Dynamic behavioral modeling of nonlinear circuits using a novel recurrent neural network technique

In this paper, a new method called local-global feedback recurrent neural network (LGFRNN) is proposed for dynamic behavioral modeling of nonlinear circuits. The structure of the proposed method is based on recurrent neural network and constructed by time-delayed local and global feedbacks. Adding time-delayed feedbacks has a great impact on the learning capability of previous neural network-based methods. Moreover, time-delayed local feedbacks alleviate the problem of slow convergency of the conventional neural network-based methods in the training phase. The proposed LGFRNN can be trained only by having sampled input-output waveforms of the original circuit without knowing the internal details of the circuit. A training algorithm based on real-time recurrent learning (RTRL) is used to train LGFRNN. After the training phase, the proposed LGFRNN provides accurate macromodel of a nonlinear circuit. The proposed method is more accurate compared with the conventional neural-based models (which do not benefit from time-delayed local-global feedbacks) and also significantly reduces the training time of the conventional models. Moreover, proposed LGFRNN is faster than the existing models in simulation tools. The validity of the proposed method is verified by time-domain modeling of three nonlinear devices including commercial TI's SN74AHCT540 device, five-stage complementary metal-oxide-semiconductor (CMOS) receiver, and commercial TI's LM324 power amplifier.     

Study of the effect of electric field and electroneutrality on transport of biomolecules in microreactors

In this article, the effect of electrophoresis on the transport of a sample (like biomolecules) in active microreactors is numerically investigated. Navier–Stokes equations are solved along with the equations of electrostatics, species mass transport in the buffer, and chemical reaction kinetics at reactive surfaces. Unlike previous studies, in which the effect of the charge of the sample molecules on the electric field has been neglected (i.e., the assumption of electroneutrality), here the space charge density is assumed to be nonzero and a function of biomolecule concentration. As a result, the governing equations become fully coupled. The validity of the assumption is examined against experimental results. Then, the effect of electroneutrality on the efficiency of the microreactor device is analyzed for the parallel plate open channel geometry, commonly used in biomolecule separation. It is shown that the electroneutrality assumption can drastically influence the final adsorbed concentration depending on the device configuration. Average adsorbed surface concentration and capture efficiency are compared as measures of the performance of the device for a wide range of physiochemical parameters. The sensitivity of the simulation with respect to the ionic concentration of the buffer is investigated. It is also discussed how the electric field and nonzero space charge density alter the bulk concentration profile and the velocity field inside the microreactor.     

Surface functionalization of SBA-15 nanorods for anticancer drug delivery

SBA-15 nanorods with high surface area (1010 m² g⁻¹) were functionalized by post grafting method with three different alkoxysilanes including (3-aminopropyl) triethoxysilane (APTES), 3-[bis(2-hydroxyethyl)amino] propyl triethoxysilane (HAPS) and 3-[2-(2-aminoethylamino) ethylamino] propyl trimethoxysilane (AEPS). The prepared materials were used as nanocarriers for an anticancer drug (gemcitabine). The obtained samples were characterized by SAXS, elemental analysis, TGA, N₂ adsorption/desorption, SEM, TEM, FTIR and UV spectroscopies. The adsorption and release properties of all samples were investigated. It was found that the surface functionalization increases the interaction between the carrier and gemcitabine and results in the loading enhancement of the drug. In addition, the adsorption of gemcitabine on the modified mesoporous matrix depends on the type and the amount of alkoxysilanes groups. The maximum content of the deposited drug in the modified SBA-15 nanorods is close to 22 wt.%. The rate of the drug release from the modified samples containing NH₂ groups on their surfaces is pH dependent.     

Evaluation on Properties of CaO-BaO-B2O3-Al2O3-SiO2 Glass-Ceramic Sealants for Intermediate Temperature Solid Oxide Fuel Cells

To develop suitable sealants for intermediate temperature solid oxide fuel cells (IT-SOFC), glasseceramics based on the CaO-BaO-B2O3-Al2O3-SiO2 system were studied. Coefficient of thermal expansion (CTE), glass transition temperature (Tg) and dilatometric softening point temperature (Td) of specimens were determined by means of dilatometer analysis and crystallization temperature was measured by differential thermal analysis (DTA). Also, crystallization behavior during prolonged heat-treatment and microstructure properties were studied by means of X-ray diffraction (XRD) and scanning electron microscopy (SEM), respectively. Electrical properties were measured at different temperatures, and the results showed a high resistance (>10 4Ω) at the SOFC operation temperature (600-800℃). Moreover, mechanical properties of heat-treated specimens (1, 10, 30, 50 h) were measured. Microstructure investigation revealed a well-adhered bonding between the sealant glasseceramic electrolyte and glass.     

Lipoxygenase and hydroperoxide lyase activities in two olive varieties from Northern Italy

Lipoxygenase (LOX) and hydroperoxide lyase (HPL) activities were characterised in olive pulp microsomes from two cultivars (Ghiacciolo and Nostrana di Brisighella) from Northern Italy. LOX activity exhibited a maximum at pH 5.5 in both cultivars, and the highest value was found in cv Ghiacciolo. This was correlated with the higher total antioxidant capacity detected in cv Nostrana, rather than by a different LOX expression, as demonstrated by immunoblotting assay. Furthermore, isomer characterisation showed the predominance of 13‐hydroperoxides of linoleic acid (HPOD) in both cultivars, suggesting the occurrence of a 13‐LOX. HPL activity exhibited an optimum at pH 7.5 in the two cultivars, but was higher in cv Nostrana, as confirmed by the increased amount of hexanal production after 13‐HPOD addition. In addition, the constitutive aldehyde profile in cv Nostrana fruits were shown to be enriched in aldehydes too when compared to cv Ghiacciolo. These results suggest that the different features in the two olive cultivars are mainly due to genetic rather than environmental factors. Practical applications: In this paper we studied the lipoxygenase (LOX) and hydroperoxide lyase (HPL) activities, and the formation of their products (hydroperoxides and aldehydes) in microsomes extracted from olive pulp of two Italian cultivars. The study of LOX and HPL, belonging to the so‐called ‘oxylipin pathway’, has important implications on the aroma development in both fruit and oil. Thus, a better knowledge of the properties of these enzymes can be useful to improve the organoleptic features of the oil. In fact, ‘LOX pathway’ may play a positive role in the formation of pleasant flavours during the technological processes. The preliminary study of the activity of the LOX/HPL enzymes could represent an important tool to facilitate the varietal choice in order to improve oil quality.     

Modeling uncertainties in sodium spatial dispersion using a computational intelligence-based kriging method

Classical and geostatistical methods have been used to create continuous surfaces from sampled data. A common geostatistical method is kriging, which provides an accurate estimation based on the existing spatial structure of sample points. However, kriging is sensitive to errors in the input data, the dispersion of the sample points, and the fit of the model to the variogram. The purpose of this research is to develop a new method to address the uncertainties resulting from the input data and choice of model in the kriging method. In our approach, the existing uncertainties in the input data are modeled by fuzzy computations, and the variogram variables are optimized by a genetic algorithm. To test this new hybrid method, sodium contamination values in the Zanjan aquifer were used. The results show a general improvement in accuracy compared with the ordinary kriging method. Consideration of all equations and values in fuzzy computations highlights the complexity of the computation. Herein, the integration problems experienced by other researchers when trying to use fuzzy kriging are resolved.     

Substance use and the paradox of good and bad attentional bias.

Habitual substance use is associated with attentional bias for stimuli related to the use. The current study tested whether individuals’ substance use can be predicted from their attentional bias for concern-related and substance-related stimuli. Participants (N = 71; 54% male) were selected among university students and the community. The study was conducted in Iran, in which alcohol consumption is illegal. Participants completed a substance use questionnaire and classic, substance-, and concern-related Stroop tests. The results show that after controlling for demographic variables and classic Stroop interference, increases in substance-related but decreases in concern-related reaction times predicted the amount of substances that had been consumed by the participants. Individuals’ attentional bias for both substance-related and substance-unrelated goals may be important in predicting substance use behavior. The implication of the findings for treatment prognosis has been discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Enzymatically modified tea seed oil as cocoa butter replacer in dark chocolate

Cocoa butter replacer (CBR) was prepared by enzymatic interesterification of hydrogenated and solid fraction (SF) of tea seed oil at weight percent ratio of 30:70, using sn‐1,3 specific lipase from Thermomyces lanuginosus. Dark chocolate samples were then prepared with the prepared CBR as a replacement for 5%, 10%, 15% and 20% of cocoa butter (CB) and the effect of the replacement on hardness (as a key quality factor in chocolate) of the chocolate samples was investigated. Results showed that chocolate samples containing 5% and 10% of interesterified sample (EIS), had the closer texture to that of CB chocolate than other samples. The solid fat content (SFC) profiles also revealed that blending 10% of EIS with CB in chocolate formulation dose not affect the sharp melting point of CB. Based on the results taken from bloom formation, polymorphic structure and sensory evaluation, adding up to 10% of EIS in chocolate formulation reduces the bloom development without adverse affecting the desirable β crystal formation and sensory qualities in the chocolate samples.     

Penalized Gaussian mixture probability hypothesis density filter for multiple target tracking

Bayesian multi-target filter develops a theoretical framework for estimating the full multi-target posterior which is intractable in practice. The probability hypothesis density (PHD) is a practical solution for Bayesian multi-target filter which propagates the first order moment of the multi-target posterior instead of the full version. Recently, the Gaussian Mixture PHD (GM-PHD) has been proposed as an implementation of the PHD filter which provides a close form solution. The performance of this filter degrades when targets are moving near each other such as crossing targets. In this paper, we propose a novel approach called penalized GM-PHD (PGM-PHD) filter to improve this drawback. The simulation results provided for various probabilities of detection, clutter rates, targets velocities and frame rates indicate that the proposed method achieves better performance compared to the GM-PHD filter.