Spatial Descriptors Research Articles

From Low-Level Features to Semantic Classes: Spatial and Temporal Descriptors for Video Indexing

As the quantity of publicly available multimedia material becomes larger and larger, automatic indexing becomes increasingly important in accessing multimedia databases. In this paper, a novel set of low-level descriptors is presented for the aim of content-based video classification. Concerning temporal features, we use a modified PMES descriptor for the spatial distribution of local motion and a Dominant Direction Histogram we have developed to represent the temporal distribution of camera motion. Concerning color, we present the Weighted Color Histogram we have designed in order to model color distribution. The histogram models the H parameter of the HSV color space, and we combine it with weighted means for the S and V parameters. For the selection of key-frames from which to extract the spatial descriptors we use a modified version of a simple efficient method. We then proceed to evaluate our descriptor set on a database of video shots resulting from the temporal segmentation of the archive of a real-world TV station. Results demonstrate that our approach can achieve high success rates on a wide range of semantic classes.

QSAR analysis of centrally fused 1,5-diaryl pyrazoles for cyclooxygenase inhibition using MOE-Qua-SAR descriptors

Quantitative structure–activity relationship (QSAR) analysis has been carried out on a series of conformationally restricted 1,5-diaryl pyrazoles reported as selective cyclooxygenase-2 (COX-2) inhibitors in order to explore the selectivity requirements for COX-2 inhibition among these congeners. QSAR analysis was based on regression analysis between various computed physicochemical and topological descriptors and biological activity. Derived QSAR models evinced a satisfactory correlation of COX-2 inhibitory potency with a three-dimensional (3D) spatial descriptor, std_dim3, and a two-dimensional (2D) partial charge descriptor, PEOE_VSA-1. Balaban J, a highly discriminating topological descriptor, was found to play an imperative role in governing both COX-1 inhibitory potency as well as selective inhibition of COX-2 over COX-1. The selective COX-2 inhibition could be influenced by the size, shape, and polarizability of the whole molecules and was discerned by the contribution of molar refractivity (MR), Balaban J descriptors. The findings are in good consonance with earlier X-ray crystallographic investigations of binding mode of these types of selective COX-2 inhibitors. Results discussed herein bring important structural insights to aid the design and development of novel COX-2 inhibitors.

Predictive QSAR modeling of CCR5 antagonist piperidine derivatives using chemometric tools

Quantitative structure-activity relationship (QSAR) studies have been performed on piperidine derivatives (n = 119) as CCR5 antagonists. The whole data set was divided into a training set (75% of the dataset) and a test set (remaining 25%) on the basis of K-means clustering technique. Models developed from the training set were used to assess the predictive potential of the models using test set compounds. Initially classical type QSAR models were developed using structural, spatial, electronic, physicochemical and/or topological parameters using statistical methods like stepwise regression, partial least squares (PLS) and factor analysis followed by multiple linear regression (FA-MLR). Using topological and structural parameters, FA-MLR provided the best equation based on internal validation (Q2 = 0.514) but the best externally validated model was obtained with PLS ( = 0.565). When structural, physicochemical, spatial and electronic descriptors were used, the best Q2 value (0.562) was obtained from the stepwise regression derived model whereas the best value (0.571) came from the PLS model. When topological descriptors were used in combination with the structural, physicochemical, spatial and electronic descriptors, the best Q2 and values obtained were 0.530 (stepwise regression) and 0.580 (PLS) respectively. Attempt was made to develop 3D-QSAR models using molecular shape analysis descriptors in combination with structural, physicochemical, spatial and electronic parameters. Linear models were developed using genetic function algorithm coupled with multiple linear regression. However, the results from the 3D-QSAR study were not superior to those of the classical QSAR models. Finally, artificial neural network was employed for development of nonlinear models. The ANN models showed acceptable values of squared correlation coefficient for the observed and predicted values of the test set compounds. From the view point of external predictability, selected ANN models were superior to the linear QSAR models. All reported models satisfy the criteria of external validation as recommended by Golbraikh and Tropsha (J Mol Graphics Mod 2002; 20: 269–276), whereas the majority of the models have modified r2 () value of the test set for external validation more than 0.5 as suggested by Roy and Roy (QSAR Comb Sci 2008; 27: 302-313).

Representative volume element of anisotropic unidirectional carbon–epoxy composite with high-fibre volume fraction

The knowledge of thermal properties of orthotropic layered composite materials is very important in the aeronautics industry. They can be measured with a dedicated apparatus but numerical computations develop strongly. It is well known that the microstructure has a strong impact on the calculation of the effective properties of these heterogeneous materials. The representative volume element (RVE) is then a crucial input to predict reliable results. In composites, fibre distribution often exhibits fibre-rich and fibre-poor regions. In this contribution, we first investigated a quantitative characterization of the microstructure using optical images and spatial descriptors. They give rise to microstructural features but also anisotropy. In a second time, we defined the RVEs of this microstructure for statistical parameters and effective thermal conductivities.

Predictive QSAR modeling of HIV reverse transcriptase inhibitor TIBO derivatives

Comparative quantitative structure–activity relationship (QSAR) studies have been carried out on tetrahydroimidazo[4,5,1- jk][1,4]benzodiazepine (TIBO) derivatives as reverse transcriptase inhibitors ( n = 70) using topological, structural, physicochemical, electronic and spatial descriptors. The data set was divided into training and test sets using a cluster-based method. Linear models were developed using multiple regression (with stepwise regression, factor analysis and genetic function approximation (GFA) as variable selection tools) and partial least squares (PLS) and combination of factor analysis and partial least squares (FA–PLS). Genetic function approximation (spline) and artificial neural networks (ANN) were used for the development of non-linear models. Using topological and structural descriptors, the best equation was obtained from GFA (spline) based on internal validation ( Q 2 = 0.737), but the model with the best external validation characteristics was obtained with FA–PLS ( R pred 2 = 0.707). When structural, physicochemical, electronic and spatial descriptors were used, the best Q 2 (0.740) value was obtained from GFA (spline) whereas PLS provided the best R pred 2 (0.784) value. When all descriptors were used in combination, the best R pred 2 (0.760) value and the best Q 2 (0.800) value were obtained from ANN and GFA (spline), respectively. The majority of the models satisfied the criteria of external validation recommended by Golbraikh and Tropsha (2002) and the criteria of modified r 2 ( r m 2) values of the test set for external validation as suggested by Roy and Roy (2008). In order to further validate selected models, an external set of 10 TIBO derivatives, which fall within the applicability domain of the models and are not shared with the compounds of the present data set, was taken from a different source, and reverse transcriptase inhibitory activity of these compounds was predicted. Acceptable values of squared correlation coefficients between the observed and predicted values of the external set compounds were obtained from the selected models suggesting true predictive potential of the models.

A new approach for content-based video retrieval

In this paper, we propose a new approach for content-based video retrieval using non-parametric based motion classification in the shot-based video indexing structure. Our system proposed in this paper has supported the real-time video retrieval using spatio temporal feature comparison by measuring the similarity between visual features and between motion features, respectively, after extracting representative frame and non-parametric motion information from shot-based video clips segmented by scene change detection method. The extraction of non-parametric based motion features, after the normalized motion vectors are created from an MPEG-compressed stream, is effectively fulfilled by discretizing each normalized motion vector into various angle bins, and by considering the mean, variance, and direction of motion vectors in these bins. To obtain visual feature in representative frame, we use the edge-based spatial descriptor. Experimental results show that our approach is superior to conventional methods with regard to the performance for video indexing and retrieval.

Using Quantitative Structure–Activity Relationships (QSAR) to Predict Toxic Endpoints for Polycyclic Aromatic Hydrocarbons (PAH)

Quantitative structure–activity relationships (QSAR) offer a reliable, cost-effective alternative to the time, money, and animal lives necessary to determine chemical toxicity by traditional methods. Additionally, humans are exposed to tens of thousands of chemicals in their lifetimes, necessitating the determination of chemical toxicity and screening for those posing the greatest risk to human health. This study developed models to predict toxic endpoints for three bioassays specific to several stages of carcinogenesis. The ethoxyresorufin O-deethylase assay (EROD), the Salmonella/microsome assay, and a gap junction intercellular communication (GJIC) assay were chosen for their ability to measure toxic endpoints specific to activation-, induction-, and promotion-related effects of polycyclic aromatic hydrocarbons (PAH). Shape-electronic, spatial, information content, and topological descriptors proved to be important descriptors in predicting the toxicity of PAH in these bioassays. Bioassay-based toxic equivalency factors (TEFB) were developed for several PAH using the quantitative structure–toxicity relationships (QSTR) developed. Predicting toxicity for a specific PAH compound, such as a bioassay-based potential potency (PPB) or a TEFB, is possible by combining the predicted behavior from the QSTR models. These toxicity estimates may then be incorporated into a risk assessment for compounds that lack toxicity data. Accurate toxicity predictions are made by examining each type of endpoint important to the process of carcinogenicity, and a clearer understanding between composition and toxicity can be obtained.

Catchment descriptors to optimise hydrometric networks

Operational needs commonly dictate the evolution of hydrometric networks. Such an approach can fail to meet long-term water management information objectives. This paper investigates how spatial descriptors can be used to assess the strategic value of individual catchments in the UK gauging station network. A catchment utility index (CUI) is presented based on an automated implementation of the Flood Estimation Handbook pooling-group procedure for assessing catchment similarity. The CUI is derived from the frequency with which gauged catchments across the UK are called in the pooling-groups for around four million catchments. Several case studies illustrate how the index is interpreted and used—in combination with the hydrometric performance of gauging stations and the degree of disturbance to the natural flow regime—to identify the most strategically useful gauged catchments. Such information is an essential component in guiding network evolution and in improving the effectiveness of procedures to estimate river flows in ungauged catchments.

Quantitative Structure Activity Analysis of 2-Alkoxydihydrocinnamates as PPARα /γ Dual Agonist

To optimize the physiochemical properties of 2-alkoxydihydrocinnamates as PPARalpha/gamma dual agonist, a quantitative structure activity relationship, Hansch approach was made using combination of various thermodynamic, electronic and spatial descriptors. Several regression expressions are obtained using multiple linear regression analysis. The best QSAR model is further validated by leave-one-out cross validation method. Analyses of results from the present QSAR study suggest that for favorable dual PPARalpha/gamma agonist activity electronic property of the substituents in hydrophobic tail phenyl ring plays a key role. The contribution of Hammett constant and dipole moment in the models deduced the importance of electron withdrawing substituents for dual activity. Additionally the study also indicates that bulky substituents in head acid moiety not confer selectivity towards the PPAR activity. Thus the QSAR study brings important structural insight to aid the design of dual PPARalpha/gamma receptor agonist.

QUANTITATIVE STRUCTURE–ACTIVITY RELATIONSHIPS FOR KINETIC PARAMETERS OF POLYCYCLIC AROMATIC HYDROCARBON BIOTRANSFORMATION

Quantitative structure-activity relationships (QSARs) were developed for three Monod-type parameters--qmax, Ks, and qmax/Ks--that express the kinetics of polycyclic aromatic hydrocarbon (PAH) biotransformation by Sphingomonas paucimobilis strain EPA505. The training sets contained high-quality experimental values of the kinetic parameters for 20 unsubstituted and methylated PAHs as well as values of 41 meaningful molecular descriptors. A genetic function approximation algorithm was used to develop the QSARs. Statistical evaluation of the developed QSARs showed that the relationships are statistically significant and satisfy the assumptions of linear-regression analysis. The Organization for Economic Co-operation and Development principles for (Q)SAR validation were followed to evaluate the developed QSARs, which showed that the QSARs are valid. The QSARs contain spatial, spatial and electronic, topological, and thermodynamic molecular descriptors. Whereas spatial descriptors were essential in explaining biotransformation kinetics, electronic descriptors were not. Mechanistic interpretation of the QSARs resulted in evidence that is consistent with the hypothesis of membrane transport as being the rate-limiting process in PAH biotransformation by strain EPA505. The present study demonstrates the value of QSAR not only as a predictive tool but also as a framework for understanding the mechanisms governing biodegradation at the molecular level.

Exploration of Rate-Limiting Conformational State for 5-[(7-Chloro-4-quinolinyl)amino]-3-[(alkylamino)methyl][1,1‘-biphenyl]-2-ols and Nω-Oxides (Tebuquine Analogues) for Antimalarial Activity Using Molecular Shape Analysis and Molecular Field Analysis Studies

Tebuquine is a 4-aminoquinoline that shows significantly more potency as an antimalarial than amodiaquine and chloroquine both in vitro and in vivo. To explore the conformation in the rate-limiting step and to elucidate pharmacophoric properties of tebuquine-related analogues, molecular shape analysis (MSA) along with molecular field analysis (MFA) methods were applied on a series of 5-[(7-chloro-4-quinolinyl)amino]-3-[(alkylamino)methyl][1,1'-biphenyl]-2-ol analogues and their Nomega-oxides possessing antimalarial activity. The study was performed using 45 compounds in which 37 molecules were taken as a training set for the derivation of the 3D quantitative structure-activity relationship models and eight molecules were kept as a test set to evaluate the predictive ability of the derived models. Both methods were analyzed in terms of their predictive abilities and produced comparable results with good conventional and cross-validated r2 values (0.908 and 0.886, respectively, for the MFA model and 0.846 and 0.812, respectively, for the MSA model). In external data set prediction, the MSA model scored much better than MFA. Steric, electrostatic, and hydrogen-bond donor/acceptor fields of molecules were found to be relevant descriptors for structure-activity relationships. The inclusion of polar solvent-accessible charged surface area and spatial descriptors in the MSA model generation resulted in a model with significant predictive ability for the test set molecules. This indicates the importance of the orientation of conformationally favored molecules inside the receptor site and solvation of the charged surfaces of the molecule by a polar solvent for the activity of the molecule. The results provided the appropriate tools for predicting the affinity of related compounds using a ligand-based approach, and for guiding the design and synthesis of novel and more potent antimalarial agents.

Experimental and model-based study of the robustness of line-edge roughness metric extraction in the presence of noise

As critical dimensions shrink, line edge roughness (LER) and linewidth roughness (LWR) become of increasing concern. Crucial to the goal of reducing LER is its accurate characterization. LER has traditionally been represented as a single rms value. More recently, the use of power spectral density (PSD), height-height correlation (HHCF), and σ versus length plots has been proposed in order to extract the additional spatial descriptors of correlation length and roughness exponent. Here, the authors perform a modeling-based noise-sensitivity study on the extraction of spatial descriptors from line-edge data as well as an experimental study of the robustness of these various descriptors using a large data set of recent extreme-ultraviolet exposure data. The results show that in the presence of noise and in the large data set limit, the PSD method provides higher accuracy in the extraction of the roughness exponent, whereas the HHCF method provides higher accuracy for the correlation length. On the other hand, when considering precision, the HHCF method is superior for both metrics.

Distribution and habitats of <i>Bulinus depressus</i> and possible role as intermediate host of economically important helminth parasites in South Africa

This article documents the large-scale spatial distribution and ecological descriptors of associated habitats of Bulinus depressus by analysis of samples taken from 552 collection sites on record in the database of the National Freshwater Snail Collection (NFSC) at the Potchefstroom Campus of the North-West University. This snail species is experimentally susceptible to Schistosoma margrebowiei , a helminth parasite of game animals and cattle and can possibly also exploit humans as definitive hosts. The 125 different loci (1/16 degree squares) on record reflect a geographical distribution that is largely limited to the central and western part of the Limpopo Province and westwards down the basins of the Vaal and Orange Rivers. Details of each habitat as described by collectors during surveys, as well as altitude and mean annual air temperature and rainfall for each locality, were processed and chi-square and effect size values calculated. A decision tree constructed from all the available data indicated that temperature and altitude, followed by the type of water-body, seemed to be the more important factors that significantly influenced the distribution of this species in South Africa. The possible role of this species as intermediate host of economically important helminth species is briefly looked at and the urgent need to update the geographical distribution of host snails is emphasised. It is recommended that efforts be made to determine the exact role of B. depressus in the epidemiology of economically important helminth parasites. Keywords : Bulinus depressus , geographical distribution, habitat preferences, Schistosoma margrebowiei Water SA Vol. 31(4) 2005: 491-496

Exploring improved pesticide management in sub-tropical environments with GIS-supported fate modeling

The sensitivity analysis of pesticide models to input parameters related to crop management practices supplies working hypotheses to improve pesticide uses and environmental quality. Parameters of pesticide models that are influential to model output vary depending on regional environmental conditions, and their probability distribution functions must be identified on a case-oriented basis. While the performance of pesticide models has been extensively tested in temperate regions, comparative studies in subtropical areas are relatively scarce. In this study, we coupled results of landscape analyses supported with a geographical information system (GIS), field data and information about management scenarios of citrus crops in Misiones (Argentina) to inspect the behavior of a field-scale pesticide model (GLEAMSv3.0). Probability distribution functions of model parameters relevant to hydrology, geo-forms and crop distribution were derived from satellite imagery (SAC-C, SRTM), while crop characteristics, information on soils and pesticides were obtained from field data. Spatial descriptors were used to generate sensitivity scenarios to explore the potential effect of management practices on the fate of the pesticides chlorpyrifos, mancozeb, mercaptothion, copper hydroxide, carbendazem, glyphosate and 2-4-D used in citrus crops. Our results indicate that management practices to change the roughness-contouring of the soil, maintaining a high vegetation cover below the citrus crops, and devising pesticide spraying techniques that would efficiently increase the contact with the crop leaves would be expected to significantly reduce pesticide losses. Plant spacing, improving soil textural conditions through soil-correction practices and selecting adequate soil conditions for installing new crops are also potentially effective techniques to the same goal. Glyphosate losses are almost insensitive to management manipulation, which is a favorable trait in cases where management alternatives are constrained by practical or economic considerations. We present comparisons of the sensitivity of the pesticide model in these scenarios in relation to previously reported results with the same model in other cases, and formulate proposals on a normalized format to report sensitivity results to facilitate comparisons among models and cases.

Compactness Versus Interior-to-Edge Ratio; Two Approaches for Habitat's Ranking

In landscape ecology spatial descriptors (or indices) can be used to characterize habitats. Some of these descriptors can be used for habitat's ranking; this ranking is very important for conservation purposes. We would like to show that two traditional descriptors, namely the compactness and interior-to-edge ratio can give contradictory results. Being the second one is a more relevant descriptor, we would like to propose to avoid the further use the compactness in habitat's ranking.

QSAR analysis of N-Alkyl imidazole analogues as antibacterial agents

A quantitative structure activity relationship study on a series of N-alkyl imidazole analogues was made using combination of various thermodynamic electronic and spatial descriptors. Several statistical expressions were developed using stepwise multiple liner regression analysis. The best quantitative structure activity relationship models were further validated by leave-one-out method of cross-validation. The study revealed that the electronic property, i.e., dipole moment contributed positively, and spatial descriptor (principal moment of inertia at Y axis) contributed negatively. The study suggested that substitution of group at R1 position on imidazole ring with hydrophobic nature and low bulkiness are favourable for the antibacterial activity in the concerned microbes. The quantitative structure activity relationship study provides important structural insights in designing of potent antibacterial agents.

QSAR analysis of a series of 2-aryl(heteroaryl)-2,5-dihydropyrazolo[4,3- c]quinolin-3-(3 H)-ones using piecewise hyper-sphere modeling by particle swarm optimization

In the present work, we employed piecewise hyper-sphere modeling by particle swarm optimization (PHMPSO) which splits the dataset into subsets with desired linearity in each model for QSAR studies of a series of 2-aryl(heteroaryl)-2,5-dihydropyrazolo[4,3- c]quinolin-3-(3 H)-ones (PQs) for their affinity to benzodiazepine receptor (BzR). The results were compared to those obtained by MLR modeling in a single model with the whole data set as well as in submodels based on K-means clustering analysis. It has been clearly shown that electronic descriptors and spatial descriptors play the important roles in the compounds’ affinity to BzR. In addition, the molecular density, the Y component of the principal moment of inertia, the magnitude and the Y component of the dipole moment of the molecules can detrimentally affect PQ analogue BzR affinity, while the X component of the dipole moment of the molecules can favorably affect compounds’ affinity.

Literature review

Mamluk sultans were known for their patronage of the arts and architecture. Their educational institutions were among the wide array of architectural projects that linked them as ruling elites to the religious scholars of their times. Their tombs were placed in a mausoleum attached to their educational–religious complexes to attest to their legacy. The evolution of their buildings such that both educational and memorial functions are integrated with the dense surroundings is scrutinized through chronological–spatial analysis. The configuration of the built form, the disposition of its boundaries, its patterns of accessibility, and its visual properties are the features that present the buildings to one’s experience and bring certain perceptions into play. In this study, various spatial descriptor tools of space syntax are employed to analyze the data of 14 Mamluk examples (1260–1517A.D.) and capture the differences in the experience where the expression is preserved. Analyses of the configurational characteristics, axial attributes, visibility structures, and isovists highlight how the spatial and formal properties of the layouts were used to express certain representational relationships. The advantages of combining different spatial investigations allows for understanding historical design principles and how the geometry of forms could hide in its abstract rules, conceptual and perceptual qualities.

The response of epiphytes to anthropogenic disturbance of pine-oak forests in the highlands of Chiapas, Mexico

Epiphytes contribute up to over 30% of the vascular plant diversity of old-growth tropical rain forests, but little is known about their occurrence in exploited forests that are structurally altered. Here, I estimate epiphyte species richness and biomass on 35 oak host trees, equally divided over several trunk diameter classes, in each of 16 sites in anthropogenic disturbed montane pine-oak forests at similar elevations. The sites vary in their amount of disturbance from scarcely to heavily disturbed, related to the structure of the forest, and in their underlying distance in the landscape with a maximum of ca. 25 km. The explainable variation in the epiphyte vegetation is partitioned between environmental and spatial variables, using multivariate data analysis. In total, 74 species of epiphytes were encountered. Bromeliads dominate at all sites in terms of their biomass. Forest disturbance, measured as the proportion of sprouted oaks, has an expected negative effect on the epiphyte biomass and alpha diversity per ground surface area, but also on the epiphytes on the remaining and re-grown trees. This pattern was sustained after corrections for differences in host-tree size were made. Nevertheless, the epiphytes show resilience to disturbance if forests are selectively logged to spare big trees. Such remnant trees are essential for epiphytes that require the presence of accumulated suspended soil and they may also serve as nearby epiphyte seed sources for the re-growing trees. Anthropogenic disturbances also force a shift from mesic to more drought tolerant species. Hence, disturbance exerts an influence on the regional distribution of epiphytes, but a similar amount of variation (20–30%, depending on the used spatial descriptors) could entirely be attributed to the geographic position of the sites, independent from the influence of environmental variables. Nearby sites are more similar in epiphytes than distant sites (Mantel's r = 0.44, P = 0.002) and I postulate that this relates to differences in seed supply, viewing the development of the epiphyte community from a dispersal assembly perspective. For epiphyte conservation purposes, it is recommended to adopt a management of selective logging instead of cyclic clear-cutting and to spare large trees during logging. In addition, it is wise to try to attain a homogeneous distribution of epiphyte protective reserves within a uniform physiographic region.

QSAR analysis of substituted bis[(acridine-4-carboxamide)propyl]methylamines using optimized block-wise variable combination by particle swarm optimization for partial least squares modeling

In the current work, we employed optimized block-wise variable combination (OBVC) by particle swarm optimization (PSO) based on partial least squares (PLS) modeling for variable combination and compared it to the traditional methods. It has been demonstrated that the modified PSO is a useful tool for searching optimized variable combination. Quantitative structure–activity relationship (QSAR) model has been formulated for a set of DNA binding topoisomerase (topo) (substituted bis[(acridine-4-carboxamide)propyl]methylamines) on murine Lewis lung carcinoma (LL c) cells. The spatial descriptors especially Jurs descriptors play important roles in predicting the compound's inhibitory activity to murine LL c cells, and polar interactions are the principal binding strength between compounds and murine LL c cells. In addition, rotatable bonds in molecules and molar refractivity of the compounds will markedly affect the compounds’ inhibitory activity.