916 resultados para 3D hydrothermal model


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Purpose: Cardiomyocytes are terminally differentiated cells in the adult heart and ischemia and cardiotoxic compounds can lead to cell death and irreversible decline of cardiac function. As testing platforms, isolated organs and primary cells from rodents have been the standard in research and toxicology, but there is a need for better models that more faithfully recapitulate native human biology. Hence, a new in vitro model comprising the advantages of 3D cell culture and the availability of induced pluripotent stem cells (iPSC) from human origin was developed and characterized. Methods: Human cardiomyocytes (CMs) derived from induced pluripotent stem cells (iPSCs) were studied in standard 2D culture and as cardiac microtissues (MTs) formed in hanging drops. 2D cultures were examined using immunofluorescence microscopy and Western blotting while the cardiac MTs were subjected to immunofluorescence, contractility, and pharmacological investigations. Results: iPSC-derived CMs in 2D culture showed well-formed myofibrils, cell-cell contacts positive for connexin-43, and other typical cardiac proteins. The cells reacted to pro-hypertrophic growth factors with a substantial increase in myofibrils and sarcomeric proteins. In hanging drop cultures, iPSC-derived cardiomyocytes formed spheroidal MTs within 4 days showing a homogeneous tissue structure with well-developed myofibrils extending throughout the whole spheroid without a necrotic core. MTs showed spontaneous contractions for more than 4 weeks that were recorded by optical motion tracking, sensitive to temperature, and responsive to electrical pacing. Contractile pharmacology was tested with several agents known to modulate cardiac rate and viability. Calcium-transients underlay the contractile activity and were also responsive to electrical stimulation, caffeine-induced Ca2+-release, extracellular calcium levels. Conclusions: 3D culture using iPSC-derived human cardiomyocytes provides an organoid human-based cellular platform that is free of necrosis and recapitulates vital cardiac functionality, thereby providing new and promising relevant model for the evaluation and development of new therapies and detection of cardiotoxicity.

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An extended 3D distributed model based on distributed circuit units for the simulation of triple‐junction solar cells under realistic conditions for the light distribution has been developed. A special emphasis has been put in the capability of the model to accurately account for current mismatch and chromatic aberration effects. This model has been validated, as shown by the good agreement between experimental and simulation results, for different light spot characteristics including spectral mismatch and irradiance non‐uniformities. This model is then used for the prediction of the performance of a triple‐junction solar cell for a light spot corresponding to a real optical architecture in order to illustrate its suitability in assisting concentrator system analysis and design process.

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We address the problem of 3D-assisted 2D face recognition in scenarios when the input image is subject to degradations or exhibits intra-personal variations not captured by the 3D model. The proposed solution involves a novel approach to learn a subspace spanned by perturbations caused by the missing modes of variation and image degradations, using 3D face data reconstructed from 2D images rather than 3D capture. This is accomplished by modelling the difference in the texture map of the 3D aligned input and reference images. A training set of these texture maps then defines a perturbation space which can be represented using PCA bases. Assuming that the image perturbation subspace is orthogonal to the 3D face model space, then these additive components can be recovered from an unseen input image, resulting in an improved fit of the 3D face model. The linearity of the model leads to efficient fitting. Experiments show that our method achieves very competitive face recognition performance on Multi-PIE and AR databases. We also present baseline face recognition results on a new data set exhibiting combined pose and illumination variations as well as occlusion.

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Staphylococcus aureus necrotizing pneumonia is recognized as a toxin-mediated disease, yet the tissue-destructive events remain elusive, partly as a result of lack of mechanistic studies in human lung tissue. In this study, a three-dimensional (3D) tissue model composed of human lung epithelial cells and fibroblasts was used to delineate the role of specific staphylococcal exotoxins in tissue pathology associated with severe pneumonia. To this end, the models were exposed to the mixture of exotoxins produced by S. aureus strains isolated from patients with varying severity of lung infection, namely necrotizing pneumonia or lung empyema, or to purified toxins. The necrotizing pneumonia strains secreted high levels of alpha-toxin and Panton-Valentine leukocidin (PVL), and triggered high cytotoxicity, inflammation, necrosis and loss of E-cadherin from the lung epithelium. In contrast, the lung empyema strain produced moderate levels of PVL, but negligible amounts of alpha-toxin, and triggered limited tissue damage. alpha-toxin had a direct damaging effect on the epithelium, as verified using toxin-deficient mutants and pure alpha-toxin. Moreover, PVL contributed to pathology through the lysis of neutrophils. A combination of alpha-toxin and PVL resulted in the most severe epithelial injury. In addition, toxin-induced release of pro-inflammatory mediators from lung tissue models resulted in enhanced neutrophil migration. Using a collection of 31 strains from patients with staphylococcal pneumonia revealed that strains producing high levels of alpha-toxin and PVL were cytotoxic and associated with fatal outcome. Also, the strains that produced the highest toxin levels induced significantly greater epithelial disruption. Of importance, toxin-mediated lung epithelium destruction could be inhibited by polyspecific intravenous immunoglobulin containing antibodies against alpha-toxin and PVL. This study introduces a novel model system for study of staphylococcal pneumonia in a human setting. The results reveal that the combination and levels of alpha-toxin and PVL correlate with tissue pathology and clinical outcome associated with pneumonia.

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The aim of this study was to determine whether image artifacts caused by orthodontic metal accessories interfere with the accuracy of 3D CBCT model superimposition. A human dry skull was subjected three times to a CBCT scan: at first without orthodontic brackets (T1), then with stainless steel brackets bonded without (T2) and with orthodontic arch wires (T3) inserted into the brackets' slots. The registration of image surfaces and the superimposition of 3D models were performed. Within-subject surface distances between T1-T2, T1-T3 and T2-T3 were computed and calculated for comparison among the three data sets. The minimum and maximum Hausdorff Distance units (HDu) computed between the corresponding data points of the T1 and T2 CBCT 3D surface images were 0.000000 and 0.049280 HDu, respectively, and the mean distance was 0.002497 HDu. The minimum and maximum Hausdorff Distances between T1 and T3 were 0.000000 and 0.047440 HDu, respectively, with a mean distance of 0.002585 HDu. In the comparison between T2 and T3, the minimum, maximum and mean Hausdorff Distances were 0.000000, 0.025616 and 0.000347 HDu, respectively. In the current study, the image artifacts caused by metal orthodontic accessories did not compromise the accuracy of the 3D model superimposition. Color-coded maps of overlaid structures complemented the computed Hausdorff Distances and demonstrated a precise fusion between the data sets.

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Until few years ago, 3D modelling was a topic confined into a professional environment. Nowadays technological innovations, the 3D printer among all, have attracted novice users to this application field. This sudden breakthrough was not supported by adequate software solutions. The 3D editing tools currently available do not assist the non-expert user during the various stages of generation, interaction and manipulation of 3D virtual models. This is mainly due to the current paradigm that is largely supported by two-dimensional input/output devices and strongly affected by obvious geometrical constraints. We have identified three main phases that characterize the creation and management of 3D virtual models. We investigated these directions evaluating and simplifying the classic editing techniques in order to propose more natural and intuitive tools in a pure 3D modelling environment. In particular, we focused on freehand sketch-based modelling to create 3D virtual models, interaction and navigation in a 3D modelling environment and advanced editing tools for free-form deformation and objects composition. To pursuing these goals we wondered how new gesture-based interaction technologies can be successfully employed in a 3D modelling environments, how we could improve the depth perception and the interaction in 3D environments and which operations could be developed to simplify the classical virtual models editing paradigm. Our main aims were to propose a set of solutions with which a common user can realize an idea in a 3D virtual model, drawing in the air just as he would on paper. Moreover, we tried to use gestures and mid-air movements to explore and interact in 3D virtual environment, and we studied simple and effective 3D form transformations. The work was carried out adopting the discrete representation of the models, thanks to its intuitiveness, but especially because it is full of open challenges.

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Purpose Accurate three-dimensional (3D) models of lumbar vertebrae can enable image-based 3D kinematic analysis. The common approach to derive 3D models is by direct segmentation of CT or MRI datasets. However, these have the disadvantages that they are expensive, timeconsuming and/or induce high-radiation doses to the patient. In this study, we present a technique to automatically reconstruct a scaled 3D lumbar vertebral model from a single two-dimensional (2D) lateral fluoroscopic image. Methods Our technique is based on a hybrid 2D/3D deformable registration strategy combining a landmark-to-ray registration with a statistical shape model-based 2D/3D reconstruction scheme. Fig. 1 shows different stages of the reconstruction process. Four cadaveric lumbar spine segments (total twelve lumbar vertebrae) were used to validate the technique. To evaluate the reconstruction accuracy, the surface models reconstructed from the lateral fluoroscopic images were compared to the associated ground truth data derived from a 3D CT-scan reconstruction technique. For each case, a surface-based matching was first used to recover the scale and the rigid transformation between the reconstructed surface model Results Our technique could successfully reconstruct 3D surface models of all twelve vertebrae. After recovering the scale and the rigid transformation between the reconstructed surface models and the ground truth models, the average error of the 2D/3D surface model reconstruction over the twelve lumbar vertebrae was found to be 1.0 mm. The errors of reconstructing surface models of all twelve vertebrae are shown in Fig. 2. It was found that the mean errors of the reconstructed surface models in comparison to their associated ground truths after iterative scaled rigid registrations ranged from 0.7 mm to 1.3 mm and the rootmean squared (RMS) errors ranged from 1.0 mm to 1.7 mm. The average mean reconstruction error was found to be 1.0 mm. Conclusion An accurate, scaled 3D reconstruction of the lumbar vertebra can be obtained from a single lateral fluoroscopic image using a statistical shape model based 2D/3D reconstruction technique. Future work will focus on applying the reconstructed model for 3D kinematic analysis of lumbar vertebrae, an extension of our previously-reported imagebased kinematic analysis. The developed method also has potential applications in surgical planning and navigation.

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The indoor air quality (IAQ) in buildings is currently assessed by measurement of pollutants during building operation for comparison with air quality standards. Current practice at the design stage tries to minimise potential indoor air quality impacts of new building materials and contents by selecting low-emission materials. However low-emission materials are not always available, and even when used the aggregated pollutant concentrations from such materials are generally overlooked. This paper presents an innovative tool for estimating indoor air pollutant concentrations at the design stage, based on emissions over time from large area building materials, furniture and office equipment. The estimator considers volatile organic compounds, formaldehyde and airborne particles from indoor materials and office equipment and the contribution of outdoor urban air pollutants affected by urban location and ventilation system filtration. The estimated pollutants are for a single, fully mixed and ventilated zone in an office building with acceptable levels derived from Australian and international health-based standards. The model acquires its dimensional data for the indoor spaces from a 3D CAD model via IFC files and the emission data from a building products/contents emissions database. This paper describes the underlying approach to estimating indoor air quality and discusses the benefits of such an approach for designers and the occupants of buildings.

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The Lockyer Valley, southeast Queensland, hosts intensive irrigated agriculture using groundwater from over 5000 alluvial bores. A current project is considering introduction of PRW (purified recycled water) to augment groundwater supplies. To assess this, a valley-wide MODFLOW simulation model is being developed plus a new unsaturated zone flow model. To underpin these models and provide a realistic understanding of the aquifer framework a 3D visualisation model has been developed using Groundwater Visualisation System (GVS) software produced at QUT.

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The Lockyer Valley in southeast Queensland supports important and intensive irrigation which is dependant on the quality and availability of groundwater. Prolonged drought conditions from ~1997 resulted in a depletion of the alluvial aquifers, and concern for the long-term sustainability of this resource. By 2008, many areas of the valley were at < 20% of storage. Some relief occurred with rain events in early 2009, then in December 2010 - January 2011, most of southeast Queensland experienced unprecedented flooding. These storm-based events have caused a shift in research focus from investigations of drought conditions and mitigation to flood response analysis. For the alluvial aquifer system of the valley, a preliminary assessment of groundwater observation bore data, prior to and during the flood, indicates that there is a spatially variable aquifer response. While water levels in some bores screened in unconfined shallow aquifers have recovered by more than 10 m within a short period of time (months), others show only a small or moderate response. Measurements of pre- and post-flood groundwater levels and high-resolution time-series records from data loggers are considered within the framework of a 3D geological model of the Lockyer Valley using Groundwater Visualisation System(GVS). Groundwater level fluctuations covering both drought and flood periods are used to estimate groundwater recharge using the water table fluctuation method (WTF), supplemented by estimates derived using chloride mass balance. The presentation of hydraulic and recharge information in a 3D format has considerable advantages over the traditional 2D presentation of data. The 3D approach allows the distillation of multiple types of information(topography, geological, hydraulic and spatial) into one representation that provides valuable insights into the major controls of groundwater flow and recharge. The influence of aquifer lithology on the spatial variability of groundwater recharge is also demonstrated.

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Gait recognition approaches continue to struggle with challenges including view-invariance, low-resolution data, robustness to unconstrained environments, and fluctuating gait patterns due to subjects carrying goods or wearing different clothes. Although computationally expensive, model based techniques offer promise over appearance based techniques for these challenges as they gather gait features and interpret gait dynamics in skeleton form. In this paper, we propose a fast 3D ellipsoidal-based gait recognition algorithm using a 3D voxel model derived from multi-view silhouette images. This approach directly solves the limitations of view dependency and self-occlusion in existing ellipse fitting model-based approaches. Voxel models are segmented into four components (left and right legs, above and below the knee), and ellipsoids are fitted to each region using eigenvalue decomposition. Features derived from the ellipsoid parameters are modeled using a Fourier representation to retain the temporal dynamic pattern for classification. We demonstrate the proposed approach using the CMU MoBo database and show that an improvement of 15-20% can be achieved over a 2D ellipse fitting baseline.

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The Lockyer Valley in southeast Queensland, Australia, hosts an economically significant alluvial aquifer system which has been impacted by prolonged drought conditions (~1997 to ~ 2009). Throughout this time, the system was under continued groundwater extraction, resulting in severe aquifer depletion. By 2008, much of the aquifer was at <30% of storage but some relief occurred with rains in early 2009. However, between December 2010 and January 2011, most of southeast Queensland experienced unprecedented flooding, which generated significant aquifer recharge. In order to understand the spatial and temporal controls of groundwater recharge in the alluvium, a detailed 3D lithological property model of gravels, sands and clays was developed using GOCAD software. The spatial distribution of recharge throughout the catchment was assessed using hydrograph data from about 400 groundwater observation wells screened at the base of the alluvium. Water levels from these bores were integrated into a catchment-wide 3D geological model using the 3D geological modelling software GOCAD; the model highlights the complexity of recharge mechanisms. To support this analysis, groundwater tracers (e.g. major and minor ions, stable isotopes, 3H and 14C) were used as independent verification. The use of these complementary methods has allowed the identification of zones where alluvial recharge primarily occurs from stream water during episodic flood events. However, the study also demonstrates that in some sections of the alluvium, rainfall recharge and discharge from the underlying basement into the alluvium are the primary recharge mechanisms of the alluvium. This is indicated by the absence of any response to the flood, as well as the observed old radiocarbon ages and distinct basement water chemistry signatures at these locations. Within the 3D geological model, integration of water chemistry and time-series displays of water level surfaces before and after the flood suggests that the spatial variations of the flood response in the alluvium are primarily controlled by the valley morphology and lithological variations within the alluvium. The integration of time-series of groundwater level surfaces in the 3D geological model also enables the quantification of the volumetric change of groundwater stored in the unconfined sections of this alluvial aquifer during drought and following flood events. The 3D representation and analysis of hydraulic and recharge information has considerable advantages over the traditional 2D approach. For example, while many studies focus on singular aspects of catchment dynamics and groundwater-surface water interactions, the 3D approach is capable of integrating multiple types of information (topography, geological, hydraulic, water chemistry and spatial) into a single representation which provides valuable insights into the major factors controlling aquifer processes.