Object-oriented DBMS requirements

The requirements on an object-oriented DBMS for management of information in a large, complex enterprise are presented. These requirements aid in the achievement of an environment characterized by data sharing, open architectures, application and data portability, and assurance of data integrity. They were defined from the point of view of a user of the DBMS; therefore they describe the expected functionality of the DBMS and do not specify the method of implementation to achieve this functionality. They encompass requirements on the data model, query and data manipulation languages, the system architecure, interfaces to the system, change management, and transaction management.     

Rate of ammonia oxidation in a synthetic saline wastewater by a nitrifying mixed‐culture

Most of the kinetic studies on nitrification have been performed in diluted salts medium. In this work, the ammonia oxidation rate (AOR) was determined by respirometry at different ammonia (0.01 and 33.5 mg N‐NH₃ L^?1), nitrite (0–450 mg N‐NO₂^? L^?1) and nitrate (0 and 275 mg N‐NO₃^? L^?1) concentrations in a saline medium at 30 °C and pH 7.5. Sodium azide was used to uncouple the ammonia and nitrite oxidation, so as to measure independently the AOR. It was determined that ammonia causes substrate inhibition and that nitrite and nitrate exhibit product inhibition upon the AOR. The effects of ammonia, nitrite and nitrate were represented by the Andrews equation (maximal ammonia oxidation rate, r_AOMAX, = 43.2 [mg N‐NH₃ (g VSS_AO h)^?1]; half saturation constant, K_SAO, = 0.11 mg N‐NH₃ L^?1; inhibition constant K_IAO, = 7.65 mg N‐NH₃ L^?1), by the non‐competitive inhibition model (inhibition constant, K_INI, = 176 mg N‐NO₂^? L^?1) and by the partially competitive inhibition model (inhibition constant, K_INA, = 3.3 mg N‐NO₃^? L^?1; α factor = 0.24), respectively. The r_AOMAX value is smaller, and the K_SAO value larger, than the values reported in diluted salts medium; the K_IAO value is comparable to those reported. Process simulations with the kinetic model in batch nitrifying reactors showed that the inhibitory effects of nitrite and nitrate are significant for initial ammonia concentrations larger than 100 mg N‐NH₄⁺ L^?1. Copyright © 2005 Society of Chemical Industry     

A new distributed approximation algorithm for constructing minimum connected dominating set in wireless ad hoc networks

In recent years, constructing a virtual backbone by nodes in a connected dominating set (CDS) has been proposed to improve the performance of ad hoc wireless networks. In general, a dominating set satisfies that every vertex in the graph is either in the set or adjacent to a vertex in the set. A CDS is a dominating set that also induces a connected sub‐graph. However, finding the minimum connected dominating set (MCDS) is a well‐known NP‐hard problem in graph theory. Approximation algorithms for MCDS have been proposed in the literature. Most of these algorithms suffer from a poor approximation ratio, and from high time complexity and message complexity. In this paper, we present a new distributed approximation algorithm that constructs a MCDS for wireless ad hoc networks based on a maximal independent set (MIS). Our algorithm, which is fully localized, has a constant approximation ratio, and O(n) time and O(n) message complexity. In this algorithm, each node only requires the knowledge of its one‐hop neighbours and there is only one shortest path connecting two dominators that are at most three hops away. We not only give theoretical performance analysis for our algorithm, but also conduct extensive simulation to compare our algorithm with other algorithms in the literature. Simulation results and theoretical analysis show that our algorithm has better efficiency and performance than others. Copyright © 2005 John Wiley & Sons, Ltd.     

A Bayesian propensity score adjustment for latent variable modeling and MCMC algorithm

The estimation of the differences among groups in observational studies is frequently inaccurate owing to a bias caused by differences in the distributions of covariates. In order to estimate the average treatment effects when the treatment variable is binary, Rosenbaum and Rubin [1983. The central role of the propensity score in observational studies for causal effects. Biometrika 70, 41-55] proposed an adjustment method for pre-treatment variables using propensity scores. Imbens [2000. The role of the propensity score in estimating dose-response functions. Biometrika 87, 706-710] extended the propensity score methodology for estimation of average treatment effects with multivalued treatments.However, these studies focused only on estimating the marginal mean structure. In many substantive sciences such as the biological and social sciences, a general estimation method is required to deal with more complex analyses other than regression, such as testing group differences on latent variables. For latent variable models, the EM algorithm or the traditional Monte Carlo methods are necessary. However, in propensity score adjustment, these methods cannot be used because the full distribution is not specified.In this paper, we propose a quasi-Bayesian estimation method for general parametric models that integrate out the distributions of covariates using propensity scores. Although the proposed Bayes estimates are shown to be consistent, they can be calculated by existing Markov chain Monte Carlo methods such as Gibbs sampler. The proposed method is useful to estimate parameters in latent variable models, while the previous methods were unable to provide valid estimates for complex models such as latent variable models.We also illustrated the procedure using the data obtained from the US National Longitudinal Survey of Children and Youth (NLSY1979-2002) for estimating the effect of maternal smoking during pregnancy on the development of the child's cognitive functioning.     

Sequential batch reactor for eucalypt kraft pulp effluent treatment with Trametes versicolor

BACKGROUND: A sequential batch reactor (SBR) was used for eucalypt kraft pulp effluent treatment with Trametes versicolor. A 2³ full factorial design and response surface methodology were applied to optimise the batch fermentation conditions. Effluent concentration, culture medium and inoculum age were the factors selected for this study in order to optimise the reduction of chemical oxygen demand (COD). RESULTS: The presence of Trametes Defined Medium (TDM) in the fermentation was required to obtain a significant COD reduction. Experiments in the batch reactor confirmed, in general, the predicted results of optimisation developed from Erlenmeyer batch assays. The T. versicolor culture remained active during 42 days of study in the SBR, providing approximately 80% of COD reduction. CONCLUSION: Trametes versicolor may be considered as very promising for the biological treatment of effluents from kraft pulp mills in an SBR system instead of the activated sludge mixed cultures traditionally used. Copyright © 2008 Society of Chemical Industry     

Age of acquisition: Its neural and computational mechanisms.

The acquisition of new skills over a life span is a remarkable human ability. This ability, however, is constrained by age of acquisition (AoA); that is, the age at which learning occurs significantly affects the outcome. This is most clearly reflected in domains such as language, music, and athletics. This article provides a perspective on the neural and computational mechanisms underlying AoA in language acquisition. The authors show how AoA modulates both monolingual lexical processing and bilingual language acquisition. They consider the conditions under which syntactic processing and semantic processing may be differentially sensitive to AoA effects in second-language acquisition. The authors conclude that AoA effects are pervasive and that the neural and computational mechanisms underlying learning and sensorimotor integration provide a general account of these effects. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Measuring consistency in TTL-based caches

We propose a general modeling framework to evaluate the performance of cache consistency algorithms. In addition to the usual hit rate, we introduce the hit^* rate as a consistency measure, which captures the fraction of non-stale downloads from the cache. We apply these ideas to the analysis of the fixed TTL consistency algorithm in the presence of network delays. The hit and hit^* rates are evaluated when requests and updates are modeled by renewal processes. Classical results on the renewal function lead to various bounds.     

Modeling for local dynamic behaviors of phenol biodegradation in bubble columns

A coupled three-dimensional (3-D) model, combining hydrodynamics with biochemical reactions, was developed to simulate the local transient flow patterns and the dynamic behaviors of cell growth and phenol biodegradation by yeast Candida tropicalis in the bubble-column bioreactor, using the computational fluid dynamic (CFD) method. In order to validate this proposed model effectively, the validation of the local hydrodynamic characteristics of the gas-mineral salt solution (gas-liquid) two-phase system, with the phenol concentration of 1200 mg/L, and with the absence of cells, was performed in a square-sectioned bubble column bioreactor using the LDA system and conductivity probe. Furthermore, the validation of phenol biodegradation behaviors by yeast Candida tropicalis at different initial concentrations of phenol and cell was also carried out in the above bubble-column bioreactor. The results indicated that the model simulations had a satisfying agreement with the experimental data. Finally, the local instantaneous flow and phenol biodegradation features including gas holdup, gas velocity, liquid velocity, cell concentration and phenol concentration inside the bioreactor were successfully predicted in different-scale bubble columns by the proposed model. © 2006 American Institute of Chemical Engineers AIChE J, 2006     

Optimal design of gating systems by gradient search methods

A numerical optimization technique based on gradient-search is applied to obtain an optimal design of a typical gating system used for the gravity process to produce aluminum parts. This represents a novel application of coupling nonlinear optimization techniques with a foundry process simulator, and it is motivated by the fact that a scientifically guided search for better designs based on techniques that take into account the mathematical structure of the problem is preferred to commonly found trial-and-error approaches. The simulator applies the finite volume method and the VOF algorithm for CFD analysis. The direct gradient optimization algorithm, sequential quadratic programming (SQP), was used to solve both a 2D and a 3D gating system design problems using two design variables. The results clearly show the effectiveness of the proposed approach for finding high quality castings when compared with current industry practices.