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.

Interlaboratory comparison of real-time polymerase chain reaction methods to detect Coxiella burnetii, the causative agent of Q fever

The bacterium Coxiella burnetii, which has a wide host range, causes Q fever. Infection with C burnetii can cause abortions, stillbirth, and the delivery of weak offspring in ruminants. Coxiella burnetii infection is zoonotic, and in human beings it can cause chronic, potentially fatal disease. Real-time polymerase chain reaction (PCR) is increasingly being used to detect the organism and to aid in diagnosis both in human and animal cases. Many different real-time PCR methods, which target different genes, have been described. To assess the comparability of the C. burnetii real-time PCR assays in use in different European laboratories, a panel of nucleic acid extracts was dispatched to 7 separate testing centers. The testing centers included laboratories from both human and animal health agencies. Each laboratory tested the samples using their in-house real-time PCR methods. The results of this comparison show that the most common target gene for real-time PCR assays is the IS1111 repeat element that is present in multiple copies in the C. burnetii genome. Many laboratories also use additional real-time PCR tests that target single-copy genes. The results of the current study demonstrate that the assays in use in the different laboratories are comparable, with general agreement of results for the panel of samples.

Resistance of Staphylococcus aureus to the cationic antimicrobial agent poly(2-(dimethylamino ethyl)methacrylate) (pDMAEMA) is influenced by cell-surface charge and hydrophobicity

Cationic antimicrobial agents may prevent device-associated infections caused by Staphylococcus epidermidis and Staphylococcus aureus. This study reports that the cationic antimicrobial polymer poly(2-(dimethylamino ethyl)methacrylate) (pDMAEMA) was more effective at antagonizing growth of clinical isolates of S. epidermidis than of S. aureus. Importantly, mature S. epidermidis biofilms were significantly inactivated by pDMAEMA. The S. aureus isolates tested were generally more hydrophobic than the S. epidermidis isolates and had a less negative charge, although a number of individual S. aureus and S. epidermidis clinical isolates had similar surface hydrophobicity and charge values. Fluorescence spectroscopy and flow cytometry revealed that fluorescently labelled pDMAEMA interacted strongly with S. epidermidis compared with S. aureus. S. aureus Delta dltA and Delta mprF mutants were less hydrophobic and therefore more susceptible to pDMAEMA than wild-type S. aureus. Although the different susceptibility of S. epidermidis and S. aureus isolates to pDMAEMA is complex, influenced in part by surface hydrophobicity and charge, these findings nevertheless reveal the potential of pDMAEMA to treat S. epidermidis infections.

Nuclear factor-kappaB as a potential therapeutic target for the novel cytotoxic agent LC-1 in acute myeloid leukaemia

Nuclear factor-kappaB (NF-kappaB) has been implicated in a number of malignancies and has been suggested to be a potential molecular target in the treatment of leukaemia. This study demonstrated the constitutive activation of NF-kappaB in human myeloid blasts and a clear correlation between NF-kappaB expression and in vitro cytoprotection. High NF-kappaB expression was found in many of the poor prognostic acute myeloid leukaemia (AML) subtypes, such as French-American-British classification M0 and M7, and the poor cytogenetic risk group. The in vitro effects of LC-1, a novel dimethylamino-parthenolide analogue, were assessed in 62 primary untreated AML samples. LC-1 was found to be cytotoxic to AML cells in a dose-dependent manner, mediated through the induction of apoptosis. The median drug concentration necessary to kill 50% of the cells was 4.5 micromol/l for AML cells, compared with 12.8 micromol/l for normal marrow cells. LC-1 was shown to reduce the five individual human NF-kappaB Rel proteins in a dose-dependent manner. The subsequent inhibition of many NF-kappaB-regulated cytokines was also demonstrated. Importantly, sensitivity to LC-1 was correlated with the basal NF-kappaB activity. Consequently, LC-1 treatment provides a proof of principle for the use of NF-kappaB inhibitors in the treatment of AML.

Evaluation of Four Designed Virtual Agent Personalities

Convincing conversational agents require a coherent set of behavioral responses that can be interpreted by a human observer as indicative of a personality. This paper discusses the continued development and subsequent evaluation of virtual agents based on sound psychological principles. We use Eysenck's theoretical basis to explain aspects of the characterization of our agents, and we describe an architecture where personality affects the agent's global behavior quality as well as their back-channel productions. Drawing on psychological research, we evaluate perception of our agents' personalities and credibility by human viewers (N = 187). Our results suggest that we succeeded in validating theoretically grounded indicators of personality in our virtual agents, and that it is feasible to place our characters on Eysenck's scales. A key finding is that the presence of behavioral characteristics reinforces the prescribed personality profiles that are already emerging from the still images. Our long-term goal is to enhance agents' ability to sustain realistic interaction with human users, and we discuss how this preliminary work may be further developed to include more systematic variation of Eysenck's personality scales. © 2012 IEEE.


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