Earticle

Distributed Bragg reflector porous silicon of different characteristics were formed to determine their optical constants in the visible wavelength range using a periodic square wave current between low and high current densities. The surface and cross-sectional SEM images of distributed Bragg reflector porous silicon were obtained using a cold field emission scanning electron microscope. The surface image of distributed Bragg reflector porous silicon indicates that the distributions of pores are even. The cross-sectional image illustrates that the multilayer of distributed Bragg reflector porous silicon exhibits a depth of few microns and applying of square current density during the etching process results two distinct refractive indices in the contrast. Distributed Bragg reflector porous silicon exhibited a porosity depth profile that related directly to the current-time profile used in etch. Its free-standing film was obtained by applying an electropolishing current.

A study that copolymerized Ag nanoparticle and furfuryl isocyanate with the crosslinking agent EGDMA (ethylene glycol dimethacrylate), HEMA (2-hydroxyethyl methacrylate), MMA (methyl methacrylate), MA (methacrylic acid) and the initiating agent AIBN (azobisisobutyronitrile) is presented. Measurement of the physical characteristics of the produced macromolecule showed that the water content is 32.08~32.67%, refractive index 1.446~1.448, visible light transparency 83.2~67.6%, contact angle 68.2~83.5o and tensile strength 0.541~0.755 kgf. It is also demonstrated that the addition of Ag nanoparticles is associated with the reduction of UV-B transmittance and increase in tensile strength. The results show that the produced copolymer can be used as a material for ophthalmic lenses with durability and UV -blocking properties.

Formation of amyloid-β (Aβ) aggregates is a core process in the pathogenesis of Alzheimer’s disease. Importance of interaction of the length variants, Aβ42 and Aβ40 in the process and consequent cytotoxicity has been pointed out for wild-type Aβ previously. In addition to confirming the findings, the current study demonstrates that the potential interaction is also important for cytotoxicity of the Flemish and Dutch sequence variants. The interaction could strengthen or inhibit cytotoxicity of Aβ42/Aβ40 mixture, depending on interaction time of the length variants as well as the ratio and amyloidogenic property. The inhibitory effect was prominent at the early stage of aggregate formation in less amyloidogenic Flemish Aβ42/Aβ40 mixture, while strengthened cytotoxicity was exhibited at the stage in potently amyloidogenic Dutch variant and at the later stage in wild-type and the Flemish variant. The samples showing relatively robust cytotoxicity were those enriched in Aβ protofibril-like structures, implying strong correlation of the structure with cytotoxicity. The different consequence of the interaction on sequence variants is likely due to differential amyloidogenic property of each Aβ40 variant, rather than that of Aβ42, because aggregation rates and levels of Aβ40 variants are greatly variable depending on the sequence, compared to Aβ42 variants. These studies may highlight a potential role of Aβ40 in the cytotoxicity, providing a novel mechanistic insight into the pathogenesis of each FAD- associated variant.

Amyloid-β-peptide (Aβ) is important in the pathogenesis of Alzheimer’s disease (AD). Calpain (Ca2+ -dependent protease) and caspase-8 (the initiating caspase for the extrinsic, receptor-mediated apoptosis pathway) have been implicated in AD/Aβ toxicity. We found that Aβ promoted degradation of calpastatin (the specific endogenous calpain inhibitor); calpastatin degradation was prevented by inhibitors of either calpain or caspase-8. The results implied a cross-talk between the two proteases and suggested that one protease was responsible for the activity of the other one. In neuron-like differentiated PC12 cells, calpain promotes active caspase-8 formation from procaspase-8 via the Aβ and CD95 pathways, along with degradation of the procaspase-8 processing inhibitor caspase-8 (FLICE)-like inhibitory protein, short isoform (FLIPS). Inhibition of calpain (by pharmacological inhibitors and by overexpression of calpastatin) prevents the cleavage of procaspase-8 to mature, active caspase-8, and inhibits FLIPS degradation in the Aβ-treated and CD95-triggered cells. Increased cellular Ca2+ per se results in calpain activation but does not lead to caspase-8 activation or FLIPS degradation. The results suggest that procaspase-8 and FLIPS association with cell membrane receptor complexes is required for calpain-induced caspase-8 activation. The results presented here add to the understanding of the roles of calpain, caspase- 8, and CD95 pathway in AD/Aβ toxicity. Calpain-promoted activation of caspase-8 may have implications for other types of CD95-induced cell damage, and for nonapoptotic functions of caspase-8. Inhibition of calpain may be useful for modulating certain caspase-8-dependent processes.

The results of the synoptic meteorological analysis showed that when the cold and dry continental high pressure was extended, heavy snow occurred at dawn when the upper atmosphere cooled. In particular, when the continental high pressure was extended and the upper pressure trough passed through, heavy snow occurred due to the convergence region formed in the west coast area, sometimes in the inland of the Honam area. In addition, it was verified that the changes in the humidity coefficients in the upper and lower layers are important data for the determination of the probability, start/ end and intensity of heavy snow. However, when the area was influenced by the middle-latitude low pressure, the heavy snow was influenced by the wind in the lower layer (925 hPa and 850 hPa), the equivalent potential temperature, the convergence field, the moisture convergence and the topography. In Case 2010 (30 December 2010), OSTIA had the best numerical simulation with diverse atmospheric conditions, and the maximum difference in the numerically simulated snowfall between NCEP/NCAR SST and OSTIA was 20 cm. Although there was a regional difference in the snowfall according to the difference in the SST, OSTIA and RTG SST numerical tests, it was not as significant as in the previous results. A higher SST led to the numerical simulation of larger snowfall, and the difference was greatest near Buan in the west coast area.

The (c-Jun N-terminal kinase 3) JNK3 is a potential therapeutic target for various neurological disorders. Here, a three dimensional quantitative structure–activity relationship (3D-QSAR) study on phenoxypyridine as JNK3 inhibitors was performed to rationalize the structural requirements responsible for the inhibitory activity of these compounds. The comparative molecular field analysis (CoMFA) using different partial atomic charges, was employed to understand the structural factors affecting JNK3 inhibitory potency. The Gasteiger-Marsili yielded a CoMFA model with cross-validated correlation coefficient (q2) of 0.54 and non-cross-validated correlation coefficient (r2) of 0.93 with five components. Furthermore, contour maps suggested that bulky substitution with oxygen atom in R3 position could enhance the activity considerably. The work suggests that further chemical modifications of the compounds could lead to enhanced activity and could assist in the design of novel JNK3 inhibitors.

To explore effects on each the emotional awareness, emotional expression, emotional empathy, and emotional regulation, of the sub-factors of the child's emotional intelligence, to mural preference, emotion cultivation, and community connection, the hierarchical multiple regression analyses are performed(as in Table 1, 2, and 3). As the results, we found the following facts. Children's mural preference, emotion cultivation, and community connection were expressed by the following equations in order, respectively. Mural Preference = .170×[Emotional Awareness] (t=2.118, p=.036*) − .025×[Emotional Expression](t=-.275, p=.783) + .088×[Emotional Empathy](t=.938, p=.350) + .139× [Emotional Regulation] (t=1.529, p=.128). Mural Emotion Cultivation = -.021×[Emotional Awareness](t=-.294, p=.769) − .205× [Emotional Expression]( t=-2.573, p=.011*) + .265×[Emotional Empathy](t=3.156, p=.002*) + .192×[Emotional Regulation] (t=2.361, p=.019*). Mural Community Connection = −.001×[Emotional Awareness](t=-.007, p=.995) − .132×[Emotional Expression](t=-1.478, p=.141) + .172×[Emotional Empathy](t=1.732, p=.027*) + .098×[Emotional Regulation](t=1.072, p=.285).

This study measured the stream data from the several sensors, and stores the database in MapReduce framework environment, and it aims to design system with the small performance and cluster analysis error rate through the KMSVM algorithm. Through the KM-SVM algorithm, the cluster analysis effective data was used for U-health system. In the results of experiment by using 2003 data sets obtained from 52 test subjects, the k-NN algorithm showed 79.29% cluster analysis accuracy, K-means algorithm showed 87.15 cluster analysis accuracy, and SVM algorithm showed 83.72%, KM-SVM showed 90.72%. As a result, the process speed and cluster analysis effective ratio of KM- SVM algorithm was better.

This study aims to implement the emergency monitoring robot system which predicts the current state of the patients without visiting the medical institutions by measuring the basic health status of the user's blood pressure, heartbeat, and basic health status of body temperature in the disaster emergency situation based on the Smart Grid. By arranging a large number of sensor(blood pressure, heartbeat, body temperature sensor) and measuring the bio signs, so the attached wireless XBee sensor can be stored in DB of robot, and it aims to draw the current state of the patients by analysis of stored bio data. Among 300 data obtained from the sensor, 1st data to 100th data were used for learning, and from 101st data to 300th data were used for assessment. 12 results were different among the total 300 assessment data, so it shows about 96% accuracy.

We consider the mean value function for NHPP software reliability model and time series regression model in software failure data. We estimate parameters for the proposed models from two data sets. The values of SSE and MSE is presented from two data sets. We compare the predicted number of faults with the actual two data sets using the mean value function and regression curve.