Characterization of coil coatings by thermal analysis

The interrelationship between the network formation process and performance properties makes cure process studies critically important in the coil‐coating industry. The objective of this work was to introduce thermal analysis into the evaluation of curing of uncured samples and in studies of the glass‐transition temperatures of cured samples. Thermal analysis, dynamic mechanical analysis (DMA), and differential scanning calorimetry (DSC) were used to characterize gelation and curing of three types of samples: paints, coated sheets, and free films. In addition to the generally used three‐point‐bending and extension geometries, a cup‐and‐plate geometry also was used in analyzing gelation and curing of liquid samples. These thermal analyses are suited to the purpose of characterizing coil coatings. A correlation between PMT (peak metal temperature) and measured T_g (glass‐transition temperature) was found, as well as effectively distinguishing different curing conditions. © 2003 Wiley Periodicals, Inc. J Appl Polym Sci 87: 2016–2022, 2003     

Monitoring the autonomic nervous system in the ICU throughcardiovascular variability signals

Studies the usefulness of cardiovascular variability parameters for monitoring intensive-care unit (ICU) patients, and discusses assessing ICU patient status using spectral analysis parameters. Both short-term and long-term spectral parameters were employed for the assessment of patient status in the ICU. Short-term parameters were sensitive to the airway suction (AWS) and may also be employed to monitor the response to different therapeutic interventions. Long-term parameters showed significantly increased α-slope values in nonsurviving patients. This result suggests that the α-slope value on 24-hour RR spectra obtained from the ECG signal may be a relevant prognostic index     

Differential Expression of Inflammasome-Related Genes in Induced Pluripotent Stem-Cell-Derived Retinal Pigment Epithelial Cells with or without History of Age-Related Macular Degeneration

Inflammation is a key underlying factor of age-related macular degeneration (AMD) and inflammasome activation has been linked to disease development. Induced pluripotent stem-cell-derived retinal pigment epithelial cells (iPSC-RPE) are an attractive novel model system that can help to further elucidate disease pathways of this complex disease. Here, we analyzed the effect of dysfunctional protein clearance on inflammation and inflammasome activation in iPSC-RPE cells generated from a patient suffering from age-related macular degeneration (AMD) and an age-matched control. We primed iPSC-RPE cells with IL-1α and then inhibited both proteasomal degradation and autophagic clearance using MG-132 and bafilomycin A1, respectively, causing inflammasome activation. Subsequently, we determined cell viability, analyzed the expression levels of inflammasome-related genes using a PCR array, and measured the levels of pro-inflammatory cytokines IL-1β, IL-6, IL-8, and MCP-1 secreted into the medium. Cell treatments modified the expression of 48 inflammasome-related genes and increased the secretion of mature IL-1β, while reducing the levels of IL-6 and MCP-1. Interestingly, iPSC-RPE from an AMD donor secreted more IL-1β and expressed more Hsp90 prior to the inhibition of protein clearance, while MCP-1 and IL-6 were reduced at both protein and mRNA levels. Overall, our results suggest that cellular clearance mechanisms might already be dysfunctional, and the inflammasome activated, in cells with a disease origin.     

Computational and experimental study of an industrial centrifugal compressor volute

IntrotctionThe overall performance of a centrifugal compressoris a combination of the dueller, diffuser, and voluteperformances. Each component has to be designedcarefully in order tO' minimize the losses and maximizethe efficiency. In this paper, a centrifugal compressorvolute (or spiral) is stUdied numerically, and the CFDresults are compared with measured data.A volute is used to collect the flow from a vaned orvaneless diffuser and to gUide it Ollt of the compressor.The volute geometry…     

Angiotensin I converting enzyme (ACE) inhibitory activity and antihypertensive effect of fermented milk

Milk was fermented with a total of 25 lactic acid bacteria to assay in vitro inhibitory activity towards angiotensin I converting enzyme (ACE). The tested strains belonged to Lactobacillus acidophilus, Lactobacillus casei, Lacobacillus helveticus, Lactobacillus jensenii, Lactobacillus reuteri, Lactobacillus rhamnosus, Lactococcus lactis ssp. lactis, Lactococcus. raffinolactis and Leuconostoc mesenteroides ssp. cremoris. The ACE inhibitory potencies of theses strains varied and seven of them showing the highest ACE inhibitory activity were selected for further studies. The development of ACE inhibitory activity during fermentation correlated with degree of hydrolysis. Modification of fermentation conditions or pH control did not affect the ACE inhibitory activity. ACE inhibitory compounds from Lb. jensenii fermented milk were isolated by reversed phase HPLC and identified by MS-analysis and amino acid sequencing. The active compounds were peptides from β-casein. The milk fermented with Lb. jensenii caused a transient reduction of blood pressure in spontaneously hypertensive rats.     

一种新的RFID传感网络中多阅读器防碰撞协议

阅读器碰撞问题(RCP)是影响射频识别(RFID)系统读取效率的关键问题。提出了一种新的解决阅读器碰撞问题的协议——DREAM协议。新协议根据阅读器间的信号干扰情况在多个阅读器中动态产生若干个临时的控制中心作为簇首,合理安排各个阅读器的读取顺序,完全避免了阅读器间的信息碰撞。理论和仿真结果表明DREAM协议相对于现有性能较优的PULSE协议,在极大地提高系统读取效率的同时,大大地节省了阅读器的功率消耗。     

Modelling lidar-derived boreal forest canopy cover with SPOT 4 HRVIR data

Forest canopy cover (C) is needed in forest area monitoring and for many ecological models. Airborne scanning lidar sensors can produce fairly accurate C estimates even without field training data. However, optical satellite images are more cost-efficient for large area inventories. Our objective was to use airborne lidar data to obtain accurate estimates of C for a set of sample plots in a boreal forest and to generalize C for a large area using a satellite image. The normalized difference vegetation index (NDVI) and reduced simple ratio (RSR) were calculated from the satellite image and used as predictors in the regressions. RSR, which combines information from the red, near-infrared, and shortwave infrared bands, provided the best performance in terms of absolute root mean square error (RMSE) (7.3%) in the training data. NDVI produced a markedly larger RMSE (10.0%). However, in an independent validation data set, RMSE increased (13.0–17.1%) because the systematic sample of validation plots contained more variation than the training plots. Our results are better than those reported earlier, which is probably explained by more consistent C estimates derived from the lidar. Our approach provides an efficient method for creating C maps for large areas.