Analysis of ingredient and heating value of municipal solid waste

Great differences between municipal solid wastes(MSW)produced at different places and different times in terms of such parameters as physical ingredient and heating value lead to difficulty in effective handling of MSW. In this paper, ingredient, heating value and their temporal varying trends of typical MSW in Beijing were continuously measured and analyzed. With consideration of the process in pyrolysis and incineration, correlation between physical ingredients and heating values was induced, favorable for evaluation of heating value needed in handling of MSW from simple analysis of physical ingredients of it.

A simple approach to solve boundary-value problems in gradient elasticity

We outline a procedure for obtaining solutions of certain boundary value problems of a recently proposed theory of gradient elasticity in terms of solutions of classical elasticity. The method is applied to illustrate, among other things, how the gradient theory can remove the strain singularity from some typical examples of the classical theory.

Numerical-Value Perturbation Method with Application of Solving Convective-Diffusion Integral Equation

The convective--diffusion equation is of primary importance in such fields as fluid dynamics and heat transfer hi the numerical methods solving the convective-diffusion equation, the finite volume method can use conveniently diversified grids (structured and unstructured grids) and is suitable for very complex geometry The disadvantage of FV methods compared to the finite difference method is that FV-methods of order higher than second are more difficult to develop in three-dimensional cases. The second-order central scheme (2cs) offers a good compromise among accuracy, simplicity and efficiency, however, it will produce oscillatory solutions when the grid Reynolds numbers are large and then very fine grids are required to obtain accurate solution. The simplest first-order upwind (IUW) scheme satisfies the convective boundedness criteria, however. Its numerical diffusion is large. The power-law scheme, QMCK and second-order upwind (2UW) schemes are also often used in some commercial codes. Their numerical accurate are roughly consistent with that of ZCS. Therefore, it is meaningful to offer higher-accurate three point FV scheme. In this paper, the numerical-value perturbational method suggested by Zhi Gao is used to develop an upwind and mixed FV scheme using any higher-order interpolation and second-order integration approximations, which is called perturbational finite volume (PFV) scheme. The PFV scheme uses the least nodes similar to the standard three-point schemes, namely, the number of the nodes needed equals to unity plus the face-number of the control volume. For instanc6, in the two-dimensional (2-D) case, only four nodes for the triangle grids and five nodes for the Cartesian grids are utilized, respectively. The PFV scheme is applied on a number of 1-D problems, 2~Dand 3-D flow model equations. Comparing with other standard three-point schemes, The PFV scheme has much smaller numerical diffusion than the first-order upwind (IUW) scheme, its numerical accuracy are also higher than the second-order central scheme (2CS), the power-law scheme (PLS), the QUICK scheme and the second-order upwind(ZUW) scheme.

Different protein tyrosine phosphatase superfamilies resulting from different gene reading frames

Protein tyrosine phosphatases (PTPs) are comprised of two superfamilies, the phosphatase I superfamily containing a single low-molecular-weight PTP (lmwPTP) family and the phosphatase II superfamily including both the higher-molecular-weight PTP (hmwPTP) and the dual-specificity phosphatase (DSP) families. The phosphatase I and H superfamilies are often considered to be the result of convergent evolution. The PTP sequence and structure analyses indicate that lmwPTPs, hmwPTPs, and DSPs share similar structures, functions, and a common signature motif, although they have low sequence identities and a different order of active sites in sequence or a circular permutation. The results of this work suggest that lmwPTPs and hmwPTPs/DSPs are remotely related in evolution. The earliest ancestral gene of PTPs could be from a short fragment containing about 90similar to120 nucleotides or 30similar to40 residues; however, a probable full PTP ancestral gene contained one transcript unit with two lmwPTP genes. All three PTP families may have resulted from a common ancestral gene by a series of duplications, fusions, and circular permutations. The circular permutation in PTPs is caused by a reading frame difference, which is similar to that in DNA methyltransferases. Nevertheless, the evolutionary mechanism of circular permutation in PTP genes seems to be more complicated than that in DNA methyltransferase genes. Both mechanisms in PTPs and DNA methyltransferases can be used to explain how some protein families and superfamilies came to be formed by circular permutations during molecular evolution.

Identification and characterization of hypoxia-induced genes in Carassius auratus blastulae embryonic cells using suppression subtractive hybridization

Organisms living in water are inevitably exposed to periods of hypoxia. Environmental hypoxia has been an important stressor having manifold effects on aquatic life. Many fish species have evolved behavioral, physiological, biochemical and molecular adaptations that enable them to cope with hypoxia. However, the molecular mechanisms of hypoxia tolerance in fish, remain unknown. in this study, we used suppression subtractive hybridization to examine the differential gene expression in CAB cells (Carassius auratus blastulae embryonic cells) exposed to hypoxia for 24 h. We isolated 2100 clones and identified 211 differentially expressed genes (e-value <= 5e-3; Identity > 45%). Among the genes whose expression is modified in cells, a vast majority involved in metabolism, signal transduction, cell defense, angiogenesis, cell growth and proliferation. Twelve genes encoding for ERO1-L, p53, CPO, HO-1, MKP2, PFK-2, cystatin B, GLUT1, BTG1, TGF beta 1, PGAM1, hypothetical protein F1508, were selected and identified to be hypoxia-induced using semi-quantitive RT-PCR and real-time PCR. Among the identified genes, two open reading frames (ORFs) encoding for CaBTG1 and Cacystatin B were obtained. The deduced amino acid sequence of CaBTG1 had 94.1%, 72.8%, 72.8%, 72.8%, 68.6% identity with that of DrBTG1, HsBTG1, BtBTG1, MmBTG1 and XIBTG1. Comparison of Cacystatin B with known cystatin B, the molecules exhibited 49.5 to 76.0% identity overall. These results may provide significant information for further understanding of the adaptive mechanism by which C. auratus responds to hypoxia. (c) 2008 Elsevier Inc. All rights reserved.

The mean value concept in mono-linear regression of multi-variables and its application to trace studies in geosciences

IEECAS SKLLQG

Retention modeling and simultaneous optimization of pH value and gradient steepness in RP-HPLC using feed-forward neural networks

A novel approach is proposed for the simultaneous optimization of mobile phase pH and gradient steepness in RP-HPLC using artificial neural networks. By presetting the initial and final concentration of the organic solvent, a limited number of experiments with different gradient time and pH value of mobile phase are arranged in the two-dimensional space of mobile phase parameters. The retention behavior of each solute is modeled using an individual artificial neural network. An "early stopping" strategy is adopted to ensure the predicting capability of neural networks. The trained neural networks can be used to predict the retention time of solutes under arbitrary mobile phase conditions in the optimization region. Finally, the optimal separation conditions can be found according to a global resolution function. The effectiveness of this method is validated by optimization of separation conditions for amino acids derivatised by a new fluorescent reagent.

Retention modeling and optimization of pH value and solvent composition in HPLC using back-propagation neural networks and uniform design

A novel method for the optimization of pH value and composition of mobile phase in HPLC using artificial neural networks and uniform design is proposed. As the first step. seven initial experiments were arranged and run according to uniform design. Then the retention behavior of the solutes is modeled using back-propagation neural networks. A trial method is used to ensure the predicting capability of neural networks. Finally, the optimal separation conditions can be found according to a global resolution function. The effectiveness of this method is validated by optimization of separation conditions for both basic and acidic samples.