Serious Games in Cultural Heritage

Although the widespread use of gaming for leisure purposes has been well documented, the use of games to support cultural heritage purposes, such as historical teaching and learning, or for enhancing museum visits, has been less well considered. The state-of-the-art in serious game technology is identical to that of the state-of-the-art in entertainment games technology. As a result the field of serious heritage games concerns itself with recent advances in computer games, real-time computer graphics, virtual and augmented reality and artificial intelligence. On the other hand, the main strengths of serious gaming applications may be generalised as being in the areas of communication, visual expression of information, collaboration mechanisms, interactivity and entertainment. In this report, we will focus on the state-of-the-art with respect to the theories, methods and technologies used in serious heritage games. We provide an overview of existing literature of relevance to the domain, discuss the strengths and weaknesses of the described methods and point out unsolved problems and challenges. In addition, several case studies illustrating the application of methods and technologies used in cultural heritage are presented

Back Analysis of the Lower San Fernando Dam Slide Using a Multi-block Model

A multi-block sliding system model has been developed to simulate the displacement of sliding geo-masses. This model is a useful tool, especially when displacements are very large and computer codes based on the Finite Element Method cannot be applied. The paper investigates the ability of the model to predict the response of the well-documented Lower San Fernando Dam slide. The predicted movement, and deformation agreed reasonably well with that of the upper part of the slide. Yet, the lower part of the slide slid more that the model prediction. The multi-block model was applied a second time. This 2-slide approach predicts movement, and deformation in very good agreement with that measured. In addition, the time duration of motion is in general agreement with the observed

Exposing knowledge: providing a real-time view of the domain under study for students

With the amount of information that exists online, it is impossible for a student to find relevant information or stay focused on the domain under study. Research showed that search engines have deficiencies that might prevent students from finding relevant information. To this end, this research proposes a technical solution that takes the personal search history of a student into consideration and provides a holistic view of the domain under study. Based on algorithmic approaches to assert semantic similarity, the proposed framework makes use of a user interface to dynamically assist students through aggregated results and wordcloud visualizations. The effectiveness of our approach is finally evaluated through the use of commonly used datasets and compared in line with existing research

Surface Corrosion from Implant–Abutment Couplings with Different Connection Designs Influences Osteoblasts’ Function: A Novel Technique

The improved peri-implant bone response demonstrated when utilizing the platform-switching concept may result from the reduced levels of metal ions released from implant–abutment surfaces to the surrounding tissues. These corrosion products may play a major role in crestal bone remodeling around dental implants. This study evaluated the effect of different implant–abutment couplings (platform-matched vs. platform-switched) on osteoblasts’ function. Titanium alloy and cobalt–chrome alloy abutments were coupled with titanium cylinders, forming either platform-switched or platform-matched groups, and were incubated in human osteoblast cultures utilizing a novel direct-exposure technique. Viability was evaluated over 21 days using Alamar Blue assay. Apoptosis was measured after 24 h using flow cytometry. The expression of genes related to bone resorption was analysed over 21 days using a real-time quantitative polymerase chain reaction assay. Cell viability was reduced from day 4 to day 21 (p < 0.05), with higher rates of early apoptosis (p < 0.05) compared to the controls. Apoptosis was higher in the platform-matched groups (p < 0.05). The tested genes’ expression was up-regulated after 1 and 3 days of exposure to implant–abutment couplings (p < 0.05). The upregulation was more pronounced in platform-matched groups (p < 0.05). Exposure of osteoblasts to implant–abutment couplings induced adverse biological responses, which were more pronounced with platform-matched couplings. These reactions might be related to the increased amounts of metal ions released from the platform-matched couplings, highlighting the possible role of corrosion products in the mediation of crestal bone loss around dental implants

Mechanism of lignin inhibition of enzymatic biomass deconstruction

Background The conversion of plant biomass to ethanol via enzymatic cellulose hydrolysis offers a potentially sustainable route to biofuel production. However, the inhibition of enzymatic activity in pretreated biomass by lignin severely limits the efficiency of this process. Results By performing atomic-detail molecular dynamics simulation of a biomass model containing cellulose, lignin, and cellulases (TrCel7A), we elucidate detailed lignin inhibition mechanisms. We find that lignin binds preferentially both to the elements of cellulose to which the cellulases also preferentially bind (the hydrophobic faces) and also to the specific residues on the cellulose-binding module of the cellulase that are critical for cellulose binding of TrCel7A (Y466, Y492, and Y493). Conclusions Lignin thus binds exactly where for industrial purposes it is least desired, providing a simple explanation of why hydrolysis yields increase with lignin removal

Deep-learned estimation of uncertainty in measurements of apparent diffusion coefficient from whole-body diffusion-weighted MRI.

PURPOSE: To use deep learning to calculate the uncertainty in apparent diffusion coefficient (σADC) voxel-wise measurements to clinically impact the monitoring of treatment response and improve the quality of ADC maps. MATERIALS AND METHODS: We use a uniquely designed diffusion-weighted imaging (DWI) acquisition protocol that provides gold-standard measurements of σADC to train a deep learning model on two separate cohorts: 16 patients with prostate cancer and 28 patients with mesothelioma. Our network was trained with a novel cost function, which incorporates a perception metric and a b-value regularisation term, on ADC maps calculated by combinations of 2 or 3 b-values (e.g. 50/600/900, 50/900, 50/600, 600/900 s/mm2). We compare the accuracy of the deep-learning based approach for estimation of σADC with gold-standard measurements. RESULTS: The model accurately predicted the σADC for every b-value combination in both cohorts. Mean values of σADC within areas of active disease deviated from those measured by the gold-standard by 4.3% (range, 2.87-6.13%) for the prostate and 3.7% (range, 3.06-4.54%) for the mesothelioma cohort. We also showed that the model can easily be adapted for a different DWI protocol and field-of-view with only a few images (as little as a single patient) using transfer learning. CONCLUSION: Deep learning produces maps of σADC from standard clinical diffusion-weighted images (DWI) when 2 or more b-values are available

Predicting Landslide Risk Combining Space Measurements and Geotechnical Modeling: Application at Kerasia Slide

The work developed and applied a methodology combining (a) space measurement of past displacement and (b) geotechnical modelling of displacement to predict and mitigate the risk of ground displacement cased by progressive slope instability. The area of study is in Kerasea village in Plastiras Lake Municipality. The problem under treatment is a creeping landslide in an inhabited area. Mitigation measures were analyzed