New progress in R&D of lower olefin synthesis

This paper gives a brief review of R&D researches for light olefin synthesis directly and indirectly from synthesis gas in the Dalian Institute of Chemical Physics (DICP). The first pilot plant test was on methanol to olefin (MTO) reaction and was finished in 1993, which was based on ZSM-5-type catalyst and fixed bed reaction. In the meantime, a new indirect method designated as SDTO (syngas via dimethylether to olefin) was proposed. In this process, metal-acid bifunctional catalyst was applied for synthesis gas to dimethylether(DME) reaction, and modified SAPO-34 catalyst that was synthesized by a new low-cost method with optimal crystal size was used to convert DME to light olefin on a fluidized bed reactor. The pilot plant test on SDTO was performed and finished in 1995. Evaluation of the pilot plant data showed that 190-200 g of DME were yielded by single-pass for each standard cubic meter of synthesis gas. For the second reaction, 1.880 tons of DME or 2.615 tons of methanol produced 1 ton of light olefins, which constitutes of 0.533 ton of ethylene, 0.349 ton of propylene and 0.118 ton of butene. DICP also paid some attention on direct conversion of synthesis gas to light olefins. A semi-pilot plant test (catalyst 1.8 1) was finished in 1995 with a CO conversion > 70% and a C(2)(=)-C(4)(=) olefin selectivity 71-74% in 1000 h. (C) 2000 Published by Elsevier Science B.V. All rights reserved.

Stable tetrahedral aluminum sites in hexagonal mesoporous aluminosilicates

A unique templating approach for the synthesis of hexagonal mesoporous aluminosilicates via self-assembly of pre-formed aluminosilcate nanoclusters with the templating micella formed by cetyltrimethylammonium bromide (CTAB) is described. The obtained materials of MAS-5 are hydrothermally stable, which is shown by X-ray diffraction (XRD) analysis. Furthermore, as characterized by NMR technique, MAS-5 has stable tetrahedral aluminum sites that is the major contributions to the acidity of aluminosilicate molecular sieve, and on non-framework aluminium species in the samples was observed.

Synthesis and characterization of manganese-modified MCM-41

Manganese-modified mesoporous MCM-41 molecular sieves were synthesized at the absence of alkaline metal ions under mild alkaline condition using cetylpyridinium bromide surfactant as a template, and characterized with X-ray diffraction, N-2 adsorption, transmission electron microscopy, electron spin resonance (ESR), and nuclear magnetic resonance (NMR) spectroscopies. The synthesized MnMCM-41 has a high pore volume of 1.30 cm(3) g(-1) with a corresponding surface area of 1510 m(2) g(-1). The ESR and Si-29 MAS NMR spectra revealed the presence of framework manganese ions in either the as-synthesized or calcined forms. (C) 2002 Elsevier Science B.V. All rights reserved.

Ammonia synthesis over Ru/C catalysts with different carbon supports promoted by barium and potassium compounds

Ammonia synthesis over ruthenium catalysts supported on different carbon materials using Ba or K compounds as promoters has been investigated. Ba(NO3)(2), KOH, and KNO3 are used as the promoter or promoter precursor, and activated carbon (AC), activated carbon fiber (ACF). and carbon molecular sieve (CMS) are used as the support. The activity measurement for ammonia synthesis was carried out in a flow micro-reactor under mild conditions: 350-450 degreesC and 3.0 MPa. Results show that KOH promoter was more effective than KNO3. and that Ba(NO3)(2) was the most effective promoter among the three. The roles of promoters can be divided into the electronic modification of ruthenium, the neutralization of surface functional groups on the carbon support and the ruthenium precursor. The catalyst with AC as the support gave the highest ammonia concentration in the effluent among the supports used, while the catalyst with ACF as the support showed the highest turnover-frequency (TOF) value. It seems that the larger particles of Ru on the carbon supports are more active for ammonia synthesis in terms of TOF value. (C) 2001 Elsevier Science B.V. All rights reserved.

元音和复合音识别中噪音分离机制的实验研究

Harmonicity is one of the important features of a vowel. It makes great contribution to pitch and quality of vowel. However, contribution of a mistuned harmonic will decrease as it is mistuned increasingly. A mistuned harmonic will be segregated as noise from complex by auditory system, which was called harmonic sieve (Duifhuis, 1982). According to Darwin (1986) and Moore et al (1985), the critical value of one mistuned harmonic would be segregated from vowel or complex is 3% to 8%－－Harmonic Mistuned Effect (HME). Further questions need to be answered. For example, how will the harmonic sieve separate noise or whether the critical value change when more than two harmonics are mistuned? And what affect the HME? Three experiments were conducted to these questions. Experiment one was dealt with the number of mistuned harmonics as a factor affecting the HME. The position effect of HME was concerned in experiment two. The last experiment considered the relationship between HME and phase of the mistuned harmonic. The results indicated that (1) the HME was much greater when more than two harmonics were mistuned than only one harmonic was mistuned; (2) harmonic position played an important role in HME, the higher the harmonic was, the less HME was found for the complex, and the closer to formant the harmonic stood, the more significant HME existed; and (3) phase did not affect the HME significantly, however, its indirect contribution still existed, which related to the starting amplitude of a mistuned harmonic.

A Simple Model of Circuit Design

A simple analog circuit designer has been implemented as a rule based system. The system can design voltage followers. Miller integrators, and bootstrap ramp generators from functional descriptions of what these circuits do. While the designer works in a simple domain where all components are ideal, it demonstrates the abilities of skilled designers. While the domain is electronics, the design ideas are useful in many other engineering domains, such as mechanical engineering, chemical engineering, and numerical programming. Most circuit design systems are given the circuit schematic and use arithmetic constraints to select component values. This circuit designer is different because it designs the schematic. The designer uses a unidirectional CONTROL relation to find the schematic. The circuit designs are built around this relation; it restricts the search space, assigns purposes to components and finds design bugs.

Identifying framework titanium in TS-1 zeolite by UV resonance Raman spectroscopy

Framework titanium in Ti-silicalite-1 (TS-1) zeolite was selectively identified by its resonance Raman bands using ultraviolet (W) Raman spectroscopy. Raman spectra of the TS-1 and silicalite-1 zeolites were obtained and compared using continuous wave laser lines at 244, 325, and 488 nm as the excitation sources. It was only with the excitation at 244 nm that resonance enhanced Raman bands at 490, 530, and 1125 cm(-1) appeared exclusively for the TS-1 zeolite. Furthermore, these bands increased in intensity with the crystallization time of the TS-1 zeolite. The Raman bands at 490, 530, and 1125 cm(-1) are identified as the framework titanium species because they only appeared when the laser excites the charge-transfer transition of the framework titanium species in the TS-1. No resonance Raman enhancement was detected for the bands of silicalite-1 zeolite and for the band at 960 cm(-1) of TS-1 with any of the excitation sources ranging from the visible tb UV regions. This approach can be applicable for the identification of other transition metal ions substituted in the framework of a zeolite or any other molecular sieve.

Homology Induction: the use of machine learning to improve sequence similarity searches

Karwath, A. King, R. Homology induction: the use of machine learning to improve sequence similarity searches. BMC Bioinformatics. 23rd April 2002. 3:11 Additional File Describes the title organims species declaration in one string [http://www.biomedcentral.com/content/supplementary/1471- 2105-3-11-S1.doc] Sponsorship: Andreas Karwath and Ross D. King were supported by the EPSRC grant GR/L62849.

A Neural Network for Synthesizing the Pitch of an Acoustic Source

This article describes a neural network model capable of generating a spatial representation of the pitch of an acoustic source. Pitch is one of several auditory percepts used by humans to separate multiple sound sources in the environment from each other. The model provides a neural instantiation of a type of "harmonic sieve". It is capable of quantitatively simulating a large body of psychoacoustical data, including new data on octave shift perception.

A Spectral Network Model of Pitch Perception

A model of pitch perception, called the Spatial Pitch Network or SPINET model, is developed and analyzed. The model neurally instantiates ideas front the spectral pitch modeling literature and joins them to basic neural network signal processing designs to simulate a broader range of perceptual pitch data than previous spectral models. The components of the model arc interpreted as peripheral mechanical and neural processing stages, which arc capable of being incorporated into a larger network architecture for separating multiple sound sources in the environment. The core of the new model transforms a spectral representation of an acoustic source into a spatial distribution of pitch strengths. The SPINET model uses a weighted "harmonic sieve" whereby the strength of activation of a given pitch depends upon a weighted sum of narrow regions around the harmonics of the nominal pitch value, and higher harmonics contribute less to a pitch than lower ones. Suitably chosen harmonic weighting functions enable computer simulations of pitch perception data involving mistuned components, shifted harmonics, and various types of continuous spectra including rippled noise. It is shown how the weighting functions produce the dominance region, how they lead to octave shifts of pitch in response to ambiguous stimuli, and how they lead to a pitch region in response to the octave-spaced Shepard tone complexes and Deutsch tritones without the use of attentional mechanisms to limit pitch choices. An on-center off-surround network in the model helps to produce noise suppression, partial masking and edge pitch. Finally, it is shown how peripheral filtering and short term energy measurements produce a model pitch estimate that is sensitive to certain component phase relationships.

permGPU: Using graphics processing units in RNA microarray association studies.

BACKGROUND: Many analyses of microarray association studies involve permutation, bootstrap resampling and cross-validation, that are ideally formulated as embarrassingly parallel computing problems. Given that these analyses are computationally intensive, scalable approaches that can take advantage of multi-core processor systems need to be developed. RESULTS: We have developed a CUDA based implementation, permGPU, that employs graphics processing units in microarray association studies. We illustrate the performance and applicability of permGPU within the context of permutation resampling for a number of test statistics. An extensive simulation study demonstrates a dramatic increase in performance when using permGPU on an NVIDIA GTX 280 card compared to an optimized C/C++ solution running on a conventional Linux server. CONCLUSIONS: permGPU is available as an open-source stand-alone application and as an extension package for the R statistical environment. It provides a dramatic increase in performance for permutation resampling analysis in the context of microarray association studies. The current version offers six test statistics for carrying out permutation resampling analyses for binary, quantitative and censored time-to-event traits.

Missing data in randomized clinical trials for weight loss: scope of the problem, state of the field, and performance of statistical methods.

BACKGROUND: Dropouts and missing data are nearly-ubiquitous in obesity randomized controlled trails, threatening validity and generalizability of conclusions. Herein, we meta-analytically evaluate the extent of missing data, the frequency with which various analytic methods are employed to accommodate dropouts, and the performance of multiple statistical methods. METHODOLOGY/PRINCIPAL FINDINGS: We searched PubMed and Cochrane databases (2000-2006) for articles published in English and manually searched bibliographic references. Articles of pharmaceutical randomized controlled trials with weight loss or weight gain prevention as major endpoints were included. Two authors independently reviewed each publication for inclusion. 121 articles met the inclusion criteria. Two authors independently extracted treatment, sample size, drop-out rates, study duration, and statistical method used to handle missing data from all articles and resolved disagreements by consensus. In the meta-analysis, drop-out rates were substantial with the survival (non-dropout) rates being approximated by an exponential decay curve (e(-lambdat)) where lambda was estimated to be .0088 (95% bootstrap confidence interval: .0076 to .0100) and t represents time in weeks. The estimated drop-out rate at 1 year was 37%. Most studies used last observation carried forward as the primary analytic method to handle missing data. We also obtained 12 raw obesity randomized controlled trial datasets for empirical analyses. Analyses of raw randomized controlled trial data suggested that both mixed models and multiple imputation performed well, but that multiple imputation may be more robust when missing data are extensive. CONCLUSION/SIGNIFICANCE: Our analysis offers an equation for predictions of dropout rates useful for future study planning. Our raw data analyses suggests that multiple imputation is better than other methods for handling missing data in obesity randomized controlled trials, followed closely by mixed models. We suggest these methods supplant last observation carried forward as the primary method of analysis.

Beta-adrenergic receptor kinase: identification of a novel protein kinase that phosphorylates the agonist-occupied form of the receptor.

Agonist-promoted desensitization of adenylate cyclase is intimately associated with phosphorylation of the beta-adrenergic receptor in mammalian, avian, and amphibian cells. However, the nature of the protein kinase(s) involved in receptor phosphorylation remains largely unknown. We report here the identification and partial purification of a protein kinase capable of phosphorylating the agonist-occupied form of the purified beta-adrenergic receptor. The enzyme is prepared from a supernatant fraction from high-speed centrifugation of lysed kin- cells, a mutant of S49 lymphoma cells that lacks a functional cAMP-dependent protein kinase. The beta-agonist isoproterenol induces a 5- to 10-fold increase in receptor phosphorylation by this kinase, which is blocked by the antagonist alprenolol. Fractionation of the kin- supernatant on molecular-sieve HPLC and DEAE-Sephacel results in a 50- to 100-fold purified beta-adrenergic receptor kinase preparation that is largely devoid of other protein kinase activities. The kinase activity is insensitive to cAMP, cGMP, cAMP-dependent kinase inhibitor, Ca2+-calmodulin, Ca2+-phospholipid, and phorbol esters and does not phosphorylate general kinase substrates such as casein and histones. Phosphate appears to be incorporated solely into serine residues. The existence of this novel cAMP-independent kinase, which preferentially phosphorylates the agonist-occupied form of the beta-adrenergic receptor, suggests a mechanism that may explain the homologous or agonist-specific form of adenylate cyclase desensitization. It also suggests a general mechanism for regulation of receptor function in which only the agonist-occupied or "active" form of the receptor is a substrate for enzymes inducing covalent modification.

Local models for exploratory analysis of hydrological extremes

Trend analysis is widely used for detecting changes in hydrological data. Parametric methods for this employ pre-specified models and associated tests to assess significance, whereas non-parametric methods generally apply rank tests to the data. Neither approach is suitable for exploratory analysis, because parametric models impose a particular, perhaps unsuitable, form of trend, while testing may confirm that trend is present but does not describe its form. This paper describes semi-parametric approaches to trend analysis using local likelihood fitting of annual maximum and partial duration series and illustrates their application to the exploratory analysis of changes in extremes in sea level and river flow data. Bootstrap methods are used to quantify the variability of estimates.