Linear-wavelet networks

This paper proposes a nonlinear regression structure comprising a wavelet network and a linear term. The introduction of the linear term is aimed at providing a more parsimonious interpolation in high-dimensional spaces when the modelling samples are sparse. A constructive procedure for building such structures, termed linear-wavelet networks, is described. For illustration, the proposed procedure is employed in the framework of dynamic system identification. In an example involving a simulated fermentation process, it is shown that a linear-wavelet network yields a smaller approximation error when compared with a wavelet network with the same number of regressors. The proposed technique is also applied to the identification of a pressure plant from experimental data. In this case, the results show that the introduction of wavelets considerably improves the prediction ability of a linear model. Standard errors on the estimated model coefficients are also calculated to assess the numerical conditioning of the identification process.

Flavonoids as modulators of memory and learning: molecular interactions resulting in behavioural effects

There is considerable interest in the potential of a group of dietary-derived phytochemicals known as flavonoids in modulating neuronal function and thereby influencing memory, learning and cognitive function. The present review begins by detailing the molecular events that underlie the acquisition and consolidation of new memories in the brain in order to provide a critical background to understanding the impact of flavonoid-rich diets or pure flavonoids on memory. Data suggests that despite limited brain bioavailability, dietary supplementation with flavonoid-rich foods, such as blueberry, green tea and Ginkgo biloba lead to significant reversals of age-related deficits on spatial memory and learning. Furthermore, animal and cellular studies suggest that the mechanisms underpinning their ability to induce improvements in memory are linked to the potential of absorbed flavonoids and their metabolites to interact with and modulate critical signalling pathways, transcription factors and gene and/or protein expression which control memory and learning processes in the hippocampus; the brain structure where spatial learning occurs. Overall, current evidence suggests that human translation of these animal investigations are warranted, as are further studies, to better understand the precise cause-and-effect relationship between flavonoid intake and cognitive outputs.

Pocket data mining - big data on small devices

Owing to continuous advances in the computational power of handheld devices like smartphones and tablet computers, it has become possible to perform Big Data operations including modern data mining processes onboard these small devices. A decade of research has proved the feasibility of what has been termed as Mobile Data Mining, with a focus on one mobile device running data mining processes. However, it is not before 2010 until the authors of this book initiated the Pocket Data Mining (PDM) project exploiting the seamless communication among handheld devices performing data analysis tasks that were infeasible until recently. PDM is the process of collaboratively extracting knowledge from distributed data streams in a mobile computing environment. This book provides the reader with an in-depth treatment on this emerging area of research. Details of techniques used and thorough experimental studies are given. More importantly and exclusive to this book, the authors provide detailed practical guide on the deployment of PDM in the mobile environment. An important extension to the basic implementation of PDM dealing with concept drift is also reported. In the era of Big Data, potential applications of paramount importance offered by PDM in a variety of domains including security, business and telemedicine are discussed.

The polychaete worm Nereis diversicolor increases mercury lability and methylation in intertidal mudflats

The polychaete worm Nereis diversicolor engineers its environment by creating oxygenated burrows in anoxic intertidal sediments. The authors carried out a laboratory microcosm experiment to test the impact of polychaete burrowing and feeding activity on the lability and methylation of mercury in sediments from the Bay of Fundy, Canada. The concentration of labile inorganic mercury and methylmercury in burrow walls was elevated compared to worm-free sediments. Mucus secretions and organic detritus in worm burrows increased labile mercury concentrations. Worms decreased sulfide concentrations, which increased Hg bioavailability to sulfate-reducing bacteria and increased methylmercury concentrations in burrow linings. Because the walls of polychaete burrows have a greater interaction with organisms, and the overlying water, the concentrations of mercury and methylmercury they contain is more toxicologically relevant to the base of a coastal food web than bulk samples. The authors recommend that researchers examining Hg in marine environments account for sediment dwelling invertebrate activity to more fully assess mercury bioavailability.

Mercury and methylmercury bioaccumulation by polychaete worms is governed by both feeding ecology and mercury bioavailability in coastal mudflats

Polychaete worms are abundant in many mudflats but their importance to coastal food web Hg biomagnification is not known. We sampled sediments and polychaete worms from mudflats in the Bay of Fundy to investigate the bioaccumulation of mercury (Hg) and methylmercury (MeHg) in the coastal invertebrate food web. Hg concentrations in the sediments were low (<20 μg kg−1). Labile Hg (methanol/KOH sediment extraction) in surface sediments (0–1 cm) was positively correlated with Hg bioaccumulation by surface sediment-ingesting polychaetes but, surprisingly, there was a negative correlation between δ15N (i.e. trophic level) and THg bioaccumulation factors in polychaete worms. Worms feeding on deeper sediments contained the greatest MeHg concentrations (69.6 μg kg−1). Polychaetes are an important vector for Hg biomagnification to the coastal avian food web. This research demonstrates that feeding depth and method of feeding are more important than trophic position or sediment Hg concentrations for predicting Hg bioaccumulation.

Efficiency of evolutionary algorithms in water network pipe sizing

The pipe sizing of water networks via evolutionary algorithms is of great interest because it allows the selection of alternative economical solutions that meet a set of design requirements. However, available evolutionary methods are numerous, and methodologies to compare the performance of these methods beyond obtaining a minimal solution for a given problem are currently lacking. A methodology to compare algorithms based on an efficiency rate (E) is presented here and applied to the pipe-sizing problem of four medium-sized benchmark networks (Hanoi, New York Tunnel, GoYang and R-9 Joao Pessoa). E numerically determines the performance of a given algorithm while also considering the quality of the obtained solution and the required computational effort. From the wide range of available evolutionary algorithms, four algorithms were selected to implement the methodology: a PseudoGenetic Algorithm (PGA), Particle Swarm Optimization (PSO), a Harmony Search and a modified Shuffled Frog Leaping Algorithm (SFLA). After more than 500,000 simulations, a statistical analysis was performed based on the specific parameters each algorithm requires to operate, and finally, E was analyzed for each network and algorithm. The efficiency measure indicated that PGA is the most efficient algorithm for problems of greater complexity and that HS is the most efficient algorithm for less complex problems. However, the main contribution of this work is that the proposed efficiency ratio provides a neutral strategy to compare optimization algorithms and may be useful in the future to select the most appropriate algorithm for different types of optimization problems.