Preparation of core–shell type nanoparticles of diblock copolymers of poly(L‐lactide)/poly(ethylene glycol) and their characterization in vitro

Core–shell type nanoparticles of poly(L ‐lactide)/poly(ethylene glycol) (LE) diblock copolymer were prepared by a dialysis technique. Their size was confirmed as 40–70 nm using photon correlation spectroscopy. The ¹H‐NMR analysis confirmed the formation of core–shell type nanoparticles and drug loading. The particle size, drug loading, and drug release rate of the LE nanoparticles were slightly changed by the initial solvents that were used. The drug release behavior of LE core–shell type nanoparticles showed an initial burst during the first 12 h and then a sustained release until 100 h. The degradation behavior of LE block copolymer nanoparticles was divided into three phases: the initial rapid degradation phase, the stationary phase, and the rapid degradation phase until complete degradation. It was suggested that lidocaine release kinetics were predominantly governed by the diffusion mechanism in the initial burst phase and after that by both of the diffusion and degradation mechanisms. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 85: 2625–2634, 2002     

Classification and prediction of the critical heat flux using fuzzy theory and artificial neural networks

A new method to predict the critical heat flux (CHF) is proposed, based on the fuzzy clustering and artificial neural network. The fuzzy clustering classifies the experimental CHF data into a few data clusters (data groups) according to the data characteristics. After classification of the experimental data, the characteristics of the resulting clusters are discussed with emphasis on the distribution of the experimental conditions and physical mechanism. The CHF data in each group are trained in an artificial neural network to predict the CHF. The artificial neural network adjusts the weight so as to minimize the prediction error within the corresponding cluster. Application of the proposed method to the KAIST CHF data bank shows good prediction capability of the CHF, better than other existing methods.     

Deactivation of copper-ion-exchanged hydrogen-mordenite-type zeolite catalyst by SO2 for no reduction by NH3

Deactivation of copper-ion-exchanged hydrogen-mordenite-type zeolite catalyst by SO₂ for NO reduction by NH₃ was examined in a fixed-bed flow reactor. The deactivation of the catalyst was strongly dependent on reaction temperature. At high reaction temperatures over 300°C, the catalyst did not lose its initial activity up to 50 h of operation, regardless of SO₂ feed concentration from 500 to 20,000 ppm. However, at low reaction temperatures near 250°C, apparent deactivation did occur. Changes in the physicochemical properties such as surface area and sulfur content of deactivated catalyst well correlated with catalyst activity, depending upon reaction temperatures. The deactivation was due to pore blocking and/or filling by deactivating agents, which plugged and/or filled the pores of catalyst. The deactivating agents deposited on the catalyst surface were presumed to be (NH₄)₂SO₄ and/or (NH₄)HSO₄ from the results of TGA and ion-chromatography measurement.     

A novel high-efficiency linear transmitter using injection-locked pulsed oscillator

This letter presents a novel high-efficiency linear transmitter using pulse-width modulation (PWM). An envelope of radio frequency (RF) input signal is modulated by the PWM. The modulated signal is applied to the gate bias of a class F injection-locked power oscillator and switches it on and off. By filtering the pulsed oscillating output signal of the injection-locked oscillator using high-Q bandpass filter, the input signal is restored. This technique enables the transmitter to have high efficiency with good linearity. Also, there is little distortion near saturation point of an active device. The measured results show efficiency of 54.6% and very good linearity in PCS band at 26.4-dBm output power.     

A PIN diode controlled variable attenuator using a 0-dB branch-line coupler

We describe a simple PIN diode controlled variable attenuator that employs a 0-dB branch line directional coupler. The response of the attenuator was measured between 1.3 GHz and 2.6 GHz. At the center frequency, the attenuation monotonically varied from 0.7 dB to 23 dB with the control voltage, and the distributed branch-line coupler structure resulted in low input reflection. Our attenuator is easier to design, smaller in area than a double hybrid coupled attenuator, and has comparable or better reflection and attenuation performance characteristics.     

Polyaniline-multiwalled carbon nanotube composites: Characterization by WAXS and TGA

Polyaniline/carboxylated multi-walled carbon nanotube (PAni/c-MWNT) nanocomposites have been synthesized by micellar aided emulsion polymerization with various c-MWNTs compositions, viz., 0.5, 1, 5, and 10 wt %. The microcrystalline parameters such as the nanocrystal size (〈N〉), lattice strain (g), interplanar distance (d_hkl), width of the crystallite size distribution, surface weighted crystal size (D_s), and volume of the ordered regions were calculated from the X-ray data by using two mathematical models, namely the Exponential distribution and Reinhold distribution methods. The effects of heat ageing on the microcrystalline parameters of the PAni/c-MWNT nanocomposites were also studied and the results are correlated. The thermal stability and electrical resistivity of the PAni/c-MWNT nanocomposites were examined with thermogravimetric analysis (TGA) and a conventional two-probe method. The TGA data indicate that the thermal stability of the nanocomposites improved after the incorporation of c-MWNTs. The influence of temperature on the resistivity of the nanocomposites was also measured. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci 2008     

Effects of tube rupture modeling and the parameters on the analysis of multiple steam generator tube rupture event progression in APR1400

A multiple steam generator tube rupture (MSGTR) event in APR1400 has been investigated using the best estimate thermal hydraulic system code, MARS1.4. The effects of the parameters such as the number of ruptured tubes, rupture location, affected steam generator on the analysis of the MSGTR event in APR1400 are examined. In particular, tube rupture modeling methods, single tube modeling (STM) and double tube modeling (DTM), are compared. The APR1400 is found to have the capability of allowing more than 30 min to operators for the MSGTR event of five tubes. The effects of rupture location on the MSSV lift time is not significant in the case of STM, but the MSSV lift time for tube-top rupture is found to be 25.3% larger than that for rupture at the hot-leg side tube sheet in the case of DTM. The MSSV lift time for the cases that both steam generators are affected (4C5x, 4C23x) are found to be larger than that of the single steam generator cases (4A5x, 4B5x) due to a bifurcation of the primary leak flow. The discharge coefficient of Cd is found to affect the MSSV lift time only for a smaller value of 0.5. It is found that the most dominant parameter governing the MSSV lift time is the leak flow rate. Whether any modeling method is used, it gives the similar MSSV lift time if the leak flow rate is close, except in the case where both steam generators are affected. Therefore, the system performance and the MSSV lift time of the APR1400 are strongly dependent on the break flow model used in the best estimate system code.     

Reasoning about non-immediate triggers in biological networks

Modeling molecular interactions in signalling networks is important from various perspectives such as predicting side effects of drugs, explaining unusual cellular behavior and drug and therapy design. Various formal languages have been proposed for representing and reasoning about molecular interactions. The interactions are modeled as triggered events in most of the approaches. The triggering of events is assumed to be immediate: once an interaction is triggered, it should occur immediately. Although working well for engineering systems, this assumption poses a serious problem in modeling biological systems. Our knowledge about biological systems is inherently incomplete, thus molecular interactions are constantly elaborated and refined at different granularity of abstraction. The model of immediate triggers can not consistently deal with this refinement. In this paper we propose an action language to address this problem. We show that the language allows for refinements of biological knowledge, although at a higher cost in terms of complexity.