Selective Imaging of Damaged Bone Structure (Microcracks) Using a Targeting Supramolecular Eu(III) Complex As a Lanthanide Luminescent Contrast Agent

The synthesis and photophysical evaluation of a new supramolecular lanthanide complex is described which was developed as a luminescent contrast agent for bone structure analysis. We show that the Eu(III) emission of this complex is not pH dependent within the physiological pH range, and that its steady state emission is not significantly modulated by a series of group I and II as well as d-metal ions, and that this agent can be successfully employed to image mechanically formed cracks (scratches) in bone samples after 4 or 24 hours, using confocal laser-scanning microscopy.

The synthesis of BRL 49653 - a novel and potent antihyperglycemic agent.

Modifications based upon a metabolite of ciglitazone afforded BRL 49653 (I), a novel potent insulin sensitizer. A facile synthesis of this compd. is described.

Neural Network Modeling of Rheological Parameters of Grouts Containing Viscosity-Modifying Agent

The development of artificial neural network (ANN) models to predict the rheological behavior of grouts is described is this paper and the sensitivity of such parameters to the variation in mixture ingredients is also evaluated. The input parameters of the neural network were the mixture ingredients influencing the rheological behavior of grouts, namely the cement content, fly ash, ground-granulated blast-furnace slag, limestone powder, silica fume, water-binder ratio (w/b), high-range water-reducing admixture, and viscosity-modifying agent (welan gum). The six outputs of the ANN models were the mini-slump, the apparent viscosity at low shear, and the yield stress and plastic viscosity values of the Bingham and modified Bingham models, respectively. The model is based on a multi-layer feed-forward neural network. The details of the proposed ANN with its architecture, training, and validation are presented in this paper. A database of 186 mixtures from eight different studies was developed to train and test the ANN model. The effectiveness of the trained ANN model is evaluated by comparing its responses with the experimental data that were used in the training process. The results show that the ANN model can accurately predict the mini-slump, the apparent viscosity at low shear, the yield stress, and the plastic viscosity values of the Bingham and modified Bingham models of the pseudo-plastic grouts used in the training process. The results can also predict these properties of new mixtures within the practical range of the input variables used in the training with an absolute error of 2%, 0.5%, 8%, 4%, 2%, and 1.6%, respectively. The sensitivity of the ANN model showed that the trend data obtained by the models were in good agreement with the actual experimental results, demonstrating the effect of mixture ingredients on fluidity and the rheological parameters with both the Bingham and modified Bingham models.

Luminescent Terbium Contrast Agent for Bone Microdamage Detection

The synthesis and photophysical evaluation of a new lanthanide luminescence imaging agent is presented. The agent, a terbium-based cyclen complex can, through the use of an iminodiacetate moiety, bind to damaged bone surface via chelation to exposed Ca(II) sites, enabling the imaging of the damage using confocal fluorescence scanning microscopy.

The SEMAINE Database: Annotated Multimodal Records of Emotionally Colored Conversations between a Person and a Limited Agent

SEMAINE has created a large audiovisual database as a part of an iterative approach to building Sensitive Artificial Listener (SAL) agents that can engage a person in a sustained, emotionally colored conversation. Data used to build the agents came from interactions between users and an operator simulating a SAL agent, in different configurations: Solid SAL (designed so that operators displayed an appropriate nonverbal behavior) and Semi-automatic SAL (designed so that users' experience approximated interacting with a machine). We then recorded user interactions with the developed system, Automatic SAL, comparing the most communicatively competent version to versions with reduced nonverbal skills. High quality recording was provided by five high-resolution, high-framerate cameras, and four microphones, recorded synchronously. Recordings total 150 participants, for a total of 959 conversations with individual SAL characters, lasting approximately 5 minutes each. Solid SAL recordings are transcribed and extensively annotated: 6-8 raters per clip traced five affective dimensions and 27 associated categories. Other scenarios are labeled on the same pattern, but less fully. Additional information includes FACS annotation on selected extracts, identification of laughs, nods, and shakes, and measures of user engagement with the automatic system. The material is available through a web-accessible database. © 2010-2012 IEEE.