Analysing Google rankings through search engine optimization data

Purpose - The purpose of this paper is to identify the most popular techniques used to rank a web page highly in Google. Design/methodology/approach - The paper presents the results of a study into 50 highly optimized web pages that were created as part of a Search Engine Optimization competition. The study focuses on the most popular techniques that were used to rank highest in this competition, and includes an analysis on the use of PageRank, number of pages, number of in-links, domain age and the use of third party sites such as directories and social bookmarking sites. A separate study was made into 50 non-optimized web pages for comparison. Findings - The paper provides insight into the techniques that successful Search Engine Optimizers use to ensure a page ranks highly in Google. Recognizes the importance of PageRank and links as well as directories and social bookmarking sites. Research limitations/implications - Only the top 50 web sites for a specific query were analyzed. Analysing more web sites and comparing with similar studies in different competition would provide more concrete results. Practical implications - The paper offers a revealing insight into the techniques used by industry experts to rank highly in Google, and the success or other-wise of those techniques. Originality/value - This paper fulfils an identified need for web sites and e-commerce sites keen to attract a wider web audience.

Optimization of apodization functions in terahertz transient spectrometry

A quadratic programming optimization procedure for designing asymmetric apodization windows tailored to the shape of time-domain sample waveforms recorded using a terahertz transient spectrometer is proposed. By artificially degrading the waveforms, the performance of the designed window in both the time and the frequency domains is compared with that of conventional rectangular, triangular (Mertz), and Hamming windows. Examples of window optimization assuming Gaussian functions as the building elements of the apodization window are provided. The formulation is sufficiently general to accommodate other basis functions. (C) 2007 Optical Society of America

Nonlinear channel equalizer design using directional evolutionary multi-objective optimization

In this paper, a new equalizer learning scheme is introduced based on the algorithm of the directional evolutionary multi-objective optimization (EMOO). Whilst nonlinear channel equalizers such as the radial basis function (RBF) equalizers have been widely studied to combat the linear and nonlinear distortions in the modern communication systems, most of them do not take into account the equalizers' generalization capabilities. In this paper, equalizers are designed aiming at improving their generalization capabilities. It is proposed that this objective can be achieved by treating the equalizer design problem as a multi-objective optimization (MOO) problem, with each objective based on one of several training sets, followed by deriving equalizers with good capabilities of recovering the signals for all the training sets. Conventional EMOO which is widely applied in the MOO problems suffers from disadvantages such as slow convergence speed. Directional EMOO improves the computational efficiency of the conventional EMOO by explicitly making use of the directional information. The new equalizer learning scheme based on the directional EMOO is applied to the RBF equalizer design. Computer simulation demonstrates that the new scheme can be used to derive RBF equalizers with good generalization capabilities, i.e., good performance on predicting the unseen samples.

Investigation of liquid MALDI and optimization for instrument tuning and quantitative measurements

The success of Matrix-assisted laser desorption / ionisation (MALDI) in fields such as proteomics has partially but not exclusively been due to the development of improved data acquisition and sample preparation techniques. This has been required to overcome some of the short comings of the commonly used solid-state MALDI matrices such as - cyano-4-hydroxycinnamic acid (CHCA) and 2,5-dihydroxybenzoic acid (DHB). Solid state matrices form crystalline samples with highly inhomogeneous topography and morphology which results in large fluctuations in analyte signal intensity from spot to spot and positions within the spot. This means that efficient tuning of the mass spectrometer can be impeded and the use of MALDI MS for quantitative measurements is severely impeded. Recently new MALDI liquid matrices have been introduced which promise to be an effective alternative to crystalline matrices. Generally the liquid matrices comprise either ionic liquid matrices (ILMs) or a usually viscous liquid matrix which is doped with a UV lightabsorbing chromophore [1-3]. The advantages are that the droplet surface is smooth and relatively uniform with the analyte homogeneously distributed within. They have the ability to replenish a sampling position between shots negating the need to search for sample hot-spots. Also the liquid nature of the matrix allows for the use of additional additives to change the environment to which the analyte is added.

Particle swarm optimization aided orthogonal forward regression for unified data modeling

We propose a unified data modeling approach that is equally applicable to supervised regression and classification applications, as well as to unsupervised probability density function estimation. A particle swarm optimization (PSO) aided orthogonal forward regression (OFR) algorithm based on leave-one-out (LOO) criteria is developed to construct parsimonious radial basis function (RBF) networks with tunable nodes. Each stage of the construction process determines the center vector and diagonal covariance matrix of one RBF node by minimizing the LOO statistics. For regression applications, the LOO criterion is chosen to be the LOO mean square error, while the LOO misclassification rate is adopted in two-class classification applications. By adopting the Parzen window estimate as the desired response, the unsupervised density estimation problem is transformed into a constrained regression problem. This PSO aided OFR algorithm for tunable-node RBF networks is capable of constructing very parsimonious RBF models that generalize well, and our analysis and experimental results demonstrate that the algorithm is computationally even simpler than the efficient regularization assisted orthogonal least square algorithm based on LOO criteria for selecting fixed-node RBF models. Another significant advantage of the proposed learning procedure is that it does not have learning hyperparameters that have to be tuned using costly cross validation. The effectiveness of the proposed PSO aided OFR construction procedure is illustrated using several examples taken from regression and classification, as well as density estimation applications.

In vitro fermentation of rice bran combined with Lactobacillus acidophilus 14 150B or Bifidobacterium longum 05 by the canine faecal microbiota

The fermentability of rice bran (RB), alone or in combination with one of two probiotics, by canine faecal microbiota was evaluated in stirred, pH-controlled, anaerobic batch cultures. RB enhanced the levels of bacteria detected by probes Bif164 (bifidobacteria) and Lab158 (lactic acid bacteria); however, addition of the probiotics did not have a significant effect on the predominant microbial counts compared with RB alone. RB sustained levels of Bifidobacterium longum 05 throughout the fermentation; in contrast, Lactobacillus acidophilus 14 150B levels decreased significantly after 5-h fermentation. RB fermentation induced changes in the short-chain fatty acid (SCFA) profile. However, RB combined with probiotics did not alter the SCFA levels compared with RB alone. Denaturing gradient gel electrophoresis analysis of samples obtained at 24 h showed a treatment effect with RB, which was not observed in the RB plus probiotic systems. Overall, the negative controls displayed lower species richness than the treatment systems and their banding profiles were distinct. This study illustrates the ability of a common ingredient found in pet food to modulate the canine faecal microbiota and highlights that RB may be an economical alternative to prebiotics for use in dog food.

In vitro effects of synbiotic fermentation on the canine faecal microbiota.

Stirred, pH-controlled anaerobic batch cultures were used to investigate the in vitro effects of galacto-oligosaccharides (GOS) alone or combined with the probiotic Bifidobacterium bifidum 02 450B on the canine faecal microbiota of three different donors. GOS supported the growth of B. bifidum 02 450B throughout the fermentation. Quantitative analysis of bacterial populations by FISH revealed significant increases in Bifidobacterium spp. counts (Bif164) and a concomitant decrease in Clostridium histolyticum counts (Chis150) in the synbiotic-containing vessels compared with the controls and GOS vessels. Vessels containing probiotic alone displayed a transient increase in Bifidobacterium spp. and a transient decrease in Bacteroides spp. Denaturing gradient gel electrophoresis analysis showed that GOS elicited similar alterations in the microbial profiles of the three in vitro runs. However, the synbiotic did not alter the microbial diversity of the three runs to the same extent as GOS alone. Nested PCR using universal primers, followed by bifidobacterial-specific primers illustrated low bifidobacterial diversity in dogs, which did not change drastically during the in vitro fermentation. This study illustrates that the canine faecal microbiota can be modulated in vitro by GOS supplementation and that GOS can sustain the growth of B. bifidum 02 450B in a synbiotic combination.

Use of a continuous culture fermentation system to investigate the effect of GanedenBC30 (Bacillus coagulans GBI-30, 6086) supplementation on pathogen survival in the human gut microbiota

Single-stage continuous fermentation systems were employed to examine the effects of GanedenBC30 supplementation on the human gastrointestinal microbiota in relation to pathogen challenge in vitro. Denaturing gradient gel electrophoresis analysis demonstrated that GanedenBC30 supplementation modified the microbial profiles in the fermentation systems compared with controls, with profiles clustering according to treatment. Overall, GanedenBC30 supplementation did not elicit major changes in bacterial population counts in vitro, although notably higher Bcoa191 counts were seen following probiotic supplementation (compared to the controls). Pathogen challenge did not elicit significant modification of the microbial counts in vitro, although notably higher Clit135 counts were seen in the control system post-Clostridium difficile challenge than in the corresponding GanedenBC30-supplemented systems. Sporulation appears to be associated with the anti-microbial activity of GanedenBC30, suggesting that a bi-modal lifecycle of GanedenBC30 in vivo may lead to anti-microbial activity in distal regions of the gastrointestinal tract.

Prediction of Parkinson’s Disease tremor onset using a radial basis function neural network based on particle swarm optimization

Deep Brain Stimulation (DBS) has been successfully used throughout the world for the treatment of Parkinson's disease symptoms. To control abnormal spontaneous electrical activity in target brain areas DBS utilizes a continuous stimulation signal. This continuous power draw means that its implanted battery power source needs to be replaced every 18–24 months. To prolong the life span of the battery, a technique to accurately recognize and predict the onset of the Parkinson's disease tremors in human subjects and thus implement an on-demand stimulator is discussed here. The approach is to use a radial basis function neural network (RBFNN) based on particle swarm optimization (PSO) and principal component analysis (PCA) with Local Field Potential (LFP) data recorded via the stimulation electrodes to predict activity related to tremor onset. To test this approach, LFPs from the subthalamic nucleus (STN) obtained through deep brain electrodes implanted in a Parkinson patient are used to train the network. To validate the network's performance, electromyographic (EMG) signals from the patient's forearm are recorded in parallel with the LFPs to accurately determine occurrences of tremor, and these are compared to the performance of the network. It has been found that detection accuracies of up to 89% are possible. Performance comparisons have also been made between a conventional RBFNN and an RBFNN based on PSO which show a marginal decrease in performance but with notable reduction in computational overhead.

Bacterial, SCFA and gas profiles of a range of food ingredients following in vitro fermentation by human colonic microbiota.

It is now apparent that there is a strong link between health and nutrition and this can be seen clearly when we talk of obesity. The food industry is trying to capitalise on this by adapting high sugar/fat foods to become healthier alternatives. In confectionery food ingredients can be used for a range of purposes including sucrose replacement. Many of these ingredients may also evade digestion in the upper gut and be fermented by the gut microbiota upon entering the colon. This study was designed to screen a range of ingredients and their activities on the gut microbiota. In this study we screened a range of these ingredients in triplicate batch culture fermentations with known prebiotics as controls. Changes in bacteriology were monitored using FISH. SCFA were measured by GC and gas production was assessed during anaerobic batch fermentations. Bacterial enumeration showed significant increases (P ≤ 0.05) in bifidobacteria and lactobacilli with polydextrose and most polyols with no significant increases in Clostridium histolyticum/perfringens. SCFA and gas formation indicated that the substrates added to the fermenters were being utilised by the gut microbiota. It therefore appears these ingredients exert some prebiotic activity in vitro. Further studies, particularly in human volunteers, are necessary.