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.     

Pulmonary infiltrates in neutropenic patients with acute leukemia during chemotherapy: outcome and prognostic factors

STUDY OBJECTIVE: To determine predictors of mortality from pulmonary infiltrates in neutropenic patients with acute leukemia during chemotherapy, and the significance of those factors related to the underlying malignancy and its therapy as well as of those related to the severity of the illness associated with pulmonary infiltrates. DESIGN: A historical cohort study. SETTING: A university teaching hospital and tertiary referral center. PATIENTS AND METHODS: Overall, 53 patients with neutropenia during chemotherapy and with first episodes of pulmonary infiltrates during a 4-year period were studied. Prognostic analysis included 38 variables. Multivariate analyses were performed by logistic regression. RESULTS: The survival rate from pneumonia was 57% (30/53). The following eight parameters were significantly associated with death in univariate analysis: comorbidity present; development of "late" pulmonary infiltrates (> or = 14 days after hospital admission); heart rate > or = 100 beats/min; a ratio heart rate/systolic blood pressure (HR/SBP) > or = 1.2; urea nitrogen > 7 mmol/L; radiographic score > or = 3; neutropenia < 1.0x10(9)/L at the treatment end point; and failed complete remission. In a multivariate model including only parameters available at diagnosis of pulmonary infiltrates, the presence of a ratio HR/SBP > or = 1.2 and of a radiographic score > or = 3 remained independently associated with death. In a second model also including the evolutionary parameter neutropenia < or = 1.0x10(9)/L at the treatment end point, both parameters remained significant together with neutropenia <1.0x 10(9)/L at the treatment end point. The presence of a ratio HR/SBP > or = 1.2 was a strong marker of early death. CONCLUSION: Both therapy- and malignancy-associated neutropenia as well as the severity of illness associated with pulmonary infiltrates are independent prognostic factors. Patients with a ratio HR/SBP > or = 1.2 at diagnosis of pulmonary infiltrates suffer from potentially reversible acute illness, are at risk for early death and, therefore, may be appropriate candidates for treatment in an ICU.     

Grafting of enzymes on collagen films using Woodward''s reagent "K" and a water-soluble carbodiimide derivative

Two new methods of activation were developed to graft enzymes on collegen films. They involved chemical modifications of surface groups of collagen either by Woodward's reagent "K" or by EDC, a water-soluble derivative of carbodiimide. EDC was a better coupling agent and a detailed study was conducted with this agent. It could be used either in a global method of activation and coupling, or in a two-step procedure of activation of collagen, followed by spontaneous coupling of enzyme. All enzymes tested were successfully bound: malate dehydrogenase, lactate dehydrogenase, aspartate aminotransferase, urease, creatine kinase, hexokinase. The influence on the yield of grafted enzyme, of pretreatment of films, time and temperature of EDC activation, concentration of EDC and enzyme, protecting agents was studied. Stability of enzyme activity on storage was greatly increased after grafting. A co-grafted dual system creatine kinase/heoxkinase, was achieved which exhibited a good efficiency. A striking renaturing process at 0-4degreesC after thermal denaturation, was observed with hexokinase.     

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.