Estimation of missing observations in two‐level split‐plot designs

Inserting estimates for the missing observations from split‐plot designs restores their balanced or orthogonal structure and alleviates the difficulties in the statistical analysis. In this article, we extend a method due to Draper and Stoneman to estimate the missing observations from unreplicated two‐level factorial and fractional factorial split‐plot (FSP and FFSP) designs. The missing observations, which can either be from the same whole plot, from different whole plots, or comprise entire whole plots, are estimated by equating to zero a number of specific contrast columns equal to the number of the missing observations. These estimates are inserted into the design table and the estimates for the remaining effects (or alias chains of effects as the case with FFSP designs) are plotted on two half‐normal plots: one for the whole‐plot effects and the other for the subplot effects. If the smaller effects do not point at the origin, then different contrast columns to some or all of the initial ones should be discarded and the plots re‐examined for bias. Using examples, we show how the method provides estimates for the missing observations that are very close to their actual values. Copyright © 2007 John Wiley & Sons, Ltd.     

Infrared Spectra of Nitrated Polymeric Carbohydrates

Nitrated Polymeric carbohydrates are not very pure when used, as their physical constants are neither sharp nor unique for positive identification purposes. The ingredients of explosives are so numerous and it was considered beyond the scope of this investigation to include them.     

Superconductivity and Fluctuation-Induced Conductivity (FIC) Analysis of (Cu0.5Tl0.5?x M x )Ba2Ca2Cu3O10?δ

Superconductivity has been improved by partial substitution of slightly higher electronegative (M=Bi, Hg) elements at Tl sites in (Cu_0.5Tl_0.5?x M _x )Ba₂O_4??? (x=0,0.25) charge reservoir layer of (Cu_0.5Tl_0.5?x M _x )Ba₂Ca₂Cu₃O_10??? superconductor. These samples were characterized by X-ray diffractometry, dc-resistivity, ac-susceptibility, FTIR absorption spectroscopy, and fluctuation-induced conductivity (FIC) analysis. The FIC analysis has been carried out in the light of Aslamasov?CLarkin (AL) theory on the resistivity versus temperature curves of (Cu_0.5Tl_0.5?x M _x )Ba₂Ca₂Cu₃O_10??? superconductor. The microscopic parameters such as cross-over temperature (T _o ), zero-temperature coherence length ?? _c (0), inter-layer coupling (J), and critical exponents (?? _2D and ?? _3D) have been determined from FIC analysis of these samples and tried to correlate them to the superconductivity order parameters. A?direct correlation between the cross-over temperatures (T _o ) and zero resistivity critical temperature {T _c (R=0)} and carrier concentration in these samples has been observed. The improvement in T _c (R=0) and the shift of 3D AL region to higher temperature values with the doping of Bi and Hg have also been observed.     

Phase Transformation of Metastable ZnSnO3 Upon Thermal Decomposition by In‐Situ Temperature‐Dependent Raman Spectroscopy

Temperature‐dependent in‐situ Raman spectroscopy is used to investigate the phase transformation of zinc metastannate (ZnSnO₃) to zinc orthostannate (Zn₂SnO₄) induced upon annealing in the ambient. ZnSnO₃ microcubes (MCs) were synthesized at room temperature using a simple aqueous synthesis process, followed by characterization using electron microscopy, X‐ray diffraction (XRD), Fourier transform infrared (FTIR) spectroscopy, and thermogravimetric analysis (TGA). Annealing of the ZnSnO₃ MCs was carried out up to 1000°C, while recording the Raman spectra in‐situ at regular intervals. Phase transformation from metastannate to orthostannate was found to begin around 500°C with an activation energy of ~0.965 eV followed by the recrystallization into the inverse spinel orthostannate phase at ~750°C. Results from this study provide detailed understanding of the phase transformation behavior of perovskite ZnSnO₃ to inverse spinel Zn₂SnO₄ upon thermal annealing.     

Prediction models for sewer infrastructure utilizing rule-based simulation

Management of infrastructure projects is becoming increasingly challenging due to inherent uncertainties. The most effeective way to deal with uncertainty is to collect supplementary information and knowledge. When expensive or infeasible, quantification of uncertainty may be performed using analytical or simulation techniques. The City of Edmonton, Canada has approximately 4600 km of sewer pipes in the combined, sanitary, and storm sewer local systems with uncertainty issues related to deterioration. The City has taken a proactive approach with respect to sewer rehabilitation, as it is more cost-effeective to repair a defective pipe prior to failure rather than after a collapse. This article demonstrates an approach for predicting the condition of a sewer pipe and the related cost of rehabilitation, given the limited data. Three models are described in this article that are developed to assist the City of Edmonton to effeectively plan maintenance expenditure. Each model uses a combination of rule-based simulation and probability analysis to assist in the planning of future expenditures for sewer maintenance, thereby producing an invaluable planning tool.     

Silicon Seed Priming Combined with Foliar Spray of Sulfur Regulates Photosynthetic and Antioxidant Systems to Confer Drought Tolerance in Maize (Zea mays L.)

Silicon - The present study evaluated the effect of silicon (Si) seed priming and sulfur (S) foliar spray on drought tolerance of two contrasting maize hybrids viz. drought tolerant Hi-Corn 11 and...