Stability enhancement of polypyrrole thin film ammonia sensor by camphor sulfonic acid dopant

Journal of Materials Science: Materials in Electronics - The main weakness of polymer gas sensors is its stability. Here, we report stability enhancement of a 100 nm polypyrrole (PPy) thin...     

An Approximate Model of Multistage Automatic Transfer Lines with Possible Scrapping Of Workpieces

We consider multistage automatic transfer lines with unreliable stages, finite interstage buffer storages, and possible scrapping of workpieces. It is assumed that the first stage never idles and the last stage never becomes blocked. Assuming that uptimes and downtimes of a stage are geometrically distributed, an approximate model is developed to compute different performance measures of the transfer line. The results obtained through the approximate model are compared to the exact results for three-stage transfer lines and to simulation results for longer transfer lines. It is observed that the approximate results are good in almost all cases considered.     

The sinuous antenna-A dual polarized feed for reflector-based searching systems

The sinuous antennas have a numerous applications in military and civil systems such as direction finding systems and reflector feeds due to their superior broadband characteristics and simultaneous polarization capability. In this paper, design, construction and measurements of planar sinuous antennas are investigated for 1–5 GHz frequency range. Feeding sections of this antenna are realized by using microstrip tapered baluns. We have determined the microstrip tapered balun dimensions using Ansoft HFSS-simulation program. The performances of the manufactured antenna are measured using HP vector network analyzer. Polarization patterns and return loss characteristics of the designed antenna that have been measured in anechoic chamber, are presented.     

Signature analysis and defect detection in layered manufacturing of ceramic sensors and actuators

This paper presents the concept of a process signature for the use of online signature analysis and defect detection in the layered manufacturing (LM) of ceramic sensors and actuators. To achieve the high quality of parts built by the fused deposition of ceramics (FDC), an online process-monitoring system is implemented to detect the processing defects. Using a process signature extracted from the image of a layer captured by the monitoring system, an ideal image is created that is then compared to the original image to detect and identify the defects. Some results of signature analysis and defect detection for single-material and multi-material parts are also presented.Received: 22 July 1999, Accepted: 21 October 2001, Published online: 29 October 2003 Correspondence to: Mohsen A. JafariThis work was supported by the Office of Naval Research under grant # N-0014-96-1-1175. Ref. US Patent # S-5738817, April 14, 1998.     

Thermal modeling in cylindrical coordinates using effective conductivity

Predictive thermometry, utilizing minimally invasive sampling techniques, is an essential ingredient in the development of hyperthermia treatment planning capabilities. The authors demonstrate a powerful, but simple approach toward predicting temperature distributions in tissues, based on analytic solution, using in cylindrical symmetry, of the heat diffusion equation. Conduction and localized perfusion effects are combined as an effective conductivity term, readily measurable, and parametrized in a general exponential form. The proposed approach allows a first-order approximation to modeling three typical situations: hypoxic or necrotic tumor core with homogeneously perfused periphery; highly perfused periphery (in rapidly growing tumors); or perfused central cover with a less well-supplied periphery (such as for some invasive tumors). The utility and strength of this approach is that it provides a rapid, accurate model of directly observing the technical quality to be expected for different heating methods, making it possible to optimally configure source distributions in a treatment planning setting.     

Supplementing with L-Tryptophan Increases Medium Protein and Alters Expression of Genes and Proteins Involved in Milk Protein Synthesis and Energy Metabolism in Bovine Mammary Cells

The objective of this study was to investigate the effects of supplementing with L-tryptophan (L-Trp) on milk protein synthesis using an immortalized bovine mammary epithelial (MAC-T) cell line. Cells were treated with 0, 0.3, 0.6, 0.9, 1.2, and 1.5 mM of supplemental L-Trp, and the most efficient time for protein synthesis was determined by measuring cell, medium, and total protein at 0, 24, 48, 72, and 96 h. Time and dose tests showed that the 48 h incubation time and a 0.9 mM dose of L-Trp were the optimal values. The mechanism of milk protein synthesis was elucidated through proteomic analysis to identify the metabolic pathway involved. When L-Trp was supplemented, extracellular protein (medium protein) reached its peak at 48 h, whereas intracellular cell protein reached its peak at 96 h with all L-Trp doses. β-casein mRNA gene expression and genes related to milk protein synthesis, such as mammalian target of rapamycin (mTOR) and ribosomal protein 6 (RPS6) genes, were also stimulated (p < 0.05). Overall, there were 51 upregulated and 59 downregulated proteins, many of which are involved in protein synthesis. The results of protein pathway analysis showed that L-Trp stimulated glycolysis, the pentose phosphate pathway, and ATP synthesis, which are pathways involved in energy metabolism. Together, these results demonstrate that L-Trp supplementation, particularly at 0.9 mM, is an effective stimulus in β-casein synthesis by stimulating genes, proteins, and pathways related to protein and energy metabolism.     

Compatibilizing Effects on the Phase Morphology and Thermal Properties of Polymer Blends Based on PTT and m-LLDPE

Summary Morphology and thermal characteristics of poly (trimethylene terephthalate) (PTT)/ metallocene linear low-density polyethylene (m-LLDPE) blends with different amounts of a terpolymer based on glycidyl methacrylate (GMA), employed as a possible compatibilizer, were systematically examined. DMTA results show two distinct peaks for all neat blends associated with each phase. Melt crystallization degree of both phases in all the blends was observed to be reduced compared to pure components, except for that of PTT-rich phase in those blends with PTT as the matrix which slightly increases. Addition of the terpolymer to the system is found to effectively reduce the droplet size of the dispersed phase and increase phase adhesion. Also it increases the crystallinity of PTT in the system with PTT as the matrix. The influence of the compatibilizer is ascribed to the chemical interaction of PTT functional end groups with GMA functionalities. The efficiency of the terpolymer as a compatibilizer beyond 5 wt% content decreases which can be ascribed to the interface saturation and formation of micelles in the bulk phases.     

Bayesian estimation of Dirichlet mixture model with variational inference

In statistical modeling, parameter estimation is an essential and challengeable task. Estimation of the parameters in the Dirichlet mixture model (DMM) is analytically intractable, due to the integral expressions of the gamma function and its corresponding derivatives. We introduce a Bayesian estimation strategy to estimate the posterior distribution of the parameters in DMM. By assuming the gamma distribution as the prior to each parameter, we approximate both the prior and the posterior distribution of the parameters with a product of several mutually independent gamma distributions. The extended factorized approximation method is applied to introduce a single lower-bound to the variational objective function and an analytically tractable estimation solution is derived. Moreover, there is only one function that is maximized during iterations and, therefore, the convergence of the proposed algorithm is theoretically guaranteed. With synthesized data, the proposed method shows the advantages over the EM-based method and the previously proposed Bayesian estimation method. With two important multimedia signal processing applications, the good performance of the proposed Bayesian estimation method is demonstrated.     

CFD simulation and evaluation of controllable parameters effect on thermomagnetic convection in ferrofluids using Taguchi technique

In the present attempt a CFD simulation capable of coupling behaviors from the nano-scale through the full-scale system in which a ferrofluid containing magnetite particles suspended in kerosene carrier liquid is presented. The main objective of the work was to simulate the thermodiffusion and also to evaluate the factors influence on this phenomenon in a cylindrical geometry. In simulations a two-phase mixture model was used to predict the behavior of the system. To optimize the thermomagnetic effect, different parameters including temperature difference across the layer, initial magnetic phase concentration, aspect ratio of the geometry, magnetic field magnitude and diameter of magnetic particles were examined using L₁₆ orthogonal array of Taguchi at four levels. Analysis of the simulation data indicate that the magnetic Soret effect can even be higher than the conventional one and its strength depends on the magnetic field strength, confirmed experimentally by Völker and Odenbach [Völker T, Odenbach S. Thermodiffusion in magnetic fluids. J Magn Magn Mater 2005;289:289-91]. The statistic evaluation shows that temperature and initial concentration of magnetic phase have the maximum and minimum contribution on the thermodiffusion, respectively. According to the results temperature difference 80 K, initial concentration of magnetic phase 0.08, aspect ratio 0.2, magnetic field strength 100 kA/m and magnetic particles diameter 100 nm were obtained as optimum conditions in the presence of natural convection. The same result was gained in the lack of natural convection except the magnetic field strength was 160 kA/m. Finally, based on the primary results, a verification test was also performed to confirm the validity of the used statistical method.     

Energy and load balancing routing protocol for IoT

Due to the limitation of node energy resources, the management of energy consumption is one of the most important problems of the internet of things (IoT). Therefore, many studies have tried to optimize and manage energy consumption by focusing on different techniques. Although each of these studies has improved and optimized energy consumption, there are many important problems, including maintaining traffic balance and energy consumption of network nodes. Therefore, a new method is necessary to maintain the load and energy balancing of network nodes. Therefore, this paper introduces energy and load balancing routing protocol for IoT (ELBRP) based on the development of the RPL routing protocol and the efficiency of data distribution technique. The ELBRP performance has three steps. In the first step, along with the process of sending DODAG information object (DIO) messages, the status of network nodes is evaluated. In the second step, the DODAG communication graph is formed according to the ELBRP. In the third step, data transmission is done according to the distribution technique with the goal of balancing traffic and energy. The simulation results using cooja simulator showed the superiority of ELBRP in improving energy consumption and successful delivery ratio, reducing delay and increasing the network lifetime compared to the similar methods.