Virtual 3D (MUPAI Virtual 3D)

Virtual reality is currently considered a first-order resource for education and training. In this regard, artistic education, like other disciplines, is backing into this technology as a tool to overcome obstacles and contribute new ways of visualization and of providing information. And, in this case, the use of this technology presents enormous advantages for museums, especially, the more modest ones, which have few resources to disseminate and show their collections and works. Moreover, they have to resort to ingenious solutions to solve their difficulties. Therefore, the Pedagogic Museum of Children’s Art (MUPAI) backs into this technology to overcome some of the difficulties it encounters and to allow interested spectators to see its works, with great realism, and to visit its facilities anywhere in the world and at any time of the day. Hence, virtual reality unfolds new possibilities in the field of education that were inconceivable only a short time ago.

Using Virtual Reality to Analyze Sports Performance

Improving performance in sports requires a better understanding of the perception-action loop employed by athletes. Because of its inherent limitations, video playback doesn't permit this type of in-depth analysis. Interactive, immersive virtual reality can overcome these limitations and foster a better understanding of sports performance.

Does the level of graphical detail of a virtual handball thrower influence a goal-keeper's motor response?

The authors investigated how different levels of detail (LODs) of a virtual throwing action can influence a handball goalkeeper's motor response. Goalkeepers attempted to stop a virtual ball emanating from five different graphical LODs of the same virtual throwing action. The five levels of detail were: a textured reference level (L0), a non-textured level (L1), a wire-frame level (L2), a point-light-display (PLD) representation (L3) and a PLD level with reduced ball size (L4). For each motor response made by the goalkeeper we measured and analyzed the time to respond (TTR), the percentage of successful motor responses, the distance between the ball and the closest limb (when the stopping motion was incorrect) and the kinematics of the motion. Results showed that TTR, percentage of successful motor responses and distance with the closest limb were not significantly different for any of the five different graphical LODs. However the kinematics of the motion revealed that the trajectory of the stopping limb was significantly different when comparing the L1 and L3 levels, and when comparing the L1 and L4 levels. These differences in the control of the goalkeeper's actions suggests that the different level of information available in the PLD representations ( L3 and L4) are causing the goalkeeper to adopt different motor strategies to control the approach of their limb to stop the ball.

Influence of the Graphical Levels of Detail of a Virtual Thrower on the Perception of the Movement

Virtual reality has a number of advantages for analyzing sports interactions such as the standardization of experimental conditions, stereoscopic vision, and complete control of animated humanoid movement. Nevertheless, in order to be useful for sports applications, accurate perception of simulated movement in the virtual sports environment is essential. This perception depends on parameters of the synthetic character such as the number of degrees of freedom of its skeleton or the levels of detail (LOD) of its graphical representation. This study focuses on the influence of this latter parameter on the perception of the movement. In order to evaluate it, this study analyzes the judgments of immersed handball goalkeepers that play against a graphically modified virtual thrower. Five graphical representations of the throwing action were defined: a textured reference level (L0), a nontextured level (L1), a wire-frame level (L2), a moving point light display (MLD) level with a normal-sized ball (L3), and a MLD level where the ball is represented by a point of light (L4). The results show that judgments made by goalkeepers in the L4 condition are significantly less accurate than in all the other conditions (p

Providing QoS for networked peers in distributed haptic virtual environments

Haptic information originates from a different human sense (touch), therefore the quality of service (QoS) required to supporthaptic traffic is significantly different from that used to support conventional real-time traffic such as voice or video. Each type ofnetwork impairment has different (and severe) impacts on the user’s haptic experience. There has been no specific provision of QoSparameters for haptic interaction. Previous research into distributed haptic virtual environments (DHVEs) have concentrated onsynchronization of positions (haptic device or virtual objects), and are based on client-server architectures.We present a new peerto-peer DHVE architecture that further extends this to enable force interactions between two users whereby force data are sent tothe remote peer in addition to positional information. The work presented involves both simulation and practical experimentationwhere multimodal data is transmitted over a QoS-enabled IP network. Both forms of experiment produce consistent results whichshow that the use of specific QoS classes for haptic traffic will reduce network delay and jitter, leading to improvements in users’haptic experiences with these types of applications.

Discovery of novel Agonists and antagonists of the free fatty acid receptor 1 (FFAR1) using virtual screening

The G-protein-coupled receptor free fatty acid receptor 1 (FFAR1), previously named GPR40, is a possible novel target for the treatment of type 2 diabetes. In an attempt to identify new ligands for this receptor, we performed virtual screening (VS) based on two-dimensional (2D) similarity, three-dimensional (3D) pharmacophore searches, and docking studies by using the structure of known agonists and our model of the ligand binding site, which was validated by mutagenesis. VS of a database of 2.6 million compounds followed by extraction of structural neighbors of functionally confirmed hits resulted in identification of 15 compounds active at FFAR1 either as full agonists, partial agonists, or pure antagonists. Site-directed mutagenesis and docking studies revealed different patterns of ligand-receptor interactions and provided important information on the role of specific amino acids in binding and activation of FFAR1.

Fluorescence (FISH) and chromogenic (CISH) in situ hybridisation in prostate carcinoma cell lines: comparison and use of virtual microscopy

Chromogenic in situ hybridisation (CISH) has become an attractive alternative to fluorescence in situ hybridisation (FISH) due to its permanent stain which is more familiar to pathologists and because it can be viewed using light microscopy, The aim of the present study is to examine reproducibility in the assessment of abnormal chromosome number by CISH in comparison to FISH. Using three prostate cell lines - PNTIA (derived from normal epithelium), LNCAP and DU145 (derived from prostatic carcinoma), chromosomes 7 and 8 were counted in 40 nuclei in FISH preparations (x100 oil immersion) and 100 nuclei in CISH preparations (x40) by two independent observers. The CISH slides were examined using standard fight microscopy and virtual microscopy. Reproducibitity was examined using paired Student's t-test (P

Short, medium and long term load forecasting model and virtual load forecaster based on radial basis neural networks

Artificial neural networks (ANNs) can be easily applied to short-term load forecasting (STLF) models for electric power distribution applications. However, they are not typically used in medium and long term load forecasting (MLTLF) electric power models because of the difficulties associated with collecting and processing the necessary data. Virtual instrument (VI) techniques can be applied to electric power load forecasting but this is rarely reported in the literature. In this paper, we investigate the modelling and design of a VI for short, medium and long term load forecasting using ANNs. Three ANN models were built for STLF of electric power. These networks were trained using historical load data and also considering weather data which is known to have a significant affect of the use of electric power (such as wind speed, precipitation, atmospheric pressure, temperature and humidity). In order to do this a V-shape temperature processing model is proposed. With regards MLTLF, a model was developed using radial basis function neural networks (RBFNN). Results indicate that the forecasting model based on the RBFNN has a high accuracy and stability. Finally, a virtual load forecaster which integrates the VI and the RBFNN is presented.