate the Remaining Oil Workflows Powered by Hybrid Data & Physics Methods

Mature fields already account for about 70% of the hydrocarbon liquids produced globally. Since the average recovery factor for oil fields is 30 to 35%, there is substantial quantities of remaining oil at stake. Conventional simulation-based development planning approaches are well established, but their implementation on large, complex mature oil fields remains challenging given their resource, time, and cost intensity. In addition, increased attention towards reduce carbon emissions makes the case for alternative, computationally-light techniques, as part of a global digitalisation drive, leveraging modern analytics and machine learning methods. This work describes a modern digital workflow to identify and quantify by-passed oil targets. The workflow leverages an innovative hybrid physics-guided data-driven, which generates historical phase saturation maps, forecasts future fluid movements and locate infill opportunities. As deliverables, a fully probabilistic production forecast is obtained for each drilling location, as a function of the well type, its geometry, and position in the field. The new workflow can unlock remaining potential of mature fields in a shorter time-frame and generally very cost-effectively compared to the advanced dynamic reservoir modelling and history-match workflows. Over the last 5 years, this workflow has been applied to more than 30 mature oil fields in Europe, Africa, the Middle East, Asia, Australia, and New Zealand. Three case studies’ examples and application environments of applied digital workflow are described in this paper. This study demonstrates that it is now possible to deliver digitalized locating the remaining oil projects, capturing the full uncertainty ranges, including leveraging complex multi-vintage spatial 4D datasets, providing reliable non-simulation physics-compliant data-driven production forecasts within weeks.