Characterization and modeling of on-body spatial diversity within indoor environments at 868 MHz

For the first time in the open literature we present a full characterization of the performance of receiver diversity for the on-body channels found in body area networks. The study involved three commonly encountered diversity combining schemes: selection combination (SC), maximal ratio combining (MRC) and equal gain combining (EGC). Measurements were conducted for both stationary and mobile user scenarios in an anechoic chamber and open office area environment. Achievable diversity gain for various on-body dual branch diversity receivers, consisting of horizontal and vertical spatially separated antennas, was found to be dependent upon transmitter-receive array separation, user state and level of multipath contribution from the local environment. The maximum diversity gain (6.4 dB) was observed for a horizontal two branch MRC combiner while the transmitter and receiver were on opposite sides of the body, and the user was mobile in the open office area. A novel statistical characterization of the fading experienced in on-body diversity channels is also performed using purposely derived first and second order diversity statistics for combiners operating in Nakagami fading.

Characterization and Modeling of the Indoor Radio Channel at 868 MHz for a Mobile Bodyworn Wireless Personal Area Network

This letter reports the statistical characterization and modeling of the indoor radio channel for a mobile wireless personal area network operating at 868 MHz. Line of sight (LOS) and non-LOS conditions were considered for three environments: anechoic chamber, open office area and hallway. Overall, the Nakagami-m cdf best described fading for bodyworn operation in 60% of all measured channels in anechoic chamber and open office area environments. The Nakagami distribution was also found to provide a good description of Rician distributed channels which predominated in the hallway. Multipath played an important role in channel statistics with the mean recorded m value being reduced from 7.8 in the anechoic chamber to 1.3 in both the open office area and hallway.

Rhodopsin and the Others: A Historical Perspective on Structural Studies of G Protein-Coupled Receptors

The role of rhodopsin as a structural prototype for the study of the whole superfamily of G protein-coupled receptors (GPCRs) is reviewed in an historical perspective. Discovered at the end of the nineteenth century, fully sequenced since the early 1980s, and with direct three-dimensional information available since the 1990s, rhodopsin has served as a platform to gather indirect information on the structure of the other superfamily members. Recent breakthroughs have elicited the solution of the structures of additional receptors, namely the beta 1- and beta 2-adrenergic receptors and the A(2A) adenosine receptor, now providing an opportunity to gauge the accuracy of homology modeling and molecular docking techniques and to perfect the computational protocol. Notably, in coordination with the solution of the structure of the A(2A) adenosine receptor, the first "critical assessment of GPCR structural modeling and docking" has been organized, the results of which highlighted that the construction of accurate models, although challenging, is certainly achievable. The docking of the ligands and the scoring of the poses clearly emerged as the most difficult components. A further goal in the field is certainly to derive the structure of receptors in their signaling state, possibly in complex with agonists. These advances, coupled with the introduction of more sophisticated modeling algorithms and the increase in computer power, raise the expectation for a substantial boost of the robustness and accuracy of computer-aided drug discovery techniques in the coming years.

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.

Evaluation of effective groundwater recharge of freshwater lens in small islands by the combined modeling of geoelectrical data and water heads

In small islands, a freshwater lens can develop due to the recharge induced by rain. Magnitude and spatial distribution of this recharge control the elevation of freshwater and the depth of its interface with salt water. Therefore, the study of lens morphology gives useful information on both the recharge and water uptake due to evapotranspiration by vegetation. Electrical resistivity tomography was applied on a small coral reef island, giving relevant information on the lens structure. Variable density groundwater flow models were then applied to simulate freshwater behavior. Cross validation of the geoelectrical model and the groundwater model showed that recharge exceeds water uptake in dunes with little vegetation, allowing the lens to develop. Conversely, in the low-lying and densely vegetated sectors, where water uptake exceeds recharge, the lens cannot develop and seawater intrusion occurs. This combined modeling method constitutes an original approach to evaluate effective groundwater recharge in such environments.
[Comte, J.-C., O. Banton, J.-L. Join, and G. Cabioch (2010), Evaluation of effective groundwater recharge of freshwater lens in small islands by the combined modeling of geoelectrical data and water heads, Water Resour. Res., 46, W06601, doi:10.1029/2009WR008058.]

Finite difference time domain modeling of phase grating diffusion

In this paper, a method for modeling diffusion caused by non-smooth boundary surfaces in simulations of room acoustics using finite difference time domain (FDTD) technique is investigated. The proposed approach adopts the well-known theory of phase grating diffusers to efficiently model sound scattering from rough surfaces. The variation of diffuser well-depths is attained by nesting allpass filters within the reflection filters from which the digital impedance filters used in the boundary implementation are obtained. The presented technique is appropriate for modeling diffusion at high frequencies caused by small surface roughness and generally diffusers that have narrow wells and infinitely thin separators. The diffusion coefficient was measured with numerical experiments for a range of fractional Brownian diffusers.

Modeling of subsurface pulsed radar for nondestructive testing of structures

The use of pulsed radar for investigating the integrity of structural elements is gaining popularity and becoming firmly established as a nondestructive test method in civil engineering. Difficulties can often arise in the interpretation of results obtained, particularly where internal details are relatively complex. One approach that can be used to understand and evaluate radar results is through numerical modeling of signal propagation and reflection. By comparing the results of a numerical modeling with those from field measurements, engineers can gain valuable insight into the probable features embedded beneath the surface of a structural element. This paper discusses a series of numerical techniques for modeling subsurface radar and compares the precision of the results with those taken from real field data. It is found that more complex problems require more sophisticated analysis techniques to obtain realistic results, with a consequential increase in the computational resources to carry out the modeling.

A micromechanics approach for damage modeling of polymer matrix composites

A new model for damage evolution in polymer matrix composites is presented. The model is based on a combination of two constituent-level models and an interphase model. This approach reduces the number of empirical parameters since the two constituent- level models are formulated for isotropic materials, namely fiber and matrix. Decomposition of the state variables down to the micro-scale is accomplished by micromechanics. Phenomenological damage evolution models are then postulated for each constituent. Determination of material parameters is made from available experimental data. The required experimental data can be obtained with standard tests. Comparison between model predictions and additional experimental data is presented.

Bidirectional, iterative approach to the structural delineation of the functional "Chemoprint" in GPR40 for agonist recognition

GPR40, free fatty acid receptor 1 (FFAR1), is a member of the GPCR superfamily and a possible target for the treatment of type 2 diabetes. In this work, we conducted a bidirectional iterative investigation, including computational modeling and site-directed mutagenesis, aimed at delineating amino acid residues forming the functional "chemoprint" of GPR40 for agonist recognition. The computational and experimental studies revolved around the recognition of the potent synthetic agonist GW9508. Our experimentally supported model suggested that H137(4.56), R183(5.39), N244(6.55), and R258(7.35) are directly involved in interactions with the ligand. We have proposed a polarized NH-pi interaction between H137(4.56) and GW9508 as one of the contributing forces leading to the high potency of GW9508. The modeling approach presented in this work provides a general strategy for the exploration of receptor-ligand interactions in G-protein coupled receptors beginning prior to acquisition of experimental data.

Two-Ray Modeling of Recombination Effects in the Presence of a Phase Conjugation Array

This article describes by means of a simple model how signal recombination effects behave under the influence of phase conjugating retrodirective array (RDA) technology. A two-ray ground reflection model is used to predict the operational advantages of RDA technology in multipath rich environments. The simulation results show that advantageous signal recombination occurs due to automatic self-phasing. As the number of elements in the RDA increases, the fading effect normally observed due to out of phase multipath signal is mitigated to the extent that the system approaches that of one operating in a free space environment. © 2013 Wiley Periodicals, Inc. Microwave Opt Technol Lett 55:1987–1989, 2013

Finite element modeling of debonding failures in FRP-strengthened RC beams: A dynamic approach

This paper is concerned with the finite element simulation of debonding failures in FRP-strengthened concrete beams. A key challenge for such simulations is that common solution techniques such as the Newton-Raphson method and the arc-length method often fail to converge. This paper examines the effectiveness of using a dynamic analysis approach in such FE simulations, in which debonding failure is treated as a dynamic problem and solved using an appropriate time integration method. Numerical results are presented to show that an appropriate dynamic approach effectively overcomes the convergence problem and provides accurate predictions of test results.

Avoiding Overfitting in Inverse Modeling of Chloride Migration in Concrete

Inverse analysis for reactive transport of chlorides through concrete in the presence of electric field is presented. The model is solved using MATLAB’s built-in solvers “pdepe.m” and “ode15s.m”. The results from the model are compared with experimental measurements from accelerated migration test and a function representing the lack of fit is formed. This function is optimised with respect to varying amount of key parameters defining the model. Levenberg-Marquardt trust-region optimisation approach is employed. The paper presents a method by which the degree of inter-dependency between parameters and sensitivity (significance) of each parameter towards model predictions can be studied on models with or without clearly defined governing equations. Eigen value analysis of the Hessian matrix was employed to investigate and avoid over-parametrisation in inverse analysis. We investigated simultaneous fitting of parameters for diffusivity, chloride binding as defined by Freundlich isotherm (thermodynamic) and binding rate (kinetic parameter). Fitting of more than 2 parameters, simultaneously, demonstrates a high degree of parameter inter-dependency. This finding is significant as mathematical models for representing chloride transport rely on several parameters for each mode of transport (i.e., diffusivity, binding, etc.), which combined may lead to unreliable simultaneous estimation of parameters.