On Entropy-Based Molecular Descriptors: Statistical Analysis of Real and Synthetic Chemical Structures

This paper presents an analysis of entropy-based molecular descriptors. Specifically, we use real chemical structures, as well as synthetic isomeric structures, and investigate properties of and among descriptors with respect to the used data set by a statistical analysis. Our numerical results provide evidence that synthetic chemical structures are notably different to real chemical structures and, hence, should not be used to investigate molecular descriptors. Instead, an analysis based on real chemical structures is favorable. Further, we find strong hints that molecular descriptors can be partitioned into distinct classes capturing complementary information.

Quantitative structure-toxicity relationships for chlorophenols to bioluminescent lux-marked bacteria using atom-based semi-empirical molecular-orbital descriptors

Literature data on the toxicity of chlorophenols for three luminescent bacteria (Vibrio fischeri, and the lux-marked Pseudomonas fluorescens 10586s pUCD607 and Burkholderia spp. RASC c2 (Tn4431)) have been analyzed in relation to a set of computed molecular physico-chemical properties. The quantitative structure-toxicity relationships of the compounds in each species showed marked differences when based upon semi-empirical molecular-orbital molecular and atom based properties. For mono-, di- and tri-chlorophenols multiple linear regression analysis of V. fischeri toxicity showed a good correlation with the solvent accessible surface area and the charge on the oxygen atom. This correlation successfully predicted the toxicity of the heavily chlorinated phenols, suggesting in V. fischeri only one overall mechanism is present for all chlorophenols. Good correlations were also found for RASC c2 with molecular properties, such as the surface area and the nucleophilic super-delocalizability of the oxygen. In contrast the best QSTR for P. fluorescens contained the 2nd order connectivity index and ELUMO suggesting a different, more reactive mechanism. Cross-species correlations were examined, and between V. fischeri and RASC c2 the inclusion of the minimum value of the nucleophilic susceptibility on the ring carbons produced good results. Poorer correlations were found with P. fluorescens highlighting the relative similarity of V. fischeri and RASC c2, in contrast to that of P. fluorescens.

Partial shoeprint retrieval using multiple point-of-interest detectors and SIFT descriptors

Shoeprint evidence collected from crime scenes can play an important role in forensic investigations. Usually, the analysis of shoeprints is carried out manually and is based on human expertise and knowledge. As well as being error prone, such a manual process can also be time consuming; thus affecting the usability and suitability of shoeprint evidence in a court of law. Thus, an automatic system for classification and retrieval of shoeprints has the potential to be a valuable tool. This paper presents a solution for the automatic retrieval of shoeprints which is considerably more robust than existing solutions in the presence of geometric distortions such as scale, rotation and scale distortions. It addresses the issue of classifying partial shoeprints in the presence of rotation, scale and noise distortions and relies on the use of two local point-of-interest detectors whose matching scores are combined. In this work, multiscale Harris and Hessian detectors are used to select corners and blob-like structures in a scale-space representation for scale invariance, while Scale Invariant Feature Transform (SIFT) descriptor is employed to achieve rotation invariance. The proposed technique is based on combining the matching scores of the two detectors at the score level. Our evaluation has shown that it outperforms both detectors in most of our extended experiments when retrieving partial shoeprints with geometric distortions, and is clearly better than similar work published in the literature. We also demonstrate improved performance in the face of wear and tear. As matter of fact, whilst the proposed work outperforms similar algorithms in the literature, it is shown that achieving good retrieval performance is not constrained by acquiring a full print from a scene of crime as a partial print can still be used to attain comparable retrieval results to those of using the full print. This gives crime investigators more flexibility is choosing the parts of a print to search for in a database of footwear.

Partial Palmprint Matching Using Invariant Local Minutiae Descriptors

In forensic investigations, it is common for forensic investigators to obtain a photograph of evidence left at the scene of crimes to aid them catch the culprit(s). Although, fingerprints are the most popular evidence that can be used, scene of crime officers claim that more than 30% of the evidence recovered from crime scenes originate from palms. Usually, palmprints evidence left at crime scenes are partial since very rarely full palmprints are obtained. In particular, partial palmprints do not exhibit a structured shape and often do not contain a reference point that can be used for their alignment to achieve efficient matching. This makes conventional matching methods based on alignment and minutiae pairing, as used in fingerprint recognition, to fail in partial palmprint recognition problems. In this paper a new partial-to-full palmprint recognition based on invariant minutiae descriptors is proposed where the partial palmprint’s minutiae are extracted and considered as the distinctive and discriminating features for each palmprint image. This is achieved by assigning to each minutiae a feature descriptor formed using the values of all the orientation histograms of the minutiae at hand. This allows for the descriptors to be rotation invariant and as such do not require any image alignment at the matching stage. The results obtained show that the proposed technique yields a recognition rate of 99.2%. The solution does give a high confidence to the judicial jury in their deliberations and decision.

Cost Estimation of Machined Parts within an Aerospace Supply Chain

A generic, hierarchical, and multifidelity unit cost of acquisition estimating methodology for outside production machined parts is presented. The originality of the work lies with the method’s inherent capability of being able to generate multilevel and multifidelity cost relations for large volumes of parts utilizing process, supply chain costing data, and varying degrees of part design definition information. Estimates can be generated throughout the life cycle of a part using different grades of the combined information available. Considering design development for a given part, additional design definition may be used as it becomes available within the developed method to improve the quality of the resulting estimate. Via a process of analogous classification, parts are classified into groups of increasing similarity using design-based descriptors. A parametric estimating method is then applied to each subgroup of the machined part commodity in the direction of improved classification and using which, a relationship which links design variables to manufacturing cycle time may be generated. A rate cost reflective of the supply chain is then applied to the cycle time estimate for a given part to arrive at an estimate of make cost which is then totalled with the material and treatments cost components respectively to give an overall estimate of unit acquisition cost. Both the rate charge applied and the treatments cost calculated for a given procured part is derived via the use of ratio analysis.

Thresholding of noisy shoeprint images based on pixel context

In a typical shoeprint classification and retrieval system, the first step is to segment meaningful basic shapes and patterns in a noisy shoeprint image. This step has significant influence on shape descriptors and shoeprint indexing in the later stages. In this paper, we extend a recently developed denoising technique proposed by Buades, called non-local mean filtering, to give a more general model. In this model, the expected result of an operation on a pixel can be estimated by performing the same operation on all of its reference pixels in the same image. A working pixel’s reference pixels are those pixels whose neighbourhoods are similar to the working pixel’s neighbourhood. Similarity is based on the correlation between the local neighbourhoods of the working pixel and the reference pixel. We incorporate a special instance of this general case into thresholding a very noisy shoeprint image. Visual and quantitative comparisons with two benchmarking techniques, by Otsu and Kittler, are conducted in the last section, giving evidence of the effectiveness of our method for thresholding noisy shoeprint images.

AdaBoost Multiple Feature Selection and Combination for Face Recognition

Gabor features have been recognized as one of the most successful face representations. Encouraged by the results given by this approach, other kind of facial representations based on Steerable Gaussian first order kernels and Harris corner detector are proposed in this paper. In order to reduce the high dimensional feature space, PCA and LDA techniques are employed. Once the features have been extracted, AdaBoost learning algorithm is used to select and combine the most representative features. The experimental results on XM2VTS database show an encouraging recognition rate, showing an important improvement with respect to face descriptors only based on Gabor filters.

P2Y(1) antagonists: Combining receptor-based modeling and QSAR for a quantitative prediction of the biological activity based on consensus scoring

P2Y(1) is an ADP-activated G protein-coupled receptor (GPCR). Its antagonists impede platelet aggregation in vivo and are potential antithrombotic agents. Combining ligand and structure-based modeling we generated a consensus model (LIST-CM) correlating antagonist structures with their potencies. We docked 45 antagonists into our rhodopsin-based human P2Y(1) homology model and calculated docking scores and free binding energies with the Linear Interaction Energy (LIE) method in continuum-solvent. The resulting alignment was also used to build QSAR based on CoMFA, CoMSIA, and molecular descriptors. To benefit from the strength of each technique and compensate for their limitations, we generated our LIST-CM with a PLS regression based on the predictions of each methodology. A test set featuring untested substituents was synthesized and assayed in inhibition of 2-MeSADP-stimulated PLC activity and in radioligand binding. LIST-CM outperformed internal and external predictivity of any individual model to predict accurately the potency of 75% of the test set.

Toxicity of mono-, di- and tri-chlorophenols to lux marked terrestrial bacteria, Burkholderia species Rasc c2 and Pseudomonas fluorescens

Burkholderia species RASC and Pseudomonas fluorescens were marked with lux genes, encoding for bioluminescence and used to assess the toxicity of mono-, di- and tri-chlorophenols by determining the decline in bioluminescence following exposure to the compounds in aqueous solution. Toxicity was expressed as a 50% effective concentration value (EC50, equating to the concentration of compound which caused a 50% decline in bioluminescence. Comparing the toxicity values of the compounds showed that, in general, increasing the degree of chlorination, increased toxicity. By carrying out forward multiple linear regressions with log10 EC50 values and physio-chemical descriptors, it was shown that molecular parameters describing the hydrogen bonding nature of a chlorophenol provided a better fit than regressions between toxicity data and log10 Kow alone. Utilising these descriptor variables in equations, it was shown that the toxicity of chlorophenols to the lux marked bacteria could be predicted from the compounds physio-chemical characteristics. By correlating lux marked RASC c2 and P. fluorescens EC50 values with toxicity values using Pimephales promelas (fathead minnow), Tetrahymena pyriformis (ciliate) and marine bacterium Vibriofischeri, it was apparent that lux marked RASC c2 correlated well with the freshwater aquatic species (P. promelas and T. pyriformis). This implied that for predictions of toxicity of organic xenobiotic compounds to higher organisms, lux marked RASC c2 could be utilised as a rapid surrogate.

Illumination invariant facial recognition using a piecewise-constant lighting model

In this paper we demonstrate a simple and novel illumination model that can be used for illumination invariant facial recognition. This model requires no prior knowledge of the illumination conditions and can be used when there is only a single training image per-person. The proposed illumination model separates the effects of illumination over a small area of the face into two components; an additive component modelling the mean illumination and a multiplicative component, modelling the variance within the facial area. Illumination invariant facial recognition is performed in a piecewise manner, by splitting the face image into blocks, then normalizing the illumination within each block based on the new lighting model. The assumptions underlying this novel lighting model have been verified on the YaleB face database. We show that magnitude 2D Fourier features can be used as robust facial descriptors within the new lighting model. Using only a single training image per-person, our new method achieves high (in most cases 100%) identification accuracy on the YaleB, extended YaleB and CMU-PIE face databases.

Condition Assessment and Preservation of Open-Air Rock Art Panels During Climate Change

Thousands of Neolithic and Bronze Age open-air rock art panels exist across the countryside in northern England. However, desecration, pollution, and other factors are threatening the survival of these iconic stone monuments. Evidence suggest that rates of panel deterioration may be increasing, although it is not clear whether this is due to local factors or wider environmental influences accelerated by environmental change. To examine this question, 18 rock art panels with varied art motifs were studied at two major panel locations at Lordenshaw and Weetwood Moor in Northumberland. A condition assessment
tool was used to first quantify the level of deterioration of each panel (called “staging”). Stage estimates then were compared statistically with 27 geochemical and physical descriptors of local environments, such as soil moisture, salinity, pH, lichen coverage, soil anions and cation levels, and panel orientation, slope, and standing height. In parallel, climate modelling was performed using UKCP09 to assess how projected climatic conditions (to 2099) might affect the environmental descriptors most correlated with elevated stone deterioration. Only two descriptors significantly correlated (P < 0.05) with increased stage: the standing height of the panel and the exchangeable cation content of the local soils, although moisture conditions also were potentially influential at some panels. Climate modelling predicts warming temperatures, more seasonally variable precipitation, and increased wind speeds, which hint stone deterioration could accelerate in the future due to increased physiochemical weathering. We recommend key panels be targeted for immediate management intervention, focusing on reducing wind exposures, improving site drainage, and potentially immobilizing soil salts.

Food web indicators under the Marine Strategy Framework Directive: From complexity to simplicity?

The Marine Strategy Framework Directive (MSFD) requires that European Union Member States achieve "Good Environmental Status" (GES) in respect of 11 Descriptors of the marine environment by 2020. Of those, Descriptor 4, which focuses on marine food webs, is perhaps the most challenging to implement since the identification of simple indicators able to assess the health of highly dynamic and complex interactions is difficult. Here, we present the proposed food web criteria/indicators and analyse their theoretical background and applicability in order to highlight both the current knowledge gaps and the difficulties associated with the assessment of GES. We conclude that the existing suite of indicators gives variable focus to the three important food web properties: structure, functioning and dynamics, and more emphasis should be given to the latter two and the general principles that relate these three properties. The development of food web indicators should be directed towards more integrative and process-based indicators with an emphasis on their responsiveness to multiple anthropogenic pressures. (C) 2013 Elsevier Ltd. All rights reserved.