Impact behavior of aminosilane functionalized nanosilica based shear thickening fluid impregnated Kevlar fabrics

In the present work, two types of shear thickening fluids have been synthesized by using neat and aminosilane functionalized silica nanoparticles and their viscosity curves have been obtained by the rheometer. Based on the values of peak viscosity of synthesized shear thickening fluids, the surface functionalized nanosilica based shear thickening fluid has been chosen as a best candidate due to the high viscosity for impregnation into the neat Kevlar of different layers viz. four (04) and eight (08) layers for velocity impact study. The experimental investigations reveal high energy absorption of shear thickening fluid impregnated Kevlar as compared to the neat Kevlar. The maximum energy absorption 62 J is achieved corresponding to the initial velocity 154 m∙s⁻¹ for 08 layers shear thickening fluid impregnated Kevlar specimen. The data have also been analytically determined and validated with the experimental data. The experimental data have good agreement with the analytical data within the accuracy of around 15 to 20%. The present findings can have significant inferences towards the fabrication of shear thickening fluids using nanomaterials for numerous applications such as soft armors, dampers, nanofinishing and so forth.     

Finite sample properties of estimators of spatial autoregressive models with autoregressive disturbances

The article investigates the finite sample properties of estimators for spatial autoregressive models where the disturbance terms may follow a spatial autoregressive process. In particular we investigate the finite sample behavior of the feasible generalized spatial two-stage least squares (FGS2SLS) estimator introduced by Kelejian and Prucha (1998), the maximum likelihood (ML) estimator, as well as that of several other estimators. We find that the FGS2SLS estimator is virtually as efficient as the ML estimator. This is important because the ML estimator is computationally burdensome, and may even be forbidding in large samples, while the FGS2SLS estimator remains computationally feasible in large samples. Received: 20 January 2001 / Accepted: 31 August 2001     

Fast frequency estimation and tracking using Lagrange interpolation

A computationally efficient and accurate frequency estimation and tracking algorithm is proposed, based on the adaptive frequency estimator (AFE) of Etter and Hush. A Lagrange interpolator (a fractional delay filter) is used to estimate the gradient of the performance surface of the adaptation, which enables highly accurate estimation. The performance of the new algorithm is demonstrated in the context of tracking a chirp signal in noise     

Biodegradation of gelatin–g-poly(ethyl acrylate) copolymers

Gelatin-g-poly(ethyl acrylate) copolymers were prepared in an aqueous medium, using K₂S₂O₈ initiator. The composition of the graft copolymers was dependent upon temperature and duration of the reaction. The number of grafting sites was small and molecular weight of the grafted poly(ethyl acrylate) branches was high. Three copolymer samples with grafting efficiencies of 33.3%, 61.0%, and 84.0%, were tested for their microbial susceptibility in a synthetic medium employing a mixed inoculum of Bacillus subtilis, Pseudomonas aeruginosa, and Serratia marcescens and the percent weight losses were 12%, 10.1%, and 6.0%, respectively, after 6 weeks of incubation. The extent of degradation seems to decrease with increasing grafting efficiency. There was initial rapid weight loss accompanied by the exponential increase in bacterial population and pH of the culture medium during the first week. The nitrogen analysis also showed the utilization of the polymer. A parallel set of experiments, carried out by employing the samples as the only source of both carbon and nitrogen, showed a marginal but definite increase in the utilization of the polymer.     

Development of a Sensor Fusion Strategy for Robotic Application Based on Geometric Optimization

Fusion of multi-sensor information is an important technology, which is growing exponentially due to its tremendous application potential in many areas. Effective fusion of data from sensors is very critical in increasing an intelligent system's capability to accomplish complex tasks. Appropriate fusion technologies are needed to be developed specially when a system requires redundant sensors to be used. More the redundancy in sensors, more is the computational complexity for controlling the system and more is its intelligence level. This research presents a strategy developed for multiple sensor fusion, based on geometric optimization. Each sensor's uncertainty has been modeled using classical Lagrangian optimization techniques. However, the uniqueness and effectiveness of the present technique lies on the fact that starting from the optimized value as initial estimate the accuracy of the sensory information has further been improved up to any pre defined bounded range, by developing two architectures – FFA (fission–fusion architecture) and FDD (fusion in differential domain). Sufficient evidences and analyses have been provided in the paper to show its effectiveness in various applications.     

Evaluation of improvement of physical and mechanical properties of bamboo fibers due to alkali treatment

Bamboo strips treated with caustic solutions of different concentrations, e.g., 5%, 10%, 15%, 20%, 25%, and 50%, were subjected to mechanical testing giving stresses on tensile strength, percent elongation at break, flexural strength, flexural modulus, and toughness. The change in average density was ?15%, and the weight loss value shows a maximum of 21.94% at 50% alkali treatment. The mechanical properties of bamboo strips increase steadily with increasing concentration of caustic soda, showing a comparable increased value at 15 and 20%, and then exhibiting a gradual fall. The percent elongation at break corroborates these observations showing a continuous decreasing trend. The properties under investigation exhibit a clear transition in between 15 and 20% alkali concentration. The morphology of strips was studied by scanning electron microscope and polarizing light microscope. The crystal structure of both untreated and treated strips was compared by XRD analysis. In both cases, the breakdown of the crystal structures of the cellulose fibers and the recrystallization or reorientation of the degraded chains that are devoid of hemicellulose are quite apparent. However, at a very high concentration (to the extent of 25%) the breakdown of structure predominates much more over the reorientation or recrystallization. © 2007 Wiley Periodicals, Inc. J Appl Polym Sci, 2008     

Design of particle-reinforced polyurethane mould materials for soft tooling process using evolutionary multi-objective optimization algorithms

Polyurethane is used for making mould in soft tooling (ST) process for producing wax/plastic components. These wax components are later used as pattern in investment casting process. Due to low thermal conductivity of polyurethane, cooling time in ST process is long. To reduce the cooling time, thermal conductive fillers are incorporated into polyurethane to make composite mould material. However, addition of fillers affects various properties of the ST process, such as stiffness of the mould box, rendering flow-ability of melt mould material, etc. In the present work, multi-objective optimization of various conflicting objectives (namely maximization of equivalent thermal conductivity, minimization of effective modulus of elasticity, and minimization of equivalent viscosity) of composite material are conducted using evolutionary algorithms (EAs) in order to design particle-reinforced polyurethane composites by finding the optimal values of design parameters. The design parameters include volume fraction of filler content, size and shape factor of filler particle, etc. The Pareto-optimal front is targeted by solving the corresponding multi-objective problem using the NSGA-II procedure. Then, suitable multi-criterion decision-making techniques are employed to select one or a small set of the optimal solution(s) of design parameter(s) based on the higher level information of the ST process for industrial applications. Finally, the experimental study with a typical real industrial application demonstrates that the obtained optimal design parameters significantly reduce the cooling time in soft tooling process keeping other processing advantages.     

Chitosan-based magnetic molecularly imprinted polymer: synthesis and application in selective recognition of tricyclazole from rice and water samples

A tricyclazole selective chitosan/Fe₃O₄ magnetic molecularly imprinted polymer (MMIP) was synthesized using non-covalent binding polymerization involving methacrylic acid (MAA) as functional monomer, divinylbenzene (DVB-80) as crosslinker, 2,2'-azobisisobutyronitrile as initiator, acetonitrile/toluene (75:25, v/v) as porogenic solvent and tricyclazole as template. Surface morphology and magnetic characterization of the prepared imprinted and non-imprinted polymers were done using scanning electron microscopy, transmission electron microscopy, Fourier transform infrared spectrometry and vibrating sample magnetometry, respectively. The adsorption kinetic data fitted best in pseudo-second-order model. The adsorption equilibrium was achieved in 30 min and the maximum binding capacity was 4579.9 µg/g. The Freundlich isotherm model was found suitable for explaining the binding isotherm data (R² > 0.99). Negative values of thermodynamic parameters ∆G (Gibb’s free energy), ∆H (enthalpy), and ∆S (entropy) revealed exothermic and spontaneous nature of adsorption processes. It also revealed decreased randomness at the solid–liquid interface during sorption. The scatchard plot analysis suggested heterogeneity of binding sites on MMIPs. The molecular recognition selectivity of MMIPs towards tricyclazole was much higher, as compared to its structural analogues, tebuconazole (α = 28.58) and hexaconazole (α = 37.16). The MMIPs were successfully applied to separate and enrich tricyclazole from fortified samples of rice and water, with a recovery percentage of 89.4% and 90.9%, respectively. These reusable imprinted polymers possessing high selectivity and specificity can be utilized as an adsorbent for solid-phase extraction in sample preparation for tricyclazole residue analysis in complex environmental matrices.

     

Proinflammatory Interleukin-33 Induces Dichotomic Effects on Cell Proliferation in Normal Gastric Epithelium and Gastric Cancer

Interleukin (IL)-33 is a member of the interleukin (IL)-1 family of cytokines linked to the development of inflammatory conditions and cancer in the gastrointestinal tract. This study is designed to investigate whether IL-33 has a direct effect on human gastric epithelial cells (GES-1), the human gastric adenocarcinoma cell line (AGS), and the gastric carcinoma cell line (NCI-N87) by assessing its role in the regulation of cell proliferation, migration, cell cycle, and apoptosis. Cell cycle regulation was also determined in ex vivo gastric cancer samples obtained during endoscopy and surgical procedures. Cell lines and tissue samples underwent stimulation with rhIL-33. Proliferation was assessed by XTT and CFSE assays, migration by wound healing assay, and apoptosis by caspase 3/7 activity assay and annexin V assay. Cell cycle was analyzed by means of propidium iodine assay, and gene expression regulation was assessed by RT-PCR profiling. We found that IL-33 has an antiproliferative and proapoptotic effect on cancer cell lines, and it can stimulate proliferation and reduce apoptosis in normal epithelial cell lines. These effects were also confirmed by the analysis of cell cycle gene expression, which showed a reduced expression of pro-proliferative genes in cancer cells, particularly in genes involved in G0/G1 and G2/M checkpoints. These results were confirmed by gene expression analysis on bioptic and surgical specimens. The aforementioned results indicate that IL-33 may be involved in cell proliferation in an environment- and cell-type-dependent manner.     

Studies on engineering properties of PVC–PMMA semi‐interpenetrating polymer networks

Semi1 and semi2 interpenetrating polymer networks (IPNs) of PVC and in situ formed PMMA have been synthesized using diallyl phthalate and ethylene glycol dimethacrylate as the crosslinkers of PVC and PMMA, respectively. These two types of IPNs have been compared w.r.t their physical, mechanical, and thermal properties and an endeavor has been made to find a correlation of these properties with the morphology generated in these systems. The semi1 IPNs displayed a decrease in their mechanical parameters and the physical properties as well, while in contrast, the semi2 IPNs exhibited a marginal increase in the corresponding values after an initial drop upto about 15% of crosslinked PMMA incorporation when compared to the crosslinked PVC in the case of semi1 IPN and linear PVC in the case of semi2 IPN. The various samples of semi1 and semi2 IPNs showed a two‐stage degradation typical of PVC, while confirming the increased stability with the samples having higher percentages of PMMA. The influence of crosslinking of the major matrix in semi1 IPN was almost counterbalanced by the influence of crosslinking in the dispersed PMMA phase in the case of semi2 IPN. The softening characteristics as detected by the extent of penetration of the probe, as has been detected by thermomechanical analysis, are in conformity with their mechanicals. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci 97: 1725–1735, 2005