Properties of nanoporous organosilicate hybrid thin films with a bimodal pore size distribution

Low dielectric poly[methylsilsesquioxane‐ran‐trifluoropropylsilsesquioxane‐ran‐(2,4,6,8‐tetramethyl‐2,4,6,8‐tetraethylenecyclotetrasiloxane)silsesquioxane]s {P[M‐ran‐TFP‐ran‐(TCS)]SSQs} having various compositions were synthesized using trifluoropropyl trimethoxysilane, methyl trimethoxysilane and 2,4,6,8‐tetramethyl‐2,4,6,8‐tetra(trimethoxysilylethyl)cyclotetrasiloxane. The chemical composition of the polymers and the content of SiOH end‐groups were controlled by adjusting the reaction conditions, and they were characterized by ¹H‐NMR. The thermally decomposable trifluoropropyl groups on the P[M‐ran‐TFP‐ran‐(TCS)]SSQ backbone and heptakis(2,3,6‐tri‐O‐methyl)‐β‐cyclodextrin (CD) were employed as pore generators. The dielectric constants of the porous CD/P[M‐ran‐TFP‐ran‐(TCS)]SSQ films were in the range 2.0–2.7 (at 100 kHz) depending on the concentration of the porogens, and showed no change over 4 days under aqueous conditions. The pore size of the films showed a bimodal distribution, with diameters of ca 0.5–1.0 nm for those originating from the trifluoropropyl groups and 1.7 nm from the CD. The elastic modulus and hardness of the 30 vol% CD‐blended film with a dielectric constant of 2.26 were 2.40 and 0.38 GPa, respectively, as determined by a nanoindenter. Copyright © 2005 Society of Chemical Industry     

Application of artificial neural networks to the analysis of two‐dimensional fluorescence spectra in recombinant E coli fermentation processes

A two‐dimensional (2D) spectrofluorometer was used to monitor various fermentation processes with recombinant E coli for the production of 5‐aminolevulinic acid (ALA). The whole fluorescence spectral data obtained during a process were analyzed using artificial neural networks, ie self‐organizing map (SOM) and feedforward backpropagation neural network (BPNN). The SOM‐based classification of the whole spectral data has made it possible to qualitatively associate some process parameters with the normalized weights and variances, and to select some useful combinations of excitation and emission wavelengths. Based on the classified fluorescence spectra a supervised BPNN algorithm was used to predict some of the process parameters. It was also shown that the BPNN models could elucidate some sections of the process's performance, eg forecasting the process's performance. Copyright © 2005 Society of Chemical Industry     

A parallel image encryption method based on compressive sensing

Recently, compressive sensing-based encryption methods which combine sampling, compression and encryption together have been proposed. However, since the quantized measurement data obtained from linear dimension reduction projection directly serve as the encrypted image, the existing compressive sensing-based encryption methods fail to resist against the chosen-plaintext attack. To enhance the security, a block cipher structure consisting of scrambling, mixing, S-box and chaotic lattice XOR is designed to further encrypt the quantized measurement data. In particular, the proposed method works efficiently in the parallel computing environment. Moreover, a communication unit exchanges data among the multiple processors without collision. This collision-free property is equivalent to optimal diffusion. The experimental results demonstrate that the proposed encryption method not only achieves the remarkable confusion, diffusion and sensitivity but also outperforms the existing parallel image encryption methods with respect to the compressibility and the encryption speed.     

A modular algorithm for resource allocation

This paper concerns resource allocation in distributed message passing systems, i.e., the scheduling of accesses to exclusive system resources shared among concurrent processes. An efficient modular resource allocation algorithm is presented that uses any arbitrary resource allocation algorithm as a subroutine. It improves the performance of the subroutine by letting each process wait only for its currently conflicting processes, and therefore, allows more concurrency. For appropriate choices of the subroutine, we obtain resource allocation algorithms with the minimum worst case response times. Simulation studies were conducted which also indicate that on average, the obtained algorithms perform faster and require a smaller number of messages than other previously known algorithms, especially when resource contention among processes is high and the average time that a process remains in the critical region is large. Received: May 1997 / Accepted: May 1998     

Pulsed Electromagnetic Field (PEMF) Treatment Reduces Lipopolysaccharide-Induced Septic Shock in Mice

Despite advances in medicine, mortality due to sepsis has not decreased. Pulsed electromagnetic field (PEMF) therapy is emerging as an alternative treatment in many inflammation-related diseases. However, there are few studies on the application of PEMF therapy to sepsis. In the current study, we examined the effect of PEMF therapy on a mouse model of lipopolysaccharide (LPS)-induced septic shock. Mice injected with LPS and treated with PEMF showed higher survival rates compared with the LPS group. The increased survival was correlated with decreased levels of pro-inflammatory cytokine mRNA expression and lower serum nitric oxide levels and nitric oxide synthase 2 mRNA expression in the liver compared with the LPS group. In the PEMF + LPS group, there was less organ damage in the liver, lungs, spleen, and kidneys compared to the LPS group. To identify potential gene targets of PEMF treatment, microarray analysis was performed, and the results showed that 136 genes were up-regulated, and 267 genes were down-regulated in the PEMF + LPS group compared to the LPS group. These results suggest that PEMF treatment can dramatically decrease septic shock through the reduction of pro-inflammatory cytokine gene expression. In a clinical setting, PEMF may provide a beneficial effect for patients with bacteria-induced sepsis and reduce septic shock-induced mortality.     

Isolation and Characterization of Urinary Extracellular Vesicles from Healthy Donors and Patients with Castration-Resistant Prostate Cancer

Prostate cancer (PCa) is the most commonly diagnosed malignancy among men in developed countries. The five-year survival rate for men diagnosed with early-stage PCa is approximately 100%, while it is less than 30% for castration-resistant PCa (CRPC). Currently, the detection of prostate-specific antigens as biomarkers for the prognosis of CRPC is criticized because of its low accuracy, high invasiveness, and high false-positive rate. Therefore, it is important to identify new biomarkers for prediction of CRPC progression. Extracellular vesicles (EVs) derived from tumors have been highlighted as potential markers for cancer diagnosis and prognosis. Specifically, urinary EVs directly reflect changes in the pathophysiological conditions of the urogenital system because it is exposed to prostatic secretions. Thus, detecting biomarkers in urinary EVs provides a promising approach for performing an accurate and non-invasive liquid biopsy for CPRC. In this study, we effectively isolated urinary EVs with low protein impurities using size-exclusion chromatography combined with ultrafiltration. After EV isolation and characterization, we evaluated the miRNAs in urinary EVs from healthy donors and patients with CRPC. The results indicated that miRNAs (miR-21-5p, miR-574-3p, and miR-6880-5p) could be used as potential biomarkers for the prognosis of CRPC. This analysis of urinary EVs contributes to the fast and convenient prognosis of diseases, including CRPC, in the clinical setting.     

High temperature wear of semimetallic disc brake pads

The wear of friction materials as measured by isothermal techniques remains insensitive to temperature to about 230°C (drum) and increases exponentially at higher temperatures. The high temperature wear of organic friction materials was found to be related to the thermal decomposition of the organic ingredients with an activation energy of 4–10 kcal mol^?1. The results indicate that high temperature wear of semimetallic friction materials is controlled by thermal degradation of organic ingredients as it is for organic friction materials.     

Threshold voltage instability characteristics of HfO2 dielectrics n-MOSFETs

In this paper, the threshold voltage instability characteristics of HfO₂ high-k dielectric are discussed. The results from various stress bias conditions including DC and AC with variations of frequency, duty cycle, and polarity provide additional insights into the intrinsic behavior and the trapping dynamics of high-k materials. A reduced threshold voltage shift was observed at higher frequency and lower duty cycle under AC positive unipolar stress compared to DC stress. Similarly, the degradation of maximum transconductance was also reduced with AC stress. However, subthreshold swing changes were found to be negligible and fairly independent of stress frequencies and duty cycles under AC positive unipolar stress.When different polarity of stress, such as positive, negative, and bipolar stress was applied, it was observed that frequency and duty cycle dependencies were still valid in all three conditions. In contrast to positive stress, negative stress showed a decrease in the threshold voltage shift. Bipolar stress resulted in the highest threshold voltage instability, but the degradation in transconductance and subthreshold swing was actually smaller than those in negative unipolar stress. The bulk trap of HfO₂ dielectric, which is proportional to its physical thickness, is believed to be the primary factor for threshold voltage shift. AC unipolar operation would allow a higher 10-year lifetime operating voltage than the DC condition. In addition to experimental results, a plausible mechanism has been proposed.     

Analysis of PLR for Shared Switch Fabrics

A modular upgrade design for packet transport switch nodes is presented where packet loss is dramatically reduced by intra‐module and inter‐module buffer sharing. This modular design offers significant cost and power reduction in a high‐data‐rate system where buffers are highly costly and power‐greedy.     

Synthesis,characterization and application of biopolymer-ionic liquid composite membranes

Biopolymer composite membranes based on chitosan doped with an ionic liquid (IL) 1-ethyl 3-methylimidazolium thiocyanate (EMImSCN) have been developed and characterized. The doped ionic liquid films show remarkable enhancement in ionic conductivity (σ). The Fourier transform infrared (FTIR) spectroscopy, atomic force microscopy (AFM) and X-ray diffraction studies (XRD) affirmed the composite nature, good incorporation of ionic liquid and reduction in crystallinity of films, respectively. The interaction between ionic liquid, chitosan and iodide polymer electrolyte matrix was evaluated by cyclic voltammetry. The fabricated dye sensitized solar cell (DSSC) using this new biopolymer electrolyte membranes shows promising performance.