Partial oxidation of methane to syngas over Pt-Ni/Al2O3 Catalyst

The catalytic partial oxidation of methane to syngas over Ni/Al2O3, Pt/Al2O3 and a series of Pt - Ni/Al2O3 catalysts was investigated. It was found that Pt - Ni/Al2O3 catalysts exhibit higher activity and stability than Ni/Al2O3 and Pt/Al2O3. TPR and TPD methods were used to characterize Pt - Ni bimetallic interactions in the catalysts. A series of Pt - Ni/Al2O3 catalysts and unsupported Pt - Ni samples were studied by XRD and XPS. It was found the formation of Pt - Ni alloy in the Pt - Ni/Al2O3 catalysts and the enrichment of platinum on the surface of the catalysts. It is concluded that the higher activity and stability of Pt - Ni/Al2O3 catalysts were caused by Pt - Ni bimetallic interactions.

裂隙/孔隙型弹性介质中地震波场模拟与叠前逆时偏移

With the development of oil/gas seismic exploration, seismic survey for fracture/porosity type reservoir is becoming more and more important. As for China, since it has over 60% store of low porosity and low permeability oil/gas reservoir, it’s more urgent to validly describe fracture/porosity type oil/gas trap and proposing the related, developed seismic technique. To achieve mapping fracture/porosity region and its development status, it demands profound understanding of seismic wave propagation discipline in complex fractured/pored media. Meanwhile, it has profound scientific significance and applied worth to study forward modeling of fracture/porosity type media and pre-stacked reverse time migration. Especially, pre-stacked reverse-time migration is the lead edge technique in the field of seismology and seismic exploration. In this paper, the author has summarized the meaning, history and the present state of numerical simulation of seismic propagation in fractured/pored media and seismic exploration of fractured/pored reservoirs. Extensive Dilatancy Anisotropy (EDA) model is selected as media object in this work. As to forward modeling, due to local limitation of solving spatial partial derivative when using finite-difference and finite-element method, the author turns to pseudo-spectral method (PSM), which is based on the global characteristic of Fourier transform to simulate three-component elastic wave-field. Artifact boundary effect reduction and simulation algorithm stability are also discussed in the work. The author has completed successfully forward modeling coding of elastic wave-field and numerical simulation of two-dimensional and three-dimensional EDA models with different symmetric axis. Seismic dynamic and kinematical properties of EDA media are analyzed from time slices and seismic records of wave propagation. As to pre-stacked reverse-time migration for elastic wave-field in fractured/pored media, based on the successful experience in forward modeling results with PSM, the author has studied pre-stacked reverse-time depth-domain migration technique using PSM of elastic wave-field in two dimensional EDA media induced by preferred fracture/pore distribution. At the same time, different image conditions will bring up what kind of migration result is detailed in this paper. The author has worded out software for pre-stacked reverse-time depth-domain migration of elastic wave-field in EDA media. After migration processing of a series of seismic shot gathers, influences to migration from different isotropic and anisotropy models are described in the paper. In summary, following creative research achievements are obtained:  Realizing two-dimensional and three-dimensional elastic wave-field modeling for fractured/pored media and related software has been completed.  Proposed pre-stacked reverse-time depth-domain migration technique using PSM of elastic wave-field.  Through analysis of the seismic dynamic and kinematical properties of EDA media, the author made a conclusion that collection of multi-component seismic data can provide important data basis for locating and describing the fracture/pore regions and their magnitudes and the preferred directions.  Pre-stacked reverse-time depth-domain migration technique has the ability to reconstruct complex geological object with steep formations and tilt fracture distribution. Neglecting seismic anisotropy induced by the preferred fracture/pore distribution, will lead to the disastrous imaging results.

Mechanistic studies of methane partial oxidation to syngas over LiNiLaOx/Al2O3 catalyst

Temperature-programmed reduction (TPR) characterization of the LiNiLaOx/Al2O3 catalyst before or after partial oxidation of methane (POM) reaction and a series of O-2, CH4 and CH4/O-2 pulse reaction experiments over the catalyst under different pretreatments were performed. It was found that CH4 dissociatively adsorbs on active center nickel producing H-2 and surface carbon, C(a). The surface carbon reacts with surface lattice oxygen or surface adsorbed oxygen to produce CO. Because the activation barrier for the reaction C(a)+ O(a) =CO(a) is the highest among all the elementary reactions, the rate-determining step of the POM may be the reaction C(a) + O(a) =CO(a).

Rapid and quantitative detection of the microbial spoilage of meat by Fourier Transform Infrared Spectroscopy and machine learning

Ellis, D. I., Broadhurst, D., Kell, D. B., Rowland, J. J., Goodacre, R. (2002). Rapid and quantitative detection of the microbial spoilage of meat by Fourier Transform Infrared Spectroscopy and machine learning. ? Applied and Environmental Microbiology, 68, (6), 2822-2828 Sponsorship: BBSRC

Comparison of pattern detection methods in microarray time series of the segmentation clock.

While genome-wide gene expression data are generated at an increasing rate, the repertoire of approaches for pattern discovery in these data is still limited. Identifying subtle patterns of interest in large amounts of data (tens of thousands of profiles) associated with a certain level of noise remains a challenge. A microarray time series was recently generated to study the transcriptional program of the mouse segmentation clock, a biological oscillator associated with the periodic formation of the segments of the body axis. A method related to Fourier analysis, the Lomb-Scargle periodogram, was used to detect periodic profiles in the dataset, leading to the identification of a novel set of cyclic genes associated with the segmentation clock. Here, we applied to the same microarray time series dataset four distinct mathematical methods to identify significant patterns in gene expression profiles. These methods are called: Phase consistency, Address reduction, Cyclohedron test and Stable persistence, and are based on different conceptual frameworks that are either hypothesis- or data-driven. Some of the methods, unlike Fourier transforms, are not dependent on the assumption of periodicity of the pattern of interest. Remarkably, these methods identified blindly the expression profiles of known cyclic genes as the most significant patterns in the dataset. Many candidate genes predicted by more than one approach appeared to be true positive cyclic genes and will be of particular interest for future research. In addition, these methods predicted novel candidate cyclic genes that were consistent with previous biological knowledge and experimental validation in mouse embryos. Our results demonstrate the utility of these novel pattern detection strategies, notably for detection of periodic profiles, and suggest that combining several distinct mathematical approaches to analyze microarray datasets is a valuable strategy for identifying genes that exhibit novel, interesting transcriptional patterns.

Analysing partial ranks by using smoothed paired comparison methods:An investigation of value orientation in Europe

This paper introduces the paired comparison model as a suitable approach for the analysis of partially ranked data. For example, the Inglehart index, collected in international social surveys to examine shifts in post-materialistic values, generates such data on a set of attitude items. However, current analysis methods have failed to account for the complex shifts in individual item values, or to incorporate subject covariates. The paired comparison model is thus developed to allow for covariate subject effects at the individual level, and a reparameterization allows the inclusion of smooth non-linear effects of continuous covariates. The Inglehart index collected in the 1993 International Social Science Programme survey is analysed, and complex non-linear changes of item values with age, level of education and religion are identified. The model proposed provides a powerful tool for social scientists.

Thermography-based virtual MPPT scheme for improving PV energy efficiency under partial shading conditions

This paper proposes a new thermography-based maximum power point tracking (MPPT) scheme to address photovoltaic (PV) partial shading faults. Solar power generation utilizes a large number of PV cells connected in series and in parallel in an array, and that are physically distributed across a large field. When a PV module is faulted or partial shading occurs, the PV system sees a nonuniform distribution of generated electrical power and thermal profile, and the generation of multiple maximum power points (MPPs). If left untreated, this reduces the overall power generation and severe faults may propagate, resulting in damage to the system. In this paper, a thermal camera is employed for fault detection and a new MPPT scheme is developed to alter the operating point to match an optimized MPP. Extensive data mining is conducted on the images from the thermal camera in order to locate global MPPs. Based on this, a virtual MPPT is set out to find the global MPP. This can reduce MPPT time and be used to calculate the MPP reference voltage. Finally, the proposed methodology is experimentally implemented and validated by tests on a 600-W PV array. 

Analysis of financial indices by means of the windowed Fourier transform

The goal of this study is to analyze the dynamical properties of financial data series from nineteen worldwide stock market indices (SMI) during the period 1995–2009. SMI reveal a complex behavior that can be explored since it is available a considerable volume of data. In this paper is applied the window Fourier transform and methods of fractional calculus. The results reveal classification patterns typical of fractional order systems.

Dynamical Analysis and Visualization of Tornadoes Time Series

In this paper we analyze the behavior of tornado time-series in the U.S. from the perspective of dynamical systems. A tornado is a violently rotating column of air extending from a cumulonimbus cloud down to the ground. Such phenomena reveal features that are well described by power law functions and unveil characteristics found in systems with long range memory effects. Tornado time series are viewed as the output of a complex system and are interpreted as a manifestation of its dynamics. Tornadoes are modeled as sequences of Dirac impulses with amplitude proportional to the events size. First, a collection of time series involving 64 years is analyzed in the frequency domain by means of the Fourier transform. The amplitude spectra are approximated by power law functions and their parameters are read as an underlying signature of the system dynamics. Second, it is adopted the concept of circular time and the collective behavior of tornadoes analyzed. Clustering techniques are then adopted to identify and visualize the emerging patterns.

Prenatal diagnosis of urinary malformations: results in a series of 93 consecutive cases.

OBJECTIVE: To evaluate the pertinence of prenatal diagnosis in cases of congenital uropathy. STUDY DESIGN: Retrospective evaluation over a period of 6.5 years. METHOD: 93 cases were involved in the comparison of prenatal ultrasonographic diagnosis with neonatal findings, autopsy results, and follow-up data. RESULTS: 33 fetuses had renal parenchymal lesions, 44 had excretory system lesions, and 6 had bladder and/or urethral lesions. Seventy-three pregnancies lead to live births. Eighteen terminations of pregnancy were performed on the parents' request for extremely severe malformations. Two intrauterine deaths were observed, and two infants died in the postnatal period. Prenatal diagnosis was obtained at an average of 27 weeks gestation. Diagnostic concordance was excellent in 82% and partial in 12% of cases with renal parenchymal lesions; the false-positive rate was 6%. For excretory system lesions, concordance was excellent in 87% and partial in 7.4% of cases, with a false-positive rate of 5.6%. Finally, concordance was excellent in 100% of cases of bladder and/or urethral lesions. The overall rate of total concordance was 86%. Partial concordance cases consisted of malformations different from those previously diagnosed, but prenatal diagnosis nevertheless lead to further investigations in the neonatal period and to proper management. The false-positive diagnoses (5.4%) never lead to termination of pregnancy. CONCLUSION: Prenatal diagnosis of congenital uropathy is effective. A third-trimester ultrasonographic examination is necessary to ensure proper neonatal management, considering that the majority of cases are diagnosed at this gestational age.

Isolation and partial characterization of host cell wall surface glycoproteins: their involvement in agglutination, attachment and appressorium formation by piptocephalis virginiana

Cell surface proteins obtained by alkaline extraction from isolated cell walls of Mortierella pusilla and M. candelabrum, host and nonhost, respectively, to the mycoparasite, Piptocephalis virginiana, were tested for their ability to agglutinate mycoparasite spores. The host cell wall protein extract had a high agglutinating activity (788 a.u. mg- t ) as compared with the nonhost extract (21 a.li. mg- t ). SDS-polyacrylamide gel electrophoresis of the cell wall proteins revealed four protein bands, a, b, c, and d (Mr 117, 100, 85 and 64 kd, respectively) at the host surface, but not at the nonhost surface, except for the faint band c. Deletion of proteins b or c from the host cell wall protein extract significantly reduced its agglutinating activity. Proteins band c, obtained as purified preparations by a series of procedures, were shown to be two glycoproteins. Carbohydrate analysis by gas chromatography demonstrated that glucose and Nacetylglucosamine were the major carbohydrate components of the glycoproteins. It was further shown that the agglutinating activity of the pure preparation containing both band c was 500-850 times that of the single glycoproteins, suggesting the involvement of both glycoproteins in agglutination. The results suggest that the glycoproteins band c are the two subunits of agglutinin present at the host cell surface. The two glycoproteins band c purified from the host cell wall protein extract were further examined after various treatments for their possible role in agglutination, attachment and appressorium formation by the mycoparasite. Results obtained by agglutination and attachment tests showed: (1) the two glycoprotein-s are not only an agglutinin responsible for the mycoparasite spore agglutination, but may also serve as a receptor for the specific recognition, attachment and appressorium formation by the mycoparasite; (2) treatment of the rnycoparasite spores with various sugars revealed that arabinose, glucose and N-acetylglucosamine inhibited the agglutination and attachment activity of the glycoproteins, however, the relative percentage of appressorium formation was not affected by the above sugars; (3) the two glycoproteins are relatively stable with respect to their agglutinin and receptor functions. The present results suggest that the agglutination and attachment may be mediated directly by certain sugars present at the host and mycoparasite cell surfaces while the appressorlum formation may be the response of complementary combinations of both sugar and protein, the two parts of the glycoproteins at the interacting surfaces of two fungi.

Partial characterization of the cloned dihydrofolate reductase gene of Saccharomyces cerevisiae

The cloned dihydrofolate reductase gene of Saccharomyces cerevisiae (DFR 1) is expressed in Escherichia coli. Bacterial strain JF1754 transformed with plasmids containing DFR 1 is at least 5X more resistant to inhibition by the folate antagonist trimethoprim. Expression of yeast DFR 1 in E. coli suggests it is likely that the gene lacks intervening sequences. The 1.8 kbp DNA fragment encoding yeast dhfr activity probably has its own promotor, as the gene is expressed in both orientations in E. coli. Expression of the yeast dhfr gene cloned into M13 viral vectors allowed positive selection of DFR 1 - M13 bacterial transfectants in medium supplemented with trimethoprim. A series of nested deletions generated by nuclease Bal 31 digestion and by restriction endonuclease cleavage of plasmids containing DFR 1 physically mapped the gene to a 930 bp region between the Pst 1 and Sal 1 cut sites. This is consistent with the 21,000 molecular weight attributed to yeast dhfr in previous reports. From preliminary DNA sequence analysis of the dhfr DNA fragment the 3' terminus of DFR 1 was assigned to a position 27 nucleotides from the Eco Rl cut site on the Bam Hi - Eco Rl DNA segment. Several putative yeast transcription termination consensus sequences were identified 3' to the opal stop codon. DFR 1 is expressed in yeast and it confers resistance to the antifolate methotrexate when the gene is present in 2 - 10 copies per cell. Plasmid-dependent resistance to methotrexate is also observed in a rad 6 background although the effect is somewhat less than that conferred to wild-type or rad 18 cells. Integration of DFR 1 into the yeast genome showed an intermediate sensitivity to folate antagonists. This may suggest a gene dosage effect. No change in petite induction in these yeast strains was observed in transformed cells containing yeast dhfr plasmids. The sensitivity of rad 6 , rad 18 and wild-type cell populations to trimethoprim were unaffected by the presence of DFR 1 in transformants. Moreover, trimethoprim did not induce petites in any strain tested, which normally results if dhfr is inhibited by other antifolates such as methotrexate. This may suggest that the dhfr enzyme is not the only possible target of trimethoprim in yeast. rad 6 mutants showed a very low level of spontaneous petite formation. Methotrexate failed to induce respiratory deficient mutants in this strain which suggested that rad 6 might be an obligate grande. However, ethidium bromide induced petites to a level approximately 50% of that exhibited by wild-type and rad 18 strains.

Modeling and Analysis of Some Heavy Tailed Time Series

The thesis has covered various aspects of modeling and analysis of finite mean time series with symmetric stable distributed innovations. Time series analysis based on Box and Jenkins methods are the most popular approaches where the models are linear and errors are Gaussian. We highlighted the limitations of classical time series analysis tools and explored some generalized tools and organized the approach parallel to the classical set up. In the present thesis we mainly studied the estimation and prediction of signal plus noise model. Here we assumed the signal and noise follow some models with symmetric stable innovations.We start the thesis with some motivating examples and application areas of alpha stable time series models. Classical time series analysis and corresponding theories based on finite variance models are extensively discussed in second chapter. We also surveyed the existing theories and methods correspond to infinite variance models in the same chapter. We present a linear filtering method for computing the filter weights assigned to the observation for estimating unobserved signal under general noisy environment in third chapter. Here we consider both the signal and the noise as stationary processes with infinite variance innovations. We derived semi infinite, double infinite and asymmetric signal extraction filters based on minimum dispersion criteria. Finite length filters based on Kalman-Levy filters are developed and identified the pattern of the filter weights. Simulation studies show that the proposed methods are competent enough in signal extraction for processes with infinite variance.Parameter estimation of autoregressive signals observed in a symmetric stable noise environment is discussed in fourth chapter. Here we used higher order Yule-Walker type estimation using auto-covariation function and exemplify the methods by simulation and application to Sea surface temperature data. We increased the number of Yule-Walker equations and proposed a ordinary least square estimate to the autoregressive parameters. Singularity problem of the auto-covariation matrix is addressed and derived a modified version of the Generalized Yule-Walker method using singular value decomposition.In fifth chapter of the thesis we introduced partial covariation function as a tool for stable time series analysis where covariance or partial covariance is ill defined. Asymptotic results of the partial auto-covariation is studied and its application in model identification of stable auto-regressive models are discussed. We generalize the Durbin-Levinson algorithm to include infinite variance models in terms of partial auto-covariation function and introduce a new information criteria for consistent order estimation of stable autoregressive model.In chapter six we explore the application of the techniques discussed in the previous chapter in signal processing. Frequency estimation of sinusoidal signal observed in symmetric stable noisy environment is discussed in this context. Here we introduced a parametric spectrum analysis and frequency estimate using power transfer function. Estimate of the power transfer function is obtained using the modified generalized Yule-Walker approach. Another important problem in statistical signal processing is to identify the number of sinusoidal components in an observed signal. We used a modified version of the proposed information criteria for this purpose.

ARMA modeling of time series based on rational approximation of spectral density function

This study is concerned with Autoregressive Moving Average (ARMA) models of time series. ARMA models form a subclass of the class of general linear models which represents stationary time series, a phenomenon encountered most often in practice by engineers, scientists and economists. It is always desirable to employ models which use parameters parsimoniously. Parsimony will be achieved by ARMA models because it has only finite number of parameters. Even though the discussion is primarily concerned with stationary time series, later we will take up the case of homogeneous non stationary time series which can be transformed to stationary time series. Time series models, obtained with the help of the present and past data is used for forecasting future values. Physical science as well as social science take benefits of forecasting models. The role of forecasting cuts across all fields of management-—finance, marketing, production, business economics, as also in signal process, communication engineering, chemical processes, electronics etc. This high applicability of time series is the motivation to this study.

Evolution of clinical and functional results after arthroscopic treatment of Discoid Meniscus. A case series study of 31 cases.

Purpose: To evaluate the evolution of clinical and functional outcomes of symptomatic discoid lateral meniscus treated arthroscopically over time and to investigate the relationship between associated intra-articular findings and outcomes. Methods: Of all patients treated arthroscopically between 1995 and 2010, patients treated for symptomatic discoid meniscus were identified in the hospital charts. Baseline data (demographics, previous trauma of ipsilateral knee, and associated intra-articular findings) and medium term outcome data from clinical follow-up examinations (pain, locking, snapping and instability of the operated knee) were extracted from clinical records. Telephone interviews were conducted at long term in 28 patients (31 knees). Interviews comprised clinical outcomes as well as functional outcomes as assessed by the International Knee Documentation Committee Subjective Knee Evaluation Form (IKDC). Results: All patients underwent arthroscopic partial meniscectomy. The mean follow-up time for data extracted from clinical records was 11 months (SD ± 12). A significant improvement was found for pain in 77% (p<0.001), locking in 13%, (p=0.045) and snapping in 39 % (p<0.005). The mean follow-up time of the telephone interview was 60 months (SD ± 43). Improvement from baseline was generally less after five years than after one year and functional outcomes of the IKDC indicated an abnormal function after surgery (IKDC mean= 84.5, SD ± 20). In some patients, 5 year-outcomes were even worse than their preoperative condition. Nonetheless, 74% of patients perceived their knee function as improved. Furthermore, better results were seen in patients without any associated intra-articular findings. Conclusions: Arthroscopical partial meniscectomy is an effective intervention to relieve symptoms in patients with discoid meniscus in the medium-term; however, results trend to deteriorate over time. A trend towards better outcome for patients with no associated intra-articular findings was observed.