Strut-and-tie modelling of reinforced concrete beams using genetic algorithms optimization

This paper presents a method for automatically producing optimal strut-and-tie models for the design of reinforced concrete beams. The optimal model is generated by means of an optimization problem solved by using genetic algorithms. The basic idea developed here is that from an initial random generation of possible configurations of the strut-and-tie model for the beam subjected to study, new populations of possible configurations may be generated in an iterative way by using genetic operators until reaching an optimum solution for the studied problem which corresponds to the strut-and-tie configuration which minimizes the total strain energy. In the optimal configuration, compressive struts are not enforced to be parallel, which allows representing more consistently the physical reality of the flow of forces. Furthermore, the method is more simple and easier to apply than the methods based on the concepts of evolutionary structural optimization.     

Superhydrophobic surfaces with silane‐treated diatomaceous earth/resin systems

Superhydrophobic coatings were prepared using fluorosilane‐treated diatomaceous earth (DE) with either polyurethane or epoxy binders. The surface wettability and morphology of the films were analyzed using contact angle measurements and scanning electron microscopy (SEM), respectively. The water contact angles were studied as a function of the fluorocarbon fraction on DE and the particle loadings of treated DE in the coating. The contact angles exceeded 150° for coatings with at least 0.02 fluorocarbon fraction (mass of fluorosilane/mass of particle) on the DE and with 0.2 particle loadings (mass of treated particles/mass of coating). The water contact angles of the surfaces were dependent on the nature of the binder below 0.2 particle loadings of the superhydrophobic DE particles, but were independent of the binder type after attaining superhydrophobicity. The results were consistent with the superhydrophobicity resulting from the migration of the superhydrophobic DE moving to and covering the surfaces completely. It was also shown that the treatment with fluorosilanes restricted the pores in DE and reduces the specific surface area of the material. However, these changes had effectively no effect on the superhydrophobicity of the coatings. The results of this work clearly identify some important considerations relative to producing superhydrophobic coatings from inexpensive diatomaceous earth. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016 , 133, 44072.     

A comparative study on in vitro behavior of calcium silicate ceramics synthesized from biowaste resources

Calcium silicate ceramics have received significant attention for biomedical applications for their excellent bioactivity and osteoconduction properties. Sol-gel process is extensively used for the fabrication of calcium silicates. In sol-gel process, calcium nitrate tetra hydrate (Ca(NO₃)₂·4H₂O) and tetraethylorthosilicate (TEOS) are used as precursors. However, these precursors are expensive. The objective of this work was to compare in vitro behavior of calcium silicate (CaSiO₃) produced using biowaste such as rice husk ash (RHA) and eggshells (coded; NCS) with CaSiO₃ prepared using TEOS and Ca(NO₃)₂·4H₂O (coded; CCS). Thermal investigation results revealed that the crystallization temperature for NCS is relatively lower (772°C) than for CCS (870°C). Bioactivity was studied in vitro using simulated body fluid (SBF) with respect to mineralization rate of hydroxyapatite. Mineralization of a greater hydroxyapatite was observed on NCS ceramics than CCS ceramics after incubation for 3, 7, 14 days in SBF solution, which was confirmed using X-ray diffractometer, Fourier transform infrared spectroscopy, scanning electron microscopy-energy dispersive spectroscopy. Degradation studies were conducted in Tris-HCl solution and the test results revealed that NCS ceramics has lower dissolution rate than CCS ceramics. The antimicrobial assay has shown that NCS samples exhibit significant zone of inhibition against Escherichia coli and Staphylococcus aureus which confirmed that the CaSiO₃ prepared from RHA and eggshell can prevent bacteria from adhering to the surface. In addition cell culture studies revealed that NCS ceramics possess good cytocompatibility with MG-63 cells and significantly promoted cell proliferation.     

Use of artificial neural network to evaluate the vibration mitigation performance of geofoam-filled trenches

Development activities in a city often generate ground vibration that can cause discomfort to the occupants in nearby buildings, disturbances to the activities undertaken in the buildings and possible damage to nearby structures. This ground vibration is caused by construction activities such as pile driving, ground compaction etc., and road and rail traffic. The use of trenches has been an effective way to mitigate the adverse effects of such ground vibration. The effectiveness of the trench depends on many parameters including the properties of the vibration source, soil medium and trench in-fill material, trench dimensions and the requirements of the receiver. The process of selecting an effective trench for vibration mitigation can therefore become complex due to the influence of a number of parameters and their wide range of values. This paper investigates the use of artificial neural network (ANN) as a smart and efficient tool to predict the effectiveness of geofoam-filled trenches to mitigate ground vibration. Towards this end, a database is developed from an extensive study on the effects of the controlling parameters through numerical simulations with a validated finite element (FE) model. At a certain distance from the vibration source, a geofoam-filled trench is introduced to evaluate the efficiency of vibration mitigation with changes in key parameters such as excitation frequency, amplitude of load, trench configuration (i.e. depth and width), soil shear wave velocity, soil density and damping ratio. These were selected as the input parameters for the ANN while amplitude reduction ratio and peak particle velocity (PPV) were considered as outputs. A multilayer feed forward network was used and trained with the Levenberg-Marquardt algorithm. Neural networks with different configurations were evaluated by comparing coefficient of determination (R²) and mean square error (MSE). The optimum architecture was then used to predict previous results, which revealed the accuracy and the effectiveness of the ANN approach. The findings of this study will provide useful information for vibration mitigation using geofoam-filed trenches.     

Changes in composition and characteristics of latex paints applied on porous inorganic substrates

Changes in film composition and characteristics that occur during and/or immediately after the application of latex paints on porous inorganic substrates were investigated. Gas chromatography (GC) and thermal analysis were among the techniques used for this purpose. The changes in coalescing agent and binder content were determined by GC and thermogravimetric-analysis, respectively, and the changes in glass transition temperature by differential scanning calo rimetry. It was found that the type of porous substrate could significantly affect the paint composition (pigment volume concentration, coalescent level) during the film formation process. Presented at the 25th FATIPEC Congress, September 2000, Torino, Italy. Are. P. Holoffe, 1342-Limelette, Belgium; email: perera.d@cori-coatings.be Leuvensesteenweg 167–199, 1800-Vilvoorde, Belgium; email: jeanmarie.borsus@akzonobel.com.     

Toward multidimensional assignment data association in robot localization and mapping

It is well accepted that the data association or the correspondence problem is one of the toughest problems faced by any state estimation algorithm. Particularly in robotics, it is not very well addressed. This paper introduces a multidimensional assignment (MDA)-based data association algorithm for the simultaneous localization and map building (SLAM) problem in mobile robot navigation. The data association problem is cast in a general discrete optimization framework and the MDA formulation for multitarget tracking is extended for SLAM using sensor location uncertainty with the joint likelihood of measurements over multiple frames as the objective function. Methods for feature initialization and management are also integrated into the algorithm. When clutter is high and features are sparse, the compatibility information of features of a single measurement frame is not sufficient to make effective data-association decisions,thus compromising performance of single-frame-based methods. However, in a multiple-measurement-frame approach, the availability of more than one frame of measurement provides for more effective data-association decisions to be made, as consistency of measurements are looked at in several frames of measurement. Simulations are conducted to verify the performance gains over the conventional nearest neighbor (NN) data association algorithm and the joint compatibility branch and bound (JCBB) algorithm, especially in the presence of varying densities of spurious measurements and dynamic objects. Experimental results with ground truth are presented to demonstrate the practicality of the proposed data-association method in complex and large outdoor environments and its effectiveness over single-frame-based NN and JCBB schemes.     

Invariant character recognition with Zernike and orthogonal Fourier-Mellin moments

In this paper, we consider the use of orthogonal moments for invariant classification of alphanumeric characters of different size. In addition to the Zernike and pseudo-Zernike moments (ZMs and PZMs) which have been previously proposed for invariant character recognition, a new method of combining Orthogonal Fourier-Mellin moments (OFMMs) with centroid bounding circle scaling is introduced, which is shown to be useful in characterizing images with large variability. Through extensive experimentation using ZMs and OFMMs as features, different scaling methodologies and classifiers, it is shown that OFMMs give the best overall performance in terms of both image reconstruction and classification accuracy.     

Effective bandwidth estimation and testing for Markov sources

This work addresses the resource sharing problem in broadband communication networks that can guarantee some quality of service (QoS), and develops some results about data source and traffic modelling, especially in aspects of model testing and parameter estimation. The multiplexing of variable bit rate (VBR) sources poses a mathematical and statistical problem: the estimation of the resource requirements of a source or set of sources. The estimation method shall be simple enough to be practically implemented in the connection acceptance control (CAC) function.

In this paper, the VBR video sources are taken as a typical case of variable rate, with real-time constraints. This association of requirements makes the case especially interesting. A Markov model is assumed for the VBR sources. The validity of such models is under research; they seem to be appropriate at least in certain time scales. The model is tested against real video traces. In order to estimate the resource allocation or “channel occupation” of each source, the concept of equivalent bandwidth proposed by Kelly [Notes on effective bandwidth, in: F.P. Kelly, S. Zachary, I.B. Ziedins (Eds.), Stochastic Networks: Theory and Applications, Oxford University Press, Oxford, 1996, pp. 141] is used; it is based on a consistent mathematical theory, and has proven to be robust and useful for technical applications.

A calculation of the equivalent bandwidth of a Markov source, given its parameters, can be found in the literature [IEEE ACM Trans. Networking 1 (4) (1993) 424]. But in fact, one can only estimate model and parameters. In this work, an estimation of the equivalent bandwidth is given, which can be obtained from real data. The convergence and the consistency of the estimation are studied, and practical bounds are found. Illustrative calculations are performed from real video traces that were obtained using a software MPEG coder, developed by the authors. The mathematical and statistical results are valid for whatever phenomenon that can be modelled as a Markov process.     

Preparation and pharmacodynamic evaluation of liposomes of indomethacin

The side effects of indomethacin, such as ulceration of the kidney and central nervous system (CNS) toxicity, limit its use as a drug for rheumatoid arthritis. Encapsulation of this drug in liposomes may reduce the toxic effects. The aim of this study was to determine the factors influencing encapsulation of indomethacin in liposomes and to determine anti-inflammatory potential of liposomal indomethacin. A series of liposomal formulations of indomethacin were prepared using various phospholipids. The effects of method of preparation, lipid composition, charge, and cholesterol (CH) on encapsulation of indomethacin in liposomes were investigated. A significant variation in encapsulation of the drug in liposomes was observed when prepared by different methods. With all the methods of preparation tried, the favorable lipid composition for high encapsulation of this drug was egg phosphatidyl choline:CH: stearlyamine (PC:CH:SA) at a 1:0.5:0.1 molar ratio. Inclusion of cholesterol did not affect the encapsulation efficiency of the drug in liposomes. The drug release profile from the liposomes was biphasic, and the highest percentage drug release was observed with large unilamellar vesicles (LUVs) (100 nm). Inclusion of stearylamine (PC:CH:SA 1:0.5:0.1) and phosphatidyl glycerol (PG) (PC:CH:PG 1:0.5:0.2) in the liposomes reduced the release of the drug in comparison to the neutral liposomes (PC:CH 1:1). The slow release of the drug from stearylamine-containing liposomes may be explained by the electrostatic interaction between the acid moiety of the drug and the amine moiety of the lipid. It is assumed that the possible hydrogen bonding between--OH groups of phosphatidyl glycerol and the--COOH group of the drug might be the reason for the slow release of the drug from PC:CH:PG (1:0.5:0.2) containing liposomes. Pharmacodynamic evaluation of the liposomes was performed by carrageenan-induced rat paw edema (acute) and adjuvant arthritis (chronic) models. The anti-inflammatory activity was increased from the first to fifth hour PC:CH:PG (1:0.5:0.2) and PC:CH:SA (1:0.5:0.1) liposomes showed the highest percentage inhibition of edema. In both these models, anti-inflammatory activity of liposomal indomethacin was significantly higher than that of free indomethacin (p < .01). The ulcer index of the free drug was about three times more than the encapsulated drug when administered at the same dose intraperitoneally to arthritic rats consecutively for 21 days.     

Evaluating the function of hippocampal subregions with high-resolution MRI in Alzheimer's disease and aging

Memory ability declines in older age groups. There is a growing list of physiological processes that target the hippocampal formation in an age-related fashion, and some might underlie the hippocampal component of memory decline. The hippocampal formation is comprised of separate subregions, and physiological processes differentially target these subregions. The ability to evaluate the functional integrity of individual subregions-performing subregional analysis-is a major clinical goal since it can aid in the diagnosis of memory decline, as well as in elucidating mechanisms of disease and testing potential interventions. Because of its superior spatial resolution, magnetic resonance imaging (MRI) is best suited to accomplish this goal. Despite limited success, most functional MRI (fMRI) protocols have difficulty in performing complete subregional analysis of the hippocampal formation. Here we address sources of difficulty by (1) generating T2* -weighted maps of the hippocampal formation with sub-millimeter resolution; and (2) by adapting an approach used by animal investigators to identify the hippocampal subregions using anatomical landmarks. The protocol is tested in patients with Alzheimer's disease and in healthy controls, in an effort to determine whether it can detect neuronal dysfunction. Results showed diminished signal in the hippocampal formation of patients with Alzheimer's disease (AD) compared to controls, and multivariate analysis showed that this difference was most prominent in the entorhinal cortex. The protocol can be used to perform subregional analysis of the hippocampal formation. Testing the protocol in other clinical populations is needed to demonstrate its efficacy in evaluating the neuronal integrity of all hippocampal subregions.